diff --git a/.gitattributes b/.gitattributes index bed0738c7eeb449bca98b5d2f33c89a1ee56349a..bf9b0466d080de5994ddb2add1d2c9b8d0a5ecae 100644 --- a/.gitattributes +++ b/.gitattributes @@ -58,3 +58,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text # Video files - compressed *.mp4 filter=lfs diff=lfs merge=lfs -text *.webm filter=lfs diff=lfs merge=lfs -text +evaluations/deadly-corridor/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/train/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/episode_metrics.jsonl filter=lfs diff=lfs merge=lfs -text +evaluations/flappy/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/train/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/episode_metrics.jsonl filter=lfs diff=lfs merge=lfs -text diff --git a/evaluations/deadly-corridor/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/train/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/episode_metrics.jsonl b/evaluations/deadly-corridor/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/train/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/episode_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ad2c31fbcf0a8db5cf28fbdf578bbfa7f49c2e9c --- /dev/null +++ b/evaluations/deadly-corridor/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/train/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/episode_metrics.jsonl @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:47e9f369b1c80159e15bd6ed5db7be2b4f9b5377fbdbe329701de93ad7352a08 +size 192030635 diff --git a/evaluations/deadly-corridor/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/train/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/git.diff b/evaluations/deadly-corridor/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/train/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/git.diff new file mode 100644 index 0000000000000000000000000000000000000000..ba5be52a0a9c591e12621219783ef39d6893b4e8 --- /dev/null +++ b/evaluations/deadly-corridor/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/train/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/git.diff @@ -0,0 +1,1741 @@ +diff --git a/configs/experiments/fixed_latency_curve.yaml b/configs/experiments/fixed_latency_curve.yaml +deleted file mode 100644 +index 3ab184f..0000000 +--- a/configs/experiments/fixed_latency_curve.yaml ++++ /dev/null +@@ -1,17 +0,0 @@ +-__base__: ../base/dummy.yaml +- +-experiment: +- name: fixed_latency_curve +- +-executor: +- mode: simulated +- +-latency: +- method: fixed +- fixed_latency_ms: 100 +- +-evaluation: +- eval_episodes: 20 +- +-logging: +- output_dir: outputs/fixed_latency_curve +diff --git a/configs/experiments/flappy/frame_stack/base.yaml b/configs/experiments/flappy/frame_stack/base.yaml +deleted file mode 100644 +index f1557d5..0000000 +--- a/configs/experiments/flappy/frame_stack/base.yaml ++++ /dev/null +@@ -1,123 +0,0 @@ +-experiment: +- name: flappy_base +- seed: 0 +- +-backend: +- type: sample_factory +- algo: APPO +- device: cuda +- train_dir: results/checkpoints +- restart_behavior: resume +- run_mode: train +- +-executor: +- mode: simulated +- +-env: +- name: flappy +- # note that env_fps must be an integer multiple of obs_fps! +- env_fps: 30 +- obs_fps: 30 +- gym_id: FlappyBird-v0 +- render_mode: rgb_array +- observation_mode: image +- use_lidar: false +- normalize_obs: true +- audio_on: false +- frame_stack: 4 +- obs_resize: +- - 84 +- - 84 +- # for training it could be true, but for realtime mode, THIS MUST BE FALSE! +- use_gpu_render: true +- simulator: gpu +- gpu_render_device: auto +- gpu_render_profile: false +- gpu_render_profile_interval: 200 +- noop_action: noop +- action_map: +- noop: 0 +- flap: 1 +- oneshot_actions: +- - flap +- +-latency: +- method: normal +- mean_latency_ms: 66.7 +- std_latency_ms: 33.3 +- min_latency_ms: 0 +- max_latency_ms: 500.0 +- +- +-scheduler: +- # [one_frame_then_noop, hold] +- # if hold, default hold duration is: env_fps / obs_fps +- hold_policy: one_frame_then_noop +- # can be either `issue_order_fifo` or `latest ready` +- ordering_policy: latest_ready +- +-policy: +- type: random +- actions: +- - noop +- - flap +- +-training: +- train_for_env_steps: 25000000 +- num_workers: 2 +- num_envs_per_worker: 128 +- worker_num_splits: 1 +- num_policies: 1 +- batch_size: 4096 +- rollout: 128 +- recurrence: 1 +- num_epochs: 8 +- num_batches_per_epoch: 8 +- max_policy_lag: 400 +- learning_rate: 0.00025 +- gamma: 0.99 +- gae_lambda: 0.95 +- ppo_clip_ratio: 0.1 +- ppo_clip_value: 0.2 +- value_loss_coeff: 0.5 +- max_grad_norm: 0.5 +- async_rl: true +- use_rnn: false +- normalize_input: true +- normalize_returns: true +- stats_avg: 100 +- experiment_summaries_interval: 1 +- save_every_sec: 600 +- keep_checkpoints: 5 +- +-evaluation: +- eval_interval_steps: 1000000 +- eval_episodes: 100 +- eval_parallel_envs: 100 +- eval_max_steps: 3600 +- eval_deterministic: true +- eval_raw_reward: false +- eval_suites: +- fixed: +- - [0, 8] # [start, end] +- normal: +- - [2.0, 0.5, 0, 15] # low latency, low jitter +- - [2.0, 1.0, 0, 15] # low latency, medium jitter +- - [4.0, 0.5, 0, 15] # high latency, low jitter +- - [4.0, 1.0, 0, 15] # high latency, medium jitter +- - [4.0, 2.0, 0, 15] # high latency, high jitter +- uniform: +- - [1, 3] # low latency, low jitter +- - [0, 4] # low latency, high jitter +- - [3, 5] # high latency, low jitter +- - [2, 6] # high latency, high jitter +- +-logging: +- output_dir: outputs/flappy_base +- save_step_records: true +- save_action_records: true +- save_latency_records: true +- wandb_project: latency-sensitive-bench +- wandb_group: flappy-frame_stack +- wandb_job_type: sample_factory +- wandb_tags: "" +diff --git a/latency_bench/data/exporters/starvla_lerobot.py b/latency_bench/data/exporters/starvla_lerobot.py +index c693460..4ad276a 100644 +--- a/latency_bench/data/exporters/starvla_lerobot.py ++++ b/latency_bench/data/exporters/starvla_lerobot.py +@@ -18,12 +18,17 @@ from latency_bench.utils.io import write_jsonl + from latency_bench.data.action_layouts import action_spec_for_env + from latency_bench.data.filters import density_weights_clean_v1 + +-FPS_BY_ENV = { +- "flappy": 30, +- "demon_attack": 60, +- "deadly_corridor": 35, +-} + STATE_DIM = 1 ++BRIDGE_DIM = 7 ++DEADLY_CORRIDOR_BRIDGE_ACTION_LABELS = ( ++ "MOVE_FORWARD", ++ "MOVE_BACKWARD", ++ "MOVE_LEFT", ++ "MOVE_RIGHT", ++ "TURN_LEFT", ++ "TURN_RIGHT", ++ "ATTACK", ++) + + + def _png_bytes(image: Any) -> bytes: +@@ -64,30 +69,38 @@ def _load_rows(raw_export_dir: Path, split: str) -> list[dict[str, Any]]: + + + def _episode_groups(rows: list[dict[str, Any]]) -> list[list[dict[str, Any]]]: +- """Group canonical rows by episode and order by decision step. ++ """Group canonical rows by trajectory and order by decision step. + + Args: + rows: Canonical rollout rows from one split. + + Returns: +- Episode row groups sorted by episode index. ++ Trajectory row groups sorted by episode and trajectory index. + """ +- grouped: dict[int, list[dict[str, Any]]] = {} ++ grouped: dict[tuple[int, int], list[dict[str, Any]]] = {} + for row in rows: +- grouped.setdefault(int(row["episode_idx"]), []).append(row) ++ key = (int(row["episode_idx"]), int(row["trajectory_idx"])) ++ grouped.setdefault(key, []).append(row) + return [ + sorted(episode_rows, key=lambda row: int(row["decision_step"])) + for _, episode_rows in sorted(grouped.items()) + ] + + +-def _write_episode(path: Path, rows: list[dict[str, Any]], *, action_dim: int) -> None: ++def _write_episode( ++ path: Path, ++ rows: list[dict[str, Any]], ++ *, ++ action_dim: int, ++ state_dim: int, ++) -> None: + """Write one LeRobot episode parquet file. + + Args: + path: Destination episode parquet path. + rows: Converted LeRobot frame rows. + action_dim: Expected action vector dimension. ++ state_dim: Expected state carrier dimension. + """ + path.parent.mkdir(parents=True, exist_ok=True) + table = pa.table( +@@ -97,8 +110,8 @@ def _write_episode(path: Path, rows: list[dict[str, Any]], *, action_dim: int) - + type=pa.struct([("bytes", pa.binary()), ("path", pa.string())]), + ), + "observation.state": pa.array( +- [[0.0] * STATE_DIM for _ in rows], +- type=pa.list_(pa.float32(), STATE_DIM), ++ [[0.0] * state_dim for _ in rows], ++ type=pa.list_(pa.float32(), state_dim), + ), + "action": pa.array( + [row["action"] for row in rows], +@@ -131,11 +144,47 @@ def _row_action_vector(row: dict[str, Any], *, action_dim: int) -> list[float]: + return [1.0 if idx == action_id else 0.0 for idx in range(action_dim)] + + ++def _bridge_action_vector( ++ row: dict[str, Any], ++ *, ++ env_name: str, ++ active_action_dim: int, ++) -> list[float]: ++ if env_name == "deadly_corridor": ++ action_text = str(row["action_text"]).upper() ++ return [ ++ 1.0 if label in action_text else 0.0 ++ for label in DEADLY_CORRIDOR_BRIDGE_ACTION_LABELS ++ ] ++ action = _row_action_vector(row, action_dim=active_action_dim) ++ return [*action, *([0.0] * (BRIDGE_DIM - active_action_dim))] ++ ++ ++def _target_action_labels( ++ *, ++ env_name: str, ++ source_action_labels: list[str], ++ action_carrier: str, ++) -> list[str]: ++ if action_carrier == "native": ++ return source_action_labels ++ if env_name == "deadly_corridor": ++ return list(DEADLY_CORRIDOR_BRIDGE_ACTION_LABELS) ++ return [ ++ *source_action_labels, ++ *[ ++ f"BRIDGE_PAD_{idx}" ++ for idx in range(len(source_action_labels), BRIDGE_DIM) ++ ], ++ ] ++ ++ + def _write_metadata( + dataset_dir: Path, + *, +- fps: int, ++ fps: float, + action_labels: list[str], ++ state_dim: int, + episode_lengths: list[int], + task_prompts: list[str], + ) -> None: +@@ -144,7 +193,8 @@ def _write_metadata( + Args: + dataset_dir: LeRobot dataset split directory. + fps: Frame rate stored in metadata. +- action_labels: Canonical action labels in vector order. ++ action_labels: Target action labels in vector order. ++ state_dim: State carrier dimension. + episode_lengths: Number of frames per converted episode. + task_prompts: Unique prompts used as LeRobot tasks. + """ +@@ -155,10 +205,10 @@ def _write_metadata( + json.dumps( + { + "codebase_version": "v2.0", +- "fps": int(fps), ++ "fps": fps, + "features": { + "observation.image": {"dtype": "image"}, +- "observation.state": {"dtype": "float32", "shape": [STATE_DIM]}, ++ "observation.state": {"dtype": "float32", "shape": [state_dim]}, + "action": {"dtype": "float32", "shape": [action_dim], "names": action_labels}, + "timestamp": {"dtype": "float64", "shape": [1]}, + "episode_index": {"dtype": "int64", "shape": [1]}, +@@ -183,9 +233,11 @@ def _convert_split( + *, + env_name: str, + action_labels: list[str], +- fps: int, ++ fps: float, + reward_field: str, +- obs_stride: int = 1, ++ action_carrier: str, ++ active_action_dim: int, ++ state_dim: int, + density_weighting: bool = False, + ) -> dict[str, Any]: + """Convert one canonical rollout split into a LeRobot dataset directory. +@@ -195,13 +247,11 @@ def _convert_split( + output_dir: Destination LeRobot split directory. + env_name: Canonical benchmark environment name. + action_labels: Canonical action labels in vector order. +- fps: Frame rate used for timestamps. ++ fps: Observation frame rate used for timestamps. + reward_field: Source canonical reward column. +- obs_stride: Raw frames per observation decision (``round(env_fps/obs_fps)``). +- Canonical rows are recorded once per raw frame; keeping only the obs +- decisions (``decision_step % obs_stride == 0``) makes adjacent LeRobot +- rows adjacent observations, so KV-memory rollouts unroll at the eval +- observation cadence. ++ action_carrier: Target action/state carrier. ++ active_action_dim: Number of active environment action dimensions. ++ state_dim: Target state carrier dimension. + density_weighting: When True, write per-row ``density_weight`` from clean_v1's + event balancing (train split). When False, weights are uniform 1.0 (val + split keeps an unweighted held-out loss). +@@ -214,7 +264,6 @@ def _convert_split( + task_prompts: list[str] = [] + episode_lengths: list[int] = [] + for new_episode_idx, episode_rows in enumerate(_episode_groups(rows)): +- episode_rows = [row for row in episode_rows if int(row["decision_step"]) % obs_stride == 0] + density_weights = ( + density_weights_clean_v1(env_name, episode_rows) + if density_weighting +@@ -231,8 +280,14 @@ def _convert_split( + out_rows.append( + { + "image_bytes": _png_bytes(row["image"]), +- "action": _row_action_vector(row, action_dim=len(action_labels)), +- "timestamp": float(frame_idx) / int(fps), ++ "action": _bridge_action_vector( ++ row, ++ env_name=env_name, ++ active_action_dim=active_action_dim, ++ ) ++ if action_carrier == "bridge" ++ else _row_action_vector(row, action_dim=len(action_labels)), ++ "timestamp": float(frame_idx) / fps, + "episode_index": new_episode_idx, + "frame_index": frame_idx, + "task_index": prompt_to_task_index[prompt], +@@ -248,11 +303,13 @@ def _convert_split( + output_dir / f"data/chunk-{episode_chunk:03d}/episode_{new_episode_idx:06d}.parquet", + out_rows, + action_dim=len(action_labels), ++ state_dim=state_dim, + ) + _write_metadata( + output_dir, + fps=fps, + action_labels=action_labels, ++ state_dim=state_dim, + episode_lengths=episode_lengths, + task_prompts=task_prompts, + ) +@@ -269,6 +326,7 @@ def convert_canonical_rollout_to_lerobot( + raw_export_dir: Path | str, + output_dir: Path | str, + *, ++ action_carrier: str = "native", + force: bool = False, + ) -> dict[str, Any]: + """Convert a canonical rollout export into train/val LeRobot datasets. +@@ -276,6 +334,7 @@ def convert_canonical_rollout_to_lerobot( + Args: + raw_export_dir: Directory with canonical rollout parquet files and metadata. + output_dir: Destination LeRobot train dataset directory. ++ action_carrier: Target action/state carrier, ``native`` or ``bridge``. + force: Remove existing train/val output directories before writing. + + Returns: +@@ -286,11 +345,20 @@ def convert_canonical_rollout_to_lerobot( + metadata = json.loads((raw_export_dir / "metadata.json").read_text(encoding="utf-8")) + env_name = str(metadata["env_name"]) + action_spec = action_spec_for_env(env_name) +- action_labels = list(metadata["action_labels"]) ++ source_action_labels = list(metadata["action_labels"]) ++ action_labels = _target_action_labels( ++ env_name=env_name, ++ source_action_labels=source_action_labels, ++ action_carrier=action_carrier, ++ ) ++ active_action_dim = { ++ "flappy": 2, ++ "demon_attack": 6, ++ "deadly_corridor": 7, ++ }[env_name] ++ state_dim = {"native": STATE_DIM, "bridge": BRIDGE_DIM}[action_carrier] + reward_field = str(metadata["reward_field"]) +- obs_stride = int(metadata.get("obs_stride_raw_frames", 1)) +- # Rows survive at the observation cadence, so timestamps advance at obs_fps. +- fps = max(1, int(FPS_BY_ENV[env_name]) // obs_stride) ++ fps = metadata["obs_fps"] + val_output_dir = output_dir.with_name(f"{output_dir.name}__val") + if output_dir.exists() and force: + shutil.rmtree(output_dir) +@@ -303,7 +371,9 @@ def convert_canonical_rollout_to_lerobot( + action_labels=action_labels, + fps=fps, + reward_field=reward_field, +- obs_stride=obs_stride, ++ action_carrier=action_carrier, ++ active_action_dim=active_action_dim, ++ state_dim=state_dim, + density_weighting=True, + ) + val_manifest = _convert_split( +@@ -313,7 +383,9 @@ def convert_canonical_rollout_to_lerobot( + action_labels=action_labels, + fps=fps, + reward_field=reward_field, +- obs_stride=obs_stride, ++ action_carrier=action_carrier, ++ active_action_dim=active_action_dim, ++ state_dim=state_dim, + density_weighting=False, + ) + manifest = { +@@ -321,9 +393,13 @@ def convert_canonical_rollout_to_lerobot( + "format": "starvla_lerobot_v2_image_parquet", + "source": str(raw_export_dir), + "action_layout": str(metadata["action_layout"]), ++ "action_carrier": action_carrier, + "action_labels": action_labels, + "action_dim": len(action_labels), +- "active_action_dim": len(action_spec.labels), ++ "active_action_dim": active_action_dim ++ if action_carrier == "bridge" ++ else len(action_spec.labels), ++ "state_dim": state_dim, + "validation_dataset_name": val_output_dir.name, + "validation_episodes": val_manifest["episodes"], + "validation_frames": val_manifest["frames"], +diff --git a/latency_bench/data/hf_parquet.py b/latency_bench/data/hf_parquet.py +index 7a26426..6163c0d 100644 +--- a/latency_bench/data/hf_parquet.py ++++ b/latency_bench/data/hf_parquet.py +@@ -205,7 +205,9 @@ def completed_episode_indices_from_shards(output_dir: Path) -> set[int]: + with shard_path.open("r", encoding="utf-8") as handle: + for line in handle: + if line.strip(): +- completed_episode_indices.add(int(json.loads(line)["episode_idx"])) ++ row = json.loads(line) ++ row["trajectory_idx"] ++ completed_episode_indices.add(int(row["episode_idx"])) + break + return completed_episode_indices + +diff --git a/latency_bench/data/rollout_schema.py b/latency_bench/data/rollout_schema.py +index 11426b9..21d2bf5 100644 +--- a/latency_bench/data/rollout_schema.py ++++ b/latency_bench/data/rollout_schema.py +@@ -7,11 +7,12 @@ from datasets import Features, Image as HFImage, Sequence as HFSequence, Value + from latency_bench.data.action_layouts import ActionSpec + + +-SCHEMA_VERSION = 2 ++SCHEMA_VERSION = 3 + CANONICAL_ROW_FIELDS = ( + "image", + "env_name", + "episode_idx", ++ "trajectory_idx", + "decision_step", + "split", + "seed", +@@ -26,6 +27,7 @@ def _rollout_feature_map(action_spec: ActionSpec) -> dict[str, Any]: + "image": HFImage(), + "env_name": Value("string"), + "episode_idx": Value("int64"), ++ "trajectory_idx": Value("int64"), + "decision_step": Value("int64"), + "split": Value("string"), + "seed": Value("int64"), +diff --git a/latency_bench/data/sf_teacher_rollout.py b/latency_bench/data/sf_teacher_rollout.py +index af2b64f..bbbd157 100644 +--- a/latency_bench/data/sf_teacher_rollout.py ++++ b/latency_bench/data/sf_teacher_rollout.py +@@ -355,6 +355,7 @@ def _write_filtered_episode_images( + image_writer: RolloutImageWriter, + rows: list[dict[str, Any]], + frames_by_decision_step: Mapping[int, np.ndarray], ++ trajectory_by_decision_step: Mapping[int, int], + *, + context_window: int, + ) -> list[dict[str, Any]]: +@@ -364,6 +365,7 @@ def _write_filtered_episode_images( + image_writer: Image writer shared by the rollout run. + rows: Final rows selected for materialization. + frames_by_decision_step: Captured frames keyed by decision step. ++ trajectory_by_decision_step: Trajectory index keyed by decision step. + context_window: Total image window length including the current ``image`` field. + + Returns: +@@ -371,10 +373,15 @@ def _write_filtered_episode_images( + """ + if not rows: + return [] +- available_decision_steps = sorted(frames_by_decision_step) + required_steps: set[int] = set() + for row in rows: + decision_step = int(row["decision_step"]) ++ trajectory_idx = int(row["trajectory_idx"]) ++ available_decision_steps = sorted( ++ step ++ for step, step_trajectory_idx in trajectory_by_decision_step.items() ++ if step_trajectory_idx == trajectory_idx ++ ) + required_steps.add(decision_step) + if int(context_window) > 1: + required_steps.update( +@@ -396,6 +403,12 @@ def _write_filtered_episode_images( + for row in rows: + written = dict(row) + decision_step = int(written["decision_step"]) ++ trajectory_idx = int(written["trajectory_idx"]) ++ available_decision_steps = sorted( ++ step ++ for step, step_trajectory_idx in trajectory_by_decision_step.items() ++ if step_trajectory_idx == trajectory_idx ++ ) + written["image"] = written_paths_by_step[decision_step] + if int(context_window) > 1: + written["context_images"] = [ +@@ -804,6 +817,7 @@ def _replay_accepted_specs( + active_episode_rows: list[list[dict[str, Any]]] = [[] for _ in range(driver.slot_count)] + active_episode_frames: list[list[np.ndarray]] = [[] for _ in range(driver.slot_count)] + active_decision_steps = [0 for _ in range(driver.slot_count)] ++ active_trajectory_indices = [0 for _ in range(driver.slot_count)] + active_ghost_streams: list[Any | None] = [None for _ in range(driver.slot_count)] + rnn_states = torch.zeros([driver.slot_count, rnn_size], dtype=torch.float32, device=device) + image_writer = RolloutImageWriter( +@@ -844,6 +858,7 @@ def _replay_accepted_specs( + active_episode_rows[slot] = [] + active_episode_frames[slot] = [] + active_decision_steps[slot] = 0 ++ active_trajectory_indices[slot] = 0 + rnn_states[slot].zero_() + + with tqdm(total=len(specs_to_replay), initial=0, unit="episode") as progress: +@@ -881,21 +896,21 @@ def _replay_accepted_specs( + next_decision_step=next_decision_step, + max_steps_per_episode=int(max_steps_per_episode), + ) +- if not life_loss_boundary: +- active_episode_frames[slot].append(np.array(image_frame, copy=True)) +- row = teacher_dataset_row( +- env_name=env_name, +- spec=spec, +- decision_step=decision_step, +- image=str(image_path), +- raw_action=raw_actions[batch_idx], +- info=step_result.info, +- reward=step_result.reward, +- env_fps=env_fps, +- obs_fps=obs_fps, +- image_transform=image_transform_config.normalized_transform(), +- ) +- active_episode_rows[slot].append(row) ++ active_episode_frames[slot].append(np.array(image_frame, copy=True)) ++ row = teacher_dataset_row( ++ env_name=env_name, ++ spec=spec, ++ trajectory_idx=active_trajectory_indices[slot], ++ decision_step=decision_step, ++ image=str(image_path), ++ raw_action=raw_actions[batch_idx], ++ info=step_result.info, ++ reward=step_result.reward, ++ env_fps=env_fps, ++ obs_fps=obs_fps, ++ image_transform=image_transform_config.normalized_transform(), ++ ) ++ active_episode_rows[slot].append(row) + rnn_states[slot] = new_rnn_states[batch_idx] + if episode_done: + final_rows = _finalize_attempt_rows( +@@ -931,6 +946,10 @@ def _replay_accepted_specs( + image_writer, + shard_rows, + frames_by_decision_step, ++ { ++ int(row["decision_step"]): int(row["trajectory_idx"]) ++ for row in final_rows ++ }, + context_window=int(context_window), + ) + write_episode_row_shard(output_dir, shard_rows) +@@ -943,12 +962,14 @@ def _replay_accepted_specs( + active_episode_rows[slot] = [] + active_episode_frames[slot] = [] + active_decision_steps[slot] = 0 ++ active_trajectory_indices[slot] = 0 + if _is_demon_ghost_trail: + active_ghost_streams[slot] = None + rnn_states[slot].zero_() + else: + if life_loss_boundary: + active_obs[slot], reset_info = driver.continue_after_life_loss(slot) ++ active_trajectory_indices[slot] += 1 + if _is_demon_ghost_trail: + active_ghost_streams[slot].clear() + active_image_frames[slot] = frame_from_env_raw_rgb_info(reset_info).copy() +@@ -981,6 +1002,7 @@ def _replay_accepted_specs( + active_episode_rows[slot] = [] + active_episode_frames[slot] = [] + active_decision_steps[slot] = 0 ++ active_trajectory_indices[slot] = 0 + rnn_states[slot].zero_() + else: + if isinstance(driver, BatchedTeacherRolloutDriver): +diff --git a/latency_bench/data/sf_teacher_rows.py b/latency_bench/data/sf_teacher_rows.py +index efa6f3e..4e7ce9a 100644 +--- a/latency_bench/data/sf_teacher_rows.py ++++ b/latency_bench/data/sf_teacher_rows.py +@@ -14,6 +14,7 @@ def teacher_dataset_row( + *, + env_name: str, + spec: Mapping[str, Any], ++ trajectory_idx: int, + decision_step: int, + image: str, + raw_action: Any, +@@ -28,6 +29,7 @@ def teacher_dataset_row( + Args: + env_name: Canonical benchmark environment name. + spec: Episode spec containing index, split, and seed. ++ trajectory_idx: Zero-based trajectory index within the full-game episode. + decision_step: Zero-based policy decision step within the episode. + image: Path to the saved pre-step image. + raw_action: Raw teacher action for this decision. +@@ -48,6 +50,7 @@ def teacher_dataset_row( + "image": image, + "env_name": str(env_name), + "episode_idx": int(spec["episode_idx"]), ++ "trajectory_idx": int(trajectory_idx), + "decision_step": int(decision_step), + "split": str(spec["split"]), + "seed": int(spec["seed"]), +diff --git a/scripts/experiment_runner/run_manifest_jobs.py b/scripts/experiment_runner/run_manifest_jobs.py +index e2d1b5e..f425a27 100644 +--- a/scripts/experiment_runner/run_manifest_jobs.py ++++ b/scripts/experiment_runner/run_manifest_jobs.py +@@ -73,11 +73,6 @@ def _event_writer(event_log: Path) -> Callable[[dict[str, Any]], None]: + return write + + +-def _register_process(process: subprocess.Popen) -> None: +- with _ACTIVE_PROCESSES_LOCK: +- _ACTIVE_PROCESSES.add(process) +- +- + def _forget_process(process: subprocess.Popen) -> None: + with _ACTIVE_PROCESSES_LOCK: + _ACTIVE_PROCESSES.discard(process) +@@ -89,11 +84,10 @@ def _active_processes() -> list[subprocess.Popen]: + + + def _signal_process_group(process: subprocess.Popen, sig: int) -> None: +- if process.poll() is None: +- try: +- os.killpg(process.pid, sig) +- except ProcessLookupError: +- pass ++ try: ++ os.killpg(process.pid, sig) ++ except ProcessLookupError: ++ pass + + + def _terminate_active_processes(sig: int = signal.SIGTERM) -> None: +@@ -118,15 +112,24 @@ def _terminate_active_processes(sig: int = signal.SIGTERM) -> None: + pass + + +-def _run_command(command: str, *, gpu: str) -> None: ++def _run_command( ++ command: str, ++ *, ++ gpu: str, ++ cancel_event: threading.Event | None = None, ++) -> bool: + env = os.environ.copy() + env["CUDA_VISIBLE_DEVICES"] = str(gpu) +- process = subprocess.Popen(command, shell=True, env=env, start_new_session=True) +- _register_process(process) ++ with _ACTIVE_PROCESSES_LOCK: ++ if cancel_event is not None and cancel_event.is_set(): ++ return False ++ process = subprocess.Popen(command, shell=True, env=env, start_new_session=True) ++ _ACTIVE_PROCESSES.add(process) + try: + returncode = process.wait() + if returncode != 0: + raise subprocess.CalledProcessError(returncode, command) ++ return True + finally: + _forget_process(process) + +@@ -223,16 +226,6 @@ def run_jobs( + dry_run: bool = False, + uploader: Callable[[dict[str, str]], None] | None = None, + ) -> int: +- previous_sigint = signal.getsignal(signal.SIGINT) +- previous_sigterm = signal.getsignal(signal.SIGTERM) +- +- def stop_active_processes(signum, frame): +- del frame +- _terminate_active_processes(signal.SIGTERM) +- raise KeyboardInterrupt(signum) +- +- signal.signal(signal.SIGINT, stop_active_processes) +- signal.signal(signal.SIGTERM, stop_active_processes) + manifest_file = Path(manifest_path).expanduser().resolve() + event_log = event_log_path_for_manifest(manifest_file) + write_event = _event_writer(event_log) +@@ -259,6 +252,9 @@ def run_jobs( + upload_queue: queue.Queue[UploadTask | None] = queue.Queue() + failures: list[tuple[str, str]] = [] + failure_lock = threading.Lock() ++ cancel_event = threading.Event() ++ signal_event = threading.Event() ++ cleanup_started = False + uploader_fn = _default_uploader if uploader is None else uploader + + if stage != "upload": +@@ -280,28 +276,49 @@ def run_jobs( + if job is None: + job_queue.task_done() + break ++ if cancel_event.is_set(): ++ job_queue.task_done() ++ continue + next_stage = _resume_stage(job, states) if stage == "all" else stage + job_id = str(job["job_id"]) + try: + if next_stage == "train": ++ if cancel_event.is_set(): ++ continue + if dry_run: + print(f"[dry-run] CUDA_VISIBLE_DEVICES={gpu} {job['train_command']}", flush=True) + else: + write_event({"job_id": job_id, "stage": "train_started", "gpu": gpu, "ts": _now()}) +- _run_command(str(job["train_command"]), gpu=gpu) ++ started = _run_command( ++ str(job["train_command"]), ++ gpu=gpu, ++ cancel_event=cancel_event, ++ ) ++ if not started or cancel_event.is_set(): ++ continue + write_event({"job_id": job_id, "stage": "train_succeeded", "gpu": gpu, "ts": _now()}) + next_stage = "eval" if stage == "all" else "complete" + if next_stage == "eval": ++ if cancel_event.is_set(): ++ continue + if dry_run: + print(f"[dry-run] CUDA_VISIBLE_DEVICES={gpu} {job['eval_command']}", flush=True) + else: + write_event({"job_id": job_id, "stage": "eval_started", "gpu": gpu, "ts": _now()}) +- _run_command(str(job["eval_command"]), gpu=gpu) ++ started = _run_command( ++ str(job["eval_command"]), ++ gpu=gpu, ++ cancel_event=cancel_event, ++ ) ++ if not started or cancel_event.is_set(): ++ continue + write_event({"job_id": job_id, "stage": "eval_succeeded", "gpu": gpu, "ts": _now()}) + next_stage = "upload" if stage == "all" else "complete" +- if next_stage == "upload": ++ if next_stage == "upload" and not cancel_event.is_set(): + upload_queue.put(UploadTask(job)) + except subprocess.CalledProcessError: ++ if cancel_event.is_set(): ++ continue + failed_stage = "train_failed" if next_stage == "train" else "eval_failed" + write_event({"job_id": job_id, "stage": failed_stage, "gpu": gpu, "ts": _now()}) + record_failure(job_id, failed_stage) +@@ -311,48 +328,52 @@ def run_jobs( + def upload_worker() -> None: + while True: + task = upload_queue.get() +- if task is None: +- upload_queue.task_done() +- break +- job = task.job +- job_id = str(job["job_id"]) +- train_repo_id = str(job["train_upload_repo_id"]) +- eval_repo_id = str(job["eval_upload_repo_id"]) +- if dry_run: +- targets = [repo_id for repo_id in (eval_repo_id, train_repo_id) if repo_id] +- print(f"[dry-run] upload {job_id}: {', '.join(targets) or 'no upload target'}", flush=True) +- upload_queue.task_done() +- continue +- if not train_repo_id and not eval_repo_id: +- write_event({"job_id": job_id, "stage": "upload_skipped", "ts": _now()}) +- write_event({"job_id": job_id, "stage": "job_complete", "ts": _now()}) +- upload_queue.task_done() +- continue +- attempt = 0 +- success = False +- while attempt < max_upload_attempts and not success: +- attempt += 1 +- write_event({"job_id": job_id, "stage": "upload_started", "attempt": attempt, "ts": _now()}) +- try: +- if not dry_run: +- uploader_fn(job) +- write_event({"job_id": job_id, "stage": "upload_succeeded", "attempt": attempt, "ts": _now()}) ++ try: ++ if task is None: ++ break ++ if cancel_event.is_set(): ++ continue ++ job = task.job ++ job_id = str(job["job_id"]) ++ train_repo_id = str(job["train_upload_repo_id"]) ++ eval_repo_id = str(job["eval_upload_repo_id"]) ++ if dry_run: ++ targets = [repo_id for repo_id in (eval_repo_id, train_repo_id) if repo_id] ++ print(f"[dry-run] upload {job_id}: {', '.join(targets) or 'no upload target'}", flush=True) ++ continue ++ if not train_repo_id and not eval_repo_id: ++ write_event({"job_id": job_id, "stage": "upload_skipped", "ts": _now()}) + write_event({"job_id": job_id, "stage": "job_complete", "ts": _now()}) +- success = True +- except Exception as error: +- write_event( +- { +- "job_id": job_id, +- "stage": "upload_failed", +- "attempt": attempt, +- "error": repr(error), +- "ts": _now(), +- } +- ) +- print(f"upload failed for {job_id} (attempt {attempt}): {error!r}", file=sys.stderr) +- if not success: +- record_failure(job_id, "upload_failed") +- upload_queue.task_done() ++ continue ++ attempt = 0 ++ success = False ++ while attempt < max_upload_attempts and not success and not cancel_event.is_set(): ++ attempt += 1 ++ write_event({"job_id": job_id, "stage": "upload_started", "attempt": attempt, "ts": _now()}) ++ try: ++ uploader_fn(job) ++ if cancel_event.is_set(): ++ continue ++ write_event({"job_id": job_id, "stage": "upload_succeeded", "attempt": attempt, "ts": _now()}) ++ write_event({"job_id": job_id, "stage": "job_complete", "ts": _now()}) ++ success = True ++ except Exception as error: ++ if cancel_event.is_set(): ++ continue ++ write_event( ++ { ++ "job_id": job_id, ++ "stage": "upload_failed", ++ "attempt": attempt, ++ "error": repr(error), ++ "ts": _now(), ++ } ++ ) ++ print(f"upload failed for {job_id} (attempt {attempt}): {error!r}", file=sys.stderr) ++ if not success and not cancel_event.is_set(): ++ record_failure(job_id, "upload_failed") ++ finally: ++ upload_queue.task_done() + + upload_threads = [ + threading.Thread(target=upload_worker, name=f"upload-{idx}", daemon=True) +@@ -362,17 +383,44 @@ def run_jobs( + threading.Thread(target=train_worker, args=(gpu,), name=f"train-{gpu}", daemon=True) + for gpu in gpus if stage != "upload" + ] ++ previous_sigint = signal.getsignal(signal.SIGINT) ++ previous_sigterm = signal.getsignal(signal.SIGTERM) ++ ++ def stop_active_processes(signum, frame): ++ nonlocal cleanup_started ++ del frame ++ if signal_event.is_set(): ++ return ++ signal_event.set() ++ cancel_event.set() ++ if cleanup_started: ++ return ++ raise KeyboardInterrupt(signum) ++ ++ signal.signal(signal.SIGINT, stop_active_processes) ++ signal.signal(signal.SIGTERM, stop_active_processes) + try: + for thread in upload_threads + train_threads: + thread.start() + job_queue.join() +- for _ in upload_threads: +- upload_queue.put(None) + upload_queue.join() +- for thread in train_threads + upload_threads: +- thread.join() + return 1 if failures else 0 + finally: ++ cleanup_started = True ++ cancel_event.set() ++ _terminate_active_processes(signal.SIGTERM) ++ for thread in train_threads: ++ thread.join() ++ _terminate_active_processes(signal.SIGTERM) ++ if signal_event.is_set(): ++ for _ in upload_threads: ++ upload_queue.put(None) ++ else: ++ upload_queue.join() ++ for _ in upload_threads: ++ upload_queue.put(None) ++ for thread in upload_threads: ++ thread.join() + _terminate_active_processes(signal.SIGTERM) + signal.signal(signal.SIGINT, previous_sigint) + signal.signal(signal.SIGTERM, previous_sigterm) +diff --git a/scripts/rollout_data/prepare_starvla_lerobot_dataset.py b/scripts/rollout_data/prepare_starvla_lerobot_dataset.py +index e202657..2521899 100644 +--- a/scripts/rollout_data/prepare_starvla_lerobot_dataset.py ++++ b/scripts/rollout_data/prepare_starvla_lerobot_dataset.py +@@ -26,6 +26,7 @@ def convert_raw_export_to_lerobot( + raw_export_dir: Path, + lerobot_root: Path, + data_mix: str, ++ action_carrier: str = "native", + ) -> dict: + """Convert a raw rollout export into a named LeRobot data mix. + +@@ -33,6 +34,7 @@ def convert_raw_export_to_lerobot( + raw_export_dir: Canonical rollout export directory. + lerobot_root: Directory that will contain the LeRobot datasets. + data_mix: Train dataset directory name under ``lerobot_root``. ++ action_carrier: Target action/state carrier. + + Returns: + Conversion manifest returned by the LeRobot adapter. +@@ -41,6 +43,7 @@ def convert_raw_export_to_lerobot( + return convert_canonical_rollout_to_lerobot( + raw_export_dir, + output_dir, ++ action_carrier=action_carrier, + force=True, + ) + +@@ -92,6 +95,7 @@ def build_parser() -> argparse.ArgumentParser: + parser.add_argument("raw_export_dir") + parser.add_argument("lerobot_root") + parser.add_argument("data_mix") ++ parser.add_argument("--action-carrier", choices=("native", "bridge"), default="native") + parser.add_argument("--push-to-hub", default="") + parser.add_argument("--private", action="store_true") + return parser +@@ -115,6 +119,7 @@ def main(argv: Sequence[str] | None = None) -> int: + raw_export_dir=raw_export_dir, + lerobot_root=lerobot_root, + data_mix=data_mix, ++ action_carrier=args.action_carrier, + ) + if args.push_to_hub: + push_lerobot_dataset( +diff --git a/tests/data/test_rollout_dataset_schema.py b/tests/data/test_rollout_dataset_schema.py +index 06a6091..55ccebf 100644 +--- a/tests/data/test_rollout_dataset_schema.py ++++ b/tests/data/test_rollout_dataset_schema.py +@@ -8,6 +8,7 @@ def test_canonical_rollout_fields_exclude_legacy_aliases(): + "image", + "env_name", + "episode_idx", ++ "trajectory_idx", + "decision_step", + "split", + "seed", +@@ -36,6 +37,7 @@ def test_rollout_features_include_env_specific_action_fields(): + assert "action_tuple" not in deadly_features + assert "action" not in deadly_features + for features in (flappy_features, deadly_features): ++ assert "trajectory_idx" in features + assert "decision_step" in features + assert "latency_raw_frames" in features + assert "raw_reward" in features +diff --git a/tests/data/test_rollout_hf_parquet.py b/tests/data/test_rollout_hf_parquet.py +index 9fa4c48..4e56de6 100644 +--- a/tests/data/test_rollout_hf_parquet.py ++++ b/tests/data/test_rollout_hf_parquet.py +@@ -15,6 +15,7 @@ def test_hf_parquet_writes_canonical_columns_only(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -56,6 +57,7 @@ def test_hf_parquet_shards_sort_by_decision_step(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": decision_step, + "split": "train", + "seed": 11, +@@ -92,6 +94,7 @@ def test_hf_parquet_embeds_context_images_when_rows_provide_them(tmp_path): + "context_images": [str(path) for path in context_paths], + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -116,3 +119,18 @@ def test_hf_parquet_embeds_context_images_when_rows_provide_them(tmp_path): + assert "context_images" in table.column_names + assert len(exported["context_images"]) == 3 + assert exported["context_images"][0]["bytes"].startswith(b"\x89PNG\r\n\x1a\n") ++ ++ ++def test_completed_episode_shards_require_trajectory_identity(tmp_path): ++ import json ++ ++ import pytest ++ ++ from latency_bench.data.hf_parquet import completed_episode_indices_from_shards ++ ++ shard_path = tmp_path / "episode_rows" / "train" / "episode_000000.jsonl" ++ shard_path.parent.mkdir(parents=True) ++ shard_path.write_text(json.dumps({"episode_idx": 0}) + "\n", encoding="utf-8") ++ ++ with pytest.raises(KeyError, match="trajectory_idx"): ++ completed_episode_indices_from_shards(tmp_path) +diff --git a/tests/data/test_sf_teacher_dataset_export.py b/tests/data/test_sf_teacher_dataset_export.py +index 62b30a6..ba4644b 100644 +--- a/tests/data/test_sf_teacher_dataset_export.py ++++ b/tests/data/test_sf_teacher_dataset_export.py +@@ -1299,7 +1299,7 @@ def test_write_filtered_episode_images_preserves_empty_filtered_episode(tmp_path + + image_writer = RolloutImageWriter(max_workers=0, row_buffer_size=1, export_image_size=None) + +- rows = _write_filtered_episode_images(image_writer, [], {}, context_window=5) ++ rows = _write_filtered_episode_images(image_writer, [], {}, {}, context_window=5) + + assert rows == [] + +@@ -1314,6 +1314,7 @@ def test_write_filtered_episode_images_resets_context_after_decision_step_gap(tm + { + "image": str(tmp_path / "images" / "train" / "episode_000000" / f"decision_step_{step:06d}.png"), + "decision_step": step, ++ "trajectory_idx": 0, + } + for step in [0, 1, 4, 5] + ] +@@ -1326,6 +1327,7 @@ def test_write_filtered_episode_images_resets_context_after_decision_step_gap(tm + image_writer, + rows, + frames_by_decision_step, ++ {step: 0 for step in frames_by_decision_step}, + context_window=4, + ) + +@@ -1733,13 +1735,24 @@ def test_collect_teacher_dataset_demon_attack_exports_full_game_across_life_loss + image_writer_workers=0, + row_buffer_size=1, + filter_preset="none", ++ context_window=3, + ) + train_rows = _read_shard_rows(output_dir, "train") + state = json.loads((output_dir / "probe_state.json").read_text(encoding="utf-8")) + + assert ScriptedDemonEnv.reset_seeds == [100, None, None, 100, None, None] +- assert [row["decision_step"] for row in train_rows] == [2] +- assert train_rows[0]["raw_reward"] == 30.0 ++ assert [row["decision_step"] for row in train_rows] == [0, 1, 2] ++ assert [row["trajectory_idx"] for row in train_rows] == [0, 1, 2] ++ assert [row["action_id"] for row in train_rows] == [1, 1, 1] ++ assert [row["raw_reward"] for row in train_rows] == [10.0, 20.0, 30.0] ++ from PIL import Image ++ ++ context_values = [ ++ [np.asarray(Image.open(path))[0, 0, 0].item() for path in row["context_images"]] ++ for row in train_rows ++ ] ++ current_values = [np.asarray(Image.open(row["image"]))[0, 0, 0].item() for row in train_rows] ++ assert context_values == [[value, value] for value in current_values] + assert state["accepted_specs"] == [ + { + "attempt_idx": 0, +@@ -1900,6 +1913,7 @@ def test_collect_teacher_dataset_skips_runtime_when_probe_and_shards_complete(mo + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 100, +@@ -2264,6 +2278,7 @@ def test_write_parquet_splits_handles_empty_validation_rows(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -2300,6 +2315,7 @@ def test_write_parquet_splits_embeds_image_bytes(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -2336,6 +2352,7 @@ def test_write_parquet_splits_preserves_rows_across_large_exports(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": episode_idx, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11 + episode_idx, +@@ -2390,6 +2407,7 @@ def test_write_parquet_splits_from_shards_writes_train_and_val_rows(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": episode_idx, ++ "trajectory_idx": 0, + "decision_step": decision_step, + "split": split, + "seed": 11 + episode_idx, +@@ -2432,6 +2450,7 @@ def test_write_parquet_splits_from_shards_replaces_stale_partial_file(tmp_path): + "image": str(stale_image_path), + "env_name": "flappy", + "episode_idx": 99, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 99, +@@ -2452,6 +2471,7 @@ def test_write_parquet_splits_from_shards_replaces_stale_partial_file(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -2536,6 +2556,8 @@ def test_prepare_starvla_lerobot_dataset_converts_from_raw_export(monkeypatch, t + str(raw_export), + str(tmp_path / "lerobot"), + "demon_attack_train", ++ "--action-carrier", ++ "bridge", + ]) + + assert result == 0 +@@ -2543,7 +2565,7 @@ def test_prepare_starvla_lerobot_dataset_converts_from_raw_export(monkeypatch, t + ( + raw_export, + tmp_path / "lerobot" / "demon_attack_train", +- {"force": True}, ++ {"action_carrier": "bridge", "force": True}, + ) + ] + +diff --git a/tests/data/test_starvla_lerobot_exporter.py b/tests/data/test_starvla_lerobot_exporter.py +index 64b5f47..58391c7 100644 +--- a/tests/data/test_starvla_lerobot_exporter.py ++++ b/tests/data/test_starvla_lerobot_exporter.py +@@ -3,6 +3,7 @@ from __future__ import annotations + import json + + import pyarrow.parquet as pq ++import pytest + + from helpers import save_test_image + +@@ -20,6 +21,7 @@ def test_starvla_lerobot_exporter_reads_canonical_rollout_schema(tmp_path): + "image": str(image_path), + "env_name": "deadly_corridor", + "episode_idx": 3, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 14, +@@ -38,6 +40,7 @@ def test_starvla_lerobot_exporter_reads_canonical_rollout_schema(tmp_path): + "action_layout": "deadly_corridor_joint_54", + "reward_field": "raw_reward", + "action_labels": list(action_spec.labels), ++ "obs_fps": 8.75, + } + ), + encoding="utf-8", +@@ -54,10 +57,102 @@ def test_starvla_lerobot_exporter_reads_canonical_rollout_schema(tmp_path): + assert table.to_pylist()[0]["done"] is True + + +-def test_starvla_lerobot_exporter_subsamples_to_obs_cadence(tmp_path): +- """Adjacent LeRobot rows must be adjacent obs decisions (every obs_stride raw +- frames), with contiguous frame_index, so KV-memory rollouts unroll at the eval +- observation cadence rather than at every raw frame.""" ++@pytest.mark.parametrize( ++ ("env_name", "obs_fps", "latency", "action_values", "expected_action", "active_action_dim"), ++ [ ++ ("flappy", 30, 3, (1, [0.0, 1.0], "FLAP"), [0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0], 2), ++ ( ++ "demon_attack", ++ 15, ++ 6, ++ (5, [0.0, 0.0, 0.0, 0.0, 0.0, 1.0], "LEFTFIRE"), ++ [0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0], ++ 6, ++ ), ++ ( ++ "deadly_corridor", ++ 8.75, ++ 6, ++ (11, None, "MOVE_FORWARD + MOVE_RIGHT + ATTACK"), ++ [1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 1.0], ++ 7, ++ ), ++ ], ++) ++def test_starvla_lerobot_exporter_writes_bridge_carrier_with_raw_latency_prompt( ++ tmp_path, ++ env_name, ++ obs_fps, ++ latency, ++ action_values, ++ expected_action, ++ active_action_dim, ++): ++ from latency_bench.data.action_layouts import action_spec_for_env ++ from latency_bench.data.exporters.starvla_lerobot import convert_canonical_rollout_to_lerobot ++ from latency_bench.data.hf_parquet import write_parquet_splits ++ ++ image_path = tmp_path / "image.png" ++ save_test_image(image_path, 9) ++ raw_export = tmp_path / "raw" ++ action_spec = action_spec_for_env(env_name) ++ action_id, action, action_text = action_values ++ row = { ++ "image": str(image_path), ++ "env_name": env_name, ++ "episode_idx": 0, ++ "trajectory_idx": 0, ++ "decision_step": 0, ++ "split": "train", ++ "seed": 0, ++ "prompt": f"The action latency is fixed at {latency} raw environment frames.", ++ "latency_raw_frames": latency, ++ "latency_ms": latency * 1000 / {"flappy": 30, "demon_attack": 60, "deadly_corridor": 35}[env_name], ++ "raw_reward": 1.0, ++ "action_id": action_id, ++ "action_text": action_text, ++ } ++ if action is not None: ++ row["action"] = action ++ write_parquet_splits(raw_export, [row], [], action_spec=action_spec) ++ (raw_export / "metadata.json").write_text( ++ json.dumps( ++ { ++ "env_name": env_name, ++ "action_layout": action_spec.layout, ++ "reward_field": action_spec.reward_field, ++ "action_labels": list(action_spec.labels), ++ "obs_fps": obs_fps, ++ } ++ ), ++ encoding="utf-8", ++ ) ++ ++ manifest = convert_canonical_rollout_to_lerobot( ++ raw_export, ++ tmp_path / "lerobot", ++ action_carrier="bridge", ++ force=True, ++ ) ++ ++ table = pq.read_table(tmp_path / "lerobot" / "data" / "chunk-000" / "episode_000000.parquet") ++ info = json.loads((tmp_path / "lerobot" / "meta" / "info.json").read_text(encoding="utf-8")) ++ task_lines = (tmp_path / "lerobot" / "meta" / "tasks.jsonl").read_text( ++ encoding="utf-8" ++ ).splitlines() ++ tasks = [json.loads(line) for line in task_lines] ++ converted_row = table.to_pylist()[0] ++ assert converted_row["action"] == expected_action ++ assert converted_row["observation.state"] == [0.0] * 7 ++ assert info["features"]["action"]["shape"] == [7] ++ assert info["features"]["observation.state"]["shape"] == [7] ++ assert tasks == [{"task_index": 0, "task": row["prompt"]}] ++ assert manifest["action_carrier"] == "bridge" ++ assert manifest["active_action_dim"] == active_action_dim ++ ++ ++def test_starvla_lerobot_exporter_keeps_every_observation_decision(tmp_path): ++ """Canonical rows already occur at the policy observation cadence.""" + from latency_bench.data.action_layouts import action_spec_for_env + from latency_bench.data.exporters.starvla_lerobot import convert_canonical_rollout_to_lerobot + from latency_bench.data.hf_parquet import write_parquet_splits +@@ -66,12 +161,13 @@ def test_starvla_lerobot_exporter_subsamples_to_obs_cadence(tmp_path): + save_test_image(image_path, 9) + raw_export = tmp_path / "raw" + action_spec = action_spec_for_env("deadly_corridor") +- # One episode, 8 contiguous per-raw-frame decision steps; obs_stride = 4. ++ # One trajectory with eight contiguous policy-decision observations. + train_rows = [ + { + "image": str(image_path), + "env_name": "deadly_corridor", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": step, + "split": "train", + "seed": 7, +@@ -92,6 +188,7 @@ def test_starvla_lerobot_exporter_subsamples_to_obs_cadence(tmp_path): + "action_layout": "deadly_corridor_joint_54", + "reward_field": "raw_reward", + "action_labels": list(action_spec.labels), ++ "obs_fps": 8.75, + "obs_stride_raw_frames": 4, + } + ), +@@ -102,12 +199,73 @@ def test_starvla_lerobot_exporter_subsamples_to_obs_cadence(tmp_path): + + table = pq.read_table(tmp_path / "lerobot" / "data" / "chunk-000" / "episode_000000.parquet") + rows = table.to_pylist() +- # Only decision_steps 0 and 4 survive; frame_index is contiguous obs index. +- assert [r["frame_index"] for r in rows] == [0, 1] +- assert [r["episode_index"] for r in rows] == [0, 0] ++ assert [r["frame_index"] for r in rows] == list(range(8)) ++ assert [r["episode_index"] for r in rows] == [0] * 8 + assert rows[-1]["done"] is True + + ++def test_starvla_lerobot_exporter_splits_life_trajectories(tmp_path): ++ from latency_bench.data.action_layouts import action_spec_for_env ++ from latency_bench.data.exporters.starvla_lerobot import convert_canonical_rollout_to_lerobot ++ from latency_bench.data.hf_parquet import write_parquet_splits ++ ++ image_path = tmp_path / "image.png" ++ save_test_image(image_path, 9) ++ raw_export = tmp_path / "raw" ++ action_spec = action_spec_for_env("demon_attack") ++ train_rows = [ ++ { ++ "image": str(image_path), ++ "env_name": "demon_attack", ++ "episode_idx": 0, ++ "trajectory_idx": trajectory_idx, ++ "decision_step": decision_step, ++ "split": "train", ++ "seed": 7, ++ "prompt": "pick action", ++ "latency_raw_frames": 6, ++ "latency_ms": 100.0, ++ "raw_reward": 1.0, ++ "action_id": 0, ++ "action": [1.0, 0.0, 0.0, 0.0, 0.0, 0.0], ++ "action_text": "NOOP", ++ } ++ for trajectory_idx, decision_step in ((0, 0), (0, 1), (1, 2), (1, 3)) ++ ] ++ write_parquet_splits(raw_export, train_rows, [], action_spec=action_spec) ++ (raw_export / "metadata.json").write_text( ++ json.dumps( ++ { ++ "env_name": "demon_attack", ++ "action_layout": action_spec.layout, ++ "reward_field": action_spec.reward_field, ++ "action_labels": list(action_spec.labels), ++ "obs_fps": 15, ++ } ++ ), ++ encoding="utf-8", ++ ) ++ ++ manifest = convert_canonical_rollout_to_lerobot( ++ raw_export, ++ tmp_path / "lerobot", ++ action_carrier="bridge", ++ force=True, ++ ) ++ ++ first = pq.read_table( ++ tmp_path / "lerobot" / "data" / "chunk-000" / "episode_000000.parquet" ++ ).to_pylist() ++ second = pq.read_table( ++ tmp_path / "lerobot" / "data" / "chunk-000" / "episode_000001.parquet" ++ ).to_pylist() ++ assert manifest["episodes"] == 2 ++ assert [row["frame_index"] for row in first] == [0, 1] ++ assert [row["frame_index"] for row in second] == [0, 1] ++ assert [row["done"] for row in first] == [False, True] ++ assert [row["done"] for row in second] == [False, True] ++ ++ + def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + from datasets import Dataset, Features, Image as HFImage, Sequence as HFSequence, Value + from latency_bench.data.exporters.starvla_lerobot import convert_canonical_rollout_to_lerobot +@@ -121,6 +279,7 @@ def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + "image": HFImage(), + "env_name": Value("string"), + "episode_idx": Value("int64"), ++ "trajectory_idx": Value("int64"), + "decision_step": Value("int64"), + "split": Value("string"), + "seed": Value("int64"), +@@ -138,6 +297,7 @@ def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + "image": [str(image_path)], + "env_name": ["flappy"], + "episode_idx": [0], ++ "trajectory_idx": [0], + "decision_step": [0], + "split": ["train"], + "seed": [11], +@@ -156,6 +316,7 @@ def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + "image": [str(image_path)], + "env_name": ["flappy"], + "episode_idx": [1], ++ "trajectory_idx": [0], + "decision_step": [0], + "split": ["val"], + "seed": [12], +@@ -176,6 +337,7 @@ def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + "action_layout": "flappy_discrete", + "reward_field": "raw_reward", + "action_labels": ["NOOP", "FLAP"], ++ "obs_fps": 30, + } + ), + encoding="utf-8", +diff --git a/tests/scripts/test_generate_sweep_configs.py b/tests/scripts/test_generate_sweep_configs.py +index 23d79cb..1fe6cef 100644 +--- a/tests/scripts/test_generate_sweep_configs.py ++++ b/tests/scripts/test_generate_sweep_configs.py +@@ -23,6 +23,73 @@ def _read_manifest(path: Path) -> list[dict[str, str]]: + return [dict(zip(header, line.split("\t"))) for line in lines[1:]] + + ++@pytest.mark.parametrize( ++ ("env_name", "latency_label", "latency_frames", "obs_fps", "obs_fps_label"), ++ [ ++ ("flappy", "fixed_l3", 3, 30, "30"), ++ ("demon_attack", "fixed_l6", 6, 15, "15"), ++ ("deadly_corridor", "fixed_l6", 6, 8.75, "8p75"), ++ ], ++) ++def test_memory_rollout_teacher_spec_emits_single_uploadable_job( ++ tmp_path, ++ env_name, ++ latency_label, ++ latency_frames, ++ obs_fps, ++ obs_fps_label, ++): ++ generated_root = tmp_path / "configs" ++ output_root = tmp_path / "outputs" ++ train_dir = tmp_path / "checkpoints" ++ ++ generate_sweep_configs( ++ [ ++ "--spec", ++ f"configs/experiments/memory/rollout_teacher/{env_name}.yaml", ++ "--generated-root", ++ str(generated_root), ++ "--output-root", ++ str(output_root), ++ "--train-dir", ++ str(train_dir), ++ ] ++ ) ++ ++ rows = _read_manifest(generated_root / "manifest.tsv") ++ assert len(rows) == 1 ++ row = rows[0] ++ assert row["env"] == env_name ++ assert row["experiment_family"] == "memory_rollout_teacher" ++ assert row["sweep_name"] == "teacher" ++ assert row["seed"] == "0" ++ assert row["frame_stack"] == "4" ++ assert row["obs_fps"] == obs_fps_label ++ assert row["latency_label"] == latency_label ++ assert row["latency_kind"] == "fixed" ++ assert row["latency_fixed_frames"] == str(latency_frames) ++ assert row["train_upload_repo_id"] == "latency-sensitive-bench/paper-experiment-models" ++ assert row["train_upload_repo_type"] == "model" ++ assert row["eval_upload_repo_id"] == "" ++ assert row["train_artifact_repo_path"].startswith( ++ f"memory/rollout_teachers/{env_name}/train/" ++ ) ++ ++ train_cfg = yaml.safe_load(Path(row["train_config"]).read_text(encoding="utf-8")) ++ assert train_cfg["experiment"]["seed"] == 0 ++ assert train_cfg["env"]["frame_stack"] == 4 ++ assert train_cfg["env"]["obs_fps"] == pytest.approx(obs_fps) ++ assert train_cfg["latency"]["method"] == "fixed" ++ assert train_cfg["latency"]["fixed_latency_ms"] == pytest.approx( ++ latency_frames * 1000 / train_cfg["env"]["env_fps"] ++ ) ++ assert train_cfg["evaluation"]["eval_suites"] == { ++ "fixed": [[latency_frames]], ++ "normal": [], ++ "uniform": [], ++ } ++ ++ + def test_latency_bench_eval_config_disables_full_trace_records(tmp_path): + base_config = { + "backend": { +diff --git a/tests/scripts/test_manifest_jobs.py b/tests/scripts/test_manifest_jobs.py +index bd7bf03..4546ac6 100644 +--- a/tests/scripts/test_manifest_jobs.py ++++ b/tests/scripts/test_manifest_jobs.py +@@ -1,8 +1,10 @@ + from __future__ import annotations + ++import json + import os +-import subprocess ++import shlex + import signal ++import subprocess + import sys + import threading + import time +@@ -10,6 +12,7 @@ import types + from pathlib import Path + + import pytest ++from helpers import REPO_ROOT + + import scripts.experiment_runner.run_manifest_jobs as run_manifest_jobs + from scripts.experiment_runner.job_manifest import ( +@@ -310,6 +313,186 @@ def test_run_command_cleanup_terminates_child_process_group(tmp_path): + os.kill(child_pid, 0) + + ++def test_sigint_cancels_queue_and_kills_all_active_process_groups(tmp_path): ++ helper_path = tmp_path / "ignore_term_job.py" ++ helper_path.write_text( ++ """from __future__ import annotations ++ ++import json ++import os ++from pathlib import Path ++import signal ++import subprocess ++import sys ++import time ++ ++signal.signal(signal.SIGTERM, signal.SIG_IGN) ++child = subprocess.Popen( ++ [ ++ sys.executable, ++ "-c", ++ "import signal, time; signal.signal(signal.SIGTERM, signal.SIG_IGN); time.sleep(60)", ++ ] ++) ++Path(sys.argv[1]).write_text( ++ json.dumps( ++ { ++ "leader_pid": os.getpid(), ++ "leader_pgid": os.getpgid(0), ++ "child_pid": child.pid, ++ "child_pgid": os.getpgid(child.pid), ++ } ++ ), ++ encoding="utf-8", ++) ++time.sleep(60) ++""", ++ encoding="utf-8", ++ ) ++ manifest_path = tmp_path / "manifest.tsv" ++ markers = [tmp_path / f"job_{idx}.json" for idx in range(4)] ++ rows = [] ++ for idx, marker in enumerate(markers): ++ row = {column: "" for column in MANIFEST_V2_COLUMNS} ++ row.update( ++ { ++ "schema_version": "v2", ++ "job_id": f"job{idx}", ++ "train_command": f"exec {shlex.join([sys.executable, str(helper_path), str(marker)])}", ++ } ++ ) ++ rows.append(row) ++ write_manifest(manifest_path, rows) ++ ++ runner = subprocess.Popen( ++ [ ++ sys.executable, ++ "-m", ++ "scripts.experiment_runner.run_manifest_jobs", ++ "--manifest", ++ str(manifest_path), ++ "--stage", ++ "train", ++ "--gpus", ++ "0,1", ++ ], ++ cwd=REPO_ROOT, ++ stdout=subprocess.PIPE, ++ stderr=subprocess.PIPE, ++ text=True, ++ ) ++ process_groups: set[int] = set() ++ try: ++ deadline = time.time() + 10.0 ++ while sum(marker.is_file() for marker in markers) < 2 and time.time() < deadline: ++ time.sleep(0.05) ++ assert [marker.is_file() for marker in markers] == [True, True, False, False] ++ for marker in markers[:2]: ++ process_info = json.loads(marker.read_text(encoding="utf-8")) ++ assert process_info["leader_pgid"] == process_info["child_pgid"] ++ process_groups.add(int(process_info["leader_pgid"])) ++ ++ runner.send_signal(signal.SIGINT) ++ time.sleep(0.1) ++ runner.send_signal(signal.SIGINT) ++ stdout, stderr = runner.communicate(timeout=10.0) ++ assert runner.returncode != 0, (stdout, stderr) ++ assert [marker.is_file() for marker in markers] == [True, True, False, False] ++ ++ deadline = time.time() + 5.0 ++ while process_groups and time.time() < deadline: ++ for process_group in list(process_groups): ++ try: ++ os.killpg(process_group, 0) ++ except ProcessLookupError: ++ process_groups.remove(process_group) ++ time.sleep(0.05) ++ assert not process_groups ++ ++ events = load_events(event_log_path_for_manifest(manifest_path)) ++ assert [event["stage"] for event in events] == ["train_started", "train_started"] ++ finally: ++ if runner.poll() is None: ++ runner.kill() ++ runner.wait() ++ for process_group in process_groups: ++ try: ++ os.killpg(process_group, signal.SIGKILL) ++ except ProcessLookupError: ++ pass ++ ++ ++def test_sigint_does_not_wait_for_in_flight_upload(tmp_path): ++ manifest_path = tmp_path / "manifest.tsv" ++ row = {column: "" for column in MANIFEST_V2_COLUMNS} ++ row.update( ++ { ++ "schema_version": "v2", ++ "job_id": "job0", ++ "train_upload_repo_id": "repo-model", ++ "train_upload_repo_type": "model", ++ } ++ ) ++ write_manifest(manifest_path, [row]) ++ append_event( ++ event_log_path_for_manifest(manifest_path), ++ {"job_id": "job0", "stage": "eval_succeeded"}, ++ ) ++ upload_started = tmp_path / "upload_started" ++ helper_path = tmp_path / "blocking_upload_runner.py" ++ helper_path.write_text( ++ """from pathlib import Path ++import sys ++import time ++ ++from scripts.experiment_runner.run_manifest_jobs import run_jobs ++ ++manifest_path = Path(sys.argv[1]) ++upload_started = Path(sys.argv[2]) ++ ++def blocking_uploader(job): ++ del job ++ upload_started.write_text("started", encoding="utf-8") ++ time.sleep(60) ++ ++raise SystemExit( ++ run_jobs( ++ manifest_path=manifest_path, ++ gpus=[], ++ upload_workers=1, ++ max_upload_attempts=1, ++ stage="upload", ++ uploader=blocking_uploader, ++ ) ++) ++""", ++ encoding="utf-8", ++ ) ++ runner = subprocess.Popen( ++ [sys.executable, str(helper_path), str(manifest_path), str(upload_started)], ++ cwd=REPO_ROOT, ++ env={**os.environ, "PYTHONPATH": str(REPO_ROOT)}, ++ stdout=subprocess.PIPE, ++ stderr=subprocess.PIPE, ++ text=True, ++ ) ++ try: ++ deadline = time.time() + 10.0 ++ while not upload_started.is_file() and time.time() < deadline: ++ time.sleep(0.05) ++ assert upload_started.is_file() ++ ++ started_at = time.monotonic() ++ runner.send_signal(signal.SIGINT) ++ stdout, stderr = runner.communicate(timeout=5.0) ++ assert runner.returncode != 0, (stdout, stderr) ++ assert time.monotonic() - started_at < 3.0 ++ finally: ++ if runner.poll() is None: ++ runner.kill() ++ runner.wait() ++ ++ + def test_default_uploader_prefers_env_token_over_dotenv(monkeypatch, tmp_path): + monkeypatch.chdir(tmp_path) + (tmp_path / ".env").write_text("HF_TOKEN=dotenv-token\n", encoding="utf-8") diff --git a/evaluations/deadly-corridor/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/train/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/sf_log.txt b/evaluations/deadly-corridor/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/train/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/sf_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..35f77e2af3447422be12b765cbc3e124a62400ce --- /dev/null +++ b/evaluations/deadly-corridor/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/train/memory_rollout_teacher:deadly_corridor:teacher:fixed_l6:fs4:obs8p75:stride4:seed0/sf_log.txt @@ -0,0 +1,7835 @@ +[2026-07-22 18:41:43,635][3461960] Saving configuration to results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/config.json... +[2026-07-22 18:41:43,669][3461960] Rollout worker 0 uses device cpu +[2026-07-22 18:41:43,669][3461960] Rollout worker 1 uses device cpu +[2026-07-22 18:41:43,669][3461960] Rollout worker 2 uses device cpu +[2026-07-22 18:41:43,670][3461960] Rollout worker 3 uses device cpu +[2026-07-22 18:41:43,671][3461960] Rollout worker 4 uses device cpu +[2026-07-22 18:41:43,671][3461960] Rollout worker 5 uses device cpu +[2026-07-22 18:41:43,671][3461960] Rollout worker 6 uses device cpu +[2026-07-22 18:41:43,671][3461960] Rollout worker 7 uses device cpu +[2026-07-22 18:41:43,672][3461960] Rollout worker 8 uses device cpu +[2026-07-22 18:41:43,672][3461960] Rollout worker 9 uses device cpu +[2026-07-22 18:41:43,672][3461960] Rollout worker 10 uses device cpu +[2026-07-22 18:41:43,673][3461960] Rollout worker 11 uses device cpu +[2026-07-22 18:41:43,673][3461960] Rollout worker 12 uses device cpu +[2026-07-22 18:41:43,673][3461960] Rollout worker 13 uses device cpu +[2026-07-22 18:41:43,674][3461960] Rollout worker 14 uses device cpu +[2026-07-22 18:41:43,674][3461960] Rollout worker 15 uses device cpu +[2026-07-22 18:41:43,674][3461960] Rollout worker 16 uses device cpu +[2026-07-22 18:41:43,675][3461960] Rollout worker 17 uses device cpu +[2026-07-22 18:41:43,676][3461960] Rollout worker 18 uses device cpu +[2026-07-22 18:41:43,676][3461960] Rollout worker 19 uses device cpu +[2026-07-22 18:41:43,677][3461960] Rollout worker 20 uses device cpu +[2026-07-22 18:41:43,677][3461960] Rollout worker 21 uses device cpu +[2026-07-22 18:41:43,678][3461960] Rollout worker 22 uses device cpu +[2026-07-22 18:41:43,678][3461960] Rollout worker 23 uses device cpu +[2026-07-22 18:41:43,679][3461960] Rollout worker 24 uses device cpu +[2026-07-22 18:41:43,680][3461960] Rollout worker 25 uses device cpu +[2026-07-22 18:41:43,680][3461960] Rollout worker 26 uses device cpu +[2026-07-22 18:41:43,680][3461960] Rollout worker 27 uses device cpu +[2026-07-22 18:41:43,681][3461960] Rollout worker 28 uses device cpu +[2026-07-22 18:41:43,681][3461960] Rollout worker 29 uses device cpu +[2026-07-22 18:41:43,681][3461960] Rollout worker 30 uses device cpu +[2026-07-22 18:41:43,682][3461960] Rollout worker 31 uses device cpu +[2026-07-22 18:41:45,438][3461960] Using GPUs [0] for process 0 (actually maps to GPUs [0]) +[2026-07-22 18:41:45,439][3461960] InferenceWorker_p0-w0: min num requests: 10 +[2026-07-22 18:41:45,904][3461960] Starting all processes... +[2026-07-22 18:41:45,905][3461960] Starting process learner_proc0 +[2026-07-22 18:41:48,878][3461960] Starting all processes... +[2026-07-22 18:41:48,883][3461960] Starting process inference_proc0-0 +[2026-07-22 18:41:48,883][3461960] Starting process rollout_proc0 +[2026-07-22 18:41:48,883][3461960] Starting process rollout_proc1 +[2026-07-22 18:41:48,891][3469039] Using GPUs [0] for process 0 (actually maps to GPUs [0]) +[2026-07-22 18:41:48,883][3461960] Starting process rollout_proc2 +[2026-07-22 18:41:48,891][3469039] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for learning process 0 +[2026-07-22 18:41:48,884][3461960] Starting process rollout_proc3 +[2026-07-22 18:41:48,884][3461960] Starting process rollout_proc4 +[2026-07-22 18:41:48,884][3461960] Starting process rollout_proc5 +[2026-07-22 18:41:48,885][3461960] Starting process rollout_proc6 +[2026-07-22 18:41:48,890][3461960] Starting process rollout_proc7 +[2026-07-22 18:41:48,890][3461960] Starting process rollout_proc8 +[2026-07-22 18:41:48,890][3461960] Starting process rollout_proc9 +[2026-07-22 18:41:48,891][3461960] Starting process rollout_proc10 +[2026-07-22 18:41:48,891][3461960] Starting process rollout_proc11 +[2026-07-22 18:41:48,891][3461960] Starting process rollout_proc12 +[2026-07-22 18:41:48,892][3461960] Starting process rollout_proc13 +[2026-07-22 18:41:48,895][3461960] Starting process rollout_proc14 +[2026-07-22 18:41:48,932][3469039] Num visible devices: 1 +[2026-07-22 18:41:48,933][3469039] Setting fixed seed 0 +[2026-07-22 18:41:48,935][3469039] Using GPUs [0] for process 0 (actually maps to GPUs [0]) +[2026-07-22 18:41:48,935][3469039] Initializing actor-critic model on device cuda:0 +[2026-07-22 18:41:48,936][3469039] RunningMeanStd input shape: (12, 72, 128) +[2026-07-22 18:41:48,937][3469039] RunningMeanStd input shape: (1,) +[2026-07-22 18:41:48,949][3469039] ConvEncoder: input_channels=12 +[2026-07-22 18:41:49,082][3469039] Conv encoder output size: 512 +[2026-07-22 18:41:49,082][3469039] Policy head output size: 512 +[2026-07-22 18:41:49,096][3469039] Created Actor Critic model with architecture: +[2026-07-22 18:41:49,097][3469039] ActorCriticSharedWeights( + (obs_normalizer): ObservationNormalizer( + (running_mean_std): RunningMeanStdDictInPlace( + (running_mean_std): ModuleDict( + (obs): RunningMeanStdInPlace() + ) + ) + ) + (returns_normalizer): RecursiveScriptModule(original_name=RunningMeanStdInPlace) + (encoder): VizdoomEncoder( + (basic_encoder): ConvEncoder( + (enc): RecursiveScriptModule( + original_name=ConvEncoderImpl + (conv_head): RecursiveScriptModule( + original_name=Sequential + (0): RecursiveScriptModule(original_name=Conv2d) + (1): RecursiveScriptModule(original_name=ELU) + (2): RecursiveScriptModule(original_name=Conv2d) + (3): RecursiveScriptModule(original_name=ELU) + (4): RecursiveScriptModule(original_name=Conv2d) + (5): RecursiveScriptModule(original_name=ELU) + ) + (mlp_layers): RecursiveScriptModule( + original_name=Sequential + (0): RecursiveScriptModule(original_name=Linear) + (1): RecursiveScriptModule(original_name=ELU) + ) + ) + ) + ) + (core): ModelCoreRNN( + (core): GRU(512, 512) + ) + (decoder): MlpDecoder( + (mlp): Identity() + ) + (critic_linear): Linear(in_features=512, out_features=1, bias=True) + (action_parameterization): ActionParameterizationDefault( + (distribution_linear): Linear(in_features=512, out_features=11, bias=True) + ) +) +[2026-07-22 18:41:50,001][3469039] Using optimizer +[2026-07-22 18:41:51,292][3469039] No checkpoints found +[2026-07-22 18:41:51,292][3469039] Did not load from checkpoint, starting from scratch! +[2026-07-22 18:41:51,292][3469039] Initialized policy 0 weights for model version 0 +[2026-07-22 18:41:51,294][3469039] Using GPUs [0] for process 0 (actually maps to GPUs [0]) +[2026-07-22 18:41:51,298][3469039] LearnerWorker_p0 finished initialization! +[2026-07-22 18:41:52,108][3461960] Starting process rollout_proc15 +[2026-07-22 18:41:52,109][3469869] Worker 11 uses CPU cores [11] +[2026-07-22 18:41:52,124][3461960] Starting process rollout_proc16 +[2026-07-22 18:41:52,129][3469841] Using GPUs [0] for process 0 (actually maps to GPUs [0]) +[2026-07-22 18:41:52,129][3469841] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for inference process 0 +[2026-07-22 18:41:52,154][3469841] Num visible devices: 1 +[2026-07-22 18:41:52,227][3461960] Starting process rollout_proc17 +[2026-07-22 18:41:52,231][3469867] Worker 5 uses CPU cores [5] +[2026-07-22 18:41:52,236][3461960] Starting process rollout_proc18 +[2026-07-22 18:41:52,239][3469868] Worker 14 uses CPU cores [14] +[2026-07-22 18:41:52,361][3461960] Starting process rollout_proc19 +[2026-07-22 18:41:52,366][3469859] Worker 13 uses CPU cores [13] +[2026-07-22 18:41:52,402][3469841] RunningMeanStd input shape: (12, 72, 128) +[2026-07-22 18:41:52,404][3469841] RunningMeanStd input shape: (1,) +[2026-07-22 18:41:52,420][3461960] Starting process rollout_proc20 +[2026-07-22 18:41:52,420][3469841] ConvEncoder: input_channels=12 +[2026-07-22 18:41:52,424][3469857] Worker 2 uses CPU cores [2] +[2026-07-22 18:41:52,454][3461960] Starting process rollout_proc21 +[2026-07-22 18:41:52,461][3461960] Starting process rollout_proc22 +[2026-07-22 18:41:52,466][3469860] Worker 1 uses CPU cores [1] +[2026-07-22 18:41:52,470][3469858] Worker 8 uses CPU cores [8] +[2026-07-22 18:41:52,503][3461960] Starting process rollout_proc23 +[2026-07-22 18:41:52,506][3469870] Worker 4 uses CPU cores [4] +[2026-07-22 18:41:52,518][3461960] Starting process rollout_proc24 +[2026-07-22 18:41:52,538][3469861] Worker 7 uses CPU cores [7] +[2026-07-22 18:41:52,549][3469841] Conv encoder output size: 512 +[2026-07-22 18:41:52,550][3469841] Policy head output size: 512 +[2026-07-22 18:41:52,692][3461960] Starting process rollout_proc25 +[2026-07-22 18:41:52,694][3469863] Worker 3 uses CPU cores [3] +[2026-07-22 18:41:52,706][3461960] Starting process rollout_proc26 +[2026-07-22 18:41:52,714][3469871] Worker 6 uses CPU cores [6] +[2026-07-22 18:41:52,797][3461960] Starting process rollout_proc27 +[2026-07-22 18:41:52,802][3469842] Worker 0 uses CPU cores [0] +[2026-07-22 18:41:52,801][3461960] Starting process rollout_proc28 +[2026-07-22 18:41:52,802][3469862] Worker 12 uses CPU cores [12] +[2026-07-22 18:41:52,805][3461960] Starting process rollout_proc29 +[2026-07-22 18:41:52,805][3469865] Worker 9 uses CPU cores [9] +[2026-07-22 18:41:53,044][3461960] Starting process rollout_proc30 +[2026-07-22 18:41:53,054][3469864] Worker 10 uses CPU cores [10] +[2026-07-22 18:41:55,482][3461960] Starting process rollout_proc31 +[2026-07-22 18:41:55,486][3470806] Worker 16 uses CPU cores [16] +[2026-07-22 18:41:55,696][3470798] Worker 15 uses CPU cores [15] +[2026-07-22 18:41:55,727][3470824] Worker 18 uses CPU cores [18] +[2026-07-22 18:41:55,913][3470865] Worker 22 uses CPU cores [22] +[2026-07-22 18:41:56,042][3470862] Worker 21 uses CPU cores [21] +[2026-07-22 18:41:56,085][3470822] Worker 17 uses CPU cores [17] +[2026-07-22 18:41:56,095][3470845] Worker 19 uses CPU cores [19] +[2026-07-22 18:41:56,118][3470875] Worker 24 uses CPU cores [24] +[2026-07-22 18:41:56,230][3470903] Worker 25 uses CPU cores [25] +[2026-07-22 18:41:56,276][3470924] Worker 28 uses CPU cores [0, 1, 2, 3, 4, 5, 6] +[2026-07-22 18:41:56,288][3470925] Worker 29 uses CPU cores [7, 8, 9, 10, 11, 12, 13] +[2026-07-22 18:41:56,309][3470873] Worker 23 uses CPU cores [23] +[2026-07-22 18:41:56,371][3470857] Worker 20 uses CPU cores [20] +[2026-07-22 18:41:56,416][3470906] Worker 26 uses CPU cores [26] +[2026-07-22 18:41:56,541][3470922] Worker 27 uses CPU cores [27] +[2026-07-22 18:41:56,547][3471088] Worker 30 uses CPU cores [14, 15, 16, 17, 18, 19, 20] +[2026-07-22 18:41:58,255][3461960] Inference worker 0-0 is ready! +[2026-07-22 18:41:58,256][3471751] Worker 31 uses CPU cores [21, 22, 23, 24, 25, 26, 27] +[2026-07-22 18:41:58,256][3461960] All inference workers are ready! Signal rollout workers to start! +[2026-07-22 18:41:58,258][3461960] Fps is (10 sec: nan, 60 sec: nan, 300 sec: nan). Total num frames: 0. Throughput: 0: nan. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) +[2026-07-22 18:41:58,269][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 0.0. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) +[2026-07-22 18:41:58,294][3470903] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,302][3470873] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,302][3469867] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,303][3469842] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,310][3469860] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,303][3469859] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,304][3470822] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,304][3469863] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,304][3469862] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,304][3470806] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,304][3470824] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,304][3469864] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,316][3469858] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,304][3469868] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,325][3470924] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,326][3470798] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,328][3471751] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,328][3469865] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,329][3469869] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,330][3471088] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,305][3470906] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,331][3470865] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,306][3470922] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,306][3470845] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,306][3470857] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,306][3470862] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,332][3469857] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,308][3469861] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,310][3469871] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,341][3469870] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,350][3470875] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,357][3470925] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 18:41:58,880][3470865] Decorrelating experience for 0 frames... +[2026-07-22 18:41:58,880][3470903] Decorrelating experience for 0 frames... +[2026-07-22 18:41:58,881][3469842] Decorrelating experience for 0 frames... +[2026-07-22 18:41:58,883][3470845] Decorrelating experience for 0 frames... +[2026-07-22 18:41:58,888][3469863] Decorrelating experience for 0 frames... +[2026-07-22 18:41:58,906][3470806] Decorrelating experience for 0 frames... +[2026-07-22 18:41:58,906][3470822] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,066][3470857] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,069][3470865] Decorrelating experience for 128 frames... +[2026-07-22 18:41:59,073][3469869] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,078][3469842] Decorrelating experience for 128 frames... +[2026-07-22 18:41:59,100][3470924] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,108][3470925] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,136][3469865] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,142][3470875] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,266][3470824] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,277][3470862] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,349][3469870] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,372][3469860] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,396][3470903] Decorrelating experience for 128 frames... +[2026-07-22 18:41:59,438][3470875] Decorrelating experience for 128 frames... +[2026-07-22 18:41:59,541][3469870] Decorrelating experience for 128 frames... +[2026-07-22 18:41:59,554][3470906] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,578][3469865] Decorrelating experience for 128 frames... +[2026-07-22 18:41:59,616][3470806] Decorrelating experience for 128 frames... +[2026-07-22 18:41:59,617][3470922] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,641][3469861] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,760][3470865] Decorrelating experience for 256 frames... +[2026-07-22 18:41:59,772][3469842] Decorrelating experience for 256 frames... +[2026-07-22 18:41:59,774][3469859] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,806][3470922] Decorrelating experience for 128 frames... +[2026-07-22 18:41:59,818][3471751] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,925][3469858] Decorrelating experience for 0 frames... +[2026-07-22 18:41:59,965][3469859] Decorrelating experience for 128 frames... +[2026-07-22 18:42:00,010][3469867] Decorrelating experience for 0 frames... +[2026-07-22 18:42:00,025][3469871] Decorrelating experience for 0 frames... +[2026-07-22 18:42:00,069][3470873] Decorrelating experience for 0 frames... +[2026-07-22 18:42:00,082][3470903] Decorrelating experience for 256 frames... +[2026-07-22 18:42:00,143][3469858] Decorrelating experience for 128 frames... +[2026-07-22 18:42:00,214][3470798] Decorrelating experience for 0 frames... +[2026-07-22 18:42:00,215][3469870] Decorrelating experience for 256 frames... +[2026-07-22 18:42:00,257][3471088] Decorrelating experience for 0 frames... +[2026-07-22 18:42:00,329][3470922] Decorrelating experience for 256 frames... +[2026-07-22 18:42:00,337][3470862] Decorrelating experience for 128 frames... +[2026-07-22 18:42:00,438][3470824] Decorrelating experience for 128 frames... +[2026-07-22 18:42:00,448][3471088] Decorrelating experience for 128 frames... +[2026-07-22 18:42:00,448][3470806] Decorrelating experience for 256 frames... +[2026-07-22 18:42:00,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 0.0. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) +[2026-07-22 18:42:00,555][3469871] Decorrelating experience for 128 frames... +[2026-07-22 18:42:00,616][3469858] Decorrelating experience for 256 frames... +[2026-07-22 18:42:00,637][3470906] Decorrelating experience for 128 frames... +[2026-07-22 18:42:00,746][3469861] Decorrelating experience for 128 frames... +[2026-07-22 18:42:00,777][3470875] Decorrelating experience for 256 frames... +[2026-07-22 18:42:00,844][3470903] Decorrelating experience for 384 frames... +[2026-07-22 18:42:00,986][3469868] Decorrelating experience for 0 frames... +[2026-07-22 18:42:01,057][3471088] Decorrelating experience for 256 frames... +[2026-07-22 18:42:01,200][3469868] Decorrelating experience for 128 frames... +[2026-07-22 18:42:01,283][3469858] Decorrelating experience for 384 frames... +[2026-07-22 18:42:01,303][3470922] Decorrelating experience for 384 frames... +[2026-07-22 18:42:01,391][3469861] Decorrelating experience for 256 frames... +[2026-07-22 18:42:01,722][3470906] Decorrelating experience for 256 frames... +[2026-07-22 18:42:01,729][3469868] Decorrelating experience for 256 frames... +[2026-07-22 18:42:01,838][3471088] Decorrelating experience for 384 frames... +[2026-07-22 18:42:01,889][3469862] Decorrelating experience for 0 frames... +[2026-07-22 18:42:01,891][3469864] Decorrelating experience for 0 frames... +[2026-07-22 18:42:01,975][3470875] Decorrelating experience for 384 frames... +[2026-07-22 18:42:02,041][3469861] Decorrelating experience for 384 frames... +[2026-07-22 18:42:02,076][3470865] Decorrelating experience for 384 frames... +[2026-07-22 18:42:02,084][3469862] Decorrelating experience for 128 frames... +[2026-07-22 18:42:02,189][3469864] Decorrelating experience for 128 frames... +[2026-07-22 18:42:02,230][3469869] Decorrelating experience for 128 frames... +[2026-07-22 18:42:02,286][3469857] Decorrelating experience for 0 frames... +[2026-07-22 18:42:02,525][3469868] Decorrelating experience for 384 frames... +[2026-07-22 18:42:02,535][3469859] Decorrelating experience for 256 frames... +[2026-07-22 18:42:02,583][3470798] Decorrelating experience for 128 frames... +[2026-07-22 18:42:02,690][3470906] Decorrelating experience for 384 frames... +[2026-07-22 18:42:02,748][3469862] Decorrelating experience for 256 frames... +[2026-07-22 18:42:02,771][3470822] Decorrelating experience for 128 frames... +[2026-07-22 18:42:02,782][3469870] Decorrelating experience for 384 frames... +[2026-07-22 18:42:02,963][3470824] Decorrelating experience for 256 frames... +[2026-07-22 18:42:02,969][3469864] Decorrelating experience for 256 frames... +[2026-07-22 18:42:02,992][3469869] Decorrelating experience for 256 frames... +[2026-07-22 18:42:03,005][3469863] Decorrelating experience for 128 frames... +[2026-07-22 18:42:03,147][3471751] Decorrelating experience for 128 frames... +[2026-07-22 18:42:03,232][3470822] Decorrelating experience for 256 frames... +[2026-07-22 18:42:03,241][3470925] Decorrelating experience for 128 frames... +[2026-07-22 18:42:03,360][3470798] Decorrelating experience for 256 frames... +[2026-07-22 18:42:03,434][3469857] Decorrelating experience for 128 frames... +[2026-07-22 18:42:03,580][3469867] Decorrelating experience for 128 frames... +[2026-07-22 18:42:03,626][3469859] Decorrelating experience for 384 frames... +[2026-07-22 18:42:03,750][3470806] Decorrelating experience for 384 frames... +[2026-07-22 18:42:03,840][3469862] Decorrelating experience for 384 frames... +[2026-07-22 18:42:03,865][3469865] Decorrelating experience for 256 frames... +[2026-07-22 18:42:03,886][3470824] Decorrelating experience for 384 frames... +[2026-07-22 18:42:03,934][3470845] Another process currently holds the lock /tmp/sf2_lixinyuan/doom_004.lockfile, attempt: 1, max_wait_sec=60.000 +[2026-07-22 18:42:03,952][3469857] Decorrelating experience for 256 frames... +[2026-07-22 18:42:03,958][3469871] Decorrelating experience for 256 frames... +[2026-07-22 18:42:04,012][3470925] Decorrelating experience for 256 frames... +[2026-07-22 18:42:04,038][3471751] Decorrelating experience for 256 frames... +[2026-07-22 18:42:04,148][3470857] Decorrelating experience for 128 frames... +[2026-07-22 18:42:04,149][3470924] Another process currently holds the lock /tmp/sf2_lixinyuan/doom_004.lockfile, attempt: 1, max_wait_sec=60.000 +[2026-07-22 18:42:04,175][3469864] Decorrelating experience for 384 frames... +[2026-07-22 18:42:04,190][3470798] Decorrelating experience for 384 frames... +[2026-07-22 18:42:04,252][3469867] Decorrelating experience for 256 frames... +[2026-07-22 18:42:04,272][3470845] Decorrelating experience for 128 frames... +[2026-07-22 18:42:04,317][3469869] Decorrelating experience for 384 frames... +[2026-07-22 18:42:04,367][3469842] Decorrelating experience for 384 frames... +[2026-07-22 18:42:04,426][3469860] Another process currently holds the lock /tmp/sf2_lixinyuan/doom_004.lockfile, attempt: 1, max_wait_sec=60.000 +[2026-07-22 18:42:04,651][3470924] Decorrelating experience for 128 frames... +[2026-07-22 18:42:04,666][3470822] Decorrelating experience for 384 frames... +[2026-07-22 18:42:04,800][3469860] Decorrelating experience for 128 frames... +[2026-07-22 18:42:04,808][3469857] Decorrelating experience for 384 frames... +[2026-07-22 18:42:04,879][3470857] Decorrelating experience for 256 frames... +[2026-07-22 18:42:05,003][3469863] Decorrelating experience for 256 frames... +[2026-07-22 18:42:05,076][3470845] Decorrelating experience for 256 frames... +[2026-07-22 18:42:05,135][3471751] Decorrelating experience for 384 frames... +[2026-07-22 18:42:05,182][3469865] Decorrelating experience for 384 frames... +[2026-07-22 18:42:05,319][3470873] Decorrelating experience for 128 frames... +[2026-07-22 18:42:05,432][3461960] Heartbeat connected on Batcher_0 +[2026-07-22 18:42:05,435][3461960] Heartbeat connected on LearnerWorker_p0 +[2026-07-22 18:42:05,448][3461960] Heartbeat connected on InferenceWorker_p0-w0 +[2026-07-22 18:42:05,456][3469871] Decorrelating experience for 384 frames... +[2026-07-22 18:42:05,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 234.2. Samples: 1692. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) +[2026-07-22 18:42:05,482][3461960] Avg episode reward: [(0, '-68.209')] +[2026-07-22 18:42:05,551][3461960] Heartbeat connected on RolloutWorker_w4 +[2026-07-22 18:42:05,552][3461960] Heartbeat connected on RolloutWorker_w7 +[2026-07-22 18:42:05,587][3461960] Heartbeat connected on RolloutWorker_w0 +[2026-07-22 18:42:05,677][3470924] Decorrelating experience for 256 frames... +[2026-07-22 18:42:05,679][3470862] Decorrelating experience for 256 frames... +[2026-07-22 18:42:05,732][3470925] Decorrelating experience for 384 frames... +[2026-07-22 18:42:05,750][3461960] Heartbeat connected on RolloutWorker_w8 +[2026-07-22 18:42:05,758][3461960] Heartbeat connected on RolloutWorker_w10 +[2026-07-22 18:42:05,758][3461960] Heartbeat connected on RolloutWorker_w11 +[2026-07-22 18:42:05,761][3461960] Heartbeat connected on RolloutWorker_w12 +[2026-07-22 18:42:05,764][3461960] Heartbeat connected on RolloutWorker_w13 +[2026-07-22 18:42:05,767][3461960] Heartbeat connected on RolloutWorker_w14 +[2026-07-22 18:42:05,770][3461960] Heartbeat connected on RolloutWorker_w15 +[2026-07-22 18:42:05,775][3461960] Heartbeat connected on RolloutWorker_w17 +[2026-07-22 18:42:05,778][3461960] Heartbeat connected on RolloutWorker_w18 +[2026-07-22 18:42:05,789][3461960] Heartbeat connected on RolloutWorker_w22 +[2026-07-22 18:42:05,796][3461960] Heartbeat connected on RolloutWorker_w24 +[2026-07-22 18:42:05,799][3461960] Heartbeat connected on RolloutWorker_w25 +[2026-07-22 18:42:05,803][3461960] Heartbeat connected on RolloutWorker_w26 +[2026-07-22 18:42:05,809][3461960] Heartbeat connected on RolloutWorker_w27 +[2026-07-22 18:42:05,818][3461960] Heartbeat connected on RolloutWorker_w30 +[2026-07-22 18:42:05,898][3461960] Heartbeat connected on RolloutWorker_w16 +[2026-07-22 18:42:05,965][3470845] Decorrelating experience for 384 frames... +[2026-07-22 18:42:05,974][3470857] Decorrelating experience for 384 frames... +[2026-07-22 18:42:05,981][3469867] Decorrelating experience for 384 frames... +[2026-07-22 18:42:05,997][3469860] Decorrelating experience for 256 frames... +[2026-07-22 18:42:06,103][3461960] Heartbeat connected on RolloutWorker_w9 +[2026-07-22 18:42:06,127][3469863] Decorrelating experience for 384 frames... +[2026-07-22 18:42:06,189][3461960] Heartbeat connected on RolloutWorker_w2 +[2026-07-22 18:42:06,211][3470873] Decorrelating experience for 256 frames... +[2026-07-22 18:42:06,382][3461960] Heartbeat connected on RolloutWorker_w31 +[2026-07-22 18:42:06,387][3461960] Heartbeat connected on RolloutWorker_w6 +[2026-07-22 18:42:06,828][3470862] Decorrelating experience for 384 frames... +[2026-07-22 18:42:06,883][3461960] Heartbeat connected on RolloutWorker_w19 +[2026-07-22 18:42:06,931][3469860] Decorrelating experience for 384 frames... +[2026-07-22 18:42:06,932][3461960] Heartbeat connected on RolloutWorker_w29 +[2026-07-22 18:42:06,942][3470924] Decorrelating experience for 384 frames... +[2026-07-22 18:42:06,962][3461960] Heartbeat connected on RolloutWorker_w5 +[2026-07-22 18:42:07,034][3470873] Decorrelating experience for 384 frames... +[2026-07-22 18:42:07,080][3461960] Heartbeat connected on RolloutWorker_w3 +[2026-07-22 18:42:07,171][3461960] Heartbeat connected on RolloutWorker_w20 +[2026-07-22 18:42:07,875][3461960] Heartbeat connected on RolloutWorker_w21 +[2026-07-22 18:42:07,913][3461960] Heartbeat connected on RolloutWorker_w1 +[2026-07-22 18:42:07,966][3461960] Heartbeat connected on RolloutWorker_w23 +[2026-07-22 18:42:08,337][3461960] Heartbeat connected on RolloutWorker_w28 +[2026-07-22 18:42:08,563][3469039] Signal inference workers to stop experience collection... +[2026-07-22 18:42:08,577][3469841] InferenceWorker_p0-w0: stopping experience collection +[2026-07-22 18:42:09,354][3469039] Signal inference workers to resume experience collection... +[2026-07-22 18:42:09,354][3469841] InferenceWorker_p0-w0: resuming experience collection +[2026-07-22 18:42:10,481][3461960] Fps is (10 sec: 409.6, 60 sec: 335.1, 300 sec: 335.1). Total num frames: 4096. Throughput: 0: 645.6. Samples: 7892. Policy #0 lag: (min: 3.0, avg: 3.0, max: 3.0) +[2026-07-22 18:42:10,482][3461960] Avg episode reward: [(0, '-61.627')] +[2026-07-22 18:42:12,401][3469841] Updated weights for policy 0, policy_version 19 (0.0071) +[2026-07-22 18:42:13,385][3469841] Updated weights for policy 0, policy_version 31 (0.0014) +[2026-07-22 18:42:15,021][3469841] Updated weights for policy 0, policy_version 44 (0.0011) +[2026-07-22 18:42:15,481][3461960] Fps is (10 sec: 2252.8, 60 sec: 1308.0, 300 sec: 1308.0). Total num frames: 22528. Throughput: 0: 1498.9. Samples: 25816. Policy #0 lag: (min: 3.0, avg: 19.4, max: 35.0) +[2026-07-22 18:42:15,482][3461960] Avg episode reward: [(0, '-16.322')] +[2026-07-22 18:42:16,277][3469841] Updated weights for policy 0, policy_version 54 (0.0018) +[2026-07-22 18:42:16,763][3469841] Updated weights for policy 0, policy_version 64 (0.0012) +[2026-07-22 18:42:18,396][3469841] Updated weights for policy 0, policy_version 74 (0.0012) +[2026-07-22 18:42:19,223][3469841] Updated weights for policy 0, policy_version 84 (0.0016) +[2026-07-22 18:42:20,342][3469841] Updated weights for policy 0, policy_version 94 (0.0015) +[2026-07-22 18:42:20,481][3461960] Fps is (10 sec: 4505.6, 60 sec: 2211.7, 300 sec: 2211.7). Total num frames: 49152. Throughput: 0: 2439.4. Samples: 54212. Policy #0 lag: (min: 2.0, avg: 16.9, max: 34.0) +[2026-07-22 18:42:20,482][3461960] Avg episode reward: [(0, '27.513')] +[2026-07-22 18:42:22,291][3469841] Updated weights for policy 0, policy_version 107 (0.0012) +[2026-07-22 18:42:23,274][3469841] Updated weights for policy 0, policy_version 117 (0.0021) +[2026-07-22 18:42:23,660][3469841] Updated weights for policy 0, policy_version 127 (0.0012) +[2026-07-22 18:42:25,481][3461960] Fps is (10 sec: 4710.3, 60 sec: 2557.8, 300 sec: 2557.8). Total num frames: 69632. Throughput: 0: 2448.6. Samples: 66660. Policy #0 lag: (min: 3.0, avg: 20.4, max: 35.0) +[2026-07-22 18:42:25,482][3461960] Avg episode reward: [(0, '75.512')] +[2026-07-22 18:42:25,693][3469841] Updated weights for policy 0, policy_version 137 (0.0016) +[2026-07-22 18:42:26,411][3469841] Updated weights for policy 0, policy_version 150 (0.0015) +[2026-07-22 18:42:27,321][3469841] Updated weights for policy 0, policy_version 160 (0.0011) +[2026-07-22 18:42:28,871][3469841] Updated weights for policy 0, policy_version 170 (0.0013) +[2026-07-22 18:42:29,718][3469841] Updated weights for policy 0, policy_version 180 (0.0018) +[2026-07-22 18:42:30,481][3461960] Fps is (10 sec: 4710.3, 60 sec: 2987.1, 300 sec: 2987.1). Total num frames: 96256. Throughput: 0: 2980.0. Samples: 96028. Policy #0 lag: (min: 3.0, avg: 15.3, max: 35.0) +[2026-07-22 18:42:30,482][3461960] Avg episode reward: [(0, '88.168')] +[2026-07-22 18:42:31,409][3469841] Updated weights for policy 0, policy_version 194 (0.0012) +[2026-07-22 18:42:33,325][3469841] Updated weights for policy 0, policy_version 206 (0.0018) +[2026-07-22 18:42:33,682][3469841] Updated weights for policy 0, policy_version 216 (0.0013) +[2026-07-22 18:42:35,016][3469841] Updated weights for policy 0, policy_version 226 (0.0011) +[2026-07-22 18:42:35,482][3461960] Fps is (10 sec: 4710.3, 60 sec: 3136.1, 300 sec: 3136.1). Total num frames: 116736. Throughput: 0: 3312.9. Samples: 123320. Policy #0 lag: (min: 3.0, avg: 22.5, max: 43.0) +[2026-07-22 18:42:35,482][3461960] Avg episode reward: [(0, '84.164')] +[2026-07-22 18:42:35,599][3469039] Saving new best policy, reward=84.164! +[2026-07-22 18:42:36,228][3469841] Updated weights for policy 0, policy_version 240 (0.0011) +[2026-07-22 18:42:37,096][3469841] Updated weights for policy 0, policy_version 250 (0.0012) +[2026-07-22 18:42:38,465][3469841] Updated weights for policy 0, policy_version 260 (0.0010) +[2026-07-22 18:42:39,740][3469841] Updated weights for policy 0, policy_version 272 (0.0013) +[2026-07-22 18:42:40,481][3461960] Fps is (10 sec: 4505.6, 60 sec: 3346.8, 300 sec: 3346.8). Total num frames: 141312. Throughput: 0: 3271.4. Samples: 138094. Policy #0 lag: (min: 3.0, avg: 17.5, max: 43.0) +[2026-07-22 18:42:40,482][3461960] Avg episode reward: [(0, '147.512')] +[2026-07-22 18:42:40,530][3469039] Saving new best policy, reward=147.512! +[2026-07-22 18:42:40,893][3469841] Updated weights for policy 0, policy_version 282 (0.0012) +[2026-07-22 18:42:42,158][3469841] Updated weights for policy 0, policy_version 292 (0.0016) +[2026-07-22 18:42:43,458][3469841] Updated weights for policy 0, policy_version 302 (0.0011) +[2026-07-22 18:42:43,868][3469841] Updated weights for policy 0, policy_version 312 (0.0012) +[2026-07-22 18:42:45,386][3469841] Updated weights for policy 0, policy_version 322 (0.0020) +[2026-07-22 18:42:45,481][3461960] Fps is (10 sec: 4915.3, 60 sec: 3512.8, 300 sec: 3512.8). Total num frames: 165888. Throughput: 0: 3679.7. Samples: 165586. Policy #0 lag: (min: 3.0, avg: 21.2, max: 41.0) +[2026-07-22 18:42:45,482][3461960] Avg episode reward: [(0, '127.931')] +[2026-07-22 18:42:46,706][3469841] Updated weights for policy 0, policy_version 332 (0.0011) +[2026-07-22 18:42:48,145][3469841] Updated weights for policy 0, policy_version 345 (0.0016) +[2026-07-22 18:42:48,996][3469841] Updated weights for policy 0, policy_version 355 (0.0011) +[2026-07-22 18:42:50,288][3469841] Updated weights for policy 0, policy_version 365 (0.0011) +[2026-07-22 18:42:50,481][3461960] Fps is (10 sec: 4710.4, 60 sec: 3607.9, 300 sec: 3607.9). Total num frames: 188416. Throughput: 0: 4272.0. Samples: 193934. Policy #0 lag: (min: 3.0, avg: 15.6, max: 38.0) +[2026-07-22 18:42:50,482][3461960] Avg episode reward: [(0, '192.801')] +[2026-07-22 18:42:50,587][3469039] Saving new best policy, reward=192.801! +[2026-07-22 18:42:50,959][3469841] Updated weights for policy 0, policy_version 375 (0.0016) +[2026-07-22 18:42:52,010][3469841] Updated weights for policy 0, policy_version 385 (0.0021) +[2026-07-22 18:42:53,288][3469841] Updated weights for policy 0, policy_version 395 (0.0012) +[2026-07-22 18:42:54,116][3469841] Updated weights for policy 0, policy_version 405 (0.0011) +[2026-07-22 18:42:55,038][3469841] Updated weights for policy 0, policy_version 415 (0.0012) +[2026-07-22 18:42:55,482][3461960] Fps is (10 sec: 4915.0, 60 sec: 3758.6, 300 sec: 3757.9). Total num frames: 215040. Throughput: 0: 4469.2. Samples: 209008. Policy #0 lag: (min: 3.0, avg: 19.8, max: 32.0) +[2026-07-22 18:42:55,482][3461960] Avg episode reward: [(0, '169.914')] +[2026-07-22 18:42:56,498][3469841] Updated weights for policy 0, policy_version 425 (0.0011) +[2026-07-22 18:42:57,112][3469841] Updated weights for policy 0, policy_version 435 (0.0013) +[2026-07-22 18:42:58,295][3469841] Updated weights for policy 0, policy_version 445 (0.0015) +[2026-07-22 18:42:59,272][3469841] Updated weights for policy 0, policy_version 455 (0.0013) +[2026-07-22 18:43:00,481][3461960] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3752.1). Total num frames: 233472. Throughput: 0: 4745.4. Samples: 239360. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:43:00,484][3461960] Avg episode reward: [(0, '175.293')] +[2026-07-22 18:43:05,481][3461960] Fps is (10 sec: 1843.3, 60 sec: 3891.2, 300 sec: 3473.1). Total num frames: 233472. Throughput: 0: 4707.2. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:43:05,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:43:10,481][3461960] Fps is (10 sec: 0.0, 60 sec: 3822.9, 300 sec: 3232.6). Total num frames: 233472. Throughput: 0: 4430.6. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:43:10,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:43:15,481][3461960] Fps is (10 sec: 0.0, 60 sec: 3515.7, 300 sec: 3023.3). Total num frames: 233472. Throughput: 0: 3778.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:43:15,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:43:20,481][3461960] Fps is (10 sec: 0.0, 60 sec: 3072.0, 300 sec: 2839.5). Total num frames: 233472. Throughput: 0: 3171.5. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:43:20,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:43:25,481][3461960] Fps is (10 sec: 0.0, 60 sec: 2730.7, 300 sec: 2676.7). Total num frames: 233472. Throughput: 0: 2843.2. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:43:25,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:43:30,481][3461960] Fps is (10 sec: 0.0, 60 sec: 2286.9, 300 sec: 2531.6). Total num frames: 233472. Throughput: 0: 2232.2. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:43:30,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:43:35,481][3461960] Fps is (10 sec: 0.0, 60 sec: 1945.6, 300 sec: 2401.4). Total num frames: 233472. Throughput: 0: 1602.3. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:43:35,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:43:40,481][3461960] Fps is (10 sec: 0.0, 60 sec: 1536.0, 300 sec: 2283.9). Total num frames: 233472. Throughput: 0: 1267.3. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:43:40,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:43:45,481][3461960] Fps is (10 sec: 0.0, 60 sec: 1126.4, 300 sec: 2177.4). Total num frames: 233472. Throughput: 0: 592.8. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:43:45,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:43:50,481][3461960] Fps is (10 sec: 0.0, 60 sec: 750.9, 300 sec: 2080.4). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:43:50,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:43:55,481][3461960] Fps is (10 sec: 0.0, 60 sec: 307.2, 300 sec: 1991.7). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:43:55,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:44:00,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1910.2). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:44:00,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:44:05,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1835.1). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:44:05,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:44:10,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1765.7). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:44:10,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:44:15,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1701.4). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:44:15,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:44:20,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1641.6). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:44:20,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:44:25,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1585.8). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:44:25,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:44:30,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1533.7). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:44:30,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:44:35,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1485.0). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:44:35,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:44:40,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1439.2). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:44:40,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:44:45,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1396.2). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:44:45,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:44:50,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1355.6). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:44:50,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:44:55,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1317.4). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:44:55,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:45:00,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1281.2). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:45:00,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:45:05,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1247.0). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:45:05,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:45:10,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1214.6). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:45:10,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:45:15,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1183.8). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:45:15,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:45:20,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1154.5). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:45:20,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:45:25,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1126.7). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:45:25,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:45:30,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1100.1). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:45:30,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:45:35,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1074.8). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:45:35,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:45:40,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1050.6). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:45:40,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:45:45,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1027.5). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:45:45,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:45:50,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 1005.4). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:45:50,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:45:55,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 984.2). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:45:55,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:46:00,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 963.9). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:46:00,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:46:05,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 944.4). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:46:05,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:46:10,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 925.7). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:46:10,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:46:15,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 907.7). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:46:15,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:46:20,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 890.4). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:46:20,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:46:25,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 873.7). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:46:25,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:46:30,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 857.6). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:46:30,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:46:35,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 842.2). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:46:35,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:46:40,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 827.3). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:46:40,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:46:45,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 812.9). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:46:45,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:46:50,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 799.0). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:46:50,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:46:55,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 791.4). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:46:55,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:47:00,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 791.4). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:47:00,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:47:05,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 777.5). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:47:05,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:47:10,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 715.1). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:47:10,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:47:15,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 624.8). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:47:15,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 18:47:20,481][3461960] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 555.4). Total num frames: 233472. Throughput: 0: 0.0. Samples: 266036. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 18:47:20,482][3461960] Avg episode reward: [(0, '253.870')] +[2026-07-22 19:32:42,803][43431] Saving configuration to results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/config.json... +[2026-07-22 19:32:42,820][43431] Rollout worker 0 uses device cpu +[2026-07-22 19:32:42,821][43431] Rollout worker 1 uses device cpu +[2026-07-22 19:32:42,821][43431] Rollout worker 2 uses device cpu +[2026-07-22 19:32:42,821][43431] Rollout worker 3 uses device cpu +[2026-07-22 19:32:42,822][43431] Rollout worker 4 uses device cpu +[2026-07-22 19:32:42,822][43431] Rollout worker 5 uses device cpu +[2026-07-22 19:32:42,822][43431] Rollout worker 6 uses device cpu +[2026-07-22 19:32:42,822][43431] Rollout worker 7 uses device cpu +[2026-07-22 19:32:42,823][43431] Rollout worker 8 uses device cpu +[2026-07-22 19:32:42,823][43431] Rollout worker 9 uses device cpu +[2026-07-22 19:32:42,824][43431] Rollout worker 10 uses device cpu +[2026-07-22 19:32:42,824][43431] Rollout worker 11 uses device cpu +[2026-07-22 19:32:42,825][43431] Rollout worker 12 uses device cpu +[2026-07-22 19:32:42,825][43431] Rollout worker 13 uses device cpu +[2026-07-22 19:32:42,825][43431] Rollout worker 14 uses device cpu +[2026-07-22 19:32:42,826][43431] Rollout worker 15 uses device cpu +[2026-07-22 19:32:42,826][43431] Rollout worker 16 uses device cpu +[2026-07-22 19:32:42,826][43431] Rollout worker 17 uses device cpu +[2026-07-22 19:32:42,826][43431] Rollout worker 18 uses device cpu +[2026-07-22 19:32:42,827][43431] Rollout worker 19 uses device cpu +[2026-07-22 19:32:42,827][43431] Rollout worker 20 uses device cpu +[2026-07-22 19:32:42,827][43431] Rollout worker 21 uses device cpu +[2026-07-22 19:32:42,827][43431] Rollout worker 22 uses device cpu +[2026-07-22 19:32:42,827][43431] Rollout worker 23 uses device cpu +[2026-07-22 19:32:42,828][43431] Rollout worker 24 uses device cpu +[2026-07-22 19:32:42,828][43431] Rollout worker 25 uses device cpu +[2026-07-22 19:32:42,828][43431] Rollout worker 26 uses device cpu +[2026-07-22 19:32:42,828][43431] Rollout worker 27 uses device cpu +[2026-07-22 19:32:42,828][43431] Rollout worker 28 uses device cpu +[2026-07-22 19:32:42,828][43431] Rollout worker 29 uses device cpu +[2026-07-22 19:32:42,829][43431] Rollout worker 30 uses device cpu +[2026-07-22 19:32:42,829][43431] Rollout worker 31 uses device cpu +[2026-07-22 19:32:44,426][43431] Using GPUs [0] for process 0 (actually maps to GPUs [0]) +[2026-07-22 19:32:44,427][43431] InferenceWorker_p0-w0: min num requests: 10 +[2026-07-22 19:32:44,536][43431] Starting all processes... +[2026-07-22 19:32:44,537][43431] Starting process learner_proc0 +[2026-07-22 19:32:46,897][43431] Starting all processes... +[2026-07-22 19:32:46,902][43431] Starting process inference_proc0-0 +[2026-07-22 19:32:46,902][43431] Starting process rollout_proc0 +[2026-07-22 19:32:46,906][49527] Using GPUs [0] for process 0 (actually maps to GPUs [0]) +[2026-07-22 19:32:46,906][49527] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for learning process 0 +[2026-07-22 19:32:46,902][43431] Starting process rollout_proc1 +[2026-07-22 19:32:46,902][43431] Starting process rollout_proc2 +[2026-07-22 19:32:46,902][43431] Starting process rollout_proc3 +[2026-07-22 19:32:46,903][43431] Starting process rollout_proc4 +[2026-07-22 19:32:46,903][43431] Starting process rollout_proc5 +[2026-07-22 19:32:46,910][43431] Starting process rollout_proc6 +[2026-07-22 19:32:46,910][43431] Starting process rollout_proc7 +[2026-07-22 19:32:46,912][43431] Starting process rollout_proc8 +[2026-07-22 19:32:46,913][43431] Starting process rollout_proc9 +[2026-07-22 19:32:46,914][43431] Starting process rollout_proc10 +[2026-07-22 19:32:46,916][43431] Starting process rollout_proc11 +[2026-07-22 19:32:46,918][43431] Starting process rollout_proc12 +[2026-07-22 19:32:46,923][43431] Starting process rollout_proc13 +[2026-07-22 19:32:46,925][43431] Starting process rollout_proc14 +[2026-07-22 19:32:46,952][49527] Num visible devices: 1 +[2026-07-22 19:32:46,953][49527] Setting fixed seed 0 +[2026-07-22 19:32:46,954][49527] Using GPUs [0] for process 0 (actually maps to GPUs [0]) +[2026-07-22 19:32:46,955][49527] Initializing actor-critic model on device cuda:0 +[2026-07-22 19:32:46,955][49527] RunningMeanStd input shape: (12, 72, 128) +[2026-07-22 19:32:46,957][49527] RunningMeanStd input shape: (1,) +[2026-07-22 19:32:46,973][49527] ConvEncoder: input_channels=12 +[2026-07-22 19:32:47,120][49527] Conv encoder output size: 512 +[2026-07-22 19:32:47,121][49527] Policy head output size: 512 +[2026-07-22 19:32:47,139][49527] Created Actor Critic model with architecture: +[2026-07-22 19:32:47,140][49527] ActorCriticSharedWeights( + (obs_normalizer): ObservationNormalizer( + (running_mean_std): RunningMeanStdDictInPlace( + (running_mean_std): ModuleDict( + (obs): RunningMeanStdInPlace() + ) + ) + ) + (returns_normalizer): RecursiveScriptModule(original_name=RunningMeanStdInPlace) + (encoder): VizdoomEncoder( + (basic_encoder): ConvEncoder( + (enc): RecursiveScriptModule( + original_name=ConvEncoderImpl + (conv_head): RecursiveScriptModule( + original_name=Sequential + (0): RecursiveScriptModule(original_name=Conv2d) + (1): RecursiveScriptModule(original_name=ELU) + (2): RecursiveScriptModule(original_name=Conv2d) + (3): RecursiveScriptModule(original_name=ELU) + (4): RecursiveScriptModule(original_name=Conv2d) + (5): RecursiveScriptModule(original_name=ELU) + ) + (mlp_layers): RecursiveScriptModule( + original_name=Sequential + (0): RecursiveScriptModule(original_name=Linear) + (1): RecursiveScriptModule(original_name=ELU) + ) + ) + ) + ) + (core): ModelCoreRNN( + (core): GRU(512, 512) + ) + (decoder): MlpDecoder( + (mlp): Identity() + ) + (critic_linear): Linear(in_features=512, out_features=1, bias=True) + (action_parameterization): ActionParameterizationDefault( + (distribution_linear): Linear(in_features=512, out_features=11, bias=True) + ) +) +[2026-07-22 19:32:47,458][49527] Using optimizer +[2026-07-22 19:32:48,570][49527] No checkpoints found +[2026-07-22 19:32:48,570][49527] Did not load from checkpoint, starting from scratch! +[2026-07-22 19:32:48,570][49527] Initialized policy 0 weights for model version 0 +[2026-07-22 19:32:48,871][49527] LearnerWorker_p0 finished initialization! +[2026-07-22 19:32:48,872][49527] Using GPUs [0] for process 0 (actually maps to GPUs [0]) +[2026-07-22 19:32:50,166][43431] Starting process rollout_proc15 +[2026-07-22 19:32:50,174][50226] Worker 10 uses CPU cores [10] +[2026-07-22 19:32:50,191][43431] Starting process rollout_proc16 +[2026-07-22 19:32:50,193][50234] Worker 6 uses CPU cores [6] +[2026-07-22 19:32:50,322][43431] Starting process rollout_proc17 +[2026-07-22 19:32:50,327][50209] Worker 1 uses CPU cores [1] +[2026-07-22 19:32:50,473][43431] Starting process rollout_proc18 +[2026-07-22 19:32:50,477][50229] Worker 4 uses CPU cores [4] +[2026-07-22 19:32:50,513][43431] Starting process rollout_proc19 +[2026-07-22 19:32:50,516][43431] Starting process rollout_proc20 +[2026-07-22 19:32:50,518][50230] Worker 11 uses CPU cores [11] +[2026-07-22 19:32:50,518][50227] Worker 8 uses CPU cores [8] +[2026-07-22 19:32:50,613][43431] Starting process rollout_proc21 +[2026-07-22 19:32:50,618][50236] Worker 12 uses CPU cores [12] +[2026-07-22 19:32:50,618][43431] Starting process rollout_proc22 +[2026-07-22 19:32:50,630][50231] Worker 5 uses CPU cores [5] +[2026-07-22 19:32:50,634][43431] Starting process rollout_proc23 +[2026-07-22 19:32:50,636][50205] Using GPUs [0] for process 0 (actually maps to GPUs [0]) +[2026-07-22 19:32:50,636][50205] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for inference process 0 +[2026-07-22 19:32:50,749][43431] Starting process rollout_proc24 +[2026-07-22 19:32:50,754][50223] Worker 9 uses CPU cores [9] +[2026-07-22 19:32:50,824][50205] Num visible devices: 1 +[2026-07-22 19:32:50,825][43431] Starting process rollout_proc25 +[2026-07-22 19:32:50,838][50228] Worker 7 uses CPU cores [7] +[2026-07-22 19:32:50,985][43431] Starting process rollout_proc26 +[2026-07-22 19:32:50,995][50208] Worker 0 uses CPU cores [0] +[2026-07-22 19:32:51,029][43431] Starting process rollout_proc27 +[2026-07-22 19:32:51,033][50233] Worker 13 uses CPU cores [13] +[2026-07-22 19:32:51,043][43431] Starting process rollout_proc28 +[2026-07-22 19:32:51,051][50224] Worker 3 uses CPU cores [3] +[2026-07-22 19:32:51,063][43431] Starting process rollout_proc29 +[2026-07-22 19:32:51,070][50235] Worker 14 uses CPU cores [14] +[2026-07-22 19:32:51,237][50205] RunningMeanStd input shape: (12, 72, 128) +[2026-07-22 19:32:51,244][50205] RunningMeanStd input shape: (1,) +[2026-07-22 19:32:51,342][43431] Starting process rollout_proc30 +[2026-07-22 19:32:51,327][50205] ConvEncoder: input_channels=12 +[2026-07-22 19:32:51,350][50222] Worker 2 uses CPU cores [2] +[2026-07-22 19:32:51,494][50205] Conv encoder output size: 512 +[2026-07-22 19:32:51,495][50205] Policy head output size: 512 +[2026-07-22 19:32:53,553][43431] Starting process rollout_proc31 +[2026-07-22 19:32:53,556][50957] Worker 15 uses CPU cores [15] +[2026-07-22 19:32:53,606][50990] Worker 20 uses CPU cores [20] +[2026-07-22 19:32:53,874][50970] Worker 17 uses CPU cores [17] +[2026-07-22 19:32:53,890][50996] Worker 21 uses CPU cores [21] +[2026-07-22 19:32:53,894][50960] Worker 16 uses CPU cores [16] +[2026-07-22 19:32:54,022][50989] Worker 19 uses CPU cores [19] +[2026-07-22 19:32:54,090][51118] Worker 27 uses CPU cores [27] +[2026-07-22 19:32:54,118][51004] Worker 24 uses CPU cores [24] +[2026-07-22 19:32:54,188][51113] Worker 26 uses CPU cores [26] +[2026-07-22 19:32:54,200][51124] Worker 29 uses CPU cores [7, 8, 9, 10, 11, 12, 13] +[2026-07-22 19:32:54,209][50987] Worker 18 uses CPU cores [18] +[2026-07-22 19:32:54,263][51121] Worker 28 uses CPU cores [0, 1, 2, 3, 4, 5, 6] +[2026-07-22 19:32:54,272][51252] Worker 30 uses CPU cores [14, 15, 16, 17, 18, 19, 20] +[2026-07-22 19:32:54,366][51050] Worker 25 uses CPU cores [25] +[2026-07-22 19:32:54,398][50997] Worker 22 uses CPU cores [22] +[2026-07-22 19:32:54,546][50999] Worker 23 uses CPU cores [23] +[2026-07-22 19:32:56,053][51846] Worker 31 uses CPU cores [21, 22, 23, 24, 25, 26, 27] +[2026-07-22 19:32:56,055][43431] Inference worker 0-0 is ready! +[2026-07-22 19:32:56,056][43431] All inference workers are ready! Signal rollout workers to start! +[2026-07-22 19:32:56,057][43431] Fps is (10 sec: nan, 60 sec: nan, 300 sec: nan). Total num frames: 0. Throughput: 0: nan. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) +[2026-07-22 19:32:56,069][43431] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 0.0. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) +[2026-07-22 19:32:56,097][51050] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,099][50997] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,099][50960] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,101][51118] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,103][50227] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,102][50226] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,103][50990] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,102][50228] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,104][50208] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,104][50209] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,104][50230] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,101][50224] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,105][50987] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,106][50234] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,106][50233] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,106][50957] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,107][50999] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,104][50229] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,104][50231] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,112][50970] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,105][50223] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,105][50989] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,126][50222] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,131][51113] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,138][50996] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,139][50235] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,140][51124] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,140][51004] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,142][50236] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,143][51846] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,143][51252] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,148][51121] Doom resolution: 160x120, resize resolution: (128, 72) +[2026-07-22 19:32:56,343][50960] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,352][50227] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,353][50987] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,354][50230] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,356][50234] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,356][50233] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,455][50997] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,460][50999] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,472][50209] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,472][50208] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,534][50227] Decorrelating experience for 128 frames... +[2026-07-22 19:32:56,535][51124] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,542][51846] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,557][50989] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,563][51121] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,588][51113] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,640][50233] Decorrelating experience for 128 frames... +[2026-07-22 19:32:56,641][50997] Decorrelating experience for 128 frames... +[2026-07-22 19:32:56,672][50229] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,701][51004] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,743][50222] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,745][50987] Decorrelating experience for 128 frames... +[2026-07-22 19:32:56,749][51118] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,760][50209] Decorrelating experience for 128 frames... +[2026-07-22 19:32:56,761][50957] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,806][51121] Decorrelating experience for 128 frames... +[2026-07-22 19:32:56,867][50970] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,923][51252] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,933][50226] Decorrelating experience for 0 frames... +[2026-07-22 19:32:56,934][51118] Decorrelating experience for 128 frames... +[2026-07-22 19:32:56,936][51004] Decorrelating experience for 128 frames... +[2026-07-22 19:32:56,947][50230] Decorrelating experience for 128 frames... +[2026-07-22 19:32:56,998][50229] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,060][50996] Decorrelating experience for 0 frames... +[2026-07-22 19:32:57,064][50989] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,070][50208] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,112][50970] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,133][50227] Decorrelating experience for 256 frames... +[2026-07-22 19:32:57,148][50224] Decorrelating experience for 0 frames... +[2026-07-22 19:32:57,237][50236] Decorrelating experience for 0 frames... +[2026-07-22 19:32:57,244][50960] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,258][51050] Decorrelating experience for 0 frames... +[2026-07-22 19:32:57,264][50234] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,263][51252] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,273][50233] Decorrelating experience for 256 frames... +[2026-07-22 19:32:57,387][51113] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,454][50224] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,455][50222] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,486][51050] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,543][50209] Decorrelating experience for 256 frames... +[2026-07-22 19:32:57,543][50987] Decorrelating experience for 256 frames... +[2026-07-22 19:32:57,576][50223] Decorrelating experience for 0 frames... +[2026-07-22 19:32:57,578][51118] Decorrelating experience for 256 frames... +[2026-07-22 19:32:57,598][50996] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,661][51121] Decorrelating experience for 256 frames... +[2026-07-22 19:32:57,769][50997] Decorrelating experience for 256 frames... +[2026-07-22 19:32:57,803][50229] Decorrelating experience for 256 frames... +[2026-07-22 19:32:57,843][50208] Decorrelating experience for 256 frames... +[2026-07-22 19:32:57,856][50236] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,863][51846] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,883][50227] Decorrelating experience for 384 frames... +[2026-07-22 19:32:57,885][50999] Decorrelating experience for 128 frames... +[2026-07-22 19:32:57,895][50989] Decorrelating experience for 256 frames... +[2026-07-22 19:32:57,978][51004] Decorrelating experience for 256 frames... +[2026-07-22 19:32:58,070][51252] Decorrelating experience for 256 frames... +[2026-07-22 19:32:58,071][50226] Decorrelating experience for 128 frames... +[2026-07-22 19:32:58,079][50990] Decorrelating experience for 0 frames... +[2026-07-22 19:32:58,173][50222] Decorrelating experience for 256 frames... +[2026-07-22 19:32:58,189][50970] Decorrelating experience for 256 frames... +[2026-07-22 19:32:58,191][50233] Decorrelating experience for 384 frames... +[2026-07-22 19:32:58,199][51050] Decorrelating experience for 256 frames... +[2026-07-22 19:32:58,232][50960] Decorrelating experience for 256 frames... +[2026-07-22 19:32:58,372][50990] Decorrelating experience for 128 frames... +[2026-07-22 19:32:58,386][50230] Decorrelating experience for 256 frames... +[2026-07-22 19:32:58,403][50996] Decorrelating experience for 256 frames... +[2026-07-22 19:32:58,431][50231] Decorrelating experience for 0 frames... +[2026-07-22 19:32:58,623][51113] Decorrelating experience for 256 frames... +[2026-07-22 19:32:58,628][50999] Decorrelating experience for 256 frames... +[2026-07-22 19:32:58,658][51118] Decorrelating experience for 384 frames... +[2026-07-22 19:32:58,671][50987] Decorrelating experience for 384 frames... +[2026-07-22 19:32:58,683][50234] Decorrelating experience for 256 frames... +[2026-07-22 19:32:58,715][50957] Decorrelating experience for 128 frames... +[2026-07-22 19:32:58,722][50231] Decorrelating experience for 128 frames... +[2026-07-22 19:32:58,914][51121] Decorrelating experience for 384 frames... +[2026-07-22 19:32:58,941][50208] Decorrelating experience for 384 frames... +[2026-07-22 19:32:58,964][50226] Decorrelating experience for 256 frames... +[2026-07-22 19:32:58,985][50209] Decorrelating experience for 384 frames... +[2026-07-22 19:32:58,985][50228] Decorrelating experience for 0 frames... +[2026-07-22 19:32:58,989][50229] Decorrelating experience for 384 frames... +[2026-07-22 19:32:59,049][50989] Decorrelating experience for 384 frames... +[2026-07-22 19:32:59,052][50224] Decorrelating experience for 256 frames... +[2026-07-22 19:32:59,087][51050] Decorrelating experience for 384 frames... +[2026-07-22 19:32:59,203][51124] Decorrelating experience for 128 frames... +[2026-07-22 19:32:59,224][50990] Decorrelating experience for 256 frames... +[2026-07-22 19:32:59,275][50235] Decorrelating experience for 0 frames... +[2026-07-22 19:32:59,293][50228] Decorrelating experience for 128 frames... +[2026-07-22 19:32:59,306][50960] Decorrelating experience for 384 frames... +[2026-07-22 19:32:59,347][50957] Decorrelating experience for 256 frames... +[2026-07-22 19:32:59,394][50999] Decorrelating experience for 384 frames... +[2026-07-22 19:32:59,457][50222] Decorrelating experience for 384 frames... +[2026-07-22 19:32:59,525][50997] Decorrelating experience for 384 frames... +[2026-07-22 19:32:59,575][51252] Decorrelating experience for 384 frames... +[2026-07-22 19:32:59,591][50970] Decorrelating experience for 384 frames... +[2026-07-22 19:32:59,786][50234] Decorrelating experience for 384 frames... +[2026-07-22 19:32:59,809][50230] Decorrelating experience for 384 frames... +[2026-07-22 19:32:59,814][50231] Decorrelating experience for 256 frames... +[2026-07-22 19:32:59,820][51846] Decorrelating experience for 256 frames... +[2026-07-22 19:32:59,877][43431] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 0.0. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) +[2026-07-22 19:32:59,904][50226] Decorrelating experience for 384 frames... +[2026-07-22 19:32:59,972][50235] Decorrelating experience for 128 frames... +[2026-07-22 19:33:00,071][51124] Decorrelating experience for 256 frames... +[2026-07-22 19:33:00,081][51113] Decorrelating experience for 384 frames... +[2026-07-22 19:33:00,119][50224] Decorrelating experience for 384 frames... +[2026-07-22 19:33:00,130][50990] Decorrelating experience for 384 frames... +[2026-07-22 19:33:00,219][50228] Decorrelating experience for 256 frames... +[2026-07-22 19:33:00,323][50996] Decorrelating experience for 384 frames... +[2026-07-22 19:33:00,426][50957] Decorrelating experience for 384 frames... +[2026-07-22 19:33:00,615][51004] Decorrelating experience for 384 frames... +[2026-07-22 19:33:00,702][50231] Decorrelating experience for 384 frames... +[2026-07-22 19:33:00,728][50236] Decorrelating experience for 256 frames... +[2026-07-22 19:33:00,755][50235] Decorrelating experience for 256 frames... +[2026-07-22 19:33:00,937][50223] Decorrelating experience for 128 frames... +[2026-07-22 19:33:01,098][51846] Decorrelating experience for 384 frames... +[2026-07-22 19:33:01,288][50228] Decorrelating experience for 384 frames... +[2026-07-22 19:33:01,293][51124] Decorrelating experience for 384 frames... +[2026-07-22 19:33:01,585][50223] Decorrelating experience for 256 frames... +[2026-07-22 19:33:01,829][50235] Decorrelating experience for 384 frames... +[2026-07-22 19:33:01,914][50236] Decorrelating experience for 384 frames... +[2026-07-22 19:33:02,350][50223] Decorrelating experience for 384 frames... +[2026-07-22 19:33:04,421][43431] Heartbeat connected on Batcher_0 +[2026-07-22 19:33:04,426][43431] Heartbeat connected on LearnerWorker_p0 +[2026-07-22 19:33:04,436][43431] Heartbeat connected on InferenceWorker_p0-w0 +[2026-07-22 19:33:04,437][43431] Heartbeat connected on RolloutWorker_w2 +[2026-07-22 19:33:04,438][43431] Heartbeat connected on RolloutWorker_w1 +[2026-07-22 19:33:04,442][43431] Heartbeat connected on RolloutWorker_w3 +[2026-07-22 19:33:04,444][43431] Heartbeat connected on RolloutWorker_w4 +[2026-07-22 19:33:04,447][43431] Heartbeat connected on RolloutWorker_w6 +[2026-07-22 19:33:04,452][43431] Heartbeat connected on RolloutWorker_w7 +[2026-07-22 19:33:04,453][43431] Heartbeat connected on RolloutWorker_w0 +[2026-07-22 19:33:04,454][43431] Heartbeat connected on RolloutWorker_w5 +[2026-07-22 19:33:04,471][43431] Heartbeat connected on RolloutWorker_w9 +[2026-07-22 19:33:04,474][43431] Heartbeat connected on RolloutWorker_w8 +[2026-07-22 19:33:04,482][43431] Heartbeat connected on RolloutWorker_w10 +[2026-07-22 19:33:04,486][43431] Heartbeat connected on RolloutWorker_w11 +[2026-07-22 19:33:04,490][43431] Heartbeat connected on RolloutWorker_w14 +[2026-07-22 19:33:04,495][43431] Heartbeat connected on RolloutWorker_w12 +[2026-07-22 19:33:04,498][43431] Heartbeat connected on RolloutWorker_w15 +[2026-07-22 19:33:04,499][43431] Heartbeat connected on RolloutWorker_w18 +[2026-07-22 19:33:04,499][43431] Heartbeat connected on RolloutWorker_w17 +[2026-07-22 19:33:04,507][43431] Heartbeat connected on RolloutWorker_w19 +[2026-07-22 19:33:04,508][43431] Heartbeat connected on RolloutWorker_w16 +[2026-07-22 19:33:04,515][43431] Heartbeat connected on RolloutWorker_w20 +[2026-07-22 19:33:04,516][43431] Heartbeat connected on RolloutWorker_w21 +[2026-07-22 19:33:04,522][43431] Heartbeat connected on RolloutWorker_w13 +[2026-07-22 19:33:04,523][43431] Heartbeat connected on RolloutWorker_w22 +[2026-07-22 19:33:04,524][43431] Heartbeat connected on RolloutWorker_w23 +[2026-07-22 19:33:04,525][43431] Heartbeat connected on RolloutWorker_w27 +[2026-07-22 19:33:04,526][43431] Heartbeat connected on RolloutWorker_w25 +[2026-07-22 19:33:04,528][43431] Heartbeat connected on RolloutWorker_w24 +[2026-07-22 19:33:04,530][43431] Heartbeat connected on RolloutWorker_w26 +[2026-07-22 19:33:04,537][43431] Heartbeat connected on RolloutWorker_w31 +[2026-07-22 19:33:04,548][43431] Heartbeat connected on RolloutWorker_w29 +[2026-07-22 19:33:04,550][43431] Heartbeat connected on RolloutWorker_w28 +[2026-07-22 19:33:04,557][43431] Heartbeat connected on RolloutWorker_w30 +[2026-07-22 19:33:04,877][43431] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 898.1. Samples: 7922. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) +[2026-07-22 19:33:04,878][43431] Avg episode reward: [(0, '-58.228')] +[2026-07-22 19:33:05,516][49527] Signal inference workers to stop experience collection... +[2026-07-22 19:33:05,533][50205] InferenceWorker_p0-w0: stopping experience collection +[2026-07-22 19:33:06,604][49527] Signal inference workers to resume experience collection... +[2026-07-22 19:33:06,605][50205] InferenceWorker_p0-w0: resuming experience collection +[2026-07-22 19:33:07,595][50205] Updated weights for policy 0, policy_version 21 (0.0018) +[2026-07-22 19:33:08,882][50205] Updated weights for policy 0, policy_version 31 (0.0015) +[2026-07-22 19:33:09,877][43431] Fps is (10 sec: 1843.2, 60 sec: 1333.7, 300 sec: 1333.7). Total num frames: 18432. Throughput: 0: 2129.6. Samples: 29432. Policy #0 lag: (min: 1.0, avg: 20.8, max: 29.0) +[2026-07-22 19:33:09,878][43431] Avg episode reward: [(0, '-31.562')] +[2026-07-22 19:33:10,975][50205] Updated weights for policy 0, policy_version 45 (0.0020) +[2026-07-22 19:33:11,415][50205] Updated weights for policy 0, policy_version 55 (0.0011) +[2026-07-22 19:33:14,038][50205] Updated weights for policy 0, policy_version 67 (0.0016) +[2026-07-22 19:33:14,773][50205] Updated weights for policy 0, policy_version 79 (0.0014) +[2026-07-22 19:33:14,877][43431] Fps is (10 sec: 4096.1, 60 sec: 2176.4, 300 sec: 2176.4). Total num frames: 40960. Throughput: 0: 2173.9. Samples: 40914. Policy #0 lag: (min: 3.0, avg: 15.4, max: 35.0) +[2026-07-22 19:33:14,878][43431] Avg episode reward: [(0, '-4.667')] +[2026-07-22 19:33:15,965][50205] Updated weights for policy 0, policy_version 89 (0.0014) +[2026-07-22 19:33:17,137][50205] Updated weights for policy 0, policy_version 99 (0.0015) +[2026-07-22 19:33:17,967][50205] Updated weights for policy 0, policy_version 109 (0.0016) +[2026-07-22 19:33:18,499][50205] Updated weights for policy 0, policy_version 119 (0.0012) +[2026-07-22 19:33:19,877][43431] Fps is (10 sec: 4505.7, 60 sec: 2665.3, 300 sec: 2665.3). Total num frames: 63488. Throughput: 0: 2919.0. Samples: 69532. Policy #0 lag: (min: 4.0, avg: 22.1, max: 39.0) +[2026-07-22 19:33:19,878][43431] Avg episode reward: [(0, '22.036')] +[2026-07-22 19:33:20,394][50205] Updated weights for policy 0, policy_version 129 (0.0010) +[2026-07-22 19:33:21,056][50205] Updated weights for policy 0, policy_version 139 (0.0011) +[2026-07-22 19:33:21,836][50205] Updated weights for policy 0, policy_version 152 (0.0011) +[2026-07-22 19:33:24,023][50205] Updated weights for policy 0, policy_version 165 (0.0016) +[2026-07-22 19:33:24,624][50205] Updated weights for policy 0, policy_version 175 (0.0011) +[2026-07-22 19:33:24,877][43431] Fps is (10 sec: 4915.2, 60 sec: 3126.7, 300 sec: 3126.7). Total num frames: 90112. Throughput: 0: 3465.0. Samples: 99862. Policy #0 lag: (min: 2.0, avg: 19.3, max: 34.0) +[2026-07-22 19:33:24,878][43431] Avg episode reward: [(0, '28.212')] +[2026-07-22 19:33:25,500][50205] Updated weights for policy 0, policy_version 185 (0.0016) +[2026-07-22 19:33:26,454][50205] Updated weights for policy 0, policy_version 195 (0.0016) +[2026-07-22 19:33:27,522][50205] Updated weights for policy 0, policy_version 205 (0.0011) +[2026-07-22 19:33:28,402][50205] Updated weights for policy 0, policy_version 215 (0.0015) +[2026-07-22 19:33:29,479][50205] Updated weights for policy 0, policy_version 225 (0.0016) +[2026-07-22 19:33:29,877][43431] Fps is (10 sec: 5529.6, 60 sec: 3512.2, 300 sec: 3512.2). Total num frames: 118784. Throughput: 0: 3446.8. Samples: 116572. Policy #0 lag: (min: 3.0, avg: 19.4, max: 35.0) +[2026-07-22 19:33:29,878][43431] Avg episode reward: [(0, '96.794')] +[2026-07-22 19:33:29,893][49527] Saving new best policy, reward=96.794! +[2026-07-22 19:33:30,071][50205] Updated weights for policy 0, policy_version 235 (0.0011) +[2026-07-22 19:33:31,149][50205] Updated weights for policy 0, policy_version 245 (0.0011) +[2026-07-22 19:33:32,201][50205] Updated weights for policy 0, policy_version 255 (0.0016) +[2026-07-22 19:33:32,827][50205] Updated weights for policy 0, policy_version 265 (0.0011) +[2026-07-22 19:33:33,685][50205] Updated weights for policy 0, policy_version 275 (0.0015) +[2026-07-22 19:33:34,877][43431] Fps is (10 sec: 5529.6, 60 sec: 3745.7, 300 sec: 3745.7). Total num frames: 145408. Throughput: 0: 3861.0. Samples: 149884. Policy #0 lag: (min: 3.0, avg: 20.5, max: 35.0) +[2026-07-22 19:33:34,878][43431] Avg episode reward: [(0, '151.679')] +[2026-07-22 19:33:34,890][49527] Saving new best policy, reward=151.679! +[2026-07-22 19:33:35,281][50205] Updated weights for policy 0, policy_version 285 (0.0015) +[2026-07-22 19:33:35,778][50205] Updated weights for policy 0, policy_version 295 (0.0011) +[2026-07-22 19:33:36,463][50205] Updated weights for policy 0, policy_version 305 (0.0014) +[2026-07-22 19:33:37,656][50205] Updated weights for policy 0, policy_version 315 (0.0014) +[2026-07-22 19:33:38,638][50205] Updated weights for policy 0, policy_version 325 (0.0016) +[2026-07-22 19:33:39,337][50205] Updated weights for policy 0, policy_version 335 (0.0011) +[2026-07-22 19:33:39,877][43431] Fps is (10 sec: 5529.7, 60 sec: 3972.6, 300 sec: 3972.6). Total num frames: 174080. Throughput: 0: 4177.1. Samples: 182990. Policy #0 lag: (min: 3.0, avg: 16.1, max: 35.0) +[2026-07-22 19:33:39,878][43431] Avg episode reward: [(0, '164.479')] +[2026-07-22 19:33:39,955][49527] Saving new best policy, reward=164.479! +[2026-07-22 19:33:40,524][50205] Updated weights for policy 0, policy_version 347 (0.0011) +[2026-07-22 19:33:41,613][50205] Updated weights for policy 0, policy_version 357 (0.0011) +[2026-07-22 19:33:42,331][50205] Updated weights for policy 0, policy_version 367 (0.0015) +[2026-07-22 19:33:43,541][50205] Updated weights for policy 0, policy_version 377 (0.0013) +[2026-07-22 19:33:44,153][50205] Updated weights for policy 0, policy_version 387 (0.0011) +[2026-07-22 19:33:44,877][43431] Fps is (10 sec: 5529.6, 60 sec: 4111.1, 300 sec: 4111.1). Total num frames: 200704. Throughput: 0: 4429.1. Samples: 199310. Policy #0 lag: (min: 3.0, avg: 19.5, max: 39.0) +[2026-07-22 19:33:44,878][43431] Avg episode reward: [(0, '187.318')] +[2026-07-22 19:33:44,914][49527] Saving new best policy, reward=187.318! +[2026-07-22 19:33:45,389][50205] Updated weights for policy 0, policy_version 397 (0.0025) +[2026-07-22 19:33:46,267][50205] Updated weights for policy 0, policy_version 407 (0.0014) +[2026-07-22 19:33:47,203][50205] Updated weights for policy 0, policy_version 417 (0.0016) +[2026-07-22 19:33:48,780][50205] Updated weights for policy 0, policy_version 431 (0.0016) +[2026-07-22 19:33:49,877][43431] Fps is (10 sec: 5119.9, 60 sec: 4185.8, 300 sec: 4185.8). Total num frames: 225280. Throughput: 0: 4937.4. Samples: 230106. Policy #0 lag: (min: 3.0, avg: 17.8, max: 39.0) +[2026-07-22 19:33:49,878][43431] Avg episode reward: [(0, '212.810')] +[2026-07-22 19:33:49,895][49527] Saving new best policy, reward=212.810! +[2026-07-22 19:33:50,023][50205] Updated weights for policy 0, policy_version 441 (0.0011) +[2026-07-22 19:33:50,611][50205] Updated weights for policy 0, policy_version 451 (0.0011) +[2026-07-22 19:33:51,673][50205] Updated weights for policy 0, policy_version 461 (0.0011) +[2026-07-22 19:33:52,451][50205] Updated weights for policy 0, policy_version 471 (0.0011) +[2026-07-22 19:33:53,673][50205] Updated weights for policy 0, policy_version 481 (0.0016) +[2026-07-22 19:33:54,391][50205] Updated weights for policy 0, policy_version 491 (0.0010) +[2026-07-22 19:33:54,877][43431] Fps is (10 sec: 5324.8, 60 sec: 4318.3, 300 sec: 4317.4). Total num frames: 253952. Throughput: 0: 5190.5. Samples: 263004. Policy #0 lag: (min: 3.0, avg: 17.8, max: 35.0) +[2026-07-22 19:33:54,878][43431] Avg episode reward: [(0, '230.769')] +[2026-07-22 19:33:54,892][49527] Saving new best policy, reward=230.769! +[2026-07-22 19:33:55,405][50205] Updated weights for policy 0, policy_version 501 (0.0011) +[2026-07-22 19:33:56,191][50205] Updated weights for policy 0, policy_version 511 (0.0011) +[2026-07-22 19:33:57,775][50205] Updated weights for policy 0, policy_version 521 (0.0016) +[2026-07-22 19:33:58,571][50205] Updated weights for policy 0, policy_version 531 (0.0011) +[2026-07-22 19:33:59,427][50205] Updated weights for policy 0, policy_version 541 (0.0011) +[2026-07-22 19:33:59,877][43431] Fps is (10 sec: 5324.9, 60 sec: 4642.1, 300 sec: 4364.3). Total num frames: 278528. Throughput: 0: 5267.0. Samples: 277930. Policy #0 lag: (min: 5.0, avg: 20.7, max: 43.0) +[2026-07-22 19:33:59,878][43431] Avg episode reward: [(0, '256.141')] +[2026-07-22 19:33:59,916][49527] Saving new best policy, reward=256.141! +[2026-07-22 19:34:00,478][50205] Updated weights for policy 0, policy_version 551 (0.0011) +[2026-07-22 19:34:01,526][50205] Updated weights for policy 0, policy_version 561 (0.0011) +[2026-07-22 19:34:02,846][50205] Updated weights for policy 0, policy_version 576 (0.0010) +[2026-07-22 19:34:04,242][50205] Updated weights for policy 0, policy_version 586 (0.0011) +[2026-07-22 19:34:04,856][50205] Updated weights for policy 0, policy_version 596 (0.0014) +[2026-07-22 19:34:04,879][43431] Fps is (10 sec: 5119.2, 60 sec: 5085.8, 300 sec: 4433.9). Total num frames: 305152. Throughput: 0: 5310.0. Samples: 308488. Policy #0 lag: (min: 3.0, avg: 16.4, max: 35.0) +[2026-07-22 19:34:04,879][43431] Avg episode reward: [(0, '223.089')] +[2026-07-22 19:34:05,835][50205] Updated weights for policy 0, policy_version 606 (0.0021) +[2026-07-22 19:34:06,572][50205] Updated weights for policy 0, policy_version 616 (0.0011) +[2026-07-22 19:34:07,625][50205] Updated weights for policy 0, policy_version 626 (0.0013) +[2026-07-22 19:34:08,422][50205] Updated weights for policy 0, policy_version 636 (0.0011) +[2026-07-22 19:34:09,628][50205] Updated weights for policy 0, policy_version 646 (0.0010) +[2026-07-22 19:34:09,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5222.4, 300 sec: 4494.4). Total num frames: 331776. Throughput: 0: 5376.8. Samples: 341818. Policy #0 lag: (min: 3.0, avg: 17.1, max: 32.0) +[2026-07-22 19:34:09,878][43431] Avg episode reward: [(0, '251.692')] +[2026-07-22 19:34:10,534][50205] Updated weights for policy 0, policy_version 658 (0.0011) +[2026-07-22 19:34:11,498][50205] Updated weights for policy 0, policy_version 668 (0.0016) +[2026-07-22 19:34:12,599][50205] Updated weights for policy 0, policy_version 678 (0.0011) +[2026-07-22 19:34:13,450][50205] Updated weights for policy 0, policy_version 688 (0.0011) +[2026-07-22 19:34:14,362][50205] Updated weights for policy 0, policy_version 698 (0.0012) +[2026-07-22 19:34:14,877][43431] Fps is (10 sec: 5530.4, 60 sec: 5324.8, 300 sec: 4573.0). Total num frames: 360448. Throughput: 0: 5367.3. Samples: 358102. Policy #0 lag: (min: 3.0, avg: 18.3, max: 35.0) +[2026-07-22 19:34:14,878][43431] Avg episode reward: [(0, '272.780')] +[2026-07-22 19:34:14,919][49527] Saving new best policy, reward=272.780! +[2026-07-22 19:34:15,240][50205] Updated weights for policy 0, policy_version 708 (0.0012) +[2026-07-22 19:34:16,681][50205] Updated weights for policy 0, policy_version 718 (0.0011) +[2026-07-22 19:34:17,477][50205] Updated weights for policy 0, policy_version 728 (0.0016) +[2026-07-22 19:34:18,208][50205] Updated weights for policy 0, policy_version 738 (0.0011) +[2026-07-22 19:34:19,453][50205] Updated weights for policy 0, policy_version 748 (0.0012) +[2026-07-22 19:34:19,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5358.9, 300 sec: 4593.4). Total num frames: 385024. Throughput: 0: 5328.8. Samples: 389680. Policy #0 lag: (min: 3.0, avg: 22.2, max: 43.0) +[2026-07-22 19:34:19,878][43431] Avg episode reward: [(0, '312.300')] +[2026-07-22 19:34:20,071][49527] Saving new best policy, reward=312.300! +[2026-07-22 19:34:20,448][50205] Updated weights for policy 0, policy_version 758 (0.0011) +[2026-07-22 19:34:21,132][50205] Updated weights for policy 0, policy_version 768 (0.0015) +[2026-07-22 19:34:22,279][50205] Updated weights for policy 0, policy_version 778 (0.0012) +[2026-07-22 19:34:22,825][50205] Updated weights for policy 0, policy_version 788 (0.0011) +[2026-07-22 19:34:23,957][50205] Updated weights for policy 0, policy_version 798 (0.0011) +[2026-07-22 19:34:24,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5358.9, 300 sec: 4634.6). Total num frames: 411648. Throughput: 0: 5332.2. Samples: 422942. Policy #0 lag: (min: 3.0, avg: 16.0, max: 35.0) +[2026-07-22 19:34:24,878][43431] Avg episode reward: [(0, '308.290')] +[2026-07-22 19:34:24,890][50205] Updated weights for policy 0, policy_version 808 (0.0011) +[2026-07-22 19:34:25,861][50205] Updated weights for policy 0, policy_version 819 (0.0018) +[2026-07-22 19:34:26,733][50205] Updated weights for policy 0, policy_version 829 (0.0016) +[2026-07-22 19:34:27,898][50205] Updated weights for policy 0, policy_version 839 (0.0016) +[2026-07-22 19:34:28,817][50205] Updated weights for policy 0, policy_version 849 (0.0020) +[2026-07-22 19:34:29,504][50205] Updated weights for policy 0, policy_version 859 (0.0010) +[2026-07-22 19:34:29,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5393.1, 300 sec: 4715.1). Total num frames: 442368. Throughput: 0: 5336.5. Samples: 439454. Policy #0 lag: (min: 3.0, avg: 18.3, max: 36.0) +[2026-07-22 19:34:29,879][43431] Avg episode reward: [(0, '327.141')] +[2026-07-22 19:34:29,907][49527] Saving new best policy, reward=327.141! +[2026-07-22 19:34:30,805][50205] Updated weights for policy 0, policy_version 869 (0.0011) +[2026-07-22 19:34:31,554][50205] Updated weights for policy 0, policy_version 879 (0.0012) +[2026-07-22 19:34:32,543][50205] Updated weights for policy 0, policy_version 889 (0.0015) +[2026-07-22 19:34:33,367][50205] Updated weights for policy 0, policy_version 900 (0.0016) +[2026-07-22 19:34:34,577][50205] Updated weights for policy 0, policy_version 910 (0.0012) +[2026-07-22 19:34:34,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5358.9, 300 sec: 4725.2). Total num frames: 466944. Throughput: 0: 5364.2. Samples: 471496. Policy #0 lag: (min: 1.0, avg: 17.4, max: 37.0) +[2026-07-22 19:34:34,878][43431] Avg episode reward: [(0, '336.304')] +[2026-07-22 19:34:34,900][49527] Saving new best policy, reward=336.304! +[2026-07-22 19:34:35,579][50205] Updated weights for policy 0, policy_version 920 (0.0013) +[2026-07-22 19:34:36,423][50205] Updated weights for policy 0, policy_version 930 (0.0010) +[2026-07-22 19:34:37,449][50205] Updated weights for policy 0, policy_version 940 (0.0011) +[2026-07-22 19:34:38,673][50205] Updated weights for policy 0, policy_version 950 (0.0011) +[2026-07-22 19:34:39,174][50205] Updated weights for policy 0, policy_version 960 (0.0013) +[2026-07-22 19:34:39,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5324.8, 300 sec: 4754.1). Total num frames: 493568. Throughput: 0: 5336.5. Samples: 503148. Policy #0 lag: (min: 3.0, avg: 18.4, max: 35.0) +[2026-07-22 19:34:39,878][43431] Avg episode reward: [(0, '322.273')] +[2026-07-22 19:34:40,272][50205] Updated weights for policy 0, policy_version 970 (0.0016) +[2026-07-22 19:34:41,098][50205] Updated weights for policy 0, policy_version 980 (0.0016) +[2026-07-22 19:34:42,569][50205] Updated weights for policy 0, policy_version 992 (0.0011) +[2026-07-22 19:34:43,504][50205] Updated weights for policy 0, policy_version 1002 (0.0011) +[2026-07-22 19:34:44,178][50205] Updated weights for policy 0, policy_version 1012 (0.0014) +[2026-07-22 19:34:44,882][43431] Fps is (10 sec: 5322.5, 60 sec: 5324.4, 300 sec: 4780.1). Total num frames: 520192. Throughput: 0: 5347.4. Samples: 518588. Policy #0 lag: (min: 3.0, avg: 18.0, max: 43.0) +[2026-07-22 19:34:44,882][43431] Avg episode reward: [(0, '379.907')] +[2026-07-22 19:34:44,904][49527] Saving new best policy, reward=379.907! +[2026-07-22 19:34:45,404][50205] Updated weights for policy 0, policy_version 1022 (0.0014) +[2026-07-22 19:34:46,248][50205] Updated weights for policy 0, policy_version 1032 (0.0016) +[2026-07-22 19:34:47,185][50205] Updated weights for policy 0, policy_version 1042 (0.0016) +[2026-07-22 19:34:48,050][50205] Updated weights for policy 0, policy_version 1052 (0.0011) +[2026-07-22 19:34:48,995][50205] Updated weights for policy 0, policy_version 1062 (0.0012) +[2026-07-22 19:34:49,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5358.9, 300 sec: 4804.2). Total num frames: 546816. Throughput: 0: 5409.5. Samples: 551906. Policy #0 lag: (min: 6.0, avg: 20.2, max: 38.0) +[2026-07-22 19:34:49,878][43431] Avg episode reward: [(0, '362.136')] +[2026-07-22 19:34:49,882][50205] Updated weights for policy 0, policy_version 1072 (0.0011) +[2026-07-22 19:34:51,341][50205] Updated weights for policy 0, policy_version 1083 (0.0011) +[2026-07-22 19:34:52,322][50205] Updated weights for policy 0, policy_version 1093 (0.0011) +[2026-07-22 19:34:53,592][50205] Updated weights for policy 0, policy_version 1105 (0.0020) +[2026-07-22 19:34:54,666][50205] Updated weights for policy 0, policy_version 1115 (0.0011) +[2026-07-22 19:34:54,877][43431] Fps is (10 sec: 5122.1, 60 sec: 5290.6, 300 sec: 4808.9). Total num frames: 571392. Throughput: 0: 5333.2. Samples: 581812. Policy #0 lag: (min: 3.0, avg: 15.7, max: 31.0) +[2026-07-22 19:34:54,878][43431] Avg episode reward: [(0, '396.106')] +[2026-07-22 19:34:54,888][49527] Saving new best policy, reward=396.106! +[2026-07-22 19:34:55,527][50205] Updated weights for policy 0, policy_version 1125 (0.0011) +[2026-07-22 19:34:56,263][50205] Updated weights for policy 0, policy_version 1135 (0.0015) +[2026-07-22 19:34:57,635][50205] Updated weights for policy 0, policy_version 1145 (0.0013) +[2026-07-22 19:34:58,300][50205] Updated weights for policy 0, policy_version 1155 (0.0012) +[2026-07-22 19:34:59,181][50205] Updated weights for policy 0, policy_version 1167 (0.0011) +[2026-07-22 19:34:59,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5358.9, 300 sec: 4846.2). Total num frames: 600064. Throughput: 0: 5339.1. Samples: 598362. Policy #0 lag: (min: 2.0, avg: 17.1, max: 34.0) +[2026-07-22 19:34:59,878][43431] Avg episode reward: [(0, '382.156')] +[2026-07-22 19:35:00,497][50205] Updated weights for policy 0, policy_version 1177 (0.0016) +[2026-07-22 19:35:01,443][50205] Updated weights for policy 0, policy_version 1187 (0.0011) +[2026-07-22 19:35:02,266][50205] Updated weights for policy 0, policy_version 1197 (0.0013) +[2026-07-22 19:35:03,152][50205] Updated weights for policy 0, policy_version 1207 (0.0016) +[2026-07-22 19:35:04,436][50205] Updated weights for policy 0, policy_version 1217 (0.0017) +[2026-07-22 19:35:04,878][43431] Fps is (10 sec: 5529.5, 60 sec: 5359.0, 300 sec: 4864.8). Total num frames: 626688. Throughput: 0: 5365.6. Samples: 631132. Policy #0 lag: (min: 0.0, avg: 18.3, max: 36.0) +[2026-07-22 19:35:04,878][43431] Avg episode reward: [(0, '450.552')] +[2026-07-22 19:35:04,970][50205] Updated weights for policy 0, policy_version 1227 (0.0016) +[2026-07-22 19:35:04,990][49527] Saving new best policy, reward=450.552! +[2026-07-22 19:35:06,093][50205] Updated weights for policy 0, policy_version 1237 (0.0012) +[2026-07-22 19:35:06,887][50205] Updated weights for policy 0, policy_version 1247 (0.0011) +[2026-07-22 19:35:07,820][50205] Updated weights for policy 0, policy_version 1257 (0.0010) +[2026-07-22 19:35:08,808][50205] Updated weights for policy 0, policy_version 1267 (0.0016) +[2026-07-22 19:35:09,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5358.9, 300 sec: 4882.0). Total num frames: 653312. Throughput: 0: 5354.0. Samples: 663870. Policy #0 lag: (min: 3.0, avg: 18.4, max: 39.0) +[2026-07-22 19:35:09,878][43431] Avg episode reward: [(0, '344.916')] +[2026-07-22 19:35:09,930][50205] Updated weights for policy 0, policy_version 1277 (0.0017) +[2026-07-22 19:35:10,613][50205] Updated weights for policy 0, policy_version 1287 (0.0015) +[2026-07-22 19:35:12,066][50205] Updated weights for policy 0, policy_version 1297 (0.0019) +[2026-07-22 19:35:12,623][50205] Updated weights for policy 0, policy_version 1307 (0.0011) +[2026-07-22 19:35:13,871][50205] Updated weights for policy 0, policy_version 1317 (0.0016) +[2026-07-22 19:35:14,778][50205] Updated weights for policy 0, policy_version 1327 (0.0011) +[2026-07-22 19:35:14,877][43431] Fps is (10 sec: 5325.0, 60 sec: 5324.8, 300 sec: 4898.0). Total num frames: 679936. Throughput: 0: 5318.1. Samples: 678768. Policy #0 lag: (min: 0.0, avg: 16.3, max: 34.0) +[2026-07-22 19:35:14,878][43431] Avg episode reward: [(0, '408.432')] +[2026-07-22 19:35:15,944][50205] Updated weights for policy 0, policy_version 1337 (0.0015) +[2026-07-22 19:35:16,732][50205] Updated weights for policy 0, policy_version 1347 (0.0012) +[2026-07-22 19:35:17,342][50205] Updated weights for policy 0, policy_version 1357 (0.0012) +[2026-07-22 19:35:18,880][50205] Updated weights for policy 0, policy_version 1369 (0.0013) +[2026-07-22 19:35:19,861][50205] Updated weights for policy 0, policy_version 1379 (0.0011) +[2026-07-22 19:35:19,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5358.9, 300 sec: 4912.8). Total num frames: 706560. Throughput: 0: 5304.5. Samples: 710200. Policy #0 lag: (min: 3.0, avg: 17.9, max: 35.0) +[2026-07-22 19:35:19,878][43431] Avg episode reward: [(0, '416.329')] +[2026-07-22 19:35:20,734][50205] Updated weights for policy 0, policy_version 1389 (0.0020) +[2026-07-22 19:35:21,434][50205] Updated weights for policy 0, policy_version 1399 (0.0015) +[2026-07-22 19:35:22,781][50205] Updated weights for policy 0, policy_version 1409 (0.0011) +[2026-07-22 19:35:23,290][50205] Updated weights for policy 0, policy_version 1419 (0.0015) +[2026-07-22 19:35:24,376][50205] Updated weights for policy 0, policy_version 1429 (0.0011) +[2026-07-22 19:35:24,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5358.9, 300 sec: 4926.6). Total num frames: 733184. Throughput: 0: 5339.9. Samples: 743446. Policy #0 lag: (min: 3.0, avg: 21.4, max: 43.0) +[2026-07-22 19:35:24,878][43431] Avg episode reward: [(0, '416.213')] +[2026-07-22 19:35:25,317][50205] Updated weights for policy 0, policy_version 1439 (0.0018) +[2026-07-22 19:35:26,027][50205] Updated weights for policy 0, policy_version 1449 (0.0010) +[2026-07-22 19:35:27,099][50205] Updated weights for policy 0, policy_version 1459 (0.0010) +[2026-07-22 19:35:28,637][50205] Updated weights for policy 0, policy_version 1472 (0.0011) +[2026-07-22 19:35:29,406][50205] Updated weights for policy 0, policy_version 1482 (0.0011) +[2026-07-22 19:35:29,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5290.7, 300 sec: 4939.6). Total num frames: 759808. Throughput: 0: 5372.1. Samples: 760308. Policy #0 lag: (min: 3.0, avg: 16.8, max: 39.0) +[2026-07-22 19:35:29,878][43431] Avg episode reward: [(0, '499.492')] +[2026-07-22 19:35:29,896][49527] Saving new best policy, reward=499.492! +[2026-07-22 19:35:30,357][50205] Updated weights for policy 0, policy_version 1492 (0.0011) +[2026-07-22 19:35:32,049][50205] Updated weights for policy 0, policy_version 1505 (0.0011) +[2026-07-22 19:35:32,758][50205] Updated weights for policy 0, policy_version 1515 (0.0011) +[2026-07-22 19:35:34,376][50205] Updated weights for policy 0, policy_version 1525 (0.0016) +[2026-07-22 19:35:34,877][43431] Fps is (10 sec: 5120.1, 60 sec: 5290.7, 300 sec: 4938.8). Total num frames: 784384. Throughput: 0: 5286.9. Samples: 789818. Policy #0 lag: (min: 3.0, avg: 16.5, max: 39.0) +[2026-07-22 19:35:34,878][43431] Avg episode reward: [(0, '415.595')] +[2026-07-22 19:35:35,318][50205] Updated weights for policy 0, policy_version 1539 (0.0023) +[2026-07-22 19:35:36,540][50205] Updated weights for policy 0, policy_version 1549 (0.0011) +[2026-07-22 19:35:37,570][50205] Updated weights for policy 0, policy_version 1559 (0.0017) +[2026-07-22 19:35:38,197][50205] Updated weights for policy 0, policy_version 1569 (0.0011) +[2026-07-22 19:35:39,210][50205] Updated weights for policy 0, policy_version 1579 (0.0011) +[2026-07-22 19:35:39,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5290.7, 300 sec: 4950.6). Total num frames: 811008. Throughput: 0: 5320.1. Samples: 821214. Policy #0 lag: (min: 2.0, avg: 20.1, max: 42.0) +[2026-07-22 19:35:39,878][43431] Avg episode reward: [(0, '428.945')] +[2026-07-22 19:35:40,416][50205] Updated weights for policy 0, policy_version 1591 (0.0011) +[2026-07-22 19:35:41,237][50205] Updated weights for policy 0, policy_version 1601 (0.0012) +[2026-07-22 19:35:42,174][50205] Updated weights for policy 0, policy_version 1611 (0.0012) +[2026-07-22 19:35:43,560][50205] Updated weights for policy 0, policy_version 1621 (0.0016) +[2026-07-22 19:35:44,092][50205] Updated weights for policy 0, policy_version 1633 (0.0015) +[2026-07-22 19:35:44,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5325.2, 300 sec: 4973.8). Total num frames: 839680. Throughput: 0: 5319.2. Samples: 837728. Policy #0 lag: (min: 3.0, avg: 18.6, max: 35.0) +[2026-07-22 19:35:44,878][43431] Avg episode reward: [(0, '462.134')] +[2026-07-22 19:35:45,074][50205] Updated weights for policy 0, policy_version 1643 (0.0012) +[2026-07-22 19:35:46,423][50205] Updated weights for policy 0, policy_version 1653 (0.0018) +[2026-07-22 19:35:47,032][50205] Updated weights for policy 0, policy_version 1663 (0.0011) +[2026-07-22 19:35:48,371][50205] Updated weights for policy 0, policy_version 1673 (0.0011) +[2026-07-22 19:35:49,203][50205] Updated weights for policy 0, policy_version 1683 (0.0017) +[2026-07-22 19:35:49,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5290.7, 300 sec: 4972.1). Total num frames: 864256. Throughput: 0: 5291.3. Samples: 869238. Policy #0 lag: (min: 1.0, avg: 20.4, max: 45.0) +[2026-07-22 19:35:49,878][43431] Avg episode reward: [(0, '451.029')] +[2026-07-22 19:35:50,337][50205] Updated weights for policy 0, policy_version 1693 (0.0016) +[2026-07-22 19:35:51,086][50205] Updated weights for policy 0, policy_version 1703 (0.0015) +[2026-07-22 19:35:52,198][50205] Updated weights for policy 0, policy_version 1713 (0.0016) +[2026-07-22 19:35:52,700][50205] Updated weights for policy 0, policy_version 1723 (0.0012) +[2026-07-22 19:35:54,008][50205] Updated weights for policy 0, policy_version 1733 (0.0020) +[2026-07-22 19:35:54,877][43431] Fps is (10 sec: 5120.1, 60 sec: 5324.8, 300 sec: 4982.0). Total num frames: 890880. Throughput: 0: 5290.9. Samples: 901962. Policy #0 lag: (min: 3.0, avg: 17.3, max: 35.0) +[2026-07-22 19:35:54,878][43431] Avg episode reward: [(0, '494.582')] +[2026-07-22 19:35:54,953][50205] Updated weights for policy 0, policy_version 1743 (0.0013) +[2026-07-22 19:35:55,729][50205] Updated weights for policy 0, policy_version 1753 (0.0012) +[2026-07-22 19:35:56,491][50205] Updated weights for policy 0, policy_version 1763 (0.0012) +[2026-07-22 19:35:57,817][50205] Updated weights for policy 0, policy_version 1773 (0.0011) +[2026-07-22 19:35:58,462][50205] Updated weights for policy 0, policy_version 1783 (0.0011) +[2026-07-22 19:35:59,337][50205] Updated weights for policy 0, policy_version 1793 (0.0017) +[2026-07-22 19:35:59,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5324.8, 300 sec: 5002.4). Total num frames: 919552. Throughput: 0: 5326.2. Samples: 918448. Policy #0 lag: (min: 3.0, avg: 19.8, max: 35.0) +[2026-07-22 19:35:59,878][43431] Avg episode reward: [(0, '510.540')] +[2026-07-22 19:35:59,907][49527] Saving new best policy, reward=510.540! +[2026-07-22 19:36:00,493][50205] Updated weights for policy 0, policy_version 1803 (0.0018) +[2026-07-22 19:36:01,310][50205] Updated weights for policy 0, policy_version 1813 (0.0011) +[2026-07-22 19:36:02,336][50205] Updated weights for policy 0, policy_version 1823 (0.0011) +[2026-07-22 19:36:03,335][50205] Updated weights for policy 0, policy_version 1833 (0.0013) +[2026-07-22 19:36:04,226][50205] Updated weights for policy 0, policy_version 1843 (0.0019) +[2026-07-22 19:36:04,879][43431] Fps is (10 sec: 5528.6, 60 sec: 5324.7, 300 sec: 5010.9). Total num frames: 946176. Throughput: 0: 5352.8. Samples: 951084. Policy #0 lag: (min: 3.0, avg: 19.4, max: 38.0) +[2026-07-22 19:36:04,881][43431] Avg episode reward: [(0, '543.648')] +[2026-07-22 19:36:05,001][49527] Saving new best policy, reward=543.648! +[2026-07-22 19:36:05,178][50205] Updated weights for policy 0, policy_version 1853 (0.0012) +[2026-07-22 19:36:05,927][50205] Updated weights for policy 0, policy_version 1863 (0.0016) +[2026-07-22 19:36:06,959][50205] Updated weights for policy 0, policy_version 1873 (0.0012) +[2026-07-22 19:36:07,870][50205] Updated weights for policy 0, policy_version 1883 (0.0016) +[2026-07-22 19:36:08,845][50205] Updated weights for policy 0, policy_version 1893 (0.0011) +[2026-07-22 19:36:09,747][50205] Updated weights for policy 0, policy_version 1903 (0.0011) +[2026-07-22 19:36:09,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5358.9, 300 sec: 5029.6). Total num frames: 974848. Throughput: 0: 5349.2. Samples: 984158. Policy #0 lag: (min: 2.0, avg: 20.5, max: 38.0) +[2026-07-22 19:36:09,878][43431] Avg episode reward: [(0, '460.532')] +[2026-07-22 19:36:10,753][50205] Updated weights for policy 0, policy_version 1913 (0.0011) +[2026-07-22 19:36:11,522][50205] Updated weights for policy 0, policy_version 1923 (0.0016) +[2026-07-22 19:36:12,822][50205] Updated weights for policy 0, policy_version 1933 (0.0012) +[2026-07-22 19:36:13,425][50205] Updated weights for policy 0, policy_version 1943 (0.0010) +[2026-07-22 19:36:14,358][50205] Updated weights for policy 0, policy_version 1953 (0.0011) +[2026-07-22 19:36:14,877][43431] Fps is (10 sec: 5530.6, 60 sec: 5358.9, 300 sec: 5037.1). Total num frames: 1001472. Throughput: 0: 5343.6. Samples: 1000772. Policy #0 lag: (min: 3.0, avg: 21.3, max: 43.0) +[2026-07-22 19:36:14,878][43431] Avg episode reward: [(0, '513.201')] +[2026-07-22 19:36:15,304][50205] Updated weights for policy 0, policy_version 1963 (0.0017) +[2026-07-22 19:36:16,338][50205] Updated weights for policy 0, policy_version 1973 (0.0012) +[2026-07-22 19:36:17,249][50205] Updated weights for policy 0, policy_version 1983 (0.0011) +[2026-07-22 19:36:18,154][50205] Updated weights for policy 0, policy_version 1993 (0.0012) +[2026-07-22 19:36:18,870][50205] Updated weights for policy 0, policy_version 2003 (0.0011) +[2026-07-22 19:36:19,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5393.1, 300 sec: 5054.2). Total num frames: 1030144. Throughput: 0: 5428.5. Samples: 1034102. Policy #0 lag: (min: 3.0, avg: 17.4, max: 35.0) +[2026-07-22 19:36:19,878][43431] Avg episode reward: [(0, '506.519')] +[2026-07-22 19:36:20,075][50205] Updated weights for policy 0, policy_version 2013 (0.0014) +[2026-07-22 19:36:20,758][50205] Updated weights for policy 0, policy_version 2023 (0.0015) +[2026-07-22 19:36:21,723][50205] Updated weights for policy 0, policy_version 2033 (0.0011) +[2026-07-22 19:36:22,742][50205] Updated weights for policy 0, policy_version 2043 (0.0011) +[2026-07-22 19:36:23,977][50205] Updated weights for policy 0, policy_version 2053 (0.0011) +[2026-07-22 19:36:24,605][50205] Updated weights for policy 0, policy_version 2063 (0.0010) +[2026-07-22 19:36:24,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5427.2, 300 sec: 5070.5). Total num frames: 1058816. Throughput: 0: 5464.8. Samples: 1067130. Policy #0 lag: (min: 0.0, avg: 20.6, max: 44.0) +[2026-07-22 19:36:24,878][43431] Avg episode reward: [(0, '525.837')] +[2026-07-22 19:36:25,494][50205] Updated weights for policy 0, policy_version 2073 (0.0014) +[2026-07-22 19:36:26,643][50205] Updated weights for policy 0, policy_version 2083 (0.0014) +[2026-07-22 19:36:27,762][50205] Updated weights for policy 0, policy_version 2093 (0.0015) +[2026-07-22 19:36:29,178][50205] Updated weights for policy 0, policy_version 2107 (0.0020) +[2026-07-22 19:36:29,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5358.9, 300 sec: 5057.3). Total num frames: 1081344. Throughput: 0: 5435.7. Samples: 1082332. Policy #0 lag: (min: 3.0, avg: 14.0, max: 39.0) +[2026-07-22 19:36:29,878][43431] Avg episode reward: [(0, '523.246')] +[2026-07-22 19:36:30,360][50205] Updated weights for policy 0, policy_version 2117 (0.0017) +[2026-07-22 19:36:31,140][50205] Updated weights for policy 0, policy_version 2127 (0.0015) +[2026-07-22 19:36:32,145][50205] Updated weights for policy 0, policy_version 2137 (0.0011) +[2026-07-22 19:36:33,194][50205] Updated weights for policy 0, policy_version 2147 (0.0015) +[2026-07-22 19:36:34,120][50205] Updated weights for policy 0, policy_version 2157 (0.0013) +[2026-07-22 19:36:34,818][50205] Updated weights for policy 0, policy_version 2167 (0.0010) +[2026-07-22 19:36:34,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5427.2, 300 sec: 5072.7). Total num frames: 1110016. Throughput: 0: 5406.2. Samples: 1112518. Policy #0 lag: (min: 0.0, avg: 19.4, max: 38.0) +[2026-07-22 19:36:34,878][43431] Avg episode reward: [(0, '505.023')] +[2026-07-22 19:36:36,386][50205] Updated weights for policy 0, policy_version 2177 (0.0015) +[2026-07-22 19:36:36,937][50205] Updated weights for policy 0, policy_version 2187 (0.0015) +[2026-07-22 19:36:38,000][50205] Updated weights for policy 0, policy_version 2197 (0.0011) +[2026-07-22 19:36:39,737][50205] Updated weights for policy 0, policy_version 2209 (0.0017) +[2026-07-22 19:36:39,879][43431] Fps is (10 sec: 5119.2, 60 sec: 5358.8, 300 sec: 5060.0). Total num frames: 1132544. Throughput: 0: 5357.8. Samples: 1143072. Policy #0 lag: (min: 3.0, avg: 19.1, max: 35.0) +[2026-07-22 19:36:39,880][43431] Avg episode reward: [(0, '491.290')] +[2026-07-22 19:36:40,144][50205] Updated weights for policy 0, policy_version 2219 (0.0011) +[2026-07-22 19:36:41,153][50205] Updated weights for policy 0, policy_version 2229 (0.0015) +[2026-07-22 19:36:42,327][50205] Updated weights for policy 0, policy_version 2239 (0.0014) +[2026-07-22 19:36:43,009][50205] Updated weights for policy 0, policy_version 2249 (0.0012) +[2026-07-22 19:36:43,720][50205] Updated weights for policy 0, policy_version 2259 (0.0021) +[2026-07-22 19:36:44,877][43431] Fps is (10 sec: 4915.3, 60 sec: 5324.8, 300 sec: 5065.8). Total num frames: 1159168. Throughput: 0: 5361.0. Samples: 1159692. Policy #0 lag: (min: 0.0, avg: 14.9, max: 32.0) +[2026-07-22 19:36:44,878][43431] Avg episode reward: [(0, '477.180')] +[2026-07-22 19:36:45,168][50205] Updated weights for policy 0, policy_version 2269 (0.0010) +[2026-07-22 19:36:45,750][50205] Updated weights for policy 0, policy_version 2279 (0.0011) +[2026-07-22 19:36:46,647][50205] Updated weights for policy 0, policy_version 2289 (0.0012) +[2026-07-22 19:36:47,817][50205] Updated weights for policy 0, policy_version 2299 (0.0018) +[2026-07-22 19:36:48,680][50205] Updated weights for policy 0, policy_version 2309 (0.0014) +[2026-07-22 19:36:49,389][50205] Updated weights for policy 0, policy_version 2319 (0.0011) +[2026-07-22 19:36:49,877][43431] Fps is (10 sec: 5735.4, 60 sec: 5427.2, 300 sec: 5088.9). Total num frames: 1189888. Throughput: 0: 5376.1. Samples: 1193000. Policy #0 lag: (min: 3.0, avg: 21.2, max: 39.0) +[2026-07-22 19:36:49,878][43431] Avg episode reward: [(0, '524.866')] +[2026-07-22 19:36:50,681][50205] Updated weights for policy 0, policy_version 2329 (0.0021) +[2026-07-22 19:36:51,341][50205] Updated weights for policy 0, policy_version 2339 (0.0017) +[2026-07-22 19:36:52,081][50205] Updated weights for policy 0, policy_version 2349 (0.0011) +[2026-07-22 19:36:53,412][50205] Updated weights for policy 0, policy_version 2359 (0.0011) +[2026-07-22 19:36:54,329][50205] Updated weights for policy 0, policy_version 2369 (0.0020) +[2026-07-22 19:36:54,812][50205] Updated weights for policy 0, policy_version 2379 (0.0011) +[2026-07-22 19:36:54,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5461.3, 300 sec: 5102.4). Total num frames: 1218560. Throughput: 0: 5386.0. Samples: 1226526. Policy #0 lag: (min: 1.0, avg: 19.1, max: 37.0) +[2026-07-22 19:36:54,878][43431] Avg episode reward: [(0, '566.760')] +[2026-07-22 19:36:54,893][49527] Saving new best policy, reward=566.760! +[2026-07-22 19:36:56,117][50205] Updated weights for policy 0, policy_version 2389 (0.0010) +[2026-07-22 19:36:57,075][50205] Updated weights for policy 0, policy_version 2399 (0.0011) +[2026-07-22 19:36:57,772][50205] Updated weights for policy 0, policy_version 2409 (0.0017) +[2026-07-22 19:36:58,491][50205] Updated weights for policy 0, policy_version 2419 (0.0013) +[2026-07-22 19:36:59,864][50205] Updated weights for policy 0, policy_version 2429 (0.0014) +[2026-07-22 19:36:59,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5393.1, 300 sec: 5098.6). Total num frames: 1243136. Throughput: 0: 5388.8. Samples: 1243268. Policy #0 lag: (min: 1.0, avg: 13.3, max: 33.0) +[2026-07-22 19:36:59,878][43431] Avg episode reward: [(0, '555.003')] +[2026-07-22 19:37:00,376][50205] Updated weights for policy 0, policy_version 2439 (0.0017) +[2026-07-22 19:37:01,708][50205] Updated weights for policy 0, policy_version 2449 (0.0016) +[2026-07-22 19:37:02,378][50205] Updated weights for policy 0, policy_version 2459 (0.0014) +[2026-07-22 19:37:03,519][50205] Updated weights for policy 0, policy_version 2469 (0.0028) +[2026-07-22 19:37:04,750][50205] Updated weights for policy 0, policy_version 2479 (0.0016) +[2026-07-22 19:37:04,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5393.2, 300 sec: 5103.1). Total num frames: 1269760. Throughput: 0: 5352.1. Samples: 1274946. Policy #0 lag: (min: 3.0, avg: 17.2, max: 35.0) +[2026-07-22 19:37:04,878][43431] Avg episode reward: [(0, '541.871')] +[2026-07-22 19:37:05,688][50205] Updated weights for policy 0, policy_version 2489 (0.0016) +[2026-07-22 19:37:06,269][50205] Updated weights for policy 0, policy_version 2499 (0.0019) +[2026-07-22 19:37:07,640][50205] Updated weights for policy 0, policy_version 2509 (0.0016) +[2026-07-22 19:37:08,450][50205] Updated weights for policy 0, policy_version 2519 (0.0022) +[2026-07-22 19:37:09,343][50205] Updated weights for policy 0, policy_version 2529 (0.0017) +[2026-07-22 19:37:09,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5393.1, 300 sec: 5115.6). Total num frames: 1298432. Throughput: 0: 5334.8. Samples: 1307198. Policy #0 lag: (min: 0.0, avg: 18.7, max: 36.0) +[2026-07-22 19:37:09,878][43431] Avg episode reward: [(0, '533.263')] +[2026-07-22 19:37:10,168][50205] Updated weights for policy 0, policy_version 2539 (0.0016) +[2026-07-22 19:37:11,364][50205] Updated weights for policy 0, policy_version 2549 (0.0012) +[2026-07-22 19:37:12,015][50205] Updated weights for policy 0, policy_version 2559 (0.0014) +[2026-07-22 19:37:13,172][50205] Updated weights for policy 0, policy_version 2569 (0.0012) +[2026-07-22 19:37:14,181][50205] Updated weights for policy 0, policy_version 2579 (0.0014) +[2026-07-22 19:37:14,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5393.1, 300 sec: 5119.6). Total num frames: 1325056. Throughput: 0: 5348.5. Samples: 1323014. Policy #0 lag: (min: 6.0, avg: 20.1, max: 42.0) +[2026-07-22 19:37:14,878][43431] Avg episode reward: [(0, '592.896')] +[2026-07-22 19:37:14,895][49527] Saving new best policy, reward=592.896! +[2026-07-22 19:37:15,018][50205] Updated weights for policy 0, policy_version 2589 (0.0017) +[2026-07-22 19:37:15,816][50205] Updated weights for policy 0, policy_version 2599 (0.0014) +[2026-07-22 19:37:17,292][50205] Updated weights for policy 0, policy_version 2609 (0.0021) +[2026-07-22 19:37:18,445][50205] Updated weights for policy 0, policy_version 2623 (0.0012) +[2026-07-22 19:37:19,388][50205] Updated weights for policy 0, policy_version 2633 (0.0011) +[2026-07-22 19:37:19,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5358.9, 300 sec: 5123.5). Total num frames: 1351680. Throughput: 0: 5379.0. Samples: 1354574. Policy #0 lag: (min: 0.0, avg: 18.4, max: 36.0) +[2026-07-22 19:37:19,878][43431] Avg episode reward: [(0, '539.654')] +[2026-07-22 19:37:20,524][50205] Updated weights for policy 0, policy_version 2643 (0.0012) +[2026-07-22 19:37:21,229][50205] Updated weights for policy 0, policy_version 2653 (0.0014) +[2026-07-22 19:37:21,907][50205] Updated weights for policy 0, policy_version 2663 (0.0011) +[2026-07-22 19:37:23,353][50205] Updated weights for policy 0, policy_version 2673 (0.0016) +[2026-07-22 19:37:24,056][50205] Updated weights for policy 0, policy_version 2683 (0.0012) +[2026-07-22 19:37:24,727][50205] Updated weights for policy 0, policy_version 2693 (0.0011) +[2026-07-22 19:37:24,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5358.9, 300 sec: 5134.8). Total num frames: 1380352. Throughput: 0: 5440.7. Samples: 1387892. Policy #0 lag: (min: 3.0, avg: 19.4, max: 35.0) +[2026-07-22 19:37:24,878][43431] Avg episode reward: [(0, '574.452')] +[2026-07-22 19:37:26,004][50205] Updated weights for policy 0, policy_version 2703 (0.0011) +[2026-07-22 19:37:26,862][50205] Updated weights for policy 0, policy_version 2713 (0.0013) +[2026-07-22 19:37:27,479][50205] Updated weights for policy 0, policy_version 2723 (0.0021) +[2026-07-22 19:37:28,759][50205] Updated weights for policy 0, policy_version 2733 (0.0016) +[2026-07-22 19:37:29,471][50205] Updated weights for policy 0, policy_version 2743 (0.0016) +[2026-07-22 19:37:29,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5427.2, 300 sec: 5138.3). Total num frames: 1406976. Throughput: 0: 5443.3. Samples: 1404642. Policy #0 lag: (min: 3.0, avg: 18.1, max: 35.0) +[2026-07-22 19:37:29,878][43431] Avg episode reward: [(0, '542.148')] +[2026-07-22 19:37:30,372][50205] Updated weights for policy 0, policy_version 2753 (0.0011) +[2026-07-22 19:37:31,255][50205] Updated weights for policy 0, policy_version 2763 (0.0015) +[2026-07-22 19:37:32,246][50205] Updated weights for policy 0, policy_version 2773 (0.0018) +[2026-07-22 19:37:33,098][50205] Updated weights for policy 0, policy_version 2783 (0.0010) +[2026-07-22 19:37:34,347][50205] Updated weights for policy 0, policy_version 2793 (0.0016) +[2026-07-22 19:37:34,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5393.1, 300 sec: 5141.7). Total num frames: 1433600. Throughput: 0: 5448.6. Samples: 1438186. Policy #0 lag: (min: 3.0, avg: 21.0, max: 36.0) +[2026-07-22 19:37:34,878][43431] Avg episode reward: [(0, '580.553')] +[2026-07-22 19:37:35,120][50205] Updated weights for policy 0, policy_version 2803 (0.0015) +[2026-07-22 19:37:36,010][50205] Updated weights for policy 0, policy_version 2813 (0.0012) +[2026-07-22 19:37:37,069][50205] Updated weights for policy 0, policy_version 2825 (0.0015) +[2026-07-22 19:37:38,107][50205] Updated weights for policy 0, policy_version 2835 (0.0021) +[2026-07-22 19:37:38,863][50205] Updated weights for policy 0, policy_version 2846 (0.0012) +[2026-07-22 19:37:39,576][50205] Updated weights for policy 0, policy_version 2856 (0.0020) +[2026-07-22 19:37:39,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.6, 300 sec: 5152.1). Total num frames: 1462272. Throughput: 0: 5422.8. Samples: 1470552. Policy #0 lag: (min: 3.0, avg: 16.3, max: 31.0) +[2026-07-22 19:37:39,878][43431] Avg episode reward: [(0, '554.386')] +[2026-07-22 19:37:41,118][50205] Updated weights for policy 0, policy_version 2866 (0.0013) +[2026-07-22 19:37:42,010][50205] Updated weights for policy 0, policy_version 2876 (0.0019) +[2026-07-22 19:37:43,043][50205] Updated weights for policy 0, policy_version 2886 (0.0011) +[2026-07-22 19:37:44,033][50205] Updated weights for policy 0, policy_version 2896 (0.0016) +[2026-07-22 19:37:44,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5427.2, 300 sec: 5140.9). Total num frames: 1484800. Throughput: 0: 5386.0. Samples: 1485640. Policy #0 lag: (min: 3.0, avg: 15.4, max: 31.0) +[2026-07-22 19:37:44,878][43431] Avg episode reward: [(0, '534.635')] +[2026-07-22 19:37:45,228][50205] Updated weights for policy 0, policy_version 2906 (0.0016) +[2026-07-22 19:37:45,671][50205] Updated weights for policy 0, policy_version 2916 (0.0031) +[2026-07-22 19:37:46,911][50205] Updated weights for policy 0, policy_version 2926 (0.0013) +[2026-07-22 19:37:48,585][50205] Updated weights for policy 0, policy_version 2937 (0.0012) +[2026-07-22 19:37:49,143][50205] Updated weights for policy 0, policy_version 2947 (0.0011) +[2026-07-22 19:37:49,877][43431] Fps is (10 sec: 4915.2, 60 sec: 5358.9, 300 sec: 5144.3). Total num frames: 1511424. Throughput: 0: 5352.8. Samples: 1515820. Policy #0 lag: (min: 3.0, avg: 19.7, max: 39.0) +[2026-07-22 19:37:49,878][43431] Avg episode reward: [(0, '563.155')] +[2026-07-22 19:37:50,201][50205] Updated weights for policy 0, policy_version 2957 (0.0020) +[2026-07-22 19:37:51,204][50205] Updated weights for policy 0, policy_version 2967 (0.0011) +[2026-07-22 19:37:52,026][50205] Updated weights for policy 0, policy_version 2977 (0.0011) +[2026-07-22 19:37:52,950][50205] Updated weights for policy 0, policy_version 2987 (0.0013) +[2026-07-22 19:37:53,963][50205] Updated weights for policy 0, policy_version 2997 (0.0012) +[2026-07-22 19:37:54,698][50205] Updated weights for policy 0, policy_version 3007 (0.0011) +[2026-07-22 19:37:54,878][43431] Fps is (10 sec: 5733.7, 60 sec: 5392.9, 300 sec: 5227.6). Total num frames: 1542144. Throughput: 0: 5378.0. Samples: 1549216. Policy #0 lag: (min: 3.0, avg: 18.3, max: 35.0) +[2026-07-22 19:37:54,879][43431] Avg episode reward: [(0, '535.916')] +[2026-07-22 19:37:55,823][50205] Updated weights for policy 0, policy_version 3017 (0.0015) +[2026-07-22 19:37:56,758][50205] Updated weights for policy 0, policy_version 3027 (0.0016) +[2026-07-22 19:37:57,498][50205] Updated weights for policy 0, policy_version 3037 (0.0014) +[2026-07-22 19:37:58,461][50205] Updated weights for policy 0, policy_version 3047 (0.0018) +[2026-07-22 19:37:59,597][50205] Updated weights for policy 0, policy_version 3057 (0.0012) +[2026-07-22 19:37:59,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5427.2, 300 sec: 5317.9). Total num frames: 1568768. Throughput: 0: 5398.1. Samples: 1565930. Policy #0 lag: (min: 3.0, avg: 21.1, max: 39.0) +[2026-07-22 19:37:59,878][43431] Avg episode reward: [(0, '583.649')] +[2026-07-22 19:38:00,467][50205] Updated weights for policy 0, policy_version 3067 (0.0012) +[2026-07-22 19:38:01,236][50205] Updated weights for policy 0, policy_version 3077 (0.0010) +[2026-07-22 19:38:02,203][50205] Updated weights for policy 0, policy_version 3087 (0.0014) +[2026-07-22 19:38:03,339][50205] Updated weights for policy 0, policy_version 3097 (0.0012) +[2026-07-22 19:38:04,094][50205] Updated weights for policy 0, policy_version 3107 (0.0011) +[2026-07-22 19:38:04,877][43431] Fps is (10 sec: 5325.5, 60 sec: 5427.2, 300 sec: 5345.6). Total num frames: 1595392. Throughput: 0: 5431.0. Samples: 1598970. Policy #0 lag: (min: 0.0, avg: 20.1, max: 40.0) +[2026-07-22 19:38:04,878][43431] Avg episode reward: [(0, '593.897')] +[2026-07-22 19:38:04,906][49527] Saving new best policy, reward=593.897! +[2026-07-22 19:38:05,127][50205] Updated weights for policy 0, policy_version 3117 (0.0011) +[2026-07-22 19:38:05,879][50205] Updated weights for policy 0, policy_version 3127 (0.0011) +[2026-07-22 19:38:06,839][50205] Updated weights for policy 0, policy_version 3137 (0.0012) +[2026-07-22 19:38:07,743][50205] Updated weights for policy 0, policy_version 3147 (0.0016) +[2026-07-22 19:38:08,709][50205] Updated weights for policy 0, policy_version 3157 (0.0014) +[2026-07-22 19:38:09,496][50205] Updated weights for policy 0, policy_version 3167 (0.0011) +[2026-07-22 19:38:09,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5393.1, 300 sec: 5359.5). Total num frames: 1622016. Throughput: 0: 5434.3. Samples: 1632438. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 19:38:09,878][43431] Avg episode reward: [(0, '586.183')] +[2026-07-22 19:38:10,635][50205] Updated weights for policy 0, policy_version 3177 (0.0017) +[2026-07-22 19:38:11,349][50205] Updated weights for policy 0, policy_version 3187 (0.0015) +[2026-07-22 19:38:12,299][50205] Updated weights for policy 0, policy_version 3197 (0.0011) +[2026-07-22 19:38:13,117][50205] Updated weights for policy 0, policy_version 3207 (0.0013) +[2026-07-22 19:38:14,281][50205] Updated weights for policy 0, policy_version 3217 (0.0011) +[2026-07-22 19:38:14,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5393.1, 300 sec: 5373.4). Total num frames: 1648640. Throughput: 0: 5432.8. Samples: 1649118. Policy #0 lag: (min: 1.0, avg: 17.4, max: 36.0) +[2026-07-22 19:38:14,878][43431] Avg episode reward: [(0, '558.018')] +[2026-07-22 19:38:15,245][49527] Signal inference workers to stop experience collection... (50 times) +[2026-07-22 19:38:15,254][50205] Updated weights for policy 0, policy_version 3227 (0.0012) +[2026-07-22 19:38:15,261][50205] InferenceWorker_p0-w0: stopping experience collection (50 times) +[2026-07-22 19:38:15,271][49527] Signal inference workers to resume experience collection... (50 times) +[2026-07-22 19:38:15,274][50205] InferenceWorker_p0-w0: resuming experience collection (50 times) +[2026-07-22 19:38:16,122][50205] Updated weights for policy 0, policy_version 3237 (0.0011) +[2026-07-22 19:38:16,753][50205] Updated weights for policy 0, policy_version 3247 (0.0015) +[2026-07-22 19:38:18,147][50205] Updated weights for policy 0, policy_version 3257 (0.0016) +[2026-07-22 19:38:18,691][50205] Updated weights for policy 0, policy_version 3267 (0.0012) +[2026-07-22 19:38:19,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5393.1, 300 sec: 5373.4). Total num frames: 1675264. Throughput: 0: 5399.2. Samples: 1681152. Policy #0 lag: (min: 3.0, avg: 20.8, max: 43.0) +[2026-07-22 19:38:19,878][43431] Avg episode reward: [(0, '598.995')] +[2026-07-22 19:38:19,971][49527] Saving new best policy, reward=598.995! +[2026-07-22 19:38:20,081][50205] Updated weights for policy 0, policy_version 3277 (0.0013) +[2026-07-22 19:38:21,147][50205] Updated weights for policy 0, policy_version 3287 (0.0012) +[2026-07-22 19:38:22,071][50205] Updated weights for policy 0, policy_version 3297 (0.0014) +[2026-07-22 19:38:23,179][50205] Updated weights for policy 0, policy_version 3307 (0.0020) +[2026-07-22 19:38:24,075][50205] Updated weights for policy 0, policy_version 3317 (0.0011) +[2026-07-22 19:38:24,735][50205] Updated weights for policy 0, policy_version 3327 (0.0011) +[2026-07-22 19:38:24,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5393.1, 300 sec: 5373.4). Total num frames: 1703936. Throughput: 0: 5382.0. Samples: 1712740. Policy #0 lag: (min: 3.0, avg: 19.8, max: 43.0) +[2026-07-22 19:38:24,878][43431] Avg episode reward: [(0, '623.789')] +[2026-07-22 19:38:25,084][49527] Saving new best policy, reward=623.789! +[2026-07-22 19:38:25,932][50205] Updated weights for policy 0, policy_version 3337 (0.0011) +[2026-07-22 19:38:26,800][50205] Updated weights for policy 0, policy_version 3347 (0.0013) +[2026-07-22 19:38:27,584][50205] Updated weights for policy 0, policy_version 3357 (0.0016) +[2026-07-22 19:38:28,700][50205] Updated weights for policy 0, policy_version 3367 (0.0017) +[2026-07-22 19:38:29,555][50205] Updated weights for policy 0, policy_version 3377 (0.0012) +[2026-07-22 19:38:29,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5393.1, 300 sec: 5373.4). Total num frames: 1730560. Throughput: 0: 5419.3. Samples: 1729510. Policy #0 lag: (min: 3.0, avg: 17.5, max: 35.0) +[2026-07-22 19:38:29,878][43431] Avg episode reward: [(0, '634.070')] +[2026-07-22 19:38:29,950][49527] Saving new best policy, reward=634.070! +[2026-07-22 19:38:30,241][50205] Updated weights for policy 0, policy_version 3387 (0.0011) +[2026-07-22 19:38:31,553][50205] Updated weights for policy 0, policy_version 3397 (0.0020) +[2026-07-22 19:38:32,252][50205] Updated weights for policy 0, policy_version 3407 (0.0011) +[2026-07-22 19:38:33,080][50205] Updated weights for policy 0, policy_version 3417 (0.0010) +[2026-07-22 19:38:33,945][50205] Updated weights for policy 0, policy_version 3427 (0.0012) +[2026-07-22 19:38:34,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5427.2, 300 sec: 5373.4). Total num frames: 1759232. Throughput: 0: 5493.9. Samples: 1763044. Policy #0 lag: (min: 3.0, avg: 19.8, max: 35.0) +[2026-07-22 19:38:34,878][43431] Avg episode reward: [(0, '698.440')] +[2026-07-22 19:38:34,952][50205] Updated weights for policy 0, policy_version 3437 (0.0015) +[2026-07-22 19:38:35,016][49527] Saving new best policy, reward=698.440! +[2026-07-22 19:38:35,832][50205] Updated weights for policy 0, policy_version 3447 (0.0011) +[2026-07-22 19:38:36,962][50205] Updated weights for policy 0, policy_version 3457 (0.0011) +[2026-07-22 19:38:37,606][50205] Updated weights for policy 0, policy_version 3467 (0.0011) +[2026-07-22 19:38:38,611][50205] Updated weights for policy 0, policy_version 3477 (0.0011) +[2026-07-22 19:38:39,632][50205] Updated weights for policy 0, policy_version 3487 (0.0014) +[2026-07-22 19:38:39,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5393.1, 300 sec: 5373.4). Total num frames: 1785856. Throughput: 0: 5496.7. Samples: 1796560. Policy #0 lag: (min: 0.0, avg: 19.4, max: 34.0) +[2026-07-22 19:38:39,878][43431] Avg episode reward: [(0, '697.764')] +[2026-07-22 19:38:40,514][50205] Updated weights for policy 0, policy_version 3497 (0.0011) +[2026-07-22 19:38:41,278][50205] Updated weights for policy 0, policy_version 3507 (0.0011) +[2026-07-22 19:38:42,267][50205] Updated weights for policy 0, policy_version 3517 (0.0013) +[2026-07-22 19:38:43,163][50205] Updated weights for policy 0, policy_version 3527 (0.0012) +[2026-07-22 19:38:44,178][50205] Updated weights for policy 0, policy_version 3537 (0.0016) +[2026-07-22 19:38:44,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5387.3). Total num frames: 1814528. Throughput: 0: 5499.4. Samples: 1813402. Policy #0 lag: (min: 3.0, avg: 18.4, max: 43.0) +[2026-07-22 19:38:44,878][43431] Avg episode reward: [(0, '706.964')] +[2026-07-22 19:38:45,273][49527] Saving new best policy, reward=706.964! +[2026-07-22 19:38:45,387][50205] Updated weights for policy 0, policy_version 3549 (0.0011) +[2026-07-22 19:38:46,077][50205] Updated weights for policy 0, policy_version 3559 (0.0015) +[2026-07-22 19:38:47,313][50205] Updated weights for policy 0, policy_version 3569 (0.0018) +[2026-07-22 19:38:47,741][50205] Updated weights for policy 0, policy_version 3579 (0.0011) +[2026-07-22 19:38:48,872][50205] Updated weights for policy 0, policy_version 3589 (0.0016) +[2026-07-22 19:38:49,838][50205] Updated weights for policy 0, policy_version 3599 (0.0011) +[2026-07-22 19:38:49,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5529.6, 300 sec: 5387.3). Total num frames: 1843200. Throughput: 0: 5504.8. Samples: 1846684. Policy #0 lag: (min: 3.0, avg: 19.4, max: 39.0) +[2026-07-22 19:38:49,878][43431] Avg episode reward: [(0, '587.882')] +[2026-07-22 19:38:50,727][50205] Updated weights for policy 0, policy_version 3609 (0.0013) +[2026-07-22 19:38:51,601][50205] Updated weights for policy 0, policy_version 3619 (0.0013) +[2026-07-22 19:38:52,728][50205] Updated weights for policy 0, policy_version 3629 (0.0016) +[2026-07-22 19:38:53,200][50205] Updated weights for policy 0, policy_version 3639 (0.0020) +[2026-07-22 19:38:54,594][50205] Updated weights for policy 0, policy_version 3649 (0.0012) +[2026-07-22 19:38:54,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5495.6, 300 sec: 5401.2). Total num frames: 1871872. Throughput: 0: 5506.6. Samples: 1880232. Policy #0 lag: (min: 3.0, avg: 19.8, max: 39.0) +[2026-07-22 19:38:54,878][43431] Avg episode reward: [(0, '618.945')] +[2026-07-22 19:38:55,370][50205] Updated weights for policy 0, policy_version 3659 (0.0015) +[2026-07-22 19:38:56,293][50205] Updated weights for policy 0, policy_version 3669 (0.0011) +[2026-07-22 19:38:57,212][50205] Updated weights for policy 0, policy_version 3679 (0.0011) +[2026-07-22 19:38:58,500][50205] Updated weights for policy 0, policy_version 3689 (0.0012) +[2026-07-22 19:38:59,375][50205] Updated weights for policy 0, policy_version 3699 (0.0011) +[2026-07-22 19:38:59,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5461.3, 300 sec: 5394.3). Total num frames: 1896448. Throughput: 0: 5479.1. Samples: 1895676. Policy #0 lag: (min: 3.0, avg: 18.1, max: 35.0) +[2026-07-22 19:38:59,878][43431] Avg episode reward: [(0, '572.639')] +[2026-07-22 19:39:00,335][50205] Updated weights for policy 0, policy_version 3709 (0.0016) +[2026-07-22 19:39:01,388][50205] Updated weights for policy 0, policy_version 3719 (0.0011) +[2026-07-22 19:39:02,847][50205] Updated weights for policy 0, policy_version 3732 (0.0011) +[2026-07-22 19:39:03,704][50205] Updated weights for policy 0, policy_version 3742 (0.0011) +[2026-07-22 19:39:04,476][50205] Updated weights for policy 0, policy_version 3752 (0.0014) +[2026-07-22 19:39:04,877][43431] Fps is (10 sec: 4915.2, 60 sec: 5427.2, 300 sec: 5387.3). Total num frames: 1921024. Throughput: 0: 5432.4. Samples: 1925612. Policy #0 lag: (min: 3.0, avg: 16.1, max: 36.0) +[2026-07-22 19:39:04,878][43431] Avg episode reward: [(0, '596.585')] +[2026-07-22 19:39:05,856][50205] Updated weights for policy 0, policy_version 3762 (0.0011) +[2026-07-22 19:39:06,346][50205] Updated weights for policy 0, policy_version 3772 (0.0021) +[2026-07-22 19:39:07,562][50205] Updated weights for policy 0, policy_version 3782 (0.0015) +[2026-07-22 19:39:08,208][50205] Updated weights for policy 0, policy_version 3792 (0.0013) +[2026-07-22 19:39:09,340][50205] Updated weights for policy 0, policy_version 3802 (0.0011) +[2026-07-22 19:39:09,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5461.4, 300 sec: 5387.3). Total num frames: 1949696. Throughput: 0: 5478.5. Samples: 1959274. Policy #0 lag: (min: 3.0, avg: 18.7, max: 39.0) +[2026-07-22 19:39:09,878][43431] Avg episode reward: [(0, '613.580')] +[2026-07-22 19:39:10,203][50205] Updated weights for policy 0, policy_version 3812 (0.0011) +[2026-07-22 19:39:10,967][50205] Updated weights for policy 0, policy_version 3823 (0.0012) +[2026-07-22 19:39:12,130][50205] Updated weights for policy 0, policy_version 3833 (0.0010) +[2026-07-22 19:39:13,235][50205] Updated weights for policy 0, policy_version 3843 (0.0016) +[2026-07-22 19:39:14,003][50205] Updated weights for policy 0, policy_version 3853 (0.0017) +[2026-07-22 19:39:14,770][50205] Updated weights for policy 0, policy_version 3863 (0.0020) +[2026-07-22 19:39:14,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5495.5, 300 sec: 5401.2). Total num frames: 1978368. Throughput: 0: 5474.9. Samples: 1975880. Policy #0 lag: (min: 3.0, avg: 20.5, max: 43.0) +[2026-07-22 19:39:14,878][43431] Avg episode reward: [(0, '680.270')] +[2026-07-22 19:39:16,021][50205] Updated weights for policy 0, policy_version 3873 (0.0016) +[2026-07-22 19:39:16,843][50205] Updated weights for policy 0, policy_version 3883 (0.0011) +[2026-07-22 19:39:17,611][50205] Updated weights for policy 0, policy_version 3893 (0.0017) +[2026-07-22 19:39:18,451][50205] Updated weights for policy 0, policy_version 3903 (0.0016) +[2026-07-22 19:39:19,582][50205] Updated weights for policy 0, policy_version 3913 (0.0012) +[2026-07-22 19:39:19,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5401.2). Total num frames: 2004992. Throughput: 0: 5476.9. Samples: 2009506. Policy #0 lag: (min: 3.0, avg: 20.6, max: 47.0) +[2026-07-22 19:39:19,878][43431] Avg episode reward: [(0, '616.227')] +[2026-07-22 19:39:20,292][50205] Updated weights for policy 0, policy_version 3923 (0.0011) +[2026-07-22 19:39:21,413][50205] Updated weights for policy 0, policy_version 3933 (0.0013) +[2026-07-22 19:39:22,221][50205] Updated weights for policy 0, policy_version 3943 (0.0014) +[2026-07-22 19:39:23,110][50205] Updated weights for policy 0, policy_version 3953 (0.0013) +[2026-07-22 19:39:24,057][50205] Updated weights for policy 0, policy_version 3963 (0.0011) +[2026-07-22 19:39:24,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5394.2). Total num frames: 2033664. Throughput: 0: 5475.2. Samples: 2042944. Policy #0 lag: (min: 3.0, avg: 17.1, max: 35.0) +[2026-07-22 19:39:24,878][43431] Avg episode reward: [(0, '728.863')] +[2026-07-22 19:39:24,893][49527] Saving new best policy, reward=728.863! +[2026-07-22 19:39:25,064][50205] Updated weights for policy 0, policy_version 3973 (0.0012) +[2026-07-22 19:39:25,840][50205] Updated weights for policy 0, policy_version 3983 (0.0011) +[2026-07-22 19:39:27,038][50205] Updated weights for policy 0, policy_version 3993 (0.0011) +[2026-07-22 19:39:27,647][50205] Updated weights for policy 0, policy_version 4003 (0.0011) +[2026-07-22 19:39:28,656][50205] Updated weights for policy 0, policy_version 4013 (0.0012) +[2026-07-22 19:39:29,595][50205] Updated weights for policy 0, policy_version 4023 (0.0011) +[2026-07-22 19:39:29,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5529.6, 300 sec: 5408.1). Total num frames: 2062336. Throughput: 0: 5472.6. Samples: 2059670. Policy #0 lag: (min: 3.0, avg: 16.0, max: 35.0) +[2026-07-22 19:39:29,878][43431] Avg episode reward: [(0, '782.459')] +[2026-07-22 19:39:29,900][49527] Saving new best policy, reward=782.459! +[2026-07-22 19:39:30,456][50205] Updated weights for policy 0, policy_version 4033 (0.0011) +[2026-07-22 19:39:31,412][50205] Updated weights for policy 0, policy_version 4043 (0.0011) +[2026-07-22 19:39:32,536][50205] Updated weights for policy 0, policy_version 4053 (0.0015) +[2026-07-22 19:39:33,146][50205] Updated weights for policy 0, policy_version 4063 (0.0015) +[2026-07-22 19:39:34,271][50205] Updated weights for policy 0, policy_version 4073 (0.0015) +[2026-07-22 19:39:34,861][50205] Updated weights for policy 0, policy_version 4083 (0.0015) +[2026-07-22 19:39:34,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5529.6, 300 sec: 5415.1). Total num frames: 2091008. Throughput: 0: 5480.4. Samples: 2093300. Policy #0 lag: (min: 3.0, avg: 16.4, max: 31.0) +[2026-07-22 19:39:34,878][43431] Avg episode reward: [(0, '724.928')] +[2026-07-22 19:39:36,295][50205] Updated weights for policy 0, policy_version 4093 (0.0014) +[2026-07-22 19:39:37,247][50205] Updated weights for policy 0, policy_version 4103 (0.0011) +[2026-07-22 19:39:38,334][50205] Updated weights for policy 0, policy_version 4113 (0.0011) +[2026-07-22 19:39:39,186][50205] Updated weights for policy 0, policy_version 4123 (0.0011) +[2026-07-22 19:39:39,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5495.5, 300 sec: 5408.2). Total num frames: 2115584. Throughput: 0: 5424.7. Samples: 2124342. Policy #0 lag: (min: 3.0, avg: 16.1, max: 35.0) +[2026-07-22 19:39:39,878][43431] Avg episode reward: [(0, '679.861')] +[2026-07-22 19:39:40,108][50205] Updated weights for policy 0, policy_version 4133 (0.0017) +[2026-07-22 19:39:40,657][50205] Updated weights for policy 0, policy_version 4143 (0.0012) +[2026-07-22 19:39:41,988][50205] Updated weights for policy 0, policy_version 4153 (0.0017) +[2026-07-22 19:39:42,680][50205] Updated weights for policy 0, policy_version 4163 (0.0011) +[2026-07-22 19:39:44,877][43431] Fps is (10 sec: 4710.3, 60 sec: 5393.1, 300 sec: 5394.2). Total num frames: 2138112. Throughput: 0: 5454.8. Samples: 2141144. Policy #0 lag: (min: 3.0, avg: 20.1, max: 43.0) +[2026-07-22 19:39:44,879][43431] Avg episode reward: [(0, '612.767')] +[2026-07-22 19:39:44,883][50205] Updated weights for policy 0, policy_version 4177 (0.0012) +[2026-07-22 19:39:45,431][50205] Updated weights for policy 0, policy_version 4187 (0.0012) +[2026-07-22 19:39:46,362][50205] Updated weights for policy 0, policy_version 4197 (0.0011) +[2026-07-22 19:39:47,027][50205] Updated weights for policy 0, policy_version 4207 (0.0011) +[2026-07-22 19:39:48,278][50205] Updated weights for policy 0, policy_version 4217 (0.0011) +[2026-07-22 19:39:48,937][50205] Updated weights for policy 0, policy_version 4227 (0.0022) +[2026-07-22 19:39:49,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5427.2, 300 sec: 5415.1). Total num frames: 2168832. Throughput: 0: 5488.5. Samples: 2172596. Policy #0 lag: (min: 3.0, avg: 17.0, max: 36.0) +[2026-07-22 19:39:49,878][43431] Avg episode reward: [(0, '638.084')] +[2026-07-22 19:39:49,892][50205] Updated weights for policy 0, policy_version 4237 (0.0013) +[2026-07-22 19:39:51,122][50205] Updated weights for policy 0, policy_version 4249 (0.0011) +[2026-07-22 19:39:52,040][50205] Updated weights for policy 0, policy_version 4259 (0.0012) +[2026-07-22 19:39:52,965][50205] Updated weights for policy 0, policy_version 4269 (0.0010) +[2026-07-22 19:39:53,955][50205] Updated weights for policy 0, policy_version 4279 (0.0012) +[2026-07-22 19:39:54,775][50205] Updated weights for policy 0, policy_version 4289 (0.0021) +[2026-07-22 19:39:54,877][43431] Fps is (10 sec: 5939.3, 60 sec: 5427.2, 300 sec: 5415.1). Total num frames: 2197504. Throughput: 0: 5478.4. Samples: 2205802. Policy #0 lag: (min: 3.0, avg: 20.9, max: 43.0) +[2026-07-22 19:39:54,878][43431] Avg episode reward: [(0, '739.590')] +[2026-07-22 19:39:55,598][50205] Updated weights for policy 0, policy_version 4299 (0.0011) +[2026-07-22 19:39:56,809][50205] Updated weights for policy 0, policy_version 4309 (0.0013) +[2026-07-22 19:39:57,379][50205] Updated weights for policy 0, policy_version 4320 (0.0014) +[2026-07-22 19:39:58,612][50205] Updated weights for policy 0, policy_version 4330 (0.0010) +[2026-07-22 19:39:59,594][50205] Updated weights for policy 0, policy_version 4340 (0.0011) +[2026-07-22 19:39:59,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5461.3, 300 sec: 5415.1). Total num frames: 2224128. Throughput: 0: 5482.4. Samples: 2222586. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 19:39:59,878][43431] Avg episode reward: [(0, '696.005')] +[2026-07-22 19:40:00,842][50205] Updated weights for policy 0, policy_version 4353 (0.0017) +[2026-07-22 19:40:02,104][50205] Updated weights for policy 0, policy_version 4366 (0.0011) +[2026-07-22 19:40:02,931][50205] Updated weights for policy 0, policy_version 4376 (0.0016) +[2026-07-22 19:40:04,026][50205] Updated weights for policy 0, policy_version 4386 (0.0016) +[2026-07-22 19:40:04,613][50205] Updated weights for policy 0, policy_version 4396 (0.0012) +[2026-07-22 19:40:04,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5495.5, 300 sec: 5415.1). Total num frames: 2250752. Throughput: 0: 5434.0. Samples: 2254038. Policy #0 lag: (min: 0.0, avg: 16.6, max: 36.0) +[2026-07-22 19:40:04,878][43431] Avg episode reward: [(0, '754.718')] +[2026-07-22 19:40:05,775][50205] Updated weights for policy 0, policy_version 4406 (0.0013) +[2026-07-22 19:40:06,575][50205] Updated weights for policy 0, policy_version 4416 (0.0018) +[2026-07-22 19:40:07,740][50205] Updated weights for policy 0, policy_version 4426 (0.0015) +[2026-07-22 19:40:08,578][50205] Updated weights for policy 0, policy_version 4436 (0.0012) +[2026-07-22 19:40:09,373][50205] Updated weights for policy 0, policy_version 4446 (0.0018) +[2026-07-22 19:40:09,878][43431] Fps is (10 sec: 5529.4, 60 sec: 5495.4, 300 sec: 5422.0). Total num frames: 2279424. Throughput: 0: 5438.0. Samples: 2287656. Policy #0 lag: (min: 3.0, avg: 18.7, max: 39.0) +[2026-07-22 19:40:09,878][43431] Avg episode reward: [(0, '761.506')] +[2026-07-22 19:40:10,292][50205] Updated weights for policy 0, policy_version 4456 (0.0016) +[2026-07-22 19:40:11,397][50205] Updated weights for policy 0, policy_version 4466 (0.0015) +[2026-07-22 19:40:12,171][50205] Updated weights for policy 0, policy_version 4476 (0.0013) +[2026-07-22 19:40:13,452][50205] Updated weights for policy 0, policy_version 4486 (0.0011) +[2026-07-22 19:40:14,264][50205] Updated weights for policy 0, policy_version 4496 (0.0011) +[2026-07-22 19:40:14,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5393.1, 300 sec: 5408.1). Total num frames: 2301952. Throughput: 0: 5418.2. Samples: 2303488. Policy #0 lag: (min: 4.0, avg: 20.4, max: 42.0) +[2026-07-22 19:40:14,878][43431] Avg episode reward: [(0, '772.629')] +[2026-07-22 19:40:15,912][50205] Updated weights for policy 0, policy_version 4510 (0.0013) +[2026-07-22 19:40:16,699][50205] Updated weights for policy 0, policy_version 4520 (0.0014) +[2026-07-22 19:40:17,614][50205] Updated weights for policy 0, policy_version 4530 (0.0018) +[2026-07-22 19:40:18,421][50205] Updated weights for policy 0, policy_version 4540 (0.0013) +[2026-07-22 19:40:19,629][50205] Updated weights for policy 0, policy_version 4550 (0.0014) +[2026-07-22 19:40:19,877][43431] Fps is (10 sec: 5325.0, 60 sec: 5461.3, 300 sec: 5422.0). Total num frames: 2332672. Throughput: 0: 5376.5. Samples: 2335242. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 19:40:19,878][43431] Avg episode reward: [(0, '714.789')] +[2026-07-22 19:40:20,289][50205] Updated weights for policy 0, policy_version 4560 (0.0011) +[2026-07-22 19:40:21,221][50205] Updated weights for policy 0, policy_version 4570 (0.0011) +[2026-07-22 19:40:22,287][50205] Updated weights for policy 0, policy_version 4580 (0.0016) +[2026-07-22 19:40:23,088][50205] Updated weights for policy 0, policy_version 4590 (0.0011) +[2026-07-22 19:40:23,964][50205] Updated weights for policy 0, policy_version 4600 (0.0011) +[2026-07-22 19:40:24,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5427.2, 300 sec: 5422.0). Total num frames: 2359296. Throughput: 0: 5432.0. Samples: 2368782. Policy #0 lag: (min: 3.0, avg: 16.9, max: 35.0) +[2026-07-22 19:40:24,878][43431] Avg episode reward: [(0, '790.748')] +[2026-07-22 19:40:24,886][49527] Saving new best policy, reward=790.748! +[2026-07-22 19:40:25,026][50205] Updated weights for policy 0, policy_version 4610 (0.0022) +[2026-07-22 19:40:25,950][50205] Updated weights for policy 0, policy_version 4620 (0.0016) +[2026-07-22 19:40:26,727][50205] Updated weights for policy 0, policy_version 4630 (0.0026) +[2026-07-22 19:40:27,664][50205] Updated weights for policy 0, policy_version 4640 (0.0015) +[2026-07-22 19:40:28,675][50205] Updated weights for policy 0, policy_version 4650 (0.0017) +[2026-07-22 19:40:29,580][50205] Updated weights for policy 0, policy_version 4660 (0.0013) +[2026-07-22 19:40:29,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5393.1, 300 sec: 5428.9). Total num frames: 2385920. Throughput: 0: 5429.0. Samples: 2385448. Policy #0 lag: (min: 2.0, avg: 18.4, max: 37.0) +[2026-07-22 19:40:29,878][43431] Avg episode reward: [(0, '908.846')] +[2026-07-22 19:40:29,935][49527] Saving new best policy, reward=908.846! +[2026-07-22 19:40:30,780][50205] Updated weights for policy 0, policy_version 4670 (0.0011) +[2026-07-22 19:40:31,240][50205] Updated weights for policy 0, policy_version 4680 (0.0011) +[2026-07-22 19:40:32,458][50205] Updated weights for policy 0, policy_version 4690 (0.0017) +[2026-07-22 19:40:33,196][50205] Updated weights for policy 0, policy_version 4700 (0.0010) +[2026-07-22 19:40:34,243][50205] Updated weights for policy 0, policy_version 4710 (0.0011) +[2026-07-22 19:40:34,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5393.1, 300 sec: 5435.9). Total num frames: 2414592. Throughput: 0: 5471.8. Samples: 2418828. Policy #0 lag: (min: 0.0, avg: 17.1, max: 35.0) +[2026-07-22 19:40:34,878][43431] Avg episode reward: [(0, '835.308')] +[2026-07-22 19:40:34,893][50205] Updated weights for policy 0, policy_version 4720 (0.0024) +[2026-07-22 19:40:36,128][50205] Updated weights for policy 0, policy_version 4730 (0.0011) +[2026-07-22 19:40:36,826][50205] Updated weights for policy 0, policy_version 4740 (0.0012) +[2026-07-22 19:40:37,966][50205] Updated weights for policy 0, policy_version 4750 (0.0011) +[2026-07-22 19:40:38,658][50205] Updated weights for policy 0, policy_version 4760 (0.0011) +[2026-07-22 19:40:39,633][50205] Updated weights for policy 0, policy_version 4770 (0.0013) +[2026-07-22 19:40:39,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5461.3, 300 sec: 5435.9). Total num frames: 2443264. Throughput: 0: 5474.5. Samples: 2452156. Policy #0 lag: (min: 3.0, avg: 15.9, max: 35.0) +[2026-07-22 19:40:39,878][43431] Avg episode reward: [(0, '741.331')] +[2026-07-22 19:40:40,450][50205] Updated weights for policy 0, policy_version 4780 (0.0011) +[2026-07-22 19:40:41,641][50205] Updated weights for policy 0, policy_version 4790 (0.0011) +[2026-07-22 19:40:42,376][50205] Updated weights for policy 0, policy_version 4800 (0.0011) +[2026-07-22 19:40:43,584][50205] Updated weights for policy 0, policy_version 4810 (0.0011) +[2026-07-22 19:40:44,300][50205] Updated weights for policy 0, policy_version 4820 (0.0011) +[2026-07-22 19:40:44,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5529.6, 300 sec: 5442.8). Total num frames: 2469888. Throughput: 0: 5471.7. Samples: 2468812. Policy #0 lag: (min: 4.0, avg: 19.2, max: 38.0) +[2026-07-22 19:40:44,878][43431] Avg episode reward: [(0, '887.186')] +[2026-07-22 19:40:45,319][50205] Updated weights for policy 0, policy_version 4830 (0.0011) +[2026-07-22 19:40:46,004][50205] Updated weights for policy 0, policy_version 4840 (0.0011) +[2026-07-22 19:40:47,109][50205] Updated weights for policy 0, policy_version 4850 (0.0015) +[2026-07-22 19:40:47,936][50205] Updated weights for policy 0, policy_version 4860 (0.0012) +[2026-07-22 19:40:49,045][50205] Updated weights for policy 0, policy_version 4870 (0.0020) +[2026-07-22 19:40:49,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5461.3, 300 sec: 5442.8). Total num frames: 2496512. Throughput: 0: 5506.4. Samples: 2501828. Policy #0 lag: (min: 3.0, avg: 16.5, max: 35.0) +[2026-07-22 19:40:49,878][43431] Avg episode reward: [(0, '897.926')] +[2026-07-22 19:40:50,070][50205] Updated weights for policy 0, policy_version 4880 (0.0011) +[2026-07-22 19:40:51,100][50205] Updated weights for policy 0, policy_version 4890 (0.0011) +[2026-07-22 19:40:51,834][50205] Updated weights for policy 0, policy_version 4900 (0.0011) +[2026-07-22 19:40:53,036][50205] Updated weights for policy 0, policy_version 4910 (0.0012) +[2026-07-22 19:40:53,979][50205] Updated weights for policy 0, policy_version 4920 (0.0011) +[2026-07-22 19:40:54,878][43431] Fps is (10 sec: 5324.5, 60 sec: 5427.2, 300 sec: 5435.9). Total num frames: 2523136. Throughput: 0: 5454.7. Samples: 2533116. Policy #0 lag: (min: 3.0, avg: 19.1, max: 35.0) +[2026-07-22 19:40:54,878][43431] Avg episode reward: [(0, '864.356')] +[2026-07-22 19:40:54,913][50205] Updated weights for policy 0, policy_version 4930 (0.0016) +[2026-07-22 19:40:55,799][50205] Updated weights for policy 0, policy_version 4940 (0.0012) +[2026-07-22 19:40:56,872][50205] Updated weights for policy 0, policy_version 4950 (0.0013) +[2026-07-22 19:40:57,598][50205] Updated weights for policy 0, policy_version 4960 (0.0013) +[2026-07-22 19:40:58,735][50205] Updated weights for policy 0, policy_version 4970 (0.0017) +[2026-07-22 19:40:59,588][50205] Updated weights for policy 0, policy_version 4980 (0.0011) +[2026-07-22 19:40:59,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5461.3, 300 sec: 5442.8). Total num frames: 2551808. Throughput: 0: 5468.4. Samples: 2549568. Policy #0 lag: (min: 3.0, avg: 20.5, max: 39.0) +[2026-07-22 19:40:59,878][43431] Avg episode reward: [(0, '928.979')] +[2026-07-22 19:40:59,898][49527] Saving new best policy, reward=928.979! +[2026-07-22 19:41:00,477][50205] Updated weights for policy 0, policy_version 4990 (0.0023) +[2026-07-22 19:41:01,047][50205] Updated weights for policy 0, policy_version 5000 (0.0021) +[2026-07-22 19:41:02,557][50205] Updated weights for policy 0, policy_version 5010 (0.0015) +[2026-07-22 19:41:03,515][50205] Updated weights for policy 0, policy_version 5020 (0.0015) +[2026-07-22 19:41:04,153][50205] Updated weights for policy 0, policy_version 5030 (0.0010) +[2026-07-22 19:41:04,877][43431] Fps is (10 sec: 5529.8, 60 sec: 5461.3, 300 sec: 5435.9). Total num frames: 2578432. Throughput: 0: 5474.6. Samples: 2581598. Policy #0 lag: (min: 3.0, avg: 14.4, max: 31.0) +[2026-07-22 19:41:04,878][43431] Avg episode reward: [(0, '885.482')] +[2026-07-22 19:41:05,074][50205] Updated weights for policy 0, policy_version 5040 (0.0011) +[2026-07-22 19:41:06,444][50205] Updated weights for policy 0, policy_version 5050 (0.0012) +[2026-07-22 19:41:06,768][50205] Updated weights for policy 0, policy_version 5060 (0.0012) +[2026-07-22 19:41:07,943][50205] Updated weights for policy 0, policy_version 5070 (0.0014) +[2026-07-22 19:41:09,019][50205] Updated weights for policy 0, policy_version 5080 (0.0011) +[2026-07-22 19:41:09,708][50205] Updated weights for policy 0, policy_version 5090 (0.0016) +[2026-07-22 19:41:09,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5461.3, 300 sec: 5442.8). Total num frames: 2607104. Throughput: 0: 5470.9. Samples: 2614976. Policy #0 lag: (min: 3.0, avg: 19.3, max: 39.0) +[2026-07-22 19:41:09,878][43431] Avg episode reward: [(0, '738.090')] +[2026-07-22 19:41:10,814][50205] Updated weights for policy 0, policy_version 5100 (0.0010) +[2026-07-22 19:41:11,664][50205] Updated weights for policy 0, policy_version 5110 (0.0015) +[2026-07-22 19:41:12,406][50205] Updated weights for policy 0, policy_version 5120 (0.0015) +[2026-07-22 19:41:13,842][50205] Updated weights for policy 0, policy_version 5130 (0.0011) +[2026-07-22 19:41:14,336][50205] Updated weights for policy 0, policy_version 5140 (0.0010) +[2026-07-22 19:41:14,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5529.6, 300 sec: 5435.9). Total num frames: 2633728. Throughput: 0: 5474.1. Samples: 2631784. Policy #0 lag: (min: 1.0, avg: 15.4, max: 33.0) +[2026-07-22 19:41:14,878][43431] Avg episode reward: [(0, '971.623')] +[2026-07-22 19:41:14,910][49527] Saving new best policy, reward=971.623! +[2026-07-22 19:41:16,067][50205] Updated weights for policy 0, policy_version 5155 (0.0017) +[2026-07-22 19:41:17,483][50205] Updated weights for policy 0, policy_version 5165 (0.0017) +[2026-07-22 19:41:18,200][50205] Updated weights for policy 0, policy_version 5175 (0.0012) +[2026-07-22 19:41:19,039][50205] Updated weights for policy 0, policy_version 5185 (0.0015) +[2026-07-22 19:41:19,878][43431] Fps is (10 sec: 5120.0, 60 sec: 5427.2, 300 sec: 5422.0). Total num frames: 2658304. Throughput: 0: 5420.4. Samples: 2662748. Policy #0 lag: (min: 1.0, avg: 17.2, max: 37.0) +[2026-07-22 19:41:19,878][43431] Avg episode reward: [(0, '898.101')] +[2026-07-22 19:41:20,100][50205] Updated weights for policy 0, policy_version 5195 (0.0010) +[2026-07-22 19:41:21,080][50205] Updated weights for policy 0, policy_version 5205 (0.0014) +[2026-07-22 19:41:21,785][50205] Updated weights for policy 0, policy_version 5215 (0.0027) +[2026-07-22 19:41:23,070][50205] Updated weights for policy 0, policy_version 5225 (0.0014) +[2026-07-22 19:41:23,592][50205] Updated weights for policy 0, policy_version 5235 (0.0021) +[2026-07-22 19:41:24,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5427.2, 300 sec: 5435.9). Total num frames: 2684928. Throughput: 0: 5406.0. Samples: 2695426. Policy #0 lag: (min: 2.0, avg: 18.8, max: 36.0) +[2026-07-22 19:41:24,878][43431] Avg episode reward: [(0, '983.381')] +[2026-07-22 19:41:24,900][50205] Updated weights for policy 0, policy_version 5245 (0.0016) +[2026-07-22 19:41:24,966][49527] Saving new best policy, reward=983.381! +[2026-07-22 19:41:26,174][50205] Updated weights for policy 0, policy_version 5255 (0.0015) +[2026-07-22 19:41:26,716][50205] Updated weights for policy 0, policy_version 5265 (0.0026) +[2026-07-22 19:41:27,423][50205] Updated weights for policy 0, policy_version 5275 (0.0015) +[2026-07-22 19:41:29,325][50205] Updated weights for policy 0, policy_version 5285 (0.0020) +[2026-07-22 19:41:29,781][50205] Updated weights for policy 0, policy_version 5295 (0.0011) +[2026-07-22 19:41:29,877][43431] Fps is (10 sec: 5325.0, 60 sec: 5427.2, 300 sec: 5428.9). Total num frames: 2711552. Throughput: 0: 5370.1. Samples: 2710468. Policy #0 lag: (min: 2.0, avg: 19.3, max: 40.0) +[2026-07-22 19:41:29,878][43431] Avg episode reward: [(0, '859.623')] +[2026-07-22 19:41:30,292][50205] Updated weights for policy 0, policy_version 5305 (0.0012) +[2026-07-22 19:41:31,524][50205] Updated weights for policy 0, policy_version 5315 (0.0015) +[2026-07-22 19:41:32,676][50205] Updated weights for policy 0, policy_version 5325 (0.0016) +[2026-07-22 19:41:33,078][50205] Updated weights for policy 0, policy_version 5336 (0.0012) +[2026-07-22 19:41:34,524][50205] Updated weights for policy 0, policy_version 5346 (0.0011) +[2026-07-22 19:41:34,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5393.1, 300 sec: 5442.9). Total num frames: 2738176. Throughput: 0: 5366.3. Samples: 2743310. Policy #0 lag: (min: 3.0, avg: 18.4, max: 35.0) +[2026-07-22 19:41:34,878][43431] Avg episode reward: [(0, '1024.199')] +[2026-07-22 19:41:34,912][49527] Saving new best policy, reward=1024.199! +[2026-07-22 19:41:35,437][50205] Updated weights for policy 0, policy_version 5356 (0.0011) +[2026-07-22 19:41:36,600][50205] Updated weights for policy 0, policy_version 5371 (0.0013) +[2026-07-22 19:41:38,145][50205] Updated weights for policy 0, policy_version 5381 (0.0015) +[2026-07-22 19:41:38,737][50205] Updated weights for policy 0, policy_version 5391 (0.0011) +[2026-07-22 19:41:39,680][50205] Updated weights for policy 0, policy_version 5401 (0.0013) +[2026-07-22 19:41:39,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5393.1, 300 sec: 5449.8). Total num frames: 2766848. Throughput: 0: 5389.9. Samples: 2775658. Policy #0 lag: (min: 3.0, avg: 18.4, max: 35.0) +[2026-07-22 19:41:39,878][43431] Avg episode reward: [(0, '1105.412')] +[2026-07-22 19:41:39,906][49527] Saving new best policy, reward=1105.412! +[2026-07-22 19:41:40,775][50205] Updated weights for policy 0, policy_version 5411 (0.0014) +[2026-07-22 19:41:41,581][50205] Updated weights for policy 0, policy_version 5421 (0.0011) +[2026-07-22 19:41:42,269][50205] Updated weights for policy 0, policy_version 5431 (0.0013) +[2026-07-22 19:41:43,626][50205] Updated weights for policy 0, policy_version 5441 (0.0024) +[2026-07-22 19:41:44,264][50205] Updated weights for policy 0, policy_version 5451 (0.0016) +[2026-07-22 19:41:44,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5393.1, 300 sec: 5435.9). Total num frames: 2793472. Throughput: 0: 5399.4. Samples: 2792542. Policy #0 lag: (min: 0.0, avg: 20.1, max: 40.0) +[2026-07-22 19:41:44,878][43431] Avg episode reward: [(0, '1012.770')] +[2026-07-22 19:41:45,232][50205] Updated weights for policy 0, policy_version 5463 (0.0015) +[2026-07-22 19:41:46,560][50205] Updated weights for policy 0, policy_version 5473 (0.0013) +[2026-07-22 19:41:47,153][50205] Updated weights for policy 0, policy_version 5483 (0.0011) +[2026-07-22 19:41:48,007][50205] Updated weights for policy 0, policy_version 5493 (0.0014) +[2026-07-22 19:41:48,961][50205] Updated weights for policy 0, policy_version 5503 (0.0011) +[2026-07-22 19:41:49,877][43431] Fps is (10 sec: 5529.4, 60 sec: 5427.2, 300 sec: 5435.9). Total num frames: 2822144. Throughput: 0: 5429.0. Samples: 2825906. Policy #0 lag: (min: 3.0, avg: 21.0, max: 38.0) +[2026-07-22 19:41:49,878][43431] Avg episode reward: [(0, '869.705')] +[2026-07-22 19:41:50,080][50205] Updated weights for policy 0, policy_version 5513 (0.0018) +[2026-07-22 19:41:50,726][50205] Updated weights for policy 0, policy_version 5523 (0.0017) +[2026-07-22 19:41:51,863][50205] Updated weights for policy 0, policy_version 5533 (0.0013) +[2026-07-22 19:41:52,588][50205] Updated weights for policy 0, policy_version 5543 (0.0016) +[2026-07-22 19:41:53,735][50205] Updated weights for policy 0, policy_version 5554 (0.0011) +[2026-07-22 19:41:54,609][50205] Updated weights for policy 0, policy_version 5564 (0.0016) +[2026-07-22 19:41:54,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5427.2, 300 sec: 5442.8). Total num frames: 2848768. Throughput: 0: 5427.1. Samples: 2859192. Policy #0 lag: (min: 3.0, avg: 21.1, max: 43.0) +[2026-07-22 19:41:54,878][43431] Avg episode reward: [(0, '1048.735')] +[2026-07-22 19:41:55,536][50205] Updated weights for policy 0, policy_version 5574 (0.0019) +[2026-07-22 19:41:56,018][50205] Updated weights for policy 0, policy_version 5584 (0.0022) +[2026-07-22 19:41:57,483][50205] Updated weights for policy 0, policy_version 5594 (0.0023) +[2026-07-22 19:41:58,472][50205] Updated weights for policy 0, policy_version 5604 (0.0011) +[2026-07-22 19:41:59,011][50205] Updated weights for policy 0, policy_version 5614 (0.0015) +[2026-07-22 19:41:59,841][50205] Updated weights for policy 0, policy_version 5624 (0.0011) +[2026-07-22 19:41:59,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5461.3, 300 sec: 5456.7). Total num frames: 2879488. Throughput: 0: 5426.0. Samples: 2875954. Policy #0 lag: (min: 3.0, avg: 19.7, max: 35.0) +[2026-07-22 19:41:59,878][43431] Avg episode reward: [(0, '1030.114')] +[2026-07-22 19:42:01,444][50205] Updated weights for policy 0, policy_version 5634 (0.0010) +[2026-07-22 19:42:02,515][50205] Updated weights for policy 0, policy_version 5645 (0.0010) +[2026-07-22 19:42:03,380][50205] Updated weights for policy 0, policy_version 5655 (0.0011) +[2026-07-22 19:42:04,848][50205] Updated weights for policy 0, policy_version 5665 (0.0010) +[2026-07-22 19:42:04,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5358.9, 300 sec: 5428.9). Total num frames: 2899968. Throughput: 0: 5401.4. Samples: 2905810. Policy #0 lag: (min: 3.0, avg: 20.6, max: 35.0) +[2026-07-22 19:42:04,878][43431] Avg episode reward: [(0, '1096.155')] +[2026-07-22 19:42:05,520][50205] Updated weights for policy 0, policy_version 5675 (0.0017) +[2026-07-22 19:42:06,634][50205] Updated weights for policy 0, policy_version 5685 (0.0011) +[2026-07-22 19:42:07,422][50205] Updated weights for policy 0, policy_version 5695 (0.0011) +[2026-07-22 19:42:08,383][50205] Updated weights for policy 0, policy_version 5705 (0.0011) +[2026-07-22 19:42:09,287][50205] Updated weights for policy 0, policy_version 5715 (0.0011) +[2026-07-22 19:42:09,877][43431] Fps is (10 sec: 4915.3, 60 sec: 5358.9, 300 sec: 5435.9). Total num frames: 2928640. Throughput: 0: 5407.1. Samples: 2938746. Policy #0 lag: (min: 3.0, avg: 17.3, max: 35.0) +[2026-07-22 19:42:09,878][43431] Avg episode reward: [(0, '1041.047')] +[2026-07-22 19:42:10,268][50205] Updated weights for policy 0, policy_version 5725 (0.0014) +[2026-07-22 19:42:10,858][50205] Updated weights for policy 0, policy_version 5735 (0.0016) +[2026-07-22 19:42:12,228][50205] Updated weights for policy 0, policy_version 5745 (0.0014) +[2026-07-22 19:42:12,987][50205] Updated weights for policy 0, policy_version 5755 (0.0018) +[2026-07-22 19:42:13,887][50205] Updated weights for policy 0, policy_version 5765 (0.0011) +[2026-07-22 19:42:14,680][50205] Updated weights for policy 0, policy_version 5775 (0.0011) +[2026-07-22 19:42:14,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5393.1, 300 sec: 5442.8). Total num frames: 2957312. Throughput: 0: 5445.0. Samples: 2955494. Policy #0 lag: (min: 1.0, avg: 17.2, max: 33.0) +[2026-07-22 19:42:14,878][43431] Avg episode reward: [(0, '1074.732')] +[2026-07-22 19:42:15,869][50205] Updated weights for policy 0, policy_version 5785 (0.0010) +[2026-07-22 19:42:16,506][50205] Updated weights for policy 0, policy_version 5795 (0.0015) +[2026-07-22 19:42:17,861][50205] Updated weights for policy 0, policy_version 5807 (0.0011) +[2026-07-22 19:42:18,844][50205] Updated weights for policy 0, policy_version 5817 (0.0015) +[2026-07-22 19:42:19,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5393.1, 300 sec: 5428.9). Total num frames: 2981888. Throughput: 0: 5430.4. Samples: 2987680. Policy #0 lag: (min: 1.0, avg: 17.2, max: 33.0) +[2026-07-22 19:42:19,878][43431] Avg episode reward: [(0, '944.051')] +[2026-07-22 19:42:19,920][50205] Updated weights for policy 0, policy_version 5827 (0.0010) +[2026-07-22 19:42:20,858][50205] Updated weights for policy 0, policy_version 5837 (0.0016) +[2026-07-22 19:42:21,351][50205] Updated weights for policy 0, policy_version 5847 (0.0011) +[2026-07-22 19:42:22,661][50205] Updated weights for policy 0, policy_version 5857 (0.0011) +[2026-07-22 19:42:23,476][50205] Updated weights for policy 0, policy_version 5867 (0.0011) +[2026-07-22 19:42:24,427][50205] Updated weights for policy 0, policy_version 5877 (0.0011) +[2026-07-22 19:42:24,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5427.2, 300 sec: 5435.9). Total num frames: 3010560. Throughput: 0: 5458.2. Samples: 3021278. Policy #0 lag: (min: 3.0, avg: 17.6, max: 39.0) +[2026-07-22 19:42:24,878][43431] Avg episode reward: [(0, '1109.559')] +[2026-07-22 19:42:24,939][49527] Saving new best policy, reward=1109.559! +[2026-07-22 19:42:25,200][50205] Updated weights for policy 0, policy_version 5887 (0.0011) +[2026-07-22 19:42:26,175][50205] Updated weights for policy 0, policy_version 5897 (0.0014) +[2026-07-22 19:42:27,115][50205] Updated weights for policy 0, policy_version 5907 (0.0019) +[2026-07-22 19:42:28,129][50205] Updated weights for policy 0, policy_version 5917 (0.0016) +[2026-07-22 19:42:28,852][50205] Updated weights for policy 0, policy_version 5927 (0.0012) +[2026-07-22 19:42:29,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5461.3, 300 sec: 5442.8). Total num frames: 3039232. Throughput: 0: 5455.0. Samples: 3038018. Policy #0 lag: (min: 3.0, avg: 20.2, max: 39.0) +[2026-07-22 19:42:29,878][43431] Avg episode reward: [(0, '1199.872')] +[2026-07-22 19:42:30,049][50205] Updated weights for policy 0, policy_version 5937 (0.0016) +[2026-07-22 19:42:30,167][49527] Saving new best policy, reward=1199.872! +[2026-07-22 19:42:30,715][50205] Updated weights for policy 0, policy_version 5947 (0.0012) +[2026-07-22 19:42:31,732][50205] Updated weights for policy 0, policy_version 5957 (0.0011) +[2026-07-22 19:42:32,389][50205] Updated weights for policy 0, policy_version 5967 (0.0012) +[2026-07-22 19:42:33,647][50205] Updated weights for policy 0, policy_version 5977 (0.0013) +[2026-07-22 19:42:34,468][50205] Updated weights for policy 0, policy_version 5987 (0.0011) +[2026-07-22 19:42:34,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5495.5, 300 sec: 5442.8). Total num frames: 3067904. Throughput: 0: 5456.2. Samples: 3071434. Policy #0 lag: (min: 2.0, avg: 19.1, max: 38.0) +[2026-07-22 19:42:34,878][43431] Avg episode reward: [(0, '888.020')] +[2026-07-22 19:42:35,580][50205] Updated weights for policy 0, policy_version 5997 (0.0016) +[2026-07-22 19:42:36,168][50205] Updated weights for policy 0, policy_version 6007 (0.0018) +[2026-07-22 19:42:37,427][50205] Updated weights for policy 0, policy_version 6017 (0.0011) +[2026-07-22 19:42:38,055][50205] Updated weights for policy 0, policy_version 6027 (0.0011) +[2026-07-22 19:42:39,508][50205] Updated weights for policy 0, policy_version 6037 (0.0016) +[2026-07-22 19:42:39,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5427.2, 300 sec: 5449.8). Total num frames: 3092480. Throughput: 0: 5404.8. Samples: 3102408. Policy #0 lag: (min: 3.0, avg: 17.5, max: 35.0) +[2026-07-22 19:42:39,878][43431] Avg episode reward: [(0, '1080.869')] +[2026-07-22 19:42:39,905][49527] Saving results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/checkpoint_p0/checkpoint_000006040_3092480.pth... +[2026-07-22 19:42:40,676][50205] Updated weights for policy 0, policy_version 6047 (0.0011) +[2026-07-22 19:42:41,528][50205] Updated weights for policy 0, policy_version 6057 (0.0020) +[2026-07-22 19:42:42,639][50205] Updated weights for policy 0, policy_version 6067 (0.0016) +[2026-07-22 19:42:43,920][50205] Updated weights for policy 0, policy_version 6077 (0.0011) +[2026-07-22 19:42:44,262][50205] Updated weights for policy 0, policy_version 6087 (0.0011) +[2026-07-22 19:42:44,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5427.2, 300 sec: 5449.8). Total num frames: 3119104. Throughput: 0: 5360.6. Samples: 3117180. Policy #0 lag: (min: 3.0, avg: 21.9, max: 39.0) +[2026-07-22 19:42:44,878][43431] Avg episode reward: [(0, '976.145')] +[2026-07-22 19:42:45,694][50205] Updated weights for policy 0, policy_version 6099 (0.0010) +[2026-07-22 19:42:46,744][50205] Updated weights for policy 0, policy_version 6109 (0.0011) +[2026-07-22 19:42:47,329][50205] Updated weights for policy 0, policy_version 6119 (0.0020) +[2026-07-22 19:42:48,613][50205] Updated weights for policy 0, policy_version 6129 (0.0011) +[2026-07-22 19:42:49,348][50205] Updated weights for policy 0, policy_version 6139 (0.0012) +[2026-07-22 19:42:49,878][43431] Fps is (10 sec: 5324.4, 60 sec: 5393.0, 300 sec: 5435.9). Total num frames: 3145728. Throughput: 0: 5431.1. Samples: 3150214. Policy #0 lag: (min: 3.0, avg: 19.5, max: 39.0) +[2026-07-22 19:42:49,879][43431] Avg episode reward: [(0, '1156.835')] +[2026-07-22 19:42:50,159][50205] Updated weights for policy 0, policy_version 6149 (0.0016) +[2026-07-22 19:42:50,895][50205] Updated weights for policy 0, policy_version 6159 (0.0017) +[2026-07-22 19:42:52,237][50205] Updated weights for policy 0, policy_version 6169 (0.0010) +[2026-07-22 19:42:52,928][50205] Updated weights for policy 0, policy_version 6179 (0.0013) +[2026-07-22 19:42:53,845][50205] Updated weights for policy 0, policy_version 6189 (0.0015) +[2026-07-22 19:42:54,767][50205] Updated weights for policy 0, policy_version 6199 (0.0016) +[2026-07-22 19:42:54,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5427.2, 300 sec: 5442.8). Total num frames: 3174400. Throughput: 0: 5442.3. Samples: 3183648. Policy #0 lag: (min: 3.0, avg: 18.3, max: 35.0) +[2026-07-22 19:42:54,878][43431] Avg episode reward: [(0, '1026.688')] +[2026-07-22 19:42:55,716][50205] Updated weights for policy 0, policy_version 6209 (0.0011) +[2026-07-22 19:42:56,538][50205] Updated weights for policy 0, policy_version 6219 (0.0011) +[2026-07-22 19:42:57,611][50205] Updated weights for policy 0, policy_version 6231 (0.0017) +[2026-07-22 19:42:58,608][50205] Updated weights for policy 0, policy_version 6241 (0.0020) +[2026-07-22 19:42:59,344][50205] Updated weights for policy 0, policy_version 6251 (0.0011) +[2026-07-22 19:42:59,877][43431] Fps is (10 sec: 5734.8, 60 sec: 5393.1, 300 sec: 5449.8). Total num frames: 3203072. Throughput: 0: 5440.0. Samples: 3200294. Policy #0 lag: (min: 3.0, avg: 18.3, max: 35.0) +[2026-07-22 19:42:59,878][43431] Avg episode reward: [(0, '1101.566')] +[2026-07-22 19:43:00,670][50205] Updated weights for policy 0, policy_version 6261 (0.0020) +[2026-07-22 19:43:01,291][50205] Updated weights for policy 0, policy_version 6271 (0.0011) +[2026-07-22 19:43:02,202][50205] Updated weights for policy 0, policy_version 6281 (0.0015) +[2026-07-22 19:43:03,653][50205] Updated weights for policy 0, policy_version 6291 (0.0011) +[2026-07-22 19:43:04,669][50205] Updated weights for policy 0, policy_version 6301 (0.0012) +[2026-07-22 19:43:04,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5461.3, 300 sec: 5442.8). Total num frames: 3227648. Throughput: 0: 5416.9. Samples: 3231440. Policy #0 lag: (min: 3.0, avg: 17.8, max: 39.0) +[2026-07-22 19:43:04,878][43431] Avg episode reward: [(0, '1360.283')] +[2026-07-22 19:43:04,890][49527] Saving new best policy, reward=1360.283! +[2026-07-22 19:43:05,396][50205] Updated weights for policy 0, policy_version 6311 (0.0011) +[2026-07-22 19:43:06,611][50205] Updated weights for policy 0, policy_version 6321 (0.0011) +[2026-07-22 19:43:07,422][50205] Updated weights for policy 0, policy_version 6331 (0.0016) +[2026-07-22 19:43:08,329][50205] Updated weights for policy 0, policy_version 6341 (0.0011) +[2026-07-22 19:43:09,091][50205] Updated weights for policy 0, policy_version 6351 (0.0011) +[2026-07-22 19:43:09,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5427.2, 300 sec: 5442.8). Total num frames: 3254272. Throughput: 0: 5414.4. Samples: 3264926. Policy #0 lag: (min: 1.0, avg: 16.6, max: 33.0) +[2026-07-22 19:43:09,878][43431] Avg episode reward: [(0, '1153.599')] +[2026-07-22 19:43:10,118][50205] Updated weights for policy 0, policy_version 6361 (0.0011) +[2026-07-22 19:43:10,965][50205] Updated weights for policy 0, policy_version 6371 (0.0019) +[2026-07-22 19:43:12,039][50205] Updated weights for policy 0, policy_version 6381 (0.0015) +[2026-07-22 19:43:12,930][50205] Updated weights for policy 0, policy_version 6391 (0.0015) +[2026-07-22 19:43:13,619][50205] Updated weights for policy 0, policy_version 6401 (0.0012) +[2026-07-22 19:43:14,878][43431] Fps is (10 sec: 5324.8, 60 sec: 5393.0, 300 sec: 5442.8). Total num frames: 3280896. Throughput: 0: 5418.1. Samples: 3281832. Policy #0 lag: (min: 1.0, avg: 16.5, max: 41.0) +[2026-07-22 19:43:14,878][43431] Avg episode reward: [(0, '1214.929')] +[2026-07-22 19:43:14,971][50205] Updated weights for policy 0, policy_version 6411 (0.0019) +[2026-07-22 19:43:15,826][50205] Updated weights for policy 0, policy_version 6421 (0.0011) +[2026-07-22 19:43:16,157][49527] Signal inference workers to stop experience collection... (100 times) +[2026-07-22 19:43:16,174][50205] InferenceWorker_p0-w0: stopping experience collection (100 times) +[2026-07-22 19:43:16,204][49527] Signal inference workers to resume experience collection... (100 times) +[2026-07-22 19:43:16,205][50205] InferenceWorker_p0-w0: resuming experience collection (100 times) +[2026-07-22 19:43:17,384][50205] Updated weights for policy 0, policy_version 6433 (0.0012) +[2026-07-22 19:43:18,366][50205] Updated weights for policy 0, policy_version 6443 (0.0011) +[2026-07-22 19:43:19,289][50205] Updated weights for policy 0, policy_version 6453 (0.0012) +[2026-07-22 19:43:19,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5427.2, 300 sec: 5435.9). Total num frames: 3307520. Throughput: 0: 5321.5. Samples: 3310902. Policy #0 lag: (min: 2.0, avg: 17.6, max: 38.0) +[2026-07-22 19:43:19,878][43431] Avg episode reward: [(0, '1211.302')] +[2026-07-22 19:43:20,134][50205] Updated weights for policy 0, policy_version 6463 (0.0012) +[2026-07-22 19:43:21,097][50205] Updated weights for policy 0, policy_version 6473 (0.0015) +[2026-07-22 19:43:22,066][50205] Updated weights for policy 0, policy_version 6483 (0.0011) +[2026-07-22 19:43:23,128][50205] Updated weights for policy 0, policy_version 6493 (0.0011) +[2026-07-22 19:43:23,882][50205] Updated weights for policy 0, policy_version 6503 (0.0011) +[2026-07-22 19:43:24,868][50205] Updated weights for policy 0, policy_version 6513 (0.0015) +[2026-07-22 19:43:24,877][43431] Fps is (10 sec: 5325.0, 60 sec: 5393.1, 300 sec: 5435.9). Total num frames: 3334144. Throughput: 0: 5378.0. Samples: 3344416. Policy #0 lag: (min: 1.0, avg: 16.7, max: 37.0) +[2026-07-22 19:43:24,878][43431] Avg episode reward: [(0, '1242.467')] +[2026-07-22 19:43:25,311][50205] Updated weights for policy 0, policy_version 6523 (0.0015) +[2026-07-22 19:43:26,636][50205] Updated weights for policy 0, policy_version 6533 (0.0012) +[2026-07-22 19:43:27,688][50205] Updated weights for policy 0, policy_version 6543 (0.0016) +[2026-07-22 19:43:28,181][50205] Updated weights for policy 0, policy_version 6553 (0.0012) +[2026-07-22 19:43:29,224][50205] Updated weights for policy 0, policy_version 6563 (0.0012) +[2026-07-22 19:43:29,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5393.1, 300 sec: 5435.9). Total num frames: 3362816. Throughput: 0: 5424.6. Samples: 3361286. Policy #0 lag: (min: 1.0, avg: 16.7, max: 37.0) +[2026-07-22 19:43:29,878][43431] Avg episode reward: [(0, '1237.033')] +[2026-07-22 19:43:30,513][50205] Updated weights for policy 0, policy_version 6573 (0.0011) +[2026-07-22 19:43:30,934][50205] Updated weights for policy 0, policy_version 6583 (0.0012) +[2026-07-22 19:43:32,090][50205] Updated weights for policy 0, policy_version 6593 (0.0012) +[2026-07-22 19:43:33,261][50205] Updated weights for policy 0, policy_version 6603 (0.0018) +[2026-07-22 19:43:34,665][50205] Updated weights for policy 0, policy_version 6617 (0.0012) +[2026-07-22 19:43:34,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5358.9, 300 sec: 5435.9). Total num frames: 3389440. Throughput: 0: 5409.6. Samples: 3393642. Policy #0 lag: (min: 5.0, avg: 16.9, max: 37.0) +[2026-07-22 19:43:34,878][43431] Avg episode reward: [(0, '1295.804')] +[2026-07-22 19:43:35,383][50205] Updated weights for policy 0, policy_version 6627 (0.0015) +[2026-07-22 19:43:36,590][50205] Updated weights for policy 0, policy_version 6637 (0.0015) +[2026-07-22 19:43:36,931][50205] Updated weights for policy 0, policy_version 6647 (0.0011) +[2026-07-22 19:43:38,310][50205] Updated weights for policy 0, policy_version 6657 (0.0015) +[2026-07-22 19:43:38,994][50205] Updated weights for policy 0, policy_version 6667 (0.0014) +[2026-07-22 19:43:39,674][50205] Updated weights for policy 0, policy_version 6677 (0.0019) +[2026-07-22 19:43:39,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5461.3, 300 sec: 5442.8). Total num frames: 3420160. Throughput: 0: 5409.6. Samples: 3427078. Policy #0 lag: (min: 3.0, avg: 16.3, max: 36.0) +[2026-07-22 19:43:39,878][43431] Avg episode reward: [(0, '1237.087')] +[2026-07-22 19:43:40,926][50205] Updated weights for policy 0, policy_version 6687 (0.0011) +[2026-07-22 19:43:41,962][50205] Updated weights for policy 0, policy_version 6697 (0.0016) +[2026-07-22 19:43:42,465][50205] Updated weights for policy 0, policy_version 6707 (0.0013) +[2026-07-22 19:43:43,763][50205] Updated weights for policy 0, policy_version 6717 (0.0011) +[2026-07-22 19:43:44,878][43431] Fps is (10 sec: 5324.7, 60 sec: 5393.0, 300 sec: 5422.0). Total num frames: 3442688. Throughput: 0: 5413.8. Samples: 3443918. Policy #0 lag: (min: 3.0, avg: 24.2, max: 43.0) +[2026-07-22 19:43:44,878][43431] Avg episode reward: [(0, '1308.757')] +[2026-07-22 19:43:45,202][50205] Updated weights for policy 0, policy_version 6732 (0.0011) +[2026-07-22 19:43:45,959][50205] Updated weights for policy 0, policy_version 6742 (0.0011) +[2026-07-22 19:43:46,638][50205] Updated weights for policy 0, policy_version 6752 (0.0010) +[2026-07-22 19:43:47,970][50205] Updated weights for policy 0, policy_version 6762 (0.0012) +[2026-07-22 19:43:48,369][50205] Updated weights for policy 0, policy_version 6772 (0.0011) +[2026-07-22 19:43:49,673][50205] Updated weights for policy 0, policy_version 6782 (0.0011) +[2026-07-22 19:43:49,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5461.4, 300 sec: 5428.9). Total num frames: 3473408. Throughput: 0: 5462.4. Samples: 3477246. Policy #0 lag: (min: 3.0, avg: 17.4, max: 35.0) +[2026-07-22 19:43:49,878][43431] Avg episode reward: [(0, '1268.682')] +[2026-07-22 19:43:50,617][50205] Updated weights for policy 0, policy_version 6792 (0.0011) +[2026-07-22 19:43:51,322][50205] Updated weights for policy 0, policy_version 6802 (0.0015) +[2026-07-22 19:43:52,491][50205] Updated weights for policy 0, policy_version 6812 (0.0013) +[2026-07-22 19:43:53,496][50205] Updated weights for policy 0, policy_version 6822 (0.0014) +[2026-07-22 19:43:54,072][50205] Updated weights for policy 0, policy_version 6832 (0.0012) +[2026-07-22 19:43:54,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5427.2, 300 sec: 5435.9). Total num frames: 3500032. Throughput: 0: 5427.3. Samples: 3509156. Policy #0 lag: (min: 3.0, avg: 17.4, max: 35.0) +[2026-07-22 19:43:54,878][43431] Avg episode reward: [(0, '1258.120')] +[2026-07-22 19:43:55,576][50205] Updated weights for policy 0, policy_version 6842 (0.0010) +[2026-07-22 19:43:56,512][50205] Updated weights for policy 0, policy_version 6852 (0.0015) +[2026-07-22 19:43:57,140][50205] Updated weights for policy 0, policy_version 6862 (0.0012) +[2026-07-22 19:43:58,138][50205] Updated weights for policy 0, policy_version 6872 (0.0011) +[2026-07-22 19:43:59,628][50205] Updated weights for policy 0, policy_version 6882 (0.0016) +[2026-07-22 19:43:59,878][43431] Fps is (10 sec: 5324.1, 60 sec: 5393.0, 300 sec: 5442.8). Total num frames: 3526656. Throughput: 0: 5404.4. Samples: 3525034. Policy #0 lag: (min: 3.0, avg: 16.4, max: 35.0) +[2026-07-22 19:43:59,879][43431] Avg episode reward: [(0, '1410.801')] +[2026-07-22 19:43:59,985][49527] Saving new best policy, reward=1410.801! +[2026-07-22 19:44:00,091][50205] Updated weights for policy 0, policy_version 6893 (0.0014) +[2026-07-22 19:44:01,008][50205] Updated weights for policy 0, policy_version 6903 (0.0017) +[2026-07-22 19:44:02,722][50205] Updated weights for policy 0, policy_version 6913 (0.0016) +[2026-07-22 19:44:03,056][50205] Updated weights for policy 0, policy_version 6923 (0.0016) +[2026-07-22 19:44:04,308][50205] Updated weights for policy 0, policy_version 6933 (0.0012) +[2026-07-22 19:44:04,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5427.2, 300 sec: 5435.9). Total num frames: 3553280. Throughput: 0: 5473.7. Samples: 3557218. Policy #0 lag: (min: 2.0, avg: 21.4, max: 41.0) +[2026-07-22 19:44:04,878][43431] Avg episode reward: [(0, '1437.458')] +[2026-07-22 19:44:04,920][49527] Saving new best policy, reward=1437.458! +[2026-07-22 19:44:05,124][50205] Updated weights for policy 0, policy_version 6943 (0.0011) +[2026-07-22 19:44:06,095][50205] Updated weights for policy 0, policy_version 6955 (0.0018) +[2026-07-22 19:44:07,250][50205] Updated weights for policy 0, policy_version 6965 (0.0018) +[2026-07-22 19:44:08,112][50205] Updated weights for policy 0, policy_version 6975 (0.0012) +[2026-07-22 19:44:08,974][50205] Updated weights for policy 0, policy_version 6985 (0.0014) +[2026-07-22 19:44:09,838][50205] Updated weights for policy 0, policy_version 6995 (0.0011) +[2026-07-22 19:44:09,877][43431] Fps is (10 sec: 5530.3, 60 sec: 5461.3, 300 sec: 5435.9). Total num frames: 3581952. Throughput: 0: 5473.2. Samples: 3590710. Policy #0 lag: (min: 4.0, avg: 16.7, max: 32.0) +[2026-07-22 19:44:09,878][43431] Avg episode reward: [(0, '1347.837')] +[2026-07-22 19:44:11,118][50205] Updated weights for policy 0, policy_version 7005 (0.0011) +[2026-07-22 19:44:11,508][50205] Updated weights for policy 0, policy_version 7015 (0.0016) +[2026-07-22 19:44:12,614][50205] Updated weights for policy 0, policy_version 7025 (0.0014) +[2026-07-22 19:44:13,526][50205] Updated weights for policy 0, policy_version 7035 (0.0011) +[2026-07-22 19:44:14,456][50205] Updated weights for policy 0, policy_version 7045 (0.0012) +[2026-07-22 19:44:14,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5461.4, 300 sec: 5435.9). Total num frames: 3608576. Throughput: 0: 5471.8. Samples: 3607516. Policy #0 lag: (min: 3.0, avg: 16.6, max: 36.0) +[2026-07-22 19:44:14,878][43431] Avg episode reward: [(0, '1472.743')] +[2026-07-22 19:44:15,257][49527] Saving new best policy, reward=1472.743! +[2026-07-22 19:44:15,409][50205] Updated weights for policy 0, policy_version 7055 (0.0011) +[2026-07-22 19:44:16,289][50205] Updated weights for policy 0, policy_version 7065 (0.0012) +[2026-07-22 19:44:17,149][50205] Updated weights for policy 0, policy_version 7076 (0.0012) +[2026-07-22 19:44:18,380][50205] Updated weights for policy 0, policy_version 7086 (0.0012) +[2026-07-22 19:44:18,923][50205] Updated weights for policy 0, policy_version 7096 (0.0015) +[2026-07-22 19:44:19,873][50205] Updated weights for policy 0, policy_version 7106 (0.0016) +[2026-07-22 19:44:19,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5435.9). Total num frames: 3637248. Throughput: 0: 5499.9. Samples: 3641136. Policy #0 lag: (min: 3.0, avg: 16.6, max: 36.0) +[2026-07-22 19:44:19,879][43431] Avg episode reward: [(0, '1425.622')] +[2026-07-22 19:44:20,950][50205] Updated weights for policy 0, policy_version 7116 (0.0012) +[2026-07-22 19:44:21,812][50205] Updated weights for policy 0, policy_version 7126 (0.0015) +[2026-07-22 19:44:22,656][50205] Updated weights for policy 0, policy_version 7136 (0.0011) +[2026-07-22 19:44:23,647][50205] Updated weights for policy 0, policy_version 7146 (0.0013) +[2026-07-22 19:44:24,405][50205] Updated weights for policy 0, policy_version 7156 (0.0016) +[2026-07-22 19:44:24,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5495.4, 300 sec: 5428.9). Total num frames: 3663872. Throughput: 0: 5504.3. Samples: 3674774. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 19:44:24,878][43431] Avg episode reward: [(0, '1326.507')] +[2026-07-22 19:44:25,550][50205] Updated weights for policy 0, policy_version 7166 (0.0011) +[2026-07-22 19:44:26,345][50205] Updated weights for policy 0, policy_version 7176 (0.0012) +[2026-07-22 19:44:27,150][50205] Updated weights for policy 0, policy_version 7186 (0.0022) +[2026-07-22 19:44:28,291][50205] Updated weights for policy 0, policy_version 7196 (0.0011) +[2026-07-22 19:44:29,220][50205] Updated weights for policy 0, policy_version 7206 (0.0011) +[2026-07-22 19:44:29,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5495.5, 300 sec: 5428.9). Total num frames: 3692544. Throughput: 0: 5503.2. Samples: 3691558. Policy #0 lag: (min: 0.0, avg: 18.1, max: 36.0) +[2026-07-22 19:44:29,878][43431] Avg episode reward: [(0, '1356.416')] +[2026-07-22 19:44:29,951][50205] Updated weights for policy 0, policy_version 7216 (0.0018) +[2026-07-22 19:44:31,168][50205] Updated weights for policy 0, policy_version 7226 (0.0010) +[2026-07-22 19:44:32,056][50205] Updated weights for policy 0, policy_version 7236 (0.0014) +[2026-07-22 19:44:33,085][50205] Updated weights for policy 0, policy_version 7246 (0.0012) +[2026-07-22 19:44:34,220][50205] Updated weights for policy 0, policy_version 7256 (0.0011) +[2026-07-22 19:44:34,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5495.5, 300 sec: 5435.9). Total num frames: 3719168. Throughput: 0: 5453.9. Samples: 3722672. Policy #0 lag: (min: 0.0, avg: 17.7, max: 34.0) +[2026-07-22 19:44:34,878][43431] Avg episode reward: [(0, '1222.671')] +[2026-07-22 19:44:35,119][50205] Updated weights for policy 0, policy_version 7266 (0.0018) +[2026-07-22 19:44:35,874][50205] Updated weights for policy 0, policy_version 7276 (0.0013) +[2026-07-22 19:44:37,033][50205] Updated weights for policy 0, policy_version 7286 (0.0011) +[2026-07-22 19:44:37,669][50205] Updated weights for policy 0, policy_version 7296 (0.0015) +[2026-07-22 19:44:38,788][50205] Updated weights for policy 0, policy_version 7306 (0.0011) +[2026-07-22 19:44:39,577][50205] Updated weights for policy 0, policy_version 7316 (0.0014) +[2026-07-22 19:44:39,881][43431] Fps is (10 sec: 5322.9, 60 sec: 5426.9, 300 sec: 5449.7). Total num frames: 3745792. Throughput: 0: 5489.5. Samples: 3756204. Policy #0 lag: (min: 0.0, avg: 17.7, max: 34.0) +[2026-07-22 19:44:39,881][43431] Avg episode reward: [(0, '1360.763')] +[2026-07-22 19:44:40,772][50205] Updated weights for policy 0, policy_version 7326 (0.0013) +[2026-07-22 19:44:41,259][50205] Updated weights for policy 0, policy_version 7336 (0.0016) +[2026-07-22 19:44:42,649][50205] Updated weights for policy 0, policy_version 7346 (0.0019) +[2026-07-22 19:44:43,420][50205] Updated weights for policy 0, policy_version 7356 (0.0010) +[2026-07-22 19:44:44,231][50205] Updated weights for policy 0, policy_version 7366 (0.0021) +[2026-07-22 19:44:44,815][50205] Updated weights for policy 0, policy_version 7376 (0.0017) +[2026-07-22 19:44:44,879][43431] Fps is (10 sec: 5733.2, 60 sec: 5563.6, 300 sec: 5449.7). Total num frames: 3776512. Throughput: 0: 5509.9. Samples: 3772986. Policy #0 lag: (min: 1.0, avg: 18.1, max: 33.0) +[2026-07-22 19:44:44,880][43431] Avg episode reward: [(0, '1480.144')] +[2026-07-22 19:44:44,904][49527] Saving new best policy, reward=1480.144! +[2026-07-22 19:44:46,240][50205] Updated weights for policy 0, policy_version 7386 (0.0010) +[2026-07-22 19:44:46,798][50205] Updated weights for policy 0, policy_version 7396 (0.0011) +[2026-07-22 19:44:47,951][50205] Updated weights for policy 0, policy_version 7406 (0.0015) +[2026-07-22 19:44:48,724][50205] Updated weights for policy 0, policy_version 7416 (0.0011) +[2026-07-22 19:44:49,764][50205] Updated weights for policy 0, policy_version 7426 (0.0016) +[2026-07-22 19:44:49,890][43431] Fps is (10 sec: 5729.1, 60 sec: 5494.3, 300 sec: 5442.6). Total num frames: 3803136. Throughput: 0: 5540.0. Samples: 3806588. Policy #0 lag: (min: 0.0, avg: 18.1, max: 32.0) +[2026-07-22 19:44:49,891][43431] Avg episode reward: [(0, '1444.909')] +[2026-07-22 19:44:50,430][50205] Updated weights for policy 0, policy_version 7436 (0.0012) +[2026-07-22 19:44:51,743][50205] Updated weights for policy 0, policy_version 7446 (0.0011) +[2026-07-22 19:44:52,232][50205] Updated weights for policy 0, policy_version 7456 (0.0011) +[2026-07-22 19:44:53,322][50205] Updated weights for policy 0, policy_version 7466 (0.0011) +[2026-07-22 19:44:54,303][50205] Updated weights for policy 0, policy_version 7476 (0.0011) +[2026-07-22 19:44:54,877][43431] Fps is (10 sec: 5326.0, 60 sec: 5495.5, 300 sec: 5442.8). Total num frames: 3829760. Throughput: 0: 5542.9. Samples: 3840142. Policy #0 lag: (min: 3.0, avg: 15.4, max: 34.0) +[2026-07-22 19:44:54,878][43431] Avg episode reward: [(0, '1498.949')] +[2026-07-22 19:44:54,963][49527] Saving new best policy, reward=1498.949! +[2026-07-22 19:44:55,133][50205] Updated weights for policy 0, policy_version 7486 (0.0010) +[2026-07-22 19:44:55,636][50205] Updated weights for policy 0, policy_version 7496 (0.0013) +[2026-07-22 19:44:57,275][50205] Updated weights for policy 0, policy_version 7506 (0.0011) +[2026-07-22 19:44:57,998][50205] Updated weights for policy 0, policy_version 7516 (0.0013) +[2026-07-22 19:44:58,704][50205] Updated weights for policy 0, policy_version 7526 (0.0016) +[2026-07-22 19:44:59,684][50205] Updated weights for policy 0, policy_version 7536 (0.0011) +[2026-07-22 19:44:59,878][43431] Fps is (10 sec: 5536.4, 60 sec: 5529.7, 300 sec: 5449.8). Total num frames: 3858432. Throughput: 0: 5544.0. Samples: 3856996. Policy #0 lag: (min: 3.0, avg: 15.4, max: 34.0) +[2026-07-22 19:44:59,878][43431] Avg episode reward: [(0, '1288.324')] +[2026-07-22 19:45:00,795][50205] Updated weights for policy 0, policy_version 7546 (0.0011) +[2026-07-22 19:45:01,408][50205] Updated weights for policy 0, policy_version 7556 (0.0011) +[2026-07-22 19:45:02,709][50205] Updated weights for policy 0, policy_version 7566 (0.0013) +[2026-07-22 19:45:03,492][50205] Updated weights for policy 0, policy_version 7576 (0.0014) +[2026-07-22 19:45:04,172][50205] Updated weights for policy 0, policy_version 7586 (0.0018) +[2026-07-22 19:45:04,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5529.6, 300 sec: 5442.8). Total num frames: 3885056. Throughput: 0: 5538.7. Samples: 3890376. Policy #0 lag: (min: 3.0, avg: 19.1, max: 38.0) +[2026-07-22 19:45:04,878][43431] Avg episode reward: [(0, '1140.624')] +[2026-07-22 19:45:05,236][50205] Updated weights for policy 0, policy_version 7596 (0.0011) +[2026-07-22 19:45:06,271][50205] Updated weights for policy 0, policy_version 7606 (0.0011) +[2026-07-22 19:45:06,811][50205] Updated weights for policy 0, policy_version 7616 (0.0010) +[2026-07-22 19:45:08,166][50205] Updated weights for policy 0, policy_version 7626 (0.0011) +[2026-07-22 19:45:08,964][50205] Updated weights for policy 0, policy_version 7636 (0.0017) +[2026-07-22 19:45:09,877][50205] Updated weights for policy 0, policy_version 7646 (0.0010) +[2026-07-22 19:45:09,877][43431] Fps is (10 sec: 5529.8, 60 sec: 5529.6, 300 sec: 5463.6). Total num frames: 3913728. Throughput: 0: 5511.0. Samples: 3922768. Policy #0 lag: (min: 1.0, avg: 15.9, max: 33.0) +[2026-07-22 19:45:09,878][43431] Avg episode reward: [(0, '1501.523')] +[2026-07-22 19:45:09,946][49527] Saving new best policy, reward=1501.523! +[2026-07-22 19:45:10,952][50205] Updated weights for policy 0, policy_version 7656 (0.0013) +[2026-07-22 19:45:12,212][50205] Updated weights for policy 0, policy_version 7666 (0.0011) +[2026-07-22 19:45:13,052][50205] Updated weights for policy 0, policy_version 7676 (0.0013) +[2026-07-22 19:45:13,820][50205] Updated weights for policy 0, policy_version 7686 (0.0011) +[2026-07-22 19:45:14,841][50205] Updated weights for policy 0, policy_version 7696 (0.0012) +[2026-07-22 19:45:14,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5529.6, 300 sec: 5449.8). Total num frames: 3940352. Throughput: 0: 5482.3. Samples: 3938264. Policy #0 lag: (min: 0.0, avg: 16.6, max: 32.0) +[2026-07-22 19:45:14,878][43431] Avg episode reward: [(0, '1552.036')] +[2026-07-22 19:45:14,910][49527] Saving new best policy, reward=1552.036! +[2026-07-22 19:45:15,887][50205] Updated weights for policy 0, policy_version 7706 (0.0015) +[2026-07-22 19:45:16,699][50205] Updated weights for policy 0, policy_version 7716 (0.0023) +[2026-07-22 19:45:17,639][50205] Updated weights for policy 0, policy_version 7726 (0.0015) +[2026-07-22 19:45:18,725][50205] Updated weights for policy 0, policy_version 7736 (0.0011) +[2026-07-22 19:45:19,507][50205] Updated weights for policy 0, policy_version 7746 (0.0021) +[2026-07-22 19:45:19,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5529.6, 300 sec: 5456.7). Total num frames: 3969024. Throughput: 0: 5531.7. Samples: 3971598. Policy #0 lag: (min: 0.0, avg: 16.6, max: 32.0) +[2026-07-22 19:45:19,878][43431] Avg episode reward: [(0, '1333.346')] +[2026-07-22 19:45:20,198][50205] Updated weights for policy 0, policy_version 7756 (0.0016) +[2026-07-22 19:45:21,462][50205] Updated weights for policy 0, policy_version 7766 (0.0011) +[2026-07-22 19:45:22,022][50205] Updated weights for policy 0, policy_version 7776 (0.0011) +[2026-07-22 19:45:23,103][50205] Updated weights for policy 0, policy_version 7786 (0.0024) +[2026-07-22 19:45:24,156][50205] Updated weights for policy 0, policy_version 7796 (0.0015) +[2026-07-22 19:45:24,843][50205] Updated weights for policy 0, policy_version 7806 (0.0011) +[2026-07-22 19:45:24,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5529.6, 300 sec: 5456.7). Total num frames: 3995648. Throughput: 0: 5533.4. Samples: 4005188. Policy #0 lag: (min: 3.0, avg: 16.4, max: 39.0) +[2026-07-22 19:45:24,878][43431] Avg episode reward: [(0, '1596.757')] +[2026-07-22 19:45:24,926][49527] Saving new best policy, reward=1596.757! +[2026-07-22 19:45:25,752][50205] Updated weights for policy 0, policy_version 7816 (0.0011) +[2026-07-22 19:45:26,840][50205] Updated weights for policy 0, policy_version 7826 (0.0010) +[2026-07-22 19:45:27,538][50205] Updated weights for policy 0, policy_version 7836 (0.0010) +[2026-07-22 19:45:28,654][50205] Updated weights for policy 0, policy_version 7846 (0.0013) +[2026-07-22 19:45:29,481][50205] Updated weights for policy 0, policy_version 7856 (0.0011) +[2026-07-22 19:45:29,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5495.5, 300 sec: 5449.8). Total num frames: 4022272. Throughput: 0: 5534.1. Samples: 4022010. Policy #0 lag: (min: 3.0, avg: 20.6, max: 44.0) +[2026-07-22 19:45:29,878][43431] Avg episode reward: [(0, '1390.794')] +[2026-07-22 19:45:30,361][50205] Updated weights for policy 0, policy_version 7866 (0.0011) +[2026-07-22 19:45:31,267][50205] Updated weights for policy 0, policy_version 7876 (0.0014) +[2026-07-22 19:45:32,199][50205] Updated weights for policy 0, policy_version 7886 (0.0011) +[2026-07-22 19:45:33,047][50205] Updated weights for policy 0, policy_version 7896 (0.0020) +[2026-07-22 19:45:34,094][50205] Updated weights for policy 0, policy_version 7906 (0.0011) +[2026-07-22 19:45:34,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5529.6, 300 sec: 5449.8). Total num frames: 4050944. Throughput: 0: 5535.4. Samples: 4055610. Policy #0 lag: (min: 3.0, avg: 20.6, max: 44.0) +[2026-07-22 19:45:34,878][43431] Avg episode reward: [(0, '1386.208')] +[2026-07-22 19:45:34,953][50205] Updated weights for policy 0, policy_version 7916 (0.0011) +[2026-07-22 19:45:36,020][50205] Updated weights for policy 0, policy_version 7926 (0.0011) +[2026-07-22 19:45:36,763][50205] Updated weights for policy 0, policy_version 7936 (0.0017) +[2026-07-22 19:45:37,830][50205] Updated weights for policy 0, policy_version 7946 (0.0011) +[2026-07-22 19:45:38,657][50205] Updated weights for policy 0, policy_version 7956 (0.0011) +[2026-07-22 19:45:39,586][50205] Updated weights for policy 0, policy_version 7966 (0.0011) +[2026-07-22 19:45:39,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5564.1, 300 sec: 5456.7). Total num frames: 4079616. Throughput: 0: 5533.9. Samples: 4089168. Policy #0 lag: (min: 2.0, avg: 20.4, max: 42.0) +[2026-07-22 19:45:39,878][43431] Avg episode reward: [(0, '1322.296')] +[2026-07-22 19:45:40,333][50205] Updated weights for policy 0, policy_version 7976 (0.0013) +[2026-07-22 19:45:41,549][50205] Updated weights for policy 0, policy_version 7986 (0.0010) +[2026-07-22 19:45:42,224][50205] Updated weights for policy 0, policy_version 7996 (0.0010) +[2026-07-22 19:45:43,292][50205] Updated weights for policy 0, policy_version 8006 (0.0012) +[2026-07-22 19:45:44,077][50205] Updated weights for policy 0, policy_version 8016 (0.0011) +[2026-07-22 19:45:44,878][43431] Fps is (10 sec: 5529.3, 60 sec: 5495.6, 300 sec: 5456.7). Total num frames: 4106240. Throughput: 0: 5532.2. Samples: 4105946. Policy #0 lag: (min: 1.0, avg: 16.6, max: 29.0) +[2026-07-22 19:45:44,879][43431] Avg episode reward: [(0, '1437.956')] +[2026-07-22 19:45:45,220][50205] Updated weights for policy 0, policy_version 8028 (0.0011) +[2026-07-22 19:45:46,274][50205] Updated weights for policy 0, policy_version 8038 (0.0012) +[2026-07-22 19:45:47,358][50205] Updated weights for policy 0, policy_version 8048 (0.0010) +[2026-07-22 19:45:48,323][50205] Updated weights for policy 0, policy_version 8058 (0.0015) +[2026-07-22 19:45:49,235][50205] Updated weights for policy 0, policy_version 8068 (0.0011) +[2026-07-22 19:45:49,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5496.6, 300 sec: 5456.7). Total num frames: 4132864. Throughput: 0: 5480.7. Samples: 4137006. Policy #0 lag: (min: 2.0, avg: 20.0, max: 36.0) +[2026-07-22 19:45:49,878][43431] Avg episode reward: [(0, '1594.310')] +[2026-07-22 19:45:50,628][50205] Updated weights for policy 0, policy_version 8078 (0.0015) +[2026-07-22 19:45:51,275][50205] Updated weights for policy 0, policy_version 8088 (0.0011) +[2026-07-22 19:45:52,223][50205] Updated weights for policy 0, policy_version 8098 (0.0011) +[2026-07-22 19:45:53,101][50205] Updated weights for policy 0, policy_version 8108 (0.0012) +[2026-07-22 19:45:54,180][50205] Updated weights for policy 0, policy_version 8118 (0.0014) +[2026-07-22 19:45:54,816][50205] Updated weights for policy 0, policy_version 8128 (0.0010) +[2026-07-22 19:45:54,877][43431] Fps is (10 sec: 5529.8, 60 sec: 5529.6, 300 sec: 5456.7). Total num frames: 4161536. Throughput: 0: 5489.5. Samples: 4169796. Policy #0 lag: (min: 2.0, avg: 20.0, max: 36.0) +[2026-07-22 19:45:54,878][43431] Avg episode reward: [(0, '1420.265')] +[2026-07-22 19:45:55,910][50205] Updated weights for policy 0, policy_version 8138 (0.0011) +[2026-07-22 19:45:56,869][50205] Updated weights for policy 0, policy_version 8148 (0.0011) +[2026-07-22 19:45:57,775][50205] Updated weights for policy 0, policy_version 8158 (0.0012) +[2026-07-22 19:45:58,665][50205] Updated weights for policy 0, policy_version 8168 (0.0011) +[2026-07-22 19:45:59,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5461.4, 300 sec: 5449.8). Total num frames: 4186112. Throughput: 0: 5513.4. Samples: 4186366. Policy #0 lag: (min: 3.0, avg: 15.5, max: 35.0) +[2026-07-22 19:45:59,878][43431] Avg episode reward: [(0, '1326.087')] +[2026-07-22 19:46:00,046][50205] Updated weights for policy 0, policy_version 8180 (0.0014) +[2026-07-22 19:46:00,839][50205] Updated weights for policy 0, policy_version 8192 (0.0012) +[2026-07-22 19:46:02,163][50205] Updated weights for policy 0, policy_version 8202 (0.0011) +[2026-07-22 19:46:03,044][50205] Updated weights for policy 0, policy_version 8212 (0.0015) +[2026-07-22 19:46:03,751][50205] Updated weights for policy 0, policy_version 8222 (0.0015) +[2026-07-22 19:46:04,659][50205] Updated weights for policy 0, policy_version 8232 (0.0015) +[2026-07-22 19:46:04,877][43431] Fps is (10 sec: 5325.0, 60 sec: 5495.5, 300 sec: 5449.8). Total num frames: 4214784. Throughput: 0: 5493.9. Samples: 4218824. Policy #0 lag: (min: 3.0, avg: 20.2, max: 43.0) +[2026-07-22 19:46:04,878][43431] Avg episode reward: [(0, '1403.813')] +[2026-07-22 19:46:05,931][50205] Updated weights for policy 0, policy_version 8242 (0.0020) +[2026-07-22 19:46:06,488][50205] Updated weights for policy 0, policy_version 8252 (0.0010) +[2026-07-22 19:46:07,593][50205] Updated weights for policy 0, policy_version 8262 (0.0015) +[2026-07-22 19:46:08,324][50205] Updated weights for policy 0, policy_version 8272 (0.0013) +[2026-07-22 19:46:09,252][50205] Updated weights for policy 0, policy_version 8282 (0.0016) +[2026-07-22 19:46:09,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5495.5, 300 sec: 5456.7). Total num frames: 4243456. Throughput: 0: 5493.7. Samples: 4252404. Policy #0 lag: (min: 3.0, avg: 20.2, max: 43.0) +[2026-07-22 19:46:09,878][43431] Avg episode reward: [(0, '1516.119')] +[2026-07-22 19:46:10,206][50205] Updated weights for policy 0, policy_version 8292 (0.0015) +[2026-07-22 19:46:11,401][50205] Updated weights for policy 0, policy_version 8302 (0.0013) +[2026-07-22 19:46:12,100][50205] Updated weights for policy 0, policy_version 8314 (0.0011) +[2026-07-22 19:46:13,049][50205] Updated weights for policy 0, policy_version 8324 (0.0018) +[2026-07-22 19:46:14,338][50205] Updated weights for policy 0, policy_version 8334 (0.0011) +[2026-07-22 19:46:14,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5495.5, 300 sec: 5463.7). Total num frames: 4270080. Throughput: 0: 5487.9. Samples: 4268968. Policy #0 lag: (min: 3.0, avg: 19.4, max: 39.0) +[2026-07-22 19:46:14,878][43431] Avg episode reward: [(0, '1572.137')] +[2026-07-22 19:46:15,140][50205] Updated weights for policy 0, policy_version 8344 (0.0016) +[2026-07-22 19:46:16,036][50205] Updated weights for policy 0, policy_version 8354 (0.0015) +[2026-07-22 19:46:17,003][50205] Updated weights for policy 0, policy_version 8364 (0.0016) +[2026-07-22 19:46:17,780][50205] Updated weights for policy 0, policy_version 8374 (0.0011) +[2026-07-22 19:46:18,630][50205] Updated weights for policy 0, policy_version 8384 (0.0011) +[2026-07-22 19:46:19,724][50205] Updated weights for policy 0, policy_version 8394 (0.0015) +[2026-07-22 19:46:19,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5470.6). Total num frames: 4298752. Throughput: 0: 5482.5. Samples: 4302322. Policy #0 lag: (min: 3.0, avg: 21.4, max: 47.0) +[2026-07-22 19:46:19,878][43431] Avg episode reward: [(0, '1467.062')] +[2026-07-22 19:46:20,466][50205] Updated weights for policy 0, policy_version 8404 (0.0016) +[2026-07-22 19:46:21,527][50205] Updated weights for policy 0, policy_version 8414 (0.0012) +[2026-07-22 19:46:22,282][50205] Updated weights for policy 0, policy_version 8424 (0.0012) +[2026-07-22 19:46:23,634][50205] Updated weights for policy 0, policy_version 8434 (0.0010) +[2026-07-22 19:46:24,230][50205] Updated weights for policy 0, policy_version 8444 (0.0013) +[2026-07-22 19:46:24,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5461.3, 300 sec: 5463.6). Total num frames: 4323328. Throughput: 0: 5445.5. Samples: 4334214. Policy #0 lag: (min: 3.0, avg: 21.4, max: 47.0) +[2026-07-22 19:46:24,878][43431] Avg episode reward: [(0, '1345.073')] +[2026-07-22 19:46:25,540][50205] Updated weights for policy 0, policy_version 8454 (0.0011) +[2026-07-22 19:46:26,365][50205] Updated weights for policy 0, policy_version 8464 (0.0011) +[2026-07-22 19:46:27,610][50205] Updated weights for policy 0, policy_version 8474 (0.0014) +[2026-07-22 19:46:28,348][50205] Updated weights for policy 0, policy_version 8484 (0.0011) +[2026-07-22 19:46:29,424][50205] Updated weights for policy 0, policy_version 8494 (0.0020) +[2026-07-22 19:46:29,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5495.5, 300 sec: 5470.6). Total num frames: 4352000. Throughput: 0: 5417.6. Samples: 4349734. Policy #0 lag: (min: 1.0, avg: 15.3, max: 33.0) +[2026-07-22 19:46:29,878][43431] Avg episode reward: [(0, '1527.165')] +[2026-07-22 19:46:30,136][50205] Updated weights for policy 0, policy_version 8504 (0.0011) +[2026-07-22 19:46:31,395][50205] Updated weights for policy 0, policy_version 8514 (0.0011) +[2026-07-22 19:46:32,091][50205] Updated weights for policy 0, policy_version 8524 (0.0011) +[2026-07-22 19:46:33,168][50205] Updated weights for policy 0, policy_version 8534 (0.0011) +[2026-07-22 19:46:33,885][50205] Updated weights for policy 0, policy_version 8544 (0.0014) +[2026-07-22 19:46:34,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5461.3, 300 sec: 5463.6). Total num frames: 4378624. Throughput: 0: 5444.3. Samples: 4382000. Policy #0 lag: (min: 3.0, avg: 18.3, max: 35.0) +[2026-07-22 19:46:34,878][43431] Avg episode reward: [(0, '1352.766')] +[2026-07-22 19:46:34,992][50205] Updated weights for policy 0, policy_version 8554 (0.0014) +[2026-07-22 19:46:36,024][50205] Updated weights for policy 0, policy_version 8564 (0.0011) +[2026-07-22 19:46:37,038][50205] Updated weights for policy 0, policy_version 8574 (0.0019) +[2026-07-22 19:46:38,176][50205] Updated weights for policy 0, policy_version 8585 (0.0011) +[2026-07-22 19:46:38,988][50205] Updated weights for policy 0, policy_version 8595 (0.0013) +[2026-07-22 19:46:39,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5427.2, 300 sec: 5463.6). Total num frames: 4405248. Throughput: 0: 5433.7. Samples: 4414310. Policy #0 lag: (min: 3.0, avg: 15.2, max: 35.0) +[2026-07-22 19:46:39,878][43431] Avg episode reward: [(0, '1557.108')] +[2026-07-22 19:46:40,206][50205] Updated weights for policy 0, policy_version 8605 (0.0020) +[2026-07-22 19:46:40,737][50205] Updated weights for policy 0, policy_version 8615 (0.0011) +[2026-07-22 19:46:41,812][50205] Updated weights for policy 0, policy_version 8625 (0.0011) +[2026-07-22 19:46:42,954][50205] Updated weights for policy 0, policy_version 8635 (0.0015) +[2026-07-22 19:46:43,792][50205] Updated weights for policy 0, policy_version 8645 (0.0019) +[2026-07-22 19:46:44,619][50205] Updated weights for policy 0, policy_version 8655 (0.0011) +[2026-07-22 19:46:44,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5427.3, 300 sec: 5456.7). Total num frames: 4431872. Throughput: 0: 5423.4. Samples: 4430420. Policy #0 lag: (min: 3.0, avg: 15.2, max: 35.0) +[2026-07-22 19:46:44,878][43431] Avg episode reward: [(0, '1397.254')] +[2026-07-22 19:46:45,964][50205] Updated weights for policy 0, policy_version 8665 (0.0016) +[2026-07-22 19:46:46,423][50205] Updated weights for policy 0, policy_version 8675 (0.0012) +[2026-07-22 19:46:48,051][50205] Updated weights for policy 0, policy_version 8685 (0.0010) +[2026-07-22 19:46:48,703][50205] Updated weights for policy 0, policy_version 8695 (0.0016) +[2026-07-22 19:46:49,324][50205] Updated weights for policy 0, policy_version 8705 (0.0013) +[2026-07-22 19:46:49,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5427.2, 300 sec: 5456.7). Total num frames: 4458496. Throughput: 0: 5420.8. Samples: 4462758. Policy #0 lag: (min: 3.0, avg: 19.5, max: 35.0) +[2026-07-22 19:46:49,878][43431] Avg episode reward: [(0, '1421.578')] +[2026-07-22 19:46:50,265][50205] Updated weights for policy 0, policy_version 8715 (0.0021) +[2026-07-22 19:46:51,769][50205] Updated weights for policy 0, policy_version 8725 (0.0011) +[2026-07-22 19:46:52,131][50205] Updated weights for policy 0, policy_version 8735 (0.0015) +[2026-07-22 19:46:53,176][50205] Updated weights for policy 0, policy_version 8745 (0.0016) +[2026-07-22 19:46:54,533][50205] Updated weights for policy 0, policy_version 8755 (0.0011) +[2026-07-22 19:46:54,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5393.1, 300 sec: 5442.8). Total num frames: 4485120. Throughput: 0: 5394.6. Samples: 4495162. Policy #0 lag: (min: 3.0, avg: 14.9, max: 39.0) +[2026-07-22 19:46:54,878][43431] Avg episode reward: [(0, '1342.238')] +[2026-07-22 19:46:55,284][50205] Updated weights for policy 0, policy_version 8765 (0.0013) +[2026-07-22 19:46:55,905][50205] Updated weights for policy 0, policy_version 8775 (0.0011) +[2026-07-22 19:46:57,507][50205] Updated weights for policy 0, policy_version 8785 (0.0011) +[2026-07-22 19:46:58,006][50205] Updated weights for policy 0, policy_version 8795 (0.0016) +[2026-07-22 19:46:58,920][50205] Updated weights for policy 0, policy_version 8805 (0.0012) +[2026-07-22 19:46:59,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5427.2, 300 sec: 5463.6). Total num frames: 4511744. Throughput: 0: 5383.6. Samples: 4511230. Policy #0 lag: (min: 3.0, avg: 14.9, max: 39.0) +[2026-07-22 19:46:59,878][43431] Avg episode reward: [(0, '1426.875')] +[2026-07-22 19:47:00,066][50205] Updated weights for policy 0, policy_version 8815 (0.0022) +[2026-07-22 19:47:00,959][50205] Updated weights for policy 0, policy_version 8825 (0.0011) +[2026-07-22 19:47:01,619][50205] Updated weights for policy 0, policy_version 8835 (0.0011) +[2026-07-22 19:47:03,605][50205] Updated weights for policy 0, policy_version 8848 (0.0012) +[2026-07-22 19:47:04,605][50205] Updated weights for policy 0, policy_version 8858 (0.0011) +[2026-07-22 19:47:04,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5358.9, 300 sec: 5449.8). Total num frames: 4536320. Throughput: 0: 5308.3. Samples: 4541194. Policy #0 lag: (min: 0.0, avg: 20.3, max: 36.0) +[2026-07-22 19:47:04,878][43431] Avg episode reward: [(0, '1503.162')] +[2026-07-22 19:47:05,293][50205] Updated weights for policy 0, policy_version 8868 (0.0011) +[2026-07-22 19:47:06,890][50205] Updated weights for policy 0, policy_version 8878 (0.0016) +[2026-07-22 19:47:07,674][50205] Updated weights for policy 0, policy_version 8888 (0.0012) +[2026-07-22 19:47:08,517][50205] Updated weights for policy 0, policy_version 8898 (0.0014) +[2026-07-22 19:47:09,159][49527] Signal inference workers to stop experience collection... (150 times) +[2026-07-22 19:47:09,172][49527] Signal inference workers to resume experience collection... (150 times) +[2026-07-22 19:47:09,177][50205] InferenceWorker_p0-w0: stopping experience collection (150 times) +[2026-07-22 19:47:09,190][50205] InferenceWorker_p0-w0: resuming experience collection (150 times) +[2026-07-22 19:47:09,283][50205] Updated weights for policy 0, policy_version 8908 (0.0011) +[2026-07-22 19:47:09,877][43431] Fps is (10 sec: 4915.3, 60 sec: 5290.7, 300 sec: 5435.9). Total num frames: 4560896. Throughput: 0: 5272.8. Samples: 4571490. Policy #0 lag: (min: 0.0, avg: 20.3, max: 36.0) +[2026-07-22 19:47:09,878][43431] Avg episode reward: [(0, '1434.253')] +[2026-07-22 19:47:10,827][50205] Updated weights for policy 0, policy_version 8918 (0.0011) +[2026-07-22 19:47:11,108][50205] Updated weights for policy 0, policy_version 8928 (0.0018) +[2026-07-22 19:47:12,602][50205] Updated weights for policy 0, policy_version 8938 (0.0011) +[2026-07-22 19:47:13,458][50205] Updated weights for policy 0, policy_version 8948 (0.0010) +[2026-07-22 19:47:14,086][50205] Updated weights for policy 0, policy_version 8958 (0.0012) +[2026-07-22 19:47:14,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5324.8, 300 sec: 5449.8). Total num frames: 4589568. Throughput: 0: 5287.1. Samples: 4587654. Policy #0 lag: (min: 3.0, avg: 15.2, max: 35.0) +[2026-07-22 19:47:14,878][43431] Avg episode reward: [(0, '1549.549')] +[2026-07-22 19:47:15,036][50205] Updated weights for policy 0, policy_version 8968 (0.0011) +[2026-07-22 19:47:16,502][50205] Updated weights for policy 0, policy_version 8978 (0.0011) +[2026-07-22 19:47:17,146][50205] Updated weights for policy 0, policy_version 8988 (0.0014) +[2026-07-22 19:47:18,161][50205] Updated weights for policy 0, policy_version 8998 (0.0011) +[2026-07-22 19:47:19,089][50205] Updated weights for policy 0, policy_version 9008 (0.0011) +[2026-07-22 19:47:19,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5290.7, 300 sec: 5442.8). Total num frames: 4616192. Throughput: 0: 5288.2. Samples: 4619970. Policy #0 lag: (min: 3.0, avg: 20.7, max: 41.0) +[2026-07-22 19:47:19,878][43431] Avg episode reward: [(0, '1495.391')] +[2026-07-22 19:47:20,089][50205] Updated weights for policy 0, policy_version 9018 (0.0012) +[2026-07-22 19:47:20,991][50205] Updated weights for policy 0, policy_version 9028 (0.0017) +[2026-07-22 19:47:21,893][50205] Updated weights for policy 0, policy_version 9038 (0.0017) +[2026-07-22 19:47:22,739][50205] Updated weights for policy 0, policy_version 9048 (0.0016) +[2026-07-22 19:47:23,817][50205] Updated weights for policy 0, policy_version 9058 (0.0016) +[2026-07-22 19:47:24,836][50205] Updated weights for policy 0, policy_version 9068 (0.0011) +[2026-07-22 19:47:24,877][43431] Fps is (10 sec: 5324.6, 60 sec: 5324.8, 300 sec: 5435.9). Total num frames: 4642816. Throughput: 0: 5292.0. Samples: 4652450. Policy #0 lag: (min: 3.0, avg: 20.7, max: 41.0) +[2026-07-22 19:47:24,878][43431] Avg episode reward: [(0, '1262.679')] +[2026-07-22 19:47:25,647][50205] Updated weights for policy 0, policy_version 9078 (0.0011) +[2026-07-22 19:47:26,369][50205] Updated weights for policy 0, policy_version 9088 (0.0011) +[2026-07-22 19:47:27,810][50205] Updated weights for policy 0, policy_version 9098 (0.0019) +[2026-07-22 19:47:28,474][50205] Updated weights for policy 0, policy_version 9108 (0.0011) +[2026-07-22 19:47:29,345][50205] Updated weights for policy 0, policy_version 9118 (0.0010) +[2026-07-22 19:47:29,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5324.8, 300 sec: 5435.9). Total num frames: 4671488. Throughput: 0: 5293.5. Samples: 4668626. Policy #0 lag: (min: 3.0, avg: 18.7, max: 43.0) +[2026-07-22 19:47:29,878][43431] Avg episode reward: [(0, '1489.825')] +[2026-07-22 19:47:30,545][50205] Updated weights for policy 0, policy_version 9128 (0.0011) +[2026-07-22 19:47:31,484][50205] Updated weights for policy 0, policy_version 9138 (0.0011) +[2026-07-22 19:47:32,150][50205] Updated weights for policy 0, policy_version 9148 (0.0011) +[2026-07-22 19:47:33,458][50205] Updated weights for policy 0, policy_version 9158 (0.0011) +[2026-07-22 19:47:34,246][50205] Updated weights for policy 0, policy_version 9168 (0.0016) +[2026-07-22 19:47:34,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5290.7, 300 sec: 5435.9). Total num frames: 4696064. Throughput: 0: 5295.8. Samples: 4701072. Policy #0 lag: (min: 3.0, avg: 19.6, max: 39.0) +[2026-07-22 19:47:34,878][43431] Avg episode reward: [(0, '1481.903')] +[2026-07-22 19:47:35,057][50205] Updated weights for policy 0, policy_version 9180 (0.0016) +[2026-07-22 19:47:36,426][50205] Updated weights for policy 0, policy_version 9190 (0.0015) +[2026-07-22 19:47:37,296][50205] Updated weights for policy 0, policy_version 9200 (0.0011) +[2026-07-22 19:47:38,049][50205] Updated weights for policy 0, policy_version 9210 (0.0012) +[2026-07-22 19:47:39,440][50205] Updated weights for policy 0, policy_version 9220 (0.0011) +[2026-07-22 19:47:39,877][43431] Fps is (10 sec: 4915.2, 60 sec: 5256.5, 300 sec: 5428.9). Total num frames: 4720640. Throughput: 0: 5274.9. Samples: 4732534. Policy #0 lag: (min: 3.0, avg: 19.6, max: 39.0) +[2026-07-22 19:47:39,878][43431] Avg episode reward: [(0, '1458.167')] +[2026-07-22 19:47:40,395][50205] Updated weights for policy 0, policy_version 9231 (0.0011) +[2026-07-22 19:47:41,560][50205] Updated weights for policy 0, policy_version 9241 (0.0011) +[2026-07-22 19:47:43,164][50205] Updated weights for policy 0, policy_version 9251 (0.0014) +[2026-07-22 19:47:43,532][50205] Updated weights for policy 0, policy_version 9262 (0.0016) +[2026-07-22 19:47:44,278][50205] Updated weights for policy 0, policy_version 9272 (0.0016) +[2026-07-22 19:47:44,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5256.5, 300 sec: 5428.9). Total num frames: 4747264. Throughput: 0: 5245.1. Samples: 4747260. Policy #0 lag: (min: 5.0, avg: 16.4, max: 38.0) +[2026-07-22 19:47:44,878][43431] Avg episode reward: [(0, '1486.967')] +[2026-07-22 19:47:45,865][50205] Updated weights for policy 0, policy_version 9282 (0.0015) +[2026-07-22 19:47:46,577][50205] Updated weights for policy 0, policy_version 9294 (0.0011) +[2026-07-22 19:47:47,400][50205] Updated weights for policy 0, policy_version 9304 (0.0011) +[2026-07-22 19:47:49,025][50205] Updated weights for policy 0, policy_version 9314 (0.0015) +[2026-07-22 19:47:49,355][50205] Updated weights for policy 0, policy_version 9324 (0.0012) +[2026-07-22 19:47:49,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5290.7, 300 sec: 5428.9). Total num frames: 4775936. Throughput: 0: 5291.8. Samples: 4779324. Policy #0 lag: (min: 3.0, avg: 24.1, max: 43.0) +[2026-07-22 19:47:49,878][43431] Avg episode reward: [(0, '1565.132')] +[2026-07-22 19:47:50,320][50205] Updated weights for policy 0, policy_version 9334 (0.0015) +[2026-07-22 19:47:51,281][50205] Updated weights for policy 0, policy_version 9344 (0.0016) +[2026-07-22 19:47:52,252][50205] Updated weights for policy 0, policy_version 9354 (0.0023) +[2026-07-22 19:47:53,061][50205] Updated weights for policy 0, policy_version 9364 (0.0010) +[2026-07-22 19:47:54,356][50205] Updated weights for policy 0, policy_version 9374 (0.0015) +[2026-07-22 19:47:54,878][43431] Fps is (10 sec: 5324.5, 60 sec: 5256.5, 300 sec: 5415.0). Total num frames: 4800512. Throughput: 0: 5343.0. Samples: 4811928. Policy #0 lag: (min: 3.0, avg: 24.1, max: 43.0) +[2026-07-22 19:47:54,878][43431] Avg episode reward: [(0, '1472.982')] +[2026-07-22 19:47:55,047][50205] Updated weights for policy 0, policy_version 9384 (0.0016) +[2026-07-22 19:47:55,969][50205] Updated weights for policy 0, policy_version 9394 (0.0015) +[2026-07-22 19:47:57,175][50205] Updated weights for policy 0, policy_version 9404 (0.0011) +[2026-07-22 19:47:58,162][50205] Updated weights for policy 0, policy_version 9414 (0.0012) +[2026-07-22 19:47:58,677][50205] Updated weights for policy 0, policy_version 9424 (0.0011) +[2026-07-22 19:47:59,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5290.7, 300 sec: 5428.9). Total num frames: 4829184. Throughput: 0: 5339.4. Samples: 4827928. Policy #0 lag: (min: 3.0, avg: 20.4, max: 39.0) +[2026-07-22 19:47:59,878][43431] Avg episode reward: [(0, '1477.066')] +[2026-07-22 19:48:00,054][50205] Updated weights for policy 0, policy_version 9434 (0.0011) +[2026-07-22 19:48:01,081][50205] Updated weights for policy 0, policy_version 9444 (0.0011) +[2026-07-22 19:48:01,609][50205] Updated weights for policy 0, policy_version 9454 (0.0012) +[2026-07-22 19:48:02,854][50205] Updated weights for policy 0, policy_version 9464 (0.0016) +[2026-07-22 19:48:04,062][50205] Updated weights for policy 0, policy_version 9474 (0.0015) +[2026-07-22 19:48:04,562][50205] Updated weights for policy 0, policy_version 9484 (0.0017) +[2026-07-22 19:48:04,877][43431] Fps is (10 sec: 5734.7, 60 sec: 5358.9, 300 sec: 5435.9). Total num frames: 4857856. Throughput: 0: 5339.3. Samples: 4860240. Policy #0 lag: (min: 2.0, avg: 22.6, max: 42.0) +[2026-07-22 19:48:04,878][43431] Avg episode reward: [(0, '1582.958')] +[2026-07-22 19:48:05,695][50205] Updated weights for policy 0, policy_version 9494 (0.0015) +[2026-07-22 19:48:06,564][50205] Updated weights for policy 0, policy_version 9504 (0.0012) +[2026-07-22 19:48:07,505][50205] Updated weights for policy 0, policy_version 9514 (0.0012) +[2026-07-22 19:48:08,472][50205] Updated weights for policy 0, policy_version 9524 (0.0019) +[2026-07-22 19:48:09,469][50205] Updated weights for policy 0, policy_version 9534 (0.0014) +[2026-07-22 19:48:09,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5393.1, 300 sec: 5435.9). Total num frames: 4884480. Throughput: 0: 5336.6. Samples: 4892594. Policy #0 lag: (min: 2.0, avg: 22.6, max: 42.0) +[2026-07-22 19:48:09,878][43431] Avg episode reward: [(0, '1654.920')] +[2026-07-22 19:48:09,934][49527] Saving new best policy, reward=1654.920! +[2026-07-22 19:48:10,393][50205] Updated weights for policy 0, policy_version 9544 (0.0011) +[2026-07-22 19:48:11,405][50205] Updated weights for policy 0, policy_version 9554 (0.0012) +[2026-07-22 19:48:12,285][50205] Updated weights for policy 0, policy_version 9564 (0.0012) +[2026-07-22 19:48:13,247][50205] Updated weights for policy 0, policy_version 9574 (0.0017) +[2026-07-22 19:48:14,051][50205] Updated weights for policy 0, policy_version 9584 (0.0016) +[2026-07-22 19:48:14,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5324.8, 300 sec: 5428.9). Total num frames: 4909056. Throughput: 0: 5337.7. Samples: 4908824. Policy #0 lag: (min: 2.0, avg: 18.8, max: 35.0) +[2026-07-22 19:48:14,878][43431] Avg episode reward: [(0, '1392.050')] +[2026-07-22 19:48:15,218][50205] Updated weights for policy 0, policy_version 9594 (0.0016) +[2026-07-22 19:48:16,232][50205] Updated weights for policy 0, policy_version 9604 (0.0011) +[2026-07-22 19:48:17,230][50205] Updated weights for policy 0, policy_version 9614 (0.0016) +[2026-07-22 19:48:18,404][50205] Updated weights for policy 0, policy_version 9624 (0.0011) +[2026-07-22 19:48:19,302][50205] Updated weights for policy 0, policy_version 9634 (0.0014) +[2026-07-22 19:48:19,877][43431] Fps is (10 sec: 4915.2, 60 sec: 5290.7, 300 sec: 5422.0). Total num frames: 4933632. Throughput: 0: 5286.4. Samples: 4938960. Policy #0 lag: (min: 3.0, avg: 16.1, max: 35.0) +[2026-07-22 19:48:19,878][43431] Avg episode reward: [(0, '1706.214')] +[2026-07-22 19:48:19,947][49527] Saving new best policy, reward=1706.214! +[2026-07-22 19:48:20,198][50205] Updated weights for policy 0, policy_version 9644 (0.0014) +[2026-07-22 19:48:21,460][50205] Updated weights for policy 0, policy_version 9654 (0.0011) +[2026-07-22 19:48:22,220][50205] Updated weights for policy 0, policy_version 9664 (0.0022) +[2026-07-22 19:48:23,214][50205] Updated weights for policy 0, policy_version 9674 (0.0012) +[2026-07-22 19:48:24,089][50205] Updated weights for policy 0, policy_version 9684 (0.0014) +[2026-07-22 19:48:24,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5290.7, 300 sec: 5415.1). Total num frames: 4960256. Throughput: 0: 5303.9. Samples: 4971208. Policy #0 lag: (min: 3.0, avg: 16.1, max: 35.0) +[2026-07-22 19:48:24,878][43431] Avg episode reward: [(0, '1507.706')] +[2026-07-22 19:48:25,149][50205] Updated weights for policy 0, policy_version 9694 (0.0011) +[2026-07-22 19:48:25,869][50205] Updated weights for policy 0, policy_version 9704 (0.0011) +[2026-07-22 19:48:26,967][50205] Updated weights for policy 0, policy_version 9714 (0.0011) +[2026-07-22 19:48:27,868][50205] Updated weights for policy 0, policy_version 9724 (0.0011) +[2026-07-22 19:48:28,886][50205] Updated weights for policy 0, policy_version 9734 (0.0011) +[2026-07-22 19:48:29,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5290.7, 300 sec: 5422.0). Total num frames: 4988928. Throughput: 0: 5331.6. Samples: 4987182. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 19:48:29,878][43431] Avg episode reward: [(0, '1596.286')] +[2026-07-22 19:48:30,130][50205] Updated weights for policy 0, policy_version 9746 (0.0011) +[2026-07-22 19:48:31,091][50205] Updated weights for policy 0, policy_version 9756 (0.0019) +[2026-07-22 19:48:32,192][50205] Updated weights for policy 0, policy_version 9766 (0.0025) +[2026-07-22 19:48:32,679][50205] Updated weights for policy 0, policy_version 9776 (0.0012) +[2026-07-22 19:48:34,072][50205] Updated weights for policy 0, policy_version 9786 (0.0011) +[2026-07-22 19:48:34,875][50205] Updated weights for policy 0, policy_version 9796 (0.0017) +[2026-07-22 19:48:34,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5324.8, 300 sec: 5408.1). Total num frames: 5015552. Throughput: 0: 5336.4. Samples: 5019464. Policy #0 lag: (min: 1.0, avg: 17.7, max: 41.0) +[2026-07-22 19:48:34,878][43431] Avg episode reward: [(0, '1540.659')] +[2026-07-22 19:48:35,698][50205] Updated weights for policy 0, policy_version 9806 (0.0020) +[2026-07-22 19:48:36,560][50205] Updated weights for policy 0, policy_version 9816 (0.0013) +[2026-07-22 19:48:37,753][50205] Updated weights for policy 0, policy_version 9826 (0.0013) +[2026-07-22 19:48:38,402][50205] Updated weights for policy 0, policy_version 9836 (0.0021) +[2026-07-22 19:48:39,502][50205] Updated weights for policy 0, policy_version 9846 (0.0020) +[2026-07-22 19:48:39,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5358.9, 300 sec: 5422.0). Total num frames: 5042176. Throughput: 0: 5333.9. Samples: 5051952. Policy #0 lag: (min: 1.0, avg: 17.7, max: 41.0) +[2026-07-22 19:48:39,878][43431] Avg episode reward: [(0, '1549.322')] +[2026-07-22 19:48:40,579][50205] Updated weights for policy 0, policy_version 9856 (0.0014) +[2026-07-22 19:48:41,371][50205] Updated weights for policy 0, policy_version 9866 (0.0014) +[2026-07-22 19:48:42,243][50205] Updated weights for policy 0, policy_version 9876 (0.0011) +[2026-07-22 19:48:43,553][50205] Updated weights for policy 0, policy_version 9886 (0.0011) +[2026-07-22 19:48:44,161][50205] Updated weights for policy 0, policy_version 9896 (0.0022) +[2026-07-22 19:48:44,878][43431] Fps is (10 sec: 5529.2, 60 sec: 5393.0, 300 sec: 5415.0). Total num frames: 5070848. Throughput: 0: 5340.5. Samples: 5068254. Policy #0 lag: (min: 3.0, avg: 20.9, max: 39.0) +[2026-07-22 19:48:44,879][43431] Avg episode reward: [(0, '1456.789')] +[2026-07-22 19:48:45,237][50205] Updated weights for policy 0, policy_version 9906 (0.0011) +[2026-07-22 19:48:46,197][50205] Updated weights for policy 0, policy_version 9916 (0.0016) +[2026-07-22 19:48:47,234][50205] Updated weights for policy 0, policy_version 9926 (0.0015) +[2026-07-22 19:48:48,008][50205] Updated weights for policy 0, policy_version 9936 (0.0014) +[2026-07-22 19:48:49,604][50205] Updated weights for policy 0, policy_version 9946 (0.0021) +[2026-07-22 19:48:49,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5324.8, 300 sec: 5408.1). Total num frames: 5095424. Throughput: 0: 5311.9. Samples: 5099274. Policy #0 lag: (min: 3.0, avg: 20.9, max: 39.0) +[2026-07-22 19:48:49,878][43431] Avg episode reward: [(0, '1533.042')] +[2026-07-22 19:48:50,267][50205] Updated weights for policy 0, policy_version 9956 (0.0015) +[2026-07-22 19:48:51,227][50205] Updated weights for policy 0, policy_version 9966 (0.0014) +[2026-07-22 19:48:52,334][50205] Updated weights for policy 0, policy_version 9976 (0.0015) +[2026-07-22 19:48:53,539][50205] Updated weights for policy 0, policy_version 9986 (0.0016) +[2026-07-22 19:48:54,030][50205] Updated weights for policy 0, policy_version 9996 (0.0013) +[2026-07-22 19:48:54,877][43431] Fps is (10 sec: 4915.5, 60 sec: 5324.8, 300 sec: 5401.2). Total num frames: 5120000. Throughput: 0: 5255.6. Samples: 5129098. Policy #0 lag: (min: 3.0, avg: 16.4, max: 31.0) +[2026-07-22 19:48:54,878][43431] Avg episode reward: [(0, '1461.868')] +[2026-07-22 19:48:55,977][50205] Updated weights for policy 0, policy_version 10006 (0.0011) +[2026-07-22 19:48:56,530][50205] Updated weights for policy 0, policy_version 10016 (0.0011) +[2026-07-22 19:48:57,479][50205] Updated weights for policy 0, policy_version 10026 (0.0021) +[2026-07-22 19:48:58,271][50205] Updated weights for policy 0, policy_version 10036 (0.0013) +[2026-07-22 19:48:59,641][50205] Updated weights for policy 0, policy_version 10046 (0.0018) +[2026-07-22 19:48:59,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5290.7, 300 sec: 5401.2). Total num frames: 5146624. Throughput: 0: 5227.8. Samples: 5144074. Policy #0 lag: (min: 3.0, avg: 20.7, max: 39.0) +[2026-07-22 19:48:59,878][43431] Avg episode reward: [(0, '1552.030')] +[2026-07-22 19:49:00,073][50205] Updated weights for policy 0, policy_version 10056 (0.0011) +[2026-07-22 19:49:01,571][50205] Updated weights for policy 0, policy_version 10066 (0.0016) +[2026-07-22 19:49:03,000][50205] Updated weights for policy 0, policy_version 10077 (0.0020) +[2026-07-22 19:49:03,338][50205] Updated weights for policy 0, policy_version 10087 (0.0013) +[2026-07-22 19:49:04,772][50205] Updated weights for policy 0, policy_version 10097 (0.0012) +[2026-07-22 19:49:04,877][43431] Fps is (10 sec: 5120.1, 60 sec: 5222.4, 300 sec: 5387.3). Total num frames: 5171200. Throughput: 0: 5234.6. Samples: 5174516. Policy #0 lag: (min: 3.0, avg: 20.7, max: 39.0) +[2026-07-22 19:49:04,878][43431] Avg episode reward: [(0, '1598.223')] +[2026-07-22 19:49:05,614][50205] Updated weights for policy 0, policy_version 10107 (0.0013) +[2026-07-22 19:49:06,638][50205] Updated weights for policy 0, policy_version 10117 (0.0013) +[2026-07-22 19:49:07,111][50205] Updated weights for policy 0, policy_version 10127 (0.0011) +[2026-07-22 19:49:08,461][50205] Updated weights for policy 0, policy_version 10137 (0.0011) +[2026-07-22 19:49:09,043][50205] Updated weights for policy 0, policy_version 10147 (0.0011) +[2026-07-22 19:49:09,856][50205] Updated weights for policy 0, policy_version 10157 (0.0013) +[2026-07-22 19:49:09,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5256.5, 300 sec: 5394.2). Total num frames: 5199872. Throughput: 0: 5268.7. Samples: 5208300. Policy #0 lag: (min: 3.0, avg: 21.3, max: 41.0) +[2026-07-22 19:49:09,878][43431] Avg episode reward: [(0, '1483.732')] +[2026-07-22 19:49:11,196][50205] Updated weights for policy 0, policy_version 10167 (0.0017) +[2026-07-22 19:49:12,062][50205] Updated weights for policy 0, policy_version 10177 (0.0011) +[2026-07-22 19:49:12,525][50205] Updated weights for policy 0, policy_version 10187 (0.0013) +[2026-07-22 19:49:14,115][50205] Updated weights for policy 0, policy_version 10197 (0.0011) +[2026-07-22 19:49:14,507][50205] Updated weights for policy 0, policy_version 10207 (0.0018) +[2026-07-22 19:49:14,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5324.8, 300 sec: 5394.2). Total num frames: 5228544. Throughput: 0: 5289.0. Samples: 5225188. Policy #0 lag: (min: 3.0, avg: 23.6, max: 47.0) +[2026-07-22 19:49:14,878][43431] Avg episode reward: [(0, '1392.010')] +[2026-07-22 19:49:15,446][50205] Updated weights for policy 0, policy_version 10217 (0.0012) +[2026-07-22 19:49:16,893][50205] Updated weights for policy 0, policy_version 10227 (0.0015) +[2026-07-22 19:49:17,381][50205] Updated weights for policy 0, policy_version 10237 (0.0010) +[2026-07-22 19:49:18,286][50205] Updated weights for policy 0, policy_version 10249 (0.0018) +[2026-07-22 19:49:19,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5290.7, 300 sec: 5380.3). Total num frames: 5251072. Throughput: 0: 5318.9. Samples: 5258814. Policy #0 lag: (min: 3.0, avg: 23.6, max: 47.0) +[2026-07-22 19:49:19,878][43431] Avg episode reward: [(0, '1418.757')] +[2026-07-22 19:49:19,891][50205] Updated weights for policy 0, policy_version 10260 (0.0011) +[2026-07-22 19:49:20,295][50205] Updated weights for policy 0, policy_version 10271 (0.0021) +[2026-07-22 19:49:21,373][50205] Updated weights for policy 0, policy_version 10281 (0.0017) +[2026-07-22 19:49:22,708][50205] Updated weights for policy 0, policy_version 10291 (0.0011) +[2026-07-22 19:49:23,161][50205] Updated weights for policy 0, policy_version 10302 (0.0012) +[2026-07-22 19:49:24,063][50205] Updated weights for policy 0, policy_version 10312 (0.0016) +[2026-07-22 19:49:24,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5358.9, 300 sec: 5387.3). Total num frames: 5281792. Throughput: 0: 5338.0. Samples: 5292160. Policy #0 lag: (min: 2.0, avg: 13.9, max: 37.0) +[2026-07-22 19:49:24,879][43431] Avg episode reward: [(0, '1627.883')] +[2026-07-22 19:49:25,508][50205] Updated weights for policy 0, policy_version 10322 (0.0010) +[2026-07-22 19:49:25,987][50205] Updated weights for policy 0, policy_version 10332 (0.0020) +[2026-07-22 19:49:26,774][50205] Updated weights for policy 0, policy_version 10342 (0.0012) +[2026-07-22 19:49:28,228][50205] Updated weights for policy 0, policy_version 10352 (0.0020) +[2026-07-22 19:49:28,960][50205] Updated weights for policy 0, policy_version 10362 (0.0018) +[2026-07-22 19:49:29,878][43431] Fps is (10 sec: 5734.0, 60 sec: 5324.7, 300 sec: 5387.3). Total num frames: 5308416. Throughput: 0: 5348.3. Samples: 5308926. Policy #0 lag: (min: 2.0, avg: 13.9, max: 37.0) +[2026-07-22 19:49:29,879][43431] Avg episode reward: [(0, '1515.347')] +[2026-07-22 19:49:29,975][50205] Updated weights for policy 0, policy_version 10373 (0.0020) +[2026-07-22 19:49:31,471][50205] Updated weights for policy 0, policy_version 10383 (0.0012) +[2026-07-22 19:49:32,256][50205] Updated weights for policy 0, policy_version 10393 (0.0020) +[2026-07-22 19:49:32,819][50205] Updated weights for policy 0, policy_version 10403 (0.0016) +[2026-07-22 19:49:34,390][50205] Updated weights for policy 0, policy_version 10413 (0.0013) +[2026-07-22 19:49:34,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5324.8, 300 sec: 5387.3). Total num frames: 5335040. Throughput: 0: 5353.3. Samples: 5340174. Policy #0 lag: (min: 3.0, avg: 16.1, max: 39.0) +[2026-07-22 19:49:34,878][43431] Avg episode reward: [(0, '1501.590')] +[2026-07-22 19:49:34,989][50205] Updated weights for policy 0, policy_version 10423 (0.0011) +[2026-07-22 19:49:35,688][50205] Updated weights for policy 0, policy_version 10434 (0.0011) +[2026-07-22 19:49:36,830][50205] Updated weights for policy 0, policy_version 10444 (0.0015) +[2026-07-22 19:49:37,832][50205] Updated weights for policy 0, policy_version 10454 (0.0011) +[2026-07-22 19:49:38,384][50205] Updated weights for policy 0, policy_version 10464 (0.0014) +[2026-07-22 19:49:39,710][50205] Updated weights for policy 0, policy_version 10474 (0.0011) +[2026-07-22 19:49:39,877][43431] Fps is (10 sec: 5530.0, 60 sec: 5358.9, 300 sec: 5380.4). Total num frames: 5363712. Throughput: 0: 5435.6. Samples: 5373698. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 19:49:39,878][43431] Avg episode reward: [(0, '1352.782')] +[2026-07-22 19:49:40,440][50205] Updated weights for policy 0, policy_version 10484 (0.0011) +[2026-07-22 19:49:41,275][50205] Updated weights for policy 0, policy_version 10494 (0.0010) +[2026-07-22 19:49:41,745][50205] Updated weights for policy 0, policy_version 10504 (0.0011) +[2026-07-22 19:49:43,306][50205] Updated weights for policy 0, policy_version 10514 (0.0018) +[2026-07-22 19:49:44,003][50205] Updated weights for policy 0, policy_version 10524 (0.0019) +[2026-07-22 19:49:44,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5359.0, 300 sec: 5387.5). Total num frames: 5392384. Throughput: 0: 5477.8. Samples: 5390574. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 19:49:44,878][43431] Avg episode reward: [(0, '1735.204')] +[2026-07-22 19:49:44,889][49527] Saving new best policy, reward=1735.204! +[2026-07-22 19:49:45,037][50205] Updated weights for policy 0, policy_version 10534 (0.0018) +[2026-07-22 19:49:46,046][50205] Updated weights for policy 0, policy_version 10544 (0.0014) +[2026-07-22 19:49:46,768][50205] Updated weights for policy 0, policy_version 10554 (0.0012) +[2026-07-22 19:49:47,398][50205] Updated weights for policy 0, policy_version 10564 (0.0011) +[2026-07-22 19:49:48,864][50205] Updated weights for policy 0, policy_version 10574 (0.0011) +[2026-07-22 19:49:49,492][50205] Updated weights for policy 0, policy_version 10584 (0.0011) +[2026-07-22 19:49:49,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5427.2, 300 sec: 5394.2). Total num frames: 5421056. Throughput: 0: 5548.2. Samples: 5424186. Policy #0 lag: (min: 1.0, avg: 15.4, max: 29.0) +[2026-07-22 19:49:49,878][43431] Avg episode reward: [(0, '1638.566')] +[2026-07-22 19:49:50,277][50205] Updated weights for policy 0, policy_version 10594 (0.0017) +[2026-07-22 19:49:51,634][50205] Updated weights for policy 0, policy_version 10604 (0.0017) +[2026-07-22 19:49:52,358][50205] Updated weights for policy 0, policy_version 10614 (0.0011) +[2026-07-22 19:49:52,989][50205] Updated weights for policy 0, policy_version 10624 (0.0011) +[2026-07-22 19:49:54,355][50205] Updated weights for policy 0, policy_version 10634 (0.0015) +[2026-07-22 19:49:54,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5461.3, 300 sec: 5387.3). Total num frames: 5447680. Throughput: 0: 5542.7. Samples: 5457720. Policy #0 lag: (min: 1.0, avg: 15.4, max: 29.0) +[2026-07-22 19:49:54,878][43431] Avg episode reward: [(0, '1529.751')] +[2026-07-22 19:49:54,910][50205] Updated weights for policy 0, policy_version 10644 (0.0010) +[2026-07-22 19:49:55,838][50205] Updated weights for policy 0, policy_version 10654 (0.0020) +[2026-07-22 19:49:57,004][50205] Updated weights for policy 0, policy_version 10664 (0.0011) +[2026-07-22 19:49:57,759][50205] Updated weights for policy 0, policy_version 10674 (0.0012) +[2026-07-22 19:49:58,475][50205] Updated weights for policy 0, policy_version 10684 (0.0019) +[2026-07-22 19:49:59,675][50205] Updated weights for policy 0, policy_version 10694 (0.0012) +[2026-07-22 19:49:59,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5394.2). Total num frames: 5476352. Throughput: 0: 5541.9. Samples: 5474574. Policy #0 lag: (min: 0.0, avg: 14.1, max: 32.0) +[2026-07-22 19:49:59,878][43431] Avg episode reward: [(0, '1558.930')] +[2026-07-22 19:50:00,399][50205] Updated weights for policy 0, policy_version 10704 (0.0016) +[2026-07-22 19:50:01,293][50205] Updated weights for policy 0, policy_version 10714 (0.0016) +[2026-07-22 19:50:02,425][50205] Updated weights for policy 0, policy_version 10724 (0.0012) +[2026-07-22 19:50:03,334][50205] Updated weights for policy 0, policy_version 10734 (0.0011) +[2026-07-22 19:50:04,066][50205] Updated weights for policy 0, policy_version 10744 (0.0020) +[2026-07-22 19:50:04,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5563.7, 300 sec: 5394.2). Total num frames: 5505024. Throughput: 0: 5528.7. Samples: 5507606. Policy #0 lag: (min: 0.0, avg: 14.1, max: 32.0) +[2026-07-22 19:50:04,878][43431] Avg episode reward: [(0, '1706.770')] +[2026-07-22 19:50:05,428][50205] Updated weights for policy 0, policy_version 10754 (0.0011) +[2026-07-22 19:50:06,355][50205] Updated weights for policy 0, policy_version 10764 (0.0011) +[2026-07-22 19:50:07,367][50205] Updated weights for policy 0, policy_version 10774 (0.0016) +[2026-07-22 19:50:08,455][50205] Updated weights for policy 0, policy_version 10784 (0.0016) +[2026-07-22 19:50:09,330][50205] Updated weights for policy 0, policy_version 10794 (0.0011) +[2026-07-22 19:50:09,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5495.5, 300 sec: 5387.3). Total num frames: 5529600. Throughput: 0: 5485.7. Samples: 5539016. Policy #0 lag: (min: 3.0, avg: 15.8, max: 35.0) +[2026-07-22 19:50:09,878][43431] Avg episode reward: [(0, '1521.572')] +[2026-07-22 19:50:10,111][50205] Updated weights for policy 0, policy_version 10804 (0.0012) +[2026-07-22 19:50:11,185][50205] Updated weights for policy 0, policy_version 10814 (0.0011) +[2026-07-22 19:50:12,050][50205] Updated weights for policy 0, policy_version 10824 (0.0011) +[2026-07-22 19:50:13,071][50205] Updated weights for policy 0, policy_version 10834 (0.0016) +[2026-07-22 19:50:13,627][50205] Updated weights for policy 0, policy_version 10844 (0.0012) +[2026-07-22 19:50:14,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5461.4, 300 sec: 5380.3). Total num frames: 5556224. Throughput: 0: 5484.3. Samples: 5555716. Policy #0 lag: (min: 0.0, avg: 21.3, max: 44.0) +[2026-07-22 19:50:14,878][43431] Avg episode reward: [(0, '1452.361')] +[2026-07-22 19:50:15,021][50205] Updated weights for policy 0, policy_version 10854 (0.0013) +[2026-07-22 19:50:15,656][50205] Updated weights for policy 0, policy_version 10864 (0.0011) +[2026-07-22 19:50:16,345][50205] Updated weights for policy 0, policy_version 10874 (0.0011) +[2026-07-22 19:50:17,572][50205] Updated weights for policy 0, policy_version 10884 (0.0020) +[2026-07-22 19:50:18,376][50205] Updated weights for policy 0, policy_version 10894 (0.0015) +[2026-07-22 19:50:19,105][50205] Updated weights for policy 0, policy_version 10904 (0.0017) +[2026-07-22 19:50:19,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5563.7, 300 sec: 5387.3). Total num frames: 5584896. Throughput: 0: 5535.8. Samples: 5589284. Policy #0 lag: (min: 0.0, avg: 21.3, max: 44.0) +[2026-07-22 19:50:19,878][43431] Avg episode reward: [(0, '1608.397')] +[2026-07-22 19:50:20,617][50205] Updated weights for policy 0, policy_version 10914 (0.0015) +[2026-07-22 19:50:21,032][50205] Updated weights for policy 0, policy_version 10924 (0.0011) +[2026-07-22 19:50:21,961][50205] Updated weights for policy 0, policy_version 10934 (0.0016) +[2026-07-22 19:50:22,925][50205] Updated weights for policy 0, policy_version 10944 (0.0012) +[2026-07-22 19:50:23,850][50205] Updated weights for policy 0, policy_version 10954 (0.0012) +[2026-07-22 19:50:24,676][50205] Updated weights for policy 0, policy_version 10964 (0.0017) +[2026-07-22 19:50:24,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5529.6, 300 sec: 5394.2). Total num frames: 5613568. Throughput: 0: 5538.9. Samples: 5622950. Policy #0 lag: (min: 3.0, avg: 20.0, max: 39.0) +[2026-07-22 19:50:24,878][43431] Avg episode reward: [(0, '1682.557')] +[2026-07-22 19:50:25,947][50205] Updated weights for policy 0, policy_version 10974 (0.0016) +[2026-07-22 19:50:26,485][50205] Updated weights for policy 0, policy_version 10984 (0.0020) +[2026-07-22 19:50:27,628][50205] Updated weights for policy 0, policy_version 10994 (0.0015) +[2026-07-22 19:50:28,316][50205] Updated weights for policy 0, policy_version 11004 (0.0011) +[2026-07-22 19:50:29,335][50205] Updated weights for policy 0, policy_version 11014 (0.0017) +[2026-07-22 19:50:29,878][43431] Fps is (10 sec: 5734.2, 60 sec: 5563.8, 300 sec: 5394.2). Total num frames: 5642240. Throughput: 0: 5536.5. Samples: 5639720. Policy #0 lag: (min: 3.0, avg: 20.0, max: 39.0) +[2026-07-22 19:50:29,878][43431] Avg episode reward: [(0, '1637.401')] +[2026-07-22 19:50:30,144][50205] Updated weights for policy 0, policy_version 11024 (0.0015) +[2026-07-22 19:50:31,316][50205] Updated weights for policy 0, policy_version 11034 (0.0011) +[2026-07-22 19:50:32,004][50205] Updated weights for policy 0, policy_version 11044 (0.0014) +[2026-07-22 19:50:33,248][50205] Updated weights for policy 0, policy_version 11054 (0.0012) +[2026-07-22 19:50:33,878][50205] Updated weights for policy 0, policy_version 11064 (0.0015) +[2026-07-22 19:50:34,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5563.7, 300 sec: 5387.3). Total num frames: 5668864. Throughput: 0: 5539.8. Samples: 5673476. Policy #0 lag: (min: 3.0, avg: 19.9, max: 43.0) +[2026-07-22 19:50:34,878][43431] Avg episode reward: [(0, '1438.401')] +[2026-07-22 19:50:34,930][50205] Updated weights for policy 0, policy_version 11074 (0.0019) +[2026-07-22 19:50:35,553][50205] Updated weights for policy 0, policy_version 11084 (0.0015) +[2026-07-22 19:50:36,873][50205] Updated weights for policy 0, policy_version 11096 (0.0011) +[2026-07-22 19:50:37,815][50205] Updated weights for policy 0, policy_version 11106 (0.0011) +[2026-07-22 19:50:38,680][50205] Updated weights for policy 0, policy_version 11116 (0.0021) +[2026-07-22 19:50:39,475][50205] Updated weights for policy 0, policy_version 11126 (0.0018) +[2026-07-22 19:50:39,877][43431] Fps is (10 sec: 5529.8, 60 sec: 5563.7, 300 sec: 5394.2). Total num frames: 5697536. Throughput: 0: 5538.8. Samples: 5706966. Policy #0 lag: (min: 3.0, avg: 19.9, max: 43.0) +[2026-07-22 19:50:39,878][43431] Avg episode reward: [(0, '1717.282')] +[2026-07-22 19:50:40,597][50205] Updated weights for policy 0, policy_version 11136 (0.0015) +[2026-07-22 19:50:41,524][50205] Updated weights for policy 0, policy_version 11146 (0.0010) +[2026-07-22 19:50:42,324][50205] Updated weights for policy 0, policy_version 11156 (0.0019) +[2026-07-22 19:50:43,603][50205] Updated weights for policy 0, policy_version 11166 (0.0011) +[2026-07-22 19:50:44,508][50205] Updated weights for policy 0, policy_version 11176 (0.0016) +[2026-07-22 19:50:44,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5529.6, 300 sec: 5394.2). Total num frames: 5724160. Throughput: 0: 5511.9. Samples: 5722608. Policy #0 lag: (min: 1.0, avg: 13.6, max: 33.0) +[2026-07-22 19:50:44,878][43431] Avg episode reward: [(0, '1538.614')] +[2026-07-22 19:50:45,546][50205] Updated weights for policy 0, policy_version 11186 (0.0028) +[2026-07-22 19:50:46,481][50205] Updated weights for policy 0, policy_version 11196 (0.0015) +[2026-07-22 19:50:47,528][50205] Updated weights for policy 0, policy_version 11206 (0.0015) +[2026-07-22 19:50:48,059][50205] Updated weights for policy 0, policy_version 11216 (0.0015) +[2026-07-22 19:50:49,378][50205] Updated weights for policy 0, policy_version 11226 (0.0011) +[2026-07-22 19:50:49,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5495.5, 300 sec: 5387.3). Total num frames: 5750784. Throughput: 0: 5498.5. Samples: 5755038. Policy #0 lag: (min: 3.0, avg: 17.9, max: 35.0) +[2026-07-22 19:50:49,878][43431] Avg episode reward: [(0, '1515.126')] +[2026-07-22 19:50:50,057][50205] Updated weights for policy 0, policy_version 11236 (0.0015) +[2026-07-22 19:50:51,026][50205] Updated weights for policy 0, policy_version 11246 (0.0014) +[2026-07-22 19:50:51,740][50205] Updated weights for policy 0, policy_version 11256 (0.0015) +[2026-07-22 19:50:52,845][50205] Updated weights for policy 0, policy_version 11266 (0.0011) +[2026-07-22 19:50:53,729][50205] Updated weights for policy 0, policy_version 11276 (0.0011) +[2026-07-22 19:50:54,878][43431] Fps is (10 sec: 5324.6, 60 sec: 5495.4, 300 sec: 5394.2). Total num frames: 5777408. Throughput: 0: 5544.8. Samples: 5788536. Policy #0 lag: (min: 3.0, avg: 17.9, max: 35.0) +[2026-07-22 19:50:54,878][43431] Avg episode reward: [(0, '1600.547')] +[2026-07-22 19:50:54,975][50205] Updated weights for policy 0, policy_version 11286 (0.0014) +[2026-07-22 19:50:55,547][50205] Updated weights for policy 0, policy_version 11296 (0.0013) +[2026-07-22 19:50:56,405][50205] Updated weights for policy 0, policy_version 11306 (0.0011) +[2026-07-22 19:50:57,403][50205] Updated weights for policy 0, policy_version 11316 (0.0020) +[2026-07-22 19:50:58,580][50205] Updated weights for policy 0, policy_version 11326 (0.0011) +[2026-07-22 19:50:58,977][50205] Updated weights for policy 0, policy_version 11336 (0.0021) +[2026-07-22 19:50:59,878][43431] Fps is (10 sec: 5734.0, 60 sec: 5529.5, 300 sec: 5401.2). Total num frames: 5808128. Throughput: 0: 5550.0. Samples: 5805468. Policy #0 lag: (min: 3.0, avg: 15.9, max: 35.0) +[2026-07-22 19:50:59,879][43431] Avg episode reward: [(0, '1628.951')] +[2026-07-22 19:51:00,460][50205] Updated weights for policy 0, policy_version 11346 (0.0011) +[2026-07-22 19:51:01,027][50205] Updated weights for policy 0, policy_version 11356 (0.0016) +[2026-07-22 19:51:01,821][50205] Updated weights for policy 0, policy_version 11366 (0.0011) +[2026-07-22 19:51:03,617][50205] Updated weights for policy 0, policy_version 11377 (0.0011) +[2026-07-22 19:51:04,430][50205] Updated weights for policy 0, policy_version 11387 (0.0021) +[2026-07-22 19:51:04,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5461.3, 300 sec: 5387.3). Total num frames: 5832704. Throughput: 0: 5502.8. Samples: 5836912. Policy #0 lag: (min: 3.0, avg: 15.9, max: 35.0) +[2026-07-22 19:51:04,878][43431] Avg episode reward: [(0, '1531.301')] +[2026-07-22 19:51:05,200][50205] Updated weights for policy 0, policy_version 11400 (0.0016) +[2026-07-22 19:51:06,634][50205] Updated weights for policy 0, policy_version 11410 (0.0019) +[2026-07-22 19:51:07,418][50205] Updated weights for policy 0, policy_version 11420 (0.0021) +[2026-07-22 19:51:08,235][50205] Updated weights for policy 0, policy_version 11430 (0.0012) +[2026-07-22 19:51:08,998][50205] Updated weights for policy 0, policy_version 11440 (0.0016) +[2026-07-22 19:51:09,877][43431] Fps is (10 sec: 5120.2, 60 sec: 5495.4, 300 sec: 5387.3). Total num frames: 5859328. Throughput: 0: 5499.4. Samples: 5870426. Policy #0 lag: (min: 1.0, avg: 15.6, max: 33.0) +[2026-07-22 19:51:09,878][43431] Avg episode reward: [(0, '1556.600')] +[2026-07-22 19:51:10,120][50205] Updated weights for policy 0, policy_version 11450 (0.0011) +[2026-07-22 19:51:10,755][50205] Updated weights for policy 0, policy_version 11460 (0.0012) +[2026-07-22 19:51:11,992][50205] Updated weights for policy 0, policy_version 11470 (0.0010) +[2026-07-22 19:51:12,887][50205] Updated weights for policy 0, policy_version 11480 (0.0011) +[2026-07-22 19:51:13,497][50205] Updated weights for policy 0, policy_version 11490 (0.0021) +[2026-07-22 19:51:14,634][50205] Updated weights for policy 0, policy_version 11500 (0.0011) +[2026-07-22 19:51:14,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5529.6, 300 sec: 5387.3). Total num frames: 5888000. Throughput: 0: 5499.3. Samples: 5887186. Policy #0 lag: (min: 1.0, avg: 15.6, max: 33.0) +[2026-07-22 19:51:14,878][43431] Avg episode reward: [(0, '1573.824')] +[2026-07-22 19:51:15,809][50205] Updated weights for policy 0, policy_version 11510 (0.0010) +[2026-07-22 19:51:16,240][50205] Updated weights for policy 0, policy_version 11520 (0.0016) +[2026-07-22 19:51:17,587][50205] Updated weights for policy 0, policy_version 11530 (0.0016) +[2026-07-22 19:51:18,870][50205] Updated weights for policy 0, policy_version 11540 (0.0011) +[2026-07-22 19:51:19,584][50205] Updated weights for policy 0, policy_version 11550 (0.0016) +[2026-07-22 19:51:19,878][43431] Fps is (10 sec: 5529.4, 60 sec: 5495.4, 300 sec: 5394.2). Total num frames: 5914624. Throughput: 0: 5446.1. Samples: 5918554. Policy #0 lag: (min: 3.0, avg: 17.9, max: 39.0) +[2026-07-22 19:51:19,879][43431] Avg episode reward: [(0, '1639.994')] +[2026-07-22 19:51:20,407][50205] Updated weights for policy 0, policy_version 11560 (0.0021) +[2026-07-22 19:51:21,873][50205] Updated weights for policy 0, policy_version 11570 (0.0011) +[2026-07-22 19:51:22,440][50205] Updated weights for policy 0, policy_version 11580 (0.0023) +[2026-07-22 19:51:23,274][50205] Updated weights for policy 0, policy_version 11590 (0.0012) +[2026-07-22 19:51:24,640][50205] Updated weights for policy 0, policy_version 11600 (0.0012) +[2026-07-22 19:51:24,879][43431] Fps is (10 sec: 5119.3, 60 sec: 5427.1, 300 sec: 5380.3). Total num frames: 5939200. Throughput: 0: 5407.5. Samples: 5950312. Policy #0 lag: (min: 3.0, avg: 18.2, max: 39.0) +[2026-07-22 19:51:24,880][43431] Avg episode reward: [(0, '1524.589')] +[2026-07-22 19:51:25,375][50205] Updated weights for policy 0, policy_version 11610 (0.0011) +[2026-07-22 19:51:26,074][50205] Updated weights for policy 0, policy_version 11620 (0.0011) +[2026-07-22 19:51:27,680][50205] Updated weights for policy 0, policy_version 11630 (0.0011) +[2026-07-22 19:51:28,245][50205] Updated weights for policy 0, policy_version 11640 (0.0013) +[2026-07-22 19:51:28,910][50205] Updated weights for policy 0, policy_version 11650 (0.0011) +[2026-07-22 19:51:29,877][43431] Fps is (10 sec: 5325.1, 60 sec: 5427.2, 300 sec: 5387.3). Total num frames: 5967872. Throughput: 0: 5423.1. Samples: 5966650. Policy #0 lag: (min: 3.0, avg: 18.2, max: 39.0) +[2026-07-22 19:51:29,878][43431] Avg episode reward: [(0, '1672.440')] +[2026-07-22 19:51:30,467][50205] Updated weights for policy 0, policy_version 11660 (0.0014) +[2026-07-22 19:51:31,212][50205] Updated weights for policy 0, policy_version 11670 (0.0012) +[2026-07-22 19:51:31,715][50205] Updated weights for policy 0, policy_version 11680 (0.0011) +[2026-07-22 19:51:33,319][50205] Updated weights for policy 0, policy_version 11690 (0.0012) +[2026-07-22 19:51:34,416][50205] Updated weights for policy 0, policy_version 11701 (0.0010) +[2026-07-22 19:51:34,747][50205] Updated weights for policy 0, policy_version 11711 (0.0011) +[2026-07-22 19:51:34,877][43431] Fps is (10 sec: 5735.3, 60 sec: 5461.3, 300 sec: 5394.2). Total num frames: 5996544. Throughput: 0: 5410.0. Samples: 5998488. Policy #0 lag: (min: 1.0, avg: 14.0, max: 36.0) +[2026-07-22 19:51:34,878][43431] Avg episode reward: [(0, '1639.702')] +[2026-07-22 19:51:36,384][50205] Updated weights for policy 0, policy_version 11721 (0.0014) +[2026-07-22 19:51:36,928][50205] Updated weights for policy 0, policy_version 11731 (0.0011) +[2026-07-22 19:51:37,923][50205] Updated weights for policy 0, policy_version 11741 (0.0019) +[2026-07-22 19:51:39,045][50205] Updated weights for policy 0, policy_version 11751 (0.0017) +[2026-07-22 19:51:39,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5393.1, 300 sec: 5387.3). Total num frames: 6021120. Throughput: 0: 5374.3. Samples: 6030378. Policy #0 lag: (min: 1.0, avg: 14.0, max: 36.0) +[2026-07-22 19:51:39,878][43431] Avg episode reward: [(0, '1501.356')] +[2026-07-22 19:51:40,063][50205] Updated weights for policy 0, policy_version 11761 (0.0017) +[2026-07-22 19:51:40,591][50205] Updated weights for policy 0, policy_version 11771 (0.0013) +[2026-07-22 19:51:42,270][50205] Updated weights for policy 0, policy_version 11781 (0.0015) +[2026-07-22 19:51:42,844][50205] Updated weights for policy 0, policy_version 11791 (0.0014) +[2026-07-22 19:51:43,598][50205] Updated weights for policy 0, policy_version 11801 (0.0016) +[2026-07-22 19:51:44,833][50205] Updated weights for policy 0, policy_version 11811 (0.0017) +[2026-07-22 19:51:44,877][43431] Fps is (10 sec: 5119.9, 60 sec: 5393.0, 300 sec: 5387.3). Total num frames: 6047744. Throughput: 0: 5352.0. Samples: 6046308. Policy #0 lag: (min: 3.0, avg: 18.9, max: 39.0) +[2026-07-22 19:51:44,878][43431] Avg episode reward: [(0, '1542.775')] +[2026-07-22 19:51:45,845][50205] Updated weights for policy 0, policy_version 11821 (0.0014) +[2026-07-22 19:51:46,460][49527] Signal inference workers to stop experience collection... (200 times) +[2026-07-22 19:51:46,477][50205] InferenceWorker_p0-w0: stopping experience collection (200 times) +[2026-07-22 19:51:46,507][49527] Signal inference workers to resume experience collection... (200 times) +[2026-07-22 19:51:46,507][50205] InferenceWorker_p0-w0: resuming experience collection (200 times) +[2026-07-22 19:51:46,616][50205] Updated weights for policy 0, policy_version 11832 (0.0012) +[2026-07-22 19:51:47,743][50205] Updated weights for policy 0, policy_version 11842 (0.0012) +[2026-07-22 19:51:48,756][50205] Updated weights for policy 0, policy_version 11852 (0.0012) +[2026-07-22 19:51:49,727][50205] Updated weights for policy 0, policy_version 11862 (0.0014) +[2026-07-22 19:51:49,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5393.1, 300 sec: 5387.3). Total num frames: 6074368. Throughput: 0: 5355.5. Samples: 6077908. Policy #0 lag: (min: 3.0, avg: 18.9, max: 39.0) +[2026-07-22 19:51:49,878][43431] Avg episode reward: [(0, '1680.005')] +[2026-07-22 19:51:50,680][50205] Updated weights for policy 0, policy_version 11872 (0.0019) +[2026-07-22 19:51:51,785][50205] Updated weights for policy 0, policy_version 11882 (0.0023) +[2026-07-22 19:51:52,523][50205] Updated weights for policy 0, policy_version 11892 (0.0010) +[2026-07-22 19:51:54,043][50205] Updated weights for policy 0, policy_version 11902 (0.0011) +[2026-07-22 19:51:54,720][50205] Updated weights for policy 0, policy_version 11912 (0.0011) +[2026-07-22 19:51:54,878][43431] Fps is (10 sec: 5119.8, 60 sec: 5358.9, 300 sec: 5380.3). Total num frames: 6098944. Throughput: 0: 5283.3. Samples: 6108176. Policy #0 lag: (min: 3.0, avg: 18.2, max: 39.0) +[2026-07-22 19:51:54,879][43431] Avg episode reward: [(0, '1500.491')] +[2026-07-22 19:51:55,890][50205] Updated weights for policy 0, policy_version 11922 (0.0014) +[2026-07-22 19:51:56,797][50205] Updated weights for policy 0, policy_version 11932 (0.0016) +[2026-07-22 19:51:57,977][50205] Updated weights for policy 0, policy_version 11942 (0.0012) +[2026-07-22 19:51:59,022][50205] Updated weights for policy 0, policy_version 11952 (0.0023) +[2026-07-22 19:51:59,843][50205] Updated weights for policy 0, policy_version 11962 (0.0014) +[2026-07-22 19:51:59,877][43431] Fps is (10 sec: 4915.2, 60 sec: 5256.6, 300 sec: 5380.3). Total num frames: 6123520. Throughput: 0: 5235.8. Samples: 6122796. Policy #0 lag: (min: 3.0, avg: 18.2, max: 39.0) +[2026-07-22 19:51:59,878][43431] Avg episode reward: [(0, '1639.572')] +[2026-07-22 19:52:00,985][50205] Updated weights for policy 0, policy_version 11972 (0.0013) +[2026-07-22 19:52:01,992][50205] Updated weights for policy 0, policy_version 11982 (0.0016) +[2026-07-22 19:52:02,951][50205] Updated weights for policy 0, policy_version 11992 (0.0011) +[2026-07-22 19:52:03,999][50205] Updated weights for policy 0, policy_version 12002 (0.0010) +[2026-07-22 19:52:04,782][50205] Updated weights for policy 0, policy_version 12012 (0.0021) +[2026-07-22 19:52:04,877][43431] Fps is (10 sec: 5120.4, 60 sec: 5290.7, 300 sec: 5387.3). Total num frames: 6150144. Throughput: 0: 5229.2. Samples: 6153866. Policy #0 lag: (min: 3.0, avg: 17.5, max: 35.0) +[2026-07-22 19:52:04,878][43431] Avg episode reward: [(0, '1584.443')] +[2026-07-22 19:52:05,959][50205] Updated weights for policy 0, policy_version 12022 (0.0012) +[2026-07-22 19:52:06,780][50205] Updated weights for policy 0, policy_version 12032 (0.0016) +[2026-07-22 19:52:07,720][50205] Updated weights for policy 0, policy_version 12042 (0.0011) +[2026-07-22 19:52:08,833][50205] Updated weights for policy 0, policy_version 12052 (0.0016) +[2026-07-22 19:52:09,822][50205] Updated weights for policy 0, policy_version 12062 (0.0016) +[2026-07-22 19:52:09,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5290.7, 300 sec: 5380.3). Total num frames: 6176768. Throughput: 0: 5230.1. Samples: 6185658. Policy #0 lag: (min: 3.0, avg: 17.5, max: 35.0) +[2026-07-22 19:52:09,878][43431] Avg episode reward: [(0, '1666.341')] +[2026-07-22 19:52:10,531][50205] Updated weights for policy 0, policy_version 12072 (0.0017) +[2026-07-22 19:52:11,489][50205] Updated weights for policy 0, policy_version 12082 (0.0014) +[2026-07-22 19:52:12,697][50205] Updated weights for policy 0, policy_version 12092 (0.0011) +[2026-07-22 19:52:13,605][50205] Updated weights for policy 0, policy_version 12102 (0.0011) +[2026-07-22 19:52:14,348][50205] Updated weights for policy 0, policy_version 12112 (0.0015) +[2026-07-22 19:52:14,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5256.6, 300 sec: 5380.3). Total num frames: 6203392. Throughput: 0: 5222.2. Samples: 6201650. Policy #0 lag: (min: 6.0, avg: 22.5, max: 46.0) +[2026-07-22 19:52:14,878][43431] Avg episode reward: [(0, '1474.936')] +[2026-07-22 19:52:15,744][50205] Updated weights for policy 0, policy_version 12122 (0.0020) +[2026-07-22 19:52:16,262][50205] Updated weights for policy 0, policy_version 12132 (0.0012) +[2026-07-22 19:52:17,315][50205] Updated weights for policy 0, policy_version 12142 (0.0012) +[2026-07-22 19:52:18,182][50205] Updated weights for policy 0, policy_version 12152 (0.0012) +[2026-07-22 19:52:19,878][43431] Fps is (10 sec: 5119.7, 60 sec: 5222.4, 300 sec: 5373.4). Total num frames: 6227968. Throughput: 0: 5215.2. Samples: 6233176. Policy #0 lag: (min: 6.0, avg: 22.5, max: 46.0) +[2026-07-22 19:52:19,879][43431] Avg episode reward: [(0, '1624.087')] +[2026-07-22 19:52:19,910][50205] Updated weights for policy 0, policy_version 12165 (0.0020) +[2026-07-22 19:52:20,426][50205] Updated weights for policy 0, policy_version 12175 (0.0011) +[2026-07-22 19:52:21,694][50205] Updated weights for policy 0, policy_version 12185 (0.0015) +[2026-07-22 19:52:22,591][50205] Updated weights for policy 0, policy_version 12195 (0.0013) +[2026-07-22 19:52:23,535][50205] Updated weights for policy 0, policy_version 12205 (0.0016) +[2026-07-22 19:52:24,452][50205] Updated weights for policy 0, policy_version 12215 (0.0011) +[2026-07-22 19:52:24,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5256.7, 300 sec: 5366.5). Total num frames: 6254592. Throughput: 0: 5217.6. Samples: 6265172. Policy #0 lag: (min: 3.0, avg: 18.7, max: 35.0) +[2026-07-22 19:52:24,878][43431] Avg episode reward: [(0, '1484.578')] +[2026-07-22 19:52:25,601][50205] Updated weights for policy 0, policy_version 12225 (0.0016) +[2026-07-22 19:52:26,447][50205] Updated weights for policy 0, policy_version 12235 (0.0011) +[2026-07-22 19:52:27,499][50205] Updated weights for policy 0, policy_version 12245 (0.0012) +[2026-07-22 19:52:28,283][50205] Updated weights for policy 0, policy_version 12255 (0.0012) +[2026-07-22 19:52:29,575][50205] Updated weights for policy 0, policy_version 12265 (0.0012) +[2026-07-22 19:52:29,877][43431] Fps is (10 sec: 5325.0, 60 sec: 5222.4, 300 sec: 5373.4). Total num frames: 6281216. Throughput: 0: 5216.5. Samples: 6281052. Policy #0 lag: (min: 0.0, avg: 14.9, max: 32.0) +[2026-07-22 19:52:29,878][43431] Avg episode reward: [(0, '1686.199')] +[2026-07-22 19:52:30,318][50205] Updated weights for policy 0, policy_version 12275 (0.0011) +[2026-07-22 19:52:31,535][50205] Updated weights for policy 0, policy_version 12285 (0.0013) +[2026-07-22 19:52:32,663][50205] Updated weights for policy 0, policy_version 12295 (0.0011) +[2026-07-22 19:52:33,721][50205] Updated weights for policy 0, policy_version 12305 (0.0011) +[2026-07-22 19:52:34,760][50205] Updated weights for policy 0, policy_version 12315 (0.0016) +[2026-07-22 19:52:34,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5154.1, 300 sec: 5373.4). Total num frames: 6305792. Throughput: 0: 5159.6. Samples: 6310090. Policy #0 lag: (min: 0.0, avg: 14.9, max: 32.0) +[2026-07-22 19:52:34,878][43431] Avg episode reward: [(0, '1577.658')] +[2026-07-22 19:52:35,641][50205] Updated weights for policy 0, policy_version 12325 (0.0016) +[2026-07-22 19:52:36,646][50205] Updated weights for policy 0, policy_version 12335 (0.0012) +[2026-07-22 19:52:37,622][50205] Updated weights for policy 0, policy_version 12345 (0.0017) +[2026-07-22 19:52:38,438][50205] Updated weights for policy 0, policy_version 12355 (0.0011) +[2026-07-22 19:52:39,648][50205] Updated weights for policy 0, policy_version 12365 (0.0020) +[2026-07-22 19:52:39,878][43431] Fps is (10 sec: 5119.6, 60 sec: 5188.2, 300 sec: 5373.4). Total num frames: 6332416. Throughput: 0: 5193.9. Samples: 6341904. Policy #0 lag: (min: 3.0, avg: 19.5, max: 35.0) +[2026-07-22 19:52:39,879][43431] Avg episode reward: [(0, '1571.933')] +[2026-07-22 19:52:39,936][49527] Saving results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/checkpoint_p0/checkpoint_000012368_6332416.pth... +[2026-07-22 19:52:40,540][50205] Updated weights for policy 0, policy_version 12375 (0.0018) +[2026-07-22 19:52:41,464][50205] Updated weights for policy 0, policy_version 12385 (0.0015) +[2026-07-22 19:52:42,131][50205] Updated weights for policy 0, policy_version 12395 (0.0013) +[2026-07-22 19:52:43,445][50205] Updated weights for policy 0, policy_version 12405 (0.0012) +[2026-07-22 19:52:44,256][50205] Updated weights for policy 0, policy_version 12415 (0.0012) +[2026-07-22 19:52:44,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5154.2, 300 sec: 5359.5). Total num frames: 6356992. Throughput: 0: 5226.1. Samples: 6357970. Policy #0 lag: (min: 3.0, avg: 19.5, max: 35.0) +[2026-07-22 19:52:44,878][43431] Avg episode reward: [(0, '1580.900')] +[2026-07-22 19:52:45,926][50205] Updated weights for policy 0, policy_version 12430 (0.0011) +[2026-07-22 19:52:46,895][50205] Updated weights for policy 0, policy_version 12440 (0.0011) +[2026-07-22 19:52:47,746][50205] Updated weights for policy 0, policy_version 12450 (0.0011) +[2026-07-22 19:52:48,633][50205] Updated weights for policy 0, policy_version 12460 (0.0027) +[2026-07-22 19:52:49,742][50205] Updated weights for policy 0, policy_version 12470 (0.0016) +[2026-07-22 19:52:49,877][43431] Fps is (10 sec: 5325.3, 60 sec: 5188.3, 300 sec: 5373.4). Total num frames: 6385664. Throughput: 0: 5235.2. Samples: 6389450. Policy #0 lag: (min: 3.0, avg: 19.6, max: 35.0) +[2026-07-22 19:52:49,878][43431] Avg episode reward: [(0, '1506.632')] +[2026-07-22 19:52:50,558][50205] Updated weights for policy 0, policy_version 12480 (0.0012) +[2026-07-22 19:52:51,647][50205] Updated weights for policy 0, policy_version 12490 (0.0017) +[2026-07-22 19:52:52,494][50205] Updated weights for policy 0, policy_version 12500 (0.0011) +[2026-07-22 19:52:53,450][50205] Updated weights for policy 0, policy_version 12510 (0.0016) +[2026-07-22 19:52:54,223][50205] Updated weights for policy 0, policy_version 12520 (0.0014) +[2026-07-22 19:52:54,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5222.5, 300 sec: 5366.5). Total num frames: 6412288. Throughput: 0: 5236.1. Samples: 6421280. Policy #0 lag: (min: 3.0, avg: 19.6, max: 35.0) +[2026-07-22 19:52:54,878][43431] Avg episode reward: [(0, '1467.055')] +[2026-07-22 19:52:55,656][50205] Updated weights for policy 0, policy_version 12530 (0.0011) +[2026-07-22 19:52:56,375][50205] Updated weights for policy 0, policy_version 12540 (0.0011) +[2026-07-22 19:52:57,148][50205] Updated weights for policy 0, policy_version 12550 (0.0010) +[2026-07-22 19:52:58,362][50205] Updated weights for policy 0, policy_version 12560 (0.0017) +[2026-07-22 19:52:59,609][50205] Updated weights for policy 0, policy_version 12570 (0.0011) +[2026-07-22 19:52:59,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5256.5, 300 sec: 5359.5). Total num frames: 6438912. Throughput: 0: 5235.5. Samples: 6437248. Policy #0 lag: (min: 3.0, avg: 21.3, max: 39.0) +[2026-07-22 19:52:59,878][43431] Avg episode reward: [(0, '1615.264')] +[2026-07-22 19:52:59,964][50205] Updated weights for policy 0, policy_version 12580 (0.0020) +[2026-07-22 19:53:01,149][50205] Updated weights for policy 0, policy_version 12590 (0.0012) +[2026-07-22 19:53:02,519][50205] Updated weights for policy 0, policy_version 12600 (0.0021) +[2026-07-22 19:53:03,322][50205] Updated weights for policy 0, policy_version 12610 (0.0012) +[2026-07-22 19:53:04,157][50205] Updated weights for policy 0, policy_version 12620 (0.0019) +[2026-07-22 19:53:04,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5222.4, 300 sec: 5352.6). Total num frames: 6463488. Throughput: 0: 5213.6. Samples: 6467784. Policy #0 lag: (min: 3.0, avg: 21.3, max: 39.0) +[2026-07-22 19:53:04,878][43431] Avg episode reward: [(0, '1635.668')] +[2026-07-22 19:53:05,610][50205] Updated weights for policy 0, policy_version 12630 (0.0015) +[2026-07-22 19:53:06,173][50205] Updated weights for policy 0, policy_version 12640 (0.0012) +[2026-07-22 19:53:07,285][50205] Updated weights for policy 0, policy_version 12650 (0.0014) +[2026-07-22 19:53:08,673][50205] Updated weights for policy 0, policy_version 12661 (0.0012) +[2026-07-22 19:53:09,436][50205] Updated weights for policy 0, policy_version 12671 (0.0011) +[2026-07-22 19:53:09,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5222.4, 300 sec: 5359.5). Total num frames: 6490112. Throughput: 0: 5176.6. Samples: 6498118. Policy #0 lag: (min: 3.0, avg: 20.1, max: 39.0) +[2026-07-22 19:53:09,878][43431] Avg episode reward: [(0, '1672.901')] +[2026-07-22 19:53:10,593][50205] Updated weights for policy 0, policy_version 12681 (0.0010) +[2026-07-22 19:53:11,756][50205] Updated weights for policy 0, policy_version 12691 (0.0011) +[2026-07-22 19:53:12,643][50205] Updated weights for policy 0, policy_version 12701 (0.0013) +[2026-07-22 19:53:13,262][50205] Updated weights for policy 0, policy_version 12711 (0.0011) +[2026-07-22 19:53:14,879][43431] Fps is (10 sec: 4914.4, 60 sec: 5154.0, 300 sec: 5352.5). Total num frames: 6512640. Throughput: 0: 5157.6. Samples: 6513150. Policy #0 lag: (min: 3.0, avg: 20.1, max: 39.0) +[2026-07-22 19:53:14,880][43431] Avg episode reward: [(0, '1556.858')] +[2026-07-22 19:53:15,182][50205] Updated weights for policy 0, policy_version 12721 (0.0016) +[2026-07-22 19:53:15,545][50205] Updated weights for policy 0, policy_version 12732 (0.0015) +[2026-07-22 19:53:16,415][50205] Updated weights for policy 0, policy_version 12742 (0.0015) +[2026-07-22 19:53:17,675][50205] Updated weights for policy 0, policy_version 12752 (0.0018) +[2026-07-22 19:53:18,493][50205] Updated weights for policy 0, policy_version 12762 (0.0011) +[2026-07-22 19:53:19,424][50205] Updated weights for policy 0, policy_version 12772 (0.0012) +[2026-07-22 19:53:19,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5222.4, 300 sec: 5359.5). Total num frames: 6541312. Throughput: 0: 5219.9. Samples: 6544984. Policy #0 lag: (min: 1.0, avg: 19.7, max: 35.0) +[2026-07-22 19:53:19,878][43431] Avg episode reward: [(0, '1567.374')] +[2026-07-22 19:53:20,445][50205] Updated weights for policy 0, policy_version 12782 (0.0014) +[2026-07-22 19:53:21,272][50205] Updated weights for policy 0, policy_version 12792 (0.0011) +[2026-07-22 19:53:22,429][50205] Updated weights for policy 0, policy_version 12802 (0.0011) +[2026-07-22 19:53:23,304][50205] Updated weights for policy 0, policy_version 12812 (0.0017) +[2026-07-22 19:53:24,208][50205] Updated weights for policy 0, policy_version 12822 (0.0016) +[2026-07-22 19:53:24,877][43431] Fps is (10 sec: 5530.5, 60 sec: 5222.4, 300 sec: 5352.6). Total num frames: 6567936. Throughput: 0: 5227.3. Samples: 6577128. Policy #0 lag: (min: 1.0, avg: 19.7, max: 35.0) +[2026-07-22 19:53:24,878][43431] Avg episode reward: [(0, '1665.443')] +[2026-07-22 19:53:24,972][50205] Updated weights for policy 0, policy_version 12832 (0.0011) +[2026-07-22 19:53:26,434][50205] Updated weights for policy 0, policy_version 12842 (0.0012) +[2026-07-22 19:53:26,987][50205] Updated weights for policy 0, policy_version 12852 (0.0011) +[2026-07-22 19:53:28,023][50205] Updated weights for policy 0, policy_version 12862 (0.0013) +[2026-07-22 19:53:29,097][50205] Updated weights for policy 0, policy_version 12872 (0.0020) +[2026-07-22 19:53:29,878][43431] Fps is (10 sec: 5119.8, 60 sec: 5188.2, 300 sec: 5345.6). Total num frames: 6592512. Throughput: 0: 5224.4. Samples: 6593072. Policy #0 lag: (min: 3.0, avg: 15.8, max: 35.0) +[2026-07-22 19:53:29,878][43431] Avg episode reward: [(0, '1513.521')] +[2026-07-22 19:53:30,140][50205] Updated weights for policy 0, policy_version 12882 (0.0012) +[2026-07-22 19:53:30,915][50205] Updated weights for policy 0, policy_version 12892 (0.0011) +[2026-07-22 19:53:32,077][50205] Updated weights for policy 0, policy_version 12902 (0.0011) +[2026-07-22 19:53:32,980][50205] Updated weights for policy 0, policy_version 12912 (0.0011) +[2026-07-22 19:53:33,952][50205] Updated weights for policy 0, policy_version 12922 (0.0011) +[2026-07-22 19:53:34,619][50205] Updated weights for policy 0, policy_version 12932 (0.0016) +[2026-07-22 19:53:34,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5256.5, 300 sec: 5352.6). Total num frames: 6621184. Throughput: 0: 5236.4. Samples: 6625088. Policy #0 lag: (min: 3.0, avg: 15.8, max: 35.0) +[2026-07-22 19:53:34,878][43431] Avg episode reward: [(0, '1729.541')] +[2026-07-22 19:53:35,895][50205] Updated weights for policy 0, policy_version 12942 (0.0017) +[2026-07-22 19:53:36,594][50205] Updated weights for policy 0, policy_version 12952 (0.0012) +[2026-07-22 19:53:37,907][50205] Updated weights for policy 0, policy_version 12962 (0.0021) +[2026-07-22 19:53:38,638][50205] Updated weights for policy 0, policy_version 12972 (0.0011) +[2026-07-22 19:53:39,538][50205] Updated weights for policy 0, policy_version 12982 (0.0013) +[2026-07-22 19:53:39,878][43431] Fps is (10 sec: 5529.5, 60 sec: 5256.6, 300 sec: 5345.6). Total num frames: 6647808. Throughput: 0: 5246.3. Samples: 6657366. Policy #0 lag: (min: 4.0, avg: 19.0, max: 38.0) +[2026-07-22 19:53:39,878][43431] Avg episode reward: [(0, '1595.182')] +[2026-07-22 19:53:40,484][50205] Updated weights for policy 0, policy_version 12992 (0.0013) +[2026-07-22 19:53:41,634][50205] Updated weights for policy 0, policy_version 13002 (0.0015) +[2026-07-22 19:53:42,383][50205] Updated weights for policy 0, policy_version 13012 (0.0011) +[2026-07-22 19:53:43,452][50205] Updated weights for policy 0, policy_version 13022 (0.0011) +[2026-07-22 19:53:44,393][50205] Updated weights for policy 0, policy_version 13032 (0.0011) +[2026-07-22 19:53:44,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5290.7, 300 sec: 5352.6). Total num frames: 6674432. Throughput: 0: 5246.4. Samples: 6673338. Policy #0 lag: (min: 4.0, avg: 19.0, max: 38.0) +[2026-07-22 19:53:44,878][43431] Avg episode reward: [(0, '1711.222')] +[2026-07-22 19:53:45,497][50205] Updated weights for policy 0, policy_version 13042 (0.0010) +[2026-07-22 19:53:46,050][50205] Updated weights for policy 0, policy_version 13052 (0.0016) +[2026-07-22 19:53:47,713][50205] Updated weights for policy 0, policy_version 13062 (0.0011) +[2026-07-22 19:53:48,660][50205] Updated weights for policy 0, policy_version 13072 (0.0019) +[2026-07-22 19:53:49,446][50205] Updated weights for policy 0, policy_version 13082 (0.0014) +[2026-07-22 19:53:49,877][43431] Fps is (10 sec: 5120.2, 60 sec: 5222.4, 300 sec: 5352.6). Total num frames: 6699008. Throughput: 0: 5236.8. Samples: 6703440. Policy #0 lag: (min: 3.0, avg: 20.0, max: 43.0) +[2026-07-22 19:53:49,878][43431] Avg episode reward: [(0, '1541.043')] +[2026-07-22 19:53:50,566][50205] Updated weights for policy 0, policy_version 13092 (0.0011) +[2026-07-22 19:53:51,754][50205] Updated weights for policy 0, policy_version 13102 (0.0012) +[2026-07-22 19:53:52,260][50205] Updated weights for policy 0, policy_version 13112 (0.0017) +[2026-07-22 19:53:53,628][50205] Updated weights for policy 0, policy_version 13122 (0.0016) +[2026-07-22 19:53:54,517][50205] Updated weights for policy 0, policy_version 13132 (0.0012) +[2026-07-22 19:53:54,877][43431] Fps is (10 sec: 5120.1, 60 sec: 5222.4, 300 sec: 5352.6). Total num frames: 6725632. Throughput: 0: 5258.3. Samples: 6734742. Policy #0 lag: (min: 3.0, avg: 20.0, max: 43.0) +[2026-07-22 19:53:54,878][43431] Avg episode reward: [(0, '1649.551')] +[2026-07-22 19:53:55,302][50205] Updated weights for policy 0, policy_version 13142 (0.0017) +[2026-07-22 19:53:56,205][50205] Updated weights for policy 0, policy_version 13152 (0.0015) +[2026-07-22 19:53:57,577][50205] Updated weights for policy 0, policy_version 13162 (0.0011) +[2026-07-22 19:53:58,069][50205] Updated weights for policy 0, policy_version 13172 (0.0011) +[2026-07-22 19:53:59,272][50205] Updated weights for policy 0, policy_version 13182 (0.0023) +[2026-07-22 19:53:59,877][43431] Fps is (10 sec: 5120.1, 60 sec: 5188.3, 300 sec: 5352.6). Total num frames: 6750208. Throughput: 0: 5280.1. Samples: 6750744. Policy #0 lag: (min: 3.0, avg: 21.0, max: 39.0) +[2026-07-22 19:53:59,878][43431] Avg episode reward: [(0, '1662.971')] +[2026-07-22 19:54:00,451][50205] Updated weights for policy 0, policy_version 13192 (0.0011) +[2026-07-22 19:54:01,119][50205] Updated weights for policy 0, policy_version 13202 (0.0015) +[2026-07-22 19:54:01,820][50205] Updated weights for policy 0, policy_version 13212 (0.0013) +[2026-07-22 19:54:03,389][50205] Updated weights for policy 0, policy_version 13222 (0.0011) +[2026-07-22 19:54:03,834][50205] Updated weights for policy 0, policy_version 13232 (0.0016) +[2026-07-22 19:54:04,834][50205] Updated weights for policy 0, policy_version 13242 (0.0011) +[2026-07-22 19:54:04,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5290.7, 300 sec: 5359.5). Total num frames: 6780928. Throughput: 0: 5291.7. Samples: 6783108. Policy #0 lag: (min: 3.0, avg: 21.0, max: 39.0) +[2026-07-22 19:54:04,878][43431] Avg episode reward: [(0, '1628.974')] +[2026-07-22 19:54:05,951][50205] Updated weights for policy 0, policy_version 13252 (0.0016) +[2026-07-22 19:54:07,040][50205] Updated weights for policy 0, policy_version 13262 (0.0016) +[2026-07-22 19:54:07,849][50205] Updated weights for policy 0, policy_version 13272 (0.0012) +[2026-07-22 19:54:09,105][50205] Updated weights for policy 0, policy_version 13282 (0.0012) +[2026-07-22 19:54:09,571][50205] Updated weights for policy 0, policy_version 13292 (0.0016) +[2026-07-22 19:54:09,879][43431] Fps is (10 sec: 5528.7, 60 sec: 5256.4, 300 sec: 5345.6). Total num frames: 6805504. Throughput: 0: 5277.6. Samples: 6814630. Policy #0 lag: (min: 3.0, avg: 19.8, max: 39.0) +[2026-07-22 19:54:09,880][43431] Avg episode reward: [(0, '1515.069')] +[2026-07-22 19:54:10,811][50205] Updated weights for policy 0, policy_version 13302 (0.0019) +[2026-07-22 19:54:12,042][50205] Updated weights for policy 0, policy_version 13312 (0.0011) +[2026-07-22 19:54:12,569][50205] Updated weights for policy 0, policy_version 13322 (0.0012) +[2026-07-22 19:54:13,361][50205] Updated weights for policy 0, policy_version 13332 (0.0011) +[2026-07-22 19:54:14,877][43431] Fps is (10 sec: 4710.3, 60 sec: 5256.7, 300 sec: 5345.6). Total num frames: 6828032. Throughput: 0: 5279.1. Samples: 6830628. Policy #0 lag: (min: 3.0, avg: 19.8, max: 39.0) +[2026-07-22 19:54:14,878][43431] Avg episode reward: [(0, '1689.959')] +[2026-07-22 19:54:15,271][50205] Updated weights for policy 0, policy_version 13346 (0.0012) +[2026-07-22 19:54:15,893][50205] Updated weights for policy 0, policy_version 13356 (0.0016) +[2026-07-22 19:54:16,895][50205] Updated weights for policy 0, policy_version 13366 (0.0011) +[2026-07-22 19:54:18,059][50205] Updated weights for policy 0, policy_version 13376 (0.0016) +[2026-07-22 19:54:18,733][50205] Updated weights for policy 0, policy_version 13386 (0.0021) +[2026-07-22 19:54:19,777][50205] Updated weights for policy 0, policy_version 13396 (0.0012) +[2026-07-22 19:54:19,877][43431] Fps is (10 sec: 5325.7, 60 sec: 5290.7, 300 sec: 5345.6). Total num frames: 6858752. Throughput: 0: 5271.6. Samples: 6862308. Policy #0 lag: (min: 3.0, avg: 18.6, max: 35.0) +[2026-07-22 19:54:19,878][43431] Avg episode reward: [(0, '1548.411')] +[2026-07-22 19:54:20,895][50205] Updated weights for policy 0, policy_version 13406 (0.0011) +[2026-07-22 19:54:21,518][50205] Updated weights for policy 0, policy_version 13416 (0.0012) +[2026-07-22 19:54:22,810][50205] Updated weights for policy 0, policy_version 13426 (0.0012) +[2026-07-22 19:54:23,863][50205] Updated weights for policy 0, policy_version 13436 (0.0012) +[2026-07-22 19:54:24,523][50205] Updated weights for policy 0, policy_version 13446 (0.0016) +[2026-07-22 19:54:24,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5290.7, 300 sec: 5345.6). Total num frames: 6885376. Throughput: 0: 5259.5. Samples: 6894042. Policy #0 lag: (min: 3.0, avg: 18.6, max: 35.0) +[2026-07-22 19:54:24,878][43431] Avg episode reward: [(0, '1745.347')] +[2026-07-22 19:54:24,959][49527] Saving new best policy, reward=1745.347! +[2026-07-22 19:54:25,529][50205] Updated weights for policy 0, policy_version 13456 (0.0022) +[2026-07-22 19:54:27,298][50205] Updated weights for policy 0, policy_version 13466 (0.0013) +[2026-07-22 19:54:27,796][50205] Updated weights for policy 0, policy_version 13476 (0.0011) +[2026-07-22 19:54:28,747][50205] Updated weights for policy 0, policy_version 13486 (0.0015) +[2026-07-22 19:54:29,877][43431] Fps is (10 sec: 4915.2, 60 sec: 5256.6, 300 sec: 5331.7). Total num frames: 6907904. Throughput: 0: 5230.1. Samples: 6908692. Policy #0 lag: (min: 3.0, avg: 20.9, max: 35.0) +[2026-07-22 19:54:29,878][43431] Avg episode reward: [(0, '1639.874')] +[2026-07-22 19:54:29,890][50205] Updated weights for policy 0, policy_version 13496 (0.0018) +[2026-07-22 19:54:30,775][50205] Updated weights for policy 0, policy_version 13506 (0.0011) +[2026-07-22 19:54:31,512][50205] Updated weights for policy 0, policy_version 13516 (0.0011) +[2026-07-22 19:54:33,057][50205] Updated weights for policy 0, policy_version 13526 (0.0016) +[2026-07-22 19:54:33,745][50205] Updated weights for policy 0, policy_version 13536 (0.0014) +[2026-07-22 19:54:34,615][50205] Updated weights for policy 0, policy_version 13546 (0.0011) +[2026-07-22 19:54:34,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5256.5, 300 sec: 5331.7). Total num frames: 6936576. Throughput: 0: 5262.1. Samples: 6940232. Policy #0 lag: (min: 3.0, avg: 20.9, max: 35.0) +[2026-07-22 19:54:34,878][43431] Avg episode reward: [(0, '1632.215')] +[2026-07-22 19:54:35,510][50205] Updated weights for policy 0, policy_version 13556 (0.0017) +[2026-07-22 19:54:36,673][50205] Updated weights for policy 0, policy_version 13566 (0.0018) +[2026-07-22 19:54:37,355][50205] Updated weights for policy 0, policy_version 13576 (0.0020) +[2026-07-22 19:54:38,778][50205] Updated weights for policy 0, policy_version 13586 (0.0013) +[2026-07-22 19:54:39,500][50205] Updated weights for policy 0, policy_version 13596 (0.0021) +[2026-07-22 19:54:39,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5290.7, 300 sec: 5331.7). Total num frames: 6965248. Throughput: 0: 5282.6. Samples: 6972458. Policy #0 lag: (min: 1.0, avg: 15.6, max: 29.0) +[2026-07-22 19:54:39,878][43431] Avg episode reward: [(0, '1689.549')] +[2026-07-22 19:54:40,080][50205] Updated weights for policy 0, policy_version 13606 (0.0010) +[2026-07-22 19:54:41,126][50205] Updated weights for policy 0, policy_version 13616 (0.0012) +[2026-07-22 19:54:42,511][50205] Updated weights for policy 0, policy_version 13626 (0.0013) +[2026-07-22 19:54:42,950][50205] Updated weights for policy 0, policy_version 13636 (0.0016) +[2026-07-22 19:54:44,025][50205] Updated weights for policy 0, policy_version 13646 (0.0011) +[2026-07-22 19:54:44,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5222.4, 300 sec: 5310.9). Total num frames: 6987776. Throughput: 0: 5287.1. Samples: 6988662. Policy #0 lag: (min: 1.0, avg: 15.6, max: 29.0) +[2026-07-22 19:54:44,878][43431] Avg episode reward: [(0, '1634.859')] +[2026-07-22 19:54:45,315][50205] Updated weights for policy 0, policy_version 13656 (0.0012) +[2026-07-22 19:54:46,013][50205] Updated weights for policy 0, policy_version 13666 (0.0011) +[2026-07-22 19:54:46,795][50205] Updated weights for policy 0, policy_version 13676 (0.0012) +[2026-07-22 19:54:48,221][50205] Updated weights for policy 0, policy_version 13686 (0.0011) +[2026-07-22 19:54:48,718][50205] Updated weights for policy 0, policy_version 13696 (0.0011) +[2026-07-22 19:54:49,877][43431] Fps is (10 sec: 5119.9, 60 sec: 5290.7, 300 sec: 5317.9). Total num frames: 7016448. Throughput: 0: 5286.9. Samples: 7021022. Policy #0 lag: (min: 4.0, avg: 14.7, max: 36.0) +[2026-07-22 19:54:49,878][43431] Avg episode reward: [(0, '1715.464')] +[2026-07-22 19:54:49,956][50205] Updated weights for policy 0, policy_version 13706 (0.0012) +[2026-07-22 19:54:50,969][50205] Updated weights for policy 0, policy_version 13716 (0.0016) +[2026-07-22 19:54:51,699][50205] Updated weights for policy 0, policy_version 13726 (0.0011) +[2026-07-22 19:54:52,541][50205] Updated weights for policy 0, policy_version 13736 (0.0013) +[2026-07-22 19:54:53,919][50205] Updated weights for policy 0, policy_version 13746 (0.0015) +[2026-07-22 19:54:54,502][50205] Updated weights for policy 0, policy_version 13756 (0.0012) +[2026-07-22 19:54:54,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5324.8, 300 sec: 5317.9). Total num frames: 7045120. Throughput: 0: 5307.2. Samples: 7053444. Policy #0 lag: (min: 4.0, avg: 14.7, max: 36.0) +[2026-07-22 19:54:54,878][43431] Avg episode reward: [(0, '1471.774')] +[2026-07-22 19:54:55,412][50205] Updated weights for policy 0, policy_version 13766 (0.0011) +[2026-07-22 19:54:56,680][50205] Updated weights for policy 0, policy_version 13776 (0.0012) +[2026-07-22 19:54:57,413][50205] Updated weights for policy 0, policy_version 13786 (0.0011) +[2026-07-22 19:54:58,008][50205] Updated weights for policy 0, policy_version 13796 (0.0016) +[2026-07-22 19:54:59,684][50205] Updated weights for policy 0, policy_version 13806 (0.0011) +[2026-07-22 19:54:59,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5324.8, 300 sec: 5304.0). Total num frames: 7069696. Throughput: 0: 5311.0. Samples: 7069622. Policy #0 lag: (min: 2.0, avg: 21.5, max: 36.0) +[2026-07-22 19:54:59,878][43431] Avg episode reward: [(0, '1594.951')] +[2026-07-22 19:55:00,235][50205] Updated weights for policy 0, policy_version 13816 (0.0013) +[2026-07-22 19:55:01,178][50205] Updated weights for policy 0, policy_version 13826 (0.0015) +[2026-07-22 19:55:02,837][50205] Updated weights for policy 0, policy_version 13836 (0.0011) +[2026-07-22 19:55:03,874][50205] Updated weights for policy 0, policy_version 13846 (0.0013) +[2026-07-22 19:55:04,620][50205] Updated weights for policy 0, policy_version 13856 (0.0012) +[2026-07-22 19:55:04,878][43431] Fps is (10 sec: 4915.1, 60 sec: 5222.4, 300 sec: 5304.0). Total num frames: 7094272. Throughput: 0: 5247.1. Samples: 7098428. Policy #0 lag: (min: 2.0, avg: 21.5, max: 36.0) +[2026-07-22 19:55:04,878][43431] Avg episode reward: [(0, '1707.702')] +[2026-07-22 19:55:06,094][50205] Updated weights for policy 0, policy_version 13866 (0.0015) +[2026-07-22 19:55:07,062][50205] Updated weights for policy 0, policy_version 13876 (0.0012) +[2026-07-22 19:55:07,848][50205] Updated weights for policy 0, policy_version 13886 (0.0016) +[2026-07-22 19:55:09,028][50205] Updated weights for policy 0, policy_version 13896 (0.0012) +[2026-07-22 19:55:09,877][43431] Fps is (10 sec: 4915.1, 60 sec: 5222.5, 300 sec: 5297.0). Total num frames: 7118848. Throughput: 0: 5203.9. Samples: 7128216. Policy #0 lag: (min: 3.0, avg: 14.8, max: 35.0) +[2026-07-22 19:55:09,878][43431] Avg episode reward: [(0, '1698.309')] +[2026-07-22 19:55:10,233][50205] Updated weights for policy 0, policy_version 13906 (0.0022) +[2026-07-22 19:55:10,859][50205] Updated weights for policy 0, policy_version 13916 (0.0013) +[2026-07-22 19:55:11,947][50205] Updated weights for policy 0, policy_version 13926 (0.0012) +[2026-07-22 19:55:13,208][50205] Updated weights for policy 0, policy_version 13936 (0.0014) +[2026-07-22 19:55:13,891][50205] Updated weights for policy 0, policy_version 13946 (0.0024) +[2026-07-22 19:55:14,635][50205] Updated weights for policy 0, policy_version 13956 (0.0015) +[2026-07-22 19:55:14,878][43431] Fps is (10 sec: 5119.7, 60 sec: 5290.6, 300 sec: 5290.1). Total num frames: 7145472. Throughput: 0: 5218.2. Samples: 7143516. Policy #0 lag: (min: 3.0, avg: 14.8, max: 35.0) +[2026-07-22 19:55:14,879][43431] Avg episode reward: [(0, '1735.595')] +[2026-07-22 19:55:16,166][50205] Updated weights for policy 0, policy_version 13966 (0.0018) +[2026-07-22 19:55:16,861][50205] Updated weights for policy 0, policy_version 13976 (0.0012) +[2026-07-22 19:55:17,709][50205] Updated weights for policy 0, policy_version 13986 (0.0016) +[2026-07-22 19:55:18,760][50205] Updated weights for policy 0, policy_version 13996 (0.0011) +[2026-07-22 19:55:19,796][50205] Updated weights for policy 0, policy_version 14006 (0.0011) +[2026-07-22 19:55:19,878][43431] Fps is (10 sec: 5324.3, 60 sec: 5222.3, 300 sec: 5283.1). Total num frames: 7172096. Throughput: 0: 5227.5. Samples: 7175476. Policy #0 lag: (min: 5.0, avg: 18.6, max: 34.0) +[2026-07-22 19:55:19,879][43431] Avg episode reward: [(0, '1679.747')] +[2026-07-22 19:55:20,499][50205] Updated weights for policy 0, policy_version 14016 (0.0021) +[2026-07-22 19:55:21,823][50205] Updated weights for policy 0, policy_version 14026 (0.0013) +[2026-07-22 19:55:22,525][50205] Updated weights for policy 0, policy_version 14036 (0.0011) +[2026-07-22 19:55:23,302][50205] Updated weights for policy 0, policy_version 14046 (0.0022) +[2026-07-22 19:55:24,503][50205] Updated weights for policy 0, policy_version 14056 (0.0020) +[2026-07-22 19:55:24,877][43431] Fps is (10 sec: 5120.5, 60 sec: 5188.3, 300 sec: 5269.3). Total num frames: 7196672. Throughput: 0: 5246.5. Samples: 7208552. Policy #0 lag: (min: 5.0, avg: 18.6, max: 34.0) +[2026-07-22 19:55:24,878][43431] Avg episode reward: [(0, '1785.692')] +[2026-07-22 19:55:24,944][49527] Saving new best policy, reward=1785.692! +[2026-07-22 19:55:25,508][50205] Updated weights for policy 0, policy_version 14066 (0.0011) +[2026-07-22 19:55:25,894][50205] Updated weights for policy 0, policy_version 14076 (0.0010) +[2026-07-22 19:55:27,551][50205] Updated weights for policy 0, policy_version 14086 (0.0011) +[2026-07-22 19:55:28,177][50205] Updated weights for policy 0, policy_version 14096 (0.0011) +[2026-07-22 19:55:28,872][50205] Updated weights for policy 0, policy_version 14107 (0.0016) +[2026-07-22 19:55:29,877][43431] Fps is (10 sec: 5530.2, 60 sec: 5324.8, 300 sec: 5283.1). Total num frames: 7227392. Throughput: 0: 5255.0. Samples: 7225138. Policy #0 lag: (min: 2.0, avg: 19.2, max: 44.0) +[2026-07-22 19:55:29,878][43431] Avg episode reward: [(0, '1565.862')] +[2026-07-22 19:55:30,379][50205] Updated weights for policy 0, policy_version 14117 (0.0017) +[2026-07-22 19:55:31,076][50205] Updated weights for policy 0, policy_version 14127 (0.0014) +[2026-07-22 19:55:31,837][50205] Updated weights for policy 0, policy_version 14137 (0.0014) +[2026-07-22 19:55:32,925][50205] Updated weights for policy 0, policy_version 14147 (0.0014) +[2026-07-22 19:55:33,961][50205] Updated weights for policy 0, policy_version 14157 (0.0010) +[2026-07-22 19:55:34,507][50205] Updated weights for policy 0, policy_version 14167 (0.0011) +[2026-07-22 19:55:34,877][43431] Fps is (10 sec: 5939.1, 60 sec: 5324.8, 300 sec: 5283.1). Total num frames: 7256064. Throughput: 0: 5266.1. Samples: 7257998. Policy #0 lag: (min: 2.0, avg: 19.2, max: 44.0) +[2026-07-22 19:55:34,878][43431] Avg episode reward: [(0, '1588.066')] +[2026-07-22 19:55:35,933][50205] Updated weights for policy 0, policy_version 14177 (0.0011) +[2026-07-22 19:55:36,767][50205] Updated weights for policy 0, policy_version 14188 (0.0012) +[2026-07-22 19:55:37,457][50205] Updated weights for policy 0, policy_version 14198 (0.0011) +[2026-07-22 19:55:38,660][50205] Updated weights for policy 0, policy_version 14208 (0.0011) +[2026-07-22 19:55:39,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5222.4, 300 sec: 5269.3). Total num frames: 7278592. Throughput: 0: 5244.4. Samples: 7289440. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 19:55:39,878][43431] Avg episode reward: [(0, '1648.046')] +[2026-07-22 19:55:40,036][50205] Updated weights for policy 0, policy_version 14218 (0.0011) +[2026-07-22 19:55:40,416][50205] Updated weights for policy 0, policy_version 14228 (0.0011) +[2026-07-22 19:55:41,950][50205] Updated weights for policy 0, policy_version 14238 (0.0011) +[2026-07-22 19:55:42,983][50205] Updated weights for policy 0, policy_version 14248 (0.0026) +[2026-07-22 19:55:43,532][50205] Updated weights for policy 0, policy_version 14258 (0.0010) +[2026-07-22 19:55:44,378][50205] Updated weights for policy 0, policy_version 14268 (0.0014) +[2026-07-22 19:55:44,877][43431] Fps is (10 sec: 4915.1, 60 sec: 5290.6, 300 sec: 5269.3). Total num frames: 7305216. Throughput: 0: 5227.3. Samples: 7304852. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 19:55:44,878][43431] Avg episode reward: [(0, '1792.981')] +[2026-07-22 19:55:44,952][49527] Saving new best policy, reward=1792.981! +[2026-07-22 19:55:45,892][50205] Updated weights for policy 0, policy_version 14278 (0.0010) +[2026-07-22 19:55:46,310][50205] Updated weights for policy 0, policy_version 14288 (0.0015) +[2026-07-22 19:55:47,426][50205] Updated weights for policy 0, policy_version 14298 (0.0016) +[2026-07-22 19:55:48,643][50205] Updated weights for policy 0, policy_version 14308 (0.0013) +[2026-07-22 19:55:49,185][50205] Updated weights for policy 0, policy_version 14319 (0.0011) +[2026-07-22 19:55:49,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5290.7, 300 sec: 5276.2). Total num frames: 7333888. Throughput: 0: 5318.4. Samples: 7337752. Policy #0 lag: (min: 3.0, avg: 17.0, max: 35.0) +[2026-07-22 19:55:49,878][43431] Avg episode reward: [(0, '1608.443')] +[2026-07-22 19:55:50,322][50205] Updated weights for policy 0, policy_version 14329 (0.0012) +[2026-07-22 19:55:51,459][50205] Updated weights for policy 0, policy_version 14339 (0.0011) +[2026-07-22 19:55:52,058][50205] Updated weights for policy 0, policy_version 14349 (0.0014) +[2026-07-22 19:55:52,917][50205] Updated weights for policy 0, policy_version 14359 (0.0011) +[2026-07-22 19:55:54,382][50205] Updated weights for policy 0, policy_version 14369 (0.0016) +[2026-07-22 19:55:54,853][50205] Updated weights for policy 0, policy_version 14379 (0.0012) +[2026-07-22 19:55:54,877][43431] Fps is (10 sec: 5734.6, 60 sec: 5290.7, 300 sec: 5269.3). Total num frames: 7362560. Throughput: 0: 5390.1. Samples: 7370768. Policy #0 lag: (min: 3.0, avg: 17.0, max: 35.0) +[2026-07-22 19:55:54,878][43431] Avg episode reward: [(0, '1799.279')] +[2026-07-22 19:55:54,908][49527] Saving new best policy, reward=1799.279! +[2026-07-22 19:55:55,904][50205] Updated weights for policy 0, policy_version 14389 (0.0015) +[2026-07-22 19:55:57,085][50205] Updated weights for policy 0, policy_version 14399 (0.0011) +[2026-07-22 19:55:57,777][50205] Updated weights for policy 0, policy_version 14409 (0.0011) +[2026-07-22 19:55:58,378][50205] Updated weights for policy 0, policy_version 14419 (0.0016) +[2026-07-22 19:55:59,793][50205] Updated weights for policy 0, policy_version 14429 (0.0014) +[2026-07-22 19:55:59,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5324.8, 300 sec: 5276.2). Total num frames: 7389184. Throughput: 0: 5414.7. Samples: 7387174. Policy #0 lag: (min: 3.0, avg: 17.1, max: 35.0) +[2026-07-22 19:55:59,878][43431] Avg episode reward: [(0, '1719.942')] +[2026-07-22 19:56:00,690][50205] Updated weights for policy 0, policy_version 14441 (0.0016) +[2026-07-22 19:56:01,433][50205] Updated weights for policy 0, policy_version 14451 (0.0011) +[2026-07-22 19:56:02,881][50205] Updated weights for policy 0, policy_version 14461 (0.0012) +[2026-07-22 19:56:03,799][50205] Updated weights for policy 0, policy_version 14471 (0.0011) +[2026-07-22 19:56:04,812][50205] Updated weights for policy 0, policy_version 14481 (0.0012) +[2026-07-22 19:56:04,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5359.0, 300 sec: 5276.2). Total num frames: 7415808. Throughput: 0: 5400.3. Samples: 7418486. Policy #0 lag: (min: 3.0, avg: 17.1, max: 35.0) +[2026-07-22 19:56:04,878][43431] Avg episode reward: [(0, '1524.415')] +[2026-07-22 19:56:06,128][50205] Updated weights for policy 0, policy_version 14491 (0.0010) +[2026-07-22 19:56:07,051][50205] Updated weights for policy 0, policy_version 14501 (0.0011) +[2026-07-22 19:56:07,833][50205] Updated weights for policy 0, policy_version 14511 (0.0011) +[2026-07-22 19:56:09,112][50205] Updated weights for policy 0, policy_version 14521 (0.0011) +[2026-07-22 19:56:09,751][50205] Updated weights for policy 0, policy_version 14531 (0.0014) +[2026-07-22 19:56:09,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5358.9, 300 sec: 5262.3). Total num frames: 7440384. Throughput: 0: 5357.4. Samples: 7449636. Policy #0 lag: (min: 3.0, avg: 17.1, max: 35.0) +[2026-07-22 19:56:09,878][43431] Avg episode reward: [(0, '1513.755')] +[2026-07-22 19:56:10,742][50205] Updated weights for policy 0, policy_version 14541 (0.0019) +[2026-07-22 19:56:11,565][50205] Updated weights for policy 0, policy_version 14551 (0.0021) +[2026-07-22 19:56:12,723][50205] Updated weights for policy 0, policy_version 14561 (0.0018) +[2026-07-22 19:56:13,747][50205] Updated weights for policy 0, policy_version 14571 (0.0025) +[2026-07-22 19:56:14,877][43431] Fps is (10 sec: 4915.2, 60 sec: 5324.9, 300 sec: 5255.4). Total num frames: 7464960. Throughput: 0: 5341.7. Samples: 7465514. Policy #0 lag: (min: 3.0, avg: 17.1, max: 35.0) +[2026-07-22 19:56:14,878][43431] Avg episode reward: [(0, '1576.110')] +[2026-07-22 19:56:14,925][50205] Updated weights for policy 0, policy_version 14583 (0.0016) +[2026-07-22 19:56:16,011][50205] Updated weights for policy 0, policy_version 14593 (0.0017) +[2026-07-22 19:56:16,817][50205] Updated weights for policy 0, policy_version 14603 (0.0012) +[2026-07-22 19:56:17,896][50205] Updated weights for policy 0, policy_version 14613 (0.0011) +[2026-07-22 19:56:18,784][50205] Updated weights for policy 0, policy_version 14623 (0.0011) +[2026-07-22 19:56:19,853][50205] Updated weights for policy 0, policy_version 14633 (0.0014) +[2026-07-22 19:56:19,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5324.9, 300 sec: 5262.3). Total num frames: 7491584. Throughput: 0: 5307.2. Samples: 7496820. Policy #0 lag: (min: 3.0, avg: 17.1, max: 35.0) +[2026-07-22 19:56:19,878][43431] Avg episode reward: [(0, '1664.093')] +[2026-07-22 19:56:20,467][50205] Updated weights for policy 0, policy_version 14643 (0.0014) +[2026-07-22 19:56:21,615][50205] Updated weights for policy 0, policy_version 14653 (0.0012) +[2026-07-22 19:56:22,458][50205] Updated weights for policy 0, policy_version 14663 (0.0015) +[2026-07-22 19:56:23,631][50205] Updated weights for policy 0, policy_version 14673 (0.0020) +[2026-07-22 19:56:23,961][50205] Updated weights for policy 0, policy_version 14683 (0.0020) +[2026-07-22 19:56:24,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5393.1, 300 sec: 5262.3). Total num frames: 7520256. Throughput: 0: 5347.6. Samples: 7530084. Policy #0 lag: (min: 3.0, avg: 16.0, max: 35.0) +[2026-07-22 19:56:24,878][43431] Avg episode reward: [(0, '1561.072')] +[2026-07-22 19:56:25,378][50205] Updated weights for policy 0, policy_version 14693 (0.0011) +[2026-07-22 19:56:26,104][50205] Updated weights for policy 0, policy_version 14703 (0.0011) +[2026-07-22 19:56:27,191][50205] Updated weights for policy 0, policy_version 14713 (0.0011) +[2026-07-22 19:56:27,826][50205] Updated weights for policy 0, policy_version 14723 (0.0019) +[2026-07-22 19:56:29,072][50205] Updated weights for policy 0, policy_version 14733 (0.0020) +[2026-07-22 19:56:29,810][50205] Updated weights for policy 0, policy_version 14743 (0.0021) +[2026-07-22 19:56:29,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5358.9, 300 sec: 5262.3). Total num frames: 7548928. Throughput: 0: 5372.3. Samples: 7546602. Policy #0 lag: (min: 3.0, avg: 16.0, max: 35.0) +[2026-07-22 19:56:29,878][43431] Avg episode reward: [(0, '1545.704')] +[2026-07-22 19:56:30,858][50205] Updated weights for policy 0, policy_version 14753 (0.0019) +[2026-07-22 19:56:31,599][50205] Updated weights for policy 0, policy_version 14763 (0.0011) +[2026-07-22 19:56:32,742][50205] Updated weights for policy 0, policy_version 14773 (0.0019) +[2026-07-22 19:56:33,450][50205] Updated weights for policy 0, policy_version 14783 (0.0013) +[2026-07-22 19:56:34,603][50205] Updated weights for policy 0, policy_version 14793 (0.0011) +[2026-07-22 19:56:34,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5358.9, 300 sec: 5276.2). Total num frames: 7577600. Throughput: 0: 5384.8. Samples: 7580068. Policy #0 lag: (min: 1.0, avg: 16.2, max: 33.0) +[2026-07-22 19:56:34,878][43431] Avg episode reward: [(0, '1668.916')] +[2026-07-22 19:56:35,100][50205] Updated weights for policy 0, policy_version 14803 (0.0011) +[2026-07-22 19:56:36,328][50205] Updated weights for policy 0, policy_version 14813 (0.0015) +[2026-07-22 19:56:36,991][50205] Updated weights for policy 0, policy_version 14823 (0.0011) +[2026-07-22 19:56:38,099][50205] Updated weights for policy 0, policy_version 14833 (0.0018) +[2026-07-22 19:56:38,979][50205] Updated weights for policy 0, policy_version 14843 (0.0015) +[2026-07-22 19:56:39,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5427.2, 300 sec: 5276.2). Total num frames: 7604224. Throughput: 0: 5397.0. Samples: 7613632. Policy #0 lag: (min: 1.0, avg: 16.2, max: 33.0) +[2026-07-22 19:56:39,878][43431] Avg episode reward: [(0, '1689.844')] +[2026-07-22 19:56:40,064][50205] Updated weights for policy 0, policy_version 14853 (0.0014) +[2026-07-22 19:56:40,603][50205] Updated weights for policy 0, policy_version 14863 (0.0018) +[2026-07-22 19:56:41,901][50205] Updated weights for policy 0, policy_version 14873 (0.0011) +[2026-07-22 19:56:42,697][50205] Updated weights for policy 0, policy_version 14883 (0.0011) +[2026-07-22 19:56:43,529][50205] Updated weights for policy 0, policy_version 14893 (0.0011) +[2026-07-22 19:56:44,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5393.1, 300 sec: 5269.3). Total num frames: 7628800. Throughput: 0: 5406.6. Samples: 7630470. Policy #0 lag: (min: 3.0, avg: 17.5, max: 35.0) +[2026-07-22 19:56:44,878][43431] Avg episode reward: [(0, '1651.882')] +[2026-07-22 19:56:45,126][50205] Updated weights for policy 0, policy_version 14905 (0.0011) +[2026-07-22 19:56:45,761][50205] Updated weights for policy 0, policy_version 14917 (0.0011) +[2026-07-22 19:56:46,549][50205] Updated weights for policy 0, policy_version 14927 (0.0015) +[2026-07-22 19:56:47,941][50205] Updated weights for policy 0, policy_version 14937 (0.0011) +[2026-07-22 19:56:48,786][50205] Updated weights for policy 0, policy_version 14947 (0.0011) +[2026-07-22 19:56:49,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5393.1, 300 sec: 5283.2). Total num frames: 7657472. Throughput: 0: 5415.9. Samples: 7662200. Policy #0 lag: (min: 3.0, avg: 17.5, max: 35.0) +[2026-07-22 19:56:49,878][43431] Avg episode reward: [(0, '1639.086')] +[2026-07-22 19:56:49,960][50205] Updated weights for policy 0, policy_version 14957 (0.0010) +[2026-07-22 19:56:50,937][50205] Updated weights for policy 0, policy_version 14967 (0.0016) +[2026-07-22 19:56:51,839][50205] Updated weights for policy 0, policy_version 14977 (0.0013) +[2026-07-22 19:56:52,532][50205] Updated weights for policy 0, policy_version 14987 (0.0011) +[2026-07-22 19:56:53,655][50205] Updated weights for policy 0, policy_version 14997 (0.0010) +[2026-07-22 19:56:54,593][50205] Updated weights for policy 0, policy_version 15007 (0.0015) +[2026-07-22 19:56:54,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5393.1, 300 sec: 5297.0). Total num frames: 7686144. Throughput: 0: 5449.9. Samples: 7694880. Policy #0 lag: (min: 3.0, avg: 18.6, max: 38.0) +[2026-07-22 19:56:54,878][43431] Avg episode reward: [(0, '1471.032')] +[2026-07-22 19:56:55,318][50205] Updated weights for policy 0, policy_version 15017 (0.0022) +[2026-07-22 19:56:56,369][50205] Updated weights for policy 0, policy_version 15027 (0.0011) +[2026-07-22 19:56:57,309][50205] Updated weights for policy 0, policy_version 15037 (0.0019) +[2026-07-22 19:56:57,927][50205] Updated weights for policy 0, policy_version 15047 (0.0011) +[2026-07-22 19:56:59,216][50205] Updated weights for policy 0, policy_version 15057 (0.0012) +[2026-07-22 19:56:59,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5393.1, 300 sec: 5297.0). Total num frames: 7712768. Throughput: 0: 5467.2. Samples: 7711536. Policy #0 lag: (min: 3.0, avg: 18.6, max: 38.0) +[2026-07-22 19:56:59,878][43431] Avg episode reward: [(0, '1564.553')] +[2026-07-22 19:57:00,099][50205] Updated weights for policy 0, policy_version 15067 (0.0014) +[2026-07-22 19:57:00,730][50205] Updated weights for policy 0, policy_version 15077 (0.0011) +[2026-07-22 19:57:02,257][50205] Updated weights for policy 0, policy_version 15090 (0.0014) +[2026-07-22 19:57:03,116][50205] Updated weights for policy 0, policy_version 15100 (0.0011) +[2026-07-22 19:57:03,766][50205] Updated weights for policy 0, policy_version 15111 (0.0011) +[2026-07-22 19:57:04,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5393.1, 300 sec: 5297.0). Total num frames: 7739392. Throughput: 0: 5503.3. Samples: 7744468. Policy #0 lag: (min: 3.0, avg: 18.6, max: 38.0) +[2026-07-22 19:57:04,878][43431] Avg episode reward: [(0, '1721.505')] +[2026-07-22 19:57:05,203][50205] Updated weights for policy 0, policy_version 15121 (0.0020) +[2026-07-22 19:57:06,035][50205] Updated weights for policy 0, policy_version 15131 (0.0010) +[2026-07-22 19:57:06,788][50205] Updated weights for policy 0, policy_version 15141 (0.0011) +[2026-07-22 19:57:07,797][50205] Updated weights for policy 0, policy_version 15151 (0.0011) +[2026-07-22 19:57:09,014][50205] Updated weights for policy 0, policy_version 15161 (0.0011) +[2026-07-22 19:57:09,671][50205] Updated weights for policy 0, policy_version 15173 (0.0020) +[2026-07-22 19:57:09,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5495.5, 300 sec: 5310.9). Total num frames: 7770112. Throughput: 0: 5504.8. Samples: 7777800. Policy #0 lag: (min: 2.0, avg: 16.9, max: 34.0) +[2026-07-22 19:57:09,878][43431] Avg episode reward: [(0, '1653.575')] +[2026-07-22 19:57:10,730][50205] Updated weights for policy 0, policy_version 15183 (0.0011) +[2026-07-22 19:57:11,879][50205] Updated weights for policy 0, policy_version 15193 (0.0015) +[2026-07-22 19:57:12,418][50205] Updated weights for policy 0, policy_version 15204 (0.0016) +[2026-07-22 19:57:13,586][50205] Updated weights for policy 0, policy_version 15214 (0.0011) +[2026-07-22 19:57:14,627][50205] Updated weights for policy 0, policy_version 15224 (0.0011) +[2026-07-22 19:57:14,878][43431] Fps is (10 sec: 5529.2, 60 sec: 5495.4, 300 sec: 5310.9). Total num frames: 7794688. Throughput: 0: 5510.1. Samples: 7794562. Policy #0 lag: (min: 2.0, avg: 16.9, max: 34.0) +[2026-07-22 19:57:14,878][43431] Avg episode reward: [(0, '1670.674')] +[2026-07-22 19:57:15,928][50205] Updated weights for policy 0, policy_version 15238 (0.0013) +[2026-07-22 19:57:16,639][50205] Updated weights for policy 0, policy_version 15248 (0.0016) +[2026-07-22 19:57:17,578][49527] Signal inference workers to stop experience collection... (250 times) +[2026-07-22 19:57:17,591][50205] InferenceWorker_p0-w0: stopping experience collection (250 times) +[2026-07-22 19:57:17,628][49527] Signal inference workers to resume experience collection... (250 times) +[2026-07-22 19:57:17,629][50205] InferenceWorker_p0-w0: resuming experience collection (250 times) +[2026-07-22 19:57:18,047][50205] Updated weights for policy 0, policy_version 15261 (0.0010) +[2026-07-22 19:57:18,779][50205] Updated weights for policy 0, policy_version 15271 (0.0017) +[2026-07-22 19:57:19,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5529.6, 300 sec: 5317.9). Total num frames: 7823360. Throughput: 0: 5495.6. Samples: 7827370. Policy #0 lag: (min: 3.0, avg: 19.9, max: 35.0) +[2026-07-22 19:57:19,878][43431] Avg episode reward: [(0, '1643.062')] +[2026-07-22 19:57:20,303][50205] Updated weights for policy 0, policy_version 15281 (0.0016) +[2026-07-22 19:57:20,779][50205] Updated weights for policy 0, policy_version 15291 (0.0010) +[2026-07-22 19:57:21,988][50205] Updated weights for policy 0, policy_version 15301 (0.0011) +[2026-07-22 19:57:23,036][50205] Updated weights for policy 0, policy_version 15311 (0.0015) +[2026-07-22 19:57:23,977][50205] Updated weights for policy 0, policy_version 15321 (0.0011) +[2026-07-22 19:57:24,645][50205] Updated weights for policy 0, policy_version 15331 (0.0012) +[2026-07-22 19:57:24,877][43431] Fps is (10 sec: 5530.0, 60 sec: 5495.5, 300 sec: 5317.9). Total num frames: 7849984. Throughput: 0: 5439.7. Samples: 7858418. Policy #0 lag: (min: 3.0, avg: 19.9, max: 35.0) +[2026-07-22 19:57:24,878][43431] Avg episode reward: [(0, '1754.186')] +[2026-07-22 19:57:25,992][50205] Updated weights for policy 0, policy_version 15341 (0.0012) +[2026-07-22 19:57:26,777][50205] Updated weights for policy 0, policy_version 15351 (0.0010) +[2026-07-22 19:57:27,543][50205] Updated weights for policy 0, policy_version 15361 (0.0023) +[2026-07-22 19:57:28,724][50205] Updated weights for policy 0, policy_version 15371 (0.0016) +[2026-07-22 19:57:29,567][50205] Updated weights for policy 0, policy_version 15381 (0.0012) +[2026-07-22 19:57:29,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5461.3, 300 sec: 5324.8). Total num frames: 7876608. Throughput: 0: 5439.6. Samples: 7875252. Policy #0 lag: (min: 0.0, avg: 16.5, max: 36.0) +[2026-07-22 19:57:29,878][43431] Avg episode reward: [(0, '1721.363')] +[2026-07-22 19:57:30,134][50205] Updated weights for policy 0, policy_version 15391 (0.0011) +[2026-07-22 19:57:31,512][50205] Updated weights for policy 0, policy_version 15401 (0.0016) +[2026-07-22 19:57:32,302][50205] Updated weights for policy 0, policy_version 15411 (0.0012) +[2026-07-22 19:57:32,989][50205] Updated weights for policy 0, policy_version 15421 (0.0011) +[2026-07-22 19:57:33,812][50205] Updated weights for policy 0, policy_version 15431 (0.0012) +[2026-07-22 19:57:34,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5461.3, 300 sec: 5331.8). Total num frames: 7905280. Throughput: 0: 5477.4. Samples: 7908686. Policy #0 lag: (min: 0.0, avg: 16.5, max: 36.0) +[2026-07-22 19:57:34,878][43431] Avg episode reward: [(0, '1652.020')] +[2026-07-22 19:57:35,201][50205] Updated weights for policy 0, policy_version 15441 (0.0015) +[2026-07-22 19:57:35,855][50205] Updated weights for policy 0, policy_version 15451 (0.0011) +[2026-07-22 19:57:36,699][50205] Updated weights for policy 0, policy_version 15461 (0.0014) +[2026-07-22 19:57:37,672][50205] Updated weights for policy 0, policy_version 15471 (0.0015) +[2026-07-22 19:57:38,686][50205] Updated weights for policy 0, policy_version 15482 (0.0011) +[2026-07-22 19:57:39,415][50205] Updated weights for policy 0, policy_version 15492 (0.0011) +[2026-07-22 19:57:39,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5495.4, 300 sec: 5345.6). Total num frames: 7933952. Throughput: 0: 5497.4. Samples: 7942262. Policy #0 lag: (min: 3.0, avg: 16.9, max: 39.0) +[2026-07-22 19:57:39,878][43431] Avg episode reward: [(0, '1596.211')] +[2026-07-22 19:57:40,464][50205] Updated weights for policy 0, policy_version 15502 (0.0012) +[2026-07-22 19:57:41,448][50205] Updated weights for policy 0, policy_version 15512 (0.0011) +[2026-07-22 19:57:42,356][50205] Updated weights for policy 0, policy_version 15522 (0.0011) +[2026-07-22 19:57:43,194][50205] Updated weights for policy 0, policy_version 15532 (0.0011) +[2026-07-22 19:57:44,205][50205] Updated weights for policy 0, policy_version 15542 (0.0012) +[2026-07-22 19:57:44,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5529.6, 300 sec: 5338.7). Total num frames: 7960576. Throughput: 0: 5501.1. Samples: 7959084. Policy #0 lag: (min: 3.0, avg: 16.9, max: 39.0) +[2026-07-22 19:57:44,878][43431] Avg episode reward: [(0, '1502.120')] +[2026-07-22 19:57:45,130][50205] Updated weights for policy 0, policy_version 15552 (0.0014) +[2026-07-22 19:57:46,051][50205] Updated weights for policy 0, policy_version 15562 (0.0011) +[2026-07-22 19:57:47,047][50205] Updated weights for policy 0, policy_version 15572 (0.0013) +[2026-07-22 19:57:47,884][50205] Updated weights for policy 0, policy_version 15582 (0.0011) +[2026-07-22 19:57:48,845][50205] Updated weights for policy 0, policy_version 15592 (0.0025) +[2026-07-22 19:57:49,797][50205] Updated weights for policy 0, policy_version 15602 (0.0020) +[2026-07-22 19:57:49,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5529.6, 300 sec: 5345.6). Total num frames: 7989248. Throughput: 0: 5519.0. Samples: 7992822. Policy #0 lag: (min: 1.0, avg: 14.7, max: 33.0) +[2026-07-22 19:57:49,878][43431] Avg episode reward: [(0, '1618.610')] +[2026-07-22 19:57:50,552][50205] Updated weights for policy 0, policy_version 15612 (0.0021) +[2026-07-22 19:57:51,344][50205] Updated weights for policy 0, policy_version 15622 (0.0021) +[2026-07-22 19:57:52,559][50205] Updated weights for policy 0, policy_version 15632 (0.0011) +[2026-07-22 19:57:53,442][50205] Updated weights for policy 0, policy_version 15642 (0.0011) +[2026-07-22 19:57:54,099][50205] Updated weights for policy 0, policy_version 15652 (0.0016) +[2026-07-22 19:57:54,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5529.6, 300 sec: 5352.6). Total num frames: 8017920. Throughput: 0: 5513.2. Samples: 8025894. Policy #0 lag: (min: 1.0, avg: 14.7, max: 33.0) +[2026-07-22 19:57:54,878][43431] Avg episode reward: [(0, '1645.789')] +[2026-07-22 19:57:55,432][50205] Updated weights for policy 0, policy_version 15662 (0.0011) +[2026-07-22 19:57:56,327][50205] Updated weights for policy 0, policy_version 15672 (0.0011) +[2026-07-22 19:57:57,119][50205] Updated weights for policy 0, policy_version 15682 (0.0010) +[2026-07-22 19:57:58,347][50205] Updated weights for policy 0, policy_version 15692 (0.0014) +[2026-07-22 19:57:59,275][50205] Updated weights for policy 0, policy_version 15702 (0.0016) +[2026-07-22 19:57:59,877][43431] Fps is (10 sec: 5120.1, 60 sec: 5461.3, 300 sec: 5345.6). Total num frames: 8040448. Throughput: 0: 5476.6. Samples: 8041004. Policy #0 lag: (min: 1.0, avg: 14.7, max: 33.0) +[2026-07-22 19:57:59,879][43431] Avg episode reward: [(0, '1633.557')] +[2026-07-22 19:58:00,220][50205] Updated weights for policy 0, policy_version 15712 (0.0011) +[2026-07-22 19:58:01,277][50205] Updated weights for policy 0, policy_version 15722 (0.0020) +[2026-07-22 19:58:01,721][50205] Updated weights for policy 0, policy_version 15732 (0.0012) +[2026-07-22 19:58:03,347][50205] Updated weights for policy 0, policy_version 15742 (0.0012) +[2026-07-22 19:58:04,078][50205] Updated weights for policy 0, policy_version 15752 (0.0011) +[2026-07-22 19:58:04,824][50205] Updated weights for policy 0, policy_version 15762 (0.0015) +[2026-07-22 19:58:04,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5529.6, 300 sec: 5359.5). Total num frames: 8071168. Throughput: 0: 5458.2. Samples: 8072990. Policy #0 lag: (min: 2.0, avg: 22.4, max: 46.0) +[2026-07-22 19:58:04,878][43431] Avg episode reward: [(0, '1665.049')] +[2026-07-22 19:58:05,825][50205] Updated weights for policy 0, policy_version 15772 (0.0017) +[2026-07-22 19:58:06,936][50205] Updated weights for policy 0, policy_version 15782 (0.0011) +[2026-07-22 19:58:07,563][50205] Updated weights for policy 0, policy_version 15792 (0.0020) +[2026-07-22 19:58:08,735][50205] Updated weights for policy 0, policy_version 15802 (0.0018) +[2026-07-22 19:58:09,445][50205] Updated weights for policy 0, policy_version 15812 (0.0011) +[2026-07-22 19:58:09,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5461.3, 300 sec: 5373.4). Total num frames: 8097792. Throughput: 0: 5515.0. Samples: 8106592. Policy #0 lag: (min: 2.0, avg: 22.4, max: 46.0) +[2026-07-22 19:58:09,878][43431] Avg episode reward: [(0, '1542.443')] +[2026-07-22 19:58:10,404][50205] Updated weights for policy 0, policy_version 15822 (0.0011) +[2026-07-22 19:58:11,270][50205] Updated weights for policy 0, policy_version 15832 (0.0010) +[2026-07-22 19:58:12,331][50205] Updated weights for policy 0, policy_version 15842 (0.0020) +[2026-07-22 19:58:13,032][50205] Updated weights for policy 0, policy_version 15852 (0.0012) +[2026-07-22 19:58:14,096][50205] Updated weights for policy 0, policy_version 15862 (0.0011) +[2026-07-22 19:58:14,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5495.5, 300 sec: 5366.5). Total num frames: 8124416. Throughput: 0: 5514.2. Samples: 8123392. Policy #0 lag: (min: 3.0, avg: 19.8, max: 43.0) +[2026-07-22 19:58:14,878][43431] Avg episode reward: [(0, '1687.268')] +[2026-07-22 19:58:14,988][50205] Updated weights for policy 0, policy_version 15872 (0.0010) +[2026-07-22 19:58:15,979][50205] Updated weights for policy 0, policy_version 15882 (0.0021) +[2026-07-22 19:58:16,750][50205] Updated weights for policy 0, policy_version 15892 (0.0024) +[2026-07-22 19:58:17,949][50205] Updated weights for policy 0, policy_version 15902 (0.0021) +[2026-07-22 19:58:18,417][50205] Updated weights for policy 0, policy_version 15912 (0.0011) +[2026-07-22 19:58:19,560][50205] Updated weights for policy 0, policy_version 15922 (0.0020) +[2026-07-22 19:58:19,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5373.4). Total num frames: 8153088. Throughput: 0: 5521.7. Samples: 8157160. Policy #0 lag: (min: 3.0, avg: 19.8, max: 43.0) +[2026-07-22 19:58:19,878][43431] Avg episode reward: [(0, '1765.882')] +[2026-07-22 19:58:20,388][50205] Updated weights for policy 0, policy_version 15932 (0.0011) +[2026-07-22 19:58:21,362][50205] Updated weights for policy 0, policy_version 15942 (0.0016) +[2026-07-22 19:58:22,193][50205] Updated weights for policy 0, policy_version 15952 (0.0011) +[2026-07-22 19:58:23,360][50205] Updated weights for policy 0, policy_version 15962 (0.0011) +[2026-07-22 19:58:23,942][50205] Updated weights for policy 0, policy_version 15972 (0.0012) +[2026-07-22 19:58:24,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5529.6, 300 sec: 5387.3). Total num frames: 8181760. Throughput: 0: 5522.2. Samples: 8190760. Policy #0 lag: (min: 1.0, avg: 19.2, max: 45.0) +[2026-07-22 19:58:24,878][43431] Avg episode reward: [(0, '1695.312')] +[2026-07-22 19:58:25,121][50205] Updated weights for policy 0, policy_version 15982 (0.0018) +[2026-07-22 19:58:25,929][50205] Updated weights for policy 0, policy_version 15992 (0.0012) +[2026-07-22 19:58:26,771][50205] Updated weights for policy 0, policy_version 16002 (0.0017) +[2026-07-22 19:58:27,696][50205] Updated weights for policy 0, policy_version 16012 (0.0015) +[2026-07-22 19:58:28,903][50205] Updated weights for policy 0, policy_version 16022 (0.0011) +[2026-07-22 19:58:29,519][50205] Updated weights for policy 0, policy_version 16032 (0.0011) +[2026-07-22 19:58:29,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5563.7, 300 sec: 5387.3). Total num frames: 8210432. Throughput: 0: 5518.8. Samples: 8207428. Policy #0 lag: (min: 1.0, avg: 19.2, max: 45.0) +[2026-07-22 19:58:29,878][43431] Avg episode reward: [(0, '1723.084')] +[2026-07-22 19:58:30,573][50205] Updated weights for policy 0, policy_version 16042 (0.0013) +[2026-07-22 19:58:31,705][50205] Updated weights for policy 0, policy_version 16052 (0.0011) +[2026-07-22 19:58:32,772][50205] Updated weights for policy 0, policy_version 16062 (0.0011) +[2026-07-22 19:58:33,595][50205] Updated weights for policy 0, policy_version 16072 (0.0016) +[2026-07-22 19:58:34,668][50205] Updated weights for policy 0, policy_version 16082 (0.0018) +[2026-07-22 19:58:34,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5495.5, 300 sec: 5380.4). Total num frames: 8235008. Throughput: 0: 5463.8. Samples: 8238690. Policy #0 lag: (min: 1.0, avg: 19.2, max: 45.0) +[2026-07-22 19:58:34,878][43431] Avg episode reward: [(0, '1740.283')] +[2026-07-22 19:58:35,509][50205] Updated weights for policy 0, policy_version 16092 (0.0016) +[2026-07-22 19:58:36,445][50205] Updated weights for policy 0, policy_version 16102 (0.0015) +[2026-07-22 19:58:37,358][50205] Updated weights for policy 0, policy_version 16112 (0.0018) +[2026-07-22 19:58:38,524][50205] Updated weights for policy 0, policy_version 16122 (0.0021) +[2026-07-22 19:58:39,036][50205] Updated weights for policy 0, policy_version 16132 (0.0013) +[2026-07-22 19:58:39,877][43431] Fps is (10 sec: 5119.9, 60 sec: 5461.3, 300 sec: 5380.3). Total num frames: 8261632. Throughput: 0: 5467.8. Samples: 8271948. Policy #0 lag: (min: 3.0, avg: 17.6, max: 39.0) +[2026-07-22 19:58:39,878][43431] Avg episode reward: [(0, '1696.494')] +[2026-07-22 19:58:40,283][50205] Updated weights for policy 0, policy_version 16142 (0.0021) +[2026-07-22 19:58:41,090][50205] Updated weights for policy 0, policy_version 16152 (0.0015) +[2026-07-22 19:58:41,884][50205] Updated weights for policy 0, policy_version 16162 (0.0011) +[2026-07-22 19:58:42,791][50205] Updated weights for policy 0, policy_version 16172 (0.0012) +[2026-07-22 19:58:43,914][50205] Updated weights for policy 0, policy_version 16182 (0.0017) +[2026-07-22 19:58:44,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5461.3, 300 sec: 5387.3). Total num frames: 8288256. Throughput: 0: 5505.1. Samples: 8288736. Policy #0 lag: (min: 3.0, avg: 17.6, max: 39.0) +[2026-07-22 19:58:44,878][43431] Avg episode reward: [(0, '1808.843')] +[2026-07-22 19:58:44,990][49527] Saving new best policy, reward=1808.843! +[2026-07-22 19:58:45,122][50205] Updated weights for policy 0, policy_version 16194 (0.0015) +[2026-07-22 19:58:45,740][50205] Updated weights for policy 0, policy_version 16204 (0.0011) +[2026-07-22 19:58:46,825][50205] Updated weights for policy 0, policy_version 16214 (0.0017) +[2026-07-22 19:58:47,752][50205] Updated weights for policy 0, policy_version 16224 (0.0011) +[2026-07-22 19:58:48,729][50205] Updated weights for policy 0, policy_version 16234 (0.0014) +[2026-07-22 19:58:49,631][50205] Updated weights for policy 0, policy_version 16245 (0.0011) +[2026-07-22 19:58:49,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5495.5, 300 sec: 5401.2). Total num frames: 8318976. Throughput: 0: 5534.0. Samples: 8322022. Policy #0 lag: (min: 3.0, avg: 20.0, max: 43.0) +[2026-07-22 19:58:49,878][43431] Avg episode reward: [(0, '1529.653')] +[2026-07-22 19:58:50,571][50205] Updated weights for policy 0, policy_version 16255 (0.0011) +[2026-07-22 19:58:51,814][50205] Updated weights for policy 0, policy_version 16265 (0.0010) +[2026-07-22 19:58:52,298][50205] Updated weights for policy 0, policy_version 16275 (0.0011) +[2026-07-22 19:58:53,329][50205] Updated weights for policy 0, policy_version 16285 (0.0011) +[2026-07-22 19:58:54,199][50205] Updated weights for policy 0, policy_version 16295 (0.0011) +[2026-07-22 19:58:54,880][43431] Fps is (10 sec: 5732.9, 60 sec: 5461.1, 300 sec: 5408.1). Total num frames: 8345600. Throughput: 0: 5538.3. Samples: 8355832. Policy #0 lag: (min: 3.0, avg: 20.0, max: 43.0) +[2026-07-22 19:58:54,881][43431] Avg episode reward: [(0, '1540.698')] +[2026-07-22 19:58:55,234][50205] Updated weights for policy 0, policy_version 16305 (0.0012) +[2026-07-22 19:58:56,033][50205] Updated weights for policy 0, policy_version 16315 (0.0015) +[2026-07-22 19:58:56,987][50205] Updated weights for policy 0, policy_version 16325 (0.0018) +[2026-07-22 19:58:58,114][50205] Updated weights for policy 0, policy_version 16335 (0.0017) +[2026-07-22 19:58:58,835][50205] Updated weights for policy 0, policy_version 16345 (0.0011) +[2026-07-22 19:58:59,495][50205] Updated weights for policy 0, policy_version 16355 (0.0012) +[2026-07-22 19:58:59,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5597.9, 300 sec: 5408.1). Total num frames: 8376320. Throughput: 0: 5539.0. Samples: 8372646. Policy #0 lag: (min: 1.0, avg: 18.1, max: 37.0) +[2026-07-22 19:58:59,878][43431] Avg episode reward: [(0, '1835.714')] +[2026-07-22 19:58:59,944][49527] Saving new best policy, reward=1835.714! +[2026-07-22 19:59:00,970][50205] Updated weights for policy 0, policy_version 16365 (0.0011) +[2026-07-22 19:59:01,500][50205] Updated weights for policy 0, policy_version 16375 (0.0011) +[2026-07-22 19:59:02,426][50205] Updated weights for policy 0, policy_version 16385 (0.0016) +[2026-07-22 19:59:03,476][50205] Updated weights for policy 0, policy_version 16395 (0.0017) +[2026-07-22 19:59:04,486][50205] Updated weights for policy 0, policy_version 16405 (0.0012) +[2026-07-22 19:59:04,877][43431] Fps is (10 sec: 5735.7, 60 sec: 5529.6, 300 sec: 5415.1). Total num frames: 8402944. Throughput: 0: 5526.9. Samples: 8405874. Policy #0 lag: (min: 1.0, avg: 18.1, max: 37.0) +[2026-07-22 19:59:04,878][43431] Avg episode reward: [(0, '1625.040')] +[2026-07-22 19:59:05,142][50205] Updated weights for policy 0, policy_version 16415 (0.0011) +[2026-07-22 19:59:06,378][50205] Updated weights for policy 0, policy_version 16425 (0.0016) +[2026-07-22 19:59:07,286][50205] Updated weights for policy 0, policy_version 16435 (0.0011) +[2026-07-22 19:59:08,329][50205] Updated weights for policy 0, policy_version 16445 (0.0016) +[2026-07-22 19:59:09,385][50205] Updated weights for policy 0, policy_version 16455 (0.0011) +[2026-07-22 19:59:09,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5495.5, 300 sec: 5422.0). Total num frames: 8427520. Throughput: 0: 5465.2. Samples: 8436694. Policy #0 lag: (min: 1.0, avg: 18.1, max: 37.0) +[2026-07-22 19:59:09,878][43431] Avg episode reward: [(0, '1567.829')] +[2026-07-22 19:59:10,249][50205] Updated weights for policy 0, policy_version 16465 (0.0015) +[2026-07-22 19:59:11,058][50205] Updated weights for policy 0, policy_version 16475 (0.0011) +[2026-07-22 19:59:12,343][50205] Updated weights for policy 0, policy_version 16485 (0.0011) +[2026-07-22 19:59:13,041][50205] Updated weights for policy 0, policy_version 16495 (0.0011) +[2026-07-22 19:59:13,906][50205] Updated weights for policy 0, policy_version 16505 (0.0011) +[2026-07-22 19:59:14,877][43431] Fps is (10 sec: 4915.3, 60 sec: 5461.3, 300 sec: 5401.2). Total num frames: 8452096. Throughput: 0: 5460.7. Samples: 8453162. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 19:59:14,878][43431] Avg episode reward: [(0, '1626.861')] +[2026-07-22 19:59:15,163][50205] Updated weights for policy 0, policy_version 16516 (0.0016) +[2026-07-22 19:59:15,975][50205] Updated weights for policy 0, policy_version 16526 (0.0016) +[2026-07-22 19:59:16,764][50205] Updated weights for policy 0, policy_version 16536 (0.0012) +[2026-07-22 19:59:18,093][50205] Updated weights for policy 0, policy_version 16546 (0.0015) +[2026-07-22 19:59:18,543][50205] Updated weights for policy 0, policy_version 16556 (0.0011) +[2026-07-22 19:59:19,691][50205] Updated weights for policy 0, policy_version 16566 (0.0011) +[2026-07-22 19:59:19,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5495.5, 300 sec: 5415.1). Total num frames: 8482816. Throughput: 0: 5508.2. Samples: 8486560. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 19:59:19,878][43431] Avg episode reward: [(0, '1644.557')] +[2026-07-22 19:59:20,766][50205] Updated weights for policy 0, policy_version 16576 (0.0019) +[2026-07-22 19:59:21,331][50205] Updated weights for policy 0, policy_version 16586 (0.0016) +[2026-07-22 19:59:22,246][50205] Updated weights for policy 0, policy_version 16596 (0.0015) +[2026-07-22 19:59:23,742][50205] Updated weights for policy 0, policy_version 16606 (0.0012) +[2026-07-22 19:59:24,141][50205] Updated weights for policy 0, policy_version 16616 (0.0016) +[2026-07-22 19:59:24,877][43431] Fps is (10 sec: 5939.3, 60 sec: 5495.5, 300 sec: 5435.9). Total num frames: 8511488. Throughput: 0: 5510.6. Samples: 8519926. Policy #0 lag: (min: 3.0, avg: 19.4, max: 35.0) +[2026-07-22 19:59:24,878][43431] Avg episode reward: [(0, '1712.747')] +[2026-07-22 19:59:25,071][50205] Updated weights for policy 0, policy_version 16626 (0.0011) +[2026-07-22 19:59:26,080][50205] Updated weights for policy 0, policy_version 16636 (0.0012) +[2026-07-22 19:59:27,087][50205] Updated weights for policy 0, policy_version 16647 (0.0015) +[2026-07-22 19:59:27,971][50205] Updated weights for policy 0, policy_version 16657 (0.0017) +[2026-07-22 19:59:29,165][50205] Updated weights for policy 0, policy_version 16667 (0.0011) +[2026-07-22 19:59:29,872][50205] Updated weights for policy 0, policy_version 16677 (0.0011) +[2026-07-22 19:59:29,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5461.3, 300 sec: 5428.9). Total num frames: 8538112. Throughput: 0: 5510.4. Samples: 8536702. Policy #0 lag: (min: 3.0, avg: 19.4, max: 35.0) +[2026-07-22 19:59:29,878][43431] Avg episode reward: [(0, '1630.302')] +[2026-07-22 19:59:30,684][50205] Updated weights for policy 0, policy_version 16687 (0.0011) +[2026-07-22 19:59:32,035][50205] Updated weights for policy 0, policy_version 16697 (0.0011) +[2026-07-22 19:59:32,459][50205] Updated weights for policy 0, policy_version 16707 (0.0012) +[2026-07-22 19:59:33,510][50205] Updated weights for policy 0, policy_version 16717 (0.0011) +[2026-07-22 19:59:34,569][50205] Updated weights for policy 0, policy_version 16727 (0.0012) +[2026-07-22 19:59:34,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5495.5, 300 sec: 5422.0). Total num frames: 8564736. Throughput: 0: 5519.5. Samples: 8570400. Policy #0 lag: (min: 3.0, avg: 18.2, max: 39.0) +[2026-07-22 19:59:34,878][43431] Avg episode reward: [(0, '1739.379')] +[2026-07-22 19:59:35,324][50205] Updated weights for policy 0, policy_version 16737 (0.0014) +[2026-07-22 19:59:36,335][50205] Updated weights for policy 0, policy_version 16749 (0.0017) +[2026-07-22 19:59:37,546][50205] Updated weights for policy 0, policy_version 16759 (0.0021) +[2026-07-22 19:59:38,395][50205] Updated weights for policy 0, policy_version 16769 (0.0026) +[2026-07-22 19:59:39,009][50205] Updated weights for policy 0, policy_version 16779 (0.0015) +[2026-07-22 19:59:39,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5529.6, 300 sec: 5442.8). Total num frames: 8593408. Throughput: 0: 5499.6. Samples: 8603300. Policy #0 lag: (min: 3.0, avg: 18.2, max: 39.0) +[2026-07-22 19:59:39,878][43431] Avg episode reward: [(0, '1635.006')] +[2026-07-22 19:59:40,517][50205] Updated weights for policy 0, policy_version 16789 (0.0016) +[2026-07-22 19:59:41,133][50205] Updated weights for policy 0, policy_version 16799 (0.0016) +[2026-07-22 19:59:42,154][50205] Updated weights for policy 0, policy_version 16809 (0.0011) +[2026-07-22 19:59:43,206][50205] Updated weights for policy 0, policy_version 16819 (0.0012) +[2026-07-22 19:59:44,619][50205] Updated weights for policy 0, policy_version 16829 (0.0011) +[2026-07-22 19:59:44,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5529.6, 300 sec: 5435.9). Total num frames: 8620032. Throughput: 0: 5465.1. Samples: 8618574. Policy #0 lag: (min: 3.0, avg: 18.2, max: 39.0) +[2026-07-22 19:59:44,878][43431] Avg episode reward: [(0, '1840.574')] +[2026-07-22 19:59:44,900][49527] Saving new best policy, reward=1840.574! +[2026-07-22 19:59:45,104][50205] Updated weights for policy 0, policy_version 16839 (0.0011) +[2026-07-22 19:59:46,149][50205] Updated weights for policy 0, policy_version 16849 (0.0016) +[2026-07-22 19:59:46,762][50205] Updated weights for policy 0, policy_version 16859 (0.0014) +[2026-07-22 19:59:47,900][50205] Updated weights for policy 0, policy_version 16869 (0.0011) +[2026-07-22 19:59:48,866][50205] Updated weights for policy 0, policy_version 16879 (0.0011) +[2026-07-22 19:59:49,764][50205] Updated weights for policy 0, policy_version 16889 (0.0016) +[2026-07-22 19:59:49,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5435.9). Total num frames: 8648704. Throughput: 0: 5465.7. Samples: 8651830. Policy #0 lag: (min: 3.0, avg: 19.5, max: 35.0) +[2026-07-22 19:59:49,878][43431] Avg episode reward: [(0, '1537.243')] +[2026-07-22 19:59:50,760][50205] Updated weights for policy 0, policy_version 16902 (0.0015) +[2026-07-22 19:59:51,879][50205] Updated weights for policy 0, policy_version 16912 (0.0012) +[2026-07-22 19:59:52,789][50205] Updated weights for policy 0, policy_version 16922 (0.0011) +[2026-07-22 19:59:53,597][50205] Updated weights for policy 0, policy_version 16933 (0.0012) +[2026-07-22 19:59:54,626][50205] Updated weights for policy 0, policy_version 16943 (0.0011) +[2026-07-22 19:59:54,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.7, 300 sec: 5442.8). Total num frames: 8675328. Throughput: 0: 5526.0. Samples: 8685362. Policy #0 lag: (min: 3.0, avg: 19.5, max: 35.0) +[2026-07-22 19:59:54,878][43431] Avg episode reward: [(0, '1588.264')] +[2026-07-22 19:59:55,625][50205] Updated weights for policy 0, policy_version 16953 (0.0021) +[2026-07-22 19:59:56,407][50205] Updated weights for policy 0, policy_version 16964 (0.0016) +[2026-07-22 19:59:57,574][50205] Updated weights for policy 0, policy_version 16974 (0.0013) +[2026-07-22 19:59:58,227][50205] Updated weights for policy 0, policy_version 16984 (0.0012) +[2026-07-22 19:59:59,205][50205] Updated weights for policy 0, policy_version 16994 (0.0013) +[2026-07-22 19:59:59,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5427.2, 300 sec: 5449.8). Total num frames: 8701952. Throughput: 0: 5532.7. Samples: 8702132. Policy #0 lag: (min: 3.0, avg: 18.8, max: 35.0) +[2026-07-22 19:59:59,879][43431] Avg episode reward: [(0, '1850.171')] +[2026-07-22 19:59:59,904][49527] Saving new best policy, reward=1850.171! +[2026-07-22 20:00:00,097][50205] Updated weights for policy 0, policy_version 17004 (0.0013) +[2026-07-22 20:00:01,035][50205] Updated weights for policy 0, policy_version 17014 (0.0014) +[2026-07-22 20:00:01,873][50205] Updated weights for policy 0, policy_version 17024 (0.0012) +[2026-07-22 20:00:03,152][50205] Updated weights for policy 0, policy_version 17034 (0.0015) +[2026-07-22 20:00:03,833][50205] Updated weights for policy 0, policy_version 17044 (0.0019) +[2026-07-22 20:00:04,783][50205] Updated weights for policy 0, policy_version 17054 (0.0011) +[2026-07-22 20:00:04,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5495.5, 300 sec: 5470.6). Total num frames: 8732672. Throughput: 0: 5531.5. Samples: 8735480. Policy #0 lag: (min: 3.0, avg: 18.8, max: 35.0) +[2026-07-22 20:00:04,878][43431] Avg episode reward: [(0, '1743.067')] +[2026-07-22 20:00:05,615][50205] Updated weights for policy 0, policy_version 17064 (0.0010) +[2026-07-22 20:00:06,800][50205] Updated weights for policy 0, policy_version 17074 (0.0011) +[2026-07-22 20:00:07,580][50205] Updated weights for policy 0, policy_version 17084 (0.0011) +[2026-07-22 20:00:08,505][50205] Updated weights for policy 0, policy_version 17094 (0.0011) +[2026-07-22 20:00:09,129][50205] Updated weights for policy 0, policy_version 17104 (0.0011) +[2026-07-22 20:00:09,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5529.6, 300 sec: 5470.6). Total num frames: 8759296. Throughput: 0: 5537.2. Samples: 8769100. Policy #0 lag: (min: 3.0, avg: 18.8, max: 35.0) +[2026-07-22 20:00:09,878][43431] Avg episode reward: [(0, '1572.651')] +[2026-07-22 20:00:10,489][50205] Updated weights for policy 0, policy_version 17114 (0.0011) +[2026-07-22 20:00:11,179][50205] Updated weights for policy 0, policy_version 17124 (0.0011) +[2026-07-22 20:00:12,080][50205] Updated weights for policy 0, policy_version 17134 (0.0015) +[2026-07-22 20:00:13,089][50205] Updated weights for policy 0, policy_version 17144 (0.0011) +[2026-07-22 20:00:14,214][50205] Updated weights for policy 0, policy_version 17154 (0.0011) +[2026-07-22 20:00:14,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5563.7, 300 sec: 5470.6). Total num frames: 8785920. Throughput: 0: 5534.0. Samples: 8785730. Policy #0 lag: (min: 3.0, avg: 19.1, max: 35.0) +[2026-07-22 20:00:14,878][43431] Avg episode reward: [(0, '1628.925')] +[2026-07-22 20:00:15,177][50205] Updated weights for policy 0, policy_version 17164 (0.0017) +[2026-07-22 20:00:16,256][50205] Updated weights for policy 0, policy_version 17174 (0.0011) +[2026-07-22 20:00:17,001][50205] Updated weights for policy 0, policy_version 17184 (0.0011) +[2026-07-22 20:00:18,270][50205] Updated weights for policy 0, policy_version 17194 (0.0020) +[2026-07-22 20:00:19,018][50205] Updated weights for policy 0, policy_version 17204 (0.0011) +[2026-07-22 20:00:19,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5495.5, 300 sec: 5477.5). Total num frames: 8812544. Throughput: 0: 5467.2. Samples: 8816422. Policy #0 lag: (min: 3.0, avg: 19.1, max: 35.0) +[2026-07-22 20:00:19,878][43431] Avg episode reward: [(0, '1721.765')] +[2026-07-22 20:00:20,122][50205] Updated weights for policy 0, policy_version 17214 (0.0011) +[2026-07-22 20:00:21,506][50205] Updated weights for policy 0, policy_version 17226 (0.0012) +[2026-07-22 20:00:22,315][50205] Updated weights for policy 0, policy_version 17236 (0.0011) +[2026-07-22 20:00:23,304][50205] Updated weights for policy 0, policy_version 17246 (0.0011) +[2026-07-22 20:00:23,983][50205] Updated weights for policy 0, policy_version 17256 (0.0015) +[2026-07-22 20:00:24,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5427.2, 300 sec: 5456.7). Total num frames: 8837120. Throughput: 0: 5437.4. Samples: 8847980. Policy #0 lag: (min: 0.0, avg: 17.8, max: 44.0) +[2026-07-22 20:00:24,878][43431] Avg episode reward: [(0, '1690.524')] +[2026-07-22 20:00:25,256][50205] Updated weights for policy 0, policy_version 17266 (0.0017) +[2026-07-22 20:00:25,955][50205] Updated weights for policy 0, policy_version 17276 (0.0014) +[2026-07-22 20:00:26,846][50205] Updated weights for policy 0, policy_version 17286 (0.0017) +[2026-07-22 20:00:27,865][50205] Updated weights for policy 0, policy_version 17296 (0.0015) +[2026-07-22 20:00:28,920][50205] Updated weights for policy 0, policy_version 17306 (0.0012) +[2026-07-22 20:00:29,444][50205] Updated weights for policy 0, policy_version 17316 (0.0011) +[2026-07-22 20:00:29,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5495.4, 300 sec: 5463.6). Total num frames: 8867840. Throughput: 0: 5472.2. Samples: 8864824. Policy #0 lag: (min: 0.0, avg: 17.8, max: 44.0) +[2026-07-22 20:00:29,878][43431] Avg episode reward: [(0, '1634.657')] +[2026-07-22 20:00:30,587][50205] Updated weights for policy 0, policy_version 17326 (0.0018) +[2026-07-22 20:00:31,563][50205] Updated weights for policy 0, policy_version 17336 (0.0013) +[2026-07-22 20:00:32,378][50205] Updated weights for policy 0, policy_version 17346 (0.0011) +[2026-07-22 20:00:33,027][50205] Updated weights for policy 0, policy_version 17356 (0.0016) +[2026-07-22 20:00:34,327][50205] Updated weights for policy 0, policy_version 17366 (0.0016) +[2026-07-22 20:00:34,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5461.3, 300 sec: 5470.6). Total num frames: 8892416. Throughput: 0: 5481.4. Samples: 8898492. Policy #0 lag: (min: 0.0, avg: 17.8, max: 44.0) +[2026-07-22 20:00:34,878][43431] Avg episode reward: [(0, '1759.693')] +[2026-07-22 20:00:35,219][50205] Updated weights for policy 0, policy_version 17377 (0.0011) +[2026-07-22 20:00:36,424][50205] Updated weights for policy 0, policy_version 17387 (0.0012) +[2026-07-22 20:00:37,272][50205] Updated weights for policy 0, policy_version 17397 (0.0010) +[2026-07-22 20:00:37,955][50205] Updated weights for policy 0, policy_version 17407 (0.0019) +[2026-07-22 20:00:39,036][50205] Updated weights for policy 0, policy_version 17417 (0.0020) +[2026-07-22 20:00:39,877][43431] Fps is (10 sec: 5325.0, 60 sec: 5461.4, 300 sec: 5477.5). Total num frames: 8921088. Throughput: 0: 5481.2. Samples: 8932014. Policy #0 lag: (min: 1.0, avg: 18.3, max: 33.0) +[2026-07-22 20:00:39,878][43431] Avg episode reward: [(0, '1851.905')] +[2026-07-22 20:00:39,902][50205] Updated weights for policy 0, policy_version 17427 (0.0013) +[2026-07-22 20:00:39,920][49527] Saving new best policy, reward=1851.905! +[2026-07-22 20:00:40,873][50205] Updated weights for policy 0, policy_version 17437 (0.0011) +[2026-07-22 20:00:41,395][50205] Updated weights for policy 0, policy_version 17447 (0.0024) +[2026-07-22 20:00:42,668][50205] Updated weights for policy 0, policy_version 17457 (0.0014) +[2026-07-22 20:00:43,514][50205] Updated weights for policy 0, policy_version 17467 (0.0011) +[2026-07-22 20:00:44,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5461.3, 300 sec: 5470.6). Total num frames: 8947712. Throughput: 0: 5474.8. Samples: 8948498. Policy #0 lag: (min: 1.0, avg: 18.3, max: 33.0) +[2026-07-22 20:00:44,879][43431] Avg episode reward: [(0, '1797.770')] +[2026-07-22 20:00:45,002][50205] Updated weights for policy 0, policy_version 17477 (0.0010) +[2026-07-22 20:00:45,937][50205] Updated weights for policy 0, policy_version 17491 (0.0011) +[2026-07-22 20:00:46,623][50205] Updated weights for policy 0, policy_version 17501 (0.0013) +[2026-07-22 20:00:47,586][50205] Updated weights for policy 0, policy_version 17511 (0.0014) +[2026-07-22 20:00:49,115][50205] Updated weights for policy 0, policy_version 17521 (0.0016) +[2026-07-22 20:00:49,492][50205] Updated weights for policy 0, policy_version 17531 (0.0014) +[2026-07-22 20:00:49,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5461.4, 300 sec: 5470.6). Total num frames: 8976384. Throughput: 0: 5454.0. Samples: 8980910. Policy #0 lag: (min: 1.0, avg: 17.6, max: 37.0) +[2026-07-22 20:00:49,878][43431] Avg episode reward: [(0, '1790.722')] +[2026-07-22 20:00:50,712][50205] Updated weights for policy 0, policy_version 17541 (0.0011) +[2026-07-22 20:00:51,888][50205] Updated weights for policy 0, policy_version 17551 (0.0011) +[2026-07-22 20:00:52,561][50205] Updated weights for policy 0, policy_version 17561 (0.0011) +[2026-07-22 20:00:53,571][50205] Updated weights for policy 0, policy_version 17571 (0.0014) +[2026-07-22 20:00:54,694][50205] Updated weights for policy 0, policy_version 17581 (0.0014) +[2026-07-22 20:00:54,887][43431] Fps is (10 sec: 5524.4, 60 sec: 5460.5, 300 sec: 5470.4). Total num frames: 9003008. Throughput: 0: 5420.8. Samples: 9013086. Policy #0 lag: (min: 1.0, avg: 17.6, max: 37.0) +[2026-07-22 20:00:54,888][43431] Avg episode reward: [(0, '1736.003')] +[2026-07-22 20:00:55,343][50205] Updated weights for policy 0, policy_version 17591 (0.0012) +[2026-07-22 20:00:56,318][50205] Updated weights for policy 0, policy_version 17601 (0.0011) +[2026-07-22 20:00:56,813][50205] Updated weights for policy 0, policy_version 17611 (0.0012) +[2026-07-22 20:00:58,194][50205] Updated weights for policy 0, policy_version 17621 (0.0026) +[2026-07-22 20:00:59,062][50205] Updated weights for policy 0, policy_version 17631 (0.0012) +[2026-07-22 20:00:59,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5477.5). Total num frames: 9031680. Throughput: 0: 5425.4. Samples: 9029874. Policy #0 lag: (min: 1.0, avg: 17.6, max: 37.0) +[2026-07-22 20:00:59,879][43431] Avg episode reward: [(0, '1680.368')] +[2026-07-22 20:01:00,209][50205] Updated weights for policy 0, policy_version 17641 (0.0011) +[2026-07-22 20:01:01,032][50205] Updated weights for policy 0, policy_version 17651 (0.0010) +[2026-07-22 20:01:02,030][50205] Updated weights for policy 0, policy_version 17664 (0.0011) +[2026-07-22 20:01:03,295][50205] Updated weights for policy 0, policy_version 17674 (0.0012) +[2026-07-22 20:01:04,005][50205] Updated weights for policy 0, policy_version 17684 (0.0011) +[2026-07-22 20:01:04,877][43431] Fps is (10 sec: 5534.9, 60 sec: 5427.2, 300 sec: 5484.5). Total num frames: 9058304. Throughput: 0: 5462.1. Samples: 9062218. Policy #0 lag: (min: 3.0, avg: 19.1, max: 39.0) +[2026-07-22 20:01:04,878][43431] Avg episode reward: [(0, '1580.132')] +[2026-07-22 20:01:05,052][50205] Updated weights for policy 0, policy_version 17694 (0.0011) +[2026-07-22 20:01:05,733][50205] Updated weights for policy 0, policy_version 17704 (0.0010) +[2026-07-22 20:01:06,814][50205] Updated weights for policy 0, policy_version 17714 (0.0015) +[2026-07-22 20:01:07,553][50205] Updated weights for policy 0, policy_version 17724 (0.0016) +[2026-07-22 20:01:08,706][50205] Updated weights for policy 0, policy_version 17734 (0.0012) +[2026-07-22 20:01:09,580][50205] Updated weights for policy 0, policy_version 17744 (0.0014) +[2026-07-22 20:01:09,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5427.2, 300 sec: 5491.4). Total num frames: 9084928. Throughput: 0: 5503.3. Samples: 9095630. Policy #0 lag: (min: 3.0, avg: 19.1, max: 39.0) +[2026-07-22 20:01:09,878][43431] Avg episode reward: [(0, '1720.081')] +[2026-07-22 20:01:10,578][50205] Updated weights for policy 0, policy_version 17754 (0.0017) +[2026-07-22 20:01:11,294][50205] Updated weights for policy 0, policy_version 17764 (0.0012) +[2026-07-22 20:01:12,425][50205] Updated weights for policy 0, policy_version 17774 (0.0011) +[2026-07-22 20:01:13,351][50205] Updated weights for policy 0, policy_version 17784 (0.0011) +[2026-07-22 20:01:14,194][50205] Updated weights for policy 0, policy_version 17794 (0.0011) +[2026-07-22 20:01:14,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5461.3, 300 sec: 5498.4). Total num frames: 9113600. Throughput: 0: 5496.7. Samples: 9112176. Policy #0 lag: (min: 1.0, avg: 17.6, max: 36.0) +[2026-07-22 20:01:14,878][43431] Avg episode reward: [(0, '1601.411')] +[2026-07-22 20:01:15,011][50205] Updated weights for policy 0, policy_version 17804 (0.0015) +[2026-07-22 20:01:16,162][50205] Updated weights for policy 0, policy_version 17814 (0.0012) +[2026-07-22 20:01:16,938][50205] Updated weights for policy 0, policy_version 17824 (0.0010) +[2026-07-22 20:01:18,084][50205] Updated weights for policy 0, policy_version 17834 (0.0013) +[2026-07-22 20:01:18,614][50205] Updated weights for policy 0, policy_version 17844 (0.0012) +[2026-07-22 20:01:19,730][50205] Updated weights for policy 0, policy_version 17854 (0.0017) +[2026-07-22 20:01:19,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5495.5, 300 sec: 5498.4). Total num frames: 9142272. Throughput: 0: 5490.8. Samples: 9145578. Policy #0 lag: (min: 1.0, avg: 17.6, max: 36.0) +[2026-07-22 20:01:19,878][43431] Avg episode reward: [(0, '1628.685')] +[2026-07-22 20:01:20,552][50205] Updated weights for policy 0, policy_version 17864 (0.0012) +[2026-07-22 20:01:21,706][50205] Updated weights for policy 0, policy_version 17874 (0.0011) +[2026-07-22 20:01:22,549][50205] Updated weights for policy 0, policy_version 17884 (0.0015) +[2026-07-22 20:01:23,972][50205] Updated weights for policy 0, policy_version 17894 (0.0010) +[2026-07-22 20:01:24,745][50205] Updated weights for policy 0, policy_version 17904 (0.0016) +[2026-07-22 20:01:24,882][43431] Fps is (10 sec: 5322.3, 60 sec: 5495.0, 300 sec: 5484.4). Total num frames: 9166848. Throughput: 0: 5413.3. Samples: 9175640. Policy #0 lag: (min: 1.0, avg: 17.6, max: 36.0) +[2026-07-22 20:01:24,882][43431] Avg episode reward: [(0, '1713.616')] +[2026-07-22 20:01:26,031][50205] Updated weights for policy 0, policy_version 17914 (0.0014) +[2026-07-22 20:01:26,998][50205] Updated weights for policy 0, policy_version 17924 (0.0017) +[2026-07-22 20:01:27,921][50205] Updated weights for policy 0, policy_version 17934 (0.0015) +[2026-07-22 20:01:28,792][50205] Updated weights for policy 0, policy_version 17944 (0.0020) +[2026-07-22 20:01:29,759][50205] Updated weights for policy 0, policy_version 17954 (0.0011) +[2026-07-22 20:01:29,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5427.2, 300 sec: 5477.5). Total num frames: 9193472. Throughput: 0: 5391.6. Samples: 9191116. Policy #0 lag: (min: 3.0, avg: 21.5, max: 43.0) +[2026-07-22 20:01:29,878][43431] Avg episode reward: [(0, '1535.067')] +[2026-07-22 20:01:30,563][50205] Updated weights for policy 0, policy_version 17964 (0.0017) +[2026-07-22 20:01:31,654][50205] Updated weights for policy 0, policy_version 17974 (0.0010) +[2026-07-22 20:01:32,496][50205] Updated weights for policy 0, policy_version 17984 (0.0011) +[2026-07-22 20:01:33,531][50205] Updated weights for policy 0, policy_version 17994 (0.0019) +[2026-07-22 20:01:34,308][50205] Updated weights for policy 0, policy_version 18004 (0.0011) +[2026-07-22 20:01:34,877][43431] Fps is (10 sec: 5532.2, 60 sec: 5495.5, 300 sec: 5484.5). Total num frames: 9222144. Throughput: 0: 5417.8. Samples: 9224712. Policy #0 lag: (min: 3.0, avg: 21.5, max: 43.0) +[2026-07-22 20:01:34,878][43431] Avg episode reward: [(0, '1589.102')] +[2026-07-22 20:01:35,295][50205] Updated weights for policy 0, policy_version 18015 (0.0016) +[2026-07-22 20:01:36,358][50205] Updated weights for policy 0, policy_version 18025 (0.0011) +[2026-07-22 20:01:37,302][50205] Updated weights for policy 0, policy_version 18035 (0.0018) +[2026-07-22 20:01:38,177][50205] Updated weights for policy 0, policy_version 18045 (0.0013) +[2026-07-22 20:01:39,048][50205] Updated weights for policy 0, policy_version 18055 (0.0012) +[2026-07-22 20:01:39,878][43431] Fps is (10 sec: 5324.4, 60 sec: 5427.1, 300 sec: 5484.5). Total num frames: 9246720. Throughput: 0: 5447.8. Samples: 9258190. Policy #0 lag: (min: 3.0, avg: 18.6, max: 35.0) +[2026-07-22 20:01:39,879][43431] Avg episode reward: [(0, '1669.343')] +[2026-07-22 20:01:40,110][50205] Updated weights for policy 0, policy_version 18065 (0.0018) +[2026-07-22 20:01:40,617][50205] Updated weights for policy 0, policy_version 18075 (0.0017) +[2026-07-22 20:01:41,911][50205] Updated weights for policy 0, policy_version 18085 (0.0012) +[2026-07-22 20:01:42,681][50205] Updated weights for policy 0, policy_version 18095 (0.0011) +[2026-07-22 20:01:43,481][50205] Updated weights for policy 0, policy_version 18105 (0.0011) +[2026-07-22 20:01:44,476][50205] Updated weights for policy 0, policy_version 18115 (0.0021) +[2026-07-22 20:01:44,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5491.4). Total num frames: 9277440. Throughput: 0: 5447.0. Samples: 9274988. Policy #0 lag: (min: 3.0, avg: 18.6, max: 35.0) +[2026-07-22 20:01:44,878][43431] Avg episode reward: [(0, '1809.251')] +[2026-07-22 20:01:45,741][50205] Updated weights for policy 0, policy_version 18125 (0.0010) +[2026-07-22 20:01:46,177][50205] Updated weights for policy 0, policy_version 18135 (0.0010) +[2026-07-22 20:01:47,401][50205] Updated weights for policy 0, policy_version 18145 (0.0010) +[2026-07-22 20:01:48,043][50205] Updated weights for policy 0, policy_version 18155 (0.0010) +[2026-07-22 20:01:49,007][50205] Updated weights for policy 0, policy_version 18165 (0.0010) +[2026-07-22 20:01:49,697][50205] Updated weights for policy 0, policy_version 18175 (0.0011) +[2026-07-22 20:01:49,877][43431] Fps is (10 sec: 5939.5, 60 sec: 5495.5, 300 sec: 5491.4). Total num frames: 9306112. Throughput: 0: 5477.9. Samples: 9308724. Policy #0 lag: (min: 3.0, avg: 18.6, max: 35.0) +[2026-07-22 20:01:49,878][43431] Avg episode reward: [(0, '1663.394')] +[2026-07-22 20:01:50,796][50205] Updated weights for policy 0, policy_version 18185 (0.0011) +[2026-07-22 20:01:51,789][50205] Updated weights for policy 0, policy_version 18195 (0.0011) +[2026-07-22 20:01:52,904][50205] Updated weights for policy 0, policy_version 18205 (0.0015) +[2026-07-22 20:01:53,533][50205] Updated weights for policy 0, policy_version 18215 (0.0011) +[2026-07-22 20:01:54,643][50205] Updated weights for policy 0, policy_version 18225 (0.0011) +[2026-07-22 20:01:54,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5496.3, 300 sec: 5491.4). Total num frames: 9332736. Throughput: 0: 5482.5. Samples: 9342342. Policy #0 lag: (min: 3.0, avg: 18.2, max: 39.0) +[2026-07-22 20:01:54,878][43431] Avg episode reward: [(0, '1716.774')] +[2026-07-22 20:01:55,364][50205] Updated weights for policy 0, policy_version 18235 (0.0011) +[2026-07-22 20:01:56,554][50205] Updated weights for policy 0, policy_version 18245 (0.0011) +[2026-07-22 20:01:57,125][50205] Updated weights for policy 0, policy_version 18255 (0.0011) +[2026-07-22 20:01:58,430][50205] Updated weights for policy 0, policy_version 18265 (0.0015) +[2026-07-22 20:01:59,184][50205] Updated weights for policy 0, policy_version 18275 (0.0020) +[2026-07-22 20:01:59,878][43431] Fps is (10 sec: 5324.7, 60 sec: 5461.3, 300 sec: 5491.4). Total num frames: 9359360. Throughput: 0: 5484.0. Samples: 9358958. Policy #0 lag: (min: 3.0, avg: 18.2, max: 39.0) +[2026-07-22 20:01:59,878][43431] Avg episode reward: [(0, '1674.341')] +[2026-07-22 20:02:00,282][50205] Updated weights for policy 0, policy_version 18285 (0.0016) +[2026-07-22 20:02:00,944][50205] Updated weights for policy 0, policy_version 18295 (0.0011) +[2026-07-22 20:02:02,471][50205] Updated weights for policy 0, policy_version 18305 (0.0020) +[2026-07-22 20:02:03,250][50205] Updated weights for policy 0, policy_version 18315 (0.0016) +[2026-07-22 20:02:04,209][50205] Updated weights for policy 0, policy_version 18325 (0.0016) +[2026-07-22 20:02:04,878][43431] Fps is (10 sec: 5324.7, 60 sec: 5461.3, 300 sec: 5477.5). Total num frames: 9385984. Throughput: 0: 5430.3. Samples: 9389944. Policy #0 lag: (min: 1.0, avg: 17.6, max: 34.0) +[2026-07-22 20:02:04,878][43431] Avg episode reward: [(0, '1616.498')] +[2026-07-22 20:02:05,041][50205] Updated weights for policy 0, policy_version 18335 (0.0011) +[2026-07-22 20:02:06,171][50205] Updated weights for policy 0, policy_version 18345 (0.0014) +[2026-07-22 20:02:06,624][50205] Updated weights for policy 0, policy_version 18355 (0.0011) +[2026-07-22 20:02:08,034][50205] Updated weights for policy 0, policy_version 18365 (0.0014) +[2026-07-22 20:02:08,947][50205] Updated weights for policy 0, policy_version 18375 (0.0011) +[2026-07-22 20:02:09,521][50205] Updated weights for policy 0, policy_version 18385 (0.0011) +[2026-07-22 20:02:09,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5495.5, 300 sec: 5491.4). Total num frames: 9414656. Throughput: 0: 5501.2. Samples: 9423168. Policy #0 lag: (min: 1.0, avg: 17.6, max: 34.0) +[2026-07-22 20:02:09,878][43431] Avg episode reward: [(0, '1761.435')] +[2026-07-22 20:02:10,604][50205] Updated weights for policy 0, policy_version 18395 (0.0021) +[2026-07-22 20:02:11,759][50205] Updated weights for policy 0, policy_version 18405 (0.0012) +[2026-07-22 20:02:12,227][50205] Updated weights for policy 0, policy_version 18415 (0.0011) +[2026-07-22 20:02:13,653][50205] Updated weights for policy 0, policy_version 18425 (0.0011) +[2026-07-22 20:02:14,330][50205] Updated weights for policy 0, policy_version 18435 (0.0016) +[2026-07-22 20:02:14,877][43431] Fps is (10 sec: 5529.8, 60 sec: 5461.3, 300 sec: 5484.5). Total num frames: 9441280. Throughput: 0: 5527.7. Samples: 9439862. Policy #0 lag: (min: 1.0, avg: 17.6, max: 34.0) +[2026-07-22 20:02:14,878][43431] Avg episode reward: [(0, '1590.339')] +[2026-07-22 20:02:15,133][50205] Updated weights for policy 0, policy_version 18445 (0.0011) +[2026-07-22 20:02:16,149][50205] Updated weights for policy 0, policy_version 18455 (0.0010) +[2026-07-22 20:02:17,394][50205] Updated weights for policy 0, policy_version 18465 (0.0011) +[2026-07-22 20:02:17,856][50205] Updated weights for policy 0, policy_version 18475 (0.0011) +[2026-07-22 20:02:18,954][50205] Updated weights for policy 0, policy_version 18485 (0.0011) +[2026-07-22 20:02:19,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5427.2, 300 sec: 5484.5). Total num frames: 9467904. Throughput: 0: 5528.0. Samples: 9473474. Policy #0 lag: (min: 3.0, avg: 16.8, max: 35.0) +[2026-07-22 20:02:19,878][43431] Avg episode reward: [(0, '1645.109')] +[2026-07-22 20:02:19,897][50205] Updated weights for policy 0, policy_version 18495 (0.0011) +[2026-07-22 20:02:21,179][50205] Updated weights for policy 0, policy_version 18509 (0.0016) +[2026-07-22 20:02:22,058][50205] Updated weights for policy 0, policy_version 18519 (0.0016) +[2026-07-22 20:02:23,337][50205] Updated weights for policy 0, policy_version 18529 (0.0011) +[2026-07-22 20:02:23,860][50205] Updated weights for policy 0, policy_version 18539 (0.0011) +[2026-07-22 20:02:24,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5495.9, 300 sec: 5491.4). Total num frames: 9496576. Throughput: 0: 5509.7. Samples: 9506124. Policy #0 lag: (min: 3.0, avg: 16.8, max: 35.0) +[2026-07-22 20:02:24,878][43431] Avg episode reward: [(0, '1581.106')] +[2026-07-22 20:02:25,032][50205] Updated weights for policy 0, policy_version 18549 (0.0011) +[2026-07-22 20:02:25,916][50205] Updated weights for policy 0, policy_version 18559 (0.0019) +[2026-07-22 20:02:26,912][50205] Updated weights for policy 0, policy_version 18569 (0.0011) +[2026-07-22 20:02:27,552][50205] Updated weights for policy 0, policy_version 18579 (0.0022) +[2026-07-22 20:02:28,778][50205] Updated weights for policy 0, policy_version 18589 (0.0015) +[2026-07-22 20:02:29,396][50205] Updated weights for policy 0, policy_version 18599 (0.0014) +[2026-07-22 20:02:29,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5484.5). Total num frames: 9523200. Throughput: 0: 5504.2. Samples: 9522676. Policy #0 lag: (min: 3.0, avg: 16.8, max: 35.0) +[2026-07-22 20:02:29,878][43431] Avg episode reward: [(0, '1546.984')] +[2026-07-22 20:02:30,496][50205] Updated weights for policy 0, policy_version 18609 (0.0011) +[2026-07-22 20:02:31,455][50205] Updated weights for policy 0, policy_version 18619 (0.0012) +[2026-07-22 20:02:32,210][50205] Updated weights for policy 0, policy_version 18629 (0.0010) +[2026-07-22 20:02:33,325][50205] Updated weights for policy 0, policy_version 18639 (0.0010) +[2026-07-22 20:02:34,681][50205] Updated weights for policy 0, policy_version 18649 (0.0016) +[2026-07-22 20:02:34,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5461.3, 300 sec: 5477.5). Total num frames: 9549824. Throughput: 0: 5472.6. Samples: 9554990. Policy #0 lag: (min: 1.0, avg: 18.1, max: 37.0) +[2026-07-22 20:02:34,878][43431] Avg episode reward: [(0, '1708.401')] +[2026-07-22 20:02:35,143][50205] Updated weights for policy 0, policy_version 18659 (0.0010) +[2026-07-22 20:02:36,436][50205] Updated weights for policy 0, policy_version 18669 (0.0011) +[2026-07-22 20:02:37,314][50205] Updated weights for policy 0, policy_version 18679 (0.0016) +[2026-07-22 20:02:38,325][50205] Updated weights for policy 0, policy_version 18689 (0.0012) +[2026-07-22 20:02:39,131][50205] Updated weights for policy 0, policy_version 18699 (0.0011) +[2026-07-22 20:02:39,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5529.6, 300 sec: 5484.5). Total num frames: 9578496. Throughput: 0: 5441.3. Samples: 9587200. Policy #0 lag: (min: 1.0, avg: 18.1, max: 37.0) +[2026-07-22 20:02:39,878][43431] Avg episode reward: [(0, '1572.972')] +[2026-07-22 20:02:39,892][49527] Saving results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/checkpoint_p0/checkpoint_000018708_9578496.pth... +[2026-07-22 20:02:40,443][50205] Updated weights for policy 0, policy_version 18709 (0.0011) +[2026-07-22 20:02:41,087][50205] Updated weights for policy 0, policy_version 18721 (0.0011) +[2026-07-22 20:02:42,194][50205] Updated weights for policy 0, policy_version 18731 (0.0013) +[2026-07-22 20:02:43,267][50205] Updated weights for policy 0, policy_version 18741 (0.0013) +[2026-07-22 20:02:43,716][50205] Updated weights for policy 0, policy_version 18751 (0.0013) +[2026-07-22 20:02:44,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5427.2, 300 sec: 5470.6). Total num frames: 9603072. Throughput: 0: 5439.7. Samples: 9603744. Policy #0 lag: (min: 6.0, avg: 17.9, max: 38.0) +[2026-07-22 20:02:44,878][43431] Avg episode reward: [(0, '1768.126')] +[2026-07-22 20:02:45,132][50205] Updated weights for policy 0, policy_version 18761 (0.0011) +[2026-07-22 20:02:46,038][50205] Updated weights for policy 0, policy_version 18771 (0.0018) +[2026-07-22 20:02:46,844][50205] Updated weights for policy 0, policy_version 18781 (0.0010) +[2026-07-22 20:02:47,554][50205] Updated weights for policy 0, policy_version 18791 (0.0019) +[2026-07-22 20:02:48,972][50205] Updated weights for policy 0, policy_version 18801 (0.0011) +[2026-07-22 20:02:49,529][50205] Updated weights for policy 0, policy_version 18811 (0.0011) +[2026-07-22 20:02:49,877][43431] Fps is (10 sec: 5529.8, 60 sec: 5461.3, 300 sec: 5477.5). Total num frames: 9633792. Throughput: 0: 5474.2. Samples: 9636280. Policy #0 lag: (min: 6.0, avg: 17.9, max: 38.0) +[2026-07-22 20:02:49,878][43431] Avg episode reward: [(0, '1750.811')] +[2026-07-22 20:02:50,442][50205] Updated weights for policy 0, policy_version 18821 (0.0015) +[2026-07-22 20:02:51,476][50205] Updated weights for policy 0, policy_version 18831 (0.0011) +[2026-07-22 20:02:52,481][50205] Updated weights for policy 0, policy_version 18841 (0.0016) +[2026-07-22 20:02:53,188][50205] Updated weights for policy 0, policy_version 18851 (0.0011) +[2026-07-22 20:02:54,244][50205] Updated weights for policy 0, policy_version 18861 (0.0011) +[2026-07-22 20:02:54,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5461.3, 300 sec: 5491.4). Total num frames: 9660416. Throughput: 0: 5485.1. Samples: 9669998. Policy #0 lag: (min: 6.0, avg: 17.9, max: 38.0) +[2026-07-22 20:02:54,878][43431] Avg episode reward: [(0, '1686.205')] +[2026-07-22 20:02:55,083][50205] Updated weights for policy 0, policy_version 18871 (0.0018) +[2026-07-22 20:02:55,963][50205] Updated weights for policy 0, policy_version 18881 (0.0012) +[2026-07-22 20:02:57,056][50205] Updated weights for policy 0, policy_version 18891 (0.0011) +[2026-07-22 20:02:57,864][50205] Updated weights for policy 0, policy_version 18901 (0.0011) +[2026-07-22 20:02:58,703][50205] Updated weights for policy 0, policy_version 18911 (0.0011) +[2026-07-22 20:02:59,820][50205] Updated weights for policy 0, policy_version 18921 (0.0011) +[2026-07-22 20:02:59,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5461.4, 300 sec: 5477.5). Total num frames: 9687040. Throughput: 0: 5488.7. Samples: 9686852. Policy #0 lag: (min: 3.0, avg: 18.8, max: 39.0) +[2026-07-22 20:02:59,878][43431] Avg episode reward: [(0, '1603.984')] +[2026-07-22 20:03:00,672][50205] Updated weights for policy 0, policy_version 18931 (0.0011) +[2026-07-22 20:03:01,571][50205] Updated weights for policy 0, policy_version 18941 (0.0020) +[2026-07-22 20:03:03,028][50205] Updated weights for policy 0, policy_version 18953 (0.0010) +[2026-07-22 20:03:03,731][50205] Updated weights for policy 0, policy_version 18963 (0.0016) +[2026-07-22 20:03:04,682][50205] Updated weights for policy 0, policy_version 18973 (0.0014) +[2026-07-22 20:03:04,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5484.5). Total num frames: 9715712. Throughput: 0: 5463.5. Samples: 9719332. Policy #0 lag: (min: 3.0, avg: 18.8, max: 39.0) +[2026-07-22 20:03:04,878][43431] Avg episode reward: [(0, '1771.195')] +[2026-07-22 20:03:05,482][50205] Updated weights for policy 0, policy_version 18983 (0.0011) +[2026-07-22 20:03:06,523][50205] Updated weights for policy 0, policy_version 18993 (0.0011) +[2026-07-22 20:03:07,245][50205] Updated weights for policy 0, policy_version 19003 (0.0011) +[2026-07-22 20:03:08,393][50205] Updated weights for policy 0, policy_version 19013 (0.0015) +[2026-07-22 20:03:09,564][50205] Updated weights for policy 0, policy_version 19023 (0.0013) +[2026-07-22 20:03:09,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5461.3, 300 sec: 5484.5). Total num frames: 9742336. Throughput: 0: 5451.9. Samples: 9751456. Policy #0 lag: (min: 3.0, avg: 17.4, max: 35.0) +[2026-07-22 20:03:09,878][43431] Avg episode reward: [(0, '1607.991')] +[2026-07-22 20:03:10,158][50205] Updated weights for policy 0, policy_version 19033 (0.0015) +[2026-07-22 20:03:11,297][50205] Updated weights for policy 0, policy_version 19043 (0.0015) +[2026-07-22 20:03:12,558][50205] Updated weights for policy 0, policy_version 19053 (0.0011) +[2026-07-22 20:03:13,047][50205] Updated weights for policy 0, policy_version 19063 (0.0013) +[2026-07-22 20:03:14,058][50205] Updated weights for policy 0, policy_version 19073 (0.0011) +[2026-07-22 20:03:14,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5427.2, 300 sec: 5470.6). Total num frames: 9766912. Throughput: 0: 5436.6. Samples: 9767322. Policy #0 lag: (min: 3.0, avg: 17.4, max: 35.0) +[2026-07-22 20:03:14,878][43431] Avg episode reward: [(0, '1639.877')] +[2026-07-22 20:03:15,497][50205] Updated weights for policy 0, policy_version 19083 (0.0011) +[2026-07-22 20:03:15,838][49527] Signal inference workers to stop experience collection... (300 times) +[2026-07-22 20:03:15,839][49527] Signal inference workers to resume experience collection... (300 times) +[2026-07-22 20:03:15,855][50205] InferenceWorker_p0-w0: stopping experience collection (300 times) +[2026-07-22 20:03:15,855][50205] InferenceWorker_p0-w0: resuming experience collection (300 times) +[2026-07-22 20:03:15,878][50205] Updated weights for policy 0, policy_version 19093 (0.0011) +[2026-07-22 20:03:16,900][50205] Updated weights for policy 0, policy_version 19103 (0.0014) +[2026-07-22 20:03:18,311][50205] Updated weights for policy 0, policy_version 19113 (0.0011) +[2026-07-22 20:03:18,672][50205] Updated weights for policy 0, policy_version 19123 (0.0013) +[2026-07-22 20:03:19,572][50205] Updated weights for policy 0, policy_version 19133 (0.0019) +[2026-07-22 20:03:19,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5495.5, 300 sec: 5477.5). Total num frames: 9797632. Throughput: 0: 5462.9. Samples: 9800822. Policy #0 lag: (min: 3.0, avg: 17.4, max: 35.0) +[2026-07-22 20:03:19,878][43431] Avg episode reward: [(0, '1628.772')] +[2026-07-22 20:03:20,441][50205] Updated weights for policy 0, policy_version 19143 (0.0011) +[2026-07-22 20:03:21,480][50205] Updated weights for policy 0, policy_version 19153 (0.0011) +[2026-07-22 20:03:22,518][50205] Updated weights for policy 0, policy_version 19163 (0.0015) +[2026-07-22 20:03:23,145][50205] Updated weights for policy 0, policy_version 19173 (0.0011) +[2026-07-22 20:03:24,196][50205] Updated weights for policy 0, policy_version 19183 (0.0016) +[2026-07-22 20:03:24,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5495.5, 300 sec: 5477.5). Total num frames: 9826304. Throughput: 0: 5493.5. Samples: 9834404. Policy #0 lag: (min: 3.0, avg: 23.4, max: 47.0) +[2026-07-22 20:03:24,878][43431] Avg episode reward: [(0, '1668.328')] +[2026-07-22 20:03:25,269][50205] Updated weights for policy 0, policy_version 19193 (0.0010) +[2026-07-22 20:03:25,921][50205] Updated weights for policy 0, policy_version 19203 (0.0012) +[2026-07-22 20:03:26,989][50205] Updated weights for policy 0, policy_version 19213 (0.0016) +[2026-07-22 20:03:27,691][50205] Updated weights for policy 0, policy_version 19223 (0.0011) +[2026-07-22 20:03:28,797][50205] Updated weights for policy 0, policy_version 19233 (0.0011) +[2026-07-22 20:03:29,766][50205] Updated weights for policy 0, policy_version 19243 (0.0016) +[2026-07-22 20:03:29,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5484.5). Total num frames: 9852928. Throughput: 0: 5500.7. Samples: 9851274. Policy #0 lag: (min: 3.0, avg: 23.4, max: 47.0) +[2026-07-22 20:03:29,878][43431] Avg episode reward: [(0, '1621.158')] +[2026-07-22 20:03:30,485][50205] Updated weights for policy 0, policy_version 19253 (0.0011) +[2026-07-22 20:03:31,453][50205] Updated weights for policy 0, policy_version 19263 (0.0011) +[2026-07-22 20:03:32,600][50205] Updated weights for policy 0, policy_version 19273 (0.0011) +[2026-07-22 20:03:33,228][50205] Updated weights for policy 0, policy_version 19283 (0.0021) +[2026-07-22 20:03:34,385][50205] Updated weights for policy 0, policy_version 19294 (0.0017) +[2026-07-22 20:03:34,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5529.6, 300 sec: 5491.4). Total num frames: 9881600. Throughput: 0: 5527.1. Samples: 9885000. Policy #0 lag: (min: 3.0, avg: 23.4, max: 47.0) +[2026-07-22 20:03:34,878][43431] Avg episode reward: [(0, '1793.614')] +[2026-07-22 20:03:35,293][50205] Updated weights for policy 0, policy_version 19304 (0.0011) +[2026-07-22 20:03:36,079][50205] Updated weights for policy 0, policy_version 19314 (0.0019) +[2026-07-22 20:03:37,176][50205] Updated weights for policy 0, policy_version 19324 (0.0011) +[2026-07-22 20:03:38,088][50205] Updated weights for policy 0, policy_version 19334 (0.0021) +[2026-07-22 20:03:38,715][50205] Updated weights for policy 0, policy_version 19344 (0.0011) +[2026-07-22 20:03:39,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5491.4). Total num frames: 9908224. Throughput: 0: 5525.8. Samples: 9918660. Policy #0 lag: (min: 3.0, avg: 15.1, max: 31.0) +[2026-07-22 20:03:39,878][43431] Avg episode reward: [(0, '1662.028')] +[2026-07-22 20:03:40,023][50205] Updated weights for policy 0, policy_version 19354 (0.0015) +[2026-07-22 20:03:40,744][50205] Updated weights for policy 0, policy_version 19364 (0.0010) +[2026-07-22 20:03:41,387][50205] Updated weights for policy 0, policy_version 19374 (0.0011) +[2026-07-22 20:03:42,641][50205] Updated weights for policy 0, policy_version 19384 (0.0016) +[2026-07-22 20:03:43,690][50205] Updated weights for policy 0, policy_version 19394 (0.0011) +[2026-07-22 20:03:44,227][50205] Updated weights for policy 0, policy_version 19404 (0.0022) +[2026-07-22 20:03:44,881][43431] Fps is (10 sec: 5527.7, 60 sec: 5563.4, 300 sec: 5484.4). Total num frames: 9936896. Throughput: 0: 5526.3. Samples: 9935556. Policy #0 lag: (min: 3.0, avg: 15.1, max: 31.0) +[2026-07-22 20:03:44,881][43431] Avg episode reward: [(0, '1660.369')] +[2026-07-22 20:03:45,987][50205] Updated weights for policy 0, policy_version 19414 (0.0011) +[2026-07-22 20:03:46,542][50205] Updated weights for policy 0, policy_version 19424 (0.0015) +[2026-07-22 20:03:47,350][50205] Updated weights for policy 0, policy_version 19435 (0.0018) +[2026-07-22 20:03:49,032][50205] Updated weights for policy 0, policy_version 19445 (0.0011) +[2026-07-22 20:03:49,597][50205] Updated weights for policy 0, policy_version 19455 (0.0018) +[2026-07-22 20:03:49,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5484.5). Total num frames: 9963520. Throughput: 0: 5496.7. Samples: 9966684. Policy #0 lag: (min: 3.0, avg: 15.1, max: 31.0) +[2026-07-22 20:03:49,878][43431] Avg episode reward: [(0, '1647.067')] +[2026-07-22 20:03:50,391][50205] Updated weights for policy 0, policy_version 19465 (0.0012) +[2026-07-22 20:03:51,489][50205] Updated weights for policy 0, policy_version 19475 (0.0015) +[2026-07-22 20:03:52,416][50205] Updated weights for policy 0, policy_version 19485 (0.0018) +[2026-07-22 20:03:53,032][50205] Updated weights for policy 0, policy_version 19495 (0.0019) +[2026-07-22 20:03:54,421][50205] Updated weights for policy 0, policy_version 19505 (0.0011) +[2026-07-22 20:03:54,877][43431] Fps is (10 sec: 5326.7, 60 sec: 5495.5, 300 sec: 5470.6). Total num frames: 9990144. Throughput: 0: 5529.4. Samples: 10000278. Policy #0 lag: (min: 3.0, avg: 20.0, max: 35.0) +[2026-07-22 20:03:54,878][43431] Avg episode reward: [(0, '1644.936')] +[2026-07-22 20:03:55,151][50205] Updated weights for policy 0, policy_version 19515 (0.0011) +[2026-07-22 20:03:55,790][50205] Updated weights for policy 0, policy_version 19525 (0.0020) +[2026-07-22 20:03:56,633][50205] Updated weights for policy 0, policy_version 19535 (0.0011) +[2026-07-22 20:03:57,895][50205] Updated weights for policy 0, policy_version 19545 (0.0012) +[2026-07-22 20:03:58,632][50205] Updated weights for policy 0, policy_version 19555 (0.0015) +[2026-07-22 20:03:59,440][50205] Updated weights for policy 0, policy_version 19565 (0.0011) +[2026-07-22 20:03:59,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5529.6, 300 sec: 5477.5). Total num frames: 10018816. Throughput: 0: 5553.5. Samples: 10017228. Policy #0 lag: (min: 3.0, avg: 20.0, max: 35.0) +[2026-07-22 20:03:59,878][43431] Avg episode reward: [(0, '1618.993')] +[2026-07-22 20:04:00,435][50205] Updated weights for policy 0, policy_version 19575 (0.0011) +[2026-07-22 20:04:01,438][50205] Updated weights for policy 0, policy_version 19585 (0.0012) +[2026-07-22 20:04:03,131][50205] Updated weights for policy 0, policy_version 19598 (0.0011) +[2026-07-22 20:04:03,816][50205] Updated weights for policy 0, policy_version 19608 (0.0015) +[2026-07-22 20:04:04,691][50205] Updated weights for policy 0, policy_version 19618 (0.0011) +[2026-07-22 20:04:04,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5484.5). Total num frames: 10045440. Throughput: 0: 5505.7. Samples: 10048578. Policy #0 lag: (min: 3.0, avg: 19.9, max: 35.0) +[2026-07-22 20:04:04,878][43431] Avg episode reward: [(0, '1757.142')] +[2026-07-22 20:04:05,538][50205] Updated weights for policy 0, policy_version 19628 (0.0011) +[2026-07-22 20:04:07,172][50205] Updated weights for policy 0, policy_version 19641 (0.0011) +[2026-07-22 20:04:08,125][50205] Updated weights for policy 0, policy_version 19651 (0.0011) +[2026-07-22 20:04:09,195][50205] Updated weights for policy 0, policy_version 19661 (0.0016) +[2026-07-22 20:04:09,877][43431] Fps is (10 sec: 5119.9, 60 sec: 5461.3, 300 sec: 5484.5). Total num frames: 10070016. Throughput: 0: 5467.3. Samples: 10080432. Policy #0 lag: (min: 3.0, avg: 19.9, max: 35.0) +[2026-07-22 20:04:09,878][43431] Avg episode reward: [(0, '1694.637')] +[2026-07-22 20:04:10,015][50205] Updated weights for policy 0, policy_version 19671 (0.0016) +[2026-07-22 20:04:10,717][50205] Updated weights for policy 0, policy_version 19681 (0.0016) +[2026-07-22 20:04:11,864][50205] Updated weights for policy 0, policy_version 19691 (0.0015) +[2026-07-22 20:04:12,800][50205] Updated weights for policy 0, policy_version 19701 (0.0011) +[2026-07-22 20:04:13,541][50205] Updated weights for policy 0, policy_version 19711 (0.0011) +[2026-07-22 20:04:14,691][50205] Updated weights for policy 0, policy_version 19721 (0.0016) +[2026-07-22 20:04:14,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5529.6, 300 sec: 5477.5). Total num frames: 10098688. Throughput: 0: 5466.5. Samples: 10097268. Policy #0 lag: (min: 3.0, avg: 19.9, max: 35.0) +[2026-07-22 20:04:14,878][43431] Avg episode reward: [(0, '1634.508')] +[2026-07-22 20:04:15,354][50205] Updated weights for policy 0, policy_version 19731 (0.0012) +[2026-07-22 20:04:16,240][50205] Updated weights for policy 0, policy_version 19741 (0.0017) +[2026-07-22 20:04:17,548][50205] Updated weights for policy 0, policy_version 19751 (0.0011) +[2026-07-22 20:04:18,381][50205] Updated weights for policy 0, policy_version 19761 (0.0015) +[2026-07-22 20:04:19,230][50205] Updated weights for policy 0, policy_version 19771 (0.0010) +[2026-07-22 20:04:19,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5461.3, 300 sec: 5470.6). Total num frames: 10125312. Throughput: 0: 5438.5. Samples: 10129734. Policy #0 lag: (min: 4.0, avg: 17.0, max: 33.0) +[2026-07-22 20:04:19,878][43431] Avg episode reward: [(0, '1774.695')] +[2026-07-22 20:04:20,474][50205] Updated weights for policy 0, policy_version 19781 (0.0011) +[2026-07-22 20:04:21,483][50205] Updated weights for policy 0, policy_version 19791 (0.0016) +[2026-07-22 20:04:22,116][50205] Updated weights for policy 0, policy_version 19801 (0.0016) +[2026-07-22 20:04:23,042][50205] Updated weights for policy 0, policy_version 19811 (0.0010) +[2026-07-22 20:04:24,374][50205] Updated weights for policy 0, policy_version 19821 (0.0011) +[2026-07-22 20:04:24,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5427.2, 300 sec: 5470.6). Total num frames: 10151936. Throughput: 0: 5412.4. Samples: 10162218. Policy #0 lag: (min: 4.0, avg: 17.0, max: 33.0) +[2026-07-22 20:04:24,879][43431] Avg episode reward: [(0, '1615.687')] +[2026-07-22 20:04:24,931][50205] Updated weights for policy 0, policy_version 19831 (0.0016) +[2026-07-22 20:04:26,012][50205] Updated weights for policy 0, policy_version 19841 (0.0019) +[2026-07-22 20:04:26,634][50205] Updated weights for policy 0, policy_version 19851 (0.0011) +[2026-07-22 20:04:27,666][50205] Updated weights for policy 0, policy_version 19861 (0.0015) +[2026-07-22 20:04:28,479][50205] Updated weights for policy 0, policy_version 19871 (0.0022) +[2026-07-22 20:04:29,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5427.2, 300 sec: 5470.6). Total num frames: 10178560. Throughput: 0: 5409.9. Samples: 10178984. Policy #0 lag: (min: 4.0, avg: 17.0, max: 33.0) +[2026-07-22 20:04:29,878][43431] Avg episode reward: [(0, '1689.465')] +[2026-07-22 20:04:29,917][50205] Updated weights for policy 0, policy_version 19881 (0.0013) +[2026-07-22 20:04:30,510][50205] Updated weights for policy 0, policy_version 19892 (0.0017) +[2026-07-22 20:04:32,233][50205] Updated weights for policy 0, policy_version 19905 (0.0012) +[2026-07-22 20:04:33,204][50205] Updated weights for policy 0, policy_version 19915 (0.0012) +[2026-07-22 20:04:33,870][50205] Updated weights for policy 0, policy_version 19925 (0.0011) +[2026-07-22 20:04:34,454][50205] Updated weights for policy 0, policy_version 19935 (0.0028) +[2026-07-22 20:04:34,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5427.2, 300 sec: 5470.6). Total num frames: 10207232. Throughput: 0: 5423.2. Samples: 10210730. Policy #0 lag: (min: 3.0, avg: 22.5, max: 41.0) +[2026-07-22 20:04:34,878][43431] Avg episode reward: [(0, '1628.994')] +[2026-07-22 20:04:36,161][50205] Updated weights for policy 0, policy_version 19945 (0.0011) +[2026-07-22 20:04:36,529][50205] Updated weights for policy 0, policy_version 19955 (0.0013) +[2026-07-22 20:04:37,399][50205] Updated weights for policy 0, policy_version 19965 (0.0011) +[2026-07-22 20:04:38,589][50205] Updated weights for policy 0, policy_version 19975 (0.0013) +[2026-07-22 20:04:39,466][50205] Updated weights for policy 0, policy_version 19985 (0.0012) +[2026-07-22 20:04:39,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5461.3, 300 sec: 5477.5). Total num frames: 10235904. Throughput: 0: 5426.2. Samples: 10244456. Policy #0 lag: (min: 3.0, avg: 22.5, max: 41.0) +[2026-07-22 20:04:39,878][43431] Avg episode reward: [(0, '1642.555')] +[2026-07-22 20:04:40,061][50205] Updated weights for policy 0, policy_version 19995 (0.0011) +[2026-07-22 20:04:41,365][50205] Updated weights for policy 0, policy_version 20005 (0.0011) +[2026-07-22 20:04:42,315][50205] Updated weights for policy 0, policy_version 20017 (0.0011) +[2026-07-22 20:04:43,132][50205] Updated weights for policy 0, policy_version 20027 (0.0014) +[2026-07-22 20:04:44,878][43431] Fps is (10 sec: 5119.8, 60 sec: 5359.2, 300 sec: 5456.7). Total num frames: 10258432. Throughput: 0: 5418.3. Samples: 10261052. Policy #0 lag: (min: 3.0, avg: 22.5, max: 41.0) +[2026-07-22 20:04:44,878][43431] Avg episode reward: [(0, '1497.493')] +[2026-07-22 20:04:45,060][50205] Updated weights for policy 0, policy_version 20037 (0.0016) +[2026-07-22 20:04:45,463][50205] Updated weights for policy 0, policy_version 20051 (0.0021) +[2026-07-22 20:04:46,233][50205] Updated weights for policy 0, policy_version 20061 (0.0012) +[2026-07-22 20:04:47,490][50205] Updated weights for policy 0, policy_version 20071 (0.0010) +[2026-07-22 20:04:48,291][50205] Updated weights for policy 0, policy_version 20081 (0.0011) +[2026-07-22 20:04:48,883][50205] Updated weights for policy 0, policy_version 20091 (0.0019) +[2026-07-22 20:04:49,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5427.2, 300 sec: 5470.6). Total num frames: 10289152. Throughput: 0: 5458.4. Samples: 10294206. Policy #0 lag: (min: 3.0, avg: 15.2, max: 35.0) +[2026-07-22 20:04:49,878][43431] Avg episode reward: [(0, '1735.792')] +[2026-07-22 20:04:50,418][50205] Updated weights for policy 0, policy_version 20101 (0.0020) +[2026-07-22 20:04:51,020][50205] Updated weights for policy 0, policy_version 20111 (0.0020) +[2026-07-22 20:04:52,031][50205] Updated weights for policy 0, policy_version 20121 (0.0012) +[2026-07-22 20:04:53,366][50205] Updated weights for policy 0, policy_version 20131 (0.0014) +[2026-07-22 20:04:54,251][50205] Updated weights for policy 0, policy_version 20141 (0.0011) +[2026-07-22 20:04:54,809][50205] Updated weights for policy 0, policy_version 20151 (0.0016) +[2026-07-22 20:04:54,877][43431] Fps is (10 sec: 5939.4, 60 sec: 5461.3, 300 sec: 5477.5). Total num frames: 10317824. Throughput: 0: 5442.0. Samples: 10325322. Policy #0 lag: (min: 3.0, avg: 15.2, max: 35.0) +[2026-07-22 20:04:54,878][43431] Avg episode reward: [(0, '1577.075')] +[2026-07-22 20:04:56,301][50205] Updated weights for policy 0, policy_version 20161 (0.0012) +[2026-07-22 20:04:57,063][50205] Updated weights for policy 0, policy_version 20171 (0.0014) +[2026-07-22 20:04:57,791][50205] Updated weights for policy 0, policy_version 20181 (0.0011) +[2026-07-22 20:04:58,522][50205] Updated weights for policy 0, policy_version 20191 (0.0011) +[2026-07-22 20:04:59,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5393.1, 300 sec: 5456.7). Total num frames: 10342400. Throughput: 0: 5434.4. Samples: 10341818. Policy #0 lag: (min: 3.0, avg: 16.6, max: 35.0) +[2026-07-22 20:04:59,878][43431] Avg episode reward: [(0, '1779.019')] +[2026-07-22 20:04:59,932][50205] Updated weights for policy 0, policy_version 20201 (0.0010) +[2026-07-22 20:05:00,580][50205] Updated weights for policy 0, policy_version 20211 (0.0012) +[2026-07-22 20:05:01,517][50205] Updated weights for policy 0, policy_version 20221 (0.0012) +[2026-07-22 20:05:02,690][50205] Updated weights for policy 0, policy_version 20231 (0.0016) +[2026-07-22 20:05:03,551][50205] Updated weights for policy 0, policy_version 20241 (0.0012) +[2026-07-22 20:05:04,291][50205] Updated weights for policy 0, policy_version 20251 (0.0012) +[2026-07-22 20:05:04,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5393.1, 300 sec: 5456.7). Total num frames: 10369024. Throughput: 0: 5439.1. Samples: 10374492. Policy #0 lag: (min: 3.0, avg: 16.6, max: 35.0) +[2026-07-22 20:05:04,878][43431] Avg episode reward: [(0, '1619.325')] +[2026-07-22 20:05:05,530][50205] Updated weights for policy 0, policy_version 20261 (0.0012) +[2026-07-22 20:05:05,997][50205] Updated weights for policy 0, policy_version 20271 (0.0017) +[2026-07-22 20:05:07,096][50205] Updated weights for policy 0, policy_version 20281 (0.0014) +[2026-07-22 20:05:08,339][50205] Updated weights for policy 0, policy_version 20291 (0.0017) +[2026-07-22 20:05:08,918][50205] Updated weights for policy 0, policy_version 20301 (0.0010) +[2026-07-22 20:05:09,704][50205] Updated weights for policy 0, policy_version 20311 (0.0016) +[2026-07-22 20:05:09,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5495.5, 300 sec: 5470.6). Total num frames: 10399744. Throughput: 0: 5464.9. Samples: 10408140. Policy #0 lag: (min: 3.0, avg: 16.6, max: 35.0) +[2026-07-22 20:05:09,878][43431] Avg episode reward: [(0, '1733.427')] +[2026-07-22 20:05:11,092][50205] Updated weights for policy 0, policy_version 20321 (0.0011) +[2026-07-22 20:05:11,576][50205] Updated weights for policy 0, policy_version 20331 (0.0011) +[2026-07-22 20:05:12,754][50205] Updated weights for policy 0, policy_version 20341 (0.0011) +[2026-07-22 20:05:13,683][50205] Updated weights for policy 0, policy_version 20351 (0.0011) +[2026-07-22 20:05:14,450][50205] Updated weights for policy 0, policy_version 20361 (0.0018) +[2026-07-22 20:05:14,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5461.3, 300 sec: 5470.6). Total num frames: 10426368. Throughput: 0: 5461.4. Samples: 10424746. Policy #0 lag: (min: 1.0, avg: 17.9, max: 32.0) +[2026-07-22 20:05:14,878][43431] Avg episode reward: [(0, '1563.682')] +[2026-07-22 20:05:15,384][50205] Updated weights for policy 0, policy_version 20371 (0.0016) +[2026-07-22 20:05:16,704][50205] Updated weights for policy 0, policy_version 20381 (0.0011) +[2026-07-22 20:05:17,204][50205] Updated weights for policy 0, policy_version 20391 (0.0016) +[2026-07-22 20:05:18,159][50205] Updated weights for policy 0, policy_version 20401 (0.0019) +[2026-07-22 20:05:19,228][50205] Updated weights for policy 0, policy_version 20411 (0.0011) +[2026-07-22 20:05:19,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5461.3, 300 sec: 5477.5). Total num frames: 10452992. Throughput: 0: 5502.1. Samples: 10458324. Policy #0 lag: (min: 1.0, avg: 17.9, max: 32.0) +[2026-07-22 20:05:19,878][43431] Avg episode reward: [(0, '1533.911')] +[2026-07-22 20:05:20,143][50205] Updated weights for policy 0, policy_version 20421 (0.0015) +[2026-07-22 20:05:20,821][50205] Updated weights for policy 0, policy_version 20431 (0.0011) +[2026-07-22 20:05:22,076][50205] Updated weights for policy 0, policy_version 20441 (0.0012) +[2026-07-22 20:05:22,869][50205] Updated weights for policy 0, policy_version 20451 (0.0011) +[2026-07-22 20:05:23,699][50205] Updated weights for policy 0, policy_version 20461 (0.0011) +[2026-07-22 20:05:24,487][50205] Updated weights for policy 0, policy_version 20471 (0.0011) +[2026-07-22 20:05:24,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5495.5, 300 sec: 5470.6). Total num frames: 10481664. Throughput: 0: 5500.4. Samples: 10491974. Policy #0 lag: (min: 1.0, avg: 17.9, max: 32.0) +[2026-07-22 20:05:24,878][43431] Avg episode reward: [(0, '1678.109')] +[2026-07-22 20:05:25,735][50205] Updated weights for policy 0, policy_version 20481 (0.0016) +[2026-07-22 20:05:26,437][50205] Updated weights for policy 0, policy_version 20491 (0.0012) +[2026-07-22 20:05:27,676][50205] Updated weights for policy 0, policy_version 20501 (0.0015) +[2026-07-22 20:05:28,506][50205] Updated weights for policy 0, policy_version 20511 (0.0014) +[2026-07-22 20:05:29,598][50205] Updated weights for policy 0, policy_version 20521 (0.0014) +[2026-07-22 20:05:29,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5495.5, 300 sec: 5477.5). Total num frames: 10508288. Throughput: 0: 5469.2. Samples: 10507164. Policy #0 lag: (min: 6.0, avg: 21.0, max: 41.0) +[2026-07-22 20:05:29,878][43431] Avg episode reward: [(0, '1803.966')] +[2026-07-22 20:05:30,406][50205] Updated weights for policy 0, policy_version 20531 (0.0016) +[2026-07-22 20:05:31,467][50205] Updated weights for policy 0, policy_version 20541 (0.0016) +[2026-07-22 20:05:32,195][50205] Updated weights for policy 0, policy_version 20551 (0.0011) +[2026-07-22 20:05:33,259][50205] Updated weights for policy 0, policy_version 20561 (0.0011) +[2026-07-22 20:05:34,150][50205] Updated weights for policy 0, policy_version 20571 (0.0012) +[2026-07-22 20:05:34,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5461.3, 300 sec: 5470.6). Total num frames: 10534912. Throughput: 0: 5459.6. Samples: 10539888. Policy #0 lag: (min: 6.0, avg: 21.0, max: 41.0) +[2026-07-22 20:05:34,878][43431] Avg episode reward: [(0, '1739.511')] +[2026-07-22 20:05:35,181][50205] Updated weights for policy 0, policy_version 20581 (0.0011) +[2026-07-22 20:05:35,796][50205] Updated weights for policy 0, policy_version 20591 (0.0011) +[2026-07-22 20:05:36,996][50205] Updated weights for policy 0, policy_version 20601 (0.0022) +[2026-07-22 20:05:37,892][50205] Updated weights for policy 0, policy_version 20611 (0.0011) +[2026-07-22 20:05:38,669][50205] Updated weights for policy 0, policy_version 20621 (0.0011) +[2026-07-22 20:05:39,658][50205] Updated weights for policy 0, policy_version 20631 (0.0018) +[2026-07-22 20:05:39,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5461.3, 300 sec: 5477.5). Total num frames: 10563584. Throughput: 0: 5513.9. Samples: 10573450. Policy #0 lag: (min: 6.0, avg: 21.0, max: 41.0) +[2026-07-22 20:05:39,878][43431] Avg episode reward: [(0, '1675.356')] +[2026-07-22 20:05:40,860][50205] Updated weights for policy 0, policy_version 20641 (0.0016) +[2026-07-22 20:05:41,435][50205] Updated weights for policy 0, policy_version 20651 (0.0015) +[2026-07-22 20:05:42,504][50205] Updated weights for policy 0, policy_version 20661 (0.0011) +[2026-07-22 20:05:43,372][50205] Updated weights for policy 0, policy_version 20671 (0.0011) +[2026-07-22 20:05:44,285][50205] Updated weights for policy 0, policy_version 20681 (0.0011) +[2026-07-22 20:05:44,877][50205] Updated weights for policy 0, policy_version 20691 (0.0013) +[2026-07-22 20:05:44,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5563.8, 300 sec: 5477.5). Total num frames: 10592256. Throughput: 0: 5519.1. Samples: 10590176. Policy #0 lag: (min: 0.0, avg: 19.7, max: 32.0) +[2026-07-22 20:05:44,878][43431] Avg episode reward: [(0, '1722.685')] +[2026-07-22 20:05:46,259][50205] Updated weights for policy 0, policy_version 20701 (0.0011) +[2026-07-22 20:05:47,196][50205] Updated weights for policy 0, policy_version 20713 (0.0017) +[2026-07-22 20:05:48,140][50205] Updated weights for policy 0, policy_version 20723 (0.0013) +[2026-07-22 20:05:49,344][50205] Updated weights for policy 0, policy_version 20733 (0.0011) +[2026-07-22 20:05:49,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5495.5, 300 sec: 5477.7). Total num frames: 10618880. Throughput: 0: 5533.4. Samples: 10623496. Policy #0 lag: (min: 0.0, avg: 19.7, max: 32.0) +[2026-07-22 20:05:49,878][43431] Avg episode reward: [(0, '1518.226')] +[2026-07-22 20:05:49,933][50205] Updated weights for policy 0, policy_version 20743 (0.0019) +[2026-07-22 20:05:50,943][50205] Updated weights for policy 0, policy_version 20753 (0.0011) +[2026-07-22 20:05:51,878][50205] Updated weights for policy 0, policy_version 20763 (0.0015) +[2026-07-22 20:05:52,887][50205] Updated weights for policy 0, policy_version 20773 (0.0011) +[2026-07-22 20:05:54,291][50205] Updated weights for policy 0, policy_version 20787 (0.0015) +[2026-07-22 20:05:54,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5461.3, 300 sec: 5470.6). Total num frames: 10645504. Throughput: 0: 5475.8. Samples: 10654550. Policy #0 lag: (min: 0.0, avg: 19.7, max: 32.0) +[2026-07-22 20:05:54,878][43431] Avg episode reward: [(0, '1571.769')] +[2026-07-22 20:05:55,793][50205] Updated weights for policy 0, policy_version 20797 (0.0013) +[2026-07-22 20:05:56,157][50205] Updated weights for policy 0, policy_version 20807 (0.0015) +[2026-07-22 20:05:57,060][50205] Updated weights for policy 0, policy_version 20817 (0.0016) +[2026-07-22 20:05:58,358][50205] Updated weights for policy 0, policy_version 20827 (0.0016) +[2026-07-22 20:05:59,221][50205] Updated weights for policy 0, policy_version 20837 (0.0014) +[2026-07-22 20:05:59,859][50205] Updated weights for policy 0, policy_version 20847 (0.0015) +[2026-07-22 20:05:59,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5529.6, 300 sec: 5477.5). Total num frames: 10674176. Throughput: 0: 5479.0. Samples: 10671302. Policy #0 lag: (min: 4.0, avg: 19.0, max: 35.0) +[2026-07-22 20:05:59,878][43431] Avg episode reward: [(0, '1637.122')] +[2026-07-22 20:06:01,445][50205] Updated weights for policy 0, policy_version 20857 (0.0021) +[2026-07-22 20:06:02,115][50205] Updated weights for policy 0, policy_version 20867 (0.0012) +[2026-07-22 20:06:03,036][50205] Updated weights for policy 0, policy_version 20877 (0.0011) +[2026-07-22 20:06:04,552][50205] Updated weights for policy 0, policy_version 20889 (0.0013) +[2026-07-22 20:06:04,877][43431] Fps is (10 sec: 5120.1, 60 sec: 5461.3, 300 sec: 5463.6). Total num frames: 10696704. Throughput: 0: 5415.6. Samples: 10702028. Policy #0 lag: (min: 4.0, avg: 19.0, max: 35.0) +[2026-07-22 20:06:04,878][43431] Avg episode reward: [(0, '1691.941')] +[2026-07-22 20:06:05,142][50205] Updated weights for policy 0, policy_version 20899 (0.0011) +[2026-07-22 20:06:06,075][50205] Updated weights for policy 0, policy_version 20909 (0.0011) +[2026-07-22 20:06:06,745][50205] Updated weights for policy 0, policy_version 20919 (0.0012) +[2026-07-22 20:06:07,987][50205] Updated weights for policy 0, policy_version 20929 (0.0010) +[2026-07-22 20:06:08,335][50205] Updated weights for policy 0, policy_version 20939 (0.0014) +[2026-07-22 20:06:09,643][50205] Updated weights for policy 0, policy_version 20949 (0.0013) +[2026-07-22 20:06:09,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5461.3, 300 sec: 5470.6). Total num frames: 10727424. Throughput: 0: 5451.0. Samples: 10737270. Policy #0 lag: (min: 4.0, avg: 19.0, max: 35.0) +[2026-07-22 20:06:09,878][43431] Avg episode reward: [(0, '1678.812')] +[2026-07-22 20:06:10,544][50205] Updated weights for policy 0, policy_version 20960 (0.0016) +[2026-07-22 20:06:11,213][50205] Updated weights for policy 0, policy_version 20970 (0.0011) +[2026-07-22 20:06:11,921][50205] Updated weights for policy 0, policy_version 20980 (0.0011) +[2026-07-22 20:06:13,430][50205] Updated weights for policy 0, policy_version 20990 (0.0012) +[2026-07-22 20:06:13,733][50205] Updated weights for policy 0, policy_version 21000 (0.0014) +[2026-07-22 20:06:14,832][50205] Updated weights for policy 0, policy_version 21010 (0.0017) +[2026-07-22 20:06:14,877][43431] Fps is (10 sec: 6144.1, 60 sec: 5529.6, 300 sec: 5477.5). Total num frames: 10758144. Throughput: 0: 5498.5. Samples: 10754594. Policy #0 lag: (min: 3.0, avg: 16.0, max: 35.0) +[2026-07-22 20:06:14,878][43431] Avg episode reward: [(0, '1813.817')] +[2026-07-22 20:06:16,037][50205] Updated weights for policy 0, policy_version 21020 (0.0011) +[2026-07-22 20:06:16,502][50205] Updated weights for policy 0, policy_version 21030 (0.0019) +[2026-07-22 20:06:17,115][50205] Updated weights for policy 0, policy_version 21040 (0.0015) +[2026-07-22 20:06:18,825][50205] Updated weights for policy 0, policy_version 21050 (0.0011) +[2026-07-22 20:06:19,190][50205] Updated weights for policy 0, policy_version 21060 (0.0018) +[2026-07-22 20:06:19,878][43431] Fps is (10 sec: 5939.1, 60 sec: 5563.7, 300 sec: 5491.5). Total num frames: 10786816. Throughput: 0: 5541.7. Samples: 10789268. Policy #0 lag: (min: 3.0, avg: 16.0, max: 35.0) +[2026-07-22 20:06:19,878][43431] Avg episode reward: [(0, '1713.289')] +[2026-07-22 20:06:19,999][50205] Updated weights for policy 0, policy_version 21070 (0.0011) +[2026-07-22 20:06:21,261][50205] Updated weights for policy 0, policy_version 21080 (0.0012) +[2026-07-22 20:06:22,033][50205] Updated weights for policy 0, policy_version 21090 (0.0011) +[2026-07-22 20:06:22,502][50205] Updated weights for policy 0, policy_version 21100 (0.0012) +[2026-07-22 20:06:24,200][50205] Updated weights for policy 0, policy_version 21110 (0.0012) +[2026-07-22 20:06:24,562][50205] Updated weights for policy 0, policy_version 21120 (0.0012) +[2026-07-22 20:06:24,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5529.6, 300 sec: 5491.4). Total num frames: 10813440. Throughput: 0: 5569.8. Samples: 10824090. Policy #0 lag: (min: 3.0, avg: 16.0, max: 35.0) +[2026-07-22 20:06:24,878][43431] Avg episode reward: [(0, '1675.948')] +[2026-07-22 20:06:25,366][50205] Updated weights for policy 0, policy_version 21130 (0.0020) +[2026-07-22 20:06:26,058][50205] Updated weights for policy 0, policy_version 21140 (0.0011) +[2026-07-22 20:06:27,372][50205] Updated weights for policy 0, policy_version 21150 (0.0012) +[2026-07-22 20:06:27,768][50205] Updated weights for policy 0, policy_version 21160 (0.0017) +[2026-07-22 20:06:29,291][50205] Updated weights for policy 0, policy_version 21170 (0.0015) +[2026-07-22 20:06:29,877][43431] Fps is (10 sec: 5325.0, 60 sec: 5529.6, 300 sec: 5484.5). Total num frames: 10840064. Throughput: 0: 5582.9. Samples: 10841408. Policy #0 lag: (min: 3.0, avg: 18.3, max: 35.0) +[2026-07-22 20:06:29,878][43431] Avg episode reward: [(0, '1702.511')] +[2026-07-22 20:06:30,084][50205] Updated weights for policy 0, policy_version 21181 (0.0013) +[2026-07-22 20:06:30,572][50205] Updated weights for policy 0, policy_version 21191 (0.0011) +[2026-07-22 20:06:32,288][50205] Updated weights for policy 0, policy_version 21201 (0.0015) +[2026-07-22 20:06:32,663][50205] Updated weights for policy 0, policy_version 21211 (0.0016) +[2026-07-22 20:06:33,322][50205] Updated weights for policy 0, policy_version 21221 (0.0020) +[2026-07-22 20:06:34,844][50205] Updated weights for policy 0, policy_version 21231 (0.0013) +[2026-07-22 20:06:34,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5597.9, 300 sec: 5505.3). Total num frames: 10870784. Throughput: 0: 5600.7. Samples: 10875528. Policy #0 lag: (min: 3.0, avg: 18.3, max: 35.0) +[2026-07-22 20:06:34,878][43431] Avg episode reward: [(0, '1734.706')] +[2026-07-22 20:06:35,868][50205] Updated weights for policy 0, policy_version 21241 (0.0013) +[2026-07-22 20:06:36,432][50205] Updated weights for policy 0, policy_version 21251 (0.0015) +[2026-07-22 20:06:37,831][50205] Updated weights for policy 0, policy_version 21261 (0.0013) +[2026-07-22 20:06:38,756][50205] Updated weights for policy 0, policy_version 21272 (0.0016) +[2026-07-22 20:06:39,184][50205] Updated weights for policy 0, policy_version 21282 (0.0012) +[2026-07-22 20:06:39,877][43431] Fps is (10 sec: 5939.1, 60 sec: 5597.9, 300 sec: 5498.4). Total num frames: 10899456. Throughput: 0: 5634.6. Samples: 10908108. Policy #0 lag: (min: 5.0, avg: 23.2, max: 36.0) +[2026-07-22 20:06:39,878][43431] Avg episode reward: [(0, '1653.395')] +[2026-07-22 20:06:40,192][50205] Updated weights for policy 0, policy_version 21292 (0.0012) +[2026-07-22 20:06:41,411][50205] Updated weights for policy 0, policy_version 21302 (0.0011) +[2026-07-22 20:06:41,851][50205] Updated weights for policy 0, policy_version 21312 (0.0015) +[2026-07-22 20:06:43,079][50205] Updated weights for policy 0, policy_version 21322 (0.0013) +[2026-07-22 20:06:43,946][50205] Updated weights for policy 0, policy_version 21332 (0.0016) +[2026-07-22 20:06:44,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5597.9, 300 sec: 5498.4). Total num frames: 10928128. Throughput: 0: 5650.3. Samples: 10925564. Policy #0 lag: (min: 5.0, avg: 23.2, max: 36.0) +[2026-07-22 20:06:44,878][43431] Avg episode reward: [(0, '1723.838')] +[2026-07-22 20:06:45,029][50205] Updated weights for policy 0, policy_version 21346 (0.0011) +[2026-07-22 20:06:45,979][50205] Updated weights for policy 0, policy_version 21356 (0.0016) +[2026-07-22 20:06:47,106][49527] Signal inference workers to stop experience collection... (350 times) +[2026-07-22 20:06:47,119][50205] InferenceWorker_p0-w0: stopping experience collection (350 times) +[2026-07-22 20:06:47,157][49527] Signal inference workers to resume experience collection... (350 times) +[2026-07-22 20:06:47,158][50205] InferenceWorker_p0-w0: resuming experience collection (350 times) +[2026-07-22 20:06:47,159][50205] Updated weights for policy 0, policy_version 21368 (0.0011) +[2026-07-22 20:06:47,662][50205] Updated weights for policy 0, policy_version 21378 (0.0010) +[2026-07-22 20:06:48,869][50205] Updated weights for policy 0, policy_version 21388 (0.0011) +[2026-07-22 20:06:49,769][50205] Updated weights for policy 0, policy_version 21398 (0.0011) +[2026-07-22 20:06:49,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5632.0, 300 sec: 5505.3). Total num frames: 10956800. Throughput: 0: 5735.8. Samples: 10960138. Policy #0 lag: (min: 5.0, avg: 23.2, max: 36.0) +[2026-07-22 20:06:49,878][43431] Avg episode reward: [(0, '1574.947')] +[2026-07-22 20:06:50,244][50205] Updated weights for policy 0, policy_version 21408 (0.0012) +[2026-07-22 20:06:51,717][50205] Updated weights for policy 0, policy_version 21418 (0.0016) +[2026-07-22 20:06:52,397][50205] Updated weights for policy 0, policy_version 21428 (0.0025) +[2026-07-22 20:06:53,088][50205] Updated weights for policy 0, policy_version 21439 (0.0016) +[2026-07-22 20:06:54,496][50205] Updated weights for policy 0, policy_version 21449 (0.0017) +[2026-07-22 20:06:54,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5666.1, 300 sec: 5512.2). Total num frames: 10985472. Throughput: 0: 5720.4. Samples: 10994688. Policy #0 lag: (min: 0.0, avg: 18.3, max: 36.0) +[2026-07-22 20:06:54,878][43431] Avg episode reward: [(0, '1616.869')] +[2026-07-22 20:06:55,076][50205] Updated weights for policy 0, policy_version 21459 (0.0010) +[2026-07-22 20:06:55,927][50205] Updated weights for policy 0, policy_version 21469 (0.0015) +[2026-07-22 20:06:57,024][50205] Updated weights for policy 0, policy_version 21479 (0.0011) +[2026-07-22 20:06:57,971][50205] Updated weights for policy 0, policy_version 21489 (0.0012) +[2026-07-22 20:06:58,461][50205] Updated weights for policy 0, policy_version 21499 (0.0011) +[2026-07-22 20:06:59,815][50205] Updated weights for policy 0, policy_version 21509 (0.0011) +[2026-07-22 20:06:59,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5666.1, 300 sec: 5519.2). Total num frames: 11014144. Throughput: 0: 5724.8. Samples: 11012210. Policy #0 lag: (min: 0.0, avg: 18.3, max: 36.0) +[2026-07-22 20:06:59,878][43431] Avg episode reward: [(0, '1633.907')] +[2026-07-22 20:07:00,372][50205] Updated weights for policy 0, policy_version 21519 (0.0011) +[2026-07-22 20:07:01,309][50205] Updated weights for policy 0, policy_version 21529 (0.0011) +[2026-07-22 20:07:02,432][50205] Updated weights for policy 0, policy_version 21539 (0.0011) +[2026-07-22 20:07:03,537][50205] Updated weights for policy 0, policy_version 21549 (0.0020) +[2026-07-22 20:07:04,178][50205] Updated weights for policy 0, policy_version 21559 (0.0011) +[2026-07-22 20:07:04,878][43431] Fps is (10 sec: 5734.2, 60 sec: 5768.5, 300 sec: 5519.2). Total num frames: 11042816. Throughput: 0: 5685.6. Samples: 11045122. Policy #0 lag: (min: 0.0, avg: 18.3, max: 36.0) +[2026-07-22 20:07:04,878][43431] Avg episode reward: [(0, '1773.590')] +[2026-07-22 20:07:05,428][50205] Updated weights for policy 0, policy_version 21569 (0.0012) +[2026-07-22 20:07:06,030][50205] Updated weights for policy 0, policy_version 21579 (0.0013) +[2026-07-22 20:07:06,967][50205] Updated weights for policy 0, policy_version 21589 (0.0025) +[2026-07-22 20:07:07,635][50205] Updated weights for policy 0, policy_version 21599 (0.0013) +[2026-07-22 20:07:08,980][50205] Updated weights for policy 0, policy_version 21609 (0.0010) +[2026-07-22 20:07:09,772][50205] Updated weights for policy 0, policy_version 21619 (0.0011) +[2026-07-22 20:07:09,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5700.3, 300 sec: 5519.2). Total num frames: 11069440. Throughput: 0: 5646.6. Samples: 11078186. Policy #0 lag: (min: 6.0, avg: 20.1, max: 42.0) +[2026-07-22 20:07:09,878][43431] Avg episode reward: [(0, '1583.656')] +[2026-07-22 20:07:10,751][50205] Updated weights for policy 0, policy_version 21629 (0.0012) +[2026-07-22 20:07:12,005][50205] Updated weights for policy 0, policy_version 21639 (0.0011) +[2026-07-22 20:07:12,667][50205] Updated weights for policy 0, policy_version 21649 (0.0015) +[2026-07-22 20:07:13,287][50205] Updated weights for policy 0, policy_version 21659 (0.0011) +[2026-07-22 20:07:14,877][43431] Fps is (10 sec: 5120.2, 60 sec: 5597.9, 300 sec: 5512.2). Total num frames: 11094016. Throughput: 0: 5627.2. Samples: 11094632. Policy #0 lag: (min: 6.0, avg: 20.1, max: 42.0) +[2026-07-22 20:07:14,878][43431] Avg episode reward: [(0, '1644.043')] +[2026-07-22 20:07:15,271][50205] Updated weights for policy 0, policy_version 21669 (0.0019) +[2026-07-22 20:07:15,729][50205] Updated weights for policy 0, policy_version 21683 (0.0017) +[2026-07-22 20:07:16,331][50205] Updated weights for policy 0, policy_version 21693 (0.0016) +[2026-07-22 20:07:17,793][50205] Updated weights for policy 0, policy_version 21703 (0.0016) +[2026-07-22 20:07:18,356][50205] Updated weights for policy 0, policy_version 21713 (0.0012) +[2026-07-22 20:07:19,002][50205] Updated weights for policy 0, policy_version 21723 (0.0011) +[2026-07-22 20:07:19,878][43431] Fps is (10 sec: 5529.1, 60 sec: 5631.9, 300 sec: 5519.2). Total num frames: 11124736. Throughput: 0: 5632.5. Samples: 11128996. Policy #0 lag: (min: 6.0, avg: 20.1, max: 42.0) +[2026-07-22 20:07:19,879][43431] Avg episode reward: [(0, '1574.831')] +[2026-07-22 20:07:20,444][50205] Updated weights for policy 0, policy_version 21733 (0.0018) +[2026-07-22 20:07:20,980][50205] Updated weights for policy 0, policy_version 21743 (0.0011) +[2026-07-22 20:07:21,810][50205] Updated weights for policy 0, policy_version 21753 (0.0016) +[2026-07-22 20:07:23,081][50205] Updated weights for policy 0, policy_version 21763 (0.0013) +[2026-07-22 20:07:23,732][50205] Updated weights for policy 0, policy_version 21775 (0.0011) +[2026-07-22 20:07:24,745][50205] Updated weights for policy 0, policy_version 21785 (0.0011) +[2026-07-22 20:07:24,877][43431] Fps is (10 sec: 6143.9, 60 sec: 5700.3, 300 sec: 5533.1). Total num frames: 11155456. Throughput: 0: 5678.6. Samples: 11163644. Policy #0 lag: (min: 1.0, avg: 17.7, max: 33.0) +[2026-07-22 20:07:24,878][43431] Avg episode reward: [(0, '1775.397')] +[2026-07-22 20:07:25,919][50205] Updated weights for policy 0, policy_version 21795 (0.0017) +[2026-07-22 20:07:26,507][50205] Updated weights for policy 0, policy_version 21805 (0.0012) +[2026-07-22 20:07:27,180][50205] Updated weights for policy 0, policy_version 21815 (0.0015) +[2026-07-22 20:07:28,751][50205] Updated weights for policy 0, policy_version 21825 (0.0013) +[2026-07-22 20:07:29,121][50205] Updated weights for policy 0, policy_version 21835 (0.0019) +[2026-07-22 20:07:29,878][43431] Fps is (10 sec: 5939.3, 60 sec: 5734.3, 300 sec: 5540.0). Total num frames: 11184128. Throughput: 0: 5672.9. Samples: 11180850. Policy #0 lag: (min: 1.0, avg: 17.7, max: 33.0) +[2026-07-22 20:07:29,879][43431] Avg episode reward: [(0, '1729.857')] +[2026-07-22 20:07:30,113][50205] Updated weights for policy 0, policy_version 21845 (0.0010) +[2026-07-22 20:07:30,857][50205] Updated weights for policy 0, policy_version 21855 (0.0018) +[2026-07-22 20:07:31,991][50205] Updated weights for policy 0, policy_version 21865 (0.0012) +[2026-07-22 20:07:32,558][50205] Updated weights for policy 0, policy_version 21875 (0.0014) +[2026-07-22 20:07:33,987][50205] Updated weights for policy 0, policy_version 21885 (0.0012) +[2026-07-22 20:07:34,565][50205] Updated weights for policy 0, policy_version 21895 (0.0011) +[2026-07-22 20:07:34,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5700.3, 300 sec: 5540.0). Total num frames: 11212800. Throughput: 0: 5679.4. Samples: 11215710. Policy #0 lag: (min: 1.0, avg: 17.7, max: 33.0) +[2026-07-22 20:07:34,878][43431] Avg episode reward: [(0, '1482.168')] +[2026-07-22 20:07:35,471][50205] Updated weights for policy 0, policy_version 21905 (0.0013) +[2026-07-22 20:07:36,128][50205] Updated weights for policy 0, policy_version 21915 (0.0011) +[2026-07-22 20:07:37,327][50205] Updated weights for policy 0, policy_version 21925 (0.0016) +[2026-07-22 20:07:37,754][50205] Updated weights for policy 0, policy_version 21935 (0.0012) +[2026-07-22 20:07:38,980][50205] Updated weights for policy 0, policy_version 21945 (0.0016) +[2026-07-22 20:07:39,877][43431] Fps is (10 sec: 5530.1, 60 sec: 5666.1, 300 sec: 5547.0). Total num frames: 11239424. Throughput: 0: 5686.0. Samples: 11250556. Policy #0 lag: (min: 3.0, avg: 19.9, max: 35.0) +[2026-07-22 20:07:39,878][43431] Avg episode reward: [(0, '1800.464')] +[2026-07-22 20:07:39,955][50205] Updated weights for policy 0, policy_version 21955 (0.0012) +[2026-07-22 20:07:40,709][50205] Updated weights for policy 0, policy_version 21965 (0.0010) +[2026-07-22 20:07:41,449][50205] Updated weights for policy 0, policy_version 21975 (0.0009) +[2026-07-22 20:07:42,851][50205] Updated weights for policy 0, policy_version 21985 (0.0015) +[2026-07-22 20:07:43,388][50205] Updated weights for policy 0, policy_version 21995 (0.0012) +[2026-07-22 20:07:44,595][50205] Updated weights for policy 0, policy_version 22005 (0.0012) +[2026-07-22 20:07:44,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5666.1, 300 sec: 5540.0). Total num frames: 11268096. Throughput: 0: 5664.7. Samples: 11267122. Policy #0 lag: (min: 3.0, avg: 19.9, max: 35.0) +[2026-07-22 20:07:44,878][43431] Avg episode reward: [(0, '1487.079')] +[2026-07-22 20:07:45,705][50205] Updated weights for policy 0, policy_version 22015 (0.0021) +[2026-07-22 20:07:46,491][50205] Updated weights for policy 0, policy_version 22025 (0.0011) +[2026-07-22 20:07:47,175][50205] Updated weights for policy 0, policy_version 22035 (0.0015) +[2026-07-22 20:07:48,409][50205] Updated weights for policy 0, policy_version 22045 (0.0011) +[2026-07-22 20:07:48,996][50205] Updated weights for policy 0, policy_version 22055 (0.0011) +[2026-07-22 20:07:49,803][50205] Updated weights for policy 0, policy_version 22065 (0.0017) +[2026-07-22 20:07:49,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5700.3, 300 sec: 5553.9). Total num frames: 11298816. Throughput: 0: 5671.5. Samples: 11300338. Policy #0 lag: (min: 3.0, avg: 19.9, max: 35.0) +[2026-07-22 20:07:49,878][43431] Avg episode reward: [(0, '1697.088')] +[2026-07-22 20:07:50,837][50205] Updated weights for policy 0, policy_version 22075 (0.0016) +[2026-07-22 20:07:51,896][50205] Updated weights for policy 0, policy_version 22085 (0.0016) +[2026-07-22 20:07:52,465][50205] Updated weights for policy 0, policy_version 22095 (0.0017) +[2026-07-22 20:07:53,738][50205] Updated weights for policy 0, policy_version 22105 (0.0011) +[2026-07-22 20:07:54,197][50205] Updated weights for policy 0, policy_version 22115 (0.0016) +[2026-07-22 20:07:54,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5666.1, 300 sec: 5553.9). Total num frames: 11325440. Throughput: 0: 5705.8. Samples: 11334950. Policy #0 lag: (min: 3.0, avg: 19.2, max: 39.0) +[2026-07-22 20:07:54,878][43431] Avg episode reward: [(0, '1916.253')] +[2026-07-22 20:07:54,886][49527] Saving new best policy, reward=1916.253! +[2026-07-22 20:07:55,316][50205] Updated weights for policy 0, policy_version 22125 (0.0011) +[2026-07-22 20:07:56,154][50205] Updated weights for policy 0, policy_version 22135 (0.0015) +[2026-07-22 20:07:56,951][50205] Updated weights for policy 0, policy_version 22145 (0.0011) +[2026-07-22 20:07:57,958][50205] Updated weights for policy 0, policy_version 22155 (0.0016) +[2026-07-22 20:07:58,886][50205] Updated weights for policy 0, policy_version 22165 (0.0017) +[2026-07-22 20:07:59,526][50205] Updated weights for policy 0, policy_version 22175 (0.0015) +[2026-07-22 20:07:59,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5700.3, 300 sec: 5560.8). Total num frames: 11356160. Throughput: 0: 5730.6. Samples: 11352508. Policy #0 lag: (min: 3.0, avg: 19.2, max: 39.0) +[2026-07-22 20:07:59,878][43431] Avg episode reward: [(0, '1860.905')] +[2026-07-22 20:08:00,564][50205] Updated weights for policy 0, policy_version 22185 (0.0011) +[2026-07-22 20:08:01,356][50205] Updated weights for policy 0, policy_version 22195 (0.0015) +[2026-07-22 20:08:02,296][50205] Updated weights for policy 0, policy_version 22205 (0.0024) +[2026-07-22 20:08:03,064][50205] Updated weights for policy 0, policy_version 22215 (0.0016) +[2026-07-22 20:08:04,194][50205] Updated weights for policy 0, policy_version 22225 (0.0011) +[2026-07-22 20:08:04,877][43431] Fps is (10 sec: 5734.6, 60 sec: 5666.2, 300 sec: 5560.8). Total num frames: 11382784. Throughput: 0: 5738.4. Samples: 11387218. Policy #0 lag: (min: 3.0, avg: 19.2, max: 39.0) +[2026-07-22 20:08:04,878][43431] Avg episode reward: [(0, '1787.122')] +[2026-07-22 20:08:05,033][50205] Updated weights for policy 0, policy_version 22235 (0.0011) +[2026-07-22 20:08:05,822][50205] Updated weights for policy 0, policy_version 22245 (0.0011) +[2026-07-22 20:08:06,781][50205] Updated weights for policy 0, policy_version 22255 (0.0011) +[2026-07-22 20:08:07,677][50205] Updated weights for policy 0, policy_version 22265 (0.0013) +[2026-07-22 20:08:08,294][50205] Updated weights for policy 0, policy_version 22275 (0.0011) +[2026-07-22 20:08:09,411][50205] Updated weights for policy 0, policy_version 22285 (0.0017) +[2026-07-22 20:08:09,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5734.4, 300 sec: 5581.7). Total num frames: 11413504. Throughput: 0: 5747.1. Samples: 11422264. Policy #0 lag: (min: 3.0, avg: 19.0, max: 43.0) +[2026-07-22 20:08:09,878][43431] Avg episode reward: [(0, '1805.430')] +[2026-07-22 20:08:10,308][50205] Updated weights for policy 0, policy_version 22295 (0.0011) +[2026-07-22 20:08:11,115][50205] Updated weights for policy 0, policy_version 22305 (0.0011) +[2026-07-22 20:08:12,010][50205] Updated weights for policy 0, policy_version 22315 (0.0016) +[2026-07-22 20:08:13,073][50205] Updated weights for policy 0, policy_version 22325 (0.0017) +[2026-07-22 20:08:13,618][50205] Updated weights for policy 0, policy_version 22335 (0.0017) +[2026-07-22 20:08:14,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5768.5, 300 sec: 5567.8). Total num frames: 11440128. Throughput: 0: 5753.7. Samples: 11439764. Policy #0 lag: (min: 3.0, avg: 19.0, max: 43.0) +[2026-07-22 20:08:14,878][43431] Avg episode reward: [(0, '1697.530')] +[2026-07-22 20:08:14,985][50205] Updated weights for policy 0, policy_version 22345 (0.0011) +[2026-07-22 20:08:15,952][50205] Updated weights for policy 0, policy_version 22357 (0.0011) +[2026-07-22 20:08:16,457][50205] Updated weights for policy 0, policy_version 22367 (0.0013) +[2026-07-22 20:08:17,882][50205] Updated weights for policy 0, policy_version 22377 (0.0011) +[2026-07-22 20:08:18,686][50205] Updated weights for policy 0, policy_version 22387 (0.0017) +[2026-07-22 20:08:19,640][50205] Updated weights for policy 0, policy_version 22397 (0.0011) +[2026-07-22 20:08:19,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5734.5, 300 sec: 5567.8). Total num frames: 11468800. Throughput: 0: 5705.2. Samples: 11472444. Policy #0 lag: (min: 3.0, avg: 19.0, max: 43.0) +[2026-07-22 20:08:19,878][43431] Avg episode reward: [(0, '1739.959')] +[2026-07-22 20:08:20,615][50205] Updated weights for policy 0, policy_version 22407 (0.0012) +[2026-07-22 20:08:21,643][50205] Updated weights for policy 0, policy_version 22417 (0.0016) +[2026-07-22 20:08:22,149][50205] Updated weights for policy 0, policy_version 22427 (0.0011) +[2026-07-22 20:08:23,478][50205] Updated weights for policy 0, policy_version 22437 (0.0021) +[2026-07-22 20:08:24,212][50205] Updated weights for policy 0, policy_version 22447 (0.0018) +[2026-07-22 20:08:24,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5700.3, 300 sec: 5574.7). Total num frames: 11497472. Throughput: 0: 5683.1. Samples: 11506296. Policy #0 lag: (min: 3.0, avg: 16.7, max: 35.0) +[2026-07-22 20:08:24,878][43431] Avg episode reward: [(0, '1668.156')] +[2026-07-22 20:08:24,992][50205] Updated weights for policy 0, policy_version 22457 (0.0021) +[2026-07-22 20:08:25,954][50205] Updated weights for policy 0, policy_version 22467 (0.0010) +[2026-07-22 20:08:26,946][50205] Updated weights for policy 0, policy_version 22477 (0.0016) +[2026-07-22 20:08:27,701][50205] Updated weights for policy 0, policy_version 22487 (0.0014) +[2026-07-22 20:08:28,804][50205] Updated weights for policy 0, policy_version 22497 (0.0011) +[2026-07-22 20:08:29,512][50205] Updated weights for policy 0, policy_version 22507 (0.0011) +[2026-07-22 20:08:29,879][43431] Fps is (10 sec: 5733.3, 60 sec: 5700.1, 300 sec: 5574.7). Total num frames: 11526144. Throughput: 0: 5701.4. Samples: 11523696. Policy #0 lag: (min: 3.0, avg: 16.7, max: 35.0) +[2026-07-22 20:08:29,880][43431] Avg episode reward: [(0, '1736.709')] +[2026-07-22 20:08:30,422][50205] Updated weights for policy 0, policy_version 22517 (0.0011) +[2026-07-22 20:08:31,248][50205] Updated weights for policy 0, policy_version 22527 (0.0011) +[2026-07-22 20:08:32,190][50205] Updated weights for policy 0, policy_version 22537 (0.0012) +[2026-07-22 20:08:32,883][50205] Updated weights for policy 0, policy_version 22547 (0.0012) +[2026-07-22 20:08:33,915][50205] Updated weights for policy 0, policy_version 22557 (0.0016) +[2026-07-22 20:08:34,847][50205] Updated weights for policy 0, policy_version 22567 (0.0011) +[2026-07-22 20:08:34,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5666.1, 300 sec: 5574.7). Total num frames: 11552768. Throughput: 0: 5739.7. Samples: 11558624. Policy #0 lag: (min: 3.0, avg: 16.7, max: 35.0) +[2026-07-22 20:08:34,878][43431] Avg episode reward: [(0, '1702.083')] +[2026-07-22 20:08:35,707][50205] Updated weights for policy 0, policy_version 22577 (0.0016) +[2026-07-22 20:08:36,248][50205] Updated weights for policy 0, policy_version 22587 (0.0019) +[2026-07-22 20:08:37,405][50205] Updated weights for policy 0, policy_version 22597 (0.0011) +[2026-07-22 20:08:38,211][50205] Updated weights for policy 0, policy_version 22607 (0.0012) +[2026-07-22 20:08:39,147][50205] Updated weights for policy 0, policy_version 22617 (0.0011) +[2026-07-22 20:08:39,877][43431] Fps is (10 sec: 5735.5, 60 sec: 5734.4, 300 sec: 5581.7). Total num frames: 11583488. Throughput: 0: 5740.3. Samples: 11593260. Policy #0 lag: (min: 3.0, avg: 19.4, max: 39.0) +[2026-07-22 20:08:39,878][43431] Avg episode reward: [(0, '1810.718')] +[2026-07-22 20:08:40,062][50205] Updated weights for policy 0, policy_version 22627 (0.0016) +[2026-07-22 20:08:40,816][50205] Updated weights for policy 0, policy_version 22639 (0.0023) +[2026-07-22 20:08:41,898][50205] Updated weights for policy 0, policy_version 22649 (0.0012) +[2026-07-22 20:08:42,733][50205] Updated weights for policy 0, policy_version 22660 (0.0024) +[2026-07-22 20:08:43,760][50205] Updated weights for policy 0, policy_version 22670 (0.0011) +[2026-07-22 20:08:44,330][50205] Updated weights for policy 0, policy_version 22680 (0.0011) +[2026-07-22 20:08:44,877][43431] Fps is (10 sec: 5939.1, 60 sec: 5734.4, 300 sec: 5588.6). Total num frames: 11612160. Throughput: 0: 5748.0. Samples: 11611168. Policy #0 lag: (min: 3.0, avg: 19.4, max: 39.0) +[2026-07-22 20:08:44,878][43431] Avg episode reward: [(0, '1715.419')] +[2026-07-22 20:08:45,505][50205] Updated weights for policy 0, policy_version 22692 (0.0014) +[2026-07-22 20:08:46,460][50205] Updated weights for policy 0, policy_version 22702 (0.0011) +[2026-07-22 20:08:47,126][50205] Updated weights for policy 0, policy_version 22712 (0.0013) +[2026-07-22 20:08:48,094][50205] Updated weights for policy 0, policy_version 22722 (0.0012) +[2026-07-22 20:08:49,111][50205] Updated weights for policy 0, policy_version 22732 (0.0014) +[2026-07-22 20:08:49,827][50205] Updated weights for policy 0, policy_version 22742 (0.0010) +[2026-07-22 20:08:49,877][43431] Fps is (10 sec: 6144.0, 60 sec: 5768.5, 300 sec: 5609.4). Total num frames: 11644928. Throughput: 0: 5775.6. Samples: 11647120. Policy #0 lag: (min: 3.0, avg: 19.4, max: 39.0) +[2026-07-22 20:08:49,878][43431] Avg episode reward: [(0, '1764.165')] +[2026-07-22 20:08:50,636][50205] Updated weights for policy 0, policy_version 22752 (0.0011) +[2026-07-22 20:08:51,690][50205] Updated weights for policy 0, policy_version 22762 (0.0015) +[2026-07-22 20:08:52,471][50205] Updated weights for policy 0, policy_version 22772 (0.0011) +[2026-07-22 20:08:53,228][50205] Updated weights for policy 0, policy_version 22782 (0.0010) +[2026-07-22 20:08:53,776][50205] Updated weights for policy 0, policy_version 22792 (0.0018) +[2026-07-22 20:08:54,877][43431] Fps is (10 sec: 6144.1, 60 sec: 5802.7, 300 sec: 5609.4). Total num frames: 11673600. Throughput: 0: 5803.5. Samples: 11683420. Policy #0 lag: (min: 3.0, avg: 19.4, max: 39.0) +[2026-07-22 20:08:54,878][43431] Avg episode reward: [(0, '1573.870')] +[2026-07-22 20:08:55,116][50205] Updated weights for policy 0, policy_version 22802 (0.0011) +[2026-07-22 20:08:55,676][50205] Updated weights for policy 0, policy_version 22812 (0.0016) +[2026-07-22 20:08:56,563][50205] Updated weights for policy 0, policy_version 22822 (0.0011) +[2026-07-22 20:08:57,413][50205] Updated weights for policy 0, policy_version 22832 (0.0016) +[2026-07-22 20:08:58,264][50205] Updated weights for policy 0, policy_version 22842 (0.0016) +[2026-07-22 20:08:58,943][50205] Updated weights for policy 0, policy_version 22852 (0.0011) +[2026-07-22 20:08:59,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5802.7, 300 sec: 5623.3). Total num frames: 11704320. Throughput: 0: 5820.1. Samples: 11701670. Policy #0 lag: (min: 1.0, avg: 15.4, max: 37.0) +[2026-07-22 20:08:59,878][43431] Avg episode reward: [(0, '1668.893')] +[2026-07-22 20:09:00,147][50205] Updated weights for policy 0, policy_version 22862 (0.0010) +[2026-07-22 20:09:00,879][50205] Updated weights for policy 0, policy_version 22872 (0.0015) +[2026-07-22 20:09:01,507][50205] Updated weights for policy 0, policy_version 22882 (0.0011) +[2026-07-22 20:09:02,802][50205] Updated weights for policy 0, policy_version 22892 (0.0017) +[2026-07-22 20:09:03,840][50205] Updated weights for policy 0, policy_version 22902 (0.0010) +[2026-07-22 20:09:04,316][50205] Updated weights for policy 0, policy_version 22912 (0.0011) +[2026-07-22 20:09:04,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5836.8, 300 sec: 5637.2). Total num frames: 11732992. Throughput: 0: 5851.4. Samples: 11735754. Policy #0 lag: (min: 1.0, avg: 15.4, max: 37.0) +[2026-07-22 20:09:04,878][43431] Avg episode reward: [(0, '1656.302')] +[2026-07-22 20:09:05,626][50205] Updated weights for policy 0, policy_version 22922 (0.0013) +[2026-07-22 20:09:06,358][50205] Updated weights for policy 0, policy_version 22932 (0.0016) +[2026-07-22 20:09:07,140][50205] Updated weights for policy 0, policy_version 22942 (0.0011) +[2026-07-22 20:09:07,750][50205] Updated weights for policy 0, policy_version 22952 (0.0016) +[2026-07-22 20:09:08,888][50205] Updated weights for policy 0, policy_version 22962 (0.0012) +[2026-07-22 20:09:09,518][50205] Updated weights for policy 0, policy_version 22972 (0.0011) +[2026-07-22 20:09:09,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5836.8, 300 sec: 5644.1). Total num frames: 11763712. Throughput: 0: 5906.5. Samples: 11772088. Policy #0 lag: (min: 1.0, avg: 15.4, max: 37.0) +[2026-07-22 20:09:09,878][43431] Avg episode reward: [(0, '1512.595')] +[2026-07-22 20:09:10,708][50205] Updated weights for policy 0, policy_version 22982 (0.0011) +[2026-07-22 20:09:11,371][50205] Updated weights for policy 0, policy_version 22992 (0.0012) +[2026-07-22 20:09:12,199][50205] Updated weights for policy 0, policy_version 23002 (0.0011) +[2026-07-22 20:09:12,665][50205] Updated weights for policy 0, policy_version 23012 (0.0011) +[2026-07-22 20:09:14,005][50205] Updated weights for policy 0, policy_version 23022 (0.0011) +[2026-07-22 20:09:14,708][50205] Updated weights for policy 0, policy_version 23032 (0.0010) +[2026-07-22 20:09:14,877][43431] Fps is (10 sec: 5939.1, 60 sec: 5870.9, 300 sec: 5651.1). Total num frames: 11792384. Throughput: 0: 5925.6. Samples: 11790338. Policy #0 lag: (min: 1.0, avg: 15.7, max: 33.0) +[2026-07-22 20:09:14,878][43431] Avg episode reward: [(0, '1759.133')] +[2026-07-22 20:09:15,434][50205] Updated weights for policy 0, policy_version 23042 (0.0011) +[2026-07-22 20:09:16,322][50205] Updated weights for policy 0, policy_version 23052 (0.0021) +[2026-07-22 20:09:17,434][50205] Updated weights for policy 0, policy_version 23062 (0.0011) +[2026-07-22 20:09:18,200][50205] Updated weights for policy 0, policy_version 23073 (0.0016) +[2026-07-22 20:09:19,112][50205] Updated weights for policy 0, policy_version 23083 (0.0013) +[2026-07-22 20:09:19,877][43431] Fps is (10 sec: 5939.1, 60 sec: 5905.1, 300 sec: 5665.0). Total num frames: 11823104. Throughput: 0: 5956.3. Samples: 11826660. Policy #0 lag: (min: 1.0, avg: 15.7, max: 33.0) +[2026-07-22 20:09:19,878][43431] Avg episode reward: [(0, '1645.316')] +[2026-07-22 20:09:20,105][50205] Updated weights for policy 0, policy_version 23093 (0.0013) +[2026-07-22 20:09:20,637][50205] Updated weights for policy 0, policy_version 23103 (0.0011) +[2026-07-22 20:09:21,681][50205] Updated weights for policy 0, policy_version 23114 (0.0011) +[2026-07-22 20:09:22,365][50205] Updated weights for policy 0, policy_version 23124 (0.0011) +[2026-07-22 20:09:23,362][50205] Updated weights for policy 0, policy_version 23136 (0.0017) +[2026-07-22 20:09:24,394][50205] Updated weights for policy 0, policy_version 23146 (0.0011) +[2026-07-22 20:09:24,877][43431] Fps is (10 sec: 6144.0, 60 sec: 5939.2, 300 sec: 5678.9). Total num frames: 11853824. Throughput: 0: 5990.5. Samples: 11862832. Policy #0 lag: (min: 1.0, avg: 15.7, max: 33.0) +[2026-07-22 20:09:24,878][43431] Avg episode reward: [(0, '1669.812')] +[2026-07-22 20:09:25,188][50205] Updated weights for policy 0, policy_version 23156 (0.0011) +[2026-07-22 20:09:26,104][50205] Updated weights for policy 0, policy_version 23166 (0.0021) +[2026-07-22 20:09:26,885][50205] Updated weights for policy 0, policy_version 23176 (0.0016) +[2026-07-22 20:09:27,832][50205] Updated weights for policy 0, policy_version 23186 (0.0016) +[2026-07-22 20:09:28,324][50205] Updated weights for policy 0, policy_version 23196 (0.0011) +[2026-07-22 20:09:29,450][50205] Updated weights for policy 0, policy_version 23206 (0.0016) +[2026-07-22 20:09:29,877][43431] Fps is (10 sec: 6144.1, 60 sec: 5973.5, 300 sec: 5685.8). Total num frames: 11884544. Throughput: 0: 5998.8. Samples: 11881114. Policy #0 lag: (min: 3.0, avg: 15.2, max: 35.0) +[2026-07-22 20:09:29,878][43431] Avg episode reward: [(0, '1759.720')] +[2026-07-22 20:09:30,170][50205] Updated weights for policy 0, policy_version 23216 (0.0015) +[2026-07-22 20:09:31,239][50205] Updated weights for policy 0, policy_version 23226 (0.0011) +[2026-07-22 20:09:32,092][50205] Updated weights for policy 0, policy_version 23238 (0.0011) +[2026-07-22 20:09:32,977][50205] Updated weights for policy 0, policy_version 23248 (0.0013) +[2026-07-22 20:09:33,864][50205] Updated weights for policy 0, policy_version 23258 (0.0013) +[2026-07-22 20:09:34,739][50205] Updated weights for policy 0, policy_version 23268 (0.0011) +[2026-07-22 20:09:34,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6007.5, 300 sec: 5685.8). Total num frames: 11913216. Throughput: 0: 6005.7. Samples: 11917376. Policy #0 lag: (min: 3.0, avg: 15.2, max: 35.0) +[2026-07-22 20:09:34,878][43431] Avg episode reward: [(0, '1608.930')] +[2026-07-22 20:09:35,507][50205] Updated weights for policy 0, policy_version 23278 (0.0011) +[2026-07-22 20:09:36,118][50205] Updated weights for policy 0, policy_version 23288 (0.0017) +[2026-07-22 20:09:37,366][50205] Updated weights for policy 0, policy_version 23298 (0.0011) +[2026-07-22 20:09:38,037][50205] Updated weights for policy 0, policy_version 23308 (0.0022) +[2026-07-22 20:09:38,772][50205] Updated weights for policy 0, policy_version 23318 (0.0012) +[2026-07-22 20:09:39,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5973.3, 300 sec: 5706.6). Total num frames: 11941888. Throughput: 0: 6012.4. Samples: 11953980. Policy #0 lag: (min: 3.0, avg: 15.2, max: 35.0) +[2026-07-22 20:09:39,878][43431] Avg episode reward: [(0, '1814.636')] +[2026-07-22 20:09:39,892][50205] Updated weights for policy 0, policy_version 23328 (0.0011) +[2026-07-22 20:09:40,523][50205] Updated weights for policy 0, policy_version 23338 (0.0016) +[2026-07-22 20:09:41,148][50205] Updated weights for policy 0, policy_version 23348 (0.0012) +[2026-07-22 20:09:42,385][50205] Updated weights for policy 0, policy_version 23358 (0.0011) +[2026-07-22 20:09:43,104][50205] Updated weights for policy 0, policy_version 23368 (0.0012) +[2026-07-22 20:09:43,729][50205] Updated weights for policy 0, policy_version 23378 (0.0011) +[2026-07-22 20:09:44,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6007.5, 300 sec: 5706.6). Total num frames: 11972608. Throughput: 0: 6008.0. Samples: 11972030. Policy #0 lag: (min: 4.0, avg: 20.4, max: 34.0) +[2026-07-22 20:09:44,878][43431] Avg episode reward: [(0, '1623.307')] +[2026-07-22 20:09:45,016][50205] Updated weights for policy 0, policy_version 23388 (0.0012) +[2026-07-22 20:09:45,804][50205] Updated weights for policy 0, policy_version 23398 (0.0011) +[2026-07-22 20:09:46,310][50205] Updated weights for policy 0, policy_version 23408 (0.0011) +[2026-07-22 20:09:47,473][50205] Updated weights for policy 0, policy_version 23418 (0.0012) +[2026-07-22 20:09:48,287][50205] Updated weights for policy 0, policy_version 23428 (0.0016) +[2026-07-22 20:09:48,951][50205] Updated weights for policy 0, policy_version 23438 (0.0015) +[2026-07-22 20:09:49,716][50205] Updated weights for policy 0, policy_version 23448 (0.0011) +[2026-07-22 20:09:49,877][43431] Fps is (10 sec: 6348.9, 60 sec: 6007.5, 300 sec: 5720.5). Total num frames: 12005376. Throughput: 0: 6054.7. Samples: 12008216. Policy #0 lag: (min: 4.0, avg: 20.4, max: 34.0) +[2026-07-22 20:09:49,878][43431] Avg episode reward: [(0, '1628.311')] +[2026-07-22 20:09:50,799][50205] Updated weights for policy 0, policy_version 23458 (0.0011) +[2026-07-22 20:09:51,503][50205] Updated weights for policy 0, policy_version 23468 (0.0019) +[2026-07-22 20:09:52,348][50205] Updated weights for policy 0, policy_version 23478 (0.0013) +[2026-07-22 20:09:53,300][50205] Updated weights for policy 0, policy_version 23488 (0.0011) +[2026-07-22 20:09:54,101][50205] Updated weights for policy 0, policy_version 23498 (0.0011) +[2026-07-22 20:09:54,876][50205] Updated weights for policy 0, policy_version 23508 (0.0016) +[2026-07-22 20:09:54,877][43431] Fps is (10 sec: 6348.8, 60 sec: 6041.6, 300 sec: 5741.3). Total num frames: 12036096. Throughput: 0: 6055.6. Samples: 12044592. Policy #0 lag: (min: 4.0, avg: 20.4, max: 34.0) +[2026-07-22 20:09:54,878][43431] Avg episode reward: [(0, '1648.983')] +[2026-07-22 20:09:55,975][50205] Updated weights for policy 0, policy_version 23518 (0.0019) +[2026-07-22 20:09:56,463][50205] Updated weights for policy 0, policy_version 23528 (0.0011) +[2026-07-22 20:09:57,497][50205] Updated weights for policy 0, policy_version 23538 (0.0012) +[2026-07-22 20:09:58,259][50205] Updated weights for policy 0, policy_version 23548 (0.0017) +[2026-07-22 20:09:59,206][50205] Updated weights for policy 0, policy_version 23558 (0.0016) +[2026-07-22 20:09:59,847][50205] Updated weights for policy 0, policy_version 23568 (0.0012) +[2026-07-22 20:09:59,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 5755.2). Total num frames: 12066816. Throughput: 0: 6051.4. Samples: 12062652. Policy #0 lag: (min: 3.0, avg: 18.7, max: 35.0) +[2026-07-22 20:09:59,878][43431] Avg episode reward: [(0, '1703.261')] +[2026-07-22 20:10:00,852][50205] Updated weights for policy 0, policy_version 23578 (0.0011) +[2026-07-22 20:10:01,821][50205] Updated weights for policy 0, policy_version 23589 (0.0011) +[2026-07-22 20:10:03,221][50205] Updated weights for policy 0, policy_version 23601 (0.0010) +[2026-07-22 20:10:03,831][50205] Updated weights for policy 0, policy_version 23611 (0.0016) +[2026-07-22 20:10:04,705][50205] Updated weights for policy 0, policy_version 23621 (0.0014) +[2026-07-22 20:10:04,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 5748.3). Total num frames: 12095488. Throughput: 0: 6019.1. Samples: 12097518. Policy #0 lag: (min: 3.0, avg: 18.7, max: 35.0) +[2026-07-22 20:10:04,878][43431] Avg episode reward: [(0, '1631.951')] +[2026-07-22 20:10:05,596][50205] Updated weights for policy 0, policy_version 23631 (0.0011) +[2026-07-22 20:10:06,485][50205] Updated weights for policy 0, policy_version 23641 (0.0012) +[2026-07-22 20:10:07,282][50205] Updated weights for policy 0, policy_version 23651 (0.0015) +[2026-07-22 20:10:08,216][50205] Updated weights for policy 0, policy_version 23661 (0.0010) +[2026-07-22 20:10:08,991][50205] Updated weights for policy 0, policy_version 23671 (0.0015) +[2026-07-22 20:10:09,877][43431] Fps is (10 sec: 5734.5, 60 sec: 6007.5, 300 sec: 5755.2). Total num frames: 12124160. Throughput: 0: 6026.3. Samples: 12134016. Policy #0 lag: (min: 3.0, avg: 18.7, max: 35.0) +[2026-07-22 20:10:09,878][43431] Avg episode reward: [(0, '1739.197')] +[2026-07-22 20:10:09,886][50205] Updated weights for policy 0, policy_version 23681 (0.0012) +[2026-07-22 20:10:10,578][50205] Updated weights for policy 0, policy_version 23691 (0.0017) +[2026-07-22 20:10:11,618][50205] Updated weights for policy 0, policy_version 23702 (0.0015) +[2026-07-22 20:10:12,454][50205] Updated weights for policy 0, policy_version 23712 (0.0011) +[2026-07-22 20:10:13,404][50205] Updated weights for policy 0, policy_version 23722 (0.0012) +[2026-07-22 20:10:14,122][50205] Updated weights for policy 0, policy_version 23732 (0.0016) +[2026-07-22 20:10:14,877][43431] Fps is (10 sec: 5734.4, 60 sec: 6007.5, 300 sec: 5762.2). Total num frames: 12152832. Throughput: 0: 6019.0. Samples: 12151970. Policy #0 lag: (min: 3.0, avg: 17.4, max: 35.0) +[2026-07-22 20:10:14,878][43431] Avg episode reward: [(0, '1757.028')] +[2026-07-22 20:10:15,140][49527] Signal inference workers to stop experience collection... (400 times) +[2026-07-22 20:10:15,155][50205] InferenceWorker_p0-w0: stopping experience collection (400 times) +[2026-07-22 20:10:15,191][49527] Signal inference workers to resume experience collection... (400 times) +[2026-07-22 20:10:15,191][50205] InferenceWorker_p0-w0: resuming experience collection (400 times) +[2026-07-22 20:10:15,378][50205] Updated weights for policy 0, policy_version 23746 (0.0010) +[2026-07-22 20:10:16,099][50205] Updated weights for policy 0, policy_version 23756 (0.0019) +[2026-07-22 20:10:17,208][50205] Updated weights for policy 0, policy_version 23766 (0.0011) +[2026-07-22 20:10:17,793][50205] Updated weights for policy 0, policy_version 23776 (0.0012) +[2026-07-22 20:10:18,660][50205] Updated weights for policy 0, policy_version 23786 (0.0012) +[2026-07-22 20:10:19,581][50205] Updated weights for policy 0, policy_version 23796 (0.0014) +[2026-07-22 20:10:19,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6007.5, 300 sec: 5769.1). Total num frames: 12183552. Throughput: 0: 6010.0. Samples: 12187824. Policy #0 lag: (min: 3.0, avg: 17.4, max: 35.0) +[2026-07-22 20:10:19,878][43431] Avg episode reward: [(0, '1771.180')] +[2026-07-22 20:10:20,496][50205] Updated weights for policy 0, policy_version 23806 (0.0015) +[2026-07-22 20:10:21,092][50205] Updated weights for policy 0, policy_version 23816 (0.0012) +[2026-07-22 20:10:22,167][50205] Updated weights for policy 0, policy_version 23827 (0.0011) +[2026-07-22 20:10:23,038][50205] Updated weights for policy 0, policy_version 23837 (0.0012) +[2026-07-22 20:10:23,986][50205] Updated weights for policy 0, policy_version 23847 (0.0012) +[2026-07-22 20:10:24,855][50205] Updated weights for policy 0, policy_version 23857 (0.0011) +[2026-07-22 20:10:24,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 5783.0). Total num frames: 12214272. Throughput: 0: 6006.5. Samples: 12224272. Policy #0 lag: (min: 3.0, avg: 17.4, max: 35.0) +[2026-07-22 20:10:24,878][43431] Avg episode reward: [(0, '1765.483')] +[2026-07-22 20:10:25,749][50205] Updated weights for policy 0, policy_version 23869 (0.0014) +[2026-07-22 20:10:26,661][50205] Updated weights for policy 0, policy_version 23879 (0.0013) +[2026-07-22 20:10:27,635][50205] Updated weights for policy 0, policy_version 23889 (0.0012) +[2026-07-22 20:10:28,280][50205] Updated weights for policy 0, policy_version 23899 (0.0011) +[2026-07-22 20:10:29,245][50205] Updated weights for policy 0, policy_version 23909 (0.0014) +[2026-07-22 20:10:29,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6007.5, 300 sec: 5796.9). Total num frames: 12244992. Throughput: 0: 6006.0. Samples: 12242302. Policy #0 lag: (min: 3.0, avg: 17.4, max: 35.0) +[2026-07-22 20:10:29,878][43431] Avg episode reward: [(0, '1546.084')] +[2026-07-22 20:10:30,154][50205] Updated weights for policy 0, policy_version 23919 (0.0012) +[2026-07-22 20:10:30,901][50205] Updated weights for policy 0, policy_version 23929 (0.0016) +[2026-07-22 20:10:31,815][50205] Updated weights for policy 0, policy_version 23939 (0.0019) +[2026-07-22 20:10:32,749][50205] Updated weights for policy 0, policy_version 23949 (0.0012) +[2026-07-22 20:10:33,396][50205] Updated weights for policy 0, policy_version 23959 (0.0011) +[2026-07-22 20:10:34,447][50205] Updated weights for policy 0, policy_version 23969 (0.0011) +[2026-07-22 20:10:34,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 5803.8). Total num frames: 12275712. Throughput: 0: 6007.6. Samples: 12278560. Policy #0 lag: (min: 0.0, avg: 15.8, max: 32.0) +[2026-07-22 20:10:34,878][43431] Avg episode reward: [(0, '1734.601')] +[2026-07-22 20:10:35,091][50205] Updated weights for policy 0, policy_version 23979 (0.0011) +[2026-07-22 20:10:36,007][50205] Updated weights for policy 0, policy_version 23989 (0.0025) +[2026-07-22 20:10:36,919][50205] Updated weights for policy 0, policy_version 23999 (0.0017) +[2026-07-22 20:10:37,856][50205] Updated weights for policy 0, policy_version 24010 (0.0011) +[2026-07-22 20:10:38,495][50205] Updated weights for policy 0, policy_version 24020 (0.0012) +[2026-07-22 20:10:39,604][50205] Updated weights for policy 0, policy_version 24030 (0.0012) +[2026-07-22 20:10:39,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 5803.8). Total num frames: 12304384. Throughput: 0: 6006.4. Samples: 12314880. Policy #0 lag: (min: 0.0, avg: 15.8, max: 32.0) +[2026-07-22 20:10:39,878][43431] Avg episode reward: [(0, '1758.990')] +[2026-07-22 20:10:40,300][50205] Updated weights for policy 0, policy_version 24040 (0.0021) +[2026-07-22 20:10:41,234][50205] Updated weights for policy 0, policy_version 24050 (0.0018) +[2026-07-22 20:10:41,879][50205] Updated weights for policy 0, policy_version 24060 (0.0015) +[2026-07-22 20:10:42,862][50205] Updated weights for policy 0, policy_version 24070 (0.0016) +[2026-07-22 20:10:43,702][50205] Updated weights for policy 0, policy_version 24080 (0.0017) +[2026-07-22 20:10:44,723][50205] Updated weights for policy 0, policy_version 24090 (0.0011) +[2026-07-22 20:10:44,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6041.6, 300 sec: 5817.7). Total num frames: 12335104. Throughput: 0: 6008.2. Samples: 12333024. Policy #0 lag: (min: 0.0, avg: 15.8, max: 32.0) +[2026-07-22 20:10:44,878][43431] Avg episode reward: [(0, '1505.435')] +[2026-07-22 20:10:45,390][50205] Updated weights for policy 0, policy_version 24100 (0.0011) +[2026-07-22 20:10:46,332][50205] Updated weights for policy 0, policy_version 24110 (0.0011) +[2026-07-22 20:10:46,795][50205] Updated weights for policy 0, policy_version 24120 (0.0016) +[2026-07-22 20:10:48,067][50205] Updated weights for policy 0, policy_version 24130 (0.0017) +[2026-07-22 20:10:48,758][50205] Updated weights for policy 0, policy_version 24140 (0.0011) +[2026-07-22 20:10:49,483][50205] Updated weights for policy 0, policy_version 24150 (0.0012) +[2026-07-22 20:10:49,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 5831.6). Total num frames: 12365824. Throughput: 0: 6037.3. Samples: 12369196. Policy #0 lag: (min: 3.0, avg: 19.9, max: 43.0) +[2026-07-22 20:10:49,878][43431] Avg episode reward: [(0, '1765.525')] +[2026-07-22 20:10:50,562][50205] Updated weights for policy 0, policy_version 24160 (0.0011) +[2026-07-22 20:10:51,481][50205] Updated weights for policy 0, policy_version 24170 (0.0012) +[2026-07-22 20:10:52,077][50205] Updated weights for policy 0, policy_version 24180 (0.0011) +[2026-07-22 20:10:53,198][50205] Updated weights for policy 0, policy_version 24190 (0.0026) +[2026-07-22 20:10:53,721][50205] Updated weights for policy 0, policy_version 24200 (0.0013) +[2026-07-22 20:10:54,752][50205] Updated weights for policy 0, policy_version 24210 (0.0011) +[2026-07-22 20:10:54,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6007.5, 300 sec: 5838.5). Total num frames: 12396544. Throughput: 0: 6034.1. Samples: 12405550. Policy #0 lag: (min: 3.0, avg: 19.9, max: 43.0) +[2026-07-22 20:10:54,878][43431] Avg episode reward: [(0, '1770.961')] +[2026-07-22 20:10:55,498][50205] Updated weights for policy 0, policy_version 24220 (0.0011) +[2026-07-22 20:10:56,493][50205] Updated weights for policy 0, policy_version 24230 (0.0013) +[2026-07-22 20:10:57,008][50205] Updated weights for policy 0, policy_version 24240 (0.0011) +[2026-07-22 20:10:58,224][50205] Updated weights for policy 0, policy_version 24250 (0.0011) +[2026-07-22 20:10:58,926][50205] Updated weights for policy 0, policy_version 24260 (0.0015) +[2026-07-22 20:10:59,546][50205] Updated weights for policy 0, policy_version 24270 (0.0010) +[2026-07-22 20:10:59,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 5866.3). Total num frames: 12427264. Throughput: 0: 6040.9. Samples: 12423810. Policy #0 lag: (min: 3.0, avg: 19.9, max: 43.0) +[2026-07-22 20:10:59,878][43431] Avg episode reward: [(0, '1585.488')] +[2026-07-22 20:11:00,408][50205] Updated weights for policy 0, policy_version 24280 (0.0011) +[2026-07-22 20:11:01,631][50205] Updated weights for policy 0, policy_version 24290 (0.0011) +[2026-07-22 20:11:02,197][50205] Updated weights for policy 0, policy_version 24300 (0.0011) +[2026-07-22 20:11:03,319][50205] Updated weights for policy 0, policy_version 24310 (0.0011) +[2026-07-22 20:11:04,295][50205] Updated weights for policy 0, policy_version 24320 (0.0013) +[2026-07-22 20:11:04,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6007.5, 300 sec: 5859.4). Total num frames: 12455936. Throughput: 0: 6023.8. Samples: 12458894. Policy #0 lag: (min: 3.0, avg: 18.2, max: 31.0) +[2026-07-22 20:11:04,878][43431] Avg episode reward: [(0, '1639.217')] +[2026-07-22 20:11:05,003][50205] Updated weights for policy 0, policy_version 24330 (0.0011) +[2026-07-22 20:11:05,821][50205] Updated weights for policy 0, policy_version 24340 (0.0011) +[2026-07-22 20:11:06,887][50205] Updated weights for policy 0, policy_version 24350 (0.0012) +[2026-07-22 20:11:07,338][50205] Updated weights for policy 0, policy_version 24360 (0.0012) +[2026-07-22 20:11:08,462][50205] Updated weights for policy 0, policy_version 24370 (0.0010) +[2026-07-22 20:11:09,528][50205] Updated weights for policy 0, policy_version 24380 (0.0019) +[2026-07-22 20:11:09,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 5859.4). Total num frames: 12486656. Throughput: 0: 6017.4. Samples: 12495054. Policy #0 lag: (min: 3.0, avg: 18.2, max: 31.0) +[2026-07-22 20:11:09,878][43431] Avg episode reward: [(0, '1784.617')] +[2026-07-22 20:11:10,253][50205] Updated weights for policy 0, policy_version 24394 (0.0014) +[2026-07-22 20:11:11,122][50205] Updated weights for policy 0, policy_version 24404 (0.0012) +[2026-07-22 20:11:12,393][50205] Updated weights for policy 0, policy_version 24414 (0.0016) +[2026-07-22 20:11:13,204][50205] Updated weights for policy 0, policy_version 24425 (0.0012) +[2026-07-22 20:11:14,003][50205] Updated weights for policy 0, policy_version 24435 (0.0014) +[2026-07-22 20:11:14,877][43431] Fps is (10 sec: 5734.4, 60 sec: 6007.5, 300 sec: 5852.4). Total num frames: 12513280. Throughput: 0: 6017.2. Samples: 12513076. Policy #0 lag: (min: 3.0, avg: 18.2, max: 31.0) +[2026-07-22 20:11:14,878][43431] Avg episode reward: [(0, '1690.708')] +[2026-07-22 20:11:15,021][50205] Updated weights for policy 0, policy_version 24445 (0.0014) +[2026-07-22 20:11:15,461][50205] Updated weights for policy 0, policy_version 24455 (0.0012) +[2026-07-22 20:11:16,706][50205] Updated weights for policy 0, policy_version 24465 (0.0017) +[2026-07-22 20:11:17,302][50205] Updated weights for policy 0, policy_version 24475 (0.0011) +[2026-07-22 20:11:18,052][50205] Updated weights for policy 0, policy_version 24485 (0.0017) +[2026-07-22 20:11:18,992][50205] Updated weights for policy 0, policy_version 24495 (0.0012) +[2026-07-22 20:11:19,877][43431] Fps is (10 sec: 5734.5, 60 sec: 6007.5, 300 sec: 5866.3). Total num frames: 12544000. Throughput: 0: 6017.7. Samples: 12549354. Policy #0 lag: (min: 3.0, avg: 15.2, max: 32.0) +[2026-07-22 20:11:19,878][43431] Avg episode reward: [(0, '1660.891')] +[2026-07-22 20:11:20,228][50205] Updated weights for policy 0, policy_version 24505 (0.0011) +[2026-07-22 20:11:20,530][50205] Updated weights for policy 0, policy_version 24515 (0.0011) +[2026-07-22 20:11:21,538][50205] Updated weights for policy 0, policy_version 24525 (0.0011) +[2026-07-22 20:11:22,512][50205] Updated weights for policy 0, policy_version 24535 (0.0014) +[2026-07-22 20:11:23,337][50205] Updated weights for policy 0, policy_version 24547 (0.0012) +[2026-07-22 20:11:24,311][50205] Updated weights for policy 0, policy_version 24557 (0.0010) +[2026-07-22 20:11:24,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6007.5, 300 sec: 5880.2). Total num frames: 12574720. Throughput: 0: 6012.8. Samples: 12585454. Policy #0 lag: (min: 3.0, avg: 15.2, max: 32.0) +[2026-07-22 20:11:24,878][43431] Avg episode reward: [(0, '1636.246')] +[2026-07-22 20:11:25,153][50205] Updated weights for policy 0, policy_version 24567 (0.0015) +[2026-07-22 20:11:26,135][50205] Updated weights for policy 0, policy_version 24577 (0.0020) +[2026-07-22 20:11:26,855][50205] Updated weights for policy 0, policy_version 24587 (0.0010) +[2026-07-22 20:11:27,785][50205] Updated weights for policy 0, policy_version 24597 (0.0019) +[2026-07-22 20:11:28,405][50205] Updated weights for policy 0, policy_version 24607 (0.0011) +[2026-07-22 20:11:29,483][50205] Updated weights for policy 0, policy_version 24617 (0.0016) +[2026-07-22 20:11:29,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 5880.2). Total num frames: 12605440. Throughput: 0: 6011.4. Samples: 12603536. Policy #0 lag: (min: 3.0, avg: 15.2, max: 32.0) +[2026-07-22 20:11:29,878][43431] Avg episode reward: [(0, '1785.884')] +[2026-07-22 20:11:30,325][50205] Updated weights for policy 0, policy_version 24627 (0.0012) +[2026-07-22 20:11:31,058][50205] Updated weights for policy 0, policy_version 24637 (0.0014) +[2026-07-22 20:11:31,881][50205] Updated weights for policy 0, policy_version 24647 (0.0012) +[2026-07-22 20:11:32,925][50205] Updated weights for policy 0, policy_version 24657 (0.0011) +[2026-07-22 20:11:33,721][50205] Updated weights for policy 0, policy_version 24667 (0.0016) +[2026-07-22 20:11:34,584][50205] Updated weights for policy 0, policy_version 24677 (0.0015) +[2026-07-22 20:11:34,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 12636160. Throughput: 0: 6011.6. Samples: 12639720. Policy #0 lag: (min: 3.0, avg: 15.2, max: 32.0) +[2026-07-22 20:11:34,878][43431] Avg episode reward: [(0, '1766.807')] +[2026-07-22 20:11:35,346][50205] Updated weights for policy 0, policy_version 24687 (0.0019) +[2026-07-22 20:11:36,397][50205] Updated weights for policy 0, policy_version 24697 (0.0011) +[2026-07-22 20:11:37,219][50205] Updated weights for policy 0, policy_version 24707 (0.0011) +[2026-07-22 20:11:38,003][50205] Updated weights for policy 0, policy_version 24717 (0.0011) +[2026-07-22 20:11:38,669][50205] Updated weights for policy 0, policy_version 24727 (0.0011) +[2026-07-22 20:11:39,743][50205] Updated weights for policy 0, policy_version 24737 (0.0015) +[2026-07-22 20:11:39,877][43431] Fps is (10 sec: 6143.8, 60 sec: 6041.6, 300 sec: 5894.1). Total num frames: 12666880. Throughput: 0: 6010.6. Samples: 12676030. Policy #0 lag: (min: 3.0, avg: 16.9, max: 35.0) +[2026-07-22 20:11:39,878][43431] Avg episode reward: [(0, '1689.921')] +[2026-07-22 20:11:40,520][50205] Updated weights for policy 0, policy_version 24747 (0.0011) +[2026-07-22 20:11:41,346][50205] Updated weights for policy 0, policy_version 24757 (0.0013) +[2026-07-22 20:11:42,168][50205] Updated weights for policy 0, policy_version 24767 (0.0015) +[2026-07-22 20:11:43,120][50205] Updated weights for policy 0, policy_version 24777 (0.0012) +[2026-07-22 20:11:43,886][50205] Updated weights for policy 0, policy_version 24787 (0.0013) +[2026-07-22 20:11:44,836][50205] Updated weights for policy 0, policy_version 24797 (0.0015) +[2026-07-22 20:11:44,878][43431] Fps is (10 sec: 5938.8, 60 sec: 6007.4, 300 sec: 5894.1). Total num frames: 12695552. Throughput: 0: 6009.3. Samples: 12694232. Policy #0 lag: (min: 3.0, avg: 16.9, max: 35.0) +[2026-07-22 20:11:44,878][43431] Avg episode reward: [(0, '1806.354')] +[2026-07-22 20:11:45,583][50205] Updated weights for policy 0, policy_version 24807 (0.0015) +[2026-07-22 20:11:46,408][50205] Updated weights for policy 0, policy_version 24817 (0.0010) +[2026-07-22 20:11:47,382][50205] Updated weights for policy 0, policy_version 24827 (0.0011) +[2026-07-22 20:11:48,352][50205] Updated weights for policy 0, policy_version 24837 (0.0015) +[2026-07-22 20:11:48,924][50205] Updated weights for policy 0, policy_version 24847 (0.0012) +[2026-07-22 20:11:49,877][43431] Fps is (10 sec: 5939.3, 60 sec: 6007.5, 300 sec: 5901.0). Total num frames: 12726272. Throughput: 0: 6029.2. Samples: 12730208. Policy #0 lag: (min: 3.0, avg: 16.9, max: 35.0) +[2026-07-22 20:11:49,878][43431] Avg episode reward: [(0, '1736.633')] +[2026-07-22 20:11:49,883][50205] Updated weights for policy 0, policy_version 24857 (0.0021) +[2026-07-22 20:11:50,826][50205] Updated weights for policy 0, policy_version 24867 (0.0014) +[2026-07-22 20:11:51,572][50205] Updated weights for policy 0, policy_version 24877 (0.0011) +[2026-07-22 20:11:52,377][50205] Updated weights for policy 0, policy_version 24887 (0.0010) +[2026-07-22 20:11:53,347][50205] Updated weights for policy 0, policy_version 24897 (0.0020) +[2026-07-22 20:11:54,177][50205] Updated weights for policy 0, policy_version 24907 (0.0011) +[2026-07-22 20:11:54,877][43431] Fps is (10 sec: 6144.4, 60 sec: 6007.5, 300 sec: 5908.0). Total num frames: 12756992. Throughput: 0: 6032.6. Samples: 12766520. Policy #0 lag: (min: 3.0, avg: 20.2, max: 39.0) +[2026-07-22 20:11:54,878][43431] Avg episode reward: [(0, '1868.426')] +[2026-07-22 20:11:55,055][50205] Updated weights for policy 0, policy_version 24917 (0.0011) +[2026-07-22 20:11:55,622][50205] Updated weights for policy 0, policy_version 24927 (0.0020) +[2026-07-22 20:11:56,649][50205] Updated weights for policy 0, policy_version 24937 (0.0011) +[2026-07-22 20:11:57,505][50205] Updated weights for policy 0, policy_version 24947 (0.0014) +[2026-07-22 20:11:58,282][50205] Updated weights for policy 0, policy_version 24957 (0.0011) +[2026-07-22 20:11:59,176][50205] Updated weights for policy 0, policy_version 24967 (0.0013) +[2026-07-22 20:11:59,878][43431] Fps is (10 sec: 6143.7, 60 sec: 6007.4, 300 sec: 5914.9). Total num frames: 12787712. Throughput: 0: 6034.2. Samples: 12784616. Policy #0 lag: (min: 3.0, avg: 20.2, max: 39.0) +[2026-07-22 20:11:59,878][43431] Avg episode reward: [(0, '1842.685')] +[2026-07-22 20:12:00,119][50205] Updated weights for policy 0, policy_version 24977 (0.0013) +[2026-07-22 20:12:00,686][50205] Updated weights for policy 0, policy_version 24987 (0.0013) +[2026-07-22 20:12:02,206][50205] Updated weights for policy 0, policy_version 25000 (0.0011) +[2026-07-22 20:12:03,122][50205] Updated weights for policy 0, policy_version 25010 (0.0016) +[2026-07-22 20:12:03,725][50205] Updated weights for policy 0, policy_version 25020 (0.0011) +[2026-07-22 20:12:04,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5973.4, 300 sec: 5914.9). Total num frames: 12814336. Throughput: 0: 5984.2. Samples: 12818644. Policy #0 lag: (min: 3.0, avg: 20.2, max: 39.0) +[2026-07-22 20:12:04,878][43431] Avg episode reward: [(0, '1886.093')] +[2026-07-22 20:12:04,903][50205] Updated weights for policy 0, policy_version 25030 (0.0017) +[2026-07-22 20:12:05,550][50205] Updated weights for policy 0, policy_version 25040 (0.0015) +[2026-07-22 20:12:06,454][50205] Updated weights for policy 0, policy_version 25050 (0.0011) +[2026-07-22 20:12:07,408][50205] Updated weights for policy 0, policy_version 25060 (0.0011) +[2026-07-22 20:12:08,329][50205] Updated weights for policy 0, policy_version 25070 (0.0024) +[2026-07-22 20:12:08,960][50205] Updated weights for policy 0, policy_version 25080 (0.0014) +[2026-07-22 20:12:09,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5973.3, 300 sec: 5935.7). Total num frames: 12845056. Throughput: 0: 5988.2. Samples: 12854922. Policy #0 lag: (min: 3.0, avg: 20.2, max: 39.0) +[2026-07-22 20:12:09,878][43431] Avg episode reward: [(0, '1758.308')] +[2026-07-22 20:12:10,081][50205] Updated weights for policy 0, policy_version 25090 (0.0015) +[2026-07-22 20:12:10,734][50205] Updated weights for policy 0, policy_version 25100 (0.0014) +[2026-07-22 20:12:11,467][50205] Updated weights for policy 0, policy_version 25110 (0.0016) +[2026-07-22 20:12:12,441][50205] Updated weights for policy 0, policy_version 25120 (0.0016) +[2026-07-22 20:12:13,464][50205] Updated weights for policy 0, policy_version 25130 (0.0012) +[2026-07-22 20:12:14,001][50205] Updated weights for policy 0, policy_version 25140 (0.0011) +[2026-07-22 20:12:14,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6041.6, 300 sec: 5935.7). Total num frames: 12875776. Throughput: 0: 5989.8. Samples: 12873078. Policy #0 lag: (min: 3.0, avg: 17.2, max: 35.0) +[2026-07-22 20:12:14,878][43431] Avg episode reward: [(0, '1675.835')] +[2026-07-22 20:12:15,243][50205] Updated weights for policy 0, policy_version 25150 (0.0019) +[2026-07-22 20:12:15,899][50205] Updated weights for policy 0, policy_version 25160 (0.0015) +[2026-07-22 20:12:16,779][50205] Updated weights for policy 0, policy_version 25170 (0.0012) +[2026-07-22 20:12:17,298][50205] Updated weights for policy 0, policy_version 25180 (0.0011) +[2026-07-22 20:12:18,589][50205] Updated weights for policy 0, policy_version 25190 (0.0014) +[2026-07-22 20:12:19,267][50205] Updated weights for policy 0, policy_version 25200 (0.0011) +[2026-07-22 20:12:19,877][43431] Fps is (10 sec: 6144.2, 60 sec: 6041.6, 300 sec: 5935.7). Total num frames: 12906496. Throughput: 0: 5989.4. Samples: 12909244. Policy #0 lag: (min: 3.0, avg: 17.2, max: 35.0) +[2026-07-22 20:12:19,878][43431] Avg episode reward: [(0, '1619.826')] +[2026-07-22 20:12:19,944][50205] Updated weights for policy 0, policy_version 25210 (0.0012) +[2026-07-22 20:12:20,878][50205] Updated weights for policy 0, policy_version 25220 (0.0016) +[2026-07-22 20:12:21,746][50205] Updated weights for policy 0, policy_version 25230 (0.0010) +[2026-07-22 20:12:22,432][50205] Updated weights for policy 0, policy_version 25240 (0.0013) +[2026-07-22 20:12:23,804][50205] Updated weights for policy 0, policy_version 25250 (0.0015) +[2026-07-22 20:12:24,148][50205] Updated weights for policy 0, policy_version 25260 (0.0014) +[2026-07-22 20:12:24,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6007.5, 300 sec: 5935.7). Total num frames: 12935168. Throughput: 0: 5982.6. Samples: 12945244. Policy #0 lag: (min: 3.0, avg: 17.2, max: 35.0) +[2026-07-22 20:12:24,878][43431] Avg episode reward: [(0, '1759.080')] +[2026-07-22 20:12:25,100][50205] Updated weights for policy 0, policy_version 25270 (0.0012) +[2026-07-22 20:12:26,142][50205] Updated weights for policy 0, policy_version 25280 (0.0017) +[2026-07-22 20:12:26,719][50205] Updated weights for policy 0, policy_version 25290 (0.0022) +[2026-07-22 20:12:27,684][50205] Updated weights for policy 0, policy_version 25300 (0.0013) +[2026-07-22 20:12:28,781][50205] Updated weights for policy 0, policy_version 25310 (0.0017) +[2026-07-22 20:12:29,283][50205] Updated weights for policy 0, policy_version 25320 (0.0013) +[2026-07-22 20:12:29,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6007.5, 300 sec: 5942.7). Total num frames: 12965888. Throughput: 0: 5982.1. Samples: 12963424. Policy #0 lag: (min: 1.0, avg: 15.1, max: 29.0) +[2026-07-22 20:12:29,878][43431] Avg episode reward: [(0, '1545.529')] +[2026-07-22 20:12:30,272][50205] Updated weights for policy 0, policy_version 25330 (0.0011) +[2026-07-22 20:12:31,147][50205] Updated weights for policy 0, policy_version 25340 (0.0011) +[2026-07-22 20:12:31,895][50205] Updated weights for policy 0, policy_version 25350 (0.0014) +[2026-07-22 20:12:32,759][50205] Updated weights for policy 0, policy_version 25360 (0.0016) +[2026-07-22 20:12:33,887][50205] Updated weights for policy 0, policy_version 25370 (0.0015) +[2026-07-22 20:12:34,389][50205] Updated weights for policy 0, policy_version 25380 (0.0016) +[2026-07-22 20:12:34,877][43431] Fps is (10 sec: 6348.7, 60 sec: 6041.6, 300 sec: 5963.5). Total num frames: 12998656. Throughput: 0: 5986.3. Samples: 12999592. Policy #0 lag: (min: 1.0, avg: 15.1, max: 29.0) +[2026-07-22 20:12:34,878][43431] Avg episode reward: [(0, '1640.966')] +[2026-07-22 20:12:35,344][50205] Updated weights for policy 0, policy_version 25390 (0.0014) +[2026-07-22 20:12:36,125][50205] Updated weights for policy 0, policy_version 25400 (0.0012) +[2026-07-22 20:12:37,035][50205] Updated weights for policy 0, policy_version 25410 (0.0015) +[2026-07-22 20:12:37,828][50205] Updated weights for policy 0, policy_version 25420 (0.0011) +[2026-07-22 20:12:38,901][50205] Updated weights for policy 0, policy_version 25430 (0.0012) +[2026-07-22 20:12:39,535][50205] Updated weights for policy 0, policy_version 25440 (0.0012) +[2026-07-22 20:12:39,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 5963.5). Total num frames: 13027328. Throughput: 0: 5987.0. Samples: 13035934. Policy #0 lag: (min: 1.0, avg: 15.1, max: 29.0) +[2026-07-22 20:12:39,878][43431] Avg episode reward: [(0, '1766.450')] +[2026-07-22 20:12:39,889][49527] Saving results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/checkpoint_p0/checkpoint_000025444_13027328.pth... +[2026-07-22 20:12:40,461][50205] Updated weights for policy 0, policy_version 25450 (0.0011) +[2026-07-22 20:12:41,358][50205] Updated weights for policy 0, policy_version 25460 (0.0018) +[2026-07-22 20:12:42,049][50205] Updated weights for policy 0, policy_version 25470 (0.0011) +[2026-07-22 20:12:42,715][50205] Updated weights for policy 0, policy_version 25480 (0.0011) +[2026-07-22 20:12:44,059][50205] Updated weights for policy 0, policy_version 25490 (0.0011) +[2026-07-22 20:12:44,877][43431] Fps is (10 sec: 5734.5, 60 sec: 6007.5, 300 sec: 5956.6). Total num frames: 13056000. Throughput: 0: 5988.6. Samples: 13054102. Policy #0 lag: (min: 3.0, avg: 17.3, max: 39.0) +[2026-07-22 20:12:44,878][43431] Avg episode reward: [(0, '1631.432')] +[2026-07-22 20:12:44,924][50205] Updated weights for policy 0, policy_version 25502 (0.0011) +[2026-07-22 20:12:45,477][50205] Updated weights for policy 0, policy_version 25512 (0.0016) +[2026-07-22 20:12:46,817][50205] Updated weights for policy 0, policy_version 25522 (0.0011) +[2026-07-22 20:12:47,266][50205] Updated weights for policy 0, policy_version 25532 (0.0011) +[2026-07-22 20:12:48,329][50205] Updated weights for policy 0, policy_version 25542 (0.0014) +[2026-07-22 20:12:49,071][50205] Updated weights for policy 0, policy_version 25552 (0.0012) +[2026-07-22 20:12:49,777][50205] Updated weights for policy 0, policy_version 25562 (0.0015) +[2026-07-22 20:12:49,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 5977.4). Total num frames: 13088768. Throughput: 0: 6036.4. Samples: 13090282. Policy #0 lag: (min: 3.0, avg: 17.3, max: 39.0) +[2026-07-22 20:12:49,878][43431] Avg episode reward: [(0, '1774.960')] +[2026-07-22 20:12:50,595][50205] Updated weights for policy 0, policy_version 25572 (0.0011) +[2026-07-22 20:12:51,943][50205] Updated weights for policy 0, policy_version 25582 (0.0015) +[2026-07-22 20:12:52,286][50205] Updated weights for policy 0, policy_version 25592 (0.0013) +[2026-07-22 20:12:53,141][50205] Updated weights for policy 0, policy_version 25602 (0.0020) +[2026-07-22 20:12:54,336][50205] Updated weights for policy 0, policy_version 25612 (0.0018) +[2026-07-22 20:12:54,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6007.4, 300 sec: 5970.4). Total num frames: 13117440. Throughput: 0: 6035.1. Samples: 13126502. Policy #0 lag: (min: 3.0, avg: 17.3, max: 39.0) +[2026-07-22 20:12:54,878][43431] Avg episode reward: [(0, '1760.633')] +[2026-07-22 20:12:55,035][50205] Updated weights for policy 0, policy_version 25622 (0.0011) +[2026-07-22 20:12:55,598][50205] Updated weights for policy 0, policy_version 25632 (0.0013) +[2026-07-22 20:12:57,012][50205] Updated weights for policy 0, policy_version 25642 (0.0010) +[2026-07-22 20:12:57,494][50205] Updated weights for policy 0, policy_version 25652 (0.0011) +[2026-07-22 20:12:58,310][50205] Updated weights for policy 0, policy_version 25662 (0.0014) +[2026-07-22 20:12:59,073][50205] Updated weights for policy 0, policy_version 25672 (0.0011) +[2026-07-22 20:12:59,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5973.4, 300 sec: 5977.4). Total num frames: 13146112. Throughput: 0: 6035.4. Samples: 13144670. Policy #0 lag: (min: 3.0, avg: 17.3, max: 39.0) +[2026-07-22 20:12:59,878][43431] Avg episode reward: [(0, '1677.937')] +[2026-07-22 20:13:00,143][50205] Updated weights for policy 0, policy_version 25682 (0.0011) +[2026-07-22 20:13:00,679][50205] Updated weights for policy 0, policy_version 25692 (0.0011) +[2026-07-22 20:13:02,295][50205] Updated weights for policy 0, policy_version 25705 (0.0011) +[2026-07-22 20:13:02,858][50205] Updated weights for policy 0, policy_version 25715 (0.0013) +[2026-07-22 20:13:03,798][50205] Updated weights for policy 0, policy_version 25725 (0.0016) +[2026-07-22 20:13:04,690][50205] Updated weights for policy 0, policy_version 25735 (0.0013) +[2026-07-22 20:13:04,877][43431] Fps is (10 sec: 5939.4, 60 sec: 6041.6, 300 sec: 5977.4). Total num frames: 13176832. Throughput: 0: 6034.9. Samples: 13180812. Policy #0 lag: (min: 3.0, avg: 19.1, max: 38.0) +[2026-07-22 20:13:04,878][43431] Avg episode reward: [(0, '1739.199')] +[2026-07-22 20:13:05,661][50205] Updated weights for policy 0, policy_version 25745 (0.0011) +[2026-07-22 20:13:06,134][50205] Updated weights for policy 0, policy_version 25755 (0.0011) +[2026-07-22 20:13:07,306][50205] Updated weights for policy 0, policy_version 25765 (0.0016) +[2026-07-22 20:13:08,176][50205] Updated weights for policy 0, policy_version 25775 (0.0011) +[2026-07-22 20:13:08,932][50205] Updated weights for policy 0, policy_version 25785 (0.0016) +[2026-07-22 20:13:09,526][50205] Updated weights for policy 0, policy_version 25795 (0.0016) +[2026-07-22 20:13:09,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6041.6, 300 sec: 5991.3). Total num frames: 13207552. Throughput: 0: 6041.9. Samples: 13217130. Policy #0 lag: (min: 3.0, avg: 19.1, max: 38.0) +[2026-07-22 20:13:09,878][43431] Avg episode reward: [(0, '1888.160')] +[2026-07-22 20:13:10,829][50205] Updated weights for policy 0, policy_version 25805 (0.0015) +[2026-07-22 20:13:11,314][50205] Updated weights for policy 0, policy_version 25816 (0.0012) +[2026-07-22 20:13:12,226][50205] Updated weights for policy 0, policy_version 25826 (0.0017) +[2026-07-22 20:13:13,193][50205] Updated weights for policy 0, policy_version 25836 (0.0011) +[2026-07-22 20:13:13,995][50205] Updated weights for policy 0, policy_version 25846 (0.0011) +[2026-07-22 20:13:14,878][43431] Fps is (10 sec: 5938.9, 60 sec: 6007.4, 300 sec: 5991.3). Total num frames: 13236224. Throughput: 0: 6039.7. Samples: 13235212. Policy #0 lag: (min: 3.0, avg: 19.1, max: 38.0) +[2026-07-22 20:13:14,878][43431] Avg episode reward: [(0, '1684.448')] +[2026-07-22 20:13:15,128][50205] Updated weights for policy 0, policy_version 25858 (0.0011) +[2026-07-22 20:13:16,019][50205] Updated weights for policy 0, policy_version 25868 (0.0012) +[2026-07-22 20:13:16,751][50205] Updated weights for policy 0, policy_version 25878 (0.0012) +[2026-07-22 20:13:17,407][50205] Updated weights for policy 0, policy_version 25888 (0.0015) +[2026-07-22 20:13:18,700][50205] Updated weights for policy 0, policy_version 25898 (0.0011) +[2026-07-22 20:13:19,228][50205] Updated weights for policy 0, policy_version 25908 (0.0013) +[2026-07-22 20:13:19,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 6005.2). Total num frames: 13268992. Throughput: 0: 6031.7. Samples: 13271016. Policy #0 lag: (min: 3.0, avg: 17.6, max: 39.0) +[2026-07-22 20:13:19,878][43431] Avg episode reward: [(0, '1638.297')] +[2026-07-22 20:13:20,024][50205] Updated weights for policy 0, policy_version 25918 (0.0011) +[2026-07-22 20:13:21,225][50205] Updated weights for policy 0, policy_version 25928 (0.0011) +[2026-07-22 20:13:22,005][50205] Updated weights for policy 0, policy_version 25938 (0.0014) +[2026-07-22 20:13:22,565][50205] Updated weights for policy 0, policy_version 25948 (0.0011) +[2026-07-22 20:13:23,880][50205] Updated weights for policy 0, policy_version 25958 (0.0012) +[2026-07-22 20:13:24,566][50205] Updated weights for policy 0, policy_version 25969 (0.0015) +[2026-07-22 20:13:24,877][43431] Fps is (10 sec: 6144.2, 60 sec: 6041.6, 300 sec: 6005.2). Total num frames: 13297664. Throughput: 0: 6024.5. Samples: 13307038. Policy #0 lag: (min: 3.0, avg: 17.6, max: 39.0) +[2026-07-22 20:13:24,878][43431] Avg episode reward: [(0, '1838.250')] +[2026-07-22 20:13:25,300][50205] Updated weights for policy 0, policy_version 25979 (0.0011) +[2026-07-22 20:13:26,629][50205] Updated weights for policy 0, policy_version 25989 (0.0010) +[2026-07-22 20:13:27,175][50205] Updated weights for policy 0, policy_version 25999 (0.0011) +[2026-07-22 20:13:27,967][50205] Updated weights for policy 0, policy_version 26009 (0.0011) +[2026-07-22 20:13:29,081][50205] Updated weights for policy 0, policy_version 26019 (0.0016) +[2026-07-22 20:13:29,710][50205] Updated weights for policy 0, policy_version 26029 (0.0012) +[2026-07-22 20:13:29,878][43431] Fps is (10 sec: 5938.9, 60 sec: 6041.6, 300 sec: 6019.0). Total num frames: 13328384. Throughput: 0: 6021.7. Samples: 13325080. Policy #0 lag: (min: 3.0, avg: 17.6, max: 39.0) +[2026-07-22 20:13:29,878][43431] Avg episode reward: [(0, '1713.195')] +[2026-07-22 20:13:30,624][50205] Updated weights for policy 0, policy_version 26041 (0.0011) +[2026-07-22 20:13:31,949][50205] Updated weights for policy 0, policy_version 26051 (0.0012) +[2026-07-22 20:13:32,404][50205] Updated weights for policy 0, policy_version 26061 (0.0011) +[2026-07-22 20:13:33,170][50205] Updated weights for policy 0, policy_version 26071 (0.0011) +[2026-07-22 20:13:34,489][50205] Updated weights for policy 0, policy_version 26081 (0.0011) +[2026-07-22 20:13:34,863][50205] Updated weights for policy 0, policy_version 26091 (0.0011) +[2026-07-22 20:13:34,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6007.5, 300 sec: 6019.0). Total num frames: 13359104. Throughput: 0: 6018.8. Samples: 13361130. Policy #0 lag: (min: 3.0, avg: 17.6, max: 39.0) +[2026-07-22 20:13:34,878][43431] Avg episode reward: [(0, '1727.163')] +[2026-07-22 20:13:35,787][50205] Updated weights for policy 0, policy_version 26101 (0.0016) +[2026-07-22 20:13:36,632][50205] Updated weights for policy 0, policy_version 26111 (0.0012) +[2026-07-22 20:13:37,580][50205] Updated weights for policy 0, policy_version 26121 (0.0010) +[2026-07-22 20:13:38,187][50205] Updated weights for policy 0, policy_version 26131 (0.0022) +[2026-07-22 20:13:39,397][50205] Updated weights for policy 0, policy_version 26141 (0.0011) +[2026-07-22 20:13:39,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5973.3, 300 sec: 6012.1). Total num frames: 13385728. Throughput: 0: 6022.3. Samples: 13397508. Policy #0 lag: (min: 3.0, avg: 20.8, max: 39.0) +[2026-07-22 20:13:39,878][43431] Avg episode reward: [(0, '1754.775')] +[2026-07-22 20:13:40,196][50205] Updated weights for policy 0, policy_version 26151 (0.0011) +[2026-07-22 20:13:40,872][50205] Updated weights for policy 0, policy_version 26161 (0.0011) +[2026-07-22 20:13:41,572][50205] Updated weights for policy 0, policy_version 26171 (0.0016) +[2026-07-22 20:13:42,844][50205] Updated weights for policy 0, policy_version 26181 (0.0013) +[2026-07-22 20:13:43,205][50205] Updated weights for policy 0, policy_version 26191 (0.0017) +[2026-07-22 20:13:44,413][50205] Updated weights for policy 0, policy_version 26201 (0.0010) +[2026-07-22 20:13:44,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 6012.1). Total num frames: 13418496. Throughput: 0: 6022.3. Samples: 13415674. Policy #0 lag: (min: 3.0, avg: 20.8, max: 39.0) +[2026-07-22 20:13:44,878][43431] Avg episode reward: [(0, '1631.820')] +[2026-07-22 20:13:45,353][50205] Updated weights for policy 0, policy_version 26211 (0.0011) +[2026-07-22 20:13:45,871][50205] Updated weights for policy 0, policy_version 26221 (0.0021) +[2026-07-22 20:13:46,731][50205] Updated weights for policy 0, policy_version 26231 (0.0011) +[2026-07-22 20:13:47,998][50205] Updated weights for policy 0, policy_version 26241 (0.0022) +[2026-07-22 20:13:48,436][50205] Updated weights for policy 0, policy_version 26251 (0.0012) +[2026-07-22 20:13:49,274][50205] Updated weights for policy 0, policy_version 26261 (0.0020) +[2026-07-22 20:13:49,877][43431] Fps is (10 sec: 6144.1, 60 sec: 5973.3, 300 sec: 6012.1). Total num frames: 13447168. Throughput: 0: 6021.8. Samples: 13451794. Policy #0 lag: (min: 3.0, avg: 20.8, max: 39.0) +[2026-07-22 20:13:49,878][43431] Avg episode reward: [(0, '1731.411')] +[2026-07-22 20:13:50,488][50205] Updated weights for policy 0, policy_version 26271 (0.0011) +[2026-07-22 20:13:51,140][50205] Updated weights for policy 0, policy_version 26283 (0.0013) +[2026-07-22 20:13:52,061][50205] Updated weights for policy 0, policy_version 26293 (0.0016) +[2026-07-22 20:13:53,183][50205] Updated weights for policy 0, policy_version 26303 (0.0011) +[2026-07-22 20:13:53,770][50205] Updated weights for policy 0, policy_version 26313 (0.0015) +[2026-07-22 20:13:54,333][50205] Updated weights for policy 0, policy_version 26323 (0.0015) +[2026-07-22 20:13:54,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 6019.0). Total num frames: 13479936. Throughput: 0: 6021.1. Samples: 13488080. Policy #0 lag: (min: 4.0, avg: 15.5, max: 36.0) +[2026-07-22 20:13:54,878][43431] Avg episode reward: [(0, '1841.273')] +[2026-07-22 20:13:55,637][50205] Updated weights for policy 0, policy_version 26333 (0.0011) +[2026-07-22 20:13:56,312][50205] Updated weights for policy 0, policy_version 26343 (0.0012) +[2026-07-22 20:13:57,159][50205] Updated weights for policy 0, policy_version 26353 (0.0012) +[2026-07-22 20:13:58,202][50205] Updated weights for policy 0, policy_version 26363 (0.0013) +[2026-07-22 20:13:58,916][50205] Updated weights for policy 0, policy_version 26373 (0.0014) +[2026-07-22 20:13:58,968][49527] Signal inference workers to stop experience collection... (450 times) +[2026-07-22 20:13:58,978][50205] InferenceWorker_p0-w0: stopping experience collection (450 times) +[2026-07-22 20:13:58,998][49527] Signal inference workers to resume experience collection... (450 times) +[2026-07-22 20:13:58,999][50205] InferenceWorker_p0-w0: resuming experience collection (450 times) +[2026-07-22 20:13:59,481][50205] Updated weights for policy 0, policy_version 26383 (0.0011) +[2026-07-22 20:13:59,878][43431] Fps is (10 sec: 6143.6, 60 sec: 6041.6, 300 sec: 6019.0). Total num frames: 13508608. Throughput: 0: 6025.5. Samples: 13506360. Policy #0 lag: (min: 4.0, avg: 15.5, max: 36.0) +[2026-07-22 20:13:59,878][43431] Avg episode reward: [(0, '1563.731')] +[2026-07-22 20:14:00,803][50205] Updated weights for policy 0, policy_version 26393 (0.0011) +[2026-07-22 20:14:01,503][50205] Updated weights for policy 0, policy_version 26403 (0.0020) +[2026-07-22 20:14:02,601][50205] Updated weights for policy 0, policy_version 26414 (0.0021) +[2026-07-22 20:14:03,643][50205] Updated weights for policy 0, policy_version 26424 (0.0012) +[2026-07-22 20:14:04,546][50205] Updated weights for policy 0, policy_version 26434 (0.0012) +[2026-07-22 20:14:04,877][43431] Fps is (10 sec: 5734.3, 60 sec: 6007.4, 300 sec: 6012.1). Total num frames: 13537280. Throughput: 0: 5980.8. Samples: 13540154. Policy #0 lag: (min: 4.0, avg: 15.5, max: 36.0) +[2026-07-22 20:14:04,878][43431] Avg episode reward: [(0, '1723.887')] +[2026-07-22 20:14:04,935][50205] Updated weights for policy 0, policy_version 26444 (0.0012) +[2026-07-22 20:14:06,185][50205] Updated weights for policy 0, policy_version 26454 (0.0016) +[2026-07-22 20:14:07,120][50205] Updated weights for policy 0, policy_version 26464 (0.0011) +[2026-07-22 20:14:07,663][50205] Updated weights for policy 0, policy_version 26474 (0.0013) +[2026-07-22 20:14:08,356][50205] Updated weights for policy 0, policy_version 26484 (0.0017) +[2026-07-22 20:14:09,722][50205] Updated weights for policy 0, policy_version 26494 (0.0011) +[2026-07-22 20:14:09,877][43431] Fps is (10 sec: 5734.8, 60 sec: 5973.3, 300 sec: 6012.1). Total num frames: 13565952. Throughput: 0: 5982.5. Samples: 13576250. Policy #0 lag: (min: 4.0, avg: 15.5, max: 36.0) +[2026-07-22 20:14:09,878][43431] Avg episode reward: [(0, '1687.782')] +[2026-07-22 20:14:10,073][50205] Updated weights for policy 0, policy_version 26504 (0.0011) +[2026-07-22 20:14:11,167][50205] Updated weights for policy 0, policy_version 26514 (0.0012) +[2026-07-22 20:14:12,244][50205] Updated weights for policy 0, policy_version 26524 (0.0012) +[2026-07-22 20:14:12,799][50205] Updated weights for policy 0, policy_version 26534 (0.0015) +[2026-07-22 20:14:13,593][50205] Updated weights for policy 0, policy_version 26544 (0.0014) +[2026-07-22 20:14:14,824][50205] Updated weights for policy 0, policy_version 26554 (0.0011) +[2026-07-22 20:14:14,877][43431] Fps is (10 sec: 5939.3, 60 sec: 6007.5, 300 sec: 6012.1). Total num frames: 13596672. Throughput: 0: 5980.5. Samples: 13594202. Policy #0 lag: (min: 1.0, avg: 20.9, max: 41.0) +[2026-07-22 20:14:14,878][43431] Avg episode reward: [(0, '1735.373')] +[2026-07-22 20:14:15,333][50205] Updated weights for policy 0, policy_version 26564 (0.0012) +[2026-07-22 20:14:16,296][50205] Updated weights for policy 0, policy_version 26574 (0.0012) +[2026-07-22 20:14:17,064][50205] Updated weights for policy 0, policy_version 26584 (0.0013) +[2026-07-22 20:14:17,945][50205] Updated weights for policy 0, policy_version 26594 (0.0011) +[2026-07-22 20:14:18,715][50205] Updated weights for policy 0, policy_version 26604 (0.0011) +[2026-07-22 20:14:19,875][50205] Updated weights for policy 0, policy_version 26614 (0.0017) +[2026-07-22 20:14:19,877][43431] Fps is (10 sec: 5939.1, 60 sec: 5939.2, 300 sec: 6005.2). Total num frames: 13625344. Throughput: 0: 5991.4. Samples: 13630746. Policy #0 lag: (min: 1.0, avg: 20.9, max: 41.0) +[2026-07-22 20:14:19,878][43431] Avg episode reward: [(0, '1785.208')] +[2026-07-22 20:14:20,300][50205] Updated weights for policy 0, policy_version 26624 (0.0012) +[2026-07-22 20:14:21,308][50205] Updated weights for policy 0, policy_version 26634 (0.0013) +[2026-07-22 20:14:22,164][50205] Updated weights for policy 0, policy_version 26644 (0.0015) +[2026-07-22 20:14:22,972][50205] Updated weights for policy 0, policy_version 26654 (0.0012) +[2026-07-22 20:14:23,692][50205] Updated weights for policy 0, policy_version 26664 (0.0011) +[2026-07-22 20:14:24,769][50205] Updated weights for policy 0, policy_version 26674 (0.0011) +[2026-07-22 20:14:24,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 6012.1). Total num frames: 13658112. Throughput: 0: 5995.6. Samples: 13667310. Policy #0 lag: (min: 1.0, avg: 20.9, max: 41.0) +[2026-07-22 20:14:24,878][43431] Avg episode reward: [(0, '1759.286')] +[2026-07-22 20:14:25,496][50205] Updated weights for policy 0, policy_version 26684 (0.0013) +[2026-07-22 20:14:26,539][50205] Updated weights for policy 0, policy_version 26694 (0.0019) +[2026-07-22 20:14:27,177][50205] Updated weights for policy 0, policy_version 26704 (0.0011) +[2026-07-22 20:14:28,121][50205] Updated weights for policy 0, policy_version 26714 (0.0011) +[2026-07-22 20:14:28,931][50205] Updated weights for policy 0, policy_version 26724 (0.0016) +[2026-07-22 20:14:29,877][43431] Fps is (10 sec: 6144.1, 60 sec: 5973.4, 300 sec: 6012.1). Total num frames: 13686784. Throughput: 0: 5993.8. Samples: 13685396. Policy #0 lag: (min: 3.0, avg: 18.5, max: 35.0) +[2026-07-22 20:14:29,878][43431] Avg episode reward: [(0, '1800.491')] +[2026-07-22 20:14:30,232][50205] Updated weights for policy 0, policy_version 26737 (0.0012) +[2026-07-22 20:14:31,063][50205] Updated weights for policy 0, policy_version 26747 (0.0017) +[2026-07-22 20:14:32,057][50205] Updated weights for policy 0, policy_version 26757 (0.0010) +[2026-07-22 20:14:32,665][50205] Updated weights for policy 0, policy_version 26767 (0.0014) +[2026-07-22 20:14:33,699][50205] Updated weights for policy 0, policy_version 26777 (0.0015) +[2026-07-22 20:14:34,577][50205] Updated weights for policy 0, policy_version 26787 (0.0017) +[2026-07-22 20:14:34,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5973.3, 300 sec: 6019.0). Total num frames: 13717504. Throughput: 0: 5974.0. Samples: 13720622. Policy #0 lag: (min: 3.0, avg: 18.5, max: 35.0) +[2026-07-22 20:14:34,879][43431] Avg episode reward: [(0, '1598.406')] +[2026-07-22 20:14:35,409][50205] Updated weights for policy 0, policy_version 26797 (0.0011) +[2026-07-22 20:14:36,175][50205] Updated weights for policy 0, policy_version 26807 (0.0016) +[2026-07-22 20:14:37,258][50205] Updated weights for policy 0, policy_version 26817 (0.0011) +[2026-07-22 20:14:37,780][50205] Updated weights for policy 0, policy_version 26827 (0.0010) +[2026-07-22 20:14:38,876][50205] Updated weights for policy 0, policy_version 26837 (0.0012) +[2026-07-22 20:14:39,678][50205] Updated weights for policy 0, policy_version 26847 (0.0013) +[2026-07-22 20:14:39,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6007.5, 300 sec: 6012.1). Total num frames: 13746176. Throughput: 0: 5973.0. Samples: 13756864. Policy #0 lag: (min: 3.0, avg: 18.5, max: 35.0) +[2026-07-22 20:14:39,878][43431] Avg episode reward: [(0, '1705.000')] +[2026-07-22 20:14:40,392][50205] Updated weights for policy 0, policy_version 26857 (0.0012) +[2026-07-22 20:14:41,066][50205] Updated weights for policy 0, policy_version 26867 (0.0011) +[2026-07-22 20:14:42,349][50205] Updated weights for policy 0, policy_version 26877 (0.0011) +[2026-07-22 20:14:42,844][50205] Updated weights for policy 0, policy_version 26887 (0.0011) +[2026-07-22 20:14:43,672][50205] Updated weights for policy 0, policy_version 26897 (0.0011) +[2026-07-22 20:14:44,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5939.2, 300 sec: 5998.2). Total num frames: 13774848. Throughput: 0: 5969.7. Samples: 13774994. Policy #0 lag: (min: 3.0, avg: 18.5, max: 35.0) +[2026-07-22 20:14:44,878][43431] Avg episode reward: [(0, '1616.301')] +[2026-07-22 20:14:45,057][50205] Updated weights for policy 0, policy_version 26909 (0.0017) +[2026-07-22 20:14:45,675][50205] Updated weights for policy 0, policy_version 26919 (0.0017) +[2026-07-22 20:14:46,308][50205] Updated weights for policy 0, policy_version 26929 (0.0022) +[2026-07-22 20:14:47,427][50205] Updated weights for policy 0, policy_version 26939 (0.0016) +[2026-07-22 20:14:48,222][50205] Updated weights for policy 0, policy_version 26949 (0.0017) +[2026-07-22 20:14:48,942][50205] Updated weights for policy 0, policy_version 26959 (0.0012) +[2026-07-22 20:14:49,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 6005.2). Total num frames: 13807616. Throughput: 0: 6021.7. Samples: 13811132. Policy #0 lag: (min: 3.0, avg: 19.5, max: 47.0) +[2026-07-22 20:14:49,878][43431] Avg episode reward: [(0, '1709.244')] +[2026-07-22 20:14:50,002][50205] Updated weights for policy 0, policy_version 26969 (0.0022) +[2026-07-22 20:14:50,713][50205] Updated weights for policy 0, policy_version 26979 (0.0011) +[2026-07-22 20:14:51,552][50205] Updated weights for policy 0, policy_version 26989 (0.0017) +[2026-07-22 20:14:52,433][50205] Updated weights for policy 0, policy_version 26999 (0.0017) +[2026-07-22 20:14:53,314][50205] Updated weights for policy 0, policy_version 27009 (0.0011) +[2026-07-22 20:14:54,047][50205] Updated weights for policy 0, policy_version 27019 (0.0010) +[2026-07-22 20:14:54,877][43431] Fps is (10 sec: 6348.8, 60 sec: 5973.3, 300 sec: 6005.2). Total num frames: 13838336. Throughput: 0: 6024.2. Samples: 13847340. Policy #0 lag: (min: 3.0, avg: 19.5, max: 47.0) +[2026-07-22 20:14:54,878][43431] Avg episode reward: [(0, '1765.742')] +[2026-07-22 20:14:55,091][50205] Updated weights for policy 0, policy_version 27029 (0.0016) +[2026-07-22 20:14:55,920][50205] Updated weights for policy 0, policy_version 27039 (0.0016) +[2026-07-22 20:14:56,659][50205] Updated weights for policy 0, policy_version 27049 (0.0011) +[2026-07-22 20:14:57,416][50205] Updated weights for policy 0, policy_version 27059 (0.0011) +[2026-07-22 20:14:58,534][50205] Updated weights for policy 0, policy_version 27069 (0.0018) +[2026-07-22 20:14:59,181][50205] Updated weights for policy 0, policy_version 27079 (0.0011) +[2026-07-22 20:14:59,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 6012.1). Total num frames: 13869056. Throughput: 0: 6031.5. Samples: 13865620. Policy #0 lag: (min: 3.0, avg: 19.5, max: 47.0) +[2026-07-22 20:14:59,878][43431] Avg episode reward: [(0, '1828.167')] +[2026-07-22 20:15:00,080][50205] Updated weights for policy 0, policy_version 27089 (0.0011) +[2026-07-22 20:15:00,927][50205] Updated weights for policy 0, policy_version 27099 (0.0011) +[2026-07-22 20:15:01,667][50205] Updated weights for policy 0, policy_version 27109 (0.0012) +[2026-07-22 20:15:02,464][50205] Updated weights for policy 0, policy_version 27119 (0.0012) +[2026-07-22 20:15:03,659][50205] Updated weights for policy 0, policy_version 27129 (0.0011) +[2026-07-22 20:15:04,279][50205] Updated weights for policy 0, policy_version 27139 (0.0018) +[2026-07-22 20:15:04,878][43431] Fps is (10 sec: 6143.8, 60 sec: 6041.6, 300 sec: 6019.0). Total num frames: 13899776. Throughput: 0: 6022.8. Samples: 13901772. Policy #0 lag: (min: 3.0, avg: 19.5, max: 47.0) +[2026-07-22 20:15:04,879][43431] Avg episode reward: [(0, '1678.477')] +[2026-07-22 20:15:05,231][50205] Updated weights for policy 0, policy_version 27149 (0.0013) +[2026-07-22 20:15:06,017][50205] Updated weights for policy 0, policy_version 27159 (0.0016) +[2026-07-22 20:15:06,978][50205] Updated weights for policy 0, policy_version 27169 (0.0011) +[2026-07-22 20:15:07,546][50205] Updated weights for policy 0, policy_version 27179 (0.0015) +[2026-07-22 20:15:08,764][50205] Updated weights for policy 0, policy_version 27189 (0.0013) +[2026-07-22 20:15:09,416][50205] Updated weights for policy 0, policy_version 27199 (0.0014) +[2026-07-22 20:15:09,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6075.7, 300 sec: 6026.0). Total num frames: 13930496. Throughput: 0: 6010.1. Samples: 13937764. Policy #0 lag: (min: 1.0, avg: 19.5, max: 41.0) +[2026-07-22 20:15:09,878][43431] Avg episode reward: [(0, '1781.324')] +[2026-07-22 20:15:10,259][50205] Updated weights for policy 0, policy_version 27211 (0.0017) +[2026-07-22 20:15:11,402][50205] Updated weights for policy 0, policy_version 27221 (0.0012) +[2026-07-22 20:15:12,270][50205] Updated weights for policy 0, policy_version 27232 (0.0011) +[2026-07-22 20:15:12,959][50205] Updated weights for policy 0, policy_version 27242 (0.0014) +[2026-07-22 20:15:13,945][50205] Updated weights for policy 0, policy_version 27252 (0.0010) +[2026-07-22 20:15:14,782][50205] Updated weights for policy 0, policy_version 27262 (0.0013) +[2026-07-22 20:15:14,878][43431] Fps is (10 sec: 5939.3, 60 sec: 6041.6, 300 sec: 6019.0). Total num frames: 13959168. Throughput: 0: 6010.6. Samples: 13955874. Policy #0 lag: (min: 1.0, avg: 19.5, max: 41.0) +[2026-07-22 20:15:14,879][43431] Avg episode reward: [(0, '1845.284')] +[2026-07-22 20:15:15,377][50205] Updated weights for policy 0, policy_version 27272 (0.0018) +[2026-07-22 20:15:16,628][50205] Updated weights for policy 0, policy_version 27282 (0.0011) +[2026-07-22 20:15:17,447][50205] Updated weights for policy 0, policy_version 27292 (0.0011) +[2026-07-22 20:15:18,016][50205] Updated weights for policy 0, policy_version 27302 (0.0013) +[2026-07-22 20:15:19,287][50205] Updated weights for policy 0, policy_version 27312 (0.0015) +[2026-07-22 20:15:19,877][43431] Fps is (10 sec: 5529.7, 60 sec: 6007.5, 300 sec: 6005.2). Total num frames: 13985792. Throughput: 0: 6018.8. Samples: 13991468. Policy #0 lag: (min: 1.0, avg: 19.5, max: 41.0) +[2026-07-22 20:15:19,878][43431] Avg episode reward: [(0, '1554.197')] +[2026-07-22 20:15:20,075][50205] Updated weights for policy 0, policy_version 27322 (0.0016) +[2026-07-22 20:15:20,546][50205] Updated weights for policy 0, policy_version 27332 (0.0017) +[2026-07-22 20:15:22,027][50205] Updated weights for policy 0, policy_version 27342 (0.0017) +[2026-07-22 20:15:22,821][50205] Updated weights for policy 0, policy_version 27352 (0.0012) +[2026-07-22 20:15:23,432][50205] Updated weights for policy 0, policy_version 27362 (0.0012) +[2026-07-22 20:15:24,641][50205] Updated weights for policy 0, policy_version 27372 (0.0012) +[2026-07-22 20:15:24,877][43431] Fps is (10 sec: 5529.8, 60 sec: 5939.2, 300 sec: 5998.2). Total num frames: 14014464. Throughput: 0: 5972.1. Samples: 14025608. Policy #0 lag: (min: 1.0, avg: 16.8, max: 33.0) +[2026-07-22 20:15:24,878][43431] Avg episode reward: [(0, '1775.677')] +[2026-07-22 20:15:25,536][50205] Updated weights for policy 0, policy_version 27382 (0.0011) +[2026-07-22 20:15:26,135][50205] Updated weights for policy 0, policy_version 27392 (0.0011) +[2026-07-22 20:15:27,507][50205] Updated weights for policy 0, policy_version 27402 (0.0016) +[2026-07-22 20:15:28,285][50205] Updated weights for policy 0, policy_version 27412 (0.0022) +[2026-07-22 20:15:28,838][50205] Updated weights for policy 0, policy_version 27422 (0.0012) +[2026-07-22 20:15:29,569][50205] Updated weights for policy 0, policy_version 27432 (0.0013) +[2026-07-22 20:15:29,877][43431] Fps is (10 sec: 5939.1, 60 sec: 5973.3, 300 sec: 5998.2). Total num frames: 14045184. Throughput: 0: 5947.4. Samples: 14042628. Policy #0 lag: (min: 1.0, avg: 16.8, max: 33.0) +[2026-07-22 20:15:29,878][43431] Avg episode reward: [(0, '1658.076')] +[2026-07-22 20:15:31,130][50205] Updated weights for policy 0, policy_version 27442 (0.0011) +[2026-07-22 20:15:31,463][50205] Updated weights for policy 0, policy_version 27452 (0.0014) +[2026-07-22 20:15:32,779][50205] Updated weights for policy 0, policy_version 27462 (0.0011) +[2026-07-22 20:15:33,719][50205] Updated weights for policy 0, policy_version 27472 (0.0012) +[2026-07-22 20:15:34,339][50205] Updated weights for policy 0, policy_version 27482 (0.0011) +[2026-07-22 20:15:34,878][43431] Fps is (10 sec: 5939.0, 60 sec: 5939.2, 300 sec: 5998.2). Total num frames: 14073856. Throughput: 0: 5897.5. Samples: 14076522. Policy #0 lag: (min: 1.0, avg: 16.8, max: 33.0) +[2026-07-22 20:15:34,878][43431] Avg episode reward: [(0, '1808.372')] +[2026-07-22 20:15:35,068][50205] Updated weights for policy 0, policy_version 27492 (0.0017) +[2026-07-22 20:15:36,607][50205] Updated weights for policy 0, policy_version 27502 (0.0013) +[2026-07-22 20:15:36,996][50205] Updated weights for policy 0, policy_version 27512 (0.0016) +[2026-07-22 20:15:37,926][50205] Updated weights for policy 0, policy_version 27522 (0.0013) +[2026-07-22 20:15:39,391][50205] Updated weights for policy 0, policy_version 27532 (0.0016) +[2026-07-22 20:15:39,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5905.1, 300 sec: 5984.3). Total num frames: 14100480. Throughput: 0: 5836.8. Samples: 14109996. Policy #0 lag: (min: 1.0, avg: 16.8, max: 33.0) +[2026-07-22 20:15:39,878][43431] Avg episode reward: [(0, '1642.331')] +[2026-07-22 20:15:39,885][50205] Updated weights for policy 0, policy_version 27542 (0.0011) +[2026-07-22 20:15:40,554][50205] Updated weights for policy 0, policy_version 27552 (0.0012) +[2026-07-22 20:15:42,099][50205] Updated weights for policy 0, policy_version 27562 (0.0016) +[2026-07-22 20:15:42,903][50205] Updated weights for policy 0, policy_version 27573 (0.0011) +[2026-07-22 20:15:44,265][50205] Updated weights for policy 0, policy_version 27588 (0.0011) +[2026-07-22 20:15:44,877][43431] Fps is (10 sec: 5120.1, 60 sec: 5836.8, 300 sec: 5963.5). Total num frames: 14125056. Throughput: 0: 5805.0. Samples: 14126846. Policy #0 lag: (min: 3.0, avg: 19.1, max: 39.0) +[2026-07-22 20:15:44,878][43431] Avg episode reward: [(0, '1729.509')] +[2026-07-22 20:15:45,596][50205] Updated weights for policy 0, policy_version 27598 (0.0014) +[2026-07-22 20:15:46,198][50205] Updated weights for policy 0, policy_version 27609 (0.0017) +[2026-07-22 20:15:47,252][50205] Updated weights for policy 0, policy_version 27619 (0.0011) +[2026-07-22 20:15:48,471][50205] Updated weights for policy 0, policy_version 27632 (0.0010) +[2026-07-22 20:15:49,250][50205] Updated weights for policy 0, policy_version 27642 (0.0017) +[2026-07-22 20:15:49,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5802.7, 300 sec: 5963.5). Total num frames: 14155776. Throughput: 0: 5713.6. Samples: 14158880. Policy #0 lag: (min: 3.0, avg: 19.1, max: 39.0) +[2026-07-22 20:15:49,878][43431] Avg episode reward: [(0, '1709.824')] +[2026-07-22 20:15:50,164][50205] Updated weights for policy 0, policy_version 27652 (0.0011) +[2026-07-22 20:15:51,235][50205] Updated weights for policy 0, policy_version 27662 (0.0017) +[2026-07-22 20:15:51,709][50205] Updated weights for policy 0, policy_version 27672 (0.0011) +[2026-07-22 20:15:53,152][50205] Updated weights for policy 0, policy_version 27682 (0.0021) +[2026-07-22 20:15:54,062][50205] Updated weights for policy 0, policy_version 27692 (0.0012) +[2026-07-22 20:15:54,609][50205] Updated weights for policy 0, policy_version 27702 (0.0012) +[2026-07-22 20:15:54,877][43431] Fps is (10 sec: 5939.3, 60 sec: 5768.5, 300 sec: 5956.6). Total num frames: 14184448. Throughput: 0: 5674.8. Samples: 14193132. Policy #0 lag: (min: 3.0, avg: 19.1, max: 39.0) +[2026-07-22 20:15:54,878][43431] Avg episode reward: [(0, '1538.407')] +[2026-07-22 20:15:55,546][50205] Updated weights for policy 0, policy_version 27712 (0.0011) +[2026-07-22 20:15:56,793][50205] Updated weights for policy 0, policy_version 27722 (0.0011) +[2026-07-22 20:15:57,226][50205] Updated weights for policy 0, policy_version 27732 (0.0026) +[2026-07-22 20:15:58,324][50205] Updated weights for policy 0, policy_version 27742 (0.0011) +[2026-07-22 20:15:59,632][50205] Updated weights for policy 0, policy_version 27754 (0.0017) +[2026-07-22 20:15:59,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5700.3, 300 sec: 5949.6). Total num frames: 14211072. Throughput: 0: 5651.8. Samples: 14210204. Policy #0 lag: (min: 3.0, avg: 19.1, max: 39.0) +[2026-07-22 20:15:59,878][43431] Avg episode reward: [(0, '1686.393')] +[2026-07-22 20:16:00,155][50205] Updated weights for policy 0, policy_version 27764 (0.0017) +[2026-07-22 20:16:01,192][50205] Updated weights for policy 0, policy_version 27774 (0.0011) +[2026-07-22 20:16:02,264][50205] Updated weights for policy 0, policy_version 27784 (0.0012) +[2026-07-22 20:16:03,215][50205] Updated weights for policy 0, policy_version 27795 (0.0012) +[2026-07-22 20:16:04,624][50205] Updated weights for policy 0, policy_version 27805 (0.0017) +[2026-07-22 20:16:04,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5632.0, 300 sec: 5935.7). Total num frames: 14237696. Throughput: 0: 5564.3. Samples: 14241864. Policy #0 lag: (min: 3.0, avg: 18.8, max: 39.0) +[2026-07-22 20:16:04,878][43431] Avg episode reward: [(0, '1714.975')] +[2026-07-22 20:16:05,389][50205] Updated weights for policy 0, policy_version 27815 (0.0017) +[2026-07-22 20:16:06,211][50205] Updated weights for policy 0, policy_version 27825 (0.0012) +[2026-07-22 20:16:07,143][50205] Updated weights for policy 0, policy_version 27835 (0.0012) +[2026-07-22 20:16:08,220][50205] Updated weights for policy 0, policy_version 27845 (0.0012) +[2026-07-22 20:16:08,981][50205] Updated weights for policy 0, policy_version 27855 (0.0012) +[2026-07-22 20:16:09,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5597.9, 300 sec: 5942.7). Total num frames: 14266368. Throughput: 0: 5568.6. Samples: 14276196. Policy #0 lag: (min: 3.0, avg: 18.8, max: 39.0) +[2026-07-22 20:16:09,878][43431] Avg episode reward: [(0, '1764.094')] +[2026-07-22 20:16:09,881][50205] Updated weights for policy 0, policy_version 27865 (0.0012) +[2026-07-22 20:16:10,856][50205] Updated weights for policy 0, policy_version 27875 (0.0020) +[2026-07-22 20:16:11,730][50205] Updated weights for policy 0, policy_version 27885 (0.0011) +[2026-07-22 20:16:12,525][50205] Updated weights for policy 0, policy_version 27895 (0.0014) +[2026-07-22 20:16:13,601][50205] Updated weights for policy 0, policy_version 27905 (0.0019) +[2026-07-22 20:16:14,254][50205] Updated weights for policy 0, policy_version 27915 (0.0026) +[2026-07-22 20:16:14,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5597.9, 300 sec: 5935.7). Total num frames: 14295040. Throughput: 0: 5571.8. Samples: 14293358. Policy #0 lag: (min: 3.0, avg: 18.8, max: 39.0) +[2026-07-22 20:16:14,878][43431] Avg episode reward: [(0, '1807.839')] +[2026-07-22 20:16:15,419][50205] Updated weights for policy 0, policy_version 27928 (0.0012) +[2026-07-22 20:16:16,510][50205] Updated weights for policy 0, policy_version 27938 (0.0017) +[2026-07-22 20:16:17,234][50205] Updated weights for policy 0, policy_version 27948 (0.0012) +[2026-07-22 20:16:18,228][50205] Updated weights for policy 0, policy_version 27958 (0.0011) +[2026-07-22 20:16:19,207][50205] Updated weights for policy 0, policy_version 27968 (0.0011) +[2026-07-22 20:16:19,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5632.0, 300 sec: 5928.8). Total num frames: 14323712. Throughput: 0: 5574.0. Samples: 14327352. Policy #0 lag: (min: 2.0, avg: 21.2, max: 42.0) +[2026-07-22 20:16:19,878][43431] Avg episode reward: [(0, '1746.165')] +[2026-07-22 20:16:20,093][50205] Updated weights for policy 0, policy_version 27978 (0.0017) +[2026-07-22 20:16:20,576][50205] Updated weights for policy 0, policy_version 27988 (0.0018) +[2026-07-22 20:16:21,924][50205] Updated weights for policy 0, policy_version 27998 (0.0011) +[2026-07-22 20:16:22,478][50205] Updated weights for policy 0, policy_version 28008 (0.0011) +[2026-07-22 20:16:23,456][50205] Updated weights for policy 0, policy_version 28018 (0.0011) +[2026-07-22 20:16:24,606][50205] Updated weights for policy 0, policy_version 28028 (0.0018) +[2026-07-22 20:16:24,878][43431] Fps is (10 sec: 5734.2, 60 sec: 5632.0, 300 sec: 5921.8). Total num frames: 14352384. Throughput: 0: 5591.9. Samples: 14361632. Policy #0 lag: (min: 2.0, avg: 21.2, max: 42.0) +[2026-07-22 20:16:24,878][43431] Avg episode reward: [(0, '1766.151')] +[2026-07-22 20:16:25,434][50205] Updated weights for policy 0, policy_version 28038 (0.0019) +[2026-07-22 20:16:26,006][50205] Updated weights for policy 0, policy_version 28048 (0.0017) +[2026-07-22 20:16:27,260][50205] Updated weights for policy 0, policy_version 28058 (0.0013) +[2026-07-22 20:16:28,080][50205] Updated weights for policy 0, policy_version 28068 (0.0011) +[2026-07-22 20:16:28,875][50205] Updated weights for policy 0, policy_version 28078 (0.0016) +[2026-07-22 20:16:29,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5563.7, 300 sec: 5908.0). Total num frames: 14379008. Throughput: 0: 5599.8. Samples: 14378834. Policy #0 lag: (min: 2.0, avg: 21.2, max: 42.0) +[2026-07-22 20:16:29,878][43431] Avg episode reward: [(0, '1642.946')] +[2026-07-22 20:16:29,958][50205] Updated weights for policy 0, policy_version 28088 (0.0012) +[2026-07-22 20:16:30,681][50205] Updated weights for policy 0, policy_version 28098 (0.0016) +[2026-07-22 20:16:31,594][50205] Updated weights for policy 0, policy_version 28108 (0.0016) +[2026-07-22 20:16:32,729][50205] Updated weights for policy 0, policy_version 28118 (0.0024) +[2026-07-22 20:16:33,260][50205] Updated weights for policy 0, policy_version 28128 (0.0013) +[2026-07-22 20:16:34,246][50205] Updated weights for policy 0, policy_version 28138 (0.0012) +[2026-07-22 20:16:34,877][43431] Fps is (10 sec: 5734.8, 60 sec: 5597.9, 300 sec: 5908.0). Total num frames: 14409728. Throughput: 0: 5656.8. Samples: 14413434. Policy #0 lag: (min: 2.0, avg: 21.2, max: 42.0) +[2026-07-22 20:16:34,878][43431] Avg episode reward: [(0, '1698.113')] +[2026-07-22 20:16:35,439][50205] Updated weights for policy 0, policy_version 28148 (0.0022) +[2026-07-22 20:16:35,961][50205] Updated weights for policy 0, policy_version 28158 (0.0018) +[2026-07-22 20:16:36,794][50205] Updated weights for policy 0, policy_version 28168 (0.0010) +[2026-07-22 20:16:38,038][50205] Updated weights for policy 0, policy_version 28178 (0.0011) +[2026-07-22 20:16:38,696][50205] Updated weights for policy 0, policy_version 28188 (0.0011) +[2026-07-22 20:16:39,708][50205] Updated weights for policy 0, policy_version 28198 (0.0013) +[2026-07-22 20:16:39,877][43431] Fps is (10 sec: 5939.3, 60 sec: 5632.0, 300 sec: 5908.0). Total num frames: 14438400. Throughput: 0: 5659.6. Samples: 14447812. Policy #0 lag: (min: 3.0, avg: 21.8, max: 47.0) +[2026-07-22 20:16:39,878][43431] Avg episode reward: [(0, '1771.561')] +[2026-07-22 20:16:40,381][50205] Updated weights for policy 0, policy_version 28208 (0.0013) +[2026-07-22 20:16:41,471][50205] Updated weights for policy 0, policy_version 28218 (0.0012) +[2026-07-22 20:16:42,130][50205] Updated weights for policy 0, policy_version 28228 (0.0017) +[2026-07-22 20:16:43,232][50205] Updated weights for policy 0, policy_version 28238 (0.0015) +[2026-07-22 20:16:44,142][50205] Updated weights for policy 0, policy_version 28248 (0.0012) +[2026-07-22 20:16:44,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5666.2, 300 sec: 5894.1). Total num frames: 14465024. Throughput: 0: 5662.3. Samples: 14465006. Policy #0 lag: (min: 3.0, avg: 21.8, max: 47.0) +[2026-07-22 20:16:44,878][43431] Avg episode reward: [(0, '1679.176')] +[2026-07-22 20:16:45,493][50205] Updated weights for policy 0, policy_version 28263 (0.0011) +[2026-07-22 20:16:46,636][50205] Updated weights for policy 0, policy_version 28273 (0.0011) +[2026-07-22 20:16:47,268][50205] Updated weights for policy 0, policy_version 28283 (0.0011) +[2026-07-22 20:16:48,264][50205] Updated weights for policy 0, policy_version 28294 (0.0012) +[2026-07-22 20:16:49,170][50205] Updated weights for policy 0, policy_version 28304 (0.0017) +[2026-07-22 20:16:49,877][43431] Fps is (10 sec: 5529.4, 60 sec: 5632.0, 300 sec: 5887.1). Total num frames: 14493696. Throughput: 0: 5710.6. Samples: 14498844. Policy #0 lag: (min: 3.0, avg: 21.8, max: 47.0) +[2026-07-22 20:16:49,878][43431] Avg episode reward: [(0, '1534.126')] +[2026-07-22 20:16:50,335][50205] Updated weights for policy 0, policy_version 28314 (0.0012) +[2026-07-22 20:16:50,772][50205] Updated weights for policy 0, policy_version 28324 (0.0016) +[2026-07-22 20:16:51,924][50205] Updated weights for policy 0, policy_version 28334 (0.0014) +[2026-07-22 20:16:52,705][50205] Updated weights for policy 0, policy_version 28344 (0.0014) +[2026-07-22 20:16:53,672][50205] Updated weights for policy 0, policy_version 28354 (0.0016) +[2026-07-22 20:16:54,468][50205] Updated weights for policy 0, policy_version 28364 (0.0020) +[2026-07-22 20:16:54,877][43431] Fps is (10 sec: 5939.0, 60 sec: 5666.1, 300 sec: 5887.1). Total num frames: 14524416. Throughput: 0: 5716.1. Samples: 14533422. Policy #0 lag: (min: 3.0, avg: 21.8, max: 47.0) +[2026-07-22 20:16:54,878][43431] Avg episode reward: [(0, '1796.679')] +[2026-07-22 20:16:55,382][50205] Updated weights for policy 0, policy_version 28374 (0.0017) +[2026-07-22 20:16:56,149][50205] Updated weights for policy 0, policy_version 28384 (0.0017) +[2026-07-22 20:16:57,309][50205] Updated weights for policy 0, policy_version 28394 (0.0011) +[2026-07-22 20:16:58,103][50205] Updated weights for policy 0, policy_version 28404 (0.0018) +[2026-07-22 20:16:58,897][50205] Updated weights for policy 0, policy_version 28414 (0.0020) +[2026-07-22 20:16:59,815][50205] Updated weights for policy 0, policy_version 28424 (0.0012) +[2026-07-22 20:16:59,877][43431] Fps is (10 sec: 5939.4, 60 sec: 5700.3, 300 sec: 5894.1). Total num frames: 14553088. Throughput: 0: 5716.9. Samples: 14550618. Policy #0 lag: (min: 6.0, avg: 18.3, max: 35.0) +[2026-07-22 20:16:59,878][43431] Avg episode reward: [(0, '1826.892')] +[2026-07-22 20:17:00,932][50205] Updated weights for policy 0, policy_version 28434 (0.0011) +[2026-07-22 20:17:01,460][50205] Updated weights for policy 0, policy_version 28444 (0.0023) +[2026-07-22 20:17:03,127][50205] Updated weights for policy 0, policy_version 28454 (0.0017) +[2026-07-22 20:17:04,031][50205] Updated weights for policy 0, policy_version 28464 (0.0017) +[2026-07-22 20:17:04,713][50205] Updated weights for policy 0, policy_version 28474 (0.0020) +[2026-07-22 20:17:04,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5700.3, 300 sec: 5880.2). Total num frames: 14579712. Throughput: 0: 5671.5. Samples: 14582570. Policy #0 lag: (min: 6.0, avg: 18.3, max: 35.0) +[2026-07-22 20:17:04,878][43431] Avg episode reward: [(0, '1773.598')] +[2026-07-22 20:17:05,679][50205] Updated weights for policy 0, policy_version 28484 (0.0016) +[2026-07-22 20:17:06,836][50205] Updated weights for policy 0, policy_version 28494 (0.0012) +[2026-07-22 20:17:07,413][50205] Updated weights for policy 0, policy_version 28504 (0.0015) +[2026-07-22 20:17:08,325][50205] Updated weights for policy 0, policy_version 28514 (0.0017) +[2026-07-22 20:17:09,133][50205] Updated weights for policy 0, policy_version 28524 (0.0016) +[2026-07-22 20:17:09,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5666.1, 300 sec: 5866.3). Total num frames: 14606336. Throughput: 0: 5674.4. Samples: 14616980. Policy #0 lag: (min: 6.0, avg: 18.3, max: 35.0) +[2026-07-22 20:17:09,878][43431] Avg episode reward: [(0, '1707.345')] +[2026-07-22 20:17:10,208][50205] Updated weights for policy 0, policy_version 28534 (0.0011) +[2026-07-22 20:17:10,649][50205] Updated weights for policy 0, policy_version 28544 (0.0013) +[2026-07-22 20:17:12,063][50205] Updated weights for policy 0, policy_version 28554 (0.0013) +[2026-07-22 20:17:12,816][50205] Updated weights for policy 0, policy_version 28564 (0.0016) +[2026-07-22 20:17:13,722][50205] Updated weights for policy 0, policy_version 28574 (0.0011) +[2026-07-22 20:17:14,712][50205] Updated weights for policy 0, policy_version 28584 (0.0012) +[2026-07-22 20:17:14,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5700.3, 300 sec: 5866.3). Total num frames: 14637056. Throughput: 0: 5674.5. Samples: 14634188. Policy #0 lag: (min: 3.0, avg: 19.4, max: 39.0) +[2026-07-22 20:17:14,878][43431] Avg episode reward: [(0, '1770.426')] +[2026-07-22 20:17:15,584][50205] Updated weights for policy 0, policy_version 28594 (0.0012) +[2026-07-22 20:17:16,105][50205] Updated weights for policy 0, policy_version 28604 (0.0017) +[2026-07-22 20:17:17,548][50205] Updated weights for policy 0, policy_version 28614 (0.0017) +[2026-07-22 20:17:18,044][50205] Updated weights for policy 0, policy_version 28624 (0.0012) +[2026-07-22 20:17:18,802][50205] Updated weights for policy 0, policy_version 28634 (0.0012) +[2026-07-22 20:17:19,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5666.1, 300 sec: 5859.4). Total num frames: 14663680. Throughput: 0: 5668.3. Samples: 14668510. Policy #0 lag: (min: 3.0, avg: 19.4, max: 39.0) +[2026-07-22 20:17:19,878][43431] Avg episode reward: [(0, '1667.810')] +[2026-07-22 20:17:20,050][50205] Updated weights for policy 0, policy_version 28644 (0.0012) +[2026-07-22 20:17:20,872][50205] Updated weights for policy 0, policy_version 28654 (0.0012) +[2026-07-22 20:17:21,504][50205] Updated weights for policy 0, policy_version 28664 (0.0012) +[2026-07-22 20:17:22,952][50205] Updated weights for policy 0, policy_version 28674 (0.0016) +[2026-07-22 20:17:23,477][50205] Updated weights for policy 0, policy_version 28684 (0.0014) +[2026-07-22 20:17:24,280][50205] Updated weights for policy 0, policy_version 28694 (0.0016) +[2026-07-22 20:17:24,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5700.3, 300 sec: 5859.4). Total num frames: 14694400. Throughput: 0: 5670.8. Samples: 14702998. Policy #0 lag: (min: 3.0, avg: 19.4, max: 39.0) +[2026-07-22 20:17:24,878][43431] Avg episode reward: [(0, '1680.067')] +[2026-07-22 20:17:25,450][50205] Updated weights for policy 0, policy_version 28704 (0.0011) +[2026-07-22 20:17:26,069][49527] Signal inference workers to stop experience collection... (500 times) +[2026-07-22 20:17:26,070][49527] Signal inference workers to resume experience collection... (500 times) +[2026-07-22 20:17:26,082][50205] InferenceWorker_p0-w0: stopping experience collection (500 times) +[2026-07-22 20:17:26,083][50205] InferenceWorker_p0-w0: resuming experience collection (500 times) +[2026-07-22 20:17:26,134][50205] Updated weights for policy 0, policy_version 28714 (0.0013) +[2026-07-22 20:17:26,966][50205] Updated weights for policy 0, policy_version 28724 (0.0011) +[2026-07-22 20:17:28,149][50205] Updated weights for policy 0, policy_version 28734 (0.0011) +[2026-07-22 20:17:28,842][50205] Updated weights for policy 0, policy_version 28744 (0.0012) +[2026-07-22 20:17:29,584][50205] Updated weights for policy 0, policy_version 28754 (0.0012) +[2026-07-22 20:17:29,878][43431] Fps is (10 sec: 5939.0, 60 sec: 5734.4, 300 sec: 5845.5). Total num frames: 14723072. Throughput: 0: 5672.3. Samples: 14720260. Policy #0 lag: (min: 3.0, avg: 19.4, max: 39.0) +[2026-07-22 20:17:29,878][43431] Avg episode reward: [(0, '1702.034')] +[2026-07-22 20:17:30,764][50205] Updated weights for policy 0, policy_version 28764 (0.0015) +[2026-07-22 20:17:31,666][50205] Updated weights for policy 0, policy_version 28774 (0.0014) +[2026-07-22 20:17:32,261][50205] Updated weights for policy 0, policy_version 28784 (0.0011) +[2026-07-22 20:17:33,394][50205] Updated weights for policy 0, policy_version 28794 (0.0016) +[2026-07-22 20:17:34,288][50205] Updated weights for policy 0, policy_version 28804 (0.0017) +[2026-07-22 20:17:34,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5700.2, 300 sec: 5845.5). Total num frames: 14751744. Throughput: 0: 5681.7. Samples: 14754518. Policy #0 lag: (min: 2.0, avg: 19.0, max: 37.0) +[2026-07-22 20:17:34,878][43431] Avg episode reward: [(0, '1650.605')] +[2026-07-22 20:17:35,016][50205] Updated weights for policy 0, policy_version 28814 (0.0012) +[2026-07-22 20:17:36,018][50205] Updated weights for policy 0, policy_version 28824 (0.0011) +[2026-07-22 20:17:37,083][50205] Updated weights for policy 0, policy_version 28834 (0.0016) +[2026-07-22 20:17:37,607][50205] Updated weights for policy 0, policy_version 28844 (0.0011) +[2026-07-22 20:17:38,804][50205] Updated weights for policy 0, policy_version 28854 (0.0011) +[2026-07-22 20:17:39,768][50205] Updated weights for policy 0, policy_version 28864 (0.0011) +[2026-07-22 20:17:39,878][43431] Fps is (10 sec: 5529.5, 60 sec: 5666.1, 300 sec: 5838.5). Total num frames: 14778368. Throughput: 0: 5675.1. Samples: 14788804. Policy #0 lag: (min: 2.0, avg: 19.0, max: 37.0) +[2026-07-22 20:17:39,878][43431] Avg episode reward: [(0, '1759.464')] +[2026-07-22 20:17:40,431][50205] Updated weights for policy 0, policy_version 28874 (0.0015) +[2026-07-22 20:17:41,358][50205] Updated weights for policy 0, policy_version 28884 (0.0012) +[2026-07-22 20:17:42,525][50205] Updated weights for policy 0, policy_version 28894 (0.0013) +[2026-07-22 20:17:43,069][50205] Updated weights for policy 0, policy_version 28904 (0.0021) +[2026-07-22 20:17:44,156][50205] Updated weights for policy 0, policy_version 28914 (0.0010) +[2026-07-22 20:17:44,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5700.2, 300 sec: 5824.6). Total num frames: 14807040. Throughput: 0: 5674.4. Samples: 14805968. Policy #0 lag: (min: 2.0, avg: 19.0, max: 37.0) +[2026-07-22 20:17:44,878][43431] Avg episode reward: [(0, '1656.037')] +[2026-07-22 20:17:45,255][50205] Updated weights for policy 0, policy_version 28924 (0.0011) +[2026-07-22 20:17:45,859][50205] Updated weights for policy 0, policy_version 28935 (0.0019) +[2026-07-22 20:17:46,830][50205] Updated weights for policy 0, policy_version 28945 (0.0015) +[2026-07-22 20:17:48,016][50205] Updated weights for policy 0, policy_version 28955 (0.0014) +[2026-07-22 20:17:48,713][50205] Updated weights for policy 0, policy_version 28965 (0.0011) +[2026-07-22 20:17:49,414][50205] Updated weights for policy 0, policy_version 28975 (0.0012) +[2026-07-22 20:17:49,877][43431] Fps is (10 sec: 5734.7, 60 sec: 5700.3, 300 sec: 5824.7). Total num frames: 14835712. Throughput: 0: 5720.3. Samples: 14839982. Policy #0 lag: (min: 2.0, avg: 19.0, max: 37.0) +[2026-07-22 20:17:49,879][43431] Avg episode reward: [(0, '1619.131')] +[2026-07-22 20:17:50,925][50205] Updated weights for policy 0, policy_version 28985 (0.0021) +[2026-07-22 20:17:51,493][50205] Updated weights for policy 0, policy_version 28997 (0.0012) +[2026-07-22 20:17:52,187][50205] Updated weights for policy 0, policy_version 29008 (0.0021) +[2026-07-22 20:17:53,997][50205] Updated weights for policy 0, policy_version 29018 (0.0014) +[2026-07-22 20:17:54,438][50205] Updated weights for policy 0, policy_version 29029 (0.0017) +[2026-07-22 20:17:54,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5666.2, 300 sec: 5824.7). Total num frames: 14864384. Throughput: 0: 5704.0. Samples: 14873660. Policy #0 lag: (min: 3.0, avg: 16.3, max: 35.0) +[2026-07-22 20:17:54,878][43431] Avg episode reward: [(0, '1678.761')] +[2026-07-22 20:17:55,028][50205] Updated weights for policy 0, policy_version 29039 (0.0013) +[2026-07-22 20:17:56,715][50205] Updated weights for policy 0, policy_version 29049 (0.0013) +[2026-07-22 20:17:57,225][50205] Updated weights for policy 0, policy_version 29059 (0.0013) +[2026-07-22 20:17:57,950][50205] Updated weights for policy 0, policy_version 29069 (0.0010) +[2026-07-22 20:17:59,231][50205] Updated weights for policy 0, policy_version 29079 (0.0012) +[2026-07-22 20:17:59,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5632.0, 300 sec: 5810.8). Total num frames: 14891008. Throughput: 0: 5704.2. Samples: 14890876. Policy #0 lag: (min: 3.0, avg: 16.3, max: 35.0) +[2026-07-22 20:17:59,878][43431] Avg episode reward: [(0, '1670.139')] +[2026-07-22 20:18:00,048][50205] Updated weights for policy 0, policy_version 29089 (0.0012) +[2026-07-22 20:18:00,529][50205] Updated weights for policy 0, policy_version 29100 (0.0014) +[2026-07-22 20:18:02,029][50205] Updated weights for policy 0, policy_version 29110 (0.0014) +[2026-07-22 20:18:02,643][50205] Updated weights for policy 0, policy_version 29120 (0.0012) +[2026-07-22 20:18:03,280][50205] Updated weights for policy 0, policy_version 29130 (0.0011) +[2026-07-22 20:18:04,763][50205] Updated weights for policy 0, policy_version 29140 (0.0016) +[2026-07-22 20:18:04,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5666.1, 300 sec: 5803.8). Total num frames: 14919680. Throughput: 0: 5702.6. Samples: 14925126. Policy #0 lag: (min: 3.0, avg: 16.3, max: 35.0) +[2026-07-22 20:18:04,878][43431] Avg episode reward: [(0, '1644.504')] +[2026-07-22 20:18:05,448][50205] Updated weights for policy 0, policy_version 29150 (0.0013) +[2026-07-22 20:18:05,902][50205] Updated weights for policy 0, policy_version 29160 (0.0015) +[2026-07-22 20:18:07,433][50205] Updated weights for policy 0, policy_version 29170 (0.0012) +[2026-07-22 20:18:08,155][50205] Updated weights for policy 0, policy_version 29180 (0.0016) +[2026-07-22 20:18:08,779][50205] Updated weights for policy 0, policy_version 29190 (0.0021) +[2026-07-22 20:18:09,865][50205] Updated weights for policy 0, policy_version 29200 (0.0017) +[2026-07-22 20:18:09,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5734.4, 300 sec: 5810.8). Total num frames: 14950400. Throughput: 0: 5698.3. Samples: 14959424. Policy #0 lag: (min: 3.0, avg: 16.3, max: 35.0) +[2026-07-22 20:18:09,878][43431] Avg episode reward: [(0, '1776.041')] +[2026-07-22 20:18:10,857][50205] Updated weights for policy 0, policy_version 29210 (0.0026) +[2026-07-22 20:18:11,624][50205] Updated weights for policy 0, policy_version 29221 (0.0012) +[2026-07-22 20:18:12,793][50205] Updated weights for policy 0, policy_version 29231 (0.0017) +[2026-07-22 20:18:13,621][50205] Updated weights for policy 0, policy_version 29241 (0.0012) +[2026-07-22 20:18:14,091][50205] Updated weights for policy 0, policy_version 29251 (0.0021) +[2026-07-22 20:18:14,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5666.1, 300 sec: 5789.9). Total num frames: 14977024. Throughput: 0: 5696.5. Samples: 14976604. Policy #0 lag: (min: 1.0, avg: 14.8, max: 33.0) +[2026-07-22 20:18:14,878][43431] Avg episode reward: [(0, '1582.170')] +[2026-07-22 20:18:15,677][50205] Updated weights for policy 0, policy_version 29261 (0.0016) +[2026-07-22 20:18:16,406][50205] Updated weights for policy 0, policy_version 29271 (0.0013) +[2026-07-22 20:18:16,932][50205] Updated weights for policy 0, policy_version 29281 (0.0012) +[2026-07-22 20:18:18,245][50205] Updated weights for policy 0, policy_version 29291 (0.0014) +[2026-07-22 20:18:19,220][50205] Updated weights for policy 0, policy_version 29301 (0.0012) +[2026-07-22 20:18:19,697][50205] Updated weights for policy 0, policy_version 29312 (0.0013) +[2026-07-22 20:18:19,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5734.4, 300 sec: 5796.9). Total num frames: 15007744. Throughput: 0: 5692.3. Samples: 15010672. Policy #0 lag: (min: 1.0, avg: 14.8, max: 33.0) +[2026-07-22 20:18:19,878][43431] Avg episode reward: [(0, '1632.466')] +[2026-07-22 20:18:20,900][50205] Updated weights for policy 0, policy_version 29322 (0.0011) +[2026-07-22 20:18:21,819][50205] Updated weights for policy 0, policy_version 29332 (0.0012) +[2026-07-22 20:18:22,528][50205] Updated weights for policy 0, policy_version 29342 (0.0022) +[2026-07-22 20:18:23,558][50205] Updated weights for policy 0, policy_version 29352 (0.0012) +[2026-07-22 20:18:24,604][50205] Updated weights for policy 0, policy_version 29362 (0.0022) +[2026-07-22 20:18:24,877][43431] Fps is (10 sec: 5939.3, 60 sec: 5700.3, 300 sec: 5789.9). Total num frames: 15036416. Throughput: 0: 5687.1. Samples: 15044720. Policy #0 lag: (min: 1.0, avg: 14.8, max: 33.0) +[2026-07-22 20:18:24,878][43431] Avg episode reward: [(0, '1730.897')] +[2026-07-22 20:18:25,004][50205] Updated weights for policy 0, policy_version 29372 (0.0011) +[2026-07-22 20:18:26,389][50205] Updated weights for policy 0, policy_version 29382 (0.0015) +[2026-07-22 20:18:27,217][50205] Updated weights for policy 0, policy_version 29392 (0.0012) +[2026-07-22 20:18:27,851][50205] Updated weights for policy 0, policy_version 29402 (0.0016) +[2026-07-22 20:18:28,628][50205] Updated weights for policy 0, policy_version 29412 (0.0010) +[2026-07-22 20:18:29,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5666.2, 300 sec: 5776.1). Total num frames: 15063040. Throughput: 0: 5691.7. Samples: 15062092. Policy #0 lag: (min: 1.0, avg: 14.8, max: 33.0) +[2026-07-22 20:18:29,878][43431] Avg episode reward: [(0, '1695.721')] +[2026-07-22 20:18:30,046][50205] Updated weights for policy 0, policy_version 29422 (0.0012) +[2026-07-22 20:18:30,729][50205] Updated weights for policy 0, policy_version 29432 (0.0011) +[2026-07-22 20:18:31,590][50205] Updated weights for policy 0, policy_version 29442 (0.0011) +[2026-07-22 20:18:32,484][50205] Updated weights for policy 0, policy_version 29452 (0.0012) +[2026-07-22 20:18:33,461][50205] Updated weights for policy 0, policy_version 29462 (0.0011) +[2026-07-22 20:18:34,091][50205] Updated weights for policy 0, policy_version 29472 (0.0016) +[2026-07-22 20:18:34,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5666.1, 300 sec: 5783.0). Total num frames: 15091712. Throughput: 0: 5696.4. Samples: 15096322. Policy #0 lag: (min: 3.0, avg: 21.4, max: 43.0) +[2026-07-22 20:18:34,878][43431] Avg episode reward: [(0, '1640.565')] +[2026-07-22 20:18:35,270][50205] Updated weights for policy 0, policy_version 29482 (0.0012) +[2026-07-22 20:18:35,905][50205] Updated weights for policy 0, policy_version 29492 (0.0012) +[2026-07-22 20:18:36,933][50205] Updated weights for policy 0, policy_version 29502 (0.0012) +[2026-07-22 20:18:37,982][50205] Updated weights for policy 0, policy_version 29512 (0.0012) +[2026-07-22 20:18:38,824][50205] Updated weights for policy 0, policy_version 29522 (0.0011) +[2026-07-22 20:18:39,300][50205] Updated weights for policy 0, policy_version 29532 (0.0011) +[2026-07-22 20:18:39,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5700.3, 300 sec: 5769.1). Total num frames: 15120384. Throughput: 0: 5711.3. Samples: 15130670. Policy #0 lag: (min: 3.0, avg: 21.4, max: 43.0) +[2026-07-22 20:18:39,878][43431] Avg episode reward: [(0, '1607.283')] +[2026-07-22 20:18:40,865][50205] Updated weights for policy 0, policy_version 29542 (0.0012) +[2026-07-22 20:18:41,300][50205] Updated weights for policy 0, policy_version 29552 (0.0012) +[2026-07-22 20:18:42,461][50205] Updated weights for policy 0, policy_version 29562 (0.0012) +[2026-07-22 20:18:43,278][50205] Updated weights for policy 0, policy_version 29572 (0.0011) +[2026-07-22 20:18:44,195][50205] Updated weights for policy 0, policy_version 29582 (0.0011) +[2026-07-22 20:18:44,766][50205] Updated weights for policy 0, policy_version 29592 (0.0020) +[2026-07-22 20:18:44,877][43431] Fps is (10 sec: 5939.3, 60 sec: 5734.4, 300 sec: 5776.1). Total num frames: 15151104. Throughput: 0: 5714.0. Samples: 15148004. Policy #0 lag: (min: 3.0, avg: 21.4, max: 43.0) +[2026-07-22 20:18:44,878][43431] Avg episode reward: [(0, '1758.685')] +[2026-07-22 20:18:46,038][50205] Updated weights for policy 0, policy_version 29602 (0.0015) +[2026-07-22 20:18:46,650][50205] Updated weights for policy 0, policy_version 29612 (0.0012) +[2026-07-22 20:18:47,549][50205] Updated weights for policy 0, policy_version 29622 (0.0012) +[2026-07-22 20:18:48,640][50205] Updated weights for policy 0, policy_version 29632 (0.0011) +[2026-07-22 20:18:49,593][50205] Updated weights for policy 0, policy_version 29642 (0.0011) +[2026-07-22 20:18:49,879][43431] Fps is (10 sec: 5938.4, 60 sec: 5734.3, 300 sec: 5762.1). Total num frames: 15179776. Throughput: 0: 5720.3. Samples: 15182548. Policy #0 lag: (min: 3.0, avg: 21.4, max: 43.0) +[2026-07-22 20:18:49,880][43431] Avg episode reward: [(0, '1686.954')] +[2026-07-22 20:18:50,041][50205] Updated weights for policy 0, policy_version 29652 (0.0020) +[2026-07-22 20:18:51,565][50205] Updated weights for policy 0, policy_version 29662 (0.0012) +[2026-07-22 20:18:52,086][50205] Updated weights for policy 0, policy_version 29672 (0.0012) +[2026-07-22 20:18:52,894][50205] Updated weights for policy 0, policy_version 29682 (0.0016) +[2026-07-22 20:18:53,748][50205] Updated weights for policy 0, policy_version 29692 (0.0019) +[2026-07-22 20:18:54,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5700.3, 300 sec: 5755.2). Total num frames: 15206400. Throughput: 0: 5720.2. Samples: 15216834. Policy #0 lag: (min: 3.0, avg: 15.0, max: 35.0) +[2026-07-22 20:18:54,878][43431] Avg episode reward: [(0, '1664.001')] +[2026-07-22 20:18:54,964][50205] Updated weights for policy 0, policy_version 29702 (0.0012) +[2026-07-22 20:18:55,420][50205] Updated weights for policy 0, policy_version 29712 (0.0011) +[2026-07-22 20:18:56,631][50205] Updated weights for policy 0, policy_version 29722 (0.0024) +[2026-07-22 20:18:57,586][50205] Updated weights for policy 0, policy_version 29732 (0.0011) +[2026-07-22 20:18:58,135][50205] Updated weights for policy 0, policy_version 29742 (0.0018) +[2026-07-22 20:18:59,103][50205] Updated weights for policy 0, policy_version 29752 (0.0017) +[2026-07-22 20:18:59,877][43431] Fps is (10 sec: 5530.3, 60 sec: 5734.4, 300 sec: 5755.2). Total num frames: 15235072. Throughput: 0: 5719.2. Samples: 15233966. Policy #0 lag: (min: 3.0, avg: 15.0, max: 35.0) +[2026-07-22 20:18:59,878][43431] Avg episode reward: [(0, '1787.308')] +[2026-07-22 20:19:00,378][50205] Updated weights for policy 0, policy_version 29762 (0.0012) +[2026-07-22 20:19:00,936][50205] Updated weights for policy 0, policy_version 29772 (0.0012) +[2026-07-22 20:19:01,850][50205] Updated weights for policy 0, policy_version 29782 (0.0011) +[2026-07-22 20:19:03,196][50205] Updated weights for policy 0, policy_version 29792 (0.0010) +[2026-07-22 20:19:04,042][50205] Updated weights for policy 0, policy_version 29804 (0.0018) +[2026-07-22 20:19:04,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5734.4, 300 sec: 5755.2). Total num frames: 15263744. Throughput: 0: 5687.0. Samples: 15266586. Policy #0 lag: (min: 3.0, avg: 15.0, max: 35.0) +[2026-07-22 20:19:04,878][43431] Avg episode reward: [(0, '1680.382')] +[2026-07-22 20:19:05,124][50205] Updated weights for policy 0, policy_version 29814 (0.0015) +[2026-07-22 20:19:06,783][50205] Updated weights for policy 0, policy_version 29828 (0.0012) +[2026-07-22 20:19:07,589][50205] Updated weights for policy 0, policy_version 29838 (0.0015) +[2026-07-22 20:19:08,745][50205] Updated weights for policy 0, policy_version 29848 (0.0011) +[2026-07-22 20:19:09,497][50205] Updated weights for policy 0, policy_version 29858 (0.0012) +[2026-07-22 20:19:09,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5632.0, 300 sec: 5734.4). Total num frames: 15288320. Throughput: 0: 5645.0. Samples: 15298746. Policy #0 lag: (min: 3.0, avg: 15.0, max: 35.0) +[2026-07-22 20:19:09,878][43431] Avg episode reward: [(0, '1774.465')] +[2026-07-22 20:19:10,135][50205] Updated weights for policy 0, policy_version 29868 (0.0017) +[2026-07-22 20:19:11,735][50205] Updated weights for policy 0, policy_version 29878 (0.0012) +[2026-07-22 20:19:12,224][50205] Updated weights for policy 0, policy_version 29889 (0.0016) +[2026-07-22 20:19:12,907][50205] Updated weights for policy 0, policy_version 29899 (0.0017) +[2026-07-22 20:19:14,452][50205] Updated weights for policy 0, policy_version 29909 (0.0012) +[2026-07-22 20:19:14,878][43431] Fps is (10 sec: 5324.7, 60 sec: 5666.1, 300 sec: 5734.4). Total num frames: 15316992. Throughput: 0: 5640.1. Samples: 15315900. Policy #0 lag: (min: 3.0, avg: 14.8, max: 35.0) +[2026-07-22 20:19:14,878][43431] Avg episode reward: [(0, '1755.916')] +[2026-07-22 20:19:14,971][50205] Updated weights for policy 0, policy_version 29919 (0.0011) +[2026-07-22 20:19:15,728][50205] Updated weights for policy 0, policy_version 29929 (0.0011) +[2026-07-22 20:19:16,734][50205] Updated weights for policy 0, policy_version 29939 (0.0011) +[2026-07-22 20:19:17,656][50205] Updated weights for policy 0, policy_version 29949 (0.0010) +[2026-07-22 20:19:18,286][50205] Updated weights for policy 0, policy_version 29959 (0.0011) +[2026-07-22 20:19:19,808][50205] Updated weights for policy 0, policy_version 29969 (0.0013) +[2026-07-22 20:19:19,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5632.0, 300 sec: 5720.5). Total num frames: 15345664. Throughput: 0: 5637.8. Samples: 15350020. Policy #0 lag: (min: 3.0, avg: 14.8, max: 35.0) +[2026-07-22 20:19:19,878][43431] Avg episode reward: [(0, '1657.882')] +[2026-07-22 20:19:20,363][50205] Updated weights for policy 0, policy_version 29979 (0.0012) +[2026-07-22 20:19:21,120][50205] Updated weights for policy 0, policy_version 29989 (0.0012) +[2026-07-22 20:19:22,078][50205] Updated weights for policy 0, policy_version 29999 (0.0013) +[2026-07-22 20:19:23,208][50205] Updated weights for policy 0, policy_version 30009 (0.0012) +[2026-07-22 20:19:23,686][50205] Updated weights for policy 0, policy_version 30019 (0.0011) +[2026-07-22 20:19:24,877][43431] Fps is (10 sec: 5734.6, 60 sec: 5632.0, 300 sec: 5720.5). Total num frames: 15374336. Throughput: 0: 5637.6. Samples: 15384360. Policy #0 lag: (min: 3.0, avg: 14.8, max: 35.0) +[2026-07-22 20:19:24,878][43431] Avg episode reward: [(0, '1660.144')] +[2026-07-22 20:19:24,988][50205] Updated weights for policy 0, policy_version 30029 (0.0012) +[2026-07-22 20:19:25,872][50205] Updated weights for policy 0, policy_version 30039 (0.0015) +[2026-07-22 20:19:26,500][50205] Updated weights for policy 0, policy_version 30049 (0.0014) +[2026-07-22 20:19:27,418][50205] Updated weights for policy 0, policy_version 30059 (0.0017) +[2026-07-22 20:19:28,638][50205] Updated weights for policy 0, policy_version 30069 (0.0016) +[2026-07-22 20:19:29,145][50205] Updated weights for policy 0, policy_version 30079 (0.0011) +[2026-07-22 20:19:29,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5666.1, 300 sec: 5713.6). Total num frames: 15403008. Throughput: 0: 5634.1. Samples: 15401542. Policy #0 lag: (min: 3.0, avg: 14.8, max: 35.0) +[2026-07-22 20:19:29,878][43431] Avg episode reward: [(0, '1898.165')] +[2026-07-22 20:19:30,212][50205] Updated weights for policy 0, policy_version 30089 (0.0024) +[2026-07-22 20:19:31,283][50205] Updated weights for policy 0, policy_version 30099 (0.0011) +[2026-07-22 20:19:31,800][50205] Updated weights for policy 0, policy_version 30109 (0.0011) +[2026-07-22 20:19:32,746][50205] Updated weights for policy 0, policy_version 30119 (0.0015) +[2026-07-22 20:19:34,071][50205] Updated weights for policy 0, policy_version 30129 (0.0022) +[2026-07-22 20:19:34,507][50205] Updated weights for policy 0, policy_version 30139 (0.0012) +[2026-07-22 20:19:34,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5700.3, 300 sec: 5720.5). Total num frames: 15433728. Throughput: 0: 5633.1. Samples: 15436030. Policy #0 lag: (min: 3.0, avg: 16.8, max: 35.0) +[2026-07-22 20:19:34,878][43431] Avg episode reward: [(0, '1631.668')] +[2026-07-22 20:19:35,523][50205] Updated weights for policy 0, policy_version 30149 (0.0025) +[2026-07-22 20:19:36,456][50205] Updated weights for policy 0, policy_version 30159 (0.0011) +[2026-07-22 20:19:37,272][50205] Updated weights for policy 0, policy_version 30169 (0.0013) +[2026-07-22 20:19:38,059][50205] Updated weights for policy 0, policy_version 30179 (0.0012) +[2026-07-22 20:19:39,393][50205] Updated weights for policy 0, policy_version 30189 (0.0014) +[2026-07-22 20:19:39,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5666.1, 300 sec: 5713.6). Total num frames: 15460352. Throughput: 0: 5634.2. Samples: 15470370. Policy #0 lag: (min: 3.0, avg: 16.8, max: 35.0) +[2026-07-22 20:19:39,878][43431] Avg episode reward: [(0, '1520.381')] +[2026-07-22 20:19:40,047][50205] Updated weights for policy 0, policy_version 30199 (0.0014) +[2026-07-22 20:19:40,748][50205] Updated weights for policy 0, policy_version 30209 (0.0012) +[2026-07-22 20:19:41,770][50205] Updated weights for policy 0, policy_version 30219 (0.0012) +[2026-07-22 20:19:42,719][50205] Updated weights for policy 0, policy_version 30229 (0.0014) +[2026-07-22 20:19:43,293][50205] Updated weights for policy 0, policy_version 30239 (0.0012) +[2026-07-22 20:19:44,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5597.9, 300 sec: 5692.7). Total num frames: 15486976. Throughput: 0: 5639.6. Samples: 15487750. Policy #0 lag: (min: 3.0, avg: 16.8, max: 35.0) +[2026-07-22 20:19:44,878][43431] Avg episode reward: [(0, '1625.498')] +[2026-07-22 20:19:45,045][50205] Updated weights for policy 0, policy_version 30249 (0.0012) +[2026-07-22 20:19:45,647][50205] Updated weights for policy 0, policy_version 30261 (0.0012) +[2026-07-22 20:19:46,122][50205] Updated weights for policy 0, policy_version 30271 (0.0011) +[2026-07-22 20:19:47,422][50205] Updated weights for policy 0, policy_version 30281 (0.0012) +[2026-07-22 20:19:48,333][50205] Updated weights for policy 0, policy_version 30291 (0.0015) +[2026-07-22 20:19:49,015][50205] Updated weights for policy 0, policy_version 30301 (0.0012) +[2026-07-22 20:19:49,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5632.1, 300 sec: 5692.7). Total num frames: 15517696. Throughput: 0: 5678.4. Samples: 15522112. Policy #0 lag: (min: 3.0, avg: 16.8, max: 35.0) +[2026-07-22 20:19:49,878][43431] Avg episode reward: [(0, '1658.250')] +[2026-07-22 20:19:50,087][50205] Updated weights for policy 0, policy_version 30311 (0.0013) +[2026-07-22 20:19:50,974][50205] Updated weights for policy 0, policy_version 30321 (0.0013) +[2026-07-22 20:19:51,439][50205] Updated weights for policy 0, policy_version 30331 (0.0011) +[2026-07-22 20:19:52,813][50205] Updated weights for policy 0, policy_version 30341 (0.0011) +[2026-07-22 20:19:53,672][50205] Updated weights for policy 0, policy_version 30351 (0.0012) +[2026-07-22 20:19:54,425][50205] Updated weights for policy 0, policy_version 30361 (0.0015) +[2026-07-22 20:19:54,877][43431] Fps is (10 sec: 6144.1, 60 sec: 5700.3, 300 sec: 5692.7). Total num frames: 15548416. Throughput: 0: 5732.6. Samples: 15556714. Policy #0 lag: (min: 1.0, avg: 19.2, max: 45.0) +[2026-07-22 20:19:54,878][43431] Avg episode reward: [(0, '1665.407')] +[2026-07-22 20:19:55,240][50205] Updated weights for policy 0, policy_version 30371 (0.0011) +[2026-07-22 20:19:56,514][50205] Updated weights for policy 0, policy_version 30381 (0.0012) +[2026-07-22 20:19:56,873][50205] Updated weights for policy 0, policy_version 30391 (0.0015) +[2026-07-22 20:19:58,124][50205] Updated weights for policy 0, policy_version 30401 (0.0015) +[2026-07-22 20:19:59,120][50205] Updated weights for policy 0, policy_version 30411 (0.0016) +[2026-07-22 20:19:59,693][50205] Updated weights for policy 0, policy_version 30421 (0.0012) +[2026-07-22 20:19:59,877][43431] Fps is (10 sec: 5939.1, 60 sec: 5700.3, 300 sec: 5685.8). Total num frames: 15577088. Throughput: 0: 5733.8. Samples: 15573922. Policy #0 lag: (min: 1.0, avg: 19.2, max: 45.0) +[2026-07-22 20:19:59,878][43431] Avg episode reward: [(0, '1797.448')] +[2026-07-22 20:20:00,335][50205] Updated weights for policy 0, policy_version 30431 (0.0011) +[2026-07-22 20:20:02,108][50205] Updated weights for policy 0, policy_version 30444 (0.0016) +[2026-07-22 20:20:02,930][50205] Updated weights for policy 0, policy_version 30454 (0.0021) +[2026-07-22 20:20:03,649][50205] Updated weights for policy 0, policy_version 30464 (0.0017) +[2026-07-22 20:20:04,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5632.0, 300 sec: 5665.0). Total num frames: 15601664. Throughput: 0: 5708.7. Samples: 15606914. Policy #0 lag: (min: 1.0, avg: 19.2, max: 45.0) +[2026-07-22 20:20:04,878][43431] Avg episode reward: [(0, '1774.084')] +[2026-07-22 20:20:05,053][50205] Updated weights for policy 0, policy_version 30474 (0.0012) +[2026-07-22 20:20:05,474][50205] Updated weights for policy 0, policy_version 30484 (0.0015) +[2026-07-22 20:20:06,749][50205] Updated weights for policy 0, policy_version 30494 (0.0012) +[2026-07-22 20:20:07,848][50205] Updated weights for policy 0, policy_version 30505 (0.0015) +[2026-07-22 20:20:08,337][50205] Updated weights for policy 0, policy_version 30515 (0.0012) +[2026-07-22 20:20:09,349][50205] Updated weights for policy 0, policy_version 30525 (0.0020) +[2026-07-22 20:20:09,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5734.4, 300 sec: 5671.9). Total num frames: 15632384. Throughput: 0: 5706.9. Samples: 15641170. Policy #0 lag: (min: 1.0, avg: 19.2, max: 45.0) +[2026-07-22 20:20:09,879][43431] Avg episode reward: [(0, '1719.610')] +[2026-07-22 20:20:10,317][50205] Updated weights for policy 0, policy_version 30535 (0.0010) +[2026-07-22 20:20:11,044][50205] Updated weights for policy 0, policy_version 30545 (0.0014) +[2026-07-22 20:20:11,701][50205] Updated weights for policy 0, policy_version 30555 (0.0020) +[2026-07-22 20:20:13,081][50205] Updated weights for policy 0, policy_version 30565 (0.0012) +[2026-07-22 20:20:13,729][50205] Updated weights for policy 0, policy_version 30575 (0.0011) +[2026-07-22 20:20:14,696][50205] Updated weights for policy 0, policy_version 30585 (0.0012) +[2026-07-22 20:20:14,877][43431] Fps is (10 sec: 5939.3, 60 sec: 5734.4, 300 sec: 5678.9). Total num frames: 15661056. Throughput: 0: 5709.6. Samples: 15658474. Policy #0 lag: (min: 4.0, avg: 17.4, max: 32.0) +[2026-07-22 20:20:14,878][43431] Avg episode reward: [(0, '1561.889')] +[2026-07-22 20:20:15,440][50205] Updated weights for policy 0, policy_version 30595 (0.0012) +[2026-07-22 20:20:16,607][50205] Updated weights for policy 0, policy_version 30605 (0.0011) +[2026-07-22 20:20:17,211][50205] Updated weights for policy 0, policy_version 30615 (0.0011) +[2026-07-22 20:20:18,201][50205] Updated weights for policy 0, policy_version 30625 (0.0012) +[2026-07-22 20:20:19,070][50205] Updated weights for policy 0, policy_version 30635 (0.0015) +[2026-07-22 20:20:19,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5734.4, 300 sec: 5678.9). Total num frames: 15689728. Throughput: 0: 5721.7. Samples: 15693508. Policy #0 lag: (min: 4.0, avg: 17.4, max: 32.0) +[2026-07-22 20:20:19,878][43431] Avg episode reward: [(0, '1686.631')] +[2026-07-22 20:20:20,038][50205] Updated weights for policy 0, policy_version 30645 (0.0013) +[2026-07-22 20:20:20,592][50205] Updated weights for policy 0, policy_version 30655 (0.0011) +[2026-07-22 20:20:21,761][50205] Updated weights for policy 0, policy_version 30665 (0.0011) +[2026-07-22 20:20:22,334][50205] Updated weights for policy 0, policy_version 30675 (0.0011) +[2026-07-22 20:20:23,269][50205] Updated weights for policy 0, policy_version 30685 (0.0017) +[2026-07-22 20:20:24,221][50205] Updated weights for policy 0, policy_version 30695 (0.0022) +[2026-07-22 20:20:24,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5768.5, 300 sec: 5678.9). Total num frames: 15720448. Throughput: 0: 5765.0. Samples: 15729794. Policy #0 lag: (min: 4.0, avg: 17.4, max: 32.0) +[2026-07-22 20:20:24,878][43431] Avg episode reward: [(0, '1812.451')] +[2026-07-22 20:20:25,072][50205] Updated weights for policy 0, policy_version 30705 (0.0014) +[2026-07-22 20:20:25,691][50205] Updated weights for policy 0, policy_version 30715 (0.0012) +[2026-07-22 20:20:26,875][50205] Updated weights for policy 0, policy_version 30725 (0.0013) +[2026-07-22 20:20:27,297][50205] Updated weights for policy 0, policy_version 30735 (0.0011) +[2026-07-22 20:20:28,351][50205] Updated weights for policy 0, policy_version 30745 (0.0016) +[2026-07-22 20:20:29,170][50205] Updated weights for policy 0, policy_version 30755 (0.0013) +[2026-07-22 20:20:29,877][43431] Fps is (10 sec: 6144.0, 60 sec: 5802.7, 300 sec: 5685.8). Total num frames: 15751168. Throughput: 0: 5784.9. Samples: 15748070. Policy #0 lag: (min: 4.0, avg: 17.4, max: 32.0) +[2026-07-22 20:20:29,878][43431] Avg episode reward: [(0, '1590.382')] +[2026-07-22 20:20:29,893][50205] Updated weights for policy 0, policy_version 30765 (0.0012) +[2026-07-22 20:20:30,752][50205] Updated weights for policy 0, policy_version 30775 (0.0014) +[2026-07-22 20:20:31,967][50205] Updated weights for policy 0, policy_version 30785 (0.0017) +[2026-07-22 20:20:32,509][50205] Updated weights for policy 0, policy_version 30795 (0.0011) +[2026-07-22 20:20:33,703][50205] Updated weights for policy 0, policy_version 30805 (0.0011) +[2026-07-22 20:20:34,286][50205] Updated weights for policy 0, policy_version 30815 (0.0024) +[2026-07-22 20:20:34,877][43431] Fps is (10 sec: 5939.1, 60 sec: 5768.5, 300 sec: 5692.7). Total num frames: 15779840. Throughput: 0: 5808.1. Samples: 15783476. Policy #0 lag: (min: 1.0, avg: 17.6, max: 32.0) +[2026-07-22 20:20:34,878][43431] Avg episode reward: [(0, '1800.386')] +[2026-07-22 20:20:35,256][50205] Updated weights for policy 0, policy_version 30825 (0.0011) +[2026-07-22 20:20:36,155][50205] Updated weights for policy 0, policy_version 30835 (0.0016) +[2026-07-22 20:20:37,396][50205] Updated weights for policy 0, policy_version 30845 (0.0015) +[2026-07-22 20:20:38,030][50205] Updated weights for policy 0, policy_version 30855 (0.0012) +[2026-07-22 20:20:39,001][50205] Updated weights for policy 0, policy_version 30865 (0.0012) +[2026-07-22 20:20:39,795][50205] Updated weights for policy 0, policy_version 30875 (0.0011) +[2026-07-22 20:20:39,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5802.7, 300 sec: 5706.6). Total num frames: 15808512. Throughput: 0: 5793.9. Samples: 15817440. Policy #0 lag: (min: 1.0, avg: 17.6, max: 32.0) +[2026-07-22 20:20:39,878][43431] Avg episode reward: [(0, '1748.849')] +[2026-07-22 20:20:40,908][50205] Updated weights for policy 0, policy_version 30885 (0.0013) +[2026-07-22 20:20:41,869][50205] Updated weights for policy 0, policy_version 30896 (0.0011) +[2026-07-22 20:20:42,687][50205] Updated weights for policy 0, policy_version 30906 (0.0015) +[2026-07-22 20:20:43,483][50205] Updated weights for policy 0, policy_version 30916 (0.0011) +[2026-07-22 20:20:44,682][50205] Updated weights for policy 0, policy_version 30926 (0.0011) +[2026-07-22 20:20:44,878][43431] Fps is (10 sec: 5529.5, 60 sec: 5802.7, 300 sec: 5692.7). Total num frames: 15835136. Throughput: 0: 5785.0. Samples: 15834250. Policy #0 lag: (min: 1.0, avg: 17.6, max: 32.0) +[2026-07-22 20:20:44,878][43431] Avg episode reward: [(0, '1723.461')] +[2026-07-22 20:20:45,197][50205] Updated weights for policy 0, policy_version 30936 (0.0012) +[2026-07-22 20:20:46,371][50205] Updated weights for policy 0, policy_version 30946 (0.0011) +[2026-07-22 20:20:47,258][50205] Updated weights for policy 0, policy_version 30956 (0.0017) +[2026-07-22 20:20:48,115][50205] Updated weights for policy 0, policy_version 30966 (0.0017) +[2026-07-22 20:20:49,247][50205] Updated weights for policy 0, policy_version 30977 (0.0015) +[2026-07-22 20:20:49,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5768.5, 300 sec: 5692.7). Total num frames: 15863808. Throughput: 0: 5788.7. Samples: 15867402. Policy #0 lag: (min: 1.0, avg: 17.6, max: 32.0) +[2026-07-22 20:20:49,878][43431] Avg episode reward: [(0, '1742.171')] +[2026-07-22 20:20:50,209][50205] Updated weights for policy 0, policy_version 30987 (0.0011) +[2026-07-22 20:20:51,037][50205] Updated weights for policy 0, policy_version 30997 (0.0013) +[2026-07-22 20:20:52,111][50205] Updated weights for policy 0, policy_version 31007 (0.0011) +[2026-07-22 20:20:53,042][50205] Updated weights for policy 0, policy_version 31017 (0.0011) +[2026-07-22 20:20:53,762][50205] Updated weights for policy 0, policy_version 31027 (0.0012) +[2026-07-22 20:20:54,877][43431] Fps is (10 sec: 5529.8, 60 sec: 5700.3, 300 sec: 5692.7). Total num frames: 15890432. Throughput: 0: 5765.6. Samples: 15900622. Policy #0 lag: (min: 0.0, avg: 18.5, max: 36.0) +[2026-07-22 20:20:54,878][43431] Avg episode reward: [(0, '1807.432')] +[2026-07-22 20:20:54,914][50205] Updated weights for policy 0, policy_version 31037 (0.0012) +[2026-07-22 20:20:55,672][50205] Updated weights for policy 0, policy_version 31047 (0.0013) +[2026-07-22 20:20:56,699][50205] Updated weights for policy 0, policy_version 31057 (0.0012) +[2026-07-22 20:20:57,482][50205] Updated weights for policy 0, policy_version 31067 (0.0012) +[2026-07-22 20:20:58,471][50205] Updated weights for policy 0, policy_version 31077 (0.0014) +[2026-07-22 20:20:59,239][50205] Updated weights for policy 0, policy_version 31087 (0.0012) +[2026-07-22 20:20:59,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5700.3, 300 sec: 5699.7). Total num frames: 15919104. Throughput: 0: 5754.8. Samples: 15917438. Policy #0 lag: (min: 0.0, avg: 18.5, max: 36.0) +[2026-07-22 20:20:59,878][43431] Avg episode reward: [(0, '1539.088')] +[2026-07-22 20:21:00,446][50205] Updated weights for policy 0, policy_version 31097 (0.0012) +[2026-07-22 20:21:01,152][50205] Updated weights for policy 0, policy_version 31107 (0.0012) +[2026-07-22 20:21:02,144][50205] Updated weights for policy 0, policy_version 31117 (0.0011) +[2026-07-22 20:21:03,157][50205] Updated weights for policy 0, policy_version 31127 (0.0012) +[2026-07-22 20:21:04,431][50205] Updated weights for policy 0, policy_version 31137 (0.0012) +[2026-07-22 20:21:04,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5700.3, 300 sec: 5685.8). Total num frames: 15943680. Throughput: 0: 5675.1. Samples: 15948890. Policy #0 lag: (min: 0.0, avg: 18.5, max: 36.0) +[2026-07-22 20:21:04,878][43431] Avg episode reward: [(0, '1661.293')] +[2026-07-22 20:21:05,787][50205] Updated weights for policy 0, policy_version 31152 (0.0011) +[2026-07-22 20:21:07,140][50205] Updated weights for policy 0, policy_version 31162 (0.0015) +[2026-07-22 20:21:07,714][50205] Updated weights for policy 0, policy_version 31172 (0.0011) +[2026-07-22 20:21:08,753][50205] Updated weights for policy 0, policy_version 31182 (0.0012) +[2026-07-22 20:21:09,635][50205] Updated weights for policy 0, policy_version 31192 (0.0011) +[2026-07-22 20:21:09,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5632.0, 300 sec: 5678.9). Total num frames: 15970304. Throughput: 0: 5562.1. Samples: 15980088. Policy #0 lag: (min: 0.0, avg: 18.5, max: 36.0) +[2026-07-22 20:21:09,878][43431] Avg episode reward: [(0, '1699.073')] +[2026-07-22 20:21:10,529][50205] Updated weights for policy 0, policy_version 31202 (0.0011) +[2026-07-22 20:21:11,391][50205] Updated weights for policy 0, policy_version 31212 (0.0018) +[2026-07-22 20:21:12,637][50205] Updated weights for policy 0, policy_version 31222 (0.0011) +[2026-07-22 20:21:13,229][50205] Updated weights for policy 0, policy_version 31232 (0.0012) +[2026-07-22 20:21:14,336][50205] Updated weights for policy 0, policy_version 31242 (0.0018) +[2026-07-22 20:21:14,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5597.9, 300 sec: 5671.9). Total num frames: 15996928. Throughput: 0: 5531.6. Samples: 15996990. Policy #0 lag: (min: 3.0, avg: 17.7, max: 35.0) +[2026-07-22 20:21:14,878][43431] Avg episode reward: [(0, '1722.091')] +[2026-07-22 20:21:15,215][50205] Updated weights for policy 0, policy_version 31252 (0.0012) +[2026-07-22 20:21:16,283][50205] Updated weights for policy 0, policy_version 31262 (0.0016) +[2026-07-22 20:21:16,976][50205] Updated weights for policy 0, policy_version 31272 (0.0016) +[2026-07-22 20:21:18,130][50205] Updated weights for policy 0, policy_version 31282 (0.0015) +[2026-07-22 20:21:18,794][50205] Updated weights for policy 0, policy_version 31292 (0.0022) +[2026-07-22 20:21:19,881][43431] Fps is (10 sec: 5527.5, 60 sec: 5597.5, 300 sec: 5671.9). Total num frames: 16025600. Throughput: 0: 5488.3. Samples: 16030470. Policy #0 lag: (min: 3.0, avg: 17.7, max: 35.0) +[2026-07-22 20:21:19,882][43431] Avg episode reward: [(0, '1644.677')] +[2026-07-22 20:21:19,987][50205] Updated weights for policy 0, policy_version 31302 (0.0016) +[2026-07-22 20:21:20,397][50205] Updated weights for policy 0, policy_version 31312 (0.0012) +[2026-07-22 20:21:21,640][50205] Updated weights for policy 0, policy_version 31322 (0.0017) +[2026-07-22 20:21:22,438][50205] Updated weights for policy 0, policy_version 31332 (0.0012) +[2026-07-22 20:21:23,457][50205] Updated weights for policy 0, policy_version 31342 (0.0012) +[2026-07-22 20:21:24,377][50205] Updated weights for policy 0, policy_version 31352 (0.0016) +[2026-07-22 20:21:24,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5563.7, 300 sec: 5678.9). Total num frames: 16054272. Throughput: 0: 5469.5. Samples: 16063570. Policy #0 lag: (min: 3.0, avg: 17.7, max: 35.0) +[2026-07-22 20:21:24,878][43431] Avg episode reward: [(0, '1707.128')] +[2026-07-22 20:21:25,386][50205] Updated weights for policy 0, policy_version 31362 (0.0012) +[2026-07-22 20:21:26,111][50205] Updated weights for policy 0, policy_version 31372 (0.0012) +[2026-07-22 20:21:27,297][50205] Updated weights for policy 0, policy_version 31382 (0.0011) +[2026-07-22 20:21:27,931][50205] Updated weights for policy 0, policy_version 31392 (0.0011) +[2026-07-22 20:21:29,023][50205] Updated weights for policy 0, policy_version 31402 (0.0014) +[2026-07-22 20:21:29,877][43431] Fps is (10 sec: 5531.5, 60 sec: 5495.4, 300 sec: 5665.0). Total num frames: 16080896. Throughput: 0: 5469.5. Samples: 16080378. Policy #0 lag: (min: 3.0, avg: 17.7, max: 35.0) +[2026-07-22 20:21:29,878][43431] Avg episode reward: [(0, '1845.095')] +[2026-07-22 20:21:29,889][50205] Updated weights for policy 0, policy_version 31412 (0.0011) +[2026-07-22 20:21:30,872][50205] Updated weights for policy 0, policy_version 31422 (0.0016) +[2026-07-22 20:21:31,680][50205] Updated weights for policy 0, policy_version 31432 (0.0011) +[2026-07-22 20:21:32,778][50205] Updated weights for policy 0, policy_version 31442 (0.0013) +[2026-07-22 20:21:33,517][50205] Updated weights for policy 0, policy_version 31452 (0.0015) +[2026-07-22 20:21:34,649][50205] Updated weights for policy 0, policy_version 31462 (0.0014) +[2026-07-22 20:21:34,740][49527] Signal inference workers to stop experience collection... (550 times) +[2026-07-22 20:21:34,740][49527] Signal inference workers to resume experience collection... (550 times) +[2026-07-22 20:21:34,755][50205] InferenceWorker_p0-w0: stopping experience collection (550 times) +[2026-07-22 20:21:34,755][50205] InferenceWorker_p0-w0: resuming experience collection (550 times) +[2026-07-22 20:21:34,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5529.6, 300 sec: 5671.9). Total num frames: 16111616. Throughput: 0: 5481.1. Samples: 16114052. Policy #0 lag: (min: 3.0, avg: 20.0, max: 36.0) +[2026-07-22 20:21:34,878][43431] Avg episode reward: [(0, '1653.058')] +[2026-07-22 20:21:35,453][50205] Updated weights for policy 0, policy_version 31472 (0.0021) +[2026-07-22 20:21:36,329][50205] Updated weights for policy 0, policy_version 31482 (0.0021) +[2026-07-22 20:21:37,156][50205] Updated weights for policy 0, policy_version 31492 (0.0020) +[2026-07-22 20:21:38,345][50205] Updated weights for policy 0, policy_version 31502 (0.0013) +[2026-07-22 20:21:39,045][50205] Updated weights for policy 0, policy_version 31512 (0.0013) +[2026-07-22 20:21:39,877][43431] Fps is (10 sec: 5734.6, 60 sec: 5495.5, 300 sec: 5671.9). Total num frames: 16138240. Throughput: 0: 5491.1. Samples: 16147722. Policy #0 lag: (min: 3.0, avg: 20.0, max: 36.0) +[2026-07-22 20:21:39,878][43431] Avg episode reward: [(0, '1665.988')] +[2026-07-22 20:21:40,056][50205] Updated weights for policy 0, policy_version 31522 (0.0011) +[2026-07-22 20:21:40,579][50205] Updated weights for policy 0, policy_version 31532 (0.0014) +[2026-07-22 20:21:41,901][50205] Updated weights for policy 0, policy_version 31542 (0.0012) +[2026-07-22 20:21:42,935][50205] Updated weights for policy 0, policy_version 31553 (0.0013) +[2026-07-22 20:21:43,643][50205] Updated weights for policy 0, policy_version 31563 (0.0016) +[2026-07-22 20:21:44,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5495.5, 300 sec: 5665.0). Total num frames: 16164864. Throughput: 0: 5489.5. Samples: 16164466. Policy #0 lag: (min: 3.0, avg: 20.0, max: 36.0) +[2026-07-22 20:21:44,878][43431] Avg episode reward: [(0, '1698.076')] +[2026-07-22 20:21:45,021][50205] Updated weights for policy 0, policy_version 31573 (0.0012) +[2026-07-22 20:21:45,545][50205] Updated weights for policy 0, policy_version 31583 (0.0012) +[2026-07-22 20:21:46,492][50205] Updated weights for policy 0, policy_version 31593 (0.0013) +[2026-07-22 20:21:47,356][50205] Updated weights for policy 0, policy_version 31603 (0.0015) +[2026-07-22 20:21:48,378][50205] Updated weights for policy 0, policy_version 31613 (0.0011) +[2026-07-22 20:21:48,823][50205] Updated weights for policy 0, policy_version 31623 (0.0016) +[2026-07-22 20:21:49,877][43431] Fps is (10 sec: 5324.6, 60 sec: 5461.3, 300 sec: 5651.1). Total num frames: 16191488. Throughput: 0: 5535.5. Samples: 16197988. Policy #0 lag: (min: 3.0, avg: 20.0, max: 36.0) +[2026-07-22 20:21:49,878][43431] Avg episode reward: [(0, '1683.347')] +[2026-07-22 20:21:50,236][50205] Updated weights for policy 0, policy_version 31633 (0.0011) +[2026-07-22 20:21:51,067][50205] Updated weights for policy 0, policy_version 31643 (0.0011) +[2026-07-22 20:21:51,930][50205] Updated weights for policy 0, policy_version 31653 (0.0015) +[2026-07-22 20:21:52,958][50205] Updated weights for policy 0, policy_version 31663 (0.0012) +[2026-07-22 20:21:54,048][50205] Updated weights for policy 0, policy_version 31673 (0.0012) +[2026-07-22 20:21:54,524][50205] Updated weights for policy 0, policy_version 31684 (0.0011) +[2026-07-22 20:21:54,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5529.6, 300 sec: 5658.0). Total num frames: 16222208. Throughput: 0: 5574.4. Samples: 16230934. Policy #0 lag: (min: 3.0, avg: 16.7, max: 35.0) +[2026-07-22 20:21:54,878][43431] Avg episode reward: [(0, '1796.859')] +[2026-07-22 20:21:55,928][50205] Updated weights for policy 0, policy_version 31694 (0.0020) +[2026-07-22 20:21:56,757][50205] Updated weights for policy 0, policy_version 31704 (0.0020) +[2026-07-22 20:21:57,749][50205] Updated weights for policy 0, policy_version 31714 (0.0016) +[2026-07-22 20:21:58,750][50205] Updated weights for policy 0, policy_version 31724 (0.0011) +[2026-07-22 20:21:59,586][50205] Updated weights for policy 0, policy_version 31734 (0.0013) +[2026-07-22 20:21:59,877][43431] Fps is (10 sec: 5734.6, 60 sec: 5495.5, 300 sec: 5658.0). Total num frames: 16248832. Throughput: 0: 5565.4. Samples: 16247432. Policy #0 lag: (min: 3.0, avg: 16.7, max: 35.0) +[2026-07-22 20:21:59,878][43431] Avg episode reward: [(0, '1864.484')] +[2026-07-22 20:22:00,253][50205] Updated weights for policy 0, policy_version 31744 (0.0014) +[2026-07-22 20:22:01,706][50205] Updated weights for policy 0, policy_version 31754 (0.0019) +[2026-07-22 20:22:02,984][50205] Updated weights for policy 0, policy_version 31767 (0.0011) +[2026-07-22 20:22:03,844][50205] Updated weights for policy 0, policy_version 31777 (0.0012) +[2026-07-22 20:22:04,872][50205] Updated weights for policy 0, policy_version 31787 (0.0013) +[2026-07-22 20:22:04,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5495.5, 300 sec: 5651.1). Total num frames: 16273408. Throughput: 0: 5517.7. Samples: 16278746. Policy #0 lag: (min: 3.0, avg: 16.7, max: 35.0) +[2026-07-22 20:22:04,878][43431] Avg episode reward: [(0, '1648.569')] +[2026-07-22 20:22:05,823][50205] Updated weights for policy 0, policy_version 31797 (0.0016) +[2026-07-22 20:22:06,551][50205] Updated weights for policy 0, policy_version 31807 (0.0011) +[2026-07-22 20:22:07,833][50205] Updated weights for policy 0, policy_version 31817 (0.0012) +[2026-07-22 20:22:08,375][50205] Updated weights for policy 0, policy_version 31827 (0.0018) +[2026-07-22 20:22:09,676][50205] Updated weights for policy 0, policy_version 31837 (0.0022) +[2026-07-22 20:22:09,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5529.6, 300 sec: 5644.1). Total num frames: 16302080. Throughput: 0: 5500.4. Samples: 16311088. Policy #0 lag: (min: 3.0, avg: 16.7, max: 35.0) +[2026-07-22 20:22:09,878][43431] Avg episode reward: [(0, '1772.625')] +[2026-07-22 20:22:10,604][50205] Updated weights for policy 0, policy_version 31847 (0.0012) +[2026-07-22 20:22:11,553][50205] Updated weights for policy 0, policy_version 31857 (0.0016) +[2026-07-22 20:22:12,411][50205] Updated weights for policy 0, policy_version 31867 (0.0013) +[2026-07-22 20:22:13,881][50205] Updated weights for policy 0, policy_version 31877 (0.0021) +[2026-07-22 20:22:14,619][50205] Updated weights for policy 0, policy_version 31887 (0.0014) +[2026-07-22 20:22:14,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5495.5, 300 sec: 5637.2). Total num frames: 16326656. Throughput: 0: 5467.5. Samples: 16326414. Policy #0 lag: (min: 2.0, avg: 18.2, max: 38.0) +[2026-07-22 20:22:14,878][43431] Avg episode reward: [(0, '1624.624')] +[2026-07-22 20:22:15,479][50205] Updated weights for policy 0, policy_version 31897 (0.0011) +[2026-07-22 20:22:16,930][50205] Updated weights for policy 0, policy_version 31907 (0.0017) +[2026-07-22 20:22:17,615][50205] Updated weights for policy 0, policy_version 31918 (0.0012) +[2026-07-22 20:22:18,478][50205] Updated weights for policy 0, policy_version 31928 (0.0020) +[2026-07-22 20:22:19,868][50205] Updated weights for policy 0, policy_version 31938 (0.0011) +[2026-07-22 20:22:19,877][43431] Fps is (10 sec: 4915.2, 60 sec: 5427.5, 300 sec: 5616.4). Total num frames: 16351232. Throughput: 0: 5407.7. Samples: 16357400. Policy #0 lag: (min: 2.0, avg: 18.2, max: 38.0) +[2026-07-22 20:22:19,878][43431] Avg episode reward: [(0, '1790.235')] +[2026-07-22 20:22:20,403][50205] Updated weights for policy 0, policy_version 31948 (0.0021) +[2026-07-22 20:22:21,459][50205] Updated weights for policy 0, policy_version 31958 (0.0024) +[2026-07-22 20:22:22,691][50205] Updated weights for policy 0, policy_version 31968 (0.0012) +[2026-07-22 20:22:23,490][50205] Updated weights for policy 0, policy_version 31978 (0.0015) +[2026-07-22 20:22:24,244][50205] Updated weights for policy 0, policy_version 31988 (0.0015) +[2026-07-22 20:22:24,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5427.2, 300 sec: 5616.4). Total num frames: 16379904. Throughput: 0: 5363.9. Samples: 16389098. Policy #0 lag: (min: 2.0, avg: 18.2, max: 38.0) +[2026-07-22 20:22:24,879][43431] Avg episode reward: [(0, '1564.997')] +[2026-07-22 20:22:25,874][50205] Updated weights for policy 0, policy_version 31998 (0.0013) +[2026-07-22 20:22:26,509][50205] Updated weights for policy 0, policy_version 32008 (0.0011) +[2026-07-22 20:22:27,319][50205] Updated weights for policy 0, policy_version 32020 (0.0011) +[2026-07-22 20:22:28,832][50205] Updated weights for policy 0, policy_version 32030 (0.0011) +[2026-07-22 20:22:29,691][50205] Updated weights for policy 0, policy_version 32040 (0.0016) +[2026-07-22 20:22:29,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5393.1, 300 sec: 5602.5). Total num frames: 16404480. Throughput: 0: 5344.1. Samples: 16404952. Policy #0 lag: (min: 2.0, avg: 18.2, max: 38.0) +[2026-07-22 20:22:29,878][43431] Avg episode reward: [(0, '1474.871')] +[2026-07-22 20:22:30,432][50205] Updated weights for policy 0, policy_version 32050 (0.0021) +[2026-07-22 20:22:31,197][50205] Updated weights for policy 0, policy_version 32060 (0.0012) +[2026-07-22 20:22:32,730][50205] Updated weights for policy 0, policy_version 32070 (0.0011) +[2026-07-22 20:22:33,236][50205] Updated weights for policy 0, policy_version 32080 (0.0011) +[2026-07-22 20:22:34,548][50205] Updated weights for policy 0, policy_version 32090 (0.0012) +[2026-07-22 20:22:34,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5324.8, 300 sec: 5602.5). Total num frames: 16431104. Throughput: 0: 5295.8. Samples: 16436300. Policy #0 lag: (min: 2.0, avg: 24.1, max: 42.0) +[2026-07-22 20:22:34,878][43431] Avg episode reward: [(0, '1502.629')] +[2026-07-22 20:22:35,591][50205] Updated weights for policy 0, policy_version 32100 (0.0011) +[2026-07-22 20:22:36,277][50205] Updated weights for policy 0, policy_version 32112 (0.0012) +[2026-07-22 20:22:37,734][50205] Updated weights for policy 0, policy_version 32122 (0.0012) +[2026-07-22 20:22:38,848][50205] Updated weights for policy 0, policy_version 32133 (0.0011) +[2026-07-22 20:22:39,236][50205] Updated weights for policy 0, policy_version 32143 (0.0012) +[2026-07-22 20:22:39,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5358.9, 300 sec: 5602.5). Total num frames: 16459776. Throughput: 0: 5280.3. Samples: 16468546. Policy #0 lag: (min: 2.0, avg: 24.1, max: 42.0) +[2026-07-22 20:22:39,878][43431] Avg episode reward: [(0, '1671.795')] +[2026-07-22 20:22:39,936][49527] Saving results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/checkpoint_p0/checkpoint_000032152_16461824.pth... +[2026-07-22 20:22:40,627][50205] Updated weights for policy 0, policy_version 32153 (0.0021) +[2026-07-22 20:22:41,477][50205] Updated weights for policy 0, policy_version 32163 (0.0014) +[2026-07-22 20:22:42,118][50205] Updated weights for policy 0, policy_version 32173 (0.0017) +[2026-07-22 20:22:42,847][50205] Updated weights for policy 0, policy_version 32183 (0.0011) +[2026-07-22 20:22:44,272][50205] Updated weights for policy 0, policy_version 32193 (0.0012) +[2026-07-22 20:22:44,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5358.9, 300 sec: 5595.6). Total num frames: 16486400. Throughput: 0: 5287.1. Samples: 16485350. Policy #0 lag: (min: 2.0, avg: 24.1, max: 42.0) +[2026-07-22 20:22:44,878][43431] Avg episode reward: [(0, '1752.944')] +[2026-07-22 20:22:45,079][50205] Updated weights for policy 0, policy_version 32206 (0.0011) +[2026-07-22 20:22:45,941][50205] Updated weights for policy 0, policy_version 32216 (0.0014) +[2026-07-22 20:22:47,198][50205] Updated weights for policy 0, policy_version 32226 (0.0018) +[2026-07-22 20:22:47,751][50205] Updated weights for policy 0, policy_version 32236 (0.0021) +[2026-07-22 20:22:48,943][50205] Updated weights for policy 0, policy_version 32246 (0.0017) +[2026-07-22 20:22:49,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5358.9, 300 sec: 5588.6). Total num frames: 16513024. Throughput: 0: 5332.6. Samples: 16518714. Policy #0 lag: (min: 2.0, avg: 24.1, max: 42.0) +[2026-07-22 20:22:49,878][43431] Avg episode reward: [(0, '1558.298')] +[2026-07-22 20:22:49,927][50205] Updated weights for policy 0, policy_version 32256 (0.0013) +[2026-07-22 20:22:50,616][50205] Updated weights for policy 0, policy_version 32266 (0.0012) +[2026-07-22 20:22:51,610][50205] Updated weights for policy 0, policy_version 32276 (0.0011) +[2026-07-22 20:22:52,833][50205] Updated weights for policy 0, policy_version 32286 (0.0011) +[2026-07-22 20:22:53,227][50205] Updated weights for policy 0, policy_version 32296 (0.0013) +[2026-07-22 20:22:54,356][50205] Updated weights for policy 0, policy_version 32306 (0.0015) +[2026-07-22 20:22:54,879][43431] Fps is (10 sec: 5528.7, 60 sec: 5324.7, 300 sec: 5595.5). Total num frames: 16541696. Throughput: 0: 5356.0. Samples: 16552118. Policy #0 lag: (min: 2.0, avg: 24.1, max: 42.0) +[2026-07-22 20:22:54,880][43431] Avg episode reward: [(0, '1683.232')] +[2026-07-22 20:22:55,427][50205] Updated weights for policy 0, policy_version 32316 (0.0016) +[2026-07-22 20:22:56,184][50205] Updated weights for policy 0, policy_version 32326 (0.0011) +[2026-07-22 20:22:57,004][50205] Updated weights for policy 0, policy_version 32336 (0.0011) +[2026-07-22 20:22:58,353][50205] Updated weights for policy 0, policy_version 32346 (0.0016) +[2026-07-22 20:22:58,894][50205] Updated weights for policy 0, policy_version 32356 (0.0017) +[2026-07-22 20:22:59,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5358.9, 300 sec: 5595.5). Total num frames: 16570368. Throughput: 0: 5389.1. Samples: 16568924. Policy #0 lag: (min: 3.0, avg: 16.2, max: 35.0) +[2026-07-22 20:22:59,878][43431] Avg episode reward: [(0, '1729.222')] +[2026-07-22 20:23:00,091][50205] Updated weights for policy 0, policy_version 32366 (0.0016) +[2026-07-22 20:23:01,022][50205] Updated weights for policy 0, policy_version 32376 (0.0012) +[2026-07-22 20:23:01,669][50205] Updated weights for policy 0, policy_version 32386 (0.0016) +[2026-07-22 20:23:02,416][50205] Updated weights for policy 0, policy_version 32396 (0.0011) +[2026-07-22 20:23:03,922][50205] Updated weights for policy 0, policy_version 32406 (0.0011) +[2026-07-22 20:23:04,527][50205] Updated weights for policy 0, policy_version 32416 (0.0011) +[2026-07-22 20:23:04,877][43431] Fps is (10 sec: 5735.3, 60 sec: 5427.2, 300 sec: 5588.6). Total num frames: 16599040. Throughput: 0: 5442.3. Samples: 16602302. Policy #0 lag: (min: 3.0, avg: 16.2, max: 35.0) +[2026-07-22 20:23:04,878][43431] Avg episode reward: [(0, '1709.147')] +[2026-07-22 20:23:05,381][50205] Updated weights for policy 0, policy_version 32426 (0.0014) +[2026-07-22 20:23:06,779][50205] Updated weights for policy 0, policy_version 32436 (0.0019) +[2026-07-22 20:23:07,601][50205] Updated weights for policy 0, policy_version 32446 (0.0013) +[2026-07-22 20:23:08,352][50205] Updated weights for policy 0, policy_version 32456 (0.0019) +[2026-07-22 20:23:09,572][50205] Updated weights for policy 0, policy_version 32466 (0.0014) +[2026-07-22 20:23:09,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5358.9, 300 sec: 5581.7). Total num frames: 16623616. Throughput: 0: 5440.0. Samples: 16633898. Policy #0 lag: (min: 3.0, avg: 16.2, max: 35.0) +[2026-07-22 20:23:09,878][43431] Avg episode reward: [(0, '1585.579')] +[2026-07-22 20:23:10,349][50205] Updated weights for policy 0, policy_version 32476 (0.0012) +[2026-07-22 20:23:11,239][50205] Updated weights for policy 0, policy_version 32486 (0.0013) +[2026-07-22 20:23:12,425][50205] Updated weights for policy 0, policy_version 32496 (0.0018) +[2026-07-22 20:23:13,068][50205] Updated weights for policy 0, policy_version 32506 (0.0018) +[2026-07-22 20:23:13,809][50205] Updated weights for policy 0, policy_version 32516 (0.0012) +[2026-07-22 20:23:14,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5427.2, 300 sec: 5574.7). Total num frames: 16652288. Throughput: 0: 5457.6. Samples: 16650544. Policy #0 lag: (min: 3.0, avg: 16.2, max: 35.0) +[2026-07-22 20:23:14,878][43431] Avg episode reward: [(0, '1846.191')] +[2026-07-22 20:23:15,371][50205] Updated weights for policy 0, policy_version 32526 (0.0012) +[2026-07-22 20:23:15,864][50205] Updated weights for policy 0, policy_version 32536 (0.0015) +[2026-07-22 20:23:16,716][50205] Updated weights for policy 0, policy_version 32546 (0.0023) +[2026-07-22 20:23:17,652][50205] Updated weights for policy 0, policy_version 32556 (0.0011) +[2026-07-22 20:23:18,667][50205] Updated weights for policy 0, policy_version 32566 (0.0021) +[2026-07-22 20:23:19,415][50205] Updated weights for policy 0, policy_version 32576 (0.0012) +[2026-07-22 20:23:19,878][43431] Fps is (10 sec: 5734.2, 60 sec: 5495.4, 300 sec: 5574.7). Total num frames: 16680960. Throughput: 0: 5506.8. Samples: 16684106. Policy #0 lag: (min: 3.0, avg: 22.5, max: 43.0) +[2026-07-22 20:23:19,878][43431] Avg episode reward: [(0, '1768.685')] +[2026-07-22 20:23:20,364][50205] Updated weights for policy 0, policy_version 32586 (0.0012) +[2026-07-22 20:23:21,348][50205] Updated weights for policy 0, policy_version 32596 (0.0011) +[2026-07-22 20:23:22,153][50205] Updated weights for policy 0, policy_version 32606 (0.0011) +[2026-07-22 20:23:23,138][50205] Updated weights for policy 0, policy_version 32616 (0.0011) +[2026-07-22 20:23:24,245][50205] Updated weights for policy 0, policy_version 32626 (0.0013) +[2026-07-22 20:23:24,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5461.3, 300 sec: 5574.7). Total num frames: 16707584. Throughput: 0: 5511.3. Samples: 16716556. Policy #0 lag: (min: 3.0, avg: 22.5, max: 43.0) +[2026-07-22 20:23:24,878][43431] Avg episode reward: [(0, '1664.573')] +[2026-07-22 20:23:25,645][50205] Updated weights for policy 0, policy_version 32640 (0.0011) +[2026-07-22 20:23:26,852][50205] Updated weights for policy 0, policy_version 32650 (0.0019) +[2026-07-22 20:23:27,287][50205] Updated weights for policy 0, policy_version 32660 (0.0015) +[2026-07-22 20:23:28,427][50205] Updated weights for policy 0, policy_version 32670 (0.0011) +[2026-07-22 20:23:29,038][50205] Updated weights for policy 0, policy_version 32680 (0.0011) +[2026-07-22 20:23:29,877][43431] Fps is (10 sec: 5325.0, 60 sec: 5495.5, 300 sec: 5567.8). Total num frames: 16734208. Throughput: 0: 5515.1. Samples: 16733528. Policy #0 lag: (min: 3.0, avg: 22.5, max: 43.0) +[2026-07-22 20:23:29,878][43431] Avg episode reward: [(0, '1659.231')] +[2026-07-22 20:23:30,003][50205] Updated weights for policy 0, policy_version 32690 (0.0019) +[2026-07-22 20:23:31,053][50205] Updated weights for policy 0, policy_version 32700 (0.0017) +[2026-07-22 20:23:31,833][50205] Updated weights for policy 0, policy_version 32710 (0.0017) +[2026-07-22 20:23:32,694][50205] Updated weights for policy 0, policy_version 32720 (0.0016) +[2026-07-22 20:23:33,720][50205] Updated weights for policy 0, policy_version 32731 (0.0014) +[2026-07-22 20:23:34,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5529.6, 300 sec: 5567.8). Total num frames: 16762880. Throughput: 0: 5521.2. Samples: 16767168. Policy #0 lag: (min: 3.0, avg: 22.5, max: 43.0) +[2026-07-22 20:23:34,878][43431] Avg episode reward: [(0, '1883.816')] +[2026-07-22 20:23:35,066][50205] Updated weights for policy 0, policy_version 32741 (0.0012) +[2026-07-22 20:23:35,546][50205] Updated weights for policy 0, policy_version 32751 (0.0012) +[2026-07-22 20:23:36,803][50205] Updated weights for policy 0, policy_version 32761 (0.0014) +[2026-07-22 20:23:37,498][50205] Updated weights for policy 0, policy_version 32771 (0.0011) +[2026-07-22 20:23:38,454][50205] Updated weights for policy 0, policy_version 32781 (0.0012) +[2026-07-22 20:23:39,260][50205] Updated weights for policy 0, policy_version 32791 (0.0016) +[2026-07-22 20:23:39,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5529.6, 300 sec: 5560.8). Total num frames: 16791552. Throughput: 0: 5530.1. Samples: 16800964. Policy #0 lag: (min: 2.0, avg: 18.1, max: 38.0) +[2026-07-22 20:23:39,878][43431] Avg episode reward: [(0, '1683.116')] +[2026-07-22 20:23:40,376][50205] Updated weights for policy 0, policy_version 32801 (0.0011) +[2026-07-22 20:23:40,965][50205] Updated weights for policy 0, policy_version 32811 (0.0011) +[2026-07-22 20:23:42,379][50205] Updated weights for policy 0, policy_version 32821 (0.0011) +[2026-07-22 20:23:42,922][50205] Updated weights for policy 0, policy_version 32831 (0.0022) +[2026-07-22 20:23:43,779][50205] Updated weights for policy 0, policy_version 32841 (0.0011) +[2026-07-22 20:23:44,836][50205] Updated weights for policy 0, policy_version 32851 (0.0011) +[2026-07-22 20:23:44,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5563.7, 300 sec: 5560.9). Total num frames: 16820224. Throughput: 0: 5536.0. Samples: 16818044. Policy #0 lag: (min: 2.0, avg: 18.1, max: 38.0) +[2026-07-22 20:23:44,878][43431] Avg episode reward: [(0, '1851.570')] +[2026-07-22 20:23:45,993][50205] Updated weights for policy 0, policy_version 32861 (0.0011) +[2026-07-22 20:23:46,388][50205] Updated weights for policy 0, policy_version 32871 (0.0015) +[2026-07-22 20:23:47,994][50205] Updated weights for policy 0, policy_version 32881 (0.0013) +[2026-07-22 20:23:48,417][50205] Updated weights for policy 0, policy_version 32891 (0.0014) +[2026-07-22 20:23:49,344][50205] Updated weights for policy 0, policy_version 32901 (0.0012) +[2026-07-22 20:23:49,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5597.9, 300 sec: 5567.8). Total num frames: 16848896. Throughput: 0: 5541.6. Samples: 16851676. Policy #0 lag: (min: 2.0, avg: 18.1, max: 38.0) +[2026-07-22 20:23:49,878][43431] Avg episode reward: [(0, '1786.011')] +[2026-07-22 20:23:50,421][50205] Updated weights for policy 0, policy_version 32911 (0.0011) +[2026-07-22 20:23:51,299][50205] Updated weights for policy 0, policy_version 32921 (0.0020) +[2026-07-22 20:23:51,941][50205] Updated weights for policy 0, policy_version 32931 (0.0012) +[2026-07-22 20:23:53,341][50205] Updated weights for policy 0, policy_version 32941 (0.0012) +[2026-07-22 20:23:54,009][50205] Updated weights for policy 0, policy_version 32951 (0.0013) +[2026-07-22 20:23:54,747][50205] Updated weights for policy 0, policy_version 32961 (0.0011) +[2026-07-22 20:23:54,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5598.0, 300 sec: 5567.8). Total num frames: 16877568. Throughput: 0: 5589.6. Samples: 16885428. Policy #0 lag: (min: 2.0, avg: 18.1, max: 38.0) +[2026-07-22 20:23:54,878][43431] Avg episode reward: [(0, '1626.570')] +[2026-07-22 20:23:55,579][50205] Updated weights for policy 0, policy_version 32971 (0.0016) +[2026-07-22 20:23:56,965][50205] Updated weights for policy 0, policy_version 32981 (0.0018) +[2026-07-22 20:23:57,559][50205] Updated weights for policy 0, policy_version 32991 (0.0011) +[2026-07-22 20:23:58,535][50205] Updated weights for policy 0, policy_version 33001 (0.0026) +[2026-07-22 20:23:59,457][50205] Updated weights for policy 0, policy_version 33011 (0.0012) +[2026-07-22 20:23:59,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5529.6, 300 sec: 5553.9). Total num frames: 16902144. Throughput: 0: 5587.7. Samples: 16901990. Policy #0 lag: (min: 3.0, avg: 17.1, max: 35.0) +[2026-07-22 20:23:59,878][43431] Avg episode reward: [(0, '1807.588')] +[2026-07-22 20:24:00,305][50205] Updated weights for policy 0, policy_version 33021 (0.0020) +[2026-07-22 20:24:01,321][50205] Updated weights for policy 0, policy_version 33031 (0.0017) +[2026-07-22 20:24:02,368][50205] Updated weights for policy 0, policy_version 33041 (0.0022) +[2026-07-22 20:24:03,100][50205] Updated weights for policy 0, policy_version 33051 (0.0014) +[2026-07-22 20:24:04,310][50205] Updated weights for policy 0, policy_version 33062 (0.0022) +[2026-07-22 20:24:04,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5529.6, 300 sec: 5567.8). Total num frames: 16930816. Throughput: 0: 5581.6. Samples: 16935276. Policy #0 lag: (min: 3.0, avg: 17.1, max: 35.0) +[2026-07-22 20:24:04,878][43431] Avg episode reward: [(0, '1763.568')] +[2026-07-22 20:24:05,159][50205] Updated weights for policy 0, policy_version 33072 (0.0011) +[2026-07-22 20:24:05,883][50205] Updated weights for policy 0, policy_version 33082 (0.0017) +[2026-07-22 20:24:06,471][50205] Updated weights for policy 0, policy_version 33092 (0.0016) +[2026-07-22 20:24:08,067][50205] Updated weights for policy 0, policy_version 33102 (0.0018) +[2026-07-22 20:24:08,665][50205] Updated weights for policy 0, policy_version 33112 (0.0011) +[2026-07-22 20:24:09,499][50205] Updated weights for policy 0, policy_version 33122 (0.0021) +[2026-07-22 20:24:09,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5597.8, 300 sec: 5567.8). Total num frames: 16959488. Throughput: 0: 5614.3. Samples: 16969202. Policy #0 lag: (min: 3.0, avg: 17.1, max: 35.0) +[2026-07-22 20:24:09,878][43431] Avg episode reward: [(0, '1687.022')] +[2026-07-22 20:24:10,569][50205] Updated weights for policy 0, policy_version 33132 (0.0011) +[2026-07-22 20:24:11,453][50205] Updated weights for policy 0, policy_version 33142 (0.0013) +[2026-07-22 20:24:12,081][50205] Updated weights for policy 0, policy_version 33152 (0.0016) +[2026-07-22 20:24:13,374][50205] Updated weights for policy 0, policy_version 33162 (0.0015) +[2026-07-22 20:24:14,109][50205] Updated weights for policy 0, policy_version 33172 (0.0014) +[2026-07-22 20:24:14,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5597.9, 300 sec: 5567.8). Total num frames: 16988160. Throughput: 0: 5615.1. Samples: 16986206. Policy #0 lag: (min: 3.0, avg: 17.1, max: 35.0) +[2026-07-22 20:24:14,878][43431] Avg episode reward: [(0, '1758.145')] +[2026-07-22 20:24:15,059][50205] Updated weights for policy 0, policy_version 33182 (0.0018) +[2026-07-22 20:24:15,820][50205] Updated weights for policy 0, policy_version 33192 (0.0012) +[2026-07-22 20:24:17,017][50205] Updated weights for policy 0, policy_version 33202 (0.0022) +[2026-07-22 20:24:17,472][50205] Updated weights for policy 0, policy_version 33212 (0.0015) +[2026-07-22 20:24:18,578][50205] Updated weights for policy 0, policy_version 33222 (0.0022) +[2026-07-22 20:24:19,647][50205] Updated weights for policy 0, policy_version 33232 (0.0024) +[2026-07-22 20:24:19,878][43431] Fps is (10 sec: 5529.0, 60 sec: 5563.7, 300 sec: 5560.8). Total num frames: 17014784. Throughput: 0: 5612.8. Samples: 17019752. Policy #0 lag: (min: 3.0, avg: 17.1, max: 35.0) +[2026-07-22 20:24:19,879][43431] Avg episode reward: [(0, '1648.324')] +[2026-07-22 20:24:20,445][50205] Updated weights for policy 0, policy_version 33242 (0.0020) +[2026-07-22 20:24:21,249][50205] Updated weights for policy 0, policy_version 33252 (0.0014) +[2026-07-22 20:24:22,341][50205] Updated weights for policy 0, policy_version 33262 (0.0016) +[2026-07-22 20:24:23,139][50205] Updated weights for policy 0, policy_version 33272 (0.0011) +[2026-07-22 20:24:24,190][50205] Updated weights for policy 0, policy_version 33283 (0.0012) +[2026-07-22 20:24:24,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5597.8, 300 sec: 5560.8). Total num frames: 17043456. Throughput: 0: 5604.2. Samples: 17053154. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 20:24:24,878][43431] Avg episode reward: [(0, '1860.765')] +[2026-07-22 20:24:25,223][50205] Updated weights for policy 0, policy_version 33293 (0.0017) +[2026-07-22 20:24:25,927][50205] Updated weights for policy 0, policy_version 33303 (0.0012) +[2026-07-22 20:24:27,275][50205] Updated weights for policy 0, policy_version 33313 (0.0011) +[2026-07-22 20:24:27,922][50205] Updated weights for policy 0, policy_version 33323 (0.0012) +[2026-07-22 20:24:28,817][50205] Updated weights for policy 0, policy_version 33333 (0.0013) +[2026-07-22 20:24:29,877][43431] Fps is (10 sec: 5530.3, 60 sec: 5597.9, 300 sec: 5547.0). Total num frames: 17070080. Throughput: 0: 5599.8. Samples: 17070036. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 20:24:29,878][43431] Avg episode reward: [(0, '1774.589')] +[2026-07-22 20:24:30,007][50205] Updated weights for policy 0, policy_version 33343 (0.0011) +[2026-07-22 20:24:30,806][50205] Updated weights for policy 0, policy_version 33353 (0.0012) +[2026-07-22 20:24:31,427][50205] Updated weights for policy 0, policy_version 33363 (0.0011) +[2026-07-22 20:24:32,641][50205] Updated weights for policy 0, policy_version 33373 (0.0012) +[2026-07-22 20:24:33,199][50205] Updated weights for policy 0, policy_version 33383 (0.0014) +[2026-07-22 20:24:34,470][50205] Updated weights for policy 0, policy_version 33393 (0.0015) +[2026-07-22 20:24:34,878][43431] Fps is (10 sec: 5529.5, 60 sec: 5597.8, 300 sec: 5553.9). Total num frames: 17098752. Throughput: 0: 5607.4. Samples: 17104010. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 20:24:34,878][43431] Avg episode reward: [(0, '1800.590')] +[2026-07-22 20:24:35,208][50205] Updated weights for policy 0, policy_version 33403 (0.0012) +[2026-07-22 20:24:36,108][50205] Updated weights for policy 0, policy_version 33413 (0.0016) +[2026-07-22 20:24:36,832][50205] Updated weights for policy 0, policy_version 33423 (0.0016) +[2026-07-22 20:24:38,128][50205] Updated weights for policy 0, policy_version 33433 (0.0021) +[2026-07-22 20:24:38,800][50205] Updated weights for policy 0, policy_version 33443 (0.0016) +[2026-07-22 20:24:39,851][50205] Updated weights for policy 0, policy_version 33453 (0.0017) +[2026-07-22 20:24:39,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5597.9, 300 sec: 5560.8). Total num frames: 17127424. Throughput: 0: 5607.5. Samples: 17137764. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 20:24:39,878][43431] Avg episode reward: [(0, '1671.939')] +[2026-07-22 20:24:40,540][50205] Updated weights for policy 0, policy_version 33463 (0.0017) +[2026-07-22 20:24:41,695][50205] Updated weights for policy 0, policy_version 33473 (0.0017) +[2026-07-22 20:24:42,495][50205] Updated weights for policy 0, policy_version 33483 (0.0012) +[2026-07-22 20:24:43,534][50205] Updated weights for policy 0, policy_version 33493 (0.0012) +[2026-07-22 20:24:44,032][50205] Updated weights for policy 0, policy_version 33503 (0.0011) +[2026-07-22 20:24:44,878][43431] Fps is (10 sec: 5734.4, 60 sec: 5597.8, 300 sec: 5553.9). Total num frames: 17156096. Throughput: 0: 5616.3. Samples: 17154724. Policy #0 lag: (min: 3.0, avg: 19.7, max: 43.0) +[2026-07-22 20:24:44,878][43431] Avg episode reward: [(0, '1738.580')] +[2026-07-22 20:24:45,238][50205] Updated weights for policy 0, policy_version 33513 (0.0013) +[2026-07-22 20:24:46,375][50205] Updated weights for policy 0, policy_version 33525 (0.0012) +[2026-07-22 20:24:47,218][50205] Updated weights for policy 0, policy_version 33535 (0.0012) +[2026-07-22 20:24:48,247][50205] Updated weights for policy 0, policy_version 33545 (0.0013) +[2026-07-22 20:24:49,079][50205] Updated weights for policy 0, policy_version 33555 (0.0020) +[2026-07-22 20:24:49,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5597.9, 300 sec: 5547.0). Total num frames: 17184768. Throughput: 0: 5628.2. Samples: 17188544. Policy #0 lag: (min: 3.0, avg: 19.7, max: 43.0) +[2026-07-22 20:24:49,878][43431] Avg episode reward: [(0, '1680.190')] +[2026-07-22 20:24:50,007][50205] Updated weights for policy 0, policy_version 33565 (0.0012) +[2026-07-22 20:24:50,841][50205] Updated weights for policy 0, policy_version 33575 (0.0011) +[2026-07-22 20:24:52,033][50205] Updated weights for policy 0, policy_version 33585 (0.0012) +[2026-07-22 20:24:52,469][50205] Updated weights for policy 0, policy_version 33595 (0.0012) +[2026-07-22 20:24:53,582][50205] Updated weights for policy 0, policy_version 33605 (0.0012) +[2026-07-22 20:24:54,704][50205] Updated weights for policy 0, policy_version 33615 (0.0015) +[2026-07-22 20:24:54,877][43431] Fps is (10 sec: 5529.8, 60 sec: 5563.7, 300 sec: 5540.0). Total num frames: 17211392. Throughput: 0: 5625.2. Samples: 17222334. Policy #0 lag: (min: 3.0, avg: 19.7, max: 43.0) +[2026-07-22 20:24:54,878][43431] Avg episode reward: [(0, '1729.449')] +[2026-07-22 20:24:55,352][50205] Updated weights for policy 0, policy_version 33625 (0.0011) +[2026-07-22 20:24:55,897][50205] Updated weights for policy 0, policy_version 33635 (0.0012) +[2026-07-22 20:24:57,525][50205] Updated weights for policy 0, policy_version 33645 (0.0016) +[2026-07-22 20:24:57,957][50205] Updated weights for policy 0, policy_version 33655 (0.0011) +[2026-07-22 20:24:58,912][50205] Updated weights for policy 0, policy_version 33665 (0.0013) +[2026-07-22 20:24:59,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5632.0, 300 sec: 5553.9). Total num frames: 17240064. Throughput: 0: 5624.3. Samples: 17239300. Policy #0 lag: (min: 3.0, avg: 19.7, max: 43.0) +[2026-07-22 20:24:59,878][43431] Avg episode reward: [(0, '1588.255')] +[2026-07-22 20:25:00,072][50205] Updated weights for policy 0, policy_version 33675 (0.0011) +[2026-07-22 20:25:00,835][50205] Updated weights for policy 0, policy_version 33685 (0.0021) +[2026-07-22 20:25:01,416][50205] Updated weights for policy 0, policy_version 33695 (0.0012) +[2026-07-22 20:25:03,343][50205] Updated weights for policy 0, policy_version 33705 (0.0015) +[2026-07-22 20:25:03,806][50205] Updated weights for policy 0, policy_version 33715 (0.0021) +[2026-07-22 20:25:04,704][50205] Updated weights for policy 0, policy_version 33725 (0.0013) +[2026-07-22 20:25:04,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5632.0, 300 sec: 5547.0). Total num frames: 17268736. Throughput: 0: 5585.7. Samples: 17271102. Policy #0 lag: (min: 3.0, avg: 20.2, max: 35.0) +[2026-07-22 20:25:04,878][43431] Avg episode reward: [(0, '1852.699')] +[2026-07-22 20:25:05,800][50205] Updated weights for policy 0, policy_version 33735 (0.0014) +[2026-07-22 20:25:06,676][50205] Updated weights for policy 0, policy_version 33745 (0.0013) +[2026-07-22 20:25:07,201][50205] Updated weights for policy 0, policy_version 33755 (0.0015) +[2026-07-22 20:25:08,701][50205] Updated weights for policy 0, policy_version 33765 (0.0011) +[2026-07-22 20:25:09,222][50205] Updated weights for policy 0, policy_version 33775 (0.0016) +[2026-07-22 20:25:09,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5597.9, 300 sec: 5540.0). Total num frames: 17295360. Throughput: 0: 5600.1. Samples: 17305158. Policy #0 lag: (min: 3.0, avg: 20.2, max: 35.0) +[2026-07-22 20:25:09,878][43431] Avg episode reward: [(0, '1759.297')] +[2026-07-22 20:25:10,144][50205] Updated weights for policy 0, policy_version 33785 (0.0019) +[2026-07-22 20:25:11,217][50205] Updated weights for policy 0, policy_version 33795 (0.0019) +[2026-07-22 20:25:12,099][50205] Updated weights for policy 0, policy_version 33805 (0.0012) +[2026-07-22 20:25:12,675][50205] Updated weights for policy 0, policy_version 33815 (0.0014) +[2026-07-22 20:25:14,124][50205] Updated weights for policy 0, policy_version 33825 (0.0015) +[2026-07-22 20:25:14,699][50205] Updated weights for policy 0, policy_version 33835 (0.0011) +[2026-07-22 20:25:14,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5597.9, 300 sec: 5540.0). Total num frames: 17324032. Throughput: 0: 5605.2. Samples: 17322270. Policy #0 lag: (min: 3.0, avg: 20.2, max: 35.0) +[2026-07-22 20:25:14,878][43431] Avg episode reward: [(0, '1476.864')] +[2026-07-22 20:25:15,590][50205] Updated weights for policy 0, policy_version 33845 (0.0012) +[2026-07-22 20:25:16,793][50205] Updated weights for policy 0, policy_version 33855 (0.0017) +[2026-07-22 20:25:17,513][50205] Updated weights for policy 0, policy_version 33865 (0.0012) +[2026-07-22 20:25:18,194][50205] Updated weights for policy 0, policy_version 33875 (0.0013) +[2026-07-22 20:25:19,698][50205] Updated weights for policy 0, policy_version 33885 (0.0011) +[2026-07-22 20:25:19,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5598.0, 300 sec: 5526.1). Total num frames: 17350656. Throughput: 0: 5606.1. Samples: 17356284. Policy #0 lag: (min: 3.0, avg: 20.2, max: 35.0) +[2026-07-22 20:25:19,878][43431] Avg episode reward: [(0, '1752.738')] +[2026-07-22 20:25:20,382][50205] Updated weights for policy 0, policy_version 33898 (0.0012) +[2026-07-22 20:25:21,245][50205] Updated weights for policy 0, policy_version 33908 (0.0012) +[2026-07-22 20:25:22,753][50205] Updated weights for policy 0, policy_version 33918 (0.0013) +[2026-07-22 20:25:23,059][50205] Updated weights for policy 0, policy_version 33928 (0.0011) +[2026-07-22 20:25:23,964][50205] Updated weights for policy 0, policy_version 33938 (0.0012) +[2026-07-22 20:25:24,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5597.9, 300 sec: 5519.2). Total num frames: 17379328. Throughput: 0: 5605.9. Samples: 17390028. Policy #0 lag: (min: 3.0, avg: 20.2, max: 35.0) +[2026-07-22 20:25:24,878][43431] Avg episode reward: [(0, '1559.416')] +[2026-07-22 20:25:25,039][50205] Updated weights for policy 0, policy_version 33948 (0.0011) +[2026-07-22 20:25:25,830][50205] Updated weights for policy 0, policy_version 33959 (0.0011) +[2026-07-22 20:25:26,789][50205] Updated weights for policy 0, policy_version 33969 (0.0015) +[2026-07-22 20:25:27,976][50205] Updated weights for policy 0, policy_version 33979 (0.0017) +[2026-07-22 20:25:28,738][50205] Updated weights for policy 0, policy_version 33989 (0.0012) +[2026-07-22 20:25:29,380][50205] Updated weights for policy 0, policy_version 33999 (0.0017) +[2026-07-22 20:25:29,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5666.1, 300 sec: 5526.1). Total num frames: 17410048. Throughput: 0: 5605.8. Samples: 17406984. Policy #0 lag: (min: 3.0, avg: 21.2, max: 47.0) +[2026-07-22 20:25:29,878][43431] Avg episode reward: [(0, '1678.532')] +[2026-07-22 20:25:30,986][50205] Updated weights for policy 0, policy_version 34009 (0.0016) +[2026-07-22 20:25:31,419][50205] Updated weights for policy 0, policy_version 34019 (0.0016) +[2026-07-22 20:25:32,270][50205] Updated weights for policy 0, policy_version 34029 (0.0019) +[2026-07-22 20:25:32,869][50205] Updated weights for policy 0, policy_version 34039 (0.0012) +[2026-07-22 20:25:34,217][50205] Updated weights for policy 0, policy_version 34049 (0.0017) +[2026-07-22 20:25:34,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5632.0, 300 sec: 5519.2). Total num frames: 17436672. Throughput: 0: 5612.6. Samples: 17441110. Policy #0 lag: (min: 3.0, avg: 21.2, max: 47.0) +[2026-07-22 20:25:34,878][43431] Avg episode reward: [(0, '1522.559')] +[2026-07-22 20:25:34,952][50205] Updated weights for policy 0, policy_version 34059 (0.0016) +[2026-07-22 20:25:36,208][50205] Updated weights for policy 0, policy_version 34069 (0.0017) +[2026-07-22 20:25:36,819][50205] Updated weights for policy 0, policy_version 34079 (0.0015) +[2026-07-22 20:25:37,649][50205] Updated weights for policy 0, policy_version 34089 (0.0012) +[2026-07-22 20:25:38,329][50205] Updated weights for policy 0, policy_version 34099 (0.0011) +[2026-07-22 20:25:39,451][50205] Updated weights for policy 0, policy_version 34109 (0.0021) +[2026-07-22 20:25:39,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5666.1, 300 sec: 5533.1). Total num frames: 17467392. Throughput: 0: 5643.2. Samples: 17476278. Policy #0 lag: (min: 3.0, avg: 21.2, max: 47.0) +[2026-07-22 20:25:39,878][43431] Avg episode reward: [(0, '1779.573')] +[2026-07-22 20:25:40,187][50205] Updated weights for policy 0, policy_version 34119 (0.0020) +[2026-07-22 20:25:41,051][50205] Updated weights for policy 0, policy_version 34129 (0.0016) +[2026-07-22 20:25:41,868][50205] Updated weights for policy 0, policy_version 34139 (0.0011) +[2026-07-22 20:25:42,810][50205] Updated weights for policy 0, policy_version 34149 (0.0015) +[2026-07-22 20:25:43,484][50205] Updated weights for policy 0, policy_version 34159 (0.0013) +[2026-07-22 20:25:44,872][50205] Updated weights for policy 0, policy_version 34169 (0.0012) +[2026-07-22 20:25:44,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5632.0, 300 sec: 5526.1). Total num frames: 17494016. Throughput: 0: 5672.2. Samples: 17494548. Policy #0 lag: (min: 3.0, avg: 21.2, max: 47.0) +[2026-07-22 20:25:44,878][43431] Avg episode reward: [(0, '1722.362')] +[2026-07-22 20:25:45,605][50205] Updated weights for policy 0, policy_version 34181 (0.0016) +[2026-07-22 20:25:46,154][50205] Updated weights for policy 0, policy_version 34191 (0.0012) +[2026-07-22 20:25:47,119][50205] Updated weights for policy 0, policy_version 34201 (0.0011) +[2026-07-22 20:25:48,078][50205] Updated weights for policy 0, policy_version 34211 (0.0020) +[2026-07-22 20:25:48,813][50205] Updated weights for policy 0, policy_version 34221 (0.0011) +[2026-07-22 20:25:49,576][50205] Updated weights for policy 0, policy_version 34231 (0.0012) +[2026-07-22 20:25:49,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5700.3, 300 sec: 5547.0). Total num frames: 17526784. Throughput: 0: 5769.3. Samples: 17530720. Policy #0 lag: (min: 2.0, avg: 20.6, max: 42.0) +[2026-07-22 20:25:49,878][43431] Avg episode reward: [(0, '1884.112')] +[2026-07-22 20:25:50,577][50205] Updated weights for policy 0, policy_version 34241 (0.0010) +[2026-07-22 20:25:51,320][50205] Updated weights for policy 0, policy_version 34251 (0.0011) +[2026-07-22 20:25:51,890][49527] Signal inference workers to stop experience collection... (600 times) +[2026-07-22 20:25:51,906][50205] InferenceWorker_p0-w0: stopping experience collection (600 times) +[2026-07-22 20:25:51,937][49527] Signal inference workers to resume experience collection... (600 times) +[2026-07-22 20:25:51,937][50205] InferenceWorker_p0-w0: resuming experience collection (600 times) +[2026-07-22 20:25:52,272][50205] Updated weights for policy 0, policy_version 34262 (0.0015) +[2026-07-22 20:25:53,156][50205] Updated weights for policy 0, policy_version 34272 (0.0011) +[2026-07-22 20:25:53,922][50205] Updated weights for policy 0, policy_version 34282 (0.0011) +[2026-07-22 20:25:54,686][50205] Updated weights for policy 0, policy_version 34292 (0.0016) +[2026-07-22 20:25:54,877][43431] Fps is (10 sec: 6553.6, 60 sec: 5802.7, 300 sec: 5560.8). Total num frames: 17559552. Throughput: 0: 5822.6. Samples: 17567176. Policy #0 lag: (min: 2.0, avg: 20.6, max: 42.0) +[2026-07-22 20:25:54,878][43431] Avg episode reward: [(0, '1793.399')] +[2026-07-22 20:25:55,841][50205] Updated weights for policy 0, policy_version 34302 (0.0011) +[2026-07-22 20:25:56,289][50205] Updated weights for policy 0, policy_version 34312 (0.0017) +[2026-07-22 20:25:57,232][50205] Updated weights for policy 0, policy_version 34322 (0.0011) +[2026-07-22 20:25:57,880][50205] Updated weights for policy 0, policy_version 34332 (0.0011) +[2026-07-22 20:25:59,038][50205] Updated weights for policy 0, policy_version 34342 (0.0011) +[2026-07-22 20:25:59,760][50205] Updated weights for policy 0, policy_version 34352 (0.0011) +[2026-07-22 20:25:59,877][43431] Fps is (10 sec: 6144.0, 60 sec: 5802.7, 300 sec: 5574.7). Total num frames: 17588224. Throughput: 0: 5846.7. Samples: 17585372. Policy #0 lag: (min: 2.0, avg: 20.6, max: 42.0) +[2026-07-22 20:25:59,878][43431] Avg episode reward: [(0, '1611.029')] +[2026-07-22 20:26:00,577][50205] Updated weights for policy 0, policy_version 34362 (0.0021) +[2026-07-22 20:26:01,405][50205] Updated weights for policy 0, policy_version 34372 (0.0011) +[2026-07-22 20:26:02,379][50205] Updated weights for policy 0, policy_version 34382 (0.0011) +[2026-07-22 20:26:02,967][50205] Updated weights for policy 0, policy_version 34392 (0.0011) +[2026-07-22 20:26:04,089][50205] Updated weights for policy 0, policy_version 34402 (0.0012) +[2026-07-22 20:26:04,804][50205] Updated weights for policy 0, policy_version 34412 (0.0021) +[2026-07-22 20:26:04,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5836.8, 300 sec: 5588.6). Total num frames: 17618944. Throughput: 0: 5897.4. Samples: 17621668. Policy #0 lag: (min: 2.0, avg: 20.6, max: 42.0) +[2026-07-22 20:26:04,878][43431] Avg episode reward: [(0, '1824.279')] +[2026-07-22 20:26:05,929][50205] Updated weights for policy 0, policy_version 34422 (0.0011) +[2026-07-22 20:26:06,588][50205] Updated weights for policy 0, policy_version 34432 (0.0011) +[2026-07-22 20:26:07,414][50205] Updated weights for policy 0, policy_version 34442 (0.0012) +[2026-07-22 20:26:08,132][50205] Updated weights for policy 0, policy_version 34452 (0.0011) +[2026-07-22 20:26:09,307][50205] Updated weights for policy 0, policy_version 34462 (0.0012) +[2026-07-22 20:26:09,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5870.9, 300 sec: 5595.6). Total num frames: 17647616. Throughput: 0: 5953.1. Samples: 17657916. Policy #0 lag: (min: 2.0, avg: 20.6, max: 42.0) +[2026-07-22 20:26:09,878][43431] Avg episode reward: [(0, '1615.790')] +[2026-07-22 20:26:09,891][50205] Updated weights for policy 0, policy_version 34472 (0.0011) +[2026-07-22 20:26:10,814][50205] Updated weights for policy 0, policy_version 34482 (0.0015) +[2026-07-22 20:26:11,830][50205] Updated weights for policy 0, policy_version 34492 (0.0011) +[2026-07-22 20:26:12,508][50205] Updated weights for policy 0, policy_version 34502 (0.0011) +[2026-07-22 20:26:13,246][50205] Updated weights for policy 0, policy_version 34512 (0.0011) +[2026-07-22 20:26:14,463][50205] Updated weights for policy 0, policy_version 34522 (0.0011) +[2026-07-22 20:26:14,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5870.9, 300 sec: 5595.6). Total num frames: 17676288. Throughput: 0: 5980.1. Samples: 17676088. Policy #0 lag: (min: 3.0, avg: 18.8, max: 35.0) +[2026-07-22 20:26:14,878][43431] Avg episode reward: [(0, '1775.901')] +[2026-07-22 20:26:15,340][50205] Updated weights for policy 0, policy_version 34535 (0.0010) +[2026-07-22 20:26:16,201][50205] Updated weights for policy 0, policy_version 34545 (0.0011) +[2026-07-22 20:26:17,202][50205] Updated weights for policy 0, policy_version 34555 (0.0011) +[2026-07-22 20:26:17,978][50205] Updated weights for policy 0, policy_version 34565 (0.0013) +[2026-07-22 20:26:18,670][50205] Updated weights for policy 0, policy_version 34575 (0.0015) +[2026-07-22 20:26:19,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5939.2, 300 sec: 5602.5). Total num frames: 17707008. Throughput: 0: 6021.1. Samples: 17712060. Policy #0 lag: (min: 3.0, avg: 18.8, max: 35.0) +[2026-07-22 20:26:19,878][43431] Avg episode reward: [(0, '1745.519')] +[2026-07-22 20:26:19,891][50205] Updated weights for policy 0, policy_version 34585 (0.0015) +[2026-07-22 20:26:20,328][50205] Updated weights for policy 0, policy_version 34595 (0.0011) +[2026-07-22 20:26:21,304][50205] Updated weights for policy 0, policy_version 34605 (0.0017) +[2026-07-22 20:26:22,288][50205] Updated weights for policy 0, policy_version 34615 (0.0011) +[2026-07-22 20:26:23,121][50205] Updated weights for policy 0, policy_version 34625 (0.0013) +[2026-07-22 20:26:23,711][50205] Updated weights for policy 0, policy_version 34635 (0.0014) +[2026-07-22 20:26:24,877][43431] Fps is (10 sec: 6144.0, 60 sec: 5973.3, 300 sec: 5616.4). Total num frames: 17737728. Throughput: 0: 6050.4. Samples: 17748544. Policy #0 lag: (min: 3.0, avg: 18.8, max: 35.0) +[2026-07-22 20:26:24,878][43431] Avg episode reward: [(0, '1752.403')] +[2026-07-22 20:26:24,925][50205] Updated weights for policy 0, policy_version 34645 (0.0017) +[2026-07-22 20:26:25,363][50205] Updated weights for policy 0, policy_version 34656 (0.0026) +[2026-07-22 20:26:26,714][50205] Updated weights for policy 0, policy_version 34666 (0.0016) +[2026-07-22 20:26:27,138][50205] Updated weights for policy 0, policy_version 34676 (0.0016) +[2026-07-22 20:26:28,235][50205] Updated weights for policy 0, policy_version 34686 (0.0020) +[2026-07-22 20:26:29,013][50205] Updated weights for policy 0, policy_version 34696 (0.0016) +[2026-07-22 20:26:29,877][43431] Fps is (10 sec: 6144.0, 60 sec: 5973.3, 300 sec: 5616.4). Total num frames: 17768448. Throughput: 0: 6041.7. Samples: 17766426. Policy #0 lag: (min: 3.0, avg: 18.8, max: 35.0) +[2026-07-22 20:26:29,878][43431] Avg episode reward: [(0, '1821.262')] +[2026-07-22 20:26:30,009][50205] Updated weights for policy 0, policy_version 34706 (0.0011) +[2026-07-22 20:26:30,595][50205] Updated weights for policy 0, policy_version 34716 (0.0013) +[2026-07-22 20:26:31,690][50205] Updated weights for policy 0, policy_version 34726 (0.0011) +[2026-07-22 20:26:32,259][50205] Updated weights for policy 0, policy_version 34736 (0.0011) +[2026-07-22 20:26:33,132][50205] Updated weights for policy 0, policy_version 34746 (0.0014) +[2026-07-22 20:26:34,095][50205] Updated weights for policy 0, policy_version 34756 (0.0014) +[2026-07-22 20:26:34,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 5630.3). Total num frames: 17799168. Throughput: 0: 6046.7. Samples: 17802822. Policy #0 lag: (min: 0.0, avg: 19.3, max: 44.0) +[2026-07-22 20:26:34,878][43431] Avg episode reward: [(0, '1635.189')] +[2026-07-22 20:26:34,987][50205] Updated weights for policy 0, policy_version 34766 (0.0012) +[2026-07-22 20:26:35,624][50205] Updated weights for policy 0, policy_version 34776 (0.0010) +[2026-07-22 20:26:36,917][50205] Updated weights for policy 0, policy_version 34786 (0.0013) +[2026-07-22 20:26:37,408][50205] Updated weights for policy 0, policy_version 34796 (0.0011) +[2026-07-22 20:26:38,232][50205] Updated weights for policy 0, policy_version 34806 (0.0015) +[2026-07-22 20:26:39,170][50205] Updated weights for policy 0, policy_version 34816 (0.0017) +[2026-07-22 20:26:39,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 5644.1). Total num frames: 17829888. Throughput: 0: 6050.8. Samples: 17839462. Policy #0 lag: (min: 0.0, avg: 19.3, max: 44.0) +[2026-07-22 20:26:39,878][43431] Avg episode reward: [(0, '1705.630')] +[2026-07-22 20:26:39,978][50205] Updated weights for policy 0, policy_version 34826 (0.0011) +[2026-07-22 20:26:40,753][50205] Updated weights for policy 0, policy_version 34836 (0.0011) +[2026-07-22 20:26:41,755][50205] Updated weights for policy 0, policy_version 34846 (0.0011) +[2026-07-22 20:26:42,487][50205] Updated weights for policy 0, policy_version 34856 (0.0012) +[2026-07-22 20:26:43,289][50205] Updated weights for policy 0, policy_version 34866 (0.0010) +[2026-07-22 20:26:44,124][50205] Updated weights for policy 0, policy_version 34876 (0.0010) +[2026-07-22 20:26:44,878][43431] Fps is (10 sec: 5938.9, 60 sec: 6075.7, 300 sec: 5651.1). Total num frames: 17858560. Throughput: 0: 6048.2. Samples: 17857542. Policy #0 lag: (min: 0.0, avg: 19.3, max: 44.0) +[2026-07-22 20:26:44,878][43431] Avg episode reward: [(0, '1806.708')] +[2026-07-22 20:26:45,167][50205] Updated weights for policy 0, policy_version 34886 (0.0011) +[2026-07-22 20:26:45,692][50205] Updated weights for policy 0, policy_version 34896 (0.0011) +[2026-07-22 20:26:46,868][50205] Updated weights for policy 0, policy_version 34906 (0.0012) +[2026-07-22 20:26:47,712][50205] Updated weights for policy 0, policy_version 34916 (0.0011) +[2026-07-22 20:26:48,363][50205] Updated weights for policy 0, policy_version 34926 (0.0012) +[2026-07-22 20:26:48,864][50205] Updated weights for policy 0, policy_version 34936 (0.0012) +[2026-07-22 20:26:49,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 5651.1). Total num frames: 17889280. Throughput: 0: 6050.7. Samples: 17893952. Policy #0 lag: (min: 0.0, avg: 19.3, max: 44.0) +[2026-07-22 20:26:49,878][43431] Avg episode reward: [(0, '1890.830')] +[2026-07-22 20:26:50,367][50205] Updated weights for policy 0, policy_version 34946 (0.0018) +[2026-07-22 20:26:50,988][50205] Updated weights for policy 0, policy_version 34957 (0.0013) +[2026-07-22 20:26:51,595][50205] Updated weights for policy 0, policy_version 34967 (0.0011) +[2026-07-22 20:26:53,025][50205] Updated weights for policy 0, policy_version 34977 (0.0014) +[2026-07-22 20:26:53,566][50205] Updated weights for policy 0, policy_version 34987 (0.0011) +[2026-07-22 20:26:54,577][50205] Updated weights for policy 0, policy_version 34997 (0.0015) +[2026-07-22 20:26:54,877][43431] Fps is (10 sec: 6349.1, 60 sec: 6041.6, 300 sec: 5671.9). Total num frames: 17922048. Throughput: 0: 6051.1. Samples: 17930216. Policy #0 lag: (min: 0.0, avg: 19.3, max: 44.0) +[2026-07-22 20:26:54,879][43431] Avg episode reward: [(0, '1741.211')] +[2026-07-22 20:26:55,540][50205] Updated weights for policy 0, policy_version 35007 (0.0016) +[2026-07-22 20:26:56,090][50205] Updated weights for policy 0, policy_version 35017 (0.0011) +[2026-07-22 20:26:56,828][50205] Updated weights for policy 0, policy_version 35027 (0.0011) +[2026-07-22 20:26:58,197][50205] Updated weights for policy 0, policy_version 35037 (0.0013) +[2026-07-22 20:26:58,663][50205] Updated weights for policy 0, policy_version 35047 (0.0011) +[2026-07-22 20:26:59,352][50205] Updated weights for policy 0, policy_version 35057 (0.0012) +[2026-07-22 20:26:59,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 5685.8). Total num frames: 17950720. Throughput: 0: 6055.3. Samples: 17948578. Policy #0 lag: (min: 3.0, avg: 14.6, max: 35.0) +[2026-07-22 20:26:59,878][43431] Avg episode reward: [(0, '1511.186')] +[2026-07-22 20:27:00,681][50205] Updated weights for policy 0, policy_version 35067 (0.0011) +[2026-07-22 20:27:01,276][50205] Updated weights for policy 0, policy_version 35079 (0.0012) +[2026-07-22 20:27:02,078][50205] Updated weights for policy 0, policy_version 35089 (0.0016) +[2026-07-22 20:27:03,304][50205] Updated weights for policy 0, policy_version 35099 (0.0011) +[2026-07-22 20:27:03,935][50205] Updated weights for policy 0, policy_version 35109 (0.0011) +[2026-07-22 20:27:04,504][50205] Updated weights for policy 0, policy_version 35119 (0.0017) +[2026-07-22 20:27:04,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6041.6, 300 sec: 5692.7). Total num frames: 17981440. Throughput: 0: 6052.8. Samples: 17984436. Policy #0 lag: (min: 3.0, avg: 14.6, max: 35.0) +[2026-07-22 20:27:04,878][43431] Avg episode reward: [(0, '1735.198')] +[2026-07-22 20:27:05,873][50205] Updated weights for policy 0, policy_version 35129 (0.0016) +[2026-07-22 20:27:07,030][50205] Updated weights for policy 0, policy_version 35144 (0.0012) +[2026-07-22 20:27:08,351][50205] Updated weights for policy 0, policy_version 35154 (0.0017) +[2026-07-22 20:27:09,136][50205] Updated weights for policy 0, policy_version 35164 (0.0012) +[2026-07-22 20:27:09,721][50205] Updated weights for policy 0, policy_version 35174 (0.0019) +[2026-07-22 20:27:09,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6041.6, 300 sec: 5706.6). Total num frames: 18010112. Throughput: 0: 5992.1. Samples: 18018188. Policy #0 lag: (min: 3.0, avg: 14.6, max: 35.0) +[2026-07-22 20:27:09,878][43431] Avg episode reward: [(0, '1829.853')] +[2026-07-22 20:27:10,413][50205] Updated weights for policy 0, policy_version 35184 (0.0011) +[2026-07-22 20:27:11,879][50205] Updated weights for policy 0, policy_version 35194 (0.0011) +[2026-07-22 20:27:12,366][50205] Updated weights for policy 0, policy_version 35205 (0.0010) +[2026-07-22 20:27:13,072][50205] Updated weights for policy 0, policy_version 35215 (0.0016) +[2026-07-22 20:27:14,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5973.3, 300 sec: 5706.6). Total num frames: 18034688. Throughput: 0: 5997.9. Samples: 18036334. Policy #0 lag: (min: 3.0, avg: 14.6, max: 35.0) +[2026-07-22 20:27:14,878][43431] Avg episode reward: [(0, '1603.450')] +[2026-07-22 20:27:14,962][50205] Updated weights for policy 0, policy_version 35225 (0.0012) +[2026-07-22 20:27:15,434][50205] Updated weights for policy 0, policy_version 35241 (0.0012) +[2026-07-22 20:27:16,653][50205] Updated weights for policy 0, policy_version 35251 (0.0016) +[2026-07-22 20:27:17,437][50205] Updated weights for policy 0, policy_version 35261 (0.0011) +[2026-07-22 20:27:17,838][50205] Updated weights for policy 0, policy_version 35271 (0.0016) +[2026-07-22 20:27:19,526][50205] Updated weights for policy 0, policy_version 35281 (0.0016) +[2026-07-22 20:27:19,877][43431] Fps is (10 sec: 5734.5, 60 sec: 6007.5, 300 sec: 5720.5). Total num frames: 18067456. Throughput: 0: 5984.4. Samples: 18072118. Policy #0 lag: (min: 3.0, avg: 22.1, max: 36.0) +[2026-07-22 20:27:19,878][43431] Avg episode reward: [(0, '1663.206')] +[2026-07-22 20:27:19,997][50205] Updated weights for policy 0, policy_version 35291 (0.0019) +[2026-07-22 20:27:20,556][50205] Updated weights for policy 0, policy_version 35301 (0.0011) +[2026-07-22 20:27:21,562][50205] Updated weights for policy 0, policy_version 35311 (0.0010) +[2026-07-22 20:27:22,594][50205] Updated weights for policy 0, policy_version 35321 (0.0015) +[2026-07-22 20:27:23,173][50205] Updated weights for policy 0, policy_version 35331 (0.0014) +[2026-07-22 20:27:24,060][50205] Updated weights for policy 0, policy_version 35341 (0.0011) +[2026-07-22 20:27:24,877][43431] Fps is (10 sec: 6348.8, 60 sec: 6007.4, 300 sec: 5741.3). Total num frames: 18098176. Throughput: 0: 5972.9. Samples: 18108246. Policy #0 lag: (min: 3.0, avg: 22.1, max: 36.0) +[2026-07-22 20:27:24,878][43431] Avg episode reward: [(0, '1600.887')] +[2026-07-22 20:27:25,117][50205] Updated weights for policy 0, policy_version 35351 (0.0017) +[2026-07-22 20:27:25,802][50205] Updated weights for policy 0, policy_version 35361 (0.0013) +[2026-07-22 20:27:26,574][50205] Updated weights for policy 0, policy_version 35371 (0.0010) +[2026-07-22 20:27:27,659][50205] Updated weights for policy 0, policy_version 35381 (0.0011) +[2026-07-22 20:27:28,276][50205] Updated weights for policy 0, policy_version 35391 (0.0011) +[2026-07-22 20:27:29,095][50205] Updated weights for policy 0, policy_version 35401 (0.0011) +[2026-07-22 20:27:29,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5973.3, 300 sec: 5748.3). Total num frames: 18126848. Throughput: 0: 5975.5. Samples: 18126438. Policy #0 lag: (min: 3.0, avg: 22.1, max: 36.0) +[2026-07-22 20:27:29,878][43431] Avg episode reward: [(0, '1837.771')] +[2026-07-22 20:27:30,174][50205] Updated weights for policy 0, policy_version 35411 (0.0011) +[2026-07-22 20:27:31,092][50205] Updated weights for policy 0, policy_version 35421 (0.0012) +[2026-07-22 20:27:31,721][50205] Updated weights for policy 0, policy_version 35433 (0.0011) +[2026-07-22 20:27:32,919][50205] Updated weights for policy 0, policy_version 35443 (0.0019) +[2026-07-22 20:27:33,777][50205] Updated weights for policy 0, policy_version 35453 (0.0016) +[2026-07-22 20:27:34,177][50205] Updated weights for policy 0, policy_version 35463 (0.0017) +[2026-07-22 20:27:34,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6007.5, 300 sec: 5762.2). Total num frames: 18159616. Throughput: 0: 5966.5. Samples: 18162444. Policy #0 lag: (min: 3.0, avg: 22.1, max: 36.0) +[2026-07-22 20:27:34,878][43431] Avg episode reward: [(0, '1712.998')] +[2026-07-22 20:27:35,472][50205] Updated weights for policy 0, policy_version 35473 (0.0012) +[2026-07-22 20:27:36,280][50205] Updated weights for policy 0, policy_version 35483 (0.0011) +[2026-07-22 20:27:37,007][50205] Updated weights for policy 0, policy_version 35493 (0.0018) +[2026-07-22 20:27:37,803][50205] Updated weights for policy 0, policy_version 35503 (0.0011) +[2026-07-22 20:27:38,777][50205] Updated weights for policy 0, policy_version 35513 (0.0011) +[2026-07-22 20:27:39,493][50205] Updated weights for policy 0, policy_version 35523 (0.0014) +[2026-07-22 20:27:39,877][43431] Fps is (10 sec: 6143.9, 60 sec: 5973.3, 300 sec: 5769.1). Total num frames: 18188288. Throughput: 0: 5969.4. Samples: 18198840. Policy #0 lag: (min: 3.0, avg: 22.1, max: 36.0) +[2026-07-22 20:27:39,878][43431] Avg episode reward: [(0, '1756.316')] +[2026-07-22 20:27:40,447][50205] Updated weights for policy 0, policy_version 35533 (0.0015) +[2026-07-22 20:27:41,176][50205] Updated weights for policy 0, policy_version 35543 (0.0017) +[2026-07-22 20:27:42,052][50205] Updated weights for policy 0, policy_version 35553 (0.0011) +[2026-07-22 20:27:43,168][50205] Updated weights for policy 0, policy_version 35563 (0.0016) +[2026-07-22 20:27:43,922][50205] Updated weights for policy 0, policy_version 35575 (0.0016) +[2026-07-22 20:27:44,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6007.5, 300 sec: 5783.0). Total num frames: 18219008. Throughput: 0: 5963.6. Samples: 18216940. Policy #0 lag: (min: 3.0, avg: 18.4, max: 35.0) +[2026-07-22 20:27:44,878][43431] Avg episode reward: [(0, '1677.481')] +[2026-07-22 20:27:45,191][50205] Updated weights for policy 0, policy_version 35585 (0.0011) +[2026-07-22 20:27:45,842][50205] Updated weights for policy 0, policy_version 35596 (0.0010) +[2026-07-22 20:27:46,713][50205] Updated weights for policy 0, policy_version 35606 (0.0024) +[2026-07-22 20:27:47,301][50205] Updated weights for policy 0, policy_version 35616 (0.0011) +[2026-07-22 20:27:48,331][50205] Updated weights for policy 0, policy_version 35626 (0.0011) +[2026-07-22 20:27:49,231][50205] Updated weights for policy 0, policy_version 35636 (0.0013) +[2026-07-22 20:27:49,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6007.4, 300 sec: 5790.0). Total num frames: 18249728. Throughput: 0: 5969.0. Samples: 18253042. Policy #0 lag: (min: 3.0, avg: 18.4, max: 35.0) +[2026-07-22 20:27:49,878][43431] Avg episode reward: [(0, '1783.761')] +[2026-07-22 20:27:50,027][50205] Updated weights for policy 0, policy_version 35646 (0.0016) +[2026-07-22 20:27:50,772][50205] Updated weights for policy 0, policy_version 35656 (0.0011) +[2026-07-22 20:27:51,942][50205] Updated weights for policy 0, policy_version 35666 (0.0012) +[2026-07-22 20:27:52,552][50205] Updated weights for policy 0, policy_version 35677 (0.0011) +[2026-07-22 20:27:53,455][50205] Updated weights for policy 0, policy_version 35687 (0.0012) +[2026-07-22 20:27:54,525][50205] Updated weights for policy 0, policy_version 35697 (0.0016) +[2026-07-22 20:27:54,877][43431] Fps is (10 sec: 6144.1, 60 sec: 5973.3, 300 sec: 5796.9). Total num frames: 18280448. Throughput: 0: 6026.7. Samples: 18289386. Policy #0 lag: (min: 3.0, avg: 18.4, max: 35.0) +[2026-07-22 20:27:54,878][43431] Avg episode reward: [(0, '1622.249')] +[2026-07-22 20:27:54,931][50205] Updated weights for policy 0, policy_version 35707 (0.0011) +[2026-07-22 20:27:55,982][50205] Updated weights for policy 0, policy_version 35717 (0.0011) +[2026-07-22 20:27:57,000][50205] Updated weights for policy 0, policy_version 35727 (0.0011) +[2026-07-22 20:27:57,691][50205] Updated weights for policy 0, policy_version 35737 (0.0016) +[2026-07-22 20:27:58,392][50205] Updated weights for policy 0, policy_version 35747 (0.0011) +[2026-07-22 20:27:59,592][50205] Updated weights for policy 0, policy_version 35757 (0.0011) +[2026-07-22 20:27:59,877][43431] Fps is (10 sec: 5939.4, 60 sec: 5973.3, 300 sec: 5796.9). Total num frames: 18309120. Throughput: 0: 6029.6. Samples: 18307666. Policy #0 lag: (min: 3.0, avg: 18.4, max: 35.0) +[2026-07-22 20:27:59,878][43431] Avg episode reward: [(0, '1874.780')] +[2026-07-22 20:28:00,070][50205] Updated weights for policy 0, policy_version 35767 (0.0013) +[2026-07-22 20:28:01,122][50205] Updated weights for policy 0, policy_version 35777 (0.0012) +[2026-07-22 20:28:01,840][50205] Updated weights for policy 0, policy_version 35787 (0.0014) +[2026-07-22 20:28:02,727][50205] Updated weights for policy 0, policy_version 35797 (0.0016) +[2026-07-22 20:28:03,486][50205] Updated weights for policy 0, policy_version 35807 (0.0018) +[2026-07-22 20:28:04,606][50205] Updated weights for policy 0, policy_version 35820 (0.0023) +[2026-07-22 20:28:04,877][43431] Fps is (10 sec: 5939.1, 60 sec: 5973.3, 300 sec: 5817.7). Total num frames: 18339840. Throughput: 0: 6050.9. Samples: 18344408. Policy #0 lag: (min: 3.0, avg: 19.7, max: 43.0) +[2026-07-22 20:28:04,878][43431] Avg episode reward: [(0, '1798.538')] +[2026-07-22 20:28:05,482][50205] Updated weights for policy 0, policy_version 35830 (0.0011) +[2026-07-22 20:28:06,256][50205] Updated weights for policy 0, policy_version 35840 (0.0020) +[2026-07-22 20:28:07,300][50205] Updated weights for policy 0, policy_version 35850 (0.0010) +[2026-07-22 20:28:08,028][50205] Updated weights for policy 0, policy_version 35860 (0.0011) +[2026-07-22 20:28:08,859][50205] Updated weights for policy 0, policy_version 35870 (0.0011) +[2026-07-22 20:28:09,741][50205] Updated weights for policy 0, policy_version 35880 (0.0011) +[2026-07-22 20:28:09,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 5824.7). Total num frames: 18370560. Throughput: 0: 6050.3. Samples: 18380506. Policy #0 lag: (min: 3.0, avg: 19.7, max: 43.0) +[2026-07-22 20:28:09,878][43431] Avg episode reward: [(0, '1750.893')] +[2026-07-22 20:28:10,667][50205] Updated weights for policy 0, policy_version 35890 (0.0014) +[2026-07-22 20:28:11,364][50205] Updated weights for policy 0, policy_version 35900 (0.0013) +[2026-07-22 20:28:12,311][50205] Updated weights for policy 0, policy_version 35910 (0.0015) +[2026-07-22 20:28:13,097][50205] Updated weights for policy 0, policy_version 35920 (0.0014) +[2026-07-22 20:28:13,904][50205] Updated weights for policy 0, policy_version 35930 (0.0011) +[2026-07-22 20:28:14,874][50205] Updated weights for policy 0, policy_version 35940 (0.0013) +[2026-07-22 20:28:14,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6109.9, 300 sec: 5831.6). Total num frames: 18401280. Throughput: 0: 6053.3. Samples: 18398836. Policy #0 lag: (min: 3.0, avg: 19.7, max: 43.0) +[2026-07-22 20:28:14,878][43431] Avg episode reward: [(0, '1706.787')] +[2026-07-22 20:28:15,684][50205] Updated weights for policy 0, policy_version 35950 (0.0012) +[2026-07-22 20:28:16,267][50205] Updated weights for policy 0, policy_version 35960 (0.0020) +[2026-07-22 20:28:17,512][50205] Updated weights for policy 0, policy_version 35970 (0.0011) +[2026-07-22 20:28:18,292][50205] Updated weights for policy 0, policy_version 35980 (0.0011) +[2026-07-22 20:28:19,014][50205] Updated weights for policy 0, policy_version 35990 (0.0016) +[2026-07-22 20:28:19,722][50205] Updated weights for policy 0, policy_version 36000 (0.0011) +[2026-07-22 20:28:19,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6075.7, 300 sec: 5845.5). Total num frames: 18432000. Throughput: 0: 6058.8. Samples: 18435088. Policy #0 lag: (min: 3.0, avg: 19.7, max: 43.0) +[2026-07-22 20:28:19,878][43431] Avg episode reward: [(0, '1694.108')] +[2026-07-22 20:28:20,845][50205] Updated weights for policy 0, policy_version 36010 (0.0011) +[2026-07-22 20:28:21,468][50205] Updated weights for policy 0, policy_version 36020 (0.0016) +[2026-07-22 20:28:22,526][50205] Updated weights for policy 0, policy_version 36030 (0.0012) +[2026-07-22 20:28:23,084][50205] Updated weights for policy 0, policy_version 36040 (0.0024) +[2026-07-22 20:28:24,146][50205] Updated weights for policy 0, policy_version 36050 (0.0011) +[2026-07-22 20:28:24,553][50205] Updated weights for policy 0, policy_version 36060 (0.0011) +[2026-07-22 20:28:24,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6075.8, 300 sec: 5859.4). Total num frames: 18462720. Throughput: 0: 6062.2. Samples: 18471636. Policy #0 lag: (min: 3.0, avg: 19.7, max: 43.0) +[2026-07-22 20:28:24,878][43431] Avg episode reward: [(0, '1679.424')] +[2026-07-22 20:28:25,689][50205] Updated weights for policy 0, policy_version 36070 (0.0016) +[2026-07-22 20:28:26,477][50205] Updated weights for policy 0, policy_version 36080 (0.0011) +[2026-07-22 20:28:27,227][50205] Updated weights for policy 0, policy_version 36090 (0.0011) +[2026-07-22 20:28:28,219][50205] Updated weights for policy 0, policy_version 36100 (0.0011) +[2026-07-22 20:28:29,081][50205] Updated weights for policy 0, policy_version 36110 (0.0015) +[2026-07-22 20:28:29,757][50205] Updated weights for policy 0, policy_version 36120 (0.0012) +[2026-07-22 20:28:29,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6109.9, 300 sec: 5866.3). Total num frames: 18493440. Throughput: 0: 6068.5. Samples: 18490022. Policy #0 lag: (min: 3.0, avg: 16.7, max: 35.0) +[2026-07-22 20:28:29,878][43431] Avg episode reward: [(0, '1686.966')] +[2026-07-22 20:28:30,771][50205] Updated weights for policy 0, policy_version 36130 (0.0013) +[2026-07-22 20:28:31,565][50205] Updated weights for policy 0, policy_version 36140 (0.0011) +[2026-07-22 20:28:32,502][50205] Updated weights for policy 0, policy_version 36150 (0.0015) +[2026-07-22 20:28:33,268][50205] Updated weights for policy 0, policy_version 36160 (0.0011) +[2026-07-22 20:28:34,097][50205] Updated weights for policy 0, policy_version 36170 (0.0011) +[2026-07-22 20:28:34,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 5866.3). Total num frames: 18522112. Throughput: 0: 6071.5. Samples: 18526256. Policy #0 lag: (min: 3.0, avg: 16.7, max: 35.0) +[2026-07-22 20:28:34,878][43431] Avg episode reward: [(0, '1749.558')] +[2026-07-22 20:28:35,095][50205] Updated weights for policy 0, policy_version 36180 (0.0011) +[2026-07-22 20:28:35,803][50205] Updated weights for policy 0, policy_version 36190 (0.0016) +[2026-07-22 20:28:36,731][50205] Updated weights for policy 0, policy_version 36200 (0.0012) +[2026-07-22 20:28:37,689][50205] Updated weights for policy 0, policy_version 36211 (0.0013) +[2026-07-22 20:28:38,405][50205] Updated weights for policy 0, policy_version 36221 (0.0011) +[2026-07-22 20:28:39,663][50205] Updated weights for policy 0, policy_version 36233 (0.0013) +[2026-07-22 20:28:39,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6075.7, 300 sec: 5873.2). Total num frames: 18552832. Throughput: 0: 6067.6. Samples: 18562430. Policy #0 lag: (min: 3.0, avg: 16.7, max: 35.0) +[2026-07-22 20:28:39,878][43431] Avg episode reward: [(0, '1911.358')] +[2026-07-22 20:28:40,402][50205] Updated weights for policy 0, policy_version 36243 (0.0011) +[2026-07-22 20:28:41,179][50205] Updated weights for policy 0, policy_version 36253 (0.0012) +[2026-07-22 20:28:42,166][50205] Updated weights for policy 0, policy_version 36263 (0.0011) +[2026-07-22 20:28:43,027][50205] Updated weights for policy 0, policy_version 36273 (0.0011) +[2026-07-22 20:28:43,603][50205] Updated weights for policy 0, policy_version 36283 (0.0014) +[2026-07-22 20:28:44,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 5873.2). Total num frames: 18581504. Throughput: 0: 6066.0. Samples: 18580638. Policy #0 lag: (min: 3.0, avg: 16.7, max: 35.0) +[2026-07-22 20:28:44,878][43431] Avg episode reward: [(0, '1609.977')] +[2026-07-22 20:28:45,092][50205] Updated weights for policy 0, policy_version 36293 (0.0011) +[2026-07-22 20:28:45,643][50205] Updated weights for policy 0, policy_version 36304 (0.0016) +[2026-07-22 20:28:46,416][50205] Updated weights for policy 0, policy_version 36314 (0.0015) +[2026-07-22 20:28:47,210][50205] Updated weights for policy 0, policy_version 36324 (0.0014) +[2026-07-22 20:28:48,207][50205] Updated weights for policy 0, policy_version 36334 (0.0010) +[2026-07-22 20:28:48,928][50205] Updated weights for policy 0, policy_version 36344 (0.0011) +[2026-07-22 20:28:49,846][50205] Updated weights for policy 0, policy_version 36354 (0.0011) +[2026-07-22 20:28:49,877][43431] Fps is (10 sec: 5939.3, 60 sec: 6041.6, 300 sec: 5880.2). Total num frames: 18612224. Throughput: 0: 6054.7. Samples: 18616868. Policy #0 lag: (min: 3.0, avg: 16.7, max: 35.0) +[2026-07-22 20:28:49,878][43431] Avg episode reward: [(0, '1732.353')] +[2026-07-22 20:28:50,566][50205] Updated weights for policy 0, policy_version 36364 (0.0011) +[2026-07-22 20:28:51,552][50205] Updated weights for policy 0, policy_version 36376 (0.0016) +[2026-07-22 20:28:52,593][50205] Updated weights for policy 0, policy_version 36386 (0.0011) +[2026-07-22 20:28:53,435][50205] Updated weights for policy 0, policy_version 36397 (0.0020) +[2026-07-22 20:28:54,152][50205] Updated weights for policy 0, policy_version 36407 (0.0012) +[2026-07-22 20:28:54,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6041.6, 300 sec: 5901.0). Total num frames: 18642944. Throughput: 0: 6060.0. Samples: 18653206. Policy #0 lag: (min: 3.0, avg: 17.5, max: 35.0) +[2026-07-22 20:28:54,878][43431] Avg episode reward: [(0, '1651.424')] +[2026-07-22 20:28:55,189][50205] Updated weights for policy 0, policy_version 36417 (0.0014) +[2026-07-22 20:28:55,927][50205] Updated weights for policy 0, policy_version 36427 (0.0019) +[2026-07-22 20:28:56,801][50205] Updated weights for policy 0, policy_version 36437 (0.0012) +[2026-07-22 20:28:57,681][50205] Updated weights for policy 0, policy_version 36447 (0.0011) +[2026-07-22 20:28:58,519][50205] Updated weights for policy 0, policy_version 36457 (0.0013) +[2026-07-22 20:28:59,178][50205] Updated weights for policy 0, policy_version 36467 (0.0012) +[2026-07-22 20:28:59,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6075.7, 300 sec: 5908.0). Total num frames: 18673664. Throughput: 0: 6053.7. Samples: 18671250. Policy #0 lag: (min: 3.0, avg: 17.5, max: 35.0) +[2026-07-22 20:28:59,878][43431] Avg episode reward: [(0, '1743.076')] +[2026-07-22 20:29:00,352][50205] Updated weights for policy 0, policy_version 36477 (0.0011) +[2026-07-22 20:29:01,015][50205] Updated weights for policy 0, policy_version 36487 (0.0014) +[2026-07-22 20:29:02,295][50205] Updated weights for policy 0, policy_version 36500 (0.0016) +[2026-07-22 20:29:03,617][50205] Updated weights for policy 0, policy_version 36510 (0.0016) +[2026-07-22 20:29:04,323][49527] Signal inference workers to stop experience collection... (650 times) +[2026-07-22 20:29:04,343][50205] InferenceWorker_p0-w0: stopping experience collection (650 times) +[2026-07-22 20:29:04,360][49527] Signal inference workers to resume experience collection... (650 times) +[2026-07-22 20:29:04,360][50205] InferenceWorker_p0-w0: resuming experience collection (650 times) +[2026-07-22 20:29:04,362][50205] Updated weights for policy 0, policy_version 36520 (0.0020) +[2026-07-22 20:29:04,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 5908.0). Total num frames: 18702336. Throughput: 0: 5999.5. Samples: 18705064. Policy #0 lag: (min: 3.0, avg: 17.5, max: 35.0) +[2026-07-22 20:29:04,878][43431] Avg episode reward: [(0, '1740.032')] +[2026-07-22 20:29:04,971][50205] Updated weights for policy 0, policy_version 36530 (0.0012) +[2026-07-22 20:29:05,859][50205] Updated weights for policy 0, policy_version 36540 (0.0016) +[2026-07-22 20:29:06,942][50205] Updated weights for policy 0, policy_version 36551 (0.0011) +[2026-07-22 20:29:07,662][50205] Updated weights for policy 0, policy_version 36561 (0.0011) +[2026-07-22 20:29:08,624][50205] Updated weights for policy 0, policy_version 36571 (0.0011) +[2026-07-22 20:29:09,510][50205] Updated weights for policy 0, policy_version 36581 (0.0016) +[2026-07-22 20:29:09,879][43431] Fps is (10 sec: 5938.2, 60 sec: 6041.4, 300 sec: 5914.9). Total num frames: 18733056. Throughput: 0: 5993.7. Samples: 18741362. Policy #0 lag: (min: 3.0, avg: 17.5, max: 35.0) +[2026-07-22 20:29:09,880][43431] Avg episode reward: [(0, '1834.328')] +[2026-07-22 20:29:10,141][50205] Updated weights for policy 0, policy_version 36591 (0.0021) +[2026-07-22 20:29:11,372][50205] Updated weights for policy 0, policy_version 36601 (0.0011) +[2026-07-22 20:29:11,968][50205] Updated weights for policy 0, policy_version 36611 (0.0011) +[2026-07-22 20:29:12,606][50205] Updated weights for policy 0, policy_version 36621 (0.0016) +[2026-07-22 20:29:13,724][50205] Updated weights for policy 0, policy_version 36631 (0.0011) +[2026-07-22 20:29:14,672][50205] Updated weights for policy 0, policy_version 36641 (0.0020) +[2026-07-22 20:29:14,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 5928.8). Total num frames: 18763776. Throughput: 0: 5991.8. Samples: 18759654. Policy #0 lag: (min: 3.0, avg: 17.5, max: 35.0) +[2026-07-22 20:29:14,878][43431] Avg episode reward: [(0, '1727.454')] +[2026-07-22 20:29:15,105][50205] Updated weights for policy 0, policy_version 36651 (0.0011) +[2026-07-22 20:29:16,323][50205] Updated weights for policy 0, policy_version 36661 (0.0012) +[2026-07-22 20:29:17,195][50205] Updated weights for policy 0, policy_version 36671 (0.0016) +[2026-07-22 20:29:17,783][50205] Updated weights for policy 0, policy_version 36681 (0.0020) +[2026-07-22 20:29:18,388][50205] Updated weights for policy 0, policy_version 36691 (0.0011) +[2026-07-22 20:29:19,776][50205] Updated weights for policy 0, policy_version 36701 (0.0016) +[2026-07-22 20:29:19,877][43431] Fps is (10 sec: 5940.2, 60 sec: 6007.5, 300 sec: 5928.8). Total num frames: 18792448. Throughput: 0: 5997.0. Samples: 18796122. Policy #0 lag: (min: 5.0, avg: 24.2, max: 48.0) +[2026-07-22 20:29:19,878][43431] Avg episode reward: [(0, '1885.046')] +[2026-07-22 20:29:20,285][50205] Updated weights for policy 0, policy_version 36711 (0.0012) +[2026-07-22 20:29:21,391][50205] Updated weights for policy 0, policy_version 36721 (0.0011) +[2026-07-22 20:29:22,076][50205] Updated weights for policy 0, policy_version 36731 (0.0018) +[2026-07-22 20:29:22,912][50205] Updated weights for policy 0, policy_version 36743 (0.0015) +[2026-07-22 20:29:24,132][50205] Updated weights for policy 0, policy_version 36753 (0.0011) +[2026-07-22 20:29:24,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5973.3, 300 sec: 5935.7). Total num frames: 18821120. Throughput: 0: 6006.1. Samples: 18832704. Policy #0 lag: (min: 5.0, avg: 24.2, max: 48.0) +[2026-07-22 20:29:24,878][43431] Avg episode reward: [(0, '1844.207')] +[2026-07-22 20:29:24,913][50205] Updated weights for policy 0, policy_version 36763 (0.0012) +[2026-07-22 20:29:25,543][50205] Updated weights for policy 0, policy_version 36773 (0.0011) +[2026-07-22 20:29:26,086][50205] Updated weights for policy 0, policy_version 36783 (0.0020) +[2026-07-22 20:29:27,675][50205] Updated weights for policy 0, policy_version 36793 (0.0028) +[2026-07-22 20:29:28,156][50205] Updated weights for policy 0, policy_version 36803 (0.0011) +[2026-07-22 20:29:28,882][50205] Updated weights for policy 0, policy_version 36813 (0.0011) +[2026-07-22 20:29:29,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5973.3, 300 sec: 5942.7). Total num frames: 18851840. Throughput: 0: 6005.2. Samples: 18850870. Policy #0 lag: (min: 5.0, avg: 24.2, max: 48.0) +[2026-07-22 20:29:29,878][43431] Avg episode reward: [(0, '1811.599')] +[2026-07-22 20:29:29,905][50205] Updated weights for policy 0, policy_version 36823 (0.0016) +[2026-07-22 20:29:30,649][50205] Updated weights for policy 0, policy_version 36834 (0.0012) +[2026-07-22 20:29:31,117][50205] Updated weights for policy 0, policy_version 36844 (0.0015) +[2026-07-22 20:29:32,674][50205] Updated weights for policy 0, policy_version 36854 (0.0012) +[2026-07-22 20:29:33,133][50205] Updated weights for policy 0, policy_version 36864 (0.0011) +[2026-07-22 20:29:33,737][50205] Updated weights for policy 0, policy_version 36874 (0.0013) +[2026-07-22 20:29:34,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 5949.6). Total num frames: 18882560. Throughput: 0: 6010.6. Samples: 18887346. Policy #0 lag: (min: 5.0, avg: 24.2, max: 48.0) +[2026-07-22 20:29:34,878][43431] Avg episode reward: [(0, '1777.124')] +[2026-07-22 20:29:35,275][50205] Updated weights for policy 0, policy_version 36884 (0.0012) +[2026-07-22 20:29:35,816][50205] Updated weights for policy 0, policy_version 36894 (0.0011) +[2026-07-22 20:29:36,130][50205] Updated weights for policy 0, policy_version 36904 (0.0022) +[2026-07-22 20:29:37,894][50205] Updated weights for policy 0, policy_version 36914 (0.0018) +[2026-07-22 20:29:38,440][50205] Updated weights for policy 0, policy_version 36924 (0.0015) +[2026-07-22 20:29:38,824][50205] Updated weights for policy 0, policy_version 36936 (0.0011) +[2026-07-22 20:29:39,877][43431] Fps is (10 sec: 6348.7, 60 sec: 6041.6, 300 sec: 5963.5). Total num frames: 18915328. Throughput: 0: 6010.3. Samples: 18923668. Policy #0 lag: (min: 3.0, avg: 22.0, max: 51.0) +[2026-07-22 20:29:39,878][43431] Avg episode reward: [(0, '1690.003')] +[2026-07-22 20:29:40,544][50205] Updated weights for policy 0, policy_version 36946 (0.0026) +[2026-07-22 20:29:41,075][50205] Updated weights for policy 0, policy_version 36956 (0.0011) +[2026-07-22 20:29:41,622][50205] Updated weights for policy 0, policy_version 36966 (0.0012) +[2026-07-22 20:29:42,591][50205] Updated weights for policy 0, policy_version 36976 (0.0011) +[2026-07-22 20:29:43,626][50205] Updated weights for policy 0, policy_version 36986 (0.0011) +[2026-07-22 20:29:44,049][50205] Updated weights for policy 0, policy_version 36996 (0.0021) +[2026-07-22 20:29:44,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 5963.5). Total num frames: 18944000. Throughput: 0: 6012.4. Samples: 18941806. Policy #0 lag: (min: 3.0, avg: 22.0, max: 51.0) +[2026-07-22 20:29:44,878][43431] Avg episode reward: [(0, '1758.202')] +[2026-07-22 20:29:45,627][50205] Updated weights for policy 0, policy_version 37006 (0.0011) +[2026-07-22 20:29:46,194][50205] Updated weights for policy 0, policy_version 37016 (0.0016) +[2026-07-22 20:29:46,695][50205] Updated weights for policy 0, policy_version 37026 (0.0018) +[2026-07-22 20:29:47,526][50205] Updated weights for policy 0, policy_version 37036 (0.0012) +[2026-07-22 20:29:48,781][50205] Updated weights for policy 0, policy_version 37048 (0.0012) +[2026-07-22 20:29:49,509][50205] Updated weights for policy 0, policy_version 37058 (0.0014) +[2026-07-22 20:29:49,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6075.7, 300 sec: 5984.3). Total num frames: 18976768. Throughput: 0: 6069.1. Samples: 18978172. Policy #0 lag: (min: 3.0, avg: 22.0, max: 51.0) +[2026-07-22 20:29:49,878][43431] Avg episode reward: [(0, '1561.404')] +[2026-07-22 20:29:50,305][50205] Updated weights for policy 0, policy_version 37068 (0.0014) +[2026-07-22 20:29:51,393][50205] Updated weights for policy 0, policy_version 37078 (0.0014) +[2026-07-22 20:29:51,964][50205] Updated weights for policy 0, policy_version 37088 (0.0016) +[2026-07-22 20:29:53,011][50205] Updated weights for policy 0, policy_version 37098 (0.0016) +[2026-07-22 20:29:53,856][50205] Updated weights for policy 0, policy_version 37108 (0.0021) +[2026-07-22 20:29:54,579][50205] Updated weights for policy 0, policy_version 37118 (0.0017) +[2026-07-22 20:29:54,877][43431] Fps is (10 sec: 6348.7, 60 sec: 6075.7, 300 sec: 5991.3). Total num frames: 19007488. Throughput: 0: 6073.3. Samples: 19014652. Policy #0 lag: (min: 3.0, avg: 22.0, max: 51.0) +[2026-07-22 20:29:54,878][43431] Avg episode reward: [(0, '1850.349')] +[2026-07-22 20:29:55,483][50205] Updated weights for policy 0, policy_version 37128 (0.0011) +[2026-07-22 20:29:56,484][50205] Updated weights for policy 0, policy_version 37138 (0.0011) +[2026-07-22 20:29:57,130][50205] Updated weights for policy 0, policy_version 37149 (0.0011) +[2026-07-22 20:29:58,105][50205] Updated weights for policy 0, policy_version 37159 (0.0011) +[2026-07-22 20:29:59,328][50205] Updated weights for policy 0, policy_version 37169 (0.0011) +[2026-07-22 20:29:59,661][50205] Updated weights for policy 0, policy_version 37179 (0.0011) +[2026-07-22 20:29:59,878][43431] Fps is (10 sec: 5939.0, 60 sec: 6041.6, 300 sec: 5991.3). Total num frames: 19036160. Throughput: 0: 6067.5. Samples: 19032694. Policy #0 lag: (min: 3.0, avg: 22.0, max: 51.0) +[2026-07-22 20:29:59,878][43431] Avg episode reward: [(0, '1669.285')] +[2026-07-22 20:30:00,793][50205] Updated weights for policy 0, policy_version 37189 (0.0012) +[2026-07-22 20:30:01,630][50205] Updated weights for policy 0, policy_version 37199 (0.0023) +[2026-07-22 20:30:02,385][50205] Updated weights for policy 0, policy_version 37209 (0.0016) +[2026-07-22 20:30:03,769][50205] Updated weights for policy 0, policy_version 37222 (0.0011) +[2026-07-22 20:30:04,455][50205] Updated weights for policy 0, policy_version 37232 (0.0011) +[2026-07-22 20:30:04,878][43431] Fps is (10 sec: 5734.2, 60 sec: 6041.6, 300 sec: 5998.2). Total num frames: 19064832. Throughput: 0: 6048.4. Samples: 19068302. Policy #0 lag: (min: 3.0, avg: 20.6, max: 39.0) +[2026-07-22 20:30:04,878][43431] Avg episode reward: [(0, '1867.731')] +[2026-07-22 20:30:05,184][50205] Updated weights for policy 0, policy_version 37242 (0.0016) +[2026-07-22 20:30:06,111][50205] Updated weights for policy 0, policy_version 37252 (0.0011) +[2026-07-22 20:30:07,158][50205] Updated weights for policy 0, policy_version 37262 (0.0016) +[2026-07-22 20:30:07,716][50205] Updated weights for policy 0, policy_version 37272 (0.0016) +[2026-07-22 20:30:08,637][50205] Updated weights for policy 0, policy_version 37282 (0.0012) +[2026-07-22 20:30:09,683][50205] Updated weights for policy 0, policy_version 37292 (0.0026) +[2026-07-22 20:30:09,877][43431] Fps is (10 sec: 5734.6, 60 sec: 6007.6, 300 sec: 5998.2). Total num frames: 19093504. Throughput: 0: 6038.2. Samples: 19104424. Policy #0 lag: (min: 3.0, avg: 20.6, max: 39.0) +[2026-07-22 20:30:09,878][43431] Avg episode reward: [(0, '1749.634')] +[2026-07-22 20:30:10,457][50205] Updated weights for policy 0, policy_version 37302 (0.0016) +[2026-07-22 20:30:10,999][50205] Updated weights for policy 0, policy_version 37312 (0.0011) +[2026-07-22 20:30:12,199][50205] Updated weights for policy 0, policy_version 37322 (0.0012) +[2026-07-22 20:30:12,888][50205] Updated weights for policy 0, policy_version 37332 (0.0012) +[2026-07-22 20:30:13,903][50205] Updated weights for policy 0, policy_version 37342 (0.0011) +[2026-07-22 20:30:14,504][50205] Updated weights for policy 0, policy_version 37352 (0.0011) +[2026-07-22 20:30:14,877][43431] Fps is (10 sec: 5939.4, 60 sec: 6007.5, 300 sec: 6012.1). Total num frames: 19124224. Throughput: 0: 6037.3. Samples: 19122548. Policy #0 lag: (min: 3.0, avg: 20.6, max: 39.0) +[2026-07-22 20:30:14,878][43431] Avg episode reward: [(0, '1471.939')] +[2026-07-22 20:30:15,503][50205] Updated weights for policy 0, policy_version 37364 (0.0011) +[2026-07-22 20:30:16,671][50205] Updated weights for policy 0, policy_version 37374 (0.0030) +[2026-07-22 20:30:17,440][50205] Updated weights for policy 0, policy_version 37384 (0.0011) +[2026-07-22 20:30:18,235][50205] Updated weights for policy 0, policy_version 37394 (0.0011) +[2026-07-22 20:30:18,824][50205] Updated weights for policy 0, policy_version 37404 (0.0012) +[2026-07-22 20:30:19,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 6019.0). Total num frames: 19154944. Throughput: 0: 6029.9. Samples: 19158692. Policy #0 lag: (min: 3.0, avg: 20.6, max: 39.0) +[2026-07-22 20:30:19,878][43431] Avg episode reward: [(0, '1700.687')] +[2026-07-22 20:30:19,959][50205] Updated weights for policy 0, policy_version 37414 (0.0010) +[2026-07-22 20:30:20,620][50205] Updated weights for policy 0, policy_version 37424 (0.0011) +[2026-07-22 20:30:21,595][50205] Updated weights for policy 0, policy_version 37434 (0.0016) +[2026-07-22 20:30:22,425][50205] Updated weights for policy 0, policy_version 37444 (0.0012) +[2026-07-22 20:30:23,359][50205] Updated weights for policy 0, policy_version 37454 (0.0015) +[2026-07-22 20:30:24,171][50205] Updated weights for policy 0, policy_version 37464 (0.0011) +[2026-07-22 20:30:24,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6075.7, 300 sec: 6019.0). Total num frames: 19185664. Throughput: 0: 6033.9. Samples: 19195192. Policy #0 lag: (min: 3.0, avg: 20.6, max: 39.0) +[2026-07-22 20:30:24,878][43431] Avg episode reward: [(0, '1797.526')] +[2026-07-22 20:30:24,977][50205] Updated weights for policy 0, policy_version 37474 (0.0016) +[2026-07-22 20:30:25,448][50205] Updated weights for policy 0, policy_version 37484 (0.0011) +[2026-07-22 20:30:26,712][50205] Updated weights for policy 0, policy_version 37494 (0.0016) +[2026-07-22 20:30:27,602][50205] Updated weights for policy 0, policy_version 37504 (0.0016) +[2026-07-22 20:30:28,048][50205] Updated weights for policy 0, policy_version 37514 (0.0016) +[2026-07-22 20:30:28,996][50205] Updated weights for policy 0, policy_version 37524 (0.0012) +[2026-07-22 20:30:29,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 19214336. Throughput: 0: 6037.5. Samples: 19213496. Policy #0 lag: (min: 3.0, avg: 19.7, max: 39.0) +[2026-07-22 20:30:29,878][43431] Avg episode reward: [(0, '1683.452')] +[2026-07-22 20:30:30,228][50205] Updated weights for policy 0, policy_version 37534 (0.0011) +[2026-07-22 20:30:30,698][50205] Updated weights for policy 0, policy_version 37544 (0.0011) +[2026-07-22 20:30:31,722][50205] Updated weights for policy 0, policy_version 37554 (0.0016) +[2026-07-22 20:30:32,754][50205] Updated weights for policy 0, policy_version 37564 (0.0012) +[2026-07-22 20:30:33,245][50205] Updated weights for policy 0, policy_version 37574 (0.0011) +[2026-07-22 20:30:34,371][50205] Updated weights for policy 0, policy_version 37584 (0.0016) +[2026-07-22 20:30:34,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6075.7, 300 sec: 6032.9). Total num frames: 19247104. Throughput: 0: 6037.1. Samples: 19249842. Policy #0 lag: (min: 3.0, avg: 19.7, max: 39.0) +[2026-07-22 20:30:34,878][43431] Avg episode reward: [(0, '1681.330')] +[2026-07-22 20:30:35,227][50205] Updated weights for policy 0, policy_version 37594 (0.0016) +[2026-07-22 20:30:35,626][50205] Updated weights for policy 0, policy_version 37604 (0.0013) +[2026-07-22 20:30:36,939][50205] Updated weights for policy 0, policy_version 37614 (0.0015) +[2026-07-22 20:30:37,923][50205] Updated weights for policy 0, policy_version 37624 (0.0016) +[2026-07-22 20:30:38,368][50205] Updated weights for policy 0, policy_version 37634 (0.0011) +[2026-07-22 20:30:38,896][50205] Updated weights for policy 0, policy_version 37644 (0.0016) +[2026-07-22 20:30:39,877][43431] Fps is (10 sec: 6144.2, 60 sec: 6007.5, 300 sec: 6039.9). Total num frames: 19275776. Throughput: 0: 6035.6. Samples: 19286252. Policy #0 lag: (min: 3.0, avg: 19.7, max: 39.0) +[2026-07-22 20:30:39,878][43431] Avg episode reward: [(0, '1727.226')] +[2026-07-22 20:30:40,420][50205] Updated weights for policy 0, policy_version 37654 (0.0019) +[2026-07-22 20:30:40,931][50205] Updated weights for policy 0, policy_version 37664 (0.0010) +[2026-07-22 20:30:41,943][50205] Updated weights for policy 0, policy_version 37674 (0.0018) +[2026-07-22 20:30:42,702][50205] Updated weights for policy 0, policy_version 37684 (0.0024) +[2026-07-22 20:30:43,449][50205] Updated weights for policy 0, policy_version 37694 (0.0013) +[2026-07-22 20:30:44,282][50205] Updated weights for policy 0, policy_version 37704 (0.0019) +[2026-07-22 20:30:44,877][43431] Fps is (10 sec: 5939.3, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 19306496. Throughput: 0: 6039.8. Samples: 19304482. Policy #0 lag: (min: 3.0, avg: 19.7, max: 39.0) +[2026-07-22 20:30:44,878][43431] Avg episode reward: [(0, '1839.394')] +[2026-07-22 20:30:45,374][50205] Updated weights for policy 0, policy_version 37714 (0.0015) +[2026-07-22 20:30:46,170][50205] Updated weights for policy 0, policy_version 37725 (0.0016) +[2026-07-22 20:30:46,966][50205] Updated weights for policy 0, policy_version 37735 (0.0012) +[2026-07-22 20:30:48,222][50205] Updated weights for policy 0, policy_version 37745 (0.0016) +[2026-07-22 20:30:48,643][50205] Updated weights for policy 0, policy_version 37755 (0.0011) +[2026-07-22 20:30:49,464][50205] Updated weights for policy 0, policy_version 37765 (0.0013) +[2026-07-22 20:30:49,877][43431] Fps is (10 sec: 6143.8, 60 sec: 6007.4, 300 sec: 6026.0). Total num frames: 19337216. Throughput: 0: 6053.0. Samples: 19340684. Policy #0 lag: (min: 3.0, avg: 19.7, max: 39.0) +[2026-07-22 20:30:49,878][43431] Avg episode reward: [(0, '1590.204')] +[2026-07-22 20:30:50,520][50205] Updated weights for policy 0, policy_version 37775 (0.0011) +[2026-07-22 20:30:51,387][50205] Updated weights for policy 0, policy_version 37785 (0.0011) +[2026-07-22 20:30:51,959][50205] Updated weights for policy 0, policy_version 37795 (0.0015) +[2026-07-22 20:30:53,053][50205] Updated weights for policy 0, policy_version 37805 (0.0011) +[2026-07-22 20:30:53,671][50205] Updated weights for policy 0, policy_version 37815 (0.0014) +[2026-07-22 20:30:54,700][50205] Updated weights for policy 0, policy_version 37825 (0.0017) +[2026-07-22 20:30:54,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6007.5, 300 sec: 6032.9). Total num frames: 19367936. Throughput: 0: 6062.0. Samples: 19377216. Policy #0 lag: (min: 2.0, avg: 18.6, max: 38.0) +[2026-07-22 20:30:54,878][43431] Avg episode reward: [(0, '1915.145')] +[2026-07-22 20:30:55,573][50205] Updated weights for policy 0, policy_version 37835 (0.0022) +[2026-07-22 20:30:56,163][50205] Updated weights for policy 0, policy_version 37845 (0.0016) +[2026-07-22 20:30:57,041][50205] Updated weights for policy 0, policy_version 37855 (0.0011) +[2026-07-22 20:30:58,243][50205] Updated weights for policy 0, policy_version 37865 (0.0015) +[2026-07-22 20:30:58,716][50205] Updated weights for policy 0, policy_version 37875 (0.0011) +[2026-07-22 20:30:59,598][50205] Updated weights for policy 0, policy_version 37885 (0.0010) +[2026-07-22 20:30:59,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 19398656. Throughput: 0: 6069.1. Samples: 19395656. Policy #0 lag: (min: 2.0, avg: 18.6, max: 38.0) +[2026-07-22 20:30:59,878][43431] Avg episode reward: [(0, '1753.136')] +[2026-07-22 20:31:00,487][50205] Updated weights for policy 0, policy_version 37895 (0.0012) +[2026-07-22 20:31:01,264][50205] Updated weights for policy 0, policy_version 37905 (0.0017) +[2026-07-22 20:31:02,142][50205] Updated weights for policy 0, policy_version 37915 (0.0015) +[2026-07-22 20:31:03,359][50205] Updated weights for policy 0, policy_version 37925 (0.0016) +[2026-07-22 20:31:04,160][50205] Updated weights for policy 0, policy_version 37936 (0.0011) +[2026-07-22 20:31:04,877][43431] Fps is (10 sec: 5734.5, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 19425280. Throughput: 0: 6030.9. Samples: 19430082. Policy #0 lag: (min: 2.0, avg: 18.6, max: 38.0) +[2026-07-22 20:31:04,878][43431] Avg episode reward: [(0, '1861.508')] +[2026-07-22 20:31:05,858][50205] Updated weights for policy 0, policy_version 37949 (0.0012) +[2026-07-22 20:31:06,745][50205] Updated weights for policy 0, policy_version 37959 (0.0011) +[2026-07-22 20:31:07,249][50205] Updated weights for policy 0, policy_version 37972 (0.0010) +[2026-07-22 20:31:08,544][50205] Updated weights for policy 0, policy_version 37982 (0.0014) +[2026-07-22 20:31:09,496][50205] Updated weights for policy 0, policy_version 37992 (0.0012) +[2026-07-22 20:31:09,877][43431] Fps is (10 sec: 5734.4, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 19456000. Throughput: 0: 5973.2. Samples: 19463988. Policy #0 lag: (min: 2.0, avg: 18.6, max: 38.0) +[2026-07-22 20:31:09,878][43431] Avg episode reward: [(0, '1691.522')] +[2026-07-22 20:31:10,224][50205] Updated weights for policy 0, policy_version 38004 (0.0013) +[2026-07-22 20:31:11,138][50205] Updated weights for policy 0, policy_version 38014 (0.0011) +[2026-07-22 20:31:12,288][50205] Updated weights for policy 0, policy_version 38025 (0.0013) +[2026-07-22 20:31:13,092][50205] Updated weights for policy 0, policy_version 38035 (0.0016) +[2026-07-22 20:31:14,108][50205] Updated weights for policy 0, policy_version 38047 (0.0011) +[2026-07-22 20:31:14,877][43431] Fps is (10 sec: 5939.3, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 19484672. Throughput: 0: 5969.3. Samples: 19482114. Policy #0 lag: (min: 1.0, avg: 14.8, max: 33.0) +[2026-07-22 20:31:14,878][43431] Avg episode reward: [(0, '1845.103')] +[2026-07-22 20:31:14,901][50205] Updated weights for policy 0, policy_version 38057 (0.0016) +[2026-07-22 20:31:15,805][50205] Updated weights for policy 0, policy_version 38067 (0.0017) +[2026-07-22 20:31:16,903][50205] Updated weights for policy 0, policy_version 38077 (0.0011) +[2026-07-22 20:31:17,422][50205] Updated weights for policy 0, policy_version 38087 (0.0015) +[2026-07-22 20:31:18,376][50205] Updated weights for policy 0, policy_version 38097 (0.0011) +[2026-07-22 20:31:18,869][50205] Updated weights for policy 0, policy_version 38107 (0.0011) +[2026-07-22 20:31:19,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5973.3, 300 sec: 6019.0). Total num frames: 19513344. Throughput: 0: 5965.6. Samples: 19518294. Policy #0 lag: (min: 1.0, avg: 14.8, max: 33.0) +[2026-07-22 20:31:19,878][43431] Avg episode reward: [(0, '1733.406')] +[2026-07-22 20:31:20,076][50205] Updated weights for policy 0, policy_version 38117 (0.0011) +[2026-07-22 20:31:20,646][50205] Updated weights for policy 0, policy_version 38127 (0.0011) +[2026-07-22 20:31:21,503][50205] Updated weights for policy 0, policy_version 38137 (0.0012) +[2026-07-22 20:31:22,490][50205] Updated weights for policy 0, policy_version 38147 (0.0011) +[2026-07-22 20:31:23,521][50205] Updated weights for policy 0, policy_version 38157 (0.0016) +[2026-07-22 20:31:24,152][50205] Updated weights for policy 0, policy_version 38167 (0.0017) +[2026-07-22 20:31:24,877][43431] Fps is (10 sec: 5939.1, 60 sec: 5973.3, 300 sec: 6019.0). Total num frames: 19544064. Throughput: 0: 5970.7. Samples: 19554936. Policy #0 lag: (min: 1.0, avg: 14.8, max: 33.0) +[2026-07-22 20:31:24,878][43431] Avg episode reward: [(0, '1856.433')] +[2026-07-22 20:31:25,079][50205] Updated weights for policy 0, policy_version 38177 (0.0012) +[2026-07-22 20:31:25,685][50205] Updated weights for policy 0, policy_version 38187 (0.0011) +[2026-07-22 20:31:26,847][50205] Updated weights for policy 0, policy_version 38197 (0.0011) +[2026-07-22 20:31:27,594][50205] Updated weights for policy 0, policy_version 38207 (0.0017) +[2026-07-22 20:31:28,417][50205] Updated weights for policy 0, policy_version 38217 (0.0012) +[2026-07-22 20:31:29,231][50205] Updated weights for policy 0, policy_version 38227 (0.0011) +[2026-07-22 20:31:29,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6007.5, 300 sec: 6019.0). Total num frames: 19574784. Throughput: 0: 5968.4. Samples: 19573058. Policy #0 lag: (min: 1.0, avg: 14.8, max: 33.0) +[2026-07-22 20:31:29,878][43431] Avg episode reward: [(0, '1831.144')] +[2026-07-22 20:31:30,280][50205] Updated weights for policy 0, policy_version 38237 (0.0014) +[2026-07-22 20:31:30,923][50205] Updated weights for policy 0, policy_version 38247 (0.0013) +[2026-07-22 20:31:31,825][50205] Updated weights for policy 0, policy_version 38257 (0.0025) +[2026-07-22 20:31:32,662][50205] Updated weights for policy 0, policy_version 38267 (0.0016) +[2026-07-22 20:31:33,642][50205] Updated weights for policy 0, policy_version 38277 (0.0013) +[2026-07-22 20:31:34,287][50205] Updated weights for policy 0, policy_version 38287 (0.0011) +[2026-07-22 20:31:34,877][43431] Fps is (10 sec: 6144.0, 60 sec: 5973.4, 300 sec: 6019.0). Total num frames: 19605504. Throughput: 0: 5974.8. Samples: 19609548. Policy #0 lag: (min: 1.0, avg: 14.8, max: 33.0) +[2026-07-22 20:31:34,878][43431] Avg episode reward: [(0, '1869.591')] +[2026-07-22 20:31:35,231][50205] Updated weights for policy 0, policy_version 38297 (0.0011) +[2026-07-22 20:31:35,723][50205] Updated weights for policy 0, policy_version 38307 (0.0011) +[2026-07-22 20:31:36,958][50205] Updated weights for policy 0, policy_version 38317 (0.0013) +[2026-07-22 20:31:37,676][50205] Updated weights for policy 0, policy_version 38327 (0.0016) +[2026-07-22 20:31:38,500][50205] Updated weights for policy 0, policy_version 38337 (0.0012) +[2026-07-22 20:31:39,299][50205] Updated weights for policy 0, policy_version 38347 (0.0011) +[2026-07-22 20:31:39,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 19636224. Throughput: 0: 5974.9. Samples: 19646084. Policy #0 lag: (min: 0.0, avg: 18.4, max: 36.0) +[2026-07-22 20:31:39,878][43431] Avg episode reward: [(0, '1687.188')] +[2026-07-22 20:31:40,331][50205] Updated weights for policy 0, policy_version 38357 (0.0011) +[2026-07-22 20:31:40,955][50205] Updated weights for policy 0, policy_version 38367 (0.0015) +[2026-07-22 20:31:42,024][50205] Updated weights for policy 0, policy_version 38377 (0.0017) +[2026-07-22 20:31:42,624][50205] Updated weights for policy 0, policy_version 38387 (0.0010) +[2026-07-22 20:31:43,482][50205] Updated weights for policy 0, policy_version 38397 (0.0013) +[2026-07-22 20:31:44,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5939.2, 300 sec: 6012.1). Total num frames: 19662848. Throughput: 0: 5968.9. Samples: 19664256. Policy #0 lag: (min: 0.0, avg: 18.4, max: 36.0) +[2026-07-22 20:31:44,878][43431] Avg episode reward: [(0, '1784.521')] +[2026-07-22 20:31:45,093][50205] Updated weights for policy 0, policy_version 38409 (0.0014) +[2026-07-22 20:31:45,715][50205] Updated weights for policy 0, policy_version 38423 (0.0016) +[2026-07-22 20:31:46,787][50205] Updated weights for policy 0, policy_version 38433 (0.0014) +[2026-07-22 20:31:47,668][50205] Updated weights for policy 0, policy_version 38443 (0.0023) +[2026-07-22 20:31:48,412][50205] Updated weights for policy 0, policy_version 38453 (0.0012) +[2026-07-22 20:31:49,171][50205] Updated weights for policy 0, policy_version 38463 (0.0021) +[2026-07-22 20:31:49,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5973.4, 300 sec: 6012.1). Total num frames: 19695616. Throughput: 0: 6004.1. Samples: 19700264. Policy #0 lag: (min: 0.0, avg: 18.4, max: 36.0) +[2026-07-22 20:31:49,878][43431] Avg episode reward: [(0, '1898.050')] +[2026-07-22 20:31:50,249][50205] Updated weights for policy 0, policy_version 38473 (0.0013) +[2026-07-22 20:31:50,957][50205] Updated weights for policy 0, policy_version 38483 (0.0012) +[2026-07-22 20:31:51,005][49527] Signal inference workers to stop experience collection... (700 times) +[2026-07-22 20:31:51,007][49527] Signal inference workers to resume experience collection... (700 times) +[2026-07-22 20:31:51,023][50205] InferenceWorker_p0-w0: stopping experience collection (700 times) +[2026-07-22 20:31:51,024][50205] InferenceWorker_p0-w0: resuming experience collection (700 times) +[2026-07-22 20:31:51,808][50205] Updated weights for policy 0, policy_version 38493 (0.0012) +[2026-07-22 20:31:52,703][50205] Updated weights for policy 0, policy_version 38503 (0.0016) +[2026-07-22 20:31:53,472][50205] Updated weights for policy 0, policy_version 38513 (0.0011) +[2026-07-22 20:31:54,172][50205] Updated weights for policy 0, policy_version 38523 (0.0011) +[2026-07-22 20:31:54,877][43431] Fps is (10 sec: 6348.8, 60 sec: 5973.3, 300 sec: 6019.0). Total num frames: 19726336. Throughput: 0: 6061.3. Samples: 19736746. Policy #0 lag: (min: 0.0, avg: 18.4, max: 36.0) +[2026-07-22 20:31:54,878][43431] Avg episode reward: [(0, '1855.403')] +[2026-07-22 20:31:55,277][50205] Updated weights for policy 0, policy_version 38533 (0.0011) +[2026-07-22 20:31:55,990][50205] Updated weights for policy 0, policy_version 38543 (0.0013) +[2026-07-22 20:31:56,777][50205] Updated weights for policy 0, policy_version 38553 (0.0011) +[2026-07-22 20:31:58,108][50205] Updated weights for policy 0, policy_version 38564 (0.0011) +[2026-07-22 20:31:58,702][50205] Updated weights for policy 0, policy_version 38574 (0.0016) +[2026-07-22 20:31:59,232][50205] Updated weights for policy 0, policy_version 38584 (0.0013) +[2026-07-22 20:31:59,877][43431] Fps is (10 sec: 6348.8, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 19759104. Throughput: 0: 6059.4. Samples: 19754786. Policy #0 lag: (min: 0.0, avg: 18.4, max: 36.0) +[2026-07-22 20:31:59,878][43431] Avg episode reward: [(0, '1756.836')] +[2026-07-22 20:32:00,630][50205] Updated weights for policy 0, policy_version 38594 (0.0012) +[2026-07-22 20:32:01,050][50205] Updated weights for policy 0, policy_version 38604 (0.0014) +[2026-07-22 20:32:02,243][50205] Updated weights for policy 0, policy_version 38614 (0.0012) +[2026-07-22 20:32:02,898][50205] Updated weights for policy 0, policy_version 38624 (0.0011) +[2026-07-22 20:32:04,034][50205] Updated weights for policy 0, policy_version 38636 (0.0012) +[2026-07-22 20:32:04,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6007.5, 300 sec: 6019.0). Total num frames: 19785728. Throughput: 0: 6018.5. Samples: 19789128. Policy #0 lag: (min: 1.0, avg: 17.3, max: 37.0) +[2026-07-22 20:32:04,878][43431] Avg episode reward: [(0, '1860.544')] +[2026-07-22 20:32:05,032][50205] Updated weights for policy 0, policy_version 38646 (0.0020) +[2026-07-22 20:32:05,791][50205] Updated weights for policy 0, policy_version 38656 (0.0017) +[2026-07-22 20:32:06,549][50205] Updated weights for policy 0, policy_version 38666 (0.0011) +[2026-07-22 20:32:07,262][50205] Updated weights for policy 0, policy_version 38676 (0.0013) +[2026-07-22 20:32:08,785][50205] Updated weights for policy 0, policy_version 38686 (0.0019) +[2026-07-22 20:32:09,163][50205] Updated weights for policy 0, policy_version 38696 (0.0016) +[2026-07-22 20:32:09,819][50205] Updated weights for policy 0, policy_version 38706 (0.0011) +[2026-07-22 20:32:09,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 6046.8). Total num frames: 19818496. Throughput: 0: 6015.1. Samples: 19825618. Policy #0 lag: (min: 1.0, avg: 17.3, max: 37.0) +[2026-07-22 20:32:09,878][43431] Avg episode reward: [(0, '1810.264')] +[2026-07-22 20:32:10,844][50205] Updated weights for policy 0, policy_version 38716 (0.0011) +[2026-07-22 20:32:11,813][50205] Updated weights for policy 0, policy_version 38726 (0.0011) +[2026-07-22 20:32:12,319][50205] Updated weights for policy 0, policy_version 38736 (0.0013) +[2026-07-22 20:32:13,453][50205] Updated weights for policy 0, policy_version 38746 (0.0012) +[2026-07-22 20:32:14,196][50205] Updated weights for policy 0, policy_version 38756 (0.0010) +[2026-07-22 20:32:14,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 19847168. Throughput: 0: 6020.7. Samples: 19843990. Policy #0 lag: (min: 1.0, avg: 17.3, max: 37.0) +[2026-07-22 20:32:14,878][43431] Avg episode reward: [(0, '1812.981')] +[2026-07-22 20:32:14,921][50205] Updated weights for policy 0, policy_version 38766 (0.0011) +[2026-07-22 20:32:16,049][50205] Updated weights for policy 0, policy_version 38776 (0.0011) +[2026-07-22 20:32:16,736][50205] Updated weights for policy 0, policy_version 38786 (0.0011) +[2026-07-22 20:32:17,389][50205] Updated weights for policy 0, policy_version 38796 (0.0011) +[2026-07-22 20:32:18,624][50205] Updated weights for policy 0, policy_version 38806 (0.0012) +[2026-07-22 20:32:19,283][50205] Updated weights for policy 0, policy_version 38816 (0.0021) +[2026-07-22 20:32:19,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6075.7, 300 sec: 6032.9). Total num frames: 19877888. Throughput: 0: 6019.0. Samples: 19880402. Policy #0 lag: (min: 1.0, avg: 17.3, max: 37.0) +[2026-07-22 20:32:19,878][43431] Avg episode reward: [(0, '1791.319')] +[2026-07-22 20:32:20,009][50205] Updated weights for policy 0, policy_version 38826 (0.0011) +[2026-07-22 20:32:20,828][50205] Updated weights for policy 0, policy_version 38836 (0.0011) +[2026-07-22 20:32:21,899][50205] Updated weights for policy 0, policy_version 38846 (0.0015) +[2026-07-22 20:32:22,516][50205] Updated weights for policy 0, policy_version 38856 (0.0016) +[2026-07-22 20:32:23,484][50205] Updated weights for policy 0, policy_version 38866 (0.0012) +[2026-07-22 20:32:24,302][50205] Updated weights for policy 0, policy_version 38876 (0.0015) +[2026-07-22 20:32:24,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6075.7, 300 sec: 6039.9). Total num frames: 19908608. Throughput: 0: 6014.1. Samples: 19916718. Policy #0 lag: (min: 1.0, avg: 17.3, max: 37.0) +[2026-07-22 20:32:24,878][43431] Avg episode reward: [(0, '1710.650')] +[2026-07-22 20:32:25,142][50205] Updated weights for policy 0, policy_version 38886 (0.0011) +[2026-07-22 20:32:25,951][50205] Updated weights for policy 0, policy_version 38896 (0.0012) +[2026-07-22 20:32:26,866][50205] Updated weights for policy 0, policy_version 38907 (0.0012) +[2026-07-22 20:32:27,861][50205] Updated weights for policy 0, policy_version 38917 (0.0013) +[2026-07-22 20:32:28,641][50205] Updated weights for policy 0, policy_version 38927 (0.0011) +[2026-07-22 20:32:29,748][50205] Updated weights for policy 0, policy_version 38937 (0.0011) +[2026-07-22 20:32:29,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 19937280. Throughput: 0: 6015.7. Samples: 19934964. Policy #0 lag: (min: 3.0, avg: 17.7, max: 35.0) +[2026-07-22 20:32:29,878][43431] Avg episode reward: [(0, '1787.968')] +[2026-07-22 20:32:30,167][50205] Updated weights for policy 0, policy_version 38947 (0.0011) +[2026-07-22 20:32:31,345][50205] Updated weights for policy 0, policy_version 38957 (0.0020) +[2026-07-22 20:32:32,051][50205] Updated weights for policy 0, policy_version 38967 (0.0013) +[2026-07-22 20:32:33,012][50205] Updated weights for policy 0, policy_version 38977 (0.0013) +[2026-07-22 20:32:33,870][50205] Updated weights for policy 0, policy_version 38987 (0.0012) +[2026-07-22 20:32:34,678][50205] Updated weights for policy 0, policy_version 38997 (0.0015) +[2026-07-22 20:32:34,878][43431] Fps is (10 sec: 5939.0, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 19968000. Throughput: 0: 6021.4. Samples: 19971228. Policy #0 lag: (min: 3.0, avg: 17.7, max: 35.0) +[2026-07-22 20:32:34,878][43431] Avg episode reward: [(0, '1651.810')] +[2026-07-22 20:32:35,239][50205] Updated weights for policy 0, policy_version 39007 (0.0011) +[2026-07-22 20:32:36,625][50205] Updated weights for policy 0, policy_version 39017 (0.0011) +[2026-07-22 20:32:36,994][50205] Updated weights for policy 0, policy_version 39027 (0.0014) +[2026-07-22 20:32:37,840][50205] Updated weights for policy 0, policy_version 39037 (0.0016) +[2026-07-22 20:32:38,700][50205] Updated weights for policy 0, policy_version 39047 (0.0011) +[2026-07-22 20:32:39,785][50205] Updated weights for policy 0, policy_version 39057 (0.0019) +[2026-07-22 20:32:39,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 19998720. Throughput: 0: 6019.4. Samples: 20007620. Policy #0 lag: (min: 3.0, avg: 17.7, max: 35.0) +[2026-07-22 20:32:39,878][43431] Avg episode reward: [(0, '1706.257')] +[2026-07-22 20:32:39,891][49527] Saving results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/checkpoint_p0/checkpoint_000039060_19998720.pth... +[2026-07-22 20:32:39,945][49527] Removing results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/checkpoint_p0/checkpoint_000006040_3092480.pth +[2026-07-22 20:32:40,377][50205] Updated weights for policy 0, policy_version 39067 (0.0010) +[2026-07-22 20:32:41,641][50205] Updated weights for policy 0, policy_version 39077 (0.0010) +[2026-07-22 20:32:42,064][50205] Updated weights for policy 0, policy_version 39087 (0.0015) +[2026-07-22 20:32:42,942][50205] Updated weights for policy 0, policy_version 39097 (0.0015) +[2026-07-22 20:32:43,931][50205] Updated weights for policy 0, policy_version 39107 (0.0014) +[2026-07-22 20:32:44,878][43431] Fps is (10 sec: 5939.1, 60 sec: 6075.7, 300 sec: 6026.0). Total num frames: 20027392. Throughput: 0: 6022.5. Samples: 20025802. Policy #0 lag: (min: 3.0, avg: 17.7, max: 35.0) +[2026-07-22 20:32:44,878][43431] Avg episode reward: [(0, '1841.470')] +[2026-07-22 20:32:44,903][50205] Updated weights for policy 0, policy_version 39119 (0.0016) +[2026-07-22 20:32:45,633][50205] Updated weights for policy 0, policy_version 39131 (0.0012) +[2026-07-22 20:32:47,062][50205] Updated weights for policy 0, policy_version 39141 (0.0011) +[2026-07-22 20:32:47,651][50205] Updated weights for policy 0, policy_version 39151 (0.0015) +[2026-07-22 20:32:48,302][50205] Updated weights for policy 0, policy_version 39161 (0.0013) +[2026-07-22 20:32:49,394][50205] Updated weights for policy 0, policy_version 39171 (0.0011) +[2026-07-22 20:32:49,877][43431] Fps is (10 sec: 5939.3, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 20058112. Throughput: 0: 6062.3. Samples: 20061930. Policy #0 lag: (min: 3.0, avg: 17.7, max: 35.0) +[2026-07-22 20:32:49,878][43431] Avg episode reward: [(0, '1832.415')] +[2026-07-22 20:32:50,388][50205] Updated weights for policy 0, policy_version 39181 (0.0012) +[2026-07-22 20:32:50,933][50205] Updated weights for policy 0, policy_version 39191 (0.0012) +[2026-07-22 20:32:51,887][50205] Updated weights for policy 0, policy_version 39201 (0.0018) +[2026-07-22 20:32:52,594][50205] Updated weights for policy 0, policy_version 39211 (0.0011) +[2026-07-22 20:32:53,528][50205] Updated weights for policy 0, policy_version 39221 (0.0012) +[2026-07-22 20:32:54,505][50205] Updated weights for policy 0, policy_version 39231 (0.0017) +[2026-07-22 20:32:54,877][43431] Fps is (10 sec: 6144.3, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 20088832. Throughput: 0: 6058.8. Samples: 20098262. Policy #0 lag: (min: 3.0, avg: 19.4, max: 42.0) +[2026-07-22 20:32:54,878][43431] Avg episode reward: [(0, '1844.368')] +[2026-07-22 20:32:55,315][50205] Updated weights for policy 0, policy_version 39241 (0.0015) +[2026-07-22 20:32:55,948][50205] Updated weights for policy 0, policy_version 39252 (0.0015) +[2026-07-22 20:32:57,209][50205] Updated weights for policy 0, policy_version 39262 (0.0013) +[2026-07-22 20:32:57,777][50205] Updated weights for policy 0, policy_version 39272 (0.0011) +[2026-07-22 20:32:58,576][50205] Updated weights for policy 0, policy_version 39283 (0.0021) +[2026-07-22 20:32:59,732][50205] Updated weights for policy 0, policy_version 39293 (0.0011) +[2026-07-22 20:32:59,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 6032.9). Total num frames: 20119552. Throughput: 0: 6055.7. Samples: 20116496. Policy #0 lag: (min: 3.0, avg: 19.4, max: 42.0) +[2026-07-22 20:32:59,878][43431] Avg episode reward: [(0, '1736.057')] +[2026-07-22 20:33:00,446][50205] Updated weights for policy 0, policy_version 39303 (0.0016) +[2026-07-22 20:33:01,357][50205] Updated weights for policy 0, policy_version 39313 (0.0014) +[2026-07-22 20:33:02,143][50205] Updated weights for policy 0, policy_version 39323 (0.0016) +[2026-07-22 20:33:03,008][50205] Updated weights for policy 0, policy_version 39333 (0.0012) +[2026-07-22 20:33:03,890][50205] Updated weights for policy 0, policy_version 39343 (0.0013) +[2026-07-22 20:33:04,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 20148224. Throughput: 0: 6055.1. Samples: 20152880. Policy #0 lag: (min: 3.0, avg: 19.4, max: 42.0) +[2026-07-22 20:33:04,878][43431] Avg episode reward: [(0, '1681.045')] +[2026-07-22 20:33:04,929][50205] Updated weights for policy 0, policy_version 39353 (0.0012) +[2026-07-22 20:33:05,494][50205] Updated weights for policy 0, policy_version 39363 (0.0011) +[2026-07-22 20:33:06,385][50205] Updated weights for policy 0, policy_version 39373 (0.0011) +[2026-07-22 20:33:07,428][50205] Updated weights for policy 0, policy_version 39383 (0.0018) +[2026-07-22 20:33:08,132][50205] Updated weights for policy 0, policy_version 39393 (0.0011) +[2026-07-22 20:33:08,758][50205] Updated weights for policy 0, policy_version 39403 (0.0021) +[2026-07-22 20:33:09,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 20178944. Throughput: 0: 6050.1. Samples: 20188974. Policy #0 lag: (min: 3.0, avg: 19.4, max: 42.0) +[2026-07-22 20:33:09,878][43431] Avg episode reward: [(0, '1819.132')] +[2026-07-22 20:33:10,049][50205] Updated weights for policy 0, policy_version 39413 (0.0012) +[2026-07-22 20:33:10,770][50205] Updated weights for policy 0, policy_version 39423 (0.0012) +[2026-07-22 20:33:11,633][50205] Updated weights for policy 0, policy_version 39433 (0.0017) +[2026-07-22 20:33:12,277][50205] Updated weights for policy 0, policy_version 39443 (0.0015) +[2026-07-22 20:33:13,353][50205] Updated weights for policy 0, policy_version 39453 (0.0011) +[2026-07-22 20:33:13,871][50205] Updated weights for policy 0, policy_version 39463 (0.0013) +[2026-07-22 20:33:14,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6007.5, 300 sec: 6019.0). Total num frames: 20207616. Throughput: 0: 6049.5. Samples: 20207192. Policy #0 lag: (min: 3.0, avg: 19.4, max: 42.0) +[2026-07-22 20:33:14,878][43431] Avg episode reward: [(0, '1777.489')] +[2026-07-22 20:33:15,144][50205] Updated weights for policy 0, policy_version 39475 (0.0013) +[2026-07-22 20:33:16,047][50205] Updated weights for policy 0, policy_version 39485 (0.0015) +[2026-07-22 20:33:16,840][50205] Updated weights for policy 0, policy_version 39495 (0.0011) +[2026-07-22 20:33:17,739][50205] Updated weights for policy 0, policy_version 39505 (0.0011) +[2026-07-22 20:33:18,548][50205] Updated weights for policy 0, policy_version 39515 (0.0010) +[2026-07-22 20:33:19,468][50205] Updated weights for policy 0, policy_version 39525 (0.0012) +[2026-07-22 20:33:19,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6007.5, 300 sec: 6019.0). Total num frames: 20238336. Throughput: 0: 6046.7. Samples: 20243330. Policy #0 lag: (min: 3.0, avg: 18.8, max: 35.0) +[2026-07-22 20:33:19,878][43431] Avg episode reward: [(0, '1786.308')] +[2026-07-22 20:33:20,146][50205] Updated weights for policy 0, policy_version 39535 (0.0017) +[2026-07-22 20:33:21,066][50205] Updated weights for policy 0, policy_version 39545 (0.0012) +[2026-07-22 20:33:21,937][50205] Updated weights for policy 0, policy_version 39555 (0.0014) +[2026-07-22 20:33:22,664][50205] Updated weights for policy 0, policy_version 39565 (0.0020) +[2026-07-22 20:33:23,454][50205] Updated weights for policy 0, policy_version 39575 (0.0011) +[2026-07-22 20:33:24,491][50205] Updated weights for policy 0, policy_version 39585 (0.0012) +[2026-07-22 20:33:24,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 6019.0). Total num frames: 20269056. Throughput: 0: 6049.7. Samples: 20279858. Policy #0 lag: (min: 3.0, avg: 18.8, max: 35.0) +[2026-07-22 20:33:24,878][43431] Avg episode reward: [(0, '1822.508')] +[2026-07-22 20:33:25,269][50205] Updated weights for policy 0, policy_version 39595 (0.0011) +[2026-07-22 20:33:26,139][50205] Updated weights for policy 0, policy_version 39605 (0.0021) +[2026-07-22 20:33:26,981][50205] Updated weights for policy 0, policy_version 39615 (0.0020) +[2026-07-22 20:33:27,890][50205] Updated weights for policy 0, policy_version 39625 (0.0016) +[2026-07-22 20:33:28,563][50205] Updated weights for policy 0, policy_version 39635 (0.0021) +[2026-07-22 20:33:29,484][50205] Updated weights for policy 0, policy_version 39645 (0.0012) +[2026-07-22 20:33:29,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 20299776. Throughput: 0: 6047.0. Samples: 20297912. Policy #0 lag: (min: 3.0, avg: 18.8, max: 35.0) +[2026-07-22 20:33:29,878][43431] Avg episode reward: [(0, '1696.260')] +[2026-07-22 20:33:30,371][50205] Updated weights for policy 0, policy_version 39655 (0.0020) +[2026-07-22 20:33:31,155][50205] Updated weights for policy 0, policy_version 39665 (0.0017) +[2026-07-22 20:33:32,017][50205] Updated weights for policy 0, policy_version 39675 (0.0011) +[2026-07-22 20:33:32,935][50205] Updated weights for policy 0, policy_version 39685 (0.0021) +[2026-07-22 20:33:33,827][50205] Updated weights for policy 0, policy_version 39697 (0.0011) +[2026-07-22 20:33:34,612][50205] Updated weights for policy 0, policy_version 39707 (0.0012) +[2026-07-22 20:33:34,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 20330496. Throughput: 0: 6050.1. Samples: 20334186. Policy #0 lag: (min: 3.0, avg: 18.8, max: 35.0) +[2026-07-22 20:33:34,878][43431] Avg episode reward: [(0, '1678.916')] +[2026-07-22 20:33:35,690][50205] Updated weights for policy 0, policy_version 39717 (0.0011) +[2026-07-22 20:33:36,372][50205] Updated weights for policy 0, policy_version 39727 (0.0011) +[2026-07-22 20:33:37,403][50205] Updated weights for policy 0, policy_version 39737 (0.0016) +[2026-07-22 20:33:38,047][50205] Updated weights for policy 0, policy_version 39747 (0.0020) +[2026-07-22 20:33:39,039][50205] Updated weights for policy 0, policy_version 39757 (0.0011) +[2026-07-22 20:33:39,675][50205] Updated weights for policy 0, policy_version 39767 (0.0013) +[2026-07-22 20:33:39,878][43431] Fps is (10 sec: 6143.5, 60 sec: 6041.5, 300 sec: 6032.9). Total num frames: 20361216. Throughput: 0: 6049.2. Samples: 20370480. Policy #0 lag: (min: 3.0, avg: 18.8, max: 35.0) +[2026-07-22 20:33:39,880][43431] Avg episode reward: [(0, '1844.901')] +[2026-07-22 20:33:40,753][50205] Updated weights for policy 0, policy_version 39777 (0.0019) +[2026-07-22 20:33:41,464][50205] Updated weights for policy 0, policy_version 39787 (0.0025) +[2026-07-22 20:33:42,532][50205] Updated weights for policy 0, policy_version 39797 (0.0015) +[2026-07-22 20:33:43,126][50205] Updated weights for policy 0, policy_version 39807 (0.0020) +[2026-07-22 20:33:44,092][50205] Updated weights for policy 0, policy_version 39817 (0.0017) +[2026-07-22 20:33:44,733][50205] Updated weights for policy 0, policy_version 39827 (0.0016) +[2026-07-22 20:33:44,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6075.8, 300 sec: 6032.9). Total num frames: 20391936. Throughput: 0: 6048.8. Samples: 20388692. Policy #0 lag: (min: 3.0, avg: 18.6, max: 37.0) +[2026-07-22 20:33:44,878][43431] Avg episode reward: [(0, '1703.544')] +[2026-07-22 20:33:45,730][50205] Updated weights for policy 0, policy_version 39837 (0.0012) +[2026-07-22 20:33:46,481][50205] Updated weights for policy 0, policy_version 39847 (0.0013) +[2026-07-22 20:33:47,417][50205] Updated weights for policy 0, policy_version 39857 (0.0014) +[2026-07-22 20:33:48,217][50205] Updated weights for policy 0, policy_version 39867 (0.0013) +[2026-07-22 20:33:49,192][50205] Updated weights for policy 0, policy_version 39877 (0.0021) +[2026-07-22 20:33:49,877][43431] Fps is (10 sec: 5939.6, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 20420608. Throughput: 0: 6049.2. Samples: 20425096. Policy #0 lag: (min: 3.0, avg: 18.6, max: 37.0) +[2026-07-22 20:33:49,878][43431] Avg episode reward: [(0, '1723.161')] +[2026-07-22 20:33:49,984][50205] Updated weights for policy 0, policy_version 39887 (0.0016) +[2026-07-22 20:33:50,736][50205] Updated weights for policy 0, policy_version 39897 (0.0011) +[2026-07-22 20:33:51,829][50205] Updated weights for policy 0, policy_version 39909 (0.0011) +[2026-07-22 20:33:52,623][50205] Updated weights for policy 0, policy_version 39919 (0.0016) +[2026-07-22 20:33:53,733][50205] Updated weights for policy 0, policy_version 39929 (0.0011) +[2026-07-22 20:33:54,560][50205] Updated weights for policy 0, policy_version 39939 (0.0011) +[2026-07-22 20:33:54,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 20451328. Throughput: 0: 6022.0. Samples: 20459962. Policy #0 lag: (min: 3.0, avg: 18.6, max: 37.0) +[2026-07-22 20:33:54,878][43431] Avg episode reward: [(0, '1965.589')] +[2026-07-22 20:33:54,900][49527] Saving new best policy, reward=1965.589! +[2026-07-22 20:33:55,248][50205] Updated weights for policy 0, policy_version 39949 (0.0011) +[2026-07-22 20:33:56,233][50205] Updated weights for policy 0, policy_version 39959 (0.0015) +[2026-07-22 20:33:57,251][50205] Updated weights for policy 0, policy_version 39969 (0.0011) +[2026-07-22 20:33:57,621][50205] Updated weights for policy 0, policy_version 39979 (0.0010) +[2026-07-22 20:33:58,779][50205] Updated weights for policy 0, policy_version 39989 (0.0017) +[2026-07-22 20:33:59,602][50205] Updated weights for policy 0, policy_version 39999 (0.0012) +[2026-07-22 20:33:59,878][43431] Fps is (10 sec: 5939.0, 60 sec: 6007.4, 300 sec: 6026.0). Total num frames: 20480000. Throughput: 0: 6021.6. Samples: 20478168. Policy #0 lag: (min: 3.0, avg: 18.6, max: 37.0) +[2026-07-22 20:33:59,878][43431] Avg episode reward: [(0, '1770.914')] +[2026-07-22 20:34:00,511][50205] Updated weights for policy 0, policy_version 40009 (0.0011) +[2026-07-22 20:34:01,164][50205] Updated weights for policy 0, policy_version 40019 (0.0011) +[2026-07-22 20:34:02,553][50205] Updated weights for policy 0, policy_version 40029 (0.0018) +[2026-07-22 20:34:03,201][50205] Updated weights for policy 0, policy_version 40039 (0.0019) +[2026-07-22 20:34:04,431][50205] Updated weights for policy 0, policy_version 40049 (0.0011) +[2026-07-22 20:34:04,877][43431] Fps is (10 sec: 5734.3, 60 sec: 6007.4, 300 sec: 6019.1). Total num frames: 20508672. Throughput: 0: 5975.9. Samples: 20512246. Policy #0 lag: (min: 3.0, avg: 18.6, max: 37.0) +[2026-07-22 20:34:04,878][43431] Avg episode reward: [(0, '1930.527')] +[2026-07-22 20:34:05,064][50205] Updated weights for policy 0, policy_version 40059 (0.0014) +[2026-07-22 20:34:05,853][50205] Updated weights for policy 0, policy_version 40069 (0.0015) +[2026-07-22 20:34:06,685][50205] Updated weights for policy 0, policy_version 40079 (0.0016) +[2026-07-22 20:34:07,827][50205] Updated weights for policy 0, policy_version 40089 (0.0022) +[2026-07-22 20:34:08,321][50205] Updated weights for policy 0, policy_version 40099 (0.0016) +[2026-07-22 20:34:09,316][50205] Updated weights for policy 0, policy_version 40109 (0.0013) +[2026-07-22 20:34:09,878][43431] Fps is (10 sec: 5939.1, 60 sec: 6007.4, 300 sec: 6019.0). Total num frames: 20539392. Throughput: 0: 5974.1. Samples: 20548694. Policy #0 lag: (min: 2.0, avg: 19.3, max: 38.0) +[2026-07-22 20:34:09,879][43431] Avg episode reward: [(0, '1726.543')] +[2026-07-22 20:34:10,017][50205] Updated weights for policy 0, policy_version 40119 (0.0010) +[2026-07-22 20:34:11,111][50205] Updated weights for policy 0, policy_version 40131 (0.0014) +[2026-07-22 20:34:12,005][50205] Updated weights for policy 0, policy_version 40141 (0.0013) +[2026-07-22 20:34:12,828][50205] Updated weights for policy 0, policy_version 40151 (0.0011) +[2026-07-22 20:34:13,626][50205] Updated weights for policy 0, policy_version 40161 (0.0010) +[2026-07-22 20:34:14,728][50205] Updated weights for policy 0, policy_version 40171 (0.0012) +[2026-07-22 20:34:14,877][43431] Fps is (10 sec: 5939.3, 60 sec: 6007.5, 300 sec: 6019.0). Total num frames: 20568064. Throughput: 0: 5975.9. Samples: 20566828. Policy #0 lag: (min: 2.0, avg: 19.3, max: 38.0) +[2026-07-22 20:34:14,878][43431] Avg episode reward: [(0, '1769.843')] +[2026-07-22 20:34:15,320][50205] Updated weights for policy 0, policy_version 40181 (0.0014) +[2026-07-22 20:34:16,209][50205] Updated weights for policy 0, policy_version 40191 (0.0011) +[2026-07-22 20:34:17,346][50205] Updated weights for policy 0, policy_version 40201 (0.0011) +[2026-07-22 20:34:17,949][50205] Updated weights for policy 0, policy_version 40211 (0.0015) +[2026-07-22 20:34:18,724][50205] Updated weights for policy 0, policy_version 40221 (0.0012) +[2026-07-22 20:34:19,388][50205] Updated weights for policy 0, policy_version 40231 (0.0013) +[2026-07-22 20:34:19,877][43431] Fps is (10 sec: 5939.4, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 20598784. Throughput: 0: 5975.0. Samples: 20603062. Policy #0 lag: (min: 2.0, avg: 19.3, max: 38.0) +[2026-07-22 20:34:19,878][43431] Avg episode reward: [(0, '1745.356')] +[2026-07-22 20:34:20,435][50205] Updated weights for policy 0, policy_version 40241 (0.0016) +[2026-07-22 20:34:21,376][50205] Updated weights for policy 0, policy_version 40251 (0.0011) +[2026-07-22 20:34:22,206][50205] Updated weights for policy 0, policy_version 40261 (0.0013) +[2026-07-22 20:34:22,915][50205] Updated weights for policy 0, policy_version 40271 (0.0011) +[2026-07-22 20:34:23,862][50205] Updated weights for policy 0, policy_version 40281 (0.0011) +[2026-07-22 20:34:24,853][50205] Updated weights for policy 0, policy_version 40291 (0.0014) +[2026-07-22 20:34:24,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 20629504. Throughput: 0: 5977.2. Samples: 20639450. Policy #0 lag: (min: 2.0, avg: 19.3, max: 38.0) +[2026-07-22 20:34:24,878][43431] Avg episode reward: [(0, '1763.520')] +[2026-07-22 20:34:25,610][50205] Updated weights for policy 0, policy_version 40301 (0.0015) +[2026-07-22 20:34:26,360][50205] Updated weights for policy 0, policy_version 40311 (0.0010) +[2026-07-22 20:34:27,328][50205] Updated weights for policy 0, policy_version 40321 (0.0016) +[2026-07-22 20:34:28,158][50205] Updated weights for policy 0, policy_version 40331 (0.0015) +[2026-07-22 20:34:28,856][50205] Updated weights for policy 0, policy_version 40341 (0.0012) +[2026-07-22 20:34:29,770][50205] Updated weights for policy 0, policy_version 40351 (0.0016) +[2026-07-22 20:34:29,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 20660224. Throughput: 0: 5975.2. Samples: 20657574. Policy #0 lag: (min: 2.0, avg: 19.3, max: 38.0) +[2026-07-22 20:34:29,878][43431] Avg episode reward: [(0, '1595.806')] +[2026-07-22 20:34:30,784][50205] Updated weights for policy 0, policy_version 40361 (0.0015) +[2026-07-22 20:34:31,318][50205] Updated weights for policy 0, policy_version 40371 (0.0012) +[2026-07-22 20:34:32,451][50205] Updated weights for policy 0, policy_version 40381 (0.0011) +[2026-07-22 20:34:33,001][50205] Updated weights for policy 0, policy_version 40391 (0.0011) +[2026-07-22 20:34:33,892][50205] Updated weights for policy 0, policy_version 40401 (0.0010) +[2026-07-22 20:34:34,858][50205] Updated weights for policy 0, policy_version 40411 (0.0014) +[2026-07-22 20:34:34,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6007.5, 300 sec: 6019.0). Total num frames: 20690944. Throughput: 0: 5975.7. Samples: 20694004. Policy #0 lag: (min: 2.0, avg: 19.3, max: 38.0) +[2026-07-22 20:34:34,878][43431] Avg episode reward: [(0, '1817.407')] +[2026-07-22 20:34:35,843][50205] Updated weights for policy 0, policy_version 40421 (0.0010) +[2026-07-22 20:34:36,255][50205] Updated weights for policy 0, policy_version 40431 (0.0017) +[2026-07-22 20:34:37,401][50205] Updated weights for policy 0, policy_version 40441 (0.0016) +[2026-07-22 20:34:38,271][50205] Updated weights for policy 0, policy_version 40451 (0.0018) +[2026-07-22 20:34:39,058][50205] Updated weights for policy 0, policy_version 40461 (0.0014) +[2026-07-22 20:34:39,561][50205] Updated weights for policy 0, policy_version 40471 (0.0016) +[2026-07-22 20:34:39,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 20721664. Throughput: 0: 6009.9. Samples: 20730406. Policy #0 lag: (min: 3.0, avg: 16.8, max: 35.0) +[2026-07-22 20:34:39,878][43431] Avg episode reward: [(0, '1588.121')] +[2026-07-22 20:34:40,890][50205] Updated weights for policy 0, policy_version 40481 (0.0011) +[2026-07-22 20:34:41,453][50205] Updated weights for policy 0, policy_version 40491 (0.0011) +[2026-07-22 20:34:42,427][50205] Updated weights for policy 0, policy_version 40501 (0.0011) +[2026-07-22 20:34:43,287][50205] Updated weights for policy 0, policy_version 40511 (0.0016) +[2026-07-22 20:34:44,197][50205] Updated weights for policy 0, policy_version 40521 (0.0011) +[2026-07-22 20:34:44,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5973.3, 300 sec: 6012.1). Total num frames: 20750336. Throughput: 0: 6010.2. Samples: 20748626. Policy #0 lag: (min: 3.0, avg: 16.8, max: 35.0) +[2026-07-22 20:34:44,878][43431] Avg episode reward: [(0, '1803.619')] +[2026-07-22 20:34:45,007][50205] Updated weights for policy 0, policy_version 40531 (0.0020) +[2026-07-22 20:34:46,032][50205] Updated weights for policy 0, policy_version 40541 (0.0011) +[2026-07-22 20:34:46,417][50205] Updated weights for policy 0, policy_version 40551 (0.0010) +[2026-07-22 20:34:47,501][50205] Updated weights for policy 0, policy_version 40561 (0.0015) +[2026-07-22 20:34:48,418][50205] Updated weights for policy 0, policy_version 40571 (0.0014) +[2026-07-22 20:34:49,338][50205] Updated weights for policy 0, policy_version 40581 (0.0011) +[2026-07-22 20:34:49,791][50205] Updated weights for policy 0, policy_version 40591 (0.0015) +[2026-07-22 20:34:49,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6041.6, 300 sec: 6019.0). Total num frames: 20783104. Throughput: 0: 6058.1. Samples: 20784860. Policy #0 lag: (min: 3.0, avg: 16.8, max: 35.0) +[2026-07-22 20:34:49,878][43431] Avg episode reward: [(0, '1605.190')] +[2026-07-22 20:34:51,028][50205] Updated weights for policy 0, policy_version 40601 (0.0014) +[2026-07-22 20:34:51,760][50205] Updated weights for policy 0, policy_version 40611 (0.0013) +[2026-07-22 20:34:52,705][50205] Updated weights for policy 0, policy_version 40621 (0.0018) +[2026-07-22 20:34:53,465][50205] Updated weights for policy 0, policy_version 40631 (0.0011) +[2026-07-22 20:34:54,213][50205] Updated weights for policy 0, policy_version 40641 (0.0011) +[2026-07-22 20:34:54,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6007.5, 300 sec: 6019.0). Total num frames: 20811776. Throughput: 0: 6056.6. Samples: 20821236. Policy #0 lag: (min: 3.0, avg: 16.8, max: 35.0) +[2026-07-22 20:34:54,878][43431] Avg episode reward: [(0, '1839.395')] +[2026-07-22 20:34:54,949][50205] Updated weights for policy 0, policy_version 40651 (0.0013) +[2026-07-22 20:34:56,187][50205] Updated weights for policy 0, policy_version 40661 (0.0010) +[2026-07-22 20:34:56,616][50205] Updated weights for policy 0, policy_version 40671 (0.0018) +[2026-07-22 20:34:57,547][50205] Updated weights for policy 0, policy_version 40681 (0.0020) +[2026-07-22 20:34:58,516][50205] Updated weights for policy 0, policy_version 40691 (0.0017) +[2026-07-22 20:34:59,283][50205] Updated weights for policy 0, policy_version 40701 (0.0014) +[2026-07-22 20:34:59,877][43431] Fps is (10 sec: 5939.4, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 20842496. Throughput: 0: 6056.9. Samples: 20839388. Policy #0 lag: (min: 3.0, avg: 16.8, max: 35.0) +[2026-07-22 20:34:59,878][43431] Avg episode reward: [(0, '1923.917')] +[2026-07-22 20:35:00,048][50205] Updated weights for policy 0, policy_version 40711 (0.0016) +[2026-07-22 20:35:01,124][50205] Updated weights for policy 0, policy_version 40723 (0.0011) +[2026-07-22 20:35:02,297][50205] Updated weights for policy 0, policy_version 40734 (0.0012) +[2026-07-22 20:35:03,049][50205] Updated weights for policy 0, policy_version 40744 (0.0011) +[2026-07-22 20:35:03,964][50205] Updated weights for policy 0, policy_version 40754 (0.0010) +[2026-07-22 20:35:04,649][50205] Updated weights for policy 0, policy_version 40764 (0.0016) +[2026-07-22 20:35:04,877][43431] Fps is (10 sec: 5939.0, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 20871168. Throughput: 0: 6030.5. Samples: 20874436. Policy #0 lag: (min: 2.0, avg: 20.2, max: 40.0) +[2026-07-22 20:35:04,878][43431] Avg episode reward: [(0, '1840.654')] +[2026-07-22 20:35:05,679][50205] Updated weights for policy 0, policy_version 40774 (0.0012) +[2026-07-22 20:35:06,544][50205] Updated weights for policy 0, policy_version 40784 (0.0011) +[2026-07-22 20:35:07,336][50205] Updated weights for policy 0, policy_version 40795 (0.0012) +[2026-07-22 20:35:08,395][50205] Updated weights for policy 0, policy_version 40805 (0.0011) +[2026-07-22 20:35:09,195][50205] Updated weights for policy 0, policy_version 40815 (0.0011) +[2026-07-22 20:35:09,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 20901888. Throughput: 0: 6031.0. Samples: 20910846. Policy #0 lag: (min: 2.0, avg: 20.2, max: 40.0) +[2026-07-22 20:35:09,878][43431] Avg episode reward: [(0, '1733.404')] +[2026-07-22 20:35:10,228][50205] Updated weights for policy 0, policy_version 40825 (0.0011) +[2026-07-22 20:35:10,666][50205] Updated weights for policy 0, policy_version 40835 (0.0011) +[2026-07-22 20:35:11,918][50205] Updated weights for policy 0, policy_version 40845 (0.0015) +[2026-07-22 20:35:12,453][50205] Updated weights for policy 0, policy_version 40855 (0.0010) +[2026-07-22 20:35:13,497][50205] Updated weights for policy 0, policy_version 40865 (0.0011) +[2026-07-22 20:35:14,266][50205] Updated weights for policy 0, policy_version 40875 (0.0027) +[2026-07-22 20:35:14,877][43431] Fps is (10 sec: 5939.3, 60 sec: 6041.6, 300 sec: 6019.0). Total num frames: 20930560. Throughput: 0: 6031.5. Samples: 20928990. Policy #0 lag: (min: 2.0, avg: 20.2, max: 40.0) +[2026-07-22 20:35:14,878][43431] Avg episode reward: [(0, '1820.056')] +[2026-07-22 20:35:15,035][50205] Updated weights for policy 0, policy_version 40885 (0.0012) +[2026-07-22 20:35:15,816][50205] Updated weights for policy 0, policy_version 40895 (0.0011) +[2026-07-22 20:35:17,114][50205] Updated weights for policy 0, policy_version 40905 (0.0015) +[2026-07-22 20:35:17,646][50205] Updated weights for policy 0, policy_version 40915 (0.0025) +[2026-07-22 20:35:18,413][50205] Updated weights for policy 0, policy_version 40925 (0.0012) +[2026-07-22 20:35:19,363][50205] Updated weights for policy 0, policy_version 40935 (0.0014) +[2026-07-22 20:35:19,877][43431] Fps is (10 sec: 5939.3, 60 sec: 6041.6, 300 sec: 6019.0). Total num frames: 20961280. Throughput: 0: 6032.2. Samples: 20965454. Policy #0 lag: (min: 2.0, avg: 20.2, max: 40.0) +[2026-07-22 20:35:19,878][43431] Avg episode reward: [(0, '1681.833')] +[2026-07-22 20:35:20,141][50205] Updated weights for policy 0, policy_version 40945 (0.0011) +[2026-07-22 20:35:20,978][50205] Updated weights for policy 0, policy_version 40955 (0.0012) +[2026-07-22 20:35:21,811][50205] Updated weights for policy 0, policy_version 40965 (0.0011) +[2026-07-22 20:35:22,627][50205] Updated weights for policy 0, policy_version 40975 (0.0011) +[2026-07-22 20:35:23,513][50205] Updated weights for policy 0, policy_version 40985 (0.0023) +[2026-07-22 20:35:24,496][50205] Updated weights for policy 0, policy_version 40995 (0.0013) +[2026-07-22 20:35:24,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 20992000. Throughput: 0: 6033.6. Samples: 21001918. Policy #0 lag: (min: 2.0, avg: 20.2, max: 40.0) +[2026-07-22 20:35:24,878][43431] Avg episode reward: [(0, '1857.896')] +[2026-07-22 20:35:25,282][50205] Updated weights for policy 0, policy_version 41005 (0.0011) +[2026-07-22 20:35:25,983][50205] Updated weights for policy 0, policy_version 41015 (0.0021) +[2026-07-22 20:35:26,911][50205] Updated weights for policy 0, policy_version 41025 (0.0011) +[2026-07-22 20:35:27,701][50205] Updated weights for policy 0, policy_version 41035 (0.0011) +[2026-07-22 20:35:28,419][50205] Updated weights for policy 0, policy_version 41045 (0.0012) +[2026-07-22 20:35:29,157][50205] Updated weights for policy 0, policy_version 41055 (0.0018) +[2026-07-22 20:35:29,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 6019.0). Total num frames: 21022720. Throughput: 0: 6036.2. Samples: 21020256. Policy #0 lag: (min: 0.0, avg: 17.0, max: 36.0) +[2026-07-22 20:35:29,878][43431] Avg episode reward: [(0, '1701.096')] +[2026-07-22 20:35:30,399][50205] Updated weights for policy 0, policy_version 41065 (0.0011) +[2026-07-22 20:35:31,103][50205] Updated weights for policy 0, policy_version 41075 (0.0011) +[2026-07-22 20:35:31,752][50205] Updated weights for policy 0, policy_version 41085 (0.0014) +[2026-07-22 20:35:32,770][50205] Updated weights for policy 0, policy_version 41095 (0.0011) +[2026-07-22 20:35:33,692][50205] Updated weights for policy 0, policy_version 41105 (0.0011) +[2026-07-22 20:35:34,484][50205] Updated weights for policy 0, policy_version 41115 (0.0011) +[2026-07-22 20:35:34,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 21053440. Throughput: 0: 6041.0. Samples: 21056706. Policy #0 lag: (min: 0.0, avg: 17.0, max: 36.0) +[2026-07-22 20:35:34,878][43431] Avg episode reward: [(0, '1822.331')] +[2026-07-22 20:35:35,271][50205] Updated weights for policy 0, policy_version 41125 (0.0011) +[2026-07-22 20:35:36,018][50205] Updated weights for policy 0, policy_version 41135 (0.0012) +[2026-07-22 20:35:36,944][50205] Updated weights for policy 0, policy_version 41145 (0.0015) +[2026-07-22 20:35:37,929][50205] Updated weights for policy 0, policy_version 41155 (0.0013) +[2026-07-22 20:35:38,735][50205] Updated weights for policy 0, policy_version 41165 (0.0026) +[2026-07-22 20:35:39,326][50205] Updated weights for policy 0, policy_version 41175 (0.0017) +[2026-07-22 20:35:39,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 21084160. Throughput: 0: 6043.8. Samples: 21093208. Policy #0 lag: (min: 0.0, avg: 17.0, max: 36.0) +[2026-07-22 20:35:39,878][43431] Avg episode reward: [(0, '1756.803')] +[2026-07-22 20:35:40,538][50205] Updated weights for policy 0, policy_version 41185 (0.0017) +[2026-07-22 20:35:41,183][50205] Updated weights for policy 0, policy_version 41195 (0.0011) +[2026-07-22 20:35:42,029][50205] Updated weights for policy 0, policy_version 41205 (0.0010) +[2026-07-22 20:35:42,693][50205] Updated weights for policy 0, policy_version 41215 (0.0011) +[2026-07-22 20:35:43,888][50205] Updated weights for policy 0, policy_version 41225 (0.0011) +[2026-07-22 20:35:44,399][50205] Updated weights for policy 0, policy_version 41235 (0.0012) +[2026-07-22 20:35:44,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6075.7, 300 sec: 6026.0). Total num frames: 21114880. Throughput: 0: 6044.7. Samples: 21111398. Policy #0 lag: (min: 0.0, avg: 17.0, max: 36.0) +[2026-07-22 20:35:44,878][43431] Avg episode reward: [(0, '1980.371')] +[2026-07-22 20:35:44,918][49527] Saving new best policy, reward=1980.371! +[2026-07-22 20:35:45,514][50205] Updated weights for policy 0, policy_version 41245 (0.0015) +[2026-07-22 20:35:46,081][50205] Updated weights for policy 0, policy_version 41255 (0.0011) +[2026-07-22 20:35:47,219][50205] Updated weights for policy 0, policy_version 41265 (0.0024) +[2026-07-22 20:35:47,860][50205] Updated weights for policy 0, policy_version 41275 (0.0013) +[2026-07-22 20:35:48,844][50205] Updated weights for policy 0, policy_version 41285 (0.0011) +[2026-07-22 20:35:49,460][50205] Updated weights for policy 0, policy_version 41295 (0.0014) +[2026-07-22 20:35:49,880][43431] Fps is (10 sec: 6142.2, 60 sec: 6041.3, 300 sec: 6025.9). Total num frames: 21145600. Throughput: 0: 6074.8. Samples: 21147820. Policy #0 lag: (min: 0.0, avg: 17.0, max: 36.0) +[2026-07-22 20:35:49,881][43431] Avg episode reward: [(0, '1650.021')] +[2026-07-22 20:35:50,724][50205] Updated weights for policy 0, policy_version 41305 (0.0011) +[2026-07-22 20:35:51,213][50205] Updated weights for policy 0, policy_version 41315 (0.0020) +[2026-07-22 20:35:52,221][50205] Updated weights for policy 0, policy_version 41325 (0.0013) +[2026-07-22 20:35:52,744][50205] Updated weights for policy 0, policy_version 41335 (0.0011) +[2026-07-22 20:35:53,845][50205] Updated weights for policy 0, policy_version 41345 (0.0016) +[2026-07-22 20:35:54,715][50205] Updated weights for policy 0, policy_version 41355 (0.0010) +[2026-07-22 20:35:54,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 6019.0). Total num frames: 21174272. Throughput: 0: 6076.5. Samples: 21184286. Policy #0 lag: (min: 2.0, avg: 20.9, max: 38.0) +[2026-07-22 20:35:54,879][43431] Avg episode reward: [(0, '1849.849')] +[2026-07-22 20:35:55,690][50205] Updated weights for policy 0, policy_version 41365 (0.0011) +[2026-07-22 20:35:56,209][50205] Updated weights for policy 0, policy_version 41375 (0.0012) +[2026-07-22 20:35:57,449][50205] Updated weights for policy 0, policy_version 41385 (0.0011) +[2026-07-22 20:35:57,885][50205] Updated weights for policy 0, policy_version 41395 (0.0020) +[2026-07-22 20:35:58,980][50205] Updated weights for policy 0, policy_version 41405 (0.0015) +[2026-07-22 20:35:59,495][50205] Updated weights for policy 0, policy_version 41415 (0.0016) +[2026-07-22 20:35:59,877][43431] Fps is (10 sec: 5941.1, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 21204992. Throughput: 0: 6080.9. Samples: 21202632. Policy #0 lag: (min: 2.0, avg: 20.9, max: 38.0) +[2026-07-22 20:35:59,878][43431] Avg episode reward: [(0, '1691.418')] +[2026-07-22 20:36:00,590][50205] Updated weights for policy 0, policy_version 41425 (0.0011) +[2026-07-22 20:36:01,424][50205] Updated weights for policy 0, policy_version 41435 (0.0012) +[2026-07-22 20:36:02,632][50205] Updated weights for policy 0, policy_version 41445 (0.0011) +[2026-07-22 20:36:02,991][50205] Updated weights for policy 0, policy_version 41455 (0.0011) +[2026-07-22 20:36:04,066][50205] Updated weights for policy 0, policy_version 41465 (0.0015) +[2026-07-22 20:36:04,777][50205] Updated weights for policy 0, policy_version 41475 (0.0011) +[2026-07-22 20:36:04,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6075.8, 300 sec: 6032.9). Total num frames: 21235712. Throughput: 0: 6071.9. Samples: 21238688. Policy #0 lag: (min: 2.0, avg: 20.9, max: 38.0) +[2026-07-22 20:36:04,878][43431] Avg episode reward: [(0, '1685.339')] +[2026-07-22 20:36:05,882][50205] Updated weights for policy 0, policy_version 41485 (0.0016) +[2026-07-22 20:36:06,406][50205] Updated weights for policy 0, policy_version 41495 (0.0013) +[2026-07-22 20:36:07,334][50205] Updated weights for policy 0, policy_version 41505 (0.0013) +[2026-07-22 20:36:08,273][50205] Updated weights for policy 0, policy_version 41515 (0.0016) +[2026-07-22 20:36:09,196][50205] Updated weights for policy 0, policy_version 41525 (0.0010) +[2026-07-22 20:36:09,819][50205] Updated weights for policy 0, policy_version 41535 (0.0016) +[2026-07-22 20:36:09,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6075.7, 300 sec: 6039.9). Total num frames: 21266432. Throughput: 0: 6063.9. Samples: 21274796. Policy #0 lag: (min: 2.0, avg: 20.9, max: 38.0) +[2026-07-22 20:36:09,878][43431] Avg episode reward: [(0, '1725.259')] +[2026-07-22 20:36:10,907][50205] Updated weights for policy 0, policy_version 41545 (0.0012) +[2026-07-22 20:36:11,620][50205] Updated weights for policy 0, policy_version 41555 (0.0011) +[2026-07-22 20:36:12,456][50205] Updated weights for policy 0, policy_version 41565 (0.0011) +[2026-07-22 20:36:13,299][50205] Updated weights for policy 0, policy_version 41575 (0.0012) +[2026-07-22 20:36:14,186][50205] Updated weights for policy 0, policy_version 41585 (0.0012) +[2026-07-22 20:36:14,877][43431] Fps is (10 sec: 5734.4, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 21293056. Throughput: 0: 6061.1. Samples: 21293004. Policy #0 lag: (min: 2.0, avg: 20.9, max: 38.0) +[2026-07-22 20:36:14,878][43431] Avg episode reward: [(0, '1820.441')] +[2026-07-22 20:36:15,258][50205] Updated weights for policy 0, policy_version 41597 (0.0011) +[2026-07-22 20:36:16,343][50205] Updated weights for policy 0, policy_version 41607 (0.0016) +[2026-07-22 20:36:16,810][50205] Updated weights for policy 0, policy_version 41617 (0.0011) +[2026-07-22 20:36:17,546][50205] Updated weights for policy 0, policy_version 41627 (0.0012) +[2026-07-22 20:36:18,870][50205] Updated weights for policy 0, policy_version 41637 (0.0015) +[2026-07-22 20:36:19,499][50205] Updated weights for policy 0, policy_version 41648 (0.0012) +[2026-07-22 20:36:19,877][43431] Fps is (10 sec: 5939.3, 60 sec: 6075.7, 300 sec: 6039.9). Total num frames: 21325824. Throughput: 0: 6053.2. Samples: 21329100. Policy #0 lag: (min: 2.0, avg: 20.9, max: 38.0) +[2026-07-22 20:36:19,878][43431] Avg episode reward: [(0, '1931.207')] +[2026-07-22 20:36:20,243][50205] Updated weights for policy 0, policy_version 41658 (0.0012) +[2026-07-22 20:36:21,373][50205] Updated weights for policy 0, policy_version 41668 (0.0012) +[2026-07-22 20:36:22,027][50205] Updated weights for policy 0, policy_version 41679 (0.0011) +[2026-07-22 20:36:23,169][50205] Updated weights for policy 0, policy_version 41689 (0.0015) +[2026-07-22 20:36:24,004][50205] Updated weights for policy 0, policy_version 41699 (0.0011) +[2026-07-22 20:36:24,552][50205] Updated weights for policy 0, policy_version 41710 (0.0011) +[2026-07-22 20:36:24,877][43431] Fps is (10 sec: 6348.8, 60 sec: 6075.7, 300 sec: 6039.9). Total num frames: 21356544. Throughput: 0: 6044.9. Samples: 21365228. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 20:36:24,878][43431] Avg episode reward: [(0, '1748.680')] +[2026-07-22 20:36:25,415][50205] Updated weights for policy 0, policy_version 41720 (0.0011) +[2026-07-22 20:36:26,677][50205] Updated weights for policy 0, policy_version 41730 (0.0011) +[2026-07-22 20:36:27,273][50205] Updated weights for policy 0, policy_version 41740 (0.0013) +[2026-07-22 20:36:27,947][50205] Updated weights for policy 0, policy_version 41750 (0.0014) +[2026-07-22 20:36:28,966][50205] Updated weights for policy 0, policy_version 41760 (0.0011) +[2026-07-22 20:36:29,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 21385216. Throughput: 0: 6043.5. Samples: 21383354. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 20:36:29,878][43431] Avg episode reward: [(0, '1799.467')] +[2026-07-22 20:36:29,895][50205] Updated weights for policy 0, policy_version 41770 (0.0013) +[2026-07-22 20:36:30,555][50205] Updated weights for policy 0, policy_version 41780 (0.0011) +[2026-07-22 20:36:31,532][50205] Updated weights for policy 0, policy_version 41790 (0.0011) +[2026-07-22 20:36:32,340][50205] Updated weights for policy 0, policy_version 41800 (0.0016) +[2026-07-22 20:36:33,370][50205] Updated weights for policy 0, policy_version 41810 (0.0022) +[2026-07-22 20:36:34,083][50205] Updated weights for policy 0, policy_version 41820 (0.0012) +[2026-07-22 20:36:34,875][50205] Updated weights for policy 0, policy_version 41830 (0.0011) +[2026-07-22 20:36:34,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 21415936. Throughput: 0: 6046.5. Samples: 21419896. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 20:36:34,878][43431] Avg episode reward: [(0, '1741.872')] +[2026-07-22 20:36:35,492][50205] Updated weights for policy 0, policy_version 41840 (0.0017) +[2026-07-22 20:36:36,812][50205] Updated weights for policy 0, policy_version 41850 (0.0020) +[2026-07-22 20:36:36,892][49527] Signal inference workers to stop experience collection... (750 times) +[2026-07-22 20:36:36,892][49527] Signal inference workers to resume experience collection... (750 times) +[2026-07-22 20:36:36,908][50205] InferenceWorker_p0-w0: stopping experience collection (750 times) +[2026-07-22 20:36:36,908][50205] InferenceWorker_p0-w0: resuming experience collection (750 times) +[2026-07-22 20:36:37,292][50205] Updated weights for policy 0, policy_version 41860 (0.0011) +[2026-07-22 20:36:38,159][50205] Updated weights for policy 0, policy_version 41870 (0.0013) +[2026-07-22 20:36:39,022][50205] Updated weights for policy 0, policy_version 41880 (0.0015) +[2026-07-22 20:36:39,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 6046.8). Total num frames: 21446656. Throughput: 0: 6045.8. Samples: 21456348. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 20:36:39,878][43431] Avg episode reward: [(0, '1737.245')] +[2026-07-22 20:36:40,007][50205] Updated weights for policy 0, policy_version 41890 (0.0019) +[2026-07-22 20:36:40,863][50205] Updated weights for policy 0, policy_version 41900 (0.0011) +[2026-07-22 20:36:41,584][50205] Updated weights for policy 0, policy_version 41910 (0.0011) +[2026-07-22 20:36:42,290][50205] Updated weights for policy 0, policy_version 41920 (0.0011) +[2026-07-22 20:36:43,412][50205] Updated weights for policy 0, policy_version 41930 (0.0013) +[2026-07-22 20:36:43,941][50205] Updated weights for policy 0, policy_version 41940 (0.0010) +[2026-07-22 20:36:44,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 6039.9). Total num frames: 21477376. Throughput: 0: 6044.9. Samples: 21474654. Policy #0 lag: (min: 3.0, avg: 18.9, max: 35.0) +[2026-07-22 20:36:44,878][43431] Avg episode reward: [(0, '1802.333')] +[2026-07-22 20:36:45,237][50205] Updated weights for policy 0, policy_version 41951 (0.0011) +[2026-07-22 20:36:46,190][50205] Updated weights for policy 0, policy_version 41961 (0.0011) +[2026-07-22 20:36:46,688][50205] Updated weights for policy 0, policy_version 41971 (0.0013) +[2026-07-22 20:36:47,892][50205] Updated weights for policy 0, policy_version 41981 (0.0011) +[2026-07-22 20:36:48,481][50205] Updated weights for policy 0, policy_version 41991 (0.0011) +[2026-07-22 20:36:49,187][50205] Updated weights for policy 0, policy_version 42001 (0.0016) +[2026-07-22 20:36:49,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.9, 300 sec: 6039.9). Total num frames: 21508096. Throughput: 0: 6048.4. Samples: 21510866. Policy #0 lag: (min: 4.0, avg: 19.1, max: 36.0) +[2026-07-22 20:36:49,878][43431] Avg episode reward: [(0, '1614.916')] +[2026-07-22 20:36:50,400][50205] Updated weights for policy 0, policy_version 42011 (0.0016) +[2026-07-22 20:36:51,339][50205] Updated weights for policy 0, policy_version 42021 (0.0014) +[2026-07-22 20:36:51,719][50205] Updated weights for policy 0, policy_version 42031 (0.0010) +[2026-07-22 20:36:52,967][50205] Updated weights for policy 0, policy_version 42041 (0.0012) +[2026-07-22 20:36:53,704][50205] Updated weights for policy 0, policy_version 42051 (0.0016) +[2026-07-22 20:36:54,463][50205] Updated weights for policy 0, policy_version 42061 (0.0017) +[2026-07-22 20:36:54,868][50205] Updated weights for policy 0, policy_version 42071 (0.0019) +[2026-07-22 20:36:54,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6075.7, 300 sec: 6032.9). Total num frames: 21538816. Throughput: 0: 6055.8. Samples: 21547306. Policy #0 lag: (min: 4.0, avg: 19.1, max: 36.0) +[2026-07-22 20:36:54,878][43431] Avg episode reward: [(0, '1785.814')] +[2026-07-22 20:36:56,038][50205] Updated weights for policy 0, policy_version 42081 (0.0015) +[2026-07-22 20:36:56,881][50205] Updated weights for policy 0, policy_version 42091 (0.0013) +[2026-07-22 20:36:58,011][50205] Updated weights for policy 0, policy_version 42101 (0.0014) +[2026-07-22 20:36:58,479][50205] Updated weights for policy 0, policy_version 42111 (0.0011) +[2026-07-22 20:36:59,433][50205] Updated weights for policy 0, policy_version 42121 (0.0018) +[2026-07-22 20:36:59,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6075.7, 300 sec: 6046.8). Total num frames: 21569536. Throughput: 0: 6059.3. Samples: 21565672. Policy #0 lag: (min: 4.0, avg: 19.1, max: 36.0) +[2026-07-22 20:36:59,878][43431] Avg episode reward: [(0, '1757.248')] +[2026-07-22 20:37:00,019][50205] Updated weights for policy 0, policy_version 42131 (0.0015) +[2026-07-22 20:37:01,342][50205] Updated weights for policy 0, policy_version 42141 (0.0012) +[2026-07-22 20:37:01,890][50205] Updated weights for policy 0, policy_version 42151 (0.0012) +[2026-07-22 20:37:02,964][50205] Updated weights for policy 0, policy_version 42161 (0.0011) +[2026-07-22 20:37:04,151][50205] Updated weights for policy 0, policy_version 42171 (0.0015) +[2026-07-22 20:37:04,878][43431] Fps is (10 sec: 5734.3, 60 sec: 6007.4, 300 sec: 6026.0). Total num frames: 21596160. Throughput: 0: 6015.8. Samples: 21599814. Policy #0 lag: (min: 4.0, avg: 19.1, max: 36.0) +[2026-07-22 20:37:04,878][43431] Avg episode reward: [(0, '1689.687')] +[2026-07-22 20:37:05,093][50205] Updated weights for policy 0, policy_version 42181 (0.0012) +[2026-07-22 20:37:05,609][50205] Updated weights for policy 0, policy_version 42191 (0.0011) +[2026-07-22 20:37:06,800][50205] Updated weights for policy 0, policy_version 42201 (0.0011) +[2026-07-22 20:37:07,394][50205] Updated weights for policy 0, policy_version 42211 (0.0015) +[2026-07-22 20:37:08,189][50205] Updated weights for policy 0, policy_version 42221 (0.0013) +[2026-07-22 20:37:09,117][50205] Updated weights for policy 0, policy_version 42231 (0.0012) +[2026-07-22 20:37:09,877][43431] Fps is (10 sec: 5734.3, 60 sec: 6007.5, 300 sec: 6032.9). Total num frames: 21626880. Throughput: 0: 6020.6. Samples: 21636158. Policy #0 lag: (min: 4.0, avg: 19.1, max: 36.0) +[2026-07-22 20:37:09,878][43431] Avg episode reward: [(0, '1718.783')] +[2026-07-22 20:37:09,885][50205] Updated weights for policy 0, policy_version 42241 (0.0016) +[2026-07-22 20:37:10,691][50205] Updated weights for policy 0, policy_version 42251 (0.0013) +[2026-07-22 20:37:11,827][50205] Updated weights for policy 0, policy_version 42261 (0.0013) +[2026-07-22 20:37:12,500][50205] Updated weights for policy 0, policy_version 42271 (0.0015) +[2026-07-22 20:37:13,211][50205] Updated weights for policy 0, policy_version 42281 (0.0011) +[2026-07-22 20:37:14,041][50205] Updated weights for policy 0, policy_version 42291 (0.0013) +[2026-07-22 20:37:14,877][43431] Fps is (10 sec: 5939.4, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 21655552. Throughput: 0: 6023.2. Samples: 21654398. Policy #0 lag: (min: 3.0, avg: 20.0, max: 38.0) +[2026-07-22 20:37:14,878][43431] Avg episode reward: [(0, '1759.350')] +[2026-07-22 20:37:15,102][50205] Updated weights for policy 0, policy_version 42301 (0.0013) +[2026-07-22 20:37:15,902][50205] Updated weights for policy 0, policy_version 42311 (0.0012) +[2026-07-22 20:37:16,575][50205] Updated weights for policy 0, policy_version 42321 (0.0011) +[2026-07-22 20:37:17,658][50205] Updated weights for policy 0, policy_version 42331 (0.0010) +[2026-07-22 20:37:18,576][50205] Updated weights for policy 0, policy_version 42342 (0.0011) +[2026-07-22 20:37:19,260][50205] Updated weights for policy 0, policy_version 42352 (0.0011) +[2026-07-22 20:37:19,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 21688320. Throughput: 0: 6013.7. Samples: 21690514. Policy #0 lag: (min: 3.0, avg: 20.0, max: 38.0) +[2026-07-22 20:37:19,878][43431] Avg episode reward: [(0, '1742.824')] +[2026-07-22 20:37:20,234][50205] Updated weights for policy 0, policy_version 42362 (0.0010) +[2026-07-22 20:37:21,084][50205] Updated weights for policy 0, policy_version 42372 (0.0010) +[2026-07-22 20:37:21,870][50205] Updated weights for policy 0, policy_version 42382 (0.0015) +[2026-07-22 20:37:22,756][50205] Updated weights for policy 0, policy_version 42392 (0.0015) +[2026-07-22 20:37:23,627][50205] Updated weights for policy 0, policy_version 42402 (0.0012) +[2026-07-22 20:37:24,166][50205] Updated weights for policy 0, policy_version 42412 (0.0015) +[2026-07-22 20:37:24,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 6032.9). Total num frames: 21716992. Throughput: 0: 6019.7. Samples: 21727234. Policy #0 lag: (min: 3.0, avg: 20.0, max: 38.0) +[2026-07-22 20:37:24,878][43431] Avg episode reward: [(0, '1767.498')] +[2026-07-22 20:37:25,255][50205] Updated weights for policy 0, policy_version 42422 (0.0011) +[2026-07-22 20:37:26,208][50205] Updated weights for policy 0, policy_version 42432 (0.0014) +[2026-07-22 20:37:26,782][50205] Updated weights for policy 0, policy_version 42442 (0.0019) +[2026-07-22 20:37:27,602][50205] Updated weights for policy 0, policy_version 42452 (0.0015) +[2026-07-22 20:37:28,923][50205] Updated weights for policy 0, policy_version 42462 (0.0010) +[2026-07-22 20:37:29,355][50205] Updated weights for policy 0, policy_version 42472 (0.0013) +[2026-07-22 20:37:29,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 21747712. Throughput: 0: 6016.3. Samples: 21745386. Policy #0 lag: (min: 3.0, avg: 20.0, max: 38.0) +[2026-07-22 20:37:29,878][43431] Avg episode reward: [(0, '1796.225')] +[2026-07-22 20:37:30,046][50205] Updated weights for policy 0, policy_version 42482 (0.0013) +[2026-07-22 20:37:31,074][50205] Updated weights for policy 0, policy_version 42492 (0.0011) +[2026-07-22 20:37:31,921][50205] Updated weights for policy 0, policy_version 42502 (0.0011) +[2026-07-22 20:37:32,846][50205] Updated weights for policy 0, policy_version 42512 (0.0011) +[2026-07-22 20:37:33,614][50205] Updated weights for policy 0, policy_version 42522 (0.0011) +[2026-07-22 20:37:34,314][50205] Updated weights for policy 0, policy_version 42532 (0.0011) +[2026-07-22 20:37:34,877][43431] Fps is (10 sec: 6348.6, 60 sec: 6075.7, 300 sec: 6039.9). Total num frames: 21780480. Throughput: 0: 6021.6. Samples: 21781842. Policy #0 lag: (min: 3.0, avg: 20.0, max: 38.0) +[2026-07-22 20:37:34,878][43431] Avg episode reward: [(0, '1751.214')] +[2026-07-22 20:37:35,448][50205] Updated weights for policy 0, policy_version 42542 (0.0019) +[2026-07-22 20:37:36,576][50205] Updated weights for policy 0, policy_version 42553 (0.0017) +[2026-07-22 20:37:36,974][50205] Updated weights for policy 0, policy_version 42563 (0.0011) +[2026-07-22 20:37:37,908][50205] Updated weights for policy 0, policy_version 42573 (0.0011) +[2026-07-22 20:37:38,863][50205] Updated weights for policy 0, policy_version 42583 (0.0012) +[2026-07-22 20:37:39,819][50205] Updated weights for policy 0, policy_version 42593 (0.0011) +[2026-07-22 20:37:39,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6007.4, 300 sec: 6032.9). Total num frames: 21807104. Throughput: 0: 6021.4. Samples: 21818270. Policy #0 lag: (min: 3.0, avg: 20.0, max: 38.0) +[2026-07-22 20:37:39,878][43431] Avg episode reward: [(0, '1782.045')] +[2026-07-22 20:37:40,502][50205] Updated weights for policy 0, policy_version 42604 (0.0012) +[2026-07-22 20:37:41,381][50205] Updated weights for policy 0, policy_version 42614 (0.0017) +[2026-07-22 20:37:42,169][50205] Updated weights for policy 0, policy_version 42624 (0.0013) +[2026-07-22 20:37:43,303][50205] Updated weights for policy 0, policy_version 42634 (0.0016) +[2026-07-22 20:37:44,001][50205] Updated weights for policy 0, policy_version 42644 (0.0012) +[2026-07-22 20:37:44,877][43431] Fps is (10 sec: 5734.6, 60 sec: 6007.5, 300 sec: 6032.9). Total num frames: 21837824. Throughput: 0: 6009.4. Samples: 21836096. Policy #0 lag: (min: 3.0, avg: 20.5, max: 47.0) +[2026-07-22 20:37:44,878][43431] Avg episode reward: [(0, '1704.349')] +[2026-07-22 20:37:45,023][50205] Updated weights for policy 0, policy_version 42654 (0.0011) +[2026-07-22 20:37:45,899][50205] Updated weights for policy 0, policy_version 42665 (0.0011) +[2026-07-22 20:37:46,673][50205] Updated weights for policy 0, policy_version 42675 (0.0011) +[2026-07-22 20:37:47,479][50205] Updated weights for policy 0, policy_version 42685 (0.0011) +[2026-07-22 20:37:47,942][50205] Updated weights for policy 0, policy_version 42695 (0.0019) +[2026-07-22 20:37:49,298][50205] Updated weights for policy 0, policy_version 42705 (0.0015) +[2026-07-22 20:37:49,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6007.5, 300 sec: 6032.9). Total num frames: 21868544. Throughput: 0: 6056.4. Samples: 21872350. Policy #0 lag: (min: 3.0, avg: 20.5, max: 47.0) +[2026-07-22 20:37:49,878][43431] Avg episode reward: [(0, '1891.850')] +[2026-07-22 20:37:50,155][50205] Updated weights for policy 0, policy_version 42715 (0.0011) +[2026-07-22 20:37:50,780][50205] Updated weights for policy 0, policy_version 42725 (0.0010) +[2026-07-22 20:37:51,495][50205] Updated weights for policy 0, policy_version 42735 (0.0014) +[2026-07-22 20:37:52,702][50205] Updated weights for policy 0, policy_version 42745 (0.0021) +[2026-07-22 20:37:53,269][50205] Updated weights for policy 0, policy_version 42755 (0.0011) +[2026-07-22 20:37:54,273][50205] Updated weights for policy 0, policy_version 42765 (0.0014) +[2026-07-22 20:37:54,878][43431] Fps is (10 sec: 6143.8, 60 sec: 6007.4, 300 sec: 6032.9). Total num frames: 21899264. Throughput: 0: 6056.3. Samples: 21908690. Policy #0 lag: (min: 3.0, avg: 20.5, max: 47.0) +[2026-07-22 20:37:54,879][43431] Avg episode reward: [(0, '1709.311')] +[2026-07-22 20:37:55,081][50205] Updated weights for policy 0, policy_version 42775 (0.0011) +[2026-07-22 20:37:55,939][50205] Updated weights for policy 0, policy_version 42785 (0.0016) +[2026-07-22 20:37:56,845][50205] Updated weights for policy 0, policy_version 42795 (0.0011) +[2026-07-22 20:37:57,706][50205] Updated weights for policy 0, policy_version 42805 (0.0010) +[2026-07-22 20:37:58,217][50205] Updated weights for policy 0, policy_version 42815 (0.0016) +[2026-07-22 20:37:59,388][50205] Updated weights for policy 0, policy_version 42825 (0.0011) +[2026-07-22 20:37:59,877][43431] Fps is (10 sec: 5939.1, 60 sec: 5973.3, 300 sec: 6032.9). Total num frames: 21927936. Throughput: 0: 6057.7. Samples: 21926998. Policy #0 lag: (min: 3.0, avg: 20.5, max: 47.0) +[2026-07-22 20:37:59,878][43431] Avg episode reward: [(0, '1620.671')] +[2026-07-22 20:38:00,200][50205] Updated weights for policy 0, policy_version 42835 (0.0016) +[2026-07-22 20:38:01,120][50205] Updated weights for policy 0, policy_version 42845 (0.0011) +[2026-07-22 20:38:02,199][50205] Updated weights for policy 0, policy_version 42857 (0.0011) +[2026-07-22 20:38:03,008][50205] Updated weights for policy 0, policy_version 42867 (0.0011) +[2026-07-22 20:38:03,978][50205] Updated weights for policy 0, policy_version 42877 (0.0014) +[2026-07-22 20:38:04,852][50205] Updated weights for policy 0, policy_version 42887 (0.0018) +[2026-07-22 20:38:04,877][43431] Fps is (10 sec: 5734.5, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 21956608. Throughput: 0: 6040.2. Samples: 21962322. Policy #0 lag: (min: 3.0, avg: 20.5, max: 47.0) +[2026-07-22 20:38:04,878][43431] Avg episode reward: [(0, '1802.833')] +[2026-07-22 20:38:05,476][50205] Updated weights for policy 0, policy_version 42897 (0.0012) +[2026-07-22 20:38:06,385][50205] Updated weights for policy 0, policy_version 42907 (0.0015) +[2026-07-22 20:38:07,522][50205] Updated weights for policy 0, policy_version 42917 (0.0016) +[2026-07-22 20:38:08,394][50205] Updated weights for policy 0, policy_version 42928 (0.0021) +[2026-07-22 20:38:09,019][50205] Updated weights for policy 0, policy_version 42938 (0.0016) +[2026-07-22 20:38:09,537][50205] Updated weights for policy 0, policy_version 42948 (0.0011) +[2026-07-22 20:38:09,877][43431] Fps is (10 sec: 6144.2, 60 sec: 6041.6, 300 sec: 6039.9). Total num frames: 21989376. Throughput: 0: 6006.9. Samples: 21997544. Policy #0 lag: (min: 4.0, avg: 20.5, max: 36.0) +[2026-07-22 20:38:09,878][43431] Avg episode reward: [(0, '1723.122')] +[2026-07-22 20:38:11,135][50205] Updated weights for policy 0, policy_version 42958 (0.0011) +[2026-07-22 20:38:11,875][50205] Updated weights for policy 0, policy_version 42968 (0.0011) +[2026-07-22 20:38:12,232][50205] Updated weights for policy 0, policy_version 42980 (0.0010) +[2026-07-22 20:38:14,008][50205] Updated weights for policy 0, policy_version 42990 (0.0011) +[2026-07-22 20:38:14,639][50205] Updated weights for policy 0, policy_version 43000 (0.0011) +[2026-07-22 20:38:14,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 22018048. Throughput: 0: 5988.1. Samples: 22014852. Policy #0 lag: (min: 4.0, avg: 20.5, max: 36.0) +[2026-07-22 20:38:14,878][43431] Avg episode reward: [(0, '1739.349')] +[2026-07-22 20:38:15,433][50205] Updated weights for policy 0, policy_version 43010 (0.0011) +[2026-07-22 20:38:16,441][50205] Updated weights for policy 0, policy_version 43020 (0.0016) +[2026-07-22 20:38:17,291][50205] Updated weights for policy 0, policy_version 43030 (0.0020) +[2026-07-22 20:38:17,649][50205] Updated weights for policy 0, policy_version 43040 (0.0014) +[2026-07-22 20:38:19,000][50205] Updated weights for policy 0, policy_version 43050 (0.0016) +[2026-07-22 20:38:19,667][50205] Updated weights for policy 0, policy_version 43060 (0.0013) +[2026-07-22 20:38:19,878][43431] Fps is (10 sec: 5733.9, 60 sec: 5973.3, 300 sec: 6026.0). Total num frames: 22046720. Throughput: 0: 5974.1. Samples: 22050682. Policy #0 lag: (min: 4.0, avg: 20.5, max: 36.0) +[2026-07-22 20:38:19,880][43431] Avg episode reward: [(0, '1640.185')] +[2026-07-22 20:38:20,279][50205] Updated weights for policy 0, policy_version 43070 (0.0013) +[2026-07-22 20:38:21,447][50205] Updated weights for policy 0, policy_version 43080 (0.0011) +[2026-07-22 20:38:22,518][50205] Updated weights for policy 0, policy_version 43092 (0.0011) +[2026-07-22 20:38:22,929][50205] Updated weights for policy 0, policy_version 43102 (0.0011) +[2026-07-22 20:38:24,252][50205] Updated weights for policy 0, policy_version 43112 (0.0012) +[2026-07-22 20:38:24,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5973.3, 300 sec: 6019.0). Total num frames: 22075392. Throughput: 0: 5964.9. Samples: 22086690. Policy #0 lag: (min: 4.0, avg: 20.5, max: 36.0) +[2026-07-22 20:38:24,878][43431] Avg episode reward: [(0, '1723.247')] +[2026-07-22 20:38:25,131][50205] Updated weights for policy 0, policy_version 43122 (0.0010) +[2026-07-22 20:38:25,709][50205] Updated weights for policy 0, policy_version 43132 (0.0012) +[2026-07-22 20:38:26,770][50205] Updated weights for policy 0, policy_version 43142 (0.0017) +[2026-07-22 20:38:27,504][50205] Updated weights for policy 0, policy_version 43152 (0.0016) +[2026-07-22 20:38:28,344][50205] Updated weights for policy 0, policy_version 43162 (0.0014) +[2026-07-22 20:38:29,373][50205] Updated weights for policy 0, policy_version 43172 (0.0016) +[2026-07-22 20:38:29,877][43431] Fps is (10 sec: 6144.5, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 22108160. Throughput: 0: 5968.4. Samples: 22104672. Policy #0 lag: (min: 4.0, avg: 20.5, max: 36.0) +[2026-07-22 20:38:29,878][43431] Avg episode reward: [(0, '1589.277')] +[2026-07-22 20:38:30,020][50205] Updated weights for policy 0, policy_version 43182 (0.0015) +[2026-07-22 20:38:30,736][50205] Updated weights for policy 0, policy_version 43192 (0.0011) +[2026-07-22 20:38:32,070][50205] Updated weights for policy 0, policy_version 43202 (0.0016) +[2026-07-22 20:38:32,596][50205] Updated weights for policy 0, policy_version 43212 (0.0013) +[2026-07-22 20:38:33,399][50205] Updated weights for policy 0, policy_version 43222 (0.0021) +[2026-07-22 20:38:34,374][50205] Updated weights for policy 0, policy_version 43232 (0.0016) +[2026-07-22 20:38:34,877][43431] Fps is (10 sec: 6144.0, 60 sec: 5939.2, 300 sec: 6019.1). Total num frames: 22136832. Throughput: 0: 5971.9. Samples: 22141086. Policy #0 lag: (min: 3.0, avg: 16.1, max: 39.0) +[2026-07-22 20:38:34,878][43431] Avg episode reward: [(0, '1895.874')] +[2026-07-22 20:38:35,223][50205] Updated weights for policy 0, policy_version 43242 (0.0011) +[2026-07-22 20:38:36,069][50205] Updated weights for policy 0, policy_version 43252 (0.0011) +[2026-07-22 20:38:36,924][50205] Updated weights for policy 0, policy_version 43262 (0.0014) +[2026-07-22 20:38:37,608][50205] Updated weights for policy 0, policy_version 43272 (0.0015) +[2026-07-22 20:38:38,617][50205] Updated weights for policy 0, policy_version 43282 (0.0011) +[2026-07-22 20:38:39,628][50205] Updated weights for policy 0, policy_version 43292 (0.0018) +[2026-07-22 20:38:39,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6007.5, 300 sec: 6019.0). Total num frames: 22167552. Throughput: 0: 5976.8. Samples: 22177642. Policy #0 lag: (min: 3.0, avg: 16.1, max: 39.0) +[2026-07-22 20:38:39,878][43431] Avg episode reward: [(0, '1745.372')] +[2026-07-22 20:38:40,169][50205] Updated weights for policy 0, policy_version 43302 (0.0013) +[2026-07-22 20:38:40,911][50205] Updated weights for policy 0, policy_version 43312 (0.0011) +[2026-07-22 20:38:42,088][50205] Updated weights for policy 0, policy_version 43322 (0.0012) +[2026-07-22 20:38:42,778][50205] Updated weights for policy 0, policy_version 43332 (0.0011) +[2026-07-22 20:38:43,540][50205] Updated weights for policy 0, policy_version 43342 (0.0011) +[2026-07-22 20:38:44,300][50205] Updated weights for policy 0, policy_version 43352 (0.0010) +[2026-07-22 20:38:44,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 22198272. Throughput: 0: 5971.4. Samples: 22195710. Policy #0 lag: (min: 3.0, avg: 16.1, max: 39.0) +[2026-07-22 20:38:44,878][43431] Avg episode reward: [(0, '1710.915')] +[2026-07-22 20:38:45,391][50205] Updated weights for policy 0, policy_version 43362 (0.0021) +[2026-07-22 20:38:46,233][50205] Updated weights for policy 0, policy_version 43372 (0.0015) +[2026-07-22 20:38:46,905][50205] Updated weights for policy 0, policy_version 43382 (0.0016) +[2026-07-22 20:38:47,868][50205] Updated weights for policy 0, policy_version 43392 (0.0015) +[2026-07-22 20:38:48,780][50205] Updated weights for policy 0, policy_version 43402 (0.0011) +[2026-07-22 20:38:49,484][50205] Updated weights for policy 0, policy_version 43412 (0.0013) +[2026-07-22 20:38:49,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5973.4, 300 sec: 6019.0). Total num frames: 22226944. Throughput: 0: 5989.4. Samples: 22231844. Policy #0 lag: (min: 3.0, avg: 16.1, max: 39.0) +[2026-07-22 20:38:49,878][43431] Avg episode reward: [(0, '1819.158')] +[2026-07-22 20:38:50,451][50205] Updated weights for policy 0, policy_version 43422 (0.0013) +[2026-07-22 20:38:50,978][50205] Updated weights for policy 0, policy_version 43432 (0.0015) +[2026-07-22 20:38:52,294][50205] Updated weights for policy 0, policy_version 43442 (0.0014) +[2026-07-22 20:38:52,950][50205] Updated weights for policy 0, policy_version 43452 (0.0016) +[2026-07-22 20:38:53,808][50205] Updated weights for policy 0, policy_version 43462 (0.0014) +[2026-07-22 20:38:54,182][50205] Updated weights for policy 0, policy_version 43472 (0.0011) +[2026-07-22 20:38:54,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5973.4, 300 sec: 6026.0). Total num frames: 22257664. Throughput: 0: 6017.4. Samples: 22268326. Policy #0 lag: (min: 3.0, avg: 16.1, max: 39.0) +[2026-07-22 20:38:54,878][43431] Avg episode reward: [(0, '1826.507')] +[2026-07-22 20:38:55,570][50205] Updated weights for policy 0, policy_version 43482 (0.0013) +[2026-07-22 20:38:56,186][50205] Updated weights for policy 0, policy_version 43492 (0.0017) +[2026-07-22 20:38:57,312][50205] Updated weights for policy 0, policy_version 43502 (0.0017) +[2026-07-22 20:38:58,044][50205] Updated weights for policy 0, policy_version 43512 (0.0014) +[2026-07-22 20:38:58,788][50205] Updated weights for policy 0, policy_version 43522 (0.0017) +[2026-07-22 20:38:59,639][50205] Updated weights for policy 0, policy_version 43532 (0.0016) +[2026-07-22 20:38:59,877][43431] Fps is (10 sec: 6144.0, 60 sec: 6007.5, 300 sec: 6032.9). Total num frames: 22288384. Throughput: 0: 6036.2. Samples: 22286480. Policy #0 lag: (min: 3.0, avg: 16.1, max: 39.0) +[2026-07-22 20:38:59,878][43431] Avg episode reward: [(0, '1685.823')] +[2026-07-22 20:39:00,669][50205] Updated weights for policy 0, policy_version 43542 (0.0011) +[2026-07-22 20:39:01,173][50205] Updated weights for policy 0, policy_version 43552 (0.0011) +[2026-07-22 20:39:02,142][50205] Updated weights for policy 0, policy_version 43562 (0.0011) +[2026-07-22 20:39:03,239][50205] Updated weights for policy 0, policy_version 43572 (0.0019) +[2026-07-22 20:39:03,910][50205] Updated weights for policy 0, policy_version 43582 (0.0012) +[2026-07-22 20:39:04,321][50205] Updated weights for policy 0, policy_version 43592 (0.0011) +[2026-07-22 20:39:04,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 22319104. Throughput: 0: 6049.7. Samples: 22322912. Policy #0 lag: (min: 3.0, avg: 20.3, max: 35.0) +[2026-07-22 20:39:04,878][43431] Avg episode reward: [(0, '1647.510')] +[2026-07-22 20:39:05,801][50205] Updated weights for policy 0, policy_version 43602 (0.0010) +[2026-07-22 20:39:06,299][50205] Updated weights for policy 0, policy_version 43612 (0.0017) +[2026-07-22 20:39:07,381][50205] Updated weights for policy 0, policy_version 43622 (0.0015) +[2026-07-22 20:39:07,845][50205] Updated weights for policy 0, policy_version 43632 (0.0016) +[2026-07-22 20:39:08,913][50205] Updated weights for policy 0, policy_version 43642 (0.0015) +[2026-07-22 20:39:09,803][50205] Updated weights for policy 0, policy_version 43652 (0.0012) +[2026-07-22 20:39:09,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6007.4, 300 sec: 6039.9). Total num frames: 22349824. Throughput: 0: 6063.2. Samples: 22359534. Policy #0 lag: (min: 3.0, avg: 20.3, max: 35.0) +[2026-07-22 20:39:09,878][43431] Avg episode reward: [(0, '1763.930')] +[2026-07-22 20:39:10,874][50205] Updated weights for policy 0, policy_version 43662 (0.0011) +[2026-07-22 20:39:11,287][50205] Updated weights for policy 0, policy_version 43672 (0.0011) +[2026-07-22 20:39:12,740][50205] Updated weights for policy 0, policy_version 43682 (0.0012) +[2026-07-22 20:39:13,663][50205] Updated weights for policy 0, policy_version 43692 (0.0012) +[2026-07-22 20:39:14,259][50205] Updated weights for policy 0, policy_version 43702 (0.0016) +[2026-07-22 20:39:14,878][43431] Fps is (10 sec: 5939.0, 60 sec: 6007.4, 300 sec: 6032.9). Total num frames: 22378496. Throughput: 0: 6028.2. Samples: 22375944. Policy #0 lag: (min: 3.0, avg: 20.3, max: 35.0) +[2026-07-22 20:39:14,878][43431] Avg episode reward: [(0, '1643.478')] +[2026-07-22 20:39:15,353][50205] Updated weights for policy 0, policy_version 43714 (0.0012) +[2026-07-22 20:39:16,248][50205] Updated weights for policy 0, policy_version 43724 (0.0014) +[2026-07-22 20:39:16,965][50205] Updated weights for policy 0, policy_version 43734 (0.0019) +[2026-07-22 20:39:17,943][50205] Updated weights for policy 0, policy_version 43744 (0.0017) +[2026-07-22 20:39:18,744][50205] Updated weights for policy 0, policy_version 43754 (0.0011) +[2026-07-22 20:39:19,347][50205] Updated weights for policy 0, policy_version 43764 (0.0011) +[2026-07-22 20:39:19,877][43431] Fps is (10 sec: 5939.3, 60 sec: 6041.7, 300 sec: 6032.9). Total num frames: 22409216. Throughput: 0: 6024.4. Samples: 22412182. Policy #0 lag: (min: 3.0, avg: 20.3, max: 35.0) +[2026-07-22 20:39:19,878][43431] Avg episode reward: [(0, '1678.313')] +[2026-07-22 20:39:20,466][50205] Updated weights for policy 0, policy_version 43774 (0.0011) +[2026-07-22 20:39:21,453][50205] Updated weights for policy 0, policy_version 43784 (0.0016) +[2026-07-22 20:39:21,964][50205] Updated weights for policy 0, policy_version 43795 (0.0011) +[2026-07-22 20:39:23,192][50205] Updated weights for policy 0, policy_version 43805 (0.0011) +[2026-07-22 20:39:24,032][50205] Updated weights for policy 0, policy_version 43815 (0.0010) +[2026-07-22 20:39:24,760][50205] Updated weights for policy 0, policy_version 43825 (0.0011) +[2026-07-22 20:39:24,877][43431] Fps is (10 sec: 6144.2, 60 sec: 6075.7, 300 sec: 6032.9). Total num frames: 22439936. Throughput: 0: 6019.5. Samples: 22448520. Policy #0 lag: (min: 3.0, avg: 20.3, max: 35.0) +[2026-07-22 20:39:24,878][43431] Avg episode reward: [(0, '1795.364')] +[2026-07-22 20:39:25,488][50205] Updated weights for policy 0, policy_version 43835 (0.0013) +[2026-07-22 20:39:26,557][50205] Updated weights for policy 0, policy_version 43845 (0.0014) +[2026-07-22 20:39:27,133][50205] Updated weights for policy 0, policy_version 43855 (0.0010) +[2026-07-22 20:39:28,454][50205] Updated weights for policy 0, policy_version 43865 (0.0011) +[2026-07-22 20:39:28,927][50205] Updated weights for policy 0, policy_version 43875 (0.0012) +[2026-07-22 20:39:29,767][50205] Updated weights for policy 0, policy_version 43885 (0.0011) +[2026-07-22 20:39:29,877][43431] Fps is (10 sec: 6143.8, 60 sec: 6041.6, 300 sec: 6032.9). Total num frames: 22470656. Throughput: 0: 6021.5. Samples: 22466678. Policy #0 lag: (min: 2.0, avg: 20.8, max: 38.0) +[2026-07-22 20:39:29,878][43431] Avg episode reward: [(0, '1787.879')] +[2026-07-22 20:39:30,339][50205] Updated weights for policy 0, policy_version 43895 (0.0012) +[2026-07-22 20:39:31,686][50205] Updated weights for policy 0, policy_version 43905 (0.0019) +[2026-07-22 20:39:32,216][50205] Updated weights for policy 0, policy_version 43915 (0.0011) +[2026-07-22 20:39:32,949][50205] Updated weights for policy 0, policy_version 43925 (0.0012) +[2026-07-22 20:39:34,125][50205] Updated weights for policy 0, policy_version 43935 (0.0011) +[2026-07-22 20:39:34,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 22499328. Throughput: 0: 6031.8. Samples: 22503276. Policy #0 lag: (min: 2.0, avg: 20.8, max: 38.0) +[2026-07-22 20:39:34,878][43431] Avg episode reward: [(0, '1851.443')] +[2026-07-22 20:39:35,128][50205] Updated weights for policy 0, policy_version 43945 (0.0011) +[2026-07-22 20:39:35,457][50205] Updated weights for policy 0, policy_version 43955 (0.0015) +[2026-07-22 20:39:36,800][50205] Updated weights for policy 0, policy_version 43965 (0.0011) +[2026-07-22 20:39:37,296][50205] Updated weights for policy 0, policy_version 43975 (0.0016) +[2026-07-22 20:39:38,245][50205] Updated weights for policy 0, policy_version 43985 (0.0011) +[2026-07-22 20:39:39,076][50205] Updated weights for policy 0, policy_version 43995 (0.0011) +[2026-07-22 20:39:39,790][50205] Updated weights for policy 0, policy_version 44005 (0.0012) +[2026-07-22 20:39:39,877][43431] Fps is (10 sec: 6144.2, 60 sec: 6075.7, 300 sec: 6039.9). Total num frames: 22532096. Throughput: 0: 6028.5. Samples: 22539610. Policy #0 lag: (min: 2.0, avg: 20.8, max: 38.0) +[2026-07-22 20:39:39,878][43431] Avg episode reward: [(0, '1857.114')] +[2026-07-22 20:39:40,507][50205] Updated weights for policy 0, policy_version 44015 (0.0013) +[2026-07-22 20:39:41,987][50205] Updated weights for policy 0, policy_version 44025 (0.0013) +[2026-07-22 20:39:42,538][50205] Updated weights for policy 0, policy_version 44037 (0.0015) +[2026-07-22 20:39:43,248][50205] Updated weights for policy 0, policy_version 44047 (0.0017) +[2026-07-22 20:39:44,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5973.3, 300 sec: 6012.1). Total num frames: 22556672. Throughput: 0: 6024.4. Samples: 22557580. Policy #0 lag: (min: 2.0, avg: 20.8, max: 38.0) +[2026-07-22 20:39:44,878][43431] Avg episode reward: [(0, '1762.576')] +[2026-07-22 20:39:45,212][50205] Updated weights for policy 0, policy_version 44057 (0.0017) +[2026-07-22 20:39:45,600][50205] Updated weights for policy 0, policy_version 44071 (0.0020) +[2026-07-22 20:39:46,511][50205] Updated weights for policy 0, policy_version 44081 (0.0011) +[2026-07-22 20:39:47,416][50205] Updated weights for policy 0, policy_version 44091 (0.0013) +[2026-07-22 20:39:48,287][50205] Updated weights for policy 0, policy_version 44101 (0.0011) +[2026-07-22 20:39:49,050][50205] Updated weights for policy 0, policy_version 44111 (0.0015) +[2026-07-22 20:39:49,877][43431] Fps is (10 sec: 5734.3, 60 sec: 6041.6, 300 sec: 6026.0). Total num frames: 22589440. Throughput: 0: 6005.6. Samples: 22593164. Policy #0 lag: (min: 2.0, avg: 20.8, max: 38.0) +[2026-07-22 20:39:49,878][43431] Avg episode reward: [(0, '1727.744')] +[2026-07-22 20:39:50,038][50205] Updated weights for policy 0, policy_version 44121 (0.0013) +[2026-07-22 20:39:50,531][50205] Updated weights for policy 0, policy_version 44131 (0.0011) +[2026-07-22 20:39:51,659][50205] Updated weights for policy 0, policy_version 44141 (0.0013) +[2026-07-22 20:39:52,555][50205] Updated weights for policy 0, policy_version 44151 (0.0012) +[2026-07-22 20:39:53,236][50205] Updated weights for policy 0, policy_version 44161 (0.0012) +[2026-07-22 20:39:54,144][50205] Updated weights for policy 0, policy_version 44171 (0.0011) +[2026-07-22 20:39:54,877][43431] Fps is (10 sec: 6144.1, 60 sec: 6007.5, 300 sec: 6019.0). Total num frames: 22618112. Throughput: 0: 5970.4. Samples: 22628200. Policy #0 lag: (min: 2.0, avg: 20.8, max: 38.0) +[2026-07-22 20:39:54,878][43431] Avg episode reward: [(0, '1607.790')] +[2026-07-22 20:39:55,440][50205] Updated weights for policy 0, policy_version 44181 (0.0011) +[2026-07-22 20:39:55,547][49527] Signal inference workers to stop experience collection... (800 times) +[2026-07-22 20:39:55,548][49527] Signal inference workers to resume experience collection... (800 times) +[2026-07-22 20:39:55,564][50205] InferenceWorker_p0-w0: stopping experience collection (800 times) +[2026-07-22 20:39:55,564][50205] InferenceWorker_p0-w0: resuming experience collection (800 times) +[2026-07-22 20:39:55,842][50205] Updated weights for policy 0, policy_version 44191 (0.0012) +[2026-07-22 20:39:57,045][50205] Updated weights for policy 0, policy_version 44201 (0.0011) +[2026-07-22 20:39:57,977][50205] Updated weights for policy 0, policy_version 44211 (0.0010) +[2026-07-22 20:39:58,676][50205] Updated weights for policy 0, policy_version 44221 (0.0016) +[2026-07-22 20:39:59,749][50205] Updated weights for policy 0, policy_version 44231 (0.0012) +[2026-07-22 20:39:59,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5973.3, 300 sec: 6019.0). Total num frames: 22646784. Throughput: 0: 5985.2. Samples: 22645278. Policy #0 lag: (min: 0.0, avg: 15.2, max: 32.0) +[2026-07-22 20:39:59,878][43431] Avg episode reward: [(0, '1700.055')] +[2026-07-22 20:40:00,776][50205] Updated weights for policy 0, policy_version 44241 (0.0012) +[2026-07-22 20:40:01,262][50205] Updated weights for policy 0, policy_version 44251 (0.0012) +[2026-07-22 20:40:03,050][50205] Updated weights for policy 0, policy_version 44261 (0.0014) +[2026-07-22 20:40:04,000][50205] Updated weights for policy 0, policy_version 44271 (0.0011) +[2026-07-22 20:40:04,770][50205] Updated weights for policy 0, policy_version 44281 (0.0011) +[2026-07-22 20:40:04,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5905.1, 300 sec: 6005.2). Total num frames: 22673408. Throughput: 0: 5875.5. Samples: 22676578. Policy #0 lag: (min: 0.0, avg: 15.2, max: 32.0) +[2026-07-22 20:40:04,878][43431] Avg episode reward: [(0, '1854.310')] +[2026-07-22 20:40:05,469][50205] Updated weights for policy 0, policy_version 44291 (0.0013) +[2026-07-22 20:40:06,871][50205] Updated weights for policy 0, policy_version 44301 (0.0012) +[2026-07-22 20:40:07,599][50205] Updated weights for policy 0, policy_version 44311 (0.0012) +[2026-07-22 20:40:08,881][50205] Updated weights for policy 0, policy_version 44321 (0.0012) +[2026-07-22 20:40:09,724][50205] Updated weights for policy 0, policy_version 44331 (0.0026) +[2026-07-22 20:40:09,877][43431] Fps is (10 sec: 5120.1, 60 sec: 5802.7, 300 sec: 5991.3). Total num frames: 22697984. Throughput: 0: 5758.3. Samples: 22707642. Policy #0 lag: (min: 0.0, avg: 15.2, max: 32.0) +[2026-07-22 20:40:09,878][43431] Avg episode reward: [(0, '1758.755')] +[2026-07-22 20:40:10,630][50205] Updated weights for policy 0, policy_version 44341 (0.0012) +[2026-07-22 20:40:11,752][50205] Updated weights for policy 0, policy_version 44351 (0.0014) +[2026-07-22 20:40:12,722][50205] Updated weights for policy 0, policy_version 44361 (0.0011) +[2026-07-22 20:40:13,191][50205] Updated weights for policy 0, policy_version 44371 (0.0011) +[2026-07-22 20:40:14,702][50205] Updated weights for policy 0, policy_version 44381 (0.0016) +[2026-07-22 20:40:14,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5768.6, 300 sec: 5977.4). Total num frames: 22724608. Throughput: 0: 5715.1. Samples: 22723858. Policy #0 lag: (min: 0.0, avg: 15.2, max: 32.0) +[2026-07-22 20:40:14,878][43431] Avg episode reward: [(0, '1796.036')] +[2026-07-22 20:40:15,741][50205] Updated weights for policy 0, policy_version 44391 (0.0022) +[2026-07-22 20:40:16,637][50205] Updated weights for policy 0, policy_version 44401 (0.0012) +[2026-07-22 20:40:17,171][50205] Updated weights for policy 0, policy_version 44411 (0.0019) +[2026-07-22 20:40:18,657][50205] Updated weights for policy 0, policy_version 44421 (0.0011) +[2026-07-22 20:40:19,438][50205] Updated weights for policy 0, policy_version 44431 (0.0012) +[2026-07-22 20:40:19,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5666.1, 300 sec: 5956.6). Total num frames: 22749184. Throughput: 0: 5583.0. Samples: 22754512. Policy #0 lag: (min: 0.0, avg: 15.2, max: 32.0) +[2026-07-22 20:40:19,878][43431] Avg episode reward: [(0, '1899.580')] +[2026-07-22 20:40:20,564][50205] Updated weights for policy 0, policy_version 44441 (0.0015) +[2026-07-22 20:40:21,707][50205] Updated weights for policy 0, policy_version 44451 (0.0011) +[2026-07-22 20:40:22,485][50205] Updated weights for policy 0, policy_version 44461 (0.0016) +[2026-07-22 20:40:23,104][50205] Updated weights for policy 0, policy_version 44471 (0.0020) +[2026-07-22 20:40:24,611][50205] Updated weights for policy 0, policy_version 44481 (0.0012) +[2026-07-22 20:40:24,877][43431] Fps is (10 sec: 5120.0, 60 sec: 5597.9, 300 sec: 5942.7). Total num frames: 22775808. Throughput: 0: 5490.6. Samples: 22786688. Policy #0 lag: (min: 0.0, avg: 15.2, max: 32.0) +[2026-07-22 20:40:24,878][43431] Avg episode reward: [(0, '1660.211')] +[2026-07-22 20:40:25,040][50205] Updated weights for policy 0, policy_version 44491 (0.0020) +[2026-07-22 20:40:25,926][50205] Updated weights for policy 0, policy_version 44501 (0.0012) +[2026-07-22 20:40:27,442][50205] Updated weights for policy 0, policy_version 44511 (0.0012) +[2026-07-22 20:40:28,141][50205] Updated weights for policy 0, policy_version 44521 (0.0019) +[2026-07-22 20:40:28,739][50205] Updated weights for policy 0, policy_version 44531 (0.0012) +[2026-07-22 20:40:29,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5563.8, 300 sec: 5935.7). Total num frames: 22804480. Throughput: 0: 5454.9. Samples: 22803052. Policy #0 lag: (min: 3.0, avg: 22.8, max: 39.0) +[2026-07-22 20:40:29,878][43431] Avg episode reward: [(0, '1758.487')] +[2026-07-22 20:40:30,111][50205] Updated weights for policy 0, policy_version 44541 (0.0013) +[2026-07-22 20:40:30,882][50205] Updated weights for policy 0, policy_version 44551 (0.0011) +[2026-07-22 20:40:31,854][50205] Updated weights for policy 0, policy_version 44561 (0.0018) +[2026-07-22 20:40:32,719][50205] Updated weights for policy 0, policy_version 44571 (0.0018) +[2026-07-22 20:40:33,773][50205] Updated weights for policy 0, policy_version 44581 (0.0015) +[2026-07-22 20:40:34,172][50205] Updated weights for policy 0, policy_version 44591 (0.0019) +[2026-07-22 20:40:34,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5563.7, 300 sec: 5928.8). Total num frames: 22833152. Throughput: 0: 5407.4. Samples: 22836498. Policy #0 lag: (min: 3.0, avg: 22.8, max: 39.0) +[2026-07-22 20:40:34,878][43431] Avg episode reward: [(0, '1661.002')] +[2026-07-22 20:40:35,747][50205] Updated weights for policy 0, policy_version 44601 (0.0012) +[2026-07-22 20:40:36,702][50205] Updated weights for policy 0, policy_version 44613 (0.0013) +[2026-07-22 20:40:37,110][50205] Updated weights for policy 0, policy_version 44623 (0.0021) +[2026-07-22 20:40:38,551][50205] Updated weights for policy 0, policy_version 44633 (0.0016) +[2026-07-22 20:40:39,471][50205] Updated weights for policy 0, policy_version 44643 (0.0011) +[2026-07-22 20:40:39,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5495.5, 300 sec: 5921.8). Total num frames: 22861824. Throughput: 0: 5367.5. Samples: 22869740. Policy #0 lag: (min: 3.0, avg: 22.8, max: 39.0) +[2026-07-22 20:40:39,878][43431] Avg episode reward: [(0, '2039.002')] +[2026-07-22 20:40:39,909][50205] Updated weights for policy 0, policy_version 44653 (0.0013) +[2026-07-22 20:40:39,971][49527] Saving new best policy, reward=2039.002! +[2026-07-22 20:40:41,232][50205] Updated weights for policy 0, policy_version 44663 (0.0012) +[2026-07-22 20:40:42,301][50205] Updated weights for policy 0, policy_version 44673 (0.0012) +[2026-07-22 20:40:42,880][50205] Updated weights for policy 0, policy_version 44683 (0.0011) +[2026-07-22 20:40:44,243][50205] Updated weights for policy 0, policy_version 44695 (0.0014) +[2026-07-22 20:40:44,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5495.5, 300 sec: 5901.1). Total num frames: 22886400. Throughput: 0: 5354.2. Samples: 22886214. Policy #0 lag: (min: 3.0, avg: 22.8, max: 39.0) +[2026-07-22 20:40:44,878][43431] Avg episode reward: [(0, '1874.806')] +[2026-07-22 20:40:45,154][50205] Updated weights for policy 0, policy_version 44705 (0.0011) +[2026-07-22 20:40:45,677][50205] Updated weights for policy 0, policy_version 44715 (0.0016) +[2026-07-22 20:40:47,021][50205] Updated weights for policy 0, policy_version 44725 (0.0012) +[2026-07-22 20:40:47,783][50205] Updated weights for policy 0, policy_version 44735 (0.0011) +[2026-07-22 20:40:48,545][50205] Updated weights for policy 0, policy_version 44745 (0.0011) +[2026-07-22 20:40:49,828][50205] Updated weights for policy 0, policy_version 44755 (0.0019) +[2026-07-22 20:40:49,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5427.2, 300 sec: 5901.0). Total num frames: 22915072. Throughput: 0: 5398.6. Samples: 22919516. Policy #0 lag: (min: 3.0, avg: 22.8, max: 39.0) +[2026-07-22 20:40:49,878][43431] Avg episode reward: [(0, '1659.380')] +[2026-07-22 20:40:50,756][50205] Updated weights for policy 0, policy_version 44765 (0.0012) +[2026-07-22 20:40:51,227][50205] Updated weights for policy 0, policy_version 44776 (0.0016) +[2026-07-22 20:40:52,682][50205] Updated weights for policy 0, policy_version 44786 (0.0013) +[2026-07-22 20:40:53,398][50205] Updated weights for policy 0, policy_version 44796 (0.0014) +[2026-07-22 20:40:54,160][50205] Updated weights for policy 0, policy_version 44806 (0.0017) +[2026-07-22 20:40:54,878][43431] Fps is (10 sec: 5734.0, 60 sec: 5427.1, 300 sec: 5894.1). Total num frames: 22943744. Throughput: 0: 5454.1. Samples: 22953080. Policy #0 lag: (min: 3.0, avg: 19.5, max: 34.0) +[2026-07-22 20:40:54,879][43431] Avg episode reward: [(0, '1706.456')] +[2026-07-22 20:40:54,928][50205] Updated weights for policy 0, policy_version 44816 (0.0023) +[2026-07-22 20:40:56,243][50205] Updated weights for policy 0, policy_version 44826 (0.0012) +[2026-07-22 20:40:56,783][50205] Updated weights for policy 0, policy_version 44836 (0.0013) +[2026-07-22 20:40:58,347][50205] Updated weights for policy 0, policy_version 44848 (0.0011) +[2026-07-22 20:40:59,191][50205] Updated weights for policy 0, policy_version 44858 (0.0012) +[2026-07-22 20:40:59,679][50205] Updated weights for policy 0, policy_version 44868 (0.0017) +[2026-07-22 20:40:59,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5427.2, 300 sec: 5887.1). Total num frames: 22972416. Throughput: 0: 5466.9. Samples: 22969868. Policy #0 lag: (min: 3.0, avg: 19.5, max: 34.0) +[2026-07-22 20:40:59,878][43431] Avg episode reward: [(0, '1776.239')] +[2026-07-22 20:41:01,103][50205] Updated weights for policy 0, policy_version 44878 (0.0017) +[2026-07-22 20:41:02,131][50205] Updated weights for policy 0, policy_version 44890 (0.0017) +[2026-07-22 20:41:02,694][50205] Updated weights for policy 0, policy_version 44900 (0.0012) +[2026-07-22 20:41:04,076][50205] Updated weights for policy 0, policy_version 44910 (0.0012) +[2026-07-22 20:41:04,878][43431] Fps is (10 sec: 5324.9, 60 sec: 5393.0, 300 sec: 5866.3). Total num frames: 22996992. Throughput: 0: 5522.4. Samples: 23003022. Policy #0 lag: (min: 3.0, avg: 19.5, max: 34.0) +[2026-07-22 20:41:04,879][43431] Avg episode reward: [(0, '1765.224')] +[2026-07-22 20:41:04,940][50205] Updated weights for policy 0, policy_version 44920 (0.0013) +[2026-07-22 20:41:05,749][50205] Updated weights for policy 0, policy_version 44930 (0.0012) +[2026-07-22 20:41:06,648][50205] Updated weights for policy 0, policy_version 44940 (0.0016) +[2026-07-22 20:41:07,697][50205] Updated weights for policy 0, policy_version 44950 (0.0012) +[2026-07-22 20:41:08,402][50205] Updated weights for policy 0, policy_version 44960 (0.0012) +[2026-07-22 20:41:09,487][50205] Updated weights for policy 0, policy_version 44970 (0.0011) +[2026-07-22 20:41:09,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5461.3, 300 sec: 5873.2). Total num frames: 23025664. Throughput: 0: 5547.0. Samples: 23036304. Policy #0 lag: (min: 3.0, avg: 19.5, max: 34.0) +[2026-07-22 20:41:09,878][43431] Avg episode reward: [(0, '1829.066')] +[2026-07-22 20:41:10,391][50205] Updated weights for policy 0, policy_version 44980 (0.0012) +[2026-07-22 20:41:11,191][50205] Updated weights for policy 0, policy_version 44990 (0.0013) +[2026-07-22 20:41:11,974][50205] Updated weights for policy 0, policy_version 45000 (0.0016) +[2026-07-22 20:41:13,247][50205] Updated weights for policy 0, policy_version 45010 (0.0013) +[2026-07-22 20:41:13,678][50205] Updated weights for policy 0, policy_version 45020 (0.0011) +[2026-07-22 20:41:14,877][43431] Fps is (10 sec: 5734.6, 60 sec: 5495.5, 300 sec: 5859.4). Total num frames: 23054336. Throughput: 0: 5561.5. Samples: 23053318. Policy #0 lag: (min: 3.0, avg: 19.5, max: 34.0) +[2026-07-22 20:41:14,878][43431] Avg episode reward: [(0, '1720.462')] +[2026-07-22 20:41:15,097][50205] Updated weights for policy 0, policy_version 45030 (0.0013) +[2026-07-22 20:41:15,893][50205] Updated weights for policy 0, policy_version 45040 (0.0012) +[2026-07-22 20:41:16,875][50205] Updated weights for policy 0, policy_version 45050 (0.0022) +[2026-07-22 20:41:17,396][50205] Updated weights for policy 0, policy_version 45060 (0.0012) +[2026-07-22 20:41:18,693][50205] Updated weights for policy 0, policy_version 45070 (0.0011) +[2026-07-22 20:41:19,384][50205] Updated weights for policy 0, policy_version 45080 (0.0016) +[2026-07-22 20:41:19,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5563.7, 300 sec: 5852.4). Total num frames: 23083008. Throughput: 0: 5561.7. Samples: 23086774. Policy #0 lag: (min: 3.0, avg: 19.5, max: 34.0) +[2026-07-22 20:41:19,878][43431] Avg episode reward: [(0, '1806.040')] +[2026-07-22 20:41:20,548][50205] Updated weights for policy 0, policy_version 45090 (0.0016) +[2026-07-22 20:41:21,125][50205] Updated weights for policy 0, policy_version 45100 (0.0011) +[2026-07-22 20:41:22,168][50205] Updated weights for policy 0, policy_version 45110 (0.0011) +[2026-07-22 20:41:22,951][50205] Updated weights for policy 0, policy_version 45120 (0.0011) +[2026-07-22 20:41:24,221][50205] Updated weights for policy 0, policy_version 45130 (0.0011) +[2026-07-22 20:41:24,847][50205] Updated weights for policy 0, policy_version 45140 (0.0012) +[2026-07-22 20:41:24,878][43431] Fps is (10 sec: 5734.2, 60 sec: 5597.8, 300 sec: 5852.4). Total num frames: 23111680. Throughput: 0: 5573.0. Samples: 23120526. Policy #0 lag: (min: 0.0, avg: 18.7, max: 34.0) +[2026-07-22 20:41:24,879][43431] Avg episode reward: [(0, '1816.181')] +[2026-07-22 20:41:25,809][50205] Updated weights for policy 0, policy_version 45150 (0.0012) +[2026-07-22 20:41:26,676][50205] Updated weights for policy 0, policy_version 45160 (0.0011) +[2026-07-22 20:41:27,808][50205] Updated weights for policy 0, policy_version 45170 (0.0016) +[2026-07-22 20:41:28,478][50205] Updated weights for policy 0, policy_version 45180 (0.0016) +[2026-07-22 20:41:29,709][50205] Updated weights for policy 0, policy_version 45190 (0.0011) +[2026-07-22 20:41:29,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5563.7, 300 sec: 5838.5). Total num frames: 23138304. Throughput: 0: 5578.5. Samples: 23137246. Policy #0 lag: (min: 0.0, avg: 18.7, max: 34.0) +[2026-07-22 20:41:29,878][43431] Avg episode reward: [(0, '1643.889')] +[2026-07-22 20:41:30,644][50205] Updated weights for policy 0, policy_version 45201 (0.0011) +[2026-07-22 20:41:31,559][50205] Updated weights for policy 0, policy_version 45211 (0.0018) +[2026-07-22 20:41:32,698][50205] Updated weights for policy 0, policy_version 45221 (0.0016) +[2026-07-22 20:41:33,276][50205] Updated weights for policy 0, policy_version 45231 (0.0011) +[2026-07-22 20:41:34,382][50205] Updated weights for policy 0, policy_version 45241 (0.0011) +[2026-07-22 20:41:34,877][43431] Fps is (10 sec: 5529.8, 60 sec: 5563.7, 300 sec: 5831.6). Total num frames: 23166976. Throughput: 0: 5577.0. Samples: 23170482. Policy #0 lag: (min: 0.0, avg: 18.7, max: 34.0) +[2026-07-22 20:41:34,878][43431] Avg episode reward: [(0, '1809.497')] +[2026-07-22 20:41:35,125][50205] Updated weights for policy 0, policy_version 45251 (0.0011) +[2026-07-22 20:41:36,111][50205] Updated weights for policy 0, policy_version 45261 (0.0012) +[2026-07-22 20:41:36,725][50205] Updated weights for policy 0, policy_version 45271 (0.0011) +[2026-07-22 20:41:38,143][50205] Updated weights for policy 0, policy_version 45281 (0.0012) +[2026-07-22 20:41:38,823][50205] Updated weights for policy 0, policy_version 45291 (0.0013) +[2026-07-22 20:41:39,513][50205] Updated weights for policy 0, policy_version 45301 (0.0012) +[2026-07-22 20:41:39,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5563.7, 300 sec: 5824.7). Total num frames: 23195648. Throughput: 0: 5587.5. Samples: 23204512. Policy #0 lag: (min: 0.0, avg: 18.7, max: 34.0) +[2026-07-22 20:41:39,878][43431] Avg episode reward: [(0, '1796.511')] +[2026-07-22 20:41:40,446][50205] Updated weights for policy 0, policy_version 45311 (0.0012) +[2026-07-22 20:41:41,759][50205] Updated weights for policy 0, policy_version 45321 (0.0018) +[2026-07-22 20:41:42,205][50205] Updated weights for policy 0, policy_version 45331 (0.0011) +[2026-07-22 20:41:43,388][50205] Updated weights for policy 0, policy_version 45341 (0.0020) +[2026-07-22 20:41:44,398][50205] Updated weights for policy 0, policy_version 45351 (0.0011) +[2026-07-22 20:41:44,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5632.0, 300 sec: 5817.7). Total num frames: 23224320. Throughput: 0: 5585.0. Samples: 23221192. Policy #0 lag: (min: 0.0, avg: 18.7, max: 34.0) +[2026-07-22 20:41:44,878][43431] Avg episode reward: [(0, '1675.400')] +[2026-07-22 20:41:45,325][50205] Updated weights for policy 0, policy_version 45361 (0.0012) +[2026-07-22 20:41:45,991][50205] Updated weights for policy 0, policy_version 45371 (0.0013) +[2026-07-22 20:41:47,201][50205] Updated weights for policy 0, policy_version 45381 (0.0016) +[2026-07-22 20:41:47,647][50205] Updated weights for policy 0, policy_version 45391 (0.0012) +[2026-07-22 20:41:48,953][50205] Updated weights for policy 0, policy_version 45401 (0.0015) +[2026-07-22 20:41:49,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5563.7, 300 sec: 5796.9). Total num frames: 23248896. Throughput: 0: 5600.3. Samples: 23255036. Policy #0 lag: (min: 0.0, avg: 18.7, max: 34.0) +[2026-07-22 20:41:49,878][43431] Avg episode reward: [(0, '1744.122')] +[2026-07-22 20:41:50,040][50205] Updated weights for policy 0, policy_version 45411 (0.0012) +[2026-07-22 20:41:50,665][50205] Updated weights for policy 0, policy_version 45421 (0.0012) +[2026-07-22 20:41:51,336][50205] Updated weights for policy 0, policy_version 45431 (0.0011) +[2026-07-22 20:41:52,742][50205] Updated weights for policy 0, policy_version 45441 (0.0012) +[2026-07-22 20:41:53,440][50205] Updated weights for policy 0, policy_version 45451 (0.0016) +[2026-07-22 20:41:54,213][50205] Updated weights for policy 0, policy_version 45461 (0.0011) +[2026-07-22 20:41:54,878][43431] Fps is (10 sec: 5529.0, 60 sec: 5597.8, 300 sec: 5796.9). Total num frames: 23279616. Throughput: 0: 5606.7. Samples: 23288610. Policy #0 lag: (min: 3.0, avg: 23.6, max: 47.0) +[2026-07-22 20:41:54,879][43431] Avg episode reward: [(0, '1728.425')] +[2026-07-22 20:41:54,901][50205] Updated weights for policy 0, policy_version 45471 (0.0012) +[2026-07-22 20:41:56,262][50205] Updated weights for policy 0, policy_version 45481 (0.0015) +[2026-07-22 20:41:57,030][50205] Updated weights for policy 0, policy_version 45491 (0.0012) +[2026-07-22 20:41:58,040][50205] Updated weights for policy 0, policy_version 45501 (0.0016) +[2026-07-22 20:41:58,684][50205] Updated weights for policy 0, policy_version 45511 (0.0012) +[2026-07-22 20:41:59,748][50205] Updated weights for policy 0, policy_version 45521 (0.0016) +[2026-07-22 20:41:59,879][43431] Fps is (10 sec: 5938.2, 60 sec: 5597.7, 300 sec: 5803.8). Total num frames: 23308288. Throughput: 0: 5602.0. Samples: 23305418. Policy #0 lag: (min: 3.0, avg: 23.6, max: 47.0) +[2026-07-22 20:41:59,880][43431] Avg episode reward: [(0, '1681.785')] +[2026-07-22 20:42:00,699][50205] Updated weights for policy 0, policy_version 45531 (0.0012) +[2026-07-22 20:42:01,632][50205] Updated weights for policy 0, policy_version 45541 (0.0018) +[2026-07-22 20:42:02,653][50205] Updated weights for policy 0, policy_version 45552 (0.0013) +[2026-07-22 20:42:04,653][50205] Updated weights for policy 0, policy_version 45565 (0.0018) +[2026-07-22 20:42:04,877][43431] Fps is (10 sec: 5120.6, 60 sec: 5563.8, 300 sec: 5776.1). Total num frames: 23330816. Throughput: 0: 5516.6. Samples: 23335022. Policy #0 lag: (min: 3.0, avg: 23.6, max: 47.0) +[2026-07-22 20:42:04,878][43431] Avg episode reward: [(0, '1679.401')] +[2026-07-22 20:42:05,497][50205] Updated weights for policy 0, policy_version 45575 (0.0012) +[2026-07-22 20:42:06,287][50205] Updated weights for policy 0, policy_version 45585 (0.0020) +[2026-07-22 20:42:07,126][50205] Updated weights for policy 0, policy_version 45595 (0.0014) +[2026-07-22 20:42:08,392][50205] Updated weights for policy 0, policy_version 45605 (0.0011) +[2026-07-22 20:42:08,987][50205] Updated weights for policy 0, policy_version 45615 (0.0012) +[2026-07-22 20:42:09,877][43431] Fps is (10 sec: 5120.9, 60 sec: 5563.7, 300 sec: 5776.1). Total num frames: 23359488. Throughput: 0: 5518.5. Samples: 23368854. Policy #0 lag: (min: 3.0, avg: 23.6, max: 47.0) +[2026-07-22 20:42:09,878][43431] Avg episode reward: [(0, '1801.411')] +[2026-07-22 20:42:09,914][50205] Updated weights for policy 0, policy_version 45625 (0.0014) +[2026-07-22 20:42:10,646][50205] Updated weights for policy 0, policy_version 45635 (0.0012) +[2026-07-22 20:42:11,735][50205] Updated weights for policy 0, policy_version 45645 (0.0019) +[2026-07-22 20:42:12,681][50205] Updated weights for policy 0, policy_version 45655 (0.0017) +[2026-07-22 20:42:13,524][50205] Updated weights for policy 0, policy_version 45665 (0.0012) +[2026-07-22 20:42:14,291][50205] Updated weights for policy 0, policy_version 45675 (0.0015) +[2026-07-22 20:42:14,878][43431] Fps is (10 sec: 5529.3, 60 sec: 5529.6, 300 sec: 5755.2). Total num frames: 23386112. Throughput: 0: 5523.7. Samples: 23385814. Policy #0 lag: (min: 3.0, avg: 23.6, max: 47.0) +[2026-07-22 20:42:14,879][43431] Avg episode reward: [(0, '1712.511')] +[2026-07-22 20:42:15,421][50205] Updated weights for policy 0, policy_version 45687 (0.0011) +[2026-07-22 20:42:16,671][50205] Updated weights for policy 0, policy_version 45697 (0.0012) +[2026-07-22 20:42:17,323][50205] Updated weights for policy 0, policy_version 45707 (0.0011) +[2026-07-22 20:42:18,247][50205] Updated weights for policy 0, policy_version 45717 (0.0012) +[2026-07-22 20:42:19,173][50205] Updated weights for policy 0, policy_version 45727 (0.0013) +[2026-07-22 20:42:19,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5529.6, 300 sec: 5755.2). Total num frames: 23414784. Throughput: 0: 5531.6. Samples: 23419404. Policy #0 lag: (min: 0.0, avg: 15.5, max: 34.0) +[2026-07-22 20:42:19,878][43431] Avg episode reward: [(0, '1774.441')] +[2026-07-22 20:42:20,210][50205] Updated weights for policy 0, policy_version 45737 (0.0014) +[2026-07-22 20:42:20,981][50205] Updated weights for policy 0, policy_version 45747 (0.0012) +[2026-07-22 20:42:22,223][50205] Updated weights for policy 0, policy_version 45757 (0.0018) +[2026-07-22 20:42:22,720][50205] Updated weights for policy 0, policy_version 45767 (0.0011) +[2026-07-22 20:42:23,657][50205] Updated weights for policy 0, policy_version 45777 (0.0012) +[2026-07-22 20:42:24,616][50205] Updated weights for policy 0, policy_version 45787 (0.0011) +[2026-07-22 20:42:24,877][43431] Fps is (10 sec: 5734.7, 60 sec: 5529.6, 300 sec: 5748.3). Total num frames: 23443456. Throughput: 0: 5530.5. Samples: 23453386. Policy #0 lag: (min: 0.0, avg: 15.5, max: 34.0) +[2026-07-22 20:42:24,878][43431] Avg episode reward: [(0, '1585.600')] +[2026-07-22 20:42:25,461][50205] Updated weights for policy 0, policy_version 45797 (0.0012) +[2026-07-22 20:42:26,273][50205] Updated weights for policy 0, policy_version 45807 (0.0013) +[2026-07-22 20:42:27,825][50205] Updated weights for policy 0, policy_version 45817 (0.0016) +[2026-07-22 20:42:28,291][50205] Updated weights for policy 0, policy_version 45827 (0.0011) +[2026-07-22 20:42:29,023][50205] Updated weights for policy 0, policy_version 45837 (0.0011) +[2026-07-22 20:42:29,725][50205] Updated weights for policy 0, policy_version 45847 (0.0018) +[2026-07-22 20:42:29,877][43431] Fps is (10 sec: 5939.3, 60 sec: 5597.9, 300 sec: 5741.3). Total num frames: 23474176. Throughput: 0: 5537.5. Samples: 23470380. Policy #0 lag: (min: 0.0, avg: 15.5, max: 34.0) +[2026-07-22 20:42:29,878][43431] Avg episode reward: [(0, '1835.699')] +[2026-07-22 20:42:31,323][50205] Updated weights for policy 0, policy_version 45857 (0.0012) +[2026-07-22 20:42:31,778][50205] Updated weights for policy 0, policy_version 45867 (0.0020) +[2026-07-22 20:42:32,816][50205] Updated weights for policy 0, policy_version 45877 (0.0011) +[2026-07-22 20:42:33,653][50205] Updated weights for policy 0, policy_version 45887 (0.0021) +[2026-07-22 20:42:34,617][50205] Updated weights for policy 0, policy_version 45897 (0.0012) +[2026-07-22 20:42:34,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5563.7, 300 sec: 5741.3). Total num frames: 23500800. Throughput: 0: 5534.7. Samples: 23504098. Policy #0 lag: (min: 0.0, avg: 15.5, max: 34.0) +[2026-07-22 20:42:34,878][43431] Avg episode reward: [(0, '1748.888')] +[2026-07-22 20:42:35,632][50205] Updated weights for policy 0, policy_version 45907 (0.0020) +[2026-07-22 20:42:36,550][50205] Updated weights for policy 0, policy_version 45917 (0.0015) +[2026-07-22 20:42:37,300][50205] Updated weights for policy 0, policy_version 45927 (0.0011) +[2026-07-22 20:42:38,429][50205] Updated weights for policy 0, policy_version 45937 (0.0011) +[2026-07-22 20:42:39,341][50205] Updated weights for policy 0, policy_version 45947 (0.0011) +[2026-07-22 20:42:39,878][43431] Fps is (10 sec: 5324.3, 60 sec: 5529.5, 300 sec: 5727.4). Total num frames: 23527424. Throughput: 0: 5545.2. Samples: 23538142. Policy #0 lag: (min: 0.0, avg: 15.5, max: 34.0) +[2026-07-22 20:42:39,879][43431] Avg episode reward: [(0, '1713.324')] +[2026-07-22 20:42:39,952][49527] Saving results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/checkpoint_p0/checkpoint_000045956_23529472.pth... +[2026-07-22 20:42:40,019][49527] Removing results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/checkpoint_p0/checkpoint_000012368_6332416.pth +[2026-07-22 20:42:40,131][50205] Updated weights for policy 0, policy_version 45957 (0.0011) +[2026-07-22 20:42:40,465][50205] Updated weights for policy 0, policy_version 45967 (0.0020) +[2026-07-22 20:42:42,142][50205] Updated weights for policy 0, policy_version 45977 (0.0011) +[2026-07-22 20:42:42,948][50205] Updated weights for policy 0, policy_version 45987 (0.0011) +[2026-07-22 20:42:43,657][50205] Updated weights for policy 0, policy_version 45999 (0.0022) +[2026-07-22 20:42:44,877][43431] Fps is (10 sec: 5529.5, 60 sec: 5529.6, 300 sec: 5720.5). Total num frames: 23556096. Throughput: 0: 5545.8. Samples: 23554970. Policy #0 lag: (min: 0.0, avg: 15.5, max: 34.0) +[2026-07-22 20:42:44,878][43431] Avg episode reward: [(0, '1774.341')] +[2026-07-22 20:42:45,054][50205] Updated weights for policy 0, policy_version 46009 (0.0011) +[2026-07-22 20:42:45,748][50205] Updated weights for policy 0, policy_version 46019 (0.0013) +[2026-07-22 20:42:46,911][50205] Updated weights for policy 0, policy_version 46029 (0.0012) +[2026-07-22 20:42:47,565][50205] Updated weights for policy 0, policy_version 46039 (0.0019) +[2026-07-22 20:42:48,467][50205] Updated weights for policy 0, policy_version 46049 (0.0011) +[2026-07-22 20:42:49,083][50205] Updated weights for policy 0, policy_version 46059 (0.0021) +[2026-07-22 20:42:49,877][43431] Fps is (10 sec: 5734.8, 60 sec: 5597.9, 300 sec: 5713.6). Total num frames: 23584768. Throughput: 0: 5636.3. Samples: 23588658. Policy #0 lag: (min: 5.0, avg: 19.2, max: 35.0) +[2026-07-22 20:42:49,878][43431] Avg episode reward: [(0, '1634.308')] +[2026-07-22 20:42:50,699][50205] Updated weights for policy 0, policy_version 46069 (0.0014) +[2026-07-22 20:42:51,152][50205] Updated weights for policy 0, policy_version 46079 (0.0012) +[2026-07-22 20:42:51,701][50205] Updated weights for policy 0, policy_version 46089 (0.0015) +[2026-07-22 20:42:53,273][50205] Updated weights for policy 0, policy_version 46099 (0.0012) +[2026-07-22 20:42:54,132][50205] Updated weights for policy 0, policy_version 46109 (0.0011) +[2026-07-22 20:42:54,621][50205] Updated weights for policy 0, policy_version 46119 (0.0016) +[2026-07-22 20:42:54,878][43431] Fps is (10 sec: 5939.0, 60 sec: 5597.9, 300 sec: 5720.5). Total num frames: 23615488. Throughput: 0: 5636.8. Samples: 23622512. Policy #0 lag: (min: 5.0, avg: 19.2, max: 35.0) +[2026-07-22 20:42:54,878][43431] Avg episode reward: [(0, '1758.393')] +[2026-07-22 20:42:55,889][50205] Updated weights for policy 0, policy_version 46129 (0.0017) +[2026-07-22 20:42:56,551][50205] Updated weights for policy 0, policy_version 46139 (0.0017) +[2026-07-22 20:42:57,456][50205] Updated weights for policy 0, policy_version 46149 (0.0012) +[2026-07-22 20:42:58,423][50205] Updated weights for policy 0, policy_version 46159 (0.0020) +[2026-07-22 20:42:59,262][50205] Updated weights for policy 0, policy_version 46169 (0.0017) +[2026-07-22 20:42:59,877][43431] Fps is (10 sec: 5529.8, 60 sec: 5529.8, 300 sec: 5706.6). Total num frames: 23640064. Throughput: 0: 5640.3. Samples: 23639622. Policy #0 lag: (min: 5.0, avg: 19.2, max: 35.0) +[2026-07-22 20:42:59,878][43431] Avg episode reward: [(0, '1750.262')] +[2026-07-22 20:43:00,118][50205] Updated weights for policy 0, policy_version 46179 (0.0011) +[2026-07-22 20:43:01,547][50205] Updated weights for policy 0, policy_version 46189 (0.0012) +[2026-07-22 20:43:02,904][50205] Updated weights for policy 0, policy_version 46202 (0.0012) +[2026-07-22 20:43:03,335][50205] Updated weights for policy 0, policy_version 46212 (0.0012) +[2026-07-22 20:43:04,877][43431] Fps is (10 sec: 4915.2, 60 sec: 5563.7, 300 sec: 5678.9). Total num frames: 23664640. Throughput: 0: 5587.5. Samples: 23670844. Policy #0 lag: (min: 5.0, avg: 19.2, max: 35.0) +[2026-07-22 20:43:04,878][43431] Avg episode reward: [(0, '1675.070')] +[2026-07-22 20:43:04,979][50205] Updated weights for policy 0, policy_version 46222 (0.0012) +[2026-07-22 20:43:05,646][50205] Updated weights for policy 0, policy_version 46232 (0.0016) +[2026-07-22 20:43:06,275][50205] Updated weights for policy 0, policy_version 46242 (0.0017) +[2026-07-22 20:43:07,012][50205] Updated weights for policy 0, policy_version 46252 (0.0011) +[2026-07-22 20:43:08,505][50205] Updated weights for policy 0, policy_version 46262 (0.0015) +[2026-07-22 20:43:08,960][50205] Updated weights for policy 0, policy_version 46272 (0.0012) +[2026-07-22 20:43:09,877][43431] Fps is (10 sec: 5324.7, 60 sec: 5563.7, 300 sec: 5678.9). Total num frames: 23693312. Throughput: 0: 5575.4. Samples: 23704278. Policy #0 lag: (min: 5.0, avg: 19.2, max: 35.0) +[2026-07-22 20:43:09,878][43431] Avg episode reward: [(0, '1862.365')] +[2026-07-22 20:43:10,212][50205] Updated weights for policy 0, policy_version 46282 (0.0016) +[2026-07-22 20:43:10,806][50205] Updated weights for policy 0, policy_version 46292 (0.0012) +[2026-07-22 20:43:11,884][50205] Updated weights for policy 0, policy_version 46302 (0.0019) +[2026-07-22 20:43:12,920][50205] Updated weights for policy 0, policy_version 46312 (0.0019) +[2026-07-22 20:43:13,891][50205] Updated weights for policy 0, policy_version 46322 (0.0025) +[2026-07-22 20:43:14,640][50205] Updated weights for policy 0, policy_version 46332 (0.0011) +[2026-07-22 20:43:14,877][43431] Fps is (10 sec: 5939.3, 60 sec: 5632.0, 300 sec: 5685.8). Total num frames: 23724032. Throughput: 0: 5573.8. Samples: 23721202. Policy #0 lag: (min: 5.0, avg: 19.2, max: 35.0) +[2026-07-22 20:43:14,878][43431] Avg episode reward: [(0, '1810.395')] +[2026-07-22 20:43:15,651][50205] Updated weights for policy 0, policy_version 46342 (0.0014) +[2026-07-22 20:43:16,567][50205] Updated weights for policy 0, policy_version 46352 (0.0014) +[2026-07-22 20:43:17,551][50205] Updated weights for policy 0, policy_version 46362 (0.0014) +[2026-07-22 20:43:17,880][50205] Updated weights for policy 0, policy_version 46372 (0.0012) +[2026-07-22 20:43:19,313][50205] Updated weights for policy 0, policy_version 46382 (0.0011) +[2026-07-22 20:43:19,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5563.7, 300 sec: 5671.9). Total num frames: 23748608. Throughput: 0: 5569.4. Samples: 23754720. Policy #0 lag: (min: 3.0, avg: 19.4, max: 43.0) +[2026-07-22 20:43:19,878][43431] Avg episode reward: [(0, '1853.269')] +[2026-07-22 20:43:20,184][50205] Updated weights for policy 0, policy_version 46392 (0.0011) +[2026-07-22 20:43:20,967][50205] Updated weights for policy 0, policy_version 46402 (0.0016) +[2026-07-22 20:43:21,772][50205] Updated weights for policy 0, policy_version 46412 (0.0015) +[2026-07-22 20:43:22,844][50205] Updated weights for policy 0, policy_version 46422 (0.0019) +[2026-07-22 20:43:23,436][50205] Updated weights for policy 0, policy_version 46432 (0.0011) +[2026-07-22 20:43:24,872][50205] Updated weights for policy 0, policy_version 46442 (0.0015) +[2026-07-22 20:43:24,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5563.7, 300 sec: 5658.0). Total num frames: 23777280. Throughput: 0: 5569.0. Samples: 23788740. Policy #0 lag: (min: 3.0, avg: 19.4, max: 43.0) +[2026-07-22 20:43:24,878][43431] Avg episode reward: [(0, '1702.714')] +[2026-07-22 20:43:25,530][50205] Updated weights for policy 0, policy_version 46452 (0.0011) +[2026-07-22 20:43:26,222][50205] Updated weights for policy 0, policy_version 46462 (0.0016) +[2026-07-22 20:43:27,480][50205] Updated weights for policy 0, policy_version 46472 (0.0016) +[2026-07-22 20:43:28,571][50205] Updated weights for policy 0, policy_version 46482 (0.0016) +[2026-07-22 20:43:29,092][50205] Updated weights for policy 0, policy_version 46492 (0.0022) +[2026-07-22 20:43:29,877][43431] Fps is (10 sec: 5939.3, 60 sec: 5563.7, 300 sec: 5665.0). Total num frames: 23808000. Throughput: 0: 5563.9. Samples: 23805344. Policy #0 lag: (min: 3.0, avg: 19.4, max: 43.0) +[2026-07-22 20:43:29,878][43431] Avg episode reward: [(0, '1818.083')] +[2026-07-22 20:43:30,127][50205] Updated weights for policy 0, policy_version 46502 (0.0011) +[2026-07-22 20:43:31,193][50205] Updated weights for policy 0, policy_version 46512 (0.0015) +[2026-07-22 20:43:31,999][50205] Updated weights for policy 0, policy_version 46522 (0.0013) +[2026-07-22 20:43:32,448][50205] Updated weights for policy 0, policy_version 46532 (0.0011) +[2026-07-22 20:43:33,884][50205] Updated weights for policy 0, policy_version 46542 (0.0012) +[2026-07-22 20:43:34,798][50205] Updated weights for policy 0, policy_version 46552 (0.0015) +[2026-07-22 20:43:34,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5563.7, 300 sec: 5651.1). Total num frames: 23834624. Throughput: 0: 5567.2. Samples: 23839180. Policy #0 lag: (min: 3.0, avg: 19.4, max: 43.0) +[2026-07-22 20:43:34,878][43431] Avg episode reward: [(0, '1738.781')] +[2026-07-22 20:43:35,492][50205] Updated weights for policy 0, policy_version 46562 (0.0012) +[2026-07-22 20:43:36,563][50205] Updated weights for policy 0, policy_version 46572 (0.0017) +[2026-07-22 20:43:37,390][50205] Updated weights for policy 0, policy_version 46582 (0.0011) +[2026-07-22 20:43:37,961][50205] Updated weights for policy 0, policy_version 46592 (0.0014) +[2026-07-22 20:43:39,472][50205] Updated weights for policy 0, policy_version 46602 (0.0012) +[2026-07-22 20:43:39,879][43431] Fps is (10 sec: 5528.8, 60 sec: 5597.8, 300 sec: 5644.1). Total num frames: 23863296. Throughput: 0: 5570.9. Samples: 23873208. Policy #0 lag: (min: 3.0, avg: 19.4, max: 43.0) +[2026-07-22 20:43:39,879][43431] Avg episode reward: [(0, '1768.089')] +[2026-07-22 20:43:40,021][50205] Updated weights for policy 0, policy_version 46612 (0.0012) +[2026-07-22 20:43:40,895][50205] Updated weights for policy 0, policy_version 46622 (0.0011) +[2026-07-22 20:43:41,805][50205] Updated weights for policy 0, policy_version 46632 (0.0014) +[2026-07-22 20:43:42,868][50205] Updated weights for policy 0, policy_version 46642 (0.0016) +[2026-07-22 20:43:43,732][50205] Updated weights for policy 0, policy_version 46652 (0.0012) +[2026-07-22 20:43:44,482][50205] Updated weights for policy 0, policy_version 46662 (0.0013) +[2026-07-22 20:43:44,878][43431] Fps is (10 sec: 5734.0, 60 sec: 5597.8, 300 sec: 5644.1). Total num frames: 23891968. Throughput: 0: 5569.2. Samples: 23890242. Policy #0 lag: (min: 3.0, avg: 19.4, max: 43.0) +[2026-07-22 20:43:44,879][43431] Avg episode reward: [(0, '1622.193')] +[2026-07-22 20:43:45,396][50205] Updated weights for policy 0, policy_version 46672 (0.0013) +[2026-07-22 20:43:46,574][50205] Updated weights for policy 0, policy_version 46682 (0.0015) +[2026-07-22 20:43:47,098][50205] Updated weights for policy 0, policy_version 46692 (0.0011) +[2026-07-22 20:43:48,274][50205] Updated weights for policy 0, policy_version 46702 (0.0013) +[2026-07-22 20:43:49,058][50205] Updated weights for policy 0, policy_version 46712 (0.0011) +[2026-07-22 20:43:49,877][43431] Fps is (10 sec: 5735.2, 60 sec: 5597.9, 300 sec: 5637.2). Total num frames: 23920640. Throughput: 0: 5624.6. Samples: 23923950. Policy #0 lag: (min: 0.0, avg: 16.7, max: 36.0) +[2026-07-22 20:43:49,878][43431] Avg episode reward: [(0, '1806.043')] +[2026-07-22 20:43:50,181][50205] Updated weights for policy 0, policy_version 46722 (0.0012) +[2026-07-22 20:43:51,038][50205] Updated weights for policy 0, policy_version 46732 (0.0012) +[2026-07-22 20:43:51,773][50205] Updated weights for policy 0, policy_version 46742 (0.0011) +[2026-07-22 20:43:52,647][50205] Updated weights for policy 0, policy_version 46752 (0.0012) +[2026-07-22 20:43:53,984][50205] Updated weights for policy 0, policy_version 46762 (0.0011) +[2026-07-22 20:43:54,487][50205] Updated weights for policy 0, policy_version 46772 (0.0016) +[2026-07-22 20:43:54,877][43431] Fps is (10 sec: 5734.7, 60 sec: 5563.7, 300 sec: 5630.3). Total num frames: 23949312. Throughput: 0: 5628.6. Samples: 23957564. Policy #0 lag: (min: 0.0, avg: 16.7, max: 36.0) +[2026-07-22 20:43:54,878][43431] Avg episode reward: [(0, '1688.088')] +[2026-07-22 20:43:55,482][50205] Updated weights for policy 0, policy_version 46782 (0.0017) +[2026-07-22 20:43:56,333][50205] Updated weights for policy 0, policy_version 46792 (0.0014) +[2026-07-22 20:43:57,355][50205] Updated weights for policy 0, policy_version 46802 (0.0016) +[2026-07-22 20:43:58,224][50205] Updated weights for policy 0, policy_version 46812 (0.0011) +[2026-07-22 20:43:59,233][50205] Updated weights for policy 0, policy_version 46822 (0.0015) +[2026-07-22 20:43:59,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5597.9, 300 sec: 5616.4). Total num frames: 23975936. Throughput: 0: 5625.3. Samples: 23974340. Policy #0 lag: (min: 0.0, avg: 16.7, max: 36.0) +[2026-07-22 20:43:59,878][43431] Avg episode reward: [(0, '1951.803')] +[2026-07-22 20:43:59,977][50205] Updated weights for policy 0, policy_version 46832 (0.0016) +[2026-07-22 20:44:01,065][50205] Updated weights for policy 0, policy_version 46842 (0.0011) +[2026-07-22 20:44:02,035][50205] Updated weights for policy 0, policy_version 46852 (0.0017) +[2026-07-22 20:44:03,291][50205] Updated weights for policy 0, policy_version 46866 (0.0017) +[2026-07-22 20:44:04,095][50205] Updated weights for policy 0, policy_version 46876 (0.0015) +[2026-07-22 20:44:04,877][43431] Fps is (10 sec: 5324.9, 60 sec: 5632.0, 300 sec: 5602.5). Total num frames: 24002560. Throughput: 0: 5614.9. Samples: 24007390. Policy #0 lag: (min: 0.0, avg: 16.7, max: 36.0) +[2026-07-22 20:44:04,878][43431] Avg episode reward: [(0, '1664.331')] +[2026-07-22 20:44:05,403][50205] Updated weights for policy 0, policy_version 46886 (0.0011) +[2026-07-22 20:44:06,717][50205] Updated weights for policy 0, policy_version 46900 (0.0021) +[2026-07-22 20:44:07,750][50205] Updated weights for policy 0, policy_version 46910 (0.0011) +[2026-07-22 20:44:08,583][49527] Signal inference workers to stop experience collection... (850 times) +[2026-07-22 20:44:08,594][50205] InferenceWorker_p0-w0: stopping experience collection (850 times) +[2026-07-22 20:44:08,640][49527] Signal inference workers to resume experience collection... (850 times) +[2026-07-22 20:44:08,641][50205] InferenceWorker_p0-w0: resuming experience collection (850 times) +[2026-07-22 20:44:09,504][50205] Updated weights for policy 0, policy_version 46925 (0.0017) +[2026-07-22 20:44:09,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5597.9, 300 sec: 5595.6). Total num frames: 24029184. Throughput: 0: 5538.5. Samples: 24037974. Policy #0 lag: (min: 0.0, avg: 16.7, max: 36.0) +[2026-07-22 20:44:09,878][43431] Avg episode reward: [(0, '1882.294')] +[2026-07-22 20:44:10,221][50205] Updated weights for policy 0, policy_version 46935 (0.0016) +[2026-07-22 20:44:11,273][50205] Updated weights for policy 0, policy_version 46945 (0.0011) +[2026-07-22 20:44:11,796][50205] Updated weights for policy 0, policy_version 46955 (0.0011) +[2026-07-22 20:44:13,267][50205] Updated weights for policy 0, policy_version 46965 (0.0014) +[2026-07-22 20:44:13,977][50205] Updated weights for policy 0, policy_version 46975 (0.0012) +[2026-07-22 20:44:14,877][43431] Fps is (10 sec: 5324.8, 60 sec: 5529.6, 300 sec: 5581.7). Total num frames: 24055808. Throughput: 0: 5545.2. Samples: 24054876. Policy #0 lag: (min: 0.0, avg: 16.7, max: 36.0) +[2026-07-22 20:44:14,878][43431] Avg episode reward: [(0, '1600.961')] +[2026-07-22 20:44:14,942][50205] Updated weights for policy 0, policy_version 46985 (0.0012) +[2026-07-22 20:44:15,748][50205] Updated weights for policy 0, policy_version 46995 (0.0015) +[2026-07-22 20:44:16,837][50205] Updated weights for policy 0, policy_version 47005 (0.0012) +[2026-07-22 20:44:17,261][50205] Updated weights for policy 0, policy_version 47015 (0.0013) +[2026-07-22 20:44:18,583][50205] Updated weights for policy 0, policy_version 47025 (0.0014) +[2026-07-22 20:44:19,008][50205] Updated weights for policy 0, policy_version 47035 (0.0016) +[2026-07-22 20:44:19,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5597.9, 300 sec: 5574.7). Total num frames: 24084480. Throughput: 0: 5547.6. Samples: 24088820. Policy #0 lag: (min: 3.0, avg: 19.7, max: 39.0) +[2026-07-22 20:44:19,886][43431] Avg episode reward: [(0, '1948.468')] +[2026-07-22 20:44:20,352][50205] Updated weights for policy 0, policy_version 47045 (0.0014) +[2026-07-22 20:44:21,197][50205] Updated weights for policy 0, policy_version 47055 (0.0021) +[2026-07-22 20:44:22,014][50205] Updated weights for policy 0, policy_version 47065 (0.0023) +[2026-07-22 20:44:22,850][50205] Updated weights for policy 0, policy_version 47075 (0.0015) +[2026-07-22 20:44:23,984][50205] Updated weights for policy 0, policy_version 47085 (0.0013) +[2026-07-22 20:44:24,544][50205] Updated weights for policy 0, policy_version 47095 (0.0010) +[2026-07-22 20:44:24,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5597.8, 300 sec: 5567.8). Total num frames: 24113152. Throughput: 0: 5547.8. Samples: 24122850. Policy #0 lag: (min: 3.0, avg: 19.7, max: 39.0) +[2026-07-22 20:44:24,878][43431] Avg episode reward: [(0, '1643.635')] +[2026-07-22 20:44:25,650][50205] Updated weights for policy 0, policy_version 47105 (0.0012) +[2026-07-22 20:44:26,573][50205] Updated weights for policy 0, policy_version 47115 (0.0012) +[2026-07-22 20:44:27,404][50205] Updated weights for policy 0, policy_version 47125 (0.0011) +[2026-07-22 20:44:28,364][50205] Updated weights for policy 0, policy_version 47135 (0.0013) +[2026-07-22 20:44:29,305][50205] Updated weights for policy 0, policy_version 47145 (0.0015) +[2026-07-22 20:44:29,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5563.7, 300 sec: 5567.8). Total num frames: 24141824. Throughput: 0: 5541.9. Samples: 24139624. Policy #0 lag: (min: 3.0, avg: 19.7, max: 39.0) +[2026-07-22 20:44:29,878][43431] Avg episode reward: [(0, '1737.701')] +[2026-07-22 20:44:30,089][50205] Updated weights for policy 0, policy_version 47155 (0.0011) +[2026-07-22 20:44:31,472][50205] Updated weights for policy 0, policy_version 47165 (0.0018) +[2026-07-22 20:44:32,047][50205] Updated weights for policy 0, policy_version 47175 (0.0017) +[2026-07-22 20:44:32,887][50205] Updated weights for policy 0, policy_version 47185 (0.0012) +[2026-07-22 20:44:33,798][50205] Updated weights for policy 0, policy_version 47195 (0.0016) +[2026-07-22 20:44:34,836][50205] Updated weights for policy 0, policy_version 47205 (0.0011) +[2026-07-22 20:44:34,877][43431] Fps is (10 sec: 5529.7, 60 sec: 5563.7, 300 sec: 5547.0). Total num frames: 24168448. Throughput: 0: 5543.3. Samples: 24173398. Policy #0 lag: (min: 3.0, avg: 19.7, max: 39.0) +[2026-07-22 20:44:34,878][43431] Avg episode reward: [(0, '1884.567')] +[2026-07-22 20:44:35,647][50205] Updated weights for policy 0, policy_version 47215 (0.0019) +[2026-07-22 20:44:36,674][50205] Updated weights for policy 0, policy_version 47225 (0.0013) +[2026-07-22 20:44:37,676][50205] Updated weights for policy 0, policy_version 47237 (0.0016) +[2026-07-22 20:44:38,393][50205] Updated weights for policy 0, policy_version 47247 (0.0015) +[2026-07-22 20:44:39,784][50205] Updated weights for policy 0, policy_version 47257 (0.0017) +[2026-07-22 20:44:39,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5563.9, 300 sec: 5560.8). Total num frames: 24197120. Throughput: 0: 5545.9. Samples: 24207130. Policy #0 lag: (min: 3.0, avg: 19.7, max: 39.0) +[2026-07-22 20:44:39,878][43431] Avg episode reward: [(0, '1853.943')] +[2026-07-22 20:44:40,483][50205] Updated weights for policy 0, policy_version 47267 (0.0012) +[2026-07-22 20:44:41,301][50205] Updated weights for policy 0, policy_version 47277 (0.0012) +[2026-07-22 20:44:42,275][50205] Updated weights for policy 0, policy_version 47287 (0.0015) +[2026-07-22 20:44:43,284][50205] Updated weights for policy 0, policy_version 47297 (0.0011) +[2026-07-22 20:44:43,808][50205] Updated weights for policy 0, policy_version 47307 (0.0012) +[2026-07-22 20:44:44,878][43431] Fps is (10 sec: 5733.8, 60 sec: 5563.7, 300 sec: 5546.9). Total num frames: 24225792. Throughput: 0: 5545.7. Samples: 24223902. Policy #0 lag: (min: 3.0, avg: 19.7, max: 39.0) +[2026-07-22 20:44:44,879][43431] Avg episode reward: [(0, '1785.738')] +[2026-07-22 20:44:45,315][50205] Updated weights for policy 0, policy_version 47317 (0.0016) +[2026-07-22 20:44:45,908][50205] Updated weights for policy 0, policy_version 47327 (0.0013) +[2026-07-22 20:44:46,760][50205] Updated weights for policy 0, policy_version 47337 (0.0012) +[2026-07-22 20:44:47,403][50205] Updated weights for policy 0, policy_version 47347 (0.0012) +[2026-07-22 20:44:48,612][50205] Updated weights for policy 0, policy_version 47357 (0.0015) +[2026-07-22 20:44:49,246][50205] Updated weights for policy 0, policy_version 47367 (0.0011) +[2026-07-22 20:44:49,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5563.7, 300 sec: 5547.0). Total num frames: 24254464. Throughput: 0: 5571.2. Samples: 24258096. Policy #0 lag: (min: 1.0, avg: 14.3, max: 33.0) +[2026-07-22 20:44:49,878][43431] Avg episode reward: [(0, '1743.789')] +[2026-07-22 20:44:50,359][50205] Updated weights for policy 0, policy_version 47377 (0.0012) +[2026-07-22 20:44:51,121][50205] Updated weights for policy 0, policy_version 47387 (0.0011) +[2026-07-22 20:44:51,836][50205] Updated weights for policy 0, policy_version 47397 (0.0012) +[2026-07-22 20:44:52,641][50205] Updated weights for policy 0, policy_version 47407 (0.0011) +[2026-07-22 20:44:53,912][50205] Updated weights for policy 0, policy_version 47417 (0.0017) +[2026-07-22 20:44:54,380][50205] Updated weights for policy 0, policy_version 47427 (0.0012) +[2026-07-22 20:44:54,877][43431] Fps is (10 sec: 5734.9, 60 sec: 5563.7, 300 sec: 5547.0). Total num frames: 24283136. Throughput: 0: 5688.0. Samples: 24293936. Policy #0 lag: (min: 1.0, avg: 14.3, max: 33.0) +[2026-07-22 20:44:54,878][43431] Avg episode reward: [(0, '1785.746')] +[2026-07-22 20:44:55,196][50205] Updated weights for policy 0, policy_version 47437 (0.0016) +[2026-07-22 20:44:56,360][50205] Updated weights for policy 0, policy_version 47447 (0.0016) +[2026-07-22 20:44:57,190][50205] Updated weights for policy 0, policy_version 47457 (0.0011) +[2026-07-22 20:44:57,803][50205] Updated weights for policy 0, policy_version 47467 (0.0010) +[2026-07-22 20:44:59,194][50205] Updated weights for policy 0, policy_version 47477 (0.0011) +[2026-07-22 20:44:59,701][50205] Updated weights for policy 0, policy_version 47487 (0.0015) +[2026-07-22 20:44:59,877][43431] Fps is (10 sec: 6144.1, 60 sec: 5666.1, 300 sec: 5567.8). Total num frames: 24315904. Throughput: 0: 5710.3. Samples: 24311840. Policy #0 lag: (min: 1.0, avg: 14.3, max: 33.0) +[2026-07-22 20:44:59,878][43431] Avg episode reward: [(0, '1841.970')] +[2026-07-22 20:45:00,439][50205] Updated weights for policy 0, policy_version 47497 (0.0011) +[2026-07-22 20:45:01,444][50205] Updated weights for policy 0, policy_version 47507 (0.0011) +[2026-07-22 20:45:02,658][50205] Updated weights for policy 0, policy_version 47518 (0.0013) +[2026-07-22 20:45:03,383][50205] Updated weights for policy 0, policy_version 47528 (0.0016) +[2026-07-22 20:45:04,529][50205] Updated weights for policy 0, policy_version 47538 (0.0021) +[2026-07-22 20:45:04,877][43431] Fps is (10 sec: 5734.5, 60 sec: 5632.0, 300 sec: 5567.8). Total num frames: 24340480. Throughput: 0: 5707.7. Samples: 24345666. Policy #0 lag: (min: 1.0, avg: 14.3, max: 33.0) +[2026-07-22 20:45:04,878][43431] Avg episode reward: [(0, '1838.295')] +[2026-07-22 20:45:05,362][50205] Updated weights for policy 0, policy_version 47548 (0.0011) +[2026-07-22 20:45:05,923][50205] Updated weights for policy 0, policy_version 47558 (0.0010) +[2026-07-22 20:45:06,957][50205] Updated weights for policy 0, policy_version 47568 (0.0011) +[2026-07-22 20:45:07,961][50205] Updated weights for policy 0, policy_version 47578 (0.0012) +[2026-07-22 20:45:08,634][50205] Updated weights for policy 0, policy_version 47588 (0.0013) +[2026-07-22 20:45:09,693][50205] Updated weights for policy 0, policy_version 47598 (0.0021) +[2026-07-22 20:45:09,877][43431] Fps is (10 sec: 5529.6, 60 sec: 5700.3, 300 sec: 5581.7). Total num frames: 24371200. Throughput: 0: 5743.7. Samples: 24381314. Policy #0 lag: (min: 1.0, avg: 14.3, max: 33.0) +[2026-07-22 20:45:09,878][43431] Avg episode reward: [(0, '1841.260')] +[2026-07-22 20:45:10,468][50205] Updated weights for policy 0, policy_version 47608 (0.0010) +[2026-07-22 20:45:11,196][50205] Updated weights for policy 0, policy_version 47618 (0.0011) +[2026-07-22 20:45:11,931][50205] Updated weights for policy 0, policy_version 47628 (0.0014) +[2026-07-22 20:45:13,008][50205] Updated weights for policy 0, policy_version 47638 (0.0012) +[2026-07-22 20:45:13,690][50205] Updated weights for policy 0, policy_version 47648 (0.0021) +[2026-07-22 20:45:14,685][50205] Updated weights for policy 0, policy_version 47658 (0.0013) +[2026-07-22 20:45:14,877][43431] Fps is (10 sec: 6144.0, 60 sec: 5768.5, 300 sec: 5602.5). Total num frames: 24401920. Throughput: 0: 5775.1. Samples: 24399504. Policy #0 lag: (min: 1.0, avg: 14.3, max: 33.0) +[2026-07-22 20:45:14,878][43431] Avg episode reward: [(0, '1789.158')] +[2026-07-22 20:45:15,580][50205] Updated weights for policy 0, policy_version 47668 (0.0014) +[2026-07-22 20:45:16,242][50205] Updated weights for policy 0, policy_version 47678 (0.0014) +[2026-07-22 20:45:16,900][50205] Updated weights for policy 0, policy_version 47688 (0.0011) +[2026-07-22 20:45:18,212][50205] Updated weights for policy 0, policy_version 47698 (0.0013) +[2026-07-22 20:45:18,845][50205] Updated weights for policy 0, policy_version 47708 (0.0014) +[2026-07-22 20:45:19,533][50205] Updated weights for policy 0, policy_version 47718 (0.0011) +[2026-07-22 20:45:19,877][43431] Fps is (10 sec: 6144.0, 60 sec: 5802.7, 300 sec: 5616.4). Total num frames: 24432640. Throughput: 0: 5831.2. Samples: 24435804. Policy #0 lag: (min: 3.0, avg: 16.5, max: 32.0) +[2026-07-22 20:45:19,878][43431] Avg episode reward: [(0, '1735.891')] +[2026-07-22 20:45:20,567][50205] Updated weights for policy 0, policy_version 47728 (0.0011) +[2026-07-22 20:45:21,473][50205] Updated weights for policy 0, policy_version 47738 (0.0011) +[2026-07-22 20:45:22,185][50205] Updated weights for policy 0, policy_version 47748 (0.0011) +[2026-07-22 20:45:23,253][50205] Updated weights for policy 0, policy_version 47758 (0.0016) +[2026-07-22 20:45:24,000][50205] Updated weights for policy 0, policy_version 47768 (0.0016) +[2026-07-22 20:45:24,698][50205] Updated weights for policy 0, policy_version 47778 (0.0010) +[2026-07-22 20:45:24,877][43431] Fps is (10 sec: 6143.9, 60 sec: 5836.8, 300 sec: 5623.3). Total num frames: 24463360. Throughput: 0: 5883.0. Samples: 24471868. Policy #0 lag: (min: 3.0, avg: 16.5, max: 32.0) +[2026-07-22 20:45:24,878][43431] Avg episode reward: [(0, '1894.014')] +[2026-07-22 20:45:25,536][50205] Updated weights for policy 0, policy_version 47788 (0.0013) +[2026-07-22 20:45:26,688][50205] Updated weights for policy 0, policy_version 47798 (0.0013) +[2026-07-22 20:45:27,093][50205] Updated weights for policy 0, policy_version 47808 (0.0014) +[2026-07-22 20:45:28,182][50205] Updated weights for policy 0, policy_version 47818 (0.0012) +[2026-07-22 20:45:29,165][50205] Updated weights for policy 0, policy_version 47828 (0.0012) +[2026-07-22 20:45:29,790][50205] Updated weights for policy 0, policy_version 47838 (0.0016) +[2026-07-22 20:45:29,877][43431] Fps is (10 sec: 6144.0, 60 sec: 5870.9, 300 sec: 5630.3). Total num frames: 24494080. Throughput: 0: 5914.1. Samples: 24490030. Policy #0 lag: (min: 3.0, avg: 16.5, max: 32.0) +[2026-07-22 20:45:29,878][43431] Avg episode reward: [(0, '1725.145')] +[2026-07-22 20:45:30,604][50205] Updated weights for policy 0, policy_version 47848 (0.0019) +[2026-07-22 20:45:31,763][50205] Updated weights for policy 0, policy_version 47858 (0.0016) +[2026-07-22 20:45:32,261][50205] Updated weights for policy 0, policy_version 47868 (0.0015) +[2026-07-22 20:45:33,216][50205] Updated weights for policy 0, policy_version 47878 (0.0014) +[2026-07-22 20:45:34,147][50205] Updated weights for policy 0, policy_version 47888 (0.0011) +[2026-07-22 20:45:34,877][43431] Fps is (10 sec: 5939.3, 60 sec: 5905.1, 300 sec: 5630.3). Total num frames: 24522752. Throughput: 0: 5962.3. Samples: 24526400. Policy #0 lag: (min: 3.0, avg: 16.5, max: 32.0) +[2026-07-22 20:45:34,878][43431] Avg episode reward: [(0, '1832.746')] +[2026-07-22 20:45:34,992][50205] Updated weights for policy 0, policy_version 47898 (0.0010) +[2026-07-22 20:45:35,590][50205] Updated weights for policy 0, policy_version 47908 (0.0015) +[2026-07-22 20:45:36,753][50205] Updated weights for policy 0, policy_version 47918 (0.0011) +[2026-07-22 20:45:37,346][50205] Updated weights for policy 0, policy_version 47928 (0.0011) +[2026-07-22 20:45:38,183][50205] Updated weights for policy 0, policy_version 47938 (0.0011) +[2026-07-22 20:45:39,211][50205] Updated weights for policy 0, policy_version 47948 (0.0011) +[2026-07-22 20:45:39,877][43431] Fps is (10 sec: 5939.2, 60 sec: 5939.2, 300 sec: 5651.1). Total num frames: 24553472. Throughput: 0: 5976.8. Samples: 24562890. Policy #0 lag: (min: 3.0, avg: 16.5, max: 32.0) +[2026-07-22 20:45:39,878][43431] Avg episode reward: [(0, '1890.333')] +[2026-07-22 20:45:40,142][50205] Updated weights for policy 0, policy_version 47958 (0.0013) +[2026-07-22 20:45:41,247][50205] Updated weights for policy 0, policy_version 47971 (0.0011) +[2026-07-22 20:45:42,530][50205] Updated weights for policy 0, policy_version 47981 (0.0011) +[2026-07-22 20:45:43,210][50205] Updated weights for policy 0, policy_version 47991 (0.0011) +[2026-07-22 20:45:44,051][50205] Updated weights for policy 0, policy_version 48001 (0.0014) +[2026-07-22 20:45:44,878][43431] Fps is (10 sec: 5733.8, 60 sec: 5905.1, 300 sec: 5644.1). Total num frames: 24580096. Throughput: 0: 5926.4. Samples: 24578536. Policy #0 lag: (min: 3.0, avg: 16.5, max: 32.0) +[2026-07-22 20:45:44,879][43431] Avg episode reward: [(0, '1749.555')] +[2026-07-22 20:45:44,917][50205] Updated weights for policy 0, policy_version 48011 (0.0011) +[2026-07-22 20:45:45,843][50205] Updated weights for policy 0, policy_version 48021 (0.0014) +[2026-07-22 20:45:46,418][50205] Updated weights for policy 0, policy_version 48031 (0.0012) +[2026-07-22 20:45:47,558][50205] Updated weights for policy 0, policy_version 48041 (0.0013) +[2026-07-22 20:45:48,328][50205] Updated weights for policy 0, policy_version 48051 (0.0023) +[2026-07-22 20:45:49,141][50205] Updated weights for policy 0, policy_version 48061 (0.0018) +[2026-07-22 20:45:49,877][43431] Fps is (10 sec: 5734.4, 60 sec: 5939.2, 300 sec: 5651.1). Total num frames: 24610816. Throughput: 0: 5984.4. Samples: 24614962. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 20:45:49,878][43431] Avg episode reward: [(0, '1780.301')] +[2026-07-22 20:45:49,992][50205] Updated weights for policy 0, policy_version 48071 (0.0011) +[2026-07-22 20:45:50,931][50205] Updated weights for policy 0, policy_version 48081 (0.0016) +[2026-07-22 20:45:51,493][50205] Updated weights for policy 0, policy_version 48091 (0.0015) +[2026-07-22 20:45:52,700][50205] Updated weights for policy 0, policy_version 48101 (0.0011) +[2026-07-22 20:45:53,395][50205] Updated weights for policy 0, policy_version 48111 (0.0011) +[2026-07-22 20:45:54,127][50205] Updated weights for policy 0, policy_version 48121 (0.0011) +[2026-07-22 20:45:54,877][43431] Fps is (10 sec: 6144.6, 60 sec: 5973.3, 300 sec: 5658.0). Total num frames: 24641536. Throughput: 0: 6004.4. Samples: 24651510. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 20:45:54,878][43431] Avg episode reward: [(0, '1723.046')] +[2026-07-22 20:45:54,992][50205] Updated weights for policy 0, policy_version 48131 (0.0011) +[2026-07-22 20:45:56,041][50205] Updated weights for policy 0, policy_version 48141 (0.0015) +[2026-07-22 20:45:56,568][50205] Updated weights for policy 0, policy_version 48151 (0.0011) +[2026-07-22 20:45:57,620][50205] Updated weights for policy 0, policy_version 48161 (0.0013) +[2026-07-22 20:45:58,343][50205] Updated weights for policy 0, policy_version 48171 (0.0011) +[2026-07-22 20:45:59,232][50205] Updated weights for policy 0, policy_version 48181 (0.0010) +[2026-07-22 20:45:59,877][43431] Fps is (10 sec: 6144.0, 60 sec: 5939.2, 300 sec: 5678.9). Total num frames: 24672256. Throughput: 0: 6006.9. Samples: 24669812. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 20:45:59,878][43431] Avg episode reward: [(0, '1743.139')] +[2026-07-22 20:46:00,193][50205] Updated weights for policy 0, policy_version 48191 (0.0012) +[2026-07-22 20:46:00,994][50205] Updated weights for policy 0, policy_version 48201 (0.0021) +[2026-07-22 20:46:01,567][50205] Updated weights for policy 0, policy_version 48211 (0.0014) +[2026-07-22 20:46:03,018][50205] Updated weights for policy 0, policy_version 48224 (0.0016) +[2026-07-22 20:46:03,767][50205] Updated weights for policy 0, policy_version 48234 (0.0011) +[2026-07-22 20:46:04,368][50205] Updated weights for policy 0, policy_version 48244 (0.0011) +[2026-07-22 20:46:04,877][43431] Fps is (10 sec: 5939.3, 60 sec: 6007.5, 300 sec: 5678.9). Total num frames: 24700928. Throughput: 0: 5996.9. Samples: 24705666. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 20:46:04,878][43431] Avg episode reward: [(0, '1851.790')] +[2026-07-22 20:46:05,579][50205] Updated weights for policy 0, policy_version 48254 (0.0012) +[2026-07-22 20:46:05,991][50205] Updated weights for policy 0, policy_version 48264 (0.0011) +[2026-07-22 20:46:07,001][50205] Updated weights for policy 0, policy_version 48274 (0.0016) +[2026-07-22 20:46:07,996][50205] Updated weights for policy 0, policy_version 48284 (0.0012) +[2026-07-22 20:46:08,795][50205] Updated weights for policy 0, policy_version 48296 (0.0014) +[2026-07-22 20:46:09,854][50205] Updated weights for policy 0, policy_version 48306 (0.0016) +[2026-07-22 20:46:09,877][43431] Fps is (10 sec: 5939.2, 60 sec: 6007.5, 300 sec: 5685.8). Total num frames: 24731648. Throughput: 0: 5999.6. Samples: 24741848. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 20:46:09,878][43431] Avg episode reward: [(0, '1778.853')] +[2026-07-22 20:46:10,873][50205] Updated weights for policy 0, policy_version 48316 (0.0014) +[2026-07-22 20:46:11,343][50205] Updated weights for policy 0, policy_version 48326 (0.0011) +[2026-07-22 20:46:12,134][50205] Updated weights for policy 0, policy_version 48336 (0.0012) +[2026-07-22 20:46:13,463][50205] Updated weights for policy 0, policy_version 48346 (0.0011) +[2026-07-22 20:46:13,813][50205] Updated weights for policy 0, policy_version 48356 (0.0013) +[2026-07-22 20:46:14,798][50205] Updated weights for policy 0, policy_version 48366 (0.0011) +[2026-07-22 20:46:14,877][43431] Fps is (10 sec: 6348.8, 60 sec: 6041.6, 300 sec: 5699.7). Total num frames: 24764416. Throughput: 0: 6004.2. Samples: 24760220. Policy #0 lag: (min: 3.0, avg: 18.0, max: 35.0) +[2026-07-22 20:46:14,878][43431] Avg episode reward: [(0, '1854.495')] +[2026-07-22 20:46:15,755][50205] Updated weights for policy 0, policy_version 48376 (0.0011) +[2026-07-22 20:46:16,580][50205] Updated weights for policy 0, policy_version 48386 (0.0015) +[2026-07-22 20:46:17,236][50205] Updated weights for policy 0, policy_version 48396 (0.0011) +[2026-07-22 20:46:18,331][50205] Updated weights for policy 0, policy_version 48406 (0.0013) +[2026-07-22 20:46:19,101][50205] Updated weights for policy 0, policy_version 48416 (0.0011) +[2026-07-22 20:46:19,819][50205] Updated weights for policy 0, policy_version 48426 (0.0011) +[2026-07-22 20:46:19,877][43431] Fps is (10 sec: 6348.8, 60 sec: 6041.6, 300 sec: 5706.6). Total num frames: 24795136. Throughput: 0: 6007.2. Samples: 24796724. Policy #0 lag: (min: 3.0, avg: 17.7, max: 43.0) +[2026-07-22 20:46:19,878][43431] Avg episode reward: [(0, '1782.322')] +[2026-07-22 20:46:20,680][50205] Updated weights for policy 0, policy_version 48436 (0.0011) +[2026-07-22 20:46:21,746][50205] Updated weights for policy 0, policy_version 48446 (0.0010) +[2026-07-22 20:46:22,321][50205] Updated weights for policy 0, policy_version 48456 (0.0010) +[2026-07-22 20:46:23,249][50205] Updated weights for policy 0, policy_version 48466 (0.0011) +[2026-07-22 20:46:24,180][50205] Updated weights for policy 0, policy_version 48476 (0.0013) +[2026-07-22 20:46:24,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5973.3, 300 sec: 5706.6). Total num frames: 24821760. Throughput: 0: 6011.3. Samples: 24833400. Policy #0 lag: (min: 3.0, avg: 17.7, max: 43.0) +[2026-07-22 20:46:24,878][43431] Avg episode reward: [(0, '1673.444')] +[2026-07-22 20:46:25,013][50205] Updated weights for policy 0, policy_version 48486 (0.0011) +[2026-07-22 20:46:25,857][50205] Updated weights for policy 0, policy_version 48497 (0.0011) +[2026-07-22 20:46:26,800][50205] Updated weights for policy 0, policy_version 48507 (0.0011) +[2026-07-22 20:46:27,677][50205] Updated weights for policy 0, policy_version 48517 (0.0012) +[2026-07-22 20:46:28,369][50205] Updated weights for policy 0, policy_version 48527 (0.0011) +[2026-07-22 20:46:29,374][50205] Updated weights for policy 0, policy_version 48537 (0.0010) +[2026-07-22 20:46:29,877][43431] Fps is (10 sec: 5734.3, 60 sec: 5973.3, 300 sec: 5713.6). Total num frames: 24852480. Throughput: 0: 6066.5. Samples: 24851524. Policy #0 lag: (min: 3.0, avg: 17.7, max: 43.0) +[2026-07-22 20:46:29,878][43431] Avg episode reward: [(0, '1808.374')] +[2026-07-22 20:46:30,194][50205] Updated weights for policy 0, policy_version 48547 (0.0011) +[2026-07-22 20:46:30,972][50205] Updated weights for policy 0, policy_version 48557 (0.0021) +[2026-07-22 20:46:31,882][50205] Updated weights for policy 0, policy_version 48567 (0.0011) +[2026-07-22 20:46:32,696][50205] Updated weights for policy 0, policy_version 48577 (0.0012) +[2026-07-22 20:46:33,384][50205] Updated weights for policy 0, policy_version 48587 (0.0012) +[2026-07-22 20:46:34,607][50205] Updated weights for policy 0, policy_version 48597 (0.0011) +[2026-07-22 20:46:34,877][43431] Fps is (10 sec: 6144.2, 60 sec: 6007.5, 300 sec: 5720.5). Total num frames: 24883200. Throughput: 0: 6070.9. Samples: 24888150. Policy #0 lag: (min: 3.0, avg: 17.7, max: 43.0) +[2026-07-22 20:46:34,878][43431] Avg episode reward: [(0, '1878.212')] +[2026-07-22 20:46:35,293][50205] Updated weights for policy 0, policy_version 48607 (0.0011) +[2026-07-22 20:46:35,937][50205] Updated weights for policy 0, policy_version 48618 (0.0011) +[2026-07-22 20:46:36,940][50205] Updated weights for policy 0, policy_version 48628 (0.0011) +[2026-07-22 20:46:37,893][50205] Updated weights for policy 0, policy_version 48638 (0.0016) +[2026-07-22 20:46:38,435][50205] Updated weights for policy 0, policy_version 48648 (0.0016) +[2026-07-22 20:46:39,601][50205] Updated weights for policy 0, policy_version 48658 (0.0011) +[2026-07-22 20:46:39,877][43431] Fps is (10 sec: 6144.2, 60 sec: 6007.5, 300 sec: 5727.5). Total num frames: 24913920. Throughput: 0: 6066.7. Samples: 24924510. Policy #0 lag: (min: 3.0, avg: 17.7, max: 43.0) +[2026-07-22 20:46:39,878][43431] Avg episode reward: [(0, '1758.355')] +[2026-07-22 20:46:40,437][50205] Updated weights for policy 0, policy_version 48669 (0.0010) +[2026-07-22 20:46:41,043][50205] Updated weights for policy 0, policy_version 48679 (0.0015) +[2026-07-22 20:46:42,406][50205] Updated weights for policy 0, policy_version 48689 (0.0011) +[2026-07-22 20:46:43,149][50205] Updated weights for policy 0, policy_version 48701 (0.0015) +[2026-07-22 20:46:43,881][50205] Updated weights for policy 0, policy_version 48712 (0.0011) +[2026-07-22 20:46:44,877][43431] Fps is (10 sec: 6143.9, 60 sec: 6075.8, 300 sec: 5748.3). Total num frames: 24944640. Throughput: 0: 6064.7. Samples: 24942726. Policy #0 lag: (min: 3.0, avg: 17.7, max: 43.0) +[2026-07-22 20:46:44,878][43431] Avg episode reward: [(0, '1795.750')] +[2026-07-22 20:46:45,131][50205] Updated weights for policy 0, policy_version 48722 (0.0011) +[2026-07-22 20:46:45,744][50205] Updated weights for policy 0, policy_version 48732 (0.0013) +[2026-07-22 20:46:46,407][50205] Updated weights for policy 0, policy_version 48742 (0.0016) +[2026-07-22 20:46:47,297][50205] Updated weights for policy 0, policy_version 48752 (0.0012) +[2026-07-22 20:46:48,321][50205] Updated weights for policy 0, policy_version 48762 (0.0019) +[2026-07-22 20:46:48,938][50205] Updated weights for policy 0, policy_version 48772 (0.0013) +[2026-07-22 20:46:49,877][43431] Fps is (10 sec: 5939.1, 60 sec: 6041.6, 300 sec: 5741.4). Total num frames: 24973312. Throughput: 0: 6069.2. Samples: 24978780. Policy #0 lag: (min: 3.0, avg: 21.0, max: 39.0) +[2026-07-22 20:46:49,878][43431] Avg episode reward: [(0, '1850.146')] +[2026-07-22 20:46:50,118][50205] Updated weights for policy 0, policy_version 48782 (0.0015) +[2026-07-22 20:46:50,833][50205] Updated weights for policy 0, policy_version 48792 (0.0011) +[2026-07-22 20:46:51,601][50205] Updated weights for policy 0, policy_version 48802 (0.0013) +[2026-07-22 20:46:52,638][50205] Updated weights for policy 0, policy_version 48812 (0.0011) +[2026-07-22 20:46:53,450][50205] Updated weights for policy 0, policy_version 48822 (0.0019) +[2026-07-22 20:46:53,925][50205] Updated weights for policy 0, policy_version 48832 (0.0011) +[2026-07-22 20:46:54,252][49527] Stopping Batcher_0... +[2026-07-22 20:46:54,252][43431] Component Batcher_0 stopped! +[2026-07-22 20:46:54,252][49527] Loop batcher_evt_loop terminating... +[2026-07-22 20:46:54,253][49527] Saving results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/checkpoint_p0/checkpoint_000048836_25004032.pth... +[2026-07-22 20:46:54,281][50205] Weights refcount: 2 0 +[2026-07-22 20:46:54,297][49527] Removing results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/checkpoint_p0/checkpoint_000018708_9578496.pth +[2026-07-22 20:46:54,303][49527] Saving results/checkpoints/memory/rollout_teacher/deadly_corridor_teacher_fixed_l6_obs8p75_seed0/checkpoint_p0/checkpoint_000048836_25004032.pth... +[2026-07-22 20:46:54,392][49527] Stopping LearnerWorker_p0... +[2026-07-22 20:46:54,393][43431] Component LearnerWorker_p0 stopped! +[2026-07-22 20:46:54,393][49527] Loop learner_proc0_evt_loop terminating... +[2026-07-22 20:46:54,407][50205] Stopping InferenceWorker_p0-w0... +[2026-07-22 20:46:54,407][43431] Component InferenceWorker_p0-w0 stopped! +[2026-07-22 20:46:54,407][50205] Loop inference_proc0-0_evt_loop terminating... +[2026-07-22 20:46:54,433][50987] Stopping RolloutWorker_w18... +[2026-07-22 20:46:54,433][50987] Loop rollout_proc18_evt_loop terminating... +[2026-07-22 20:46:54,433][43431] Component RolloutWorker_w18 stopped! +[2026-07-22 20:46:54,543][50231] Stopping RolloutWorker_w5... +[2026-07-22 20:46:54,543][43431] Component RolloutWorker_w5 stopped! +[2026-07-22 20:46:54,543][50231] Loop rollout_proc5_evt_loop terminating... +[2026-07-22 20:46:54,632][51846] Stopping RolloutWorker_w31... +[2026-07-22 20:46:54,632][43431] Component RolloutWorker_w1 stopped! +[2026-07-22 20:46:54,632][50209] Stopping RolloutWorker_w1... +[2026-07-22 20:46:54,635][51846] Loop rollout_proc31_evt_loop terminating... +[2026-07-22 20:46:54,635][43431] Component RolloutWorker_w31 stopped! +[2026-07-22 20:46:54,635][50209] Loop rollout_proc1_evt_loop terminating... +[2026-07-22 20:46:54,635][43431] Component RolloutWorker_w13 stopped! +[2026-07-22 20:46:54,635][50233] Stopping RolloutWorker_w13... +[2026-07-22 20:46:54,636][50233] Loop rollout_proc13_evt_loop terminating... +[2026-07-22 20:46:54,639][43431] Component RolloutWorker_w28 stopped! +[2026-07-22 20:46:54,638][51121] Stopping RolloutWorker_w28... +[2026-07-22 20:46:54,639][51121] Loop rollout_proc28_evt_loop terminating... +[2026-07-22 20:46:54,645][51124] Stopping RolloutWorker_w29... +[2026-07-22 20:46:54,645][51124] Loop rollout_proc29_evt_loop terminating... +[2026-07-22 20:46:54,646][43431] Component RolloutWorker_w29 stopped! +[2026-07-22 20:46:54,658][50226] Stopping RolloutWorker_w10... +[2026-07-22 20:46:54,658][43431] Component RolloutWorker_w10 stopped! +[2026-07-22 20:46:54,659][50226] Loop rollout_proc10_evt_loop terminating... +[2026-07-22 20:46:54,665][50236] Stopping RolloutWorker_w12... +[2026-07-22 20:46:54,665][43431] Component RolloutWorker_w12 stopped! +[2026-07-22 20:46:54,665][50236] Loop rollout_proc12_evt_loop terminating... +[2026-07-22 20:46:54,667][50960] Stopping RolloutWorker_w16... +[2026-07-22 20:46:54,667][43431] Component RolloutWorker_w16 stopped! +[2026-07-22 20:46:54,668][50960] Loop rollout_proc16_evt_loop terminating... +[2026-07-22 20:46:54,693][50999] Stopping RolloutWorker_w23... +[2026-07-22 20:46:54,694][43431] Component RolloutWorker_w23 stopped! +[2026-07-22 20:46:54,694][50999] Loop rollout_proc23_evt_loop terminating... +[2026-07-22 20:46:54,697][50208] Stopping RolloutWorker_w0... +[2026-07-22 20:46:54,697][43431] Component RolloutWorker_w0 stopped! +[2026-07-22 20:46:54,697][50208] Loop rollout_proc0_evt_loop terminating... +[2026-07-22 20:46:54,709][43431] Component RolloutWorker_w6 stopped! +[2026-07-22 20:46:54,709][50234] Stopping RolloutWorker_w6... +[2026-07-22 20:46:54,710][50234] Loop rollout_proc6_evt_loop terminating... +[2026-07-22 20:46:54,713][51004] Stopping RolloutWorker_w24... +[2026-07-22 20:46:54,713][43431] Component RolloutWorker_w24 stopped! +[2026-07-22 20:46:54,714][51004] Loop rollout_proc24_evt_loop terminating... +[2026-07-22 20:46:54,786][50996] Stopping RolloutWorker_w21... +[2026-07-22 20:46:54,787][50996] Loop rollout_proc21_evt_loop terminating... +[2026-07-22 20:46:54,790][43431] Component RolloutWorker_w21 stopped! +[2026-07-22 20:46:54,811][50235] Stopping RolloutWorker_w14... +[2026-07-22 20:46:54,811][50235] Loop rollout_proc14_evt_loop terminating... +[2026-07-22 20:46:54,814][43431] Component RolloutWorker_w14 stopped! +[2026-07-22 20:46:54,817][51113] Stopping RolloutWorker_w26... +[2026-07-22 20:46:54,817][43431] Component RolloutWorker_w26 stopped! +[2026-07-22 20:46:54,818][51113] Loop rollout_proc26_evt_loop terminating... +[2026-07-22 20:46:54,876][50990] Stopping RolloutWorker_w20... +[2026-07-22 20:46:54,877][43431] Component RolloutWorker_w20 stopped! +[2026-07-22 20:46:54,877][50990] Loop rollout_proc20_evt_loop terminating... +[2026-07-22 20:46:54,984][50989] Stopping RolloutWorker_w19... +[2026-07-22 20:46:54,984][50989] Loop rollout_proc19_evt_loop terminating... +[2026-07-22 20:46:54,985][50222] Stopping RolloutWorker_w2... +[2026-07-22 20:46:54,985][50222] Loop rollout_proc2_evt_loop terminating... +[2026-07-22 20:46:54,990][43431] Component RolloutWorker_w19 stopped! +[2026-07-22 20:46:54,990][43431] Component RolloutWorker_w2 stopped! +[2026-07-22 20:46:55,038][50228] Stopping RolloutWorker_w7... +[2026-07-22 20:46:55,039][50228] Loop rollout_proc7_evt_loop terminating... +[2026-07-22 20:46:55,042][43431] Component RolloutWorker_w7 stopped! +[2026-07-22 20:46:55,065][51050] Stopping RolloutWorker_w25... +[2026-07-22 20:46:55,066][43431] Component RolloutWorker_w25 stopped! +[2026-07-22 20:46:55,066][51050] Loop rollout_proc25_evt_loop terminating... +[2026-07-22 20:46:55,098][50970] Stopping RolloutWorker_w17... +[2026-07-22 20:46:55,098][43431] Component RolloutWorker_w17 stopped! +[2026-07-22 20:46:55,098][50970] Loop rollout_proc17_evt_loop terminating... +[2026-07-22 20:46:55,117][50227] Stopping RolloutWorker_w8... +[2026-07-22 20:46:55,117][50957] Stopping RolloutWorker_w15... +[2026-07-22 20:46:55,117][43431] Component RolloutWorker_w15 stopped! +[2026-07-22 20:46:55,118][50957] Loop rollout_proc15_evt_loop terminating... +[2026-07-22 20:46:55,118][50227] Loop rollout_proc8_evt_loop terminating... +[2026-07-22 20:46:55,118][43431] Component RolloutWorker_w8 stopped! +[2026-07-22 20:46:55,165][51118] Stopping RolloutWorker_w27... +[2026-07-22 20:46:55,166][43431] Component RolloutWorker_w27 stopped! +[2026-07-22 20:46:55,166][51118] Loop rollout_proc27_evt_loop terminating... +[2026-07-22 20:46:55,186][51252] Stopping RolloutWorker_w30... +[2026-07-22 20:46:55,186][43431] Component RolloutWorker_w30 stopped! +[2026-07-22 20:46:55,186][51252] Loop rollout_proc30_evt_loop terminating... +[2026-07-22 20:46:55,214][50223] Stopping RolloutWorker_w9... +[2026-07-22 20:46:55,214][43431] Component RolloutWorker_w9 stopped! +[2026-07-22 20:46:55,215][50223] Loop rollout_proc9_evt_loop terminating... +[2026-07-22 20:46:55,234][50997] Stopping RolloutWorker_w22... +[2026-07-22 20:46:55,234][43431] Component RolloutWorker_w22 stopped! +[2026-07-22 20:46:55,235][50997] Loop rollout_proc22_evt_loop terminating... +[2026-07-22 20:46:55,433][50229] Stopping RolloutWorker_w4... +[2026-07-22 20:46:55,433][43431] Component RolloutWorker_w4 stopped! +[2026-07-22 20:46:55,433][50229] Loop rollout_proc4_evt_loop terminating... +[2026-07-22 20:46:55,479][50230] Stopping RolloutWorker_w11... +[2026-07-22 20:46:55,479][43431] Component RolloutWorker_w11 stopped! +[2026-07-22 20:46:55,479][50230] Loop rollout_proc11_evt_loop terminating... +[2026-07-22 20:46:55,526][50224] Stopping RolloutWorker_w3... +[2026-07-22 20:46:55,526][43431] Component RolloutWorker_w3 stopped! +[2026-07-22 20:46:55,527][50224] Loop rollout_proc3_evt_loop terminating... +[2026-07-22 20:46:55,527][43431] Waiting for process learner_proc0 to stop... +[2026-07-22 20:46:55,795][43431] Waiting for process inference_proc0-0 to join... +[2026-07-22 20:46:55,796][43431] Waiting for process rollout_proc0 to join... +[2026-07-22 20:46:55,797][43431] Waiting for process rollout_proc1 to join... +[2026-07-22 20:46:55,797][43431] Waiting for process rollout_proc2 to join... +[2026-07-22 20:46:55,884][43431] Waiting for process rollout_proc3 to join... +[2026-07-22 20:46:56,274][43431] Waiting for process rollout_proc4 to join... +[2026-07-22 20:46:56,275][43431] Waiting for process rollout_proc5 to join... +[2026-07-22 20:46:56,275][43431] Waiting for process rollout_proc6 to join... +[2026-07-22 20:46:56,276][43431] Waiting for process rollout_proc7 to join... +[2026-07-22 20:46:56,277][43431] Waiting for process rollout_proc8 to join... +[2026-07-22 20:46:56,277][43431] Waiting for process rollout_proc9 to join... +[2026-07-22 20:46:56,277][43431] Waiting for process rollout_proc10 to join... +[2026-07-22 20:46:56,278][43431] Waiting for process rollout_proc11 to join... +[2026-07-22 20:46:56,278][43431] Waiting for process rollout_proc12 to join... +[2026-07-22 20:46:56,278][43431] Waiting for process rollout_proc13 to join... +[2026-07-22 20:46:56,278][43431] Waiting for process rollout_proc14 to join... +[2026-07-22 20:46:56,279][43431] Waiting for process rollout_proc15 to join... +[2026-07-22 20:46:56,279][43431] Waiting for process rollout_proc16 to join... +[2026-07-22 20:46:56,279][43431] Waiting for process rollout_proc17 to join... +[2026-07-22 20:46:56,280][43431] Waiting for process rollout_proc18 to join... +[2026-07-22 20:46:56,280][43431] Waiting for process rollout_proc19 to join... +[2026-07-22 20:46:56,280][43431] Waiting for process rollout_proc20 to join... +[2026-07-22 20:46:56,281][43431] Waiting for process rollout_proc21 to join... +[2026-07-22 20:46:56,281][43431] Waiting for process rollout_proc22 to join... +[2026-07-22 20:46:56,282][43431] Waiting for process rollout_proc23 to join... +[2026-07-22 20:46:56,282][43431] Waiting for process rollout_proc24 to join... +[2026-07-22 20:46:56,282][43431] Waiting for process rollout_proc25 to join... +[2026-07-22 20:46:56,282][43431] Waiting for process rollout_proc26 to join... +[2026-07-22 20:46:56,283][43431] Waiting for process rollout_proc27 to join... +[2026-07-22 20:46:56,283][43431] Waiting for process rollout_proc28 to join... +[2026-07-22 20:46:56,283][43431] Waiting for process rollout_proc29 to join... +[2026-07-22 20:46:56,284][43431] Waiting for process rollout_proc30 to join... +[2026-07-22 20:46:56,284][43431] Waiting for process rollout_proc31 to join... +[2026-07-22 20:46:56,284][43431] Batcher 0 profile tree view: +batching: 575.7711, releasing_batches: 1.5911 +[2026-07-22 20:46:56,285][43431] InferenceWorker_p0-w0 profile tree view: +wait_policy: 0.0001 + wait_policy_total: 243.2051 +update_model: 101.7838 + weight_update: 0.0011 +one_step: 0.0047 + handle_policy_step: 3954.4658 + deserialize: 561.7708, stack: 19.3880, obs_to_device_normalize: 915.4410, forward: 1722.0744, send_messages: 290.4986 + prepare_outputs: 328.2461 + to_cpu: 185.6044 +[2026-07-22 20:46:56,285][43431] Learner 0 profile tree view: +misc: 0.0605, prepare_batch: 155.6494 +train: 1115.7033 + epoch_init: 0.3100, minibatch_init: 6.8536, losses_postprocess: 23.1249, kl_divergence: 44.9202, after_optimizer: 62.8617 + calculate_losses: 547.5385 + losses_init: 0.2018, forward_head: 33.3237, bptt_initial: 271.1377, tail: 53.1037, advantages_returns: 8.8813, losses: 91.2607 + bptt: 78.8948 + bptt_forward_core: 75.7174 + update: 417.9666 + clip: 41.4641 +[2026-07-22 20:46:56,285][43431] RolloutWorker_w0 profile tree view: +wait_for_trajectories: 0.2791, enqueue_policy_requests: 62.1450, env_step: 3234.5672, overhead: 52.9704, complete_rollouts: 4.9300 +save_policy_outputs: 72.1092 + split_output_tensors: 24.9384 +[2026-07-22 20:46:56,285][43431] RolloutWorker_w31 profile tree view: +wait_for_trajectories: 0.1918, enqueue_policy_requests: 46.1322, env_step: 3908.3727, overhead: 42.7803, complete_rollouts: 1.6983 +save_policy_outputs: 52.4840 + split_output_tensors: 17.9028 +[2026-07-22 20:46:56,289][43431] Loop Runner_EvtLoop terminating... +[2026-07-22 20:46:56,289][43431] Runner profile tree view: +main_loop: 4451.7532 +[2026-07-22 20:46:56,290][43431] Collected {0: 25004032}, FPS: 5616.7 diff --git a/evaluations/deadly-corridor/wan_oft_deadly_corridor_fix_latency_6_context5_standard_sft_1000_effbs128_224_currentbce/eval/fixed_6/eval_latency_6/episode_metrics.jsonl b/evaluations/deadly-corridor/wan_oft_deadly_corridor_fix_latency_6_context5_standard_sft_1000_effbs128_224_currentbce/eval/fixed_6/eval_latency_6/episode_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3e0c8382dce5469c608ee71e5fc9f2c7c7981234 --- /dev/null +++ b/evaluations/deadly-corridor/wan_oft_deadly_corridor_fix_latency_6_context5_standard_sft_1000_effbs128_224_currentbce/eval/fixed_6/eval_latency_6/episode_metrics.jsonl @@ -0,0 +1,20 @@ +{"episode_id": 0, "episode_return": 145.67367553710938, "episode_return_env": 145.67367553710938, "game_score": null, "mean_latency_ms": 171.42857142857142, "metadata": {"checkpoint_path": "/workspace/runtime/wanoft/wan_oft_deadly_corridor_fix_latency_6_context5_standard_sft_1000_effbs128_224_currentbce/checkpoints/steps_1000_pytorch_model.pt", "config_name": "starvla_wan_oft_deadly_corridor_raw6_maxsteps14400", "configured_latency_ms": 171.42857142857142, "env_fps": 35.0, "env_id": "doom_deadly_corridor", "episode_seed": 42, "eval_latency_steps": 6, "frame_ms": 28.571428571428573, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 8.75, "output_dir": "/workspace/evals/wan_oft_deadly_corridor_fix_latency_6_context5_standard_sft_1000_effbs128_224_currentbce/latency_bench_eval/fixed_6/eval_latency_6", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_deadly_corridor_raw6_maxsteps14400", "suite_name": "fixed_6", "target_device": null, "train_latency_steps": 6}, "num_actions": 13, "num_dropped_actions": 1, "num_invalid_actions": 0, "p90_latency_ms": 171.42857142857142, "p99_latency_ms": 171.42857142857142, "return_raw": null, "survival_steps": 50} +{"episode_id": 1, "episode_return": 46.77955627441406, "episode_return_env": 46.77955627441406, "game_score": null, "mean_latency_ms": 171.42857142857142, "metadata": {"checkpoint_path": "/workspace/runtime/wanoft/wan_oft_deadly_corridor_fix_latency_6_context5_standard_sft_1000_effbs128_224_currentbce/checkpoints/steps_1000_pytorch_model.pt", "config_name": "starvla_wan_oft_deadly_corridor_raw6_maxsteps14400", "configured_latency_ms": 171.42857142857142, "env_fps": 35.0, "env_id": "doom_deadly_corridor", "episode_seed": 43, "eval_latency_steps": 6, "frame_ms": 28.571428571428573, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 8.75, "output_dir": "/workspace/evals/wan_oft_deadly_corridor_fix_latency_6_context5_standard_sft_1000_effbs128_224_currentbce/latency_bench_eval/fixed_6/eval_latency_6", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_deadly_corridor_raw6_maxsteps14400", "suite_name": "fixed_6", "target_device": null, "train_latency_steps": 6}, "num_actions": 12, "num_dropped_actions": 1, "num_invalid_actions": 0, "p90_latency_ms": 171.42857142857142, "p99_latency_ms": 171.42857142857142, "return_raw": null, "survival_steps": 46} +{"episode_id": 2, "episode_return": 382.1748809814453, "episode_return_env": 382.1748809814453, "game_score": null, "mean_latency_ms": 171.42857142857142, "metadata": {"checkpoint_path": "/workspace/runtime/wanoft/wan_oft_deadly_corridor_fix_latency_6_context5_standard_sft_1000_effbs128_224_currentbce/checkpoints/steps_1000_pytorch_model.pt", "config_name": "starvla_wan_oft_deadly_corridor_raw6_maxsteps14400", "configured_latency_ms": 171.42857142857142, "env_fps": 35.0, "env_id": "doom_deadly_corridor", "episode_seed": 44, "eval_latency_steps": 6, "frame_ms": 28.571428571428573, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 8.75, "output_dir": "/workspace/evals/wan_oft_deadly_corridor_fix_latency_6_context5_standard_sft_1000_effbs128_224_currentbce/latency_bench_eval/fixed_6/eval_latency_6", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_deadly_corridor_raw6_maxsteps14400", "suite_name": "fixed_6", "target_device": null, "train_latency_steps": 6}, "num_actions": 23, "num_dropped_actions": 0, "num_invalid_actions": 0, "p90_latency_ms": 171.42857142857142, "p99_latency_ms": 171.42857142857142, "return_raw": null, "survival_steps": 92} +{"episode_id": 3, "episode_return": 112.09428405761719, "episode_return_env": 112.09428405761719, "game_score": null, "mean_latency_ms": 171.42857142857142, "metadata": {"checkpoint_path": "/workspace/runtime/wanoft/wan_oft_deadly_corridor_fix_latency_6_context5_standard_sft_1000_effbs128_224_currentbce/checkpoints/steps_1000_pytorch_model.pt", "config_name": "starvla_wan_oft_deadly_corridor_raw6_maxsteps14400", "configured_latency_ms": 171.42857142857142, "env_fps": 35.0, "env_id": "doom_deadly_corridor", "episode_seed": 45, "eval_latency_steps": 6, "frame_ms": 28.571428571428573, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 8.75, "output_dir": "/workspace/evals/wan_oft_deadly_corridor_fix_latency_6_context5_standard_sft_1000_effbs128_224_currentbce/latency_bench_eval/fixed_6/eval_latency_6", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_deadly_corridor_raw6_maxsteps14400", "suite_name": "fixed_6", "target_device": null, "train_latency_steps": 6}, "num_actions": 13, "num_dropped_actions": 1, "num_invalid_actions": 0, "p90_latency_ms": 171.42857142857142, "p99_latency_ms": 171.42857142857142, "return_raw": null, "survival_steps": 50} +{"episode_id": 4, "episode_return": 433.02099609375, "episode_return_env": 433.02099609375, "game_score": null, "mean_latency_ms": 171.42857142857142, "metadata": {"checkpoint_path": "/workspace/runtime/wanoft/wan_oft_deadly_corridor_fix_latency_6_context5_standard_sft_1000_effbs128_224_currentbce/checkpoints/steps_1000_pytorch_model.pt", "config_name": "starvla_wan_oft_deadly_corridor_raw6_maxsteps14400", "configured_latency_ms": 171.42857142857142, "env_fps": 35.0, "env_id": "doom_deadly_corridor", "episode_seed": 46, "eval_latency_steps": 6, "frame_ms": 28.571428571428573, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 8.75, "output_dir": 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"latency_raw_frames": 6, "length": 4619, "raw_frames": 18476, "raw_return": 7120.0, "return": 7120.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 209, "episode_idx": 20, "latency_raw_frames": 6, "length": 4163, "raw_frames": 16652, "raw_return": 6990.0, "return": 6990.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 432, "episode_idx": 20, "latency_raw_frames": 6, "length": 4291, "raw_frames": 17164, "raw_return": 6950.0, "return": 6950.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 507, "episode_idx": 20, "latency_raw_frames": 6, "length": 4024, "raw_frames": 16096, "raw_return": 6955.0, "return": 6955.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 482, "episode_idx": 20, "latency_raw_frames": 6, "length": 7786, "raw_frames": 31144, "raw_return": 18595.0, "return": 18595.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 288, "episode_idx": 19, "latency_raw_frames": 6, "length": 6436, "raw_frames": 25744, "raw_return": 12940.0, "return": 12940.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 456, "episode_idx": 19, "latency_raw_frames": 6, "length": 4236, "raw_frames": 16944, "raw_return": 7325.0, "return": 7325.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 374, "episode_idx": 18, "latency_raw_frames": 6, "length": 4506, "raw_frames": 18024, "raw_return": 7495.0, "return": 7495.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 17, "episode_idx": 21, "latency_raw_frames": 6, "length": 4465, "raw_frames": 17860, "raw_return": 6885.0, "return": 6885.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 445, "episode_idx": 19, "latency_raw_frames": 6, "length": 2383, "raw_frames": 9532, "raw_return": 1680.0, "return": 1680.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 336, "episode_idx": 19, "latency_raw_frames": 6, "length": 5105, "raw_frames": 20420, "raw_return": 8705.0, "return": 8705.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 497, "episode_idx": 16, "latency_raw_frames": 6, "length": 6764, "raw_frames": 27056, "raw_return": 12010.0, "return": 12010.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 79, "episode_idx": 18, "latency_raw_frames": 6, "length": 5194, "raw_frames": 20776, "raw_return": 10040.0, "return": 10040.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 357, "episode_idx": 20, "latency_raw_frames": 6, "length": 3569, "raw_frames": 14276, "raw_return": 6240.0, "return": 6240.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 477, "episode_idx": 21, "latency_raw_frames": 6, "length": 5073, "raw_frames": 20292, "raw_return": 9165.0, "return": 9165.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} +{"done_reason": "terminated", "env_id": 265, "episode_idx": 18, "latency_raw_frames": 6, "length": 5960, "raw_frames": 23840, "raw_return": 9880.0, "return": 9880.0, "terminated": true, "time_limit_truncated": false, "timeout": false, "truncated": false, "vector_index": 0, "worker_index": 0} diff --git a/evaluations/demon-attack/memory_rollout_teacher:demon_attack:teacher:fixed_l6:fs4:obs15:stride4:seed0/train/memory_rollout_teacher:demon_attack:teacher:fixed_l6:fs4:obs15:stride4:seed0/git.diff b/evaluations/demon-attack/memory_rollout_teacher:demon_attack:teacher:fixed_l6:fs4:obs15:stride4:seed0/train/memory_rollout_teacher:demon_attack:teacher:fixed_l6:fs4:obs15:stride4:seed0/git.diff new file mode 100644 index 0000000000000000000000000000000000000000..2e5ef18405c3fcb10565c79d1f33088ee1c4af38 --- /dev/null +++ b/evaluations/demon-attack/memory_rollout_teacher:demon_attack:teacher:fixed_l6:fs4:obs15:stride4:seed0/train/memory_rollout_teacher:demon_attack:teacher:fixed_l6:fs4:obs15:stride4:seed0/git.diff @@ -0,0 +1,1829 @@ +diff --git a/configs/experiments/fixed_latency_curve.yaml b/configs/experiments/fixed_latency_curve.yaml +deleted file mode 100644 +index 3ab184f..0000000 +--- a/configs/experiments/fixed_latency_curve.yaml ++++ /dev/null +@@ -1,17 +0,0 @@ +-__base__: ../base/dummy.yaml +- +-experiment: +- name: fixed_latency_curve +- +-executor: +- mode: simulated +- +-latency: +- method: fixed +- fixed_latency_ms: 100 +- +-evaluation: +- eval_episodes: 20 +- +-logging: +- output_dir: outputs/fixed_latency_curve +diff --git a/configs/experiments/flappy/frame_stack/base.yaml b/configs/experiments/flappy/frame_stack/base.yaml +deleted file mode 100644 +index f1557d5..0000000 +--- a/configs/experiments/flappy/frame_stack/base.yaml ++++ /dev/null +@@ -1,123 +0,0 @@ +-experiment: +- name: flappy_base +- seed: 0 +- +-backend: +- type: sample_factory +- algo: APPO +- device: cuda +- train_dir: results/checkpoints +- restart_behavior: resume +- run_mode: train +- +-executor: +- mode: simulated +- +-env: +- name: flappy +- # note that env_fps must be an integer multiple of obs_fps! +- env_fps: 30 +- obs_fps: 30 +- gym_id: FlappyBird-v0 +- render_mode: rgb_array +- observation_mode: image +- use_lidar: false +- normalize_obs: true +- audio_on: false +- frame_stack: 4 +- obs_resize: +- - 84 +- - 84 +- # for training it could be true, but for realtime mode, THIS MUST BE FALSE! +- use_gpu_render: true +- simulator: gpu +- gpu_render_device: auto +- gpu_render_profile: false +- gpu_render_profile_interval: 200 +- noop_action: noop +- action_map: +- noop: 0 +- flap: 1 +- oneshot_actions: +- - flap +- +-latency: +- method: normal +- mean_latency_ms: 66.7 +- std_latency_ms: 33.3 +- min_latency_ms: 0 +- max_latency_ms: 500.0 +- +- +-scheduler: +- # [one_frame_then_noop, hold] +- # if hold, default hold duration is: env_fps / obs_fps +- hold_policy: one_frame_then_noop +- # can be either `issue_order_fifo` or `latest ready` +- ordering_policy: latest_ready +- +-policy: +- type: random +- actions: +- - noop +- - flap +- +-training: +- train_for_env_steps: 25000000 +- num_workers: 2 +- num_envs_per_worker: 128 +- worker_num_splits: 1 +- num_policies: 1 +- batch_size: 4096 +- rollout: 128 +- recurrence: 1 +- num_epochs: 8 +- num_batches_per_epoch: 8 +- max_policy_lag: 400 +- learning_rate: 0.00025 +- gamma: 0.99 +- gae_lambda: 0.95 +- ppo_clip_ratio: 0.1 +- ppo_clip_value: 0.2 +- value_loss_coeff: 0.5 +- max_grad_norm: 0.5 +- async_rl: true +- use_rnn: false +- normalize_input: true +- normalize_returns: true +- stats_avg: 100 +- experiment_summaries_interval: 1 +- save_every_sec: 600 +- keep_checkpoints: 5 +- +-evaluation: +- eval_interval_steps: 1000000 +- eval_episodes: 100 +- eval_parallel_envs: 100 +- eval_max_steps: 3600 +- eval_deterministic: true +- eval_raw_reward: false +- eval_suites: +- fixed: +- - [0, 8] # [start, end] +- normal: +- - [2.0, 0.5, 0, 15] # low latency, low jitter +- - [2.0, 1.0, 0, 15] # low latency, medium jitter +- - [4.0, 0.5, 0, 15] # high latency, low jitter +- - [4.0, 1.0, 0, 15] # high latency, medium jitter +- - [4.0, 2.0, 0, 15] # high latency, high jitter +- uniform: +- - [1, 3] # low latency, low jitter +- - [0, 4] # low latency, high jitter +- - [3, 5] # high latency, low jitter +- - [2, 6] # high latency, high jitter +- +-logging: +- output_dir: outputs/flappy_base +- save_step_records: true +- save_action_records: true +- save_latency_records: true +- wandb_project: latency-sensitive-bench +- wandb_group: flappy-frame_stack +- wandb_job_type: sample_factory +- wandb_tags: "" +diff --git a/latency_bench/data/exporters/starvla_lerobot.py b/latency_bench/data/exporters/starvla_lerobot.py +index c693460..4ad276a 100644 +--- a/latency_bench/data/exporters/starvla_lerobot.py ++++ b/latency_bench/data/exporters/starvla_lerobot.py +@@ -18,12 +18,17 @@ from latency_bench.utils.io import write_jsonl + from latency_bench.data.action_layouts import action_spec_for_env + from latency_bench.data.filters import density_weights_clean_v1 + +-FPS_BY_ENV = { +- "flappy": 30, +- "demon_attack": 60, +- "deadly_corridor": 35, +-} + STATE_DIM = 1 ++BRIDGE_DIM = 7 ++DEADLY_CORRIDOR_BRIDGE_ACTION_LABELS = ( ++ "MOVE_FORWARD", ++ "MOVE_BACKWARD", ++ "MOVE_LEFT", ++ "MOVE_RIGHT", ++ "TURN_LEFT", ++ "TURN_RIGHT", ++ "ATTACK", ++) + + + def _png_bytes(image: Any) -> bytes: +@@ -64,30 +69,38 @@ def _load_rows(raw_export_dir: Path, split: str) -> list[dict[str, Any]]: + + + def _episode_groups(rows: list[dict[str, Any]]) -> list[list[dict[str, Any]]]: +- """Group canonical rows by episode and order by decision step. ++ """Group canonical rows by trajectory and order by decision step. + + Args: + rows: Canonical rollout rows from one split. + + Returns: +- Episode row groups sorted by episode index. ++ Trajectory row groups sorted by episode and trajectory index. + """ +- grouped: dict[int, list[dict[str, Any]]] = {} ++ grouped: dict[tuple[int, int], list[dict[str, Any]]] = {} + for row in rows: +- grouped.setdefault(int(row["episode_idx"]), []).append(row) ++ key = (int(row["episode_idx"]), int(row["trajectory_idx"])) ++ grouped.setdefault(key, []).append(row) + return [ + sorted(episode_rows, key=lambda row: int(row["decision_step"])) + for _, episode_rows in sorted(grouped.items()) + ] + + +-def _write_episode(path: Path, rows: list[dict[str, Any]], *, action_dim: int) -> None: ++def _write_episode( ++ path: Path, ++ rows: list[dict[str, Any]], ++ *, ++ action_dim: int, ++ state_dim: int, ++) -> None: + """Write one LeRobot episode parquet file. + + Args: + path: Destination episode parquet path. + rows: Converted LeRobot frame rows. + action_dim: Expected action vector dimension. ++ state_dim: Expected state carrier dimension. + """ + path.parent.mkdir(parents=True, exist_ok=True) + table = pa.table( +@@ -97,8 +110,8 @@ def _write_episode(path: Path, rows: list[dict[str, Any]], *, action_dim: int) - + type=pa.struct([("bytes", pa.binary()), ("path", pa.string())]), + ), + "observation.state": pa.array( +- [[0.0] * STATE_DIM for _ in rows], +- type=pa.list_(pa.float32(), STATE_DIM), ++ [[0.0] * state_dim for _ in rows], ++ type=pa.list_(pa.float32(), state_dim), + ), + "action": pa.array( + [row["action"] for row in rows], +@@ -131,11 +144,47 @@ def _row_action_vector(row: dict[str, Any], *, action_dim: int) -> list[float]: + return [1.0 if idx == action_id else 0.0 for idx in range(action_dim)] + + ++def _bridge_action_vector( ++ row: dict[str, Any], ++ *, ++ env_name: str, ++ active_action_dim: int, ++) -> list[float]: ++ if env_name == "deadly_corridor": ++ action_text = str(row["action_text"]).upper() ++ return [ ++ 1.0 if label in action_text else 0.0 ++ for label in DEADLY_CORRIDOR_BRIDGE_ACTION_LABELS ++ ] ++ action = _row_action_vector(row, action_dim=active_action_dim) ++ return [*action, *([0.0] * (BRIDGE_DIM - active_action_dim))] ++ ++ ++def _target_action_labels( ++ *, ++ env_name: str, ++ source_action_labels: list[str], ++ action_carrier: str, ++) -> list[str]: ++ if action_carrier == "native": ++ return source_action_labels ++ if env_name == "deadly_corridor": ++ return list(DEADLY_CORRIDOR_BRIDGE_ACTION_LABELS) ++ return [ ++ *source_action_labels, ++ *[ ++ f"BRIDGE_PAD_{idx}" ++ for idx in range(len(source_action_labels), BRIDGE_DIM) ++ ], ++ ] ++ ++ + def _write_metadata( + dataset_dir: Path, + *, +- fps: int, ++ fps: float, + action_labels: list[str], ++ state_dim: int, + episode_lengths: list[int], + task_prompts: list[str], + ) -> None: +@@ -144,7 +193,8 @@ def _write_metadata( + Args: + dataset_dir: LeRobot dataset split directory. + fps: Frame rate stored in metadata. +- action_labels: Canonical action labels in vector order. ++ action_labels: Target action labels in vector order. ++ state_dim: State carrier dimension. + episode_lengths: Number of frames per converted episode. + task_prompts: Unique prompts used as LeRobot tasks. + """ +@@ -155,10 +205,10 @@ def _write_metadata( + json.dumps( + { + "codebase_version": "v2.0", +- "fps": int(fps), ++ "fps": fps, + "features": { + "observation.image": {"dtype": "image"}, +- "observation.state": {"dtype": "float32", "shape": [STATE_DIM]}, ++ "observation.state": {"dtype": "float32", "shape": [state_dim]}, + "action": {"dtype": "float32", "shape": [action_dim], "names": action_labels}, + "timestamp": {"dtype": "float64", "shape": [1]}, + "episode_index": {"dtype": "int64", "shape": [1]}, +@@ -183,9 +233,11 @@ def _convert_split( + *, + env_name: str, + action_labels: list[str], +- fps: int, ++ fps: float, + reward_field: str, +- obs_stride: int = 1, ++ action_carrier: str, ++ active_action_dim: int, ++ state_dim: int, + density_weighting: bool = False, + ) -> dict[str, Any]: + """Convert one canonical rollout split into a LeRobot dataset directory. +@@ -195,13 +247,11 @@ def _convert_split( + output_dir: Destination LeRobot split directory. + env_name: Canonical benchmark environment name. + action_labels: Canonical action labels in vector order. +- fps: Frame rate used for timestamps. ++ fps: Observation frame rate used for timestamps. + reward_field: Source canonical reward column. +- obs_stride: Raw frames per observation decision (``round(env_fps/obs_fps)``). +- Canonical rows are recorded once per raw frame; keeping only the obs +- decisions (``decision_step % obs_stride == 0``) makes adjacent LeRobot +- rows adjacent observations, so KV-memory rollouts unroll at the eval +- observation cadence. ++ action_carrier: Target action/state carrier. ++ active_action_dim: Number of active environment action dimensions. ++ state_dim: Target state carrier dimension. + density_weighting: When True, write per-row ``density_weight`` from clean_v1's + event balancing (train split). When False, weights are uniform 1.0 (val + split keeps an unweighted held-out loss). +@@ -214,7 +264,6 @@ def _convert_split( + task_prompts: list[str] = [] + episode_lengths: list[int] = [] + for new_episode_idx, episode_rows in enumerate(_episode_groups(rows)): +- episode_rows = [row for row in episode_rows if int(row["decision_step"]) % obs_stride == 0] + density_weights = ( + density_weights_clean_v1(env_name, episode_rows) + if density_weighting +@@ -231,8 +280,14 @@ def _convert_split( + out_rows.append( + { + "image_bytes": _png_bytes(row["image"]), +- "action": _row_action_vector(row, action_dim=len(action_labels)), +- "timestamp": float(frame_idx) / int(fps), ++ "action": _bridge_action_vector( ++ row, ++ env_name=env_name, ++ active_action_dim=active_action_dim, ++ ) ++ if action_carrier == "bridge" ++ else _row_action_vector(row, action_dim=len(action_labels)), ++ "timestamp": float(frame_idx) / fps, + "episode_index": new_episode_idx, + "frame_index": frame_idx, + "task_index": prompt_to_task_index[prompt], +@@ -248,11 +303,13 @@ def _convert_split( + output_dir / f"data/chunk-{episode_chunk:03d}/episode_{new_episode_idx:06d}.parquet", + out_rows, + action_dim=len(action_labels), ++ state_dim=state_dim, + ) + _write_metadata( + output_dir, + fps=fps, + action_labels=action_labels, ++ state_dim=state_dim, + episode_lengths=episode_lengths, + task_prompts=task_prompts, + ) +@@ -269,6 +326,7 @@ def convert_canonical_rollout_to_lerobot( + raw_export_dir: Path | str, + output_dir: Path | str, + *, ++ action_carrier: str = "native", + force: bool = False, + ) -> dict[str, Any]: + """Convert a canonical rollout export into train/val LeRobot datasets. +@@ -276,6 +334,7 @@ def convert_canonical_rollout_to_lerobot( + Args: + raw_export_dir: Directory with canonical rollout parquet files and metadata. + output_dir: Destination LeRobot train dataset directory. ++ action_carrier: Target action/state carrier, ``native`` or ``bridge``. + force: Remove existing train/val output directories before writing. + + Returns: +@@ -286,11 +345,20 @@ def convert_canonical_rollout_to_lerobot( + metadata = json.loads((raw_export_dir / "metadata.json").read_text(encoding="utf-8")) + env_name = str(metadata["env_name"]) + action_spec = action_spec_for_env(env_name) +- action_labels = list(metadata["action_labels"]) ++ source_action_labels = list(metadata["action_labels"]) ++ action_labels = _target_action_labels( ++ env_name=env_name, ++ source_action_labels=source_action_labels, ++ action_carrier=action_carrier, ++ ) ++ active_action_dim = { ++ "flappy": 2, ++ "demon_attack": 6, ++ "deadly_corridor": 7, ++ }[env_name] ++ state_dim = {"native": STATE_DIM, "bridge": BRIDGE_DIM}[action_carrier] + reward_field = str(metadata["reward_field"]) +- obs_stride = int(metadata.get("obs_stride_raw_frames", 1)) +- # Rows survive at the observation cadence, so timestamps advance at obs_fps. +- fps = max(1, int(FPS_BY_ENV[env_name]) // obs_stride) ++ fps = metadata["obs_fps"] + val_output_dir = output_dir.with_name(f"{output_dir.name}__val") + if output_dir.exists() and force: + shutil.rmtree(output_dir) +@@ -303,7 +371,9 @@ def convert_canonical_rollout_to_lerobot( + action_labels=action_labels, + fps=fps, + reward_field=reward_field, +- obs_stride=obs_stride, ++ action_carrier=action_carrier, ++ active_action_dim=active_action_dim, ++ state_dim=state_dim, + density_weighting=True, + ) + val_manifest = _convert_split( +@@ -313,7 +383,9 @@ def convert_canonical_rollout_to_lerobot( + action_labels=action_labels, + fps=fps, + reward_field=reward_field, +- obs_stride=obs_stride, ++ action_carrier=action_carrier, ++ active_action_dim=active_action_dim, ++ state_dim=state_dim, + density_weighting=False, + ) + manifest = { +@@ -321,9 +393,13 @@ def convert_canonical_rollout_to_lerobot( + "format": "starvla_lerobot_v2_image_parquet", + "source": str(raw_export_dir), + "action_layout": str(metadata["action_layout"]), ++ "action_carrier": action_carrier, + "action_labels": action_labels, + "action_dim": len(action_labels), +- "active_action_dim": len(action_spec.labels), ++ "active_action_dim": active_action_dim ++ if action_carrier == "bridge" ++ else len(action_spec.labels), ++ "state_dim": state_dim, + "validation_dataset_name": val_output_dir.name, + "validation_episodes": val_manifest["episodes"], + "validation_frames": val_manifest["frames"], +diff --git a/latency_bench/data/hf_parquet.py b/latency_bench/data/hf_parquet.py +index 7a26426..6163c0d 100644 +--- a/latency_bench/data/hf_parquet.py ++++ b/latency_bench/data/hf_parquet.py +@@ -205,7 +205,9 @@ def completed_episode_indices_from_shards(output_dir: Path) -> set[int]: + with shard_path.open("r", encoding="utf-8") as handle: + for line in handle: + if line.strip(): +- completed_episode_indices.add(int(json.loads(line)["episode_idx"])) ++ row = json.loads(line) ++ row["trajectory_idx"] ++ completed_episode_indices.add(int(row["episode_idx"])) + break + return completed_episode_indices + +diff --git a/latency_bench/data/rollout_schema.py b/latency_bench/data/rollout_schema.py +index 11426b9..21d2bf5 100644 +--- a/latency_bench/data/rollout_schema.py ++++ b/latency_bench/data/rollout_schema.py +@@ -7,11 +7,12 @@ from datasets import Features, Image as HFImage, Sequence as HFSequence, Value + from latency_bench.data.action_layouts import ActionSpec + + +-SCHEMA_VERSION = 2 ++SCHEMA_VERSION = 3 + CANONICAL_ROW_FIELDS = ( + "image", + "env_name", + "episode_idx", ++ "trajectory_idx", + "decision_step", + "split", + "seed", +@@ -26,6 +27,7 @@ def _rollout_feature_map(action_spec: ActionSpec) -> dict[str, Any]: + "image": HFImage(), + "env_name": Value("string"), + "episode_idx": Value("int64"), ++ "trajectory_idx": Value("int64"), + "decision_step": Value("int64"), + "split": Value("string"), + "seed": Value("int64"), +diff --git a/latency_bench/data/sf_teacher_rollout.py b/latency_bench/data/sf_teacher_rollout.py +index af2b64f..bbbd157 100644 +--- a/latency_bench/data/sf_teacher_rollout.py ++++ b/latency_bench/data/sf_teacher_rollout.py +@@ -355,6 +355,7 @@ def _write_filtered_episode_images( + image_writer: RolloutImageWriter, + rows: list[dict[str, Any]], + frames_by_decision_step: Mapping[int, np.ndarray], ++ trajectory_by_decision_step: Mapping[int, int], + *, + context_window: int, + ) -> list[dict[str, Any]]: +@@ -364,6 +365,7 @@ def _write_filtered_episode_images( + image_writer: Image writer shared by the rollout run. + rows: Final rows selected for materialization. + frames_by_decision_step: Captured frames keyed by decision step. ++ trajectory_by_decision_step: Trajectory index keyed by decision step. + context_window: Total image window length including the current ``image`` field. + + Returns: +@@ -371,10 +373,15 @@ def _write_filtered_episode_images( + """ + if not rows: + return [] +- available_decision_steps = sorted(frames_by_decision_step) + required_steps: set[int] = set() + for row in rows: + decision_step = int(row["decision_step"]) ++ trajectory_idx = int(row["trajectory_idx"]) ++ available_decision_steps = sorted( ++ step ++ for step, step_trajectory_idx in trajectory_by_decision_step.items() ++ if step_trajectory_idx == trajectory_idx ++ ) + required_steps.add(decision_step) + if int(context_window) > 1: + required_steps.update( +@@ -396,6 +403,12 @@ def _write_filtered_episode_images( + for row in rows: + written = dict(row) + decision_step = int(written["decision_step"]) ++ trajectory_idx = int(written["trajectory_idx"]) ++ available_decision_steps = sorted( ++ step ++ for step, step_trajectory_idx in trajectory_by_decision_step.items() ++ if step_trajectory_idx == trajectory_idx ++ ) + written["image"] = written_paths_by_step[decision_step] + if int(context_window) > 1: + written["context_images"] = [ +@@ -804,6 +817,7 @@ def _replay_accepted_specs( + active_episode_rows: list[list[dict[str, Any]]] = [[] for _ in range(driver.slot_count)] + active_episode_frames: list[list[np.ndarray]] = [[] for _ in range(driver.slot_count)] + active_decision_steps = [0 for _ in range(driver.slot_count)] ++ active_trajectory_indices = [0 for _ in range(driver.slot_count)] + active_ghost_streams: list[Any | None] = [None for _ in range(driver.slot_count)] + rnn_states = torch.zeros([driver.slot_count, rnn_size], dtype=torch.float32, device=device) + image_writer = RolloutImageWriter( +@@ -844,6 +858,7 @@ def _replay_accepted_specs( + active_episode_rows[slot] = [] + active_episode_frames[slot] = [] + active_decision_steps[slot] = 0 ++ active_trajectory_indices[slot] = 0 + rnn_states[slot].zero_() + + with tqdm(total=len(specs_to_replay), initial=0, unit="episode") as progress: +@@ -881,21 +896,21 @@ def _replay_accepted_specs( + next_decision_step=next_decision_step, + max_steps_per_episode=int(max_steps_per_episode), + ) +- if not life_loss_boundary: +- active_episode_frames[slot].append(np.array(image_frame, copy=True)) +- row = teacher_dataset_row( +- env_name=env_name, +- spec=spec, +- decision_step=decision_step, +- image=str(image_path), +- raw_action=raw_actions[batch_idx], +- info=step_result.info, +- reward=step_result.reward, +- env_fps=env_fps, +- obs_fps=obs_fps, +- image_transform=image_transform_config.normalized_transform(), +- ) +- active_episode_rows[slot].append(row) ++ active_episode_frames[slot].append(np.array(image_frame, copy=True)) ++ row = teacher_dataset_row( ++ env_name=env_name, ++ spec=spec, ++ trajectory_idx=active_trajectory_indices[slot], ++ decision_step=decision_step, ++ image=str(image_path), ++ raw_action=raw_actions[batch_idx], ++ info=step_result.info, ++ reward=step_result.reward, ++ env_fps=env_fps, ++ obs_fps=obs_fps, ++ image_transform=image_transform_config.normalized_transform(), ++ ) ++ active_episode_rows[slot].append(row) + rnn_states[slot] = new_rnn_states[batch_idx] + if episode_done: + final_rows = _finalize_attempt_rows( +@@ -931,6 +946,10 @@ def _replay_accepted_specs( + image_writer, + shard_rows, + frames_by_decision_step, ++ { ++ int(row["decision_step"]): int(row["trajectory_idx"]) ++ for row in final_rows ++ }, + context_window=int(context_window), + ) + write_episode_row_shard(output_dir, shard_rows) +@@ -943,12 +962,14 @@ def _replay_accepted_specs( + active_episode_rows[slot] = [] + active_episode_frames[slot] = [] + active_decision_steps[slot] = 0 ++ active_trajectory_indices[slot] = 0 + if _is_demon_ghost_trail: + active_ghost_streams[slot] = None + rnn_states[slot].zero_() + else: + if life_loss_boundary: + active_obs[slot], reset_info = driver.continue_after_life_loss(slot) ++ active_trajectory_indices[slot] += 1 + if _is_demon_ghost_trail: + active_ghost_streams[slot].clear() + active_image_frames[slot] = frame_from_env_raw_rgb_info(reset_info).copy() +@@ -981,6 +1002,7 @@ def _replay_accepted_specs( + active_episode_rows[slot] = [] + active_episode_frames[slot] = [] + active_decision_steps[slot] = 0 ++ active_trajectory_indices[slot] = 0 + rnn_states[slot].zero_() + else: + if isinstance(driver, BatchedTeacherRolloutDriver): +diff --git a/latency_bench/data/sf_teacher_rows.py b/latency_bench/data/sf_teacher_rows.py +index efa6f3e..4e7ce9a 100644 +--- a/latency_bench/data/sf_teacher_rows.py ++++ b/latency_bench/data/sf_teacher_rows.py +@@ -14,6 +14,7 @@ def teacher_dataset_row( + *, + env_name: str, + spec: Mapping[str, Any], ++ trajectory_idx: int, + decision_step: int, + image: str, + raw_action: Any, +@@ -28,6 +29,7 @@ def teacher_dataset_row( + Args: + env_name: Canonical benchmark environment name. + spec: Episode spec containing index, split, and seed. ++ trajectory_idx: Zero-based trajectory index within the full-game episode. + decision_step: Zero-based policy decision step within the episode. + image: Path to the saved pre-step image. + raw_action: Raw teacher action for this decision. +@@ -48,6 +50,7 @@ def teacher_dataset_row( + "image": image, + "env_name": str(env_name), + "episode_idx": int(spec["episode_idx"]), ++ "trajectory_idx": int(trajectory_idx), + "decision_step": int(decision_step), + "split": str(spec["split"]), + "seed": int(spec["seed"]), +diff --git a/scripts/experiment_runner/run_manifest_jobs.py b/scripts/experiment_runner/run_manifest_jobs.py +index e2d1b5e..3ba106a 100644 +--- a/scripts/experiment_runner/run_manifest_jobs.py ++++ b/scripts/experiment_runner/run_manifest_jobs.py +@@ -73,11 +73,6 @@ def _event_writer(event_log: Path) -> Callable[[dict[str, Any]], None]: + return write + + +-def _register_process(process: subprocess.Popen) -> None: +- with _ACTIVE_PROCESSES_LOCK: +- _ACTIVE_PROCESSES.add(process) +- +- + def _forget_process(process: subprocess.Popen) -> None: + with _ACTIVE_PROCESSES_LOCK: + _ACTIVE_PROCESSES.discard(process) +@@ -89,11 +84,10 @@ def _active_processes() -> list[subprocess.Popen]: + + + def _signal_process_group(process: subprocess.Popen, sig: int) -> None: +- if process.poll() is None: +- try: +- os.killpg(process.pid, sig) +- except ProcessLookupError: +- pass ++ try: ++ os.killpg(process.pid, sig) ++ except ProcessLookupError: ++ pass + + + def _terminate_active_processes(sig: int = signal.SIGTERM) -> None: +@@ -118,15 +112,24 @@ def _terminate_active_processes(sig: int = signal.SIGTERM) -> None: + pass + + +-def _run_command(command: str, *, gpu: str) -> None: ++def _run_command( ++ command: str, ++ *, ++ gpu: str, ++ cancel_event: threading.Event | None = None, ++) -> bool: + env = os.environ.copy() + env["CUDA_VISIBLE_DEVICES"] = str(gpu) +- process = subprocess.Popen(command, shell=True, env=env, start_new_session=True) +- _register_process(process) ++ with _ACTIVE_PROCESSES_LOCK: ++ if cancel_event is not None and cancel_event.is_set(): ++ return False ++ process = subprocess.Popen(command, shell=True, env=env, start_new_session=True) ++ _ACTIVE_PROCESSES.add(process) + try: + returncode = process.wait() + if returncode != 0: + raise subprocess.CalledProcessError(returncode, command) ++ return True + finally: + _forget_process(process) + +@@ -201,9 +204,9 @@ def _resume_stage(job: dict[str, str], states: dict[str, str]) -> str: + stage = states.get(str(job["job_id"]), "") + if stage in {"job_complete", "upload_skipped", "upload_succeeded"}: + return "complete" +- if stage in {"eval_succeeded", "upload_failed"}: ++ if stage in {"eval_succeeded", "upload_started", "upload_failed"}: + return "upload" +- if stage == "train_succeeded": ++ if stage in {"train_succeeded", "eval_started"}: + return "eval" + if stage == "eval_failed": + # Training already succeeded before eval ran; re-eval from the checkpoint +@@ -223,16 +226,6 @@ def run_jobs( + dry_run: bool = False, + uploader: Callable[[dict[str, str]], None] | None = None, + ) -> int: +- previous_sigint = signal.getsignal(signal.SIGINT) +- previous_sigterm = signal.getsignal(signal.SIGTERM) +- +- def stop_active_processes(signum, frame): +- del frame +- _terminate_active_processes(signal.SIGTERM) +- raise KeyboardInterrupt(signum) +- +- signal.signal(signal.SIGINT, stop_active_processes) +- signal.signal(signal.SIGTERM, stop_active_processes) + manifest_file = Path(manifest_path).expanduser().resolve() + event_log = event_log_path_for_manifest(manifest_file) + write_event = _event_writer(event_log) +@@ -253,12 +246,16 @@ def run_jobs( + jobs = [ + row + for row in rows +- if states.get(row["job_id"], "") in {"eval_succeeded", "upload_failed"} ++ if states.get(row["job_id"], "") ++ in {"eval_succeeded", "upload_started", "upload_failed"} + ] + job_queue: queue.Queue[dict[str, str] | None] = queue.Queue() + upload_queue: queue.Queue[UploadTask | None] = queue.Queue() + failures: list[tuple[str, str]] = [] + failure_lock = threading.Lock() ++ cancel_event = threading.Event() ++ signal_event = threading.Event() ++ cleanup_started = False + uploader_fn = _default_uploader if uploader is None else uploader + + if stage != "upload": +@@ -280,28 +277,49 @@ def run_jobs( + if job is None: + job_queue.task_done() + break ++ if cancel_event.is_set(): ++ job_queue.task_done() ++ continue + next_stage = _resume_stage(job, states) if stage == "all" else stage + job_id = str(job["job_id"]) + try: + if next_stage == "train": ++ if cancel_event.is_set(): ++ continue + if dry_run: + print(f"[dry-run] CUDA_VISIBLE_DEVICES={gpu} {job['train_command']}", flush=True) + else: + write_event({"job_id": job_id, "stage": "train_started", "gpu": gpu, "ts": _now()}) +- _run_command(str(job["train_command"]), gpu=gpu) ++ started = _run_command( ++ str(job["train_command"]), ++ gpu=gpu, ++ cancel_event=cancel_event, ++ ) ++ if not started or cancel_event.is_set(): ++ continue + write_event({"job_id": job_id, "stage": "train_succeeded", "gpu": gpu, "ts": _now()}) + next_stage = "eval" if stage == "all" else "complete" + if next_stage == "eval": ++ if cancel_event.is_set(): ++ continue + if dry_run: + print(f"[dry-run] CUDA_VISIBLE_DEVICES={gpu} {job['eval_command']}", flush=True) + else: + write_event({"job_id": job_id, "stage": "eval_started", "gpu": gpu, "ts": _now()}) +- _run_command(str(job["eval_command"]), gpu=gpu) ++ started = _run_command( ++ str(job["eval_command"]), ++ gpu=gpu, ++ cancel_event=cancel_event, ++ ) ++ if not started or cancel_event.is_set(): ++ continue + write_event({"job_id": job_id, "stage": "eval_succeeded", "gpu": gpu, "ts": _now()}) + next_stage = "upload" if stage == "all" else "complete" +- if next_stage == "upload": ++ if next_stage == "upload" and not cancel_event.is_set(): + upload_queue.put(UploadTask(job)) + except subprocess.CalledProcessError: ++ if cancel_event.is_set(): ++ continue + failed_stage = "train_failed" if next_stage == "train" else "eval_failed" + write_event({"job_id": job_id, "stage": failed_stage, "gpu": gpu, "ts": _now()}) + record_failure(job_id, failed_stage) +@@ -311,48 +329,52 @@ def run_jobs( + def upload_worker() -> None: + while True: + task = upload_queue.get() +- if task is None: +- upload_queue.task_done() +- break +- job = task.job +- job_id = str(job["job_id"]) +- train_repo_id = str(job["train_upload_repo_id"]) +- eval_repo_id = str(job["eval_upload_repo_id"]) +- if dry_run: +- targets = [repo_id for repo_id in (eval_repo_id, train_repo_id) if repo_id] +- print(f"[dry-run] upload {job_id}: {', '.join(targets) or 'no upload target'}", flush=True) +- upload_queue.task_done() +- continue +- if not train_repo_id and not eval_repo_id: +- write_event({"job_id": job_id, "stage": "upload_skipped", "ts": _now()}) +- write_event({"job_id": job_id, "stage": "job_complete", "ts": _now()}) +- upload_queue.task_done() +- continue +- attempt = 0 +- success = False +- while attempt < max_upload_attempts and not success: +- attempt += 1 +- write_event({"job_id": job_id, "stage": "upload_started", "attempt": attempt, "ts": _now()}) +- try: +- if not dry_run: +- uploader_fn(job) +- write_event({"job_id": job_id, "stage": "upload_succeeded", "attempt": attempt, "ts": _now()}) ++ try: ++ if task is None: ++ break ++ if cancel_event.is_set(): ++ continue ++ job = task.job ++ job_id = str(job["job_id"]) ++ train_repo_id = str(job["train_upload_repo_id"]) ++ eval_repo_id = str(job["eval_upload_repo_id"]) ++ if dry_run: ++ targets = [repo_id for repo_id in (eval_repo_id, train_repo_id) if repo_id] ++ print(f"[dry-run] upload {job_id}: {', '.join(targets) or 'no upload target'}", flush=True) ++ continue ++ if not train_repo_id and not eval_repo_id: ++ write_event({"job_id": job_id, "stage": "upload_skipped", "ts": _now()}) + write_event({"job_id": job_id, "stage": "job_complete", "ts": _now()}) +- success = True +- except Exception as error: +- write_event( +- { +- "job_id": job_id, +- "stage": "upload_failed", +- "attempt": attempt, +- "error": repr(error), +- "ts": _now(), +- } +- ) +- print(f"upload failed for {job_id} (attempt {attempt}): {error!r}", file=sys.stderr) +- if not success: +- record_failure(job_id, "upload_failed") +- upload_queue.task_done() ++ continue ++ attempt = 0 ++ success = False ++ while attempt < max_upload_attempts and not success and not cancel_event.is_set(): ++ attempt += 1 ++ write_event({"job_id": job_id, "stage": "upload_started", "attempt": attempt, "ts": _now()}) ++ try: ++ uploader_fn(job) ++ if cancel_event.is_set(): ++ continue ++ write_event({"job_id": job_id, "stage": "upload_succeeded", "attempt": attempt, "ts": _now()}) ++ write_event({"job_id": job_id, "stage": "job_complete", "ts": _now()}) ++ success = True ++ except Exception as error: ++ if cancel_event.is_set(): ++ continue ++ write_event( ++ { ++ "job_id": job_id, ++ "stage": "upload_failed", ++ "attempt": attempt, ++ "error": repr(error), ++ "ts": _now(), ++ } ++ ) ++ print(f"upload failed for {job_id} (attempt {attempt}): {error!r}", file=sys.stderr) ++ if not success and not cancel_event.is_set(): ++ record_failure(job_id, "upload_failed") ++ finally: ++ upload_queue.task_done() + + upload_threads = [ + threading.Thread(target=upload_worker, name=f"upload-{idx}", daemon=True) +@@ -362,17 +384,44 @@ def run_jobs( + threading.Thread(target=train_worker, args=(gpu,), name=f"train-{gpu}", daemon=True) + for gpu in gpus if stage != "upload" + ] ++ previous_sigint = signal.getsignal(signal.SIGINT) ++ previous_sigterm = signal.getsignal(signal.SIGTERM) ++ ++ def stop_active_processes(signum, frame): ++ nonlocal cleanup_started ++ del frame ++ if signal_event.is_set(): ++ return ++ signal_event.set() ++ cancel_event.set() ++ if cleanup_started: ++ return ++ raise KeyboardInterrupt(signum) ++ ++ signal.signal(signal.SIGINT, stop_active_processes) ++ signal.signal(signal.SIGTERM, stop_active_processes) + try: + for thread in upload_threads + train_threads: + thread.start() + job_queue.join() +- for _ in upload_threads: +- upload_queue.put(None) + upload_queue.join() +- for thread in train_threads + upload_threads: +- thread.join() + return 1 if failures else 0 + finally: ++ cleanup_started = True ++ cancel_event.set() ++ _terminate_active_processes(signal.SIGTERM) ++ for thread in train_threads: ++ thread.join() ++ _terminate_active_processes(signal.SIGTERM) ++ if signal_event.is_set(): ++ for _ in upload_threads: ++ upload_queue.put(None) ++ else: ++ upload_queue.join() ++ for _ in upload_threads: ++ upload_queue.put(None) ++ for thread in upload_threads: ++ thread.join() + _terminate_active_processes(signal.SIGTERM) + signal.signal(signal.SIGINT, previous_sigint) + signal.signal(signal.SIGTERM, previous_sigterm) +diff --git a/scripts/rollout_data/prepare_starvla_lerobot_dataset.py b/scripts/rollout_data/prepare_starvla_lerobot_dataset.py +index e202657..2521899 100644 +--- a/scripts/rollout_data/prepare_starvla_lerobot_dataset.py ++++ b/scripts/rollout_data/prepare_starvla_lerobot_dataset.py +@@ -26,6 +26,7 @@ def convert_raw_export_to_lerobot( + raw_export_dir: Path, + lerobot_root: Path, + data_mix: str, ++ action_carrier: str = "native", + ) -> dict: + """Convert a raw rollout export into a named LeRobot data mix. + +@@ -33,6 +34,7 @@ def convert_raw_export_to_lerobot( + raw_export_dir: Canonical rollout export directory. + lerobot_root: Directory that will contain the LeRobot datasets. + data_mix: Train dataset directory name under ``lerobot_root``. ++ action_carrier: Target action/state carrier. + + Returns: + Conversion manifest returned by the LeRobot adapter. +@@ -41,6 +43,7 @@ def convert_raw_export_to_lerobot( + return convert_canonical_rollout_to_lerobot( + raw_export_dir, + output_dir, ++ action_carrier=action_carrier, + force=True, + ) + +@@ -92,6 +95,7 @@ def build_parser() -> argparse.ArgumentParser: + parser.add_argument("raw_export_dir") + parser.add_argument("lerobot_root") + parser.add_argument("data_mix") ++ parser.add_argument("--action-carrier", choices=("native", "bridge"), default="native") + parser.add_argument("--push-to-hub", default="") + parser.add_argument("--private", action="store_true") + return parser +@@ -115,6 +119,7 @@ def main(argv: Sequence[str] | None = None) -> int: + raw_export_dir=raw_export_dir, + lerobot_root=lerobot_root, + data_mix=data_mix, ++ action_carrier=args.action_carrier, + ) + if args.push_to_hub: + push_lerobot_dataset( +diff --git a/scripts/sweeps/generate_sweep_configs.py b/scripts/sweeps/generate_sweep_configs.py +index 8074c79..bd5fafe 100644 +--- a/scripts/sweeps/generate_sweep_configs.py ++++ b/scripts/sweeps/generate_sweep_configs.py +@@ -116,6 +116,7 @@ ENV_KEYS_BY_NAME = { + "obs_fps", + "screen_size", + "noop_max", ++ "reset_mode", + "frame_stack", + "terminal_on_life_loss", + "clip_reward", +diff --git a/tests/data/test_rollout_dataset_schema.py b/tests/data/test_rollout_dataset_schema.py +index 06a6091..55ccebf 100644 +--- a/tests/data/test_rollout_dataset_schema.py ++++ b/tests/data/test_rollout_dataset_schema.py +@@ -8,6 +8,7 @@ def test_canonical_rollout_fields_exclude_legacy_aliases(): + "image", + "env_name", + "episode_idx", ++ "trajectory_idx", + "decision_step", + "split", + "seed", +@@ -36,6 +37,7 @@ def test_rollout_features_include_env_specific_action_fields(): + assert "action_tuple" not in deadly_features + assert "action" not in deadly_features + for features in (flappy_features, deadly_features): ++ assert "trajectory_idx" in features + assert "decision_step" in features + assert "latency_raw_frames" in features + assert "raw_reward" in features +diff --git a/tests/data/test_rollout_hf_parquet.py b/tests/data/test_rollout_hf_parquet.py +index 9fa4c48..4e56de6 100644 +--- a/tests/data/test_rollout_hf_parquet.py ++++ b/tests/data/test_rollout_hf_parquet.py +@@ -15,6 +15,7 @@ def test_hf_parquet_writes_canonical_columns_only(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -56,6 +57,7 @@ def test_hf_parquet_shards_sort_by_decision_step(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": decision_step, + "split": "train", + "seed": 11, +@@ -92,6 +94,7 @@ def test_hf_parquet_embeds_context_images_when_rows_provide_them(tmp_path): + "context_images": [str(path) for path in context_paths], + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -116,3 +119,18 @@ def test_hf_parquet_embeds_context_images_when_rows_provide_them(tmp_path): + assert "context_images" in table.column_names + assert len(exported["context_images"]) == 3 + assert exported["context_images"][0]["bytes"].startswith(b"\x89PNG\r\n\x1a\n") ++ ++ ++def test_completed_episode_shards_require_trajectory_identity(tmp_path): ++ import json ++ ++ import pytest ++ ++ from latency_bench.data.hf_parquet import completed_episode_indices_from_shards ++ ++ shard_path = tmp_path / "episode_rows" / "train" / "episode_000000.jsonl" ++ shard_path.parent.mkdir(parents=True) ++ shard_path.write_text(json.dumps({"episode_idx": 0}) + "\n", encoding="utf-8") ++ ++ with pytest.raises(KeyError, match="trajectory_idx"): ++ completed_episode_indices_from_shards(tmp_path) +diff --git a/tests/data/test_sf_teacher_dataset_export.py b/tests/data/test_sf_teacher_dataset_export.py +index 62b30a6..ba4644b 100644 +--- a/tests/data/test_sf_teacher_dataset_export.py ++++ b/tests/data/test_sf_teacher_dataset_export.py +@@ -1299,7 +1299,7 @@ def test_write_filtered_episode_images_preserves_empty_filtered_episode(tmp_path + + image_writer = RolloutImageWriter(max_workers=0, row_buffer_size=1, export_image_size=None) + +- rows = _write_filtered_episode_images(image_writer, [], {}, context_window=5) ++ rows = _write_filtered_episode_images(image_writer, [], {}, {}, context_window=5) + + assert rows == [] + +@@ -1314,6 +1314,7 @@ def test_write_filtered_episode_images_resets_context_after_decision_step_gap(tm + { + "image": str(tmp_path / "images" / "train" / "episode_000000" / f"decision_step_{step:06d}.png"), + "decision_step": step, ++ "trajectory_idx": 0, + } + for step in [0, 1, 4, 5] + ] +@@ -1326,6 +1327,7 @@ def test_write_filtered_episode_images_resets_context_after_decision_step_gap(tm + image_writer, + rows, + frames_by_decision_step, ++ {step: 0 for step in frames_by_decision_step}, + context_window=4, + ) + +@@ -1733,13 +1735,24 @@ def test_collect_teacher_dataset_demon_attack_exports_full_game_across_life_loss + image_writer_workers=0, + row_buffer_size=1, + filter_preset="none", ++ context_window=3, + ) + train_rows = _read_shard_rows(output_dir, "train") + state = json.loads((output_dir / "probe_state.json").read_text(encoding="utf-8")) + + assert ScriptedDemonEnv.reset_seeds == [100, None, None, 100, None, None] +- assert [row["decision_step"] for row in train_rows] == [2] +- assert train_rows[0]["raw_reward"] == 30.0 ++ assert [row["decision_step"] for row in train_rows] == [0, 1, 2] ++ assert [row["trajectory_idx"] for row in train_rows] == [0, 1, 2] ++ assert [row["action_id"] for row in train_rows] == [1, 1, 1] ++ assert [row["raw_reward"] for row in train_rows] == [10.0, 20.0, 30.0] ++ from PIL import Image ++ ++ context_values = [ ++ [np.asarray(Image.open(path))[0, 0, 0].item() for path in row["context_images"]] ++ for row in train_rows ++ ] ++ current_values = [np.asarray(Image.open(row["image"]))[0, 0, 0].item() for row in train_rows] ++ assert context_values == [[value, value] for value in current_values] + assert state["accepted_specs"] == [ + { + "attempt_idx": 0, +@@ -1900,6 +1913,7 @@ def test_collect_teacher_dataset_skips_runtime_when_probe_and_shards_complete(mo + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 100, +@@ -2264,6 +2278,7 @@ def test_write_parquet_splits_handles_empty_validation_rows(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -2300,6 +2315,7 @@ def test_write_parquet_splits_embeds_image_bytes(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -2336,6 +2352,7 @@ def test_write_parquet_splits_preserves_rows_across_large_exports(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": episode_idx, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11 + episode_idx, +@@ -2390,6 +2407,7 @@ def test_write_parquet_splits_from_shards_writes_train_and_val_rows(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": episode_idx, ++ "trajectory_idx": 0, + "decision_step": decision_step, + "split": split, + "seed": 11 + episode_idx, +@@ -2432,6 +2450,7 @@ def test_write_parquet_splits_from_shards_replaces_stale_partial_file(tmp_path): + "image": str(stale_image_path), + "env_name": "flappy", + "episode_idx": 99, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 99, +@@ -2452,6 +2471,7 @@ def test_write_parquet_splits_from_shards_replaces_stale_partial_file(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -2536,6 +2556,8 @@ def test_prepare_starvla_lerobot_dataset_converts_from_raw_export(monkeypatch, t + str(raw_export), + str(tmp_path / "lerobot"), + "demon_attack_train", ++ "--action-carrier", ++ "bridge", + ]) + + assert result == 0 +@@ -2543,7 +2565,7 @@ def test_prepare_starvla_lerobot_dataset_converts_from_raw_export(monkeypatch, t + ( + raw_export, + tmp_path / "lerobot" / "demon_attack_train", +- {"force": True}, ++ {"action_carrier": "bridge", "force": True}, + ) + ] + +diff --git a/tests/data/test_starvla_lerobot_exporter.py b/tests/data/test_starvla_lerobot_exporter.py +index 64b5f47..58391c7 100644 +--- a/tests/data/test_starvla_lerobot_exporter.py ++++ b/tests/data/test_starvla_lerobot_exporter.py +@@ -3,6 +3,7 @@ from __future__ import annotations + import json + + import pyarrow.parquet as pq ++import pytest + + from helpers import save_test_image + +@@ -20,6 +21,7 @@ def test_starvla_lerobot_exporter_reads_canonical_rollout_schema(tmp_path): + "image": str(image_path), + "env_name": "deadly_corridor", + "episode_idx": 3, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 14, +@@ -38,6 +40,7 @@ def test_starvla_lerobot_exporter_reads_canonical_rollout_schema(tmp_path): + "action_layout": "deadly_corridor_joint_54", + "reward_field": "raw_reward", + "action_labels": list(action_spec.labels), ++ "obs_fps": 8.75, + } + ), + encoding="utf-8", +@@ -54,10 +57,102 @@ def test_starvla_lerobot_exporter_reads_canonical_rollout_schema(tmp_path): + assert table.to_pylist()[0]["done"] is True + + +-def test_starvla_lerobot_exporter_subsamples_to_obs_cadence(tmp_path): +- """Adjacent LeRobot rows must be adjacent obs decisions (every obs_stride raw +- frames), with contiguous frame_index, so KV-memory rollouts unroll at the eval +- observation cadence rather than at every raw frame.""" ++@pytest.mark.parametrize( ++ ("env_name", "obs_fps", "latency", "action_values", "expected_action", "active_action_dim"), ++ [ ++ ("flappy", 30, 3, (1, [0.0, 1.0], "FLAP"), [0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0], 2), ++ ( ++ "demon_attack", ++ 15, ++ 6, ++ (5, [0.0, 0.0, 0.0, 0.0, 0.0, 1.0], "LEFTFIRE"), ++ [0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0], ++ 6, ++ ), ++ ( ++ "deadly_corridor", ++ 8.75, ++ 6, ++ (11, None, "MOVE_FORWARD + MOVE_RIGHT + ATTACK"), ++ [1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 1.0], ++ 7, ++ ), ++ ], ++) ++def test_starvla_lerobot_exporter_writes_bridge_carrier_with_raw_latency_prompt( ++ tmp_path, ++ env_name, ++ obs_fps, ++ latency, ++ action_values, ++ expected_action, ++ active_action_dim, ++): ++ from latency_bench.data.action_layouts import action_spec_for_env ++ from latency_bench.data.exporters.starvla_lerobot import convert_canonical_rollout_to_lerobot ++ from latency_bench.data.hf_parquet import write_parquet_splits ++ ++ image_path = tmp_path / "image.png" ++ save_test_image(image_path, 9) ++ raw_export = tmp_path / "raw" ++ action_spec = action_spec_for_env(env_name) ++ action_id, action, action_text = action_values ++ row = { ++ "image": str(image_path), ++ "env_name": env_name, ++ "episode_idx": 0, ++ "trajectory_idx": 0, ++ "decision_step": 0, ++ "split": "train", ++ "seed": 0, ++ "prompt": f"The action latency is fixed at {latency} raw environment frames.", ++ "latency_raw_frames": latency, ++ "latency_ms": latency * 1000 / {"flappy": 30, "demon_attack": 60, "deadly_corridor": 35}[env_name], ++ "raw_reward": 1.0, ++ "action_id": action_id, ++ "action_text": action_text, ++ } ++ if action is not None: ++ row["action"] = action ++ write_parquet_splits(raw_export, [row], [], action_spec=action_spec) ++ (raw_export / "metadata.json").write_text( ++ json.dumps( ++ { ++ "env_name": env_name, ++ "action_layout": action_spec.layout, ++ "reward_field": action_spec.reward_field, ++ "action_labels": list(action_spec.labels), ++ "obs_fps": obs_fps, ++ } ++ ), ++ encoding="utf-8", ++ ) ++ ++ manifest = convert_canonical_rollout_to_lerobot( ++ raw_export, ++ tmp_path / "lerobot", ++ action_carrier="bridge", ++ force=True, ++ ) ++ ++ table = pq.read_table(tmp_path / "lerobot" / "data" / "chunk-000" / "episode_000000.parquet") ++ info = json.loads((tmp_path / "lerobot" / "meta" / "info.json").read_text(encoding="utf-8")) ++ task_lines = (tmp_path / "lerobot" / "meta" / "tasks.jsonl").read_text( ++ encoding="utf-8" ++ ).splitlines() ++ tasks = [json.loads(line) for line in task_lines] ++ converted_row = table.to_pylist()[0] ++ assert converted_row["action"] == expected_action ++ assert converted_row["observation.state"] == [0.0] * 7 ++ assert info["features"]["action"]["shape"] == [7] ++ assert info["features"]["observation.state"]["shape"] == [7] ++ assert tasks == [{"task_index": 0, "task": row["prompt"]}] ++ assert manifest["action_carrier"] == "bridge" ++ assert manifest["active_action_dim"] == active_action_dim ++ ++ ++def test_starvla_lerobot_exporter_keeps_every_observation_decision(tmp_path): ++ """Canonical rows already occur at the policy observation cadence.""" + from latency_bench.data.action_layouts import action_spec_for_env + from latency_bench.data.exporters.starvla_lerobot import convert_canonical_rollout_to_lerobot + from latency_bench.data.hf_parquet import write_parquet_splits +@@ -66,12 +161,13 @@ def test_starvla_lerobot_exporter_subsamples_to_obs_cadence(tmp_path): + save_test_image(image_path, 9) + raw_export = tmp_path / "raw" + action_spec = action_spec_for_env("deadly_corridor") +- # One episode, 8 contiguous per-raw-frame decision steps; obs_stride = 4. ++ # One trajectory with eight contiguous policy-decision observations. + train_rows = [ + { + "image": str(image_path), + "env_name": "deadly_corridor", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": step, + "split": "train", + "seed": 7, +@@ -92,6 +188,7 @@ def test_starvla_lerobot_exporter_subsamples_to_obs_cadence(tmp_path): + "action_layout": "deadly_corridor_joint_54", + "reward_field": "raw_reward", + "action_labels": list(action_spec.labels), ++ "obs_fps": 8.75, + "obs_stride_raw_frames": 4, + } + ), +@@ -102,12 +199,73 @@ def test_starvla_lerobot_exporter_subsamples_to_obs_cadence(tmp_path): + + table = pq.read_table(tmp_path / "lerobot" / "data" / "chunk-000" / "episode_000000.parquet") + rows = table.to_pylist() +- # Only decision_steps 0 and 4 survive; frame_index is contiguous obs index. +- assert [r["frame_index"] for r in rows] == [0, 1] +- assert [r["episode_index"] for r in rows] == [0, 0] ++ assert [r["frame_index"] for r in rows] == list(range(8)) ++ assert [r["episode_index"] for r in rows] == [0] * 8 + assert rows[-1]["done"] is True + + ++def test_starvla_lerobot_exporter_splits_life_trajectories(tmp_path): ++ from latency_bench.data.action_layouts import action_spec_for_env ++ from latency_bench.data.exporters.starvla_lerobot import convert_canonical_rollout_to_lerobot ++ from latency_bench.data.hf_parquet import write_parquet_splits ++ ++ image_path = tmp_path / "image.png" ++ save_test_image(image_path, 9) ++ raw_export = tmp_path / "raw" ++ action_spec = action_spec_for_env("demon_attack") ++ train_rows = [ ++ { ++ "image": str(image_path), ++ "env_name": "demon_attack", ++ "episode_idx": 0, ++ "trajectory_idx": trajectory_idx, ++ "decision_step": decision_step, ++ "split": "train", ++ "seed": 7, ++ "prompt": "pick action", ++ "latency_raw_frames": 6, ++ "latency_ms": 100.0, ++ "raw_reward": 1.0, ++ "action_id": 0, ++ "action": [1.0, 0.0, 0.0, 0.0, 0.0, 0.0], ++ "action_text": "NOOP", ++ } ++ for trajectory_idx, decision_step in ((0, 0), (0, 1), (1, 2), (1, 3)) ++ ] ++ write_parquet_splits(raw_export, train_rows, [], action_spec=action_spec) ++ (raw_export / "metadata.json").write_text( ++ json.dumps( ++ { ++ "env_name": "demon_attack", ++ "action_layout": action_spec.layout, ++ "reward_field": action_spec.reward_field, ++ "action_labels": list(action_spec.labels), ++ "obs_fps": 15, ++ } ++ ), ++ encoding="utf-8", ++ ) ++ ++ manifest = convert_canonical_rollout_to_lerobot( ++ raw_export, ++ tmp_path / "lerobot", ++ action_carrier="bridge", ++ force=True, ++ ) ++ ++ first = pq.read_table( ++ tmp_path / "lerobot" / "data" / "chunk-000" / "episode_000000.parquet" ++ ).to_pylist() ++ second = pq.read_table( ++ tmp_path / "lerobot" / "data" / "chunk-000" / "episode_000001.parquet" ++ ).to_pylist() ++ assert manifest["episodes"] == 2 ++ assert [row["frame_index"] for row in first] == [0, 1] ++ assert [row["frame_index"] for row in second] == [0, 1] ++ assert [row["done"] for row in first] == [False, True] ++ assert [row["done"] for row in second] == [False, True] ++ ++ + def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + from datasets import Dataset, Features, Image as HFImage, Sequence as HFSequence, Value + from latency_bench.data.exporters.starvla_lerobot import convert_canonical_rollout_to_lerobot +@@ -121,6 +279,7 @@ def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + "image": HFImage(), + "env_name": Value("string"), + "episode_idx": Value("int64"), ++ "trajectory_idx": Value("int64"), + "decision_step": Value("int64"), + "split": Value("string"), + "seed": Value("int64"), +@@ -138,6 +297,7 @@ def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + "image": [str(image_path)], + "env_name": ["flappy"], + "episode_idx": [0], ++ "trajectory_idx": [0], + "decision_step": [0], + "split": ["train"], + "seed": [11], +@@ -156,6 +316,7 @@ def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + "image": [str(image_path)], + "env_name": ["flappy"], + "episode_idx": [1], ++ "trajectory_idx": [0], + "decision_step": [0], + "split": ["val"], + "seed": [12], +@@ -176,6 +337,7 @@ def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + "action_layout": "flappy_discrete", + "reward_field": "raw_reward", + "action_labels": ["NOOP", "FLAP"], ++ "obs_fps": 30, + } + ), + encoding="utf-8", +diff --git a/tests/scripts/test_generate_sweep_configs.py b/tests/scripts/test_generate_sweep_configs.py +index 23d79cb..438b296 100644 +--- a/tests/scripts/test_generate_sweep_configs.py ++++ b/tests/scripts/test_generate_sweep_configs.py +@@ -23,6 +23,75 @@ def _read_manifest(path: Path) -> list[dict[str, str]]: + return [dict(zip(header, line.split("\t"))) for line in lines[1:]] + + ++@pytest.mark.parametrize( ++ ("env_name", "latency_label", "latency_frames", "obs_fps", "obs_fps_label"), ++ [ ++ ("flappy", "fixed_l3", 3, 30, "30"), ++ ("demon_attack", "fixed_l6", 6, 15, "15"), ++ ("deadly_corridor", "fixed_l6", 6, 8.75, "8p75"), ++ ], ++) ++def test_memory_rollout_teacher_spec_emits_single_uploadable_job( ++ tmp_path, ++ env_name, ++ latency_label, ++ latency_frames, ++ obs_fps, ++ obs_fps_label, ++): ++ generated_root = tmp_path / "configs" ++ output_root = tmp_path / "outputs" ++ train_dir = tmp_path / "checkpoints" ++ ++ generate_sweep_configs( ++ [ ++ "--spec", ++ f"configs/experiments/memory/rollout_teacher/{env_name}.yaml", ++ "--generated-root", ++ str(generated_root), ++ "--output-root", ++ str(output_root), ++ "--train-dir", ++ str(train_dir), ++ ] ++ ) ++ ++ rows = _read_manifest(generated_root / "manifest.tsv") ++ assert len(rows) == 1 ++ row = rows[0] ++ assert row["env"] == env_name ++ assert row["experiment_family"] == "memory_rollout_teacher" ++ assert row["sweep_name"] == "teacher" ++ assert row["seed"] == "0" ++ assert row["frame_stack"] == "4" ++ assert row["obs_fps"] == obs_fps_label ++ assert row["latency_label"] == latency_label ++ assert row["latency_kind"] == "fixed" ++ assert row["latency_fixed_frames"] == str(latency_frames) ++ assert row["train_upload_repo_id"] == "latency-sensitive-bench/paper-experiment-models" ++ assert row["train_upload_repo_type"] == "model" ++ assert row["eval_upload_repo_id"] == "" ++ assert row["train_artifact_repo_path"].startswith( ++ f"memory/rollout_teachers/{env_name}/train/" ++ ) ++ ++ train_cfg = yaml.safe_load(Path(row["train_config"]).read_text(encoding="utf-8")) ++ assert train_cfg["experiment"]["seed"] == 0 ++ assert train_cfg["env"]["frame_stack"] == 4 ++ assert train_cfg["env"]["obs_fps"] == pytest.approx(obs_fps) ++ if env_name == "demon_attack": ++ assert train_cfg["env"]["reset_mode"] == "fire" ++ assert train_cfg["latency"]["method"] == "fixed" ++ assert train_cfg["latency"]["fixed_latency_ms"] == pytest.approx( ++ latency_frames * 1000 / train_cfg["env"]["env_fps"] ++ ) ++ assert train_cfg["evaluation"]["eval_suites"] == { ++ "fixed": [[latency_frames]], ++ "normal": [], ++ "uniform": [], ++ } ++ ++ + def test_latency_bench_eval_config_disables_full_trace_records(tmp_path): + base_config = { + "backend": { +diff --git a/tests/scripts/test_manifest_jobs.py b/tests/scripts/test_manifest_jobs.py +index bd7bf03..74e4f73 100644 +--- a/tests/scripts/test_manifest_jobs.py ++++ b/tests/scripts/test_manifest_jobs.py +@@ -1,8 +1,10 @@ + from __future__ import annotations + ++import json + import os +-import subprocess ++import shlex + import signal ++import subprocess + import sys + import threading + import time +@@ -10,6 +12,7 @@ import types + from pathlib import Path + + import pytest ++from helpers import REPO_ROOT + + import scripts.experiment_runner.run_manifest_jobs as run_manifest_jobs + from scripts.experiment_runner.job_manifest import ( +@@ -68,6 +71,26 @@ def test_train_stage_only_trains_and_resumes_from_success(tmp_path): + assert [event["stage"] for event in events] == ["train_started", "train_succeeded"] + + ++@pytest.mark.parametrize( ++ ("recorded_stage", "expected_stage"), ++ [ ++ ("train_started", "train"), ++ ("train_succeeded", "eval"), ++ ("eval_started", "eval"), ++ ("eval_succeeded", "upload"), ++ ("upload_started", "upload"), ++ ], ++) ++def test_resume_stage_keeps_interrupted_job_at_its_current_pipeline_stage( ++ recorded_stage, ++ expected_stage, ++): ++ assert run_manifest_jobs._resume_stage( ++ {"job_id": "job1"}, ++ {"job1": recorded_stage}, ++ ) == expected_stage ++ ++ + def test_eval_stage_does_not_train_or_upload(tmp_path): + manifest_path, train_mark, eval_mark = _write_single_job(tmp_path) + uploads: list[str] = [] +@@ -134,6 +157,26 @@ def test_upload_stage_needs_no_gpu_and_retries_failed_upload(tmp_path): + ] + + ++def test_upload_stage_resumes_interrupted_upload(tmp_path): ++ manifest_path, _, _ = _write_single_job(tmp_path) ++ append_event( ++ event_log_path_for_manifest(manifest_path), ++ {"job_id": "job1", "stage": "upload_started", "ts": 1.0}, ++ ) ++ uploads: list[str] = [] ++ ++ assert run_jobs( ++ manifest_path=manifest_path, ++ gpus=[], ++ upload_workers=1, ++ max_upload_attempts=1, ++ stage="upload", ++ uploader=lambda job: uploads.append(job["job_id"]), ++ ) == 0 ++ ++ assert uploads == ["job1"] ++ ++ + def test_dry_run_does_not_execute_or_record_success(tmp_path, capsys): + manifest_path, train_mark, eval_mark = _write_single_job(tmp_path) + +@@ -310,6 +353,186 @@ def test_run_command_cleanup_terminates_child_process_group(tmp_path): + os.kill(child_pid, 0) + + ++def test_sigint_cancels_queue_and_kills_all_active_process_groups(tmp_path): ++ helper_path = tmp_path / "ignore_term_job.py" ++ helper_path.write_text( ++ """from __future__ import annotations ++ ++import json ++import os ++from pathlib import Path ++import signal ++import subprocess ++import sys ++import time ++ ++signal.signal(signal.SIGTERM, signal.SIG_IGN) ++child = subprocess.Popen( ++ [ ++ sys.executable, ++ "-c", ++ "import signal, time; signal.signal(signal.SIGTERM, signal.SIG_IGN); time.sleep(60)", ++ ] ++) ++Path(sys.argv[1]).write_text( ++ json.dumps( ++ { ++ "leader_pid": os.getpid(), ++ "leader_pgid": os.getpgid(0), ++ "child_pid": child.pid, ++ "child_pgid": os.getpgid(child.pid), ++ } ++ ), ++ encoding="utf-8", ++) ++time.sleep(60) ++""", ++ encoding="utf-8", ++ ) ++ manifest_path = tmp_path / "manifest.tsv" ++ markers = [tmp_path / f"job_{idx}.json" for idx in range(4)] ++ rows = [] ++ for idx, marker in enumerate(markers): ++ row = {column: "" for column in MANIFEST_V2_COLUMNS} ++ row.update( ++ { ++ "schema_version": "v2", ++ "job_id": f"job{idx}", ++ "train_command": f"exec {shlex.join([sys.executable, str(helper_path), str(marker)])}", ++ } ++ ) ++ rows.append(row) ++ write_manifest(manifest_path, rows) ++ ++ runner = subprocess.Popen( ++ [ ++ sys.executable, ++ "-m", ++ "scripts.experiment_runner.run_manifest_jobs", ++ "--manifest", ++ str(manifest_path), ++ "--stage", ++ "train", ++ "--gpus", ++ "0,1", ++ ], ++ cwd=REPO_ROOT, ++ stdout=subprocess.PIPE, ++ stderr=subprocess.PIPE, ++ text=True, ++ ) ++ process_groups: set[int] = set() ++ try: ++ deadline = time.time() + 10.0 ++ while sum(marker.is_file() for marker in markers) < 2 and time.time() < deadline: ++ time.sleep(0.05) ++ assert [marker.is_file() for marker in markers] == [True, True, False, False] ++ for marker in markers[:2]: ++ process_info = json.loads(marker.read_text(encoding="utf-8")) ++ assert process_info["leader_pgid"] == process_info["child_pgid"] ++ process_groups.add(int(process_info["leader_pgid"])) ++ ++ runner.send_signal(signal.SIGINT) ++ time.sleep(0.1) ++ runner.send_signal(signal.SIGINT) ++ stdout, stderr = runner.communicate(timeout=10.0) ++ assert runner.returncode != 0, (stdout, stderr) ++ assert [marker.is_file() for marker in markers] == [True, True, False, False] ++ ++ deadline = time.time() + 5.0 ++ while process_groups and time.time() < deadline: ++ for process_group in list(process_groups): ++ try: ++ os.killpg(process_group, 0) ++ except ProcessLookupError: ++ process_groups.remove(process_group) ++ time.sleep(0.05) ++ assert not process_groups ++ ++ events = load_events(event_log_path_for_manifest(manifest_path)) ++ assert [event["stage"] for event in events] == ["train_started", "train_started"] ++ finally: ++ if runner.poll() is None: ++ runner.kill() ++ runner.wait() ++ for process_group in process_groups: ++ try: ++ os.killpg(process_group, signal.SIGKILL) ++ except ProcessLookupError: ++ pass ++ ++ ++def test_sigint_does_not_wait_for_in_flight_upload(tmp_path): ++ manifest_path = tmp_path / "manifest.tsv" ++ row = {column: "" for column in MANIFEST_V2_COLUMNS} ++ row.update( ++ { ++ "schema_version": "v2", ++ "job_id": "job0", ++ "train_upload_repo_id": "repo-model", ++ "train_upload_repo_type": "model", ++ } ++ ) ++ write_manifest(manifest_path, [row]) ++ append_event( ++ event_log_path_for_manifest(manifest_path), ++ {"job_id": "job0", "stage": "eval_succeeded"}, ++ ) ++ upload_started = tmp_path / "upload_started" ++ helper_path = tmp_path / "blocking_upload_runner.py" ++ helper_path.write_text( ++ """from pathlib import Path ++import sys ++import time ++ ++from scripts.experiment_runner.run_manifest_jobs import run_jobs ++ ++manifest_path = Path(sys.argv[1]) ++upload_started = Path(sys.argv[2]) ++ ++def blocking_uploader(job): ++ del job ++ upload_started.write_text("started", encoding="utf-8") ++ time.sleep(60) ++ ++raise SystemExit( ++ run_jobs( ++ manifest_path=manifest_path, ++ gpus=[], ++ upload_workers=1, ++ max_upload_attempts=1, ++ stage="upload", ++ uploader=blocking_uploader, ++ ) ++) ++""", ++ encoding="utf-8", ++ ) ++ runner = subprocess.Popen( ++ [sys.executable, str(helper_path), str(manifest_path), str(upload_started)], ++ cwd=REPO_ROOT, ++ env={**os.environ, "PYTHONPATH": str(REPO_ROOT)}, ++ stdout=subprocess.PIPE, ++ stderr=subprocess.PIPE, ++ text=True, ++ ) ++ try: ++ deadline = time.time() + 10.0 ++ while not upload_started.is_file() and time.time() < deadline: ++ time.sleep(0.05) ++ assert upload_started.is_file() ++ ++ started_at = time.monotonic() ++ runner.send_signal(signal.SIGINT) ++ stdout, stderr = runner.communicate(timeout=5.0) ++ assert runner.returncode != 0, (stdout, stderr) ++ assert time.monotonic() - started_at < 3.0 ++ finally: ++ if runner.poll() is None: ++ runner.kill() ++ runner.wait() ++ ++ + def test_default_uploader_prefers_env_token_over_dotenv(monkeypatch, tmp_path): + monkeypatch.chdir(tmp_path) + (tmp_path / ".env").write_text("HF_TOKEN=dotenv-token\n", encoding="utf-8") diff --git a/evaluations/demon-attack/memory_rollout_teacher:demon_attack:teacher:fixed_l6:fs4:obs15:stride4:seed0/train/memory_rollout_teacher:demon_attack:teacher:fixed_l6:fs4:obs15:stride4:seed0/sf_log.txt b/evaluations/demon-attack/memory_rollout_teacher:demon_attack:teacher:fixed_l6:fs4:obs15:stride4:seed0/train/memory_rollout_teacher:demon_attack:teacher:fixed_l6:fs4:obs15:stride4:seed0/sf_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..4e92e644050e71c13721ad3dc471a5fbc55cf7f5 --- /dev/null +++ b/evaluations/demon-attack/memory_rollout_teacher:demon_attack:teacher:fixed_l6:fs4:obs15:stride4:seed0/train/memory_rollout_teacher:demon_attack:teacher:fixed_l6:fs4:obs15:stride4:seed0/sf_log.txt @@ -0,0 +1,2499 @@ +[2026-07-22 21:27:10,806][379328] Saving configuration to results/checkpoints/memory/rollout_teacher/demon_attack_teacher_fixed_l6_obs15_seed0/config.json... +[2026-07-22 21:27:10,839][379328] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 21:27:10,839][379328] Rollout worker 0 uses device cuda:0 +[2026-07-22 21:27:11,556][379328] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 21:27:11,556][379328] InferenceWorker_p0-w0: min num requests: 1 +[2026-07-22 21:27:11,560][379328] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 21:27:11,560][379328] Starting all processes... +[2026-07-22 21:27:11,561][379328] Starting process learner_proc0 +[2026-07-22 21:27:11,610][379328] Starting all processes... +[2026-07-22 21:27:11,612][379328] Starting process inference_proc0-0 +[2026-07-22 21:27:11,613][379328] Starting process rollout_proc0 +[2026-07-22 21:27:14,277][380289] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 21:27:14,277][380289] Set environment var CUDA_VISIBLE_DEVICES to '1' (GPU indices [0]) for learning process 0 +[2026-07-22 21:27:14,277][380289] Num visible devices: 1 +[2026-07-22 21:27:14,278][380289] Setting fixed seed 0 +[2026-07-22 21:27:14,279][380289] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 21:27:14,279][380289] Initializing actor-critic model on device cuda:0 +[2026-07-22 21:27:14,279][380289] RunningMeanStd input shape: (4, 84, 84) +[2026-07-22 21:27:14,280][380289] RunningMeanStd input shape: (1,) +[2026-07-22 21:27:14,290][380289] ConvEncoder: input_channels=4 +[2026-07-22 21:27:14,377][380296] Worker 0 uses CPU cores [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27] +[2026-07-22 21:27:14,377][380296] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 21:27:14,377][380296] Set environment var CUDA_VISIBLE_DEVICES to '1' (GPU indices [0]) for actor process 0 +[2026-07-22 21:27:14,377][380296] Num visible devices: 1 +[2026-07-22 21:27:14,389][380295] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 21:27:14,390][380295] Set environment var CUDA_VISIBLE_DEVICES to '1' (GPU indices [0]) for inference process 0 +[2026-07-22 21:27:14,390][380295] Num visible devices: 1 +[2026-07-22 21:27:14,394][380289] Conv encoder output size: 512 +[2026-07-22 21:27:14,396][380289] Created Actor Critic model with architecture: +[2026-07-22 21:27:14,396][380289] ActorCriticSharedWeights( + (obs_normalizer): ObservationNormalizer( + (running_mean_std): RunningMeanStdDictInPlace( + (running_mean_std): ModuleDict( + (obs): RunningMeanStdInPlace() + ) + ) + ) + (returns_normalizer): RecursiveScriptModule(original_name=RunningMeanStdInPlace) + (encoder): MultiInputEncoder( + (encoders): ModuleDict( + (obs): ConvEncoder( + (enc): RecursiveScriptModule( + original_name=ConvEncoderImpl + (conv_head): RecursiveScriptModule( + original_name=Sequential + (0): RecursiveScriptModule(original_name=Conv2d) + (1): RecursiveScriptModule(original_name=ELU) + (2): RecursiveScriptModule(original_name=Conv2d) + (3): RecursiveScriptModule(original_name=ELU) + (4): RecursiveScriptModule(original_name=Conv2d) + (5): RecursiveScriptModule(original_name=ELU) + ) + (mlp_layers): RecursiveScriptModule( + original_name=Sequential + (0): RecursiveScriptModule(original_name=Linear) + (1): RecursiveScriptModule(original_name=ELU) + ) + ) + ) + ) + ) + (core): ModelCoreIdentity() + (decoder): MlpDecoder( + (mlp): Identity() + ) + (critic_linear): Linear(in_features=512, out_features=1, bias=True) + (action_parameterization): ActionParameterizationDefault( + (distribution_linear): Linear(in_features=512, out_features=6, bias=True) + ) +) +[2026-07-22 21:27:14,400][380289] Using optimizer +[2026-07-22 21:27:15,186][380289] No checkpoints found +[2026-07-22 21:27:15,186][380289] Did not load from checkpoint, starting from scratch! +[2026-07-22 21:27:15,186][380289] Initialized policy 0 weights for model version 0 +[2026-07-22 21:27:15,188][380289] LearnerWorker_p0 finished initialization! +[2026-07-22 21:27:15,188][380289] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 21:27:15,189][380295] RunningMeanStd input shape: (4, 84, 84) +[2026-07-22 21:27:15,190][380295] RunningMeanStd input shape: (1,) +[2026-07-22 21:27:15,199][380295] ConvEncoder: input_channels=4 +[2026-07-22 21:27:15,281][380295] Conv encoder output size: 512 +[2026-07-22 21:27:15,287][379328] Inference worker 0-0 is ready! +[2026-07-22 21:27:15,288][379328] All inference workers are ready! Signal rollout workers to start! +[2026-07-22 21:27:15,289][380296] EnvRunner 0-0 uses policy 0 +[2026-07-22 21:27:16,951][379328] Fps is (10 sec: nan, 60 sec: nan, 300 sec: nan). Total num frames: 0. Throughput: 0: nan. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) +[2026-07-22 21:27:19,756][380289] Signal inference workers to stop experience collection... +[2026-07-22 21:27:19,791][380295] InferenceWorker_p0-w0: stopping experience collection +[2026-07-22 21:27:20,536][380289] Signal inference workers to resume experience collection... +[2026-07-22 21:27:20,537][380295] InferenceWorker_p0-w0: resuming experience collection +[2026-07-22 21:27:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 32768. Throughput: 0: 7782.4. Samples: 38912. Policy #0 lag: (min: 15.0, avg: 15.0, max: 15.0) +[2026-07-22 21:27:25,443][380295] Updated weights for policy 0, policy_version 96 (0.0067) +[2026-07-22 21:27:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 65536. Throughput: 0: 6092.8. Samples: 60928. Policy #0 lag: (min: 10.0, avg: 15.8, max: 74.0) +[2026-07-22 21:27:31,221][380295] Updated weights for policy 0, policy_version 192 (0.0008) +[2026-07-22 21:27:31,535][379328] Heartbeat connected on Batcher_0 +[2026-07-22 21:27:31,552][379328] Heartbeat connected on LearnerWorker_p0 +[2026-07-22 21:27:31,597][379328] Heartbeat connected on InferenceWorker_p0-w0 +[2026-07-22 21:27:31,603][379328] Heartbeat connected on RolloutWorker_w0 +[2026-07-22 21:27:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 98304. Throughput: 0: 6553.6. Samples: 98304. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:27:31,952][379328] Avg episode reward: [(0, '30.000')] +[2026-07-22 21:27:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 131072. Throughput: 0: 6656.0. Samples: 133120. Policy #0 lag: (min: 13.0, avg: 15.7, max: 77.0) +[2026-07-22 21:27:36,952][379328] Avg episode reward: [(0, '36.667')] +[2026-07-22 21:27:36,956][380289] Saving new best policy, reward=36.667! +[2026-07-22 21:27:41,653][380295] Updated weights for policy 0, policy_version 306 (0.0007) +[2026-07-22 21:27:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 163840. Throughput: 0: 6103.0. Samples: 152576. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:27:41,951][379328] Avg episode reward: [(0, '47.895')] +[2026-07-22 21:27:41,956][380289] Saving new best policy, reward=47.895! +[2026-07-22 21:27:46,951][379328] Fps is (10 sec: 5734.4, 60 sec: 6280.5, 300 sec: 6280.5). Total num frames: 188416. Throughput: 0: 6382.9. Samples: 191488. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:27:46,952][379328] Avg episode reward: [(0, '58.780')] +[2026-07-22 21:27:47,177][380289] Saving new best policy, reward=58.780! +[2026-07-22 21:27:51,951][379328] Fps is (10 sec: 4096.0, 60 sec: 5851.4, 300 sec: 5851.4). Total num frames: 204800. Throughput: 0: 6495.1. Samples: 227328. Policy #0 lag: (min: 13.0, avg: 15.7, max: 77.0) +[2026-07-22 21:27:51,952][379328] Avg episode reward: [(0, '62.167')] +[2026-07-22 21:27:52,040][380295] Updated weights for policy 0, policy_version 416 (0.0007) +[2026-07-22 21:27:52,251][380289] Saving new best policy, reward=62.167! +[2026-07-22 21:27:56,951][379328] Fps is (10 sec: 4096.0, 60 sec: 5734.4, 300 sec: 5734.4). Total num frames: 229376. Throughput: 0: 6105.6. Samples: 244224. Policy #0 lag: (min: 13.0, avg: 15.7, max: 77.0) +[2026-07-22 21:27:56,951][379328] Avg episode reward: [(0, '68.111')] +[2026-07-22 21:27:56,955][380289] Saving new best policy, reward=68.111! +[2026-07-22 21:28:01,951][379328] Fps is (10 sec: 5734.4, 60 sec: 5825.4, 300 sec: 5825.4). Total num frames: 262144. Throughput: 0: 6200.9. Samples: 279040. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:28:01,952][379328] Avg episode reward: [(0, '77.950')] +[2026-07-22 21:28:01,958][380289] Saving new best policy, reward=77.950! +[2026-07-22 21:28:03,332][380295] Updated weights for policy 0, policy_version 544 (0.0008) +[2026-07-22 21:28:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5898.2, 300 sec: 5898.2). Total num frames: 294912. Throughput: 0: 6098.5. Samples: 313344. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:28:06,952][379328] Avg episode reward: [(0, '88.800')] +[2026-07-22 21:28:06,959][380289] Saving new best policy, reward=88.800! +[2026-07-22 21:28:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5957.8, 300 sec: 5957.8). Total num frames: 327680. Throughput: 0: 5973.3. Samples: 329728. Policy #0 lag: (min: 6.0, avg: 8.6, max: 70.0) +[2026-07-22 21:28:11,952][379328] Avg episode reward: [(0, '104.500')] +[2026-07-22 21:28:11,958][380289] Saving new best policy, reward=104.500! +[2026-07-22 21:28:15,229][380295] Updated weights for policy 0, policy_version 672 (0.0008) +[2026-07-22 21:28:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6007.5). Total num frames: 360448. Throughput: 0: 5859.6. Samples: 361984. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:28:16,952][379328] Avg episode reward: [(0, '116.650')] +[2026-07-22 21:28:16,957][380289] Saving new best policy, reward=116.650! +[2026-07-22 21:28:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6049.5). Total num frames: 393216. Throughput: 0: 5814.0. Samples: 394752. Policy #0 lag: (min: 4.0, avg: 6.7, max: 68.0) +[2026-07-22 21:28:21,952][379328] Avg episode reward: [(0, '123.550')] +[2026-07-22 21:28:21,957][380289] Saving new best policy, reward=123.550! +[2026-07-22 21:28:26,724][380295] Updated weights for policy 0, policy_version 784 (0.0009) +[2026-07-22 21:28:26,951][379328] Fps is (10 sec: 4915.2, 60 sec: 5734.4, 300 sec: 5851.4). Total num frames: 409600. Throughput: 0: 5802.7. Samples: 413696. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:28:26,951][379328] Avg episode reward: [(0, '127.450')] +[2026-07-22 21:28:27,422][380289] Saving new best policy, reward=127.450! +[2026-07-22 21:28:31,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5679.8). Total num frames: 425984. Throughput: 0: 5677.5. Samples: 446976. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:28:31,951][379328] Avg episode reward: [(0, '134.550')] +[2026-07-22 21:28:31,957][380289] Saving new best policy, reward=134.550! +[2026-07-22 21:28:33,500][380295] Updated weights for policy 0, policy_version 896 (0.0009) +[2026-07-22 21:28:36,951][379328] Fps is (10 sec: 4915.2, 60 sec: 5461.3, 300 sec: 5734.4). Total num frames: 458752. Throughput: 0: 5552.4. Samples: 477184. Policy #0 lag: (min: 11.0, avg: 13.6, max: 75.0) +[2026-07-22 21:28:36,952][379328] Avg episode reward: [(0, '137.000')] +[2026-07-22 21:28:36,957][380289] Saving new best policy, reward=137.000! +[2026-07-22 21:28:41,951][379328] Fps is (10 sec: 6553.5, 60 sec: 5461.3, 300 sec: 5782.6). Total num frames: 491520. Throughput: 0: 5518.2. Samples: 492544. Policy #0 lag: (min: 12.0, avg: 14.7, max: 76.0) +[2026-07-22 21:28:41,952][379328] Avg episode reward: [(0, '142.050')] +[2026-07-22 21:28:41,957][380289] Saving new best policy, reward=142.050! +[2026-07-22 21:28:45,784][380295] Updated weights for policy 0, policy_version 1024 (0.0008) +[2026-07-22 21:28:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5597.9, 300 sec: 5825.4). Total num frames: 524288. Throughput: 0: 5472.7. Samples: 525312. Policy #0 lag: (min: 14.0, avg: 16.7, max: 78.0) +[2026-07-22 21:28:46,952][379328] Avg episode reward: [(0, '143.350')] +[2026-07-22 21:28:46,957][380289] Saving new best policy, reward=143.350! +[2026-07-22 21:28:51,467][380289] Signal inference workers to stop experience collection... (50 times) +[2026-07-22 21:28:51,498][380295] InferenceWorker_p0-w0: stopping experience collection (50 times) +[2026-07-22 21:28:51,647][380289] Signal inference workers to resume experience collection... (50 times) +[2026-07-22 21:28:51,648][380295] InferenceWorker_p0-w0: resuming experience collection (50 times) +[2026-07-22 21:28:51,951][379328] Fps is (10 sec: 6553.7, 60 sec: 5870.9, 300 sec: 5863.7). Total num frames: 557056. Throughput: 0: 5438.6. Samples: 558080. Policy #0 lag: (min: 3.0, avg: 5.7, max: 67.0) +[2026-07-22 21:28:51,952][379328] Avg episode reward: [(0, '155.450')] +[2026-07-22 21:28:51,957][380289] Saving new best policy, reward=155.450! +[2026-07-22 21:28:56,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5570.6). Total num frames: 557056. Throughput: 0: 5438.6. Samples: 574464. Policy #0 lag: (min: 3.0, avg: 5.7, max: 67.0) +[2026-07-22 21:28:56,952][379328] Avg episode reward: [(0, '163.600')] +[2026-07-22 21:28:56,957][380289] Saving new best policy, reward=163.600! +[2026-07-22 21:28:57,873][380295] Updated weights for policy 0, policy_version 1149 (0.0008) +[2026-07-22 21:29:01,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5617.4). Total num frames: 589824. Throughput: 0: 5472.7. Samples: 608256. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:29:01,952][379328] Avg episode reward: [(0, '167.150')] +[2026-07-22 21:29:01,957][380289] Saving new best policy, reward=167.150! +[2026-07-22 21:29:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5659.9). Total num frames: 622592. Throughput: 0: 5506.8. Samples: 642560. Policy #0 lag: (min: 9.0, avg: 11.7, max: 73.0) +[2026-07-22 21:29:06,951][379328] Avg episode reward: [(0, '166.250')] +[2026-07-22 21:29:09,289][380295] Updated weights for policy 0, policy_version 1270 (0.0007) +[2026-07-22 21:29:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5698.8). Total num frames: 655360. Throughput: 0: 5427.2. Samples: 657920. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:29:11,951][379328] Avg episode reward: [(0, '157.750')] +[2026-07-22 21:29:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5734.4). Total num frames: 688128. Throughput: 0: 5415.8. Samples: 690688. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:29:16,952][379328] Avg episode reward: [(0, '156.050')] +[2026-07-22 21:29:20,871][380295] Updated weights for policy 0, policy_version 1376 (0.0009) +[2026-07-22 21:29:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5767.2). Total num frames: 720896. Throughput: 0: 5472.7. Samples: 723456. Policy #0 lag: (min: 9.0, avg: 11.6, max: 73.0) +[2026-07-22 21:29:21,952][379328] Avg episode reward: [(0, '159.350')] +[2026-07-22 21:29:26,951][379328] Fps is (10 sec: 4915.2, 60 sec: 5461.3, 300 sec: 5671.4). Total num frames: 737280. Throughput: 0: 5529.6. Samples: 741376. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:29:26,952][379328] Avg episode reward: [(0, '160.000')] +[2026-07-22 21:29:31,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5582.7). Total num frames: 753664. Throughput: 0: 5495.5. Samples: 772608. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:29:31,952][379328] Avg episode reward: [(0, '169.500')] +[2026-07-22 21:29:31,957][380289] Saving new best policy, reward=169.500! +[2026-07-22 21:29:32,934][380295] Updated weights for policy 0, policy_version 1504 (0.0008) +[2026-07-22 21:29:36,951][379328] Fps is (10 sec: 4915.2, 60 sec: 5461.3, 300 sec: 5617.4). Total num frames: 786432. Throughput: 0: 5518.2. Samples: 806400. Policy #0 lag: (min: 3.0, avg: 5.7, max: 67.0) +[2026-07-22 21:29:36,951][379328] Avg episode reward: [(0, '177.150')] +[2026-07-22 21:29:36,957][380289] Saving new best policy, reward=177.150! +[2026-07-22 21:29:39,523][380295] Updated weights for policy 0, policy_version 1600 (0.0008) +[2026-07-22 21:29:41,951][379328] Fps is (10 sec: 6553.5, 60 sec: 5461.3, 300 sec: 5649.7). Total num frames: 819200. Throughput: 0: 5495.5. Samples: 821760. Policy #0 lag: (min: 4.0, avg: 6.7, max: 68.0) +[2026-07-22 21:29:41,952][379328] Avg episode reward: [(0, '174.150')] +[2026-07-22 21:29:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5679.8). Total num frames: 851968. Throughput: 0: 5472.7. Samples: 854528. Policy #0 lag: (min: 9.0, avg: 11.8, max: 73.0) +[2026-07-22 21:29:46,952][379328] Avg episode reward: [(0, '173.600')] +[2026-07-22 21:29:51,335][380295] Updated weights for policy 0, policy_version 1728 (0.0009) +[2026-07-22 21:29:51,951][379328] Fps is (10 sec: 6553.7, 60 sec: 5461.3, 300 sec: 5708.0). Total num frames: 884736. Throughput: 0: 5438.6. Samples: 887296. Policy #0 lag: (min: 9.0, avg: 11.6, max: 73.0) +[2026-07-22 21:29:51,952][379328] Avg episode reward: [(0, '168.850')] +[2026-07-22 21:29:56,951][379328] Fps is (10 sec: 4096.0, 60 sec: 5597.9, 300 sec: 5580.8). Total num frames: 892928. Throughput: 0: 5472.7. Samples: 904192. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:29:56,951][379328] Avg episode reward: [(0, '174.550')] +[2026-07-22 21:30:01,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5560.6). Total num frames: 917504. Throughput: 0: 5484.1. Samples: 937472. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:30:01,952][379328] Avg episode reward: [(0, '182.950')] +[2026-07-22 21:30:01,957][380289] Saving new best policy, reward=182.950! +[2026-07-22 21:30:03,342][380295] Updated weights for policy 0, policy_version 1850 (0.0008) +[2026-07-22 21:30:06,951][379328] Fps is (10 sec: 5734.4, 60 sec: 5461.3, 300 sec: 5589.8). Total num frames: 950272. Throughput: 0: 5506.8. Samples: 971264. Policy #0 lag: (min: 0.0, avg: 2.6, max: 64.0) +[2026-07-22 21:30:06,951][379328] Avg episode reward: [(0, '181.850')] +[2026-07-22 21:30:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5617.4). Total num frames: 983040. Throughput: 0: 5472.7. Samples: 987648. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:30:11,952][379328] Avg episode reward: [(0, '187.350')] +[2026-07-22 21:30:11,957][380289] Saving new best policy, reward=187.350! +[2026-07-22 21:30:14,817][380295] Updated weights for policy 0, policy_version 1974 (0.0009) +[2026-07-22 21:30:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5643.4). Total num frames: 1015808. Throughput: 0: 5506.8. Samples: 1020416. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:30:16,952][379328] Avg episode reward: [(0, '176.800')] +[2026-07-22 21:30:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5668.0). Total num frames: 1048576. Throughput: 0: 5529.6. Samples: 1055232. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:30:21,951][379328] Avg episode reward: [(0, '171.650')] +[2026-07-22 21:30:26,010][380295] Updated weights for policy 0, policy_version 2080 (0.0007) +[2026-07-22 21:30:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5734.4, 300 sec: 5691.3). Total num frames: 1081344. Throughput: 0: 5597.9. Samples: 1073664. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:30:26,951][379328] Avg episode reward: [(0, '178.200')] +[2026-07-22 21:30:31,547][380289] Signal inference workers to stop experience collection... (100 times) +[2026-07-22 21:30:31,577][380295] InferenceWorker_p0-w0: stopping experience collection (100 times) +[2026-07-22 21:30:31,759][380289] Signal inference workers to resume experience collection... (100 times) +[2026-07-22 21:30:31,760][380295] InferenceWorker_p0-w0: resuming experience collection (100 times) +[2026-07-22 21:30:31,951][379328] Fps is (10 sec: 5734.4, 60 sec: 5870.9, 300 sec: 5671.4). Total num frames: 1105920. Throughput: 0: 5643.4. Samples: 1108480. Policy #0 lag: (min: 7.0, avg: 9.6, max: 71.0) +[2026-07-22 21:30:31,951][379328] Avg episode reward: [(0, '177.000')] +[2026-07-22 21:30:36,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5570.6). Total num frames: 1114112. Throughput: 0: 5666.1. Samples: 1142272. Policy #0 lag: (min: 7.0, avg: 9.6, max: 71.0) +[2026-07-22 21:30:36,952][379328] Avg episode reward: [(0, '183.300')] +[2026-07-22 21:30:37,382][380295] Updated weights for policy 0, policy_version 2192 (0.0009) +[2026-07-22 21:30:41,951][379328] Fps is (10 sec: 4096.0, 60 sec: 5461.3, 300 sec: 5594.5). Total num frames: 1146880. Throughput: 0: 5632.0. Samples: 1157632. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:30:41,951][379328] Avg episode reward: [(0, '183.450')] +[2026-07-22 21:30:43,812][380295] Updated weights for policy 0, policy_version 2304 (0.0007) +[2026-07-22 21:30:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5617.4). Total num frames: 1179648. Throughput: 0: 5677.5. Samples: 1192960. Policy #0 lag: (min: 8.0, avg: 10.6, max: 72.0) +[2026-07-22 21:30:46,952][379328] Avg episode reward: [(0, '186.700')] +[2026-07-22 21:30:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5639.1). Total num frames: 1212416. Throughput: 0: 5688.9. Samples: 1227264. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:30:51,952][379328] Avg episode reward: [(0, '187.600')] +[2026-07-22 21:30:51,956][380289] Saving new best policy, reward=187.600! +[2026-07-22 21:30:55,031][380295] Updated weights for policy 0, policy_version 2423 (0.0007) +[2026-07-22 21:30:56,951][379328] Fps is (10 sec: 6553.5, 60 sec: 5870.9, 300 sec: 5659.9). Total num frames: 1245184. Throughput: 0: 5723.0. Samples: 1245184. Policy #0 lag: (min: 10.0, avg: 12.6, max: 74.0) +[2026-07-22 21:30:56,952][379328] Avg episode reward: [(0, '185.400')] +[2026-07-22 21:31:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5679.8). Total num frames: 1277952. Throughput: 0: 5734.4. Samples: 1278464. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:31:01,952][379328] Avg episode reward: [(0, '188.900')] +[2026-07-22 21:31:01,957][380289] Saving new best policy, reward=188.900! +[2026-07-22 21:31:06,464][380295] Updated weights for policy 0, policy_version 2544 (0.0008) +[2026-07-22 21:31:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5698.8). Total num frames: 1310720. Throughput: 0: 5711.6. Samples: 1312256. Policy #0 lag: (min: 13.0, avg: 15.7, max: 77.0) +[2026-07-22 21:31:06,951][379328] Avg episode reward: [(0, '197.050')] +[2026-07-22 21:31:06,958][380289] Saving new best policy, reward=197.050! +[2026-07-22 21:31:11,951][379328] Fps is (10 sec: 4096.0, 60 sec: 5597.9, 300 sec: 5612.4). Total num frames: 1318912. Throughput: 0: 5677.5. Samples: 1329152. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 21:31:11,952][379328] Avg episode reward: [(0, '202.050')] +[2026-07-22 21:31:12,307][380289] Saving new best policy, reward=202.050! +[2026-07-22 21:31:16,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5597.9). Total num frames: 1343488. Throughput: 0: 5666.1. Samples: 1363456. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 21:31:16,951][379328] Avg episode reward: [(0, '205.650')] +[2026-07-22 21:31:16,957][380289] Saving new best policy, reward=205.650! +[2026-07-22 21:31:17,593][380295] Updated weights for policy 0, policy_version 2640 (0.0008) +[2026-07-22 21:31:21,951][379328] Fps is (10 sec: 5734.4, 60 sec: 5461.3, 300 sec: 5617.4). Total num frames: 1376256. Throughput: 0: 5688.9. Samples: 1398272. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:31:21,951][379328] Avg episode reward: [(0, '197.350')] +[2026-07-22 21:31:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5636.1). Total num frames: 1409024. Throughput: 0: 5688.9. Samples: 1413632. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:31:26,951][379328] Avg episode reward: [(0, '202.600')] +[2026-07-22 21:31:29,383][380295] Updated weights for policy 0, policy_version 2768 (0.0008) +[2026-07-22 21:31:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5597.9, 300 sec: 5654.1). Total num frames: 1441792. Throughput: 0: 5632.0. Samples: 1446400. Policy #0 lag: (min: 1.0, avg: 3.7, max: 65.0) +[2026-07-22 21:31:31,952][379328] Avg episode reward: [(0, '204.200')] +[2026-07-22 21:31:35,841][380295] Updated weights for policy 0, policy_version 2878 (0.0007) +[2026-07-22 21:31:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5671.4). Total num frames: 1474560. Throughput: 0: 5632.0. Samples: 1480704. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:31:36,951][379328] Avg episode reward: [(0, '201.500')] +[2026-07-22 21:31:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5688.0). Total num frames: 1507328. Throughput: 0: 5643.4. Samples: 1499136. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:31:41,952][379328] Avg episode reward: [(0, '202.950')] +[2026-07-22 21:31:46,703][380295] Updated weights for policy 0, policy_version 2992 (0.0008) +[2026-07-22 21:31:46,951][379328] Fps is (10 sec: 5734.4, 60 sec: 5870.9, 300 sec: 5673.7). Total num frames: 1531904. Throughput: 0: 5711.6. Samples: 1535488. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:31:46,952][379328] Avg episode reward: [(0, '205.250')] +[2026-07-22 21:31:51,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5600.3). Total num frames: 1540096. Throughput: 0: 5700.3. Samples: 1568768. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:31:51,951][379328] Avg episode reward: [(0, '207.950')] +[2026-07-22 21:31:52,276][380289] Saving new best policy, reward=207.950! +[2026-07-22 21:31:56,951][379328] Fps is (10 sec: 4096.0, 60 sec: 5461.3, 300 sec: 5617.4). Total num frames: 1572864. Throughput: 0: 5700.3. Samples: 1585664. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:31:56,952][379328] Avg episode reward: [(0, '204.000')] +[2026-07-22 21:31:57,908][380295] Updated weights for policy 0, policy_version 3088 (0.0007) +[2026-07-22 21:32:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5633.8). Total num frames: 1605632. Throughput: 0: 5688.9. Samples: 1619456. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:32:01,952][379328] Avg episode reward: [(0, '199.650')] +[2026-07-22 21:32:04,456][380295] Updated weights for policy 0, policy_version 3200 (0.0009) +[2026-07-22 21:32:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5649.7). Total num frames: 1638400. Throughput: 0: 5666.1. Samples: 1653248. Policy #0 lag: (min: 4.0, avg: 6.7, max: 68.0) +[2026-07-22 21:32:06,951][379328] Avg episode reward: [(0, '193.200')] +[2026-07-22 21:32:09,239][380289] Signal inference workers to stop experience collection... (150 times) +[2026-07-22 21:32:09,265][380295] InferenceWorker_p0-w0: stopping experience collection (150 times) +[2026-07-22 21:32:09,418][380289] Signal inference workers to resume experience collection... (150 times) +[2026-07-22 21:32:09,419][380295] InferenceWorker_p0-w0: resuming experience collection (150 times) +[2026-07-22 21:32:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5870.9, 300 sec: 5665.0). Total num frames: 1671168. Throughput: 0: 5734.4. Samples: 1671680. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:32:11,952][379328] Avg episode reward: [(0, '189.150')] +[2026-07-22 21:32:15,898][380295] Updated weights for policy 0, policy_version 3328 (0.0008) +[2026-07-22 21:32:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5665.0). Total num frames: 1703936. Throughput: 0: 5745.8. Samples: 1704960. Policy #0 lag: (min: 2.0, avg: 4.6, max: 66.0) +[2026-07-22 21:32:16,952][379328] Avg episode reward: [(0, '195.150')] +[2026-07-22 21:32:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5665.0). Total num frames: 1736704. Throughput: 0: 5723.0. Samples: 1738240. Policy #0 lag: (min: 8.0, avg: 10.6, max: 72.0) +[2026-07-22 21:32:21,952][379328] Avg episode reward: [(0, '190.350')] +[2026-07-22 21:32:26,951][379328] Fps is (10 sec: 4915.2, 60 sec: 5734.4, 300 sec: 5609.4). Total num frames: 1753088. Throughput: 0: 5688.9. Samples: 1755136. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:32:26,951][379328] Avg episode reward: [(0, '199.650')] +[2026-07-22 21:32:27,226][380295] Updated weights for policy 0, policy_version 3446 (0.0008) +[2026-07-22 21:32:31,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5553.9). Total num frames: 1769472. Throughput: 0: 5654.8. Samples: 1789952. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:32:31,951][379328] Avg episode reward: [(0, '193.350')] +[2026-07-22 21:32:36,951][379328] Fps is (10 sec: 4915.2, 60 sec: 5461.3, 300 sec: 5553.9). Total num frames: 1802240. Throughput: 0: 5643.4. Samples: 1822720. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:32:36,952][379328] Avg episode reward: [(0, '208.050')] +[2026-07-22 21:32:36,957][380289] Saving new best policy, reward=208.050! +[2026-07-22 21:32:38,814][380295] Updated weights for policy 0, policy_version 3570 (0.0008) +[2026-07-22 21:32:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5581.7). Total num frames: 1835008. Throughput: 0: 5643.4. Samples: 1839616. Policy #0 lag: (min: 11.0, avg: 13.6, max: 75.0) +[2026-07-22 21:32:41,952][379328] Avg episode reward: [(0, '213.250')] +[2026-07-22 21:32:41,957][380289] Saving new best policy, reward=213.250! +[2026-07-22 21:32:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5597.9, 300 sec: 5637.2). Total num frames: 1867776. Throughput: 0: 5666.1. Samples: 1874432. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:32:46,952][379328] Avg episode reward: [(0, '224.450')] +[2026-07-22 21:32:46,956][380289] Saving new best policy, reward=224.450! +[2026-07-22 21:32:49,968][380295] Updated weights for policy 0, policy_version 3680 (0.0009) +[2026-07-22 21:32:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5665.0). Total num frames: 1900544. Throughput: 0: 5688.9. Samples: 1909248. Policy #0 lag: (min: 8.0, avg: 10.8, max: 72.0) +[2026-07-22 21:32:51,951][379328] Avg episode reward: [(0, '239.150')] +[2026-07-22 21:32:51,956][380289] Saving new best policy, reward=239.150! +[2026-07-22 21:32:55,923][380295] Updated weights for policy 0, policy_version 3776 (0.0007) +[2026-07-22 21:32:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5665.0). Total num frames: 1933312. Throughput: 0: 5711.6. Samples: 1928704. Policy #0 lag: (min: 5.0, avg: 7.7, max: 69.0) +[2026-07-22 21:32:56,952][379328] Avg episode reward: [(0, '236.800')] +[2026-07-22 21:33:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5665.0). Total num frames: 1966080. Throughput: 0: 5791.3. Samples: 1965568. Policy #0 lag: (min: 5.0, avg: 7.6, max: 69.0) +[2026-07-22 21:33:01,951][379328] Avg episode reward: [(0, '236.250')] +[2026-07-22 21:33:06,880][380295] Updated weights for policy 0, policy_version 3894 (0.0007) +[2026-07-22 21:33:06,951][379328] Fps is (10 sec: 5734.4, 60 sec: 5870.9, 300 sec: 5637.2). Total num frames: 1990656. Throughput: 0: 5802.7. Samples: 1999360. Policy #0 lag: (min: 10.0, avg: 12.7, max: 74.0) +[2026-07-22 21:33:06,951][379328] Avg episode reward: [(0, '242.300')] +[2026-07-22 21:33:07,038][380289] Saving new best policy, reward=242.300! +[2026-07-22 21:33:11,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5553.9). Total num frames: 1998848. Throughput: 0: 5825.4. Samples: 2017280. Policy #0 lag: (min: 10.0, avg: 12.7, max: 74.0) +[2026-07-22 21:33:11,952][379328] Avg episode reward: [(0, '240.850')] +[2026-07-22 21:33:16,951][379328] Fps is (10 sec: 4096.0, 60 sec: 5461.3, 300 sec: 5553.9). Total num frames: 2031616. Throughput: 0: 5825.4. Samples: 2052096. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:33:16,952][379328] Avg episode reward: [(0, '249.250')] +[2026-07-22 21:33:16,957][380289] Saving new best policy, reward=249.250! +[2026-07-22 21:33:17,847][380295] Updated weights for policy 0, policy_version 4016 (0.0008) +[2026-07-22 21:33:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5461.3, 300 sec: 5609.4). Total num frames: 2064384. Throughput: 0: 5893.7. Samples: 2087936. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:33:21,951][379328] Avg episode reward: [(0, '257.550')] +[2026-07-22 21:33:21,956][380289] Saving new best policy, reward=257.550! +[2026-07-22 21:33:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5734.4, 300 sec: 5665.0). Total num frames: 2097152. Throughput: 0: 5916.4. Samples: 2105856. Policy #0 lag: (min: 10.0, avg: 12.7, max: 74.0) +[2026-07-22 21:33:26,952][379328] Avg episode reward: [(0, '247.400')] +[2026-07-22 21:33:28,436][380295] Updated weights for policy 0, policy_version 4112 (0.0008) +[2026-07-22 21:33:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5665.0). Total num frames: 2129920. Throughput: 0: 5893.7. Samples: 2139648. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:33:31,951][379328] Avg episode reward: [(0, '241.150')] +[2026-07-22 21:33:34,955][380295] Updated weights for policy 0, policy_version 4224 (0.0007) +[2026-07-22 21:33:36,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6007.5, 300 sec: 5665.0). Total num frames: 2162688. Throughput: 0: 5893.7. Samples: 2174464. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:33:36,952][379328] Avg episode reward: [(0, '246.800')] +[2026-07-22 21:33:40,147][380289] Signal inference workers to stop experience collection... (200 times) +[2026-07-22 21:33:40,177][380295] InferenceWorker_p0-w0: stopping experience collection (200 times) +[2026-07-22 21:33:40,327][380289] Signal inference workers to resume experience collection... (200 times) +[2026-07-22 21:33:40,328][380295] InferenceWorker_p0-w0: resuming experience collection (200 times) +[2026-07-22 21:33:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5665.0). Total num frames: 2195456. Throughput: 0: 5870.9. Samples: 2192896. Policy #0 lag: (min: 8.0, avg: 10.7, max: 72.0) +[2026-07-22 21:33:41,952][379328] Avg episode reward: [(0, '240.000')] +[2026-07-22 21:33:46,291][380295] Updated weights for policy 0, policy_version 4352 (0.0008) +[2026-07-22 21:33:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5665.0). Total num frames: 2228224. Throughput: 0: 5848.2. Samples: 2228736. Policy #0 lag: (min: 3.0, avg: 5.7, max: 67.0) +[2026-07-22 21:33:46,951][379328] Avg episode reward: [(0, '254.450')] +[2026-07-22 21:33:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 2260992. Throughput: 0: 5836.8. Samples: 2262016. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:33:51,952][379328] Avg episode reward: [(0, '271.050')] +[2026-07-22 21:33:51,957][380289] Saving new best policy, reward=271.050! +[2026-07-22 21:33:56,951][379328] Fps is (10 sec: 4915.2, 60 sec: 5734.4, 300 sec: 5720.5). Total num frames: 2277376. Throughput: 0: 5836.8. Samples: 2279936. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:33:56,951][379328] Avg episode reward: [(0, '246.600')] +[2026-07-22 21:33:57,148][380295] Updated weights for policy 0, policy_version 4466 (0.0009) +[2026-07-22 21:34:01,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5665.0). Total num frames: 2293760. Throughput: 0: 5859.6. Samples: 2315776. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:34:01,952][379328] Avg episode reward: [(0, '262.900')] +[2026-07-22 21:34:06,951][379328] Fps is (10 sec: 4915.2, 60 sec: 5597.9, 300 sec: 5665.0). Total num frames: 2326528. Throughput: 0: 5905.1. Samples: 2353664. Policy #0 lag: (min: 2.0, avg: 4.9, max: 66.0) +[2026-07-22 21:34:06,952][379328] Avg episode reward: [(0, '247.400')] +[2026-07-22 21:34:07,356][380295] Updated weights for policy 0, policy_version 4560 (0.0007) +[2026-07-22 21:34:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5665.0). Total num frames: 2359296. Throughput: 0: 5870.9. Samples: 2370048. Policy #0 lag: (min: 15.0, avg: 18.6, max: 79.0) +[2026-07-22 21:34:11,952][379328] Avg episode reward: [(0, '247.150')] +[2026-07-22 21:34:13,778][380295] Updated weights for policy 0, policy_version 4672 (0.0009) +[2026-07-22 21:34:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5665.0). Total num frames: 2392064. Throughput: 0: 5893.7. Samples: 2404864. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:34:16,952][379328] Avg episode reward: [(0, '234.650')] +[2026-07-22 21:34:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5720.5). Total num frames: 2424832. Throughput: 0: 5882.3. Samples: 2439168. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:34:21,952][379328] Avg episode reward: [(0, '249.300')] +[2026-07-22 21:34:25,169][380295] Updated weights for policy 0, policy_version 4800 (0.0007) +[2026-07-22 21:34:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 2457600. Throughput: 0: 5882.3. Samples: 2457600. Policy #0 lag: (min: 9.0, avg: 11.6, max: 73.0) +[2026-07-22 21:34:26,952][379328] Avg episode reward: [(0, '271.800')] +[2026-07-22 21:34:26,957][380289] Saving new best policy, reward=271.800! +[2026-07-22 21:34:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 2490368. Throughput: 0: 5836.8. Samples: 2491392. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:34:31,952][379328] Avg episode reward: [(0, '284.650')] +[2026-07-22 21:34:31,957][380289] Saving new best policy, reward=284.650! +[2026-07-22 21:34:36,303][380295] Updated weights for policy 0, policy_version 4918 (0.0008) +[2026-07-22 21:34:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 2523136. Throughput: 0: 5859.6. Samples: 2525696. Policy #0 lag: (min: 4.0, avg: 6.7, max: 68.0) +[2026-07-22 21:34:36,951][379328] Avg episode reward: [(0, '295.900')] +[2026-07-22 21:34:36,956][380289] Saving new best policy, reward=295.900! +[2026-07-22 21:34:41,951][379328] Fps is (10 sec: 6553.7, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 2555904. Throughput: 0: 5893.7. Samples: 2545152. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:34:41,952][379328] Avg episode reward: [(0, '290.100')] +[2026-07-22 21:34:46,921][380295] Updated weights for policy 0, policy_version 5024 (0.0006) +[2026-07-22 21:34:46,951][379328] Fps is (10 sec: 4915.2, 60 sec: 5734.4, 300 sec: 5720.5). Total num frames: 2572288. Throughput: 0: 5893.7. Samples: 2580992. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:34:46,951][379328] Avg episode reward: [(0, '280.950')] +[2026-07-22 21:34:51,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5748.3). Total num frames: 2588672. Throughput: 0: 5825.4. Samples: 2615808. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:34:51,951][379328] Avg episode reward: [(0, '267.450')] +[2026-07-22 21:34:53,165][380295] Updated weights for policy 0, policy_version 5120 (0.0007) +[2026-07-22 21:34:56,951][379328] Fps is (10 sec: 4915.2, 60 sec: 5734.4, 300 sec: 5776.1). Total num frames: 2621440. Throughput: 0: 5814.1. Samples: 2631680. Policy #0 lag: (min: 6.0, avg: 8.7, max: 70.0) +[2026-07-22 21:34:56,952][379328] Avg episode reward: [(0, '275.050')] +[2026-07-22 21:35:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 2654208. Throughput: 0: 5825.4. Samples: 2667008. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:35:01,952][379328] Avg episode reward: [(0, '265.050')] +[2026-07-22 21:35:04,118][380295] Updated weights for policy 0, policy_version 5242 (0.0007) +[2026-07-22 21:35:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 2686976. Throughput: 0: 5848.2. Samples: 2702336. Policy #0 lag: (min: 9.0, avg: 11.7, max: 73.0) +[2026-07-22 21:35:06,951][379328] Avg episode reward: [(0, '268.950')] +[2026-07-22 21:35:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 2719744. Throughput: 0: 5836.8. Samples: 2720256. Policy #0 lag: (min: 12.0, avg: 14.6, max: 76.0) +[2026-07-22 21:35:11,952][379328] Avg episode reward: [(0, '283.300')] +[2026-07-22 21:35:14,943][380289] Signal inference workers to stop experience collection... (250 times) +[2026-07-22 21:35:14,973][380295] InferenceWorker_p0-w0: stopping experience collection (250 times) +[2026-07-22 21:35:15,121][380289] Signal inference workers to resume experience collection... (250 times) +[2026-07-22 21:35:15,122][380295] InferenceWorker_p0-w0: resuming experience collection (250 times) +[2026-07-22 21:35:15,299][380295] Updated weights for policy 0, policy_version 5360 (0.0007) +[2026-07-22 21:35:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 2752512. Throughput: 0: 5836.8. Samples: 2754048. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:35:16,951][379328] Avg episode reward: [(0, '293.300')] +[2026-07-22 21:35:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 2785280. Throughput: 0: 5836.8. Samples: 2788352. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:35:21,952][379328] Avg episode reward: [(0, '292.700')] +[2026-07-22 21:35:26,255][380295] Updated weights for policy 0, policy_version 5456 (0.0007) +[2026-07-22 21:35:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5803.8). Total num frames: 2818048. Throughput: 0: 5836.8. Samples: 2807808. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:35:26,951][379328] Avg episode reward: [(0, '288.550')] +[2026-07-22 21:35:31,951][379328] Fps is (10 sec: 4096.0, 60 sec: 5597.9, 300 sec: 5803.8). Total num frames: 2826240. Throughput: 0: 5825.4. Samples: 2843136. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:35:31,952][379328] Avg episode reward: [(0, '303.950')] +[2026-07-22 21:35:32,242][380289] Saving new best policy, reward=303.950! +[2026-07-22 21:35:32,585][380295] Updated weights for policy 0, policy_version 5568 (0.0007) +[2026-07-22 21:35:36,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5776.1). Total num frames: 2850816. Throughput: 0: 5848.2. Samples: 2878976. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:35:36,951][379328] Avg episode reward: [(0, '314.500')] +[2026-07-22 21:35:36,956][380289] Saving new best policy, reward=314.500! +[2026-07-22 21:35:41,951][379328] Fps is (10 sec: 5734.4, 60 sec: 5461.3, 300 sec: 5776.1). Total num frames: 2883584. Throughput: 0: 5848.2. Samples: 2894848. Policy #0 lag: (min: 11.0, avg: 14.0, max: 75.0) +[2026-07-22 21:35:41,952][379328] Avg episode reward: [(0, '323.800')] +[2026-07-22 21:35:41,956][380289] Saving new best policy, reward=323.800! +[2026-07-22 21:35:43,283][380295] Updated weights for policy 0, policy_version 5686 (0.0008) +[2026-07-22 21:35:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 5734.4, 300 sec: 5776.1). Total num frames: 2916352. Throughput: 0: 5882.3. Samples: 2931712. Policy #0 lag: (min: 31.0, avg: 33.8, max: 95.0) +[2026-07-22 21:35:46,952][379328] Avg episode reward: [(0, '310.900')] +[2026-07-22 21:35:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 2949120. Throughput: 0: 5939.2. Samples: 2969600. Policy #0 lag: (min: 63.0, avg: 65.7, max: 127.0) +[2026-07-22 21:35:51,951][379328] Avg episode reward: [(0, '290.050')] +[2026-07-22 21:35:53,631][380295] Updated weights for policy 0, policy_version 5792 (0.0007) +[2026-07-22 21:35:56,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 2981888. Throughput: 0: 5916.4. Samples: 2986496. Policy #0 lag: (min: 63.0, avg: 65.7, max: 127.0) +[2026-07-22 21:35:56,952][379328] Avg episode reward: [(0, '283.650')] +[2026-07-22 21:36:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 3014656. Throughput: 0: 5950.6. Samples: 3021824. Policy #0 lag: (min: 5.0, avg: 7.8, max: 69.0) +[2026-07-22 21:36:01,952][379328] Avg episode reward: [(0, '285.400')] +[2026-07-22 21:36:04,367][380295] Updated weights for policy 0, policy_version 5904 (0.0007) +[2026-07-22 21:36:06,951][379328] Fps is (10 sec: 6553.7, 60 sec: 6007.5, 300 sec: 5859.4). Total num frames: 3047424. Throughput: 0: 6007.5. Samples: 3058688. Policy #0 lag: (min: 31.0, avg: 33.7, max: 95.0) +[2026-07-22 21:36:06,951][379328] Avg episode reward: [(0, '278.700')] +[2026-07-22 21:36:10,425][380295] Updated weights for policy 0, policy_version 6010 (0.0007) +[2026-07-22 21:36:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3080192. Throughput: 0: 6018.8. Samples: 3078656. Policy #0 lag: (min: 47.0, avg: 49.7, max: 111.0) +[2026-07-22 21:36:11,952][379328] Avg episode reward: [(0, '286.900')] +[2026-07-22 21:36:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3112960. Throughput: 0: 6018.8. Samples: 3113984. Policy #0 lag: (min: 47.0, avg: 49.7, max: 111.0) +[2026-07-22 21:36:16,952][379328] Avg episode reward: [(0, '289.450')] +[2026-07-22 21:36:21,634][380295] Updated weights for policy 0, policy_version 6128 (0.0007) +[2026-07-22 21:36:21,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3145728. Throughput: 0: 5961.9. Samples: 3147264. Policy #0 lag: (min: 0.0, avg: 2.7, max: 64.0) +[2026-07-22 21:36:21,952][379328] Avg episode reward: [(0, '281.900')] +[2026-07-22 21:36:26,951][379328] Fps is (10 sec: 4915.2, 60 sec: 5734.4, 300 sec: 5831.6). Total num frames: 3162112. Throughput: 0: 5996.1. Samples: 3164672. Policy #0 lag: (min: 30.0, avg: 33.7, max: 94.0) +[2026-07-22 21:36:26,951][379328] Avg episode reward: [(0, '290.650')] +[2026-07-22 21:36:31,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5870.9, 300 sec: 5776.1). Total num frames: 3178496. Throughput: 0: 5950.6. Samples: 3199488. Policy #0 lag: (min: 30.0, avg: 33.7, max: 94.0) +[2026-07-22 21:36:31,952][379328] Avg episode reward: [(0, '284.100')] +[2026-07-22 21:36:32,560][380295] Updated weights for policy 0, policy_version 6224 (0.0007) +[2026-07-22 21:36:36,951][379328] Fps is (10 sec: 4915.2, 60 sec: 6007.5, 300 sec: 5776.1). Total num frames: 3211264. Throughput: 0: 5848.2. Samples: 3232768. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:36:36,951][379328] Avg episode reward: [(0, '291.650')] +[2026-07-22 21:36:38,988][380295] Updated weights for policy 0, policy_version 6336 (0.0007) +[2026-07-22 21:36:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5803.8). Total num frames: 3244032. Throughput: 0: 5836.8. Samples: 3249152. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:36:41,951][379328] Avg episode reward: [(0, '308.700')] +[2026-07-22 21:36:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3276800. Throughput: 0: 5870.9. Samples: 3286016. Policy #0 lag: (min: 63.0, avg: 65.8, max: 127.0) +[2026-07-22 21:36:46,952][379328] Avg episode reward: [(0, '294.850')] +[2026-07-22 21:36:48,976][380289] Signal inference workers to stop experience collection... (300 times) +[2026-07-22 21:36:49,027][380295] InferenceWorker_p0-w0: stopping experience collection (300 times) +[2026-07-22 21:36:49,194][380289] Signal inference workers to resume experience collection... (300 times) +[2026-07-22 21:36:49,194][380295] InferenceWorker_p0-w0: resuming experience collection (300 times) +[2026-07-22 21:36:49,371][380295] Updated weights for policy 0, policy_version 6432 (0.0007) +[2026-07-22 21:36:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3309568. Throughput: 0: 5870.9. Samples: 3322880. Policy #0 lag: (min: 63.0, avg: 65.8, max: 127.0) +[2026-07-22 21:36:51,951][379328] Avg episode reward: [(0, '296.850')] +[2026-07-22 21:36:55,232][380295] Updated weights for policy 0, policy_version 6528 (0.0006) +[2026-07-22 21:36:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3342336. Throughput: 0: 5859.6. Samples: 3342336. Policy #0 lag: (min: 9.0, avg: 12.7, max: 73.0) +[2026-07-22 21:36:56,951][379328] Avg episode reward: [(0, '300.000')] +[2026-07-22 21:37:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3375104. Throughput: 0: 5825.4. Samples: 3376128. Policy #0 lag: (min: 47.0, avg: 49.7, max: 111.0) +[2026-07-22 21:37:01,952][379328] Avg episode reward: [(0, '285.750')] +[2026-07-22 21:37:06,094][380295] Updated weights for policy 0, policy_version 6650 (0.0007) +[2026-07-22 21:37:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3407872. Throughput: 0: 5870.9. Samples: 3411456. Policy #0 lag: (min: 47.0, avg: 49.7, max: 111.0) +[2026-07-22 21:37:06,951][379328] Avg episode reward: [(0, '278.350')] +[2026-07-22 21:37:06,958][380289] Saving results/checkpoints/memory/rollout_teacher/demon_attack_teacher_fixed_l6_obs15_seed0/checkpoint_p0/checkpoint_000006656_3407872.pth... +[2026-07-22 21:37:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3440640. Throughput: 0: 5939.2. Samples: 3431936. Policy #0 lag: (min: 7.0, avg: 9.6, max: 71.0) +[2026-07-22 21:37:11,952][379328] Avg episode reward: [(0, '268.950')] +[2026-07-22 21:37:16,951][379328] Fps is (10 sec: 5734.4, 60 sec: 5870.9, 300 sec: 5859.4). Total num frames: 3465216. Throughput: 0: 5950.6. Samples: 3467264. Policy #0 lag: (min: 7.0, avg: 9.6, max: 71.0) +[2026-07-22 21:37:16,951][379328] Avg episode reward: [(0, '302.800')] +[2026-07-22 21:37:16,982][380295] Updated weights for policy 0, policy_version 6774 (0.0007) +[2026-07-22 21:37:21,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5831.6). Total num frames: 3473408. Throughput: 0: 6018.8. Samples: 3503616. Policy #0 lag: (min: 63.0, avg: 65.7, max: 127.0) +[2026-07-22 21:37:21,952][379328] Avg episode reward: [(0, '328.150')] +[2026-07-22 21:37:22,171][380289] Saving new best policy, reward=328.150! +[2026-07-22 21:37:26,951][379328] Fps is (10 sec: 4096.0, 60 sec: 5734.4, 300 sec: 5887.1). Total num frames: 3506176. Throughput: 0: 6018.8. Samples: 3520000. Policy #0 lag: (min: 63.0, avg: 65.7, max: 127.0) +[2026-07-22 21:37:26,951][379328] Avg episode reward: [(0, '341.150')] +[2026-07-22 21:37:26,956][380289] Saving new best policy, reward=341.150! +[2026-07-22 21:37:27,662][380295] Updated weights for policy 0, policy_version 6880 (0.0007) +[2026-07-22 21:37:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3538944. Throughput: 0: 6018.8. Samples: 3556864. Policy #0 lag: (min: 5.0, avg: 7.9, max: 69.0) +[2026-07-22 21:37:31,952][379328] Avg episode reward: [(0, '349.750')] +[2026-07-22 21:37:31,986][380289] Saving new best policy, reward=349.750! +[2026-07-22 21:37:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3571712. Throughput: 0: 5962.0. Samples: 3591168. Policy #0 lag: (min: 49.0, avg: 51.8, max: 113.0) +[2026-07-22 21:37:36,951][379328] Avg episode reward: [(0, '334.350')] +[2026-07-22 21:37:38,583][380295] Updated weights for policy 0, policy_version 6992 (0.0007) +[2026-07-22 21:37:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3604480. Throughput: 0: 5893.7. Samples: 3607552. Policy #0 lag: (min: 49.0, avg: 51.8, max: 113.0) +[2026-07-22 21:37:41,952][379328] Avg episode reward: [(0, '335.450')] +[2026-07-22 21:37:44,828][380295] Updated weights for policy 0, policy_version 7104 (0.0007) +[2026-07-22 21:37:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3637248. Throughput: 0: 5939.2. Samples: 3643392. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 21:37:46,951][379328] Avg episode reward: [(0, '317.700')] +[2026-07-22 21:37:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3670016. Throughput: 0: 5962.0. Samples: 3679744. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 21:37:51,951][379328] Avg episode reward: [(0, '347.500')] +[2026-07-22 21:37:55,781][380295] Updated weights for policy 0, policy_version 7223 (0.0007) +[2026-07-22 21:37:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3702784. Throughput: 0: 5927.8. Samples: 3698688. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:37:56,951][379328] Avg episode reward: [(0, '316.250')] +[2026-07-22 21:38:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5914.9). Total num frames: 3735552. Throughput: 0: 5950.6. Samples: 3735040. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:38:01,952][379328] Avg episode reward: [(0, '343.850')] +[2026-07-22 21:38:06,735][380295] Updated weights for policy 0, policy_version 7344 (0.0008) +[2026-07-22 21:38:06,951][379328] Fps is (10 sec: 5734.4, 60 sec: 5870.9, 300 sec: 5970.4). Total num frames: 3760128. Throughput: 0: 5893.7. Samples: 3768832. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:38:06,951][379328] Avg episode reward: [(0, '399.200')] +[2026-07-22 21:38:06,992][380289] Saving new best policy, reward=399.200! +[2026-07-22 21:38:11,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5887.1). Total num frames: 3768320. Throughput: 0: 5905.1. Samples: 3785728. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:38:11,952][379328] Avg episode reward: [(0, '414.850')] +[2026-07-22 21:38:12,252][380289] Saving new best policy, reward=414.850! +[2026-07-22 21:38:12,772][380295] Updated weights for policy 0, policy_version 7424 (0.0008) +[2026-07-22 21:38:16,951][379328] Fps is (10 sec: 4096.0, 60 sec: 5597.9, 300 sec: 5887.1). Total num frames: 3801088. Throughput: 0: 5905.1. Samples: 3822592. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:38:16,952][379328] Avg episode reward: [(0, '437.700')] +[2026-07-22 21:38:16,956][380289] Saving new best policy, reward=437.700! +[2026-07-22 21:38:17,471][380289] Signal inference workers to stop experience collection... (350 times) +[2026-07-22 21:38:17,500][380295] InferenceWorker_p0-w0: stopping experience collection (350 times) +[2026-07-22 21:38:17,610][380289] Signal inference workers to resume experience collection... (350 times) +[2026-07-22 21:38:17,610][380295] InferenceWorker_p0-w0: resuming experience collection (350 times) +[2026-07-22 21:38:21,951][379328] Fps is (10 sec: 6553.7, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3833856. Throughput: 0: 5916.4. Samples: 3857408. Policy #0 lag: (min: 12.0, avg: 14.9, max: 76.0) +[2026-07-22 21:38:21,951][379328] Avg episode reward: [(0, '417.550')] +[2026-07-22 21:38:23,617][380295] Updated weights for policy 0, policy_version 7542 (0.0007) +[2026-07-22 21:38:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3866624. Throughput: 0: 5905.1. Samples: 3873280. Policy #0 lag: (min: 12.0, avg: 14.9, max: 76.0) +[2026-07-22 21:38:26,951][379328] Avg episode reward: [(0, '389.000')] +[2026-07-22 21:38:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3899392. Throughput: 0: 5870.9. Samples: 3907584. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:38:31,952][379328] Avg episode reward: [(0, '381.950')] +[2026-07-22 21:38:34,839][380295] Updated weights for policy 0, policy_version 7664 (0.0007) +[2026-07-22 21:38:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3932160. Throughput: 0: 5836.8. Samples: 3942400. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:38:36,951][379328] Avg episode reward: [(0, '370.400')] +[2026-07-22 21:38:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3964928. Throughput: 0: 5848.2. Samples: 3961856. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:38:41,952][379328] Avg episode reward: [(0, '362.850')] +[2026-07-22 21:38:45,673][380295] Updated weights for policy 0, policy_version 7776 (0.0007) +[2026-07-22 21:38:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 3997696. Throughput: 0: 5848.2. Samples: 3998208. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:38:46,951][379328] Avg episode reward: [(0, '385.800')] +[2026-07-22 21:38:51,391][380295] Updated weights for policy 0, policy_version 7872 (0.0008) +[2026-07-22 21:38:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5942.7). Total num frames: 4030464. Throughput: 0: 5882.3. Samples: 4033536. Policy #0 lag: (min: 10.0, avg: 12.7, max: 74.0) +[2026-07-22 21:38:51,952][379328] Avg episode reward: [(0, '377.850')] +[2026-07-22 21:38:56,951][379328] Fps is (10 sec: 5734.4, 60 sec: 5870.9, 300 sec: 5970.4). Total num frames: 4055040. Throughput: 0: 5905.1. Samples: 4051456. Policy #0 lag: (min: 10.0, avg: 12.7, max: 74.0) +[2026-07-22 21:38:56,951][379328] Avg episode reward: [(0, '345.750')] +[2026-07-22 21:39:01,951][379328] Fps is (10 sec: 3276.8, 60 sec: 5461.3, 300 sec: 5887.1). Total num frames: 4063232. Throughput: 0: 5893.7. Samples: 4087808. Policy #0 lag: (min: 10.0, avg: 12.7, max: 74.0) +[2026-07-22 21:39:01,952][379328] Avg episode reward: [(0, '355.550')] +[2026-07-22 21:39:02,548][380295] Updated weights for policy 0, policy_version 7994 (0.0007) +[2026-07-22 21:39:06,951][379328] Fps is (10 sec: 4095.9, 60 sec: 5597.9, 300 sec: 5887.1). Total num frames: 4096000. Throughput: 0: 5870.9. Samples: 4121600. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:39:06,952][379328] Avg episode reward: [(0, '368.650')] +[2026-07-22 21:39:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 4128768. Throughput: 0: 5916.4. Samples: 4139520. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:39:11,952][379328] Avg episode reward: [(0, '353.200')] +[2026-07-22 21:39:13,157][380295] Updated weights for policy 0, policy_version 8096 (0.0007) +[2026-07-22 21:39:16,951][379328] Fps is (10 sec: 6553.7, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 4161536. Throughput: 0: 5950.6. Samples: 4175360. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:39:16,951][379328] Avg episode reward: [(0, '355.950')] +[2026-07-22 21:39:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 4194304. Throughput: 0: 5973.3. Samples: 4211200. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:39:21,952][379328] Avg episode reward: [(0, '372.150')] +[2026-07-22 21:39:24,046][380295] Updated weights for policy 0, policy_version 8208 (0.0009) +[2026-07-22 21:39:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 4227072. Throughput: 0: 5927.8. Samples: 4228608. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:39:26,951][379328] Avg episode reward: [(0, '367.300')] +[2026-07-22 21:39:30,141][380295] Updated weights for policy 0, policy_version 8320 (0.0008) +[2026-07-22 21:39:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 4259840. Throughput: 0: 5905.1. Samples: 4263936. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:39:31,952][379328] Avg episode reward: [(0, '372.100')] +[2026-07-22 21:39:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 4292608. Throughput: 0: 5916.4. Samples: 4299776. Policy #0 lag: (min: 7.0, avg: 9.6, max: 71.0) +[2026-07-22 21:39:36,951][379328] Avg episode reward: [(0, '417.550')] +[2026-07-22 21:39:40,722][380295] Updated weights for policy 0, policy_version 8442 (0.0007) +[2026-07-22 21:39:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5942.7). Total num frames: 4325376. Throughput: 0: 5996.1. Samples: 4321280. Policy #0 lag: (min: 7.0, avg: 9.6, max: 71.0) +[2026-07-22 21:39:41,952][379328] Avg episode reward: [(0, '412.700')] +[2026-07-22 21:39:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 4358144. Throughput: 0: 5996.1. Samples: 4357632. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:39:46,951][379328] Avg episode reward: [(0, '417.050')] +[2026-07-22 21:39:50,873][380289] Signal inference workers to stop experience collection... (400 times) +[2026-07-22 21:39:50,903][380295] InferenceWorker_p0-w0: stopping experience collection (400 times) +[2026-07-22 21:39:51,051][380289] Signal inference workers to resume experience collection... (400 times) +[2026-07-22 21:39:51,051][380295] InferenceWorker_p0-w0: resuming experience collection (400 times) +[2026-07-22 21:39:51,053][380295] Updated weights for policy 0, policy_version 8544 (0.0009) +[2026-07-22 21:39:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 4390912. Throughput: 0: 6030.2. Samples: 4392960. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:39:51,951][379328] Avg episode reward: [(0, '413.150')] +[2026-07-22 21:39:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6144.0, 300 sec: 5998.2). Total num frames: 4423680. Throughput: 0: 6075.7. Samples: 4412928. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:39:56,952][379328] Avg episode reward: [(0, '437.350')] +[2026-07-22 21:40:01,918][380295] Updated weights for policy 0, policy_version 8656 (0.0007) +[2026-07-22 21:40:01,951][379328] Fps is (10 sec: 4096.0, 60 sec: 6144.0, 300 sec: 5914.9). Total num frames: 4431872. Throughput: 0: 6064.3. Samples: 4448256. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:40:01,952][379328] Avg episode reward: [(0, '464.250')] +[2026-07-22 21:40:02,279][380289] Saving new best policy, reward=464.250! +[2026-07-22 21:40:06,951][379328] Fps is (10 sec: 3276.8, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 4456448. Throughput: 0: 6041.6. Samples: 4483072. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:40:06,951][379328] Avg episode reward: [(0, '533.950')] +[2026-07-22 21:40:06,957][380289] Saving new best policy, reward=533.950! +[2026-07-22 21:40:08,091][380295] Updated weights for policy 0, policy_version 8768 (0.0008) +[2026-07-22 21:40:11,951][379328] Fps is (10 sec: 5734.4, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 4489216. Throughput: 0: 6041.6. Samples: 4500480. Policy #0 lag: (min: 5.0, avg: 7.8, max: 69.0) +[2026-07-22 21:40:11,952][379328] Avg episode reward: [(0, '560.950')] +[2026-07-22 21:40:11,958][380289] Saving new best policy, reward=560.950! +[2026-07-22 21:40:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 4521984. Throughput: 0: 6064.3. Samples: 4536832. Policy #0 lag: (min: 5.0, avg: 7.8, max: 69.0) +[2026-07-22 21:40:16,952][379328] Avg episode reward: [(0, '586.950')] +[2026-07-22 21:40:16,957][380289] Saving new best policy, reward=586.950! +[2026-07-22 21:40:18,913][380295] Updated weights for policy 0, policy_version 8890 (0.0007) +[2026-07-22 21:40:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 4554752. Throughput: 0: 6075.7. Samples: 4573184. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 21:40:21,952][379328] Avg episode reward: [(0, '588.100')] +[2026-07-22 21:40:21,980][380289] Saving new best policy, reward=588.100! +[2026-07-22 21:40:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5970.4). Total num frames: 4587520. Throughput: 0: 5996.1. Samples: 4591104. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 21:40:26,951][379328] Avg episode reward: [(0, '546.700')] +[2026-07-22 21:40:29,364][380295] Updated weights for policy 0, policy_version 9008 (0.0008) +[2026-07-22 21:40:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 4620288. Throughput: 0: 5996.1. Samples: 4627456. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:40:31,952][379328] Avg episode reward: [(0, '541.300')] +[2026-07-22 21:40:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 4653056. Throughput: 0: 6030.2. Samples: 4664320. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:40:36,952][379328] Avg episode reward: [(0, '498.650')] +[2026-07-22 21:40:40,059][380295] Updated weights for policy 0, policy_version 9104 (0.0008) +[2026-07-22 21:40:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 4685824. Throughput: 0: 5996.1. Samples: 4682752. Policy #0 lag: (min: 9.0, avg: 11.8, max: 73.0) +[2026-07-22 21:40:41,951][379328] Avg episode reward: [(0, '491.000')] +[2026-07-22 21:40:46,015][380295] Updated weights for policy 0, policy_version 9210 (0.0007) +[2026-07-22 21:40:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 4718592. Throughput: 0: 6018.8. Samples: 4719104. Policy #0 lag: (min: 9.0, avg: 11.8, max: 73.0) +[2026-07-22 21:40:46,952][379328] Avg episode reward: [(0, '461.400')] +[2026-07-22 21:40:51,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 4751360. Throughput: 0: 5996.1. Samples: 4752896. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:40:51,952][379328] Avg episode reward: [(0, '499.900')] +[2026-07-22 21:40:56,468][380295] Updated weights for policy 0, policy_version 9312 (0.0009) +[2026-07-22 21:40:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 4784128. Throughput: 0: 6030.2. Samples: 4771840. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:40:56,951][379328] Avg episode reward: [(0, '516.600')] +[2026-07-22 21:41:01,951][379328] Fps is (10 sec: 5734.4, 60 sec: 6280.5, 300 sec: 5970.4). Total num frames: 4808704. Throughput: 0: 6087.1. Samples: 4810752. Policy #0 lag: (min: 5.0, avg: 7.8, max: 69.0) +[2026-07-22 21:41:01,952][379328] Avg episode reward: [(0, '514.050')] +[2026-07-22 21:41:02,068][380295] Updated weights for policy 0, policy_version 9408 (0.0008) +[2026-07-22 21:41:06,951][379328] Fps is (10 sec: 4096.0, 60 sec: 6144.0, 300 sec: 5914.9). Total num frames: 4825088. Throughput: 0: 6098.5. Samples: 4847616. Policy #0 lag: (min: 5.0, avg: 7.8, max: 69.0) +[2026-07-22 21:41:06,951][379328] Avg episode reward: [(0, '516.250')] +[2026-07-22 21:41:11,951][379328] Fps is (10 sec: 4096.0, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 4849664. Throughput: 0: 6053.0. Samples: 4863488. Policy #0 lag: (min: 5.0, avg: 7.8, max: 69.0) +[2026-07-22 21:41:11,952][379328] Avg episode reward: [(0, '542.150')] +[2026-07-22 21:41:12,943][380295] Updated weights for policy 0, policy_version 9526 (0.0008) +[2026-07-22 21:41:16,951][379328] Fps is (10 sec: 5734.4, 60 sec: 6007.5, 300 sec: 5887.1). Total num frames: 4882432. Throughput: 0: 6075.7. Samples: 4900864. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:41:16,951][379328] Avg episode reward: [(0, '532.400')] +[2026-07-22 21:41:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5942.7). Total num frames: 4915200. Throughput: 0: 6098.5. Samples: 4938752. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:41:21,952][379328] Avg episode reward: [(0, '500.850')] +[2026-07-22 21:41:22,592][380289] Signal inference workers to stop experience collection... (450 times) +[2026-07-22 21:41:22,622][380295] InferenceWorker_p0-w0: stopping experience collection (450 times) +[2026-07-22 21:41:22,775][380289] Signal inference workers to resume experience collection... (450 times) +[2026-07-22 21:41:22,776][380295] InferenceWorker_p0-w0: resuming experience collection (450 times) +[2026-07-22 21:41:23,136][380295] Updated weights for policy 0, policy_version 9648 (0.0009) +[2026-07-22 21:41:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 4947968. Throughput: 0: 6087.1. Samples: 4956672. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:41:26,952][379328] Avg episode reward: [(0, '498.400')] +[2026-07-22 21:41:31,951][379328] Fps is (10 sec: 6553.7, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 4980736. Throughput: 0: 6121.2. Samples: 4994560. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:41:31,952][379328] Avg episode reward: [(0, '546.600')] +[2026-07-22 21:41:33,718][380295] Updated weights for policy 0, policy_version 9760 (0.0009) +[2026-07-22 21:41:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5013504. Throughput: 0: 6155.4. Samples: 5029888. Policy #0 lag: (min: 3.0, avg: 5.8, max: 67.0) +[2026-07-22 21:41:36,952][379328] Avg episode reward: [(0, '595.500')] +[2026-07-22 21:41:36,992][380289] Saving new best policy, reward=595.500! +[2026-07-22 21:41:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5046272. Throughput: 0: 6121.2. Samples: 5047296. Policy #0 lag: (min: 3.0, avg: 5.8, max: 67.0) +[2026-07-22 21:41:41,952][379328] Avg episode reward: [(0, '572.650')] +[2026-07-22 21:41:44,689][380295] Updated weights for policy 0, policy_version 9872 (0.0010) +[2026-07-22 21:41:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5079040. Throughput: 0: 6018.8. Samples: 5081600. Policy #0 lag: (min: 3.0, avg: 5.6, max: 67.0) +[2026-07-22 21:41:46,951][379328] Avg episode reward: [(0, '604.150')] +[2026-07-22 21:41:46,957][380289] Saving new best policy, reward=604.150! +[2026-07-22 21:41:50,569][380295] Updated weights for policy 0, policy_version 9984 (0.0008) +[2026-07-22 21:41:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5111808. Throughput: 0: 6064.4. Samples: 5120512. Policy #0 lag: (min: 3.0, avg: 5.6, max: 67.0) +[2026-07-22 21:41:51,951][379328] Avg episode reward: [(0, '584.200')] +[2026-07-22 21:41:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5144576. Throughput: 0: 6166.8. Samples: 5140992. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:41:56,952][379328] Avg episode reward: [(0, '599.050')] +[2026-07-22 21:42:00,763][380295] Updated weights for policy 0, policy_version 10110 (0.0008) +[2026-07-22 21:42:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6144.0, 300 sec: 5998.2). Total num frames: 5177344. Throughput: 0: 6166.8. Samples: 5178368. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:42:01,951][379328] Avg episode reward: [(0, '645.350')] +[2026-07-22 21:42:01,957][380289] Saving new best policy, reward=645.350! +[2026-07-22 21:42:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6417.1, 300 sec: 5998.2). Total num frames: 5210112. Throughput: 0: 6087.1. Samples: 5212672. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 21:42:06,952][379328] Avg episode reward: [(0, '680.900')] +[2026-07-22 21:42:06,957][380289] Saving new best policy, reward=680.900! +[2026-07-22 21:42:11,168][380295] Updated weights for policy 0, policy_version 10224 (0.0008) +[2026-07-22 21:42:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6026.0). Total num frames: 5242880. Throughput: 0: 6144.0. Samples: 5233152. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 21:42:11,952][379328] Avg episode reward: [(0, '690.600')] +[2026-07-22 21:42:11,957][380289] Saving new best policy, reward=690.600! +[2026-07-22 21:42:16,951][379328] Fps is (10 sec: 5734.4, 60 sec: 6417.1, 300 sec: 6081.5). Total num frames: 5267456. Throughput: 0: 6132.6. Samples: 5270528. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:42:16,951][379328] Avg episode reward: [(0, '726.200')] +[2026-07-22 21:42:16,956][380295] Updated weights for policy 0, policy_version 10301 (0.0008) +[2026-07-22 21:42:16,993][380289] Saving new best policy, reward=726.200! +[2026-07-22 21:42:21,951][379328] Fps is (10 sec: 4915.2, 60 sec: 6280.5, 300 sec: 6053.7). Total num frames: 5292032. Throughput: 0: 6166.8. Samples: 5307392. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:42:21,951][379328] Avg episode reward: [(0, '810.150')] +[2026-07-22 21:42:22,354][380289] Saving new best policy, reward=810.150! +[2026-07-22 21:42:26,951][379328] Fps is (10 sec: 4096.0, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5308416. Throughput: 0: 6155.4. Samples: 5324288. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:42:26,952][379328] Avg episode reward: [(0, '774.650')] +[2026-07-22 21:42:27,470][380295] Updated weights for policy 0, policy_version 10416 (0.0008) +[2026-07-22 21:42:31,951][379328] Fps is (10 sec: 4915.2, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5341184. Throughput: 0: 6212.3. Samples: 5361152. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:42:31,951][379328] Avg episode reward: [(0, '775.700')] +[2026-07-22 21:42:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5373952. Throughput: 0: 6189.5. Samples: 5399040. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:42:36,952][379328] Avg episode reward: [(0, '766.300')] +[2026-07-22 21:42:37,926][380295] Updated weights for policy 0, policy_version 10528 (0.0007) +[2026-07-22 21:42:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5406720. Throughput: 0: 6132.6. Samples: 5416960. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:42:41,951][379328] Avg episode reward: [(0, '773.850')] +[2026-07-22 21:42:43,807][380295] Updated weights for policy 0, policy_version 10622 (0.0008) +[2026-07-22 21:42:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5439488. Throughput: 0: 6087.1. Samples: 5452288. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:42:46,952][379328] Avg episode reward: [(0, '795.900')] +[2026-07-22 21:42:48,733][380289] Signal inference workers to stop experience collection... (500 times) +[2026-07-22 21:42:48,766][380295] InferenceWorker_p0-w0: stopping experience collection (500 times) +[2026-07-22 21:42:48,947][380289] Signal inference workers to resume experience collection... (500 times) +[2026-07-22 21:42:48,947][380295] InferenceWorker_p0-w0: resuming experience collection (500 times) +[2026-07-22 21:42:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5472256. Throughput: 0: 6132.6. Samples: 5488640. Policy #0 lag: (min: 15.0, avg: 18.7, max: 79.0) +[2026-07-22 21:42:51,951][379328] Avg episode reward: [(0, '776.750')] +[2026-07-22 21:42:54,413][380295] Updated weights for policy 0, policy_version 10742 (0.0008) +[2026-07-22 21:42:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5505024. Throughput: 0: 6087.1. Samples: 5507072. Policy #0 lag: (min: 15.0, avg: 18.7, max: 79.0) +[2026-07-22 21:42:56,952][379328] Avg episode reward: [(0, '788.750')] +[2026-07-22 21:43:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 5537792. Throughput: 0: 6030.2. Samples: 5541888. Policy #0 lag: (min: 12.0, avg: 14.7, max: 76.0) +[2026-07-22 21:43:01,952][379328] Avg episode reward: [(0, '813.300')] +[2026-07-22 21:43:01,956][380289] Saving new best policy, reward=813.300! +[2026-07-22 21:43:04,818][380295] Updated weights for policy 0, policy_version 10848 (0.0008) +[2026-07-22 21:43:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6109.3). Total num frames: 5570560. Throughput: 0: 6064.4. Samples: 5580288. Policy #0 lag: (min: 12.0, avg: 14.7, max: 76.0) +[2026-07-22 21:43:06,951][379328] Avg episode reward: [(0, '852.900')] +[2026-07-22 21:43:06,957][380289] Saving new best policy, reward=852.900! +[2026-07-22 21:43:10,660][380295] Updated weights for policy 0, policy_version 10944 (0.0008) +[2026-07-22 21:43:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6109.3). Total num frames: 5603328. Throughput: 0: 6132.6. Samples: 5600256. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:43:11,952][379328] Avg episode reward: [(0, '827.600')] +[2026-07-22 21:43:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6144.0, 300 sec: 6109.3). Total num frames: 5636096. Throughput: 0: 6121.2. Samples: 5636608. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:43:16,952][379328] Avg episode reward: [(0, '851.500')] +[2026-07-22 21:43:21,117][380295] Updated weights for policy 0, policy_version 11062 (0.0007) +[2026-07-22 21:43:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6280.5, 300 sec: 6109.3). Total num frames: 5668864. Throughput: 0: 6075.7. Samples: 5672448. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:43:21,951][379328] Avg episode reward: [(0, '898.850')] +[2026-07-22 21:43:21,957][380289] Saving new best policy, reward=898.850! +[2026-07-22 21:43:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6109.3). Total num frames: 5701632. Throughput: 0: 6144.0. Samples: 5693440. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:43:26,952][379328] Avg episode reward: [(0, '913.300')] +[2026-07-22 21:43:26,956][380289] Saving new best policy, reward=913.300! +[2026-07-22 21:43:31,354][380295] Updated weights for policy 0, policy_version 11168 (0.0008) +[2026-07-22 21:43:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6109.3). Total num frames: 5734400. Throughput: 0: 6166.8. Samples: 5729792. Policy #0 lag: (min: 0.0, avg: 3.6, max: 64.0) +[2026-07-22 21:43:31,952][379328] Avg episode reward: [(0, '863.400')] +[2026-07-22 21:43:36,951][379328] Fps is (10 sec: 5734.4, 60 sec: 6417.1, 300 sec: 6081.5). Total num frames: 5758976. Throughput: 0: 6200.9. Samples: 5767680. Policy #0 lag: (min: 0.0, avg: 3.6, max: 64.0) +[2026-07-22 21:43:36,951][379328] Avg episode reward: [(0, '859.650')] +[2026-07-22 21:43:37,078][380295] Updated weights for policy 0, policy_version 11264 (0.0008) +[2026-07-22 21:43:41,951][379328] Fps is (10 sec: 3276.8, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5767168. Throughput: 0: 6178.1. Samples: 5785088. Policy #0 lag: (min: 0.0, avg: 3.6, max: 64.0) +[2026-07-22 21:43:41,951][379328] Avg episode reward: [(0, '924.250')] +[2026-07-22 21:43:42,152][380289] Saving new best policy, reward=924.250! +[2026-07-22 21:43:46,951][379328] Fps is (10 sec: 4096.0, 60 sec: 6007.5, 300 sec: 5998.2). Total num frames: 5799936. Throughput: 0: 6178.1. Samples: 5819904. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:43:46,952][379328] Avg episode reward: [(0, '899.550')] +[2026-07-22 21:43:47,896][380295] Updated weights for policy 0, policy_version 11378 (0.0008) +[2026-07-22 21:43:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6026.0). Total num frames: 5832704. Throughput: 0: 6200.9. Samples: 5859328. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:43:51,952][379328] Avg episode reward: [(0, '898.950')] +[2026-07-22 21:43:53,182][380295] Updated weights for policy 0, policy_version 11456 (0.0007) +[2026-07-22 21:43:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6109.3). Total num frames: 5865472. Throughput: 0: 6166.8. Samples: 5877760. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 21:43:56,951][379328] Avg episode reward: [(0, '883.000')] +[2026-07-22 21:44:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6109.3). Total num frames: 5898240. Throughput: 0: 6200.9. Samples: 5915648. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 21:44:01,952][379328] Avg episode reward: [(0, '842.000')] +[2026-07-22 21:44:03,062][380295] Updated weights for policy 0, policy_version 11582 (0.0007) +[2026-07-22 21:44:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6109.3). Total num frames: 5931008. Throughput: 0: 6337.4. Samples: 5957632. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:44:06,951][379328] Avg episode reward: [(0, '842.100')] +[2026-07-22 21:44:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6109.3). Total num frames: 5963776. Throughput: 0: 6235.0. Samples: 5974016. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:44:11,951][379328] Avg episode reward: [(0, '831.550')] +[2026-07-22 21:44:13,467][380295] Updated weights for policy 0, policy_version 11696 (0.0007) +[2026-07-22 21:44:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6109.3). Total num frames: 5996544. Throughput: 0: 6246.4. Samples: 6010880. Policy #0 lag: (min: 10.0, avg: 12.8, max: 74.0) +[2026-07-22 21:44:16,952][379328] Avg episode reward: [(0, '830.450')] +[2026-07-22 21:44:18,133][380289] Signal inference workers to stop experience collection... (550 times) +[2026-07-22 21:44:18,161][380295] InferenceWorker_p0-w0: stopping experience collection (550 times) +[2026-07-22 21:44:18,311][380289] Signal inference workers to resume experience collection... (550 times) +[2026-07-22 21:44:18,312][380295] InferenceWorker_p0-w0: resuming experience collection (550 times) +[2026-07-22 21:44:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6109.3). Total num frames: 6029312. Throughput: 0: 6280.5. Samples: 6050304. Policy #0 lag: (min: 10.0, avg: 12.8, max: 74.0) +[2026-07-22 21:44:21,952][379328] Avg episode reward: [(0, '797.800')] +[2026-07-22 21:44:23,271][380295] Updated weights for policy 0, policy_version 11808 (0.0008) +[2026-07-22 21:44:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6109.3). Total num frames: 6062080. Throughput: 0: 6337.4. Samples: 6070272. Policy #0 lag: (min: 8.0, avg: 10.7, max: 72.0) +[2026-07-22 21:44:26,952][379328] Avg episode reward: [(0, '846.350')] +[2026-07-22 21:44:28,736][380295] Updated weights for policy 0, policy_version 11904 (0.0008) +[2026-07-22 21:44:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6007.5, 300 sec: 6109.3). Total num frames: 6094848. Throughput: 0: 6439.8. Samples: 6109696. Policy #0 lag: (min: 8.0, avg: 10.7, max: 72.0) +[2026-07-22 21:44:31,951][379328] Avg episode reward: [(0, '867.600')] +[2026-07-22 21:44:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6144.0, 300 sec: 6109.3). Total num frames: 6127616. Throughput: 0: 6417.1. Samples: 6148096. Policy #0 lag: (min: 8.0, avg: 10.8, max: 72.0) +[2026-07-22 21:44:36,952][379328] Avg episode reward: [(0, '884.550')] +[2026-07-22 21:44:38,869][380295] Updated weights for policy 0, policy_version 12022 (0.0008) +[2026-07-22 21:44:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6109.3). Total num frames: 6160384. Throughput: 0: 6405.7. Samples: 6166016. Policy #0 lag: (min: 8.0, avg: 10.8, max: 72.0) +[2026-07-22 21:44:41,952][379328] Avg episode reward: [(0, '898.550')] +[2026-07-22 21:44:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6109.3). Total num frames: 6193152. Throughput: 0: 6417.1. Samples: 6204416. Policy #0 lag: (min: 4.0, avg: 6.7, max: 68.0) +[2026-07-22 21:44:46,952][379328] Avg episode reward: [(0, '922.150')] +[2026-07-22 21:44:48,689][380295] Updated weights for policy 0, policy_version 12128 (0.0007) +[2026-07-22 21:44:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6109.3). Total num frames: 6225920. Throughput: 0: 6371.6. Samples: 6244352. Policy #0 lag: (min: 4.0, avg: 6.7, max: 68.0) +[2026-07-22 21:44:51,952][379328] Avg episode reward: [(0, '930.550')] +[2026-07-22 21:44:51,956][380289] Saving new best policy, reward=930.550! +[2026-07-22 21:44:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6192.6). Total num frames: 6258688. Throughput: 0: 6405.7. Samples: 6262272. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:44:56,952][379328] Avg episode reward: [(0, '921.450')] +[2026-07-22 21:44:58,766][380295] Updated weights for policy 0, policy_version 12240 (0.0008) +[2026-07-22 21:45:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6220.4). Total num frames: 6291456. Throughput: 0: 6439.8. Samples: 6300672. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:45:01,951][379328] Avg episode reward: [(0, '948.250')] +[2026-07-22 21:45:01,957][380289] Saving new best policy, reward=948.250! +[2026-07-22 21:45:04,834][380295] Updated weights for policy 0, policy_version 12350 (0.0008) +[2026-07-22 21:45:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6220.4). Total num frames: 6324224. Throughput: 0: 6394.3. Samples: 6338048. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:45:06,951][379328] Avg episode reward: [(0, '964.400')] +[2026-07-22 21:45:06,956][380289] Saving new best policy, reward=964.400! +[2026-07-22 21:45:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6220.4). Total num frames: 6356992. Throughput: 0: 6394.3. Samples: 6358016. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:45:11,952][379328] Avg episode reward: [(0, '957.400')] +[2026-07-22 21:45:14,518][380295] Updated weights for policy 0, policy_version 12464 (0.0007) +[2026-07-22 21:45:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6220.4). Total num frames: 6389760. Throughput: 0: 6382.9. Samples: 6396928. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:45:16,952][379328] Avg episode reward: [(0, '942.800')] +[2026-07-22 21:45:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6220.4). Total num frames: 6422528. Throughput: 0: 6371.6. Samples: 6434816. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:45:21,951][379328] Avg episode reward: [(0, '902.400')] +[2026-07-22 21:45:24,866][380295] Updated weights for policy 0, policy_version 12592 (0.0007) +[2026-07-22 21:45:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6220.4). Total num frames: 6455296. Throughput: 0: 6439.8. Samples: 6455808. Policy #0 lag: (min: 0.0, avg: 2.6, max: 64.0) +[2026-07-22 21:45:26,951][379328] Avg episode reward: [(0, '1016.400')] +[2026-07-22 21:45:26,956][380289] Saving new best policy, reward=1016.400! +[2026-07-22 21:45:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6220.4). Total num frames: 6488064. Throughput: 0: 6337.4. Samples: 6489600. Policy #0 lag: (min: 0.0, avg: 2.6, max: 64.0) +[2026-07-22 21:45:31,952][379328] Avg episode reward: [(0, '991.000')] +[2026-07-22 21:45:35,386][380295] Updated weights for policy 0, policy_version 12720 (0.0009) +[2026-07-22 21:45:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6220.4). Total num frames: 6520832. Throughput: 0: 6314.7. Samples: 6528512. Policy #0 lag: (min: 11.0, avg: 13.6, max: 75.0) +[2026-07-22 21:45:36,951][379328] Avg episode reward: [(0, '985.350')] +[2026-07-22 21:45:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6220.4). Total num frames: 6553600. Throughput: 0: 6382.9. Samples: 6549504. Policy #0 lag: (min: 11.0, avg: 13.6, max: 75.0) +[2026-07-22 21:45:41,951][379328] Avg episode reward: [(0, '999.650')] +[2026-07-22 21:45:45,143][380289] Signal inference workers to stop experience collection... (600 times) +[2026-07-22 21:45:45,170][380295] InferenceWorker_p0-w0: stopping experience collection (600 times) +[2026-07-22 21:45:45,328][380289] Signal inference workers to resume experience collection... (600 times) +[2026-07-22 21:45:45,329][380295] InferenceWorker_p0-w0: resuming experience collection (600 times) +[2026-07-22 21:45:45,330][380295] Updated weights for policy 0, policy_version 12816 (0.0007) +[2026-07-22 21:45:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6220.4). Total num frames: 6586368. Throughput: 0: 6360.2. Samples: 6586880. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:45:46,951][379328] Avg episode reward: [(0, '1000.750')] +[2026-07-22 21:45:50,779][380295] Updated weights for policy 0, policy_version 12928 (0.0007) +[2026-07-22 21:45:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6220.4). Total num frames: 6619136. Throughput: 0: 6405.7. Samples: 6626304. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:45:51,952][379328] Avg episode reward: [(0, '1019.750')] +[2026-07-22 21:45:51,957][380289] Saving new best policy, reward=1019.750! +[2026-07-22 21:45:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6248.1). Total num frames: 6651904. Throughput: 0: 6428.4. Samples: 6647296. Policy #0 lag: (min: 5.0, avg: 7.7, max: 69.0) +[2026-07-22 21:45:56,952][379328] Avg episode reward: [(0, '1037.900')] +[2026-07-22 21:45:56,998][380289] Saving new best policy, reward=1037.900! +[2026-07-22 21:46:00,742][380295] Updated weights for policy 0, policy_version 13046 (0.0007) +[2026-07-22 21:46:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6303.7). Total num frames: 6684672. Throughput: 0: 6417.1. Samples: 6685696. Policy #0 lag: (min: 5.0, avg: 7.7, max: 69.0) +[2026-07-22 21:46:01,951][379328] Avg episode reward: [(0, '1043.300')] +[2026-07-22 21:46:01,956][380289] Saving new best policy, reward=1043.300! +[2026-07-22 21:46:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6331.4). Total num frames: 6717440. Throughput: 0: 6428.5. Samples: 6724096. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:46:06,952][379328] Avg episode reward: [(0, '1059.950')] +[2026-07-22 21:46:06,957][380289] Saving new best policy, reward=1059.950! +[2026-07-22 21:46:10,287][380295] Updated weights for policy 0, policy_version 13152 (0.0006) +[2026-07-22 21:46:11,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6553.6, 300 sec: 6331.4). Total num frames: 6750208. Throughput: 0: 6451.2. Samples: 6746112. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:46:11,952][379328] Avg episode reward: [(0, '1139.600')] +[2026-07-22 21:46:11,957][380289] Saving new best policy, reward=1139.600! +[2026-07-22 21:46:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6331.4). Total num frames: 6782976. Throughput: 0: 6565.0. Samples: 6785024. Policy #0 lag: (min: 31.0, avg: 33.8, max: 95.0) +[2026-07-22 21:46:16,952][379328] Avg episode reward: [(0, '1135.450')] +[2026-07-22 21:46:19,982][380295] Updated weights for policy 0, policy_version 13264 (0.0007) +[2026-07-22 21:46:21,951][379328] Fps is (10 sec: 6553.7, 60 sec: 6553.6, 300 sec: 6331.4). Total num frames: 6815744. Throughput: 0: 6610.5. Samples: 6825984. Policy #0 lag: (min: 31.0, avg: 33.8, max: 95.0) +[2026-07-22 21:46:21,951][379328] Avg episode reward: [(0, '1154.950')] +[2026-07-22 21:46:21,956][380289] Saving new best policy, reward=1154.950! +[2026-07-22 21:46:25,047][380295] Updated weights for policy 0, policy_version 13362 (0.0006) +[2026-07-22 21:46:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6331.4). Total num frames: 6848512. Throughput: 0: 6621.9. Samples: 6847488. Policy #0 lag: (min: 42.0, avg: 44.8, max: 106.0) +[2026-07-22 21:46:26,952][379328] Avg episode reward: [(0, '1161.300')] +[2026-07-22 21:46:26,956][380289] Saving new best policy, reward=1161.300! +[2026-07-22 21:46:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6331.4). Total num frames: 6881280. Throughput: 0: 6633.2. Samples: 6885376. Policy #0 lag: (min: 42.0, avg: 44.8, max: 106.0) +[2026-07-22 21:46:31,952][379328] Avg episode reward: [(0, '1221.650')] +[2026-07-22 21:46:31,957][380289] Saving new best policy, reward=1221.650! +[2026-07-22 21:46:34,625][380295] Updated weights for policy 0, policy_version 13472 (0.0007) +[2026-07-22 21:46:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6331.4). Total num frames: 6914048. Throughput: 0: 6667.4. Samples: 6926336. Policy #0 lag: (min: 60.0, avg: 62.7, max: 124.0) +[2026-07-22 21:46:36,951][379328] Avg episode reward: [(0, '1269.650')] +[2026-07-22 21:46:36,956][380289] Saving new best policy, reward=1269.650! +[2026-07-22 21:46:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6331.4). Total num frames: 6946816. Throughput: 0: 6667.4. Samples: 6947328. Policy #0 lag: (min: 60.0, avg: 62.7, max: 124.0) +[2026-07-22 21:46:41,951][379328] Avg episode reward: [(0, '1283.450')] +[2026-07-22 21:46:41,958][380289] Saving new best policy, reward=1283.450! +[2026-07-22 21:46:44,667][380295] Updated weights for policy 0, policy_version 13584 (0.0007) +[2026-07-22 21:46:46,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6553.6, 300 sec: 6331.4). Total num frames: 6979584. Throughput: 0: 6599.1. Samples: 6982656. Policy #0 lag: (min: 63.0, avg: 65.8, max: 127.0) +[2026-07-22 21:46:46,952][379328] Avg episode reward: [(0, '1284.250')] +[2026-07-22 21:46:46,980][380289] Saving new best policy, reward=1284.250! +[2026-07-22 21:46:50,190][380295] Updated weights for policy 0, policy_version 13694 (0.0007) +[2026-07-22 21:46:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6331.4). Total num frames: 7012352. Throughput: 0: 6644.6. Samples: 7023104. Policy #0 lag: (min: 63.0, avg: 65.8, max: 127.0) +[2026-07-22 21:46:51,951][379328] Avg episode reward: [(0, '1302.700')] +[2026-07-22 21:46:51,956][380289] Saving new best policy, reward=1302.700! +[2026-07-22 21:46:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6331.4). Total num frames: 7045120. Throughput: 0: 6633.3. Samples: 7044608. Policy #0 lag: (min: 63.0, avg: 65.8, max: 127.0) +[2026-07-22 21:46:56,952][379328] Avg episode reward: [(0, '1353.500')] +[2026-07-22 21:46:56,956][380289] Saving new best policy, reward=1353.500! +[2026-07-22 21:47:00,047][380295] Updated weights for policy 0, policy_version 13814 (0.0008) +[2026-07-22 21:47:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6331.4). Total num frames: 7077888. Throughput: 0: 6599.1. Samples: 7081984. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:47:01,951][379328] Avg episode reward: [(0, '1350.000')] +[2026-07-22 21:47:04,452][380289] Signal inference workers to stop experience collection... (650 times) +[2026-07-22 21:47:04,481][380295] InferenceWorker_p0-w0: stopping experience collection (650 times) +[2026-07-22 21:47:04,628][380289] Signal inference workers to resume experience collection... (650 times) +[2026-07-22 21:47:04,628][380295] InferenceWorker_p0-w0: resuming experience collection (650 times) +[2026-07-22 21:47:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6331.4). Total num frames: 7110656. Throughput: 0: 6610.5. Samples: 7123456. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:47:06,952][379328] Avg episode reward: [(0, '1399.650')] +[2026-07-22 21:47:06,956][380289] Saving results/checkpoints/memory/rollout_teacher/demon_attack_teacher_fixed_l6_obs15_seed0/checkpoint_p0/checkpoint_000013888_7110656.pth... +[2026-07-22 21:47:06,979][380289] Saving new best policy, reward=1399.650! +[2026-07-22 21:47:09,648][380295] Updated weights for policy 0, policy_version 13920 (0.0007) +[2026-07-22 21:47:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6359.2). Total num frames: 7143424. Throughput: 0: 6587.7. Samples: 7143936. Policy #0 lag: (min: 42.0, avg: 44.7, max: 106.0) +[2026-07-22 21:47:11,952][379328] Avg episode reward: [(0, '1455.000')] +[2026-07-22 21:47:11,957][380289] Saving new best policy, reward=1455.000! +[2026-07-22 21:47:14,978][380295] Updated weights for policy 0, policy_version 14010 (0.0007) +[2026-07-22 21:47:16,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6553.6, 300 sec: 6387.0). Total num frames: 7176192. Throughput: 0: 6576.3. Samples: 7181312. Policy #0 lag: (min: 42.0, avg: 44.7, max: 106.0) +[2026-07-22 21:47:16,952][379328] Avg episode reward: [(0, '1444.900')] +[2026-07-22 21:47:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7208960. Throughput: 0: 6519.5. Samples: 7219712. Policy #0 lag: (min: 42.0, avg: 44.7, max: 106.0) +[2026-07-22 21:47:21,952][379328] Avg episode reward: [(0, '1444.150')] +[2026-07-22 21:47:24,986][380295] Updated weights for policy 0, policy_version 14128 (0.0007) +[2026-07-22 21:47:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7241728. Throughput: 0: 6530.8. Samples: 7241216. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:47:26,952][379328] Avg episode reward: [(0, '1426.550')] +[2026-07-22 21:47:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7274496. Throughput: 0: 6565.0. Samples: 7278080. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:47:31,952][379328] Avg episode reward: [(0, '1490.350')] +[2026-07-22 21:47:32,025][380289] Saving new best policy, reward=1490.350! +[2026-07-22 21:47:35,000][380295] Updated weights for policy 0, policy_version 14240 (0.0007) +[2026-07-22 21:47:36,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7307264. Throughput: 0: 6530.8. Samples: 7316992. Policy #0 lag: (min: 37.0, avg: 39.7, max: 101.0) +[2026-07-22 21:47:36,952][379328] Avg episode reward: [(0, '1462.000')] +[2026-07-22 21:47:40,241][380295] Updated weights for policy 0, policy_version 14330 (0.0010) +[2026-07-22 21:47:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7340032. Throughput: 0: 6553.6. Samples: 7339520. Policy #0 lag: (min: 37.0, avg: 39.7, max: 101.0) +[2026-07-22 21:47:41,952][379328] Avg episode reward: [(0, '1566.600')] +[2026-07-22 21:47:41,957][380289] Saving new best policy, reward=1566.600! +[2026-07-22 21:47:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7372800. Throughput: 0: 6519.4. Samples: 7375360. Policy #0 lag: (min: 37.0, avg: 39.7, max: 101.0) +[2026-07-22 21:47:46,952][379328] Avg episode reward: [(0, '1611.850')] +[2026-07-22 21:47:47,013][380289] Saving new best policy, reward=1611.850! +[2026-07-22 21:47:50,090][380295] Updated weights for policy 0, policy_version 14448 (0.0007) +[2026-07-22 21:47:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7405568. Throughput: 0: 6485.3. Samples: 7415296. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:47:51,951][379328] Avg episode reward: [(0, '1613.700')] +[2026-07-22 21:47:51,957][380289] Saving new best policy, reward=1613.700! +[2026-07-22 21:47:56,951][379328] Fps is (10 sec: 6553.7, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7438336. Throughput: 0: 6496.7. Samples: 7436288. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:47:56,952][379328] Avg episode reward: [(0, '1619.550')] +[2026-07-22 21:47:56,958][380289] Saving new best policy, reward=1619.550! +[2026-07-22 21:47:59,662][380295] Updated weights for policy 0, policy_version 14544 (0.0008) +[2026-07-22 21:48:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7471104. Throughput: 0: 6519.5. Samples: 7474688. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:48:01,952][379328] Avg episode reward: [(0, '1710.150')] +[2026-07-22 21:48:01,957][380289] Saving new best policy, reward=1710.150! +[2026-07-22 21:48:05,346][380295] Updated weights for policy 0, policy_version 14656 (0.0007) +[2026-07-22 21:48:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7503872. Throughput: 0: 6519.5. Samples: 7513088. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:48:06,952][379328] Avg episode reward: [(0, '1719.000')] +[2026-07-22 21:48:06,957][380289] Saving new best policy, reward=1719.000! +[2026-07-22 21:48:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7536640. Throughput: 0: 6553.6. Samples: 7536128. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:48:11,951][379328] Avg episode reward: [(0, '1766.850')] +[2026-07-22 21:48:11,956][380289] Saving new best policy, reward=1766.850! +[2026-07-22 21:48:14,858][380295] Updated weights for policy 0, policy_version 14770 (0.0008) +[2026-07-22 21:48:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7569408. Throughput: 0: 6599.1. Samples: 7575040. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:48:16,952][379328] Avg episode reward: [(0, '1777.600')] +[2026-07-22 21:48:16,959][380289] Saving new best policy, reward=1777.600! +[2026-07-22 21:48:20,026][380295] Updated weights for policy 0, policy_version 14848 (0.0008) +[2026-07-22 21:48:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7602176. Throughput: 0: 6621.9. Samples: 7614976. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 21:48:21,952][379328] Avg episode reward: [(0, '1715.350')] +[2026-07-22 21:48:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6442.5). Total num frames: 7634944. Throughput: 0: 6587.7. Samples: 7635968. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 21:48:26,952][379328] Avg episode reward: [(0, '1674.000')] +[2026-07-22 21:48:29,172][380289] Signal inference workers to stop experience collection... (700 times) +[2026-07-22 21:48:29,202][380295] InferenceWorker_p0-w0: stopping experience collection (700 times) +[2026-07-22 21:48:29,384][380289] Signal inference workers to resume experience collection... (700 times) +[2026-07-22 21:48:29,385][380295] InferenceWorker_p0-w0: resuming experience collection (700 times) +[2026-07-22 21:48:29,667][380295] Updated weights for policy 0, policy_version 14962 (0.0008) +[2026-07-22 21:48:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6470.3). Total num frames: 7667712. Throughput: 0: 6621.9. Samples: 7673344. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 21:48:31,952][379328] Avg episode reward: [(0, '1686.050')] +[2026-07-22 21:48:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 7700480. Throughput: 0: 6610.5. Samples: 7712768. Policy #0 lag: (min: 13.0, avg: 15.8, max: 77.0) +[2026-07-22 21:48:36,952][379328] Avg episode reward: [(0, '1671.600')] +[2026-07-22 21:48:39,560][380295] Updated weights for policy 0, policy_version 15072 (0.0008) +[2026-07-22 21:48:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 7733248. Throughput: 0: 6610.5. Samples: 7733760. Policy #0 lag: (min: 13.0, avg: 15.8, max: 77.0) +[2026-07-22 21:48:41,952][379328] Avg episode reward: [(0, '1695.750')] +[2026-07-22 21:48:45,336][380295] Updated weights for policy 0, policy_version 15168 (0.0008) +[2026-07-22 21:48:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 7766016. Throughput: 0: 6553.6. Samples: 7769600. Policy #0 lag: (min: 63.0, avg: 65.6, max: 127.0) +[2026-07-22 21:48:46,952][379328] Avg episode reward: [(0, '1723.950')] +[2026-07-22 21:48:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 7798784. Throughput: 0: 6621.9. Samples: 7811072. Policy #0 lag: (min: 63.0, avg: 65.6, max: 127.0) +[2026-07-22 21:48:51,952][379328] Avg episode reward: [(0, '1728.950')] +[2026-07-22 21:48:54,927][380295] Updated weights for policy 0, policy_version 15290 (0.0009) +[2026-07-22 21:48:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 7831552. Throughput: 0: 6576.4. Samples: 7832064. Policy #0 lag: (min: 63.0, avg: 65.6, max: 127.0) +[2026-07-22 21:48:56,951][379328] Avg episode reward: [(0, '1692.500')] +[2026-07-22 21:49:01,951][379328] Fps is (10 sec: 6553.7, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 7864320. Throughput: 0: 6576.4. Samples: 7870976. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:49:01,951][379328] Avg episode reward: [(0, '1730.900')] +[2026-07-22 21:49:04,638][380295] Updated weights for policy 0, policy_version 15408 (0.0008) +[2026-07-22 21:49:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 7897088. Throughput: 0: 6576.4. Samples: 7910912. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:49:06,952][379328] Avg episode reward: [(0, '1817.000')] +[2026-07-22 21:49:06,956][380289] Saving new best policy, reward=1817.000! +[2026-07-22 21:49:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 7929856. Throughput: 0: 6542.2. Samples: 7930368. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:49:11,952][379328] Avg episode reward: [(0, '1852.300')] +[2026-07-22 21:49:11,956][380289] Saving new best policy, reward=1852.300! +[2026-07-22 21:49:14,109][380295] Updated weights for policy 0, policy_version 15504 (0.0008) +[2026-07-22 21:49:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 7962624. Throughput: 0: 6599.1. Samples: 7970304. Policy #0 lag: (min: 15.0, avg: 17.2, max: 79.0) +[2026-07-22 21:49:16,952][379328] Avg episode reward: [(0, '1909.700')] +[2026-07-22 21:49:16,957][380289] Saving new best policy, reward=1909.700! +[2026-07-22 21:49:19,195][380295] Updated weights for policy 0, policy_version 15610 (0.0009) +[2026-07-22 21:49:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 7995392. Throughput: 0: 6712.9. Samples: 8014848. Policy #0 lag: (min: 15.0, avg: 17.2, max: 79.0) +[2026-07-22 21:49:21,951][379328] Avg episode reward: [(0, '1915.050')] +[2026-07-22 21:49:21,956][380289] Saving new best policy, reward=1915.050! +[2026-07-22 21:49:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8028160. Throughput: 0: 6644.6. Samples: 8032768. Policy #0 lag: (min: 15.0, avg: 17.2, max: 79.0) +[2026-07-22 21:49:26,952][379328] Avg episode reward: [(0, '1897.400')] +[2026-07-22 21:49:28,919][380295] Updated weights for policy 0, policy_version 15728 (0.0008) +[2026-07-22 21:49:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8060928. Throughput: 0: 6724.3. Samples: 8072192. Policy #0 lag: (min: 1.0, avg: 3.8, max: 65.0) +[2026-07-22 21:49:31,952][379328] Avg episode reward: [(0, '1972.600')] +[2026-07-22 21:49:31,957][380289] Saving new best policy, reward=1972.600! +[2026-07-22 21:49:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8093696. Throughput: 0: 6667.4. Samples: 8111104. Policy #0 lag: (min: 1.0, avg: 3.8, max: 65.0) +[2026-07-22 21:49:36,952][379328] Avg episode reward: [(0, '2081.750')] +[2026-07-22 21:49:36,956][380289] Saving new best policy, reward=2081.750! +[2026-07-22 21:49:38,690][380295] Updated weights for policy 0, policy_version 15824 (0.0007) +[2026-07-22 21:49:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8126464. Throughput: 0: 6610.5. Samples: 8129536. Policy #0 lag: (min: 1.0, avg: 3.8, max: 65.0) +[2026-07-22 21:49:41,952][379328] Avg episode reward: [(0, '2127.700')] +[2026-07-22 21:49:41,957][380289] Saving new best policy, reward=2127.700! +[2026-07-22 21:49:44,177][380295] Updated weights for policy 0, policy_version 15930 (0.0007) +[2026-07-22 21:49:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8159232. Throughput: 0: 6633.2. Samples: 8169472. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:49:46,951][379328] Avg episode reward: [(0, '2153.200')] +[2026-07-22 21:49:46,956][380289] Saving new best policy, reward=2153.200! +[2026-07-22 21:49:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8192000. Throughput: 0: 6610.5. Samples: 8208384. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:49:51,952][379328] Avg episode reward: [(0, '2160.350')] +[2026-07-22 21:49:51,957][380289] Saving new best policy, reward=2160.350! +[2026-07-22 21:49:53,602][380289] Signal inference workers to stop experience collection... (750 times) +[2026-07-22 21:49:53,629][380295] InferenceWorker_p0-w0: stopping experience collection (750 times) +[2026-07-22 21:49:53,819][380289] Signal inference workers to resume experience collection... (750 times) +[2026-07-22 21:49:53,819][380295] InferenceWorker_p0-w0: resuming experience collection (750 times) +[2026-07-22 21:49:54,034][380295] Updated weights for policy 0, policy_version 16032 (0.0008) +[2026-07-22 21:49:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8224768. Throughput: 0: 6587.7. Samples: 8226816. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:49:56,952][379328] Avg episode reward: [(0, '2185.350')] +[2026-07-22 21:49:56,957][380289] Saving new best policy, reward=2185.350! +[2026-07-22 21:49:59,362][380295] Updated weights for policy 0, policy_version 16128 (0.0007) +[2026-07-22 21:50:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8257536. Throughput: 0: 6610.5. Samples: 8267776. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:50:01,952][379328] Avg episode reward: [(0, '2130.200')] +[2026-07-22 21:50:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8290304. Throughput: 0: 6485.3. Samples: 8306688. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:50:06,951][379328] Avg episode reward: [(0, '2190.450')] +[2026-07-22 21:50:06,957][380289] Saving new best policy, reward=2190.450! +[2026-07-22 21:50:09,161][380295] Updated weights for policy 0, policy_version 16242 (0.0011) +[2026-07-22 21:50:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8323072. Throughput: 0: 6519.5. Samples: 8326144. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:50:11,952][379328] Avg episode reward: [(0, '2221.200')] +[2026-07-22 21:50:11,957][380289] Saving new best policy, reward=2221.200! +[2026-07-22 21:50:16,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8355840. Throughput: 0: 6565.0. Samples: 8367616. Policy #0 lag: (min: 10.0, avg: 12.9, max: 74.0) +[2026-07-22 21:50:16,952][379328] Avg episode reward: [(0, '2233.400')] +[2026-07-22 21:50:16,957][380289] Saving new best policy, reward=2233.400! +[2026-07-22 21:50:18,628][380295] Updated weights for policy 0, policy_version 16352 (0.0009) +[2026-07-22 21:50:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8388608. Throughput: 0: 6599.1. Samples: 8408064. Policy #0 lag: (min: 10.0, avg: 12.9, max: 74.0) +[2026-07-22 21:50:21,951][379328] Avg episode reward: [(0, '2160.100')] +[2026-07-22 21:50:24,050][380295] Updated weights for policy 0, policy_version 16448 (0.0008) +[2026-07-22 21:50:26,951][379328] Fps is (10 sec: 6553.7, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8421376. Throughput: 0: 6610.5. Samples: 8427008. Policy #0 lag: (min: 10.0, avg: 12.9, max: 74.0) +[2026-07-22 21:50:26,951][379328] Avg episode reward: [(0, '2153.650')] +[2026-07-22 21:50:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8454144. Throughput: 0: 6599.1. Samples: 8466432. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:50:31,952][379328] Avg episode reward: [(0, '2216.200')] +[2026-07-22 21:50:33,979][380295] Updated weights for policy 0, policy_version 16570 (0.0007) +[2026-07-22 21:50:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8486912. Throughput: 0: 6633.2. Samples: 8506880. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:50:36,952][379328] Avg episode reward: [(0, '2177.850')] +[2026-07-22 21:50:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8519680. Throughput: 0: 6621.9. Samples: 8524800. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:50:41,952][379328] Avg episode reward: [(0, '2229.250')] +[2026-07-22 21:50:43,892][380295] Updated weights for policy 0, policy_version 16690 (0.0008) +[2026-07-22 21:50:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8552448. Throughput: 0: 6610.5. Samples: 8565248. Policy #0 lag: (min: 13.0, avg: 15.6, max: 77.0) +[2026-07-22 21:50:46,952][379328] Avg episode reward: [(0, '2182.600')] +[2026-07-22 21:50:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8585216. Throughput: 0: 6644.6. Samples: 8605696. Policy #0 lag: (min: 13.0, avg: 15.6, max: 77.0) +[2026-07-22 21:50:51,951][379328] Avg episode reward: [(0, '2154.300')] +[2026-07-22 21:50:53,379][380295] Updated weights for policy 0, policy_version 16800 (0.0007) +[2026-07-22 21:50:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8617984. Throughput: 0: 6644.6. Samples: 8625152. Policy #0 lag: (min: 13.0, avg: 15.6, max: 77.0) +[2026-07-22 21:50:56,952][379328] Avg episode reward: [(0, '1961.500')] +[2026-07-22 21:51:01,952][379328] Fps is (10 sec: 6553.3, 60 sec: 6553.5, 300 sec: 6553.6). Total num frames: 8650752. Throughput: 0: 6621.8. Samples: 8665600. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:51:01,953][379328] Avg episode reward: [(0, '2081.250')] +[2026-07-22 21:51:03,185][380295] Updated weights for policy 0, policy_version 16912 (0.0007) +[2026-07-22 21:51:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8683520. Throughput: 0: 6576.4. Samples: 8704000. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:51:06,952][379328] Avg episode reward: [(0, '2039.550')] +[2026-07-22 21:51:08,614][380295] Updated weights for policy 0, policy_version 17014 (0.0007) +[2026-07-22 21:51:11,951][379328] Fps is (10 sec: 6553.9, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8716288. Throughput: 0: 6599.1. Samples: 8723968. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:51:11,952][379328] Avg episode reward: [(0, '1976.400')] +[2026-07-22 21:51:13,144][380289] Signal inference workers to stop experience collection... (800 times) +[2026-07-22 21:51:13,174][380295] InferenceWorker_p0-w0: stopping experience collection (800 times) +[2026-07-22 21:51:13,325][380289] Signal inference workers to resume experience collection... (800 times) +[2026-07-22 21:51:13,325][380295] InferenceWorker_p0-w0: resuming experience collection (800 times) +[2026-07-22 21:51:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8749056. Throughput: 0: 6621.9. Samples: 8764416. Policy #0 lag: (min: 11.0, avg: 14.0, max: 75.0) +[2026-07-22 21:51:16,952][379328] Avg episode reward: [(0, '2029.450')] +[2026-07-22 21:51:17,891][380295] Updated weights for policy 0, policy_version 17104 (0.0007) +[2026-07-22 21:51:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8781824. Throughput: 0: 6621.9. Samples: 8804864. Policy #0 lag: (min: 11.0, avg: 14.0, max: 75.0) +[2026-07-22 21:51:21,952][379328] Avg episode reward: [(0, '2144.150')] +[2026-07-22 21:51:23,454][380295] Updated weights for policy 0, policy_version 17210 (0.0008) +[2026-07-22 21:51:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8814592. Throughput: 0: 6644.6. Samples: 8823808. Policy #0 lag: (min: 11.0, avg: 14.0, max: 75.0) +[2026-07-22 21:51:26,952][379328] Avg episode reward: [(0, '2271.650')] +[2026-07-22 21:51:26,957][380289] Saving new best policy, reward=2271.650! +[2026-07-22 21:51:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8847360. Throughput: 0: 6678.8. Samples: 8865792. Policy #0 lag: (min: 5.0, avg: 7.8, max: 69.0) +[2026-07-22 21:51:31,951][379328] Avg episode reward: [(0, '2373.900')] +[2026-07-22 21:51:31,956][380289] Saving new best policy, reward=2373.900! +[2026-07-22 21:51:32,772][380295] Updated weights for policy 0, policy_version 17312 (0.0007) +[2026-07-22 21:51:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8880128. Throughput: 0: 6656.0. Samples: 8905216. Policy #0 lag: (min: 5.0, avg: 7.8, max: 69.0) +[2026-07-22 21:51:36,952][379328] Avg episode reward: [(0, '2530.550')] +[2026-07-22 21:51:36,957][380289] Saving new best policy, reward=2530.550! +[2026-07-22 21:51:38,195][380295] Updated weights for policy 0, policy_version 17408 (0.0007) +[2026-07-22 21:51:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6553.6). Total num frames: 8912896. Throughput: 0: 6656.0. Samples: 8924672. Policy #0 lag: (min: 5.0, avg: 7.8, max: 69.0) +[2026-07-22 21:51:41,952][379328] Avg episode reward: [(0, '2547.200')] +[2026-07-22 21:51:41,957][380289] Saving new best policy, reward=2547.200! +[2026-07-22 21:51:46,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6690.1, 300 sec: 6581.4). Total num frames: 8953856. Throughput: 0: 6735.7. Samples: 8968704. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:51:46,951][379328] Avg episode reward: [(0, '2620.150')] +[2026-07-22 21:51:47,258][380289] Saving new best policy, reward=2620.150! +[2026-07-22 21:51:47,259][380295] Updated weights for policy 0, policy_version 17520 (0.0009) +[2026-07-22 21:51:51,951][379328] Fps is (10 sec: 9011.2, 60 sec: 6963.2, 300 sec: 6636.9). Total num frames: 9003008. Throughput: 0: 6815.3. Samples: 9010688. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:51:51,951][379328] Avg episode reward: [(0, '2709.050')] +[2026-07-22 21:51:52,214][380289] Saving new best policy, reward=2709.050! +[2026-07-22 21:51:56,457][380295] Updated weights for policy 0, policy_version 17616 (0.0008) +[2026-07-22 21:51:56,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6963.2, 300 sec: 6636.9). Total num frames: 9035776. Throughput: 0: 6803.9. Samples: 9030144. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:51:56,952][379328] Avg episode reward: [(0, '2841.700')] +[2026-07-22 21:51:57,111][380289] Saving new best policy, reward=2841.700! +[2026-07-22 21:52:01,333][380295] Updated weights for policy 0, policy_version 17712 (0.0007) +[2026-07-22 21:52:01,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.8, 300 sec: 6664.7). Total num frames: 9076736. Throughput: 0: 6860.8. Samples: 9073152. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:52:01,952][379328] Avg episode reward: [(0, '2836.600')] +[2026-07-22 21:52:06,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 6664.7). Total num frames: 9109504. Throughput: 0: 6815.3. Samples: 9111552. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:52:06,951][379328] Avg episode reward: [(0, '2795.350')] +[2026-07-22 21:52:10,891][380295] Updated weights for policy 0, policy_version 17808 (0.0007) +[2026-07-22 21:52:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6664.7). Total num frames: 9142272. Throughput: 0: 6860.8. Samples: 9132544. Policy #0 lag: (min: 3.0, avg: 5.7, max: 67.0) +[2026-07-22 21:52:11,952][379328] Avg episode reward: [(0, '2790.450')] +[2026-07-22 21:52:16,271][380295] Updated weights for policy 0, policy_version 17914 (0.0007) +[2026-07-22 21:52:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6664.7). Total num frames: 9175040. Throughput: 0: 6838.0. Samples: 9173504. Policy #0 lag: (min: 3.0, avg: 5.7, max: 67.0) +[2026-07-22 21:52:16,952][379328] Avg episode reward: [(0, '2853.550')] +[2026-07-22 21:52:16,957][380289] Saving new best policy, reward=2853.550! +[2026-07-22 21:52:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6664.7). Total num frames: 9207808. Throughput: 0: 6781.2. Samples: 9210368. Policy #0 lag: (min: 3.0, avg: 5.7, max: 67.0) +[2026-07-22 21:52:21,952][379328] Avg episode reward: [(0, '2759.150')] +[2026-07-22 21:52:25,777][380295] Updated weights for policy 0, policy_version 18016 (0.0007) +[2026-07-22 21:52:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6664.7). Total num frames: 9240576. Throughput: 0: 6838.1. Samples: 9232384. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:52:26,952][379328] Avg episode reward: [(0, '2791.850')] +[2026-07-22 21:52:30,882][380295] Updated weights for policy 0, policy_version 18112 (0.0008) +[2026-07-22 21:52:31,951][379328] Fps is (10 sec: 6553.7, 60 sec: 7099.7, 300 sec: 6664.7). Total num frames: 9273344. Throughput: 0: 6792.5. Samples: 9274368. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:52:31,951][379328] Avg episode reward: [(0, '2750.200')] +[2026-07-22 21:52:34,811][380289] Signal inference workers to stop experience collection... (850 times) +[2026-07-22 21:52:34,840][380295] InferenceWorker_p0-w0: stopping experience collection (850 times) +[2026-07-22 21:52:34,951][380289] Signal inference workers to resume experience collection... (850 times) +[2026-07-22 21:52:34,951][380295] InferenceWorker_p0-w0: resuming experience collection (850 times) +[2026-07-22 21:52:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6664.7). Total num frames: 9306112. Throughput: 0: 6792.5. Samples: 9316352. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:52:36,951][379328] Avg episode reward: [(0, '2646.150')] +[2026-07-22 21:52:40,161][380295] Updated weights for policy 0, policy_version 18230 (0.0007) +[2026-07-22 21:52:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6664.7). Total num frames: 9338880. Throughput: 0: 6849.4. Samples: 9338368. Policy #0 lag: (min: 8.0, avg: 10.8, max: 72.0) +[2026-07-22 21:52:41,952][379328] Avg episode reward: [(0, '2561.600')] +[2026-07-22 21:52:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 6664.7). Total num frames: 9371648. Throughput: 0: 6758.4. Samples: 9377280. Policy #0 lag: (min: 8.0, avg: 10.8, max: 72.0) +[2026-07-22 21:52:46,952][379328] Avg episode reward: [(0, '2603.150')] +[2026-07-22 21:52:49,543][380295] Updated weights for policy 0, policy_version 18336 (0.0006) +[2026-07-22 21:52:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6690.1, 300 sec: 6664.7). Total num frames: 9404416. Throughput: 0: 6815.3. Samples: 9418240. Policy #0 lag: (min: 8.0, avg: 10.8, max: 72.0) +[2026-07-22 21:52:51,952][379328] Avg episode reward: [(0, '2663.950')] +[2026-07-22 21:52:54,877][380295] Updated weights for policy 0, policy_version 18432 (0.0007) +[2026-07-22 21:52:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6690.1, 300 sec: 6664.7). Total num frames: 9437184. Throughput: 0: 6792.5. Samples: 9438208. Policy #0 lag: (min: 1.0, avg: 3.7, max: 65.0) +[2026-07-22 21:52:56,952][379328] Avg episode reward: [(0, '2668.350')] +[2026-07-22 21:53:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6664.7). Total num frames: 9469952. Throughput: 0: 6781.2. Samples: 9478656. Policy #0 lag: (min: 1.0, avg: 3.7, max: 65.0) +[2026-07-22 21:53:01,952][379328] Avg episode reward: [(0, '2614.250')] +[2026-07-22 21:53:04,346][380295] Updated weights for policy 0, policy_version 18550 (0.0007) +[2026-07-22 21:53:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6664.7). Total num frames: 9502720. Throughput: 0: 6849.4. Samples: 9518592. Policy #0 lag: (min: 1.0, avg: 3.7, max: 65.0) +[2026-07-22 21:53:06,952][379328] Avg episode reward: [(0, '2665.750')] +[2026-07-22 21:53:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6664.7). Total num frames: 9535488. Throughput: 0: 6792.5. Samples: 9538048. Policy #0 lag: (min: 3.0, avg: 5.7, max: 67.0) +[2026-07-22 21:53:11,952][379328] Avg episode reward: [(0, '2673.300')] +[2026-07-22 21:53:14,006][380295] Updated weights for policy 0, policy_version 18674 (0.0008) +[2026-07-22 21:53:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6664.7). Total num frames: 9568256. Throughput: 0: 6803.9. Samples: 9580544. Policy #0 lag: (min: 3.0, avg: 5.7, max: 67.0) +[2026-07-22 21:53:16,952][379328] Avg episode reward: [(0, '2732.600')] +[2026-07-22 21:53:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6664.7). Total num frames: 9601024. Throughput: 0: 6792.5. Samples: 9622016. Policy #0 lag: (min: 3.0, avg: 5.7, max: 67.0) +[2026-07-22 21:53:21,952][379328] Avg episode reward: [(0, '2845.150')] +[2026-07-22 21:53:23,333][380295] Updated weights for policy 0, policy_version 18784 (0.0007) +[2026-07-22 21:53:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6664.7). Total num frames: 9633792. Throughput: 0: 6712.9. Samples: 9640448. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:53:26,952][379328] Avg episode reward: [(0, '2940.200')] +[2026-07-22 21:53:26,956][380289] Saving new best policy, reward=2940.200! +[2026-07-22 21:53:28,282][380295] Updated weights for policy 0, policy_version 18877 (0.0007) +[2026-07-22 21:53:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6664.7). Total num frames: 9666560. Throughput: 0: 6860.8. Samples: 9686016. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:53:31,952][379328] Avg episode reward: [(0, '2944.400')] +[2026-07-22 21:53:31,958][380289] Saving new best policy, reward=2944.400! +[2026-07-22 21:53:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6664.7). Total num frames: 9699328. Throughput: 0: 6906.3. Samples: 9729024. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:53:36,951][379328] Avg episode reward: [(0, '2852.100')] +[2026-07-22 21:53:37,161][380295] Updated weights for policy 0, policy_version 18976 (0.0007) +[2026-07-22 21:53:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6664.7). Total num frames: 9732096. Throughput: 0: 6894.9. Samples: 9748480. Policy #0 lag: (min: 14.0, avg: 17.6, max: 78.0) +[2026-07-22 21:53:41,952][379328] Avg episode reward: [(0, '2938.250')] +[2026-07-22 21:53:42,617][380295] Updated weights for policy 0, policy_version 19072 (0.0007) +[2026-07-22 21:53:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6664.7). Total num frames: 9764864. Throughput: 0: 6872.2. Samples: 9787904. Policy #0 lag: (min: 14.0, avg: 17.6, max: 78.0) +[2026-07-22 21:53:46,952][379328] Avg episode reward: [(0, '2988.200')] +[2026-07-22 21:53:47,191][380289] Saving new best policy, reward=2988.200! +[2026-07-22 21:53:51,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6690.1, 300 sec: 6692.4). Total num frames: 9805824. Throughput: 0: 6883.6. Samples: 9828352. Policy #0 lag: (min: 5.0, avg: 8.3, max: 69.0) +[2026-07-22 21:53:51,951][379328] Avg episode reward: [(0, '3029.500')] +[2026-07-22 21:53:52,176][380289] Saving new best policy, reward=3029.500! +[2026-07-22 21:53:52,177][380295] Updated weights for policy 0, policy_version 19184 (0.0008) +[2026-07-22 21:53:56,565][380289] Signal inference workers to stop experience collection... (900 times) +[2026-07-22 21:53:56,616][380295] InferenceWorker_p0-w0: stopping experience collection (900 times) +[2026-07-22 21:53:56,740][380289] Signal inference workers to resume experience collection... (900 times) +[2026-07-22 21:53:56,740][380295] InferenceWorker_p0-w0: resuming experience collection (900 times) +[2026-07-22 21:53:56,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6690.1, 300 sec: 6692.4). Total num frames: 9838592. Throughput: 0: 6860.8. Samples: 9846784. Policy #0 lag: (min: 5.0, avg: 8.3, max: 69.0) +[2026-07-22 21:53:56,952][379328] Avg episode reward: [(0, '3050.450')] +[2026-07-22 21:53:57,439][380289] Saving new best policy, reward=3050.450! +[2026-07-22 21:54:01,567][380295] Updated weights for policy 0, policy_version 19280 (0.0008) +[2026-07-22 21:54:01,951][379328] Fps is (10 sec: 8191.9, 60 sec: 6963.2, 300 sec: 6748.0). Total num frames: 9887744. Throughput: 0: 6838.0. Samples: 9888256. Policy #0 lag: (min: 5.0, avg: 8.3, max: 69.0) +[2026-07-22 21:54:01,952][379328] Avg episode reward: [(0, '3006.500')] +[2026-07-22 21:54:06,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6826.7, 300 sec: 6720.2). Total num frames: 9912320. Throughput: 0: 6781.2. Samples: 9927168. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:54:06,951][379328] Avg episode reward: [(0, '2865.050')] +[2026-07-22 21:54:07,297][380295] Updated weights for policy 0, policy_version 19386 (0.0008) +[2026-07-22 21:54:11,951][379328] Fps is (10 sec: 4096.0, 60 sec: 6553.6, 300 sec: 6664.7). Total num frames: 9928704. Throughput: 0: 6769.8. Samples: 9945088. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:54:11,952][379328] Avg episode reward: [(0, '2733.600')] +[2026-07-22 21:54:16,696][380295] Updated weights for policy 0, policy_version 19488 (0.0008) +[2026-07-22 21:54:16,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6963.2, 300 sec: 6748.0). Total num frames: 9986048. Throughput: 0: 6667.4. Samples: 9986048. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:54:16,952][379328] Avg episode reward: [(0, '2782.350')] +[2026-07-22 21:54:21,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6826.7, 300 sec: 6720.2). Total num frames: 10010624. Throughput: 0: 6599.1. Samples: 10025984. Policy #0 lag: (min: 8.0, avg: 10.7, max: 72.0) +[2026-07-22 21:54:21,952][379328] Avg episode reward: [(0, '2719.400')] +[2026-07-22 21:54:22,351][380295] Updated weights for policy 0, policy_version 19584 (0.0007) +[2026-07-22 21:54:26,951][379328] Fps is (10 sec: 5734.4, 60 sec: 6826.7, 300 sec: 6720.2). Total num frames: 10043392. Throughput: 0: 6599.1. Samples: 10045440. Policy #0 lag: (min: 8.0, avg: 10.7, max: 72.0) +[2026-07-22 21:54:26,951][379328] Avg episode reward: [(0, '2715.800')] +[2026-07-22 21:54:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6826.7, 300 sec: 6720.2). Total num frames: 10076160. Throughput: 0: 6576.3. Samples: 10083840. Policy #0 lag: (min: 8.0, avg: 10.7, max: 72.0) +[2026-07-22 21:54:31,952][379328] Avg episode reward: [(0, '2785.500')] +[2026-07-22 21:54:32,157][380295] Updated weights for policy 0, policy_version 19702 (0.0009) +[2026-07-22 21:54:36,951][379328] Fps is (10 sec: 8192.1, 60 sec: 7099.7, 300 sec: 6775.8). Total num frames: 10125312. Throughput: 0: 6621.9. Samples: 10126336. Policy #0 lag: (min: 4.0, avg: 6.8, max: 68.0) +[2026-07-22 21:54:36,952][379328] Avg episode reward: [(0, '2793.350')] +[2026-07-22 21:54:41,185][380295] Updated weights for policy 0, policy_version 19792 (0.0008) +[2026-07-22 21:54:41,951][379328] Fps is (10 sec: 8192.0, 60 sec: 7099.7, 300 sec: 6775.8). Total num frames: 10158080. Throughput: 0: 6644.6. Samples: 10145792. Policy #0 lag: (min: 4.0, avg: 6.8, max: 68.0) +[2026-07-22 21:54:41,952][379328] Avg episode reward: [(0, '2796.400')] +[2026-07-22 21:54:46,610][380295] Updated weights for policy 0, policy_version 19898 (0.0007) +[2026-07-22 21:54:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6775.8). Total num frames: 10190848. Throughput: 0: 6633.3. Samples: 10186752. Policy #0 lag: (min: 4.0, avg: 6.8, max: 68.0) +[2026-07-22 21:54:46,952][379328] Avg episode reward: [(0, '2789.600')] +[2026-07-22 21:54:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 6775.8). Total num frames: 10223616. Throughput: 0: 6621.9. Samples: 10225152. Policy #0 lag: (min: 14.0, avg: 16.8, max: 78.0) +[2026-07-22 21:54:51,952][379328] Avg episode reward: [(0, '2909.050')] +[2026-07-22 21:54:55,826][380295] Updated weights for policy 0, policy_version 20000 (0.0007) +[2026-07-22 21:54:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 6775.8). Total num frames: 10256384. Throughput: 0: 6735.6. Samples: 10248192. Policy #0 lag: (min: 14.0, avg: 16.8, max: 78.0) +[2026-07-22 21:54:56,952][379328] Avg episode reward: [(0, '2942.450')] +[2026-07-22 21:55:01,181][380295] Updated weights for policy 0, policy_version 20096 (0.0008) +[2026-07-22 21:55:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6690.1, 300 sec: 6775.8). Total num frames: 10289152. Throughput: 0: 6735.6. Samples: 10289152. Policy #0 lag: (min: 14.0, avg: 16.8, max: 78.0) +[2026-07-22 21:55:01,951][379328] Avg episode reward: [(0, '3081.900')] +[2026-07-22 21:55:01,957][380289] Saving new best policy, reward=3081.900! +[2026-07-22 21:55:06,951][379328] Fps is (10 sec: 6553.7, 60 sec: 6826.7, 300 sec: 6775.8). Total num frames: 10321920. Throughput: 0: 6701.5. Samples: 10327552. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:55:06,951][379328] Avg episode reward: [(0, '3154.450')] +[2026-07-22 21:55:06,956][380289] Saving new best policy, reward=3154.450! +[2026-07-22 21:55:10,595][380295] Updated weights for policy 0, policy_version 20208 (0.0008) +[2026-07-22 21:55:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6775.8). Total num frames: 10354688. Throughput: 0: 6747.0. Samples: 10349056. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:55:11,951][379328] Avg episode reward: [(0, '3204.700')] +[2026-07-22 21:55:11,957][380289] Saving new best policy, reward=3204.700! +[2026-07-22 21:55:15,321][380289] Signal inference workers to stop experience collection... (950 times) +[2026-07-22 21:55:15,351][380295] InferenceWorker_p0-w0: stopping experience collection (950 times) +[2026-07-22 21:55:15,497][380289] Signal inference workers to resume experience collection... (950 times) +[2026-07-22 21:55:15,497][380295] InferenceWorker_p0-w0: resuming experience collection (950 times) +[2026-07-22 21:55:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6690.1, 300 sec: 6775.8). Total num frames: 10387456. Throughput: 0: 6769.8. Samples: 10388480. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:55:16,951][379328] Avg episode reward: [(0, '3155.150')] +[2026-07-22 21:55:20,007][380295] Updated weights for policy 0, policy_version 20304 (0.0006) +[2026-07-22 21:55:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6826.7, 300 sec: 6775.8). Total num frames: 10420224. Throughput: 0: 6735.6. Samples: 10429440. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:55:21,952][379328] Avg episode reward: [(0, '3163.100')] +[2026-07-22 21:55:25,222][380295] Updated weights for policy 0, policy_version 20402 (0.0009) +[2026-07-22 21:55:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6826.7, 300 sec: 6775.8). Total num frames: 10452992. Throughput: 0: 6792.5. Samples: 10451456. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:55:26,951][379328] Avg episode reward: [(0, '3038.750')] +[2026-07-22 21:55:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6826.7, 300 sec: 6775.8). Total num frames: 10485760. Throughput: 0: 6781.2. Samples: 10491904. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:55:31,952][379328] Avg episode reward: [(0, '3155.450')] +[2026-07-22 21:55:33,807][380295] Updated weights for policy 0, policy_version 20482 (0.0006) +[2026-07-22 21:55:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 10518528. Throughput: 0: 6894.9. Samples: 10535424. Policy #0 lag: (min: 19.0, avg: 21.6, max: 83.0) +[2026-07-22 21:55:36,951][379328] Avg episode reward: [(0, '3140.050')] +[2026-07-22 21:55:39,073][380295] Updated weights for policy 0, policy_version 20602 (0.0007) +[2026-07-22 21:55:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 10551296. Throughput: 0: 6815.3. Samples: 10554880. Policy #0 lag: (min: 19.0, avg: 21.6, max: 83.0) +[2026-07-22 21:55:41,952][379328] Avg episode reward: [(0, '3005.200')] +[2026-07-22 21:55:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 10584064. Throughput: 0: 6826.7. Samples: 10596352. Policy #0 lag: (min: 19.0, avg: 21.6, max: 83.0) +[2026-07-22 21:55:46,951][379328] Avg episode reward: [(0, '2996.450')] +[2026-07-22 21:55:48,782][380295] Updated weights for policy 0, policy_version 20726 (0.0008) +[2026-07-22 21:55:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 10616832. Throughput: 0: 6929.1. Samples: 10639360. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:55:51,951][379328] Avg episode reward: [(0, '3053.650')] +[2026-07-22 21:55:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 10649600. Throughput: 0: 6860.8. Samples: 10657792. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:55:56,952][379328] Avg episode reward: [(0, '2950.750')] +[2026-07-22 21:55:58,032][380295] Updated weights for policy 0, policy_version 20848 (0.0007) +[2026-07-22 21:56:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 10682368. Throughput: 0: 6929.1. Samples: 10700288. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:56:01,952][379328] Avg episode reward: [(0, '3031.800')] +[2026-07-22 21:56:03,286][380295] Updated weights for policy 0, policy_version 20928 (0.0007) +[2026-07-22 21:56:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 10715136. Throughput: 0: 6929.1. Samples: 10741248. Policy #0 lag: (min: 29.0, avg: 31.8, max: 93.0) +[2026-07-22 21:56:06,952][379328] Avg episode reward: [(0, '3123.250')] +[2026-07-22 21:56:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 10747904. Throughput: 0: 6872.2. Samples: 10760704. Policy #0 lag: (min: 29.0, avg: 31.8, max: 93.0) +[2026-07-22 21:56:11,952][379328] Avg episode reward: [(0, '3207.800')] +[2026-07-22 21:56:11,957][380289] Saving new best policy, reward=3207.800! +[2026-07-22 21:56:12,980][380295] Updated weights for policy 0, policy_version 21046 (0.0007) +[2026-07-22 21:56:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 10780672. Throughput: 0: 6860.8. Samples: 10800640. Policy #0 lag: (min: 29.0, avg: 31.8, max: 93.0) +[2026-07-22 21:56:16,952][379328] Avg episode reward: [(0, '3163.300')] +[2026-07-22 21:56:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 10813440. Throughput: 0: 6815.3. Samples: 10842112. Policy #0 lag: (min: 13.0, avg: 15.8, max: 77.0) +[2026-07-22 21:56:21,951][379328] Avg episode reward: [(0, '3139.500')] +[2026-07-22 21:56:21,987][380295] Updated weights for policy 0, policy_version 21122 (0.0007) +[2026-07-22 21:56:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 10846208. Throughput: 0: 6826.7. Samples: 10862080. Policy #0 lag: (min: 13.0, avg: 15.8, max: 77.0) +[2026-07-22 21:56:26,951][379328] Avg episode reward: [(0, '3130.350')] +[2026-07-22 21:56:27,424][380295] Updated weights for policy 0, policy_version 21234 (0.0006) +[2026-07-22 21:56:31,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6826.7, 300 sec: 6831.3). Total num frames: 10895360. Throughput: 0: 6826.7. Samples: 10903552. Policy #0 lag: (min: 12.0, avg: 14.8, max: 76.0) +[2026-07-22 21:56:31,952][379328] Avg episode reward: [(0, '3256.800')] +[2026-07-22 21:56:32,252][380289] Saving new best policy, reward=3256.800! +[2026-07-22 21:56:36,373][380289] Signal inference workers to stop experience collection... (1000 times) +[2026-07-22 21:56:36,401][380295] InferenceWorker_p0-w0: stopping experience collection (1000 times) +[2026-07-22 21:56:36,590][380289] Signal inference workers to resume experience collection... (1000 times) +[2026-07-22 21:56:36,591][380295] InferenceWorker_p0-w0: resuming experience collection (1000 times) +[2026-07-22 21:56:36,592][380295] Updated weights for policy 0, policy_version 21344 (0.0007) +[2026-07-22 21:56:36,951][379328] Fps is (10 sec: 9011.2, 60 sec: 6963.2, 300 sec: 6859.1). Total num frames: 10936320. Throughput: 0: 6792.5. Samples: 10945024. Policy #0 lag: (min: 12.0, avg: 14.8, max: 76.0) +[2026-07-22 21:56:36,952][379328] Avg episode reward: [(0, '3132.700')] +[2026-07-22 21:56:41,278][380295] Updated weights for policy 0, policy_version 21430 (0.0007) +[2026-07-22 21:56:41,951][379328] Fps is (10 sec: 8192.0, 60 sec: 7099.7, 300 sec: 6859.1). Total num frames: 10977280. Throughput: 0: 6860.8. Samples: 10966528. Policy #0 lag: (min: 12.0, avg: 14.8, max: 76.0) +[2026-07-22 21:56:41,952][379328] Avg episode reward: [(0, '3223.900')] +[2026-07-22 21:56:46,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 6803.5). Total num frames: 11010048. Throughput: 0: 6826.7. Samples: 11007488. Policy #0 lag: (min: 55.0, avg: 57.9, max: 119.0) +[2026-07-22 21:56:46,952][379328] Avg episode reward: [(0, '3228.200')] +[2026-07-22 21:56:50,762][380295] Updated weights for policy 0, policy_version 21520 (0.0007) +[2026-07-22 21:56:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6803.5). Total num frames: 11042816. Throughput: 0: 6769.8. Samples: 11045888. Policy #0 lag: (min: 55.0, avg: 57.9, max: 119.0) +[2026-07-22 21:56:51,951][379328] Avg episode reward: [(0, '3267.800')] +[2026-07-22 21:56:51,957][380289] Saving new best policy, reward=3267.800! +[2026-07-22 21:56:55,953][380295] Updated weights for policy 0, policy_version 21618 (0.0009) +[2026-07-22 21:56:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6775.8). Total num frames: 11075584. Throughput: 0: 6838.0. Samples: 11068416. Policy #0 lag: (min: 55.0, avg: 57.9, max: 119.0) +[2026-07-22 21:56:56,952][379328] Avg episode reward: [(0, '3267.250')] +[2026-07-22 21:57:00,866][380295] Updated weights for policy 0, policy_version 21694 (0.0009) +[2026-07-22 21:57:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6775.8). Total num frames: 11108352. Throughput: 0: 6860.8. Samples: 11109376. Policy #0 lag: (min: 55.0, avg: 57.9, max: 119.0) +[2026-07-22 21:57:01,952][379328] Avg episode reward: [(0, '3416.600')] +[2026-07-22 21:57:01,957][380289] Saving new best policy, reward=3416.600! +[2026-07-22 21:57:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6775.8). Total num frames: 11141120. Throughput: 0: 6849.4. Samples: 11150336. Policy #0 lag: (min: 3.0, avg: 5.9, max: 67.0) +[2026-07-22 21:57:06,952][379328] Avg episode reward: [(0, '3508.100')] +[2026-07-22 21:57:06,957][380289] Saving results/checkpoints/memory/rollout_teacher/demon_attack_teacher_fixed_l6_obs15_seed0/checkpoint_p0/checkpoint_000021760_11141120.pth... +[2026-07-22 21:57:06,979][380289] Saving new best policy, reward=3508.100! +[2026-07-22 21:57:09,729][380295] Updated weights for policy 0, policy_version 21792 (0.0008) +[2026-07-22 21:57:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6775.8). Total num frames: 11173888. Throughput: 0: 6929.1. Samples: 11173888. Policy #0 lag: (min: 3.0, avg: 5.9, max: 67.0) +[2026-07-22 21:57:11,952][379328] Avg episode reward: [(0, '3538.500')] +[2026-07-22 21:57:11,957][380289] Saving new best policy, reward=3538.500! +[2026-07-22 21:57:14,810][380295] Updated weights for policy 0, policy_version 21886 (0.0008) +[2026-07-22 21:57:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6775.8). Total num frames: 11206656. Throughput: 0: 6894.9. Samples: 11213824. Policy #0 lag: (min: 3.0, avg: 5.9, max: 67.0) +[2026-07-22 21:57:16,952][379328] Avg episode reward: [(0, '3561.100')] +[2026-07-22 21:57:16,956][380289] Saving new best policy, reward=3561.100! +[2026-07-22 21:57:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6775.8). Total num frames: 11239424. Throughput: 0: 6906.3. Samples: 11255808. Policy #0 lag: (min: 3.0, avg: 5.9, max: 67.0) +[2026-07-22 21:57:21,952][379328] Avg episode reward: [(0, '3607.550')] +[2026-07-22 21:57:21,958][380289] Saving new best policy, reward=3607.550! +[2026-07-22 21:57:24,255][380295] Updated weights for policy 0, policy_version 22000 (0.0008) +[2026-07-22 21:57:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6775.8). Total num frames: 11272192. Throughput: 0: 6838.0. Samples: 11274240. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:57:26,952][379328] Avg episode reward: [(0, '3559.800')] +[2026-07-22 21:57:29,556][380295] Updated weights for policy 0, policy_version 22080 (0.0008) +[2026-07-22 21:57:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6826.7, 300 sec: 6775.8). Total num frames: 11304960. Throughput: 0: 6838.0. Samples: 11315200. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:57:31,952][379328] Avg episode reward: [(0, '3474.050')] +[2026-07-22 21:57:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6690.1, 300 sec: 6775.8). Total num frames: 11337728. Throughput: 0: 6929.1. Samples: 11357696. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:57:36,951][379328] Avg episode reward: [(0, '3452.250')] +[2026-07-22 21:57:38,898][380295] Updated weights for policy 0, policy_version 22198 (0.0008) +[2026-07-22 21:57:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 11370496. Throughput: 0: 6815.3. Samples: 11375104. Policy #0 lag: (min: 63.0, avg: 65.7, max: 127.0) +[2026-07-22 21:57:41,951][379328] Avg episode reward: [(0, '3456.250')] +[2026-07-22 21:57:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 11403264. Throughput: 0: 6838.0. Samples: 11417088. Policy #0 lag: (min: 63.0, avg: 65.7, max: 127.0) +[2026-07-22 21:57:46,952][379328] Avg episode reward: [(0, '3506.800')] +[2026-07-22 21:57:48,620][380295] Updated weights for policy 0, policy_version 22320 (0.0008) +[2026-07-22 21:57:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 11436032. Throughput: 0: 6803.9. Samples: 11456512. Policy #0 lag: (min: 63.0, avg: 65.7, max: 127.0) +[2026-07-22 21:57:51,952][379328] Avg episode reward: [(0, '3475.500')] +[2026-07-22 21:57:53,781][380295] Updated weights for policy 0, policy_version 22400 (0.0008) +[2026-07-22 21:57:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 11468800. Throughput: 0: 6735.6. Samples: 11476992. Policy #0 lag: (min: 63.0, avg: 65.7, max: 127.0) +[2026-07-22 21:57:56,952][379328] Avg episode reward: [(0, '3453.200')] +[2026-07-22 21:57:57,680][380289] Signal inference workers to stop experience collection... (1050 times) +[2026-07-22 21:57:57,707][380295] InferenceWorker_p0-w0: stopping experience collection (1050 times) +[2026-07-22 21:57:57,894][380289] Signal inference workers to resume experience collection... (1050 times) +[2026-07-22 21:57:57,895][380295] InferenceWorker_p0-w0: resuming experience collection (1050 times) +[2026-07-22 21:58:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 11501568. Throughput: 0: 6769.8. Samples: 11518464. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 21:58:01,952][379328] Avg episode reward: [(0, '3391.100')] +[2026-07-22 21:58:03,299][380295] Updated weights for policy 0, policy_version 22522 (0.0008) +[2026-07-22 21:58:06,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 11534336. Throughput: 0: 6735.6. Samples: 11558912. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 21:58:06,952][379328] Avg episode reward: [(0, '3446.100')] +[2026-07-22 21:58:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 11567104. Throughput: 0: 6758.4. Samples: 11578368. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 21:58:11,951][379328] Avg episode reward: [(0, '3526.150')] +[2026-07-22 21:58:12,585][380295] Updated weights for policy 0, policy_version 22640 (0.0008) +[2026-07-22 21:58:16,951][379328] Fps is (10 sec: 7372.9, 60 sec: 6690.1, 300 sec: 6803.5). Total num frames: 11608064. Throughput: 0: 6815.3. Samples: 11621888. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:58:16,952][379328] Avg episode reward: [(0, '3536.750')] +[2026-07-22 21:58:17,568][380295] Updated weights for policy 0, policy_version 22720 (0.0008) +[2026-07-22 21:58:21,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6690.1, 300 sec: 6803.5). Total num frames: 11640832. Throughput: 0: 6781.2. Samples: 11662848. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:58:21,951][379328] Avg episode reward: [(0, '3452.500')] +[2026-07-22 21:58:26,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6963.2, 300 sec: 6859.1). Total num frames: 11689984. Throughput: 0: 6849.4. Samples: 11683328. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:58:26,952][379328] Avg episode reward: [(0, '3448.350')] +[2026-07-22 21:58:27,043][380295] Updated weights for policy 0, policy_version 22846 (0.0008) +[2026-07-22 21:58:31,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 11730944. Throughput: 0: 6872.2. Samples: 11726336. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:58:31,952][379328] Avg episode reward: [(0, '3459.200')] +[2026-07-22 21:58:36,058][380295] Updated weights for policy 0, policy_version 22944 (0.0009) +[2026-07-22 21:58:36,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 11763712. Throughput: 0: 6883.6. Samples: 11766272. Policy #0 lag: (min: 11.0, avg: 13.8, max: 75.0) +[2026-07-22 21:58:36,951][379328] Avg episode reward: [(0, '3504.900')] +[2026-07-22 21:58:41,004][380295] Updated weights for policy 0, policy_version 23040 (0.0009) +[2026-07-22 21:58:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 11796480. Throughput: 0: 6929.1. Samples: 11788800. Policy #0 lag: (min: 11.0, avg: 13.8, max: 75.0) +[2026-07-22 21:58:41,952][379328] Avg episode reward: [(0, '3452.800')] +[2026-07-22 21:58:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6859.1). Total num frames: 11829248. Throughput: 0: 6929.1. Samples: 11830272. Policy #0 lag: (min: 11.0, avg: 13.8, max: 75.0) +[2026-07-22 21:58:46,951][379328] Avg episode reward: [(0, '3393.850')] +[2026-07-22 21:58:50,555][380295] Updated weights for policy 0, policy_version 23158 (0.0007) +[2026-07-22 21:58:51,951][379328] Fps is (10 sec: 6553.5, 60 sec: 7099.7, 300 sec: 6859.1). Total num frames: 11862016. Throughput: 0: 6883.6. Samples: 11868672. Policy #0 lag: (min: 11.0, avg: 13.8, max: 75.0) +[2026-07-22 21:58:51,952][379328] Avg episode reward: [(0, '3672.700')] +[2026-07-22 21:58:51,958][380289] Saving new best policy, reward=3672.700! +[2026-07-22 21:58:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6803.5). Total num frames: 11894784. Throughput: 0: 6951.8. Samples: 11891200. Policy #0 lag: (min: 7.0, avg: 9.7, max: 71.0) +[2026-07-22 21:58:56,951][379328] Avg episode reward: [(0, '3646.350')] +[2026-07-22 21:59:00,048][380295] Updated weights for policy 0, policy_version 23282 (0.0009) +[2026-07-22 21:59:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6831.3). Total num frames: 11927552. Throughput: 0: 6872.2. Samples: 11931136. Policy #0 lag: (min: 7.0, avg: 9.7, max: 71.0) +[2026-07-22 21:59:01,952][379328] Avg episode reward: [(0, '3814.550')] +[2026-07-22 21:59:01,957][380289] Saving new best policy, reward=3814.550! +[2026-07-22 21:59:05,245][380295] Updated weights for policy 0, policy_version 23360 (0.0008) +[2026-07-22 21:59:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 11960320. Throughput: 0: 6894.9. Samples: 11973120. Policy #0 lag: (min: 7.0, avg: 9.7, max: 71.0) +[2026-07-22 21:59:06,951][379328] Avg episode reward: [(0, '3869.000')] +[2026-07-22 21:59:06,956][380289] Saving new best policy, reward=3869.000! +[2026-07-22 21:59:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6803.5). Total num frames: 11993088. Throughput: 0: 6906.3. Samples: 11994112. Policy #0 lag: (min: 7.0, avg: 9.7, max: 71.0) +[2026-07-22 21:59:11,952][379328] Avg episode reward: [(0, '3821.550')] +[2026-07-22 21:59:14,334][380289] Signal inference workers to stop experience collection... (1100 times) +[2026-07-22 21:59:14,362][380295] InferenceWorker_p0-w0: stopping experience collection (1100 times) +[2026-07-22 21:59:14,479][380289] Signal inference workers to resume experience collection... (1100 times) +[2026-07-22 21:59:14,479][380295] InferenceWorker_p0-w0: resuming experience collection (1100 times) +[2026-07-22 21:59:14,730][380295] Updated weights for policy 0, policy_version 23486 (0.0008) +[2026-07-22 21:59:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 6831.3). Total num frames: 12025856. Throughput: 0: 6826.7. Samples: 12033536. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:59:16,952][379328] Avg episode reward: [(0, '3689.650')] +[2026-07-22 21:59:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 6831.3). Total num frames: 12058624. Throughput: 0: 6860.8. Samples: 12075008. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:59:21,952][379328] Avg episode reward: [(0, '3773.300')] +[2026-07-22 21:59:24,201][380295] Updated weights for policy 0, policy_version 23600 (0.0008) +[2026-07-22 21:59:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6690.1, 300 sec: 6831.3). Total num frames: 12091392. Throughput: 0: 6781.2. Samples: 12093952. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:59:26,951][379328] Avg episode reward: [(0, '3760.900')] +[2026-07-22 21:59:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 12124160. Throughput: 0: 6735.6. Samples: 12133376. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 21:59:31,951][379328] Avg episode reward: [(0, '3834.600')] +[2026-07-22 21:59:33,653][380295] Updated weights for policy 0, policy_version 23696 (0.0009) +[2026-07-22 21:59:36,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 12156928. Throughput: 0: 6815.3. Samples: 12175360. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:59:36,952][379328] Avg episode reward: [(0, '3803.050')] +[2026-07-22 21:59:38,999][380295] Updated weights for policy 0, policy_version 23798 (0.0007) +[2026-07-22 21:59:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 12189696. Throughput: 0: 6724.3. Samples: 12193792. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:59:41,952][379328] Avg episode reward: [(0, '3978.950')] +[2026-07-22 21:59:41,957][380289] Saving new best policy, reward=3978.950! +[2026-07-22 21:59:46,951][379328] Fps is (10 sec: 6553.7, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 12222464. Throughput: 0: 6735.7. Samples: 12234240. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:59:46,952][379328] Avg episode reward: [(0, '3695.000')] +[2026-07-22 21:59:48,786][380295] Updated weights for policy 0, policy_version 23920 (0.0007) +[2026-07-22 21:59:51,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 12255232. Throughput: 0: 6724.3. Samples: 12275712. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 21:59:51,952][379328] Avg episode reward: [(0, '3529.600')] +[2026-07-22 21:59:53,906][380295] Updated weights for policy 0, policy_version 24000 (0.0007) +[2026-07-22 21:59:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 12288000. Throughput: 0: 6690.1. Samples: 12295168. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 21:59:56,952][379328] Avg episode reward: [(0, '3493.550')] +[2026-07-22 22:00:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 12320768. Throughput: 0: 6769.8. Samples: 12338176. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:00:01,952][379328] Avg episode reward: [(0, '3475.800')] +[2026-07-22 22:00:03,115][380295] Updated weights for policy 0, policy_version 24112 (0.0008) +[2026-07-22 22:00:06,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 12353536. Throughput: 0: 6758.4. Samples: 12379136. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:00:06,952][379328] Avg episode reward: [(0, '3692.500')] +[2026-07-22 22:00:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 12386304. Throughput: 0: 6781.2. Samples: 12399104. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:00:11,952][379328] Avg episode reward: [(0, '3626.500')] +[2026-07-22 22:00:12,347][380295] Updated weights for policy 0, policy_version 24208 (0.0007) +[2026-07-22 22:00:16,951][379328] Fps is (10 sec: 6553.7, 60 sec: 6553.6, 300 sec: 6775.8). Total num frames: 12419072. Throughput: 0: 6815.3. Samples: 12440064. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 22:00:16,952][379328] Avg episode reward: [(0, '3696.950')] +[2026-07-22 22:00:17,625][380295] Updated weights for policy 0, policy_version 24306 (0.0007) +[2026-07-22 22:00:21,951][379328] Fps is (10 sec: 6553.3, 60 sec: 6553.6, 300 sec: 6775.7). Total num frames: 12451840. Throughput: 0: 6803.9. Samples: 12481536. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 22:00:21,952][379328] Avg episode reward: [(0, '3698.300')] +[2026-07-22 22:00:26,848][380295] Updated weights for policy 0, policy_version 24400 (0.0007) +[2026-07-22 22:00:26,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6690.1, 300 sec: 6803.5). Total num frames: 12492800. Throughput: 0: 6803.9. Samples: 12499968. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 22:00:26,952][379328] Avg episode reward: [(0, '3659.200')] +[2026-07-22 22:00:31,894][380295] Updated weights for policy 0, policy_version 24506 (0.0008) +[2026-07-22 22:00:31,951][379328] Fps is (10 sec: 9011.6, 60 sec: 6963.2, 300 sec: 6859.1). Total num frames: 12541952. Throughput: 0: 6883.6. Samples: 12544000. Policy #0 lag: (min: 15.0, avg: 18.7, max: 79.0) +[2026-07-22 22:00:31,952][379328] Avg episode reward: [(0, '3706.050')] +[2026-07-22 22:00:35,913][380289] Signal inference workers to stop experience collection... (1150 times) +[2026-07-22 22:00:35,944][380295] InferenceWorker_p0-w0: stopping experience collection (1150 times) +[2026-07-22 22:00:36,089][380289] Signal inference workers to resume experience collection... (1150 times) +[2026-07-22 22:00:36,090][380295] InferenceWorker_p0-w0: resuming experience collection (1150 times) +[2026-07-22 22:00:36,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7099.8, 300 sec: 6886.8). Total num frames: 12582912. Throughput: 0: 6883.6. Samples: 12585472. Policy #0 lag: (min: 15.0, avg: 18.7, max: 79.0) +[2026-07-22 22:00:36,952][379328] Avg episode reward: [(0, '3861.550')] +[2026-07-22 22:00:40,515][380295] Updated weights for policy 0, policy_version 24592 (0.0007) +[2026-07-22 22:00:41,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 12615680. Throughput: 0: 6929.1. Samples: 12606976. Policy #0 lag: (min: 15.0, avg: 18.7, max: 79.0) +[2026-07-22 22:00:41,951][379328] Avg episode reward: [(0, '3953.000')] +[2026-07-22 22:00:45,507][380295] Updated weights for policy 0, policy_version 24690 (0.0009) +[2026-07-22 22:00:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 12648448. Throughput: 0: 6917.7. Samples: 12649472. Policy #0 lag: (min: 15.0, avg: 18.7, max: 79.0) +[2026-07-22 22:00:46,951][379328] Avg episode reward: [(0, '4075.850')] +[2026-07-22 22:00:46,957][380289] Saving new best policy, reward=4075.850! +[2026-07-22 22:00:51,951][379328] Fps is (10 sec: 6553.3, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 12681216. Throughput: 0: 6940.4. Samples: 12691456. Policy #0 lag: (min: 2.0, avg: 4.8, max: 66.0) +[2026-07-22 22:00:51,952][379328] Avg episode reward: [(0, '4128.700')] +[2026-07-22 22:00:51,986][380289] Saving new best policy, reward=4128.700! +[2026-07-22 22:00:54,424][380295] Updated weights for policy 0, policy_version 24784 (0.0007) +[2026-07-22 22:00:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 12713984. Throughput: 0: 7008.7. Samples: 12714496. Policy #0 lag: (min: 2.0, avg: 4.8, max: 66.0) +[2026-07-22 22:00:56,951][379328] Avg episode reward: [(0, '4053.850')] +[2026-07-22 22:00:59,747][380295] Updated weights for policy 0, policy_version 24882 (0.0008) +[2026-07-22 22:01:01,951][379328] Fps is (10 sec: 6553.9, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 12746752. Throughput: 0: 6940.4. Samples: 12752384. Policy #0 lag: (min: 2.0, avg: 4.8, max: 66.0) +[2026-07-22 22:01:01,952][379328] Avg episode reward: [(0, '4093.050')] +[2026-07-22 22:01:06,951][379328] Fps is (10 sec: 6553.4, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 12779520. Throughput: 0: 7008.7. Samples: 12796928. Policy #0 lag: (min: 2.0, avg: 4.8, max: 66.0) +[2026-07-22 22:01:06,952][379328] Avg episode reward: [(0, '4062.450')] +[2026-07-22 22:01:08,742][380295] Updated weights for policy 0, policy_version 25008 (0.0008) +[2026-07-22 22:01:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 12812288. Throughput: 0: 7065.6. Samples: 12817920. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 22:01:11,952][379328] Avg episode reward: [(0, '4199.200')] +[2026-07-22 22:01:11,957][380289] Saving new best policy, reward=4199.200! +[2026-07-22 22:01:13,862][380295] Updated weights for policy 0, policy_version 25085 (0.0008) +[2026-07-22 22:01:16,951][379328] Fps is (10 sec: 6553.9, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 12845056. Throughput: 0: 7020.1. Samples: 12859904. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 22:01:16,952][379328] Avg episode reward: [(0, '4155.700')] +[2026-07-22 22:01:21,951][379328] Fps is (10 sec: 6553.5, 60 sec: 7099.8, 300 sec: 6886.8). Total num frames: 12877824. Throughput: 0: 7065.6. Samples: 12903424. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 22:01:21,952][379328] Avg episode reward: [(0, '4222.800')] +[2026-07-22 22:01:21,958][380289] Saving new best policy, reward=4222.800! +[2026-07-22 22:01:22,814][380295] Updated weights for policy 0, policy_version 25200 (0.0007) +[2026-07-22 22:01:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 6831.3). Total num frames: 12910592. Throughput: 0: 7008.7. Samples: 12922368. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 22:01:26,952][379328] Avg episode reward: [(0, '4180.350')] +[2026-07-22 22:01:31,951][379328] Fps is (10 sec: 6553.7, 60 sec: 6690.1, 300 sec: 6803.5). Total num frames: 12943360. Throughput: 0: 7008.7. Samples: 12964864. Policy #0 lag: (min: 2.0, avg: 4.9, max: 66.0) +[2026-07-22 22:01:31,952][379328] Avg episode reward: [(0, '4264.500')] +[2026-07-22 22:01:32,033][380295] Updated weights for policy 0, policy_version 25296 (0.0008) +[2026-07-22 22:01:32,214][380289] Saving new best policy, reward=4264.500! +[2026-07-22 22:01:36,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6826.7, 300 sec: 6831.3). Total num frames: 12992512. Throughput: 0: 7031.5. Samples: 13007872. Policy #0 lag: (min: 2.0, avg: 4.9, max: 66.0) +[2026-07-22 22:01:36,952][379328] Avg episode reward: [(0, '4194.650')] +[2026-07-22 22:01:37,166][380295] Updated weights for policy 0, policy_version 25402 (0.0009) +[2026-07-22 22:01:41,951][379328] Fps is (10 sec: 9830.4, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13041664. Throughput: 0: 6963.2. Samples: 13027840. Policy #0 lag: (min: 2.0, avg: 4.9, max: 66.0) +[2026-07-22 22:01:41,951][379328] Avg episode reward: [(0, '4125.300')] +[2026-07-22 22:01:46,426][380295] Updated weights for policy 0, policy_version 25504 (0.0008) +[2026-07-22 22:01:46,951][379328] Fps is (10 sec: 8192.0, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13074432. Throughput: 0: 7054.2. Samples: 13069824. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:01:46,951][379328] Avg episode reward: [(0, '4185.050')] +[2026-07-22 22:01:51,768][380295] Updated weights for policy 0, policy_version 25600 (0.0008) +[2026-07-22 22:01:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.8, 300 sec: 6886.8). Total num frames: 13107200. Throughput: 0: 6917.7. Samples: 13108224. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:01:51,952][379328] Avg episode reward: [(0, '4230.500')] +[2026-07-22 22:01:55,678][380289] Signal inference workers to stop experience collection... (1200 times) +[2026-07-22 22:01:55,705][380295] InferenceWorker_p0-w0: stopping experience collection (1200 times) +[2026-07-22 22:01:55,891][380289] Signal inference workers to resume experience collection... (1200 times) +[2026-07-22 22:01:55,891][380295] InferenceWorker_p0-w0: resuming experience collection (1200 times) +[2026-07-22 22:01:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13139968. Throughput: 0: 6940.4. Samples: 13130240. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:01:56,952][379328] Avg episode reward: [(0, '4278.700')] +[2026-07-22 22:01:56,957][380289] Saving new best policy, reward=4278.700! +[2026-07-22 22:02:00,824][380295] Updated weights for policy 0, policy_version 25714 (0.0009) +[2026-07-22 22:02:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13172736. Throughput: 0: 6963.2. Samples: 13173248. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:02:01,952][379328] Avg episode reward: [(0, '4258.500')] +[2026-07-22 22:02:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.8, 300 sec: 6886.8). Total num frames: 13205504. Throughput: 0: 6895.0. Samples: 13213696. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:02:06,952][379328] Avg episode reward: [(0, '4329.850')] +[2026-07-22 22:02:06,958][380289] Saving new best policy, reward=4329.850! +[2026-07-22 22:02:09,898][380295] Updated weights for policy 0, policy_version 25824 (0.0007) +[2026-07-22 22:02:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13238272. Throughput: 0: 6986.0. Samples: 13236736. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:02:11,952][379328] Avg episode reward: [(0, '4440.050')] +[2026-07-22 22:02:11,957][380289] Saving new best policy, reward=4440.050! +[2026-07-22 22:02:15,165][380295] Updated weights for policy 0, policy_version 25920 (0.0007) +[2026-07-22 22:02:16,951][379328] Fps is (10 sec: 6553.7, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13271040. Throughput: 0: 6906.3. Samples: 13275648. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:02:16,952][379328] Avg episode reward: [(0, '4398.700')] +[2026-07-22 22:02:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.8, 300 sec: 6886.8). Total num frames: 13303808. Throughput: 0: 6917.7. Samples: 13319168. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:02:21,952][379328] Avg episode reward: [(0, '4537.250')] +[2026-07-22 22:02:21,958][380289] Saving new best policy, reward=4537.250! +[2026-07-22 22:02:24,385][380295] Updated weights for policy 0, policy_version 26038 (0.0007) +[2026-07-22 22:02:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13336576. Throughput: 0: 6906.3. Samples: 13338624. Policy #0 lag: (min: 12.0, avg: 14.6, max: 76.0) +[2026-07-22 22:02:26,952][379328] Avg episode reward: [(0, '4520.900')] +[2026-07-22 22:02:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13369344. Throughput: 0: 6963.2. Samples: 13383168. Policy #0 lag: (min: 12.0, avg: 14.6, max: 76.0) +[2026-07-22 22:02:31,951][379328] Avg episode reward: [(0, '4559.500')] +[2026-07-22 22:02:31,956][380289] Saving new best policy, reward=4559.500! +[2026-07-22 22:02:33,330][380295] Updated weights for policy 0, policy_version 26144 (0.0007) +[2026-07-22 22:02:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6826.7, 300 sec: 6886.8). Total num frames: 13402112. Throughput: 0: 7042.8. Samples: 13425152. Policy #0 lag: (min: 12.0, avg: 14.6, max: 76.0) +[2026-07-22 22:02:36,951][379328] Avg episode reward: [(0, '4659.750')] +[2026-07-22 22:02:36,957][380289] Saving new best policy, reward=4659.750! +[2026-07-22 22:02:38,479][380295] Updated weights for policy 0, policy_version 26240 (0.0007) +[2026-07-22 22:02:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 13434880. Throughput: 0: 6986.0. Samples: 13444608. Policy #0 lag: (min: 12.0, avg: 14.6, max: 76.0) +[2026-07-22 22:02:41,952][379328] Avg episode reward: [(0, '4537.250')] +[2026-07-22 22:02:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 13467648. Throughput: 0: 6974.6. Samples: 13487104. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:02:46,952][379328] Avg episode reward: [(0, '4588.300')] +[2026-07-22 22:02:47,619][380295] Updated weights for policy 0, policy_version 26352 (0.0007) +[2026-07-22 22:02:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 13500416. Throughput: 0: 7008.7. Samples: 13529088. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:02:51,951][379328] Avg episode reward: [(0, '4536.000')] +[2026-07-22 22:02:56,845][380295] Updated weights for policy 0, policy_version 26448 (0.0008) +[2026-07-22 22:02:56,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6690.1, 300 sec: 6914.6). Total num frames: 13541376. Throughput: 0: 6929.1. Samples: 13548544. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:02:56,952][379328] Avg episode reward: [(0, '4554.250')] +[2026-07-22 22:03:01,901][380295] Updated weights for policy 0, policy_version 26560 (0.0008) +[2026-07-22 22:03:01,951][379328] Fps is (10 sec: 9830.4, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 13598720. Throughput: 0: 7042.8. Samples: 13592576. Policy #0 lag: (min: 12.0, avg: 14.8, max: 76.0) +[2026-07-22 22:03:01,952][379328] Avg episode reward: [(0, '4530.350')] +[2026-07-22 22:03:06,952][379328] Fps is (10 sec: 9010.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 13631488. Throughput: 0: 6974.5. Samples: 13633024. Policy #0 lag: (min: 12.0, avg: 14.8, max: 76.0) +[2026-07-22 22:03:06,952][379328] Avg episode reward: [(0, '4613.750')] +[2026-07-22 22:03:11,166][380289] Signal inference workers to stop experience collection... (1250 times) +[2026-07-22 22:03:11,197][380295] InferenceWorker_p0-w0: stopping experience collection (1250 times) +[2026-07-22 22:03:11,307][380289] Signal inference workers to resume experience collection... (1250 times) +[2026-07-22 22:03:11,308][380295] InferenceWorker_p0-w0: resuming experience collection (1250 times) +[2026-07-22 22:03:11,562][380295] Updated weights for policy 0, policy_version 26686 (0.0009) +[2026-07-22 22:03:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6970.1). Total num frames: 13664256. Throughput: 0: 6997.3. Samples: 13653504. Policy #0 lag: (min: 12.0, avg: 14.8, max: 76.0) +[2026-07-22 22:03:11,952][379328] Avg episode reward: [(0, '4551.150')] +[2026-07-22 22:03:16,951][379328] Fps is (10 sec: 6554.0, 60 sec: 7099.7, 300 sec: 6970.1). Total num frames: 13697024. Throughput: 0: 6963.2. Samples: 13696512. Policy #0 lag: (min: 12.0, avg: 14.8, max: 76.0) +[2026-07-22 22:03:16,951][379328] Avg episode reward: [(0, '4405.650')] +[2026-07-22 22:03:20,595][380295] Updated weights for policy 0, policy_version 26800 (0.0008) +[2026-07-22 22:03:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6914.6). Total num frames: 13729792. Throughput: 0: 6906.3. Samples: 13735936. Policy #0 lag: (min: 5.0, avg: 7.8, max: 69.0) +[2026-07-22 22:03:21,951][379328] Avg episode reward: [(0, '4440.000')] +[2026-07-22 22:03:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13762560. Throughput: 0: 6974.6. Samples: 13758464. Policy #0 lag: (min: 5.0, avg: 7.8, max: 69.0) +[2026-07-22 22:03:26,951][379328] Avg episode reward: [(0, '4289.650')] +[2026-07-22 22:03:29,830][380295] Updated weights for policy 0, policy_version 26896 (0.0008) +[2026-07-22 22:03:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13795328. Throughput: 0: 6894.9. Samples: 13797376. Policy #0 lag: (min: 5.0, avg: 7.8, max: 69.0) +[2026-07-22 22:03:31,952][379328] Avg episode reward: [(0, '4504.350')] +[2026-07-22 22:03:36,951][379328] Fps is (10 sec: 6553.5, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13828096. Throughput: 0: 6872.2. Samples: 13838336. Policy #0 lag: (min: 5.0, avg: 7.8, max: 69.0) +[2026-07-22 22:03:36,952][379328] Avg episode reward: [(0, '4458.850')] +[2026-07-22 22:03:39,423][380295] Updated weights for policy 0, policy_version 27024 (0.0007) +[2026-07-22 22:03:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13860864. Throughput: 0: 6951.8. Samples: 13861376. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:03:41,952][379328] Avg episode reward: [(0, '4487.300')] +[2026-07-22 22:03:44,491][380295] Updated weights for policy 0, policy_version 27130 (0.0007) +[2026-07-22 22:03:46,951][379328] Fps is (10 sec: 6553.7, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13893632. Throughput: 0: 6906.3. Samples: 13903360. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:03:46,951][379328] Avg episode reward: [(0, '4505.150')] +[2026-07-22 22:03:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 13926400. Throughput: 0: 6940.5. Samples: 13945344. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:03:51,952][379328] Avg episode reward: [(0, '4568.950')] +[2026-07-22 22:03:53,703][380295] Updated weights for policy 0, policy_version 27232 (0.0008) +[2026-07-22 22:03:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 6886.8). Total num frames: 13959168. Throughput: 0: 6894.9. Samples: 13963776. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:03:56,952][379328] Avg episode reward: [(0, '4391.600')] +[2026-07-22 22:03:59,034][380295] Updated weights for policy 0, policy_version 27328 (0.0007) +[2026-07-22 22:04:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 13991936. Throughput: 0: 6860.8. Samples: 14005248. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:04:01,952][379328] Avg episode reward: [(0, '4431.550')] +[2026-07-22 22:04:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.7, 300 sec: 6886.8). Total num frames: 14024704. Throughput: 0: 6917.7. Samples: 14047232. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:04:06,952][379328] Avg episode reward: [(0, '4430.700')] +[2026-07-22 22:04:08,357][380295] Updated weights for policy 0, policy_version 27446 (0.0009) +[2026-07-22 22:04:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 14057472. Throughput: 0: 6849.4. Samples: 14066688. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:04:11,952][379328] Avg episode reward: [(0, '4625.100')] +[2026-07-22 22:04:16,951][379328] Fps is (10 sec: 6553.5, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 14090240. Throughput: 0: 6872.2. Samples: 14106624. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:04:16,952][379328] Avg episode reward: [(0, '4619.800')] +[2026-07-22 22:04:18,018][380295] Updated weights for policy 0, policy_version 27552 (0.0008) +[2026-07-22 22:04:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 14123008. Throughput: 0: 6906.3. Samples: 14149120. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:04:21,952][379328] Avg episode reward: [(0, '4661.500')] +[2026-07-22 22:04:21,957][380289] Saving new best policy, reward=4661.500! +[2026-07-22 22:04:23,089][380295] Updated weights for policy 0, policy_version 27646 (0.0007) +[2026-07-22 22:04:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 14155776. Throughput: 0: 6815.3. Samples: 14168064. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:04:26,951][379328] Avg episode reward: [(0, '4651.700')] +[2026-07-22 22:04:31,407][380289] Signal inference workers to stop experience collection... (1300 times) +[2026-07-22 22:04:31,437][380295] InferenceWorker_p0-w0: stopping experience collection (1300 times) +[2026-07-22 22:04:31,546][380289] Signal inference workers to resume experience collection... (1300 times) +[2026-07-22 22:04:31,547][380295] InferenceWorker_p0-w0: resuming experience collection (1300 times) +[2026-07-22 22:04:31,809][380295] Updated weights for policy 0, policy_version 27766 (0.0007) +[2026-07-22 22:04:31,951][379328] Fps is (10 sec: 9011.2, 60 sec: 6963.2, 300 sec: 6970.1). Total num frames: 14213120. Throughput: 0: 6917.7. Samples: 14214656. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:04:31,952][379328] Avg episode reward: [(0, '4607.500')] +[2026-07-22 22:04:36,951][379328] Fps is (10 sec: 9830.4, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14254080. Throughput: 0: 6894.9. Samples: 14255616. Policy #0 lag: (min: 31.0, avg: 33.7, max: 95.0) +[2026-07-22 22:04:36,952][379328] Avg episode reward: [(0, '4590.950')] +[2026-07-22 22:04:40,801][380295] Updated weights for policy 0, policy_version 27872 (0.0006) +[2026-07-22 22:04:41,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14286848. Throughput: 0: 6963.2. Samples: 14277120. Policy #0 lag: (min: 31.0, avg: 33.7, max: 95.0) +[2026-07-22 22:04:41,951][379328] Avg episode reward: [(0, '4582.100')] +[2026-07-22 22:04:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14319616. Throughput: 0: 7008.7. Samples: 14320640. Policy #0 lag: (min: 31.0, avg: 33.7, max: 95.0) +[2026-07-22 22:04:46,951][379328] Avg episode reward: [(0, '4647.900')] +[2026-07-22 22:04:49,786][380295] Updated weights for policy 0, policy_version 27984 (0.0007) +[2026-07-22 22:04:51,951][379328] Fps is (10 sec: 6553.5, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14352384. Throughput: 0: 7008.7. Samples: 14362624. Policy #0 lag: (min: 31.0, avg: 33.7, max: 95.0) +[2026-07-22 22:04:51,952][379328] Avg episode reward: [(0, '4546.850')] +[2026-07-22 22:04:54,791][380295] Updated weights for policy 0, policy_version 28082 (0.0007) +[2026-07-22 22:04:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14385152. Throughput: 0: 7088.4. Samples: 14385664. Policy #0 lag: (min: 47.0, avg: 49.9, max: 111.0) +[2026-07-22 22:04:56,952][379328] Avg episode reward: [(0, '4742.500')] +[2026-07-22 22:04:57,021][380289] Saving new best policy, reward=4742.500! +[2026-07-22 22:05:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14417920. Throughput: 0: 7088.4. Samples: 14425600. Policy #0 lag: (min: 47.0, avg: 49.9, max: 111.0) +[2026-07-22 22:05:01,952][379328] Avg episode reward: [(0, '4805.050')] +[2026-07-22 22:05:01,957][380289] Saving new best policy, reward=4805.050! +[2026-07-22 22:05:03,859][380295] Updated weights for policy 0, policy_version 28176 (0.0007) +[2026-07-22 22:05:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14450688. Throughput: 0: 7065.6. Samples: 14467072. Policy #0 lag: (min: 47.0, avg: 49.9, max: 111.0) +[2026-07-22 22:05:06,952][379328] Avg episode reward: [(0, '4714.200')] +[2026-07-22 22:05:09,263][380295] Updated weights for policy 0, policy_version 28286 (0.0007) +[2026-07-22 22:05:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14483456. Throughput: 0: 7077.0. Samples: 14486528. Policy #0 lag: (min: 47.0, avg: 49.9, max: 111.0) +[2026-07-22 22:05:11,952][379328] Avg episode reward: [(0, '4727.350')] +[2026-07-22 22:05:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14516224. Throughput: 0: 6997.3. Samples: 14529536. Policy #0 lag: (min: 2.0, avg: 4.8, max: 66.0) +[2026-07-22 22:05:16,952][379328] Avg episode reward: [(0, '4708.850')] +[2026-07-22 22:05:18,471][380295] Updated weights for policy 0, policy_version 28400 (0.0009) +[2026-07-22 22:05:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6970.1). Total num frames: 14548992. Throughput: 0: 7065.6. Samples: 14573568. Policy #0 lag: (min: 2.0, avg: 4.8, max: 66.0) +[2026-07-22 22:05:21,952][379328] Avg episode reward: [(0, '4749.250')] +[2026-07-22 22:05:26,951][379328] Fps is (10 sec: 6553.5, 60 sec: 7099.7, 300 sec: 6914.6). Total num frames: 14581760. Throughput: 0: 7031.5. Samples: 14593536. Policy #0 lag: (min: 2.0, avg: 4.8, max: 66.0) +[2026-07-22 22:05:26,952][379328] Avg episode reward: [(0, '4744.950')] +[2026-07-22 22:05:27,112][380295] Updated weights for policy 0, policy_version 28496 (0.0007) +[2026-07-22 22:05:31,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6826.7, 300 sec: 6914.6). Total num frames: 14622720. Throughput: 0: 7031.5. Samples: 14637056. Policy #0 lag: (min: 2.0, avg: 4.8, max: 66.0) +[2026-07-22 22:05:31,952][379328] Avg episode reward: [(0, '4652.750')] +[2026-07-22 22:05:32,488][380295] Updated weights for policy 0, policy_version 28602 (0.0007) +[2026-07-22 22:05:36,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6826.7, 300 sec: 6942.4). Total num frames: 14663680. Throughput: 0: 7020.1. Samples: 14678528. Policy #0 lag: (min: 31.0, avg: 33.8, max: 95.0) +[2026-07-22 22:05:36,952][379328] Avg episode reward: [(0, '4712.150')] +[2026-07-22 22:05:41,584][380295] Updated weights for policy 0, policy_version 28704 (0.0007) +[2026-07-22 22:05:41,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6963.2, 300 sec: 6970.1). Total num frames: 14704640. Throughput: 0: 6963.2. Samples: 14699008. Policy #0 lag: (min: 31.0, avg: 33.8, max: 95.0) +[2026-07-22 22:05:41,951][379328] Avg episode reward: [(0, '4749.200')] +[2026-07-22 22:05:46,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6963.2, 300 sec: 6970.2). Total num frames: 14737408. Throughput: 0: 6963.2. Samples: 14738944. Policy #0 lag: (min: 31.0, avg: 33.8, max: 95.0) +[2026-07-22 22:05:46,952][379328] Avg episode reward: [(0, '4756.850')] +[2026-07-22 22:05:47,042][380295] Updated weights for policy 0, policy_version 28800 (0.0007) +[2026-07-22 22:05:51,205][380289] Signal inference workers to stop experience collection... (1350 times) +[2026-07-22 22:05:51,232][380295] InferenceWorker_p0-w0: stopping experience collection (1350 times) +[2026-07-22 22:05:51,347][380289] Signal inference workers to resume experience collection... (1350 times) +[2026-07-22 22:05:51,347][380295] InferenceWorker_p0-w0: resuming experience collection (1350 times) +[2026-07-22 22:05:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 6970.1). Total num frames: 14770176. Throughput: 0: 6929.1. Samples: 14778880. Policy #0 lag: (min: 7.0, avg: 9.7, max: 71.0) +[2026-07-22 22:05:51,952][379328] Avg episode reward: [(0, '4733.650')] +[2026-07-22 22:05:56,301][380295] Updated weights for policy 0, policy_version 28922 (0.0008) +[2026-07-22 22:05:56,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14811136. Throughput: 0: 6986.0. Samples: 14800896. Policy #0 lag: (min: 7.0, avg: 9.7, max: 71.0) +[2026-07-22 22:05:56,951][379328] Avg episode reward: [(0, '4789.300')] +[2026-07-22 22:06:01,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14843904. Throughput: 0: 6940.4. Samples: 14841856. Policy #0 lag: (min: 7.0, avg: 9.7, max: 71.0) +[2026-07-22 22:06:01,952][379328] Avg episode reward: [(0, '4748.550')] +[2026-07-22 22:06:05,762][380295] Updated weights for policy 0, policy_version 29040 (0.0007) +[2026-07-22 22:06:06,951][379328] Fps is (10 sec: 6553.5, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14876672. Throughput: 0: 6849.4. Samples: 14881792. Policy #0 lag: (min: 7.0, avg: 9.7, max: 71.0) +[2026-07-22 22:06:06,952][379328] Avg episode reward: [(0, '4712.900')] +[2026-07-22 22:06:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14909440. Throughput: 0: 6894.9. Samples: 14903808. Policy #0 lag: (min: 31.0, avg: 33.7, max: 95.0) +[2026-07-22 22:06:11,951][379328] Avg episode reward: [(0, '4748.350')] +[2026-07-22 22:06:14,887][380295] Updated weights for policy 0, policy_version 29136 (0.0009) +[2026-07-22 22:06:16,951][379328] Fps is (10 sec: 6553.7, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14942208. Throughput: 0: 6826.7. Samples: 14944256. Policy #0 lag: (min: 31.0, avg: 33.7, max: 95.0) +[2026-07-22 22:06:16,951][379328] Avg episode reward: [(0, '4807.100')] +[2026-07-22 22:06:16,956][380289] Saving new best policy, reward=4807.100! +[2026-07-22 22:06:20,211][380295] Updated weights for policy 0, policy_version 29242 (0.0008) +[2026-07-22 22:06:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 14974976. Throughput: 0: 6849.4. Samples: 14986752. Policy #0 lag: (min: 31.0, avg: 33.7, max: 95.0) +[2026-07-22 22:06:21,951][379328] Avg episode reward: [(0, '4832.700')] +[2026-07-22 22:06:21,957][380289] Saving new best policy, reward=4832.700! +[2026-07-22 22:06:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 15007744. Throughput: 0: 6872.2. Samples: 15008256. Policy #0 lag: (min: 31.0, avg: 33.7, max: 95.0) +[2026-07-22 22:06:26,951][379328] Avg episode reward: [(0, '4859.200')] +[2026-07-22 22:06:26,956][380289] Saving new best policy, reward=4859.200! +[2026-07-22 22:06:29,391][380295] Updated weights for policy 0, policy_version 29360 (0.0007) +[2026-07-22 22:06:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 6942.4). Total num frames: 15040512. Throughput: 0: 6906.3. Samples: 15049728. Policy #0 lag: (min: 31.0, avg: 33.7, max: 95.0) +[2026-07-22 22:06:31,951][379328] Avg episode reward: [(0, '4928.450')] +[2026-07-22 22:06:31,956][380289] Saving new best policy, reward=4928.450! +[2026-07-22 22:06:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6826.7, 300 sec: 6886.8). Total num frames: 15073280. Throughput: 0: 6951.8. Samples: 15091712. Policy #0 lag: (min: 11.0, avg: 13.7, max: 75.0) +[2026-07-22 22:06:36,951][379328] Avg episode reward: [(0, '5050.550')] +[2026-07-22 22:06:36,957][380289] Saving new best policy, reward=5050.550! +[2026-07-22 22:06:38,301][380295] Updated weights for policy 0, policy_version 29456 (0.0007) +[2026-07-22 22:06:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6690.1, 300 sec: 6886.8). Total num frames: 15106048. Throughput: 0: 6929.1. Samples: 15112704. Policy #0 lag: (min: 11.0, avg: 13.7, max: 75.0) +[2026-07-22 22:06:41,952][379328] Avg episode reward: [(0, '5153.000')] +[2026-07-22 22:06:41,957][380289] Saving new best policy, reward=5153.000! +[2026-07-22 22:06:43,472][380295] Updated weights for policy 0, policy_version 29566 (0.0008) +[2026-07-22 22:06:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6690.1, 300 sec: 6886.8). Total num frames: 15138816. Throughput: 0: 6963.2. Samples: 15155200. Policy #0 lag: (min: 11.0, avg: 13.7, max: 75.0) +[2026-07-22 22:06:46,952][379328] Avg episode reward: [(0, '5229.050')] +[2026-07-22 22:06:46,956][380289] Saving new best policy, reward=5229.050! +[2026-07-22 22:06:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6690.1, 300 sec: 6886.8). Total num frames: 15171584. Throughput: 0: 7042.9. Samples: 15198720. Policy #0 lag: (min: 11.0, avg: 13.7, max: 75.0) +[2026-07-22 22:06:51,951][379328] Avg episode reward: [(0, '5205.600')] +[2026-07-22 22:06:52,390][380295] Updated weights for policy 0, policy_version 29664 (0.0008) +[2026-07-22 22:06:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 15204352. Throughput: 0: 7008.7. Samples: 15219200. Policy #0 lag: (min: 11.0, avg: 13.7, max: 75.0) +[2026-07-22 22:06:56,952][379328] Avg episode reward: [(0, '5268.100')] +[2026-07-22 22:06:57,239][380289] Saving new best policy, reward=5268.100! +[2026-07-22 22:06:57,547][380295] Updated weights for policy 0, policy_version 29760 (0.0007) +[2026-07-22 22:07:01,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6826.7, 300 sec: 6942.4). Total num frames: 15253504. Throughput: 0: 7054.2. Samples: 15261696. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:07:01,952][379328] Avg episode reward: [(0, '5343.300')] +[2026-07-22 22:07:02,319][380289] Saving new best policy, reward=5343.300! +[2026-07-22 22:07:06,605][380289] Signal inference workers to stop experience collection... (1400 times) +[2026-07-22 22:07:06,633][380295] InferenceWorker_p0-w0: stopping experience collection (1400 times) +[2026-07-22 22:07:06,751][380289] Signal inference workers to resume experience collection... (1400 times) +[2026-07-22 22:07:06,752][380295] InferenceWorker_p0-w0: resuming experience collection (1400 times) +[2026-07-22 22:07:06,753][380295] Updated weights for policy 0, policy_version 29872 (0.0007) +[2026-07-22 22:07:06,951][379328] Fps is (10 sec: 9011.2, 60 sec: 6963.2, 300 sec: 6970.1). Total num frames: 15294464. Throughput: 0: 7042.8. Samples: 15303680. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:07:06,952][379328] Avg episode reward: [(0, '5254.400')] +[2026-07-22 22:07:07,031][380289] Saving results/checkpoints/memory/rollout_teacher/demon_attack_teacher_fixed_l6_obs15_seed0/checkpoint_p0/checkpoint_000029888_15302656.pth... +[2026-07-22 22:07:11,710][380295] Updated weights for policy 0, policy_version 29950 (0.0007) +[2026-07-22 22:07:11,951][379328] Fps is (10 sec: 8192.0, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 15335424. Throughput: 0: 7008.7. Samples: 15323648. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:07:11,952][379328] Avg episode reward: [(0, '5336.600')] +[2026-07-22 22:07:16,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 15368192. Throughput: 0: 7054.2. Samples: 15367168. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:07:16,951][379328] Avg episode reward: [(0, '5416.450')] +[2026-07-22 22:07:16,957][380289] Saving new best policy, reward=5416.450! +[2026-07-22 22:07:20,564][380295] Updated weights for policy 0, policy_version 30048 (0.0008) +[2026-07-22 22:07:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 15400960. Throughput: 0: 7008.7. Samples: 15407104. Policy #0 lag: (min: 12.0, avg: 14.9, max: 76.0) +[2026-07-22 22:07:21,951][379328] Avg episode reward: [(0, '5475.250')] +[2026-07-22 22:07:21,957][380289] Saving new best policy, reward=5475.250! +[2026-07-22 22:07:25,568][380295] Updated weights for policy 0, policy_version 30144 (0.0007) +[2026-07-22 22:07:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 15433728. Throughput: 0: 7065.6. Samples: 15430656. Policy #0 lag: (min: 12.0, avg: 14.9, max: 76.0) +[2026-07-22 22:07:26,952][379328] Avg episode reward: [(0, '5528.050')] +[2026-07-22 22:07:26,957][380289] Saving new best policy, reward=5528.050! +[2026-07-22 22:07:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 15466496. Throughput: 0: 6997.3. Samples: 15470080. Policy #0 lag: (min: 12.0, avg: 14.9, max: 76.0) +[2026-07-22 22:07:31,952][379328] Avg episode reward: [(0, '5467.800')] +[2026-07-22 22:07:34,694][380295] Updated weights for policy 0, policy_version 30259 (0.0008) +[2026-07-22 22:07:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 15499264. Throughput: 0: 6986.0. Samples: 15513088. Policy #0 lag: (min: 12.0, avg: 14.9, max: 76.0) +[2026-07-22 22:07:36,951][379328] Avg episode reward: [(0, '5385.250')] +[2026-07-22 22:07:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 15532032. Throughput: 0: 6986.0. Samples: 15533568. Policy #0 lag: (min: 12.0, avg: 14.9, max: 76.0) +[2026-07-22 22:07:41,951][379328] Avg episode reward: [(0, '5320.900')] +[2026-07-22 22:07:43,973][380295] Updated weights for policy 0, policy_version 30368 (0.0008) +[2026-07-22 22:07:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 15564800. Throughput: 0: 6951.8. Samples: 15574528. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 22:07:46,952][379328] Avg episode reward: [(0, '5122.650')] +[2026-07-22 22:07:49,223][380295] Updated weights for policy 0, policy_version 30464 (0.0008) +[2026-07-22 22:07:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6970.1). Total num frames: 15597568. Throughput: 0: 6963.2. Samples: 15617024. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 22:07:51,952][379328] Avg episode reward: [(0, '5110.600')] +[2026-07-22 22:07:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 15630336. Throughput: 0: 6951.8. Samples: 15636480. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 22:07:56,952][379328] Avg episode reward: [(0, '5072.950')] +[2026-07-22 22:07:58,577][380295] Updated weights for policy 0, policy_version 30582 (0.0007) +[2026-07-22 22:08:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6826.7, 300 sec: 6886.8). Total num frames: 15663104. Throughput: 0: 6906.3. Samples: 15677952. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 22:08:01,952][379328] Avg episode reward: [(0, '5043.000')] +[2026-07-22 22:08:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6690.1, 300 sec: 6886.8). Total num frames: 15695872. Throughput: 0: 6906.3. Samples: 15717888. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 22:08:06,952][379328] Avg episode reward: [(0, '5143.550')] +[2026-07-22 22:08:08,131][380295] Updated weights for policy 0, policy_version 30688 (0.0008) +[2026-07-22 22:08:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 15728640. Throughput: 0: 6815.3. Samples: 15737344. Policy #0 lag: (min: 6.0, avg: 8.7, max: 70.0) +[2026-07-22 22:08:11,952][379328] Avg episode reward: [(0, '5015.300')] +[2026-07-22 22:08:13,508][380295] Updated weights for policy 0, policy_version 30784 (0.0009) +[2026-07-22 22:08:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 15761408. Throughput: 0: 6860.8. Samples: 15778816. Policy #0 lag: (min: 6.0, avg: 8.7, max: 70.0) +[2026-07-22 22:08:16,952][379328] Avg episode reward: [(0, '4894.050')] +[2026-07-22 22:08:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 15794176. Throughput: 0: 6803.9. Samples: 15819264. Policy #0 lag: (min: 6.0, avg: 8.7, max: 70.0) +[2026-07-22 22:08:21,952][379328] Avg episode reward: [(0, '4776.950')] +[2026-07-22 22:08:23,136][380295] Updated weights for policy 0, policy_version 30902 (0.0008) +[2026-07-22 22:08:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 15826944. Throughput: 0: 6769.8. Samples: 15838208. Policy #0 lag: (min: 6.0, avg: 8.7, max: 70.0) +[2026-07-22 22:08:26,951][379328] Avg episode reward: [(0, '4852.550')] +[2026-07-22 22:08:27,381][380289] Signal inference workers to stop experience collection... (1450 times) +[2026-07-22 22:08:27,411][380295] InferenceWorker_p0-w0: stopping experience collection (1450 times) +[2026-07-22 22:08:27,560][380289] Signal inference workers to resume experience collection... (1450 times) +[2026-07-22 22:08:27,561][380295] InferenceWorker_p0-w0: resuming experience collection (1450 times) +[2026-07-22 22:08:31,951][379328] Fps is (10 sec: 7372.7, 60 sec: 6690.1, 300 sec: 6914.6). Total num frames: 15867904. Throughput: 0: 6826.7. Samples: 15881728. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:08:31,952][379328] Avg episode reward: [(0, '5026.350')] +[2026-07-22 22:08:32,033][380295] Updated weights for policy 0, policy_version 31008 (0.0010) +[2026-07-22 22:08:36,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6826.7, 300 sec: 6942.4). Total num frames: 15908864. Throughput: 0: 6826.7. Samples: 15924224. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:08:36,952][379328] Avg episode reward: [(0, '5195.450')] +[2026-07-22 22:08:37,357][380295] Updated weights for policy 0, policy_version 31104 (0.0008) +[2026-07-22 22:08:41,951][379328] Fps is (10 sec: 8192.1, 60 sec: 6963.2, 300 sec: 6970.1). Total num frames: 15949824. Throughput: 0: 6826.7. Samples: 15943680. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:08:41,952][379328] Avg episode reward: [(0, '5200.800')] +[2026-07-22 22:08:46,480][380295] Updated weights for policy 0, policy_version 31219 (0.0011) +[2026-07-22 22:08:46,951][379328] Fps is (10 sec: 8191.9, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 15990784. Throughput: 0: 6860.8. Samples: 15986688. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:08:46,952][379328] Avg episode reward: [(0, '5223.650')] +[2026-07-22 22:08:51,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 16023552. Throughput: 0: 6849.4. Samples: 16026112. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:08:51,951][379328] Avg episode reward: [(0, '5216.600')] +[2026-07-22 22:08:55,555][380295] Updated weights for policy 0, policy_version 31312 (0.0008) +[2026-07-22 22:08:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 16056320. Throughput: 0: 6894.9. Samples: 16047616. Policy #0 lag: (min: 4.0, avg: 6.9, max: 68.0) +[2026-07-22 22:08:56,952][379328] Avg episode reward: [(0, '5298.250')] +[2026-07-22 22:09:01,009][380295] Updated weights for policy 0, policy_version 31424 (0.0007) +[2026-07-22 22:09:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 16089088. Throughput: 0: 6906.3. Samples: 16089600. Policy #0 lag: (min: 4.0, avg: 6.9, max: 68.0) +[2026-07-22 22:09:01,952][379328] Avg episode reward: [(0, '5316.100')] +[2026-07-22 22:09:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 16121856. Throughput: 0: 6860.8. Samples: 16128000. Policy #0 lag: (min: 4.0, avg: 6.9, max: 68.0) +[2026-07-22 22:09:06,951][379328] Avg episode reward: [(0, '5337.800')] +[2026-07-22 22:09:10,199][380295] Updated weights for policy 0, policy_version 31539 (0.0010) +[2026-07-22 22:09:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 16154624. Throughput: 0: 6974.6. Samples: 16152064. Policy #0 lag: (min: 4.0, avg: 6.9, max: 68.0) +[2026-07-22 22:09:11,952][379328] Avg episode reward: [(0, '5364.200')] +[2026-07-22 22:09:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 16187392. Throughput: 0: 6917.7. Samples: 16193024. Policy #0 lag: (min: 4.0, avg: 6.9, max: 68.0) +[2026-07-22 22:09:16,952][379328] Avg episode reward: [(0, '5395.600')] +[2026-07-22 22:09:18,985][380295] Updated weights for policy 0, policy_version 31632 (0.0008) +[2026-07-22 22:09:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 16220160. Throughput: 0: 6906.3. Samples: 16235008. Policy #0 lag: (min: 9.0, avg: 12.7, max: 73.0) +[2026-07-22 22:09:21,952][379328] Avg episode reward: [(0, '5434.000')] +[2026-07-22 22:09:24,480][380295] Updated weights for policy 0, policy_version 31744 (0.0008) +[2026-07-22 22:09:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6914.6). Total num frames: 16252928. Throughput: 0: 6929.1. Samples: 16255488. Policy #0 lag: (min: 9.0, avg: 12.7, max: 73.0) +[2026-07-22 22:09:26,952][379328] Avg episode reward: [(0, '5427.400')] +[2026-07-22 22:09:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 6886.8). Total num frames: 16285696. Throughput: 0: 6940.5. Samples: 16299008. Policy #0 lag: (min: 9.0, avg: 12.7, max: 73.0) +[2026-07-22 22:09:31,952][379328] Avg episode reward: [(0, '5351.600')] +[2026-07-22 22:09:33,410][380295] Updated weights for policy 0, policy_version 31856 (0.0009) +[2026-07-22 22:09:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6826.7, 300 sec: 6886.8). Total num frames: 16318464. Throughput: 0: 7031.5. Samples: 16342528. Policy #0 lag: (min: 9.0, avg: 12.7, max: 73.0) +[2026-07-22 22:09:36,951][379328] Avg episode reward: [(0, '5385.550')] +[2026-07-22 22:09:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6690.1, 300 sec: 6886.8). Total num frames: 16351232. Throughput: 0: 7008.7. Samples: 16363008. Policy #0 lag: (min: 9.0, avg: 12.7, max: 73.0) +[2026-07-22 22:09:41,952][379328] Avg episode reward: [(0, '5517.750')] +[2026-07-22 22:09:42,208][380295] Updated weights for policy 0, policy_version 31952 (0.0007) +[2026-07-22 22:09:46,910][380289] Signal inference workers to stop experience collection... (1500 times) +[2026-07-22 22:09:46,937][380295] InferenceWorker_p0-w0: stopping experience collection (1500 times) +[2026-07-22 22:09:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 16384000. Throughput: 0: 7020.1. Samples: 16405504. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:09:46,951][379328] Avg episode reward: [(0, '5452.050')] +[2026-07-22 22:09:47,053][380289] Signal inference workers to resume experience collection... (1500 times) +[2026-07-22 22:09:47,054][380295] InferenceWorker_p0-w0: resuming experience collection (1500 times) +[2026-07-22 22:09:47,658][380295] Updated weights for policy 0, policy_version 32061 (0.0009) +[2026-07-22 22:09:51,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6690.1, 300 sec: 6914.6). Total num frames: 16424960. Throughput: 0: 7111.1. Samples: 16448000. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:09:51,952][379328] Avg episode reward: [(0, '5412.600')] +[2026-07-22 22:09:56,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6826.7, 300 sec: 6942.4). Total num frames: 16465920. Throughput: 0: 6997.3. Samples: 16466944. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:09:56,951][379328] Avg episode reward: [(0, '5375.700')] +[2026-07-22 22:09:57,100][380295] Updated weights for policy 0, policy_version 32182 (0.0007) +[2026-07-22 22:10:01,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6963.2, 300 sec: 6970.1). Total num frames: 16506880. Throughput: 0: 7008.7. Samples: 16508416. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:10:01,952][379328] Avg episode reward: [(0, '5418.550')] +[2026-07-22 22:10:06,340][380295] Updated weights for policy 0, policy_version 32288 (0.0009) +[2026-07-22 22:10:06,951][379328] Fps is (10 sec: 8192.0, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 16547840. Throughput: 0: 6974.6. Samples: 16548864. Policy #0 lag: (min: 6.0, avg: 8.7, max: 70.0) +[2026-07-22 22:10:06,952][379328] Avg episode reward: [(0, '5386.600')] +[2026-07-22 22:10:11,585][380295] Updated weights for policy 0, policy_version 32384 (0.0008) +[2026-07-22 22:10:11,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 16580608. Throughput: 0: 7008.7. Samples: 16570880. Policy #0 lag: (min: 6.0, avg: 8.7, max: 70.0) +[2026-07-22 22:10:11,952][379328] Avg episode reward: [(0, '5429.400')] +[2026-07-22 22:10:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 16613376. Throughput: 0: 6974.6. Samples: 16612864. Policy #0 lag: (min: 6.0, avg: 8.7, max: 70.0) +[2026-07-22 22:10:16,951][379328] Avg episode reward: [(0, '5457.100')] +[2026-07-22 22:10:20,663][380295] Updated weights for policy 0, policy_version 32498 (0.0008) +[2026-07-22 22:10:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 16646144. Throughput: 0: 6894.9. Samples: 16652800. Policy #0 lag: (min: 6.0, avg: 8.7, max: 70.0) +[2026-07-22 22:10:21,952][379328] Avg episode reward: [(0, '5430.300')] +[2026-07-22 22:10:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6970.1). Total num frames: 16678912. Throughput: 0: 6940.4. Samples: 16675328. Policy #0 lag: (min: 6.0, avg: 8.7, max: 70.0) +[2026-07-22 22:10:26,952][379328] Avg episode reward: [(0, '5377.800')] +[2026-07-22 22:10:29,879][380295] Updated weights for policy 0, policy_version 32592 (0.0007) +[2026-07-22 22:10:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6942.4). Total num frames: 16711680. Throughput: 0: 6860.8. Samples: 16714240. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:10:31,951][379328] Avg episode reward: [(0, '5413.800')] +[2026-07-22 22:10:35,003][380295] Updated weights for policy 0, policy_version 32701 (0.0007) +[2026-07-22 22:10:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6914.6). Total num frames: 16744448. Throughput: 0: 6860.8. Samples: 16756736. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:10:36,951][379328] Avg episode reward: [(0, '5283.400')] +[2026-07-22 22:10:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6914.6). Total num frames: 16777216. Throughput: 0: 6906.3. Samples: 16777728. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:10:41,952][379328] Avg episode reward: [(0, '5435.550')] +[2026-07-22 22:10:44,723][380295] Updated weights for policy 0, policy_version 32800 (0.0008) +[2026-07-22 22:10:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6914.6). Total num frames: 16809984. Throughput: 0: 6815.3. Samples: 16815104. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:10:46,952][379328] Avg episode reward: [(0, '5358.450')] +[2026-07-22 22:10:49,798][380295] Updated weights for policy 0, policy_version 32896 (0.0007) +[2026-07-22 22:10:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 6886.8). Total num frames: 16842752. Throughput: 0: 6906.3. Samples: 16859648. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:10:51,952][379328] Avg episode reward: [(0, '5487.450')] +[2026-07-22 22:10:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6826.7, 300 sec: 6886.8). Total num frames: 16875520. Throughput: 0: 6872.2. Samples: 16880128. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:10:56,952][379328] Avg episode reward: [(0, '5469.250')] +[2026-07-22 22:10:58,635][380295] Updated weights for policy 0, policy_version 33008 (0.0008) +[2026-07-22 22:11:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6690.1, 300 sec: 6886.8). Total num frames: 16908288. Throughput: 0: 6849.4. Samples: 16921088. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:11:01,952][379328] Avg episode reward: [(0, '5365.150')] +[2026-07-22 22:11:03,495][380289] Signal inference workers to stop experience collection... (1550 times) +[2026-07-22 22:11:03,525][380295] InferenceWorker_p0-w0: stopping experience collection (1550 times) +[2026-07-22 22:11:03,672][380289] Signal inference workers to resume experience collection... (1550 times) +[2026-07-22 22:11:03,673][380295] InferenceWorker_p0-w0: resuming experience collection (1550 times) +[2026-07-22 22:11:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 16941056. Throughput: 0: 6883.6. Samples: 16962560. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:11:06,952][379328] Avg episode reward: [(0, '5343.750')] +[2026-07-22 22:11:08,041][380295] Updated weights for policy 0, policy_version 33104 (0.0007) +[2026-07-22 22:11:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 16973824. Throughput: 0: 6815.3. Samples: 16982016. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:11:11,952][379328] Avg episode reward: [(0, '5276.150')] +[2026-07-22 22:11:13,269][380295] Updated weights for policy 0, policy_version 33211 (0.0008) +[2026-07-22 22:11:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 17006592. Throughput: 0: 6894.9. Samples: 17024512. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:11:16,951][379328] Avg episode reward: [(0, '5242.150')] +[2026-07-22 22:11:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6553.6, 300 sec: 6886.8). Total num frames: 17039360. Throughput: 0: 6940.5. Samples: 17069056. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:11:21,952][379328] Avg episode reward: [(0, '5305.050')] +[2026-07-22 22:11:22,120][380295] Updated weights for policy 0, policy_version 33312 (0.0006) +[2026-07-22 22:11:26,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6826.7, 300 sec: 6942.4). Total num frames: 17088512. Throughput: 0: 6883.6. Samples: 17087488. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:11:26,951][379328] Avg episode reward: [(0, '5343.700')] +[2026-07-22 22:11:27,285][380295] Updated weights for policy 0, policy_version 33408 (0.0007) +[2026-07-22 22:11:31,951][379328] Fps is (10 sec: 9830.4, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17137664. Throughput: 0: 7031.5. Samples: 17131520. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:11:31,952][379328] Avg episode reward: [(0, '5383.950')] +[2026-07-22 22:11:36,501][380295] Updated weights for policy 0, policy_version 33530 (0.0006) +[2026-07-22 22:11:36,951][379328] Fps is (10 sec: 8192.0, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17170432. Throughput: 0: 6940.4. Samples: 17171968. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:11:36,952][379328] Avg episode reward: [(0, '5530.450')] +[2026-07-22 22:11:36,956][380289] Saving new best policy, reward=5530.450! +[2026-07-22 22:11:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17203200. Throughput: 0: 6997.3. Samples: 17195008. Policy #0 lag: (min: 7.0, avg: 9.6, max: 71.0) +[2026-07-22 22:11:41,952][379328] Avg episode reward: [(0, '5525.900')] +[2026-07-22 22:11:45,375][380295] Updated weights for policy 0, policy_version 33648 (0.0006) +[2026-07-22 22:11:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17235968. Throughput: 0: 7031.5. Samples: 17237504. Policy #0 lag: (min: 7.0, avg: 9.6, max: 71.0) +[2026-07-22 22:11:46,951][379328] Avg episode reward: [(0, '5457.200')] +[2026-07-22 22:11:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17268736. Throughput: 0: 7031.5. Samples: 17278976. Policy #0 lag: (min: 7.0, avg: 9.6, max: 71.0) +[2026-07-22 22:11:51,952][379328] Avg episode reward: [(0, '5463.550')] +[2026-07-22 22:11:54,460][380295] Updated weights for policy 0, policy_version 33744 (0.0006) +[2026-07-22 22:11:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6942.4). Total num frames: 17301504. Throughput: 0: 7111.1. Samples: 17302016. Policy #0 lag: (min: 7.0, avg: 9.6, max: 71.0) +[2026-07-22 22:11:56,951][379328] Avg episode reward: [(0, '5498.650')] +[2026-07-22 22:11:59,881][380295] Updated weights for policy 0, policy_version 33854 (0.0006) +[2026-07-22 22:12:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6914.6). Total num frames: 17334272. Throughput: 0: 7042.8. Samples: 17341440. Policy #0 lag: (min: 7.0, avg: 9.6, max: 71.0) +[2026-07-22 22:12:01,951][379328] Avg episode reward: [(0, '5513.650')] +[2026-07-22 22:12:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 17367040. Throughput: 0: 7031.5. Samples: 17385472. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:12:06,952][379328] Avg episode reward: [(0, '5635.100')] +[2026-07-22 22:12:06,956][380289] Saving new best policy, reward=5635.100! +[2026-07-22 22:12:08,529][380295] Updated weights for policy 0, policy_version 33952 (0.0007) +[2026-07-22 22:12:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 17399808. Throughput: 0: 7065.6. Samples: 17405440. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:12:11,952][379328] Avg episode reward: [(0, '5681.750')] +[2026-07-22 22:12:11,958][380289] Saving new best policy, reward=5681.750! +[2026-07-22 22:12:13,552][380295] Updated weights for policy 0, policy_version 34048 (0.0008) +[2026-07-22 22:12:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 17432576. Throughput: 0: 7088.4. Samples: 17450496. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:12:16,952][379328] Avg episode reward: [(0, '5737.150')] +[2026-07-22 22:12:16,956][380289] Saving new best policy, reward=5737.150! +[2026-07-22 22:12:21,951][379328] Fps is (10 sec: 6553.5, 60 sec: 7099.7, 300 sec: 6886.8). Total num frames: 17465344. Throughput: 0: 7145.2. Samples: 17493504. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:12:21,952][379328] Avg episode reward: [(0, '5780.300')] +[2026-07-22 22:12:22,096][380289] Signal inference workers to stop experience collection... (1600 times) +[2026-07-22 22:12:22,124][380295] InferenceWorker_p0-w0: stopping experience collection (1600 times) +[2026-07-22 22:12:22,273][380289] Signal inference workers to resume experience collection... (1600 times) +[2026-07-22 22:12:22,273][380289] Saving new best policy, reward=5780.300! +[2026-07-22 22:12:22,273][380295] InferenceWorker_p0-w0: resuming experience collection (1600 times) +[2026-07-22 22:12:22,576][380295] Updated weights for policy 0, policy_version 34166 (0.0006) +[2026-07-22 22:12:26,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7236.3, 300 sec: 6970.1). Total num frames: 17522688. Throughput: 0: 7122.5. Samples: 17515520. Policy #0 lag: (min: 8.0, avg: 10.7, max: 72.0) +[2026-07-22 22:12:26,952][379328] Avg episode reward: [(0, '5842.400')] +[2026-07-22 22:12:27,170][380289] Saving new best policy, reward=5842.400! +[2026-07-22 22:12:31,302][380295] Updated weights for policy 0, policy_version 34272 (0.0006) +[2026-07-22 22:12:31,951][379328] Fps is (10 sec: 9830.5, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17563648. Throughput: 0: 7156.6. Samples: 17559552. Policy #0 lag: (min: 8.0, avg: 10.7, max: 72.0) +[2026-07-22 22:12:31,952][379328] Avg episode reward: [(0, '5786.350')] +[2026-07-22 22:12:36,440][380295] Updated weights for policy 0, policy_version 34368 (0.0006) +[2026-07-22 22:12:36,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17596416. Throughput: 0: 7111.1. Samples: 17598976. Policy #0 lag: (min: 8.0, avg: 10.7, max: 72.0) +[2026-07-22 22:12:36,951][379328] Avg episode reward: [(0, '5777.300')] +[2026-07-22 22:12:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17629184. Throughput: 0: 7133.9. Samples: 17623040. Policy #0 lag: (min: 8.0, avg: 10.7, max: 72.0) +[2026-07-22 22:12:41,952][379328] Avg episode reward: [(0, '5781.050')] +[2026-07-22 22:12:45,257][380295] Updated weights for policy 0, policy_version 34486 (0.0006) +[2026-07-22 22:12:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17661952. Throughput: 0: 7179.4. Samples: 17664512. Policy #0 lag: (min: 8.0, avg: 10.7, max: 72.0) +[2026-07-22 22:12:46,951][379328] Avg episode reward: [(0, '5864.000')] +[2026-07-22 22:12:46,956][380289] Saving new best policy, reward=5864.000! +[2026-07-22 22:12:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17694720. Throughput: 0: 7133.9. Samples: 17706496. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:12:51,951][379328] Avg episode reward: [(0, '5916.300')] +[2026-07-22 22:12:51,956][380289] Saving new best policy, reward=5916.300! +[2026-07-22 22:12:54,472][380295] Updated weights for policy 0, policy_version 34592 (0.0006) +[2026-07-22 22:12:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17727488. Throughput: 0: 7168.0. Samples: 17728000. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:12:56,952][379328] Avg episode reward: [(0, '5925.750')] +[2026-07-22 22:12:56,956][380289] Saving new best policy, reward=5925.750! +[2026-07-22 22:12:59,600][380295] Updated weights for policy 0, policy_version 34688 (0.0007) +[2026-07-22 22:13:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17760256. Throughput: 0: 7088.4. Samples: 17769472. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:13:01,952][379328] Avg episode reward: [(0, '6096.450')] +[2026-07-22 22:13:01,956][380289] Saving new best policy, reward=6096.450! +[2026-07-22 22:13:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17793024. Throughput: 0: 7088.4. Samples: 17812480. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:13:06,952][379328] Avg episode reward: [(0, '6025.250')] +[2026-07-22 22:13:08,832][380295] Updated weights for policy 0, policy_version 34814 (0.0007) +[2026-07-22 22:13:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17825792. Throughput: 0: 7042.9. Samples: 17832448. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:13:11,952][379328] Avg episode reward: [(0, '6033.100')] +[2026-07-22 22:13:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17858560. Throughput: 0: 6985.9. Samples: 17873920. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:13:16,952][379328] Avg episode reward: [(0, '5905.550')] +[2026-07-22 22:13:18,099][380295] Updated weights for policy 0, policy_version 34928 (0.0006) +[2026-07-22 22:13:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 17891328. Throughput: 0: 7077.0. Samples: 17917440. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:13:21,952][379328] Avg episode reward: [(0, '5896.250')] +[2026-07-22 22:13:22,978][380295] Updated weights for policy 0, policy_version 35005 (0.0006) +[2026-07-22 22:13:26,951][379328] Fps is (10 sec: 8192.1, 60 sec: 6963.2, 300 sec: 7025.7). Total num frames: 17940480. Throughput: 0: 6986.0. Samples: 17937408. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:13:26,952][379328] Avg episode reward: [(0, '5857.750')] +[2026-07-22 22:13:31,639][380295] Updated weights for policy 0, policy_version 35120 (0.0006) +[2026-07-22 22:13:31,951][379328] Fps is (10 sec: 9830.4, 60 sec: 7099.7, 300 sec: 7053.5). Total num frames: 17989632. Throughput: 0: 7054.2. Samples: 17981952. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:13:31,951][379328] Avg episode reward: [(0, '5874.450')] +[2026-07-22 22:13:36,561][380295] Updated weights for policy 0, policy_version 35200 (0.0006) +[2026-07-22 22:13:36,951][379328] Fps is (10 sec: 8192.0, 60 sec: 7099.7, 300 sec: 7025.7). Total num frames: 18022400. Throughput: 0: 7065.6. Samples: 18024448. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:13:36,952][379328] Avg episode reward: [(0, '5969.000')] +[2026-07-22 22:13:40,362][380289] Signal inference workers to stop experience collection... (1650 times) +[2026-07-22 22:13:40,388][380295] InferenceWorker_p0-w0: stopping experience collection (1650 times) +[2026-07-22 22:13:40,537][380289] Signal inference workers to resume experience collection... (1650 times) +[2026-07-22 22:13:40,537][380295] InferenceWorker_p0-w0: resuming experience collection (1650 times) +[2026-07-22 22:13:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 18055168. Throughput: 0: 7111.1. Samples: 18048000. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:13:41,952][379328] Avg episode reward: [(0, '6050.600')] +[2026-07-22 22:13:45,419][380295] Updated weights for policy 0, policy_version 35314 (0.0008) +[2026-07-22 22:13:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 18087936. Throughput: 0: 7111.1. Samples: 18089472. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:13:46,951][379328] Avg episode reward: [(0, '6011.300')] +[2026-07-22 22:13:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 18120704. Throughput: 0: 7122.5. Samples: 18132992. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:13:51,952][379328] Avg episode reward: [(0, '5946.400')] +[2026-07-22 22:13:54,265][380295] Updated weights for policy 0, policy_version 35424 (0.0006) +[2026-07-22 22:13:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 18153472. Throughput: 0: 7168.0. Samples: 18155008. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:13:56,951][379328] Avg episode reward: [(0, '5929.600')] +[2026-07-22 22:13:59,333][380295] Updated weights for policy 0, policy_version 35513 (0.0008) +[2026-07-22 22:14:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 18186240. Throughput: 0: 7168.0. Samples: 18196480. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 22:14:01,951][379328] Avg episode reward: [(0, '5790.250')] +[2026-07-22 22:14:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 18219008. Throughput: 0: 7179.4. Samples: 18240512. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 22:14:06,952][379328] Avg episode reward: [(0, '5944.150')] +[2026-07-22 22:14:08,233][380295] Updated weights for policy 0, policy_version 35632 (0.0006) +[2026-07-22 22:14:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 18251776. Throughput: 0: 7213.5. Samples: 18262016. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 22:14:11,951][379328] Avg episode reward: [(0, '5973.700')] +[2026-07-22 22:14:12,906][380295] Updated weights for policy 0, policy_version 35712 (0.0006) +[2026-07-22 22:14:16,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7236.3, 300 sec: 7025.7). Total num frames: 18292736. Throughput: 0: 7236.3. Samples: 18307584. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 22:14:16,951][379328] Avg episode reward: [(0, '5998.900')] +[2026-07-22 22:14:21,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7509.3, 300 sec: 7081.2). Total num frames: 18341888. Throughput: 0: 7224.9. Samples: 18349568. Policy #0 lag: (min: 24.0, avg: 26.8, max: 88.0) +[2026-07-22 22:14:21,952][379328] Avg episode reward: [(0, '6036.900')] +[2026-07-22 22:14:22,014][380295] Updated weights for policy 0, policy_version 35830 (0.0006) +[2026-07-22 22:14:26,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7372.8, 300 sec: 7109.0). Total num frames: 18382848. Throughput: 0: 7156.6. Samples: 18370048. Policy #0 lag: (min: 24.0, avg: 26.8, max: 88.0) +[2026-07-22 22:14:26,951][379328] Avg episode reward: [(0, '6037.250')] +[2026-07-22 22:14:30,703][380295] Updated weights for policy 0, policy_version 35936 (0.0006) +[2026-07-22 22:14:31,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 18415616. Throughput: 0: 7247.6. Samples: 18415616. Policy #0 lag: (min: 24.0, avg: 26.8, max: 88.0) +[2026-07-22 22:14:31,951][379328] Avg episode reward: [(0, '6145.700')] +[2026-07-22 22:14:31,957][380289] Saving new best policy, reward=6145.700! +[2026-07-22 22:14:35,652][380295] Updated weights for policy 0, policy_version 36032 (0.0009) +[2026-07-22 22:14:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 18448384. Throughput: 0: 7213.5. Samples: 18457600. Policy #0 lag: (min: 24.0, avg: 26.8, max: 88.0) +[2026-07-22 22:14:36,952][379328] Avg episode reward: [(0, '6062.300')] +[2026-07-22 22:14:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 18481152. Throughput: 0: 7247.6. Samples: 18481152. Policy #0 lag: (min: 24.0, avg: 26.8, max: 88.0) +[2026-07-22 22:14:41,952][379328] Avg episode reward: [(0, '6048.700')] +[2026-07-22 22:14:44,486][380295] Updated weights for policy 0, policy_version 36144 (0.0007) +[2026-07-22 22:14:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7081.2). Total num frames: 18513920. Throughput: 0: 7213.5. Samples: 18521088. Policy #0 lag: (min: 24.0, avg: 26.8, max: 88.0) +[2026-07-22 22:14:46,952][379328] Avg episode reward: [(0, '5940.100')] +[2026-07-22 22:14:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7053.5). Total num frames: 18546688. Throughput: 0: 7224.9. Samples: 18565632. Policy #0 lag: (min: 14.0, avg: 16.7, max: 78.0) +[2026-07-22 22:14:51,951][379328] Avg episode reward: [(0, '6009.550')] +[2026-07-22 22:14:53,286][380295] Updated weights for policy 0, policy_version 36240 (0.0007) +[2026-07-22 22:14:53,462][380289] Signal inference workers to stop experience collection... (1700 times) +[2026-07-22 22:14:53,491][380295] InferenceWorker_p0-w0: stopping experience collection (1700 times) +[2026-07-22 22:14:53,637][380289] Signal inference workers to resume experience collection... (1700 times) +[2026-07-22 22:14:53,637][380295] InferenceWorker_p0-w0: resuming experience collection (1700 times) +[2026-07-22 22:14:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7025.7). Total num frames: 18579456. Throughput: 0: 7179.4. Samples: 18585088. Policy #0 lag: (min: 14.0, avg: 16.7, max: 78.0) +[2026-07-22 22:14:56,952][379328] Avg episode reward: [(0, '6184.450')] +[2026-07-22 22:14:56,956][380289] Saving new best policy, reward=6184.450! +[2026-07-22 22:14:58,618][380295] Updated weights for policy 0, policy_version 36352 (0.0006) +[2026-07-22 22:15:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 18612224. Throughput: 0: 7133.9. Samples: 18628608. Policy #0 lag: (min: 14.0, avg: 16.7, max: 78.0) +[2026-07-22 22:15:01,952][379328] Avg episode reward: [(0, '6275.200')] +[2026-07-22 22:15:01,956][380289] Saving new best policy, reward=6275.200! +[2026-07-22 22:15:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 18644992. Throughput: 0: 7213.5. Samples: 18674176. Policy #0 lag: (min: 14.0, avg: 16.7, max: 78.0) +[2026-07-22 22:15:06,952][379328] Avg episode reward: [(0, '6232.700')] +[2026-07-22 22:15:07,451][380295] Updated weights for policy 0, policy_version 36471 (0.0007) +[2026-07-22 22:15:11,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7509.3, 300 sec: 7081.2). Total num frames: 18702336. Throughput: 0: 7224.9. Samples: 18695168. Policy #0 lag: (min: 14.0, avg: 16.7, max: 78.0) +[2026-07-22 22:15:11,952][379328] Avg episode reward: [(0, '6240.650')] +[2026-07-22 22:15:16,589][380295] Updated weights for policy 0, policy_version 36576 (0.0007) +[2026-07-22 22:15:16,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7372.8, 300 sec: 7081.2). Total num frames: 18735104. Throughput: 0: 7133.9. Samples: 18736640. Policy #0 lag: (min: 63.0, avg: 65.7, max: 127.0) +[2026-07-22 22:15:16,952][379328] Avg episode reward: [(0, '6328.300')] +[2026-07-22 22:15:17,081][380289] Saving new best policy, reward=6328.300! +[2026-07-22 22:15:21,912][380295] Updated weights for policy 0, policy_version 36669 (0.0007) +[2026-07-22 22:15:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7081.2). Total num frames: 18767872. Throughput: 0: 7088.3. Samples: 18776576. Policy #0 lag: (min: 63.0, avg: 65.7, max: 127.0) +[2026-07-22 22:15:21,952][379328] Avg episode reward: [(0, '6325.950')] +[2026-07-22 22:15:26,951][379328] Fps is (10 sec: 7372.7, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 18808832. Throughput: 0: 7077.0. Samples: 18799616. Policy #0 lag: (min: 63.0, avg: 65.7, max: 127.0) +[2026-07-22 22:15:26,952][379328] Avg episode reward: [(0, '6319.050')] +[2026-07-22 22:15:30,704][380295] Updated weights for policy 0, policy_version 36784 (0.0007) +[2026-07-22 22:15:31,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 18841600. Throughput: 0: 7133.9. Samples: 18842112. Policy #0 lag: (min: 63.0, avg: 65.7, max: 127.0) +[2026-07-22 22:15:31,952][379328] Avg episode reward: [(0, '6285.500')] +[2026-07-22 22:15:36,951][379328] Fps is (10 sec: 6553.7, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 18874368. Throughput: 0: 7065.6. Samples: 18883584. Policy #0 lag: (min: 63.0, avg: 65.7, max: 127.0) +[2026-07-22 22:15:36,951][379328] Avg episode reward: [(0, '6374.650')] +[2026-07-22 22:15:36,956][380289] Saving new best policy, reward=6374.650! +[2026-07-22 22:15:39,587][380295] Updated weights for policy 0, policy_version 36880 (0.0007) +[2026-07-22 22:15:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 18907136. Throughput: 0: 7145.3. Samples: 18906624. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:15:41,952][379328] Avg episode reward: [(0, '6411.250')] +[2026-07-22 22:15:41,956][380289] Saving new best policy, reward=6411.250! +[2026-07-22 22:15:45,010][380295] Updated weights for policy 0, policy_version 36989 (0.0006) +[2026-07-22 22:15:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 18939904. Throughput: 0: 7031.5. Samples: 18945024. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:15:46,952][379328] Avg episode reward: [(0, '6620.000')] +[2026-07-22 22:15:46,957][380289] Saving new best policy, reward=6620.000! +[2026-07-22 22:15:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 18972672. Throughput: 0: 7008.7. Samples: 18989568. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:15:51,952][379328] Avg episode reward: [(0, '6638.250')] +[2026-07-22 22:15:51,956][380289] Saving new best policy, reward=6638.250! +[2026-07-22 22:15:53,788][380295] Updated weights for policy 0, policy_version 37088 (0.0007) +[2026-07-22 22:15:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19005440. Throughput: 0: 6974.6. Samples: 19009024. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:15:56,952][379328] Avg episode reward: [(0, '6702.500')] +[2026-07-22 22:15:56,956][380289] Saving new best policy, reward=6702.500! +[2026-07-22 22:15:58,680][380295] Updated weights for policy 0, policy_version 37177 (0.0006) +[2026-07-22 22:16:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19038208. Throughput: 0: 7042.8. Samples: 19053568. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:16:01,952][379328] Avg episode reward: [(0, '6794.600')] +[2026-07-22 22:16:01,957][380289] Saving new best policy, reward=6794.600! +[2026-07-22 22:16:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19070976. Throughput: 0: 7179.4. Samples: 19099648. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:16:06,952][379328] Avg episode reward: [(0, '6732.100')] +[2026-07-22 22:16:07,231][380295] Updated weights for policy 0, policy_version 37280 (0.0008) +[2026-07-22 22:16:11,466][380289] Signal inference workers to stop experience collection... (1750 times) +[2026-07-22 22:16:11,496][380295] InferenceWorker_p0-w0: stopping experience collection (1750 times) +[2026-07-22 22:16:11,642][380289] Signal inference workers to resume experience collection... (1750 times) +[2026-07-22 22:16:11,642][380295] InferenceWorker_p0-w0: resuming experience collection (1750 times) +[2026-07-22 22:16:11,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7099.7, 300 sec: 7192.3). Total num frames: 19128320. Throughput: 0: 7122.5. Samples: 19120128. Policy #0 lag: (min: 9.0, avg: 12.0, max: 73.0) +[2026-07-22 22:16:11,952][379328] Avg episode reward: [(0, '6748.350')] +[2026-07-22 22:16:11,976][380295] Updated weights for policy 0, policy_version 37370 (0.0007) +[2026-07-22 22:16:16,951][379328] Fps is (10 sec: 9830.4, 60 sec: 7236.3, 300 sec: 7220.1). Total num frames: 19169280. Throughput: 0: 7202.1. Samples: 19166208. Policy #0 lag: (min: 9.0, avg: 12.0, max: 73.0) +[2026-07-22 22:16:16,952][379328] Avg episode reward: [(0, '6772.300')] +[2026-07-22 22:16:21,040][380295] Updated weights for policy 0, policy_version 37488 (0.0009) +[2026-07-22 22:16:21,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7236.3, 300 sec: 7164.5). Total num frames: 19202048. Throughput: 0: 7156.6. Samples: 19205632. Policy #0 lag: (min: 9.0, avg: 12.0, max: 73.0) +[2026-07-22 22:16:21,952][379328] Avg episode reward: [(0, '6761.400')] +[2026-07-22 22:16:26,010][380295] Updated weights for policy 0, policy_version 37562 (0.0008) +[2026-07-22 22:16:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19234816. Throughput: 0: 7133.9. Samples: 19227648. Policy #0 lag: (min: 9.0, avg: 12.0, max: 73.0) +[2026-07-22 22:16:26,952][379328] Avg episode reward: [(0, '6759.450')] +[2026-07-22 22:16:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19267584. Throughput: 0: 7202.1. Samples: 19269120. Policy #0 lag: (min: 9.0, avg: 12.0, max: 73.0) +[2026-07-22 22:16:31,952][379328] Avg episode reward: [(0, '6738.850')] +[2026-07-22 22:16:34,713][380295] Updated weights for policy 0, policy_version 37680 (0.0007) +[2026-07-22 22:16:36,951][379328] Fps is (10 sec: 6553.7, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19300352. Throughput: 0: 7236.3. Samples: 19315200. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:16:36,952][379328] Avg episode reward: [(0, '6769.300')] +[2026-07-22 22:16:39,204][380295] Updated weights for policy 0, policy_version 37758 (0.0007) +[2026-07-22 22:16:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19333120. Throughput: 0: 7304.5. Samples: 19337728. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:16:41,952][379328] Avg episode reward: [(0, '6784.300')] +[2026-07-22 22:16:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19365888. Throughput: 0: 7270.4. Samples: 19380736. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:16:46,952][379328] Avg episode reward: [(0, '6797.200')] +[2026-07-22 22:16:46,956][380289] Saving new best policy, reward=6797.200! +[2026-07-22 22:16:48,178][380295] Updated weights for policy 0, policy_version 37856 (0.0007) +[2026-07-22 22:16:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19398656. Throughput: 0: 7190.8. Samples: 19423232. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:16:51,952][379328] Avg episode reward: [(0, '6895.500')] +[2026-07-22 22:16:51,957][380289] Saving new best policy, reward=6895.500! +[2026-07-22 22:16:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19431424. Throughput: 0: 7168.0. Samples: 19442688. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:16:56,952][379328] Avg episode reward: [(0, '6948.600')] +[2026-07-22 22:16:56,957][380289] Saving new best policy, reward=6948.600! +[2026-07-22 22:16:57,416][380295] Updated weights for policy 0, policy_version 37968 (0.0007) +[2026-07-22 22:17:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19464192. Throughput: 0: 7111.1. Samples: 19486208. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:17:01,952][379328] Avg episode reward: [(0, '6934.150')] +[2026-07-22 22:17:02,471][380295] Updated weights for policy 0, policy_version 38066 (0.0008) +[2026-07-22 22:17:06,951][379328] Fps is (10 sec: 9011.1, 60 sec: 7509.3, 300 sec: 7192.3). Total num frames: 19521536. Throughput: 0: 7179.4. Samples: 19528704. Policy #0 lag: (min: 15.0, avg: 18.0, max: 79.0) +[2026-07-22 22:17:06,952][379328] Avg episode reward: [(0, '6846.050')] +[2026-07-22 22:17:07,163][380289] Saving results/checkpoints/memory/rollout_teacher/demon_attack_teacher_fixed_l6_obs15_seed0/checkpoint_p0/checkpoint_000038144_19529728.pth... +[2026-07-22 22:17:11,105][380295] Updated weights for policy 0, policy_version 38160 (0.0013) +[2026-07-22 22:17:11,951][379328] Fps is (10 sec: 9830.4, 60 sec: 7236.3, 300 sec: 7220.1). Total num frames: 19562496. Throughput: 0: 7168.0. Samples: 19550208. Policy #0 lag: (min: 15.0, avg: 18.0, max: 79.0) +[2026-07-22 22:17:11,952][379328] Avg episode reward: [(0, '6840.450')] +[2026-07-22 22:17:16,048][380295] Updated weights for policy 0, policy_version 38262 (0.0009) +[2026-07-22 22:17:16,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 19595264. Throughput: 0: 7236.2. Samples: 19594752. Policy #0 lag: (min: 15.0, avg: 18.0, max: 79.0) +[2026-07-22 22:17:16,953][379328] Avg episode reward: [(0, '6917.400')] +[2026-07-22 22:17:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7136.8). Total num frames: 19628032. Throughput: 0: 7042.8. Samples: 19632128. Policy #0 lag: (min: 15.0, avg: 18.0, max: 79.0) +[2026-07-22 22:17:21,952][379328] Avg episode reward: [(0, '7001.400')] +[2026-07-22 22:17:21,957][380289] Saving new best policy, reward=7001.400! +[2026-07-22 22:17:25,548][380295] Updated weights for policy 0, policy_version 38368 (0.0008) +[2026-07-22 22:17:26,951][379328] Fps is (10 sec: 6553.7, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19660800. Throughput: 0: 7042.8. Samples: 19654656. Policy #0 lag: (min: 15.0, avg: 18.0, max: 79.0) +[2026-07-22 22:17:26,952][379328] Avg episode reward: [(0, '7183.100')] +[2026-07-22 22:17:27,001][380289] Saving new best policy, reward=7183.100! +[2026-07-22 22:17:29,669][380289] Signal inference workers to stop experience collection... (1800 times) +[2026-07-22 22:17:29,695][380295] InferenceWorker_p0-w0: stopping experience collection (1800 times) +[2026-07-22 22:17:29,811][380289] Signal inference workers to resume experience collection... (1800 times) +[2026-07-22 22:17:29,811][380295] InferenceWorker_p0-w0: resuming experience collection (1800 times) +[2026-07-22 22:17:30,427][380295] Updated weights for policy 0, policy_version 38464 (0.0007) +[2026-07-22 22:17:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19693568. Throughput: 0: 7008.7. Samples: 19696128. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:17:31,952][379328] Avg episode reward: [(0, '7246.450')] +[2026-07-22 22:17:31,957][380289] Saving new best policy, reward=7246.450! +[2026-07-22 22:17:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19726336. Throughput: 0: 7031.5. Samples: 19739648. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:17:36,952][379328] Avg episode reward: [(0, '7310.050')] +[2026-07-22 22:17:36,994][380289] Saving new best policy, reward=7310.050! +[2026-07-22 22:17:39,746][380295] Updated weights for policy 0, policy_version 38590 (0.0007) +[2026-07-22 22:17:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19759104. Throughput: 0: 7054.2. Samples: 19760128. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:17:41,952][379328] Avg episode reward: [(0, '7338.050')] +[2026-07-22 22:17:41,959][380289] Saving new best policy, reward=7338.050! +[2026-07-22 22:17:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19791872. Throughput: 0: 6997.3. Samples: 19801088. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:17:46,951][379328] Avg episode reward: [(0, '7328.300')] +[2026-07-22 22:17:48,884][380295] Updated weights for policy 0, policy_version 38704 (0.0007) +[2026-07-22 22:17:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19824640. Throughput: 0: 7020.1. Samples: 19844608. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:17:51,952][379328] Avg episode reward: [(0, '7292.400')] +[2026-07-22 22:17:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19857408. Throughput: 0: 6940.5. Samples: 19862528. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:17:56,952][379328] Avg episode reward: [(0, '7069.600')] +[2026-07-22 22:17:58,507][380295] Updated weights for policy 0, policy_version 38816 (0.0008) +[2026-07-22 22:18:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 19890176. Throughput: 0: 6872.2. Samples: 19904000. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:18:01,952][379328] Avg episode reward: [(0, '7071.600')] +[2026-07-22 22:18:03,317][380295] Updated weights for policy 0, policy_version 38909 (0.0007) +[2026-07-22 22:18:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6690.1, 300 sec: 7109.0). Total num frames: 19922944. Throughput: 0: 7042.8. Samples: 19949056. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:18:06,952][379328] Avg episode reward: [(0, '7108.200')] +[2026-07-22 22:18:11,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6690.1, 300 sec: 7136.8). Total num frames: 19963904. Throughput: 0: 6997.3. Samples: 19969536. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:18:11,951][379328] Avg episode reward: [(0, '7127.900')] +[2026-07-22 22:18:12,081][380295] Updated weights for policy 0, policy_version 39008 (0.0008) +[2026-07-22 22:18:16,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6826.7, 300 sec: 7164.5). Total num frames: 20004864. Throughput: 0: 7042.9. Samples: 20013056. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:18:16,952][379328] Avg episode reward: [(0, '7071.500')] +[2026-07-22 22:18:17,361][380295] Updated weights for policy 0, policy_version 39102 (0.0007) +[2026-07-22 22:18:21,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6963.2, 300 sec: 7136.8). Total num frames: 20045824. Throughput: 0: 6997.3. Samples: 20054528. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:18:21,952][379328] Avg episode reward: [(0, '6996.700')] +[2026-07-22 22:18:26,448][380295] Updated weights for policy 0, policy_version 39200 (0.0008) +[2026-07-22 22:18:26,951][379328] Fps is (10 sec: 8192.0, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20086784. Throughput: 0: 6974.6. Samples: 20073984. Policy #0 lag: (min: 0.0, avg: 2.9, max: 64.0) +[2026-07-22 22:18:26,952][379328] Avg episode reward: [(0, '7026.000')] +[2026-07-22 22:18:31,516][380295] Updated weights for policy 0, policy_version 39296 (0.0007) +[2026-07-22 22:18:31,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20119552. Throughput: 0: 7020.1. Samples: 20116992. Policy #0 lag: (min: 0.0, avg: 2.9, max: 64.0) +[2026-07-22 22:18:31,952][379328] Avg episode reward: [(0, '6940.850')] +[2026-07-22 22:18:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20152320. Throughput: 0: 6963.2. Samples: 20157952. Policy #0 lag: (min: 0.0, avg: 2.9, max: 64.0) +[2026-07-22 22:18:36,952][379328] Avg episode reward: [(0, '6940.850')] +[2026-07-22 22:18:40,503][380295] Updated weights for policy 0, policy_version 39419 (0.0007) +[2026-07-22 22:18:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20185088. Throughput: 0: 7099.7. Samples: 20182016. Policy #0 lag: (min: 0.0, avg: 2.9, max: 64.0) +[2026-07-22 22:18:41,952][379328] Avg episode reward: [(0, '6903.650')] +[2026-07-22 22:18:44,774][380289] Signal inference workers to stop experience collection... (1850 times) +[2026-07-22 22:18:44,804][380295] InferenceWorker_p0-w0: stopping experience collection (1850 times) +[2026-07-22 22:18:44,950][380289] Signal inference workers to resume experience collection... (1850 times) +[2026-07-22 22:18:44,950][380295] InferenceWorker_p0-w0: resuming experience collection (1850 times) +[2026-07-22 22:18:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20217856. Throughput: 0: 7065.6. Samples: 20221952. Policy #0 lag: (min: 0.0, avg: 2.9, max: 64.0) +[2026-07-22 22:18:46,952][379328] Avg episode reward: [(0, '6934.650')] +[2026-07-22 22:18:49,429][380295] Updated weights for policy 0, policy_version 39536 (0.0008) +[2026-07-22 22:18:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20250624. Throughput: 0: 7054.2. Samples: 20266496. Policy #0 lag: (min: 0.0, avg: 2.9, max: 64.0) +[2026-07-22 22:18:51,952][379328] Avg episode reward: [(0, '6918.500')] +[2026-07-22 22:18:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20283392. Throughput: 0: 7042.8. Samples: 20286464. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:18:56,952][379328] Avg episode reward: [(0, '7096.500')] +[2026-07-22 22:18:58,310][380295] Updated weights for policy 0, policy_version 39632 (0.0007) +[2026-07-22 22:19:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20316160. Throughput: 0: 7042.8. Samples: 20329984. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:19:01,952][379328] Avg episode reward: [(0, '7063.450')] +[2026-07-22 22:19:03,494][380295] Updated weights for policy 0, policy_version 39734 (0.0008) +[2026-07-22 22:19:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20348928. Throughput: 0: 7054.2. Samples: 20371968. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:19:06,952][379328] Avg episode reward: [(0, '7020.100')] +[2026-07-22 22:19:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 7081.2). Total num frames: 20381696. Throughput: 0: 7088.4. Samples: 20392960. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:19:11,952][379328] Avg episode reward: [(0, '7169.650')] +[2026-07-22 22:19:12,673][380295] Updated weights for policy 0, policy_version 39840 (0.0007) +[2026-07-22 22:19:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6826.7, 300 sec: 7025.7). Total num frames: 20414464. Throughput: 0: 7042.8. Samples: 20433920. Policy #0 lag: (min: 0.0, avg: 2.8, max: 64.0) +[2026-07-22 22:19:16,951][379328] Avg episode reward: [(0, '7129.550')] +[2026-07-22 22:19:17,814][380295] Updated weights for policy 0, policy_version 39936 (0.0007) +[2026-07-22 22:19:21,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6826.7, 300 sec: 7025.7). Total num frames: 20455424. Throughput: 0: 7099.7. Samples: 20477440. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:19:21,951][379328] Avg episode reward: [(0, '7132.950')] +[2026-07-22 22:19:26,951][379328] Fps is (10 sec: 9011.2, 60 sec: 6963.2, 300 sec: 7081.2). Total num frames: 20504576. Throughput: 0: 6997.3. Samples: 20496896. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:19:26,952][379328] Avg episode reward: [(0, '6993.700')] +[2026-07-22 22:19:26,962][380295] Updated weights for policy 0, policy_version 40058 (0.0008) +[2026-07-22 22:19:31,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20545536. Throughput: 0: 7077.0. Samples: 20540416. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:19:31,951][379328] Avg episode reward: [(0, '6988.500')] +[2026-07-22 22:19:36,166][380295] Updated weights for policy 0, policy_version 40176 (0.0007) +[2026-07-22 22:19:36,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20578304. Throughput: 0: 6986.0. Samples: 20580864. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:19:36,952][379328] Avg episode reward: [(0, '6975.300')] +[2026-07-22 22:19:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20611072. Throughput: 0: 7042.8. Samples: 20603392. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:19:41,952][379328] Avg episode reward: [(0, '7009.400')] +[2026-07-22 22:19:44,882][380295] Updated weights for policy 0, policy_version 40272 (0.0007) +[2026-07-22 22:19:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20643840. Throughput: 0: 7031.5. Samples: 20646400. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:19:46,952][379328] Avg episode reward: [(0, '7051.350')] +[2026-07-22 22:19:50,104][380295] Updated weights for policy 0, policy_version 40374 (0.0008) +[2026-07-22 22:19:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20676608. Throughput: 0: 7054.2. Samples: 20689408. Policy #0 lag: (min: 11.0, avg: 13.8, max: 75.0) +[2026-07-22 22:19:51,952][379328] Avg episode reward: [(0, '6936.700')] +[2026-07-22 22:19:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20709376. Throughput: 0: 7065.6. Samples: 20710912. Policy #0 lag: (min: 11.0, avg: 13.8, max: 75.0) +[2026-07-22 22:19:56,952][379328] Avg episode reward: [(0, '6911.450')] +[2026-07-22 22:19:58,651][380295] Updated weights for policy 0, policy_version 40480 (0.0006) +[2026-07-22 22:20:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20742144. Throughput: 0: 7156.6. Samples: 20755968. Policy #0 lag: (min: 11.0, avg: 13.8, max: 75.0) +[2026-07-22 22:20:01,952][379328] Avg episode reward: [(0, '6910.100')] +[2026-07-22 22:20:03,045][380289] Signal inference workers to stop experience collection... (1900 times) +[2026-07-22 22:20:03,075][380295] InferenceWorker_p0-w0: stopping experience collection (1900 times) +[2026-07-22 22:20:03,186][380289] Signal inference workers to resume experience collection... (1900 times) +[2026-07-22 22:20:03,187][380295] InferenceWorker_p0-w0: resuming experience collection (1900 times) +[2026-07-22 22:20:03,663][380295] Updated weights for policy 0, policy_version 40576 (0.0006) +[2026-07-22 22:20:06,951][379328] Fps is (10 sec: 6553.7, 60 sec: 7099.7, 300 sec: 7025.7). Total num frames: 20774912. Throughput: 0: 7145.2. Samples: 20798976. Policy #0 lag: (min: 11.0, avg: 13.8, max: 75.0) +[2026-07-22 22:20:06,952][379328] Avg episode reward: [(0, '6944.550')] +[2026-07-22 22:20:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7025.7). Total num frames: 20807680. Throughput: 0: 7168.0. Samples: 20819456. Policy #0 lag: (min: 11.0, avg: 13.8, max: 75.0) +[2026-07-22 22:20:11,952][379328] Avg episode reward: [(0, '7057.450')] +[2026-07-22 22:20:12,678][380295] Updated weights for policy 0, policy_version 40694 (0.0008) +[2026-07-22 22:20:16,951][379328] Fps is (10 sec: 8192.0, 60 sec: 7372.8, 300 sec: 7081.2). Total num frames: 20856832. Throughput: 0: 7168.0. Samples: 20862976. Policy #0 lag: (min: 4.0, avg: 6.7, max: 68.0) +[2026-07-22 22:20:16,951][379328] Avg episode reward: [(0, '6982.050')] +[2026-07-22 22:20:21,646][380295] Updated weights for policy 0, policy_version 40800 (0.0007) +[2026-07-22 22:20:21,951][379328] Fps is (10 sec: 9011.1, 60 sec: 7372.8, 300 sec: 7081.2). Total num frames: 20897792. Throughput: 0: 7236.2. Samples: 20906496. Policy #0 lag: (min: 4.0, avg: 6.7, max: 68.0) +[2026-07-22 22:20:21,952][379328] Avg episode reward: [(0, '6916.050')] +[2026-07-22 22:20:26,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 7081.2). Total num frames: 20930560. Throughput: 0: 7145.2. Samples: 20924928. Policy #0 lag: (min: 4.0, avg: 6.7, max: 68.0) +[2026-07-22 22:20:26,952][379328] Avg episode reward: [(0, '7028.750')] +[2026-07-22 22:20:26,986][380295] Updated weights for policy 0, policy_version 40896 (0.0008) +[2026-07-22 22:20:31,951][379328] Fps is (10 sec: 7372.9, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 20971520. Throughput: 0: 7133.9. Samples: 20967424. Policy #0 lag: (min: 4.0, avg: 6.7, max: 68.0) +[2026-07-22 22:20:31,952][379328] Avg episode reward: [(0, '7023.700')] +[2026-07-22 22:20:36,037][380295] Updated weights for policy 0, policy_version 41010 (0.0007) +[2026-07-22 22:20:36,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21004288. Throughput: 0: 7111.1. Samples: 21009408. Policy #0 lag: (min: 4.0, avg: 6.7, max: 68.0) +[2026-07-22 22:20:36,952][379328] Avg episode reward: [(0, '7071.350')] +[2026-07-22 22:20:40,763][380295] Updated weights for policy 0, policy_version 41088 (0.0008) +[2026-07-22 22:20:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21037056. Throughput: 0: 7133.9. Samples: 21031936. Policy #0 lag: (min: 4.0, avg: 6.7, max: 68.0) +[2026-07-22 22:20:41,952][379328] Avg episode reward: [(0, '7095.000')] +[2026-07-22 22:20:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21069824. Throughput: 0: 7042.8. Samples: 21072896. Policy #0 lag: (min: 10.0, avg: 12.7, max: 74.0) +[2026-07-22 22:20:46,952][379328] Avg episode reward: [(0, '7206.900')] +[2026-07-22 22:20:49,742][380295] Updated weights for policy 0, policy_version 41206 (0.0007) +[2026-07-22 22:20:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21102592. Throughput: 0: 7088.4. Samples: 21117952. Policy #0 lag: (min: 10.0, avg: 12.7, max: 74.0) +[2026-07-22 22:20:51,952][379328] Avg episode reward: [(0, '7220.950')] +[2026-07-22 22:20:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21135360. Throughput: 0: 7111.1. Samples: 21139456. Policy #0 lag: (min: 10.0, avg: 12.7, max: 74.0) +[2026-07-22 22:20:56,952][379328] Avg episode reward: [(0, '7176.350')] +[2026-07-22 22:20:58,441][380295] Updated weights for policy 0, policy_version 41296 (0.0007) +[2026-07-22 22:21:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21168128. Throughput: 0: 7088.4. Samples: 21181952. Policy #0 lag: (min: 10.0, avg: 12.7, max: 74.0) +[2026-07-22 22:21:01,952][379328] Avg episode reward: [(0, '7172.800')] +[2026-07-22 22:21:03,446][380295] Updated weights for policy 0, policy_version 41401 (0.0007) +[2026-07-22 22:21:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7025.7). Total num frames: 21200896. Throughput: 0: 7065.6. Samples: 21224448. Policy #0 lag: (min: 10.0, avg: 12.7, max: 74.0) +[2026-07-22 22:21:06,952][379328] Avg episode reward: [(0, '7126.700')] +[2026-07-22 22:21:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 6997.9). Total num frames: 21233664. Throughput: 0: 7122.5. Samples: 21245440. Policy #0 lag: (min: 10.0, avg: 12.7, max: 74.0) +[2026-07-22 22:21:11,952][379328] Avg episode reward: [(0, '7180.150')] +[2026-07-22 22:21:12,575][380295] Updated weights for policy 0, policy_version 41520 (0.0007) +[2026-07-22 22:21:16,951][379328] Fps is (10 sec: 7372.8, 60 sec: 6963.2, 300 sec: 7025.7). Total num frames: 21274624. Throughput: 0: 7145.2. Samples: 21288960. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 22:21:16,952][379328] Avg episode reward: [(0, '7323.550')] +[2026-07-22 22:21:17,576][380295] Updated weights for policy 0, policy_version 41600 (0.0008) +[2026-07-22 22:21:21,117][380289] Signal inference workers to stop experience collection... (1950 times) +[2026-07-22 22:21:21,143][380295] InferenceWorker_p0-w0: stopping experience collection (1950 times) +[2026-07-22 22:21:21,293][380289] Signal inference workers to resume experience collection... (1950 times) +[2026-07-22 22:21:21,293][380295] InferenceWorker_p0-w0: resuming experience collection (1950 times) +[2026-07-22 22:21:21,951][379328] Fps is (10 sec: 9830.4, 60 sec: 7236.3, 300 sec: 7109.0). Total num frames: 21331968. Throughput: 0: 7179.4. Samples: 21332480. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 22:21:21,951][379328] Avg episode reward: [(0, '7493.500')] +[2026-07-22 22:21:21,957][380289] Saving new best policy, reward=7493.500! +[2026-07-22 22:21:26,409][380295] Updated weights for policy 0, policy_version 41726 (0.0010) +[2026-07-22 22:21:26,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7236.3, 300 sec: 7109.0). Total num frames: 21364736. Throughput: 0: 7156.6. Samples: 21353984. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 22:21:26,951][379328] Avg episode reward: [(0, '7450.350')] +[2026-07-22 22:21:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21397504. Throughput: 0: 7224.9. Samples: 21398016. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 22:21:31,951][379328] Avg episode reward: [(0, '7449.450')] +[2026-07-22 22:21:35,109][380295] Updated weights for policy 0, policy_version 41840 (0.0009) +[2026-07-22 22:21:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21430272. Throughput: 0: 7190.8. Samples: 21441536. Policy #0 lag: (min: 2.0, avg: 4.7, max: 66.0) +[2026-07-22 22:21:36,952][379328] Avg episode reward: [(0, '7450.600')] +[2026-07-22 22:21:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21463040. Throughput: 0: 7202.1. Samples: 21463552. Policy #0 lag: (min: 13.0, avg: 15.9, max: 77.0) +[2026-07-22 22:21:41,952][379328] Avg episode reward: [(0, '7295.300')] +[2026-07-22 22:21:43,891][380295] Updated weights for policy 0, policy_version 41936 (0.0007) +[2026-07-22 22:21:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21495808. Throughput: 0: 7202.1. Samples: 21506048. Policy #0 lag: (min: 13.0, avg: 15.9, max: 77.0) +[2026-07-22 22:21:46,952][379328] Avg episode reward: [(0, '7297.500')] +[2026-07-22 22:21:48,894][380295] Updated weights for policy 0, policy_version 42046 (0.0008) +[2026-07-22 22:21:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21528576. Throughput: 0: 7259.0. Samples: 21551104. Policy #0 lag: (min: 13.0, avg: 15.9, max: 77.0) +[2026-07-22 22:21:51,952][379328] Avg episode reward: [(0, '7358.850')] +[2026-07-22 22:21:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21561344. Throughput: 0: 7270.4. Samples: 21572608. Policy #0 lag: (min: 13.0, avg: 15.9, max: 77.0) +[2026-07-22 22:21:56,952][379328] Avg episode reward: [(0, '7418.900')] +[2026-07-22 22:21:57,464][380295] Updated weights for policy 0, policy_version 42160 (0.0007) +[2026-07-22 22:22:01,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7236.3, 300 sec: 7053.5). Total num frames: 21602304. Throughput: 0: 7247.6. Samples: 21615104. Policy #0 lag: (min: 13.0, avg: 15.9, max: 77.0) +[2026-07-22 22:22:01,952][379328] Avg episode reward: [(0, '7387.900')] +[2026-07-22 22:22:06,392][380295] Updated weights for policy 0, policy_version 42256 (0.0007) +[2026-07-22 22:22:06,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7509.3, 300 sec: 7081.2). Total num frames: 21651456. Throughput: 0: 7281.8. Samples: 21660160. Policy #0 lag: (min: 11.0, avg: 13.7, max: 75.0) +[2026-07-22 22:22:06,952][379328] Avg episode reward: [(0, '7446.300')] +[2026-07-22 22:22:11,235][380295] Updated weights for policy 0, policy_version 42354 (0.0007) +[2026-07-22 22:22:11,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7645.9, 300 sec: 7109.0). Total num frames: 21692416. Throughput: 0: 7293.2. Samples: 21682176. Policy #0 lag: (min: 11.0, avg: 13.7, max: 75.0) +[2026-07-22 22:22:11,952][379328] Avg episode reward: [(0, '7447.200')] +[2026-07-22 22:22:16,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7509.3, 300 sec: 7109.0). Total num frames: 21725184. Throughput: 0: 7270.4. Samples: 21725184. Policy #0 lag: (min: 11.0, avg: 13.7, max: 75.0) +[2026-07-22 22:22:16,952][379328] Avg episode reward: [(0, '7507.300')] +[2026-07-22 22:22:16,957][380289] Saving new best policy, reward=7507.300! +[2026-07-22 22:22:20,246][380295] Updated weights for policy 0, policy_version 42464 (0.0007) +[2026-07-22 22:22:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21757952. Throughput: 0: 7224.9. Samples: 21766656. Policy #0 lag: (min: 11.0, avg: 13.7, max: 75.0) +[2026-07-22 22:22:21,952][379328] Avg episode reward: [(0, '7433.050')] +[2026-07-22 22:22:24,965][380295] Updated weights for policy 0, policy_version 42558 (0.0006) +[2026-07-22 22:22:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21790720. Throughput: 0: 7281.8. Samples: 21791232. Policy #0 lag: (min: 11.0, avg: 13.7, max: 75.0) +[2026-07-22 22:22:26,952][379328] Avg episode reward: [(0, '7393.400')] +[2026-07-22 22:22:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21823488. Throughput: 0: 7270.4. Samples: 21833216. Policy #0 lag: (min: 11.0, avg: 13.7, max: 75.0) +[2026-07-22 22:22:31,952][379328] Avg episode reward: [(0, '7487.450')] +[2026-07-22 22:22:33,802][380289] Signal inference workers to stop experience collection... (2000 times) +[2026-07-22 22:22:33,832][380295] InferenceWorker_p0-w0: stopping experience collection (2000 times) +[2026-07-22 22:22:33,942][380289] Signal inference workers to resume experience collection... (2000 times) +[2026-07-22 22:22:33,942][380295] InferenceWorker_p0-w0: resuming experience collection (2000 times) +[2026-07-22 22:22:33,944][380295] Updated weights for policy 0, policy_version 42672 (0.0008) +[2026-07-22 22:22:36,951][379328] Fps is (10 sec: 6553.7, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21856256. Throughput: 0: 7213.5. Samples: 21875712. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:22:36,952][379328] Avg episode reward: [(0, '7386.500')] +[2026-07-22 22:22:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21889024. Throughput: 0: 7190.8. Samples: 21896192. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:22:41,952][379328] Avg episode reward: [(0, '7423.750')] +[2026-07-22 22:22:42,752][380295] Updated weights for policy 0, policy_version 42768 (0.0007) +[2026-07-22 22:22:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21921792. Throughput: 0: 7190.8. Samples: 21938688. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:22:46,952][379328] Avg episode reward: [(0, '7451.200')] +[2026-07-22 22:22:48,070][380295] Updated weights for policy 0, policy_version 42870 (0.0007) +[2026-07-22 22:22:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 21954560. Throughput: 0: 7168.0. Samples: 21982720. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:22:51,952][379328] Avg episode reward: [(0, '7590.050')] +[2026-07-22 22:22:51,956][380289] Saving new best policy, reward=7590.050! +[2026-07-22 22:22:56,611][380295] Updated weights for policy 0, policy_version 42960 (0.0008) +[2026-07-22 22:22:56,951][379328] Fps is (10 sec: 8192.0, 60 sec: 7372.8, 300 sec: 7164.5). Total num frames: 22003712. Throughput: 0: 7133.9. Samples: 22003200. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:22:56,952][379328] Avg episode reward: [(0, '7511.000')] +[2026-07-22 22:23:01,877][380295] Updated weights for policy 0, policy_version 43070 (0.0007) +[2026-07-22 22:23:01,951][379328] Fps is (10 sec: 9830.3, 60 sec: 7509.3, 300 sec: 7220.1). Total num frames: 22052864. Throughput: 0: 7145.2. Samples: 22046720. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:23:01,952][379328] Avg episode reward: [(0, '7579.500')] +[2026-07-22 22:23:06,951][379328] Fps is (10 sec: 8192.0, 60 sec: 7236.3, 300 sec: 7192.3). Total num frames: 22085632. Throughput: 0: 7168.0. Samples: 22089216. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:23:06,952][379328] Avg episode reward: [(0, '7678.900')] +[2026-07-22 22:23:06,964][380289] Saving new best policy, reward=7678.900! +[2026-07-22 22:23:10,291][380295] Updated weights for policy 0, policy_version 43168 (0.0008) +[2026-07-22 22:23:11,951][379328] Fps is (10 sec: 6553.7, 60 sec: 7099.7, 300 sec: 7164.5). Total num frames: 22118400. Throughput: 0: 7156.6. Samples: 22113280. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:23:11,952][379328] Avg episode reward: [(0, '7693.150')] +[2026-07-22 22:23:11,973][380289] Saving new best policy, reward=7693.150! +[2026-07-22 22:23:15,184][380295] Updated weights for policy 0, policy_version 43254 (0.0007) +[2026-07-22 22:23:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7136.8). Total num frames: 22151168. Throughput: 0: 7145.2. Samples: 22154752. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:23:16,951][379328] Avg episode reward: [(0, '7793.050')] +[2026-07-22 22:23:16,974][380289] Saving new best policy, reward=7793.050! +[2026-07-22 22:23:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 22183936. Throughput: 0: 7190.8. Samples: 22199296. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:23:21,951][379328] Avg episode reward: [(0, '7600.100')] +[2026-07-22 22:23:23,868][380295] Updated weights for policy 0, policy_version 43360 (0.0008) +[2026-07-22 22:23:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 22216704. Throughput: 0: 7190.8. Samples: 22219776. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:23:26,952][379328] Avg episode reward: [(0, '7589.400')] +[2026-07-22 22:23:28,862][380295] Updated weights for policy 0, policy_version 43455 (0.0007) +[2026-07-22 22:23:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 22249472. Throughput: 0: 7236.3. Samples: 22264320. Policy #0 lag: (min: 52.0, avg: 54.6, max: 116.0) +[2026-07-22 22:23:31,952][379328] Avg episode reward: [(0, '7646.100')] +[2026-07-22 22:23:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 22282240. Throughput: 0: 7259.0. Samples: 22309376. Policy #0 lag: (min: 52.0, avg: 54.6, max: 116.0) +[2026-07-22 22:23:36,952][379328] Avg episode reward: [(0, '7600.950')] +[2026-07-22 22:23:37,454][380295] Updated weights for policy 0, policy_version 43568 (0.0008) +[2026-07-22 22:23:41,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7236.3, 300 sec: 7136.8). Total num frames: 22323200. Throughput: 0: 7259.0. Samples: 22329856. Policy #0 lag: (min: 52.0, avg: 54.6, max: 116.0) +[2026-07-22 22:23:41,951][379328] Avg episode reward: [(0, '7485.300')] +[2026-07-22 22:23:42,401][380295] Updated weights for policy 0, policy_version 43648 (0.0008) +[2026-07-22 22:23:46,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7509.3, 300 sec: 7192.3). Total num frames: 22372352. Throughput: 0: 7259.0. Samples: 22373376. Policy #0 lag: (min: 52.0, avg: 54.6, max: 116.0) +[2026-07-22 22:23:46,952][379328] Avg episode reward: [(0, '7500.900')] +[2026-07-22 22:23:51,178][380289] Signal inference workers to stop experience collection... (2050 times) +[2026-07-22 22:23:51,206][380295] InferenceWorker_p0-w0: stopping experience collection (2050 times) +[2026-07-22 22:23:51,357][380289] Signal inference workers to resume experience collection... (2050 times) +[2026-07-22 22:23:51,357][380295] InferenceWorker_p0-w0: resuming experience collection (2050 times) +[2026-07-22 22:23:51,662][380295] Updated weights for policy 0, policy_version 43766 (0.0008) +[2026-07-22 22:23:51,951][379328] Fps is (10 sec: 9011.1, 60 sec: 7645.9, 300 sec: 7220.1). Total num frames: 22413312. Throughput: 0: 7224.9. Samples: 22414336. Policy #0 lag: (min: 52.0, avg: 54.6, max: 116.0) +[2026-07-22 22:23:51,952][379328] Avg episode reward: [(0, '7637.400')] +[2026-07-22 22:23:56,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7372.8, 300 sec: 7220.1). Total num frames: 22446080. Throughput: 0: 7179.4. Samples: 22436352. Policy #0 lag: (min: 48.0, avg: 50.8, max: 112.0) +[2026-07-22 22:23:56,952][379328] Avg episode reward: [(0, '7564.350')] +[2026-07-22 22:24:00,286][380295] Updated weights for policy 0, policy_version 43872 (0.0008) +[2026-07-22 22:24:01,951][379328] Fps is (10 sec: 6553.7, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 22478848. Throughput: 0: 7236.3. Samples: 22480384. Policy #0 lag: (min: 48.0, avg: 50.8, max: 112.0) +[2026-07-22 22:24:01,951][379328] Avg episode reward: [(0, '7533.450')] +[2026-07-22 22:24:05,307][380295] Updated weights for policy 0, policy_version 43968 (0.0008) +[2026-07-22 22:24:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 22511616. Throughput: 0: 7179.4. Samples: 22522368. Policy #0 lag: (min: 48.0, avg: 50.8, max: 112.0) +[2026-07-22 22:24:06,952][379328] Avg episode reward: [(0, '7559.200')] +[2026-07-22 22:24:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 22544384. Throughput: 0: 7236.3. Samples: 22545408. Policy #0 lag: (min: 48.0, avg: 50.8, max: 112.0) +[2026-07-22 22:24:11,951][379328] Avg episode reward: [(0, '7565.450')] +[2026-07-22 22:24:14,447][380295] Updated weights for policy 0, policy_version 44086 (0.0008) +[2026-07-22 22:24:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7192.3). Total num frames: 22577152. Throughput: 0: 7133.9. Samples: 22585344. Policy #0 lag: (min: 48.0, avg: 50.8, max: 112.0) +[2026-07-22 22:24:16,952][379328] Avg episode reward: [(0, '7482.300')] +[2026-07-22 22:24:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7136.8). Total num frames: 22609920. Throughput: 0: 7133.9. Samples: 22630400. Policy #0 lag: (min: 48.0, avg: 50.8, max: 112.0) +[2026-07-22 22:24:21,952][379328] Avg episode reward: [(0, '7558.550')] +[2026-07-22 22:24:23,500][380295] Updated weights for policy 0, policy_version 44192 (0.0007) +[2026-07-22 22:24:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 22642688. Throughput: 0: 7088.4. Samples: 22648832. Policy #0 lag: (min: 48.0, avg: 50.8, max: 112.0) +[2026-07-22 22:24:26,952][379328] Avg episode reward: [(0, '7634.050')] +[2026-07-22 22:24:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 22675456. Throughput: 0: 7054.2. Samples: 22690816. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 22:24:31,952][379328] Avg episode reward: [(0, '7686.900')] +[2026-07-22 22:24:32,774][380295] Updated weights for policy 0, policy_version 44304 (0.0007) +[2026-07-22 22:24:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 22708224. Throughput: 0: 7145.3. Samples: 22735872. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 22:24:36,951][379328] Avg episode reward: [(0, '7745.200')] +[2026-07-22 22:24:37,533][380295] Updated weights for policy 0, policy_version 44402 (0.0008) +[2026-07-22 22:24:41,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7372.8, 300 sec: 7192.3). Total num frames: 22765568. Throughput: 0: 7122.5. Samples: 22756864. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 22:24:41,952][379328] Avg episode reward: [(0, '7751.250')] +[2026-07-22 22:24:46,441][380295] Updated weights for policy 0, policy_version 44528 (0.0007) +[2026-07-22 22:24:46,951][379328] Fps is (10 sec: 9830.4, 60 sec: 7236.3, 300 sec: 7220.1). Total num frames: 22806528. Throughput: 0: 7133.9. Samples: 22801408. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 22:24:46,952][379328] Avg episode reward: [(0, '7769.750')] +[2026-07-22 22:24:51,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 22839296. Throughput: 0: 7133.9. Samples: 22843392. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 22:24:51,952][379328] Avg episode reward: [(0, '7774.300')] +[2026-07-22 22:24:54,889][380295] Updated weights for policy 0, policy_version 44624 (0.0007) +[2026-07-22 22:24:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 22872064. Throughput: 0: 7179.4. Samples: 22868480. Policy #0 lag: (min: 15.0, avg: 17.6, max: 79.0) +[2026-07-22 22:24:56,951][379328] Avg episode reward: [(0, '7800.900')] +[2026-07-22 22:24:56,956][380289] Saving new best policy, reward=7800.900! +[2026-07-22 22:24:59,763][380295] Updated weights for policy 0, policy_version 44734 (0.0009) +[2026-07-22 22:25:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 22904832. Throughput: 0: 7259.0. Samples: 22912000. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:25:01,952][379328] Avg episode reward: [(0, '7935.150')] +[2026-07-22 22:25:01,975][380289] Saving new best policy, reward=7935.150! +[2026-07-22 22:25:06,951][379328] Fps is (10 sec: 6553.5, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 22937600. Throughput: 0: 7236.2. Samples: 22956032. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:25:06,952][379328] Avg episode reward: [(0, '8054.550')] +[2026-07-22 22:25:06,963][380289] Saving new best policy, reward=8054.550! +[2026-07-22 22:25:08,235][380289] Signal inference workers to stop experience collection... (2100 times) +[2026-07-22 22:25:08,264][380295] InferenceWorker_p0-w0: stopping experience collection (2100 times) +[2026-07-22 22:25:08,411][380289] Signal inference workers to resume experience collection... (2100 times) +[2026-07-22 22:25:08,412][380295] InferenceWorker_p0-w0: resuming experience collection (2100 times) +[2026-07-22 22:25:08,589][380295] Updated weights for policy 0, policy_version 44832 (0.0008) +[2026-07-22 22:25:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7164.5). Total num frames: 22970368. Throughput: 0: 7259.0. Samples: 22975488. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:25:11,952][379328] Avg episode reward: [(0, '8018.550')] +[2026-07-22 22:25:13,606][380295] Updated weights for policy 0, policy_version 44926 (0.0008) +[2026-07-22 22:25:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7136.8). Total num frames: 23003136. Throughput: 0: 7304.5. Samples: 23019520. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:25:16,952][379328] Avg episode reward: [(0, '7925.900')] +[2026-07-22 22:25:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7136.8). Total num frames: 23035904. Throughput: 0: 7270.4. Samples: 23063040. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:25:21,952][379328] Avg episode reward: [(0, '7945.150')] +[2026-07-22 22:25:22,599][380295] Updated weights for policy 0, policy_version 45040 (0.0007) +[2026-07-22 22:25:26,951][379328] Fps is (10 sec: 9011.4, 60 sec: 7509.3, 300 sec: 7192.3). Total num frames: 23093248. Throughput: 0: 7270.4. Samples: 23084032. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:25:26,952][379328] Avg episode reward: [(0, '8033.700')] +[2026-07-22 22:25:27,181][380295] Updated weights for policy 0, policy_version 45117 (0.0008) +[2026-07-22 22:25:31,951][379328] Fps is (10 sec: 9830.4, 60 sec: 7645.9, 300 sec: 7220.1). Total num frames: 23134208. Throughput: 0: 7315.9. Samples: 23130624. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 22:25:31,952][379328] Avg episode reward: [(0, '8110.500')] +[2026-07-22 22:25:31,967][380289] Saving new best policy, reward=8110.500! +[2026-07-22 22:25:35,860][380295] Updated weights for policy 0, policy_version 45232 (0.0007) +[2026-07-22 22:25:36,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7645.9, 300 sec: 7220.1). Total num frames: 23166976. Throughput: 0: 7304.5. Samples: 23172096. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 22:25:36,952][379328] Avg episode reward: [(0, '8189.350')] +[2026-07-22 22:25:36,982][380289] Saving new best policy, reward=8189.350! +[2026-07-22 22:25:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7236.3, 300 sec: 7220.1). Total num frames: 23199744. Throughput: 0: 7247.7. Samples: 23194624. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 22:25:41,952][379328] Avg episode reward: [(0, '8212.700')] +[2026-07-22 22:25:41,980][380289] Saving new best policy, reward=8212.700! +[2026-07-22 22:25:44,752][380295] Updated weights for policy 0, policy_version 45328 (0.0007) +[2026-07-22 22:25:46,951][379328] Fps is (10 sec: 6553.5, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 23232512. Throughput: 0: 7190.8. Samples: 23235584. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 22:25:46,952][379328] Avg episode reward: [(0, '8209.850')] +[2026-07-22 22:25:49,780][380295] Updated weights for policy 0, policy_version 45437 (0.0009) +[2026-07-22 22:25:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 23265280. Throughput: 0: 7179.4. Samples: 23279104. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 22:25:51,951][379328] Avg episode reward: [(0, '8050.700')] +[2026-07-22 22:25:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 23298048. Throughput: 0: 7224.9. Samples: 23300608. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 22:25:56,951][379328] Avg episode reward: [(0, '8091.650')] +[2026-07-22 22:25:58,481][380295] Updated weights for policy 0, policy_version 45536 (0.0009) +[2026-07-22 22:26:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 23330816. Throughput: 0: 7213.5. Samples: 23344128. Policy #0 lag: (min: 15.0, avg: 17.9, max: 79.0) +[2026-07-22 22:26:01,952][379328] Avg episode reward: [(0, '8236.650')] +[2026-07-22 22:26:01,967][380289] Saving new best policy, reward=8236.650! +[2026-07-22 22:26:03,376][380295] Updated weights for policy 0, policy_version 45632 (0.0007) +[2026-07-22 22:26:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 23363584. Throughput: 0: 7259.0. Samples: 23389696. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:26:06,952][379328] Avg episode reward: [(0, '8196.950')] +[2026-07-22 22:26:11,951][379328] Fps is (10 sec: 8192.0, 60 sec: 7372.8, 300 sec: 7247.8). Total num frames: 23412736. Throughput: 0: 7259.0. Samples: 23410688. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:26:11,951][379328] Avg episode reward: [(0, '8162.250')] +[2026-07-22 22:26:12,243][380295] Updated weights for policy 0, policy_version 45750 (0.0009) +[2026-07-22 22:26:16,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7509.3, 300 sec: 7192.3). Total num frames: 23453696. Throughput: 0: 7236.3. Samples: 23456256. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:26:16,952][379328] Avg episode reward: [(0, '8248.550')] +[2026-07-22 22:26:16,963][380289] Saving new best policy, reward=8248.550! +[2026-07-22 22:26:20,905][380289] Signal inference workers to stop experience collection... (2150 times) +[2026-07-22 22:26:20,906][380295] Updated weights for policy 0, policy_version 45856 (0.0009) +[2026-07-22 22:26:20,935][380295] InferenceWorker_p0-w0: stopping experience collection (2150 times) +[2026-07-22 22:26:21,046][380289] Signal inference workers to resume experience collection... (2150 times) +[2026-07-22 22:26:21,047][380295] InferenceWorker_p0-w0: resuming experience collection (2150 times) +[2026-07-22 22:26:21,951][379328] Fps is (10 sec: 8192.0, 60 sec: 7645.9, 300 sec: 7220.1). Total num frames: 23494656. Throughput: 0: 7224.9. Samples: 23497216. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:26:21,952][379328] Avg episode reward: [(0, '8312.400')] +[2026-07-22 22:26:21,968][380289] Saving new best policy, reward=8312.400! +[2026-07-22 22:26:26,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7236.3, 300 sec: 7220.1). Total num frames: 23527424. Throughput: 0: 7224.9. Samples: 23519744. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:26:26,952][379328] Avg episode reward: [(0, '8435.350')] +[2026-07-22 22:26:26,963][380289] Saving new best policy, reward=8435.350! +[2026-07-22 22:26:30,001][380295] Updated weights for policy 0, policy_version 45968 (0.0009) +[2026-07-22 22:26:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 23560192. Throughput: 0: 7247.6. Samples: 23561728. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:26:31,952][379328] Avg episode reward: [(0, '8531.050')] +[2026-07-22 22:26:31,960][380289] Saving new best policy, reward=8531.050! +[2026-07-22 22:26:34,978][380295] Updated weights for policy 0, policy_version 46074 (0.0007) +[2026-07-22 22:26:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 23592960. Throughput: 0: 7270.4. Samples: 23606272. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:26:36,952][379328] Avg episode reward: [(0, '8520.300')] +[2026-07-22 22:26:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 23625728. Throughput: 0: 7270.4. Samples: 23627776. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:26:41,952][379328] Avg episode reward: [(0, '8664.850')] +[2026-07-22 22:26:42,014][380289] Saving new best policy, reward=8664.850! +[2026-07-22 22:26:44,059][380295] Updated weights for policy 0, policy_version 46192 (0.0007) +[2026-07-22 22:26:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 23658496. Throughput: 0: 7213.5. Samples: 23668736. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:26:46,952][379328] Avg episode reward: [(0, '8758.550')] +[2026-07-22 22:26:46,972][380289] Saving new best policy, reward=8758.550! +[2026-07-22 22:26:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 23691264. Throughput: 0: 7145.2. Samples: 23711232. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:26:51,952][379328] Avg episode reward: [(0, '8801.250')] +[2026-07-22 22:26:51,956][380289] Saving new best policy, reward=8801.250! +[2026-07-22 22:26:53,160][380295] Updated weights for policy 0, policy_version 46288 (0.0010) +[2026-07-22 22:26:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7192.3). Total num frames: 23724032. Throughput: 0: 7133.9. Samples: 23731712. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:26:56,952][379328] Avg episode reward: [(0, '8871.100')] +[2026-07-22 22:26:56,961][380289] Saving new best policy, reward=8871.100! +[2026-07-22 22:26:58,185][380295] Updated weights for policy 0, policy_version 46394 (0.0009) +[2026-07-22 22:27:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7136.8). Total num frames: 23756800. Throughput: 0: 7111.1. Samples: 23776256. Policy #0 lag: (min: 15.0, avg: 17.8, max: 79.0) +[2026-07-22 22:27:01,952][379328] Avg episode reward: [(0, '8882.800')] +[2026-07-22 22:27:02,262][380289] Saving new best policy, reward=8882.800! +[2026-07-22 22:27:06,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7236.3, 300 sec: 7136.8). Total num frames: 23797760. Throughput: 0: 7168.0. Samples: 23819776. Policy #0 lag: (min: 1.0, avg: 3.9, max: 65.0) +[2026-07-22 22:27:06,952][379328] Avg episode reward: [(0, '8984.200')] +[2026-07-22 22:27:07,010][380295] Updated weights for policy 0, policy_version 46496 (0.0008) +[2026-07-22 22:27:07,187][380289] Saving results/checkpoints/memory/rollout_teacher/demon_attack_teacher_fixed_l6_obs15_seed0/checkpoint_p0/checkpoint_000046512_23814144.pth... +[2026-07-22 22:27:07,209][380289] Removing results/checkpoints/memory/rollout_teacher/demon_attack_teacher_fixed_l6_obs15_seed0/checkpoint_p0/checkpoint_000006656_3407872.pth +[2026-07-22 22:27:07,212][380289] Saving new best policy, reward=8984.200! +[2026-07-22 22:27:11,951][379328] Fps is (10 sec: 9011.3, 60 sec: 7236.3, 300 sec: 7192.3). Total num frames: 23846912. Throughput: 0: 7099.7. Samples: 23839232. Policy #0 lag: (min: 1.0, avg: 3.9, max: 65.0) +[2026-07-22 22:27:11,952][379328] Avg episode reward: [(0, '9033.700')] +[2026-07-22 22:27:12,119][380289] Saving new best policy, reward=9033.700! +[2026-07-22 22:27:12,172][380295] Updated weights for policy 0, policy_version 46592 (0.0008) +[2026-07-22 22:27:16,951][379328] Fps is (10 sec: 8192.1, 60 sec: 7099.7, 300 sec: 7192.3). Total num frames: 23879680. Throughput: 0: 7099.7. Samples: 23881216. Policy #0 lag: (min: 1.0, avg: 3.9, max: 65.0) +[2026-07-22 22:27:16,952][379328] Avg episode reward: [(0, '8985.650')] +[2026-07-22 22:27:21,951][380295] Updated weights for policy 0, policy_version 46718 (0.0011) +[2026-07-22 22:27:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 7192.3). Total num frames: 23912448. Throughput: 0: 6997.3. Samples: 23921152. Policy #0 lag: (min: 1.0, avg: 3.9, max: 65.0) +[2026-07-22 22:27:21,952][379328] Avg episode reward: [(0, '8986.000')] +[2026-07-22 22:27:26,951][379328] Fps is (10 sec: 7372.7, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 23953408. Throughput: 0: 6963.2. Samples: 23941120. Policy #0 lag: (min: 1.0, avg: 3.9, max: 65.0) +[2026-07-22 22:27:26,951][379328] Avg episode reward: [(0, '8903.450')] +[2026-07-22 22:27:30,748][380295] Updated weights for policy 0, policy_version 46832 (0.0010) +[2026-07-22 22:27:31,951][379328] Fps is (10 sec: 7372.7, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 23986176. Throughput: 0: 7065.6. Samples: 23986688. Policy #0 lag: (min: 1.0, avg: 3.9, max: 65.0) +[2026-07-22 22:27:31,952][379328] Avg episode reward: [(0, '8890.550')] +[2026-07-22 22:27:35,259][380295] Updated weights for policy 0, policy_version 46909 (0.0008) +[2026-07-22 22:27:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 24018944. Throughput: 0: 7111.1. Samples: 24031232. Policy #0 lag: (min: 1.0, avg: 3.9, max: 65.0) +[2026-07-22 22:27:36,952][379328] Avg episode reward: [(0, '8830.750')] +[2026-07-22 22:27:39,206][380289] Signal inference workers to stop experience collection... (2200 times) +[2026-07-22 22:27:39,236][380295] InferenceWorker_p0-w0: stopping experience collection (2200 times) +[2026-07-22 22:27:39,347][380289] Signal inference workers to resume experience collection... (2200 times) +[2026-07-22 22:27:39,348][380295] InferenceWorker_p0-w0: resuming experience collection (2200 times) +[2026-07-22 22:27:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 24051712. Throughput: 0: 7133.9. Samples: 24052736. Policy #0 lag: (min: 12.0, avg: 14.9, max: 76.0) +[2026-07-22 22:27:41,952][379328] Avg episode reward: [(0, '8835.750')] +[2026-07-22 22:27:44,188][380295] Updated weights for policy 0, policy_version 47024 (0.0008) +[2026-07-22 22:27:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 24084480. Throughput: 0: 7065.6. Samples: 24094208. Policy #0 lag: (min: 12.0, avg: 14.9, max: 76.0) +[2026-07-22 22:27:46,952][379328] Avg episode reward: [(0, '8815.150')] +[2026-07-22 22:27:48,920][380295] Updated weights for policy 0, policy_version 47098 (0.0008) +[2026-07-22 22:27:51,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7164.5). Total num frames: 24117248. Throughput: 0: 7099.7. Samples: 24139264. Policy #0 lag: (min: 12.0, avg: 14.9, max: 76.0) +[2026-07-22 22:27:51,952][379328] Avg episode reward: [(0, '8774.250')] +[2026-07-22 22:27:56,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 24150016. Throughput: 0: 7145.2. Samples: 24160768. Policy #0 lag: (min: 12.0, avg: 14.9, max: 76.0) +[2026-07-22 22:27:56,952][379328] Avg episode reward: [(0, '8686.950')] +[2026-07-22 22:27:57,532][380295] Updated weights for policy 0, policy_version 47200 (0.0010) +[2026-07-22 22:28:01,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 24182784. Throughput: 0: 7168.0. Samples: 24203776. Policy #0 lag: (min: 12.0, avg: 14.9, max: 76.0) +[2026-07-22 22:28:01,951][379328] Avg episode reward: [(0, '8703.400')] +[2026-07-22 22:28:02,677][380295] Updated weights for policy 0, policy_version 47293 (0.0008) +[2026-07-22 22:28:06,953][379328] Fps is (10 sec: 9009.6, 60 sec: 7372.6, 300 sec: 7192.3). Total num frames: 24240128. Throughput: 0: 7281.5. Samples: 24248832. Policy #0 lag: (min: 12.0, avg: 14.9, max: 76.0) +[2026-07-22 22:28:06,953][379328] Avg episode reward: [(0, '8685.650')] +[2026-07-22 22:28:11,018][380295] Updated weights for policy 0, policy_version 47408 (0.0008) +[2026-07-22 22:28:11,951][379328] Fps is (10 sec: 9830.4, 60 sec: 7236.3, 300 sec: 7220.1). Total num frames: 24281088. Throughput: 0: 7338.7. Samples: 24271360. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:28:11,952][379328] Avg episode reward: [(0, '8669.900')] +[2026-07-22 22:28:16,058][380295] Updated weights for policy 0, policy_version 47488 (0.0009) +[2026-07-22 22:28:16,951][379328] Fps is (10 sec: 7374.1, 60 sec: 7236.2, 300 sec: 7220.1). Total num frames: 24313856. Throughput: 0: 7281.8. Samples: 24314368. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:28:16,952][379328] Avg episode reward: [(0, '8636.850')] +[2026-07-22 22:28:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7236.3, 300 sec: 7220.1). Total num frames: 24346624. Throughput: 0: 7224.9. Samples: 24356352. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:28:21,952][379328] Avg episode reward: [(0, '8709.850')] +[2026-07-22 22:28:24,740][380295] Updated weights for policy 0, policy_version 47606 (0.0010) +[2026-07-22 22:28:26,951][379328] Fps is (10 sec: 6553.7, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 24379392. Throughput: 0: 7281.8. Samples: 24380416. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:28:26,952][379328] Avg episode reward: [(0, '8696.800')] +[2026-07-22 22:28:29,399][380295] Updated weights for policy 0, policy_version 47680 (0.0008) +[2026-07-22 22:28:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 24412160. Throughput: 0: 7327.3. Samples: 24423936. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:28:31,952][379328] Avg episode reward: [(0, '8700.050')] +[2026-07-22 22:28:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7192.3). Total num frames: 24444928. Throughput: 0: 7327.3. Samples: 24468992. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:28:36,952][379328] Avg episode reward: [(0, '8800.200')] +[2026-07-22 22:28:38,081][380295] Updated weights for policy 0, policy_version 47799 (0.0008) +[2026-07-22 22:28:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7136.8). Total num frames: 24477696. Throughput: 0: 7293.2. Samples: 24488960. Policy #0 lag: (min: 15.0, avg: 17.7, max: 79.0) +[2026-07-22 22:28:41,951][379328] Avg episode reward: [(0, '8799.600')] +[2026-07-22 22:28:46,951][379328] Fps is (10 sec: 7372.9, 60 sec: 7236.3, 300 sec: 7136.8). Total num frames: 24518656. Throughput: 0: 7327.3. Samples: 24533504. Policy #0 lag: (min: 0.0, avg: 2.7, max: 64.0) +[2026-07-22 22:28:46,952][379328] Avg episode reward: [(0, '8839.300')] +[2026-07-22 22:28:46,959][380295] Updated weights for policy 0, policy_version 47904 (0.0009) +[2026-07-22 22:28:51,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7509.3, 300 sec: 7192.3). Total num frames: 24567808. Throughput: 0: 7282.1. Samples: 24576512. Policy #0 lag: (min: 0.0, avg: 2.7, max: 64.0) +[2026-07-22 22:28:51,952][379328] Avg episode reward: [(0, '8884.300')] +[2026-07-22 22:28:52,114][380295] Updated weights for policy 0, policy_version 48000 (0.0008) +[2026-07-22 22:28:56,062][380289] Signal inference workers to stop experience collection... (2250 times) +[2026-07-22 22:28:56,091][380295] InferenceWorker_p0-w0: stopping experience collection (2250 times) +[2026-07-22 22:28:56,274][380289] Signal inference workers to resume experience collection... (2250 times) +[2026-07-22 22:28:56,275][380295] InferenceWorker_p0-w0: resuming experience collection (2250 times) +[2026-07-22 22:28:56,951][379328] Fps is (10 sec: 9011.2, 60 sec: 7645.9, 300 sec: 7220.1). Total num frames: 24608768. Throughput: 0: 7224.9. Samples: 24596480. Policy #0 lag: (min: 0.0, avg: 2.7, max: 64.0) +[2026-07-22 22:28:56,952][379328] Avg episode reward: [(0, '8911.550')] +[2026-07-22 22:29:01,499][380295] Updated weights for policy 0, policy_version 48119 (0.0008) +[2026-07-22 22:29:01,951][379328] Fps is (10 sec: 7372.8, 60 sec: 7645.9, 300 sec: 7220.1). Total num frames: 24641536. Throughput: 0: 7190.8. Samples: 24637952. Policy #0 lag: (min: 0.0, avg: 2.7, max: 64.0) +[2026-07-22 22:29:01,951][379328] Avg episode reward: [(0, '8602.500')] +[2026-07-22 22:29:06,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7236.5, 300 sec: 7220.1). Total num frames: 24674304. Throughput: 0: 7122.5. Samples: 24676864. Policy #0 lag: (min: 0.0, avg: 2.7, max: 64.0) +[2026-07-22 22:29:06,952][379328] Avg episode reward: [(0, '8631.550')] +[2026-07-22 22:29:10,608][380295] Updated weights for policy 0, policy_version 48224 (0.0008) +[2026-07-22 22:29:11,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 24707072. Throughput: 0: 7111.1. Samples: 24700416. Policy #0 lag: (min: 0.0, avg: 2.7, max: 64.0) +[2026-07-22 22:29:11,952][379328] Avg episode reward: [(0, '8638.400')] +[2026-07-22 22:29:15,479][380295] Updated weights for policy 0, policy_version 48310 (0.0009) +[2026-07-22 22:29:16,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 24739840. Throughput: 0: 7054.2. Samples: 24741376. Policy #0 lag: (min: 9.0, avg: 11.9, max: 73.0) +[2026-07-22 22:29:16,952][379328] Avg episode reward: [(0, '8640.700')] +[2026-07-22 22:29:21,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 24772608. Throughput: 0: 7020.1. Samples: 24784896. Policy #0 lag: (min: 9.0, avg: 11.9, max: 73.0) +[2026-07-22 22:29:21,952][379328] Avg episode reward: [(0, '8613.150')] +[2026-07-22 22:29:24,090][380295] Updated weights for policy 0, policy_version 48400 (0.0010) +[2026-07-22 22:29:26,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 24805376. Throughput: 0: 7065.6. Samples: 24806912. Policy #0 lag: (min: 9.0, avg: 11.9, max: 73.0) +[2026-07-22 22:29:26,952][379328] Avg episode reward: [(0, '8656.500')] +[2026-07-22 22:29:29,245][380295] Updated weights for policy 0, policy_version 48502 (0.0010) +[2026-07-22 22:29:31,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7220.1). Total num frames: 24838144. Throughput: 0: 7020.1. Samples: 24849408. Policy #0 lag: (min: 9.0, avg: 11.9, max: 73.0) +[2026-07-22 22:29:31,952][379328] Avg episode reward: [(0, '8669.350')] +[2026-07-22 22:29:36,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7136.8). Total num frames: 24870912. Throughput: 0: 7054.2. Samples: 24893952. Policy #0 lag: (min: 9.0, avg: 11.9, max: 73.0) +[2026-07-22 22:29:36,952][379328] Avg episode reward: [(0, '8782.650')] +[2026-07-22 22:29:37,865][380295] Updated weights for policy 0, policy_version 48608 (0.0008) +[2026-07-22 22:29:41,951][379328] Fps is (10 sec: 6553.6, 60 sec: 7099.7, 300 sec: 7109.0). Total num frames: 24903680. Throughput: 0: 7054.2. Samples: 24913920. Policy #0 lag: (min: 9.0, avg: 11.9, max: 73.0) +[2026-07-22 22:29:41,952][379328] Avg episode reward: [(0, '8686.050')] +[2026-07-22 22:29:43,088][380295] Updated weights for policy 0, policy_version 48700 (0.0012) +[2026-07-22 22:29:46,951][379328] Fps is (10 sec: 6553.6, 60 sec: 6963.2, 300 sec: 7109.0). Total num frames: 24936448. Throughput: 0: 7088.3. Samples: 24956928. Policy #0 lag: (min: 9.0, avg: 11.9, max: 73.0) +[2026-07-22 22:29:46,952][379328] Avg episode reward: [(0, '8775.550')] +[2026-07-22 22:29:51,951][379328] Fps is (10 sec: 8192.0, 60 sec: 6963.2, 300 sec: 7164.5). Total num frames: 24985600. Throughput: 0: 7213.5. Samples: 25001472. Policy #0 lag: (min: 9.0, avg: 12.7, max: 73.0) +[2026-07-22 22:29:51,952][379328] Avg episode reward: [(0, '8691.400')] +[2026-07-22 22:29:51,964][380295] Updated weights for policy 0, policy_version 48816 (0.0010) +[2026-07-22 22:29:56,272][380289] Early stopping after 2 epochs (16 sgd steps), loss delta 0.0000000 +[2026-07-22 22:29:56,273][380296] Stopping RolloutWorker_w0... +[2026-07-22 22:29:56,273][379328] Component RolloutWorker_w0 stopped! +[2026-07-22 22:29:56,273][380296] Loop rollout_proc0_evt_loop terminating... +[2026-07-22 22:29:56,274][380289] Stopping Batcher_0... +[2026-07-22 22:29:56,274][379328] Component Batcher_0 stopped! +[2026-07-22 22:29:56,274][380289] Loop batcher_evt_loop terminating... +[2026-07-22 22:29:56,288][380295] Weights refcount: 2 0 +[2026-07-22 22:29:56,289][380295] Stopping InferenceWorker_p0-w0... +[2026-07-22 22:29:56,290][380295] Loop inference_proc0-0_evt_loop terminating... +[2026-07-22 22:29:56,289][379328] Component InferenceWorker_p0-w0 stopped! +[2026-07-22 22:29:56,376][380289] Early stopping after 2 epochs (16 sgd steps), loss delta 0.0000000 +[2026-07-22 22:29:56,377][380289] Saving results/checkpoints/memory/rollout_teacher/demon_attack_teacher_fixed_l6_obs15_seed0/checkpoint_p0/checkpoint_000048864_25018368.pth... +[2026-07-22 22:29:56,403][380289] Removing results/checkpoints/memory/rollout_teacher/demon_attack_teacher_fixed_l6_obs15_seed0/checkpoint_p0/checkpoint_000013888_7110656.pth +[2026-07-22 22:29:56,509][380289] Early stopping after 2 epochs (16 sgd steps), loss delta 0.0000000 +[2026-07-22 22:29:56,510][380289] Saving results/checkpoints/memory/rollout_teacher/demon_attack_teacher_fixed_l6_obs15_seed0/checkpoint_p0/checkpoint_000048880_25026560.pth... +[2026-07-22 22:29:56,534][380289] Removing results/checkpoints/memory/rollout_teacher/demon_attack_teacher_fixed_l6_obs15_seed0/checkpoint_p0/checkpoint_000021760_11141120.pth +[2026-07-22 22:29:56,537][379328] Component LearnerWorker_p0 stopped! +[2026-07-22 22:29:56,538][380289] Stopping LearnerWorker_p0... +[2026-07-22 22:29:56,538][380289] Loop learner_proc0_evt_loop terminating... +[2026-07-22 22:29:56,538][379328] Waiting for process learner_proc0 to stop... +[2026-07-22 22:29:57,385][379328] Waiting for process inference_proc0-0 to join... +[2026-07-22 22:29:57,386][379328] Waiting for process rollout_proc0 to join... +[2026-07-22 22:29:57,386][379328] Batcher 0 profile tree view: +batching: 1.2287, releasing_batches: 1.2965 +[2026-07-22 22:29:57,386][379328] InferenceWorker_p0-w0 profile tree view: +wait_policy: 0.0051 + wait_policy_total: 3372.5408 +update_model: 5.7662 + weight_update: 0.0010 +one_step: 0.0019 + handle_policy_step: 88.9590 + deserialize: 4.7785, stack: 0.0785, obs_to_device_normalize: 16.1657, forward: 39.5451, prepare_outputs: 21.1181, send_messages: 2.8422 +[2026-07-22 22:29:57,387][379328] Learner 0 profile tree view: +misc: 0.0104, prepare_batch: 66.8436 +train: 539.3571 + epoch_init: 0.0648, minibatch_init: 3.8887, losses_postprocess: 119.6338, kl_divergence: 105.7003, update: 109.2450, after_optimizer: 137.8919 + calculate_losses: 58.0316 + losses_init: 0.1141, forward_head: 17.2760, bptt_initial: 0.6482, bptt: 0.5976, tail: 13.5237, advantages_returns: 4.4880, losses: 17.1295 +[2026-07-22 22:29:57,387][379328] RolloutWorker_w0 profile tree view: +wait_for_trajectories: 0.0583, enqueue_policy_requests: 10.7952, wait_policy_outputs_event: 2.3706, process_policy_outputs: 6.2846, env_step: 3489.4938, finalize_trajectories: 0.1173, complete_rollouts: 0.1120 +post_env_step: 17.0094 + process_env_step: 6.3415 +[2026-07-22 22:29:57,391][379328] Loop Runner_EvtLoop terminating... +[2026-07-22 22:29:57,392][379328] Runner profile tree view: +main_loop: 3765.8316 +[2026-07-22 22:29:57,392][379328] Collected {0: 25026560}, FPS: 6645.7 diff --git a/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/eval/fixed_6/eval_latency_6/episode_metrics.jsonl b/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/eval/fixed_6/eval_latency_6/episode_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..35b8c8213088ef00cf8fe2087ac96b928d3e31f3 --- /dev/null +++ b/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/eval/fixed_6/eval_latency_6/episode_metrics.jsonl @@ -0,0 +1,20 @@ +{"episode_id": 0, "episode_return": 1440.0, "episode_return_env": 1440.0, "game_score": null, "mean_latency_ms": 100.0, "metadata": {"checkpoint_path": "/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_5000_pytorch_model.pt", "config_name": "starvla_wan_oft_demon_attack_raw6", "configured_latency_ms": 100.0, "env_fps": 60.0, "env_id": "ALE/DemonAttack-v5", "episode_seed": 42, "eval_latency_steps": 6, "frame_ms": 16.666666666666668, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 15.0, "output_dir": "/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/eval/fixed_6/eval_latency_6", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_demon_attack_raw6", "suite_name": "fixed_6", "target_device": null, "train_latency_steps": 6}, "num_actions": 1786, "num_dropped_actions": 1, "num_invalid_actions": 0, "p90_latency_ms": 100.0, "p99_latency_ms": 100.0, "return_raw": null, "survival_steps": 7141} +{"episode_id": 1, "episode_return": 7070.0, "episode_return_env": 7070.0, "game_score": null, "mean_latency_ms": 100.0, "metadata": {"checkpoint_path": "/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_5000_pytorch_model.pt", "config_name": "starvla_wan_oft_demon_attack_raw6", "configured_latency_ms": 100.0, "env_fps": 60.0, "env_id": "ALE/DemonAttack-v5", "episode_seed": 43, "eval_latency_steps": 6, "frame_ms": 16.666666666666668, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 15.0, "output_dir": "/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/eval/fixed_6/eval_latency_6", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_demon_attack_raw6", "suite_name": "fixed_6", "target_device": null, "train_latency_steps": 6}, "num_actions": 3600, "num_dropped_actions": 0, "num_invalid_actions": 0, "p90_latency_ms": 100.0, "p99_latency_ms": 100.0, "return_raw": null, "survival_steps": 14400} +{"episode_id": 2, "episode_return": 5170.0, "episode_return_env": 5170.0, "game_score": null, "mean_latency_ms": 100.0, "metadata": {"checkpoint_path": "/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_5000_pytorch_model.pt", "config_name": "starvla_wan_oft_demon_attack_raw6", "configured_latency_ms": 100.0, "env_fps": 60.0, "env_id": "ALE/DemonAttack-v5", "episode_seed": 44, "eval_latency_steps": 6, "frame_ms": 16.666666666666668, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 15.0, "output_dir": "/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/eval/fixed_6/eval_latency_6", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_demon_attack_raw6", "suite_name": "fixed_6", "target_device": null, "train_latency_steps": 6}, "num_actions": 3600, "num_dropped_actions": 0, "num_invalid_actions": 0, "p90_latency_ms": 100.0, "p99_latency_ms": 100.0, "return_raw": null, "survival_steps": 14400} +{"episode_id": 3, "episode_return": 4970.0, "episode_return_env": 4970.0, "game_score": null, "mean_latency_ms": 100.0, "metadata": {"checkpoint_path": "/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_5000_pytorch_model.pt", "config_name": "starvla_wan_oft_demon_attack_raw6", "configured_latency_ms": 100.0, "env_fps": 60.0, "env_id": "ALE/DemonAttack-v5", "episode_seed": 45, "eval_latency_steps": 6, "frame_ms": 16.666666666666668, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 15.0, "output_dir": 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"/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_5000_pytorch_model.pt", "config_name": "starvla_wan_oft_demon_attack_raw6", "configured_latency_ms": 100.0, "env_fps": 60.0, "env_id": "ALE/DemonAttack-v5", "episode_seed": 46, "eval_latency_steps": 6, "frame_ms": 16.666666666666668, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 15.0, "output_dir": "/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/eval/fixed_6/eval_latency_6", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_demon_attack_raw6", "suite_name": "fixed_6", "target_device": null, "train_latency_steps": 6}, "num_actions": 3600, "num_dropped_actions": 0, "num_invalid_actions": 0, "p90_latency_ms": 100.0, "p99_latency_ms": 100.0, "return_raw": null, "survival_steps": 14400} +{"episode_id": 5, "episode_return": 1600.0, "episode_return_env": 1600.0, "game_score": null, "mean_latency_ms": 100.0, "metadata": {"checkpoint_path": "/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_5000_pytorch_model.pt", "config_name": "starvla_wan_oft_demon_attack_raw6", "configured_latency_ms": 100.0, "env_fps": 60.0, "env_id": "ALE/DemonAttack-v5", "episode_seed": 47, "eval_latency_steps": 6, "frame_ms": 16.666666666666668, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 15.0, "output_dir": 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"/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_5000_pytorch_model.pt", "config_name": "starvla_wan_oft_demon_attack_raw6", "configured_latency_ms": 100.0, "env_fps": 60.0, "env_id": "ALE/DemonAttack-v5", "episode_seed": 48, "eval_latency_steps": 6, "frame_ms": 16.666666666666668, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 15.0, "output_dir": "/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/eval/fixed_6/eval_latency_6", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_demon_attack_raw6", "suite_name": "fixed_6", "target_device": null, 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a/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/hydra/.hydra/hydra.yaml b/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/hydra/.hydra/hydra.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a2d220afee23f3957d167cda161a9ee97ceb3026 --- /dev/null +++ b/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/hydra/.hydra/hydra.yaml @@ -0,0 +1,379 @@ +hydra: + run: + dir: ${run_root_dir}/${run_id}/hydra + sweep: + dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S} + subdir: ${hydra.job.num} + launcher: + _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher + sweeper: + _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper + max_batch_size: null + params: null + help: + app_name: ${hydra.job.name} + header: '${hydra.help.app_name} is powered by Hydra. + + ' + footer: 'Powered by Hydra (https://hydra.cc) + + Use --hydra-help to view Hydra specific help + + ' + template: '${hydra.help.header} + + == Configuration groups == + + Compose your configuration from those groups (group=option) + + + $APP_CONFIG_GROUPS + + + == Config == + + Override anything in the config (foo.bar=value) + + + $CONFIG + + + ${hydra.help.footer} + + ' + hydra_help: + template: 'Hydra (${hydra.runtime.version}) + + See https://hydra.cc for more info. + + + == Flags == + + $FLAGS_HELP + + + == Configuration groups == + + Compose your configuration from those groups (For example, append hydra/job_logging=disabled + to command line) + + + $HYDRA_CONFIG_GROUPS + + + Use ''--cfg hydra'' to Show the Hydra config. + + ' + hydra_help: ??? + hydra_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][HYDRA] %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + root: + level: INFO + handlers: + - console + loggers: + logging_example: + level: DEBUG + disable_existing_loggers: false + job_logging: + version: 1 + formatters: + simple: + format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s' + handlers: + console: + class: logging.StreamHandler + formatter: simple + stream: ext://sys.stdout + file: + class: logging.FileHandler + formatter: simple + filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log + root: + level: INFO + handlers: + - console + - file + disable_existing_loggers: false + env: {} + mode: RUN + searchpath: [] + callbacks: {} + output_subdir: .hydra + overrides: + hydra: + - hydra.mode=RUN + task: + - model=wan_oft + - env=demon_attack + - init=wan_oft_libero + - mode=single + - ++framework.qwenvl.base_vlm=playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers + - ++framework.qwenvl.attn_implementation=sdpa + - ++framework.qwenvl.flex_backend=triton + - ++framework.qwenvl.enable_gradient_checkpointing=true + - ++framework.action_model.state_dim=7 + - ++framework.action_model.loss_type=current_discrete_ce + - ++framework.action_model.action_horizon=8 + - ++framework.action_model.future_action_window_size=7 + - ++framework.action_model.past_action_window_size=0 + - ++framework.action_model.action_model_type=MLP + - ++framework.action_model.action_dim=7 + - ++framework.action_model.action_env_dim=6 + - ++framework.action_model.action_query_source=mean + - ++framework.action_model.action_query_num_heads=24 + - ++framework.kv_memory.enabled=false + - ++framework.kv_memory.window=4 + - ++framework.kv_memory.rollout_len=8 + - ++framework.kv_memory.packed_train=false + - ++framework.kv_memory.rebased_sink=true + - ++framework.name=WanOFT + - ++framework.world_model.base_wm=playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers + - ++framework.world_model.extract_layers=[-1] + - ++framework.world_model.num_frames=5 + - ++datasets.vla_data.dataset_py=lerobot_datasets + - ++datasets.vla_data.include_state=true + - ++datasets.vla_data.data_root_dir=playground/Datasets/rl_games + - ++datasets.vla_data.data_mix=demon_attack_train__bridge + - ++datasets.vla_data.eval_data_mix=null + - ++datasets.vla_data.custom_mixtures_path=null + - ++datasets.vla_data.action_type=discrete + - ++datasets.vla_data.sequential_step_sampling=false + - ++datasets.vla_data.eval_sequential_step_sampling=null + - ++datasets.vla_data.num_workers=8 + - ++datasets.vla_data.eval_num_workers=8 + - ++datasets.vla_data.prefetch_factor=4 + - ++datasets.vla_data.persistent_workers=true + - ++datasets.vla_data.pin_memory=true + - ++datasets.vla_data.shuffle=true + - ++datasets.vla_data.action_balance.enabled=false + - ++datasets.vla_data.action_balance.strategy=balanced_epoch + - ++datasets.vla_data.action_balance.action_key=action_id + - ++datasets.vla_data.action_balance.target_flap_fraction=0.3 + - ++datasets.vla_data.action_balance.noop_id=0 + - ++datasets.vla_data.action_balance.flap_id=1 + - ++datasets.vla_data.latency_curriculum.enabled=false + - ++datasets.vla_data.latency_curriculum.strategy=exclusive + - ++datasets.vla_data.latency_curriculum.latencies=null + - ++datasets.vla_data.latency_curriculum.phase_steps=null + - ++datasets.vla_data.latency_curriculum.phase_distributions=null + - ++datasets.vla_data.latency_curriculum.new_latency_passes=1.0 + - ++datasets.vla_data.latency_curriculum.replay_passes=0.25 + - ++datasets.vla_data.latency_curriculum.target_total_passes=2.0 + - ++datasets.vla_data.latency_curriculum.final_equalization=true + - ++datasets.vla_data.latency_curriculum.step_budget_mode=auto + - ++datasets.vla_data.latency_curriculum.eval_at_phase_end=false + - ++datasets.vla_data.latency_curriculum.save_at_phase_end=false + - ++datasets.vla_data.latency_curriculum.computed_plan=null + - ++datasets.vla_data.per_device_batch_size=1 + - ++datasets.vla_data.load_all_data_for_training=true + - ++datasets.vla_data.num_obs_frames=1 + - ++datasets.vla_data.image_mode=single + - ++datasets.vla_data.prompt_mode=raw + - ++datasets.vla_data.stitch_grid=[2,2] + - ++datasets.vla_data.obs_image_size=[224,224] + - ++datasets.vla_data.video_backend=torchvision_av + - ++datasets.vla_data.observation_indices=[-4,-3,-2,-1,0] + - ++datasets.vla_data.language_indices=[0] + - ++datasets.vla_data.state_indices=[0] + - ++datasets.vla_data.action_indices=[0,1,2,3,4,5,6,7] + - ++datasets.vla_data.pack_image_sequence=true + - ++datasets.vla_data.image_sequence_length=5 + - ++datasets.vla_data.context_images_column=observation.context_images + - ++dataset.source_hf=latency-sensitive-bench/memory-rollouts + - ++dataset.config_name=demon_attack_fixed_latency_6_200ep_7k2steps + - ++dataset.source_subdir=null + - ++dataset.converted_name=demon_attack_train__bridge + - ++dataset.single_source_hf= + - ++dataset.mixed_source_hf= + - ++dataset.single_converted_name=demon_attack_train__bridge + - ++dataset.mixed_converted_name=demon_attack_mixed_latency_train__bridge + - ++dataset.single_latency_filter=null + - ++dataset.mixed_latency_filter=null + - ++dataset.force_download=false + - ++dataset.setup_force=false + - ++dataset.skip_verification=false + - ++dataset.target_latency_unit=observation_steps + - ++dataset.verify_rows=200 + - ++dataset.max_episodes=200 + - ++dataset.episodes_per_latency=null + - ++dataset.latency_filter=null + - ++dataset.debug_subset.enabled=false + - ++dataset.debug_subset.max_episodes=5 + - ++dataset.debug_subset.suffix=debug + - ++base_model.repo_id=Wan-AI/Wan2.2-TI2V-5B-Diffusers + - ++initialization.checkpoint_local_dir=playground/Pretrained_models/WM4A-Wan2d2-OFT-LIBERO-4in1 + - ++initialization.checkpoint_hf_repo_id=StarVLA/WM4A-Wan2d2-OFT-LIBERO-4in1 + - ++initialization.checkpoint_filename=checkpoints/steps_60000_pytorch_model.pt + - ++trainer.max_train_steps=5000 + - ++trainer.num_warmup_steps=0 + - ++trainer.save_interval=500 + - ++trainer.eval_interval=100 + - ++trainer.eval_num_batches=100 + - ++trainer.per_latency_eval_num_batches=null + - ++trainer.eval_action_classification=false + - ++trainer.eval_action_classification_interval=null + - ++trainer.cc_f1_tolerance=1 + - ++trainer.learning_rate.base=2.5e-05 + - ++trainer.learning_rate.qwen_vl_interface=1e-05 + - ++trainer.learning_rate.action_model=0.0001 + - ++trainer.learning_rate.action_query_proj=0.0001 + - ++trainer.lr_scheduler_type=cosine_with_min_lr + - ++trainer.scheduler_specific_kwargs.min_lr=1e-06 + - ++trainer.freeze_modules= + - ++trainer.freeze_vit=false + - ++trainer.freeze_tied_embedding=false + - ++trainer.freeze_llm_layers=[] + - ++trainer.loss_scale.vla=1.0 + - ++trainer.loss_scale.vlm=0.1 + - ++trainer.max_grad_norm=1.0 + - ++trainer.weight_decay=0.0 + - ++trainer.logging_frequency=1 + - ++trainer.profile_timing.enabled=false + - ++trainer.profile_timing.log_interval=10 + - ++trainer.gradient_clipping=1.0 + - ++trainer.gradient_accumulation_steps=16 + - ++trainer.distributed_backend=deepspeed + - ++trainer.is_resume=false + - ++trainer.pretrained_checkpoint=null + - ++trainer.resume_step=0 + - ++trainer.reload_modules=null + - ++trainer.optimizer.name=AdamW + - ++trainer.optimizer.betas=[0.9,0.95] + - ++trainer.optimizer.eps=1e-08 + - ++trainer.optimizer.weight_decay=1e-08 + - ++trainer.optimizer.fused=true + - ++trainer.save_format=pt + - ++workspace_dir=WORKSPACE_DIR + - ++run_root_dir=results/Checkpoints + - ++seed=42 + - ++auth.env_file=null + - ++auth.hf_token_env=HF_TOKEN + - ++auth.wandb_api_key_env=WANDB_API_KEY + - ++paths.run_root_dir=results/Checkpoints + - ++paths.dataset_local_dir=data/demon_attack_fix_latency_6_200ep_context5 + - ++paths.dataset_cache_dir=null + - ++paths.base_model_dir=playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers + - ++paths.accelerate_config=starVLA/config/deepseeds/deepspeed_zero2.yaml + - ++rl_games.model_alias=wan_oft + - ++rl_games.env_eval.image_size=224 + - ++rl_games.env_eval.frameskip=4 + - ++rl_games.env_eval.image_transform=raw_rgb + - ++rl_games.env_eval.prompt_mode=raw + - ++rl_games.env_eval.ghost_trail.history_frames=5 + - ++rl_games.env_eval.ghost_trail.gamma=1.3 + - ++rl_games.env_eval.ghost_trail.min_alpha=35 + - ++rl_games.env_eval.ghost_trail.scroll_px_per_step=4.0 + - ++rl_games.env_eval.ghost_trail.ground_fraction=0.22 + - ++rl_games.env_eval.seed=42 + - ++rl_games.env_eval.fixed_episode_seeds=true + - ++rl_games.env_eval.latency_seed_stride=0 + - ++rl_games.env_eval.task_seed_stride=0 + - '++rl_games.env_eval.task_description=''You are playing Demon Attack from a + single game image. Choose exactly one action from: NOOP, FIRE, RIGHT, LEFT, + RIGHTFIRE, LEFTFIRE.''' + - ++rl_games.env_eval.eval_parallel_envs=5 + - ++rl_games.env_eval.action_chunk_execution.enabled=false + - ++rl_games.env_eval.action_chunk_execution.chunk_size=null + - ++rl_games.env_eval.demon_attack.noop_max=30 + - ++rl_games.env_eval.enabled=true + - ++rl_games.env_eval.eval_backend=eval_core + - ++rl_games.env_eval.distributed_mode=rank_sharded + - ++rl_games.env_eval.vectorized.enabled=false + - ++rl_games.env_eval.vectorized.batch_size=1 + - ++rl_games.env_eval.latency.prompt_map_path=data/demon_attack_fix_latency_6_200ep_context5/demon_attack_train__bridge/latency_prompt_map.json + - ++rl_games.env_eval.latency.mode=single + - ++rl_games.env_eval.latency.values=[0] + - ++rl_games.env_eval.mid_train.enabled=false + - ++rl_games.env_eval.mid_train.interval_steps=100 + - ++rl_games.env_eval.mid_train.latencies=[0] + - ++rl_games.env_eval.mid_train.num_episodes=5 + - ++rl_games.env_eval.mid_train.max_steps_per_episode=3600 + - ++rl_games.env_eval.post_train.enabled=false + - ++rl_games.env_eval.post_train.latencies=[6] + - ++rl_games.env_eval.post_train.num_episodes=20 + - ++rl_games.env_eval.post_train.max_steps_per_episode=3600 + - ++rl_games.task=demon_attack + - ++rl_games.initialization_mode=bridge + - ++rl_games.action_carrier=bridge + - ++checkpoint.load=auto + - ++checkpoint.hf_repo_id=null + - ++checkpoint.save_best_model=false + - ++checkpoint.save_final_model=true + - ++checkpoint.save_pt_file=true + - ++checkpoint.save_training_state=true + - ++checkpoint.save_safetensors_file=false + - ++checkpoint.local.keep_last_n=1 + - ++checkpoint.sync.enabled=false + - ++checkpoint.sync.repo_id=null + - ++checkpoint.sync.keep_last_n=0 + - ++checkpoint.sync.sync_every_n_checkpoints=1 + - ++checkpoint.sync.resume_policy=local_latest + - ++run_id=wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce + - ++output_dir=null + - ++config_yaml=null + - ++is_debug=false + - ++version_id=0.21 + - ++run_root_dir=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints + - ++trainer.is_resume=true + - ++trainer.pretrained_checkpoint=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state + - ++trainer.resume_step=4000 + - ++datasets.vla_data.data_root_dir=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/data/demon_attack_fix_latency_6_200ep_context5 + - ++framework.qwenvl.base_vlm=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers + - ++framework.world_model.base_wm=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers + job: + name: train_starvla_hydra + chdir: false + override_dirname: '++auth.env_file=null,++auth.hf_token_env=HF_TOKEN,++auth.wandb_api_key_env=WANDB_API_KEY,++base_model.repo_id=Wan-AI/Wan2.2-TI2V-5B-Diffusers,++checkpoint.hf_repo_id=null,++checkpoint.load=auto,++checkpoint.local.keep_last_n=1,++checkpoint.save_best_model=false,++checkpoint.save_final_model=true,++checkpoint.save_pt_file=true,++checkpoint.save_safetensors_file=false,++checkpoint.save_training_state=true,++checkpoint.sync.enabled=false,++checkpoint.sync.keep_last_n=0,++checkpoint.sync.repo_id=null,++checkpoint.sync.resume_policy=local_latest,++checkpoint.sync.sync_every_n_checkpoints=1,++config_yaml=null,++dataset.config_name=demon_attack_fixed_latency_6_200ep_7k2steps,++dataset.converted_name=demon_attack_train__bridge,++dataset.debug_subset.enabled=false,++dataset.debug_subset.max_episodes=5,++dataset.debug_subset.suffix=debug,++dataset.episodes_per_latency=null,++dataset.force_download=false,++dataset.latency_filter=null,++dataset.max_episodes=200,++dataset.mixed_converted_name=demon_attack_mixed_latency_train__bridge,++dataset.mixed_latency_filter=null,++dataset.mixed_source_hf=,++dataset.setup_force=false,++dataset.single_converted_name=demon_attack_train__bridge,++dataset.single_latency_filter=null,++dataset.single_source_hf=,++dataset.skip_verification=false,++dataset.source_hf=latency-sensitive-bench/memory-rollouts,++dataset.source_subdir=null,++dataset.target_latency_unit=observation_steps,++dataset.verify_rows=200,++datasets.vla_data.action_balance.action_key=action_id,++datasets.vla_data.action_balance.enabled=false,++datasets.vla_data.action_balance.flap_id=1,++datasets.vla_data.action_balance.noop_id=0,++datasets.vla_data.action_balance.strategy=balanced_epoch,++datasets.vla_data.action_balance.target_flap_fraction=0.3,++datasets.vla_data.action_indices=[0,1,2,3,4,5,6,7],++datasets.vla_data.action_type=discrete,++datasets.vla_data.context_images_column=observation.context_images,++datasets.vla_data.custom_mixtures_path=null,++datasets.vla_data.data_mix=demon_attack_train__bridge,++datasets.vla_data.data_root_dir=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/data/demon_attack_fix_latency_6_200ep_context5,++datasets.vla_data.data_root_dir=playground/Datasets/rl_games,++datasets.vla_data.dataset_py=lerobot_datasets,++datasets.vla_data.eval_data_mix=null,++datasets.vla_data.eval_num_workers=8,++datasets.vla_data.eval_sequential_step_sampling=null,++datasets.vla_data.image_mode=single,++datasets.vla_data.image_sequence_length=5,++datasets.vla_data.include_state=true,++datasets.vla_data.language_indices=[0],++datasets.vla_data.latency_curriculum.computed_plan=null,++datasets.vla_data.latency_curriculum.enabled=false,++datasets.vla_data.latency_curriculum.eval_at_phase_end=false,++datasets.vla_data.latency_curriculum.final_equalization=true,++datasets.vla_data.latency_curriculum.latencies=null,++datasets.vla_data.latency_curriculum.new_latency_passes=1.0,++datasets.vla_data.latency_curriculum.phase_distributions=null,++datasets.vla_data.latency_curriculum.phase_steps=null,++datasets.vla_data.latency_curriculum.replay_passes=0.25,++datasets.vla_data.latency_curriculum.save_at_phase_end=false,++datasets.vla_data.latency_curriculum.step_budget_mode=auto,++datasets.vla_data.latency_curriculum.strategy=exclusive,++datasets.vla_data.latency_curriculum.target_total_passes=2.0,++datasets.vla_data.load_all_data_for_training=true,++datasets.vla_data.num_obs_frames=1,++datasets.vla_data.num_workers=8,++datasets.vla_data.obs_image_size=[224,224],++datasets.vla_data.observation_indices=[-4,-3,-2,-1,0],++datasets.vla_data.pack_image_sequence=true,++datasets.vla_data.per_device_batch_size=1,++datasets.vla_data.persistent_workers=true,++datasets.vla_data.pin_memory=true,++datasets.vla_data.prefetch_factor=4,++datasets.vla_data.prompt_mode=raw,++datasets.vla_data.sequential_step_sampling=false,++datasets.vla_data.shuffle=true,++datasets.vla_data.state_indices=[0],++datasets.vla_data.stitch_grid=[2,2],++datasets.vla_data.video_backend=torchvision_av,++framework.action_model.action_dim=7,++framework.action_model.action_env_dim=6,++framework.action_model.action_horizon=8,++framework.action_model.action_model_type=MLP,++framework.action_model.action_query_num_heads=24,++framework.action_model.action_query_source=mean,++framework.action_model.future_action_window_size=7,++framework.action_model.loss_type=current_discrete_ce,++framework.action_model.past_action_window_size=0,++framework.action_model.state_dim=7,++framework.kv_memory.enabled=false,++framework.kv_memory.packed_train=false,++framework.kv_memory.rebased_sink=true,++framework.kv_memory.rollout_len=8,++framework.kv_memory.window=4,++framework.name=WanOFT,++framework.qwenvl.attn_implementation=sdpa,++framework.qwenvl.base_vlm=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers,++framework.qwenvl.base_vlm=playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers,++framework.qwenvl.enable_gradient_checkpointing=true,++framework.qwenvl.flex_backend=triton,++framework.world_model.base_wm=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers,++framework.world_model.base_wm=playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers,++framework.world_model.extract_layers=[-1],++framework.world_model.num_frames=5,++initialization.checkpoint_filename=checkpoints/steps_60000_pytorch_model.pt,++initialization.checkpoint_hf_repo_id=StarVLA/WM4A-Wan2d2-OFT-LIBERO-4in1,++initialization.checkpoint_local_dir=playground/Pretrained_models/WM4A-Wan2d2-OFT-LIBERO-4in1,++is_debug=false,++output_dir=null,++paths.accelerate_config=starVLA/config/deepseeds/deepspeed_zero2.yaml,++paths.base_model_dir=playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers,++paths.dataset_cache_dir=null,++paths.dataset_local_dir=data/demon_attack_fix_latency_6_200ep_context5,++paths.run_root_dir=results/Checkpoints,++rl_games.action_carrier=bridge,++rl_games.env_eval.action_chunk_execution.chunk_size=null,++rl_games.env_eval.action_chunk_execution.enabled=false,++rl_games.env_eval.demon_attack.noop_max=30,++rl_games.env_eval.distributed_mode=rank_sharded,++rl_games.env_eval.enabled=true,++rl_games.env_eval.eval_backend=eval_core,++rl_games.env_eval.eval_parallel_envs=5,++rl_games.env_eval.fixed_episode_seeds=true,++rl_games.env_eval.frameskip=4,++rl_games.env_eval.ghost_trail.gamma=1.3,++rl_games.env_eval.ghost_trail.ground_fraction=0.22,++rl_games.env_eval.ghost_trail.history_frames=5,++rl_games.env_eval.ghost_trail.min_alpha=35,++rl_games.env_eval.ghost_trail.scroll_px_per_step=4.0,++rl_games.env_eval.image_size=224,++rl_games.env_eval.image_transform=raw_rgb,++rl_games.env_eval.latency.mode=single,++rl_games.env_eval.latency.prompt_map_path=data/demon_attack_fix_latency_6_200ep_context5/demon_attack_train__bridge/latency_prompt_map.json,++rl_games.env_eval.latency.values=[0],++rl_games.env_eval.latency_seed_stride=0,++rl_games.env_eval.mid_train.enabled=false,++rl_games.env_eval.mid_train.interval_steps=100,++rl_games.env_eval.mid_train.latencies=[0],++rl_games.env_eval.mid_train.max_steps_per_episode=3600,++rl_games.env_eval.mid_train.num_episodes=5,++rl_games.env_eval.post_train.enabled=false,++rl_games.env_eval.post_train.latencies=[6],++rl_games.env_eval.post_train.max_steps_per_episode=3600,++rl_games.env_eval.post_train.num_episodes=20,++rl_games.env_eval.prompt_mode=raw,++rl_games.env_eval.seed=42,++rl_games.env_eval.task_description=''You + are playing Demon Attack from a single game image. Choose exactly one action + from: NOOP, FIRE, RIGHT, LEFT, RIGHTFIRE, LEFTFIRE.'',++rl_games.env_eval.task_seed_stride=0,++rl_games.env_eval.vectorized.batch_size=1,++rl_games.env_eval.vectorized.enabled=false,++rl_games.initialization_mode=bridge,++rl_games.model_alias=wan_oft,++rl_games.task=demon_attack,++run_id=wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce,++run_root_dir=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints,++run_root_dir=results/Checkpoints,++seed=42,++trainer.cc_f1_tolerance=1,++trainer.distributed_backend=deepspeed,++trainer.eval_action_classification=false,++trainer.eval_action_classification_interval=null,++trainer.eval_interval=100,++trainer.eval_num_batches=100,++trainer.freeze_llm_layers=[],++trainer.freeze_modules=,++trainer.freeze_tied_embedding=false,++trainer.freeze_vit=false,++trainer.gradient_accumulation_steps=16,++trainer.gradient_clipping=1.0,++trainer.is_resume=false,++trainer.is_resume=true,++trainer.learning_rate.action_model=0.0001,++trainer.learning_rate.action_query_proj=0.0001,++trainer.learning_rate.base=2.5e-05,++trainer.learning_rate.qwen_vl_interface=1e-05,++trainer.logging_frequency=1,++trainer.loss_scale.vla=1.0,++trainer.loss_scale.vlm=0.1,++trainer.lr_scheduler_type=cosine_with_min_lr,++trainer.max_grad_norm=1.0,++trainer.max_train_steps=5000,++trainer.num_warmup_steps=0,++trainer.optimizer.betas=[0.9,0.95],++trainer.optimizer.eps=1e-08,++trainer.optimizer.fused=true,++trainer.optimizer.name=AdamW,++trainer.optimizer.weight_decay=1e-08,++trainer.per_latency_eval_num_batches=null,++trainer.pretrained_checkpoint=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state,++trainer.pretrained_checkpoint=null,++trainer.profile_timing.enabled=false,++trainer.profile_timing.log_interval=10,++trainer.reload_modules=null,++trainer.resume_step=0,++trainer.resume_step=4000,++trainer.save_format=pt,++trainer.save_interval=500,++trainer.scheduler_specific_kwargs.min_lr=1e-06,++trainer.weight_decay=0.0,++version_id=0.21,++workspace_dir=WORKSPACE_DIR,env=demon_attack,init=wan_oft_libero,mode=single,model=wan_oft' + id: ??? + num: ??? + config_name: train + env_set: {} + env_copy: [] + config: + override_dirname: + kv_sep: '=' + item_sep: ',' + exclude_keys: [] + runtime: + version: 1.3.4 + version_base: '1.1' + cwd: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA + config_sources: + - path: hydra.conf + schema: pkg + provider: hydra + - path: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/examples/rl_games/config + schema: file + provider: main + - path: '' + schema: structured + provider: schema + output_dir: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/hydra + choices: + cross_task_setup: null + checkpoint: default + mode: single + init: wan_oft_libero + env: demon_attack + model: wan_oft + hydra/env: default + hydra/callbacks: null + hydra/job_logging: default + hydra/hydra_logging: default + hydra/hydra_help: default + hydra/help: default + hydra/sweeper: basic + hydra/launcher: basic + hydra/output: default + verbose: false diff --git a/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/hydra/.hydra/overrides.yaml b/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/hydra/.hydra/overrides.yaml new file mode 100644 index 0000000000000000000000000000000000000000..5612450f396b305bc04d0f512b81748be3249b8b --- /dev/null +++ b/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/hydra/.hydra/overrides.yaml @@ -0,0 +1,217 @@ +- model=wan_oft +- env=demon_attack +- init=wan_oft_libero +- mode=single +- ++framework.qwenvl.base_vlm=playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers +- ++framework.qwenvl.attn_implementation=sdpa +- ++framework.qwenvl.flex_backend=triton +- ++framework.qwenvl.enable_gradient_checkpointing=true +- ++framework.action_model.state_dim=7 +- ++framework.action_model.loss_type=current_discrete_ce +- ++framework.action_model.action_horizon=8 +- ++framework.action_model.future_action_window_size=7 +- ++framework.action_model.past_action_window_size=0 +- ++framework.action_model.action_model_type=MLP +- ++framework.action_model.action_dim=7 +- ++framework.action_model.action_env_dim=6 +- ++framework.action_model.action_query_source=mean +- ++framework.action_model.action_query_num_heads=24 +- ++framework.kv_memory.enabled=false +- ++framework.kv_memory.window=4 +- ++framework.kv_memory.rollout_len=8 +- ++framework.kv_memory.packed_train=false +- ++framework.kv_memory.rebased_sink=true +- ++framework.name=WanOFT +- ++framework.world_model.base_wm=playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers +- ++framework.world_model.extract_layers=[-1] +- ++framework.world_model.num_frames=5 +- ++datasets.vla_data.dataset_py=lerobot_datasets +- ++datasets.vla_data.include_state=true +- ++datasets.vla_data.data_root_dir=playground/Datasets/rl_games +- ++datasets.vla_data.data_mix=demon_attack_train__bridge +- ++datasets.vla_data.eval_data_mix=null +- ++datasets.vla_data.custom_mixtures_path=null +- ++datasets.vla_data.action_type=discrete +- ++datasets.vla_data.sequential_step_sampling=false +- ++datasets.vla_data.eval_sequential_step_sampling=null +- ++datasets.vla_data.num_workers=8 +- ++datasets.vla_data.eval_num_workers=8 +- ++datasets.vla_data.prefetch_factor=4 +- ++datasets.vla_data.persistent_workers=true +- ++datasets.vla_data.pin_memory=true +- ++datasets.vla_data.shuffle=true +- ++datasets.vla_data.action_balance.enabled=false +- ++datasets.vla_data.action_balance.strategy=balanced_epoch +- ++datasets.vla_data.action_balance.action_key=action_id +- ++datasets.vla_data.action_balance.target_flap_fraction=0.3 +- ++datasets.vla_data.action_balance.noop_id=0 +- ++datasets.vla_data.action_balance.flap_id=1 +- ++datasets.vla_data.latency_curriculum.enabled=false +- ++datasets.vla_data.latency_curriculum.strategy=exclusive +- ++datasets.vla_data.latency_curriculum.latencies=null +- ++datasets.vla_data.latency_curriculum.phase_steps=null +- ++datasets.vla_data.latency_curriculum.phase_distributions=null +- ++datasets.vla_data.latency_curriculum.new_latency_passes=1.0 +- ++datasets.vla_data.latency_curriculum.replay_passes=0.25 +- ++datasets.vla_data.latency_curriculum.target_total_passes=2.0 +- ++datasets.vla_data.latency_curriculum.final_equalization=true +- ++datasets.vla_data.latency_curriculum.step_budget_mode=auto +- ++datasets.vla_data.latency_curriculum.eval_at_phase_end=false +- ++datasets.vla_data.latency_curriculum.save_at_phase_end=false +- ++datasets.vla_data.latency_curriculum.computed_plan=null +- ++datasets.vla_data.per_device_batch_size=1 +- ++datasets.vla_data.load_all_data_for_training=true +- ++datasets.vla_data.num_obs_frames=1 +- ++datasets.vla_data.image_mode=single +- ++datasets.vla_data.prompt_mode=raw +- ++datasets.vla_data.stitch_grid=[2,2] +- ++datasets.vla_data.obs_image_size=[224,224] +- ++datasets.vla_data.video_backend=torchvision_av +- ++datasets.vla_data.observation_indices=[-4,-3,-2,-1,0] +- ++datasets.vla_data.language_indices=[0] +- ++datasets.vla_data.state_indices=[0] +- ++datasets.vla_data.action_indices=[0,1,2,3,4,5,6,7] +- ++datasets.vla_data.pack_image_sequence=true +- ++datasets.vla_data.image_sequence_length=5 +- ++datasets.vla_data.context_images_column=observation.context_images +- ++dataset.source_hf=latency-sensitive-bench/memory-rollouts +- ++dataset.config_name=demon_attack_fixed_latency_6_200ep_7k2steps +- ++dataset.source_subdir=null +- ++dataset.converted_name=demon_attack_train__bridge +- ++dataset.single_source_hf= +- ++dataset.mixed_source_hf= +- ++dataset.single_converted_name=demon_attack_train__bridge +- ++dataset.mixed_converted_name=demon_attack_mixed_latency_train__bridge +- ++dataset.single_latency_filter=null +- ++dataset.mixed_latency_filter=null +- ++dataset.force_download=false +- ++dataset.setup_force=false +- ++dataset.skip_verification=false +- ++dataset.target_latency_unit=observation_steps +- ++dataset.verify_rows=200 +- ++dataset.max_episodes=200 +- ++dataset.episodes_per_latency=null +- ++dataset.latency_filter=null +- ++dataset.debug_subset.enabled=false +- ++dataset.debug_subset.max_episodes=5 +- ++dataset.debug_subset.suffix=debug +- ++base_model.repo_id=Wan-AI/Wan2.2-TI2V-5B-Diffusers +- ++initialization.checkpoint_local_dir=playground/Pretrained_models/WM4A-Wan2d2-OFT-LIBERO-4in1 +- ++initialization.checkpoint_hf_repo_id=StarVLA/WM4A-Wan2d2-OFT-LIBERO-4in1 +- ++initialization.checkpoint_filename=checkpoints/steps_60000_pytorch_model.pt +- ++trainer.max_train_steps=5000 +- ++trainer.num_warmup_steps=0 +- ++trainer.save_interval=500 +- ++trainer.eval_interval=100 +- ++trainer.eval_num_batches=100 +- ++trainer.per_latency_eval_num_batches=null +- ++trainer.eval_action_classification=false +- ++trainer.eval_action_classification_interval=null +- ++trainer.cc_f1_tolerance=1 +- ++trainer.learning_rate.base=2.5e-05 +- ++trainer.learning_rate.qwen_vl_interface=1e-05 +- ++trainer.learning_rate.action_model=0.0001 +- ++trainer.learning_rate.action_query_proj=0.0001 +- ++trainer.lr_scheduler_type=cosine_with_min_lr +- ++trainer.scheduler_specific_kwargs.min_lr=1e-06 +- ++trainer.freeze_modules= +- ++trainer.freeze_vit=false +- ++trainer.freeze_tied_embedding=false +- ++trainer.freeze_llm_layers=[] +- ++trainer.loss_scale.vla=1.0 +- ++trainer.loss_scale.vlm=0.1 +- ++trainer.max_grad_norm=1.0 +- ++trainer.weight_decay=0.0 +- ++trainer.logging_frequency=1 +- ++trainer.profile_timing.enabled=false +- ++trainer.profile_timing.log_interval=10 +- ++trainer.gradient_clipping=1.0 +- ++trainer.gradient_accumulation_steps=16 +- ++trainer.distributed_backend=deepspeed +- ++trainer.is_resume=false +- ++trainer.pretrained_checkpoint=null +- ++trainer.resume_step=0 +- ++trainer.reload_modules=null +- ++trainer.optimizer.name=AdamW +- ++trainer.optimizer.betas=[0.9,0.95] +- ++trainer.optimizer.eps=1e-08 +- ++trainer.optimizer.weight_decay=1e-08 +- ++trainer.optimizer.fused=true +- ++trainer.save_format=pt +- ++workspace_dir=WORKSPACE_DIR +- ++run_root_dir=results/Checkpoints +- ++seed=42 +- ++auth.env_file=null +- ++auth.hf_token_env=HF_TOKEN +- ++auth.wandb_api_key_env=WANDB_API_KEY +- ++paths.run_root_dir=results/Checkpoints +- ++paths.dataset_local_dir=data/demon_attack_fix_latency_6_200ep_context5 +- ++paths.dataset_cache_dir=null +- ++paths.base_model_dir=playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers +- ++paths.accelerate_config=starVLA/config/deepseeds/deepspeed_zero2.yaml +- ++rl_games.model_alias=wan_oft +- ++rl_games.env_eval.image_size=224 +- ++rl_games.env_eval.frameskip=4 +- ++rl_games.env_eval.image_transform=raw_rgb +- ++rl_games.env_eval.prompt_mode=raw +- ++rl_games.env_eval.ghost_trail.history_frames=5 +- ++rl_games.env_eval.ghost_trail.gamma=1.3 +- ++rl_games.env_eval.ghost_trail.min_alpha=35 +- ++rl_games.env_eval.ghost_trail.scroll_px_per_step=4.0 +- ++rl_games.env_eval.ghost_trail.ground_fraction=0.22 +- ++rl_games.env_eval.seed=42 +- ++rl_games.env_eval.fixed_episode_seeds=true +- ++rl_games.env_eval.latency_seed_stride=0 +- ++rl_games.env_eval.task_seed_stride=0 +- '++rl_games.env_eval.task_description=''You are playing Demon Attack from a single + game image. Choose exactly one action from: NOOP, FIRE, RIGHT, LEFT, RIGHTFIRE, + LEFTFIRE.''' +- ++rl_games.env_eval.eval_parallel_envs=5 +- ++rl_games.env_eval.action_chunk_execution.enabled=false +- ++rl_games.env_eval.action_chunk_execution.chunk_size=null +- ++rl_games.env_eval.demon_attack.noop_max=30 +- ++rl_games.env_eval.enabled=true +- ++rl_games.env_eval.eval_backend=eval_core +- ++rl_games.env_eval.distributed_mode=rank_sharded +- ++rl_games.env_eval.vectorized.enabled=false +- ++rl_games.env_eval.vectorized.batch_size=1 +- ++rl_games.env_eval.latency.prompt_map_path=data/demon_attack_fix_latency_6_200ep_context5/demon_attack_train__bridge/latency_prompt_map.json +- ++rl_games.env_eval.latency.mode=single +- ++rl_games.env_eval.latency.values=[0] +- ++rl_games.env_eval.mid_train.enabled=false +- ++rl_games.env_eval.mid_train.interval_steps=100 +- ++rl_games.env_eval.mid_train.latencies=[0] +- ++rl_games.env_eval.mid_train.num_episodes=5 +- ++rl_games.env_eval.mid_train.max_steps_per_episode=3600 +- ++rl_games.env_eval.post_train.enabled=false +- ++rl_games.env_eval.post_train.latencies=[6] +- ++rl_games.env_eval.post_train.num_episodes=20 +- ++rl_games.env_eval.post_train.max_steps_per_episode=3600 +- ++rl_games.task=demon_attack +- ++rl_games.initialization_mode=bridge +- ++rl_games.action_carrier=bridge +- ++checkpoint.load=auto +- ++checkpoint.hf_repo_id=null +- ++checkpoint.save_best_model=false +- ++checkpoint.save_final_model=true +- ++checkpoint.save_pt_file=true +- ++checkpoint.save_training_state=true +- ++checkpoint.save_safetensors_file=false +- ++checkpoint.local.keep_last_n=1 +- ++checkpoint.sync.enabled=false +- ++checkpoint.sync.repo_id=null +- ++checkpoint.sync.keep_last_n=0 +- ++checkpoint.sync.sync_every_n_checkpoints=1 +- ++checkpoint.sync.resume_policy=local_latest +- ++run_id=wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce +- ++output_dir=null +- ++config_yaml=null +- ++is_debug=false +- ++version_id=0.21 +- ++run_root_dir=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints +- ++trainer.is_resume=true +- ++trainer.pretrained_checkpoint=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state +- ++trainer.resume_step=4000 +- ++datasets.vla_data.data_root_dir=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/data/demon_attack_fix_latency_6_200ep_context5 +- ++framework.qwenvl.base_vlm=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers +- ++framework.world_model.base_wm=/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers diff --git a/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/hydra/train_starvla_hydra.log b/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/hydra/train_starvla_hydra.log new file mode 100644 index 0000000000000000000000000000000000000000..b1cf8562eaa13a084ca63721d576a06064c3164a --- /dev/null +++ b/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/hydra/train_starvla_hydra.log @@ -0,0 +1,7026 @@ +[2026-07-26 16:59:03,969][starVLA.model.framework.share_tools][INFO] - [*] [apply_config_compat] normalised config from version_id=0.21 to '0.21' +[2026-07-26 16:59:04,356][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-26 16:59:04,362][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-26 16:59:04,938][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-26 16:59:04,957][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-26 16:59:06,654][starVLA.model.modules.world_model.Wan2][INFO] - [*] Loading Wan2.2-TI2V from /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers +[2026-07-26 17:01:15,638][starVLA.training.train_starvla][INFO] - Preloaded model checkpoint before Accelerator/DeepSpeed initialization: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/WM4A-Wan2d2-OFT-LIBERO-4in1/checkpoints/steps_60000_pytorch_model.pt +[2026-07-26 17:01:15,686][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-26 17:01:17,286][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-26 17:01:17,286][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-26 17:01:17,286][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-26 17:01:17,287][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-26 17:01:17,287][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-26 17:01:17,287][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-26 17:01:17,287][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-26 17:01:17,288][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-26 17:01:17,288][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-26 17:01:17,288][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-26 17:01:17,289][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 17:01:17,289][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 17:01:17,289][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-26 17:01:17,290][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-26 17:01:17,290][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-26 17:01:17,290][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-26 17:01:17,290][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-26 17:01:17,290][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-26 17:01:17,290][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-26 17:01:17,291][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-26 17:01:17,291][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-26 17:01:17,291][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-26 17:01:17,292][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-26 17:01:17,292][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-26 17:01:17,292][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-26 17:01:17,293][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-26 17:01:17,293][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-26 17:01:17,293][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-26 17:01:17,293][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 17:01:17,294][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 17:01:17,294][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-26 17:01:37,901][starVLA.dataloader][INFO] - Created train VLA dataloader with num_workers=8, persistent_workers=True, cpu_only_workers=True +[2026-07-26 17:01:37,933][starVLA.training.train_starvla][INFO] - 📝 Full config saved at /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/config.full.yaml +[2026-07-26 17:01:37,943][starVLA.training.train_starvla][INFO] - 📊 Accessed config snapshot saved at /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/config.yaml +[2026-07-26 17:01:37,945][starVLA.training.train_starvla][INFO] - No pretrained checkpoint provided. Starting training from scratch. +[2026-07-26 17:01:52,828][starVLA.training.train_starvla][INFO] - ***** Training Configuration ***** +[2026-07-26 17:01:52,828][starVLA.training.train_starvla][INFO] - Total optimization steps = 5000 +[2026-07-26 17:01:52,828][starVLA.training.train_starvla][INFO] - Per device batch size = 4 +[2026-07-26 17:01:52,828][starVLA.training.train_starvla][INFO] - Gradient accumulation steps = 32 +[2026-07-26 17:01:52,829][starVLA.training.train_starvla][INFO] - Total batch size = 128 +[2026-07-26 17:03:31,635][starVLA.training.train_starvla][INFO] - Step 1, Loss: {'train/loss': 1.788145899772644, 'train/grad_norm_pre_clip': 11.7479887008667, 'timing/data': 0.0002928841859102249, 'timing/model': 0.8800391163676977, 'learning_rate/action_model': 9.999999052518008e-05, 'learning_rate/action_query_proj': 9.999999052518008e-05, 'learning_rate/base': 2.499999763129502e-05, 'epoch': 0.0}) +[2026-07-26 17:03:34,294][root][INFO] - /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/bin/x86_64-conda-linux-gnu-cc -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/include -DNDEBUG -D_FORTIFY_SOURCE=2 -O2 -isystem /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/include -fPIC -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/include -c /tmp/tmpkgopmd43/test.c -o /tmp/tmpkgopmd43/test.o +[2026-07-26 17:03:34,311][root][INFO] - /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/bin/x86_64-conda-linux-gnu-cc -Wl,-O2 -Wl,--sort-common -Wl,--as-needed -Wl,-z,relro -Wl,-z,now -Wl,--disable-new-dtags -Wl,--gc-sections -Wl,-rpath,/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/lib -Wl,-rpath-link,/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/lib -L/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/lib /tmp/tmpkgopmd43/test.o -laio -o /tmp/tmpkgopmd43/a.out +[2026-07-26 17:03:34,896][root][INFO] - /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/bin/x86_64-conda-linux-gnu-cc -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/include -DNDEBUG -D_FORTIFY_SOURCE=2 -O2 -isystem /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/include -fPIC -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/include -c /tmp/tmpvpozy209/test.c -o /tmp/tmpvpozy209/test.o +[2026-07-26 17:03:34,912][root][INFO] - /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/bin/x86_64-conda-linux-gnu-cc -Wl,-O2 -Wl,--sort-common -Wl,--as-needed -Wl,-z,relro -Wl,-z,now -Wl,--disable-new-dtags -Wl,--gc-sections -Wl,-rpath,/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/lib -Wl,-rpath-link,/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/lib -L/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/lib /tmp/tmpvpozy209/test.o -L/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft -L/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/lib64 -lcufile -o /tmp/tmpvpozy209/a.out +[2026-07-26 17:03:34,969][root][INFO] - /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/bin/x86_64-conda-linux-gnu-cc -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/include -DNDEBUG -D_FORTIFY_SOURCE=2 -O2 -isystem /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/include -fPIC -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/include -c /tmp/tmpck1jwdho/test.c -o /tmp/tmpck1jwdho/test.o +[2026-07-26 17:03:34,985][root][INFO] - /lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/bin/x86_64-conda-linux-gnu-cc -Wl,-O2 -Wl,--sort-common -Wl,--as-needed -Wl,-z,relro -Wl,-z,now -Wl,--disable-new-dtags -Wl,--gc-sections -Wl,-rpath,/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/lib -Wl,-rpath-link,/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/lib -L/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/starvla_wanoft/lib /tmp/tmpck1jwdho/test.o -laio -o /tmp/tmpck1jwdho/a.out +[2026-07-26 19:11:33,769][starVLA.model.framework.share_tools][INFO] - [*] [apply_config_compat] normalised config from version_id=0.21 to '0.21' +[2026-07-26 19:11:33,770][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-26 19:11:33,773][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-26 19:11:33,942][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-26 19:11:33,946][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-26 19:11:34,091][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-26 19:11:34,094][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-26 19:11:34,429][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-26 19:11:34,432][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-26 19:11:34,510][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-26 19:11:34,513][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-26 19:11:34,536][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-26 19:11:34,540][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-26 19:11:34,545][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-26 19:11:34,548][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-26 19:11:34,548][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-26 19:11:34,549][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-26 19:11:34,551][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-26 19:11:34,564][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-26 19:11:34,895][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-26 19:11:34,911][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-26 19:11:34,945][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-26 19:11:34,961][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-26 19:11:34,963][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-26 19:11:34,979][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-26 19:11:35,028][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-26 19:11:35,050][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-26 19:11:35,051][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-26 19:11:35,057][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-26 19:11:35,058][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-26 19:11:35,067][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-26 19:11:35,073][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-26 19:11:35,074][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-26 19:11:37,383][starVLA.model.modules.world_model.Wan2][INFO] - [*] Loading Wan2.2-TI2V from /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers +[2026-07-26 19:15:44,349][starVLA.training.train_starvla][INFO] - Preloaded model checkpoint before Accelerator/DeepSpeed initialization: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/WM4A-Wan2d2-OFT-LIBERO-4in1/checkpoints/steps_60000_pytorch_model.pt +[2026-07-26 19:15:44,361][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-26 19:15:44,366][starVLA.training.train_starvla][INFO] - Preloaded model checkpoint before Accelerator/DeepSpeed initialization: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/WM4A-Wan2d2-OFT-LIBERO-4in1/checkpoints/steps_60000_pytorch_model.pt +[2026-07-26 19:15:44,380][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-26 19:15:44,487][starVLA.training.train_starvla][INFO] - Preloaded model checkpoint before Accelerator/DeepSpeed initialization: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/WM4A-Wan2d2-OFT-LIBERO-4in1/checkpoints/steps_60000_pytorch_model.pt +[2026-07-26 19:15:44,498][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-26 19:15:44,509][starVLA.training.train_starvla][INFO] - Preloaded model checkpoint before Accelerator/DeepSpeed initialization: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/WM4A-Wan2d2-OFT-LIBERO-4in1/checkpoints/steps_60000_pytorch_model.pt +[2026-07-26 19:15:44,516][starVLA.training.train_starvla][INFO] - Preloaded model checkpoint before Accelerator/DeepSpeed initialization: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/WM4A-Wan2d2-OFT-LIBERO-4in1/checkpoints/steps_60000_pytorch_model.pt +[2026-07-26 19:15:44,518][starVLA.training.train_starvla][INFO] - Preloaded model checkpoint before Accelerator/DeepSpeed initialization: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/WM4A-Wan2d2-OFT-LIBERO-4in1/checkpoints/steps_60000_pytorch_model.pt +[2026-07-26 19:15:44,520][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-26 19:15:44,527][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-26 19:15:44,529][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-26 19:15:44,674][starVLA.training.train_starvla][INFO] - Preloaded model checkpoint before Accelerator/DeepSpeed initialization: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/WM4A-Wan2d2-OFT-LIBERO-4in1/checkpoints/steps_60000_pytorch_model.pt +[2026-07-26 19:15:44,685][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-26 19:15:45,053][starVLA.training.train_starvla][INFO] - Preloaded model checkpoint before Accelerator/DeepSpeed initialization: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/WM4A-Wan2d2-OFT-LIBERO-4in1/checkpoints/steps_60000_pytorch_model.pt +[2026-07-26 19:15:45,068][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-26 19:15:47,167][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-26 19:15:47,167][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-26 19:15:47,167][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-26 19:15:47,167][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-26 19:15:47,167][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-26 19:15:47,167][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-26 19:15:47,167][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-26 19:15:47,169][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-26 19:15:47,171][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-26 19:15:47,173][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-26 19:15:47,175][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,176][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-26 19:15:47,177][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-26 19:15:47,178][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-26 19:15:47,178][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-26 19:15:47,178][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-26 19:15:47,178][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-26 19:15:47,180][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-26 19:15:47,182][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-26 19:15:47,184][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-26 19:15:47,186][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-26 19:15:47,188][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-26 19:15:47,300][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-26 19:15:47,301][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-26 19:15:47,301][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-26 19:15:47,301][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-26 19:15:47,302][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-26 19:15:47,302][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-26 19:15:47,302][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-26 19:15:47,303][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-26 19:15:47,303][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-26 19:15:47,303][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-26 19:15:47,304][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,304][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-26 19:15:47,304][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-26 19:15:47,305][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-26 19:15:47,305][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-26 19:15:47,305][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-26 19:15:47,306][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-26 19:15:47,306][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-26 19:15:47,306][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-26 19:15:47,307][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-26 19:15:47,307][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-26 19:15:47,307][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-26 19:15:47,307][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-26 19:15:47,307][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-26 19:15:47,307][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-26 19:15:47,308][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-26 19:15:47,308][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-26 19:15:47,308][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-26 19:15:47,309][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,309][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-26 19:15:47,309][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-26 19:15:54,706][starVLA.dataloader][INFO] - Created train VLA dataloader with num_workers=8, persistent_workers=True, cpu_only_workers=True +[2026-07-26 19:15:54,753][starVLA.training.train_starvla][INFO] - LR Group action_model: lr=0.0001, num_params=16 +[2026-07-26 19:15:54,754][starVLA.training.train_starvla][INFO] - LR Group action_query_proj: lr=0.0001, num_params=2 +[2026-07-26 19:15:54,754][starVLA.training.train_starvla][INFO] - LR Group base: lr=2.5e-05, num_params=1263 +[2026-07-26 19:15:54,771][starVLA.training.train_starvla][INFO] - No pretrained checkpoint provided. Starting training from scratch. +[2026-07-26 19:15:54,771][starVLA.training.train_starvla][INFO] - No pretrained checkpoint provided. Starting training from scratch. +[2026-07-26 19:15:54,771][starVLA.training.train_starvla][INFO] - No pretrained checkpoint provided. Starting training from scratch. +[2026-07-26 19:15:54,771][starVLA.training.train_starvla][INFO] - No pretrained checkpoint provided. Starting training from scratch. +[2026-07-26 19:15:54,771][starVLA.training.train_starvla][INFO] - No pretrained checkpoint provided. Starting training from scratch. +[2026-07-26 19:15:54,771][starVLA.training.train_starvla][INFO] - No pretrained checkpoint provided. Starting training from scratch. +[2026-07-26 19:15:54,771][starVLA.training.train_starvla][INFO] - No pretrained checkpoint provided. Starting training from scratch. +[2026-07-26 19:15:54,784][starVLA.training.train_starvla][INFO] - 📝 Full config saved at /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/config.full.yaml +[2026-07-26 19:15:54,795][starVLA.training.train_starvla][INFO] - 📊 Accessed config snapshot saved at /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/config.yaml +[2026-07-26 19:15:54,796][starVLA.training.train_starvla][INFO] - No pretrained checkpoint provided. Starting training from scratch. +[2026-07-26 19:16:28,522][starVLA.training.train_starvla][INFO] - ***** Training Configuration ***** +[2026-07-26 19:16:28,523][starVLA.training.train_starvla][INFO] - Total optimization steps = 5000 +[2026-07-26 19:16:28,523][starVLA.training.train_starvla][INFO] - Per device batch size = 1 +[2026-07-26 19:16:28,523][starVLA.training.train_starvla][INFO] - Gradient accumulation steps = 16 +[2026-07-26 19:16:28,523][starVLA.training.train_starvla][INFO] - Total batch size = 128 +[2026-07-26 19:17:45,014][starVLA.training.train_starvla][INFO] - Step 1, Loss: {'train/loss': 1.7881466150283813, 'train/grad_norm_pre_clip': 11.719829559326172, 'timing/data': 0.00017526093870401382, 'timing/model': 1.6548246266320348, 'learning_rate/action_model': 9.999999052518008e-05, 'learning_rate/action_query_proj': 9.999999052518008e-05, 'learning_rate/base': 2.499999763129502e-05, 'epoch': 0.0}) +[2026-07-26 19:17:51,389][starVLA.training.train_starvla][INFO] - Step 2, Loss: {'train/loss': 1.73834228515625, 'train/grad_norm_pre_clip': 6.921702861785889, 'timing/data': 0.00023268815129995346, 'timing/model': 1.03607769170776, 'learning_rate/action_model': 9.99999621007241e-05, 'learning_rate/action_query_proj': 9.99999621007241e-05, 'learning_rate/base': 2.4999990525181024e-05, 'epoch': 0.0}) +[2026-07-26 19:17:57,046][starVLA.training.train_starvla][INFO] - Step 3, Loss: {'train/loss': 1.7075111865997314, 'train/grad_norm_pre_clip': 6.056496620178223, 'timing/data': 0.00020899809896945953, 'timing/model': 0.4601925411261618, 'learning_rate/action_model': 9.999991472664323e-05, 'learning_rate/action_query_proj': 9.999991472664323e-05, 'learning_rate/base': 2.4999978681660807e-05, 'epoch': 0.0}) +[2026-07-26 19:18:02,676][starVLA.training.train_starvla][INFO] - Step 4, Loss: {'train/loss': 1.747523307800293, 'train/grad_norm_pre_clip': 8.094951629638672, 'timing/data': 0.00020042480900883675, 'timing/model': 0.45786487916484475, 'learning_rate/action_model': 9.99998484029562e-05, 'learning_rate/action_query_proj': 9.99998484029562e-05, 'learning_rate/base': 2.499996210073905e-05, 'epoch': 0.0}) +[2026-07-26 19:18:08,254][starVLA.training.train_starvla][INFO] - Step 5, Loss: {'train/loss': 1.6868553161621094, 'train/grad_norm_pre_clip': 5.971827030181885, 'timing/data': 0.00020179199054837227, 'timing/model': 0.45744197303429246, 'learning_rate/action_model': 9.99997631296892e-05, 'learning_rate/action_query_proj': 9.99997631296892e-05, 'learning_rate/base': 2.49999407824223e-05, 'epoch': 0.0}) +[2026-07-26 19:18:13,793][starVLA.training.train_starvla][INFO] - Step 6, Loss: {'train/loss': 1.667550802230835, 'train/grad_norm_pre_clip': 10.485665321350098, 'timing/data': 0.00020517362281680107, 'timing/model': 0.45769959315657616, 'learning_rate/action_model': 9.999965890687587e-05, 'learning_rate/action_query_proj': 9.999965890687587e-05, 'learning_rate/base': 2.4999914726718967e-05, 'epoch': 0.0}) +[2026-07-26 19:18:19,325][starVLA.training.train_starvla][INFO] - Step 7, Loss: {'train/loss': 1.695839524269104, 'train/grad_norm_pre_clip': 6.424682140350342, 'timing/data': 0.00018790597096085548, 'timing/model': 0.45710725197568536, 'learning_rate/action_model': 9.999953573455739e-05, 'learning_rate/action_query_proj': 9.999953573455739e-05, 'learning_rate/base': 2.4999883933639347e-05, 'epoch': 0.0}) +[2026-07-26 19:18:24,847][starVLA.training.train_starvla][INFO] - Step 8, Loss: {'train/loss': 1.6456602811813354, 'train/grad_norm_pre_clip': 7.514695167541504, 'timing/data': 0.00019496586173772812, 'timing/model': 0.45796769112348557, 'learning_rate/action_model': 9.999939361278237e-05, 'learning_rate/action_query_proj': 9.999939361278237e-05, 'learning_rate/base': 2.4999848403195593e-05, 'epoch': 0.0}) +[2026-07-26 19:18:30,728][starVLA.training.train_starvla][INFO] - Step 9, Loss: {'train/loss': 1.6533175706863403, 'train/grad_norm_pre_clip': 4.393545627593994, 'timing/data': 0.0002154819667339325, 'timing/model': 0.4697054037824273, 'learning_rate/action_model': 9.999923254160689e-05, 'learning_rate/action_query_proj': 9.999923254160689e-05, 'learning_rate/base': 2.4999808135401723e-05, 'epoch': 0.0}) +[2026-07-26 19:18:36,316][starVLA.training.train_starvla][INFO] - Step 10, Loss: {'train/loss': 1.7016537189483643, 'train/grad_norm_pre_clip': 7.994240760803223, 'timing/data': 0.0001922869123518467, 'timing/model': 0.4715734529308975, 'learning_rate/action_model': 9.999905252109459e-05, 'learning_rate/action_query_proj': 9.999905252109459e-05, 'learning_rate/base': 2.4999763130273646e-05, 'epoch': 0.0}) +[2026-07-26 19:18:41,890][starVLA.training.train_starvla][INFO] - Step 11, Loss: {'train/loss': 1.59721839427948, 'train/grad_norm_pre_clip': 7.7545294761657715, 'timing/data': 0.0001924070529639721, 'timing/model': 0.4718461977317929, 'learning_rate/action_model': 9.99988535513165e-05, 'learning_rate/action_query_proj': 9.99988535513165e-05, 'learning_rate/base': 2.4999713387829125e-05, 'epoch': 0.0}) +[2026-07-26 19:18:47,716][starVLA.training.train_starvla][INFO] - Step 12, Loss: {'train/loss': 1.5730944871902466, 'train/grad_norm_pre_clip': 6.586637020111084, 'timing/data': 0.00019753770902752876, 'timing/model': 0.4737621732056141, 'learning_rate/action_model': 9.999863563235118e-05, 'learning_rate/action_query_proj': 9.999863563235118e-05, 'learning_rate/base': 2.4999658908087796e-05, 'epoch': 0.0}) +[2026-07-26 19:18:53,618][starVLA.training.train_starvla][INFO] - Step 13, Loss: {'train/loss': 1.6633145809173584, 'train/grad_norm_pre_clip': 6.445660591125488, 'timing/data': 0.00020223995670676231, 'timing/model': 0.46696572517976165, 'learning_rate/action_model': 9.999839876428467e-05, 'learning_rate/action_query_proj': 9.999839876428467e-05, 'learning_rate/base': 2.4999599691071167e-05, 'epoch': 0.0}) +[2026-07-26 19:18:59,124][starVLA.training.train_starvla][INFO] - Step 14, Loss: {'train/loss': 1.6135174036026, 'train/grad_norm_pre_clip': 3.434701681137085, 'timing/data': 0.00019659288227558136, 'timing/model': 0.4702972238883376, 'learning_rate/action_model': 9.999814294721048e-05, 'learning_rate/action_query_proj': 9.999814294721048e-05, 'learning_rate/base': 2.499953573680262e-05, 'epoch': 0.0}) +[2026-07-26 19:19:04,979][starVLA.training.train_starvla][INFO] - Step 15, Loss: {'train/loss': 1.6069525480270386, 'train/grad_norm_pre_clip': 8.668845176696777, 'timing/data': 0.0001905718818306923, 'timing/model': 0.47783742658793926, 'learning_rate/action_model': 9.99978681812296e-05, 'learning_rate/action_query_proj': 9.99978681812296e-05, 'learning_rate/base': 2.49994670453074e-05, 'epoch': 0.0}) +[2026-07-26 19:19:10,534][starVLA.training.train_starvla][INFO] - Step 16, Loss: {'train/loss': 1.6013368368148804, 'train/grad_norm_pre_clip': 10.633302688598633, 'timing/data': 0.00019880570471286774, 'timing/model': 0.46865621441975236, 'learning_rate/action_model': 9.999757446645048e-05, 'learning_rate/action_query_proj': 9.999757446645048e-05, 'learning_rate/base': 2.499939361661262e-05, 'epoch': 0.0}) +[2026-07-26 19:19:16,086][starVLA.training.train_starvla][INFO] - Step 17, Loss: {'train/loss': 1.5802422761917114, 'train/grad_norm_pre_clip': 11.599308967590332, 'timing/data': 0.00019657006487250328, 'timing/model': 0.46716655418276787, 'learning_rate/action_model': 9.999726180298913e-05, 'learning_rate/action_query_proj': 9.999726180298913e-05, 'learning_rate/base': 2.4999315450747283e-05, 'epoch': 0.0}) +[2026-07-26 19:19:21,641][starVLA.training.train_starvla][INFO] - Step 18, Loss: {'train/loss': 1.4514679908752441, 'train/grad_norm_pre_clip': 4.380980491638184, 'timing/data': 0.0002529681660234928, 'timing/model': 0.4686084482818842, 'learning_rate/action_model': 9.999693019096892e-05, 'learning_rate/action_query_proj': 9.999693019096892e-05, 'learning_rate/base': 2.499923254774223e-05, 'epoch': 0.0}) +[2026-07-26 19:19:27,204][starVLA.training.train_starvla][INFO] - Step 19, Loss: {'train/loss': 1.5567469596862793, 'train/grad_norm_pre_clip': 9.62903118133545, 'timing/data': 0.00025463104248046875, 'timing/model': 0.4680060842074454, 'learning_rate/action_model': 9.999657963052081e-05, 'learning_rate/action_query_proj': 9.999657963052081e-05, 'learning_rate/base': 2.4999144907630202e-05, 'epoch': 0.0}) +[2026-07-26 19:19:32,761][starVLA.training.train_starvla][INFO] - Step 20, Loss: {'train/loss': 1.653246283531189, 'train/grad_norm_pre_clip': 14.666534423828125, 'timing/data': 0.0002611507661640644, 'timing/model': 0.4703413397073746, 'learning_rate/action_model': 9.999621012178318e-05, 'learning_rate/action_query_proj': 9.999621012178318e-05, 'learning_rate/base': 2.4999052530445796e-05, 'epoch': 0.0}) +[2026-07-26 19:19:38,238][starVLA.training.train_starvla][INFO] - Step 21, Loss: {'train/loss': 1.5558315515518188, 'train/grad_norm_pre_clip': 12.128592491149902, 'timing/data': 0.0002659950405359268, 'timing/model': 0.45744382590055466, 'learning_rate/action_model': 9.999582166490191e-05, 'learning_rate/action_query_proj': 9.999582166490191e-05, 'learning_rate/base': 2.4998955416225478e-05, 'epoch': 0.0}) +[2026-07-26 19:19:43,715][starVLA.training.train_starvla][INFO] - Step 22, Loss: {'train/loss': 1.6107791662216187, 'train/grad_norm_pre_clip': 9.362102508544922, 'timing/data': 0.00026096682995557785, 'timing/model': 0.45755122182890773, 'learning_rate/action_model': 9.999541426003034e-05, 'learning_rate/action_query_proj': 9.999541426003034e-05, 'learning_rate/base': 2.4998853565007585e-05, 'epoch': 0.0}) +[2026-07-26 19:19:49,193][starVLA.training.train_starvla][INFO] - Step 23, Loss: {'train/loss': 1.6186612844467163, 'train/grad_norm_pre_clip': 7.101553440093994, 'timing/data': 0.00019753677770495415, 'timing/model': 0.4563234858214855, 'learning_rate/action_model': 9.999498790732934e-05, 'learning_rate/action_query_proj': 9.999498790732934e-05, 'learning_rate/base': 2.4998746976832335e-05, 'epoch': 0.0}) +[2026-07-26 19:19:54,678][starVLA.training.train_starvla][INFO] - Step 24, Loss: {'train/loss': 1.5749423503875732, 'train/grad_norm_pre_clip': 9.195722579956055, 'timing/data': 0.00020047510042786598, 'timing/model': 0.456661406904459, 'learning_rate/action_model': 9.999454260696719e-05, 'learning_rate/action_query_proj': 9.999454260696719e-05, 'learning_rate/base': 2.4998635651741797e-05, 'epoch': 0.0}) +[2026-07-26 19:20:00,165][starVLA.training.train_starvla][INFO] - Step 25, Loss: {'train/loss': 1.5611780881881714, 'train/grad_norm_pre_clip': 9.295300483703613, 'timing/data': 0.0002074912190437317, 'timing/model': 0.4582811649888754, 'learning_rate/action_model': 9.999407835911971e-05, 'learning_rate/action_query_proj': 9.999407835911971e-05, 'learning_rate/base': 2.4998519589779927e-05, 'epoch': 0.0}) +[2026-07-26 19:20:05,648][starVLA.training.train_starvla][INFO] - Step 26, Loss: {'train/loss': 1.4324593544006348, 'train/grad_norm_pre_clip': 6.760777950286865, 'timing/data': 0.00019725924357771873, 'timing/model': 0.4568042950704694, 'learning_rate/action_model': 9.999359516397018e-05, 'learning_rate/action_query_proj': 9.999359516397018e-05, 'learning_rate/base': 2.4998398790992545e-05, 'epoch': 0.0}) +[2026-07-26 19:20:11,138][starVLA.training.train_starvla][INFO] - Step 27, Loss: {'train/loss': 1.4426934719085693, 'train/grad_norm_pre_clip': 3.757725477218628, 'timing/data': 0.00019169412553310394, 'timing/model': 0.4582653590478003, 'learning_rate/action_model': 9.999309302170934e-05, 'learning_rate/action_query_proj': 9.999309302170934e-05, 'learning_rate/base': 2.4998273255427336e-05, 'epoch': 0.0}) +[2026-07-26 19:20:16,606][starVLA.training.train_starvla][INFO] - Step 28, Loss: {'train/loss': 1.4468313455581665, 'train/grad_norm_pre_clip': 6.252518177032471, 'timing/data': 0.00019232602789998055, 'timing/model': 0.45702469116076827, 'learning_rate/action_model': 9.999257193253546e-05, 'learning_rate/action_query_proj': 9.999257193253546e-05, 'learning_rate/base': 2.4998142983133864e-05, 'epoch': 0.0}) +[2026-07-26 19:20:22,075][starVLA.training.train_starvla][INFO] - Step 29, Loss: {'train/loss': 1.3965157270431519, 'train/grad_norm_pre_clip': 3.976944923400879, 'timing/data': 0.00020504090934991837, 'timing/model': 0.4572140113450587, 'learning_rate/action_model': 9.999203189665421e-05, 'learning_rate/action_query_proj': 9.999203189665421e-05, 'learning_rate/base': 2.4998007974163552e-05, 'epoch': 0.0}) +[2026-07-26 19:20:27,564][starVLA.training.train_starvla][INFO] - Step 30, Loss: {'train/loss': 1.4865096807479858, 'train/grad_norm_pre_clip': 5.490882396697998, 'timing/data': 0.00019825529307127, 'timing/model': 0.4572391561232507, 'learning_rate/action_model': 9.999147291427884e-05, 'learning_rate/action_query_proj': 9.999147291427884e-05, 'learning_rate/base': 2.499786822856971e-05, 'epoch': 0.0}) +[2026-07-26 19:20:33,051][starVLA.training.train_starvla][INFO] - Step 31, Loss: {'train/loss': 1.3784042596817017, 'train/grad_norm_pre_clip': 7.432830810546875, 'timing/data': 0.00039071496576070786, 'timing/model': 0.45838662702590227, 'learning_rate/action_model': 9.999089498562998e-05, 'learning_rate/action_query_proj': 9.999089498562998e-05, 'learning_rate/base': 2.4997723746407496e-05, 'epoch': 0.0}) +[2026-07-26 19:20:38,537][starVLA.training.train_starvla][INFO] - Step 32, Loss: {'train/loss': 1.2345125675201416, 'train/grad_norm_pre_clip': 4.768418788909912, 'timing/data': 0.0002573970705270767, 'timing/model': 0.4563508480787277, 'learning_rate/action_model': 9.999029811093582e-05, 'learning_rate/action_query_proj': 9.999029811093582e-05, 'learning_rate/base': 2.4997574527733956e-05, 'epoch': 0.0}) +[2026-07-26 19:20:44,034][starVLA.training.train_starvla][INFO] - Step 33, Loss: {'train/loss': 1.4072047472000122, 'train/grad_norm_pre_clip': 5.045231819152832, 'timing/data': 0.0002519218251109123, 'timing/model': 0.45712967962026596, 'learning_rate/action_model': 9.998968229043199e-05, 'learning_rate/action_query_proj': 9.998968229043199e-05, 'learning_rate/base': 2.4997420572607998e-05, 'epoch': 0.0}) +[2026-07-26 19:20:49,552][starVLA.training.train_starvla][INFO] - Step 34, Loss: {'train/loss': 1.3509671688079834, 'train/grad_norm_pre_clip': 7.135748386383057, 'timing/data': 0.0002528959885239601, 'timing/model': 0.4565560049377382, 'learning_rate/action_model': 9.99890475243616e-05, 'learning_rate/action_query_proj': 9.99890475243616e-05, 'learning_rate/base': 2.49972618810904e-05, 'epoch': 0.0}) +[2026-07-26 19:20:55,072][starVLA.training.train_starvla][INFO] - Step 35, Loss: {'train/loss': 1.3853750228881836, 'train/grad_norm_pre_clip': 6.242444038391113, 'timing/data': 0.000254256185144186, 'timing/model': 0.4579498851671815, 'learning_rate/action_model': 9.998839381297525e-05, 'learning_rate/action_query_proj': 9.998839381297525e-05, 'learning_rate/base': 2.4997098453243813e-05, 'epoch': 0.0}) +[2026-07-26 19:21:00,614][starVLA.training.train_starvla][INFO] - Step 36, Loss: {'train/loss': 1.175363302230835, 'train/grad_norm_pre_clip': 4.590509414672852, 'timing/data': 0.00025579193606972694, 'timing/model': 0.4588717990554869, 'learning_rate/action_model': 9.998772115653099e-05, 'learning_rate/action_query_proj': 9.998772115653099e-05, 'learning_rate/base': 2.4996930289132748e-05, 'epoch': 0.0}) +[2026-07-26 19:21:06,171][starVLA.training.train_starvla][INFO] - Step 37, Loss: {'train/loss': 1.2258294820785522, 'train/grad_norm_pre_clip': 7.187453269958496, 'timing/data': 0.00019920757040381432, 'timing/model': 0.4588606641627848, 'learning_rate/action_model': 9.998702955529441e-05, 'learning_rate/action_query_proj': 9.998702955529441e-05, 'learning_rate/base': 2.4996757388823603e-05, 'epoch': 0.0}) +[2026-07-26 19:21:11,732][starVLA.training.train_starvla][INFO] - Step 38, Loss: {'train/loss': 1.1774051189422607, 'train/grad_norm_pre_clip': 6.375002861022949, 'timing/data': 0.00027664098888635635, 'timing/model': 0.4599532810971141, 'learning_rate/action_model': 9.998631900953854e-05, 'learning_rate/action_query_proj': 9.998631900953854e-05, 'learning_rate/base': 2.4996579752384635e-05, 'epoch': 0.0}) +[2026-07-26 19:21:17,301][starVLA.training.train_starvla][INFO] - Step 39, Loss: {'train/loss': 1.2805408239364624, 'train/grad_norm_pre_clip': 6.598046779632568, 'timing/data': 0.00028554070740938187, 'timing/model': 0.4705960191786289, 'learning_rate/action_model': 9.998558951954387e-05, 'learning_rate/action_query_proj': 9.998558951954387e-05, 'learning_rate/base': 2.4996397379885968e-05, 'epoch': 0.0}) +[2026-07-26 19:21:22,854][starVLA.training.train_starvla][INFO] - Step 40, Loss: {'train/loss': 1.2881040573120117, 'train/grad_norm_pre_clip': 4.353879928588867, 'timing/data': 0.0002695568837225437, 'timing/model': 0.4704384822398424, 'learning_rate/action_model': 9.99848410855984e-05, 'learning_rate/action_query_proj': 9.99848410855984e-05, 'learning_rate/base': 2.49962102713996e-05, 'epoch': 0.0}) +[2026-07-26 19:21:28,428][starVLA.training.train_starvla][INFO] - Step 41, Loss: {'train/loss': 1.4181902408599854, 'train/grad_norm_pre_clip': 12.523743629455566, 'timing/data': 0.0002621971070766449, 'timing/model': 0.47032866906374693, 'learning_rate/action_model': 9.99840737079976e-05, 'learning_rate/action_query_proj': 9.99840737079976e-05, 'learning_rate/base': 2.49960184269994e-05, 'epoch': 0.0}) +[2026-07-26 19:21:33,924][starVLA.training.train_starvla][INFO] - Step 42, Loss: {'train/loss': 1.3315762281417847, 'train/grad_norm_pre_clip': 12.631364822387695, 'timing/data': 0.00025950977578759193, 'timing/model': 0.4579799538478255, 'learning_rate/action_model': 9.998328738704444e-05, 'learning_rate/action_query_proj': 9.998328738704444e-05, 'learning_rate/base': 2.499582184676111e-05, 'epoch': 0.01}) +[2026-07-26 19:21:39,425][starVLA.training.train_starvla][INFO] - Step 43, Loss: {'train/loss': 1.2877134084701538, 'train/grad_norm_pre_clip': 8.668269157409668, 'timing/data': 0.00019570300355553627, 'timing/model': 0.4578309068456292, 'learning_rate/action_model': 9.998248212304932e-05, 'learning_rate/action_query_proj': 9.998248212304932e-05, 'learning_rate/base': 2.499562053076233e-05, 'epoch': 0.01}) +[2026-07-26 19:21:44,934][starVLA.training.train_starvla][INFO] - Step 44, Loss: {'train/loss': 1.1876338720321655, 'train/grad_norm_pre_clip': 5.183211326599121, 'timing/data': 0.00019403919577598572, 'timing/model': 0.45858549792319536, 'learning_rate/action_model': 9.998165791633016e-05, 'learning_rate/action_query_proj': 9.998165791633016e-05, 'learning_rate/base': 2.499541447908254e-05, 'epoch': 0.01}) +[2026-07-26 19:21:50,477][starVLA.training.train_starvla][INFO] - Step 45, Loss: {'train/loss': 1.2236974239349365, 'train/grad_norm_pre_clip': 3.6810572147369385, 'timing/data': 0.00020583998411893845, 'timing/model': 0.4723310540430248, 'learning_rate/action_model': 9.998081476721232e-05, 'learning_rate/action_query_proj': 9.998081476721232e-05, 'learning_rate/base': 2.499520369180308e-05, 'epoch': 0.01}) +[2026-07-26 19:21:56,293][starVLA.training.train_starvla][INFO] - Step 46, Loss: {'train/loss': 1.1857776641845703, 'train/grad_norm_pre_clip': 7.720909118652344, 'timing/data': 0.00028529437258839607, 'timing/model': 0.46467940229922533, 'learning_rate/action_model': 9.997995267602868e-05, 'learning_rate/action_query_proj': 9.997995267602868e-05, 'learning_rate/base': 2.499498816900717e-05, 'epoch': 0.01}) +[2026-07-26 19:22:01,817][starVLA.training.train_starvla][INFO] - Step 47, Loss: {'train/loss': 1.350666880607605, 'train/grad_norm_pre_clip': 9.298501968383789, 'timing/data': 0.00020385487005114555, 'timing/model': 0.4583937800489366, 'learning_rate/action_model': 9.997907164311958e-05, 'learning_rate/action_query_proj': 9.997907164311958e-05, 'learning_rate/base': 2.4994767910779894e-05, 'epoch': 0.01}) +[2026-07-26 19:22:07,335][starVLA.training.train_starvla][INFO] - Step 48, Loss: {'train/loss': 1.207338571548462, 'train/grad_norm_pre_clip': 7.808500289916992, 'timing/data': 0.00024416809901595116, 'timing/model': 0.45778613910079, 'learning_rate/action_model': 9.997817166883286e-05, 'learning_rate/action_query_proj': 9.997817166883286e-05, 'learning_rate/base': 2.4994542917208215e-05, 'epoch': 0.01}) +[2026-07-26 19:22:12,839][starVLA.training.train_starvla][INFO] - Step 49, Loss: {'train/loss': 1.2943973541259766, 'train/grad_norm_pre_clip': 3.3338451385498047, 'timing/data': 0.00020541390404105186, 'timing/model': 0.4576616738922894, 'learning_rate/action_model': 9.997725275352378e-05, 'learning_rate/action_query_proj': 9.997725275352378e-05, 'learning_rate/base': 2.4994313188380945e-05, 'epoch': 0.01}) +[2026-07-26 19:22:18,336][starVLA.training.train_starvla][INFO] - Step 50, Loss: {'train/loss': 1.139003872871399, 'train/grad_norm_pre_clip': 6.223735809326172, 'timing/data': 0.00023910915479063988, 'timing/model': 0.4569482379592955, 'learning_rate/action_model': 9.997631489755513e-05, 'learning_rate/action_query_proj': 9.997631489755513e-05, 'learning_rate/base': 2.4994078724388782e-05, 'epoch': 0.01}) +[2026-07-26 19:22:23,863][starVLA.training.train_starvla][INFO] - Step 51, Loss: {'train/loss': 1.2298083305358887, 'train/grad_norm_pre_clip': 5.55418586730957, 'timing/data': 0.0002554450184106827, 'timing/model': 0.45742042595520616, 'learning_rate/action_model': 9.997535810129714e-05, 'learning_rate/action_query_proj': 9.997535810129714e-05, 'learning_rate/base': 2.4993839525324285e-05, 'epoch': 0.01}) +[2026-07-26 19:22:29,392][starVLA.training.train_starvla][INFO] - Step 52, Loss: {'train/loss': 1.0849413871765137, 'train/grad_norm_pre_clip': 6.427726745605469, 'timing/data': 0.00024625612422823906, 'timing/model': 0.4589944430626929, 'learning_rate/action_model': 9.997438236512756e-05, 'learning_rate/action_query_proj': 9.997438236512756e-05, 'learning_rate/base': 2.499359559128189e-05, 'epoch': 0.01}) +[2026-07-26 19:22:34,928][starVLA.training.train_starvla][INFO] - Step 53, Loss: {'train/loss': 1.2417973279953003, 'train/grad_norm_pre_clip': 6.131040096282959, 'timing/data': 0.00025014299899339676, 'timing/model': 0.45658419001847506, 'learning_rate/action_model': 9.99733876894316e-05, 'learning_rate/action_query_proj': 9.99733876894316e-05, 'learning_rate/base': 2.49933469223579e-05, 'epoch': 0.01}) +[2026-07-26 19:22:40,467][starVLA.training.train_starvla][INFO] - Step 54, Loss: {'train/loss': 1.2232402563095093, 'train/grad_norm_pre_clip': 9.229979515075684, 'timing/data': 0.0002170167863368988, 'timing/model': 0.45786035107448697, 'learning_rate/action_model': 9.997237407460191e-05, 'learning_rate/action_query_proj': 9.997237407460191e-05, 'learning_rate/base': 2.4993093518650478e-05, 'epoch': 0.01}) +[2026-07-26 19:22:46,020][starVLA.training.train_starvla][INFO] - Step 55, Loss: {'train/loss': 1.0804160833358765, 'train/grad_norm_pre_clip': 4.881915092468262, 'timing/data': 0.00019827531650662422, 'timing/model': 0.4573723282665014, 'learning_rate/action_model': 9.997134152103871e-05, 'learning_rate/action_query_proj': 9.997134152103871e-05, 'learning_rate/base': 2.4992835380259678e-05, 'epoch': 0.01}) +[2026-07-26 19:22:51,627][starVLA.training.train_starvla][INFO] - Step 56, Loss: {'train/loss': 1.138253927230835, 'train/grad_norm_pre_clip': 5.600804805755615, 'timing/data': 0.00019726715981960297, 'timing/model': 0.45825778879225254, 'learning_rate/action_model': 9.997029002914957e-05, 'learning_rate/action_query_proj': 9.997029002914957e-05, 'learning_rate/base': 2.4992572507287394e-05, 'epoch': 0.01}) +[2026-07-26 19:22:57,181][starVLA.training.train_starvla][INFO] - Step 57, Loss: {'train/loss': 1.2233436107635498, 'train/grad_norm_pre_clip': 10.988350868225098, 'timing/data': 0.00019328296184539795, 'timing/model': 0.4577955608256161, 'learning_rate/action_model': 9.996921959934963e-05, 'learning_rate/action_query_proj': 9.996921959934963e-05, 'learning_rate/base': 2.4992304899837407e-05, 'epoch': 0.01}) +[2026-07-26 19:23:02,681][starVLA.training.train_starvla][INFO] - Step 58, Loss: {'train/loss': 1.1642323732376099, 'train/grad_norm_pre_clip': 6.7080769538879395, 'timing/data': 0.00019842293113470078, 'timing/model': 0.46032419614493847, 'learning_rate/action_model': 9.996813023206148e-05, 'learning_rate/action_query_proj': 9.996813023206148e-05, 'learning_rate/base': 2.499203255801537e-05, 'epoch': 0.01}) +[2026-07-26 19:23:08,190][starVLA.training.train_starvla][INFO] - Step 59, Loss: {'train/loss': 1.0822254419326782, 'train/grad_norm_pre_clip': 3.8355424404144287, 'timing/data': 0.00019304966554045677, 'timing/model': 0.463145490270108, 'learning_rate/action_model': 9.996702192771519e-05, 'learning_rate/action_query_proj': 9.996702192771519e-05, 'learning_rate/base': 2.4991755481928798e-05, 'epoch': 0.01}) +[2026-07-26 19:23:13,740][starVLA.training.train_starvla][INFO] - Step 60, Loss: {'train/loss': 1.0392606258392334, 'train/grad_norm_pre_clip': 9.819108963012695, 'timing/data': 0.00023235799744725227, 'timing/model': 0.4610195951536298, 'learning_rate/action_model': 9.996589468674828e-05, 'learning_rate/action_query_proj': 9.996589468674828e-05, 'learning_rate/base': 2.499147367168707e-05, 'epoch': 0.01}) +[2026-07-26 19:23:19,268][starVLA.training.train_starvla][INFO] - Step 61, Loss: {'train/loss': 0.998961329460144, 'train/grad_norm_pre_clip': 4.875979900360107, 'timing/data': 0.00019412999972701073, 'timing/model': 0.4636881658807397, 'learning_rate/action_model': 9.99647485096058e-05, 'learning_rate/action_query_proj': 9.99647485096058e-05, 'learning_rate/base': 2.499118712740145e-05, 'epoch': 0.01}) +[2026-07-26 19:23:24,793][starVLA.training.train_starvla][INFO] - Step 62, Loss: {'train/loss': 1.1204406023025513, 'train/grad_norm_pre_clip': 5.392901420593262, 'timing/data': 0.00018649594858288765, 'timing/model': 0.46270979195833206, 'learning_rate/action_model': 9.996358339674021e-05, 'learning_rate/action_query_proj': 9.996358339674021e-05, 'learning_rate/base': 2.4990895849185053e-05, 'epoch': 0.01}) +[2026-07-26 19:23:30,323][starVLA.training.train_starvla][INFO] - Step 63, Loss: {'train/loss': 1.1369835138320923, 'train/grad_norm_pre_clip': 7.469062805175781, 'timing/data': 0.00019018910825252533, 'timing/model': 0.46213032584637403, 'learning_rate/action_model': 9.99623993486115e-05, 'learning_rate/action_query_proj': 9.99623993486115e-05, 'learning_rate/base': 2.4990599837152875e-05, 'epoch': 0.01}) +[2026-07-26 19:23:35,838][starVLA.training.train_starvla][INFO] - Step 64, Loss: {'train/loss': 1.205572247505188, 'train/grad_norm_pre_clip': 6.592559814453125, 'timing/data': 0.00020426325500011444, 'timing/model': 0.4697065376676619, 'learning_rate/action_model': 9.99611963656871e-05, 'learning_rate/action_query_proj': 9.99611963656871e-05, 'learning_rate/base': 2.4990299091421775e-05, 'epoch': 0.01}) +[2026-07-26 19:23:41,403][starVLA.training.train_starvla][INFO] - Step 65, Loss: {'train/loss': 1.2239609956741333, 'train/grad_norm_pre_clip': 7.581450939178467, 'timing/data': 0.0001965537667274475, 'timing/model': 0.4737620591185987, 'learning_rate/action_model': 9.995997444844192e-05, 'learning_rate/action_query_proj': 9.995997444844192e-05, 'learning_rate/base': 2.498999361211048e-05, 'epoch': 0.01}) +[2026-07-26 19:23:46,963][starVLA.training.train_starvla][INFO] - Step 66, Loss: {'train/loss': 1.0269588232040405, 'train/grad_norm_pre_clip': 7.312194347381592, 'timing/data': 0.00018936395645141602, 'timing/model': 0.4785203402861953, 'learning_rate/action_model': 9.995873359735839e-05, 'learning_rate/action_query_proj': 9.995873359735839e-05, 'learning_rate/base': 2.4989683399339598e-05, 'epoch': 0.01}) +[2026-07-26 19:23:52,508][starVLA.training.train_starvla][INFO] - Step 67, Loss: {'train/loss': 1.0186080932617188, 'train/grad_norm_pre_clip': 8.832778930664062, 'timing/data': 0.00018865568563342094, 'timing/model': 0.4681064961478114, 'learning_rate/action_model': 9.995747381292634e-05, 'learning_rate/action_query_proj': 9.995747381292634e-05, 'learning_rate/base': 2.4989368453231586e-05, 'epoch': 0.01}) +[2026-07-26 19:23:58,012][starVLA.training.train_starvla][INFO] - Step 68, Loss: {'train/loss': 1.077117919921875, 'train/grad_norm_pre_clip': 7.632099628448486, 'timing/data': 0.00018337974324822426, 'timing/model': 0.46270825574174523, 'learning_rate/action_model': 9.995619509564315e-05, 'learning_rate/action_query_proj': 9.995619509564315e-05, 'learning_rate/base': 2.4989048773910787e-05, 'epoch': 0.01}) +[2026-07-26 19:24:03,516][starVLA.training.train_starvla][INFO] - Step 69, Loss: {'train/loss': 1.0931425094604492, 'train/grad_norm_pre_clip': 7.726696968078613, 'timing/data': 0.0001915348693728447, 'timing/model': 0.4637053166516125, 'learning_rate/action_model': 9.995489744601361e-05, 'learning_rate/action_query_proj': 9.995489744601361e-05, 'learning_rate/base': 2.4988724361503402e-05, 'epoch': 0.01}) +[2026-07-26 19:24:09,046][starVLA.training.train_starvla][INFO] - Step 70, Loss: {'train/loss': 1.3559650182724, 'train/grad_norm_pre_clip': 6.941307067871094, 'timing/data': 0.00017688190564513206, 'timing/model': 0.4601404541172087, 'learning_rate/action_model': 9.995358086455e-05, 'learning_rate/action_query_proj': 9.995358086455e-05, 'learning_rate/base': 2.49883952161375e-05, 'epoch': 0.01}) +[2026-07-26 19:24:14,589][starVLA.training.train_starvla][INFO] - Step 71, Loss: {'train/loss': 1.1417956352233887, 'train/grad_norm_pre_clip': 6.22157621383667, 'timing/data': 0.00018965499475598335, 'timing/model': 0.46260972088202834, 'learning_rate/action_model': 9.99522453517721e-05, 'learning_rate/action_query_proj': 9.99522453517721e-05, 'learning_rate/base': 2.4988061337943024e-05, 'epoch': 0.01}) +[2026-07-26 19:24:20,118][starVLA.training.train_starvla][INFO] - Step 72, Loss: {'train/loss': 1.1304517984390259, 'train/grad_norm_pre_clip': 3.302685499191284, 'timing/data': 0.00018415413796901703, 'timing/model': 0.4628919647075236, 'learning_rate/action_model': 9.995089090820716e-05, 'learning_rate/action_query_proj': 9.995089090820716e-05, 'learning_rate/base': 2.498772272705179e-05, 'epoch': 0.01}) +[2026-07-26 19:24:25,658][starVLA.training.train_starvla][INFO] - Step 73, Loss: {'train/loss': 1.0834081172943115, 'train/grad_norm_pre_clip': 4.916796684265137, 'timing/data': 0.00017936108633875847, 'timing/model': 0.46266285330057144, 'learning_rate/action_model': 9.99495175343899e-05, 'learning_rate/action_query_proj': 9.99495175343899e-05, 'learning_rate/base': 2.4987379383597474e-05, 'epoch': 0.01}) +[2026-07-26 19:24:31,198][starVLA.training.train_starvla][INFO] - Step 74, Loss: {'train/loss': 0.9799066185951233, 'train/grad_norm_pre_clip': 6.316418170928955, 'timing/data': 0.0001825583167374134, 'timing/model': 0.4604519810527563, 'learning_rate/action_model': 9.994812523086248e-05, 'learning_rate/action_query_proj': 9.994812523086248e-05, 'learning_rate/base': 2.498703130771562e-05, 'epoch': 0.01}) +[2026-07-26 19:24:36,704][starVLA.training.train_starvla][INFO] - Step 75, Loss: {'train/loss': 0.9187439680099487, 'train/grad_norm_pre_clip': 4.9715423583984375, 'timing/data': 0.00018551526591181755, 'timing/model': 0.4568465952761471, 'learning_rate/action_model': 9.994671399817457e-05, 'learning_rate/action_query_proj': 9.994671399817457e-05, 'learning_rate/base': 2.4986678499543643e-05, 'epoch': 0.01}) +[2026-07-26 19:24:42,210][starVLA.training.train_starvla][INFO] - Step 76, Loss: {'train/loss': 0.935197114944458, 'train/grad_norm_pre_clip': 3.5405666828155518, 'timing/data': 0.0001902421936392784, 'timing/model': 0.4570190282538533, 'learning_rate/action_model': 9.994528383688328e-05, 'learning_rate/action_query_proj': 9.994528383688328e-05, 'learning_rate/base': 2.498632095922082e-05, 'epoch': 0.01}) +[2026-07-26 19:24:47,721][starVLA.training.train_starvla][INFO] - Step 77, Loss: {'train/loss': 0.9698812961578369, 'train/grad_norm_pre_clip': 5.964999675750732, 'timing/data': 0.0001845252700150013, 'timing/model': 0.45788525184616446, 'learning_rate/action_model': 9.994383474755328e-05, 'learning_rate/action_query_proj': 9.994383474755328e-05, 'learning_rate/base': 2.498595868688832e-05, 'epoch': 0.01}) +[2026-07-26 19:24:53,251][starVLA.training.train_starvla][INFO] - Step 78, Loss: {'train/loss': 0.9750149250030518, 'train/grad_norm_pre_clip': 5.889784812927246, 'timing/data': 0.0002503376454114914, 'timing/model': 0.45732268365100026, 'learning_rate/action_model': 9.994236673075659e-05, 'learning_rate/action_query_proj': 9.994236673075659e-05, 'learning_rate/base': 2.4985591682689147e-05, 'epoch': 0.01}) +[2026-07-26 19:24:58,770][starVLA.training.train_starvla][INFO] - Step 79, Loss: {'train/loss': 1.1030405759811401, 'train/grad_norm_pre_clip': 7.562713623046875, 'timing/data': 0.00019050156697630882, 'timing/model': 0.4570993999950588, 'learning_rate/action_model': 9.994087978707277e-05, 'learning_rate/action_query_proj': 9.994087978707277e-05, 'learning_rate/base': 2.498521994676819e-05, 'epoch': 0.01}) +[2026-07-26 19:25:04,258][starVLA.training.train_starvla][INFO] - Step 80, Loss: {'train/loss': 0.881049394607544, 'train/grad_norm_pre_clip': 3.3792665004730225, 'timing/data': 0.00019532069563865662, 'timing/model': 0.4575058310292661, 'learning_rate/action_model': 9.993937391708885e-05, 'learning_rate/action_query_proj': 9.993937391708885e-05, 'learning_rate/base': 2.4984843479272213e-05, 'epoch': 0.01}) +[2026-07-26 19:25:09,779][starVLA.training.train_starvla][INFO] - Step 81, Loss: {'train/loss': 0.9319920539855957, 'train/grad_norm_pre_clip': 8.91398811340332, 'timing/data': 0.00018330523744225502, 'timing/model': 0.45823081536218524, 'learning_rate/action_model': 9.993784912139931e-05, 'learning_rate/action_query_proj': 9.993784912139931e-05, 'learning_rate/base': 2.4984462280349827e-05, 'epoch': 0.01}) +[2026-07-26 19:25:15,455][starVLA.training.train_starvla][INFO] - Step 82, Loss: {'train/loss': 1.0053197145462036, 'train/grad_norm_pre_clip': 5.807711124420166, 'timing/data': 0.00018518604338169098, 'timing/model': 0.4733001277782023, 'learning_rate/action_model': 9.993630540060613e-05, 'learning_rate/action_query_proj': 9.993630540060613e-05, 'learning_rate/base': 2.4984076350151533e-05, 'epoch': 0.01}) +[2026-07-26 19:25:21,012][starVLA.training.train_starvla][INFO] - Step 83, Loss: {'train/loss': 1.0848441123962402, 'train/grad_norm_pre_clip': 5.854528427124023, 'timing/data': 0.00018544914200901985, 'timing/model': 0.46968705812469125, 'learning_rate/action_model': 9.993474275531877e-05, 'learning_rate/action_query_proj': 9.993474275531877e-05, 'learning_rate/base': 2.498368568882969e-05, 'epoch': 0.01}) +[2026-07-26 19:25:26,543][starVLA.training.train_starvla][INFO] - Step 84, Loss: {'train/loss': 1.1331002712249756, 'train/grad_norm_pre_clip': 6.162531852722168, 'timing/data': 0.00018648384138941765, 'timing/model': 0.4714176570996642, 'learning_rate/action_model': 9.993316118615408e-05, 'learning_rate/action_query_proj': 9.993316118615408e-05, 'learning_rate/base': 2.498329029653852e-05, 'epoch': 0.01}) +[2026-07-26 19:25:32,076][starVLA.training.train_starvla][INFO] - Step 85, Loss: {'train/loss': 0.7975212931632996, 'train/grad_norm_pre_clip': 3.502781391143799, 'timing/data': 0.00019178399816155434, 'timing/model': 0.4582435367628932, 'learning_rate/action_model': 9.993156069373646e-05, 'learning_rate/action_query_proj': 9.993156069373646e-05, 'learning_rate/base': 2.4982890173434116e-05, 'epoch': 0.01}) +[2026-07-26 19:25:37,611][starVLA.training.train_starvla][INFO] - Step 86, Loss: {'train/loss': 1.1176109313964844, 'train/grad_norm_pre_clip': 6.975309371948242, 'timing/data': 0.0001935027539730072, 'timing/model': 0.4574132589623332, 'learning_rate/action_model': 9.992994127869779e-05, 'learning_rate/action_query_proj': 9.992994127869779e-05, 'learning_rate/base': 2.4982485319674448e-05, 'epoch': 0.01}) +[2026-07-26 19:25:43,189][starVLA.training.train_starvla][INFO] - Step 87, Loss: {'train/loss': 0.9636827707290649, 'train/grad_norm_pre_clip': 4.9625020027160645, 'timing/data': 0.00018397998064756393, 'timing/model': 0.4569673310033977, 'learning_rate/action_model': 9.992830294167737e-05, 'learning_rate/action_query_proj': 9.992830294167737e-05, 'learning_rate/base': 2.4982075735419342e-05, 'epoch': 0.01}) +[2026-07-26 19:25:48,767][starVLA.training.train_starvla][INFO] - Step 88, Loss: {'train/loss': 0.9217895865440369, 'train/grad_norm_pre_clip': 5.1515889167785645, 'timing/data': 0.00018209125846624374, 'timing/model': 0.4569718982093036, 'learning_rate/action_model': 9.992664568332197e-05, 'learning_rate/action_query_proj': 9.992664568332197e-05, 'learning_rate/base': 2.4981661420830493e-05, 'epoch': 0.01}) +[2026-07-26 19:25:54,317][starVLA.training.train_starvla][INFO] - Step 89, Loss: {'train/loss': 1.104719638824463, 'train/grad_norm_pre_clip': 7.276582717895508, 'timing/data': 0.00019831117242574692, 'timing/model': 0.4566161292605102, 'learning_rate/action_model': 9.992496950428587e-05, 'learning_rate/action_query_proj': 9.992496950428587e-05, 'learning_rate/base': 2.4981242376071467e-05, 'epoch': 0.01}) +[2026-07-26 19:25:59,856][starVLA.training.train_starvla][INFO] - Step 90, Loss: {'train/loss': 1.0742995738983154, 'train/grad_norm_pre_clip': 8.195231437683105, 'timing/data': 0.00019433023408055305, 'timing/model': 0.45703836996108294, 'learning_rate/action_model': 9.992327440523081e-05, 'learning_rate/action_query_proj': 9.992327440523081e-05, 'learning_rate/base': 2.4980818601307702e-05, 'epoch': 0.01}) +[2026-07-26 19:26:05,386][starVLA.training.train_starvla][INFO] - Step 91, Loss: {'train/loss': 1.029803991317749, 'train/grad_norm_pre_clip': 8.325518608093262, 'timing/data': 0.0002636467106640339, 'timing/model': 0.4579329080879688, 'learning_rate/action_model': 9.992156038682597e-05, 'learning_rate/action_query_proj': 9.992156038682597e-05, 'learning_rate/base': 2.4980390096706492e-05, 'epoch': 0.01}) +[2026-07-26 19:26:10,938][starVLA.training.train_starvla][INFO] - Step 92, Loss: {'train/loss': 1.0385099649429321, 'train/grad_norm_pre_clip': 7.937870025634766, 'timing/data': 0.0001829969696700573, 'timing/model': 0.4571822597645223, 'learning_rate/action_model': 9.991982744974799e-05, 'learning_rate/action_query_proj': 9.991982744974799e-05, 'learning_rate/base': 2.4979956862436998e-05, 'epoch': 0.01}) +[2026-07-26 19:26:16,491][starVLA.training.train_starvla][INFO] - Step 93, Loss: {'train/loss': 1.0125675201416016, 'train/grad_norm_pre_clip': 9.57886028289795, 'timing/data': 0.00018396414816379547, 'timing/model': 0.46172701520845294, 'learning_rate/action_model': 9.991807559468107e-05, 'learning_rate/action_query_proj': 9.991807559468107e-05, 'learning_rate/base': 2.4979518898670267e-05, 'epoch': 0.01}) +[2026-07-26 19:26:22,024][starVLA.training.train_starvla][INFO] - Step 94, Loss: {'train/loss': 0.8018529415130615, 'train/grad_norm_pre_clip': 3.3761608600616455, 'timing/data': 0.0001860782504081726, 'timing/model': 0.45775276189669967, 'learning_rate/action_model': 9.991630482231677e-05, 'learning_rate/action_query_proj': 9.991630482231677e-05, 'learning_rate/base': 2.4979076205579193e-05, 'epoch': 0.01}) +[2026-07-26 19:26:27,536][starVLA.training.train_starvla][INFO] - Step 95, Loss: {'train/loss': 0.9905428886413574, 'train/grad_norm_pre_clip': 4.795289993286133, 'timing/data': 0.0001816977746784687, 'timing/model': 0.4558033458888531, 'learning_rate/action_model': 9.991451513335418e-05, 'learning_rate/action_query_proj': 9.991451513335418e-05, 'learning_rate/base': 2.4978628783338545e-05, 'epoch': 0.01}) +[2026-07-26 19:26:33,081][starVLA.training.train_starvla][INFO] - Step 96, Loss: {'train/loss': 1.087256669998169, 'train/grad_norm_pre_clip': 8.38346004486084, 'timing/data': 0.00018210429698228836, 'timing/model': 0.45701625011861324, 'learning_rate/action_model': 9.991270652849981e-05, 'learning_rate/action_query_proj': 9.991270652849981e-05, 'learning_rate/base': 2.4978176632124953e-05, 'epoch': 0.01}) +[2026-07-26 19:26:38,631][starVLA.training.train_starvla][INFO] - Step 97, Loss: {'train/loss': 0.8681777119636536, 'train/grad_norm_pre_clip': 6.716272354125977, 'timing/data': 0.0002437741495668888, 'timing/model': 0.4622392184101045, 'learning_rate/action_model': 9.991087900846772e-05, 'learning_rate/action_query_proj': 9.991087900846772e-05, 'learning_rate/base': 2.497771975211693e-05, 'epoch': 0.01}) +[2026-07-26 19:26:44,190][starVLA.training.train_starvla][INFO] - Step 98, Loss: {'train/loss': 0.9303861260414124, 'train/grad_norm_pre_clip': 5.340725421905518, 'timing/data': 0.00021304702386260033, 'timing/model': 0.46357378317043185, 'learning_rate/action_model': 9.990903257397934e-05, 'learning_rate/action_query_proj': 9.990903257397934e-05, 'learning_rate/base': 2.4977258143494836e-05, 'epoch': 0.01}) +[2026-07-26 19:26:49,762][starVLA.training.train_starvla][INFO] - Step 99, Loss: {'train/loss': 0.9781429171562195, 'train/grad_norm_pre_clip': 4.409891128540039, 'timing/data': 0.00025257980450987816, 'timing/model': 0.4623581152409315, 'learning_rate/action_model': 9.990716722576365e-05, 'learning_rate/action_query_proj': 9.990716722576365e-05, 'learning_rate/base': 2.4976791806440912e-05, 'epoch': 0.01}) +[2026-07-26 19:26:55,320][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 100 +[2026-07-26 19:26:55,320][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 100 +[2026-07-26 19:26:55,321][starVLA.training.train_starvla][INFO] - Step 100, Loss: {'train/loss': 0.8894430994987488, 'train/grad_norm_pre_clip': 4.850497245788574, 'timing/data': 0.000242684967815876, 'timing/model': 0.4638710943982005, 'learning_rate/action_model': 9.990528296455703e-05, 'learning_rate/action_query_proj': 9.990528296455703e-05, 'learning_rate/base': 2.4976320741139258e-05, 'epoch': 0.01}) +[2026-07-26 19:27:00,840][starVLA.training.train_starvla][INFO] - Step 101, Loss: {'train/loss': 0.8542892932891846, 'train/grad_norm_pre_clip': 7.208483695983887, 'timing/data': 0.00018661096692085266, 'timing/model': 0.45693327812477946, 'learning_rate/action_model': 9.990337979110337e-05, 'learning_rate/action_query_proj': 9.990337979110337e-05, 'learning_rate/base': 2.4975844947775844e-05, 'epoch': 0.01}) +[2026-07-26 19:27:06,339][starVLA.training.train_starvla][INFO] - Step 102, Loss: {'train/loss': 0.8882508873939514, 'train/grad_norm_pre_clip': 7.856451988220215, 'timing/data': 0.0001790202222764492, 'timing/model': 0.4573683678172529, 'learning_rate/action_model': 9.990145770615403e-05, 'learning_rate/action_query_proj': 9.990145770615403e-05, 'learning_rate/base': 2.4975364426538507e-05, 'epoch': 0.01}) +[2026-07-26 19:27:11,865][starVLA.training.train_starvla][INFO] - Step 103, Loss: {'train/loss': 0.8067426681518555, 'train/grad_norm_pre_clip': 6.540872097015381, 'timing/data': 0.00038486020639538765, 'timing/model': 0.47389921685680747, 'learning_rate/action_model': 9.989951671046779e-05, 'learning_rate/action_query_proj': 9.989951671046779e-05, 'learning_rate/base': 2.4974879177616947e-05, 'epoch': 0.01}) +[2026-07-26 19:27:17,442][starVLA.training.train_starvla][INFO] - Step 104, Loss: {'train/loss': 0.9455825686454773, 'train/grad_norm_pre_clip': 7.314030647277832, 'timing/data': 0.00027022697031497955, 'timing/model': 0.46008546091616154, 'learning_rate/action_model': 9.989755680481093e-05, 'learning_rate/action_query_proj': 9.989755680481093e-05, 'learning_rate/base': 2.497438920120273e-05, 'epoch': 0.01}) +[2026-07-26 19:27:23,008][starVLA.training.train_starvla][INFO] - Step 105, Loss: {'train/loss': 0.9163116216659546, 'train/grad_norm_pre_clip': 8.799156188964844, 'timing/data': 0.00019316794350743294, 'timing/model': 0.4576955549418926, 'learning_rate/action_model': 9.98955779899572e-05, 'learning_rate/action_query_proj': 9.98955779899572e-05, 'learning_rate/base': 2.49738944974893e-05, 'epoch': 0.01}) +[2026-07-26 19:27:28,574][starVLA.training.train_starvla][INFO] - Step 106, Loss: {'train/loss': 0.8247702717781067, 'train/grad_norm_pre_clip': 6.734597682952881, 'timing/data': 0.0001908252015709877, 'timing/model': 0.45759257208555937, 'learning_rate/action_model': 9.98935802666878e-05, 'learning_rate/action_query_proj': 9.98935802666878e-05, 'learning_rate/base': 2.497339506667195e-05, 'epoch': 0.01}) +[2026-07-26 19:27:34,133][starVLA.training.train_starvla][INFO] - Step 107, Loss: {'train/loss': 0.997519314289093, 'train/grad_norm_pre_clip': 10.118736267089844, 'timing/data': 0.00020400295034050941, 'timing/model': 0.4572779219597578, 'learning_rate/action_model': 9.989156363579138e-05, 'learning_rate/action_query_proj': 9.989156363579138e-05, 'learning_rate/base': 2.4972890908947846e-05, 'epoch': 0.01}) +[2026-07-26 19:27:39,694][starVLA.training.train_starvla][INFO] - Step 108, Loss: {'train/loss': 1.1264680624008179, 'train/grad_norm_pre_clip': 13.09217357635498, 'timing/data': 0.0001923949457705021, 'timing/model': 0.4573552431538701, 'learning_rate/action_model': 9.98895280980641e-05, 'learning_rate/action_query_proj': 9.98895280980641e-05, 'learning_rate/base': 2.4972382024516026e-05, 'epoch': 0.01}) +[2026-07-26 19:27:45,247][starVLA.training.train_starvla][INFO] - Step 109, Loss: {'train/loss': 0.8689830899238586, 'train/grad_norm_pre_clip': 10.561638832092285, 'timing/data': 0.00019177887588739395, 'timing/model': 0.46157380985096097, 'learning_rate/action_model': 9.988747365430957e-05, 'learning_rate/action_query_proj': 9.988747365430957e-05, 'learning_rate/base': 2.4971868413577392e-05, 'epoch': 0.01}) +[2026-07-26 19:27:50,849][starVLA.training.train_starvla][INFO] - Step 110, Loss: {'train/loss': 0.9299497604370117, 'train/grad_norm_pre_clip': 5.3675079345703125, 'timing/data': 0.00019256724044680595, 'timing/model': 0.4597189179621637, 'learning_rate/action_model': 9.98854003053388e-05, 'learning_rate/action_query_proj': 9.98854003053388e-05, 'learning_rate/base': 2.49713500763347e-05, 'epoch': 0.01}) +[2026-07-26 19:27:56,409][starVLA.training.train_starvla][INFO] - Step 111, Loss: {'train/loss': 0.9015645980834961, 'train/grad_norm_pre_clip': 6.8904829025268555, 'timing/data': 0.00020520808175206184, 'timing/model': 0.4601867259480059, 'learning_rate/action_model': 9.988330805197039e-05, 'learning_rate/action_query_proj': 9.988330805197039e-05, 'learning_rate/base': 2.4970827012992596e-05, 'epoch': 0.01}) +[2026-07-26 19:28:01,980][starVLA.training.train_starvla][INFO] - Step 112, Loss: {'train/loss': 1.1596027612686157, 'train/grad_norm_pre_clip': 8.730704307556152, 'timing/data': 0.00018761400133371353, 'timing/model': 0.46337170898914337, 'learning_rate/action_model': 9.988119689503026e-05, 'learning_rate/action_query_proj': 9.988119689503026e-05, 'learning_rate/base': 2.4970299223757564e-05, 'epoch': 0.01}) +[2026-07-26 19:28:07,549][starVLA.training.train_starvla][INFO] - Step 113, Loss: {'train/loss': 1.1291958093643188, 'train/grad_norm_pre_clip': 8.417425155639648, 'timing/data': 0.0002078050747513771, 'timing/model': 0.4617938199080527, 'learning_rate/action_model': 9.987906683535189e-05, 'learning_rate/action_query_proj': 9.987906683535189e-05, 'learning_rate/base': 2.4969766708837973e-05, 'epoch': 0.01}) +[2026-07-26 19:28:13,107][starVLA.training.train_starvla][INFO] - Step 114, Loss: {'train/loss': 0.8830200433731079, 'train/grad_norm_pre_clip': 7.6813435554504395, 'timing/data': 0.0002702767960727215, 'timing/model': 0.4644037913531065, 'learning_rate/action_model': 9.987691787377619e-05, 'learning_rate/action_query_proj': 9.987691787377619e-05, 'learning_rate/base': 2.4969229468444047e-05, 'epoch': 0.01}) +[2026-07-26 19:28:18,641][starVLA.training.train_starvla][INFO] - Step 115, Loss: {'train/loss': 0.809058666229248, 'train/grad_norm_pre_clip': 7.249608039855957, 'timing/data': 0.00019629299640655518, 'timing/model': 0.46397532103583217, 'learning_rate/action_model': 9.987475001115155e-05, 'learning_rate/action_query_proj': 9.987475001115155e-05, 'learning_rate/base': 2.4968687502787886e-05, 'epoch': 0.01}) +[2026-07-26 19:28:24,190][starVLA.training.train_starvla][INFO] - Step 116, Loss: {'train/loss': 0.9082536697387695, 'train/grad_norm_pre_clip': 3.1125128269195557, 'timing/data': 0.00020092492923140526, 'timing/model': 0.4614827549085021, 'learning_rate/action_model': 9.987256324833378e-05, 'learning_rate/action_query_proj': 9.987256324833378e-05, 'learning_rate/base': 2.4968140812083445e-05, 'epoch': 0.01}) +[2026-07-26 19:28:29,720][starVLA.training.train_starvla][INFO] - Step 117, Loss: {'train/loss': 0.9329931139945984, 'train/grad_norm_pre_clip': 5.461398124694824, 'timing/data': 0.00018806569278240204, 'timing/model': 0.45988113386556506, 'learning_rate/action_model': 9.98703575861862e-05, 'learning_rate/action_query_proj': 9.98703575861862e-05, 'learning_rate/base': 2.496758939654655e-05, 'epoch': 0.01}) +[2026-07-26 19:28:35,265][starVLA.training.train_starvla][INFO] - Step 118, Loss: {'train/loss': 0.8761709332466125, 'train/grad_norm_pre_clip': 9.87946891784668, 'timing/data': 0.00021358300000429153, 'timing/model': 0.46124200569465756, 'learning_rate/action_model': 9.986813302557955e-05, 'learning_rate/action_query_proj': 9.986813302557955e-05, 'learning_rate/base': 2.4967033256394888e-05, 'epoch': 0.01}) +[2026-07-26 19:28:40,808][starVLA.training.train_starvla][INFO] - Step 119, Loss: {'train/loss': 0.8523252606391907, 'train/grad_norm_pre_clip': 3.2613306045532227, 'timing/data': 0.00019142497330904007, 'timing/model': 0.45826926082372665, 'learning_rate/action_model': 9.98658895673921e-05, 'learning_rate/action_query_proj': 9.98658895673921e-05, 'learning_rate/base': 2.4966472391848025e-05, 'epoch': 0.01}) +[2026-07-26 19:28:46,307][starVLA.training.train_starvla][INFO] - Step 120, Loss: {'train/loss': 0.9600783586502075, 'train/grad_norm_pre_clip': 6.795823097229004, 'timing/data': 0.0002009221352636814, 'timing/model': 0.45855069113895297, 'learning_rate/action_model': 9.986362721250947e-05, 'learning_rate/action_query_proj': 9.986362721250947e-05, 'learning_rate/base': 2.4965906803127368e-05, 'epoch': 0.01}) +[2026-07-26 19:28:51,826][starVLA.training.train_starvla][INFO] - Step 121, Loss: {'train/loss': 0.8621439337730408, 'train/grad_norm_pre_clip': 5.752713203430176, 'timing/data': 0.00018272735178470612, 'timing/model': 0.4602049388922751, 'learning_rate/action_model': 9.986134596182483e-05, 'learning_rate/action_query_proj': 9.986134596182483e-05, 'learning_rate/base': 2.4965336490456208e-05, 'epoch': 0.01}) +[2026-07-26 19:28:57,350][starVLA.training.train_starvla][INFO] - Step 122, Loss: {'train/loss': 0.7947087287902832, 'train/grad_norm_pre_clip': 3.933828353881836, 'timing/data': 0.00032949773594737053, 'timing/model': 0.4611925696954131, 'learning_rate/action_model': 9.98590458162388e-05, 'learning_rate/action_query_proj': 9.98590458162388e-05, 'learning_rate/base': 2.49647614540597e-05, 'epoch': 0.01}) +[2026-07-26 19:29:02,879][starVLA.training.train_starvla][INFO] - Step 123, Loss: {'train/loss': 0.9149573445320129, 'train/grad_norm_pre_clip': 9.002182006835938, 'timing/data': 0.00019906507804989815, 'timing/model': 0.46026515075936913, 'learning_rate/action_model': 9.985672677665942e-05, 'learning_rate/action_query_proj': 9.985672677665942e-05, 'learning_rate/base': 2.4964181694164854e-05, 'epoch': 0.01}) +[2026-07-26 19:29:08,397][starVLA.training.train_starvla][INFO] - Step 124, Loss: {'train/loss': 0.825995147228241, 'train/grad_norm_pre_clip': 6.704372882843018, 'timing/data': 0.00019062403589487076, 'timing/model': 0.45995674980804324, 'learning_rate/action_model': 9.985438884400221e-05, 'learning_rate/action_query_proj': 9.985438884400221e-05, 'learning_rate/base': 2.4963597211000553e-05, 'epoch': 0.02}) +[2026-07-26 19:29:13,932][starVLA.training.train_starvla][INFO] - Step 125, Loss: {'train/loss': 0.9861830472946167, 'train/grad_norm_pre_clip': 5.951389789581299, 'timing/data': 0.0002933717332780361, 'timing/model': 0.4648878015577793, 'learning_rate/action_model': 9.985203201919016e-05, 'learning_rate/action_query_proj': 9.985203201919016e-05, 'learning_rate/base': 2.496300800479754e-05, 'epoch': 0.02}) +[2026-07-26 19:29:19,471][starVLA.training.train_starvla][INFO] - Step 126, Loss: {'train/loss': 0.987582802772522, 'train/grad_norm_pre_clip': 5.186672687530518, 'timing/data': 0.00030242325738072395, 'timing/model': 0.4608590928837657, 'learning_rate/action_model': 9.984965630315367e-05, 'learning_rate/action_query_proj': 9.984965630315367e-05, 'learning_rate/base': 2.4962414075788417e-05, 'epoch': 0.02}) +[2026-07-26 19:29:25,013][starVLA.training.train_starvla][INFO] - Step 127, Loss: {'train/loss': 0.8970778584480286, 'train/grad_norm_pre_clip': 3.1407601833343506, 'timing/data': 0.0002957908436655998, 'timing/model': 0.463735556229949, 'learning_rate/action_model': 9.984726169683069e-05, 'learning_rate/action_query_proj': 9.984726169683069e-05, 'learning_rate/base': 2.4961815424207673e-05, 'epoch': 0.02}) +[2026-07-26 19:29:30,554][starVLA.training.train_starvla][INFO] - Step 128, Loss: {'train/loss': 1.042892336845398, 'train/grad_norm_pre_clip': 6.967740058898926, 'timing/data': 0.00027473922818899155, 'timing/model': 0.4648341862484813, 'learning_rate/action_model': 9.984484820116655e-05, 'learning_rate/action_query_proj': 9.984484820116655e-05, 'learning_rate/base': 2.4961212050291636e-05, 'epoch': 0.02}) +[2026-07-26 19:29:36,097][starVLA.training.train_starvla][INFO] - Step 129, Loss: {'train/loss': 0.9321819543838501, 'train/grad_norm_pre_clip': 7.118154048919678, 'timing/data': 0.0002963361330330372, 'timing/model': 0.4634138788096607, 'learning_rate/action_model': 9.984241581711403e-05, 'learning_rate/action_query_proj': 9.984241581711403e-05, 'learning_rate/base': 2.4960603954278507e-05, 'epoch': 0.02}) +[2026-07-26 19:29:41,637][starVLA.training.train_starvla][INFO] - Step 130, Loss: {'train/loss': 0.9668105840682983, 'train/grad_norm_pre_clip': 5.96747350692749, 'timing/data': 0.00019061705097556114, 'timing/model': 0.46071548806503415, 'learning_rate/action_model': 9.983996454563343e-05, 'learning_rate/action_query_proj': 9.983996454563343e-05, 'learning_rate/base': 2.4959991136408358e-05, 'epoch': 0.02}) +[2026-07-26 19:29:47,132][starVLA.training.train_starvla][INFO] - Step 131, Loss: {'train/loss': 1.0002849102020264, 'train/grad_norm_pre_clip': 9.690631866455078, 'timing/data': 0.00019231298938393593, 'timing/model': 0.4586535352282226, 'learning_rate/action_model': 9.983749438769247e-05, 'learning_rate/action_query_proj': 9.983749438769247e-05, 'learning_rate/base': 2.4959373596923118e-05, 'epoch': 0.02}) +[2026-07-26 19:29:52,642][starVLA.training.train_starvla][INFO] - Step 132, Loss: {'train/loss': 0.8402441740036011, 'train/grad_norm_pre_clip': 5.519392013549805, 'timing/data': 0.00019133230671286583, 'timing/model': 0.4610349303111434, 'learning_rate/action_model': 9.983500534426635e-05, 'learning_rate/action_query_proj': 9.983500534426635e-05, 'learning_rate/base': 2.4958751336066588e-05, 'epoch': 0.02}) +[2026-07-26 19:29:58,421][starVLA.training.train_starvla][INFO] - Step 133, Loss: {'train/loss': 0.8987578749656677, 'train/grad_norm_pre_clip': 4.215169429779053, 'timing/data': 0.00033223116770386696, 'timing/model': 0.46166433626785874, 'learning_rate/action_model': 9.983249741633765e-05, 'learning_rate/action_query_proj': 9.983249741633765e-05, 'learning_rate/base': 2.4958124354084414e-05, 'epoch': 0.02}) +[2026-07-26 19:30:04,191][starVLA.training.train_starvla][INFO] - Step 134, Loss: {'train/loss': 0.8235031366348267, 'train/grad_norm_pre_clip': 6.035726547241211, 'timing/data': 0.0002039652317762375, 'timing/model': 0.7163332677446306, 'learning_rate/action_model': 9.98299706048965e-05, 'learning_rate/action_query_proj': 9.98299706048965e-05, 'learning_rate/base': 2.4957492651224125e-05, 'epoch': 0.02}) +[2026-07-26 19:30:09,697][starVLA.training.train_starvla][INFO] - Step 135, Loss: {'train/loss': 0.875332236289978, 'train/grad_norm_pre_clip': 7.896390914916992, 'timing/data': 0.00019283266738057137, 'timing/model': 0.4602303830906749, 'learning_rate/action_model': 9.982742491094044e-05, 'learning_rate/action_query_proj': 9.982742491094044e-05, 'learning_rate/base': 2.495685622773511e-05, 'epoch': 0.02}) +[2026-07-26 19:30:15,201][starVLA.training.train_starvla][INFO] - Step 136, Loss: {'train/loss': 0.7614229917526245, 'train/grad_norm_pre_clip': 3.8703784942626953, 'timing/data': 0.00018801121041178703, 'timing/model': 0.4576803990639746, 'learning_rate/action_model': 9.982486033547446e-05, 'learning_rate/action_query_proj': 9.982486033547446e-05, 'learning_rate/base': 2.4956215083868616e-05, 'epoch': 0.02}) +[2026-07-26 19:30:20,707][starVLA.training.train_starvla][INFO] - Step 137, Loss: {'train/loss': 1.022276520729065, 'train/grad_norm_pre_clip': 6.995839595794678, 'timing/data': 0.0001886771060526371, 'timing/model': 0.45981029234826565, 'learning_rate/action_model': 9.982227687951103e-05, 'learning_rate/action_query_proj': 9.982227687951103e-05, 'learning_rate/base': 2.4955569219877756e-05, 'epoch': 0.02}) +[2026-07-26 19:30:26,208][starVLA.training.train_starvla][INFO] - Step 138, Loss: {'train/loss': 0.995181143283844, 'train/grad_norm_pre_clip': 7.939728736877441, 'timing/data': 0.0001881723292171955, 'timing/model': 0.46084407810121775, 'learning_rate/action_model': 9.981967454407004e-05, 'learning_rate/action_query_proj': 9.981967454407004e-05, 'learning_rate/base': 2.495491863601751e-05, 'epoch': 0.02}) +[2026-07-26 19:30:31,877][starVLA.training.train_starvla][INFO] - Step 139, Loss: {'train/loss': 0.9859795570373535, 'train/grad_norm_pre_clip': 9.683131217956543, 'timing/data': 0.0002119028940796852, 'timing/model': 0.6305541358888149, 'learning_rate/action_model': 9.981705333017884e-05, 'learning_rate/action_query_proj': 9.981705333017884e-05, 'learning_rate/base': 2.495426333254471e-05, 'epoch': 0.02}) +[2026-07-26 19:30:37,641][starVLA.training.train_starvla][INFO] - Step 140, Loss: {'train/loss': 0.889386773109436, 'train/grad_norm_pre_clip': 10.479485511779785, 'timing/data': 0.00020249607041478157, 'timing/model': 0.46142777102068067, 'learning_rate/action_model': 9.981441323887228e-05, 'learning_rate/action_query_proj': 9.981441323887228e-05, 'learning_rate/base': 2.495360330971807e-05, 'epoch': 0.02}) +[2026-07-26 19:30:43,143][starVLA.training.train_starvla][INFO] - Step 141, Loss: {'train/loss': 0.9401625394821167, 'train/grad_norm_pre_clip': 7.201816558837891, 'timing/data': 0.0001951390877366066, 'timing/model': 0.45928910095244646, 'learning_rate/action_model': 9.981175427119261e-05, 'learning_rate/action_query_proj': 9.981175427119261e-05, 'learning_rate/base': 2.4952938567798152e-05, 'epoch': 0.02}) +[2026-07-26 19:30:48,943][starVLA.training.train_starvla][INFO] - Step 142, Loss: {'train/loss': 0.8984090685844421, 'train/grad_norm_pre_clip': 4.82546854019165, 'timing/data': 0.0001870887354016304, 'timing/model': 0.4600961161777377, 'learning_rate/action_model': 9.980907642818953e-05, 'learning_rate/action_query_proj': 9.980907642818953e-05, 'learning_rate/base': 2.4952269107047384e-05, 'epoch': 0.02}) +[2026-07-26 19:30:54,432][starVLA.training.train_starvla][INFO] - Step 143, Loss: {'train/loss': 0.8519095182418823, 'train/grad_norm_pre_clip': 6.877822399139404, 'timing/data': 0.00018731504678726196, 'timing/model': 0.46058497624471784, 'learning_rate/action_model': 9.980637971092024e-05, 'learning_rate/action_query_proj': 9.980637971092024e-05, 'learning_rate/base': 2.495159492773006e-05, 'epoch': 0.02}) +[2026-07-26 19:30:59,923][starVLA.training.train_starvla][INFO] - Step 144, Loss: {'train/loss': 0.8885622024536133, 'train/grad_norm_pre_clip': 4.860215663909912, 'timing/data': 0.00018344074487686157, 'timing/model': 0.4612208972685039, 'learning_rate/action_model': 9.980366412044934e-05, 'learning_rate/action_query_proj': 9.980366412044934e-05, 'learning_rate/base': 2.4950916030112335e-05, 'epoch': 0.02}) +[2026-07-26 19:31:05,433][starVLA.training.train_starvla][INFO] - Step 145, Loss: {'train/loss': 0.9568846225738525, 'train/grad_norm_pre_clip': 7.776098728179932, 'timing/data': 0.00018870597705245018, 'timing/model': 0.46090732607990503, 'learning_rate/action_model': 9.980092965784891e-05, 'learning_rate/action_query_proj': 9.980092965784891e-05, 'learning_rate/base': 2.4950232414462228e-05, 'epoch': 0.02}) +[2026-07-26 19:31:11,019][starVLA.training.train_starvla][INFO] - Step 146, Loss: {'train/loss': 0.8182224035263062, 'train/grad_norm_pre_clip': 4.377276420593262, 'timing/data': 0.00019676703959703445, 'timing/model': 0.4742187070660293, 'learning_rate/action_model': 9.979817632419848e-05, 'learning_rate/action_query_proj': 9.979817632419848e-05, 'learning_rate/base': 2.494954408104962e-05, 'epoch': 0.02}) +[2026-07-26 19:31:16,559][starVLA.training.train_starvla][INFO] - Step 147, Loss: {'train/loss': 0.8887299299240112, 'train/grad_norm_pre_clip': 7.506653785705566, 'timing/data': 0.00020180922001600266, 'timing/model': 0.46121126785874367, 'learning_rate/action_model': 9.979540412058501e-05, 'learning_rate/action_query_proj': 9.979540412058501e-05, 'learning_rate/base': 2.4948851030146252e-05, 'epoch': 0.02}) +[2026-07-26 19:31:22,070][starVLA.training.train_starvla][INFO] - Step 148, Loss: {'train/loss': 0.8784528970718384, 'train/grad_norm_pre_clip': 4.730071067810059, 'timing/data': 0.00019035488367080688, 'timing/model': 0.4628889583982527, 'learning_rate/action_model': 9.979261304810292e-05, 'learning_rate/action_query_proj': 9.979261304810292e-05, 'learning_rate/base': 2.494815326202573e-05, 'epoch': 0.02}) +[2026-07-26 19:31:27,646][starVLA.training.train_starvla][INFO] - Step 149, Loss: {'train/loss': 0.87544184923172, 'train/grad_norm_pre_clip': 6.300275802612305, 'timing/data': 0.00018838513642549515, 'timing/model': 0.46392893232405186, 'learning_rate/action_model': 9.978980310785408e-05, 'learning_rate/action_query_proj': 9.978980310785408e-05, 'learning_rate/base': 2.494745077696352e-05, 'epoch': 0.02}) +[2026-07-26 19:31:33,211][starVLA.training.train_starvla][INFO] - Step 150, Loss: {'train/loss': 0.8444546461105347, 'train/grad_norm_pre_clip': 4.692315101623535, 'timing/data': 0.00018997164443135262, 'timing/model': 0.45820132177323103, 'learning_rate/action_model': 9.978697430094785e-05, 'learning_rate/action_query_proj': 9.978697430094785e-05, 'learning_rate/base': 2.494674357523696e-05, 'epoch': 0.02}) +[2026-07-26 19:31:38,874][starVLA.training.train_starvla][INFO] - Step 151, Loss: {'train/loss': 0.8435075283050537, 'train/grad_norm_pre_clip': 4.4367756843566895, 'timing/data': 0.00019195722416043282, 'timing/model': 0.4620489948429167, 'learning_rate/action_model': 9.978412662850094e-05, 'learning_rate/action_query_proj': 9.978412662850094e-05, 'learning_rate/base': 2.4946031657125236e-05, 'epoch': 0.02}) +[2026-07-26 19:31:44,496][starVLA.training.train_starvla][INFO] - Step 152, Loss: {'train/loss': 0.919983983039856, 'train/grad_norm_pre_clip': 5.25494384765625, 'timing/data': 0.0001859930343925953, 'timing/model': 0.4622472608461976, 'learning_rate/action_model': 9.97812600916376e-05, 'learning_rate/action_query_proj': 9.97812600916376e-05, 'learning_rate/base': 2.49453150229094e-05, 'epoch': 0.02}) +[2026-07-26 19:31:50,059][starVLA.training.train_starvla][INFO] - Step 153, Loss: {'train/loss': 0.94405198097229, 'train/grad_norm_pre_clip': 7.026813507080078, 'timing/data': 0.00018929177895188332, 'timing/model': 0.46384687116369605, 'learning_rate/action_model': 9.977837469148947e-05, 'learning_rate/action_query_proj': 9.977837469148947e-05, 'learning_rate/base': 2.4944593672872368e-05, 'epoch': 0.02}) +[2026-07-26 19:31:55,612][starVLA.training.train_starvla][INFO] - Step 154, Loss: {'train/loss': 0.7884306311607361, 'train/grad_norm_pre_clip': 6.886129856109619, 'timing/data': 0.0001881662756204605, 'timing/model': 0.46451261267066, 'learning_rate/action_model': 9.977547042919569e-05, 'learning_rate/action_query_proj': 9.977547042919569e-05, 'learning_rate/base': 2.4943867607298923e-05, 'epoch': 0.02}) +[2026-07-26 19:32:01,320][starVLA.training.train_starvla][INFO] - Step 155, Loss: {'train/loss': 0.8827376365661621, 'train/grad_norm_pre_clip': 5.8697004318237305, 'timing/data': 0.00020215101540088654, 'timing/model': 0.4629037962295115, 'learning_rate/action_model': 9.977254730590281e-05, 'learning_rate/action_query_proj': 9.977254730590281e-05, 'learning_rate/base': 2.4943136826475702e-05, 'epoch': 0.02}) +[2026-07-26 19:32:07,185][starVLA.training.train_starvla][INFO] - Step 156, Loss: {'train/loss': 0.915813684463501, 'train/grad_norm_pre_clip': 6.863455295562744, 'timing/data': 0.00019204290583729744, 'timing/model': 0.4644934870302677, 'learning_rate/action_model': 9.97696053227648e-05, 'learning_rate/action_query_proj': 9.97696053227648e-05, 'learning_rate/base': 2.49424013306912e-05, 'epoch': 0.02}) +[2026-07-26 19:32:13,083][starVLA.training.train_starvla][INFO] - Step 157, Loss: {'train/loss': 0.7416989803314209, 'train/grad_norm_pre_clip': 8.256098747253418, 'timing/data': 0.00019094906747341156, 'timing/model': 0.46430522995069623, 'learning_rate/action_model': 9.976664448094316e-05, 'learning_rate/action_query_proj': 9.976664448094316e-05, 'learning_rate/base': 2.494166112023579e-05, 'epoch': 0.02}) +[2026-07-26 19:32:18,674][starVLA.training.train_starvla][INFO] - Step 158, Loss: {'train/loss': 0.7501243948936462, 'train/grad_norm_pre_clip': 4.173018932342529, 'timing/data': 0.00018601398915052414, 'timing/model': 0.4638305581174791, 'learning_rate/action_model': 9.976366478160673e-05, 'learning_rate/action_query_proj': 9.976366478160673e-05, 'learning_rate/base': 2.4940916195401682e-05, 'epoch': 0.02}) +[2026-07-26 19:32:24,289][starVLA.training.train_starvla][INFO] - Step 159, Loss: {'train/loss': 0.7973119020462036, 'train/grad_norm_pre_clip': 5.79846715927124, 'timing/data': 0.0001786467619240284, 'timing/model': 0.46380589297041297, 'learning_rate/action_model': 9.97606662259319e-05, 'learning_rate/action_query_proj': 9.97606662259319e-05, 'learning_rate/base': 2.4940166556482976e-05, 'epoch': 0.02}) +[2026-07-26 19:32:29,894][starVLA.training.train_starvla][INFO] - Step 160, Loss: {'train/loss': 0.9953498244285583, 'train/grad_norm_pre_clip': 8.772137641906738, 'timing/data': 0.00019187387079000473, 'timing/model': 0.46338300593197346, 'learning_rate/action_model': 9.975764881510242e-05, 'learning_rate/action_query_proj': 9.975764881510242e-05, 'learning_rate/base': 2.4939412203775605e-05, 'epoch': 0.02}) +[2026-07-26 19:32:35,497][starVLA.training.train_starvla][INFO] - Step 161, Loss: {'train/loss': 0.9433512687683105, 'train/grad_norm_pre_clip': 12.067906379699707, 'timing/data': 0.00019691605120897293, 'timing/model': 0.46356559731066227, 'learning_rate/action_model': 9.975461255030951e-05, 'learning_rate/action_query_proj': 9.975461255030951e-05, 'learning_rate/base': 2.493865313757738e-05, 'epoch': 0.02}) +[2026-07-26 19:32:41,103][starVLA.training.train_starvla][INFO] - Step 162, Loss: {'train/loss': 0.947211503982544, 'train/grad_norm_pre_clip': 8.645061492919922, 'timing/data': 0.000188490841537714, 'timing/model': 0.4651405210606754, 'learning_rate/action_model': 9.975155743275187e-05, 'learning_rate/action_query_proj': 9.975155743275187e-05, 'learning_rate/base': 2.4937889358187967e-05, 'epoch': 0.02}) +[2026-07-26 19:32:46,708][starVLA.training.train_starvla][INFO] - Step 163, Loss: {'train/loss': 0.8652279376983643, 'train/grad_norm_pre_clip': 6.555346488952637, 'timing/data': 0.00017949799075722694, 'timing/model': 0.46333433920517564, 'learning_rate/action_model': 9.974848346363557e-05, 'learning_rate/action_query_proj': 9.974848346363557e-05, 'learning_rate/base': 2.4937120865908894e-05, 'epoch': 0.02}) +[2026-07-26 19:32:52,294][starVLA.training.train_starvla][INFO] - Step 164, Loss: {'train/loss': 0.8918360471725464, 'train/grad_norm_pre_clip': 8.040812492370605, 'timing/data': 0.00018681585788726807, 'timing/model': 0.46148451091721654, 'learning_rate/action_model': 9.974539064417421e-05, 'learning_rate/action_query_proj': 9.974539064417421e-05, 'learning_rate/base': 2.4936347661043552e-05, 'epoch': 0.02}) +[2026-07-26 19:32:57,885][starVLA.training.train_starvla][INFO] - Step 165, Loss: {'train/loss': 0.8591217398643494, 'train/grad_norm_pre_clip': 5.270572185516357, 'timing/data': 0.00019782176241278648, 'timing/model': 0.4632235518656671, 'learning_rate/action_model': 9.974227897558876e-05, 'learning_rate/action_query_proj': 9.974227897558876e-05, 'learning_rate/base': 2.493556974389719e-05, 'epoch': 0.02}) +[2026-07-26 19:33:03,475][starVLA.training.train_starvla][INFO] - Step 166, Loss: {'train/loss': 0.8025743365287781, 'train/grad_norm_pre_clip': 6.70618200302124, 'timing/data': 0.0002009207382798195, 'timing/model': 0.463485362008214, 'learning_rate/action_model': 9.973914845910765e-05, 'learning_rate/action_query_proj': 9.973914845910765e-05, 'learning_rate/base': 2.4934787114776913e-05, 'epoch': 0.02}) +[2026-07-26 19:33:09,080][starVLA.training.train_starvla][INFO] - Step 167, Loss: {'train/loss': 1.0778158903121948, 'train/grad_norm_pre_clip': 7.157775402069092, 'timing/data': 0.0001856386661529541, 'timing/model': 0.46198623394593596, 'learning_rate/action_model': 9.973599909596679e-05, 'learning_rate/action_query_proj': 9.973599909596679e-05, 'learning_rate/base': 2.4933999773991696e-05, 'epoch': 0.02}) +[2026-07-26 19:33:14,699][starVLA.training.train_starvla][INFO] - Step 168, Loss: {'train/loss': 0.919972836971283, 'train/grad_norm_pre_clip': 10.227554321289062, 'timing/data': 0.00019375281408429146, 'timing/model': 0.4633650192990899, 'learning_rate/action_model': 9.973283088740948e-05, 'learning_rate/action_query_proj': 9.973283088740948e-05, 'learning_rate/base': 2.493320772185237e-05, 'epoch': 0.02}) +[2026-07-26 19:33:20,300][starVLA.training.train_starvla][INFO] - Step 169, Loss: {'train/loss': 0.7813398241996765, 'train/grad_norm_pre_clip': 6.327710151672363, 'timing/data': 0.00019146502017974854, 'timing/model': 0.4651619610376656, 'learning_rate/action_model': 9.972964383468646e-05, 'learning_rate/action_query_proj': 9.972964383468646e-05, 'learning_rate/base': 2.4932410958671615e-05, 'epoch': 0.02}) +[2026-07-26 19:33:25,891][starVLA.training.train_starvla][INFO] - Step 170, Loss: {'train/loss': 0.8457313776016235, 'train/grad_norm_pre_clip': 6.215808391571045, 'timing/data': 0.00018830224871635437, 'timing/model': 0.4636232228949666, 'learning_rate/action_model': 9.972643793905595e-05, 'learning_rate/action_query_proj': 9.972643793905595e-05, 'learning_rate/base': 2.4931609484763988e-05, 'epoch': 0.02}) +[2026-07-26 19:33:31,490][starVLA.training.train_starvla][INFO] - Step 171, Loss: {'train/loss': 0.7747104167938232, 'train/grad_norm_pre_clip': 5.5714192390441895, 'timing/data': 0.00019261566922068596, 'timing/model': 0.46471654903143644, 'learning_rate/action_model': 9.972321320178359e-05, 'learning_rate/action_query_proj': 9.972321320178359e-05, 'learning_rate/base': 2.4930803300445897e-05, 'epoch': 0.02}) +[2026-07-26 19:33:37,083][starVLA.training.train_starvla][INFO] - Step 172, Loss: {'train/loss': 0.9027774930000305, 'train/grad_norm_pre_clip': 4.1011505126953125, 'timing/data': 0.00018880702555179596, 'timing/model': 0.4625491015613079, 'learning_rate/action_model': 9.971996962414244e-05, 'learning_rate/action_query_proj': 9.971996962414244e-05, 'learning_rate/base': 2.492999240603561e-05, 'epoch': 0.02}) +[2026-07-26 19:33:42,732][starVLA.training.train_starvla][INFO] - Step 173, Loss: {'train/loss': 0.8978660702705383, 'train/grad_norm_pre_clip': 4.833467960357666, 'timing/data': 0.0001836833544075489, 'timing/model': 0.5025780699215829, 'learning_rate/action_model': 9.971670720741304e-05, 'learning_rate/action_query_proj': 9.971670720741304e-05, 'learning_rate/base': 2.492917680185326e-05, 'epoch': 0.02}) +[2026-07-26 19:33:48,310][starVLA.training.train_starvla][INFO] - Step 174, Loss: {'train/loss': 0.8387618660926819, 'train/grad_norm_pre_clip': 7.629541397094727, 'timing/data': 0.00018880236893892288, 'timing/model': 0.4572222288697958, 'learning_rate/action_model': 9.97134259528833e-05, 'learning_rate/action_query_proj': 9.97134259528833e-05, 'learning_rate/base': 2.4928356488220825e-05, 'epoch': 0.02}) +[2026-07-26 19:33:53,968][starVLA.training.train_starvla][INFO] - Step 175, Loss: {'train/loss': 0.774951159954071, 'train/grad_norm_pre_clip': 5.074046611785889, 'timing/data': 0.0001897118054330349, 'timing/model': 0.4574606572277844, 'learning_rate/action_model': 9.971012586184863e-05, 'learning_rate/action_query_proj': 9.971012586184863e-05, 'learning_rate/base': 2.4927531465462158e-05, 'epoch': 0.02}) +[2026-07-26 19:33:59,562][starVLA.training.train_starvla][INFO] - Step 176, Loss: {'train/loss': 0.7321220636367798, 'train/grad_norm_pre_clip': 3.929121494293213, 'timing/data': 0.00018494809046387672, 'timing/model': 0.45947093376889825, 'learning_rate/action_model': 9.970680693561186e-05, 'learning_rate/action_query_proj': 9.970680693561186e-05, 'learning_rate/base': 2.4926701733902965e-05, 'epoch': 0.02}) +[2026-07-26 19:34:05,148][starVLA.training.train_starvla][INFO] - Step 177, Loss: {'train/loss': 0.8686874508857727, 'train/grad_norm_pre_clip': 3.959390878677368, 'timing/data': 0.0001978762447834015, 'timing/model': 0.4578238548710942, 'learning_rate/action_model': 9.970346917548323e-05, 'learning_rate/action_query_proj': 9.970346917548323e-05, 'learning_rate/base': 2.4925867293870808e-05, 'epoch': 0.02}) +[2026-07-26 19:34:10,725][starVLA.training.train_starvla][INFO] - Step 178, Loss: {'train/loss': 0.8912090063095093, 'train/grad_norm_pre_clip': 8.406172752380371, 'timing/data': 0.00020256917923688889, 'timing/model': 0.4627124909311533, 'learning_rate/action_model': 9.970011258278047e-05, 'learning_rate/action_query_proj': 9.970011258278047e-05, 'learning_rate/base': 2.4925028145695118e-05, 'epoch': 0.02}) +[2026-07-26 19:34:16,333][starVLA.training.train_starvla][INFO] - Step 179, Loss: {'train/loss': 0.8818722367286682, 'train/grad_norm_pre_clip': 8.348535537719727, 'timing/data': 0.00020886585116386414, 'timing/model': 0.45749175269156694, 'learning_rate/action_model': 9.969673715882866e-05, 'learning_rate/action_query_proj': 9.969673715882866e-05, 'learning_rate/base': 2.4924184289707166e-05, 'epoch': 0.02}) +[2026-07-26 19:34:21,930][starVLA.training.train_starvla][INFO] - Step 180, Loss: {'train/loss': 0.6627435684204102, 'train/grad_norm_pre_clip': 6.317254066467285, 'timing/data': 0.00019992003217339516, 'timing/model': 0.4673207332380116, 'learning_rate/action_model': 9.96933429049604e-05, 'learning_rate/action_query_proj': 9.96933429049604e-05, 'learning_rate/base': 2.49233357262401e-05, 'epoch': 0.02}) +[2026-07-26 19:34:27,509][starVLA.training.train_starvla][INFO] - Step 181, Loss: {'train/loss': 1.0600730180740356, 'train/grad_norm_pre_clip': 6.975693702697754, 'timing/data': 0.00018933694809675217, 'timing/model': 0.4570849691517651, 'learning_rate/action_model': 9.968992982251568e-05, 'learning_rate/action_query_proj': 9.968992982251568e-05, 'learning_rate/base': 2.492248245562892e-05, 'epoch': 0.02}) +[2026-07-26 19:34:33,101][starVLA.training.train_starvla][INFO] - Step 182, Loss: {'train/loss': 0.857801079750061, 'train/grad_norm_pre_clip': 8.876409530639648, 'timing/data': 0.00018949108198285103, 'timing/model': 0.45712512359023094, 'learning_rate/action_model': 9.968649791284193e-05, 'learning_rate/action_query_proj': 9.968649791284193e-05, 'learning_rate/base': 2.4921624478210483e-05, 'epoch': 0.02}) +[2026-07-26 19:34:38,718][starVLA.training.train_starvla][INFO] - Step 183, Loss: {'train/loss': 0.8715687990188599, 'train/grad_norm_pre_clip': 7.039627552032471, 'timing/data': 0.0001923772506415844, 'timing/model': 0.45598274329677224, 'learning_rate/action_model': 9.968304717729401e-05, 'learning_rate/action_query_proj': 9.968304717729401e-05, 'learning_rate/base': 2.4920761794323503e-05, 'epoch': 0.02}) +[2026-07-26 19:34:44,391][starVLA.training.train_starvla][INFO] - Step 184, Loss: {'train/loss': 0.7693582773208618, 'train/grad_norm_pre_clip': 4.172084808349609, 'timing/data': 0.00018501514568924904, 'timing/model': 0.4779299017973244, 'learning_rate/action_model': 9.967957761723423e-05, 'learning_rate/action_query_proj': 9.967957761723423e-05, 'learning_rate/base': 2.4919894404308557e-05, 'epoch': 0.02}) +[2026-07-26 19:34:50,109][starVLA.training.train_starvla][INFO] - Step 185, Loss: {'train/loss': 0.6270536780357361, 'train/grad_norm_pre_clip': 6.535650253295898, 'timing/data': 0.00018699374049901962, 'timing/model': 0.4724520491436124, 'learning_rate/action_model': 9.96760892340323e-05, 'learning_rate/action_query_proj': 9.96760892340323e-05, 'learning_rate/base': 2.4919022308508075e-05, 'epoch': 0.02}) +[2026-07-26 19:34:55,780][starVLA.training.train_starvla][INFO] - Step 186, Loss: {'train/loss': 0.8372640609741211, 'train/grad_norm_pre_clip': 6.571858882904053, 'timing/data': 0.00019485224038362503, 'timing/model': 0.4693280039355159, 'learning_rate/action_model': 9.967258202906537e-05, 'learning_rate/action_query_proj': 9.967258202906537e-05, 'learning_rate/base': 2.4918145507266342e-05, 'epoch': 0.02}) +[2026-07-26 19:35:01,417][starVLA.training.train_starvla][INFO] - Step 187, Loss: {'train/loss': 0.8529434204101562, 'train/grad_norm_pre_clip': 7.051870346069336, 'timing/data': 0.00018643122166395187, 'timing/model': 0.4609616962261498, 'learning_rate/action_model': 9.966905600371806e-05, 'learning_rate/action_query_proj': 9.966905600371806e-05, 'learning_rate/base': 2.4917264000929515e-05, 'epoch': 0.02}) +[2026-07-26 19:35:07,008][starVLA.training.train_starvla][INFO] - Step 188, Loss: {'train/loss': 0.7328069806098938, 'train/grad_norm_pre_clip': 8.210246086120605, 'timing/data': 0.00019076000899076462, 'timing/model': 0.46028519468382, 'learning_rate/action_model': 9.966551115938236e-05, 'learning_rate/action_query_proj': 9.966551115938236e-05, 'learning_rate/base': 2.491637778984559e-05, 'epoch': 0.02}) +[2026-07-26 19:35:12,621][starVLA.training.train_starvla][INFO] - Step 189, Loss: {'train/loss': 0.6908201575279236, 'train/grad_norm_pre_clip': 5.557514667510986, 'timing/data': 0.00018455833196640015, 'timing/model': 0.45908925496041775, 'learning_rate/action_model': 9.966194749745774e-05, 'learning_rate/action_query_proj': 9.966194749745774e-05, 'learning_rate/base': 2.4915486874364434e-05, 'epoch': 0.02}) +[2026-07-26 19:35:18,214][starVLA.training.train_starvla][INFO] - Step 190, Loss: {'train/loss': 0.9577261209487915, 'train/grad_norm_pre_clip': 7.359745025634766, 'timing/data': 0.0003415849059820175, 'timing/model': 0.46025098487734795, 'learning_rate/action_model': 9.965836501935105e-05, 'learning_rate/action_query_proj': 9.965836501935105e-05, 'learning_rate/base': 2.4914591254837762e-05, 'epoch': 0.02}) +[2026-07-26 19:35:23,790][starVLA.training.train_starvla][INFO] - Step 191, Loss: {'train/loss': 0.8255618810653687, 'train/grad_norm_pre_clip': 6.812376022338867, 'timing/data': 0.00022887997329235077, 'timing/model': 0.4576629353687167, 'learning_rate/action_model': 9.965476372647662e-05, 'learning_rate/action_query_proj': 9.965476372647662e-05, 'learning_rate/base': 2.4913690931619156e-05, 'epoch': 0.02}) +[2026-07-26 19:35:29,391][starVLA.training.train_starvla][INFO] - Step 192, Loss: {'train/loss': 0.918305516242981, 'train/grad_norm_pre_clip': 10.604915618896484, 'timing/data': 0.00035632122308015823, 'timing/model': 0.4578231400810182, 'learning_rate/action_model': 9.96511436202562e-05, 'learning_rate/action_query_proj': 9.96511436202562e-05, 'learning_rate/base': 2.491278590506405e-05, 'epoch': 0.02}) +[2026-07-26 19:35:34,981][starVLA.training.train_starvla][INFO] - Step 193, Loss: {'train/loss': 0.630696177482605, 'train/grad_norm_pre_clip': 4.016857624053955, 'timing/data': 0.00019193394109606743, 'timing/model': 0.45726441591978073, 'learning_rate/action_model': 9.964750470211891e-05, 'learning_rate/action_query_proj': 9.964750470211891e-05, 'learning_rate/base': 2.491187617552973e-05, 'epoch': 0.02}) +[2026-07-26 19:35:40,562][starVLA.training.train_starvla][INFO] - Step 194, Loss: {'train/loss': 0.817412257194519, 'train/grad_norm_pre_clip': 9.194814682006836, 'timing/data': 0.0001927260309457779, 'timing/model': 0.45701372576877475, 'learning_rate/action_model': 9.964384697350134e-05, 'learning_rate/action_query_proj': 9.964384697350134e-05, 'learning_rate/base': 2.4910961743375335e-05, 'epoch': 0.02}) +[2026-07-26 19:35:46,181][starVLA.training.train_starvla][INFO] - Step 195, Loss: {'train/loss': 0.9579929709434509, 'train/grad_norm_pre_clip': 6.166290283203125, 'timing/data': 0.00020530028268694878, 'timing/model': 0.4715000940486789, 'learning_rate/action_model': 9.964017043584755e-05, 'learning_rate/action_query_proj': 9.964017043584755e-05, 'learning_rate/base': 2.4910042608961888e-05, 'epoch': 0.02}) +[2026-07-26 19:35:51,762][starVLA.training.train_starvla][INFO] - Step 196, Loss: {'train/loss': 0.9521001577377319, 'train/grad_norm_pre_clip': 6.709760665893555, 'timing/data': 0.00020161597058176994, 'timing/model': 0.4576944811269641, 'learning_rate/action_model': 9.963647509060892e-05, 'learning_rate/action_query_proj': 9.963647509060892e-05, 'learning_rate/base': 2.490911877265223e-05, 'epoch': 0.02}) +[2026-07-26 19:35:57,323][starVLA.training.train_starvla][INFO] - Step 197, Loss: {'train/loss': 0.8164067268371582, 'train/grad_norm_pre_clip': 5.890336990356445, 'timing/data': 0.0001864139921963215, 'timing/model': 0.4656162247993052, 'learning_rate/action_model': 9.963276093924435e-05, 'learning_rate/action_query_proj': 9.963276093924435e-05, 'learning_rate/base': 2.4908190234811088e-05, 'epoch': 0.02}) +[2026-07-26 19:36:02,871][starVLA.training.train_starvla][INFO] - Step 198, Loss: {'train/loss': 0.7589017152786255, 'train/grad_norm_pre_clip': 6.895502090454102, 'timing/data': 0.00019338028505444527, 'timing/model': 0.4633929398842156, 'learning_rate/action_model': 9.962902798322013e-05, 'learning_rate/action_query_proj': 9.962902798322013e-05, 'learning_rate/base': 2.4907256995805032e-05, 'epoch': 0.02}) +[2026-07-26 19:36:08,419][starVLA.training.train_starvla][INFO] - Step 199, Loss: {'train/loss': 0.9404208660125732, 'train/grad_norm_pre_clip': 9.254232406616211, 'timing/data': 0.00018402701243758202, 'timing/model': 0.4632760062813759, 'learning_rate/action_model': 9.962527622400994e-05, 'learning_rate/action_query_proj': 9.962527622400994e-05, 'learning_rate/base': 2.4906319056002486e-05, 'epoch': 0.02}) +[2026-07-26 19:36:13,960][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 200 +[2026-07-26 19:36:13,961][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 200 +[2026-07-26 19:36:13,961][starVLA.training.train_starvla][INFO] - Step 200, Loss: {'train/loss': 0.8539414405822754, 'train/grad_norm_pre_clip': 11.92563533782959, 'timing/data': 0.00018479907885193825, 'timing/model': 0.46280203107744455, 'learning_rate/action_model': 9.962150566309495e-05, 'learning_rate/action_query_proj': 9.962150566309495e-05, 'learning_rate/base': 2.4905376415773737e-05, 'epoch': 0.02}) +[2026-07-26 19:36:19,493][starVLA.training.train_starvla][INFO] - Step 201, Loss: {'train/loss': 0.8013548851013184, 'train/grad_norm_pre_clip': 5.4263916015625, 'timing/data': 0.0001880209892988205, 'timing/model': 0.46021855575963855, 'learning_rate/action_model': 9.961771630196369e-05, 'learning_rate/action_query_proj': 9.961771630196369e-05, 'learning_rate/base': 2.490442907549092e-05, 'epoch': 0.02}) +[2026-07-26 19:36:25,050][starVLA.training.train_starvla][INFO] - Step 202, Loss: {'train/loss': 0.969447910785675, 'train/grad_norm_pre_clip': 6.171998500823975, 'timing/data': 0.00020121783018112183, 'timing/model': 0.4633064200170338, 'learning_rate/action_model': 9.961390814211215e-05, 'learning_rate/action_query_proj': 9.961390814211215e-05, 'learning_rate/base': 2.4903477035528038e-05, 'epoch': 0.02}) +[2026-07-26 19:36:30,638][starVLA.training.train_starvla][INFO] - Step 203, Loss: {'train/loss': 0.9311591982841492, 'train/grad_norm_pre_clip': 9.34030532836914, 'timing/data': 0.00018683308735489845, 'timing/model': 0.4638611739501357, 'learning_rate/action_model': 9.961008118504374e-05, 'learning_rate/action_query_proj': 9.961008118504374e-05, 'learning_rate/base': 2.4902520296260936e-05, 'epoch': 0.02}) +[2026-07-26 19:36:36,215][starVLA.training.train_starvla][INFO] - Step 204, Loss: {'train/loss': 0.7697966694831848, 'train/grad_norm_pre_clip': 8.539203643798828, 'timing/data': 0.00018286192789673805, 'timing/model': 0.4632715177722275, 'learning_rate/action_model': 9.96062354322693e-05, 'learning_rate/action_query_proj': 9.96062354322693e-05, 'learning_rate/base': 2.4901558858067324e-05, 'epoch': 0.02}) +[2026-07-26 19:36:41,781][starVLA.training.train_starvla][INFO] - Step 205, Loss: {'train/loss': 0.7419072389602661, 'train/grad_norm_pre_clip': 9.99364185333252, 'timing/data': 0.00018310314044356346, 'timing/model': 0.4635299760848284, 'learning_rate/action_model': 9.960237088530703e-05, 'learning_rate/action_query_proj': 9.960237088530703e-05, 'learning_rate/base': 2.4900592721326758e-05, 'epoch': 0.02}) +[2026-07-26 19:36:47,369][starVLA.training.train_starvla][INFO] - Step 206, Loss: {'train/loss': 0.8473860621452332, 'train/grad_norm_pre_clip': 6.464334011077881, 'timing/data': 0.00018962472677230835, 'timing/model': 0.4726300542242825, 'learning_rate/action_model': 9.959848754568261e-05, 'learning_rate/action_query_proj': 9.959848754568261e-05, 'learning_rate/base': 2.4899621886420652e-05, 'epoch': 0.02}) +[2026-07-26 19:36:52,963][starVLA.training.train_starvla][INFO] - Step 207, Loss: {'train/loss': 0.803510308265686, 'train/grad_norm_pre_clip': 7.167577743530273, 'timing/data': 0.00018659979104995728, 'timing/model': 0.47396833822131157, 'learning_rate/action_model': 9.959458541492912e-05, 'learning_rate/action_query_proj': 9.959458541492912e-05, 'learning_rate/base': 2.489864635373228e-05, 'epoch': 0.03}) +[2026-07-26 19:36:58,580][starVLA.training.train_starvla][INFO] - Step 208, Loss: {'train/loss': 0.7552199959754944, 'train/grad_norm_pre_clip': 2.7298977375030518, 'timing/data': 0.00019425712525844574, 'timing/model': 0.472307117190212, 'learning_rate/action_model': 9.959066449458705e-05, 'learning_rate/action_query_proj': 9.959066449458705e-05, 'learning_rate/base': 2.4897666123646764e-05, 'epoch': 0.03}) +[2026-07-26 19:37:04,178][starVLA.training.train_starvla][INFO] - Step 209, Loss: {'train/loss': 0.7510166168212891, 'train/grad_norm_pre_clip': 5.836903095245361, 'timing/data': 0.00018987106159329414, 'timing/model': 0.47107727406546474, 'learning_rate/action_model': 9.958672478620435e-05, 'learning_rate/action_query_proj': 9.958672478620435e-05, 'learning_rate/base': 2.4896681196551088e-05, 'epoch': 0.03}) +[2026-07-26 19:37:09,769][starVLA.training.train_starvla][INFO] - Step 210, Loss: {'train/loss': 0.9058225750923157, 'train/grad_norm_pre_clip': 6.121529579162598, 'timing/data': 0.00018376298248767853, 'timing/model': 0.4629694242030382, 'learning_rate/action_model': 9.958276629133632e-05, 'learning_rate/action_query_proj': 9.958276629133632e-05, 'learning_rate/base': 2.489569157283408e-05, 'epoch': 0.03}) +[2026-07-26 19:37:15,323][starVLA.training.train_starvla][INFO] - Step 211, Loss: {'train/loss': 0.8012024760246277, 'train/grad_norm_pre_clip': 8.796856880187988, 'timing/data': 0.00018691131845116615, 'timing/model': 0.4628359149210155, 'learning_rate/action_model': 9.957878901154573e-05, 'learning_rate/action_query_proj': 9.957878901154573e-05, 'learning_rate/base': 2.4894697252886432e-05, 'epoch': 0.03}) +[2026-07-26 19:37:20,860][starVLA.training.train_starvla][INFO] - Step 212, Loss: {'train/loss': 0.7779132127761841, 'train/grad_norm_pre_clip': 8.407337188720703, 'timing/data': 0.00018257414922118187, 'timing/model': 0.4626228967681527, 'learning_rate/action_model': 9.957479294840275e-05, 'learning_rate/action_query_proj': 9.957479294840275e-05, 'learning_rate/base': 2.4893698237100686e-05, 'epoch': 0.03}) +[2026-07-26 19:37:26,408][starVLA.training.train_starvla][INFO] - Step 213, Loss: {'train/loss': 0.9199627637863159, 'train/grad_norm_pre_clip': 4.616183757781982, 'timing/data': 0.00018911482766270638, 'timing/model': 0.4646491827443242, 'learning_rate/action_model': 9.957077810348493e-05, 'learning_rate/action_query_proj': 9.957077810348493e-05, 'learning_rate/base': 2.4892694525871234e-05, 'epoch': 0.03}) +[2026-07-26 19:37:32,320][starVLA.training.train_starvla][INFO] - Step 214, Loss: {'train/loss': 0.8574281334877014, 'train/grad_norm_pre_clip': 7.736382484436035, 'timing/data': 0.0001913551241159439, 'timing/model': 0.4749112301506102, 'learning_rate/action_model': 9.95667444783773e-05, 'learning_rate/action_query_proj': 9.95667444783773e-05, 'learning_rate/base': 2.4891686119594326e-05, 'epoch': 0.03}) +[2026-07-26 19:37:37,877][starVLA.training.train_starvla][INFO] - Step 215, Loss: {'train/loss': 0.7248402237892151, 'train/grad_norm_pre_clip': 3.49658203125, 'timing/data': 0.00018752599135041237, 'timing/model': 0.4812719291076064, 'learning_rate/action_model': 9.956269207467226e-05, 'learning_rate/action_query_proj': 9.956269207467226e-05, 'learning_rate/base': 2.4890673018668066e-05, 'epoch': 0.03}) +[2026-07-26 19:37:43,404][starVLA.training.train_starvla][INFO] - Step 216, Loss: {'train/loss': 0.9301859736442566, 'train/grad_norm_pre_clip': 4.880300045013428, 'timing/data': 0.00018982728943228722, 'timing/model': 0.4739133231341839, 'learning_rate/action_model': 9.955862089396965e-05, 'learning_rate/action_query_proj': 9.955862089396965e-05, 'learning_rate/base': 2.488965522349241e-05, 'epoch': 0.03}) +[2026-07-26 19:37:48,940][starVLA.training.train_starvla][INFO] - Step 217, Loss: {'train/loss': 0.8905677795410156, 'train/grad_norm_pre_clip': 7.343987464904785, 'timing/data': 0.00018070312216877937, 'timing/model': 0.47659634705632925, 'learning_rate/action_model': 9.955453093787667e-05, 'learning_rate/action_query_proj': 9.955453093787667e-05, 'learning_rate/base': 2.488863273446917e-05, 'epoch': 0.03}) +[2026-07-26 19:37:54,475][starVLA.training.train_starvla][INFO] - Step 218, Loss: {'train/loss': 0.7909435033798218, 'train/grad_norm_pre_clip': 6.840578079223633, 'timing/data': 0.00018638325855135918, 'timing/model': 0.47177156107500196, 'learning_rate/action_model': 9.955042220800802e-05, 'learning_rate/action_query_proj': 9.955042220800802e-05, 'learning_rate/base': 2.4887605552002006e-05, 'epoch': 0.03}) +[2026-07-26 19:38:00,025][starVLA.training.train_starvla][INFO] - Step 219, Loss: {'train/loss': 0.6923534870147705, 'train/grad_norm_pre_clip': 6.452404022216797, 'timing/data': 0.00018548313528299332, 'timing/model': 0.4770922251045704, 'learning_rate/action_model': 9.954629470598571e-05, 'learning_rate/action_query_proj': 9.954629470598571e-05, 'learning_rate/base': 2.488657367649643e-05, 'epoch': 0.03}) +[2026-07-26 19:38:05,631][starVLA.training.train_starvla][INFO] - Step 220, Loss: {'train/loss': 0.8981063365936279, 'train/grad_norm_pre_clip': 6.909188747406006, 'timing/data': 0.00019100727513432503, 'timing/model': 0.4651187411509454, 'learning_rate/action_model': 9.954214843343925e-05, 'learning_rate/action_query_proj': 9.954214843343925e-05, 'learning_rate/base': 2.4885537108359812e-05, 'epoch': 0.03}) +[2026-07-26 19:38:11,189][starVLA.training.train_starvla][INFO] - Step 221, Loss: {'train/loss': 0.8536656498908997, 'train/grad_norm_pre_clip': 8.94365406036377, 'timing/data': 0.0002024858258664608, 'timing/model': 0.46287063183262944, 'learning_rate/action_model': 9.953798339200553e-05, 'learning_rate/action_query_proj': 9.953798339200553e-05, 'learning_rate/base': 2.4884495848001382e-05, 'epoch': 0.03}) +[2026-07-26 19:38:16,789][starVLA.training.train_starvla][INFO] - Step 222, Loss: {'train/loss': 0.8061012625694275, 'train/grad_norm_pre_clip': 7.843287944793701, 'timing/data': 0.00019236095249652863, 'timing/model': 0.46177464071661234, 'learning_rate/action_model': 9.95337995833288e-05, 'learning_rate/action_query_proj': 9.95337995833288e-05, 'learning_rate/base': 2.48834498958322e-05, 'epoch': 0.03}) +[2026-07-26 19:38:22,424][starVLA.training.train_starvla][INFO] - Step 223, Loss: {'train/loss': 0.8551684617996216, 'train/grad_norm_pre_clip': 5.885843276977539, 'timing/data': 0.00018459884449839592, 'timing/model': 0.46108008408918977, 'learning_rate/action_model': 9.952959700906079e-05, 'learning_rate/action_query_proj': 9.952959700906079e-05, 'learning_rate/base': 2.4882399252265197e-05, 'epoch': 0.03}) +[2026-07-26 19:38:28,044][starVLA.training.train_starvla][INFO] - Step 224, Loss: {'train/loss': 0.8613925576210022, 'train/grad_norm_pre_clip': 8.715546607971191, 'timing/data': 0.00018449034541845322, 'timing/model': 0.4640177469700575, 'learning_rate/action_model': 9.952537567086062e-05, 'learning_rate/action_query_proj': 9.952537567086062e-05, 'learning_rate/base': 2.4881343917715156e-05, 'epoch': 0.03}) +[2026-07-26 19:38:33,675][starVLA.training.train_starvla][INFO] - Step 225, Loss: {'train/loss': 0.8108855485916138, 'train/grad_norm_pre_clip': 8.972238540649414, 'timing/data': 0.0001909881830215454, 'timing/model': 0.4642364978790283, 'learning_rate/action_model': 9.952113557039477e-05, 'learning_rate/action_query_proj': 9.952113557039477e-05, 'learning_rate/base': 2.488028389259869e-05, 'epoch': 0.03}) +[2026-07-26 19:38:39,317][starVLA.training.train_starvla][INFO] - Step 226, Loss: {'train/loss': 0.9135777950286865, 'train/grad_norm_pre_clip': 6.294252395629883, 'timing/data': 0.00018934998661279678, 'timing/model': 0.4617518959566951, 'learning_rate/action_model': 9.95168767093372e-05, 'learning_rate/action_query_proj': 9.95168767093372e-05, 'learning_rate/base': 2.48792191773343e-05, 'epoch': 0.03}) +[2026-07-26 19:38:44,886][starVLA.training.train_starvla][INFO] - Step 227, Loss: {'train/loss': 0.8258665204048157, 'train/grad_norm_pre_clip': 6.219912528991699, 'timing/data': 0.0002010837197303772, 'timing/model': 0.46088852314278483, 'learning_rate/action_model': 9.951259908936921e-05, 'learning_rate/action_query_proj': 9.951259908936921e-05, 'learning_rate/base': 2.4878149772342303e-05, 'epoch': 0.03}) +[2026-07-26 19:38:50,415][starVLA.training.train_starvla][INFO] - Step 228, Loss: {'train/loss': 0.7141548991203308, 'train/grad_norm_pre_clip': 6.053246021270752, 'timing/data': 0.0001899339258670807, 'timing/model': 0.4625182328745723, 'learning_rate/action_model': 9.950830271217957e-05, 'learning_rate/action_query_proj': 9.950830271217957e-05, 'learning_rate/base': 2.487707567804489e-05, 'epoch': 0.03}) +[2026-07-26 19:38:55,963][starVLA.training.train_starvla][INFO] - Step 229, Loss: {'train/loss': 0.762481689453125, 'train/grad_norm_pre_clip': 7.046648025512695, 'timing/data': 0.0001906272955238819, 'timing/model': 0.4652230981737375, 'learning_rate/action_model': 9.95039875794644e-05, 'learning_rate/action_query_proj': 9.95039875794644e-05, 'learning_rate/base': 2.48759968948661e-05, 'epoch': 0.03}) +[2026-07-26 19:39:01,524][starVLA.training.train_starvla][INFO] - Step 230, Loss: {'train/loss': 0.834242582321167, 'train/grad_norm_pre_clip': 5.402335166931152, 'timing/data': 0.00018735043704509735, 'timing/model': 0.461334012914449, 'learning_rate/action_model': 9.949965369292724e-05, 'learning_rate/action_query_proj': 9.949965369292724e-05, 'learning_rate/base': 2.487491342323181e-05, 'epoch': 0.03}) +[2026-07-26 19:39:07,073][starVLA.training.train_starvla][INFO] - Step 231, Loss: {'train/loss': 0.7090080380439758, 'train/grad_norm_pre_clip': 6.208821773529053, 'timing/data': 0.00018829014152288437, 'timing/model': 0.4613603400066495, 'learning_rate/action_model': 9.949530105427908e-05, 'learning_rate/action_query_proj': 9.949530105427908e-05, 'learning_rate/base': 2.487382526356977e-05, 'epoch': 0.03}) +[2026-07-26 19:39:12,652][starVLA.training.train_starvla][INFO] - Step 232, Loss: {'train/loss': 0.7442181706428528, 'train/grad_norm_pre_clip': 7.891812324523926, 'timing/data': 0.0001870938576757908, 'timing/model': 0.4717091750353575, 'learning_rate/action_model': 9.949092966523822e-05, 'learning_rate/action_query_proj': 9.949092966523822e-05, 'learning_rate/base': 2.4872732416309556e-05, 'epoch': 0.03}) +[2026-07-26 19:39:18,195][starVLA.training.train_starvla][INFO] - Step 233, Loss: {'train/loss': 0.7616564035415649, 'train/grad_norm_pre_clip': 5.976849555969238, 'timing/data': 0.00018759770318865776, 'timing/model': 0.4639981952495873, 'learning_rate/action_model': 9.948653952753044e-05, 'learning_rate/action_query_proj': 9.948653952753044e-05, 'learning_rate/base': 2.487163488188261e-05, 'epoch': 0.03}) +[2026-07-26 19:39:23,740][starVLA.training.train_starvla][INFO] - Step 234, Loss: {'train/loss': 0.7530415654182434, 'train/grad_norm_pre_clip': 3.172060251235962, 'timing/data': 0.0001946273259818554, 'timing/model': 0.4640685892663896, 'learning_rate/action_model': 9.948213064288892e-05, 'learning_rate/action_query_proj': 9.948213064288892e-05, 'learning_rate/base': 2.487053266072223e-05, 'epoch': 0.03}) +[2026-07-26 19:39:29,277][starVLA.training.train_starvla][INFO] - Step 235, Loss: {'train/loss': 0.7790409326553345, 'train/grad_norm_pre_clip': 4.457376480102539, 'timing/data': 0.00019677076488733292, 'timing/model': 0.46217650221660733, 'learning_rate/action_model': 9.947770301305417e-05, 'learning_rate/action_query_proj': 9.947770301305417e-05, 'learning_rate/base': 2.486942575326354e-05, 'epoch': 0.03}) +[2026-07-26 19:39:34,809][starVLA.training.train_starvla][INFO] - Step 236, Loss: {'train/loss': 0.8716495037078857, 'train/grad_norm_pre_clip': 4.820958137512207, 'timing/data': 0.00018799956887960434, 'timing/model': 0.4641302842646837, 'learning_rate/action_model': 9.947325663977418e-05, 'learning_rate/action_query_proj': 9.947325663977418e-05, 'learning_rate/base': 2.4868314159943546e-05, 'epoch': 0.03}) +[2026-07-26 19:39:40,334][starVLA.training.train_starvla][INFO] - Step 237, Loss: {'train/loss': 0.8684332370758057, 'train/grad_norm_pre_clip': 9.334630966186523, 'timing/data': 0.0001872638240456581, 'timing/model': 0.46342418203130364, 'learning_rate/action_model': 9.946879152480431e-05, 'learning_rate/action_query_proj': 9.946879152480431e-05, 'learning_rate/base': 2.4867197881201077e-05, 'epoch': 0.03}) +[2026-07-26 19:39:45,857][starVLA.training.train_starvla][INFO] - Step 238, Loss: {'train/loss': 0.7725242972373962, 'train/grad_norm_pre_clip': 5.148656845092773, 'timing/data': 0.00019405363127589226, 'timing/model': 0.46386679261922836, 'learning_rate/action_model': 9.946430766990729e-05, 'learning_rate/action_query_proj': 9.946430766990729e-05, 'learning_rate/base': 2.4866076917476822e-05, 'epoch': 0.03}) +[2026-07-26 19:39:51,381][starVLA.training.train_starvla][INFO] - Step 239, Loss: {'train/loss': 0.9022478461265564, 'train/grad_norm_pre_clip': 6.7657904624938965, 'timing/data': 0.00018314039334654808, 'timing/model': 0.46287845401093364, 'learning_rate/action_model': 9.94598050768533e-05, 'learning_rate/action_query_proj': 9.94598050768533e-05, 'learning_rate/base': 2.4864951269213325e-05, 'epoch': 0.03}) +[2026-07-26 19:39:56,893][starVLA.training.train_starvla][INFO] - Step 240, Loss: {'train/loss': 0.6988874673843384, 'train/grad_norm_pre_clip': 5.334063529968262, 'timing/data': 0.00018581794574856758, 'timing/model': 0.46303950902074575, 'learning_rate/action_model': 9.945528374741986e-05, 'learning_rate/action_query_proj': 9.945528374741986e-05, 'learning_rate/base': 2.4863820936854966e-05, 'epoch': 0.03}) +[2026-07-26 19:40:02,406][starVLA.training.train_starvla][INFO] - Step 241, Loss: {'train/loss': 0.7926585674285889, 'train/grad_norm_pre_clip': 4.275729179382324, 'timing/data': 0.00018157996237277985, 'timing/model': 0.4655880481004715, 'learning_rate/action_model': 9.945074368339197e-05, 'learning_rate/action_query_proj': 9.945074368339197e-05, 'learning_rate/base': 2.4862685920847993e-05, 'epoch': 0.03}) +[2026-07-26 19:40:07,929][starVLA.training.train_starvla][INFO] - Step 242, Loss: {'train/loss': 0.779534101486206, 'train/grad_norm_pre_clip': 5.058417797088623, 'timing/data': 0.0001855180598795414, 'timing/model': 0.4631692380644381, 'learning_rate/action_model': 9.944618488656196e-05, 'learning_rate/action_query_proj': 9.944618488656196e-05, 'learning_rate/base': 2.486154622164049e-05, 'epoch': 0.03}) +[2026-07-26 19:40:13,440][starVLA.training.train_starvla][INFO] - Step 243, Loss: {'train/loss': 0.776912271976471, 'train/grad_norm_pre_clip': 8.456734657287598, 'timing/data': 0.00018669990822672844, 'timing/model': 0.46168513922020793, 'learning_rate/action_model': 9.944160735872952e-05, 'learning_rate/action_query_proj': 9.944160735872952e-05, 'learning_rate/base': 2.486040183968238e-05, 'epoch': 0.03}) +[2026-07-26 19:40:18,963][starVLA.training.train_starvla][INFO] - Step 244, Loss: {'train/loss': 0.6815619468688965, 'train/grad_norm_pre_clip': 5.305862903594971, 'timing/data': 0.00019128108397126198, 'timing/model': 0.46444503404200077, 'learning_rate/action_model': 9.943701110170186e-05, 'learning_rate/action_query_proj': 9.943701110170186e-05, 'learning_rate/base': 2.4859252775425466e-05, 'epoch': 0.03}) +[2026-07-26 19:40:24,470][starVLA.training.train_starvla][INFO] - Step 245, Loss: {'train/loss': 0.8057383894920349, 'train/grad_norm_pre_clip': 6.2022385597229, 'timing/data': 0.00018404703587293625, 'timing/model': 0.46088459668681026, 'learning_rate/action_model': 9.943239611729349e-05, 'learning_rate/action_query_proj': 9.943239611729349e-05, 'learning_rate/base': 2.485809902932337e-05, 'epoch': 0.03}) +[2026-07-26 19:40:29,978][starVLA.training.train_starvla][INFO] - Step 246, Loss: {'train/loss': 0.7456108331680298, 'train/grad_norm_pre_clip': 5.599495887756348, 'timing/data': 0.00018729595467448235, 'timing/model': 0.4613568400964141, 'learning_rate/action_model': 9.942776240732626e-05, 'learning_rate/action_query_proj': 9.942776240732626e-05, 'learning_rate/base': 2.4856940601831565e-05, 'epoch': 0.03}) +[2026-07-26 19:40:35,482][starVLA.training.train_starvla][INFO] - Step 247, Loss: {'train/loss': 0.6808103919029236, 'train/grad_norm_pre_clip': 8.539216041564941, 'timing/data': 0.0001882794313132763, 'timing/model': 0.4603738049045205, 'learning_rate/action_model': 9.942310997362958e-05, 'learning_rate/action_query_proj': 9.942310997362958e-05, 'learning_rate/base': 2.4855777493407395e-05, 'epoch': 0.03}) +[2026-07-26 19:40:41,042][starVLA.training.train_starvla][INFO] - Step 248, Loss: {'train/loss': 0.7573755979537964, 'train/grad_norm_pre_clip': 4.1552252769470215, 'timing/data': 0.00018368195742368698, 'timing/model': 0.47225579526275396, 'learning_rate/action_model': 9.941843881804011e-05, 'learning_rate/action_query_proj': 9.941843881804011e-05, 'learning_rate/base': 2.4854609704510027e-05, 'epoch': 0.03}) +[2026-07-26 19:40:46,655][starVLA.training.train_starvla][INFO] - Step 249, Loss: {'train/loss': 0.8703587055206299, 'train/grad_norm_pre_clip': 9.880311012268066, 'timing/data': 0.00018708780407905579, 'timing/model': 0.47283147601410747, 'learning_rate/action_model': 9.941374894240196e-05, 'learning_rate/action_query_proj': 9.941374894240196e-05, 'learning_rate/base': 2.485343723560049e-05, 'epoch': 0.03}) +[2026-07-26 19:40:52,267][starVLA.training.train_starvla][INFO] - Step 250, Loss: {'train/loss': 0.926513135433197, 'train/grad_norm_pre_clip': 6.3114776611328125, 'timing/data': 0.00019062589854002, 'timing/model': 0.4727053917013109, 'learning_rate/action_model': 9.940904034856662e-05, 'learning_rate/action_query_proj': 9.940904034856662e-05, 'learning_rate/base': 2.4852260087141655e-05, 'epoch': 0.03}) +[2026-07-26 19:40:57,869][starVLA.training.train_starvla][INFO] - Step 251, Loss: {'train/loss': 0.8230401277542114, 'train/grad_norm_pre_clip': 6.614382266998291, 'timing/data': 0.0001828949898481369, 'timing/model': 0.47169399401172996, 'learning_rate/action_model': 9.940431303839296e-05, 'learning_rate/action_query_proj': 9.940431303839296e-05, 'learning_rate/base': 2.485107825959824e-05, 'epoch': 0.03}) +[2026-07-26 19:41:03,474][starVLA.training.train_starvla][INFO] - Step 252, Loss: {'train/loss': 0.7988444566726685, 'train/grad_norm_pre_clip': 5.0235137939453125, 'timing/data': 0.0001923949457705021, 'timing/model': 0.47269004909321666, 'learning_rate/action_model': 9.939956701374724e-05, 'learning_rate/action_query_proj': 9.939956701374724e-05, 'learning_rate/base': 2.484989175343681e-05, 'epoch': 0.03}) +[2026-07-26 19:41:09,106][starVLA.training.train_starvla][INFO] - Step 253, Loss: {'train/loss': 0.7150273323059082, 'train/grad_norm_pre_clip': 4.852092266082764, 'timing/data': 0.00018787896260619164, 'timing/model': 0.4707661918364465, 'learning_rate/action_model': 9.939480227650314e-05, 'learning_rate/action_query_proj': 9.939480227650314e-05, 'learning_rate/base': 2.4848700569125786e-05, 'epoch': 0.03}) +[2026-07-26 19:41:14,737][starVLA.training.train_starvla][INFO] - Step 254, Loss: {'train/loss': 0.813503086566925, 'train/grad_norm_pre_clip': 4.706774711608887, 'timing/data': 0.00019137514755129814, 'timing/model': 0.4719481039792299, 'learning_rate/action_model': 9.93900188285417e-05, 'learning_rate/action_query_proj': 9.93900188285417e-05, 'learning_rate/base': 2.4847504707135424e-05, 'epoch': 0.03}) +[2026-07-26 19:41:20,363][starVLA.training.train_starvla][INFO] - Step 255, Loss: {'train/loss': 0.6726509928703308, 'train/grad_norm_pre_clip': 9.612258911132812, 'timing/data': 0.0001880279742181301, 'timing/model': 0.4688442521728575, 'learning_rate/action_model': 9.938521667175133e-05, 'learning_rate/action_query_proj': 9.938521667175133e-05, 'learning_rate/base': 2.484630416793783e-05, 'epoch': 0.03}) +[2026-07-26 19:41:25,991][starVLA.training.train_starvla][INFO] - Step 256, Loss: {'train/loss': 0.7530980706214905, 'train/grad_norm_pre_clip': 8.235750198364258, 'timing/data': 0.0001896270550787449, 'timing/model': 0.4700696859508753, 'learning_rate/action_model': 9.938039580802785e-05, 'learning_rate/action_query_proj': 9.938039580802785e-05, 'learning_rate/base': 2.4845098952006962e-05, 'epoch': 0.03}) +[2026-07-26 19:41:31,872][starVLA.training.train_starvla][INFO] - Step 257, Loss: {'train/loss': 0.7400839328765869, 'train/grad_norm_pre_clip': 3.53703236579895, 'timing/data': 0.00019492628052830696, 'timing/model': 0.4698316161520779, 'learning_rate/action_model': 9.937555623927447e-05, 'learning_rate/action_query_proj': 9.937555623927447e-05, 'learning_rate/base': 2.4843889059818616e-05, 'epoch': 0.03}) +[2026-07-26 19:41:37,499][starVLA.training.train_starvla][INFO] - Step 258, Loss: {'train/loss': 0.7694078683853149, 'train/grad_norm_pre_clip': 3.8180925846099854, 'timing/data': 0.00019149575382471085, 'timing/model': 0.47356608137488365, 'learning_rate/action_model': 9.937069796740176e-05, 'learning_rate/action_query_proj': 9.937069796740176e-05, 'learning_rate/base': 2.484267449185044e-05, 'epoch': 0.03}) +[2026-07-26 19:41:43,108][starVLA.training.train_starvla][INFO] - Step 259, Loss: {'train/loss': 0.7011995911598206, 'train/grad_norm_pre_clip': 5.549917697906494, 'timing/data': 0.00019273580983281136, 'timing/model': 0.47046270687133074, 'learning_rate/action_model': 9.936582099432772e-05, 'learning_rate/action_query_proj': 9.936582099432772e-05, 'learning_rate/base': 2.484145524858193e-05, 'epoch': 0.03}) +[2026-07-26 19:41:48,690][starVLA.training.train_starvla][INFO] - Step 260, Loss: {'train/loss': 0.6991811394691467, 'train/grad_norm_pre_clip': 7.937453269958496, 'timing/data': 0.00019558193162083626, 'timing/model': 0.4624141547828913, 'learning_rate/action_model': 9.936092532197766e-05, 'learning_rate/action_query_proj': 9.936092532197766e-05, 'learning_rate/base': 2.4840231330494415e-05, 'epoch': 0.03}) +[2026-07-26 19:41:54,222][starVLA.training.train_starvla][INFO] - Step 261, Loss: {'train/loss': 0.6931261420249939, 'train/grad_norm_pre_clip': 4.461982250213623, 'timing/data': 0.00018368009477853775, 'timing/model': 0.469489139970392, 'learning_rate/action_model': 9.935601095228436e-05, 'learning_rate/action_query_proj': 9.935601095228436e-05, 'learning_rate/base': 2.483900273807109e-05, 'epoch': 0.03}) +[2026-07-26 19:41:59,756][starVLA.training.train_starvla][INFO] - Step 262, Loss: {'train/loss': 0.8035269975662231, 'train/grad_norm_pre_clip': 4.366477966308594, 'timing/data': 0.00019269483163952827, 'timing/model': 0.4582951460033655, 'learning_rate/action_model': 9.935107788718789e-05, 'learning_rate/action_query_proj': 9.935107788718789e-05, 'learning_rate/base': 2.4837769471796972e-05, 'epoch': 0.03}) +[2026-07-26 19:42:05,309][starVLA.training.train_starvla][INFO] - Step 263, Loss: {'train/loss': 0.6946811079978943, 'train/grad_norm_pre_clip': 3.4820806980133057, 'timing/data': 0.0002017100341618061, 'timing/model': 0.4585251919925213, 'learning_rate/action_model': 9.934612612863578e-05, 'learning_rate/action_query_proj': 9.934612612863578e-05, 'learning_rate/base': 2.4836531532158945e-05, 'epoch': 0.03}) +[2026-07-26 19:42:10,873][starVLA.training.train_starvla][INFO] - Step 264, Loss: {'train/loss': 0.7404839396476746, 'train/grad_norm_pre_clip': 4.7034406661987305, 'timing/data': 0.000187660101801157, 'timing/model': 0.4622903917916119, 'learning_rate/action_model': 9.934115567858288e-05, 'learning_rate/action_query_proj': 9.934115567858288e-05, 'learning_rate/base': 2.483528891964572e-05, 'epoch': 0.03}) +[2026-07-26 19:42:16,434][starVLA.training.train_starvla][INFO] - Step 265, Loss: {'train/loss': 0.7508418560028076, 'train/grad_norm_pre_clip': 6.8571672439575195, 'timing/data': 0.00019222311675548553, 'timing/model': 0.4634386580437422, 'learning_rate/action_model': 9.933616653899147e-05, 'learning_rate/action_query_proj': 9.933616653899147e-05, 'learning_rate/base': 2.4834041634747868e-05, 'epoch': 0.03}) +[2026-07-26 19:42:22,246][starVLA.training.train_starvla][INFO] - Step 266, Loss: {'train/loss': 0.7195408344268799, 'train/grad_norm_pre_clip': 4.4644856452941895, 'timing/data': 0.00019220029935240746, 'timing/model': 0.47179587790742517, 'learning_rate/action_model': 9.933115871183117e-05, 'learning_rate/action_query_proj': 9.933115871183117e-05, 'learning_rate/base': 2.4832789677957792e-05, 'epoch': 0.03}) +[2026-07-26 19:42:28,116][starVLA.training.train_starvla][INFO] - Step 267, Loss: {'train/loss': 0.8355758190155029, 'train/grad_norm_pre_clip': 8.790931701660156, 'timing/data': 0.00018773507326841354, 'timing/model': 0.47022499702870846, 'learning_rate/action_model': 9.932613219907899e-05, 'learning_rate/action_query_proj': 9.932613219907899e-05, 'learning_rate/base': 2.4831533049769746e-05, 'epoch': 0.03}) +[2026-07-26 19:42:33,676][starVLA.training.train_starvla][INFO] - Step 268, Loss: {'train/loss': 0.7057293653488159, 'train/grad_norm_pre_clip': 4.797832012176514, 'timing/data': 0.00018638558685779572, 'timing/model': 0.45898885978385806, 'learning_rate/action_model': 9.93210870027193e-05, 'learning_rate/action_query_proj': 9.93210870027193e-05, 'learning_rate/base': 2.4830271750679825e-05, 'epoch': 0.03}) +[2026-07-26 19:42:39,212][starVLA.training.train_starvla][INFO] - Step 269, Loss: {'train/loss': 0.7665987610816956, 'train/grad_norm_pre_clip': 7.272431373596191, 'timing/data': 0.0001886403188109398, 'timing/model': 0.46070373663678765, 'learning_rate/action_model': 9.931602312474391e-05, 'learning_rate/action_query_proj': 9.931602312474391e-05, 'learning_rate/base': 2.4829005781185977e-05, 'epoch': 0.03}) +[2026-07-26 19:42:44,763][starVLA.training.train_starvla][INFO] - Step 270, Loss: {'train/loss': 0.9310687184333801, 'train/grad_norm_pre_clip': 9.136896133422852, 'timing/data': 0.00018760981038212776, 'timing/model': 0.45918664103373885, 'learning_rate/action_model': 9.931094056715191e-05, 'learning_rate/action_query_proj': 9.931094056715191e-05, 'learning_rate/base': 2.4827735141787978e-05, 'epoch': 0.03}) +[2026-07-26 19:42:50,391][starVLA.training.train_starvla][INFO] - Step 271, Loss: {'train/loss': 0.9473406672477722, 'train/grad_norm_pre_clip': 10.053232192993164, 'timing/data': 0.00018857000395655632, 'timing/model': 0.47046186588704586, 'learning_rate/action_model': 9.930583933194983e-05, 'learning_rate/action_query_proj': 9.930583933194983e-05, 'learning_rate/base': 2.482645983298746e-05, 'epoch': 0.03}) +[2026-07-26 19:42:56,022][starVLA.training.train_starvla][INFO] - Step 272, Loss: {'train/loss': 0.8395686745643616, 'train/grad_norm_pre_clip': 8.025918006896973, 'timing/data': 0.00019706832244992256, 'timing/model': 0.4796609487384558, 'learning_rate/action_model': 9.930071942115159e-05, 'learning_rate/action_query_proj': 9.930071942115159e-05, 'learning_rate/base': 2.4825179855287897e-05, 'epoch': 0.03}) +[2026-07-26 19:43:01,636][starVLA.training.train_starvla][INFO] - Step 273, Loss: {'train/loss': 0.7817704677581787, 'train/grad_norm_pre_clip': 4.8552985191345215, 'timing/data': 0.00018552085384726524, 'timing/model': 0.4712313860654831, 'learning_rate/action_model': 9.92955808367784e-05, 'learning_rate/action_query_proj': 9.92955808367784e-05, 'learning_rate/base': 2.48238952091946e-05, 'epoch': 0.03}) +[2026-07-26 19:43:07,203][starVLA.training.train_starvla][INFO] - Step 274, Loss: {'train/loss': 0.7023821473121643, 'train/grad_norm_pre_clip': 5.2711968421936035, 'timing/data': 0.0001908130943775177, 'timing/model': 0.46962681226432323, 'learning_rate/action_model': 9.929042358085894e-05, 'learning_rate/action_query_proj': 9.929042358085894e-05, 'learning_rate/base': 2.4822605895214735e-05, 'epoch': 0.03}) +[2026-07-26 19:43:12,785][starVLA.training.train_starvla][INFO] - Step 275, Loss: {'train/loss': 0.7979979515075684, 'train/grad_norm_pre_clip': 6.178257942199707, 'timing/data': 0.00019099004566669464, 'timing/model': 0.47556502604857087, 'learning_rate/action_model': 9.928524765542915e-05, 'learning_rate/action_query_proj': 9.928524765542915e-05, 'learning_rate/base': 2.4821311913857286e-05, 'epoch': 0.03}) +[2026-07-26 19:43:18,629][starVLA.training.train_starvla][INFO] - Step 276, Loss: {'train/loss': 0.7657114863395691, 'train/grad_norm_pre_clip': 8.735203742980957, 'timing/data': 0.00022509833797812462, 'timing/model': 0.4791090553626418, 'learning_rate/action_model': 9.928005306253245e-05, 'learning_rate/action_query_proj': 9.928005306253245e-05, 'learning_rate/base': 2.4820013265633112e-05, 'epoch': 0.03}) +[2026-07-26 19:43:24,222][starVLA.training.train_starvla][INFO] - Step 277, Loss: {'train/loss': 0.7686627507209778, 'train/grad_norm_pre_clip': 3.2909040451049805, 'timing/data': 0.00019036605954170227, 'timing/model': 0.4702050508931279, 'learning_rate/action_model': 9.927483980421959e-05, 'learning_rate/action_query_proj': 9.927483980421959e-05, 'learning_rate/base': 2.4818709951054896e-05, 'epoch': 0.03}) +[2026-07-26 19:43:29,791][starVLA.training.train_starvla][INFO] - Step 278, Loss: {'train/loss': 0.8192643523216248, 'train/grad_norm_pre_clip': 7.610496997833252, 'timing/data': 0.00018955674022436142, 'timing/model': 0.4686619625426829, 'learning_rate/action_model': 9.926960788254865e-05, 'learning_rate/action_query_proj': 9.926960788254865e-05, 'learning_rate/base': 2.4817401970637162e-05, 'epoch': 0.03}) +[2026-07-26 19:43:35,372][starVLA.training.train_starvla][INFO] - Step 279, Loss: {'train/loss': 0.8170910477638245, 'train/grad_norm_pre_clip': 6.834660530090332, 'timing/data': 0.00019100308418273926, 'timing/model': 0.46768210362643003, 'learning_rate/action_model': 9.926435729958512e-05, 'learning_rate/action_query_proj': 9.926435729958512e-05, 'learning_rate/base': 2.481608932489628e-05, 'epoch': 0.03}) +[2026-07-26 19:43:40,935][starVLA.training.train_starvla][INFO] - Step 280, Loss: {'train/loss': 0.7663376927375793, 'train/grad_norm_pre_clip': 7.205996990203857, 'timing/data': 0.00018938211724162102, 'timing/model': 0.47004549484699965, 'learning_rate/action_model': 9.925908805740186e-05, 'learning_rate/action_query_proj': 9.925908805740186e-05, 'learning_rate/base': 2.4814772014350464e-05, 'epoch': 0.03}) +[2026-07-26 19:43:46,526][starVLA.training.train_starvla][INFO] - Step 281, Loss: {'train/loss': 0.7929310202598572, 'train/grad_norm_pre_clip': 7.347952842712402, 'timing/data': 0.00019316794350743294, 'timing/model': 0.4717058651149273, 'learning_rate/action_model': 9.925380015807908e-05, 'learning_rate/action_query_proj': 9.925380015807908e-05, 'learning_rate/base': 2.481345003951977e-05, 'epoch': 0.03}) +[2026-07-26 19:43:52,124][starVLA.training.train_starvla][INFO] - Step 282, Loss: {'train/loss': 0.6178560256958008, 'train/grad_norm_pre_clip': 4.606512069702148, 'timing/data': 0.0001877741888165474, 'timing/model': 0.4715080098249018, 'learning_rate/action_model': 9.924849360370433e-05, 'learning_rate/action_query_proj': 9.924849360370433e-05, 'learning_rate/base': 2.4812123400926083e-05, 'epoch': 0.03}) +[2026-07-26 19:43:57,737][starVLA.training.train_starvla][INFO] - Step 283, Loss: {'train/loss': 0.848167359828949, 'train/grad_norm_pre_clip': 2.4641177654266357, 'timing/data': 0.00020642392337322235, 'timing/model': 0.4714540899731219, 'learning_rate/action_model': 9.924316839637261e-05, 'learning_rate/action_query_proj': 9.924316839637261e-05, 'learning_rate/base': 2.4810792099093152e-05, 'epoch': 0.03}) +[2026-07-26 19:44:03,358][starVLA.training.train_starvla][INFO] - Step 284, Loss: {'train/loss': 0.7115926146507263, 'train/grad_norm_pre_clip': 4.646142959594727, 'timing/data': 0.00019715400412678719, 'timing/model': 0.4703128091059625, 'learning_rate/action_model': 9.923782453818617e-05, 'learning_rate/action_query_proj': 9.923782453818617e-05, 'learning_rate/base': 2.4809456134546542e-05, 'epoch': 0.03}) +[2026-07-26 19:44:08,964][starVLA.training.train_starvla][INFO] - Step 285, Loss: {'train/loss': 0.7308528423309326, 'train/grad_norm_pre_clip': 3.8660736083984375, 'timing/data': 0.00019185012206435204, 'timing/model': 0.47102014627307653, 'learning_rate/action_model': 9.923246203125471e-05, 'learning_rate/action_query_proj': 9.923246203125471e-05, 'learning_rate/base': 2.480811550781368e-05, 'epoch': 0.03}) +[2026-07-26 19:44:14,560][starVLA.training.train_starvla][INFO] - Step 286, Loss: {'train/loss': 0.8068281412124634, 'train/grad_norm_pre_clip': 8.124300956726074, 'timing/data': 0.00018821004778146744, 'timing/model': 0.47187055880203843, 'learning_rate/action_model': 9.922708087769526e-05, 'learning_rate/action_query_proj': 9.922708087769526e-05, 'learning_rate/base': 2.4806770219423816e-05, 'epoch': 0.03}) +[2026-07-26 19:44:20,155][starVLA.training.train_starvla][INFO] - Step 287, Loss: {'train/loss': 0.846610426902771, 'train/grad_norm_pre_clip': 5.781831741333008, 'timing/data': 0.00019348086789250374, 'timing/model': 0.47526723984628916, 'learning_rate/action_model': 9.922168107963222e-05, 'learning_rate/action_query_proj': 9.922168107963222e-05, 'learning_rate/base': 2.4805420269908054e-05, 'epoch': 0.03}) +[2026-07-26 19:44:25,738][starVLA.training.train_starvla][INFO] - Step 288, Loss: {'train/loss': 0.7763293385505676, 'train/grad_norm_pre_clip': 6.134871482849121, 'timing/data': 0.00019504409283399582, 'timing/model': 0.4701048620045185, 'learning_rate/action_model': 9.921626263919733e-05, 'learning_rate/action_query_proj': 9.921626263919733e-05, 'learning_rate/base': 2.4804065659799333e-05, 'epoch': 0.03}) +[2026-07-26 19:44:31,318][starVLA.training.train_starvla][INFO] - Step 289, Loss: {'train/loss': 0.8255937099456787, 'train/grad_norm_pre_clip': 5.826430320739746, 'timing/data': 0.00018997211009263992, 'timing/model': 0.4704980831593275, 'learning_rate/action_model': 9.921082555852971e-05, 'learning_rate/action_query_proj': 9.921082555852971e-05, 'learning_rate/base': 2.4802706389632427e-05, 'epoch': 0.04}) +[2026-07-26 19:44:36,885][starVLA.training.train_starvla][INFO] - Step 290, Loss: {'train/loss': 0.6936467289924622, 'train/grad_norm_pre_clip': 5.014166831970215, 'timing/data': 0.000192966777831316, 'timing/model': 0.4700667173601687, 'learning_rate/action_model': 9.920536983977583e-05, 'learning_rate/action_query_proj': 9.920536983977583e-05, 'learning_rate/base': 2.4801342459943956e-05, 'epoch': 0.04}) +[2026-07-26 19:44:42,476][starVLA.training.train_starvla][INFO] - Step 291, Loss: {'train/loss': 0.6760430335998535, 'train/grad_norm_pre_clip': 4.724428176879883, 'timing/data': 0.00019593816250562668, 'timing/model': 0.4698442597873509, 'learning_rate/action_model': 9.919989548508953e-05, 'learning_rate/action_query_proj': 9.919989548508953e-05, 'learning_rate/base': 2.4799973871272383e-05, 'epoch': 0.04}) +[2026-07-26 19:44:48,044][starVLA.training.train_starvla][INFO] - Step 292, Loss: {'train/loss': 0.6750221252441406, 'train/grad_norm_pre_clip': 4.670234203338623, 'timing/data': 0.00018582865595817566, 'timing/model': 0.4705828712321818, 'learning_rate/action_model': 9.919440249663198e-05, 'learning_rate/action_query_proj': 9.919440249663198e-05, 'learning_rate/base': 2.4798600624157996e-05, 'epoch': 0.04}) +[2026-07-26 19:44:53,614][starVLA.training.train_starvla][INFO] - Step 293, Loss: {'train/loss': 0.8934199810028076, 'train/grad_norm_pre_clip': 5.190743446350098, 'timing/data': 0.00019387900829315186, 'timing/model': 0.4698186903260648, 'learning_rate/action_model': 9.918889087657177e-05, 'learning_rate/action_query_proj': 9.918889087657177e-05, 'learning_rate/base': 2.4797222719142943e-05, 'epoch': 0.04}) +[2026-07-26 19:44:59,209][starVLA.training.train_starvla][INFO] - Step 294, Loss: {'train/loss': 0.8776576519012451, 'train/grad_norm_pre_clip': 5.080217361450195, 'timing/data': 0.00018508965149521828, 'timing/model': 0.47001855820417404, 'learning_rate/action_model': 9.918336062708476e-05, 'learning_rate/action_query_proj': 9.918336062708476e-05, 'learning_rate/base': 2.479584015677119e-05, 'epoch': 0.04}) +[2026-07-26 19:45:04,794][starVLA.training.train_starvla][INFO] - Step 295, Loss: {'train/loss': 0.673445463180542, 'train/grad_norm_pre_clip': 6.21188497543335, 'timing/data': 0.000185525044798851, 'timing/model': 0.4705919069238007, 'learning_rate/action_model': 9.91778117503542e-05, 'learning_rate/action_query_proj': 9.91778117503542e-05, 'learning_rate/base': 2.479445293758855e-05, 'epoch': 0.04}) +[2026-07-26 19:45:10,333][starVLA.training.train_starvla][INFO] - Step 296, Loss: {'train/loss': 0.6703571081161499, 'train/grad_norm_pre_clip': 3.9070444107055664, 'timing/data': 0.00019108178094029427, 'timing/model': 0.4564124830067158, 'learning_rate/action_model': 9.917224424857073e-05, 'learning_rate/action_query_proj': 9.917224424857073e-05, 'learning_rate/base': 2.4793061062142682e-05, 'epoch': 0.04}) +[2026-07-26 19:45:16,120][starVLA.training.train_starvla][INFO] - Step 297, Loss: {'train/loss': 0.8148103952407837, 'train/grad_norm_pre_clip': 7.718057632446289, 'timing/data': 0.00018098577857017517, 'timing/model': 0.45658311201259494, 'learning_rate/action_model': 9.916665812393228e-05, 'learning_rate/action_query_proj': 9.916665812393228e-05, 'learning_rate/base': 2.479166453098307e-05, 'epoch': 0.04}) +[2026-07-26 19:45:21,913][starVLA.training.train_starvla][INFO] - Step 298, Loss: {'train/loss': 0.9440056085586548, 'train/grad_norm_pre_clip': 11.041519165039062, 'timing/data': 0.00019909674301743507, 'timing/model': 0.458297957200557, 'learning_rate/action_model': 9.916105337864419e-05, 'learning_rate/action_query_proj': 9.916105337864419e-05, 'learning_rate/base': 2.4790263344661048e-05, 'epoch': 0.04}) +[2026-07-26 19:45:27,443][starVLA.training.train_starvla][INFO] - Step 299, Loss: {'train/loss': 0.7528183460235596, 'train/grad_norm_pre_clip': 8.915449142456055, 'timing/data': 0.00018154503777623177, 'timing/model': 0.47086379677057266, 'learning_rate/action_model': 9.915543001491912e-05, 'learning_rate/action_query_proj': 9.915543001491912e-05, 'learning_rate/base': 2.478885750372978e-05, 'epoch': 0.04}) +[2026-07-26 19:45:32,988][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 300 +[2026-07-26 19:45:32,988][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 300 +[2026-07-26 19:45:32,989][starVLA.training.train_starvla][INFO] - Step 300, Loss: {'train/loss': 0.7848880290985107, 'train/grad_norm_pre_clip': 7.318118095397949, 'timing/data': 0.00018308917060494423, 'timing/model': 0.47277528792619705, 'learning_rate/action_model': 9.914978803497707e-05, 'learning_rate/action_query_proj': 9.914978803497707e-05, 'learning_rate/base': 2.4787447008744268e-05, 'epoch': 0.04}) +[2026-07-26 19:45:38,529][starVLA.training.train_starvla][INFO] - Step 301, Loss: {'train/loss': 0.8502764701843262, 'train/grad_norm_pre_clip': 7.4307661056518555, 'timing/data': 0.00018608709797263145, 'timing/model': 0.46942422119900584, 'learning_rate/action_model': 9.91441274410454e-05, 'learning_rate/action_query_proj': 9.91441274410454e-05, 'learning_rate/base': 2.478603186026135e-05, 'epoch': 0.04}) +[2026-07-26 19:45:44,099][starVLA.training.train_starvla][INFO] - Step 302, Loss: {'train/loss': 0.8626749515533447, 'train/grad_norm_pre_clip': 8.175483703613281, 'timing/data': 0.00018696673214435577, 'timing/model': 0.4766914388164878, 'learning_rate/action_model': 9.913844823535884e-05, 'learning_rate/action_query_proj': 9.913844823535884e-05, 'learning_rate/base': 2.478461205883971e-05, 'epoch': 0.04}) +[2026-07-26 19:45:49,926][starVLA.training.train_starvla][INFO] - Step 303, Loss: {'train/loss': 0.7837517261505127, 'train/grad_norm_pre_clip': 6.890655040740967, 'timing/data': 0.00018775463104248047, 'timing/model': 0.47624446591362357, 'learning_rate/action_model': 9.913275042015944e-05, 'learning_rate/action_query_proj': 9.913275042015944e-05, 'learning_rate/base': 2.478318760503986e-05, 'epoch': 0.04}) +[2026-07-26 19:45:55,512][starVLA.training.train_starvla][INFO] - Step 304, Loss: {'train/loss': 0.7635684013366699, 'train/grad_norm_pre_clip': 7.7778849601745605, 'timing/data': 0.00018490804359316826, 'timing/model': 0.47371064918115735, 'learning_rate/action_model': 9.912703399769664e-05, 'learning_rate/action_query_proj': 9.912703399769664e-05, 'learning_rate/base': 2.478175849942416e-05, 'epoch': 0.04}) +[2026-07-26 19:46:01,074][starVLA.training.train_starvla][INFO] - Step 305, Loss: {'train/loss': 0.8567579984664917, 'train/grad_norm_pre_clip': 7.533411026000977, 'timing/data': 0.00018966803327202797, 'timing/model': 0.4749624948017299, 'learning_rate/action_model': 9.912129897022714e-05, 'learning_rate/action_query_proj': 9.912129897022714e-05, 'learning_rate/base': 2.4780324742556786e-05, 'epoch': 0.04}) +[2026-07-26 19:46:06,613][starVLA.training.train_starvla][INFO] - Step 306, Loss: {'train/loss': 0.8142755627632141, 'train/grad_norm_pre_clip': 10.488533020019531, 'timing/data': 0.0001862579956650734, 'timing/model': 0.46878800680860877, 'learning_rate/action_model': 9.911554534001508e-05, 'learning_rate/action_query_proj': 9.911554534001508e-05, 'learning_rate/base': 2.477888633500377e-05, 'epoch': 0.04}) +[2026-07-26 19:46:12,162][starVLA.training.train_starvla][INFO] - Step 307, Loss: {'train/loss': 0.813320517539978, 'train/grad_norm_pre_clip': 7.006349563598633, 'timing/data': 0.00019487878307700157, 'timing/model': 0.4708826909773052, 'learning_rate/action_model': 9.910977310933189e-05, 'learning_rate/action_query_proj': 9.910977310933189e-05, 'learning_rate/base': 2.477744327733297e-05, 'epoch': 0.04}) +[2026-07-26 19:46:17,696][starVLA.training.train_starvla][INFO] - Step 308, Loss: {'train/loss': 0.8469746708869934, 'train/grad_norm_pre_clip': 4.616273403167725, 'timing/data': 0.00018958700820803642, 'timing/model': 0.4569053240120411, 'learning_rate/action_model': 9.910398228045635e-05, 'learning_rate/action_query_proj': 9.910398228045635e-05, 'learning_rate/base': 2.4775995570114086e-05, 'epoch': 0.04}) +[2026-07-26 19:46:23,213][starVLA.training.train_starvla][INFO] - Step 309, Loss: {'train/loss': 0.8666640520095825, 'train/grad_norm_pre_clip': 5.036192893981934, 'timing/data': 0.00019035814329981804, 'timing/model': 0.4598225820809603, 'learning_rate/action_model': 9.909817285567456e-05, 'learning_rate/action_query_proj': 9.909817285567456e-05, 'learning_rate/base': 2.477454321391864e-05, 'epoch': 0.04}) +[2026-07-26 19:46:28,745][starVLA.training.train_starvla][INFO] - Step 310, Loss: {'train/loss': 0.8675074577331543, 'train/grad_norm_pre_clip': 4.5342535972595215, 'timing/data': 0.0001903320662677288, 'timing/model': 0.4708837028592825, 'learning_rate/action_model': 9.909234483728003e-05, 'learning_rate/action_query_proj': 9.909234483728003e-05, 'learning_rate/base': 2.477308620932001e-05, 'epoch': 0.04}) +[2026-07-26 19:46:34,300][starVLA.training.train_starvla][INFO] - Step 311, Loss: {'train/loss': 0.7139862179756165, 'train/grad_norm_pre_clip': 3.8446764945983887, 'timing/data': 0.00018884101882576942, 'timing/model': 0.4697414208203554, 'learning_rate/action_model': 9.908649822757358e-05, 'learning_rate/action_query_proj': 9.908649822757358e-05, 'learning_rate/base': 2.4771624556893396e-05, 'epoch': 0.04}) +[2026-07-26 19:46:39,890][starVLA.training.train_starvla][INFO] - Step 312, Loss: {'train/loss': 0.8993864059448242, 'train/grad_norm_pre_clip': 7.542398929595947, 'timing/data': 0.00018851971253752708, 'timing/model': 0.46997199719771743, 'learning_rate/action_model': 9.908063302886332e-05, 'learning_rate/action_query_proj': 9.908063302886332e-05, 'learning_rate/base': 2.477015825721583e-05, 'epoch': 0.04}) +[2026-07-26 19:46:45,444][starVLA.training.train_starvla][INFO] - Step 313, Loss: {'train/loss': 0.7065377831459045, 'train/grad_norm_pre_clip': 3.1673381328582764, 'timing/data': 0.00018771691247820854, 'timing/model': 0.4576214556582272, 'learning_rate/action_model': 9.907474924346476e-05, 'learning_rate/action_query_proj': 9.907474924346476e-05, 'learning_rate/base': 2.476868731086619e-05, 'epoch': 0.04}) +[2026-07-26 19:46:51,003][starVLA.training.train_starvla][INFO] - Step 314, Loss: {'train/loss': 0.834511399269104, 'train/grad_norm_pre_clip': 4.690902233123779, 'timing/data': 0.00018570106476545334, 'timing/model': 0.4579374408349395, 'learning_rate/action_model': 9.906884687370069e-05, 'learning_rate/action_query_proj': 9.906884687370069e-05, 'learning_rate/base': 2.4767211718425173e-05, 'epoch': 0.04}) +[2026-07-26 19:46:56,575][starVLA.training.train_starvla][INFO] - Step 315, Loss: {'train/loss': 0.6739345788955688, 'train/grad_norm_pre_clip': 3.511549472808838, 'timing/data': 0.00019585620611906052, 'timing/model': 0.4565168167464435, 'learning_rate/action_model': 9.906292592190133e-05, 'learning_rate/action_query_proj': 9.906292592190133e-05, 'learning_rate/base': 2.4765731480475333e-05, 'epoch': 0.04}) +[2026-07-26 19:47:02,120][starVLA.training.train_starvla][INFO] - Step 316, Loss: {'train/loss': 0.680240273475647, 'train/grad_norm_pre_clip': 4.109411239624023, 'timing/data': 0.00019392604008316994, 'timing/model': 0.4588044756092131, 'learning_rate/action_model': 9.905698639040415e-05, 'learning_rate/action_query_proj': 9.905698639040415e-05, 'learning_rate/base': 2.4764246597601038e-05, 'epoch': 0.04}) +[2026-07-26 19:47:07,701][starVLA.training.train_starvla][INFO] - Step 317, Loss: {'train/loss': 0.6623018980026245, 'train/grad_norm_pre_clip': 5.394981861114502, 'timing/data': 0.000186149962246418, 'timing/model': 0.471735502127558, 'learning_rate/action_model': 9.905102828155398e-05, 'learning_rate/action_query_proj': 9.905102828155398e-05, 'learning_rate/base': 2.4762757070388494e-05, 'epoch': 0.04}) +[2026-07-26 19:47:13,295][starVLA.training.train_starvla][INFO] - Step 318, Loss: {'train/loss': 0.6412090063095093, 'train/grad_norm_pre_clip': 5.291353702545166, 'timing/data': 0.0001873779110610485, 'timing/model': 0.4717824012041092, 'learning_rate/action_model': 9.904505159770298e-05, 'learning_rate/action_query_proj': 9.904505159770298e-05, 'learning_rate/base': 2.4761262899425746e-05, 'epoch': 0.04}) +[2026-07-26 19:47:18,889][starVLA.training.train_starvla][INFO] - Step 319, Loss: {'train/loss': 0.6653199195861816, 'train/grad_norm_pre_clip': 6.980660438537598, 'timing/data': 0.0001836288720369339, 'timing/model': 0.47101499093696475, 'learning_rate/action_model': 9.903905634121067e-05, 'learning_rate/action_query_proj': 9.903905634121067e-05, 'learning_rate/base': 2.4759764085302667e-05, 'epoch': 0.04}) +[2026-07-26 19:47:24,472][starVLA.training.train_starvla][INFO] - Step 320, Loss: {'train/loss': 0.7151708602905273, 'train/grad_norm_pre_clip': 4.041257858276367, 'timing/data': 0.00019191019237041473, 'timing/model': 0.468126337043941, 'learning_rate/action_model': 9.903304251444385e-05, 'learning_rate/action_query_proj': 9.903304251444385e-05, 'learning_rate/base': 2.4758260628610964e-05, 'epoch': 0.04}) +[2026-07-26 19:47:30,055][starVLA.training.train_starvla][INFO] - Step 321, Loss: {'train/loss': 0.6566681861877441, 'train/grad_norm_pre_clip': 5.186844348907471, 'timing/data': 0.00018873810768127441, 'timing/model': 0.4710541837848723, 'learning_rate/action_model': 9.902701011977672e-05, 'learning_rate/action_query_proj': 9.902701011977672e-05, 'learning_rate/base': 2.475675252994418e-05, 'epoch': 0.04}) +[2026-07-26 19:47:35,624][starVLA.training.train_starvla][INFO] - Step 322, Loss: {'train/loss': 0.8304393291473389, 'train/grad_norm_pre_clip': 11.163311004638672, 'timing/data': 0.00036798324435949326, 'timing/model': 0.4705578819848597, 'learning_rate/action_model': 9.902095915959077e-05, 'learning_rate/action_query_proj': 9.902095915959077e-05, 'learning_rate/base': 2.475523978989769e-05, 'epoch': 0.04}) +[2026-07-26 19:47:41,222][starVLA.training.train_starvla][INFO] - Step 323, Loss: {'train/loss': 0.7288715839385986, 'train/grad_norm_pre_clip': 7.607233047485352, 'timing/data': 0.000379358883947134, 'timing/model': 0.4770834553055465, 'learning_rate/action_model': 9.901488963627479e-05, 'learning_rate/action_query_proj': 9.901488963627479e-05, 'learning_rate/base': 2.4753722409068697e-05, 'epoch': 0.04}) +[2026-07-26 19:47:46,802][starVLA.training.train_starvla][INFO] - Step 324, Loss: {'train/loss': 0.707658588886261, 'train/grad_norm_pre_clip': 3.4675283432006836, 'timing/data': 0.00037440797314047813, 'timing/model': 0.4758740100078285, 'learning_rate/action_model': 9.900880155222496e-05, 'learning_rate/action_query_proj': 9.900880155222496e-05, 'learning_rate/base': 2.475220038805624e-05, 'epoch': 0.04}) +[2026-07-26 19:47:52,366][starVLA.training.train_starvla][INFO] - Step 325, Loss: {'train/loss': 0.826064944267273, 'train/grad_norm_pre_clip': 4.352246284484863, 'timing/data': 0.0003685387782752514, 'timing/model': 0.46084860898554325, 'learning_rate/action_model': 9.900269490984477e-05, 'learning_rate/action_query_proj': 9.900269490984477e-05, 'learning_rate/base': 2.4750673727461192e-05, 'epoch': 0.04}) +[2026-07-26 19:47:57,922][starVLA.training.train_starvla][INFO] - Step 326, Loss: {'train/loss': 0.7805114388465881, 'train/grad_norm_pre_clip': 8.723597526550293, 'timing/data': 0.00037984922528266907, 'timing/model': 0.4632122777402401, 'learning_rate/action_model': 9.899656971154499e-05, 'learning_rate/action_query_proj': 9.899656971154499e-05, 'learning_rate/base': 2.4749142427886247e-05, 'epoch': 0.04}) +[2026-07-26 19:48:03,754][starVLA.training.train_starvla][INFO] - Step 327, Loss: {'train/loss': 0.7060467600822449, 'train/grad_norm_pre_clip': 8.658845901489258, 'timing/data': 0.00023566605523228645, 'timing/model': 0.4632642506621778, 'learning_rate/action_model': 9.899042595974377e-05, 'learning_rate/action_query_proj': 9.899042595974377e-05, 'learning_rate/base': 2.4747606489935942e-05, 'epoch': 0.04}) +[2026-07-26 19:48:09,342][starVLA.training.train_starvla][INFO] - Step 328, Loss: {'train/loss': 0.7587519288063049, 'train/grad_norm_pre_clip': 6.933502197265625, 'timing/data': 0.0003573708236217499, 'timing/model': 0.4726828131824732, 'learning_rate/action_model': 9.898426365686659e-05, 'learning_rate/action_query_proj': 9.898426365686659e-05, 'learning_rate/base': 2.4746065914216647e-05, 'epoch': 0.04}) +[2026-07-26 19:48:14,945][starVLA.training.train_starvla][INFO] - Step 329, Loss: {'train/loss': 0.744201123714447, 'train/grad_norm_pre_clip': 3.3317389488220215, 'timing/data': 0.0001863841898739338, 'timing/model': 0.47907296707853675, 'learning_rate/action_model': 9.897808280534616e-05, 'learning_rate/action_query_proj': 9.897808280534616e-05, 'learning_rate/base': 2.474452070133654e-05, 'epoch': 0.04}) +[2026-07-26 19:48:20,520][starVLA.training.train_starvla][INFO] - Step 330, Loss: {'train/loss': 0.7287566661834717, 'train/grad_norm_pre_clip': 6.240508079528809, 'timing/data': 0.00018379418179392815, 'timing/model': 0.4719633050262928, 'learning_rate/action_model': 9.897188340762267e-05, 'learning_rate/action_query_proj': 9.897188340762267e-05, 'learning_rate/base': 2.4742970851905668e-05, 'epoch': 0.04}) +[2026-07-26 19:48:26,095][starVLA.training.train_starvla][INFO] - Step 331, Loss: {'train/loss': 0.7846079468727112, 'train/grad_norm_pre_clip': 3.60280179977417, 'timing/data': 0.0001860661432147026, 'timing/model': 0.46933797374367714, 'learning_rate/action_model': 9.896566546614349e-05, 'learning_rate/action_query_proj': 9.896566546614349e-05, 'learning_rate/base': 2.4741416366535873e-05, 'epoch': 0.04}) +[2026-07-26 19:48:31,677][starVLA.training.train_starvla][INFO] - Step 332, Loss: {'train/loss': 0.750506579875946, 'train/grad_norm_pre_clip': 5.379093647003174, 'timing/data': 0.00022488180547952652, 'timing/model': 0.4614035929553211, 'learning_rate/action_model': 9.895942898336337e-05, 'learning_rate/action_query_proj': 9.895942898336337e-05, 'learning_rate/base': 2.4739857245840843e-05, 'epoch': 0.04}) +[2026-07-26 19:48:37,252][starVLA.training.train_starvla][INFO] - Step 333, Loss: {'train/loss': 0.6044674515724182, 'train/grad_norm_pre_clip': 6.10946798324585, 'timing/data': 0.00018804799765348434, 'timing/model': 0.460934785194695, 'learning_rate/action_model': 9.895317396174437e-05, 'learning_rate/action_query_proj': 9.895317396174437e-05, 'learning_rate/base': 2.4738293490436092e-05, 'epoch': 0.04}) +[2026-07-26 19:48:42,825][starVLA.training.train_starvla][INFO] - Step 334, Loss: {'train/loss': 0.695003867149353, 'train/grad_norm_pre_clip': 6.18806266784668, 'timing/data': 0.00038011837750673294, 'timing/model': 0.46273214370012283, 'learning_rate/action_model': 9.89469004037559e-05, 'learning_rate/action_query_proj': 9.89469004037559e-05, 'learning_rate/base': 2.4736725100938977e-05, 'epoch': 0.04}) +[2026-07-26 19:48:48,430][starVLA.training.train_starvla][INFO] - Step 335, Loss: {'train/loss': 0.64687180519104, 'train/grad_norm_pre_clip': 3.937774181365967, 'timing/data': 0.0001895981840789318, 'timing/model': 0.46282298024743795, 'learning_rate/action_model': 9.894060831187465e-05, 'learning_rate/action_query_proj': 9.894060831187465e-05, 'learning_rate/base': 2.4735152077968663e-05, 'epoch': 0.04}) +[2026-07-26 19:48:53,990][starVLA.training.train_starvla][INFO] - Step 336, Loss: {'train/loss': 0.6917685866355896, 'train/grad_norm_pre_clip': 5.112886428833008, 'timing/data': 0.0003589019179344177, 'timing/model': 0.456187488976866, 'learning_rate/action_model': 9.893429768858464e-05, 'learning_rate/action_query_proj': 9.893429768858464e-05, 'learning_rate/base': 2.473357442214616e-05, 'epoch': 0.04}) +[2026-07-26 19:48:59,557][starVLA.training.train_starvla][INFO] - Step 337, Loss: {'train/loss': 0.7528436779975891, 'train/grad_norm_pre_clip': 5.65666389465332, 'timing/data': 0.0003664339892566204, 'timing/model': 0.45829322515055537, 'learning_rate/action_model': 9.892796853637718e-05, 'learning_rate/action_query_proj': 9.892796853637718e-05, 'learning_rate/base': 2.4731992134094295e-05, 'epoch': 0.04}) +[2026-07-26 19:49:05,101][starVLA.training.train_starvla][INFO] - Step 338, Loss: {'train/loss': 0.8889638185501099, 'train/grad_norm_pre_clip': 4.704346179962158, 'timing/data': 0.0002398202195763588, 'timing/model': 0.4566119001246989, 'learning_rate/action_model': 9.892162085775094e-05, 'learning_rate/action_query_proj': 9.892162085775094e-05, 'learning_rate/base': 2.4730405214437734e-05, 'epoch': 0.04}) +[2026-07-26 19:49:10,667][starVLA.training.train_starvla][INFO] - Step 339, Loss: {'train/loss': 0.742883026599884, 'train/grad_norm_pre_clip': 5.566108226776123, 'timing/data': 0.00018222955986857414, 'timing/model': 0.4640956721268594, 'learning_rate/action_model': 9.89152546552119e-05, 'learning_rate/action_query_proj': 9.89152546552119e-05, 'learning_rate/base': 2.4728813663802975e-05, 'epoch': 0.04}) +[2026-07-26 19:49:16,247][starVLA.training.train_starvla][INFO] - Step 340, Loss: {'train/loss': 0.6115785837173462, 'train/grad_norm_pre_clip': 3.355203866958618, 'timing/data': 0.00018888898193836212, 'timing/model': 0.4575760909356177, 'learning_rate/action_model': 9.89088699312733e-05, 'learning_rate/action_query_proj': 9.89088699312733e-05, 'learning_rate/base': 2.4727217482818323e-05, 'epoch': 0.04}) +[2026-07-26 19:49:21,804][starVLA.training.train_starvla][INFO] - Step 341, Loss: {'train/loss': 0.7092984914779663, 'train/grad_norm_pre_clip': 8.682939529418945, 'timing/data': 0.00018850993365049362, 'timing/model': 0.45852641109377146, 'learning_rate/action_model': 9.890246668845574e-05, 'learning_rate/action_query_proj': 9.890246668845574e-05, 'learning_rate/base': 2.4725616672113935e-05, 'epoch': 0.04}) +[2026-07-26 19:49:27,344][starVLA.training.train_starvla][INFO] - Step 342, Loss: {'train/loss': 0.8328515291213989, 'train/grad_norm_pre_clip': 9.775458335876465, 'timing/data': 0.00018576998263597488, 'timing/model': 0.45697096129879355, 'learning_rate/action_model': 9.889604492928712e-05, 'learning_rate/action_query_proj': 9.889604492928712e-05, 'learning_rate/base': 2.472401123232178e-05, 'epoch': 0.04}) +[2026-07-26 19:49:32,952][starVLA.training.train_starvla][INFO] - Step 343, Loss: {'train/loss': 0.8643591403961182, 'train/grad_norm_pre_clip': 7.93806266784668, 'timing/data': 0.0001933104358613491, 'timing/model': 0.45695845363661647, 'learning_rate/action_model': 9.888960465630267e-05, 'learning_rate/action_query_proj': 9.888960465630267e-05, 'learning_rate/base': 2.4722401164075667e-05, 'epoch': 0.04}) +[2026-07-26 19:49:38,508][starVLA.training.train_starvla][INFO] - Step 344, Loss: {'train/loss': 0.8918865323066711, 'train/grad_norm_pre_clip': 7.012485980987549, 'timing/data': 0.00018808618187904358, 'timing/model': 0.4564401679672301, 'learning_rate/action_model': 9.888314587204488e-05, 'learning_rate/action_query_proj': 9.888314587204488e-05, 'learning_rate/base': 2.472078646801122e-05, 'epoch': 0.04}) +[2026-07-26 19:49:44,079][starVLA.training.train_starvla][INFO] - Step 345, Loss: {'train/loss': 0.8802845478057861, 'train/grad_norm_pre_clip': 9.588335990905762, 'timing/data': 0.0001864149235188961, 'timing/model': 0.45701551530510187, 'learning_rate/action_model': 9.887666857906358e-05, 'learning_rate/action_query_proj': 9.887666857906358e-05, 'learning_rate/base': 2.4719167144765895e-05, 'epoch': 0.04}) +[2026-07-26 19:49:49,629][starVLA.training.train_starvla][INFO] - Step 346, Loss: {'train/loss': 0.6989997625350952, 'train/grad_norm_pre_clip': 8.107379913330078, 'timing/data': 0.00018302025273442268, 'timing/model': 0.4566200035624206, 'learning_rate/action_model': 9.887017277991591e-05, 'learning_rate/action_query_proj': 9.887017277991591e-05, 'learning_rate/base': 2.4717543194978978e-05, 'epoch': 0.04}) +[2026-07-26 19:49:55,166][starVLA.training.train_starvla][INFO] - Step 347, Loss: {'train/loss': 0.7522611021995544, 'train/grad_norm_pre_clip': 6.976444244384766, 'timing/data': 0.00019567692652344704, 'timing/model': 0.4573216247372329, 'learning_rate/action_model': 9.886365847716633e-05, 'learning_rate/action_query_proj': 9.886365847716633e-05, 'learning_rate/base': 2.471591461929158e-05, 'epoch': 0.04}) +[2026-07-26 19:50:00,719][starVLA.training.train_starvla][INFO] - Step 348, Loss: {'train/loss': 0.760867714881897, 'train/grad_norm_pre_clip': 6.358612060546875, 'timing/data': 0.0002003381960093975, 'timing/model': 0.45810698298737407, 'learning_rate/action_model': 9.885712567338654e-05, 'learning_rate/action_query_proj': 9.885712567338654e-05, 'learning_rate/base': 2.4714281418346635e-05, 'epoch': 0.04}) +[2026-07-26 19:50:06,280][starVLA.training.train_starvla][INFO] - Step 349, Loss: {'train/loss': 0.6381257772445679, 'train/grad_norm_pre_clip': 3.274240732192993, 'timing/data': 0.0001844046637415886, 'timing/model': 0.45711297634989023, 'learning_rate/action_model': 9.885057437115561e-05, 'learning_rate/action_query_proj': 9.885057437115561e-05, 'learning_rate/base': 2.4712643592788902e-05, 'epoch': 0.04}) +[2026-07-26 19:50:11,826][starVLA.training.train_starvla][INFO] - Step 350, Loss: {'train/loss': 0.48886358737945557, 'train/grad_norm_pre_clip': 4.325867176055908, 'timing/data': 0.0001853383146226406, 'timing/model': 0.45609408896416426, 'learning_rate/action_model': 9.884400457305988e-05, 'learning_rate/action_query_proj': 9.884400457305988e-05, 'learning_rate/base': 2.471100114326497e-05, 'epoch': 0.04}) +[2026-07-26 19:50:17,419][starVLA.training.train_starvla][INFO] - Step 351, Loss: {'train/loss': 0.7258766293525696, 'train/grad_norm_pre_clip': 4.507957458496094, 'timing/data': 0.00018724799156188965, 'timing/model': 0.4567107609473169, 'learning_rate/action_model': 9.883741628169302e-05, 'learning_rate/action_query_proj': 9.883741628169302e-05, 'learning_rate/base': 2.4709354070423256e-05, 'epoch': 0.04}) +[2026-07-26 19:50:23,018][starVLA.training.train_starvla][INFO] - Step 352, Loss: {'train/loss': 0.6171691417694092, 'train/grad_norm_pre_clip': 6.967623710632324, 'timing/data': 0.00018415087834000587, 'timing/model': 0.4572591371834278, 'learning_rate/action_model': 9.883080949965597e-05, 'learning_rate/action_query_proj': 9.883080949965597e-05, 'learning_rate/base': 2.4707702374913994e-05, 'epoch': 0.04}) +[2026-07-26 19:50:28,606][starVLA.training.train_starvla][INFO] - Step 353, Loss: {'train/loss': 0.6452891826629639, 'train/grad_norm_pre_clip': 5.44775390625, 'timing/data': 0.00018977606669068336, 'timing/model': 0.45664747385308146, 'learning_rate/action_model': 9.882418422955699e-05, 'learning_rate/action_query_proj': 9.882418422955699e-05, 'learning_rate/base': 2.4706046057389246e-05, 'epoch': 0.04}) +[2026-07-26 19:50:34,190][starVLA.training.train_starvla][INFO] - Step 354, Loss: {'train/loss': 0.6449435353279114, 'train/grad_norm_pre_clip': 2.593960762023926, 'timing/data': 0.00018572388216853142, 'timing/model': 0.45619982993230224, 'learning_rate/action_model': 9.881754047401163e-05, 'learning_rate/action_query_proj': 9.881754047401163e-05, 'learning_rate/base': 2.4704385118502907e-05, 'epoch': 0.04}) +[2026-07-26 19:50:39,760][starVLA.training.train_starvla][INFO] - Step 355, Loss: {'train/loss': 0.7020410299301147, 'train/grad_norm_pre_clip': 5.326965808868408, 'timing/data': 0.00019252998754382133, 'timing/model': 0.45645322976633906, 'learning_rate/action_model': 9.881087823564272e-05, 'learning_rate/action_query_proj': 9.881087823564272e-05, 'learning_rate/base': 2.470271955891068e-05, 'epoch': 0.04}) +[2026-07-26 19:50:45,274][starVLA.training.train_starvla][INFO] - Step 356, Loss: {'train/loss': 0.7109255790710449, 'train/grad_norm_pre_clip': 4.556671142578125, 'timing/data': 0.00018960842862725258, 'timing/model': 0.4560918672941625, 'learning_rate/action_model': 9.880419751708045e-05, 'learning_rate/action_query_proj': 9.880419751708045e-05, 'learning_rate/base': 2.4701049379270112e-05, 'epoch': 0.04}) +[2026-07-26 19:50:50,816][starVLA.training.train_starvla][INFO] - Step 357, Loss: {'train/loss': 0.6224475502967834, 'train/grad_norm_pre_clip': 6.833506107330322, 'timing/data': 0.00018566474318504333, 'timing/model': 0.4566322509199381, 'learning_rate/action_model': 9.879749832096221e-05, 'learning_rate/action_query_proj': 9.879749832096221e-05, 'learning_rate/base': 2.4699374580240552e-05, 'epoch': 0.04}) +[2026-07-26 19:50:56,329][starVLA.training.train_starvla][INFO] - Step 358, Loss: {'train/loss': 0.6158442497253418, 'train/grad_norm_pre_clip': 5.662900447845459, 'timing/data': 0.00018020393326878548, 'timing/model': 0.4572967612184584, 'learning_rate/action_model': 9.87907806499328e-05, 'learning_rate/action_query_proj': 9.87907806499328e-05, 'learning_rate/base': 2.46976951624832e-05, 'epoch': 0.04}) +[2026-07-26 19:51:01,860][starVLA.training.train_starvla][INFO] - Step 359, Loss: {'train/loss': 0.6878690719604492, 'train/grad_norm_pre_clip': 5.564486980438232, 'timing/data': 0.00018673203885555267, 'timing/model': 0.45640398003160954, 'learning_rate/action_model': 9.878404450664417e-05, 'learning_rate/action_query_proj': 9.878404450664417e-05, 'learning_rate/base': 2.4696011126661043e-05, 'epoch': 0.04}) +[2026-07-26 19:51:07,382][starVLA.training.train_starvla][INFO] - Step 360, Loss: {'train/loss': 0.7103490829467773, 'train/grad_norm_pre_clip': 4.582924842834473, 'timing/data': 0.00018623098731040955, 'timing/model': 0.45587531197816133, 'learning_rate/action_model': 9.877728989375571e-05, 'learning_rate/action_query_proj': 9.877728989375571e-05, 'learning_rate/base': 2.4694322473438927e-05, 'epoch': 0.04}) +[2026-07-26 19:51:12,940][starVLA.training.train_starvla][INFO] - Step 361, Loss: {'train/loss': 0.5550984144210815, 'train/grad_norm_pre_clip': 5.34663200378418, 'timing/data': 0.00018298206850886345, 'timing/model': 0.4579467363655567, 'learning_rate/action_model': 9.8770516813934e-05, 'learning_rate/action_query_proj': 9.8770516813934e-05, 'learning_rate/base': 2.46926292034835e-05, 'epoch': 0.04}) +[2026-07-26 19:51:18,463][starVLA.training.train_starvla][INFO] - Step 362, Loss: {'train/loss': 0.651421844959259, 'train/grad_norm_pre_clip': 6.754744052886963, 'timing/data': 0.00020826887339353561, 'timing/model': 0.45800334494560957, 'learning_rate/action_model': 9.876372526985295e-05, 'learning_rate/action_query_proj': 9.876372526985295e-05, 'learning_rate/base': 2.4690931317463238e-05, 'epoch': 0.04}) +[2026-07-26 19:51:24,276][starVLA.training.train_starvla][INFO] - Step 363, Loss: {'train/loss': 0.7517728805541992, 'train/grad_norm_pre_clip': 6.88525915145874, 'timing/data': 0.00018976489081978798, 'timing/model': 0.4576695691794157, 'learning_rate/action_model': 9.875691526419377e-05, 'learning_rate/action_query_proj': 9.875691526419377e-05, 'learning_rate/base': 2.4689228816048442e-05, 'epoch': 0.04}) +[2026-07-26 19:51:29,788][starVLA.training.train_starvla][INFO] - Step 364, Loss: {'train/loss': 0.9466621279716492, 'train/grad_norm_pre_clip': 7.600001335144043, 'timing/data': 0.00019440101459622383, 'timing/model': 0.45679018879309297, 'learning_rate/action_model': 9.875008679964492e-05, 'learning_rate/action_query_proj': 9.875008679964492e-05, 'learning_rate/base': 2.468752169991123e-05, 'epoch': 0.04}) +[2026-07-26 19:51:35,322][starVLA.training.train_starvla][INFO] - Step 365, Loss: {'train/loss': 0.6462671160697937, 'train/grad_norm_pre_clip': 7.197800159454346, 'timing/data': 0.00036768801510334015, 'timing/model': 0.4575573648326099, 'learning_rate/action_model': 9.874323987890218e-05, 'learning_rate/action_query_proj': 9.874323987890218e-05, 'learning_rate/base': 2.4685809969725546e-05, 'epoch': 0.04}) +[2026-07-26 19:51:40,858][starVLA.training.train_starvla][INFO] - Step 366, Loss: {'train/loss': 0.7196869850158691, 'train/grad_norm_pre_clip': 4.897592067718506, 'timing/data': 0.000260927714407444, 'timing/model': 0.46302170399576426, 'learning_rate/action_model': 9.873637450466862e-05, 'learning_rate/action_query_proj': 9.873637450466862e-05, 'learning_rate/base': 2.4684093626167155e-05, 'epoch': 0.04}) +[2026-07-26 19:51:46,406][starVLA.training.train_starvla][INFO] - Step 367, Loss: {'train/loss': 0.6166234016418457, 'train/grad_norm_pre_clip': 4.217376232147217, 'timing/data': 0.0002508540637791157, 'timing/model': 0.4638970592059195, 'learning_rate/action_model': 9.872949067965455e-05, 'learning_rate/action_query_proj': 9.872949067965455e-05, 'learning_rate/base': 2.4682372669913638e-05, 'epoch': 0.04}) +[2026-07-26 19:51:51,932][starVLA.training.train_starvla][INFO] - Step 368, Loss: {'train/loss': 0.7677968144416809, 'train/grad_norm_pre_clip': 6.353249549865723, 'timing/data': 0.00035267695784568787, 'timing/model': 0.4629629789851606, 'learning_rate/action_model': 9.872258840657762e-05, 'learning_rate/action_query_proj': 9.872258840657762e-05, 'learning_rate/base': 2.4680647101644405e-05, 'epoch': 0.04}) +[2026-07-26 19:51:57,503][starVLA.training.train_starvla][INFO] - Step 369, Loss: {'train/loss': 0.7379682660102844, 'train/grad_norm_pre_clip': 6.487619400024414, 'timing/data': 0.0002539791166782379, 'timing/model': 0.4645543433725834, 'learning_rate/action_model': 9.871566768816274e-05, 'learning_rate/action_query_proj': 9.871566768816274e-05, 'learning_rate/base': 2.4678916922040685e-05, 'epoch': 0.04}) +[2026-07-26 19:52:03,062][starVLA.training.train_starvla][INFO] - Step 370, Loss: {'train/loss': 0.7072237730026245, 'train/grad_norm_pre_clip': 5.48748254776001, 'timing/data': 0.00025510694831609726, 'timing/model': 0.46335853869095445, 'learning_rate/action_model': 9.870872852714209e-05, 'learning_rate/action_query_proj': 9.870872852714209e-05, 'learning_rate/base': 2.4677182131785522e-05, 'epoch': 0.04}) +[2026-07-26 19:52:08,602][starVLA.training.train_starvla][INFO] - Step 371, Loss: {'train/loss': 0.6663413643836975, 'train/grad_norm_pre_clip': 4.98321008682251, 'timing/data': 0.00020125601440668106, 'timing/model': 0.45758202113211155, 'learning_rate/action_model': 9.870177092625513e-05, 'learning_rate/action_query_proj': 9.870177092625513e-05, 'learning_rate/base': 2.4675442731563782e-05, 'epoch': 0.05}) +[2026-07-26 19:52:14,146][starVLA.training.train_starvla][INFO] - Step 372, Loss: {'train/loss': 0.8090575933456421, 'train/grad_norm_pre_clip': 5.064812183380127, 'timing/data': 0.00018836790695786476, 'timing/model': 0.4569855509325862, 'learning_rate/action_model': 9.869479488824861e-05, 'learning_rate/action_query_proj': 9.869479488824861e-05, 'learning_rate/base': 2.4673698722062152e-05, 'epoch': 0.05}) +[2026-07-26 19:52:19,691][starVLA.training.train_starvla][INFO] - Step 373, Loss: {'train/loss': 0.7066613435745239, 'train/grad_norm_pre_clip': 4.583524227142334, 'timing/data': 0.00019092392176389694, 'timing/model': 0.4575770730152726, 'learning_rate/action_model': 9.868780041587659e-05, 'learning_rate/action_query_proj': 9.868780041587659e-05, 'learning_rate/base': 2.4671950103969147e-05, 'epoch': 0.05}) +[2026-07-26 19:52:25,234][starVLA.training.train_starvla][INFO] - Step 374, Loss: {'train/loss': 0.8353607654571533, 'train/grad_norm_pre_clip': 4.219630718231201, 'timing/data': 0.00019186967983841896, 'timing/model': 0.4575322400778532, 'learning_rate/action_model': 9.868078751190035e-05, 'learning_rate/action_query_proj': 9.868078751190035e-05, 'learning_rate/base': 2.4670196877975087e-05, 'epoch': 0.05}) +[2026-07-26 19:52:30,812][starVLA.training.train_starvla][INFO] - Step 375, Loss: {'train/loss': 0.5943642854690552, 'train/grad_norm_pre_clip': 3.8940393924713135, 'timing/data': 0.00019622594118118286, 'timing/model': 0.456424109172076, 'learning_rate/action_model': 9.867375617908848e-05, 'learning_rate/action_query_proj': 9.867375617908848e-05, 'learning_rate/base': 2.466843904477212e-05, 'epoch': 0.05}) +[2026-07-26 19:52:36,374][starVLA.training.train_starvla][INFO] - Step 376, Loss: {'train/loss': 0.7304161190986633, 'train/grad_norm_pre_clip': 5.968082904815674, 'timing/data': 0.00019363593310117722, 'timing/model': 0.4575790846720338, 'learning_rate/action_model': 9.866670642021684e-05, 'learning_rate/action_query_proj': 9.866670642021684e-05, 'learning_rate/base': 2.466667660505421e-05, 'epoch': 0.05}) +[2026-07-26 19:52:41,940][starVLA.training.train_starvla][INFO] - Step 377, Loss: {'train/loss': 0.6631136536598206, 'train/grad_norm_pre_clip': 4.455073833465576, 'timing/data': 0.00018533598631620407, 'timing/model': 0.45688814716413617, 'learning_rate/action_model': 9.865963823806857e-05, 'learning_rate/action_query_proj': 9.865963823806857e-05, 'learning_rate/base': 2.4664909559517144e-05, 'epoch': 0.05}) +[2026-07-26 19:52:47,503][starVLA.training.train_starvla][INFO] - Step 378, Loss: {'train/loss': 0.6315189599990845, 'train/grad_norm_pre_clip': 3.643921136856079, 'timing/data': 0.00020593497902154922, 'timing/model': 0.4613904277794063, 'learning_rate/action_model': 9.865255163543406e-05, 'learning_rate/action_query_proj': 9.865255163543406e-05, 'learning_rate/base': 2.4663137908858515e-05, 'epoch': 0.05}) +[2026-07-26 19:52:53,355][starVLA.training.train_starvla][INFO] - Step 379, Loss: {'train/loss': 0.7144477367401123, 'train/grad_norm_pre_clip': 5.14108943939209, 'timing/data': 0.00020254496484994888, 'timing/model': 0.46240366669371724, 'learning_rate/action_model': 9.864544661511101e-05, 'learning_rate/action_query_proj': 9.864544661511101e-05, 'learning_rate/base': 2.4661361653777753e-05, 'epoch': 0.05}) +[2026-07-26 19:52:58,944][starVLA.training.train_starvla][INFO] - Step 380, Loss: {'train/loss': 0.6964002847671509, 'train/grad_norm_pre_clip': 7.0081658363342285, 'timing/data': 0.00018078088760375977, 'timing/model': 0.464141545817256, 'learning_rate/action_model': 9.863832317990436e-05, 'learning_rate/action_query_proj': 9.863832317990436e-05, 'learning_rate/base': 2.465958079497609e-05, 'epoch': 0.05}) +[2026-07-26 19:53:04,547][starVLA.training.train_starvla][INFO] - Step 381, Loss: {'train/loss': 0.742119550704956, 'train/grad_norm_pre_clip': 6.7996978759765625, 'timing/data': 0.00018975324928760529, 'timing/model': 0.46385544817894697, 'learning_rate/action_model': 9.863118133262632e-05, 'learning_rate/action_query_proj': 9.863118133262632e-05, 'learning_rate/base': 2.465779533315658e-05, 'epoch': 0.05}) +[2026-07-26 19:53:10,130][starVLA.training.train_starvla][INFO] - Step 382, Loss: {'train/loss': 0.7110801339149475, 'train/grad_norm_pre_clip': 6.42863655090332, 'timing/data': 0.00020588375627994537, 'timing/model': 0.46320975199341774, 'learning_rate/action_model': 9.862402107609638e-05, 'learning_rate/action_query_proj': 9.862402107609638e-05, 'learning_rate/base': 2.4656005269024094e-05, 'epoch': 0.05}) +[2026-07-26 19:53:15,697][starVLA.training.train_starvla][INFO] - Step 383, Loss: {'train/loss': 0.5904534459114075, 'train/grad_norm_pre_clip': 2.5392961502075195, 'timing/data': 0.00019656727090477943, 'timing/model': 0.46227505803108215, 'learning_rate/action_model': 9.86168424131413e-05, 'learning_rate/action_query_proj': 9.86168424131413e-05, 'learning_rate/base': 2.4654210603285325e-05, 'epoch': 0.05}) +[2026-07-26 19:53:21,270][starVLA.training.train_starvla][INFO] - Step 384, Loss: {'train/loss': 0.6876488327980042, 'train/grad_norm_pre_clip': 5.36973237991333, 'timing/data': 0.00019411370158195496, 'timing/model': 0.4613934699445963, 'learning_rate/action_model': 9.860964534659511e-05, 'learning_rate/action_query_proj': 9.860964534659511e-05, 'learning_rate/base': 2.4652411336648777e-05, 'epoch': 0.05}) +[2026-07-26 19:53:26,863][starVLA.training.train_starvla][INFO] - Step 385, Loss: {'train/loss': 0.8152307271957397, 'train/grad_norm_pre_clip': 4.7481465339660645, 'timing/data': 0.00018553296104073524, 'timing/model': 0.4661686811596155, 'learning_rate/action_model': 9.86024298792991e-05, 'learning_rate/action_query_proj': 9.86024298792991e-05, 'learning_rate/base': 2.4650607469824774e-05, 'epoch': 0.05}) +[2026-07-26 19:53:32,437][starVLA.training.train_starvla][INFO] - Step 386, Loss: {'train/loss': 0.6797654628753662, 'train/grad_norm_pre_clip': 6.206708908081055, 'timing/data': 0.0002002180553972721, 'timing/model': 0.4640239239670336, 'learning_rate/action_model': 9.85951960141018e-05, 'learning_rate/action_query_proj': 9.85951960141018e-05, 'learning_rate/base': 2.464879900352545e-05, 'epoch': 0.05}) +[2026-07-26 19:53:38,016][starVLA.training.train_starvla][INFO] - Step 387, Loss: {'train/loss': 0.7777683138847351, 'train/grad_norm_pre_clip': 6.6957831382751465, 'timing/data': 0.0003685988485813141, 'timing/model': 0.46267809392884374, 'learning_rate/action_model': 9.858794375385903e-05, 'learning_rate/action_query_proj': 9.858794375385903e-05, 'learning_rate/base': 2.464698593846476e-05, 'epoch': 0.05}) +[2026-07-26 19:53:43,659][starVLA.training.train_starvla][INFO] - Step 388, Loss: {'train/loss': 0.6889655590057373, 'train/grad_norm_pre_clip': 4.224343776702881, 'timing/data': 0.000186883844435215, 'timing/model': 0.4573470982722938, 'learning_rate/action_model': 9.85806731014339e-05, 'learning_rate/action_query_proj': 9.85806731014339e-05, 'learning_rate/base': 2.4645168275358476e-05, 'epoch': 0.05}) +[2026-07-26 19:53:49,176][starVLA.training.train_starvla][INFO] - Step 389, Loss: {'train/loss': 0.7117806077003479, 'train/grad_norm_pre_clip': 4.353118419647217, 'timing/data': 0.0001893872395157814, 'timing/model': 0.4563086349517107, 'learning_rate/action_model': 9.857338405969672e-05, 'learning_rate/action_query_proj': 9.857338405969672e-05, 'learning_rate/base': 2.464334601492418e-05, 'epoch': 0.05}) +[2026-07-26 19:53:54,713][starVLA.training.train_starvla][INFO] - Step 390, Loss: {'train/loss': 0.7241919040679932, 'train/grad_norm_pre_clip': 5.669791221618652, 'timing/data': 0.0001805550418794155, 'timing/model': 0.45710811484605074, 'learning_rate/action_model': 9.856607663152508e-05, 'learning_rate/action_query_proj': 9.856607663152508e-05, 'learning_rate/base': 2.464151915788127e-05, 'epoch': 0.05}) +[2026-07-26 19:54:00,242][starVLA.training.train_starvla][INFO] - Step 391, Loss: {'train/loss': 0.7485756874084473, 'train/grad_norm_pre_clip': 8.450944900512695, 'timing/data': 0.00019351672381162643, 'timing/model': 0.46023341501131654, 'learning_rate/action_model': 9.855875081980387e-05, 'learning_rate/action_query_proj': 9.855875081980387e-05, 'learning_rate/base': 2.4639687704950968e-05, 'epoch': 0.05}) +[2026-07-26 19:54:06,013][starVLA.training.train_starvla][INFO] - Step 392, Loss: {'train/loss': 0.7597609758377075, 'train/grad_norm_pre_clip': 8.794286727905273, 'timing/data': 0.00018486659973859787, 'timing/model': 0.4563534762710333, 'learning_rate/action_model': 9.855140662742517e-05, 'learning_rate/action_query_proj': 9.855140662742517e-05, 'learning_rate/base': 2.4637851656856293e-05, 'epoch': 0.05}) +[2026-07-26 19:54:11,543][starVLA.training.train_starvla][INFO] - Step 393, Loss: {'train/loss': 0.7881100177764893, 'train/grad_norm_pre_clip': 7.060456275939941, 'timing/data': 0.00018673157319426537, 'timing/model': 0.456694602034986, 'learning_rate/action_model': 9.854404405728837e-05, 'learning_rate/action_query_proj': 9.854404405728837e-05, 'learning_rate/base': 2.4636011014322093e-05, 'epoch': 0.05}) +[2026-07-26 19:54:17,318][starVLA.training.train_starvla][INFO] - Step 394, Loss: {'train/loss': 0.7738734483718872, 'train/grad_norm_pre_clip': 8.797563552856445, 'timing/data': 0.00018855417147278786, 'timing/model': 0.718504382763058, 'learning_rate/action_model': 9.85366631123001e-05, 'learning_rate/action_query_proj': 9.85366631123001e-05, 'learning_rate/base': 2.4634165778075026e-05, 'epoch': 0.05}) +[2026-07-26 19:54:22,863][starVLA.training.train_starvla][INFO] - Step 395, Loss: {'train/loss': 0.7485760450363159, 'train/grad_norm_pre_clip': 5.125047206878662, 'timing/data': 0.00018781796097755432, 'timing/model': 0.4572078511118889, 'learning_rate/action_model': 9.852926379537421e-05, 'learning_rate/action_query_proj': 9.852926379537421e-05, 'learning_rate/base': 2.4632315948843552e-05, 'epoch': 0.05}) +[2026-07-26 19:54:28,385][starVLA.training.train_starvla][INFO] - Step 396, Loss: {'train/loss': 0.6116518974304199, 'train/grad_norm_pre_clip': 4.277072429656982, 'timing/data': 0.00018365588039159775, 'timing/model': 0.45708320988342166, 'learning_rate/action_model': 9.852184610943185e-05, 'learning_rate/action_query_proj': 9.852184610943185e-05, 'learning_rate/base': 2.4630461527357964e-05, 'epoch': 0.05}) +[2026-07-26 19:54:33,930][starVLA.training.train_starvla][INFO] - Step 397, Loss: {'train/loss': 0.6534289121627808, 'train/grad_norm_pre_clip': 7.2503662109375, 'timing/data': 0.00019254814833402634, 'timing/model': 0.45737418811768293, 'learning_rate/action_model': 9.851441005740144e-05, 'learning_rate/action_query_proj': 9.851441005740144e-05, 'learning_rate/base': 2.462860251435036e-05, 'epoch': 0.05}) +[2026-07-26 19:54:39,499][starVLA.training.train_starvla][INFO] - Step 398, Loss: {'train/loss': 0.6665515899658203, 'train/grad_norm_pre_clip': 3.5752999782562256, 'timing/data': 0.0002028173767030239, 'timing/model': 0.4571234658360481, 'learning_rate/action_model': 9.850695564221858e-05, 'learning_rate/action_query_proj': 9.850695564221858e-05, 'learning_rate/base': 2.4626738910554645e-05, 'epoch': 0.05}) +[2026-07-26 19:54:45,061][starVLA.training.train_starvla][INFO] - Step 399, Loss: {'train/loss': 0.6675821542739868, 'train/grad_norm_pre_clip': 3.9348649978637695, 'timing/data': 0.00017891312018036842, 'timing/model': 0.45645218808203936, 'learning_rate/action_model': 9.849948286682615e-05, 'learning_rate/action_query_proj': 9.849948286682615e-05, 'learning_rate/base': 2.4624870716706537e-05, 'epoch': 0.05}) +[2026-07-26 19:54:50,627][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 400 +[2026-07-26 19:54:50,627][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 400 +[2026-07-26 19:54:50,628][starVLA.training.train_starvla][INFO] - Step 400, Loss: {'train/loss': 0.7260534167289734, 'train/grad_norm_pre_clip': 8.309850692749023, 'timing/data': 0.00019328389316797256, 'timing/model': 0.45703034987673163, 'learning_rate/action_model': 9.849199173417429e-05, 'learning_rate/action_query_proj': 9.849199173417429e-05, 'learning_rate/base': 2.4622997933543573e-05, 'epoch': 0.05}) +[2026-07-26 19:54:56,173][starVLA.training.train_starvla][INFO] - Step 401, Loss: {'train/loss': 0.6841795444488525, 'train/grad_norm_pre_clip': 4.9493865966796875, 'timing/data': 0.00018683495000004768, 'timing/model': 0.4574546981602907, 'learning_rate/action_model': 9.84844822472204e-05, 'learning_rate/action_query_proj': 9.84844822472204e-05, 'learning_rate/base': 2.46211205618051e-05, 'epoch': 0.05}) +[2026-07-26 19:55:01,709][starVLA.training.train_starvla][INFO] - Step 402, Loss: {'train/loss': 0.7855923771858215, 'train/grad_norm_pre_clip': 5.229983329772949, 'timing/data': 0.0001880759373307228, 'timing/model': 0.45644642412662506, 'learning_rate/action_model': 9.847695440892908e-05, 'learning_rate/action_query_proj': 9.847695440892908e-05, 'learning_rate/base': 2.461923860223227e-05, 'epoch': 0.05}) +[2026-07-26 19:55:07,239][starVLA.training.train_starvla][INFO] - Step 403, Loss: {'train/loss': 0.7846868634223938, 'train/grad_norm_pre_clip': 4.848992824554443, 'timing/data': 0.00019024871289730072, 'timing/model': 0.4566222671419382, 'learning_rate/action_model': 9.846940822227222e-05, 'learning_rate/action_query_proj': 9.846940822227222e-05, 'learning_rate/base': 2.4617352055568056e-05, 'epoch': 0.05}) +[2026-07-26 19:55:12,795][starVLA.training.train_starvla][INFO] - Step 404, Loss: {'train/loss': 0.5747742652893066, 'train/grad_norm_pre_clip': 3.3999061584472656, 'timing/data': 0.0002013491466641426, 'timing/model': 0.45724333822727203, 'learning_rate/action_model': 9.846184369022893e-05, 'learning_rate/action_query_proj': 9.846184369022893e-05, 'learning_rate/base': 2.4615460922557233e-05, 'epoch': 0.05}) +[2026-07-26 19:55:18,336][starVLA.training.train_starvla][INFO] - Step 405, Loss: {'train/loss': 0.8372064232826233, 'train/grad_norm_pre_clip': 6.464589595794678, 'timing/data': 0.0002611679956316948, 'timing/model': 0.45696314610540867, 'learning_rate/action_model': 9.845426081578554e-05, 'learning_rate/action_query_proj': 9.845426081578554e-05, 'learning_rate/base': 2.4613565203946386e-05, 'epoch': 0.05}) +[2026-07-26 19:55:23,878][starVLA.training.train_starvla][INFO] - Step 406, Loss: {'train/loss': 0.5687676072120667, 'train/grad_norm_pre_clip': 3.80474591255188, 'timing/data': 0.00019203685224056244, 'timing/model': 0.4575365171767771, 'learning_rate/action_model': 9.844665960193569e-05, 'learning_rate/action_query_proj': 9.844665960193569e-05, 'learning_rate/base': 2.4611664900483923e-05, 'epoch': 0.05}) +[2026-07-26 19:55:29,418][starVLA.training.train_starvla][INFO] - Step 407, Loss: {'train/loss': 0.75718754529953, 'train/grad_norm_pre_clip': 5.866905212402344, 'timing/data': 0.00018269987776875496, 'timing/model': 0.4569014268927276, 'learning_rate/action_model': 9.84390400516802e-05, 'learning_rate/action_query_proj': 9.84390400516802e-05, 'learning_rate/base': 2.460976001292005e-05, 'epoch': 0.05}) +[2026-07-26 19:55:34,957][starVLA.training.train_starvla][INFO] - Step 408, Loss: {'train/loss': 0.6434512138366699, 'train/grad_norm_pre_clip': 4.925164222717285, 'timing/data': 0.00018574530258774757, 'timing/model': 0.4604157591238618, 'learning_rate/action_model': 9.843140216802716e-05, 'learning_rate/action_query_proj': 9.843140216802716e-05, 'learning_rate/base': 2.460785054200679e-05, 'epoch': 0.05}) +[2026-07-26 19:55:40,493][starVLA.training.train_starvla][INFO] - Step 409, Loss: {'train/loss': 0.607806384563446, 'train/grad_norm_pre_clip': 5.19663143157959, 'timing/data': 0.00018943194299936295, 'timing/model': 0.45719898911193013, 'learning_rate/action_model': 9.842374595399187e-05, 'learning_rate/action_query_proj': 9.842374595399187e-05, 'learning_rate/base': 2.4605936488497968e-05, 'epoch': 0.05}) +[2026-07-26 19:55:46,021][starVLA.training.train_starvla][INFO] - Step 410, Loss: {'train/loss': 0.7622593641281128, 'train/grad_norm_pre_clip': 4.175610542297363, 'timing/data': 0.00018796976655721664, 'timing/model': 0.457579487003386, 'learning_rate/action_model': 9.841607141259689e-05, 'learning_rate/action_query_proj': 9.841607141259689e-05, 'learning_rate/base': 2.4604017853149223e-05, 'epoch': 0.05}) +[2026-07-26 19:55:51,498][starVLA.training.train_starvla][INFO] - Step 411, Loss: {'train/loss': 0.5234305262565613, 'train/grad_norm_pre_clip': 5.185076713562012, 'timing/data': 0.00018921773880720139, 'timing/model': 0.46053634816780686, 'learning_rate/action_model': 9.840837854687199e-05, 'learning_rate/action_query_proj': 9.840837854687199e-05, 'learning_rate/base': 2.4602094636717997e-05, 'epoch': 0.05}) +[2026-07-26 19:55:56,976][starVLA.training.train_starvla][INFO] - Step 412, Loss: {'train/loss': 0.8370209336280823, 'train/grad_norm_pre_clip': 8.938655853271484, 'timing/data': 0.0001831119880080223, 'timing/model': 0.4568827380426228, 'learning_rate/action_model': 9.840066735985422e-05, 'learning_rate/action_query_proj': 9.840066735985422e-05, 'learning_rate/base': 2.4600166839963555e-05, 'epoch': 0.05}) +[2026-07-26 19:56:02,501][starVLA.training.train_starvla][INFO] - Step 413, Loss: {'train/loss': 0.627278208732605, 'train/grad_norm_pre_clip': 3.1188108921051025, 'timing/data': 0.00019349902868270874, 'timing/model': 0.45737528475001454, 'learning_rate/action_model': 9.839293785458783e-05, 'learning_rate/action_query_proj': 9.839293785458783e-05, 'learning_rate/base': 2.4598234463646957e-05, 'epoch': 0.05}) +[2026-07-26 19:56:08,006][starVLA.training.train_starvla][INFO] - Step 414, Loss: {'train/loss': 0.8281654119491577, 'train/grad_norm_pre_clip': 5.084421634674072, 'timing/data': 0.0001950669102370739, 'timing/model': 0.45813791966065764, 'learning_rate/action_model': 9.838519003412427e-05, 'learning_rate/action_query_proj': 9.838519003412427e-05, 'learning_rate/base': 2.459629750853107e-05, 'epoch': 0.05}) +[2026-07-26 19:56:13,554][starVLA.training.train_starvla][INFO] - Step 415, Loss: {'train/loss': 0.6401980519294739, 'train/grad_norm_pre_clip': 5.106070041656494, 'timing/data': 0.00018546683713793755, 'timing/model': 0.4583562589250505, 'learning_rate/action_model': 9.837742390152232e-05, 'learning_rate/action_query_proj': 9.837742390152232e-05, 'learning_rate/base': 2.459435597538058e-05, 'epoch': 0.05}) +[2026-07-26 19:56:19,085][starVLA.training.train_starvla][INFO] - Step 416, Loss: {'train/loss': 0.6169925332069397, 'train/grad_norm_pre_clip': 5.080974102020264, 'timing/data': 0.0001876060850918293, 'timing/model': 0.45733960438519716, 'learning_rate/action_model': 9.836963945984786e-05, 'learning_rate/action_query_proj': 9.836963945984786e-05, 'learning_rate/base': 2.4592409864961965e-05, 'epoch': 0.05}) +[2026-07-26 19:56:24,640][starVLA.training.train_starvla][INFO] - Step 417, Loss: {'train/loss': 0.6787603497505188, 'train/grad_norm_pre_clip': 6.025295734405518, 'timing/data': 0.00019734026864171028, 'timing/model': 0.46982781309634447, 'learning_rate/action_model': 9.83618367121741e-05, 'learning_rate/action_query_proj': 9.83618367121741e-05, 'learning_rate/base': 2.4590459178043526e-05, 'epoch': 0.05}) +[2026-07-26 19:56:30,251][starVLA.training.train_starvla][INFO] - Step 418, Loss: {'train/loss': 0.7435041666030884, 'train/grad_norm_pre_clip': 4.5172200202941895, 'timing/data': 0.00018983613699674606, 'timing/model': 0.46774607710540295, 'learning_rate/action_model': 9.835401566158145e-05, 'learning_rate/action_query_proj': 9.835401566158145e-05, 'learning_rate/base': 2.4588503915395362e-05, 'epoch': 0.05}) +[2026-07-26 19:56:36,094][starVLA.training.train_starvla][INFO] - Step 419, Loss: {'train/loss': 0.5650205016136169, 'train/grad_norm_pre_clip': 5.206226825714111, 'timing/data': 0.00018471712246537209, 'timing/model': 0.7160633662715554, 'learning_rate/action_model': 9.834617631115751e-05, 'learning_rate/action_query_proj': 9.834617631115751e-05, 'learning_rate/base': 2.4586544077789378e-05, 'epoch': 0.05}) +[2026-07-26 19:56:41,691][starVLA.training.train_starvla][INFO] - Step 420, Loss: {'train/loss': 0.7866452932357788, 'train/grad_norm_pre_clip': 6.194782733917236, 'timing/data': 0.0001882500946521759, 'timing/model': 0.4709176467731595, 'learning_rate/action_model': 9.833831866399716e-05, 'learning_rate/action_query_proj': 9.833831866399716e-05, 'learning_rate/base': 2.458457966599929e-05, 'epoch': 0.05}) +[2026-07-26 19:56:47,296][starVLA.training.train_starvla][INFO] - Step 421, Loss: {'train/loss': 0.7759756445884705, 'train/grad_norm_pre_clip': 7.36761999130249, 'timing/data': 0.00018240977078676224, 'timing/model': 0.47126301610842347, 'learning_rate/action_model': 9.833044272320245e-05, 'learning_rate/action_query_proj': 9.833044272320245e-05, 'learning_rate/base': 2.4582610680800612e-05, 'epoch': 0.05}) +[2026-07-26 19:56:52,888][starVLA.training.train_starvla][INFO] - Step 422, Loss: {'train/loss': 0.6770156025886536, 'train/grad_norm_pre_clip': 3.827613115310669, 'timing/data': 0.00018724612891674042, 'timing/model': 0.47577145090326667, 'learning_rate/action_model': 9.832254849188268e-05, 'learning_rate/action_query_proj': 9.832254849188268e-05, 'learning_rate/base': 2.458063712297067e-05, 'epoch': 0.05}) +[2026-07-26 19:56:58,484][starVLA.training.train_starvla][INFO] - Step 423, Loss: {'train/loss': 0.779514491558075, 'train/grad_norm_pre_clip': 5.240328311920166, 'timing/data': 0.00018076179549098015, 'timing/model': 0.47801556065678596, 'learning_rate/action_model': 9.831463597315437e-05, 'learning_rate/action_query_proj': 9.831463597315437e-05, 'learning_rate/base': 2.4578658993288592e-05, 'epoch': 0.05}) +[2026-07-26 19:57:04,088][starVLA.training.train_starvla][INFO] - Step 424, Loss: {'train/loss': 0.9013649225234985, 'train/grad_norm_pre_clip': 6.077177047729492, 'timing/data': 0.00019625388085842133, 'timing/model': 0.46997051080688834, 'learning_rate/action_model': 9.830670517014126e-05, 'learning_rate/action_query_proj': 9.830670517014126e-05, 'learning_rate/base': 2.4576676292535316e-05, 'epoch': 0.05}) +[2026-07-26 19:57:09,682][starVLA.training.train_starvla][INFO] - Step 425, Loss: {'train/loss': 0.6417883634567261, 'train/grad_norm_pre_clip': 4.328220367431641, 'timing/data': 0.0001973710022866726, 'timing/model': 0.4720028047449887, 'learning_rate/action_model': 9.82987560859743e-05, 'learning_rate/action_query_proj': 9.82987560859743e-05, 'learning_rate/base': 2.4574689021493577e-05, 'epoch': 0.05}) +[2026-07-26 19:57:15,230][starVLA.training.train_starvla][INFO] - Step 426, Loss: {'train/loss': 0.7855199575424194, 'train/grad_norm_pre_clip': 3.1080522537231445, 'timing/data': 0.00019204523414373398, 'timing/model': 0.47130425786599517, 'learning_rate/action_model': 9.829078872379169e-05, 'learning_rate/action_query_proj': 9.829078872379169e-05, 'learning_rate/base': 2.4572697180947923e-05, 'epoch': 0.05}) +[2026-07-26 19:57:20,754][starVLA.training.train_starvla][INFO] - Step 427, Loss: {'train/loss': 0.6243571043014526, 'train/grad_norm_pre_clip': 7.738848686218262, 'timing/data': 0.0001870580017566681, 'timing/model': 0.46876814402639866, 'learning_rate/action_model': 9.828280308673878e-05, 'learning_rate/action_query_proj': 9.828280308673878e-05, 'learning_rate/base': 2.4570700771684696e-05, 'epoch': 0.05}) +[2026-07-26 19:57:26,367][starVLA.training.train_starvla][INFO] - Step 428, Loss: {'train/loss': 0.7766290307044983, 'train/grad_norm_pre_clip': 9.286003112792969, 'timing/data': 0.0001890929415822029, 'timing/model': 0.4721648539416492, 'learning_rate/action_model': 9.82747991779682e-05, 'learning_rate/action_query_proj': 9.82747991779682e-05, 'learning_rate/base': 2.456869979449205e-05, 'epoch': 0.05}) +[2026-07-26 19:57:31,939][starVLA.training.train_starvla][INFO] - Step 429, Loss: {'train/loss': 0.7601742744445801, 'train/grad_norm_pre_clip': 6.415734767913818, 'timing/data': 0.0001936289481818676, 'timing/model': 0.4689475568011403, 'learning_rate/action_model': 9.826677700063977e-05, 'learning_rate/action_query_proj': 9.826677700063977e-05, 'learning_rate/base': 2.4566694250159943e-05, 'epoch': 0.05}) +[2026-07-26 19:57:37,524][starVLA.training.train_starvla][INFO] - Step 430, Loss: {'train/loss': 0.7739571332931519, 'train/grad_norm_pre_clip': 4.69459867477417, 'timing/data': 0.00018510594964027405, 'timing/model': 0.4687726655974984, 'learning_rate/action_model': 9.825873655792047e-05, 'learning_rate/action_query_proj': 9.825873655792047e-05, 'learning_rate/base': 2.4564684139480118e-05, 'epoch': 0.05}) +[2026-07-26 19:57:43,112][starVLA.training.train_starvla][INFO] - Step 431, Loss: {'train/loss': 0.6633681654930115, 'train/grad_norm_pre_clip': 2.9519784450531006, 'timing/data': 0.00018613087013363838, 'timing/model': 0.4700758531689644, 'learning_rate/action_model': 9.825067785298459e-05, 'learning_rate/action_query_proj': 9.825067785298459e-05, 'learning_rate/base': 2.4562669463246147e-05, 'epoch': 0.05}) +[2026-07-26 19:57:48,656][starVLA.training.train_starvla][INFO] - Step 432, Loss: {'train/loss': 0.6506129503250122, 'train/grad_norm_pre_clip': 5.419148921966553, 'timing/data': 0.00018960284069180489, 'timing/model': 0.47114854771643877, 'learning_rate/action_model': 9.824260088901355e-05, 'learning_rate/action_query_proj': 9.824260088901355e-05, 'learning_rate/base': 2.456065022225339e-05, 'epoch': 0.05}) +[2026-07-26 19:57:54,223][starVLA.training.train_starvla][INFO] - Step 433, Loss: {'train/loss': 0.6629709005355835, 'train/grad_norm_pre_clip': 5.876334190368652, 'timing/data': 0.0001864749938249588, 'timing/model': 0.4745980962179601, 'learning_rate/action_model': 9.823450566919606e-05, 'learning_rate/action_query_proj': 9.823450566919606e-05, 'learning_rate/base': 2.4558626417299015e-05, 'epoch': 0.05}) +[2026-07-26 19:57:59,796][starVLA.training.train_starvla][INFO] - Step 434, Loss: {'train/loss': 0.7102199196815491, 'train/grad_norm_pre_clip': 5.166601657867432, 'timing/data': 0.00018862495198845863, 'timing/model': 0.4784743506461382, 'learning_rate/action_model': 9.82263921967279e-05, 'learning_rate/action_query_proj': 9.82263921967279e-05, 'learning_rate/base': 2.4556598049181975e-05, 'epoch': 0.05}) +[2026-07-26 19:58:05,352][starVLA.training.train_starvla][INFO] - Step 435, Loss: {'train/loss': 0.8671703338623047, 'train/grad_norm_pre_clip': 7.233335018157959, 'timing/data': 0.00019575189799070358, 'timing/model': 0.4693245002999902, 'learning_rate/action_model': 9.821826047481222e-05, 'learning_rate/action_query_proj': 9.821826047481222e-05, 'learning_rate/base': 2.4554565118703056e-05, 'epoch': 0.05}) +[2026-07-26 19:58:10,968][starVLA.training.train_starvla][INFO] - Step 436, Loss: {'train/loss': 0.6532626748085022, 'train/grad_norm_pre_clip': 3.7986743450164795, 'timing/data': 0.0001999461092054844, 'timing/model': 0.46896276623010635, 'learning_rate/action_model': 9.821011050665924e-05, 'learning_rate/action_query_proj': 9.821011050665924e-05, 'learning_rate/base': 2.455252762666481e-05, 'epoch': 0.05}) +[2026-07-26 19:58:16,529][starVLA.training.train_starvla][INFO] - Step 437, Loss: {'train/loss': 0.7217891216278076, 'train/grad_norm_pre_clip': 6.474768161773682, 'timing/data': 0.000233466736972332, 'timing/model': 0.4771345821209252, 'learning_rate/action_model': 9.820194229548645e-05, 'learning_rate/action_query_proj': 9.820194229548645e-05, 'learning_rate/base': 2.4550485573871612e-05, 'epoch': 0.05}) +[2026-07-26 19:58:22,377][starVLA.training.train_starvla][INFO] - Step 438, Loss: {'train/loss': 0.7442903518676758, 'train/grad_norm_pre_clip': 7.472234725952148, 'timing/data': 0.0002098088152706623, 'timing/model': 0.48192591965198517, 'learning_rate/action_model': 9.819375584451857e-05, 'learning_rate/action_query_proj': 9.819375584451857e-05, 'learning_rate/base': 2.454843896112964e-05, 'epoch': 0.05}) +[2026-07-26 19:58:28,210][starVLA.training.train_starvla][INFO] - Step 439, Loss: {'train/loss': 0.6664678454399109, 'train/grad_norm_pre_clip': 6.035487651824951, 'timing/data': 0.00018793903291225433, 'timing/model': 0.4713876908645034, 'learning_rate/action_model': 9.818555115698742e-05, 'learning_rate/action_query_proj': 9.818555115698742e-05, 'learning_rate/base': 2.4546387789246856e-05, 'epoch': 0.05}) +[2026-07-26 19:58:34,058][starVLA.training.train_starvla][INFO] - Step 440, Loss: {'train/loss': 0.789255678653717, 'train/grad_norm_pre_clip': 6.326132297515869, 'timing/data': 0.00018688989803195, 'timing/model': 0.4722718158736825, 'learning_rate/action_model': 9.817732823613213e-05, 'learning_rate/action_query_proj': 9.817732823613213e-05, 'learning_rate/base': 2.4544332059033032e-05, 'epoch': 0.05}) +[2026-07-26 19:58:39,610][starVLA.training.train_starvla][INFO] - Step 441, Loss: {'train/loss': 0.6826477646827698, 'train/grad_norm_pre_clip': 5.74916410446167, 'timing/data': 0.00019123777747154236, 'timing/model': 0.46349149104207754, 'learning_rate/action_model': 9.816908708519896e-05, 'learning_rate/action_query_proj': 9.816908708519896e-05, 'learning_rate/base': 2.454227177129974e-05, 'epoch': 0.05}) +[2026-07-26 19:58:45,155][starVLA.training.train_starvla][INFO] - Step 442, Loss: {'train/loss': 0.786980152130127, 'train/grad_norm_pre_clip': 10.65489387512207, 'timing/data': 0.0001845499500632286, 'timing/model': 0.46375658037140965, 'learning_rate/action_model': 9.816082770744137e-05, 'learning_rate/action_query_proj': 9.816082770744137e-05, 'learning_rate/base': 2.4540206926860343e-05, 'epoch': 0.05}) +[2026-07-26 19:58:50,690][starVLA.training.train_starvla][INFO] - Step 443, Loss: {'train/loss': 0.7005178928375244, 'train/grad_norm_pre_clip': 6.822446823120117, 'timing/data': 0.00018586404621601105, 'timing/model': 0.4572949749417603, 'learning_rate/action_model': 9.815255010612007e-05, 'learning_rate/action_query_proj': 9.815255010612007e-05, 'learning_rate/base': 2.4538137526530018e-05, 'epoch': 0.05}) +[2026-07-26 19:58:56,236][starVLA.training.train_starvla][INFO] - Step 444, Loss: {'train/loss': 0.829230010509491, 'train/grad_norm_pre_clip': 8.136579513549805, 'timing/data': 0.0001851329579949379, 'timing/model': 0.4562320508994162, 'learning_rate/action_model': 9.814425428450289e-05, 'learning_rate/action_query_proj': 9.814425428450289e-05, 'learning_rate/base': 2.4536063571125723e-05, 'epoch': 0.05}) +[2026-07-26 19:59:01,800][starVLA.training.train_starvla][INFO] - Step 445, Loss: {'train/loss': 0.6926564574241638, 'train/grad_norm_pre_clip': 4.920053482055664, 'timing/data': 0.00018348824232816696, 'timing/model': 0.46144710294902325, 'learning_rate/action_model': 9.81359402458649e-05, 'learning_rate/action_query_proj': 9.81359402458649e-05, 'learning_rate/base': 2.4533985061466225e-05, 'epoch': 0.05}) +[2026-07-26 19:59:07,352][starVLA.training.train_starvla][INFO] - Step 446, Loss: {'train/loss': 0.6107243299484253, 'train/grad_norm_pre_clip': 6.553524494171143, 'timing/data': 0.0001883343793451786, 'timing/model': 0.46261377492919564, 'learning_rate/action_model': 9.812760799348835e-05, 'learning_rate/action_query_proj': 9.812760799348835e-05, 'learning_rate/base': 2.4531901998372088e-05, 'epoch': 0.05}) +[2026-07-26 19:59:12,871][starVLA.training.train_starvla][INFO] - Step 447, Loss: {'train/loss': 0.6453707218170166, 'train/grad_norm_pre_clip': 6.196455478668213, 'timing/data': 0.0001834542490541935, 'timing/model': 0.46166519820690155, 'learning_rate/action_model': 9.811925753066269e-05, 'learning_rate/action_query_proj': 9.811925753066269e-05, 'learning_rate/base': 2.4529814382665672e-05, 'epoch': 0.05}) +[2026-07-26 19:59:18,376][starVLA.training.train_starvla][INFO] - Step 448, Loss: {'train/loss': 0.7074288725852966, 'train/grad_norm_pre_clip': 6.087045669555664, 'timing/data': 0.00018331175670027733, 'timing/model': 0.4603443816304207, 'learning_rate/action_model': 9.811088886068454e-05, 'learning_rate/action_query_proj': 9.811088886068454e-05, 'learning_rate/base': 2.4527722215171135e-05, 'epoch': 0.05}) +[2026-07-26 19:59:23,928][starVLA.training.train_starvla][INFO] - Step 449, Loss: {'train/loss': 0.7422665953636169, 'train/grad_norm_pre_clip': 4.574645519256592, 'timing/data': 0.00019122101366519928, 'timing/model': 0.4569958350621164, 'learning_rate/action_model': 9.810250198685774e-05, 'learning_rate/action_query_proj': 9.810250198685774e-05, 'learning_rate/base': 2.4525625496714435e-05, 'epoch': 0.05}) +[2026-07-26 19:59:29,469][starVLA.training.train_starvla][INFO] - Step 450, Loss: {'train/loss': 0.7355334758758545, 'train/grad_norm_pre_clip': 5.568721771240234, 'timing/data': 0.00018631992861628532, 'timing/model': 0.45719522703439, 'learning_rate/action_model': 9.809409691249328e-05, 'learning_rate/action_query_proj': 9.809409691249328e-05, 'learning_rate/base': 2.452352422812332e-05, 'epoch': 0.05}) +[2026-07-26 19:59:34,945][starVLA.training.train_starvla][INFO] - Step 451, Loss: {'train/loss': 0.7431639432907104, 'train/grad_norm_pre_clip': 3.245417833328247, 'timing/data': 0.00018875906243920326, 'timing/model': 0.4568035448901355, 'learning_rate/action_model': 9.808567364090932e-05, 'learning_rate/action_query_proj': 9.808567364090932e-05, 'learning_rate/base': 2.452141841022733e-05, 'epoch': 0.05}) +[2026-07-26 19:59:40,419][starVLA.training.train_starvla][INFO] - Step 452, Loss: {'train/loss': 0.6466392874717712, 'train/grad_norm_pre_clip': 6.941068649291992, 'timing/data': 0.00019647739827632904, 'timing/model': 0.457809766754508, 'learning_rate/action_model': 9.80772321754313e-05, 'learning_rate/action_query_proj': 9.80772321754313e-05, 'learning_rate/base': 2.4519308043857824e-05, 'epoch': 0.05}) +[2026-07-26 19:59:45,897][starVLA.training.train_starvla][INFO] - Step 453, Loss: {'train/loss': 0.6511313915252686, 'train/grad_norm_pre_clip': 9.260141372680664, 'timing/data': 0.0002079373225569725, 'timing/model': 0.4582010046578944, 'learning_rate/action_model': 9.80687725193917e-05, 'learning_rate/action_query_proj': 9.80687725193917e-05, 'learning_rate/base': 2.4517193129847925e-05, 'epoch': 0.05}) +[2026-07-26 19:59:51,370][starVLA.training.train_starvla][INFO] - Step 454, Loss: {'train/loss': 0.6471145749092102, 'train/grad_norm_pre_clip': 6.013407230377197, 'timing/data': 0.00019897101446986198, 'timing/model': 0.457494153175503, 'learning_rate/action_model': 9.806029467613033e-05, 'learning_rate/action_query_proj': 9.806029467613033e-05, 'learning_rate/base': 2.4515073669032583e-05, 'epoch': 0.06}) +[2026-07-26 19:59:56,831][starVLA.training.train_starvla][INFO] - Step 455, Loss: {'train/loss': 0.6246227622032166, 'train/grad_norm_pre_clip': 4.163614273071289, 'timing/data': 0.00018881168216466904, 'timing/model': 0.45591114927083254, 'learning_rate/action_model': 9.805179864899407e-05, 'learning_rate/action_query_proj': 9.805179864899407e-05, 'learning_rate/base': 2.4512949662248516e-05, 'epoch': 0.06}) +[2026-07-26 20:00:02,299][starVLA.training.train_starvla][INFO] - Step 456, Loss: {'train/loss': 0.6427148580551147, 'train/grad_norm_pre_clip': 5.592648029327393, 'timing/data': 0.00019509391859173775, 'timing/model': 0.4579346440732479, 'learning_rate/action_model': 9.804328444133702e-05, 'learning_rate/action_query_proj': 9.804328444133702e-05, 'learning_rate/base': 2.4510821110334254e-05, 'epoch': 0.06}) +[2026-07-26 20:00:07,778][starVLA.training.train_starvla][INFO] - Step 457, Loss: {'train/loss': 0.649780809879303, 'train/grad_norm_pre_clip': 7.632123947143555, 'timing/data': 0.00019194092601537704, 'timing/model': 0.45735446084290743, 'learning_rate/action_model': 9.803475205652044e-05, 'learning_rate/action_query_proj': 9.803475205652044e-05, 'learning_rate/base': 2.450868801413011e-05, 'epoch': 0.06}) +[2026-07-26 20:00:13,254][starVLA.training.train_starvla][INFO] - Step 458, Loss: {'train/loss': 0.6866813898086548, 'train/grad_norm_pre_clip': 7.229982852935791, 'timing/data': 0.00019332906231284142, 'timing/model': 0.45637468388304114, 'learning_rate/action_model': 9.802620149791282e-05, 'learning_rate/action_query_proj': 9.802620149791282e-05, 'learning_rate/base': 2.4506550374478206e-05, 'epoch': 0.06}) +[2026-07-26 20:00:18,730][starVLA.training.train_starvla][INFO] - Step 459, Loss: {'train/loss': 0.6918335556983948, 'train/grad_norm_pre_clip': 4.186751842498779, 'timing/data': 0.00019417982548475266, 'timing/model': 0.4571522339247167, 'learning_rate/action_model': 9.801763276888974e-05, 'learning_rate/action_query_proj': 9.801763276888974e-05, 'learning_rate/base': 2.4504408192222436e-05, 'epoch': 0.06}) +[2026-07-26 20:00:24,286][starVLA.training.train_starvla][INFO] - Step 460, Loss: {'train/loss': 0.7198542952537537, 'train/grad_norm_pre_clip': 5.434560298919678, 'timing/data': 0.00019149016588926315, 'timing/model': 0.45680777402594686, 'learning_rate/action_model': 9.800904587283404e-05, 'learning_rate/action_query_proj': 9.800904587283404e-05, 'learning_rate/base': 2.450226146820851e-05, 'epoch': 0.06}) +[2026-07-26 20:00:29,751][starVLA.training.train_starvla][INFO] - Step 461, Loss: {'train/loss': 0.5850446820259094, 'train/grad_norm_pre_clip': 3.298391580581665, 'timing/data': 0.00018712179735302925, 'timing/model': 0.45675280410796404, 'learning_rate/action_model': 9.800044081313569e-05, 'learning_rate/action_query_proj': 9.800044081313569e-05, 'learning_rate/base': 2.4500110203283923e-05, 'epoch': 0.06}) +[2026-07-26 20:00:35,217][starVLA.training.train_starvla][INFO] - Step 462, Loss: {'train/loss': 0.6983674764633179, 'train/grad_norm_pre_clip': 3.8635501861572266, 'timing/data': 0.000198491383343935, 'timing/model': 0.45761988312005997, 'learning_rate/action_model': 9.799181759319177e-05, 'learning_rate/action_query_proj': 9.799181759319177e-05, 'learning_rate/base': 2.4497954398297944e-05, 'epoch': 0.06}) +[2026-07-26 20:00:40,686][starVLA.training.train_starvla][INFO] - Step 463, Loss: {'train/loss': 0.6451159715652466, 'train/grad_norm_pre_clip': 5.552119255065918, 'timing/data': 0.000194476917386055, 'timing/model': 0.4571350319311023, 'learning_rate/action_model': 9.798317621640667e-05, 'learning_rate/action_query_proj': 9.798317621640667e-05, 'learning_rate/base': 2.449579405410167e-05, 'epoch': 0.06}) +[2026-07-26 20:00:46,165][starVLA.training.train_starvla][INFO] - Step 464, Loss: {'train/loss': 0.6947203278541565, 'train/grad_norm_pre_clip': 4.732688903808594, 'timing/data': 0.00019699009135365486, 'timing/model': 0.45724983094260097, 'learning_rate/action_model': 9.797451668619182e-05, 'learning_rate/action_query_proj': 9.797451668619182e-05, 'learning_rate/base': 2.4493629171547955e-05, 'epoch': 0.06}) +[2026-07-26 20:00:51,637][starVLA.training.train_starvla][INFO] - Step 465, Loss: {'train/loss': 0.5316910147666931, 'train/grad_norm_pre_clip': 4.7391862869262695, 'timing/data': 0.00019142590463161469, 'timing/model': 0.45587401930242777, 'learning_rate/action_model': 9.796583900596586e-05, 'learning_rate/action_query_proj': 9.796583900596586e-05, 'learning_rate/base': 2.4491459751491465e-05, 'epoch': 0.06}) +[2026-07-26 20:00:57,109][starVLA.training.train_starvla][INFO] - Step 466, Loss: {'train/loss': 0.7121367454528809, 'train/grad_norm_pre_clip': 5.011528491973877, 'timing/data': 0.00019060121849179268, 'timing/model': 0.4573981901630759, 'learning_rate/action_model': 9.795714317915465e-05, 'learning_rate/action_query_proj': 9.795714317915465e-05, 'learning_rate/base': 2.448928579478866e-05, 'epoch': 0.06}) +[2026-07-26 20:01:02,582][starVLA.training.train_starvla][INFO] - Step 467, Loss: {'train/loss': 0.6130861639976501, 'train/grad_norm_pre_clip': 2.981494665145874, 'timing/data': 0.00018622726202011108, 'timing/model': 0.4572204928845167, 'learning_rate/action_model': 9.794842920919113e-05, 'learning_rate/action_query_proj': 9.794842920919113e-05, 'learning_rate/base': 2.4487107302297782e-05, 'epoch': 0.06}) +[2026-07-26 20:01:08,052][starVLA.training.train_starvla][INFO] - Step 468, Loss: {'train/loss': 0.5538819432258606, 'train/grad_norm_pre_clip': 4.401337623596191, 'timing/data': 0.00019589019939303398, 'timing/model': 0.4574618157930672, 'learning_rate/action_model': 9.793969709951543e-05, 'learning_rate/action_query_proj': 9.793969709951543e-05, 'learning_rate/base': 2.4484924274878857e-05, 'epoch': 0.06}) +[2026-07-26 20:01:13,521][starVLA.training.train_starvla][INFO] - Step 469, Loss: {'train/loss': 0.4992084503173828, 'train/grad_norm_pre_clip': 3.526249647140503, 'timing/data': 0.00019734026864171028, 'timing/model': 0.45658907014876604, 'learning_rate/action_model': 9.793094685357484e-05, 'learning_rate/action_query_proj': 9.793094685357484e-05, 'learning_rate/base': 2.448273671339371e-05, 'epoch': 0.06}) +[2026-07-26 20:01:18,988][starVLA.training.train_starvla][INFO] - Step 470, Loss: {'train/loss': 0.58899986743927, 'train/grad_norm_pre_clip': 5.484261512756348, 'timing/data': 0.000186786986887455, 'timing/model': 0.4566571628674865, 'learning_rate/action_model': 9.792217847482387e-05, 'learning_rate/action_query_proj': 9.792217847482387e-05, 'learning_rate/base': 2.4480544618705968e-05, 'epoch': 0.06}) +[2026-07-26 20:01:24,579][starVLA.training.train_starvla][INFO] - Step 471, Loss: {'train/loss': 0.6736264228820801, 'train/grad_norm_pre_clip': 5.083948135375977, 'timing/data': 0.00019447086378932, 'timing/model': 0.5837115389294922, 'learning_rate/action_model': 9.791339196672409e-05, 'learning_rate/action_query_proj': 9.791339196672409e-05, 'learning_rate/base': 2.4478347991681022e-05, 'epoch': 0.06}) +[2026-07-26 20:01:30,140][starVLA.training.train_starvla][INFO] - Step 472, Loss: {'train/loss': 0.806315004825592, 'train/grad_norm_pre_clip': 6.5839524269104, 'timing/data': 0.00020637409761548042, 'timing/model': 0.4608241361565888, 'learning_rate/action_model': 9.79045873327443e-05, 'learning_rate/action_query_proj': 9.79045873327443e-05, 'learning_rate/base': 2.4476146833186076e-05, 'epoch': 0.06}) +[2026-07-26 20:01:35,636][starVLA.training.train_starvla][INFO] - Step 473, Loss: {'train/loss': 0.7042820453643799, 'train/grad_norm_pre_clip': 7.110144138336182, 'timing/data': 0.00019280798733234406, 'timing/model': 0.4591537988744676, 'learning_rate/action_model': 9.789576457636042e-05, 'learning_rate/action_query_proj': 9.789576457636042e-05, 'learning_rate/base': 2.4473941144090105e-05, 'epoch': 0.06}) +[2026-07-26 20:01:41,122][starVLA.training.train_starvla][INFO] - Step 474, Loss: {'train/loss': 0.7965013980865479, 'train/grad_norm_pre_clip': 5.674123764038086, 'timing/data': 0.00019338680431246758, 'timing/model': 0.45761496387422085, 'learning_rate/action_model': 9.788692370105551e-05, 'learning_rate/action_query_proj': 9.788692370105551e-05, 'learning_rate/base': 2.4471730925263877e-05, 'epoch': 0.06}) +[2026-07-26 20:01:46,619][starVLA.training.train_starvla][INFO] - Step 475, Loss: {'train/loss': 0.5852926969528198, 'train/grad_norm_pre_clip': 5.291163921356201, 'timing/data': 0.00019255885854363441, 'timing/model': 0.4578061178326607, 'learning_rate/action_model': 9.787806471031985e-05, 'learning_rate/action_query_proj': 9.787806471031985e-05, 'learning_rate/base': 2.4469516177579963e-05, 'epoch': 0.06}) +[2026-07-26 20:01:52,107][starVLA.training.train_starvla][INFO] - Step 476, Loss: {'train/loss': 0.573352038860321, 'train/grad_norm_pre_clip': 4.941339492797852, 'timing/data': 0.00018476229161024094, 'timing/model': 0.4605303588323295, 'learning_rate/action_model': 9.786918760765082e-05, 'learning_rate/action_query_proj': 9.786918760765082e-05, 'learning_rate/base': 2.4467296901912704e-05, 'epoch': 0.06}) +[2026-07-26 20:01:57,599][starVLA.training.train_starvla][INFO] - Step 477, Loss: {'train/loss': 0.6816750168800354, 'train/grad_norm_pre_clip': 6.742445468902588, 'timing/data': 0.00019379565492272377, 'timing/model': 0.4606797629967332, 'learning_rate/action_model': 9.786029239655294e-05, 'learning_rate/action_query_proj': 9.786029239655294e-05, 'learning_rate/base': 2.4465073099138234e-05, 'epoch': 0.06}) +[2026-07-26 20:02:03,138][starVLA.training.train_starvla][INFO] - Step 478, Loss: {'train/loss': 0.5289466381072998, 'train/grad_norm_pre_clip': 6.070423603057861, 'timing/data': 0.0001896880567073822, 'timing/model': 0.46076650777831674, 'learning_rate/action_model': 9.78513790805379e-05, 'learning_rate/action_query_proj': 9.78513790805379e-05, 'learning_rate/base': 2.4462844770134474e-05, 'epoch': 0.06}) +[2026-07-26 20:02:08,621][starVLA.training.train_starvla][INFO] - Step 479, Loss: {'train/loss': 0.6745371222496033, 'train/grad_norm_pre_clip': 7.857902526855469, 'timing/data': 0.0001946752890944481, 'timing/model': 0.46029825368896127, 'learning_rate/action_model': 9.784244766312455e-05, 'learning_rate/action_query_proj': 9.784244766312455e-05, 'learning_rate/base': 2.4460611915781137e-05, 'epoch': 0.06}) +[2026-07-26 20:02:14,120][starVLA.training.train_starvla][INFO] - Step 480, Loss: {'train/loss': 0.5665190815925598, 'train/grad_norm_pre_clip': 5.65744161605835, 'timing/data': 0.00018567591905593872, 'timing/model': 0.4607800683006644, 'learning_rate/action_model': 9.783349814783888e-05, 'learning_rate/action_query_proj': 9.783349814783888e-05, 'learning_rate/base': 2.445837453695972e-05, 'epoch': 0.06}) +[2026-07-26 20:02:19,595][starVLA.training.train_starvla][INFO] - Step 481, Loss: {'train/loss': 0.776846706867218, 'train/grad_norm_pre_clip': 4.389269828796387, 'timing/data': 0.00018606986850500107, 'timing/model': 0.46162631874904037, 'learning_rate/action_model': 9.782453053821398e-05, 'learning_rate/action_query_proj': 9.782453053821398e-05, 'learning_rate/base': 2.4456132634553494e-05, 'epoch': 0.06}) +[2026-07-26 20:02:25,077][starVLA.training.train_starvla][INFO] - Step 482, Loss: {'train/loss': 0.5856029391288757, 'train/grad_norm_pre_clip': 5.352298259735107, 'timing/data': 0.0001859567128121853, 'timing/model': 0.4601992489770055, 'learning_rate/action_model': 9.781554483779016e-05, 'learning_rate/action_query_proj': 9.781554483779016e-05, 'learning_rate/base': 2.445388620944754e-05, 'epoch': 0.06}) +[2026-07-26 20:02:30,549][starVLA.training.train_starvla][INFO] - Step 483, Loss: {'train/loss': 0.6073672771453857, 'train/grad_norm_pre_clip': 3.9556238651275635, 'timing/data': 0.00019204895943403244, 'timing/model': 0.45712129585444927, 'learning_rate/action_model': 9.78065410501148e-05, 'learning_rate/action_query_proj': 9.78065410501148e-05, 'learning_rate/base': 2.44516352625287e-05, 'epoch': 0.06}) +[2026-07-26 20:02:36,012][starVLA.training.train_starvla][INFO] - Step 484, Loss: {'train/loss': 0.4541347622871399, 'train/grad_norm_pre_clip': 3.656451463699341, 'timing/data': 0.0001912349835038185, 'timing/model': 0.4570917780511081, 'learning_rate/action_model': 9.779751917874249e-05, 'learning_rate/action_query_proj': 9.779751917874249e-05, 'learning_rate/base': 2.4449379794685623e-05, 'epoch': 0.06}) +[2026-07-26 20:02:41,495][starVLA.training.train_starvla][INFO] - Step 485, Loss: {'train/loss': 0.5678656101226807, 'train/grad_norm_pre_clip': 5.551736831665039, 'timing/data': 0.00018357066437602043, 'timing/model': 0.4575682762078941, 'learning_rate/action_model': 9.77884792272349e-05, 'learning_rate/action_query_proj': 9.77884792272349e-05, 'learning_rate/base': 2.4447119806808725e-05, 'epoch': 0.06}) +[2026-07-26 20:02:46,964][starVLA.training.train_starvla][INFO] - Step 486, Loss: {'train/loss': 0.624241054058075, 'train/grad_norm_pre_clip': 3.279402256011963, 'timing/data': 0.00018532108515501022, 'timing/model': 0.45613615680485964, 'learning_rate/action_model': 9.777942119916085e-05, 'learning_rate/action_query_proj': 9.777942119916085e-05, 'learning_rate/base': 2.4444855299790212e-05, 'epoch': 0.06}) +[2026-07-26 20:02:52,429][starVLA.training.train_starvla][INFO] - Step 487, Loss: {'train/loss': 0.6693516969680786, 'train/grad_norm_pre_clip': 3.2991318702697754, 'timing/data': 0.00018977420404553413, 'timing/model': 0.4565935358405113, 'learning_rate/action_model': 9.777034509809633e-05, 'learning_rate/action_query_proj': 9.777034509809633e-05, 'learning_rate/base': 2.4442586274524083e-05, 'epoch': 0.06}) +[2026-07-26 20:02:57,900][starVLA.training.train_starvla][INFO] - Step 488, Loss: {'train/loss': 0.6032897233963013, 'train/grad_norm_pre_clip': 3.1180222034454346, 'timing/data': 0.00019415421411395073, 'timing/model': 0.4571219920180738, 'learning_rate/action_model': 9.776125092762441e-05, 'learning_rate/action_query_proj': 9.776125092762441e-05, 'learning_rate/base': 2.4440312731906103e-05, 'epoch': 0.06}) +[2026-07-26 20:03:03,369][starVLA.training.train_starvla][INFO] - Step 489, Loss: {'train/loss': 0.5592474341392517, 'train/grad_norm_pre_clip': 5.483001232147217, 'timing/data': 0.0001942911185324192, 'timing/model': 0.4570693438872695, 'learning_rate/action_model': 9.775213869133535e-05, 'learning_rate/action_query_proj': 9.775213869133535e-05, 'learning_rate/base': 2.4438034672833837e-05, 'epoch': 0.06}) +[2026-07-26 20:03:08,848][starVLA.training.train_starvla][INFO] - Step 490, Loss: {'train/loss': 0.6272478699684143, 'train/grad_norm_pre_clip': 4.5207672119140625, 'timing/data': 0.00021330220624804497, 'timing/model': 0.45723228715360165, 'learning_rate/action_model': 9.774300839282652e-05, 'learning_rate/action_query_proj': 9.774300839282652e-05, 'learning_rate/base': 2.443575209820663e-05, 'epoch': 0.06}) +[2026-07-26 20:03:14,318][starVLA.training.train_starvla][INFO] - Step 491, Loss: {'train/loss': 0.47793087363243103, 'train/grad_norm_pre_clip': 5.541975021362305, 'timing/data': 0.00020087417215108871, 'timing/model': 0.45850515691563487, 'learning_rate/action_model': 9.773386003570238e-05, 'learning_rate/action_query_proj': 9.773386003570238e-05, 'learning_rate/base': 2.4433465008925596e-05, 'epoch': 0.06}) +[2026-07-26 20:03:19,792][starVLA.training.train_starvla][INFO] - Step 492, Loss: {'train/loss': 0.6429541110992432, 'train/grad_norm_pre_clip': 3.7887237071990967, 'timing/data': 0.00019106734544038773, 'timing/model': 0.45718574384227395, 'learning_rate/action_model': 9.772469362357461e-05, 'learning_rate/action_query_proj': 9.772469362357461e-05, 'learning_rate/base': 2.4431173405893652e-05, 'epoch': 0.06}) +[2026-07-26 20:03:25,267][starVLA.training.train_starvla][INFO] - Step 493, Loss: {'train/loss': 0.6261276602745056, 'train/grad_norm_pre_clip': 5.758962631225586, 'timing/data': 0.00019186967983841896, 'timing/model': 0.45745215518400073, 'learning_rate/action_model': 9.771550916006191e-05, 'learning_rate/action_query_proj': 9.771550916006191e-05, 'learning_rate/base': 2.4428877290015478e-05, 'epoch': 0.06}) +[2026-07-26 20:03:30,733][starVLA.training.train_starvla][INFO] - Step 494, Loss: {'train/loss': 0.5039007663726807, 'train/grad_norm_pre_clip': 5.147584438323975, 'timing/data': 0.0001918962225317955, 'timing/model': 0.4563527926802635, 'learning_rate/action_model': 9.770630664879021e-05, 'learning_rate/action_query_proj': 9.770630664879021e-05, 'learning_rate/base': 2.4426576662197553e-05, 'epoch': 0.06}) +[2026-07-26 20:03:36,200][starVLA.training.train_starvla][INFO] - Step 495, Loss: {'train/loss': 0.5119121074676514, 'train/grad_norm_pre_clip': 3.6371757984161377, 'timing/data': 0.00019471719861030579, 'timing/model': 0.45768120884895325, 'learning_rate/action_model': 9.769708609339249e-05, 'learning_rate/action_query_proj': 9.769708609339249e-05, 'learning_rate/base': 2.4424271523348122e-05, 'epoch': 0.06}) +[2026-07-26 20:03:41,765][starVLA.training.train_starvla][INFO] - Step 496, Loss: {'train/loss': 0.6969249248504639, 'train/grad_norm_pre_clip': 4.905663967132568, 'timing/data': 0.00019257469102740288, 'timing/model': 0.4568197997286916, 'learning_rate/action_model': 9.768784749750887e-05, 'learning_rate/action_query_proj': 9.768784749750887e-05, 'learning_rate/base': 2.4421961874377218e-05, 'epoch': 0.06}) +[2026-07-26 20:03:47,240][starVLA.training.train_starvla][INFO] - Step 497, Loss: {'train/loss': 0.6037566661834717, 'train/grad_norm_pre_clip': 5.014855861663818, 'timing/data': 0.000186258926987648, 'timing/model': 0.4572600070387125, 'learning_rate/action_model': 9.767859086478662e-05, 'learning_rate/action_query_proj': 9.767859086478662e-05, 'learning_rate/base': 2.4419647716196655e-05, 'epoch': 0.06}) +[2026-07-26 20:03:52,849][starVLA.training.train_starvla][INFO] - Step 498, Loss: {'train/loss': 0.6749816536903381, 'train/grad_norm_pre_clip': 8.296191215515137, 'timing/data': 0.00018846802413463593, 'timing/model': 0.45664070826023817, 'learning_rate/action_model': 9.766931619888011e-05, 'learning_rate/action_query_proj': 9.766931619888011e-05, 'learning_rate/base': 2.4417329049720028e-05, 'epoch': 0.06}) +[2026-07-26 20:03:58,315][starVLA.training.train_starvla][INFO] - Step 499, Loss: {'train/loss': 0.5868222713470459, 'train/grad_norm_pre_clip': 5.77827787399292, 'timing/data': 0.00018585799261927605, 'timing/model': 0.45718616899102926, 'learning_rate/action_model': 9.766002350345082e-05, 'learning_rate/action_query_proj': 9.766002350345082e-05, 'learning_rate/base': 2.4415005875862706e-05, 'epoch': 0.06}) +[2026-07-26 20:04:03,856][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 500 +[2026-07-26 20:04:03,857][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 500 +[2026-07-26 20:04:03,857][starVLA.training.train_starvla][INFO] - Step 500, Loss: {'train/loss': 0.6461995244026184, 'train/grad_norm_pre_clip': 3.4807627201080322, 'timing/data': 0.00019077397882938385, 'timing/model': 0.45632790867239237, 'learning_rate/action_model': 9.765071278216737e-05, 'learning_rate/action_query_proj': 9.765071278216737e-05, 'learning_rate/base': 2.4412678195541843e-05, 'epoch': 0.06}) +[2026-07-26 20:04:03,860][accelerate.accelerator][INFO] - Saving current state to /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_500_state +[2026-07-26 20:04:03,860][accelerate.accelerator][INFO] - Saving DeepSpeed Model and Optimizer +[2026-07-26 20:04:49,304][accelerate.accelerator][INFO] - DeepSpeed Model and Optimizer saved to output dir /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_500_state/pytorch_model +[2026-07-26 20:04:49,304][accelerate.checkpointing][INFO] - Sampler state for dataloader 0 saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_500_state/sampler.bin +[2026-07-26 20:04:49,307][accelerate.checkpointing][INFO] - Random states saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_500_state/random_states_0.pkl +[2026-07-26 20:05:16,172][starVLA.training.rl_games.checkpoint_sync][INFO] - HF checkpoint sync disabled; skipping upload for step 500 +[2026-07-26 20:05:16,172][starVLA.training.train_starvla][INFO] - 📊 Saving accessed configuration... +[2026-07-26 20:05:16,186][starVLA.training.train_starvla][INFO] - ✅ Configuration files saved +[2026-07-26 20:05:21,982][starVLA.training.train_starvla][INFO] - Step 501, Loss: {'train/loss': 0.6135210990905762, 'train/grad_norm_pre_clip': 3.5120060443878174, 'timing/data': 0.00019420497119426727, 'timing/model': 0.45631779823452234, 'learning_rate/action_model': 9.764138403870548e-05, 'learning_rate/action_query_proj': 9.764138403870548e-05, 'learning_rate/base': 2.441034600967637e-05, 'epoch': 0.06}) +[2026-07-26 20:05:27,480][starVLA.training.train_starvla][INFO] - Step 502, Loss: {'train/loss': 0.6489186882972717, 'train/grad_norm_pre_clip': 5.261904239654541, 'timing/data': 0.00019660312682390213, 'timing/model': 0.46357297897338867, 'learning_rate/action_model': 9.7632037276748e-05, 'learning_rate/action_query_proj': 9.7632037276748e-05, 'learning_rate/base': 2.4408009319187e-05, 'epoch': 0.06}) +[2026-07-26 20:05:32,966][starVLA.training.train_starvla][INFO] - Step 503, Loss: {'train/loss': 0.6121601462364197, 'train/grad_norm_pre_clip': 3.6335489749908447, 'timing/data': 0.0002086767926812172, 'timing/model': 0.45798375410959125, 'learning_rate/action_model': 9.762267249998487e-05, 'learning_rate/action_query_proj': 9.762267249998487e-05, 'learning_rate/base': 2.4405668124996217e-05, 'epoch': 0.06}) +[2026-07-26 20:05:38,460][starVLA.training.train_starvla][INFO] - Step 504, Loss: {'train/loss': 0.6324453353881836, 'train/grad_norm_pre_clip': 3.7501094341278076, 'timing/data': 0.00021180324256420135, 'timing/model': 0.45774419978260994, 'learning_rate/action_model': 9.761328971211315e-05, 'learning_rate/action_query_proj': 9.761328971211315e-05, 'learning_rate/base': 2.4403322428028287e-05, 'epoch': 0.06}) +[2026-07-26 20:05:43,955][starVLA.training.train_starvla][INFO] - Step 505, Loss: {'train/loss': 0.6923081874847412, 'train/grad_norm_pre_clip': 4.753622055053711, 'timing/data': 0.00018966617062687874, 'timing/model': 0.45754860900342464, 'learning_rate/action_model': 9.760388891683704e-05, 'learning_rate/action_query_proj': 9.760388891683704e-05, 'learning_rate/base': 2.440097222920926e-05, 'epoch': 0.06}) +[2026-07-26 20:05:49,453][starVLA.training.train_starvla][INFO] - Step 506, Loss: {'train/loss': 0.6730932593345642, 'train/grad_norm_pre_clip': 4.2987895011901855, 'timing/data': 0.00023590028285980225, 'timing/model': 0.4566028071567416, 'learning_rate/action_model': 9.759447011786783e-05, 'learning_rate/action_query_proj': 9.759447011786783e-05, 'learning_rate/base': 2.4398617529466957e-05, 'epoch': 0.06}) +[2026-07-26 20:05:55,126][starVLA.training.train_starvla][INFO] - Step 507, Loss: {'train/loss': 0.7495481371879578, 'train/grad_norm_pre_clip': 6.4789958000183105, 'timing/data': 0.00018732668831944466, 'timing/model': 0.4604679550975561, 'learning_rate/action_model': 9.758503331892385e-05, 'learning_rate/action_query_proj': 9.758503331892385e-05, 'learning_rate/base': 2.4396258329730964e-05, 'epoch': 0.06}) +[2026-07-26 20:06:00,732][starVLA.training.train_starvla][INFO] - Step 508, Loss: {'train/loss': 0.6702308058738708, 'train/grad_norm_pre_clip': 3.1532061100006104, 'timing/data': 0.0002001090906560421, 'timing/model': 0.4591866503469646, 'learning_rate/action_model': 9.757557852373067e-05, 'learning_rate/action_query_proj': 9.757557852373067e-05, 'learning_rate/base': 2.4393894630932668e-05, 'epoch': 0.06}) +[2026-07-26 20:06:06,337][starVLA.training.train_starvla][INFO] - Step 509, Loss: {'train/loss': 0.6833671927452087, 'train/grad_norm_pre_clip': 4.221286773681641, 'timing/data': 0.0001902468502521515, 'timing/model': 0.47999873105436563, 'learning_rate/action_model': 9.756610573602087e-05, 'learning_rate/action_query_proj': 9.756610573602087e-05, 'learning_rate/base': 2.4391526434005218e-05, 'epoch': 0.06}) +[2026-07-26 20:06:11,906][starVLA.training.train_starvla][INFO] - Step 510, Loss: {'train/loss': 0.7857719659805298, 'train/grad_norm_pre_clip': 8.13940715789795, 'timing/data': 0.00019218726083636284, 'timing/model': 0.47098793694749475, 'learning_rate/action_model': 9.755661495953414e-05, 'learning_rate/action_query_proj': 9.755661495953414e-05, 'learning_rate/base': 2.4389153739883535e-05, 'epoch': 0.06}) +[2026-07-26 20:06:17,495][starVLA.training.train_starvla][INFO] - Step 511, Loss: {'train/loss': 0.6116966009140015, 'train/grad_norm_pre_clip': 4.918620586395264, 'timing/data': 0.00018579792231321335, 'timing/model': 0.47103077499195933, 'learning_rate/action_model': 9.754710619801732e-05, 'learning_rate/action_query_proj': 9.754710619801732e-05, 'learning_rate/base': 2.438677654950433e-05, 'epoch': 0.06}) +[2026-07-26 20:06:23,040][starVLA.training.train_starvla][INFO] - Step 512, Loss: {'train/loss': 0.7219157218933105, 'train/grad_norm_pre_clip': 6.913002014160156, 'timing/data': 0.00018391292542219162, 'timing/model': 0.4691356895491481, 'learning_rate/action_model': 9.753757945522428e-05, 'learning_rate/action_query_proj': 9.753757945522428e-05, 'learning_rate/base': 2.438439486380607e-05, 'epoch': 0.06}) +[2026-07-26 20:06:28,577][starVLA.training.train_starvla][INFO] - Step 513, Loss: {'train/loss': 0.7048736214637756, 'train/grad_norm_pre_clip': 4.123136043548584, 'timing/data': 0.00019550509750843048, 'timing/model': 0.47646245500072837, 'learning_rate/action_model': 9.752803473491605e-05, 'learning_rate/action_query_proj': 9.752803473491605e-05, 'learning_rate/base': 2.4382008683729013e-05, 'epoch': 0.06}) +[2026-07-26 20:06:34,081][starVLA.training.train_starvla][INFO] - Step 514, Loss: {'train/loss': 0.5674759149551392, 'train/grad_norm_pre_clip': 4.567549228668213, 'timing/data': 0.00018597813323140144, 'timing/model': 0.4716193056665361, 'learning_rate/action_model': 9.751847204086074e-05, 'learning_rate/action_query_proj': 9.751847204086074e-05, 'learning_rate/base': 2.4379618010215186e-05, 'epoch': 0.06}) +[2026-07-26 20:06:39,596][starVLA.training.train_starvla][INFO] - Step 515, Loss: {'train/loss': 0.7731733918190002, 'train/grad_norm_pre_clip': 8.212955474853516, 'timing/data': 0.0001892847940325737, 'timing/model': 0.47088258201256394, 'learning_rate/action_model': 9.750889137683354e-05, 'learning_rate/action_query_proj': 9.750889137683354e-05, 'learning_rate/base': 2.4377222844208385e-05, 'epoch': 0.06}) +[2026-07-26 20:06:45,173][starVLA.training.train_starvla][INFO] - Step 516, Loss: {'train/loss': 0.6024749875068665, 'train/grad_norm_pre_clip': 3.1012766361236572, 'timing/data': 0.00018579000607132912, 'timing/model': 0.47703328309580684, 'learning_rate/action_model': 9.749929274661674e-05, 'learning_rate/action_query_proj': 9.749929274661674e-05, 'learning_rate/base': 2.4374823186654185e-05, 'epoch': 0.06}) +[2026-07-26 20:06:50,729][starVLA.training.train_starvla][INFO] - Step 517, Loss: {'train/loss': 0.5934683680534363, 'train/grad_norm_pre_clip': 3.565246105194092, 'timing/data': 0.00021154899150133133, 'timing/model': 0.4687856277450919, 'learning_rate/action_model': 9.748967615399975e-05, 'learning_rate/action_query_proj': 9.748967615399975e-05, 'learning_rate/base': 2.4372419038499937e-05, 'epoch': 0.06}) +[2026-07-26 20:06:56,537][starVLA.training.train_starvla][INFO] - Step 518, Loss: {'train/loss': 0.5397045016288757, 'train/grad_norm_pre_clip': 4.77079963684082, 'timing/data': 0.00019293790683150291, 'timing/model': 0.47055893624201417, 'learning_rate/action_model': 9.748004160277901e-05, 'learning_rate/action_query_proj': 9.748004160277901e-05, 'learning_rate/base': 2.4370010400694753e-05, 'epoch': 0.06}) +[2026-07-26 20:07:02,085][starVLA.training.train_starvla][INFO] - Step 519, Loss: {'train/loss': 0.702762246131897, 'train/grad_norm_pre_clip': 3.851635456085205, 'timing/data': 0.00019295327365398407, 'timing/model': 0.4724643509835005, 'learning_rate/action_model': 9.747038909675812e-05, 'learning_rate/action_query_proj': 9.747038909675812e-05, 'learning_rate/base': 2.436759727418953e-05, 'epoch': 0.06}) +[2026-07-26 20:07:07,655][starVLA.training.train_starvla][INFO] - Step 520, Loss: {'train/loss': 0.5082318186759949, 'train/grad_norm_pre_clip': 3.050548791885376, 'timing/data': 0.00018690200522542, 'timing/model': 0.477732852101326, 'learning_rate/action_model': 9.746071863974773e-05, 'learning_rate/action_query_proj': 9.746071863974773e-05, 'learning_rate/base': 2.4365179659936933e-05, 'epoch': 0.06}) +[2026-07-26 20:07:13,478][starVLA.training.train_starvla][INFO] - Step 521, Loss: {'train/loss': 0.6778803467750549, 'train/grad_norm_pre_clip': 5.60844612121582, 'timing/data': 0.0001854151487350464, 'timing/model': 0.4705029116012156, 'learning_rate/action_model': 9.745103023556558e-05, 'learning_rate/action_query_proj': 9.745103023556558e-05, 'learning_rate/base': 2.4362757558891396e-05, 'epoch': 0.06}) +[2026-07-26 20:07:19,044][starVLA.training.train_starvla][INFO] - Step 522, Loss: {'train/loss': 0.7287856340408325, 'train/grad_norm_pre_clip': 6.2023210525512695, 'timing/data': 0.0001924140378832817, 'timing/model': 0.46783340303227305, 'learning_rate/action_model': 9.74413238880365e-05, 'learning_rate/action_query_proj': 9.74413238880365e-05, 'learning_rate/base': 2.4360330972009125e-05, 'epoch': 0.06}) +[2026-07-26 20:07:24,594][starVLA.training.train_starvla][INFO] - Step 523, Loss: {'train/loss': 0.7178974747657776, 'train/grad_norm_pre_clip': 4.108137607574463, 'timing/data': 0.00017987284809350967, 'timing/model': 0.4709616368636489, 'learning_rate/action_model': 9.743159960099239e-05, 'learning_rate/action_query_proj': 9.743159960099239e-05, 'learning_rate/base': 2.4357899900248097e-05, 'epoch': 0.06}) +[2026-07-26 20:07:30,142][starVLA.training.train_starvla][INFO] - Step 524, Loss: {'train/loss': 0.6509689092636108, 'train/grad_norm_pre_clip': 5.1640496253967285, 'timing/data': 0.0001899288035929203, 'timing/model': 0.4747517299838364, 'learning_rate/action_model': 9.742185737827226e-05, 'learning_rate/action_query_proj': 9.742185737827226e-05, 'learning_rate/base': 2.4355464344568065e-05, 'epoch': 0.06}) +[2026-07-26 20:07:35,692][starVLA.training.train_starvla][INFO] - Step 525, Loss: {'train/loss': 0.5414668917655945, 'train/grad_norm_pre_clip': 2.8565635681152344, 'timing/data': 0.00019461708143353462, 'timing/model': 0.4728430453687906, 'learning_rate/action_model': 9.741209722372218e-05, 'learning_rate/action_query_proj': 9.741209722372218e-05, 'learning_rate/base': 2.4353024305930544e-05, 'epoch': 0.06}) +[2026-07-26 20:07:41,236][starVLA.training.train_starvla][INFO] - Step 526, Loss: {'train/loss': 0.7550969123840332, 'train/grad_norm_pre_clip': 3.6537506580352783, 'timing/data': 0.00019901013001799583, 'timing/model': 0.4763681315816939, 'learning_rate/action_model': 9.740231914119531e-05, 'learning_rate/action_query_proj': 9.740231914119531e-05, 'learning_rate/base': 2.4350579785298827e-05, 'epoch': 0.06}) +[2026-07-26 20:07:46,775][starVLA.training.train_starvla][INFO] - Step 527, Loss: {'train/loss': 0.6076582670211792, 'train/grad_norm_pre_clip': 4.314920902252197, 'timing/data': 0.00019467202946543694, 'timing/model': 0.4715037001296878, 'learning_rate/action_model': 9.739252313455186e-05, 'learning_rate/action_query_proj': 9.739252313455186e-05, 'learning_rate/base': 2.4348130783637966e-05, 'epoch': 0.06}) +[2026-07-26 20:07:52,320][starVLA.training.train_starvla][INFO] - Step 528, Loss: {'train/loss': 0.635062038898468, 'train/grad_norm_pre_clip': 2.8109130859375, 'timing/data': 0.00018224818632006645, 'timing/model': 0.4711936619132757, 'learning_rate/action_model': 9.738270920765918e-05, 'learning_rate/action_query_proj': 9.738270920765918e-05, 'learning_rate/base': 2.4345677301914794e-05, 'epoch': 0.06}) +[2026-07-26 20:07:57,860][starVLA.training.train_starvla][INFO] - Step 529, Loss: {'train/loss': 0.7205344438552856, 'train/grad_norm_pre_clip': 4.447811126708984, 'timing/data': 0.0001820409670472145, 'timing/model': 0.4783754809759557, 'learning_rate/action_model': 9.737287736439162e-05, 'learning_rate/action_query_proj': 9.737287736439162e-05, 'learning_rate/base': 2.4343219341097904e-05, 'epoch': 0.06}) +[2026-07-26 20:08:03,437][starVLA.training.train_starvla][INFO] - Step 530, Loss: {'train/loss': 0.6539711952209473, 'train/grad_norm_pre_clip': 3.6026880741119385, 'timing/data': 0.00018272921442985535, 'timing/model': 0.4718624451197684, 'learning_rate/action_model': 9.736302760863063e-05, 'learning_rate/action_query_proj': 9.736302760863063e-05, 'learning_rate/base': 2.4340756902157657e-05, 'epoch': 0.06}) +[2026-07-26 20:08:08,960][starVLA.training.train_starvla][INFO] - Step 531, Loss: {'train/loss': 0.694893479347229, 'train/grad_norm_pre_clip': 8.170458793640137, 'timing/data': 0.00017810286954045296, 'timing/model': 0.47019420377910137, 'learning_rate/action_model': 9.735315994426476e-05, 'learning_rate/action_query_proj': 9.735315994426476e-05, 'learning_rate/base': 2.433828998606619e-05, 'epoch': 0.06}) +[2026-07-26 20:08:14,517][starVLA.training.train_starvla][INFO] - Step 532, Loss: {'train/loss': 0.8328781127929688, 'train/grad_norm_pre_clip': 8.869027137756348, 'timing/data': 0.00020504090934991837, 'timing/model': 0.46988276205956936, 'learning_rate/action_model': 9.734327437518961e-05, 'learning_rate/action_query_proj': 9.734327437518961e-05, 'learning_rate/base': 2.4335818593797402e-05, 'epoch': 0.06}) +[2026-07-26 20:08:20,110][starVLA.training.train_starvla][INFO] - Step 533, Loss: {'train/loss': 0.6372672319412231, 'train/grad_norm_pre_clip': 3.67236590385437, 'timing/data': 0.00018188590183854103, 'timing/model': 0.4716579429805279, 'learning_rate/action_model': 9.733337090530783e-05, 'learning_rate/action_query_proj': 9.733337090530783e-05, 'learning_rate/base': 2.433334272632696e-05, 'epoch': 0.06}) +[2026-07-26 20:08:25,674][starVLA.training.train_starvla][INFO] - Step 534, Loss: {'train/loss': 0.7440769672393799, 'train/grad_norm_pre_clip': 5.765049457550049, 'timing/data': 0.00018551014363765717, 'timing/model': 0.46897946298122406, 'learning_rate/action_model': 9.732344953852915e-05, 'learning_rate/action_query_proj': 9.732344953852915e-05, 'learning_rate/base': 2.4330862384632288e-05, 'epoch': 0.06}) +[2026-07-26 20:08:31,241][starVLA.training.train_starvla][INFO] - Step 535, Loss: {'train/loss': 0.7224873900413513, 'train/grad_norm_pre_clip': 5.346268653869629, 'timing/data': 0.0001871967688202858, 'timing/model': 0.47812352515757084, 'learning_rate/action_model': 9.73135102787704e-05, 'learning_rate/action_query_proj': 9.73135102787704e-05, 'learning_rate/base': 2.43283775696926e-05, 'epoch': 0.06}) +[2026-07-26 20:08:36,806][starVLA.training.train_starvla][INFO] - Step 536, Loss: {'train/loss': 0.6750466823577881, 'train/grad_norm_pre_clip': 5.508291721343994, 'timing/data': 0.0001913001760840416, 'timing/model': 0.47629026882350445, 'learning_rate/action_model': 9.73035531299554e-05, 'learning_rate/action_query_proj': 9.73035531299554e-05, 'learning_rate/base': 2.432588828248885e-05, 'epoch': 0.07}) +[2026-07-26 20:08:42,378][starVLA.training.train_starvla][INFO] - Step 537, Loss: {'train/loss': 0.5392852425575256, 'train/grad_norm_pre_clip': 2.1982407569885254, 'timing/data': 0.00019303616136312485, 'timing/model': 0.471526054199785, 'learning_rate/action_model': 9.72935780960151e-05, 'learning_rate/action_query_proj': 9.72935780960151e-05, 'learning_rate/base': 2.4323394524003775e-05, 'epoch': 0.07}) +[2026-07-26 20:08:47,954][starVLA.training.train_starvla][INFO] - Step 538, Loss: {'train/loss': 0.547153890132904, 'train/grad_norm_pre_clip': 3.044839382171631, 'timing/data': 0.0001764320768415928, 'timing/model': 0.4717169380746782, 'learning_rate/action_model': 9.728358518088747e-05, 'learning_rate/action_query_proj': 9.728358518088747e-05, 'learning_rate/base': 2.4320896295221867e-05, 'epoch': 0.07}) +[2026-07-26 20:08:53,533][starVLA.training.train_starvla][INFO] - Step 539, Loss: {'train/loss': 0.5595443248748779, 'train/grad_norm_pre_clip': 5.953236103057861, 'timing/data': 0.00018476275727152824, 'timing/model': 0.4782677008770406, 'learning_rate/action_model': 9.727357438851757e-05, 'learning_rate/action_query_proj': 9.727357438851757e-05, 'learning_rate/base': 2.4318393597129393e-05, 'epoch': 0.07}) +[2026-07-26 20:08:59,106][starVLA.training.train_starvla][INFO] - Step 540, Loss: {'train/loss': 0.6117428541183472, 'train/grad_norm_pre_clip': 5.838871002197266, 'timing/data': 0.00017870822921395302, 'timing/model': 0.4768321351148188, 'learning_rate/action_model': 9.72635457228575e-05, 'learning_rate/action_query_proj': 9.72635457228575e-05, 'learning_rate/base': 2.4315886430714374e-05, 'epoch': 0.07}) +[2026-07-26 20:09:04,674][starVLA.training.train_starvla][INFO] - Step 541, Loss: {'train/loss': 0.7066223621368408, 'train/grad_norm_pre_clip': 6.259166717529297, 'timing/data': 0.00018057692795991898, 'timing/model': 0.4700690661557019, 'learning_rate/action_model': 9.72534991878664e-05, 'learning_rate/action_query_proj': 9.72534991878664e-05, 'learning_rate/base': 2.43133747969666e-05, 'epoch': 0.07}) +[2026-07-26 20:09:10,251][starVLA.training.train_starvla][INFO] - Step 542, Loss: {'train/loss': 0.5089005827903748, 'train/grad_norm_pre_clip': 2.5711472034454346, 'timing/data': 0.00018254201859235764, 'timing/model': 0.47923186514526606, 'learning_rate/action_model': 9.724343478751052e-05, 'learning_rate/action_query_proj': 9.724343478751052e-05, 'learning_rate/base': 2.431085869687763e-05, 'epoch': 0.07}) +[2026-07-26 20:09:15,851][starVLA.training.train_starvla][INFO] - Step 543, Loss: {'train/loss': 0.5234399437904358, 'train/grad_norm_pre_clip': 5.387768268585205, 'timing/data': 0.00017827237024903297, 'timing/model': 0.47816256200894713, 'learning_rate/action_model': 9.723335252576309e-05, 'learning_rate/action_query_proj': 9.723335252576309e-05, 'learning_rate/base': 2.4308338131440773e-05, 'epoch': 0.07}) +[2026-07-26 20:09:21,457][starVLA.training.train_starvla][INFO] - Step 544, Loss: {'train/loss': 0.6628643870353699, 'train/grad_norm_pre_clip': 4.382824420928955, 'timing/data': 0.00018421700224280357, 'timing/model': 0.4720938201062381, 'learning_rate/action_model': 9.722325240660445e-05, 'learning_rate/action_query_proj': 9.722325240660445e-05, 'learning_rate/base': 2.4305813101651112e-05, 'epoch': 0.07}) +[2026-07-26 20:09:27,073][starVLA.training.train_starvla][INFO] - Step 545, Loss: {'train/loss': 0.7157107591629028, 'train/grad_norm_pre_clip': 5.057494163513184, 'timing/data': 0.00017917389050126076, 'timing/model': 0.47678377525880933, 'learning_rate/action_model': 9.721313443402194e-05, 'learning_rate/action_query_proj': 9.721313443402194e-05, 'learning_rate/base': 2.4303283608505486e-05, 'epoch': 0.07}) +[2026-07-26 20:09:32,664][starVLA.training.train_starvla][INFO] - Step 546, Loss: {'train/loss': 0.6180234551429749, 'train/grad_norm_pre_clip': 3.484546661376953, 'timing/data': 0.00017617037519812584, 'timing/model': 0.4670235519297421, 'learning_rate/action_model': 9.720299861201003e-05, 'learning_rate/action_query_proj': 9.720299861201003e-05, 'learning_rate/base': 2.4300749653002507e-05, 'epoch': 0.07}) +[2026-07-26 20:09:38,277][starVLA.training.train_starvla][INFO] - Step 547, Loss: {'train/loss': 0.6345462203025818, 'train/grad_norm_pre_clip': 5.69810152053833, 'timing/data': 0.00018139882013201714, 'timing/model': 0.47610889794304967, 'learning_rate/action_model': 9.719284494457012e-05, 'learning_rate/action_query_proj': 9.719284494457012e-05, 'learning_rate/base': 2.429821123614253e-05, 'epoch': 0.07}) +[2026-07-26 20:09:43,880][starVLA.training.train_starvla][INFO] - Step 548, Loss: {'train/loss': 0.5810476541519165, 'train/grad_norm_pre_clip': 6.2534918785095215, 'timing/data': 0.00018071243539452553, 'timing/model': 0.4716502339579165, 'learning_rate/action_model': 9.718267343571073e-05, 'learning_rate/action_query_proj': 9.718267343571073e-05, 'learning_rate/base': 2.429566835892768e-05, 'epoch': 0.07}) +[2026-07-26 20:09:49,455][starVLA.training.train_starvla][INFO] - Step 549, Loss: {'train/loss': 0.532301127910614, 'train/grad_norm_pre_clip': 2.2601406574249268, 'timing/data': 0.00017355801537632942, 'timing/model': 0.47121563693508506, 'learning_rate/action_model': 9.717248408944745e-05, 'learning_rate/action_query_proj': 9.717248408944745e-05, 'learning_rate/base': 2.4293121022361863e-05, 'epoch': 0.07}) +[2026-07-26 20:09:55,024][starVLA.training.train_starvla][INFO] - Step 550, Loss: {'train/loss': 0.5703068971633911, 'train/grad_norm_pre_clip': 6.645199298858643, 'timing/data': 0.00017695315182209015, 'timing/model': 0.4687740011140704, 'learning_rate/action_model': 9.716227690980283e-05, 'learning_rate/action_query_proj': 9.716227690980283e-05, 'learning_rate/base': 2.4290569227450707e-05, 'epoch': 0.07}) +[2026-07-26 20:10:00,587][starVLA.training.train_starvla][INFO] - Step 551, Loss: {'train/loss': 0.7262057065963745, 'train/grad_norm_pre_clip': 5.9323410987854, 'timing/data': 0.00018536578863859177, 'timing/model': 0.4728254801593721, 'learning_rate/action_model': 9.715205190080652e-05, 'learning_rate/action_query_proj': 9.715205190080652e-05, 'learning_rate/base': 2.428801297520163e-05, 'epoch': 0.07}) +[2026-07-26 20:10:06,144][starVLA.training.train_starvla][INFO] - Step 552, Loss: {'train/loss': 0.6895768046379089, 'train/grad_norm_pre_clip': 4.446195125579834, 'timing/data': 0.0001774788834154606, 'timing/model': 0.47054295102134347, 'learning_rate/action_model': 9.71418090664952e-05, 'learning_rate/action_query_proj': 9.71418090664952e-05, 'learning_rate/base': 2.42854522666238e-05, 'epoch': 0.07}) +[2026-07-26 20:10:11,699][starVLA.training.train_starvla][INFO] - Step 553, Loss: {'train/loss': 0.5969703197479248, 'train/grad_norm_pre_clip': 2.8803017139434814, 'timing/data': 0.00017285626381635666, 'timing/model': 0.472281226888299, 'learning_rate/action_model': 9.713154841091254e-05, 'learning_rate/action_query_proj': 9.713154841091254e-05, 'learning_rate/base': 2.4282887102728134e-05, 'epoch': 0.07}) +[2026-07-26 20:10:17,262][starVLA.training.train_starvla][INFO] - Step 554, Loss: {'train/loss': 0.6276658773422241, 'train/grad_norm_pre_clip': 5.522797584533691, 'timing/data': 0.00020042015239596367, 'timing/model': 0.47167001385241747, 'learning_rate/action_model': 9.712126993810933e-05, 'learning_rate/action_query_proj': 9.712126993810933e-05, 'learning_rate/base': 2.4280317484527334e-05, 'epoch': 0.07}) +[2026-07-26 20:10:22,838][starVLA.training.train_starvla][INFO] - Step 555, Loss: {'train/loss': 0.7575215101242065, 'train/grad_norm_pre_clip': 5.664031982421875, 'timing/data': 0.00021550478413701057, 'timing/model': 0.47737004701048136, 'learning_rate/action_model': 9.711097365214335e-05, 'learning_rate/action_query_proj': 9.711097365214335e-05, 'learning_rate/base': 2.4277743413035837e-05, 'epoch': 0.07}) +[2026-07-26 20:10:28,630][starVLA.training.train_starvla][INFO] - Step 556, Loss: {'train/loss': 0.536817193031311, 'train/grad_norm_pre_clip': 4.8425397872924805, 'timing/data': 0.00018840236589312553, 'timing/model': 0.4729493176564574, 'learning_rate/action_model': 9.710065955707938e-05, 'learning_rate/action_query_proj': 9.710065955707938e-05, 'learning_rate/base': 2.4275164889269844e-05, 'epoch': 0.07}) +[2026-07-26 20:10:34,177][starVLA.training.train_starvla][INFO] - Step 557, Loss: {'train/loss': 0.612140417098999, 'train/grad_norm_pre_clip': 7.087086200714111, 'timing/data': 0.00018056808039546013, 'timing/model': 0.4695581351406872, 'learning_rate/action_model': 9.709032765698926e-05, 'learning_rate/action_query_proj': 9.709032765698926e-05, 'learning_rate/base': 2.4272581914247316e-05, 'epoch': 0.07}) +[2026-07-26 20:10:39,715][starVLA.training.train_starvla][INFO] - Step 558, Loss: {'train/loss': 0.6101267337799072, 'train/grad_norm_pre_clip': 4.6145734786987305, 'timing/data': 0.00018504634499549866, 'timing/model': 0.47852194542065263, 'learning_rate/action_model': 9.70799779559519e-05, 'learning_rate/action_query_proj': 9.70799779559519e-05, 'learning_rate/base': 2.4269994488987973e-05, 'epoch': 0.07}) +[2026-07-26 20:10:45,245][starVLA.training.train_starvla][INFO] - Step 559, Loss: {'train/loss': 0.6020301580429077, 'train/grad_norm_pre_clip': 3.398310422897339, 'timing/data': 0.00018733786419034004, 'timing/model': 0.47104914858937263, 'learning_rate/action_model': 9.706961045805315e-05, 'learning_rate/action_query_proj': 9.706961045805315e-05, 'learning_rate/base': 2.426740261451329e-05, 'epoch': 0.07}) +[2026-07-26 20:10:50,773][starVLA.training.train_starvla][INFO] - Step 560, Loss: {'train/loss': 0.6757627129554749, 'train/grad_norm_pre_clip': 4.0375237464904785, 'timing/data': 0.0001926789991557598, 'timing/model': 0.47274479316547513, 'learning_rate/action_model': 9.705922516738596e-05, 'learning_rate/action_query_proj': 9.705922516738596e-05, 'learning_rate/base': 2.426480629184649e-05, 'epoch': 0.07}) +[2026-07-26 20:10:56,309][starVLA.training.train_starvla][INFO] - Step 561, Loss: {'train/loss': 0.6067506670951843, 'train/grad_norm_pre_clip': 3.8065004348754883, 'timing/data': 0.00018644193187355995, 'timing/model': 0.4724201038479805, 'learning_rate/action_model': 9.704882208805029e-05, 'learning_rate/action_query_proj': 9.704882208805029e-05, 'learning_rate/base': 2.426220552201257e-05, 'epoch': 0.07}) +[2026-07-26 20:11:01,837][starVLA.training.train_starvla][INFO] - Step 562, Loss: {'train/loss': 0.6101744174957275, 'train/grad_norm_pre_clip': 6.602581024169922, 'timing/data': 0.0001995367929339409, 'timing/model': 0.4694081572815776, 'learning_rate/action_model': 9.703840122415306e-05, 'learning_rate/action_query_proj': 9.703840122415306e-05, 'learning_rate/base': 2.4259600306038266e-05, 'epoch': 0.07}) +[2026-07-26 20:11:07,359][starVLA.training.train_starvla][INFO] - Step 563, Loss: {'train/loss': 0.5471642017364502, 'train/grad_norm_pre_clip': 6.242269515991211, 'timing/data': 0.0002461741678416729, 'timing/model': 0.4707471518777311, 'learning_rate/action_model': 9.702796257980835e-05, 'learning_rate/action_query_proj': 9.702796257980835e-05, 'learning_rate/base': 2.4256990644952087e-05, 'epoch': 0.07}) +[2026-07-26 20:11:12,892][starVLA.training.train_starvla][INFO] - Step 564, Loss: {'train/loss': 0.6766417026519775, 'train/grad_norm_pre_clip': 4.9427170753479, 'timing/data': 0.00018459884449839592, 'timing/model': 0.4640133767388761, 'learning_rate/action_model': 9.701750615913707e-05, 'learning_rate/action_query_proj': 9.701750615913707e-05, 'learning_rate/base': 2.425437653978427e-05, 'epoch': 0.07}) +[2026-07-26 20:11:18,454][starVLA.training.train_starvla][INFO] - Step 565, Loss: {'train/loss': 0.5631221532821655, 'train/grad_norm_pre_clip': 3.4333107471466064, 'timing/data': 0.00018103700131177902, 'timing/model': 0.4639375461265445, 'learning_rate/action_model': 9.700703196626731e-05, 'learning_rate/action_query_proj': 9.700703196626731e-05, 'learning_rate/base': 2.4251757991566827e-05, 'epoch': 0.07}) +[2026-07-26 20:11:24,038][starVLA.training.train_starvla][INFO] - Step 566, Loss: {'train/loss': 0.6353473663330078, 'train/grad_norm_pre_clip': 6.678514003753662, 'timing/data': 0.00019067293033003807, 'timing/model': 0.4605113798752427, 'learning_rate/action_model': 9.699654000533413e-05, 'learning_rate/action_query_proj': 9.699654000533413e-05, 'learning_rate/base': 2.4249135001333532e-05, 'epoch': 0.07}) +[2026-07-26 20:11:29,642][starVLA.training.train_starvla][INFO] - Step 567, Loss: {'train/loss': 0.5660951137542725, 'train/grad_norm_pre_clip': 3.5248446464538574, 'timing/data': 0.00018358184024691582, 'timing/model': 0.46087597496807575, 'learning_rate/action_model': 9.698603028047954e-05, 'learning_rate/action_query_proj': 9.698603028047954e-05, 'learning_rate/base': 2.4246507570119884e-05, 'epoch': 0.07}) +[2026-07-26 20:11:35,311][starVLA.training.train_starvla][INFO] - Step 568, Loss: {'train/loss': 0.6293078064918518, 'train/grad_norm_pre_clip': 7.0371809005737305, 'timing/data': 0.000184536911547184, 'timing/model': 0.4635300999507308, 'learning_rate/action_model': 9.697550279585263e-05, 'learning_rate/action_query_proj': 9.697550279585263e-05, 'learning_rate/base': 2.4243875698963157e-05, 'epoch': 0.07}) +[2026-07-26 20:11:40,978][starVLA.training.train_starvla][INFO] - Step 569, Loss: {'train/loss': 0.620280385017395, 'train/grad_norm_pre_clip': 7.129940986633301, 'timing/data': 0.00018090615049004555, 'timing/model': 0.4611504413187504, 'learning_rate/action_model': 9.69649575556095e-05, 'learning_rate/action_query_proj': 9.69649575556095e-05, 'learning_rate/base': 2.4241239388902375e-05, 'epoch': 0.07}) +[2026-07-26 20:11:46,593][starVLA.training.train_starvla][INFO] - Step 570, Loss: {'train/loss': 0.7104586362838745, 'train/grad_norm_pre_clip': 8.073452949523926, 'timing/data': 0.00018814019858837128, 'timing/model': 0.46411707904189825, 'learning_rate/action_model': 9.695439456391323e-05, 'learning_rate/action_query_proj': 9.695439456391323e-05, 'learning_rate/base': 2.4238598640978308e-05, 'epoch': 0.07}) +[2026-07-26 20:11:52,251][starVLA.training.train_starvla][INFO] - Step 571, Loss: {'train/loss': 0.7954831123352051, 'train/grad_norm_pre_clip': 5.296655178070068, 'timing/data': 0.0001852964051067829, 'timing/model': 0.46185107436031103, 'learning_rate/action_model': 9.694381382493394e-05, 'learning_rate/action_query_proj': 9.694381382493394e-05, 'learning_rate/base': 2.4235953456233485e-05, 'epoch': 0.07}) +[2026-07-26 20:11:57,847][starVLA.training.train_starvla][INFO] - Step 572, Loss: {'train/loss': 0.6361193656921387, 'train/grad_norm_pre_clip': 5.245167255401611, 'timing/data': 0.0001830151304602623, 'timing/model': 0.46411507623270154, 'learning_rate/action_model': 9.693321534284872e-05, 'learning_rate/action_query_proj': 9.693321534284872e-05, 'learning_rate/base': 2.423330383571218e-05, 'epoch': 0.07}) +[2026-07-26 20:12:03,487][starVLA.training.train_starvla][INFO] - Step 573, Loss: {'train/loss': 0.5961489677429199, 'train/grad_norm_pre_clip': 5.645922660827637, 'timing/data': 0.00018155621364712715, 'timing/model': 0.4618507381528616, 'learning_rate/action_model': 9.692259912184169e-05, 'learning_rate/action_query_proj': 9.692259912184169e-05, 'learning_rate/base': 2.4230649780460422e-05, 'epoch': 0.07}) +[2026-07-26 20:12:09,118][starVLA.training.train_starvla][INFO] - Step 574, Loss: {'train/loss': 0.559242308139801, 'train/grad_norm_pre_clip': 3.6768105030059814, 'timing/data': 0.000180885661393404, 'timing/model': 0.4622802813537419, 'learning_rate/action_model': 9.691196516610395e-05, 'learning_rate/action_query_proj': 9.691196516610395e-05, 'learning_rate/base': 2.4227991291525987e-05, 'epoch': 0.07}) +[2026-07-26 20:12:14,743][starVLA.training.train_starvla][INFO] - Step 575, Loss: {'train/loss': 0.5742342472076416, 'train/grad_norm_pre_clip': 3.9418320655822754, 'timing/data': 0.0001832791604101658, 'timing/model': 0.46520721400156617, 'learning_rate/action_model': 9.690131347983364e-05, 'learning_rate/action_query_proj': 9.690131347983364e-05, 'learning_rate/base': 2.422532836995841e-05, 'epoch': 0.07}) +[2026-07-26 20:12:20,390][starVLA.training.train_starvla][INFO] - Step 576, Loss: {'train/loss': 0.7355093359947205, 'train/grad_norm_pre_clip': 9.39899730682373, 'timing/data': 0.00034976983442902565, 'timing/model': 0.4717306960374117, 'learning_rate/action_model': 9.689064406723585e-05, 'learning_rate/action_query_proj': 9.689064406723585e-05, 'learning_rate/base': 2.4222661016808963e-05, 'epoch': 0.07}) +[2026-07-26 20:12:26,011][starVLA.training.train_starvla][INFO] - Step 577, Loss: {'train/loss': 0.565062403678894, 'train/grad_norm_pre_clip': 7.052204132080078, 'timing/data': 0.00017683999612927437, 'timing/model': 0.47233157185837626, 'learning_rate/action_model': 9.687995693252274e-05, 'learning_rate/action_query_proj': 9.687995693252274e-05, 'learning_rate/base': 2.4219989233130686e-05, 'epoch': 0.07}) +[2026-07-26 20:12:31,589][starVLA.training.train_starvla][INFO] - Step 578, Loss: {'train/loss': 0.7004107236862183, 'train/grad_norm_pre_clip': 8.792858123779297, 'timing/data': 0.00016832491382956505, 'timing/model': 0.47171463584527373, 'learning_rate/action_model': 9.686925207991339e-05, 'learning_rate/action_query_proj': 9.686925207991339e-05, 'learning_rate/base': 2.4217313019978348e-05, 'epoch': 0.07}) +[2026-07-26 20:12:37,442][starVLA.training.train_starvla][INFO] - Step 579, Loss: {'train/loss': 0.5553097128868103, 'train/grad_norm_pre_clip': 3.941952705383301, 'timing/data': 0.0001771850511431694, 'timing/model': 0.46328681986778975, 'learning_rate/action_model': 9.68585295136339e-05, 'learning_rate/action_query_proj': 9.68585295136339e-05, 'learning_rate/base': 2.4214632378408474e-05, 'epoch': 0.07}) +[2026-07-26 20:12:43,250][starVLA.training.train_starvla][INFO] - Step 580, Loss: {'train/loss': 0.5066345930099487, 'train/grad_norm_pre_clip': 3.438035726547241, 'timing/data': 0.00018206611275672913, 'timing/model': 0.45672929426655173, 'learning_rate/action_model': 9.684778923791739e-05, 'learning_rate/action_query_proj': 9.684778923791739e-05, 'learning_rate/base': 2.4211947309479347e-05, 'epoch': 0.07}) +[2026-07-26 20:12:49,016][starVLA.training.train_starvla][INFO] - Step 581, Loss: {'train/loss': 0.6193366646766663, 'train/grad_norm_pre_clip': 9.035451889038086, 'timing/data': 0.00021676719188690186, 'timing/model': 0.45663926005363464, 'learning_rate/action_model': 9.683703125700392e-05, 'learning_rate/action_query_proj': 9.683703125700392e-05, 'learning_rate/base': 2.420925781425098e-05, 'epoch': 0.07}) +[2026-07-26 20:12:54,549][starVLA.training.train_starvla][INFO] - Step 582, Loss: {'train/loss': 0.726446807384491, 'train/grad_norm_pre_clip': 8.592355728149414, 'timing/data': 0.00017398595809936523, 'timing/model': 0.46224374417215586, 'learning_rate/action_model': 9.682625557514062e-05, 'learning_rate/action_query_proj': 9.682625557514062e-05, 'learning_rate/base': 2.4206563893785156e-05, 'epoch': 0.07}) +[2026-07-26 20:13:00,114][starVLA.training.train_starvla][INFO] - Step 583, Loss: {'train/loss': 0.6370711922645569, 'train/grad_norm_pre_clip': 5.294678211212158, 'timing/data': 0.00017403298988938332, 'timing/model': 0.4632210284471512, 'learning_rate/action_model': 9.68154621965815e-05, 'learning_rate/action_query_proj': 9.68154621965815e-05, 'learning_rate/base': 2.4203865549145376e-05, 'epoch': 0.07}) +[2026-07-26 20:13:05,670][starVLA.training.train_starvla][INFO] - Step 584, Loss: {'train/loss': 0.5502011775970459, 'train/grad_norm_pre_clip': 5.794432640075684, 'timing/data': 0.00017894012853503227, 'timing/model': 0.46149086812511086, 'learning_rate/action_model': 9.680465112558767e-05, 'learning_rate/action_query_proj': 9.680465112558767e-05, 'learning_rate/base': 2.4201162781396917e-05, 'epoch': 0.07}) +[2026-07-26 20:13:11,246][starVLA.training.train_starvla][INFO] - Step 585, Loss: {'train/loss': 0.6775262355804443, 'train/grad_norm_pre_clip': 5.319969654083252, 'timing/data': 0.0001743449829518795, 'timing/model': 0.4658085950650275, 'learning_rate/action_model': 9.679382236642713e-05, 'learning_rate/action_query_proj': 9.679382236642713e-05, 'learning_rate/base': 2.4198455591606783e-05, 'epoch': 0.07}) +[2026-07-26 20:13:16,816][starVLA.training.train_starvla][INFO] - Step 586, Loss: {'train/loss': 0.6618008613586426, 'train/grad_norm_pre_clip': 5.419050693511963, 'timing/data': 0.00019344594329595566, 'timing/model': 0.463795087300241, 'learning_rate/action_model': 9.678297592337493e-05, 'learning_rate/action_query_proj': 9.678297592337493e-05, 'learning_rate/base': 2.4195743980843733e-05, 'epoch': 0.07}) +[2026-07-26 20:13:22,380][starVLA.training.train_starvla][INFO] - Step 587, Loss: {'train/loss': 0.7588507533073425, 'train/grad_norm_pre_clip': 7.679222106933594, 'timing/data': 0.00017506303265690804, 'timing/model': 0.46356853377074003, 'learning_rate/action_model': 9.677211180071304e-05, 'learning_rate/action_query_proj': 9.677211180071304e-05, 'learning_rate/base': 2.419302795017826e-05, 'epoch': 0.07}) +[2026-07-26 20:13:27,963][starVLA.training.train_starvla][INFO] - Step 588, Loss: {'train/loss': 0.5831575989723206, 'train/grad_norm_pre_clip': 5.165358066558838, 'timing/data': 0.00017634686082601547, 'timing/model': 0.4615069148130715, 'learning_rate/action_model': 9.676123000273049e-05, 'learning_rate/action_query_proj': 9.676123000273049e-05, 'learning_rate/base': 2.4190307500682622e-05, 'epoch': 0.07}) +[2026-07-26 20:13:33,538][starVLA.training.train_starvla][INFO] - Step 589, Loss: {'train/loss': 0.6208434104919434, 'train/grad_norm_pre_clip': 5.781717777252197, 'timing/data': 0.00017326883971691132, 'timing/model': 0.46395527478307486, 'learning_rate/action_model': 9.675033053372322e-05, 'learning_rate/action_query_proj': 9.675033053372322e-05, 'learning_rate/base': 2.4187582633430804e-05, 'epoch': 0.07}) +[2026-07-26 20:13:39,118][starVLA.training.train_starvla][INFO] - Step 590, Loss: {'train/loss': 0.4974210560321808, 'train/grad_norm_pre_clip': 6.284987926483154, 'timing/data': 0.00019570905715227127, 'timing/model': 0.46072312677279115, 'learning_rate/action_model': 9.673941339799412e-05, 'learning_rate/action_query_proj': 9.673941339799412e-05, 'learning_rate/base': 2.418485334949853e-05, 'epoch': 0.07}) +[2026-07-26 20:13:44,702][starVLA.training.train_starvla][INFO] - Step 591, Loss: {'train/loss': 0.6723417043685913, 'train/grad_norm_pre_clip': 6.975924015045166, 'timing/data': 0.00018653925508260727, 'timing/model': 0.4621264529414475, 'learning_rate/action_model': 9.672847859985318e-05, 'learning_rate/action_query_proj': 9.672847859985318e-05, 'learning_rate/base': 2.4182119649963294e-05, 'epoch': 0.07}) +[2026-07-26 20:13:50,290][starVLA.training.train_starvla][INFO] - Step 592, Loss: {'train/loss': 0.6486771702766418, 'train/grad_norm_pre_clip': 8.419885635375977, 'timing/data': 0.0001821666955947876, 'timing/model': 0.4623966426588595, 'learning_rate/action_model': 9.671752614361726e-05, 'learning_rate/action_query_proj': 9.671752614361726e-05, 'learning_rate/base': 2.4179381535904314e-05, 'epoch': 0.07}) +[2026-07-26 20:13:55,935][starVLA.training.train_starvla][INFO] - Step 593, Loss: {'train/loss': 0.6619083881378174, 'train/grad_norm_pre_clip': 4.649720191955566, 'timing/data': 0.00024402793496847153, 'timing/model': 0.4643614017404616, 'learning_rate/action_model': 9.670655603361018e-05, 'learning_rate/action_query_proj': 9.670655603361018e-05, 'learning_rate/base': 2.4176639008402545e-05, 'epoch': 0.07}) +[2026-07-26 20:14:01,544][starVLA.training.train_starvla][INFO] - Step 594, Loss: {'train/loss': 0.4803377389907837, 'train/grad_norm_pre_clip': 3.604078769683838, 'timing/data': 0.00019106920808553696, 'timing/model': 0.46030958089977503, 'learning_rate/action_model': 9.669556827416282e-05, 'learning_rate/action_query_proj': 9.669556827416282e-05, 'learning_rate/base': 2.4173892068540704e-05, 'epoch': 0.07}) +[2026-07-26 20:14:07,142][starVLA.training.train_starvla][INFO] - Step 595, Loss: {'train/loss': 0.5440921783447266, 'train/grad_norm_pre_clip': 6.382340908050537, 'timing/data': 0.00021668337285518646, 'timing/model': 0.46847739396616817, 'learning_rate/action_model': 9.668456286961291e-05, 'learning_rate/action_query_proj': 9.668456286961291e-05, 'learning_rate/base': 2.4171140717403227e-05, 'epoch': 0.07}) +[2026-07-26 20:14:12,684][starVLA.training.train_starvla][INFO] - Step 596, Loss: {'train/loss': 0.55198734998703, 'train/grad_norm_pre_clip': 8.35311508178711, 'timing/data': 0.00018430501222610474, 'timing/model': 0.4581981939263642, 'learning_rate/action_model': 9.667353982430528e-05, 'learning_rate/action_query_proj': 9.667353982430528e-05, 'learning_rate/base': 2.416838495607632e-05, 'epoch': 0.07}) +[2026-07-26 20:14:18,243][starVLA.training.train_starvla][INFO] - Step 597, Loss: {'train/loss': 0.7132745981216431, 'train/grad_norm_pre_clip': 8.15067195892334, 'timing/data': 0.00018954509869217873, 'timing/model': 0.4634108766913414, 'learning_rate/action_model': 9.666249914259162e-05, 'learning_rate/action_query_proj': 9.666249914259162e-05, 'learning_rate/base': 2.4165624785647904e-05, 'epoch': 0.07}) +[2026-07-26 20:14:23,815][starVLA.training.train_starvla][INFO] - Step 598, Loss: {'train/loss': 0.7298953533172607, 'train/grad_norm_pre_clip': 10.771401405334473, 'timing/data': 0.0001786341890692711, 'timing/model': 0.47243786836043, 'learning_rate/action_model': 9.665144082883059e-05, 'learning_rate/action_query_proj': 9.665144082883059e-05, 'learning_rate/base': 2.4162860207207646e-05, 'epoch': 0.07}) +[2026-07-26 20:14:29,386][starVLA.training.train_starvla][INFO] - Step 599, Loss: {'train/loss': 0.7199805378913879, 'train/grad_norm_pre_clip': 7.84757661819458, 'timing/data': 0.0001895669847726822, 'timing/model': 0.47097906237468123, 'learning_rate/action_model': 9.664036488738788e-05, 'learning_rate/action_query_proj': 9.664036488738788e-05, 'learning_rate/base': 2.416009122184697e-05, 'epoch': 0.07}) +[2026-07-26 20:14:34,944][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 600 +[2026-07-26 20:14:34,944][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 600 +[2026-07-26 20:14:34,945][starVLA.training.train_starvla][INFO] - Step 600, Loss: {'train/loss': 0.5436776876449585, 'train/grad_norm_pre_clip': 3.654341697692871, 'timing/data': 0.00017510680481791496, 'timing/model': 0.4587805881164968, 'learning_rate/action_model': 9.662927132263607e-05, 'learning_rate/action_query_proj': 9.662927132263607e-05, 'learning_rate/base': 2.4157317830659017e-05, 'epoch': 0.07}) +[2026-07-26 20:14:40,492][starVLA.training.train_starvla][INFO] - Step 601, Loss: {'train/loss': 0.6509490013122559, 'train/grad_norm_pre_clip': 5.639173984527588, 'timing/data': 0.00018506590276956558, 'timing/model': 0.46091835387051105, 'learning_rate/action_model': 9.661816013895474e-05, 'learning_rate/action_query_proj': 9.661816013895474e-05, 'learning_rate/base': 2.4154540034738685e-05, 'epoch': 0.07}) +[2026-07-26 20:14:46,009][starVLA.training.train_starvla][INFO] - Step 602, Loss: {'train/loss': 0.6424916386604309, 'train/grad_norm_pre_clip': 9.984859466552734, 'timing/data': 0.00017739087343215942, 'timing/model': 0.45845650508999825, 'learning_rate/action_model': 9.66070313407304e-05, 'learning_rate/action_query_proj': 9.66070313407304e-05, 'learning_rate/base': 2.41517578351826e-05, 'epoch': 0.07}) +[2026-07-26 20:14:51,505][starVLA.training.train_starvla][INFO] - Step 603, Loss: {'train/loss': 0.747978687286377, 'train/grad_norm_pre_clip': 8.827027320861816, 'timing/data': 0.0001704040914773941, 'timing/model': 0.4582449127919972, 'learning_rate/action_model': 9.659588493235653e-05, 'learning_rate/action_query_proj': 9.659588493235653e-05, 'learning_rate/base': 2.414897123308913e-05, 'epoch': 0.07}) +[2026-07-26 20:14:56,996][starVLA.training.train_starvla][INFO] - Step 604, Loss: {'train/loss': 0.8313806653022766, 'train/grad_norm_pre_clip': 11.092503547668457, 'timing/data': 0.00018247123807668686, 'timing/model': 0.4587792023085058, 'learning_rate/action_model': 9.658472091823355e-05, 'learning_rate/action_query_proj': 9.658472091823355e-05, 'learning_rate/base': 2.4146180229558388e-05, 'epoch': 0.07}) +[2026-07-26 20:15:02,502][starVLA.training.train_starvla][INFO] - Step 605, Loss: {'train/loss': 0.6040728092193604, 'train/grad_norm_pre_clip': 7.613739490509033, 'timing/data': 0.0002046041190624237, 'timing/model': 0.4583141813054681, 'learning_rate/action_model': 9.657353930276884e-05, 'learning_rate/action_query_proj': 9.657353930276884e-05, 'learning_rate/base': 2.414338482569221e-05, 'epoch': 0.07}) +[2026-07-26 20:15:08,005][starVLA.training.train_starvla][INFO] - Step 606, Loss: {'train/loss': 0.6096095442771912, 'train/grad_norm_pre_clip': 3.56823468208313, 'timing/data': 0.00017718598246574402, 'timing/model': 0.4587322617881, 'learning_rate/action_model': 9.656234009037672e-05, 'learning_rate/action_query_proj': 9.656234009037672e-05, 'learning_rate/base': 2.414058502259418e-05, 'epoch': 0.07}) +[2026-07-26 20:15:13,495][starVLA.training.train_starvla][INFO] - Step 607, Loss: {'train/loss': 0.6118016242980957, 'train/grad_norm_pre_clip': 5.970162868499756, 'timing/data': 0.00017480086535215378, 'timing/model': 0.4579705102369189, 'learning_rate/action_model': 9.655112328547846e-05, 'learning_rate/action_query_proj': 9.655112328547846e-05, 'learning_rate/base': 2.4137780821369614e-05, 'epoch': 0.07}) +[2026-07-26 20:15:18,986][starVLA.training.train_starvla][INFO] - Step 608, Loss: {'train/loss': 0.6249397397041321, 'train/grad_norm_pre_clip': 7.494866371154785, 'timing/data': 0.0001859869807958603, 'timing/model': 0.4575904542580247, 'learning_rate/action_model': 9.653988889250227e-05, 'learning_rate/action_query_proj': 9.653988889250227e-05, 'learning_rate/base': 2.4134972223125567e-05, 'epoch': 0.07}) +[2026-07-26 20:15:24,511][starVLA.training.train_starvla][INFO] - Step 609, Loss: {'train/loss': 0.6708627343177795, 'train/grad_norm_pre_clip': 6.866824150085449, 'timing/data': 0.0001754043623805046, 'timing/model': 0.45839657122269273, 'learning_rate/action_model': 9.652863691588334e-05, 'learning_rate/action_query_proj': 9.652863691588334e-05, 'learning_rate/base': 2.4132159228970834e-05, 'epoch': 0.07}) +[2026-07-26 20:15:30,047][starVLA.training.train_starvla][INFO] - Step 610, Loss: {'train/loss': 0.6190694570541382, 'train/grad_norm_pre_clip': 3.1460869312286377, 'timing/data': 0.00017202086746692657, 'timing/model': 0.45873300917446613, 'learning_rate/action_model': 9.651736736006375e-05, 'learning_rate/action_query_proj': 9.651736736006375e-05, 'learning_rate/base': 2.4129341840015938e-05, 'epoch': 0.07}) +[2026-07-26 20:15:35,592][starVLA.training.train_starvla][INFO] - Step 611, Loss: {'train/loss': 0.506838321685791, 'train/grad_norm_pre_clip': 4.354320049285889, 'timing/data': 0.00016823504120111465, 'timing/model': 0.4570047240704298, 'learning_rate/action_model': 9.650608022949255e-05, 'learning_rate/action_query_proj': 9.650608022949255e-05, 'learning_rate/base': 2.4126520057373138e-05, 'epoch': 0.07}) +[2026-07-26 20:15:41,165][starVLA.training.train_starvla][INFO] - Step 612, Loss: {'train/loss': 0.6359440088272095, 'train/grad_norm_pre_clip': 7.011727333068848, 'timing/data': 0.0001819739118218422, 'timing/model': 0.45701962523162365, 'learning_rate/action_model': 9.64947755286257e-05, 'learning_rate/action_query_proj': 9.64947755286257e-05, 'learning_rate/base': 2.4123693882156424e-05, 'epoch': 0.07}) +[2026-07-26 20:15:46,715][starVLA.training.train_starvla][INFO] - Step 613, Loss: {'train/loss': 0.6955208778381348, 'train/grad_norm_pre_clip': 4.867564678192139, 'timing/data': 0.00018706126138567924, 'timing/model': 0.45871904492378235, 'learning_rate/action_model': 9.648345326192614e-05, 'learning_rate/action_query_proj': 9.648345326192614e-05, 'learning_rate/base': 2.4120863315481535e-05, 'epoch': 0.07}) +[2026-07-26 20:15:52,384][starVLA.training.train_starvla][INFO] - Step 614, Loss: {'train/loss': 0.608132004737854, 'train/grad_norm_pre_clip': 4.8429155349731445, 'timing/data': 0.00018930109217762947, 'timing/model': 0.45833706203848124, 'learning_rate/action_model': 9.647211343386371e-05, 'learning_rate/action_query_proj': 9.647211343386371e-05, 'learning_rate/base': 2.4118028358465927e-05, 'epoch': 0.07}) +[2026-07-26 20:15:57,959][starVLA.training.train_starvla][INFO] - Step 615, Loss: {'train/loss': 0.47632673382759094, 'train/grad_norm_pre_clip': 2.903928518295288, 'timing/data': 0.00018287589773535728, 'timing/model': 0.4567256458103657, 'learning_rate/action_model': 9.64607560489152e-05, 'learning_rate/action_query_proj': 9.64607560489152e-05, 'learning_rate/base': 2.41151890122288e-05, 'epoch': 0.07}) +[2026-07-26 20:16:03,480][starVLA.training.train_starvla][INFO] - Step 616, Loss: {'train/loss': 0.5137022137641907, 'train/grad_norm_pre_clip': 5.010211944580078, 'timing/data': 0.00017272494733333588, 'timing/model': 0.456894570030272, 'learning_rate/action_model': 9.644938111156433e-05, 'learning_rate/action_query_proj': 9.644938111156433e-05, 'learning_rate/base': 2.4112345277891082e-05, 'epoch': 0.07}) +[2026-07-26 20:16:09,010][starVLA.training.train_starvla][INFO] - Step 617, Loss: {'train/loss': 0.5213355422019958, 'train/grad_norm_pre_clip': 4.995055198669434, 'timing/data': 0.000188509002327919, 'timing/model': 0.4577439851127565, 'learning_rate/action_model': 9.643798862630174e-05, 'learning_rate/action_query_proj': 9.643798862630174e-05, 'learning_rate/base': 2.4109497156575435e-05, 'epoch': 0.07}) +[2026-07-26 20:16:14,543][starVLA.training.train_starvla][INFO] - Step 618, Loss: {'train/loss': 0.5044130682945251, 'train/grad_norm_pre_clip': 3.564441680908203, 'timing/data': 0.0001715659163892269, 'timing/model': 0.4573924709111452, 'learning_rate/action_model': 9.6426578597625e-05, 'learning_rate/action_query_proj': 9.6426578597625e-05, 'learning_rate/base': 2.410664464940625e-05, 'epoch': 0.07}) +[2026-07-26 20:16:20,082][starVLA.training.train_starvla][INFO] - Step 619, Loss: {'train/loss': 0.6294130086898804, 'train/grad_norm_pre_clip': 2.781555414199829, 'timing/data': 0.00018331175670027733, 'timing/model': 0.45808473508805037, 'learning_rate/action_model': 9.64151510300386e-05, 'learning_rate/action_query_proj': 9.64151510300386e-05, 'learning_rate/base': 2.410378775750965e-05, 'epoch': 0.08}) +[2026-07-26 20:16:25,595][starVLA.training.train_starvla][INFO] - Step 620, Loss: {'train/loss': 0.5713695287704468, 'train/grad_norm_pre_clip': 2.7661614418029785, 'timing/data': 0.00018706917762756348, 'timing/model': 0.4581088460981846, 'learning_rate/action_model': 9.640370592805399e-05, 'learning_rate/action_query_proj': 9.640370592805399e-05, 'learning_rate/base': 2.4100926482013497e-05, 'epoch': 0.08}) +[2026-07-26 20:16:31,103][starVLA.training.train_starvla][INFO] - Step 621, Loss: {'train/loss': 0.5016851425170898, 'train/grad_norm_pre_clip': 3.4450490474700928, 'timing/data': 0.00018128380179405212, 'timing/model': 0.45731583423912525, 'learning_rate/action_model': 9.63922432961895e-05, 'learning_rate/action_query_proj': 9.63922432961895e-05, 'learning_rate/base': 2.4098060824047376e-05, 'epoch': 0.08}) +[2026-07-26 20:16:36,626][starVLA.training.train_starvla][INFO] - Step 622, Loss: {'train/loss': 0.7532991170883179, 'train/grad_norm_pre_clip': 4.702374458312988, 'timing/data': 0.0001798928715288639, 'timing/model': 0.45948707312345505, 'learning_rate/action_model': 9.638076313897037e-05, 'learning_rate/action_query_proj': 9.638076313897037e-05, 'learning_rate/base': 2.4095190784742594e-05, 'epoch': 0.08}) +[2026-07-26 20:16:42,323][starVLA.training.train_starvla][INFO] - Step 623, Loss: {'train/loss': 0.5364319086074829, 'train/grad_norm_pre_clip': 2.8224008083343506, 'timing/data': 0.0001791827380657196, 'timing/model': 0.6443565771915019, 'learning_rate/action_model': 9.636926546092883e-05, 'learning_rate/action_query_proj': 9.636926546092883e-05, 'learning_rate/base': 2.4092316365232208e-05, 'epoch': 0.08}) +[2026-07-26 20:16:47,852][starVLA.training.train_starvla][INFO] - Step 624, Loss: {'train/loss': 0.5847437977790833, 'train/grad_norm_pre_clip': 3.680149555206299, 'timing/data': 0.0001840507611632347, 'timing/model': 0.4577669412828982, 'learning_rate/action_model': 9.635775026660396e-05, 'learning_rate/action_query_proj': 9.635775026660396e-05, 'learning_rate/base': 2.408943756665099e-05, 'epoch': 0.08}) +[2026-07-26 20:16:53,372][starVLA.training.train_starvla][INFO] - Step 625, Loss: {'train/loss': 0.6417605876922607, 'train/grad_norm_pre_clip': 5.211799621582031, 'timing/data': 0.00017577502876520157, 'timing/model': 0.4586287601850927, 'learning_rate/action_model': 9.634621756054177e-05, 'learning_rate/action_query_proj': 9.634621756054177e-05, 'learning_rate/base': 2.4086554390135442e-05, 'epoch': 0.08}) +[2026-07-26 20:16:58,913][starVLA.training.train_starvla][INFO] - Step 626, Loss: {'train/loss': 0.5109058022499084, 'train/grad_norm_pre_clip': 4.980079650878906, 'timing/data': 0.00018638698384165764, 'timing/model': 0.45685567799955606, 'learning_rate/action_model': 9.63346673472952e-05, 'learning_rate/action_query_proj': 9.63346673472952e-05, 'learning_rate/base': 2.40836668368238e-05, 'epoch': 0.08}) +[2026-07-26 20:17:04,446][starVLA.training.train_starvla][INFO] - Step 627, Loss: {'train/loss': 0.6371976733207703, 'train/grad_norm_pre_clip': 4.274777889251709, 'timing/data': 0.00017887819558382034, 'timing/model': 0.4589893571101129, 'learning_rate/action_model': 9.632309963142407e-05, 'learning_rate/action_query_proj': 9.632309963142407e-05, 'learning_rate/base': 2.408077490785602e-05, 'epoch': 0.08}) +[2026-07-26 20:17:10,166][starVLA.training.train_starvla][INFO] - Step 628, Loss: {'train/loss': 0.6491130590438843, 'train/grad_norm_pre_clip': 3.178896903991699, 'timing/data': 0.00018388405442237854, 'timing/model': 0.45704902010038495, 'learning_rate/action_model': 9.631151441749517e-05, 'learning_rate/action_query_proj': 9.631151441749517e-05, 'learning_rate/base': 2.407787860437379e-05, 'epoch': 0.08}) +[2026-07-26 20:17:15,696][starVLA.training.train_starvla][INFO] - Step 629, Loss: {'train/loss': 0.6230036616325378, 'train/grad_norm_pre_clip': 5.724732398986816, 'timing/data': 0.0001788930967450142, 'timing/model': 0.4576171049848199, 'learning_rate/action_model': 9.629991171008213e-05, 'learning_rate/action_query_proj': 9.629991171008213e-05, 'learning_rate/base': 2.407497792752053e-05, 'epoch': 0.08}) +[2026-07-26 20:17:21,234][starVLA.training.train_starvla][INFO] - Step 630, Loss: {'train/loss': 0.6118643283843994, 'train/grad_norm_pre_clip': 4.400350093841553, 'timing/data': 0.0001797843724489212, 'timing/model': 0.457464758772403, 'learning_rate/action_model': 9.628829151376552e-05, 'learning_rate/action_query_proj': 9.628829151376552e-05, 'learning_rate/base': 2.407207287844138e-05, 'epoch': 0.08}) +[2026-07-26 20:17:26,776][starVLA.training.train_starvla][INFO] - Step 631, Loss: {'train/loss': 0.5345960855484009, 'train/grad_norm_pre_clip': 4.568695545196533, 'timing/data': 0.00018027424812316895, 'timing/model': 0.4577495288103819, 'learning_rate/action_model': 9.62766538331328e-05, 'learning_rate/action_query_proj': 9.62766538331328e-05, 'learning_rate/base': 2.40691634582832e-05, 'epoch': 0.08}) +[2026-07-26 20:17:32,309][starVLA.training.train_starvla][INFO] - Step 632, Loss: {'train/loss': 0.6081478595733643, 'train/grad_norm_pre_clip': 5.766516208648682, 'timing/data': 0.0001798267476260662, 'timing/model': 0.4553304733708501, 'learning_rate/action_model': 9.626499867277837e-05, 'learning_rate/action_query_proj': 9.626499867277837e-05, 'learning_rate/base': 2.4066249668194593e-05, 'epoch': 0.08}) +[2026-07-26 20:17:37,822][starVLA.training.train_starvla][INFO] - Step 633, Loss: {'train/loss': 0.6911258697509766, 'train/grad_norm_pre_clip': 5.12955904006958, 'timing/data': 0.00018969085067510605, 'timing/model': 0.4567503831349313, 'learning_rate/action_model': 9.62533260373035e-05, 'learning_rate/action_query_proj': 9.62533260373035e-05, 'learning_rate/base': 2.4063331509325873e-05, 'epoch': 0.08}) +[2026-07-26 20:17:43,344][starVLA.training.train_starvla][INFO] - Step 634, Loss: {'train/loss': 0.5515021681785583, 'train/grad_norm_pre_clip': 3.6879754066467285, 'timing/data': 0.00018456391990184784, 'timing/model': 0.45836011366918683, 'learning_rate/action_model': 9.624163593131632e-05, 'learning_rate/action_query_proj': 9.624163593131632e-05, 'learning_rate/base': 2.406040898282908e-05, 'epoch': 0.08}) +[2026-07-26 20:17:48,866][starVLA.training.train_starvla][INFO] - Step 635, Loss: {'train/loss': 0.5764368176460266, 'train/grad_norm_pre_clip': 3.1009998321533203, 'timing/data': 0.00018210988491773605, 'timing/model': 0.4600588041357696, 'learning_rate/action_model': 9.622992835943193e-05, 'learning_rate/action_query_proj': 9.622992835943193e-05, 'learning_rate/base': 2.4057482089857984e-05, 'epoch': 0.08}) +[2026-07-26 20:17:54,374][starVLA.training.train_starvla][INFO] - Step 636, Loss: {'train/loss': 0.716253399848938, 'train/grad_norm_pre_clip': 5.561460018157959, 'timing/data': 0.00017433194443583488, 'timing/model': 0.45785538386553526, 'learning_rate/action_model': 9.621820332627229e-05, 'learning_rate/action_query_proj': 9.621820332627229e-05, 'learning_rate/base': 2.4054550831568072e-05, 'epoch': 0.08}) +[2026-07-26 20:17:59,882][starVLA.training.train_starvla][INFO] - Step 637, Loss: {'train/loss': 0.559985876083374, 'train/grad_norm_pre_clip': 5.583066463470459, 'timing/data': 0.00017458805814385414, 'timing/model': 0.45727886399254203, 'learning_rate/action_model': 9.620646083646627e-05, 'learning_rate/action_query_proj': 9.620646083646627e-05, 'learning_rate/base': 2.4051615209116568e-05, 'epoch': 0.08}) +[2026-07-26 20:18:05,381][starVLA.training.train_starvla][INFO] - Step 638, Loss: {'train/loss': 0.6979920864105225, 'train/grad_norm_pre_clip': 6.211972236633301, 'timing/data': 0.000180734321475029, 'timing/model': 0.4568876945413649, 'learning_rate/action_model': 9.61947008946496e-05, 'learning_rate/action_query_proj': 9.61947008946496e-05, 'learning_rate/base': 2.40486752236624e-05, 'epoch': 0.08}) +[2026-07-26 20:18:10,936][starVLA.training.train_starvla][INFO] - Step 639, Loss: {'train/loss': 0.5548914074897766, 'train/grad_norm_pre_clip': 4.710529804229736, 'timing/data': 0.00019147386774420738, 'timing/model': 0.45684816781431437, 'learning_rate/action_model': 9.618292350546494e-05, 'learning_rate/action_query_proj': 9.618292350546494e-05, 'learning_rate/base': 2.4045730876366235e-05, 'epoch': 0.08}) +[2026-07-26 20:18:16,483][starVLA.training.train_starvla][INFO] - Step 640, Loss: {'train/loss': 0.5621826648712158, 'train/grad_norm_pre_clip': 4.663843631744385, 'timing/data': 0.00018128566443920135, 'timing/model': 0.4798651169985533, 'learning_rate/action_model': 9.617112867356178e-05, 'learning_rate/action_query_proj': 9.617112867356178e-05, 'learning_rate/base': 2.4042782168390445e-05, 'epoch': 0.08}) +[2026-07-26 20:18:22,078][starVLA.training.train_starvla][INFO] - Step 641, Loss: {'train/loss': 0.5931486487388611, 'train/grad_norm_pre_clip': 6.800608158111572, 'timing/data': 0.0001730159856379032, 'timing/model': 0.4724626038223505, 'learning_rate/action_model': 9.615931640359656e-05, 'learning_rate/action_query_proj': 9.615931640359656e-05, 'learning_rate/base': 2.403982910089914e-05, 'epoch': 0.08}) +[2026-07-26 20:18:27,695][starVLA.training.train_starvla][INFO] - Step 642, Loss: {'train/loss': 0.4775437116622925, 'train/grad_norm_pre_clip': 4.980656623840332, 'timing/data': 0.00017936108633875847, 'timing/model': 0.47883119666948915, 'learning_rate/action_model': 9.614748670023258e-05, 'learning_rate/action_query_proj': 9.614748670023258e-05, 'learning_rate/base': 2.4036871675058145e-05, 'epoch': 0.08}) +[2026-07-26 20:18:33,293][starVLA.training.train_starvla][INFO] - Step 643, Loss: {'train/loss': 0.6347492933273315, 'train/grad_norm_pre_clip': 4.788478374481201, 'timing/data': 0.00016520405188202858, 'timing/model': 0.4714204058982432, 'learning_rate/action_model': 9.613563956814003e-05, 'learning_rate/action_query_proj': 9.613563956814003e-05, 'learning_rate/base': 2.4033909892035006e-05, 'epoch': 0.08}) +[2026-07-26 20:18:38,890][starVLA.training.train_starvla][INFO] - Step 644, Loss: {'train/loss': 0.419875830411911, 'train/grad_norm_pre_clip': 4.643676280975342, 'timing/data': 0.00018045492470264435, 'timing/model': 0.47106953617185354, 'learning_rate/action_model': 9.612377501199592e-05, 'learning_rate/action_query_proj': 9.612377501199592e-05, 'learning_rate/base': 2.403094375299898e-05, 'epoch': 0.08}) +[2026-07-26 20:18:44,735][starVLA.training.train_starvla][INFO] - Step 645, Loss: {'train/loss': 0.6772218346595764, 'train/grad_norm_pre_clip': 4.66179084777832, 'timing/data': 0.0002202303148806095, 'timing/model': 0.47380116395652294, 'learning_rate/action_model': 9.611189303648423e-05, 'learning_rate/action_query_proj': 9.611189303648423e-05, 'learning_rate/base': 2.4027973259121057e-05, 'epoch': 0.08}) +[2026-07-26 20:18:50,337][starVLA.training.train_starvla][INFO] - Step 646, Loss: {'train/loss': 0.7459173202514648, 'train/grad_norm_pre_clip': 5.219666957855225, 'timing/data': 0.00018106261268258095, 'timing/model': 0.4711604700423777, 'learning_rate/action_model': 9.609999364629577e-05, 'learning_rate/action_query_proj': 9.609999364629577e-05, 'learning_rate/base': 2.4024998411573942e-05, 'epoch': 0.08}) +[2026-07-26 20:18:55,919][starVLA.training.train_starvla][INFO] - Step 647, Loss: {'train/loss': 0.7163819074630737, 'train/grad_norm_pre_clip': 9.417684555053711, 'timing/data': 0.00019281217828392982, 'timing/model': 0.4731101030483842, 'learning_rate/action_model': 9.608807684612822e-05, 'learning_rate/action_query_proj': 9.608807684612822e-05, 'learning_rate/base': 2.4022019211532055e-05, 'epoch': 0.08}) +[2026-07-26 20:19:01,761][starVLA.training.train_starvla][INFO] - Step 648, Loss: {'train/loss': 0.7233068943023682, 'train/grad_norm_pre_clip': 6.174037933349609, 'timing/data': 0.00018392177298665047, 'timing/model': 0.47176668187603354, 'learning_rate/action_model': 9.607614264068618e-05, 'learning_rate/action_query_proj': 9.607614264068618e-05, 'learning_rate/base': 2.4019035660171544e-05, 'epoch': 0.08}) +[2026-07-26 20:19:07,339][starVLA.training.train_starvla][INFO] - Step 649, Loss: {'train/loss': 0.6328015923500061, 'train/grad_norm_pre_clip': 5.621515274047852, 'timing/data': 0.000177095178514719, 'timing/model': 0.47006399603560567, 'learning_rate/action_model': 9.606419103468103e-05, 'learning_rate/action_query_proj': 9.606419103468103e-05, 'learning_rate/base': 2.4016047758670257e-05, 'epoch': 0.08}) +[2026-07-26 20:19:13,016][starVLA.training.train_starvla][INFO] - Step 650, Loss: {'train/loss': 0.5111192464828491, 'train/grad_norm_pre_clip': 6.652774810791016, 'timing/data': 0.0001714932732284069, 'timing/model': 0.48189041297882795, 'learning_rate/action_model': 9.60522220328311e-05, 'learning_rate/action_query_proj': 9.60522220328311e-05, 'learning_rate/base': 2.4013055508207773e-05, 'epoch': 0.08}) +[2026-07-26 20:19:18,651][starVLA.training.train_starvla][INFO] - Step 651, Loss: {'train/loss': 0.6610980033874512, 'train/grad_norm_pre_clip': 3.8919503688812256, 'timing/data': 0.00017146114259958267, 'timing/model': 0.4704191782511771, 'learning_rate/action_model': 9.604023563986157e-05, 'learning_rate/action_query_proj': 9.604023563986157e-05, 'learning_rate/base': 2.4010058909965392e-05, 'epoch': 0.08}) +[2026-07-26 20:19:24,256][starVLA.training.train_starvla][INFO] - Step 652, Loss: {'train/loss': 0.507568895816803, 'train/grad_norm_pre_clip': 4.724951267242432, 'timing/data': 0.00018068915233016014, 'timing/model': 0.4720303528010845, 'learning_rate/action_model': 9.602823186050448e-05, 'learning_rate/action_query_proj': 9.602823186050448e-05, 'learning_rate/base': 2.400705796512612e-05, 'epoch': 0.08}) +[2026-07-26 20:19:29,875][starVLA.training.train_starvla][INFO] - Step 653, Loss: {'train/loss': 0.5324127674102783, 'train/grad_norm_pre_clip': 6.810641288757324, 'timing/data': 0.00017540901899337769, 'timing/model': 0.47241793014109135, 'learning_rate/action_model': 9.601621069949873e-05, 'learning_rate/action_query_proj': 9.601621069949873e-05, 'learning_rate/base': 2.400405267487468e-05, 'epoch': 0.08}) +[2026-07-26 20:19:35,475][starVLA.training.train_starvla][INFO] - Step 654, Loss: {'train/loss': 0.6422110795974731, 'train/grad_norm_pre_clip': 7.26339054107666, 'timing/data': 0.00019021891057491302, 'timing/model': 0.4760842667892575, 'learning_rate/action_model': 9.600417216159006e-05, 'learning_rate/action_query_proj': 9.600417216159006e-05, 'learning_rate/base': 2.4001043040397516e-05, 'epoch': 0.08}) +[2026-07-26 20:19:41,068][starVLA.training.train_starvla][INFO] - Step 655, Loss: {'train/loss': 0.6184243559837341, 'train/grad_norm_pre_clip': 5.374269008636475, 'timing/data': 0.00017372099682688713, 'timing/model': 0.4689597240649164, 'learning_rate/action_model': 9.59921162515311e-05, 'learning_rate/action_query_proj': 9.59921162515311e-05, 'learning_rate/base': 2.3998029062882776e-05, 'epoch': 0.08}) +[2026-07-26 20:19:46,674][starVLA.training.train_starvla][INFO] - Step 656, Loss: {'train/loss': 0.5659160614013672, 'train/grad_norm_pre_clip': 6.004807949066162, 'timing/data': 0.00018010661005973816, 'timing/model': 0.4726880290545523, 'learning_rate/action_model': 9.598004297408138e-05, 'learning_rate/action_query_proj': 9.598004297408138e-05, 'learning_rate/base': 2.3995010743520345e-05, 'epoch': 0.08}) +[2026-07-26 20:19:52,274][starVLA.training.train_starvla][INFO] - Step 657, Loss: {'train/loss': 0.5797985792160034, 'train/grad_norm_pre_clip': 4.141781330108643, 'timing/data': 0.00018133502453565598, 'timing/model': 0.47885355399921536, 'learning_rate/action_model': 9.596795233400718e-05, 'learning_rate/action_query_proj': 9.596795233400718e-05, 'learning_rate/base': 2.3991988083501796e-05, 'epoch': 0.08}) +[2026-07-26 20:19:57,884][starVLA.training.train_starvla][INFO] - Step 658, Loss: {'train/loss': 0.660490870475769, 'train/grad_norm_pre_clip': 4.464383125305176, 'timing/data': 0.00018233293667435646, 'timing/model': 0.4707996677607298, 'learning_rate/action_model': 9.595584433608172e-05, 'learning_rate/action_query_proj': 9.595584433608172e-05, 'learning_rate/base': 2.398896108402043e-05, 'epoch': 0.08}) +[2026-07-26 20:20:03,480][starVLA.training.train_starvla][INFO] - Step 659, Loss: {'train/loss': 0.5175280570983887, 'train/grad_norm_pre_clip': 4.768766403198242, 'timing/data': 0.00018332106992602348, 'timing/model': 0.47274084109812975, 'learning_rate/action_model': 9.594371898508504e-05, 'learning_rate/action_query_proj': 9.594371898508504e-05, 'learning_rate/base': 2.398592974627126e-05, 'epoch': 0.08}) +[2026-07-26 20:20:09,077][starVLA.training.train_starvla][INFO] - Step 660, Loss: {'train/loss': 0.6125153303146362, 'train/grad_norm_pre_clip': 6.375771522521973, 'timing/data': 0.0001749233342707157, 'timing/model': 0.46773805702105165, 'learning_rate/action_model': 9.593157628580404e-05, 'learning_rate/action_query_proj': 9.593157628580404e-05, 'learning_rate/base': 2.398289407145101e-05, 'epoch': 0.08}) +[2026-07-26 20:20:14,677][starVLA.training.train_starvla][INFO] - Step 661, Loss: {'train/loss': 0.604551374912262, 'train/grad_norm_pre_clip': 7.824814796447754, 'timing/data': 0.00018772156909108162, 'timing/model': 0.4714113627560437, 'learning_rate/action_model': 9.591941624303247e-05, 'learning_rate/action_query_proj': 9.591941624303247e-05, 'learning_rate/base': 2.397985406075812e-05, 'epoch': 0.08}) +[2026-07-26 20:20:20,282][starVLA.training.train_starvla][INFO] - Step 662, Loss: {'train/loss': 0.6090125441551208, 'train/grad_norm_pre_clip': 6.552139759063721, 'timing/data': 0.00017998693510890007, 'timing/model': 0.4754265979863703, 'learning_rate/action_model': 9.590723886157092e-05, 'learning_rate/action_query_proj': 9.590723886157092e-05, 'learning_rate/base': 2.397680971539273e-05, 'epoch': 0.08}) +[2026-07-26 20:20:25,937][starVLA.training.train_starvla][INFO] - Step 663, Loss: {'train/loss': 0.5136750340461731, 'train/grad_norm_pre_clip': 3.680725336074829, 'timing/data': 0.00017424486577510834, 'timing/model': 0.45764462603256106, 'learning_rate/action_model': 9.589504414622682e-05, 'learning_rate/action_query_proj': 9.589504414622682e-05, 'learning_rate/base': 2.3973761036556706e-05, 'epoch': 0.08}) +[2026-07-26 20:20:31,470][starVLA.training.train_starvla][INFO] - Step 664, Loss: {'train/loss': 0.6099916100502014, 'train/grad_norm_pre_clip': 7.0001139640808105, 'timing/data': 0.0001916489563882351, 'timing/model': 0.45634285686537623, 'learning_rate/action_model': 9.588283210181446e-05, 'learning_rate/action_query_proj': 9.588283210181446e-05, 'learning_rate/base': 2.3970708025453614e-05, 'epoch': 0.08}) +[2026-07-26 20:20:37,004][starVLA.training.train_starvla][INFO] - Step 665, Loss: {'train/loss': 0.5637019276618958, 'train/grad_norm_pre_clip': 2.5449960231781006, 'timing/data': 0.00018152082338929176, 'timing/model': 0.45581843331456184, 'learning_rate/action_model': 9.587060273315493e-05, 'learning_rate/action_query_proj': 9.587060273315493e-05, 'learning_rate/base': 2.3967650683288733e-05, 'epoch': 0.08}) +[2026-07-26 20:20:42,519][starVLA.training.train_starvla][INFO] - Step 666, Loss: {'train/loss': 0.6700036525726318, 'train/grad_norm_pre_clip': 7.285720348358154, 'timing/data': 0.00017408886924386024, 'timing/model': 0.45731073385104537, 'learning_rate/action_model': 9.585835604507626e-05, 'learning_rate/action_query_proj': 9.585835604507626e-05, 'learning_rate/base': 2.3964589011269066e-05, 'epoch': 0.08}) +[2026-07-26 20:20:48,039][starVLA.training.train_starvla][INFO] - Step 667, Loss: {'train/loss': 0.5288520455360413, 'train/grad_norm_pre_clip': 3.9402029514312744, 'timing/data': 0.0001697959378361702, 'timing/model': 0.4570025112479925, 'learning_rate/action_model': 9.584609204241318e-05, 'learning_rate/action_query_proj': 9.584609204241318e-05, 'learning_rate/base': 2.3961523010603294e-05, 'epoch': 0.08}) +[2026-07-26 20:20:53,563][starVLA.training.train_starvla][INFO] - Step 668, Loss: {'train/loss': 0.5330650806427002, 'train/grad_norm_pre_clip': 4.130381107330322, 'timing/data': 0.0001769629307091236, 'timing/model': 0.4562461730092764, 'learning_rate/action_model': 9.583381073000734e-05, 'learning_rate/action_query_proj': 9.583381073000734e-05, 'learning_rate/base': 2.3958452682501835e-05, 'epoch': 0.08}) +[2026-07-26 20:20:59,077][starVLA.training.train_starvla][INFO] - Step 669, Loss: {'train/loss': 0.642885684967041, 'train/grad_norm_pre_clip': 3.9968409538269043, 'timing/data': 0.00017372984439134598, 'timing/model': 0.45642032800242305, 'learning_rate/action_model': 9.582151211270724e-05, 'learning_rate/action_query_proj': 9.582151211270724e-05, 'learning_rate/base': 2.395537802817681e-05, 'epoch': 0.08}) +[2026-07-26 20:21:04,587][starVLA.training.train_starvla][INFO] - Step 670, Loss: {'train/loss': 0.6272526979446411, 'train/grad_norm_pre_clip': 6.231424808502197, 'timing/data': 0.00018396880477666855, 'timing/model': 0.45648697298020124, 'learning_rate/action_model': 9.580919619536814e-05, 'learning_rate/action_query_proj': 9.580919619536814e-05, 'learning_rate/base': 2.3952299048842036e-05, 'epoch': 0.08}) +[2026-07-26 20:21:10,099][starVLA.training.train_starvla][INFO] - Step 671, Loss: {'train/loss': 0.6225125193595886, 'train/grad_norm_pre_clip': 5.9877471923828125, 'timing/data': 0.00017497502267360687, 'timing/model': 0.45675233006477356, 'learning_rate/action_model': 9.579686298285219e-05, 'learning_rate/action_query_proj': 9.579686298285219e-05, 'learning_rate/base': 2.3949215745713047e-05, 'epoch': 0.08}) +[2026-07-26 20:21:15,605][starVLA.training.train_starvla][INFO] - Step 672, Loss: {'train/loss': 0.5703734755516052, 'train/grad_norm_pre_clip': 4.038190841674805, 'timing/data': 0.00017860997468233109, 'timing/model': 0.4576802607625723, 'learning_rate/action_model': 9.578451248002835e-05, 'learning_rate/action_query_proj': 9.578451248002835e-05, 'learning_rate/base': 2.3946128120007087e-05, 'epoch': 0.08}) +[2026-07-26 20:21:21,112][starVLA.training.train_starvla][INFO] - Step 673, Loss: {'train/loss': 0.6076221466064453, 'train/grad_norm_pre_clip': 7.8841872215271, 'timing/data': 0.00017484882846474648, 'timing/model': 0.4565483210608363, 'learning_rate/action_model': 9.577214469177239e-05, 'learning_rate/action_query_proj': 9.577214469177239e-05, 'learning_rate/base': 2.3943036172943097e-05, 'epoch': 0.08}) +[2026-07-26 20:21:26,638][starVLA.training.train_starvla][INFO] - Step 674, Loss: {'train/loss': 0.5546342730522156, 'train/grad_norm_pre_clip': 6.154351234436035, 'timing/data': 0.00017358176410198212, 'timing/model': 0.45715829310938716, 'learning_rate/action_model': 9.575975962296692e-05, 'learning_rate/action_query_proj': 9.575975962296692e-05, 'learning_rate/base': 2.393993990574173e-05, 'epoch': 0.08}) +[2026-07-26 20:21:32,146][starVLA.training.train_starvla][INFO] - Step 675, Loss: {'train/loss': 0.878555417060852, 'train/grad_norm_pre_clip': 9.457427024841309, 'timing/data': 0.00017700064927339554, 'timing/model': 0.45668058516457677, 'learning_rate/action_model': 9.574735727850137e-05, 'learning_rate/action_query_proj': 9.574735727850137e-05, 'learning_rate/base': 2.3936839319625343e-05, 'epoch': 0.08}) +[2026-07-26 20:21:37,650][starVLA.training.train_starvla][INFO] - Step 676, Loss: {'train/loss': 0.5568792223930359, 'train/grad_norm_pre_clip': 6.234981536865234, 'timing/data': 0.00018265703693032265, 'timing/model': 0.4572094683535397, 'learning_rate/action_model': 9.573493766327201e-05, 'learning_rate/action_query_proj': 9.573493766327201e-05, 'learning_rate/base': 2.3933734415818002e-05, 'epoch': 0.08}) +[2026-07-26 20:21:43,179][starVLA.training.train_starvla][INFO] - Step 677, Loss: {'train/loss': 0.7232421636581421, 'train/grad_norm_pre_clip': 8.540128707885742, 'timing/data': 0.00017459318041801453, 'timing/model': 0.461845725774765, 'learning_rate/action_model': 9.572250078218187e-05, 'learning_rate/action_query_proj': 9.572250078218187e-05, 'learning_rate/base': 2.3930625195545466e-05, 'epoch': 0.08}) +[2026-07-26 20:21:48,803][starVLA.training.train_starvla][INFO] - Step 678, Loss: {'train/loss': 0.5022101402282715, 'train/grad_norm_pre_clip': 2.942267656326294, 'timing/data': 0.0001757340505719185, 'timing/model': 0.46279060188680887, 'learning_rate/action_model': 9.571004664014085e-05, 'learning_rate/action_query_proj': 9.571004664014085e-05, 'learning_rate/base': 2.3927511660035212e-05, 'epoch': 0.08}) +[2026-07-26 20:21:54,339][starVLA.training.train_starvla][INFO] - Step 679, Loss: {'train/loss': 0.4988783299922943, 'train/grad_norm_pre_clip': 4.519974231719971, 'timing/data': 0.0001798323355615139, 'timing/model': 0.46297771902754903, 'learning_rate/action_model': 9.569757524206567e-05, 'learning_rate/action_query_proj': 9.569757524206567e-05, 'learning_rate/base': 2.3924393810516417e-05, 'epoch': 0.08}) +[2026-07-26 20:22:00,049][starVLA.training.train_starvla][INFO] - Step 680, Loss: {'train/loss': 0.5693328380584717, 'train/grad_norm_pre_clip': 3.3747825622558594, 'timing/data': 0.0001713368110358715, 'timing/model': 0.46756199235096574, 'learning_rate/action_model': 9.568508659287979e-05, 'learning_rate/action_query_proj': 9.568508659287979e-05, 'learning_rate/base': 2.3921271648219947e-05, 'epoch': 0.08}) +[2026-07-26 20:22:05,631][starVLA.training.train_starvla][INFO] - Step 681, Loss: {'train/loss': 0.5938087105751038, 'train/grad_norm_pre_clip': 4.748185634613037, 'timing/data': 0.00017883116379380226, 'timing/model': 0.4580985619686544, 'learning_rate/action_model': 9.567258069751358e-05, 'learning_rate/action_query_proj': 9.567258069751358e-05, 'learning_rate/base': 2.3918145174378395e-05, 'epoch': 0.08}) +[2026-07-26 20:22:11,184][starVLA.training.train_starvla][INFO] - Step 682, Loss: {'train/loss': 0.7636895179748535, 'train/grad_norm_pre_clip': 7.747955799102783, 'timing/data': 0.00017484091222286224, 'timing/model': 0.45816335221752524, 'learning_rate/action_model': 9.566005756090417e-05, 'learning_rate/action_query_proj': 9.566005756090417e-05, 'learning_rate/base': 2.391501439022604e-05, 'epoch': 0.08}) +[2026-07-26 20:22:16,727][starVLA.training.train_starvla][INFO] - Step 683, Loss: {'train/loss': 0.7869522571563721, 'train/grad_norm_pre_clip': 4.096271991729736, 'timing/data': 0.00017799297347664833, 'timing/model': 0.4580132127739489, 'learning_rate/action_model': 9.564751718799543e-05, 'learning_rate/action_query_proj': 9.564751718799543e-05, 'learning_rate/base': 2.391187929699886e-05, 'epoch': 0.08}) +[2026-07-26 20:22:22,296][starVLA.training.train_starvla][INFO] - Step 684, Loss: {'train/loss': 0.5693278312683105, 'train/grad_norm_pre_clip': 4.022767066955566, 'timing/data': 0.00018470874056220055, 'timing/model': 0.4576583639718592, 'learning_rate/action_model': 9.563495958373818e-05, 'learning_rate/action_query_proj': 9.563495958373818e-05, 'learning_rate/base': 2.3908739895934545e-05, 'epoch': 0.08}) +[2026-07-26 20:22:27,881][starVLA.training.train_starvla][INFO] - Step 685, Loss: {'train/loss': 0.5599380731582642, 'train/grad_norm_pre_clip': 4.807185649871826, 'timing/data': 0.00019459333270788193, 'timing/model': 0.45752701675519347, 'learning_rate/action_model': 9.562238475308993e-05, 'learning_rate/action_query_proj': 9.562238475308993e-05, 'learning_rate/base': 2.3905596188272482e-05, 'epoch': 0.08}) +[2026-07-26 20:22:33,581][starVLA.training.train_starvla][INFO] - Step 686, Loss: {'train/loss': 0.6397377252578735, 'train/grad_norm_pre_clip': 5.868379592895508, 'timing/data': 0.00018622586503624916, 'timing/model': 0.5282733598724008, 'learning_rate/action_model': 9.560979270101502e-05, 'learning_rate/action_query_proj': 9.560979270101502e-05, 'learning_rate/base': 2.3902448175253754e-05, 'epoch': 0.08}) +[2026-07-26 20:22:39,318][starVLA.training.train_starvla][INFO] - Step 687, Loss: {'train/loss': 0.6019721031188965, 'train/grad_norm_pre_clip': 4.612777233123779, 'timing/data': 0.00018548918887972832, 'timing/model': 0.45772643806412816, 'learning_rate/action_model': 9.559718343248459e-05, 'learning_rate/action_query_proj': 9.559718343248459e-05, 'learning_rate/base': 2.3899295858121147e-05, 'epoch': 0.08}) +[2026-07-26 20:22:45,076][starVLA.training.train_starvla][INFO] - Step 688, Loss: {'train/loss': 0.6527649760246277, 'train/grad_norm_pre_clip': 5.505929470062256, 'timing/data': 0.00018716277554631233, 'timing/model': 0.4702149140648544, 'learning_rate/action_model': 9.55845569524766e-05, 'learning_rate/action_query_proj': 9.55845569524766e-05, 'learning_rate/base': 2.389613923811915e-05, 'epoch': 0.08}) +[2026-07-26 20:22:50,657][starVLA.training.train_starvla][INFO] - Step 689, Loss: {'train/loss': 0.6301112174987793, 'train/grad_norm_pre_clip': 3.780656337738037, 'timing/data': 0.00018480326980352402, 'timing/model': 0.45754425320774317, 'learning_rate/action_model': 9.557191326597575e-05, 'learning_rate/action_query_proj': 9.557191326597575e-05, 'learning_rate/base': 2.3892978316493938e-05, 'epoch': 0.08}) +[2026-07-26 20:22:56,263][starVLA.training.train_starvla][INFO] - Step 690, Loss: {'train/loss': 0.5958264470100403, 'train/grad_norm_pre_clip': 3.9537527561187744, 'timing/data': 0.00018520187586545944, 'timing/model': 0.45652761682868004, 'learning_rate/action_model': 9.555925237797362e-05, 'learning_rate/action_query_proj': 9.555925237797362e-05, 'learning_rate/base': 2.3889813094493405e-05, 'epoch': 0.08}) +[2026-07-26 20:23:01,878][starVLA.training.train_starvla][INFO] - Step 691, Loss: {'train/loss': 0.591010570526123, 'train/grad_norm_pre_clip': 3.8440513610839844, 'timing/data': 0.0001787799410521984, 'timing/model': 0.45850840816274285, 'learning_rate/action_model': 9.554657429346848e-05, 'learning_rate/action_query_proj': 9.554657429346848e-05, 'learning_rate/base': 2.388664357336712e-05, 'epoch': 0.08}) +[2026-07-26 20:23:07,491][starVLA.training.train_starvla][INFO] - Step 692, Loss: {'train/loss': 0.5838608741760254, 'train/grad_norm_pre_clip': 5.974762439727783, 'timing/data': 0.0001814691349864006, 'timing/model': 0.4567278614267707, 'learning_rate/action_model': 9.553387901746546e-05, 'learning_rate/action_query_proj': 9.553387901746546e-05, 'learning_rate/base': 2.3883469754366365e-05, 'epoch': 0.08}) +[2026-07-26 20:23:13,108][starVLA.training.train_starvla][INFO] - Step 693, Loss: {'train/loss': 0.6544756293296814, 'train/grad_norm_pre_clip': 8.14050006866455, 'timing/data': 0.00018595485016703606, 'timing/model': 0.47097260411828756, 'learning_rate/action_model': 9.552116655497644e-05, 'learning_rate/action_query_proj': 9.552116655497644e-05, 'learning_rate/base': 2.388029163874411e-05, 'epoch': 0.08}) +[2026-07-26 20:23:18,778][starVLA.training.train_starvla][INFO] - Step 694, Loss: {'train/loss': 0.4523586928844452, 'train/grad_norm_pre_clip': 5.0862226486206055, 'timing/data': 0.0001918119378387928, 'timing/model': 0.47029311675578356, 'learning_rate/action_model': 9.550843691102011e-05, 'learning_rate/action_query_proj': 9.550843691102011e-05, 'learning_rate/base': 2.3877109227755027e-05, 'epoch': 0.08}) +[2026-07-26 20:23:24,430][starVLA.training.train_starvla][INFO] - Step 695, Loss: {'train/loss': 0.447476863861084, 'train/grad_norm_pre_clip': 2.8699021339416504, 'timing/data': 0.00018234876915812492, 'timing/model': 0.461931845638901, 'learning_rate/action_model': 9.549569009062191e-05, 'learning_rate/action_query_proj': 9.549569009062191e-05, 'learning_rate/base': 2.387392252265548e-05, 'epoch': 0.08}) +[2026-07-26 20:23:30,105][starVLA.training.train_starvla][INFO] - Step 696, Loss: {'train/loss': 0.5549783110618591, 'train/grad_norm_pre_clip': 3.7960329055786133, 'timing/data': 0.0001845499500632286, 'timing/model': 0.45839529018849134, 'learning_rate/action_model': 9.548292609881412e-05, 'learning_rate/action_query_proj': 9.548292609881412e-05, 'learning_rate/base': 2.387073152470353e-05, 'epoch': 0.08}) +[2026-07-26 20:23:35,732][starVLA.training.train_starvla][INFO] - Step 697, Loss: {'train/loss': 0.631156325340271, 'train/grad_norm_pre_clip': 5.897251129150391, 'timing/data': 0.0001782621257007122, 'timing/model': 0.4591617160476744, 'learning_rate/action_model': 9.547014494063574e-05, 'learning_rate/action_query_proj': 9.547014494063574e-05, 'learning_rate/base': 2.3867536235158935e-05, 'epoch': 0.08}) +[2026-07-26 20:23:41,333][starVLA.training.train_starvla][INFO] - Step 698, Loss: {'train/loss': 0.5220056772232056, 'train/grad_norm_pre_clip': 4.589783668518066, 'timing/data': 0.00018052617087960243, 'timing/model': 0.4563484196551144, 'learning_rate/action_model': 9.545734662113257e-05, 'learning_rate/action_query_proj': 9.545734662113257e-05, 'learning_rate/base': 2.3864336655283143e-05, 'epoch': 0.08}) +[2026-07-26 20:23:46,948][starVLA.training.train_starvla][INFO] - Step 699, Loss: {'train/loss': 0.5641871690750122, 'train/grad_norm_pre_clip': 3.4246299266815186, 'timing/data': 0.00018596462905406952, 'timing/model': 0.4576708162203431, 'learning_rate/action_model': 9.544453114535719e-05, 'learning_rate/action_query_proj': 9.544453114535719e-05, 'learning_rate/base': 2.3861132786339298e-05, 'epoch': 0.08}) +[2026-07-26 20:23:52,854][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 700 +[2026-07-26 20:23:52,855][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 700 +[2026-07-26 20:23:52,855][starVLA.training.train_starvla][INFO] - Step 700, Loss: {'train/loss': 0.5594292879104614, 'train/grad_norm_pre_clip': 5.831267356872559, 'timing/data': 0.00019148923456668854, 'timing/model': 0.45779125299304724, 'learning_rate/action_model': 9.543169851836894e-05, 'learning_rate/action_query_proj': 9.543169851836894e-05, 'learning_rate/base': 2.3857924629592234e-05, 'epoch': 0.08}) +[2026-07-26 20:23:58,480][starVLA.training.train_starvla][INFO] - Step 701, Loss: {'train/loss': 0.38534051179885864, 'train/grad_norm_pre_clip': 3.8132565021514893, 'timing/data': 0.00017549609765410423, 'timing/model': 0.4564428231678903, 'learning_rate/action_model': 9.541884874523394e-05, 'learning_rate/action_query_proj': 9.541884874523394e-05, 'learning_rate/base': 2.3854712186308485e-05, 'epoch': 0.09}) +[2026-07-26 20:24:04,086][starVLA.training.train_starvla][INFO] - Step 702, Loss: {'train/loss': 0.5160166621208191, 'train/grad_norm_pre_clip': 4.480747699737549, 'timing/data': 0.0001718532294034958, 'timing/model': 0.4562324299477041, 'learning_rate/action_model': 9.540598183102508e-05, 'learning_rate/action_query_proj': 9.540598183102508e-05, 'learning_rate/base': 2.385149545775627e-05, 'epoch': 0.09}) +[2026-07-26 20:24:09,696][starVLA.training.train_starvla][INFO] - Step 703, Loss: {'train/loss': 0.5204607844352722, 'train/grad_norm_pre_clip': 4.614823341369629, 'timing/data': 0.00017331773415207863, 'timing/model': 0.4581119460053742, 'learning_rate/action_model': 9.5393097780822e-05, 'learning_rate/action_query_proj': 9.5393097780822e-05, 'learning_rate/base': 2.38482744452055e-05, 'epoch': 0.09}) +[2026-07-26 20:24:15,324][starVLA.training.train_starvla][INFO] - Step 704, Loss: {'train/loss': 0.6420513987541199, 'train/grad_norm_pre_clip': 4.564248561859131, 'timing/data': 0.00016955798491835594, 'timing/model': 0.45696213003247976, 'learning_rate/action_model': 9.538019659971116e-05, 'learning_rate/action_query_proj': 9.538019659971116e-05, 'learning_rate/base': 2.384504914992779e-05, 'epoch': 0.09}) +[2026-07-26 20:24:20,923][starVLA.training.train_starvla][INFO] - Step 705, Loss: {'train/loss': 0.44958361983299255, 'train/grad_norm_pre_clip': 4.316459655761719, 'timing/data': 0.00017379876226186752, 'timing/model': 0.4567674216814339, 'learning_rate/action_model': 9.536727829278568e-05, 'learning_rate/action_query_proj': 9.536727829278568e-05, 'learning_rate/base': 2.384181957319642e-05, 'epoch': 0.09}) +[2026-07-26 20:24:26,527][starVLA.training.train_starvla][INFO] - Step 706, Loss: {'train/loss': 0.5501358509063721, 'train/grad_norm_pre_clip': 5.569722652435303, 'timing/data': 0.00017807027325034142, 'timing/model': 0.4560011699795723, 'learning_rate/action_model': 9.535434286514555e-05, 'learning_rate/action_query_proj': 9.535434286514555e-05, 'learning_rate/base': 2.3838585716286386e-05, 'epoch': 0.09}) +[2026-07-26 20:24:32,132][starVLA.training.train_starvla][INFO] - Step 707, Loss: {'train/loss': 0.44864192605018616, 'train/grad_norm_pre_clip': 3.869518280029297, 'timing/data': 0.0001805489882826805, 'timing/model': 0.4573194710537791, 'learning_rate/action_model': 9.534139032189744e-05, 'learning_rate/action_query_proj': 9.534139032189744e-05, 'learning_rate/base': 2.383534758047436e-05, 'epoch': 0.09}) +[2026-07-26 20:24:37,742][starVLA.training.train_starvla][INFO] - Step 708, Loss: {'train/loss': 0.7665405869483948, 'train/grad_norm_pre_clip': 8.490612983703613, 'timing/data': 0.00017603300511837006, 'timing/model': 0.4571122736670077, 'learning_rate/action_model': 9.532842066815484e-05, 'learning_rate/action_query_proj': 9.532842066815484e-05, 'learning_rate/base': 2.383210516703871e-05, 'epoch': 0.09}) +[2026-07-26 20:24:43,345][starVLA.training.train_starvla][INFO] - Step 709, Loss: {'train/loss': 0.4736821949481964, 'train/grad_norm_pre_clip': 4.598788261413574, 'timing/data': 0.0001804460771381855, 'timing/model': 0.4573720428161323, 'learning_rate/action_model': 9.531543390903796e-05, 'learning_rate/action_query_proj': 9.531543390903796e-05, 'learning_rate/base': 2.382885847725949e-05, 'epoch': 0.09}) +[2026-07-26 20:24:48,967][starVLA.training.train_starvla][INFO] - Step 710, Loss: {'train/loss': 0.5656000971794128, 'train/grad_norm_pre_clip': 5.8580803871154785, 'timing/data': 0.00017897877842187881, 'timing/model': 0.45664770482107997, 'learning_rate/action_model': 9.530243004967375e-05, 'learning_rate/action_query_proj': 9.530243004967375e-05, 'learning_rate/base': 2.3825607512418436e-05, 'epoch': 0.09}) +[2026-07-26 20:24:54,851][starVLA.training.train_starvla][INFO] - Step 711, Loss: {'train/loss': 0.679358720779419, 'train/grad_norm_pre_clip': 5.290541172027588, 'timing/data': 0.0001817578449845314, 'timing/model': 0.4714319659397006, 'learning_rate/action_model': 9.528940909519591e-05, 'learning_rate/action_query_proj': 9.528940909519591e-05, 'learning_rate/base': 2.3822352273798978e-05, 'epoch': 0.09}) +[2026-07-26 20:25:00,467][starVLA.training.train_starvla][INFO] - Step 712, Loss: {'train/loss': 0.5354402661323547, 'train/grad_norm_pre_clip': 6.474916458129883, 'timing/data': 0.0001701577566564083, 'timing/model': 0.4566209460608661, 'learning_rate/action_model': 9.527637105074497e-05, 'learning_rate/action_query_proj': 9.527637105074497e-05, 'learning_rate/base': 2.381909276268624e-05, 'epoch': 0.09}) +[2026-07-26 20:25:06,088][starVLA.training.train_starvla][INFO] - Step 713, Loss: {'train/loss': 0.6674972772598267, 'train/grad_norm_pre_clip': 5.649875640869141, 'timing/data': 0.00018377788364887238, 'timing/model': 0.45643719797953963, 'learning_rate/action_model': 9.526331592146808e-05, 'learning_rate/action_query_proj': 9.526331592146808e-05, 'learning_rate/base': 2.381582898036702e-05, 'epoch': 0.09}) +[2026-07-26 20:25:11,690][starVLA.training.train_starvla][INFO] - Step 714, Loss: {'train/loss': 0.8650723695755005, 'train/grad_norm_pre_clip': 9.659032821655273, 'timing/data': 0.00017261691391468048, 'timing/model': 0.45948893716558814, 'learning_rate/action_model': 9.525024371251923e-05, 'learning_rate/action_query_proj': 9.525024371251923e-05, 'learning_rate/base': 2.3812560928129806e-05, 'epoch': 0.09}) +[2026-07-26 20:25:17,294][starVLA.training.train_starvla][INFO] - Step 715, Loss: {'train/loss': 0.5483695864677429, 'train/grad_norm_pre_clip': 6.1657633781433105, 'timing/data': 0.00017739227041602135, 'timing/model': 0.45693911239504814, 'learning_rate/action_model': 9.523715442905912e-05, 'learning_rate/action_query_proj': 9.523715442905912e-05, 'learning_rate/base': 2.380928860726478e-05, 'epoch': 0.09}) +[2026-07-26 20:25:22,903][starVLA.training.train_starvla][INFO] - Step 716, Loss: {'train/loss': 0.6462878584861755, 'train/grad_norm_pre_clip': 8.616279602050781, 'timing/data': 0.00017505325376987457, 'timing/model': 0.4562476612627506, 'learning_rate/action_model': 9.522404807625518e-05, 'learning_rate/action_query_proj': 9.522404807625518e-05, 'learning_rate/base': 2.3806012019063796e-05, 'epoch': 0.09}) +[2026-07-26 20:25:28,499][starVLA.training.train_starvla][INFO] - Step 717, Loss: {'train/loss': 0.5469933748245239, 'train/grad_norm_pre_clip': 3.294124126434326, 'timing/data': 0.00017103180289268494, 'timing/model': 0.45690611423924565, 'learning_rate/action_model': 9.52109246592816e-05, 'learning_rate/action_query_proj': 9.52109246592816e-05, 'learning_rate/base': 2.38027311648204e-05, 'epoch': 0.09}) +[2026-07-26 20:25:34,203][starVLA.training.train_starvla][INFO] - Step 718, Loss: {'train/loss': 0.7569417357444763, 'train/grad_norm_pre_clip': 4.874314308166504, 'timing/data': 0.00017570797353982925, 'timing/model': 0.45780236599966884, 'learning_rate/action_model': 9.519778418331928e-05, 'learning_rate/action_query_proj': 9.519778418331928e-05, 'learning_rate/base': 2.379944604582982e-05, 'epoch': 0.09}) +[2026-07-26 20:25:39,879][starVLA.training.train_starvla][INFO] - Step 719, Loss: {'train/loss': 0.691762387752533, 'train/grad_norm_pre_clip': 7.295592308044434, 'timing/data': 0.00017248326912522316, 'timing/model': 0.45974069787189364, 'learning_rate/action_model': 9.518462665355588e-05, 'learning_rate/action_query_proj': 9.518462665355588e-05, 'learning_rate/base': 2.379615666338897e-05, 'epoch': 0.09}) +[2026-07-26 20:25:45,842][starVLA.training.train_starvla][INFO] - Step 720, Loss: {'train/loss': 0.6249473094940186, 'train/grad_norm_pre_clip': 8.227499008178711, 'timing/data': 0.0001788581721484661, 'timing/model': 0.7200249917805195, 'learning_rate/action_model': 9.517145207518581e-05, 'learning_rate/action_query_proj': 9.517145207518581e-05, 'learning_rate/base': 2.3792863018796453e-05, 'epoch': 0.09}) +[2026-07-26 20:25:51,809][starVLA.training.train_starvla][INFO] - Step 721, Loss: {'train/loss': 0.6564268469810486, 'train/grad_norm_pre_clip': 8.14159870147705, 'timing/data': 0.000171576626598835, 'timing/model': 0.46091060899198055, 'learning_rate/action_model': 9.515826045341017e-05, 'learning_rate/action_query_proj': 9.515826045341017e-05, 'learning_rate/base': 2.3789565113352542e-05, 'epoch': 0.09}) +[2026-07-26 20:25:57,410][starVLA.training.train_starvla][INFO] - Step 722, Loss: {'train/loss': 0.562380850315094, 'train/grad_norm_pre_clip': 7.718057155609131, 'timing/data': 0.0001726001501083374, 'timing/model': 0.4590427898801863, 'learning_rate/action_model': 9.514505179343678e-05, 'learning_rate/action_query_proj': 9.514505179343678e-05, 'learning_rate/base': 2.3786262948359195e-05, 'epoch': 0.09}) +[2026-07-26 20:26:03,417][starVLA.training.train_starvla][INFO] - Step 723, Loss: {'train/loss': 0.5784922242164612, 'train/grad_norm_pre_clip': 6.870317459106445, 'timing/data': 0.00018116598948836327, 'timing/model': 0.4741405420936644, 'learning_rate/action_model': 9.513182610048024e-05, 'learning_rate/action_query_proj': 9.513182610048024e-05, 'learning_rate/base': 2.378295652512006e-05, 'epoch': 0.09}) +[2026-07-26 20:26:09,192][starVLA.training.train_starvla][INFO] - Step 724, Loss: {'train/loss': 0.633226752281189, 'train/grad_norm_pre_clip': 4.205949783325195, 'timing/data': 0.00018029380589723587, 'timing/model': 0.462070653680712, 'learning_rate/action_model': 9.511858337976182e-05, 'learning_rate/action_query_proj': 9.511858337976182e-05, 'learning_rate/base': 2.3779645844940456e-05, 'epoch': 0.09}) +[2026-07-26 20:26:14,827][starVLA.training.train_starvla][INFO] - Step 725, Loss: {'train/loss': 0.49153125286102295, 'train/grad_norm_pre_clip': 4.768282890319824, 'timing/data': 0.00017354125156998634, 'timing/model': 0.45855350932106376, 'learning_rate/action_model': 9.510532363650955e-05, 'learning_rate/action_query_proj': 9.510532363650955e-05, 'learning_rate/base': 2.3776330909127388e-05, 'epoch': 0.09}) +[2026-07-26 20:26:20,479][starVLA.training.train_starvla][INFO] - Step 726, Loss: {'train/loss': 0.5235525369644165, 'train/grad_norm_pre_clip': 2.637150287628174, 'timing/data': 0.00017714407294988632, 'timing/model': 0.46221819380298257, 'learning_rate/action_model': 9.509204687595817e-05, 'learning_rate/action_query_proj': 9.509204687595817e-05, 'learning_rate/base': 2.3773011718989542e-05, 'epoch': 0.09}) +[2026-07-26 20:26:26,113][starVLA.training.train_starvla][INFO] - Step 727, Loss: {'train/loss': 0.5668043494224548, 'train/grad_norm_pre_clip': 3.7924156188964844, 'timing/data': 0.00017264019697904587, 'timing/model': 0.4601930929347873, 'learning_rate/action_model': 9.507875310334913e-05, 'learning_rate/action_query_proj': 9.507875310334913e-05, 'learning_rate/base': 2.3769688275837283e-05, 'epoch': 0.09}) +[2026-07-26 20:26:31,764][starVLA.training.train_starvla][INFO] - Step 728, Loss: {'train/loss': 0.5199588537216187, 'train/grad_norm_pre_clip': 5.739859580993652, 'timing/data': 0.00017343414947390556, 'timing/model': 0.45954722724854946, 'learning_rate/action_model': 9.506544232393061e-05, 'learning_rate/action_query_proj': 9.506544232393061e-05, 'learning_rate/base': 2.3766360580982654e-05, 'epoch': 0.09}) +[2026-07-26 20:26:37,376][starVLA.training.train_starvla][INFO] - Step 729, Loss: {'train/loss': 0.7295947074890137, 'train/grad_norm_pre_clip': 5.767582893371582, 'timing/data': 0.0001732800155878067, 'timing/model': 0.45873683085665107, 'learning_rate/action_model': 9.505211454295747e-05, 'learning_rate/action_query_proj': 9.505211454295747e-05, 'learning_rate/base': 2.3763028635739368e-05, 'epoch': 0.09}) +[2026-07-26 20:26:42,963][starVLA.training.train_starvla][INFO] - Step 730, Loss: {'train/loss': 0.5804960131645203, 'train/grad_norm_pre_clip': 3.904900550842285, 'timing/data': 0.0001897714100778103, 'timing/model': 0.4579689810052514, 'learning_rate/action_model': 9.503876976569133e-05, 'learning_rate/action_query_proj': 9.503876976569133e-05, 'learning_rate/base': 2.3759692441422832e-05, 'epoch': 0.09}) +[2026-07-26 20:26:48,545][starVLA.training.train_starvla][INFO] - Step 731, Loss: {'train/loss': 0.5511542558670044, 'train/grad_norm_pre_clip': 6.023367881774902, 'timing/data': 0.00017592310905456543, 'timing/model': 0.4588973387144506, 'learning_rate/action_model': 9.502540799740048e-05, 'learning_rate/action_query_proj': 9.502540799740048e-05, 'learning_rate/base': 2.375635199935012e-05, 'epoch': 0.09}) +[2026-07-26 20:26:54,091][starVLA.training.train_starvla][INFO] - Step 732, Loss: {'train/loss': 0.7053385376930237, 'train/grad_norm_pre_clip': 7.800691604614258, 'timing/data': 0.000172395259141922, 'timing/model': 0.4589034589007497, 'learning_rate/action_model': 9.501202924335996e-05, 'learning_rate/action_query_proj': 9.501202924335996e-05, 'learning_rate/base': 2.375300731083999e-05, 'epoch': 0.09}) +[2026-07-26 20:26:59,664][starVLA.training.train_starvla][INFO] - Step 733, Loss: {'train/loss': 0.647367000579834, 'train/grad_norm_pre_clip': 6.835514068603516, 'timing/data': 0.00017123902216553688, 'timing/model': 0.47193065006285906, 'learning_rate/action_model': 9.499863350885146e-05, 'learning_rate/action_query_proj': 9.499863350885146e-05, 'learning_rate/base': 2.3749658377212864e-05, 'epoch': 0.09}) +[2026-07-26 20:27:05,348][starVLA.training.train_starvla][INFO] - Step 734, Loss: {'train/loss': 0.4796369671821594, 'train/grad_norm_pre_clip': 5.061995506286621, 'timing/data': 0.00017289724200963974, 'timing/model': 0.5761181185953319, 'learning_rate/action_model': 9.498522079916342e-05, 'learning_rate/action_query_proj': 9.498522079916342e-05, 'learning_rate/base': 2.3746305199790854e-05, 'epoch': 0.09}) +[2026-07-26 20:27:10,921][starVLA.training.train_starvla][INFO] - Step 735, Loss: {'train/loss': 0.5594016909599304, 'train/grad_norm_pre_clip': 4.115813255310059, 'timing/data': 0.00017254380509257317, 'timing/model': 0.47005103807896376, 'learning_rate/action_model': 9.497179111959098e-05, 'learning_rate/action_query_proj': 9.497179111959098e-05, 'learning_rate/base': 2.3742947779897744e-05, 'epoch': 0.09}) +[2026-07-26 20:27:16,502][starVLA.training.train_starvla][INFO] - Step 736, Loss: {'train/loss': 0.6462803483009338, 'train/grad_norm_pre_clip': 6.81942081451416, 'timing/data': 0.00017217407003045082, 'timing/model': 0.47175323916599154, 'learning_rate/action_model': 9.495834447543591e-05, 'learning_rate/action_query_proj': 9.495834447543591e-05, 'learning_rate/base': 2.3739586118858977e-05, 'epoch': 0.09}) +[2026-07-26 20:27:22,079][starVLA.training.train_starvla][INFO] - Step 737, Loss: {'train/loss': 0.6769879460334778, 'train/grad_norm_pre_clip': 6.450023174285889, 'timing/data': 0.00017476221546530724, 'timing/model': 0.4698722818866372, 'learning_rate/action_model': 9.49448808720068e-05, 'learning_rate/action_query_proj': 9.49448808720068e-05, 'learning_rate/base': 2.37362202180017e-05, 'epoch': 0.09}) +[2026-07-26 20:27:27,657][starVLA.training.train_starvla][INFO] - Step 738, Loss: {'train/loss': 0.4886203110218048, 'train/grad_norm_pre_clip': 4.171503067016602, 'timing/data': 0.00019295699894428253, 'timing/model': 0.47096269577741623, 'learning_rate/action_model': 9.493140031461883e-05, 'learning_rate/action_query_proj': 9.493140031461883e-05, 'learning_rate/base': 2.3732850078654708e-05, 'epoch': 0.09}) +[2026-07-26 20:27:33,241][starVLA.training.train_starvla][INFO] - Step 739, Loss: {'train/loss': 0.6349255442619324, 'train/grad_norm_pre_clip': 8.1845703125, 'timing/data': 0.00016857730224728584, 'timing/model': 0.470412565395236, 'learning_rate/action_model': 9.491790280859393e-05, 'learning_rate/action_query_proj': 9.491790280859393e-05, 'learning_rate/base': 2.3729475702148482e-05, 'epoch': 0.09}) +[2026-07-26 20:27:38,813][starVLA.training.train_starvla][INFO] - Step 740, Loss: {'train/loss': 0.48631665110588074, 'train/grad_norm_pre_clip': 4.9747796058654785, 'timing/data': 0.00017518224194645882, 'timing/model': 0.47007547272369266, 'learning_rate/action_model': 9.490438835926067e-05, 'learning_rate/action_query_proj': 9.490438835926067e-05, 'learning_rate/base': 2.3726097089815167e-05, 'epoch': 0.09}) +[2026-07-26 20:27:44,389][starVLA.training.train_starvla][INFO] - Step 741, Loss: {'train/loss': 0.5214518308639526, 'train/grad_norm_pre_clip': 4.836082935333252, 'timing/data': 0.00016991514712572098, 'timing/model': 0.4709625281393528, 'learning_rate/action_model': 9.489085697195437e-05, 'learning_rate/action_query_proj': 9.489085697195437e-05, 'learning_rate/base': 2.3722714242988593e-05, 'epoch': 0.09}) +[2026-07-26 20:27:49,950][starVLA.training.train_starvla][INFO] - Step 742, Loss: {'train/loss': 0.6377620100975037, 'train/grad_norm_pre_clip': 6.786827087402344, 'timing/data': 0.00017773592844605446, 'timing/model': 0.46974045503884554, 'learning_rate/action_model': 9.4877308652017e-05, 'learning_rate/action_query_proj': 9.4877308652017e-05, 'learning_rate/base': 2.371932716300425e-05, 'epoch': 0.09}) +[2026-07-26 20:27:55,530][starVLA.training.train_starvla][INFO] - Step 743, Loss: {'train/loss': 0.6430757641792297, 'train/grad_norm_pre_clip': 5.757160663604736, 'timing/data': 0.00017390865832567215, 'timing/model': 0.4786178767681122, 'learning_rate/action_model': 9.48637434047972e-05, 'learning_rate/action_query_proj': 9.48637434047972e-05, 'learning_rate/base': 2.37159358511993e-05, 'epoch': 0.09}) +[2026-07-26 20:28:01,133][starVLA.training.train_starvla][INFO] - Step 744, Loss: {'train/loss': 0.5765729546546936, 'train/grad_norm_pre_clip': 4.3168535232543945, 'timing/data': 0.0001780749298632145, 'timing/model': 0.47578556975349784, 'learning_rate/action_model': 9.485016123565036e-05, 'learning_rate/action_query_proj': 9.485016123565036e-05, 'learning_rate/base': 2.371254030891259e-05, 'epoch': 0.09}) +[2026-07-26 20:28:06,723][starVLA.training.train_starvla][INFO] - Step 745, Loss: {'train/loss': 0.5021035671234131, 'train/grad_norm_pre_clip': 5.9041619300842285, 'timing/data': 0.00017332611605525017, 'timing/model': 0.46973546082153916, 'learning_rate/action_model': 9.483656214993847e-05, 'learning_rate/action_query_proj': 9.483656214993847e-05, 'learning_rate/base': 2.3709140537484617e-05, 'epoch': 0.09}) +[2026-07-26 20:28:13,027][starVLA.training.train_starvla][INFO] - Step 746, Loss: {'train/loss': 0.6919395923614502, 'train/grad_norm_pre_clip': 6.768505573272705, 'timing/data': 0.0001698089763522148, 'timing/model': 0.47639806708320975, 'learning_rate/action_model': 9.482294615303024e-05, 'learning_rate/action_query_proj': 9.482294615303024e-05, 'learning_rate/base': 2.370573653825756e-05, 'epoch': 0.09}) +[2026-07-26 20:28:18,610][starVLA.training.train_starvla][INFO] - Step 747, Loss: {'train/loss': 0.6283164620399475, 'train/grad_norm_pre_clip': 4.903982639312744, 'timing/data': 0.0001777862198650837, 'timing/model': 0.4704806921072304, 'learning_rate/action_model': 9.480931325030104e-05, 'learning_rate/action_query_proj': 9.480931325030104e-05, 'learning_rate/base': 2.370232831257526e-05, 'epoch': 0.09}) +[2026-07-26 20:28:24,184][starVLA.training.train_starvla][INFO] - Step 748, Loss: {'train/loss': 0.5575518608093262, 'train/grad_norm_pre_clip': 3.5423583984375, 'timing/data': 0.0001730518415570259, 'timing/model': 0.47147901402786374, 'learning_rate/action_model': 9.479566344713298e-05, 'learning_rate/action_query_proj': 9.479566344713298e-05, 'learning_rate/base': 2.3698915861783245e-05, 'epoch': 0.09}) +[2026-07-26 20:28:29,769][starVLA.training.train_starvla][INFO] - Step 749, Loss: {'train/loss': 0.46987685561180115, 'train/grad_norm_pre_clip': 3.1204864978790283, 'timing/data': 0.0001717871055006981, 'timing/model': 0.47061898885294795, 'learning_rate/action_model': 9.478199674891471e-05, 'learning_rate/action_query_proj': 9.478199674891471e-05, 'learning_rate/base': 2.369549918722868e-05, 'epoch': 0.09}) +[2026-07-26 20:28:35,333][starVLA.training.train_starvla][INFO] - Step 750, Loss: {'train/loss': 0.6033532619476318, 'train/grad_norm_pre_clip': 4.869734287261963, 'timing/data': 0.00018583796918392181, 'timing/model': 0.46954663610085845, 'learning_rate/action_model': 9.476831316104165e-05, 'learning_rate/action_query_proj': 9.476831316104165e-05, 'learning_rate/base': 2.3692078290260413e-05, 'epoch': 0.09}) +[2026-07-26 20:28:40,880][starVLA.training.train_starvla][INFO] - Step 751, Loss: {'train/loss': 0.4824422299861908, 'train/grad_norm_pre_clip': 4.628842353820801, 'timing/data': 0.0001695919781923294, 'timing/model': 0.4671021909452975, 'learning_rate/action_model': 9.475461268891591e-05, 'learning_rate/action_query_proj': 9.475461268891591e-05, 'learning_rate/base': 2.3688653172228978e-05, 'epoch': 0.09}) +[2026-07-26 20:28:46,441][starVLA.training.train_starvla][INFO] - Step 752, Loss: {'train/loss': 0.4734277129173279, 'train/grad_norm_pre_clip': 5.498918056488037, 'timing/data': 0.00017891405150294304, 'timing/model': 0.4687706818804145, 'learning_rate/action_model': 9.474089533794616e-05, 'learning_rate/action_query_proj': 9.474089533794616e-05, 'learning_rate/base': 2.368522383448654e-05, 'epoch': 0.09}) +[2026-07-26 20:28:51,999][starVLA.training.train_starvla][INFO] - Step 753, Loss: {'train/loss': 0.5912448763847351, 'train/grad_norm_pre_clip': 3.299452304840088, 'timing/data': 0.00016883807256817818, 'timing/model': 0.47085498878732324, 'learning_rate/action_model': 9.472716111354781e-05, 'learning_rate/action_query_proj': 9.472716111354781e-05, 'learning_rate/base': 2.3681790278386953e-05, 'epoch': 0.09}) +[2026-07-26 20:28:57,545][starVLA.training.train_starvla][INFO] - Step 754, Loss: {'train/loss': 0.5275996923446655, 'train/grad_norm_pre_clip': 4.519224166870117, 'timing/data': 0.0002528224140405655, 'timing/model': 0.47025058092549443, 'learning_rate/action_model': 9.471341002114293e-05, 'learning_rate/action_query_proj': 9.471341002114293e-05, 'learning_rate/base': 2.3678352505285733e-05, 'epoch': 0.09}) +[2026-07-26 20:29:03,108][starVLA.training.train_starvla][INFO] - Step 755, Loss: {'train/loss': 0.5709549188613892, 'train/grad_norm_pre_clip': 2.6282272338867188, 'timing/data': 0.000168520025908947, 'timing/model': 0.4693606626242399, 'learning_rate/action_model': 9.469964206616023e-05, 'learning_rate/action_query_proj': 9.469964206616023e-05, 'learning_rate/base': 2.3674910516540058e-05, 'epoch': 0.09}) +[2026-07-26 20:29:08,694][starVLA.training.train_starvla][INFO] - Step 756, Loss: {'train/loss': 0.48508018255233765, 'train/grad_norm_pre_clip': 3.1708762645721436, 'timing/data': 0.00017912406474351883, 'timing/model': 0.47062185127288103, 'learning_rate/action_model': 9.468585725403506e-05, 'learning_rate/action_query_proj': 9.468585725403506e-05, 'learning_rate/base': 2.3671464313508764e-05, 'epoch': 0.09}) +[2026-07-26 20:29:14,305][starVLA.training.train_starvla][INFO] - Step 757, Loss: {'train/loss': 0.46618854999542236, 'train/grad_norm_pre_clip': 4.951297283172607, 'timing/data': 0.00018388591706752777, 'timing/model': 0.4716436229646206, 'learning_rate/action_model': 9.467205559020947e-05, 'learning_rate/action_query_proj': 9.467205559020947e-05, 'learning_rate/base': 2.3668013897552367e-05, 'epoch': 0.09}) +[2026-07-26 20:29:19,973][starVLA.training.train_starvla][INFO] - Step 758, Loss: {'train/loss': 0.5559737086296082, 'train/grad_norm_pre_clip': 3.6478333473205566, 'timing/data': 0.00017277104780077934, 'timing/model': 0.4753879061900079, 'learning_rate/action_model': 9.465823708013211e-05, 'learning_rate/action_query_proj': 9.465823708013211e-05, 'learning_rate/base': 2.3664559270033028e-05, 'epoch': 0.09}) +[2026-07-26 20:29:25,574][starVLA.training.train_starvla][INFO] - Step 759, Loss: {'train/loss': 0.5020129084587097, 'train/grad_norm_pre_clip': 4.849601745605469, 'timing/data': 0.0001674443483352661, 'timing/model': 0.4593414659611881, 'learning_rate/action_model': 9.464440172925835e-05, 'learning_rate/action_query_proj': 9.464440172925835e-05, 'learning_rate/base': 2.3661100432314587e-05, 'epoch': 0.09}) +[2026-07-26 20:29:31,141][starVLA.training.train_starvla][INFO] - Step 760, Loss: {'train/loss': 0.5535127520561218, 'train/grad_norm_pre_clip': 4.393692970275879, 'timing/data': 0.00023326463997364044, 'timing/model': 0.4590032766573131, 'learning_rate/action_model': 9.463054954305014e-05, 'learning_rate/action_query_proj': 9.463054954305014e-05, 'learning_rate/base': 2.3657637385762534e-05, 'epoch': 0.09}) +[2026-07-26 20:29:36,713][starVLA.training.train_starvla][INFO] - Step 761, Loss: {'train/loss': 0.4877071678638458, 'train/grad_norm_pre_clip': 3.8091588020324707, 'timing/data': 0.0001820339821279049, 'timing/model': 0.4602288929745555, 'learning_rate/action_model': 9.461668052697611e-05, 'learning_rate/action_query_proj': 9.461668052697611e-05, 'learning_rate/base': 2.3654170131744028e-05, 'epoch': 0.09}) +[2026-07-26 20:29:42,278][starVLA.training.train_starvla][INFO] - Step 762, Loss: {'train/loss': 0.7281138300895691, 'train/grad_norm_pre_clip': 7.002716541290283, 'timing/data': 0.0001697600819170475, 'timing/model': 0.4592786030843854, 'learning_rate/action_model': 9.460279468651152e-05, 'learning_rate/action_query_proj': 9.460279468651152e-05, 'learning_rate/base': 2.365069867162788e-05, 'epoch': 0.09}) +[2026-07-26 20:29:47,839][starVLA.training.train_starvla][INFO] - Step 763, Loss: {'train/loss': 0.5581769347190857, 'train/grad_norm_pre_clip': 5.816969394683838, 'timing/data': 0.00018456578254699707, 'timing/model': 0.4609828358516097, 'learning_rate/action_model': 9.458889202713828e-05, 'learning_rate/action_query_proj': 9.458889202713828e-05, 'learning_rate/base': 2.364722300678457e-05, 'epoch': 0.09}) +[2026-07-26 20:29:53,405][starVLA.training.train_starvla][INFO] - Step 764, Loss: {'train/loss': 0.49433663487434387, 'train/grad_norm_pre_clip': 5.954345226287842, 'timing/data': 0.00017117895185947418, 'timing/model': 0.45792071986943483, 'learning_rate/action_model': 9.457497255434495e-05, 'learning_rate/action_query_proj': 9.457497255434495e-05, 'learning_rate/base': 2.3643743138586238e-05, 'epoch': 0.09}) +[2026-07-26 20:29:58,950][starVLA.training.train_starvla][INFO] - Step 765, Loss: {'train/loss': 0.527597188949585, 'train/grad_norm_pre_clip': 6.935571670532227, 'timing/data': 0.00017450423911213875, 'timing/model': 0.4587769699282944, 'learning_rate/action_model': 9.456103627362673e-05, 'learning_rate/action_query_proj': 9.456103627362673e-05, 'learning_rate/base': 2.364025906840668e-05, 'epoch': 0.09}) +[2026-07-26 20:30:04,524][starVLA.training.train_starvla][INFO] - Step 766, Loss: {'train/loss': 0.4884442389011383, 'train/grad_norm_pre_clip': 3.133352756500244, 'timing/data': 0.0001879129558801651, 'timing/model': 0.4583104900084436, 'learning_rate/action_model': 9.45470831904854e-05, 'learning_rate/action_query_proj': 9.45470831904854e-05, 'learning_rate/base': 2.363677079762135e-05, 'epoch': 0.09}) +[2026-07-26 20:30:10,053][starVLA.training.train_starvla][INFO] - Step 767, Loss: {'train/loss': 0.5757229924201965, 'train/grad_norm_pre_clip': 4.6034674644470215, 'timing/data': 0.00017188815400004387, 'timing/model': 0.45839112577959895, 'learning_rate/action_model': 9.453311331042945e-05, 'learning_rate/action_query_proj': 9.453311331042945e-05, 'learning_rate/base': 2.3633278327607363e-05, 'epoch': 0.09}) +[2026-07-26 20:30:15,615][starVLA.training.train_starvla][INFO] - Step 768, Loss: {'train/loss': 0.4645845293998718, 'train/grad_norm_pre_clip': 5.14654541015625, 'timing/data': 0.00017250189557671547, 'timing/model': 0.45996454870328307, 'learning_rate/action_model': 9.451912663897396e-05, 'learning_rate/action_query_proj': 9.451912663897396e-05, 'learning_rate/base': 2.362978165974349e-05, 'epoch': 0.09}) +[2026-07-26 20:30:21,147][starVLA.training.train_starvla][INFO] - Step 769, Loss: {'train/loss': 0.6818557977676392, 'train/grad_norm_pre_clip': 6.855947971343994, 'timing/data': 0.00017035473138093948, 'timing/model': 0.45851833699271083, 'learning_rate/action_model': 9.450512318164065e-05, 'learning_rate/action_query_proj': 9.450512318164065e-05, 'learning_rate/base': 2.362628079541016e-05, 'epoch': 0.09}) +[2026-07-26 20:30:26,665][starVLA.training.train_starvla][INFO] - Step 770, Loss: {'train/loss': 0.5697978734970093, 'train/grad_norm_pre_clip': 5.822673320770264, 'timing/data': 0.00016999198123812675, 'timing/model': 0.4576974520459771, 'learning_rate/action_model': 9.449110294395786e-05, 'learning_rate/action_query_proj': 9.449110294395786e-05, 'learning_rate/base': 2.3622775735989464e-05, 'epoch': 0.09}) +[2026-07-26 20:30:32,501][starVLA.training.train_starvla][INFO] - Step 771, Loss: {'train/loss': 0.596240222454071, 'train/grad_norm_pre_clip': 3.629305839538574, 'timing/data': 0.00017938436940312386, 'timing/model': 0.45930632716044784, 'learning_rate/action_model': 9.447706593146055e-05, 'learning_rate/action_query_proj': 9.447706593146055e-05, 'learning_rate/base': 2.3619266482865138e-05, 'epoch': 0.09}) +[2026-07-26 20:30:38,027][starVLA.training.train_starvla][INFO] - Step 772, Loss: {'train/loss': 0.4424077272415161, 'train/grad_norm_pre_clip': 4.809517860412598, 'timing/data': 0.0001780879683792591, 'timing/model': 0.47261495189741254, 'learning_rate/action_model': 9.446301214969032e-05, 'learning_rate/action_query_proj': 9.446301214969032e-05, 'learning_rate/base': 2.361575303742258e-05, 'epoch': 0.09}) +[2026-07-26 20:30:43,536][starVLA.training.train_starvla][INFO] - Step 773, Loss: {'train/loss': 0.5039311647415161, 'train/grad_norm_pre_clip': 3.7484147548675537, 'timing/data': 0.0001677079126238823, 'timing/model': 0.4625607770867646, 'learning_rate/action_model': 9.444894160419539e-05, 'learning_rate/action_query_proj': 9.444894160419539e-05, 'learning_rate/base': 2.3612235401048847e-05, 'epoch': 0.09}) +[2026-07-26 20:30:49,040][starVLA.training.train_starvla][INFO] - Step 774, Loss: {'train/loss': 0.5987457633018494, 'train/grad_norm_pre_clip': 5.56719446182251, 'timing/data': 0.00016615400090813637, 'timing/model': 0.4593463190831244, 'learning_rate/action_model': 9.443485430053056e-05, 'learning_rate/action_query_proj': 9.443485430053056e-05, 'learning_rate/base': 2.360871357513264e-05, 'epoch': 0.09}) +[2026-07-26 20:30:54,806][starVLA.training.train_starvla][INFO] - Step 775, Loss: {'train/loss': 0.5559766888618469, 'train/grad_norm_pre_clip': 3.9362757205963135, 'timing/data': 0.00016813632100820541, 'timing/model': 0.7167411772534251, 'learning_rate/action_model': 9.44207502442573e-05, 'learning_rate/action_query_proj': 9.44207502442573e-05, 'learning_rate/base': 2.3605187561064324e-05, 'epoch': 0.09}) +[2026-07-26 20:31:00,334][starVLA.training.train_starvla][INFO] - Step 776, Loss: {'train/loss': 0.48896950483322144, 'train/grad_norm_pre_clip': 2.4922845363616943, 'timing/data': 0.00016662199050188065, 'timing/model': 0.4585374779999256, 'learning_rate/action_model': 9.440662944094364e-05, 'learning_rate/action_query_proj': 9.440662944094364e-05, 'learning_rate/base': 2.360165736023591e-05, 'epoch': 0.09}) +[2026-07-26 20:31:05,885][starVLA.training.train_starvla][INFO] - Step 777, Loss: {'train/loss': 0.595848560333252, 'train/grad_norm_pre_clip': 5.573326110839844, 'timing/data': 0.00017659272998571396, 'timing/model': 0.45888691302388906, 'learning_rate/action_model': 9.439249189616428e-05, 'learning_rate/action_query_proj': 9.439249189616428e-05, 'learning_rate/base': 2.359812297404107e-05, 'epoch': 0.09}) +[2026-07-26 20:31:11,411][starVLA.training.train_starvla][INFO] - Step 778, Loss: {'train/loss': 0.5130530595779419, 'train/grad_norm_pre_clip': 5.136038303375244, 'timing/data': 0.00016955705359578133, 'timing/model': 0.4586035208776593, 'learning_rate/action_model': 9.43783376155005e-05, 'learning_rate/action_query_proj': 9.43783376155005e-05, 'learning_rate/base': 2.3594584403875124e-05, 'epoch': 0.09}) +[2026-07-26 20:31:16,980][starVLA.training.train_starvla][INFO] - Step 779, Loss: {'train/loss': 0.6237923502922058, 'train/grad_norm_pre_clip': 5.908623218536377, 'timing/data': 0.0001695859245955944, 'timing/model': 0.47638834035024047, 'learning_rate/action_model': 9.436416660454016e-05, 'learning_rate/action_query_proj': 9.436416660454016e-05, 'learning_rate/base': 2.359104165113504e-05, 'epoch': 0.09}) +[2026-07-26 20:31:22,565][starVLA.training.train_starvla][INFO] - Step 780, Loss: {'train/loss': 0.48187968134880066, 'train/grad_norm_pre_clip': 3.595353126525879, 'timing/data': 0.00018178019672632217, 'timing/model': 0.47303373413160443, 'learning_rate/action_model': 9.434997886887776e-05, 'learning_rate/action_query_proj': 9.434997886887776e-05, 'learning_rate/base': 2.358749471721944e-05, 'epoch': 0.09}) +[2026-07-26 20:31:28,150][starVLA.training.train_starvla][INFO] - Step 781, Loss: {'train/loss': 0.6519363522529602, 'train/grad_norm_pre_clip': 3.879897356033325, 'timing/data': 0.0001749042421579361, 'timing/model': 0.46920584607869387, 'learning_rate/action_model': 9.43357744141144e-05, 'learning_rate/action_query_proj': 9.43357744141144e-05, 'learning_rate/base': 2.35839436035286e-05, 'epoch': 0.09}) +[2026-07-26 20:31:33,733][starVLA.training.train_starvla][INFO] - Step 782, Loss: {'train/loss': 0.573243260383606, 'train/grad_norm_pre_clip': 6.024022102355957, 'timing/data': 0.00018067099153995514, 'timing/model': 0.4721563709899783, 'learning_rate/action_model': 9.432155324585776e-05, 'learning_rate/action_query_proj': 9.432155324585776e-05, 'learning_rate/base': 2.358038831146444e-05, 'epoch': 0.09}) +[2026-07-26 20:31:39,582][starVLA.training.train_starvla][INFO] - Step 783, Loss: {'train/loss': 0.5678552389144897, 'train/grad_norm_pre_clip': 4.727509498596191, 'timing/data': 0.0001805778592824936, 'timing/model': 0.45945295970886946, 'learning_rate/action_model': 9.430731536972218e-05, 'learning_rate/action_query_proj': 9.430731536972218e-05, 'learning_rate/base': 2.3576828842430544e-05, 'epoch': 0.09}) +[2026-07-26 20:31:45,115][starVLA.training.train_starvla][INFO] - Step 784, Loss: {'train/loss': 0.5073749423027039, 'train/grad_norm_pre_clip': 4.957651138305664, 'timing/data': 0.00016900617629289627, 'timing/model': 0.4584552920423448, 'learning_rate/action_model': 9.429306079132849e-05, 'learning_rate/action_query_proj': 9.429306079132849e-05, 'learning_rate/base': 2.3573265197832122e-05, 'epoch': 0.1}) +[2026-07-26 20:31:50,639][starVLA.training.train_starvla][INFO] - Step 785, Loss: {'train/loss': 0.5844674110412598, 'train/grad_norm_pre_clip': 2.819247007369995, 'timing/data': 0.00017406512051820755, 'timing/model': 0.45799463288858533, 'learning_rate/action_model': 9.427878951630418e-05, 'learning_rate/action_query_proj': 9.427878951630418e-05, 'learning_rate/base': 2.3569697379076044e-05, 'epoch': 0.1}) +[2026-07-26 20:31:56,172][starVLA.training.train_starvla][INFO] - Step 786, Loss: {'train/loss': 0.6068511605262756, 'train/grad_norm_pre_clip': 4.1590094566345215, 'timing/data': 0.0001765177585184574, 'timing/model': 0.45981631614267826, 'learning_rate/action_model': 9.426450155028334e-05, 'learning_rate/action_query_proj': 9.426450155028334e-05, 'learning_rate/base': 2.3566125387570834e-05, 'epoch': 0.1}) +[2026-07-26 20:32:01,701][starVLA.training.train_starvla][INFO] - Step 787, Loss: {'train/loss': 0.47580936551094055, 'train/grad_norm_pre_clip': 5.937524318695068, 'timing/data': 0.00017462996765971184, 'timing/model': 0.4578270660713315, 'learning_rate/action_model': 9.425019689890664e-05, 'learning_rate/action_query_proj': 9.425019689890664e-05, 'learning_rate/base': 2.356254922472666e-05, 'epoch': 0.1}) +[2026-07-26 20:32:07,230][starVLA.training.train_starvla][INFO] - Step 788, Loss: {'train/loss': 0.5362479090690613, 'train/grad_norm_pre_clip': 4.912162780761719, 'timing/data': 0.00018351199105381966, 'timing/model': 0.45866314182057977, 'learning_rate/action_model': 9.42358755678213e-05, 'learning_rate/action_query_proj': 9.42358755678213e-05, 'learning_rate/base': 2.3558968891955324e-05, 'epoch': 0.1}) +[2026-07-26 20:32:12,753][starVLA.training.train_starvla][INFO] - Step 789, Loss: {'train/loss': 0.5010152459144592, 'train/grad_norm_pre_clip': 3.7110538482666016, 'timing/data': 0.00017362413927912712, 'timing/model': 0.456965961959213, 'learning_rate/action_model': 9.42215375626812e-05, 'learning_rate/action_query_proj': 9.42215375626812e-05, 'learning_rate/base': 2.35553843906703e-05, 'epoch': 0.1}) +[2026-07-26 20:32:18,287][starVLA.training.train_starvla][INFO] - Step 790, Loss: {'train/loss': 0.6093462705612183, 'train/grad_norm_pre_clip': 5.576827049255371, 'timing/data': 0.00018355483189225197, 'timing/model': 0.46084882877767086, 'learning_rate/action_model': 9.42071828891467e-05, 'learning_rate/action_query_proj': 9.42071828891467e-05, 'learning_rate/base': 2.3551795722286675e-05, 'epoch': 0.1}) +[2026-07-26 20:32:23,833][starVLA.training.train_starvla][INFO] - Step 791, Loss: {'train/loss': 0.4021638035774231, 'train/grad_norm_pre_clip': 3.497424602508545, 'timing/data': 0.0001812828704714775, 'timing/model': 0.4594122231937945, 'learning_rate/action_model': 9.419281155288484e-05, 'learning_rate/action_query_proj': 9.419281155288484e-05, 'learning_rate/base': 2.354820288822121e-05, 'epoch': 0.1}) +[2026-07-26 20:32:29,356][starVLA.training.train_starvla][INFO] - Step 792, Loss: {'train/loss': 0.6697957515716553, 'train/grad_norm_pre_clip': 6.58447265625, 'timing/data': 0.0001681302674114704, 'timing/model': 0.46069463482126594, 'learning_rate/action_model': 9.417842355956918e-05, 'learning_rate/action_query_proj': 9.417842355956918e-05, 'learning_rate/base': 2.3544605889892295e-05, 'epoch': 0.1}) +[2026-07-26 20:32:34,889][starVLA.training.train_starvla][INFO] - Step 793, Loss: {'train/loss': 0.595262348651886, 'train/grad_norm_pre_clip': 3.9140748977661133, 'timing/data': 0.00016733026131987572, 'timing/model': 0.45894087804481387, 'learning_rate/action_model': 9.416401891487989e-05, 'learning_rate/action_query_proj': 9.416401891487989e-05, 'learning_rate/base': 2.3541004728719973e-05, 'epoch': 0.1}) +[2026-07-26 20:32:40,399][starVLA.training.train_starvla][INFO] - Step 794, Loss: {'train/loss': 0.6123313903808594, 'train/grad_norm_pre_clip': 5.034204959869385, 'timing/data': 0.00018317578360438347, 'timing/model': 0.45807784982025623, 'learning_rate/action_model': 9.414959762450369e-05, 'learning_rate/action_query_proj': 9.414959762450369e-05, 'learning_rate/base': 2.353739940612592e-05, 'epoch': 0.1}) +[2026-07-26 20:32:45,916][starVLA.training.train_starvla][INFO] - Step 795, Loss: {'train/loss': 0.5574504137039185, 'train/grad_norm_pre_clip': 5.907100677490234, 'timing/data': 0.0001730453222990036, 'timing/model': 0.4577619191259146, 'learning_rate/action_model': 9.413515969413386e-05, 'learning_rate/action_query_proj': 9.413515969413386e-05, 'learning_rate/base': 2.3533789923533465e-05, 'epoch': 0.1}) +[2026-07-26 20:32:51,462][starVLA.training.train_starvla][INFO] - Step 796, Loss: {'train/loss': 0.45916467905044556, 'train/grad_norm_pre_clip': 4.186352252960205, 'timing/data': 0.00017149699851870537, 'timing/model': 0.45816740998998284, 'learning_rate/action_model': 9.412070512947025e-05, 'learning_rate/action_query_proj': 9.412070512947025e-05, 'learning_rate/base': 2.3530176282367562e-05, 'epoch': 0.1}) +[2026-07-26 20:32:57,006][starVLA.training.train_starvla][INFO] - Step 797, Loss: {'train/loss': 0.49738427996635437, 'train/grad_norm_pre_clip': 4.375504493713379, 'timing/data': 0.00017363671213388443, 'timing/model': 0.4588039726950228, 'learning_rate/action_model': 9.410623393621935e-05, 'learning_rate/action_query_proj': 9.410623393621935e-05, 'learning_rate/base': 2.3526558484054838e-05, 'epoch': 0.1}) +[2026-07-26 20:33:02,542][starVLA.training.train_starvla][INFO] - Step 798, Loss: {'train/loss': 0.5245661735534668, 'train/grad_norm_pre_clip': 6.363068580627441, 'timing/data': 0.0001721968874335289, 'timing/model': 0.4582527666352689, 'learning_rate/action_model': 9.40917461200941e-05, 'learning_rate/action_query_proj': 9.40917461200941e-05, 'learning_rate/base': 2.3522936530023525e-05, 'epoch': 0.1}) +[2026-07-26 20:33:08,095][starVLA.training.train_starvla][INFO] - Step 799, Loss: {'train/loss': 0.5901942253112793, 'train/grad_norm_pre_clip': 4.44012451171875, 'timing/data': 0.00016962364315986633, 'timing/model': 0.46022417303174734, 'learning_rate/action_model': 9.40772416868141e-05, 'learning_rate/action_query_proj': 9.40772416868141e-05, 'learning_rate/base': 2.3519310421703526e-05, 'epoch': 0.1}) +[2026-07-26 20:33:13,649][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 800 +[2026-07-26 20:33:13,651][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 800 +[2026-07-26 20:33:13,652][starVLA.training.train_starvla][INFO] - Step 800, Loss: {'train/loss': 0.7395298480987549, 'train/grad_norm_pre_clip': 5.781765460968018, 'timing/data': 0.00018361909314990044, 'timing/model': 0.45725216902792454, 'learning_rate/action_model': 9.406272064210545e-05, 'learning_rate/action_query_proj': 9.406272064210545e-05, 'learning_rate/base': 2.351568016052636e-05, 'epoch': 0.1}) +[2026-07-26 20:33:19,181][starVLA.training.train_starvla][INFO] - Step 801, Loss: {'train/loss': 0.638541042804718, 'train/grad_norm_pre_clip': 4.193973541259766, 'timing/data': 0.00017098896205425262, 'timing/model': 0.45821780199185014, 'learning_rate/action_model': 9.404818299170084e-05, 'learning_rate/action_query_proj': 9.404818299170084e-05, 'learning_rate/base': 2.351204574792521e-05, 'epoch': 0.1}) +[2026-07-26 20:33:24,718][starVLA.training.train_starvla][INFO] - Step 802, Loss: {'train/loss': 0.48305007815361023, 'train/grad_norm_pre_clip': 2.8051581382751465, 'timing/data': 0.00017190305516123772, 'timing/model': 0.4588324730284512, 'learning_rate/action_model': 9.403362874133952e-05, 'learning_rate/action_query_proj': 9.403362874133952e-05, 'learning_rate/base': 2.350840718533488e-05, 'epoch': 0.1}) +[2026-07-26 20:33:30,255][starVLA.training.train_starvla][INFO] - Step 803, Loss: {'train/loss': 0.4351597726345062, 'train/grad_norm_pre_clip': 4.028951168060303, 'timing/data': 0.00017437897622585297, 'timing/model': 0.4579380131326616, 'learning_rate/action_model': 9.401905789676722e-05, 'learning_rate/action_query_proj': 9.401905789676722e-05, 'learning_rate/base': 2.3504764474191806e-05, 'epoch': 0.1}) +[2026-07-26 20:33:35,798][starVLA.training.train_starvla][INFO] - Step 804, Loss: {'train/loss': 0.5501967072486877, 'train/grad_norm_pre_clip': 5.4795403480529785, 'timing/data': 0.00017045997083187103, 'timing/model': 0.45793444011360407, 'learning_rate/action_model': 9.400447046373634e-05, 'learning_rate/action_query_proj': 9.400447046373634e-05, 'learning_rate/base': 2.3501117615934086e-05, 'epoch': 0.1}) +[2026-07-26 20:33:41,401][starVLA.training.train_starvla][INFO] - Step 805, Loss: {'train/loss': 0.5698638558387756, 'train/grad_norm_pre_clip': 6.840872287750244, 'timing/data': 0.00017679622396826744, 'timing/model': 0.45809537591412663, 'learning_rate/action_model': 9.398986644800573e-05, 'learning_rate/action_query_proj': 9.398986644800573e-05, 'learning_rate/base': 2.3497466612001434e-05, 'epoch': 0.1}) +[2026-07-26 20:33:46,948][starVLA.training.train_starvla][INFO] - Step 806, Loss: {'train/loss': 0.6352585554122925, 'train/grad_norm_pre_clip': 5.7654008865356445, 'timing/data': 0.00016916077584028244, 'timing/model': 0.4561375640332699, 'learning_rate/action_model': 9.397524585534085e-05, 'learning_rate/action_query_proj': 9.397524585534085e-05, 'learning_rate/base': 2.3493811463835213e-05, 'epoch': 0.1}) +[2026-07-26 20:33:52,744][starVLA.training.train_starvla][INFO] - Step 807, Loss: {'train/loss': 0.5870895981788635, 'train/grad_norm_pre_clip': 3.6321775913238525, 'timing/data': 0.00017111096531152725, 'timing/model': 0.4636450386606157, 'learning_rate/action_model': 9.396060869151366e-05, 'learning_rate/action_query_proj': 9.396060869151366e-05, 'learning_rate/base': 2.3490152172878414e-05, 'epoch': 0.1}) +[2026-07-26 20:33:58,305][starVLA.training.train_starvla][INFO] - Step 808, Loss: {'train/loss': 0.4781712293624878, 'train/grad_norm_pre_clip': 6.110475063323975, 'timing/data': 0.00017154216766357422, 'timing/model': 0.4627740611322224, 'learning_rate/action_model': 9.39459549623027e-05, 'learning_rate/action_query_proj': 9.39459549623027e-05, 'learning_rate/base': 2.3486488740575675e-05, 'epoch': 0.1}) +[2026-07-26 20:34:03,845][starVLA.training.train_starvla][INFO] - Step 809, Loss: {'train/loss': 0.613448441028595, 'train/grad_norm_pre_clip': 4.698383331298828, 'timing/data': 0.00018005399033427238, 'timing/model': 0.45759111270308495, 'learning_rate/action_model': 9.393128467349301e-05, 'learning_rate/action_query_proj': 9.393128467349301e-05, 'learning_rate/base': 2.3482821168373252e-05, 'epoch': 0.1}) +[2026-07-26 20:34:09,399][starVLA.training.train_starvla][INFO] - Step 810, Loss: {'train/loss': 0.5147489309310913, 'train/grad_norm_pre_clip': 5.451705455780029, 'timing/data': 0.00018067192286252975, 'timing/model': 0.4579902873374522, 'learning_rate/action_model': 9.391659783087618e-05, 'learning_rate/action_query_proj': 9.391659783087618e-05, 'learning_rate/base': 2.3479149457719045e-05, 'epoch': 0.1}) +[2026-07-26 20:34:14,952][starVLA.training.train_starvla][INFO] - Step 811, Loss: {'train/loss': 0.5463504791259766, 'train/grad_norm_pre_clip': 5.679574012756348, 'timing/data': 0.0001734369434416294, 'timing/model': 0.4586526728235185, 'learning_rate/action_model': 9.390189444025036e-05, 'learning_rate/action_query_proj': 9.390189444025036e-05, 'learning_rate/base': 2.347547361006259e-05, 'epoch': 0.1}) +[2026-07-26 20:34:20,505][starVLA.training.train_starvla][INFO] - Step 812, Loss: {'train/loss': 0.4986932575702667, 'train/grad_norm_pre_clip': 4.494496822357178, 'timing/data': 0.00017133867368102074, 'timing/model': 0.457978755235672, 'learning_rate/action_model': 9.388717450742021e-05, 'learning_rate/action_query_proj': 9.388717450742021e-05, 'learning_rate/base': 2.3471793626855053e-05, 'epoch': 0.1}) +[2026-07-26 20:34:26,062][starVLA.training.train_starvla][INFO] - Step 813, Loss: {'train/loss': 0.5886621475219727, 'train/grad_norm_pre_clip': 5.004243850708008, 'timing/data': 0.0001713009551167488, 'timing/model': 0.45870089204981923, 'learning_rate/action_model': 9.387243803819694e-05, 'learning_rate/action_query_proj': 9.387243803819694e-05, 'learning_rate/base': 2.3468109509549235e-05, 'epoch': 0.1}) +[2026-07-26 20:34:31,634][starVLA.training.train_starvla][INFO] - Step 814, Loss: {'train/loss': 0.520218014717102, 'train/grad_norm_pre_clip': 3.9850246906280518, 'timing/data': 0.00017560599371790886, 'timing/model': 0.45906384382396936, 'learning_rate/action_model': 9.385768503839827e-05, 'learning_rate/action_query_proj': 9.385768503839827e-05, 'learning_rate/base': 2.346442125959957e-05, 'epoch': 0.1}) +[2026-07-26 20:34:37,188][starVLA.training.train_starvla][INFO] - Step 815, Loss: {'train/loss': 0.4683319926261902, 'train/grad_norm_pre_clip': 3.5419774055480957, 'timing/data': 0.00017321202903985977, 'timing/model': 0.4590081162750721, 'learning_rate/action_model': 9.384291551384843e-05, 'learning_rate/action_query_proj': 9.384291551384843e-05, 'learning_rate/base': 2.346072887846211e-05, 'epoch': 0.1}) +[2026-07-26 20:34:42,727][starVLA.training.train_starvla][INFO] - Step 816, Loss: {'train/loss': 0.5806554555892944, 'train/grad_norm_pre_clip': 4.486900329589844, 'timing/data': 0.00017116591334342957, 'timing/model': 0.4589069839566946, 'learning_rate/action_model': 9.382812947037821e-05, 'learning_rate/action_query_proj': 9.382812947037821e-05, 'learning_rate/base': 2.3457032367594552e-05, 'epoch': 0.1}) +[2026-07-26 20:34:48,271][starVLA.training.train_starvla][INFO] - Step 817, Loss: {'train/loss': 0.5097620487213135, 'train/grad_norm_pre_clip': 3.9532980918884277, 'timing/data': 0.00017191795632243156, 'timing/model': 0.45813626190647483, 'learning_rate/action_model': 9.381332691382491e-05, 'learning_rate/action_query_proj': 9.381332691382491e-05, 'learning_rate/base': 2.345333172845623e-05, 'epoch': 0.1}) +[2026-07-26 20:34:53,797][starVLA.training.train_starvla][INFO] - Step 818, Loss: {'train/loss': 0.6300550699234009, 'train/grad_norm_pre_clip': 4.919803142547607, 'timing/data': 0.00016746297478675842, 'timing/model': 0.458865141030401, 'learning_rate/action_model': 9.379850785003234e-05, 'learning_rate/action_query_proj': 9.379850785003234e-05, 'learning_rate/base': 2.3449626962508086e-05, 'epoch': 0.1}) +[2026-07-26 20:34:59,354][starVLA.training.train_starvla][INFO] - Step 819, Loss: {'train/loss': 0.44444265961647034, 'train/grad_norm_pre_clip': 3.3189799785614014, 'timing/data': 0.00017609074711799622, 'timing/model': 0.4598471401259303, 'learning_rate/action_model': 9.378367228485083e-05, 'learning_rate/action_query_proj': 9.378367228485083e-05, 'learning_rate/base': 2.3445918071212707e-05, 'epoch': 0.1}) +[2026-07-26 20:35:04,904][starVLA.training.train_starvla][INFO] - Step 820, Loss: {'train/loss': 0.45419615507125854, 'train/grad_norm_pre_clip': 4.79044771194458, 'timing/data': 0.00017681019380688667, 'timing/model': 0.45885817101225257, 'learning_rate/action_model': 9.376882022413723e-05, 'learning_rate/action_query_proj': 9.376882022413723e-05, 'learning_rate/base': 2.3442205056034307e-05, 'epoch': 0.1}) +[2026-07-26 20:35:10,438][starVLA.training.train_starvla][INFO] - Step 821, Loss: {'train/loss': 0.6214161515235901, 'train/grad_norm_pre_clip': 6.3786725997924805, 'timing/data': 0.00017019174993038177, 'timing/model': 0.46229113824665546, 'learning_rate/action_model': 9.375395167375489e-05, 'learning_rate/action_query_proj': 9.375395167375489e-05, 'learning_rate/base': 2.3438487918438723e-05, 'epoch': 0.1}) +[2026-07-26 20:35:15,994][starVLA.training.train_starvla][INFO] - Step 822, Loss: {'train/loss': 0.52630215883255, 'train/grad_norm_pre_clip': 5.597684383392334, 'timing/data': 0.00017153192311525345, 'timing/model': 0.4629761939868331, 'learning_rate/action_model': 9.37390666395737e-05, 'learning_rate/action_query_proj': 9.37390666395737e-05, 'learning_rate/base': 2.3434766659893427e-05, 'epoch': 0.1}) +[2026-07-26 20:35:21,545][starVLA.training.train_starvla][INFO] - Step 823, Loss: {'train/loss': 0.5088022351264954, 'train/grad_norm_pre_clip': 4.870778560638428, 'timing/data': 0.00017735688015818596, 'timing/model': 0.46174887008965015, 'learning_rate/action_model': 9.372416512747e-05, 'learning_rate/action_query_proj': 9.372416512747e-05, 'learning_rate/base': 2.34310412818675e-05, 'epoch': 0.1}) +[2026-07-26 20:35:27,089][starVLA.training.train_starvla][INFO] - Step 824, Loss: {'train/loss': 0.48785752058029175, 'train/grad_norm_pre_clip': 4.125202178955078, 'timing/data': 0.00016782991588115692, 'timing/model': 0.46196328522637486, 'learning_rate/action_model': 9.370924714332671e-05, 'learning_rate/action_query_proj': 9.370924714332671e-05, 'learning_rate/base': 2.3427311785831678e-05, 'epoch': 0.1}) +[2026-07-26 20:35:32,621][starVLA.training.train_starvla][INFO] - Step 825, Loss: {'train/loss': 0.5608606934547424, 'train/grad_norm_pre_clip': 5.1484293937683105, 'timing/data': 0.00017310073599219322, 'timing/model': 0.4632982490584254, 'learning_rate/action_model': 9.36943126930332e-05, 'learning_rate/action_query_proj': 9.36943126930332e-05, 'learning_rate/base': 2.34235781732583e-05, 'epoch': 0.1}) +[2026-07-26 20:35:38,215][starVLA.training.train_starvla][INFO] - Step 826, Loss: {'train/loss': 0.43951258063316345, 'train/grad_norm_pre_clip': 4.660998821258545, 'timing/data': 0.00016777962446212769, 'timing/model': 0.4717115950770676, 'learning_rate/action_model': 9.367936178248533e-05, 'learning_rate/action_query_proj': 9.367936178248533e-05, 'learning_rate/base': 2.341984044562133e-05, 'epoch': 0.1}) +[2026-07-26 20:35:43,792][starVLA.training.train_starvla][INFO] - Step 827, Loss: {'train/loss': 0.5685727000236511, 'train/grad_norm_pre_clip': 3.6322734355926514, 'timing/data': 0.00017199013382196426, 'timing/model': 0.4711965639144182, 'learning_rate/action_model': 9.36643944175855e-05, 'learning_rate/action_query_proj': 9.36643944175855e-05, 'learning_rate/base': 2.3416098604396374e-05, 'epoch': 0.1}) +[2026-07-26 20:35:49,339][starVLA.training.train_starvla][INFO] - Step 828, Loss: {'train/loss': 0.6173114776611328, 'train/grad_norm_pre_clip': 4.50351095199585, 'timing/data': 0.0001751217059791088, 'timing/model': 0.47198651172220707, 'learning_rate/action_model': 9.364941060424258e-05, 'learning_rate/action_query_proj': 9.364941060424258e-05, 'learning_rate/base': 2.3412352651060645e-05, 'epoch': 0.1}) +[2026-07-26 20:35:54,887][starVLA.training.train_starvla][INFO] - Step 829, Loss: {'train/loss': 0.38255247473716736, 'train/grad_norm_pre_clip': 3.216564178466797, 'timing/data': 0.00017493590712547302, 'timing/model': 0.47250790568068624, 'learning_rate/action_model': 9.363441034837199e-05, 'learning_rate/action_query_proj': 9.363441034837199e-05, 'learning_rate/base': 2.3408602587092997e-05, 'epoch': 0.1}) +[2026-07-26 20:36:00,434][starVLA.training.train_starvla][INFO] - Step 830, Loss: {'train/loss': 0.44664597511291504, 'train/grad_norm_pre_clip': 4.148005485534668, 'timing/data': 0.0001711561344563961, 'timing/model': 0.46975905494764447, 'learning_rate/action_model': 9.361939365589553e-05, 'learning_rate/action_query_proj': 9.361939365589553e-05, 'learning_rate/base': 2.3404848413973883e-05, 'epoch': 0.1}) +[2026-07-26 20:36:05,955][starVLA.training.train_starvla][INFO] - Step 831, Loss: {'train/loss': 0.5711806416511536, 'train/grad_norm_pre_clip': 3.7800467014312744, 'timing/data': 0.0001729670912027359, 'timing/model': 0.45750261284410954, 'learning_rate/action_model': 9.360436053274158e-05, 'learning_rate/action_query_proj': 9.360436053274158e-05, 'learning_rate/base': 2.3401090133185395e-05, 'epoch': 0.1}) +[2026-07-26 20:36:11,491][starVLA.training.train_starvla][INFO] - Step 832, Loss: {'train/loss': 0.5700187683105469, 'train/grad_norm_pre_clip': 5.078352451324463, 'timing/data': 0.00017815083265304565, 'timing/model': 0.4585017478093505, 'learning_rate/action_model': 9.358931098484499e-05, 'learning_rate/action_query_proj': 9.358931098484499e-05, 'learning_rate/base': 2.3397327746211247e-05, 'epoch': 0.1}) +[2026-07-26 20:36:17,010][starVLA.training.train_starvla][INFO] - Step 833, Loss: {'train/loss': 0.647186279296875, 'train/grad_norm_pre_clip': 4.782202243804932, 'timing/data': 0.00017291028052568436, 'timing/model': 0.4580409680493176, 'learning_rate/action_model': 9.357424501814706e-05, 'learning_rate/action_query_proj': 9.357424501814706e-05, 'learning_rate/base': 2.3393561254536764e-05, 'epoch': 0.1}) +[2026-07-26 20:36:22,524][starVLA.training.train_starvla][INFO] - Step 834, Loss: {'train/loss': 0.48203369975090027, 'train/grad_norm_pre_clip': 2.5999152660369873, 'timing/data': 0.00017567630857229233, 'timing/model': 0.45776928402483463, 'learning_rate/action_model': 9.355916263859561e-05, 'learning_rate/action_query_proj': 9.355916263859561e-05, 'learning_rate/base': 2.3389790659648904e-05, 'epoch': 0.1}) +[2026-07-26 20:36:28,036][starVLA.training.train_starvla][INFO] - Step 835, Loss: {'train/loss': 0.43499717116355896, 'train/grad_norm_pre_clip': 3.466236114501953, 'timing/data': 0.00017820904031395912, 'timing/model': 0.4580973656848073, 'learning_rate/action_model': 9.354406385214491e-05, 'learning_rate/action_query_proj': 9.354406385214491e-05, 'learning_rate/base': 2.3386015963036227e-05, 'epoch': 0.1}) +[2026-07-26 20:36:33,556][starVLA.training.train_starvla][INFO] - Step 836, Loss: {'train/loss': 0.4533941149711609, 'train/grad_norm_pre_clip': 4.87901496887207, 'timing/data': 0.00017057918012142181, 'timing/model': 0.4587059812620282, 'learning_rate/action_model': 9.352894866475575e-05, 'learning_rate/action_query_proj': 9.352894866475575e-05, 'learning_rate/base': 2.3382237166188937e-05, 'epoch': 0.1}) +[2026-07-26 20:36:39,068][starVLA.training.train_starvla][INFO] - Step 837, Loss: {'train/loss': 0.5788307189941406, 'train/grad_norm_pre_clip': 5.769286155700684, 'timing/data': 0.00017258571460843086, 'timing/model': 0.4579185456968844, 'learning_rate/action_model': 9.351381708239534e-05, 'learning_rate/action_query_proj': 9.351381708239534e-05, 'learning_rate/base': 2.3378454270598835e-05, 'epoch': 0.1}) +[2026-07-26 20:36:44,566][starVLA.training.train_starvla][INFO] - Step 838, Loss: {'train/loss': 0.5096027851104736, 'train/grad_norm_pre_clip': 5.083909511566162, 'timing/data': 0.0001729191280901432, 'timing/model': 0.45790674770250916, 'learning_rate/action_model': 9.34986691110374e-05, 'learning_rate/action_query_proj': 9.34986691110374e-05, 'learning_rate/base': 2.337466727775935e-05, 'epoch': 0.1}) +[2026-07-26 20:36:50,064][starVLA.training.train_starvla][INFO] - Step 839, Loss: {'train/loss': 0.5285240411758423, 'train/grad_norm_pre_clip': 3.972384214401245, 'timing/data': 0.00017224671319127083, 'timing/model': 0.4586951034143567, 'learning_rate/action_model': 9.34835047566621e-05, 'learning_rate/action_query_proj': 9.34835047566621e-05, 'learning_rate/base': 2.3370876189165525e-05, 'epoch': 0.1}) +[2026-07-26 20:36:55,548][starVLA.training.train_starvla][INFO] - Step 840, Loss: {'train/loss': 0.45665913820266724, 'train/grad_norm_pre_clip': 4.450830459594727, 'timing/data': 0.00016774795949459076, 'timing/model': 0.4574646237306297, 'learning_rate/action_model': 9.34683240252561e-05, 'learning_rate/action_query_proj': 9.34683240252561e-05, 'learning_rate/base': 2.3367081006314024e-05, 'epoch': 0.1}) +[2026-07-26 20:37:01,103][starVLA.training.train_starvla][INFO] - Step 841, Loss: {'train/loss': 0.4726580083370209, 'train/grad_norm_pre_clip': 3.3600709438323975, 'timing/data': 0.00017536478117108345, 'timing/model': 0.45835333736613393, 'learning_rate/action_model': 9.345312692281251e-05, 'learning_rate/action_query_proj': 9.345312692281251e-05, 'learning_rate/base': 2.3363281730703128e-05, 'epoch': 0.1}) +[2026-07-26 20:37:06,621][starVLA.training.train_starvla][INFO] - Step 842, Loss: {'train/loss': 0.5820300579071045, 'train/grad_norm_pre_clip': 5.287998676300049, 'timing/data': 0.0001760483719408512, 'timing/model': 0.45894006825983524, 'learning_rate/action_model': 9.34379134553309e-05, 'learning_rate/action_query_proj': 9.34379134553309e-05, 'learning_rate/base': 2.3359478363832725e-05, 'epoch': 0.1}) +[2026-07-26 20:37:12,149][starVLA.training.train_starvla][INFO] - Step 843, Loss: {'train/loss': 0.4623603820800781, 'train/grad_norm_pre_clip': 4.1157379150390625, 'timing/data': 0.00018284330144524574, 'timing/model': 0.45759603288024664, 'learning_rate/action_model': 9.342268362881729e-05, 'learning_rate/action_query_proj': 9.342268362881729e-05, 'learning_rate/base': 2.3355670907204323e-05, 'epoch': 0.1}) +[2026-07-26 20:37:17,873][starVLA.training.train_starvla][INFO] - Step 844, Loss: {'train/loss': 0.5728400349617004, 'train/grad_norm_pre_clip': 4.3152756690979, 'timing/data': 0.00017455080524086952, 'timing/model': 0.666212220210582, 'learning_rate/action_model': 9.340743744928422e-05, 'learning_rate/action_query_proj': 9.340743744928422e-05, 'learning_rate/base': 2.3351859362321054e-05, 'epoch': 0.1}) +[2026-07-26 20:37:23,394][starVLA.training.train_starvla][INFO] - Step 845, Loss: {'train/loss': 0.4572048485279083, 'train/grad_norm_pre_clip': 4.766704559326172, 'timing/data': 0.00017549702897667885, 'timing/model': 0.4580351081676781, 'learning_rate/action_model': 9.33921749227506e-05, 'learning_rate/action_query_proj': 9.33921749227506e-05, 'learning_rate/base': 2.334804373068765e-05, 'epoch': 0.1}) +[2026-07-26 20:37:28,914][starVLA.training.train_starvla][INFO] - Step 846, Loss: {'train/loss': 0.37352049350738525, 'train/grad_norm_pre_clip': 5.4514689445495605, 'timing/data': 0.00017113704234361649, 'timing/model': 0.4580594878643751, 'learning_rate/action_model': 9.337689605524184e-05, 'learning_rate/action_query_proj': 9.337689605524184e-05, 'learning_rate/base': 2.334422401381046e-05, 'epoch': 0.1}) +[2026-07-26 20:37:34,433][starVLA.training.train_starvla][INFO] - Step 847, Loss: {'train/loss': 0.5828598141670227, 'train/grad_norm_pre_clip': 3.7323172092437744, 'timing/data': 0.00017345556989312172, 'timing/model': 0.4569251388311386, 'learning_rate/action_model': 9.336160085278981e-05, 'learning_rate/action_query_proj': 9.336160085278981e-05, 'learning_rate/base': 2.3340400213197452e-05, 'epoch': 0.1}) +[2026-07-26 20:37:39,951][starVLA.training.train_starvla][INFO] - Step 848, Loss: {'train/loss': 0.6292136907577515, 'train/grad_norm_pre_clip': 5.667712688446045, 'timing/data': 0.00017526838928461075, 'timing/model': 0.4573177029378712, 'learning_rate/action_model': 9.33462893214328e-05, 'learning_rate/action_query_proj': 9.33462893214328e-05, 'learning_rate/base': 2.33365723303582e-05, 'epoch': 0.1}) +[2026-07-26 20:37:45,474][starVLA.training.train_starvla][INFO] - Step 849, Loss: {'train/loss': 0.6021974682807922, 'train/grad_norm_pre_clip': 4.505949020385742, 'timing/data': 0.00016805017367005348, 'timing/model': 0.45836078794673085, 'learning_rate/action_model': 9.333096146721557e-05, 'learning_rate/action_query_proj': 9.333096146721557e-05, 'learning_rate/base': 2.333274036680389e-05, 'epoch': 0.1}) +[2026-07-26 20:37:50,988][starVLA.training.train_starvla][INFO] - Step 850, Loss: {'train/loss': 0.6532562971115112, 'train/grad_norm_pre_clip': 5.051359176635742, 'timing/data': 0.00017966097220778465, 'timing/model': 0.45776675920933485, 'learning_rate/action_model': 9.33156172961893e-05, 'learning_rate/action_query_proj': 9.33156172961893e-05, 'learning_rate/base': 2.3328904324047325e-05, 'epoch': 0.1}) +[2026-07-26 20:37:56,507][starVLA.training.train_starvla][INFO] - Step 851, Loss: {'train/loss': 0.5318248271942139, 'train/grad_norm_pre_clip': 6.133580684661865, 'timing/data': 0.00017812475562095642, 'timing/model': 0.4591167704202235, 'learning_rate/action_model': 9.330025681441163e-05, 'learning_rate/action_query_proj': 9.330025681441163e-05, 'learning_rate/base': 2.3325064203602908e-05, 'epoch': 0.1}) +[2026-07-26 20:38:02,042][starVLA.training.train_starvla][INFO] - Step 852, Loss: {'train/loss': 0.5159701108932495, 'train/grad_norm_pre_clip': 5.688294410705566, 'timing/data': 0.000173947773873806, 'timing/model': 0.45782359363511205, 'learning_rate/action_model': 9.328488002794666e-05, 'learning_rate/action_query_proj': 9.328488002794666e-05, 'learning_rate/base': 2.3321220006986664e-05, 'epoch': 0.1}) +[2026-07-26 20:38:07,554][starVLA.training.train_starvla][INFO] - Step 853, Loss: {'train/loss': 0.5694651007652283, 'train/grad_norm_pre_clip': 6.153191089630127, 'timing/data': 0.000169381033629179, 'timing/model': 0.4570955731905997, 'learning_rate/action_model': 9.326948694286486e-05, 'learning_rate/action_query_proj': 9.326948694286486e-05, 'learning_rate/base': 2.3317371735716215e-05, 'epoch': 0.1}) +[2026-07-26 20:38:13,072][starVLA.training.train_starvla][INFO] - Step 854, Loss: {'train/loss': 0.5898048281669617, 'train/grad_norm_pre_clip': 7.550212383270264, 'timing/data': 0.00016539590433239937, 'timing/model': 0.47087079379707575, 'learning_rate/action_model': 9.325407756524321e-05, 'learning_rate/action_query_proj': 9.325407756524321e-05, 'learning_rate/base': 2.3313519391310802e-05, 'epoch': 0.1}) +[2026-07-26 20:38:18,651][starVLA.training.train_starvla][INFO] - Step 855, Loss: {'train/loss': 0.5401933789253235, 'train/grad_norm_pre_clip': 7.1981329917907715, 'timing/data': 0.00016934890300035477, 'timing/model': 0.4704386009834707, 'learning_rate/action_model': 9.323865190116508e-05, 'learning_rate/action_query_proj': 9.323865190116508e-05, 'learning_rate/base': 2.330966297529127e-05, 'epoch': 0.1}) +[2026-07-26 20:38:24,214][starVLA.training.train_starvla][INFO] - Step 856, Loss: {'train/loss': 0.4838760197162628, 'train/grad_norm_pre_clip': 3.3137385845184326, 'timing/data': 0.00017164694145321846, 'timing/model': 0.47758521884679794, 'learning_rate/action_model': 9.322320995672028e-05, 'learning_rate/action_query_proj': 9.322320995672028e-05, 'learning_rate/base': 2.330580248918007e-05, 'epoch': 0.1}) +[2026-07-26 20:38:29,742][starVLA.training.train_starvla][INFO] - Step 857, Loss: {'train/loss': 0.6297409534454346, 'train/grad_norm_pre_clip': 3.7212648391723633, 'timing/data': 0.00016497820615768433, 'timing/model': 0.47246408089995384, 'learning_rate/action_model': 9.3207751738005e-05, 'learning_rate/action_query_proj': 9.3207751738005e-05, 'learning_rate/base': 2.330193793450125e-05, 'epoch': 0.1}) +[2026-07-26 20:38:35,263][starVLA.training.train_starvla][INFO] - Step 858, Loss: {'train/loss': 0.4298759996891022, 'train/grad_norm_pre_clip': 3.1810476779937744, 'timing/data': 0.00017326977103948593, 'timing/model': 0.4585149260237813, 'learning_rate/action_model': 9.319227725112199e-05, 'learning_rate/action_query_proj': 9.319227725112199e-05, 'learning_rate/base': 2.3298069312780497e-05, 'epoch': 0.1}) +[2026-07-26 20:38:40,813][starVLA.training.train_starvla][INFO] - Step 859, Loss: {'train/loss': 0.5579661726951599, 'train/grad_norm_pre_clip': 6.4587082862854, 'timing/data': 0.00016745273023843765, 'timing/model': 0.4592206780798733, 'learning_rate/action_model': 9.317678650218024e-05, 'learning_rate/action_query_proj': 9.317678650218024e-05, 'learning_rate/base': 2.329419662554506e-05, 'epoch': 0.1}) +[2026-07-26 20:38:46,345][starVLA.training.train_starvla][INFO] - Step 860, Loss: {'train/loss': 0.6069319844245911, 'train/grad_norm_pre_clip': 8.676072120666504, 'timing/data': 0.00017236126586794853, 'timing/model': 0.4581713587976992, 'learning_rate/action_model': 9.316127949729531e-05, 'learning_rate/action_query_proj': 9.316127949729531e-05, 'learning_rate/base': 2.329031987432383e-05, 'epoch': 0.1}) +[2026-07-26 20:38:51,864][starVLA.training.train_starvla][INFO] - Step 861, Loss: {'train/loss': 0.6107838153839111, 'train/grad_norm_pre_clip': 3.6409213542938232, 'timing/data': 0.00017026904970407486, 'timing/model': 0.4604167779907584, 'learning_rate/action_model': 9.314575624258912e-05, 'learning_rate/action_query_proj': 9.314575624258912e-05, 'learning_rate/base': 2.328643906064728e-05, 'epoch': 0.1}) +[2026-07-26 20:38:57,880][starVLA.training.train_starvla][INFO] - Step 862, Loss: {'train/loss': 0.4349427819252014, 'train/grad_norm_pre_clip': 4.509532451629639, 'timing/data': 0.0001756809651851654, 'timing/model': 0.462313509080559, 'learning_rate/action_model': 9.313021674418996e-05, 'learning_rate/action_query_proj': 9.313021674418996e-05, 'learning_rate/base': 2.328255418604749e-05, 'epoch': 0.1}) +[2026-07-26 20:39:03,404][starVLA.training.train_starvla][INFO] - Step 863, Loss: {'train/loss': 0.4760221540927887, 'train/grad_norm_pre_clip': 4.410825252532959, 'timing/data': 0.00016947882249951363, 'timing/model': 0.45898944372311234, 'learning_rate/action_model': 9.311466100823261e-05, 'learning_rate/action_query_proj': 9.311466100823261e-05, 'learning_rate/base': 2.3278665252058152e-05, 'epoch': 0.1}) +[2026-07-26 20:39:09,187][starVLA.training.train_starvla][INFO] - Step 864, Loss: {'train/loss': 0.358646422624588, 'train/grad_norm_pre_clip': 2.664757251739502, 'timing/data': 0.00017324090003967285, 'timing/model': 0.4611410340294242, 'learning_rate/action_model': 9.309908904085823e-05, 'learning_rate/action_query_proj': 9.309908904085823e-05, 'learning_rate/base': 2.327477226021456e-05, 'epoch': 0.1}) +[2026-07-26 20:39:14,711][starVLA.training.train_starvla][INFO] - Step 865, Loss: {'train/loss': 0.5331482291221619, 'train/grad_norm_pre_clip': 5.045232772827148, 'timing/data': 0.0001681181602180004, 'timing/model': 0.4607655559666455, 'learning_rate/action_model': 9.308350084821439e-05, 'learning_rate/action_query_proj': 9.308350084821439e-05, 'learning_rate/base': 2.3270875212053597e-05, 'epoch': 0.1}) +[2026-07-26 20:39:20,261][starVLA.training.train_starvla][INFO] - Step 866, Loss: {'train/loss': 0.5350642204284668, 'train/grad_norm_pre_clip': 4.007144451141357, 'timing/data': 0.00017325486987829208, 'timing/model': 0.4610309461131692, 'learning_rate/action_model': 9.306789643645505e-05, 'learning_rate/action_query_proj': 9.306789643645505e-05, 'learning_rate/base': 2.3266974109113763e-05, 'epoch': 0.11}) +[2026-07-26 20:39:26,053][starVLA.training.train_starvla][INFO] - Step 867, Loss: {'train/loss': 0.4242992401123047, 'train/grad_norm_pre_clip': 5.7455315589904785, 'timing/data': 0.00017047720029950142, 'timing/model': 0.46215081633999944, 'learning_rate/action_model': 9.305227581174057e-05, 'learning_rate/action_query_proj': 9.305227581174057e-05, 'learning_rate/base': 2.3263068952935142e-05, 'epoch': 0.11}) +[2026-07-26 20:39:32,100][starVLA.training.train_starvla][INFO] - Step 868, Loss: {'train/loss': 0.5334654450416565, 'train/grad_norm_pre_clip': 5.641821384429932, 'timing/data': 0.00017099641263484955, 'timing/model': 0.4609862710349262, 'learning_rate/action_model': 9.303663898023776e-05, 'learning_rate/action_query_proj': 9.303663898023776e-05, 'learning_rate/base': 2.325915974505944e-05, 'epoch': 0.11}) +[2026-07-26 20:39:37,638][starVLA.training.train_starvla][INFO] - Step 869, Loss: {'train/loss': 0.5134329199790955, 'train/grad_norm_pre_clip': 5.895853519439697, 'timing/data': 0.000171721912920475, 'timing/model': 0.4601003900170326, 'learning_rate/action_model': 9.302098594811976e-05, 'learning_rate/action_query_proj': 9.302098594811976e-05, 'learning_rate/base': 2.325524648702994e-05, 'epoch': 0.11}) +[2026-07-26 20:39:43,184][starVLA.training.train_starvla][INFO] - Step 870, Loss: {'train/loss': 0.6090548038482666, 'train/grad_norm_pre_clip': 4.114086627960205, 'timing/data': 0.00017346302047371864, 'timing/model': 0.4599205330014229, 'learning_rate/action_model': 9.300531672156618e-05, 'learning_rate/action_query_proj': 9.300531672156618e-05, 'learning_rate/base': 2.3251329180391544e-05, 'epoch': 0.11}) +[2026-07-26 20:39:48,713][starVLA.training.train_starvla][INFO] - Step 871, Loss: {'train/loss': 0.36732351779937744, 'train/grad_norm_pre_clip': 5.35056734085083, 'timing/data': 0.0001811920665204525, 'timing/model': 0.4598922310397029, 'learning_rate/action_model': 9.298963130676294e-05, 'learning_rate/action_query_proj': 9.298963130676294e-05, 'learning_rate/base': 2.3247407826690736e-05, 'epoch': 0.11}) +[2026-07-26 20:39:54,253][starVLA.training.train_starvla][INFO] - Step 872, Loss: {'train/loss': 0.46476152539253235, 'train/grad_norm_pre_clip': 3.3194217681884766, 'timing/data': 0.00017943093553185463, 'timing/model': 0.4596154149621725, 'learning_rate/action_model': 9.297392970990241e-05, 'learning_rate/action_query_proj': 9.297392970990241e-05, 'learning_rate/base': 2.3243482427475603e-05, 'epoch': 0.11}) +[2026-07-26 20:39:59,787][starVLA.training.train_starvla][INFO] - Step 873, Loss: {'train/loss': 0.6068176627159119, 'train/grad_norm_pre_clip': 5.633529186248779, 'timing/data': 0.0001702709123492241, 'timing/model': 0.4623388256877661, 'learning_rate/action_model': 9.295821193718334e-05, 'learning_rate/action_query_proj': 9.295821193718334e-05, 'learning_rate/base': 2.3239552984295835e-05, 'epoch': 0.11}) +[2026-07-26 20:40:05,321][starVLA.training.train_starvla][INFO] - Step 874, Loss: {'train/loss': 0.4442436099052429, 'train/grad_norm_pre_clip': 3.738917112350464, 'timing/data': 0.00017100991681218147, 'timing/model': 0.4603720693849027, 'learning_rate/action_model': 9.294247799481083e-05, 'learning_rate/action_query_proj': 9.294247799481083e-05, 'learning_rate/base': 2.3235619498702706e-05, 'epoch': 0.11}) +[2026-07-26 20:40:10,860][starVLA.training.train_starvla][INFO] - Step 875, Loss: {'train/loss': 0.40692710876464844, 'train/grad_norm_pre_clip': 4.715498924255371, 'timing/data': 0.00018356973305344582, 'timing/model': 0.4588284268975258, 'learning_rate/action_model': 9.292672788899643e-05, 'learning_rate/action_query_proj': 9.292672788899643e-05, 'learning_rate/base': 2.3231681972249107e-05, 'epoch': 0.11}) +[2026-07-26 20:40:16,419][starVLA.training.train_starvla][INFO] - Step 876, Loss: {'train/loss': 0.5151600241661072, 'train/grad_norm_pre_clip': 5.579585552215576, 'timing/data': 0.0001794411800801754, 'timing/model': 0.45913197100162506, 'learning_rate/action_model': 9.291096162595801e-05, 'learning_rate/action_query_proj': 9.291096162595801e-05, 'learning_rate/base': 2.3227740406489503e-05, 'epoch': 0.11}) +[2026-07-26 20:40:21,938][starVLA.training.train_starvla][INFO] - Step 877, Loss: {'train/loss': 0.43501293659210205, 'train/grad_norm_pre_clip': 5.483091354370117, 'timing/data': 0.0001688818447291851, 'timing/model': 0.4600340500473976, 'learning_rate/action_model': 9.289517921191985e-05, 'learning_rate/action_query_proj': 9.289517921191985e-05, 'learning_rate/base': 2.3223794802979963e-05, 'epoch': 0.11}) +[2026-07-26 20:40:27,456][starVLA.training.train_starvla][INFO] - Step 878, Loss: {'train/loss': 0.5195376873016357, 'train/grad_norm_pre_clip': 5.8721604347229, 'timing/data': 0.00017390213906764984, 'timing/model': 0.45825241412967443, 'learning_rate/action_model': 9.287938065311258e-05, 'learning_rate/action_query_proj': 9.287938065311258e-05, 'learning_rate/base': 2.3219845163278144e-05, 'epoch': 0.11}) +[2026-07-26 20:40:33,000][starVLA.training.train_starvla][INFO] - Step 879, Loss: {'train/loss': 0.7548084259033203, 'train/grad_norm_pre_clip': 8.407663345336914, 'timing/data': 0.00018055830150842667, 'timing/model': 0.4606167459860444, 'learning_rate/action_model': 9.286356595577325e-05, 'learning_rate/action_query_proj': 9.286356595577325e-05, 'learning_rate/base': 2.3215891488943312e-05, 'epoch': 0.11}) +[2026-07-26 20:40:38,524][starVLA.training.train_starvla][INFO] - Step 880, Loss: {'train/loss': 0.6217645406723022, 'train/grad_norm_pre_clip': 4.948935508728027, 'timing/data': 0.00016847392544150352, 'timing/model': 0.460729394108057, 'learning_rate/action_model': 9.284773512614522e-05, 'learning_rate/action_query_proj': 9.284773512614522e-05, 'learning_rate/base': 2.3211933781536305e-05, 'epoch': 0.11}) +[2026-07-26 20:40:44,054][starVLA.training.train_starvla][INFO] - Step 881, Loss: {'train/loss': 0.48332589864730835, 'train/grad_norm_pre_clip': 3.310854911804199, 'timing/data': 0.0001680697314441204, 'timing/model': 0.4606888168491423, 'learning_rate/action_model': 9.283188817047826e-05, 'learning_rate/action_query_proj': 9.283188817047826e-05, 'learning_rate/base': 2.3207972042619566e-05, 'epoch': 0.11}) +[2026-07-26 20:40:49,574][starVLA.training.train_starvla][INFO] - Step 882, Loss: {'train/loss': 0.4188680946826935, 'train/grad_norm_pre_clip': 3.0431742668151855, 'timing/data': 0.00016670115292072296, 'timing/model': 0.45829323399811983, 'learning_rate/action_model': 9.281602509502851e-05, 'learning_rate/action_query_proj': 9.281602509502851e-05, 'learning_rate/base': 2.320400627375713e-05, 'epoch': 0.11}) +[2026-07-26 20:40:55,109][starVLA.training.train_starvla][INFO] - Step 883, Loss: {'train/loss': 0.524009644985199, 'train/grad_norm_pre_clip': 6.560265064239502, 'timing/data': 0.00016985274851322174, 'timing/model': 0.4578732871450484, 'learning_rate/action_model': 9.280014590605847e-05, 'learning_rate/action_query_proj': 9.280014590605847e-05, 'learning_rate/base': 2.3200036476514617e-05, 'epoch': 0.11}) +[2026-07-26 20:41:00,650][starVLA.training.train_starvla][INFO] - Step 884, Loss: {'train/loss': 0.4759966731071472, 'train/grad_norm_pre_clip': 7.690690040588379, 'timing/data': 0.00017845025286078453, 'timing/model': 0.46272817021235824, 'learning_rate/action_model': 9.278425060983696e-05, 'learning_rate/action_query_proj': 9.278425060983696e-05, 'learning_rate/base': 2.319606265245924e-05, 'epoch': 0.11}) +[2026-07-26 20:41:06,175][starVLA.training.train_starvla][INFO] - Step 885, Loss: {'train/loss': 0.6687202453613281, 'train/grad_norm_pre_clip': 8.212715148925781, 'timing/data': 0.00017304811626672745, 'timing/model': 0.4619799358770251, 'learning_rate/action_model': 9.27683392126392e-05, 'learning_rate/action_query_proj': 9.27683392126392e-05, 'learning_rate/base': 2.31920848031598e-05, 'epoch': 0.11}) +[2026-07-26 20:41:11,698][starVLA.training.train_starvla][INFO] - Step 886, Loss: {'train/loss': 0.5495510697364807, 'train/grad_norm_pre_clip': 3.991553544998169, 'timing/data': 0.00017445720732212067, 'timing/model': 0.46036136616021395, 'learning_rate/action_model': 9.275241172074677e-05, 'learning_rate/action_query_proj': 9.275241172074677e-05, 'learning_rate/base': 2.318810293018669e-05, 'epoch': 0.11}) +[2026-07-26 20:41:17,226][starVLA.training.train_starvla][INFO] - Step 887, Loss: {'train/loss': 0.36466506123542786, 'train/grad_norm_pre_clip': 3.429112434387207, 'timing/data': 0.00016907602548599243, 'timing/model': 0.46285961708053946, 'learning_rate/action_model': 9.273646814044759e-05, 'learning_rate/action_query_proj': 9.273646814044759e-05, 'learning_rate/base': 2.3184117035111898e-05, 'epoch': 0.11}) +[2026-07-26 20:41:22,751][starVLA.training.train_starvla][INFO] - Step 888, Loss: {'train/loss': 0.6272946000099182, 'train/grad_norm_pre_clip': 4.843188285827637, 'timing/data': 0.0001707109622657299, 'timing/model': 0.46032650163397193, 'learning_rate/action_model': 9.272050847803593e-05, 'learning_rate/action_query_proj': 9.272050847803593e-05, 'learning_rate/base': 2.3180127119508982e-05, 'epoch': 0.11}) +[2026-07-26 20:41:28,269][starVLA.training.train_starvla][INFO] - Step 889, Loss: {'train/loss': 0.5608593225479126, 'train/grad_norm_pre_clip': 3.168416738510132, 'timing/data': 0.00017666304484009743, 'timing/model': 0.4616597490385175, 'learning_rate/action_model': 9.270453273981241e-05, 'learning_rate/action_query_proj': 9.270453273981241e-05, 'learning_rate/base': 2.3176133184953103e-05, 'epoch': 0.11}) +[2026-07-26 20:41:33,868][starVLA.training.train_starvla][INFO] - Step 890, Loss: {'train/loss': 0.6170955896377563, 'train/grad_norm_pre_clip': 3.872988700866699, 'timing/data': 0.00017400411888957024, 'timing/model': 0.461141319014132, 'learning_rate/action_model': 9.2688540932084e-05, 'learning_rate/action_query_proj': 9.2688540932084e-05, 'learning_rate/base': 2.3172135233021e-05, 'epoch': 0.11}) +[2026-07-26 20:41:39,430][starVLA.training.train_starvla][INFO] - Step 891, Loss: {'train/loss': 0.5479302406311035, 'train/grad_norm_pre_clip': 6.607215404510498, 'timing/data': 0.00018047913908958435, 'timing/model': 0.4612731309607625, 'learning_rate/action_model': 9.267253306116401e-05, 'learning_rate/action_query_proj': 9.267253306116401e-05, 'learning_rate/base': 2.3168133265291003e-05, 'epoch': 0.11}) +[2026-07-26 20:41:45,017][starVLA.training.train_starvla][INFO] - Step 892, Loss: {'train/loss': 0.49481621384620667, 'train/grad_norm_pre_clip': 4.349918365478516, 'timing/data': 0.00016920221969485283, 'timing/model': 0.461817414034158, 'learning_rate/action_model': 9.265650913337209e-05, 'learning_rate/action_query_proj': 9.265650913337209e-05, 'learning_rate/base': 2.3164127283343022e-05, 'epoch': 0.11}) +[2026-07-26 20:41:50,588][starVLA.training.train_starvla][INFO] - Step 893, Loss: {'train/loss': 0.544194221496582, 'train/grad_norm_pre_clip': 6.1409149169921875, 'timing/data': 0.00017040595412254333, 'timing/model': 0.4620055630803108, 'learning_rate/action_model': 9.264046915503425e-05, 'learning_rate/action_query_proj': 9.264046915503425e-05, 'learning_rate/base': 2.316011728875856e-05, 'epoch': 0.11}) +[2026-07-26 20:41:56,159][starVLA.training.train_starvla][INFO] - Step 894, Loss: {'train/loss': 0.4712592661380768, 'train/grad_norm_pre_clip': 5.524084568023682, 'timing/data': 0.00017832079902291298, 'timing/model': 0.459826837759465, 'learning_rate/action_model': 9.262441313248281e-05, 'learning_rate/action_query_proj': 9.262441313248281e-05, 'learning_rate/base': 2.3156103283120703e-05, 'epoch': 0.11}) +[2026-07-26 20:42:01,713][starVLA.training.train_starvla][INFO] - Step 895, Loss: {'train/loss': 0.5629922151565552, 'train/grad_norm_pre_clip': 5.198367118835449, 'timing/data': 0.0001722988672554493, 'timing/model': 0.4616267532110214, 'learning_rate/action_model': 9.260834107205643e-05, 'learning_rate/action_query_proj': 9.260834107205643e-05, 'learning_rate/base': 2.3152085268014107e-05, 'epoch': 0.11}) +[2026-07-26 20:42:07,244][starVLA.training.train_starvla][INFO] - Step 896, Loss: {'train/loss': 0.7306855916976929, 'train/grad_norm_pre_clip': 6.02354621887207, 'timing/data': 0.0001743878237903118, 'timing/model': 0.45927731366828084, 'learning_rate/action_model': 9.259225298010011e-05, 'learning_rate/action_query_proj': 9.259225298010011e-05, 'learning_rate/base': 2.3148063245025027e-05, 'epoch': 0.11}) +[2026-07-26 20:42:12,845][starVLA.training.train_starvla][INFO] - Step 897, Loss: {'train/loss': 0.34994441270828247, 'train/grad_norm_pre_clip': 3.4303133487701416, 'timing/data': 0.00017078407108783722, 'timing/model': 0.4616154208779335, 'learning_rate/action_model': 9.257614886296516e-05, 'learning_rate/action_query_proj': 9.257614886296516e-05, 'learning_rate/base': 2.314403721574129e-05, 'epoch': 0.11}) +[2026-07-26 20:42:18,680][starVLA.training.train_starvla][INFO] - Step 898, Loss: {'train/loss': 0.487689346075058, 'train/grad_norm_pre_clip': 2.7422003746032715, 'timing/data': 0.000173225998878479, 'timing/model': 0.45893096597865224, 'learning_rate/action_model': 9.256002872700924e-05, 'learning_rate/action_query_proj': 9.256002872700924e-05, 'learning_rate/base': 2.314000718175231e-05, 'epoch': 0.11}) +[2026-07-26 20:42:24,255][starVLA.training.train_starvla][INFO] - Step 899, Loss: {'train/loss': 0.43105053901672363, 'train/grad_norm_pre_clip': 3.6318416595458984, 'timing/data': 0.00018050381913781166, 'timing/model': 0.4604911492206156, 'learning_rate/action_model': 9.254389257859633e-05, 'learning_rate/action_query_proj': 9.254389257859633e-05, 'learning_rate/base': 2.3135973144649083e-05, 'epoch': 0.11}) +[2026-07-26 20:42:29,807][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 900 +[2026-07-26 20:42:29,810][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 900 +[2026-07-26 20:42:29,811][starVLA.training.train_starvla][INFO] - Step 900, Loss: {'train/loss': 0.5498493909835815, 'train/grad_norm_pre_clip': 4.190267562866211, 'timing/data': 0.000174002256244421, 'timing/model': 0.4622472757473588, 'learning_rate/action_model': 9.252774042409673e-05, 'learning_rate/action_query_proj': 9.252774042409673e-05, 'learning_rate/base': 2.313193510602418e-05, 'epoch': 0.11}) +[2026-07-26 20:42:35,360][starVLA.training.train_starvla][INFO] - Step 901, Loss: {'train/loss': 0.5382741093635559, 'train/grad_norm_pre_clip': 4.105898857116699, 'timing/data': 0.00018319394439458847, 'timing/model': 0.4608131991699338, 'learning_rate/action_model': 9.251157226988703e-05, 'learning_rate/action_query_proj': 9.251157226988703e-05, 'learning_rate/base': 2.3127893067471758e-05, 'epoch': 0.11}) +[2026-07-26 20:42:40,912][starVLA.training.train_starvla][INFO] - Step 902, Loss: {'train/loss': 0.5419793128967285, 'train/grad_norm_pre_clip': 4.481895923614502, 'timing/data': 0.00017975596711039543, 'timing/model': 0.4598260521888733, 'learning_rate/action_model': 9.249538812235019e-05, 'learning_rate/action_query_proj': 9.249538812235019e-05, 'learning_rate/base': 2.3123847030587548e-05, 'epoch': 0.11}) +[2026-07-26 20:42:46,738][starVLA.training.train_starvla][INFO] - Step 903, Loss: {'train/loss': 0.6307281851768494, 'train/grad_norm_pre_clip': 3.3621270656585693, 'timing/data': 0.0001768842339515686, 'timing/model': 0.46455391496419907, 'learning_rate/action_model': 9.247918798787544e-05, 'learning_rate/action_query_proj': 9.247918798787544e-05, 'learning_rate/base': 2.311979699696886e-05, 'epoch': 0.11}) +[2026-07-26 20:42:52,283][starVLA.training.train_starvla][INFO] - Step 904, Loss: {'train/loss': 0.4774629771709442, 'train/grad_norm_pre_clip': 3.651470899581909, 'timing/data': 0.00017337827011942863, 'timing/model': 0.45993016799911857, 'learning_rate/action_model': 9.246297187285834e-05, 'learning_rate/action_query_proj': 9.246297187285834e-05, 'learning_rate/base': 2.3115742968214584e-05, 'epoch': 0.11}) +[2026-07-26 20:42:57,818][starVLA.training.train_starvla][INFO] - Step 905, Loss: {'train/loss': 0.5877823233604431, 'train/grad_norm_pre_clip': 5.820025444030762, 'timing/data': 0.00017984723672270775, 'timing/model': 0.46226473106071353, 'learning_rate/action_model': 9.244673978370076e-05, 'learning_rate/action_query_proj': 9.244673978370076e-05, 'learning_rate/base': 2.311168494592519e-05, 'epoch': 0.11}) +[2026-07-26 20:43:03,345][starVLA.training.train_starvla][INFO] - Step 906, Loss: {'train/loss': 0.5082453489303589, 'train/grad_norm_pre_clip': 6.278688430786133, 'timing/data': 0.00016957195475697517, 'timing/model': 0.45910715917125344, 'learning_rate/action_model': 9.243049172681085e-05, 'learning_rate/action_query_proj': 9.243049172681085e-05, 'learning_rate/base': 2.3107622931702712e-05, 'epoch': 0.11}) +[2026-07-26 20:43:08,873][starVLA.training.train_starvla][INFO] - Step 907, Loss: {'train/loss': 0.6795920729637146, 'train/grad_norm_pre_clip': 5.914398670196533, 'timing/data': 0.00017816806212067604, 'timing/model': 0.4620126453228295, 'learning_rate/action_model': 9.241422770860311e-05, 'learning_rate/action_query_proj': 9.241422770860311e-05, 'learning_rate/base': 2.3103556927150778e-05, 'epoch': 0.11}) +[2026-07-26 20:43:14,416][starVLA.training.train_starvla][INFO] - Step 908, Loss: {'train/loss': 0.5904136896133423, 'train/grad_norm_pre_clip': 4.803004264831543, 'timing/data': 0.0001724078319966793, 'timing/model': 0.4592902585864067, 'learning_rate/action_model': 9.239794773549832e-05, 'learning_rate/action_query_proj': 9.239794773549832e-05, 'learning_rate/base': 2.309948693387458e-05, 'epoch': 0.11}) +[2026-07-26 20:43:19,931][starVLA.training.train_starvla][INFO] - Step 909, Loss: {'train/loss': 0.5228726267814636, 'train/grad_norm_pre_clip': 3.7697432041168213, 'timing/data': 0.00017653265967965126, 'timing/model': 0.46127952728420496, 'learning_rate/action_model': 9.238165181392354e-05, 'learning_rate/action_query_proj': 9.238165181392354e-05, 'learning_rate/base': 2.3095412953480884e-05, 'epoch': 0.11}) +[2026-07-26 20:43:25,447][starVLA.training.train_starvla][INFO] - Step 910, Loss: {'train/loss': 0.4487658143043518, 'train/grad_norm_pre_clip': 6.007579326629639, 'timing/data': 0.0001878347247838974, 'timing/model': 0.4626515661366284, 'learning_rate/action_model': 9.236533995031212e-05, 'learning_rate/action_query_proj': 9.236533995031212e-05, 'learning_rate/base': 2.309133498757803e-05, 'epoch': 0.11}) +[2026-07-26 20:43:30,954][starVLA.training.train_starvla][INFO] - Step 911, Loss: {'train/loss': 0.7061105370521545, 'train/grad_norm_pre_clip': 5.450089931488037, 'timing/data': 0.00017494987696409225, 'timing/model': 0.4608527678065002, 'learning_rate/action_model': 9.234901215110378e-05, 'learning_rate/action_query_proj': 9.234901215110378e-05, 'learning_rate/base': 2.3087253037775945e-05, 'epoch': 0.11}) +[2026-07-26 20:43:36,469][starVLA.training.train_starvla][INFO] - Step 912, Loss: {'train/loss': 0.520139753818512, 'train/grad_norm_pre_clip': 5.64915657043457, 'timing/data': 0.0001796451397240162, 'timing/model': 0.4626201931387186, 'learning_rate/action_model': 9.233266842274442e-05, 'learning_rate/action_query_proj': 9.233266842274442e-05, 'learning_rate/base': 2.3083167105686106e-05, 'epoch': 0.11}) +[2026-07-26 20:43:41,979][starVLA.training.train_starvla][INFO] - Step 913, Loss: {'train/loss': 0.5157415270805359, 'train/grad_norm_pre_clip': 3.562298536300659, 'timing/data': 0.00017952779307961464, 'timing/model': 0.46077472111210227, 'learning_rate/action_model': 9.231630877168634e-05, 'learning_rate/action_query_proj': 9.231630877168634e-05, 'learning_rate/base': 2.3079077192921584e-05, 'epoch': 0.11}) +[2026-07-26 20:43:47,539][starVLA.training.train_starvla][INFO] - Step 914, Loss: {'train/loss': 0.523005485534668, 'train/grad_norm_pre_clip': 4.368631362915039, 'timing/data': 0.00017631100490689278, 'timing/model': 0.4626655699685216, 'learning_rate/action_model': 9.229993320438804e-05, 'learning_rate/action_query_proj': 9.229993320438804e-05, 'learning_rate/base': 2.307498330109701e-05, 'epoch': 0.11}) +[2026-07-26 20:43:53,074][starVLA.training.train_starvla][INFO] - Step 915, Loss: {'train/loss': 0.45636558532714844, 'train/grad_norm_pre_clip': 4.368470191955566, 'timing/data': 0.0001717391423881054, 'timing/model': 0.45971589628607035, 'learning_rate/action_model': 9.228354172731432e-05, 'learning_rate/action_query_proj': 9.228354172731432e-05, 'learning_rate/base': 2.307088543182858e-05, 'epoch': 0.11}) +[2026-07-26 20:43:58,584][starVLA.training.train_starvla][INFO] - Step 916, Loss: {'train/loss': 0.42018577456474304, 'train/grad_norm_pre_clip': 2.364183187484741, 'timing/data': 0.00018220208585262299, 'timing/model': 0.4588003889657557, 'learning_rate/action_model': 9.226713434693632e-05, 'learning_rate/action_query_proj': 9.226713434693632e-05, 'learning_rate/base': 2.306678358673408e-05, 'epoch': 0.11}) +[2026-07-26 20:44:04,097][starVLA.training.train_starvla][INFO] - Step 917, Loss: {'train/loss': 0.49863988161087036, 'train/grad_norm_pre_clip': 3.329310417175293, 'timing/data': 0.000177804846316576, 'timing/model': 0.46121414192020893, 'learning_rate/action_model': 9.225071106973137e-05, 'learning_rate/action_query_proj': 9.225071106973137e-05, 'learning_rate/base': 2.3062677767432842e-05, 'epoch': 0.11}) +[2026-07-26 20:44:09,618][starVLA.training.train_starvla][INFO] - Step 918, Loss: {'train/loss': 0.556037962436676, 'train/grad_norm_pre_clip': 5.73499059677124, 'timing/data': 0.00017460621893405914, 'timing/model': 0.4612886649556458, 'learning_rate/action_model': 9.223427190218314e-05, 'learning_rate/action_query_proj': 9.223427190218314e-05, 'learning_rate/base': 2.3058567975545785e-05, 'epoch': 0.11}) +[2026-07-26 20:44:15,143][starVLA.training.train_starvla][INFO] - Step 919, Loss: {'train/loss': 0.6651942729949951, 'train/grad_norm_pre_clip': 4.0238447189331055, 'timing/data': 0.00021419581025838852, 'timing/model': 0.46164418337866664, 'learning_rate/action_model': 9.221781685078157e-05, 'learning_rate/action_query_proj': 9.221781685078157e-05, 'learning_rate/base': 2.3054454212695392e-05, 'epoch': 0.11}) +[2026-07-26 20:44:20,655][starVLA.training.train_starvla][INFO] - Step 920, Loss: {'train/loss': 0.6392858028411865, 'train/grad_norm_pre_clip': 5.214559078216553, 'timing/data': 0.00018318509683012962, 'timing/model': 0.46173978596925735, 'learning_rate/action_model': 9.220134592202282e-05, 'learning_rate/action_query_proj': 9.220134592202282e-05, 'learning_rate/base': 2.3050336480505704e-05, 'epoch': 0.11}) +[2026-07-26 20:44:26,164][starVLA.training.train_starvla][INFO] - Step 921, Loss: {'train/loss': 0.4645228087902069, 'train/grad_norm_pre_clip': 4.424803256988525, 'timing/data': 0.00017182203009724617, 'timing/model': 0.45847064116969705, 'learning_rate/action_model': 9.218485912240935e-05, 'learning_rate/action_query_proj': 9.218485912240935e-05, 'learning_rate/base': 2.3046214780602336e-05, 'epoch': 0.11}) +[2026-07-26 20:44:31,670][starVLA.training.train_starvla][INFO] - Step 922, Loss: {'train/loss': 0.40714144706726074, 'train/grad_norm_pre_clip': 4.349334239959717, 'timing/data': 0.00017691124230623245, 'timing/model': 0.4580856249667704, 'learning_rate/action_model': 9.216835645844992e-05, 'learning_rate/action_query_proj': 9.216835645844992e-05, 'learning_rate/base': 2.304208911461248e-05, 'epoch': 0.11}) +[2026-07-26 20:44:37,181][starVLA.training.train_starvla][INFO] - Step 923, Loss: {'train/loss': 0.5585651397705078, 'train/grad_norm_pre_clip': 6.083953857421875, 'timing/data': 0.00017514917999505997, 'timing/model': 0.4575267960317433, 'learning_rate/action_model': 9.215183793665952e-05, 'learning_rate/action_query_proj': 9.215183793665952e-05, 'learning_rate/base': 2.303795948416488e-05, 'epoch': 0.11}) +[2026-07-26 20:44:42,688][starVLA.training.train_starvla][INFO] - Step 924, Loss: {'train/loss': 0.5073958039283752, 'train/grad_norm_pre_clip': 5.099244117736816, 'timing/data': 0.00017827097326517105, 'timing/model': 0.4573445268906653, 'learning_rate/action_model': 9.213530356355935e-05, 'learning_rate/action_query_proj': 9.213530356355935e-05, 'learning_rate/base': 2.3033825890889838e-05, 'epoch': 0.11}) +[2026-07-26 20:44:48,201][starVLA.training.train_starvla][INFO] - Step 925, Loss: {'train/loss': 0.45385366678237915, 'train/grad_norm_pre_clip': 2.816711902618408, 'timing/data': 0.00018256716430187225, 'timing/model': 0.4577440437860787, 'learning_rate/action_model': 9.211875334567698e-05, 'learning_rate/action_query_proj': 9.211875334567698e-05, 'learning_rate/base': 2.3029688336419245e-05, 'epoch': 0.11}) +[2026-07-26 20:44:53,719][starVLA.training.train_starvla][INFO] - Step 926, Loss: {'train/loss': 0.5354300737380981, 'train/grad_norm_pre_clip': 4.7901811599731445, 'timing/data': 0.0001657409593462944, 'timing/model': 0.45833077374845743, 'learning_rate/action_model': 9.210218728954614e-05, 'learning_rate/action_query_proj': 9.210218728954614e-05, 'learning_rate/base': 2.3025546822386536e-05, 'epoch': 0.11}) +[2026-07-26 20:44:59,433][starVLA.training.train_starvla][INFO] - Step 927, Loss: {'train/loss': 0.4925084412097931, 'train/grad_norm_pre_clip': 4.178709983825684, 'timing/data': 0.0001780749298632145, 'timing/model': 0.4590714070945978, 'learning_rate/action_model': 9.208560540170686e-05, 'learning_rate/action_query_proj': 9.208560540170686e-05, 'learning_rate/base': 2.3021401350426714e-05, 'epoch': 0.11}) +[2026-07-26 20:45:04,960][starVLA.training.train_starvla][INFO] - Step 928, Loss: {'train/loss': 0.4413403570652008, 'train/grad_norm_pre_clip': 3.467590093612671, 'timing/data': 0.00016774982213974, 'timing/model': 0.458171502687037, 'learning_rate/action_model': 9.20690076887054e-05, 'learning_rate/action_query_proj': 9.20690076887054e-05, 'learning_rate/base': 2.301725192217635e-05, 'epoch': 0.11}) +[2026-07-26 20:45:10,481][starVLA.training.train_starvla][INFO] - Step 929, Loss: {'train/loss': 0.5044002532958984, 'train/grad_norm_pre_clip': 6.353934288024902, 'timing/data': 0.0001744530163705349, 'timing/model': 0.4578272537328303, 'learning_rate/action_model': 9.205239415709426e-05, 'learning_rate/action_query_proj': 9.205239415709426e-05, 'learning_rate/base': 2.3013098539273564e-05, 'epoch': 0.11}) +[2026-07-26 20:45:16,011][starVLA.training.train_starvla][INFO] - Step 930, Loss: {'train/loss': 0.5324271321296692, 'train/grad_norm_pre_clip': 4.511107444763184, 'timing/data': 0.00017503229901194572, 'timing/model': 0.45975606702268124, 'learning_rate/action_model': 9.203576481343223e-05, 'learning_rate/action_query_proj': 9.203576481343223e-05, 'learning_rate/base': 2.3008941203358057e-05, 'epoch': 0.11}) +[2026-07-26 20:45:21,559][starVLA.training.train_starvla][INFO] - Step 931, Loss: {'train/loss': 0.5471091270446777, 'train/grad_norm_pre_clip': 6.4098005294799805, 'timing/data': 0.00024611223489046097, 'timing/model': 0.4579064273275435, 'learning_rate/action_model': 9.201911966428429e-05, 'learning_rate/action_query_proj': 9.201911966428429e-05, 'learning_rate/base': 2.3004779916071072e-05, 'epoch': 0.11}) +[2026-07-26 20:45:27,080][starVLA.training.train_starvla][INFO] - Step 932, Loss: {'train/loss': 0.5298669338226318, 'train/grad_norm_pre_clip': 4.419369697570801, 'timing/data': 0.0001825033687055111, 'timing/model': 0.4582991832867265, 'learning_rate/action_model': 9.200245871622167e-05, 'learning_rate/action_query_proj': 9.200245871622167e-05, 'learning_rate/base': 2.3000614679055417e-05, 'epoch': 0.11}) +[2026-07-26 20:45:32,615][starVLA.training.train_starvla][INFO] - Step 933, Loss: {'train/loss': 0.4981955587863922, 'train/grad_norm_pre_clip': 3.848947525024414, 'timing/data': 0.00017760507762432098, 'timing/model': 0.4570386493578553, 'learning_rate/action_model': 9.19857819758219e-05, 'learning_rate/action_query_proj': 9.19857819758219e-05, 'learning_rate/base': 2.2996445493955475e-05, 'epoch': 0.11}) +[2026-07-26 20:45:38,168][starVLA.training.train_starvla][INFO] - Step 934, Loss: {'train/loss': 0.5608641505241394, 'train/grad_norm_pre_clip': 7.442438125610352, 'timing/data': 0.00017386255785822868, 'timing/model': 0.4577646986581385, 'learning_rate/action_model': 9.196908944966863e-05, 'learning_rate/action_query_proj': 9.196908944966863e-05, 'learning_rate/base': 2.2992272362417158e-05, 'epoch': 0.11}) +[2026-07-26 20:45:43,723][starVLA.training.train_starvla][INFO] - Step 935, Loss: {'train/loss': 0.49231988191604614, 'train/grad_norm_pre_clip': 5.691797256469727, 'timing/data': 0.00018423562869429588, 'timing/model': 0.459563628770411, 'learning_rate/action_model': 9.195238114435186e-05, 'learning_rate/action_query_proj': 9.195238114435186e-05, 'learning_rate/base': 2.2988095286087964e-05, 'epoch': 0.11}) +[2026-07-26 20:45:49,263][starVLA.training.train_starvla][INFO] - Step 936, Loss: {'train/loss': 0.5922976136207581, 'train/grad_norm_pre_clip': 7.006601333618164, 'timing/data': 0.00021749408915638924, 'timing/model': 0.4584796819835901, 'learning_rate/action_model': 9.193565706646772e-05, 'learning_rate/action_query_proj': 9.193565706646772e-05, 'learning_rate/base': 2.298391426661693e-05, 'epoch': 0.11}) +[2026-07-26 20:45:54,778][starVLA.training.train_starvla][INFO] - Step 937, Loss: {'train/loss': 0.5773219466209412, 'train/grad_norm_pre_clip': 3.8980088233947754, 'timing/data': 0.00018399488180875778, 'timing/model': 0.45677787298336625, 'learning_rate/action_model': 9.191891722261861e-05, 'learning_rate/action_query_proj': 9.191891722261861e-05, 'learning_rate/base': 2.2979729305654653e-05, 'epoch': 0.11}) +[2026-07-26 20:46:00,298][starVLA.training.train_starvla][INFO] - Step 938, Loss: {'train/loss': 0.4891722500324249, 'train/grad_norm_pre_clip': 4.658197402954102, 'timing/data': 0.0001797899603843689, 'timing/model': 0.45832982705906034, 'learning_rate/action_model': 9.190216161941321e-05, 'learning_rate/action_query_proj': 9.190216161941321e-05, 'learning_rate/base': 2.2975540404853302e-05, 'epoch': 0.11}) +[2026-07-26 20:46:05,803][starVLA.training.train_starvla][INFO] - Step 939, Loss: {'train/loss': 0.4055424630641937, 'train/grad_norm_pre_clip': 4.720821380615234, 'timing/data': 0.00022540101781487465, 'timing/model': 0.45971855195239186, 'learning_rate/action_model': 9.188539026346632e-05, 'learning_rate/action_query_proj': 9.188539026346632e-05, 'learning_rate/base': 2.297134756586658e-05, 'epoch': 0.11}) +[2026-07-26 20:46:11,298][starVLA.training.train_starvla][INFO] - Step 940, Loss: {'train/loss': 0.39628225564956665, 'train/grad_norm_pre_clip': 2.965182065963745, 'timing/data': 0.000238694716244936, 'timing/model': 0.45949941873550415, 'learning_rate/action_model': 9.186860316139901e-05, 'learning_rate/action_query_proj': 9.186860316139901e-05, 'learning_rate/base': 2.2967150790349752e-05, 'epoch': 0.11}) +[2026-07-26 20:46:16,796][starVLA.training.train_starvla][INFO] - Step 941, Loss: {'train/loss': 0.5456657409667969, 'train/grad_norm_pre_clip': 3.983046054840088, 'timing/data': 0.00017717108130455017, 'timing/model': 0.4586351132020354, 'learning_rate/action_model': 9.185180031983857e-05, 'learning_rate/action_query_proj': 9.185180031983857e-05, 'learning_rate/base': 2.2962950079959643e-05, 'epoch': 0.11}) +[2026-07-26 20:46:22,297][starVLA.training.train_starvla][INFO] - Step 942, Loss: {'train/loss': 0.46712905168533325, 'train/grad_norm_pre_clip': 5.342493057250977, 'timing/data': 0.00016908207908272743, 'timing/model': 0.45844779862090945, 'learning_rate/action_model': 9.18349817454185e-05, 'learning_rate/action_query_proj': 9.18349817454185e-05, 'learning_rate/base': 2.2958745436354624e-05, 'epoch': 0.11}) +[2026-07-26 20:46:27,795][starVLA.training.train_starvla][INFO] - Step 943, Loss: {'train/loss': 0.5108351111412048, 'train/grad_norm_pre_clip': 5.347294330596924, 'timing/data': 0.00017389236018061638, 'timing/model': 0.45812332071363926, 'learning_rate/action_model': 9.181814744477851e-05, 'learning_rate/action_query_proj': 9.181814744477851e-05, 'learning_rate/base': 2.2954536861194627e-05, 'epoch': 0.11}) +[2026-07-26 20:46:33,294][starVLA.training.train_starvla][INFO] - Step 944, Loss: {'train/loss': 0.6148578524589539, 'train/grad_norm_pre_clip': 8.573315620422363, 'timing/data': 0.00021913181990385056, 'timing/model': 0.45881189219653606, 'learning_rate/action_model': 9.180129742456448e-05, 'learning_rate/action_query_proj': 9.180129742456448e-05, 'learning_rate/base': 2.295032435614112e-05, 'epoch': 0.11}) +[2026-07-26 20:46:38,796][starVLA.training.train_starvla][INFO] - Step 945, Loss: {'train/loss': 0.49850234389305115, 'train/grad_norm_pre_clip': 4.2545695304870605, 'timing/data': 0.00017940020188689232, 'timing/model': 0.45889821415767074, 'learning_rate/action_model': 9.178443169142858e-05, 'learning_rate/action_query_proj': 9.178443169142858e-05, 'learning_rate/base': 2.2946107922857144e-05, 'epoch': 0.11}) +[2026-07-26 20:46:44,302][starVLA.training.train_starvla][INFO] - Step 946, Loss: {'train/loss': 0.40682172775268555, 'train/grad_norm_pre_clip': 4.969424724578857, 'timing/data': 0.00019394978880882263, 'timing/model': 0.45883443811908364, 'learning_rate/action_model': 9.176755025202911e-05, 'learning_rate/action_query_proj': 9.176755025202911e-05, 'learning_rate/base': 2.2941887563007278e-05, 'epoch': 0.11}) +[2026-07-26 20:46:49,802][starVLA.training.train_starvla][INFO] - Step 947, Loss: {'train/loss': 0.5525752305984497, 'train/grad_norm_pre_clip': 4.232151031494141, 'timing/data': 0.0001841350458562374, 'timing/model': 0.45869582099840045, 'learning_rate/action_model': 9.175065311303058e-05, 'learning_rate/action_query_proj': 9.175065311303058e-05, 'learning_rate/base': 2.2937663278257646e-05, 'epoch': 0.11}) +[2026-07-26 20:46:55,296][starVLA.training.train_starvla][INFO] - Step 948, Loss: {'train/loss': 0.6019067168235779, 'train/grad_norm_pre_clip': 5.895852088928223, 'timing/data': 0.00017505791038274765, 'timing/model': 0.4579034158959985, 'learning_rate/action_model': 9.173374028110373e-05, 'learning_rate/action_query_proj': 9.173374028110373e-05, 'learning_rate/base': 2.2933435070275934e-05, 'epoch': 0.12}) +[2026-07-26 20:47:00,795][starVLA.training.train_starvla][INFO] - Step 949, Loss: {'train/loss': 0.5186346173286438, 'train/grad_norm_pre_clip': 2.5201170444488525, 'timing/data': 0.00017955806106328964, 'timing/model': 0.4596527609974146, 'learning_rate/action_model': 9.17168117629255e-05, 'learning_rate/action_query_proj': 9.17168117629255e-05, 'learning_rate/base': 2.2929202940731376e-05, 'epoch': 0.12}) +[2026-07-26 20:47:06,290][starVLA.training.train_starvla][INFO] - Step 950, Loss: {'train/loss': 0.4944339096546173, 'train/grad_norm_pre_clip': 3.6900360584259033, 'timing/data': 0.00017406512051820755, 'timing/model': 0.45814022282138467, 'learning_rate/action_model': 9.169986756517896e-05, 'learning_rate/action_query_proj': 9.169986756517896e-05, 'learning_rate/base': 2.292496689129474e-05, 'epoch': 0.12}) +[2026-07-26 20:47:11,787][starVLA.training.train_starvla][INFO] - Step 951, Loss: {'train/loss': 0.5465591549873352, 'train/grad_norm_pre_clip': 5.934185028076172, 'timing/data': 0.0001760059967637062, 'timing/model': 0.4575330400839448, 'learning_rate/action_model': 9.168290769455344e-05, 'learning_rate/action_query_proj': 9.168290769455344e-05, 'learning_rate/base': 2.292072692363836e-05, 'epoch': 0.12}) +[2026-07-26 20:47:17,310][starVLA.training.train_starvla][INFO] - Step 952, Loss: {'train/loss': 0.4321315288543701, 'train/grad_norm_pre_clip': 3.703519582748413, 'timing/data': 0.00017903326079249382, 'timing/model': 0.459393713157624, 'learning_rate/action_model': 9.166593215774442e-05, 'learning_rate/action_query_proj': 9.166593215774442e-05, 'learning_rate/base': 2.2916483039436106e-05, 'epoch': 0.12}) +[2026-07-26 20:47:22,806][starVLA.training.train_starvla][INFO] - Step 953, Loss: {'train/loss': 0.3993603587150574, 'train/grad_norm_pre_clip': 2.613894462585449, 'timing/data': 0.00023945607244968414, 'timing/model': 0.458495045080781, 'learning_rate/action_model': 9.164894096145357e-05, 'learning_rate/action_query_proj': 9.164894096145357e-05, 'learning_rate/base': 2.2912235240363393e-05, 'epoch': 0.12}) +[2026-07-26 20:47:28,307][starVLA.training.train_starvla][INFO] - Step 954, Loss: {'train/loss': 0.543938934803009, 'train/grad_norm_pre_clip': 5.066570281982422, 'timing/data': 0.00018055131658911705, 'timing/model': 0.45830259285867214, 'learning_rate/action_model': 9.163193411238875e-05, 'learning_rate/action_query_proj': 9.163193411238875e-05, 'learning_rate/base': 2.2907983528097187e-05, 'epoch': 0.12}) +[2026-07-26 20:47:33,806][starVLA.training.train_starvla][INFO] - Step 955, Loss: {'train/loss': 0.43470901250839233, 'train/grad_norm_pre_clip': 3.7123706340789795, 'timing/data': 0.00017733685672283173, 'timing/model': 0.4582223570905626, 'learning_rate/action_model': 9.161491161726398e-05, 'learning_rate/action_query_proj': 9.161491161726398e-05, 'learning_rate/base': 2.2903727904315996e-05, 'epoch': 0.12}) +[2026-07-26 20:47:39,302][starVLA.training.train_starvla][INFO] - Step 956, Loss: {'train/loss': 0.3390771150588989, 'train/grad_norm_pre_clip': 2.7697865962982178, 'timing/data': 0.0002167639322578907, 'timing/model': 0.4588798610493541, 'learning_rate/action_model': 9.15978734827995e-05, 'learning_rate/action_query_proj': 9.15978734827995e-05, 'learning_rate/base': 2.2899468370699875e-05, 'epoch': 0.12}) +[2026-07-26 20:47:44,843][starVLA.training.train_starvla][INFO] - Step 957, Loss: {'train/loss': 0.5162477493286133, 'train/grad_norm_pre_clip': 3.6035070419311523, 'timing/data': 0.0002222931943833828, 'timing/model': 0.4617881537415087, 'learning_rate/action_model': 9.158081971572165e-05, 'learning_rate/action_query_proj': 9.158081971572165e-05, 'learning_rate/base': 2.2895204928930413e-05, 'epoch': 0.12}) +[2026-07-26 20:47:50,527][starVLA.training.train_starvla][INFO] - Step 958, Loss: {'train/loss': 0.4498482644557953, 'train/grad_norm_pre_clip': 2.5909998416900635, 'timing/data': 0.00019086478278040886, 'timing/model': 0.4604438990354538, 'learning_rate/action_model': 9.156375032276305e-05, 'learning_rate/action_query_proj': 9.156375032276305e-05, 'learning_rate/base': 2.289093758069076e-05, 'epoch': 0.12}) +[2026-07-26 20:47:56,049][starVLA.training.train_starvla][INFO] - Step 959, Loss: {'train/loss': 0.571722149848938, 'train/grad_norm_pre_clip': 4.1365647315979, 'timing/data': 0.0002239053137600422, 'timing/model': 0.46018620813265443, 'learning_rate/action_model': 9.154666531066236e-05, 'learning_rate/action_query_proj': 9.154666531066236e-05, 'learning_rate/base': 2.288666632766559e-05, 'epoch': 0.12}) +[2026-07-26 20:48:01,628][starVLA.training.train_starvla][INFO] - Step 960, Loss: {'train/loss': 0.5042621493339539, 'train/grad_norm_pre_clip': 5.224361896514893, 'timing/data': 0.00017443113029003143, 'timing/model': 0.46152058197185397, 'learning_rate/action_model': 9.152956468616451e-05, 'learning_rate/action_query_proj': 9.152956468616451e-05, 'learning_rate/base': 2.2882391171541128e-05, 'epoch': 0.12}) +[2026-07-26 20:48:07,171][starVLA.training.train_starvla][INFO] - Step 961, Loss: {'train/loss': 0.304869145154953, 'train/grad_norm_pre_clip': 2.9327712059020996, 'timing/data': 0.00017064204439520836, 'timing/model': 0.46072864485904574, 'learning_rate/action_model': 9.151244845602056e-05, 'learning_rate/action_query_proj': 9.151244845602056e-05, 'learning_rate/base': 2.287811211400514e-05, 'epoch': 0.12}) +[2026-07-26 20:48:12,712][starVLA.training.train_starvla][INFO] - Step 962, Loss: {'train/loss': 0.46885961294174194, 'train/grad_norm_pre_clip': 6.053112983703613, 'timing/data': 0.00017116032540798187, 'timing/model': 0.461944165173918, 'learning_rate/action_model': 9.149531662698772e-05, 'learning_rate/action_query_proj': 9.149531662698772e-05, 'learning_rate/base': 2.287382915674693e-05, 'epoch': 0.12}) +[2026-07-26 20:48:18,270][starVLA.training.train_starvla][INFO] - Step 963, Loss: {'train/loss': 0.5175115466117859, 'train/grad_norm_pre_clip': 3.2247369289398193, 'timing/data': 0.00017951475456357002, 'timing/model': 0.471448821015656, 'learning_rate/action_model': 9.147816920582935e-05, 'learning_rate/action_query_proj': 9.147816920582935e-05, 'learning_rate/base': 2.286954230145734e-05, 'epoch': 0.12}) +[2026-07-26 20:48:23,837][starVLA.training.train_starvla][INFO] - Step 964, Loss: {'train/loss': 0.39205455780029297, 'train/grad_norm_pre_clip': 2.360955238342285, 'timing/data': 0.00019331509247422218, 'timing/model': 0.46919432701542974, 'learning_rate/action_model': 9.1461006199315e-05, 'learning_rate/action_query_proj': 9.1461006199315e-05, 'learning_rate/base': 2.286525154982875e-05, 'epoch': 0.12}) +[2026-07-26 20:48:29,398][starVLA.training.train_starvla][INFO] - Step 965, Loss: {'train/loss': 0.3530517518520355, 'train/grad_norm_pre_clip': 3.217477560043335, 'timing/data': 0.00017250794917345047, 'timing/model': 0.4703271840699017, 'learning_rate/action_model': 9.144382761422033e-05, 'learning_rate/action_query_proj': 9.144382761422033e-05, 'learning_rate/base': 2.2860956903555083e-05, 'epoch': 0.12}) +[2026-07-26 20:48:34,960][starVLA.training.train_starvla][INFO] - Step 966, Loss: {'train/loss': 0.559654951095581, 'train/grad_norm_pre_clip': 5.255471229553223, 'timing/data': 0.0001712278462946415, 'timing/model': 0.47134890081360936, 'learning_rate/action_model': 9.14266334573272e-05, 'learning_rate/action_query_proj': 9.14266334573272e-05, 'learning_rate/base': 2.28566583643318e-05, 'epoch': 0.12}) +[2026-07-26 20:48:40,523][starVLA.training.train_starvla][INFO] - Step 967, Loss: {'train/loss': 0.5138033032417297, 'train/grad_norm_pre_clip': 3.734365224838257, 'timing/data': 0.00017072539776563644, 'timing/model': 0.4801419391296804, 'learning_rate/action_model': 9.140942373542359e-05, 'learning_rate/action_query_proj': 9.140942373542359e-05, 'learning_rate/base': 2.2852355933855896e-05, 'epoch': 0.12}) +[2026-07-26 20:48:46,076][starVLA.training.train_starvla][INFO] - Step 968, Loss: {'train/loss': 0.45537808537483215, 'train/grad_norm_pre_clip': 4.986509323120117, 'timing/data': 0.00016868207603693008, 'timing/model': 0.46300025889649987, 'learning_rate/action_model': 9.139219845530359e-05, 'learning_rate/action_query_proj': 9.139219845530359e-05, 'learning_rate/base': 2.2848049613825898e-05, 'epoch': 0.12}) +[2026-07-26 20:48:51,614][starVLA.training.train_starvla][INFO] - Step 969, Loss: {'train/loss': 0.5246267318725586, 'train/grad_norm_pre_clip': 2.8577518463134766, 'timing/data': 0.0001713777892291546, 'timing/model': 0.461701893247664, 'learning_rate/action_model': 9.13749576237675e-05, 'learning_rate/action_query_proj': 9.13749576237675e-05, 'learning_rate/base': 2.2843739405941874e-05, 'epoch': 0.12}) +[2026-07-26 20:48:57,145][starVLA.training.train_starvla][INFO] - Step 970, Loss: {'train/loss': 0.3273918926715851, 'train/grad_norm_pre_clip': 2.796955108642578, 'timing/data': 0.00016992073506116867, 'timing/model': 0.4603725289925933, 'learning_rate/action_model': 9.135770124762172e-05, 'learning_rate/action_query_proj': 9.135770124762172e-05, 'learning_rate/base': 2.283942531190543e-05, 'epoch': 0.12}) +[2026-07-26 20:49:02,707][starVLA.training.train_starvla][INFO] - Step 971, Loss: {'train/loss': 0.530630350112915, 'train/grad_norm_pre_clip': 4.40991735458374, 'timing/data': 0.0001741759479045868, 'timing/model': 0.4799416237510741, 'learning_rate/action_model': 9.134042933367879e-05, 'learning_rate/action_query_proj': 9.134042933367879e-05, 'learning_rate/base': 2.2835107333419697e-05, 'epoch': 0.12}) +[2026-07-26 20:49:08,302][starVLA.training.train_starvla][INFO] - Step 972, Loss: {'train/loss': 0.4120641350746155, 'train/grad_norm_pre_clip': 3.232024908065796, 'timing/data': 0.0001753070391714573, 'timing/model': 0.47200470184907317, 'learning_rate/action_model': 9.13231418887574e-05, 'learning_rate/action_query_proj': 9.13231418887574e-05, 'learning_rate/base': 2.283078547218935e-05, 'epoch': 0.12}) +[2026-07-26 20:49:13,909][starVLA.training.train_starvla][INFO] - Step 973, Loss: {'train/loss': 0.44605332612991333, 'train/grad_norm_pre_clip': 4.048820495605469, 'timing/data': 0.00017286231741309166, 'timing/model': 0.47475437400862575, 'learning_rate/action_model': 9.130583891968233e-05, 'learning_rate/action_query_proj': 9.130583891968233e-05, 'learning_rate/base': 2.2826459729920583e-05, 'epoch': 0.12}) +[2026-07-26 20:49:19,467][starVLA.training.train_starvla][INFO] - Step 974, Loss: {'train/loss': 0.5798979997634888, 'train/grad_norm_pre_clip': 6.349754333496094, 'timing/data': 0.00018166471272706985, 'timing/model': 0.472082176245749, 'learning_rate/action_model': 9.128852043328456e-05, 'learning_rate/action_query_proj': 9.128852043328456e-05, 'learning_rate/base': 2.282213010832114e-05, 'epoch': 0.12}) +[2026-07-26 20:49:25,014][starVLA.training.train_starvla][INFO] - Step 975, Loss: {'train/loss': 0.5130625367164612, 'train/grad_norm_pre_clip': 5.396218299865723, 'timing/data': 0.00017284881323575974, 'timing/model': 0.47305091889575124, 'learning_rate/action_model': 9.127118643640112e-05, 'learning_rate/action_query_proj': 9.127118643640112e-05, 'learning_rate/base': 2.281779660910028e-05, 'epoch': 0.12}) +[2026-07-26 20:49:30,561][starVLA.training.train_starvla][INFO] - Step 976, Loss: {'train/loss': 0.5485328435897827, 'train/grad_norm_pre_clip': 5.403508186340332, 'timing/data': 0.0001694350503385067, 'timing/model': 0.4718429083004594, 'learning_rate/action_model': 9.125383693587523e-05, 'learning_rate/action_query_proj': 9.125383693587523e-05, 'learning_rate/base': 2.281345923396881e-05, 'epoch': 0.12}) +[2026-07-26 20:49:36,110][starVLA.training.train_starvla][INFO] - Step 977, Loss: {'train/loss': 0.37616050243377686, 'train/grad_norm_pre_clip': 4.725780010223389, 'timing/data': 0.0001701395958662033, 'timing/model': 0.46997863287106156, 'learning_rate/action_model': 9.123647193855617e-05, 'learning_rate/action_query_proj': 9.123647193855617e-05, 'learning_rate/base': 2.280911798463904e-05, 'epoch': 0.12}) +[2026-07-26 20:49:41,651][starVLA.training.train_starvla][INFO] - Step 978, Loss: {'train/loss': 0.3981171250343323, 'train/grad_norm_pre_clip': 4.37409782409668, 'timing/data': 0.00017316872254014015, 'timing/model': 0.47242087963968515, 'learning_rate/action_model': 9.121909145129937e-05, 'learning_rate/action_query_proj': 9.121909145129937e-05, 'learning_rate/base': 2.2804772862824842e-05, 'epoch': 0.12}) +[2026-07-26 20:49:47,182][starVLA.training.train_starvla][INFO] - Step 979, Loss: {'train/loss': 0.37988805770874023, 'train/grad_norm_pre_clip': 2.647718667984009, 'timing/data': 0.0001810169778764248, 'timing/model': 0.4713741932064295, 'learning_rate/action_model': 9.120169548096637e-05, 'learning_rate/action_query_proj': 9.120169548096637e-05, 'learning_rate/base': 2.280042387024159e-05, 'epoch': 0.12}) +[2026-07-26 20:49:52,730][starVLA.training.train_starvla][INFO] - Step 980, Loss: {'train/loss': 0.49979135394096375, 'train/grad_norm_pre_clip': 3.965094804763794, 'timing/data': 0.00017025461420416832, 'timing/model': 0.4705104250460863, 'learning_rate/action_model': 9.118428403442483e-05, 'learning_rate/action_query_proj': 9.118428403442483e-05, 'learning_rate/base': 2.2796071008606208e-05, 'epoch': 0.12}) +[2026-07-26 20:49:58,276][starVLA.training.train_starvla][INFO] - Step 981, Loss: {'train/loss': 0.4588574469089508, 'train/grad_norm_pre_clip': 3.9895777702331543, 'timing/data': 0.00017177872359752655, 'timing/model': 0.47768186731263995, 'learning_rate/action_model': 9.116685711854853e-05, 'learning_rate/action_query_proj': 9.116685711854853e-05, 'learning_rate/base': 2.2791714279637132e-05, 'epoch': 0.12}) +[2026-07-26 20:50:03,885][starVLA.training.train_starvla][INFO] - Step 982, Loss: {'train/loss': 0.368479460477829, 'train/grad_norm_pre_clip': 3.7578840255737305, 'timing/data': 0.00017181877046823502, 'timing/model': 0.47959145111963153, 'learning_rate/action_model': 9.11494147402173e-05, 'learning_rate/action_query_proj': 9.11494147402173e-05, 'learning_rate/base': 2.2787353685054325e-05, 'epoch': 0.12}) +[2026-07-26 20:50:09,429][starVLA.training.train_starvla][INFO] - Step 983, Loss: {'train/loss': 0.5002106428146362, 'train/grad_norm_pre_clip': 6.712262153625488, 'timing/data': 0.00017569493502378464, 'timing/model': 0.46781833190470934, 'learning_rate/action_model': 9.113195690631716e-05, 'learning_rate/action_query_proj': 9.113195690631716e-05, 'learning_rate/base': 2.278298922657929e-05, 'epoch': 0.12}) +[2026-07-26 20:50:14,981][starVLA.training.train_starvla][INFO] - Step 984, Loss: {'train/loss': 0.5970518589019775, 'train/grad_norm_pre_clip': 4.6708550453186035, 'timing/data': 0.0001701810397207737, 'timing/model': 0.47954214410856366, 'learning_rate/action_model': 9.111448362374014e-05, 'learning_rate/action_query_proj': 9.111448362374014e-05, 'learning_rate/base': 2.2778620905935036e-05, 'epoch': 0.12}) +[2026-07-26 20:50:20,527][starVLA.training.train_starvla][INFO] - Step 985, Loss: {'train/loss': 0.4196442663669586, 'train/grad_norm_pre_clip': 3.4477860927581787, 'timing/data': 0.00017062900587916374, 'timing/model': 0.4705329821445048, 'learning_rate/action_model': 9.109699489938446e-05, 'learning_rate/action_query_proj': 9.109699489938446e-05, 'learning_rate/base': 2.2774248724846114e-05, 'epoch': 0.12}) +[2026-07-26 20:50:26,076][starVLA.training.train_starvla][INFO] - Step 986, Loss: {'train/loss': 0.2637862265110016, 'train/grad_norm_pre_clip': 3.2200465202331543, 'timing/data': 0.00017064809799194336, 'timing/model': 0.47293052123859525, 'learning_rate/action_model': 9.107949074015435e-05, 'learning_rate/action_query_proj': 9.107949074015435e-05, 'learning_rate/base': 2.2769872685038588e-05, 'epoch': 0.12}) +[2026-07-26 20:50:31,626][starVLA.training.train_starvla][INFO] - Step 987, Loss: {'train/loss': 0.47787830233573914, 'train/grad_norm_pre_clip': 3.1824235916137695, 'timing/data': 0.0001803431659936905, 'timing/model': 0.4712151591666043, 'learning_rate/action_model': 9.106197115296022e-05, 'learning_rate/action_query_proj': 9.106197115296022e-05, 'learning_rate/base': 2.2765492788240054e-05, 'epoch': 0.12}) +[2026-07-26 20:50:37,289][starVLA.training.train_starvla][INFO] - Step 988, Loss: {'train/loss': 0.37932735681533813, 'train/grad_norm_pre_clip': 4.717034816741943, 'timing/data': 0.00018343236297369003, 'timing/model': 0.5871686767786741, 'learning_rate/action_model': 9.104443614471848e-05, 'learning_rate/action_query_proj': 9.104443614471848e-05, 'learning_rate/base': 2.276110903617962e-05, 'epoch': 0.12}) +[2026-07-26 20:50:42,832][starVLA.training.train_starvla][INFO] - Step 989, Loss: {'train/loss': 0.5375162959098816, 'train/grad_norm_pre_clip': 5.587132930755615, 'timing/data': 0.00017556734383106232, 'timing/model': 0.4718516729772091, 'learning_rate/action_model': 9.102688572235171e-05, 'learning_rate/action_query_proj': 9.102688572235171e-05, 'learning_rate/base': 2.2756721430587927e-05, 'epoch': 0.12}) +[2026-07-26 20:50:48,624][starVLA.training.train_starvla][INFO] - Step 990, Loss: {'train/loss': 0.4998518228530884, 'train/grad_norm_pre_clip': 4.538309097290039, 'timing/data': 0.00017681997269392014, 'timing/model': 0.47107506077736616, 'learning_rate/action_model': 9.100931989278851e-05, 'learning_rate/action_query_proj': 9.100931989278851e-05, 'learning_rate/base': 2.2752329973197127e-05, 'epoch': 0.12}) +[2026-07-26 20:50:54,164][starVLA.training.train_starvla][INFO] - Step 991, Loss: {'train/loss': 0.3468872904777527, 'train/grad_norm_pre_clip': 4.226667881011963, 'timing/data': 0.00017432309687137604, 'timing/model': 0.4706702260300517, 'learning_rate/action_model': 9.099173866296361e-05, 'learning_rate/action_query_proj': 9.099173866296361e-05, 'learning_rate/base': 2.2747934665740902e-05, 'epoch': 0.12}) +[2026-07-26 20:50:59,711][starVLA.training.train_starvla][INFO] - Step 992, Loss: {'train/loss': 0.3719695210456848, 'train/grad_norm_pre_clip': 3.3090546131134033, 'timing/data': 0.0001775398850440979, 'timing/model': 0.470810831990093, 'learning_rate/action_model': 9.097414203981781e-05, 'learning_rate/action_query_proj': 9.097414203981781e-05, 'learning_rate/base': 2.2743535509954454e-05, 'epoch': 0.12}) +[2026-07-26 20:51:05,268][starVLA.training.train_starvla][INFO] - Step 993, Loss: {'train/loss': 0.4419623017311096, 'train/grad_norm_pre_clip': 4.334705829620361, 'timing/data': 0.00016957195475697517, 'timing/model': 0.47011725837364793, 'learning_rate/action_model': 9.095653003029793e-05, 'learning_rate/action_query_proj': 9.095653003029793e-05, 'learning_rate/base': 2.2739132507574483e-05, 'epoch': 0.12}) +[2026-07-26 20:51:10,818][starVLA.training.train_starvla][INFO] - Step 994, Loss: {'train/loss': 0.4574885666370392, 'train/grad_norm_pre_clip': 3.1440038681030273, 'timing/data': 0.00018155528232455254, 'timing/model': 0.47032641619443893, 'learning_rate/action_model': 9.093890264135698e-05, 'learning_rate/action_query_proj': 9.093890264135698e-05, 'learning_rate/base': 2.2734725660339245e-05, 'epoch': 0.12}) +[2026-07-26 20:51:16,394][starVLA.training.train_starvla][INFO] - Step 995, Loss: {'train/loss': 0.38954809308052063, 'train/grad_norm_pre_clip': 3.533310651779175, 'timing/data': 0.00017310073599219322, 'timing/model': 0.4702940760180354, 'learning_rate/action_model': 9.092125987995393e-05, 'learning_rate/action_query_proj': 9.092125987995393e-05, 'learning_rate/base': 2.2730314969988483e-05, 'epoch': 0.12}) +[2026-07-26 20:51:21,975][starVLA.training.train_starvla][INFO] - Step 996, Loss: {'train/loss': 0.3917168974876404, 'train/grad_norm_pre_clip': 4.247981548309326, 'timing/data': 0.000175457913428545, 'timing/model': 0.4794837939552963, 'learning_rate/action_model': 9.090360175305387e-05, 'learning_rate/action_query_proj': 9.090360175305387e-05, 'learning_rate/base': 2.272590043826347e-05, 'epoch': 0.12}) +[2026-07-26 20:51:27,536][starVLA.training.train_starvla][INFO] - Step 997, Loss: {'train/loss': 0.5353222489356995, 'train/grad_norm_pre_clip': 4.555139541625977, 'timing/data': 0.00017553288489580154, 'timing/model': 0.4709666739217937, 'learning_rate/action_model': 9.088592826762795e-05, 'learning_rate/action_query_proj': 9.088592826762795e-05, 'learning_rate/base': 2.2721482066906987e-05, 'epoch': 0.12}) +[2026-07-26 20:51:33,163][starVLA.training.train_starvla][INFO] - Step 998, Loss: {'train/loss': 0.5304310917854309, 'train/grad_norm_pre_clip': 3.55599045753479, 'timing/data': 0.0001771119423210621, 'timing/model': 0.47099005803465843, 'learning_rate/action_model': 9.08682394306534e-05, 'learning_rate/action_query_proj': 9.08682394306534e-05, 'learning_rate/base': 2.271705985766335e-05, 'epoch': 0.12}) +[2026-07-26 20:51:38,715][starVLA.training.train_starvla][INFO] - Step 999, Loss: {'train/loss': 0.46506792306900024, 'train/grad_norm_pre_clip': 2.672260284423828, 'timing/data': 0.00017176801338791847, 'timing/model': 0.4693371243774891, 'learning_rate/action_model': 9.085053524911345e-05, 'learning_rate/action_query_proj': 9.085053524911345e-05, 'learning_rate/base': 2.2712633812278362e-05, 'epoch': 0.12}) +[2026-07-26 20:51:44,270][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 1000 +[2026-07-26 20:51:44,271][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 1000 +[2026-07-26 20:51:44,272][starVLA.training.train_starvla][INFO] - Step 1000, Loss: {'train/loss': 0.40895789861679077, 'train/grad_norm_pre_clip': 3.4570705890655518, 'timing/data': 0.00019129784777760506, 'timing/model': 0.470786124933511, 'learning_rate/action_model': 9.083281572999748e-05, 'learning_rate/action_query_proj': 9.083281572999748e-05, 'learning_rate/base': 2.270820393249937e-05, 'epoch': 0.12}) +[2026-07-26 20:51:44,275][accelerate.accelerator][INFO] - Saving current state to /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_1000_state +[2026-07-26 20:51:44,275][accelerate.accelerator][INFO] - Saving DeepSpeed Model and Optimizer +[2026-07-26 20:52:30,632][accelerate.accelerator][INFO] - DeepSpeed Model and Optimizer saved to output dir /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_1000_state/pytorch_model +[2026-07-26 20:52:30,632][accelerate.checkpointing][INFO] - Sampler state for dataloader 0 saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_1000_state/sampler.bin +[2026-07-26 20:52:30,638][accelerate.checkpointing][INFO] - Random states saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_1000_state/random_states_0.pkl +[2026-07-26 20:53:00,238][starVLA.training.rl_games.checkpoint_sync][INFO] - HF checkpoint sync disabled; skipping upload for step 1000 +[2026-07-26 20:53:00,239][starVLA.training.train_starvla][INFO] - 📊 Saving accessed configuration... +[2026-07-26 20:53:00,253][starVLA.training.train_starvla][INFO] - ✅ Configuration files saved +[2026-07-26 20:53:05,932][starVLA.training.train_starvla][INFO] - Step 1001, Loss: {'train/loss': 0.488756000995636, 'train/grad_norm_pre_clip': 3.5373709201812744, 'timing/data': 0.00017972523346543312, 'timing/model': 0.46441610995680094, 'learning_rate/action_model': 9.081508088030085e-05, 'learning_rate/action_query_proj': 9.081508088030085e-05, 'learning_rate/base': 2.270377022007521e-05, 'epoch': 0.12}) +[2026-07-26 20:53:11,841][starVLA.training.train_starvla][INFO] - Step 1002, Loss: {'train/loss': 0.4909230172634125, 'train/grad_norm_pre_clip': 3.4632437229156494, 'timing/data': 0.000180030707269907, 'timing/model': 0.46330360090360045, 'learning_rate/action_model': 9.079733070702499e-05, 'learning_rate/action_query_proj': 9.079733070702499e-05, 'learning_rate/base': 2.2699332676756247e-05, 'epoch': 0.12}) +[2026-07-26 20:53:17,741][starVLA.training.train_starvla][INFO] - Step 1003, Loss: {'train/loss': 0.4040672481060028, 'train/grad_norm_pre_clip': 3.2264180183410645, 'timing/data': 0.00017231982201337814, 'timing/model': 0.46864913078024983, 'learning_rate/action_model': 9.07795652171774e-05, 'learning_rate/action_query_proj': 9.07795652171774e-05, 'learning_rate/base': 2.269489130429435e-05, 'epoch': 0.12}) +[2026-07-26 20:53:23,402][starVLA.training.train_starvla][INFO] - Step 1004, Loss: {'train/loss': 0.5085732340812683, 'train/grad_norm_pre_clip': 3.1311190128326416, 'timing/data': 0.00017226533964276314, 'timing/model': 0.46410873299464583, 'learning_rate/action_model': 9.076178441777162e-05, 'learning_rate/action_query_proj': 9.076178441777162e-05, 'learning_rate/base': 2.2690446104442904e-05, 'epoch': 0.12}) +[2026-07-26 20:53:29,285][starVLA.training.train_starvla][INFO] - Step 1005, Loss: {'train/loss': 0.5135313868522644, 'train/grad_norm_pre_clip': 4.88615083694458, 'timing/data': 0.00017880089581012726, 'timing/model': 0.46690540201961994, 'learning_rate/action_model': 9.074398831582722e-05, 'learning_rate/action_query_proj': 9.074398831582722e-05, 'learning_rate/base': 2.2685997078956804e-05, 'epoch': 0.12}) +[2026-07-26 20:53:34,939][starVLA.training.train_starvla][INFO] - Step 1006, Loss: {'train/loss': 0.6095311045646667, 'train/grad_norm_pre_clip': 4.885706901550293, 'timing/data': 0.0001779487356543541, 'timing/model': 0.4661588449962437, 'learning_rate/action_model': 9.072617691836982e-05, 'learning_rate/action_query_proj': 9.072617691836982e-05, 'learning_rate/base': 2.2681544229592454e-05, 'epoch': 0.12}) +[2026-07-26 20:53:40,482][starVLA.training.train_starvla][INFO] - Step 1007, Loss: {'train/loss': 0.4636194705963135, 'train/grad_norm_pre_clip': 4.9401068687438965, 'timing/data': 0.00017545372247695923, 'timing/model': 0.4613525001332164, 'learning_rate/action_model': 9.070835023243107e-05, 'learning_rate/action_query_proj': 9.070835023243107e-05, 'learning_rate/base': 2.2677087558107767e-05, 'epoch': 0.12}) +[2026-07-26 20:53:46,109][starVLA.training.train_starvla][INFO] - Step 1008, Loss: {'train/loss': 0.42096567153930664, 'train/grad_norm_pre_clip': 3.0162880420684814, 'timing/data': 0.00017427513375878334, 'timing/model': 0.46423283498734236, 'learning_rate/action_model': 9.069050826504866e-05, 'learning_rate/action_query_proj': 9.069050826504866e-05, 'learning_rate/base': 2.2672627066262165e-05, 'epoch': 0.12}) +[2026-07-26 20:53:51,731][starVLA.training.train_starvla][INFO] - Step 1009, Loss: {'train/loss': 0.48544514179229736, 'train/grad_norm_pre_clip': 3.7099244594573975, 'timing/data': 0.00017108721658587456, 'timing/model': 0.4642639961093664, 'learning_rate/action_model': 9.067265102326634e-05, 'learning_rate/action_query_proj': 9.067265102326634e-05, 'learning_rate/base': 2.2668162755816586e-05, 'epoch': 0.12}) +[2026-07-26 20:53:57,368][starVLA.training.train_starvla][INFO] - Step 1010, Loss: {'train/loss': 0.47929060459136963, 'train/grad_norm_pre_clip': 5.3832855224609375, 'timing/data': 0.00017838692292571068, 'timing/model': 0.4658835711888969, 'learning_rate/action_model': 9.065477851413386e-05, 'learning_rate/action_query_proj': 9.065477851413386e-05, 'learning_rate/base': 2.2663694628533465e-05, 'epoch': 0.12}) +[2026-07-26 20:54:02,965][starVLA.training.train_starvla][INFO] - Step 1011, Loss: {'train/loss': 0.44410136342048645, 'train/grad_norm_pre_clip': 4.823751449584961, 'timing/data': 0.00017222575843334198, 'timing/model': 0.4677149052731693, 'learning_rate/action_model': 9.063689074470699e-05, 'learning_rate/action_query_proj': 9.063689074470699e-05, 'learning_rate/base': 2.2659222686176747e-05, 'epoch': 0.12}) +[2026-07-26 20:54:08,575][starVLA.training.train_starvla][INFO] - Step 1012, Loss: {'train/loss': 0.460639625787735, 'train/grad_norm_pre_clip': 4.3374104499816895, 'timing/data': 0.000173850916326046, 'timing/model': 0.46753155114129186, 'learning_rate/action_model': 9.061898772204755e-05, 'learning_rate/action_query_proj': 9.061898772204755e-05, 'learning_rate/base': 2.2654746930511887e-05, 'epoch': 0.12}) +[2026-07-26 20:54:14,185][starVLA.training.train_starvla][INFO] - Step 1013, Loss: {'train/loss': 0.5277777910232544, 'train/grad_norm_pre_clip': 5.7104010581970215, 'timing/data': 0.00017417874187231064, 'timing/model': 0.4662878876551986, 'learning_rate/action_model': 9.060106945322335e-05, 'learning_rate/action_query_proj': 9.060106945322335e-05, 'learning_rate/base': 2.2650267363305837e-05, 'epoch': 0.12}) +[2026-07-26 20:54:19,823][starVLA.training.train_starvla][INFO] - Step 1014, Loss: {'train/loss': 0.4619920551776886, 'train/grad_norm_pre_clip': 4.702343940734863, 'timing/data': 0.00017189094796776772, 'timing/model': 0.4670352260582149, 'learning_rate/action_model': 9.058313594530826e-05, 'learning_rate/action_query_proj': 9.058313594530826e-05, 'learning_rate/base': 2.2645783986327064e-05, 'epoch': 0.12}) +[2026-07-26 20:54:25,697][starVLA.training.train_starvla][INFO] - Step 1015, Loss: {'train/loss': 0.5752971768379211, 'train/grad_norm_pre_clip': 7.793940544128418, 'timing/data': 0.00017523020505905151, 'timing/model': 0.46725813718512654, 'learning_rate/action_model': 9.056518720538213e-05, 'learning_rate/action_query_proj': 9.056518720538213e-05, 'learning_rate/base': 2.2641296801345534e-05, 'epoch': 0.12}) +[2026-07-26 20:54:31,313][starVLA.training.train_starvla][INFO] - Step 1016, Loss: {'train/loss': 0.5080682039260864, 'train/grad_norm_pre_clip': 5.705451011657715, 'timing/data': 0.0001742057502269745, 'timing/model': 0.4631739128381014, 'learning_rate/action_model': 9.054722324053085e-05, 'learning_rate/action_query_proj': 9.054722324053085e-05, 'learning_rate/base': 2.2636805810132713e-05, 'epoch': 0.12}) +[2026-07-26 20:54:36,824][starVLA.training.train_starvla][INFO] - Step 1017, Loss: {'train/loss': 0.47475525736808777, 'train/grad_norm_pre_clip': 8.80971622467041, 'timing/data': 0.0001749759539961815, 'timing/model': 0.4592528180219233, 'learning_rate/action_model': 9.05292440578463e-05, 'learning_rate/action_query_proj': 9.05292440578463e-05, 'learning_rate/base': 2.2632311014461577e-05, 'epoch': 0.12}) +[2026-07-26 20:54:42,446][starVLA.training.train_starvla][INFO] - Step 1018, Loss: {'train/loss': 0.515541136264801, 'train/grad_norm_pre_clip': 7.465575695037842, 'timing/data': 0.0001714089885354042, 'timing/model': 0.464607872068882, 'learning_rate/action_model': 9.05112496644264e-05, 'learning_rate/action_query_proj': 9.05112496644264e-05, 'learning_rate/base': 2.26278124161066e-05, 'epoch': 0.12}) +[2026-07-26 20:54:48,056][starVLA.training.train_starvla][INFO] - Step 1019, Loss: {'train/loss': 0.5802116990089417, 'train/grad_norm_pre_clip': 5.5771026611328125, 'timing/data': 0.00017280317842960358, 'timing/model': 0.4665095452219248, 'learning_rate/action_model': 9.049324006737501e-05, 'learning_rate/action_query_proj': 9.049324006737501e-05, 'learning_rate/base': 2.2623310016843753e-05, 'epoch': 0.12}) +[2026-07-26 20:54:53,675][starVLA.training.train_starvla][INFO] - Step 1020, Loss: {'train/loss': 0.524791955947876, 'train/grad_norm_pre_clip': 3.7087581157684326, 'timing/data': 0.00017137639224529266, 'timing/model': 0.46082021901383996, 'learning_rate/action_model': 9.047521527380208e-05, 'learning_rate/action_query_proj': 9.047521527380208e-05, 'learning_rate/base': 2.261880381845052e-05, 'epoch': 0.12}) +[2026-07-26 20:54:59,282][starVLA.training.train_starvla][INFO] - Step 1021, Loss: {'train/loss': 0.5414503216743469, 'train/grad_norm_pre_clip': 5.107274055480957, 'timing/data': 0.0001699398271739483, 'timing/model': 0.4647022862918675, 'learning_rate/action_model': 9.045717529082349e-05, 'learning_rate/action_query_proj': 9.045717529082349e-05, 'learning_rate/base': 2.2614293822705872e-05, 'epoch': 0.12}) +[2026-07-26 20:55:04,884][starVLA.training.train_starvla][INFO] - Step 1022, Loss: {'train/loss': 0.630888819694519, 'train/grad_norm_pre_clip': 4.874398231506348, 'timing/data': 0.00017127813771367073, 'timing/model': 0.462185800075531, 'learning_rate/action_model': 9.043912012556112e-05, 'learning_rate/action_query_proj': 9.043912012556112e-05, 'learning_rate/base': 2.260978003139028e-05, 'epoch': 0.12}) +[2026-07-26 20:55:10,475][starVLA.training.train_starvla][INFO] - Step 1023, Loss: {'train/loss': 0.4333226680755615, 'train/grad_norm_pre_clip': 4.732274532318115, 'timing/data': 0.0001748017966747284, 'timing/model': 0.4594634808599949, 'learning_rate/action_model': 9.042104978514288e-05, 'learning_rate/action_query_proj': 9.042104978514288e-05, 'learning_rate/base': 2.260526244628572e-05, 'epoch': 0.12}) +[2026-07-26 20:55:16,320][starVLA.training.train_starvla][INFO] - Step 1024, Loss: {'train/loss': 0.47603145241737366, 'train/grad_norm_pre_clip': 3.712791919708252, 'timing/data': 0.00016742292791604996, 'timing/model': 0.46067929174751043, 'learning_rate/action_model': 9.040296427670267e-05, 'learning_rate/action_query_proj': 9.040296427670267e-05, 'learning_rate/base': 2.2600741069175667e-05, 'epoch': 0.12}) +[2026-07-26 20:55:21,922][starVLA.training.train_starvla][INFO] - Step 1025, Loss: {'train/loss': 0.3814149498939514, 'train/grad_norm_pre_clip': 5.0108537673950195, 'timing/data': 0.00017082178965210915, 'timing/model': 0.46710105519741774, 'learning_rate/action_model': 9.038486360738036e-05, 'learning_rate/action_query_proj': 9.038486360738036e-05, 'learning_rate/base': 2.259621590184509e-05, 'epoch': 0.12}) +[2026-07-26 20:55:27,539][starVLA.training.train_starvla][INFO] - Step 1026, Loss: {'train/loss': 0.3844173550605774, 'train/grad_norm_pre_clip': 3.637012481689453, 'timing/data': 0.00017692195251584053, 'timing/model': 0.4666951182298362, 'learning_rate/action_model': 9.036674778432178e-05, 'learning_rate/action_query_proj': 9.036674778432178e-05, 'learning_rate/base': 2.2591686946080444e-05, 'epoch': 0.12}) +[2026-07-26 20:55:33,184][starVLA.training.train_starvla][INFO] - Step 1027, Loss: {'train/loss': 0.5231484770774841, 'train/grad_norm_pre_clip': 4.362663745880127, 'timing/data': 0.00017220200970768929, 'timing/model': 0.4643559707328677, 'learning_rate/action_model': 9.034861681467878e-05, 'learning_rate/action_query_proj': 9.034861681467878e-05, 'learning_rate/base': 2.2587154203669696e-05, 'epoch': 0.12}) +[2026-07-26 20:55:38,816][starVLA.training.train_starvla][INFO] - Step 1028, Loss: {'train/loss': 0.5572648644447327, 'train/grad_norm_pre_clip': 5.535053253173828, 'timing/data': 0.00017886096611618996, 'timing/model': 0.4648927841335535, 'learning_rate/action_model': 9.03304707056092e-05, 'learning_rate/action_query_proj': 9.03304707056092e-05, 'learning_rate/base': 2.25826176764023e-05, 'epoch': 0.12}) +[2026-07-26 20:55:44,633][starVLA.training.train_starvla][INFO] - Step 1029, Loss: {'train/loss': 0.4618392884731293, 'train/grad_norm_pre_clip': 4.068799018859863, 'timing/data': 0.00017343880608677864, 'timing/model': 0.4586052061058581, 'learning_rate/action_model': 9.031230946427681e-05, 'learning_rate/action_query_proj': 9.031230946427681e-05, 'learning_rate/base': 2.2578077366069202e-05, 'epoch': 0.12}) +[2026-07-26 20:55:50,276][starVLA.training.train_starvla][INFO] - Step 1030, Loss: {'train/loss': 0.47387468814849854, 'train/grad_norm_pre_clip': 3.8175289630889893, 'timing/data': 0.00017630914226174355, 'timing/model': 0.46603356394916773, 'learning_rate/action_model': 9.029413309785141e-05, 'learning_rate/action_query_proj': 9.029413309785141e-05, 'learning_rate/base': 2.2573533274462853e-05, 'epoch': 0.12}) +[2026-07-26 20:55:55,817][starVLA.training.train_starvla][INFO] - Step 1031, Loss: {'train/loss': 0.47401392459869385, 'train/grad_norm_pre_clip': 3.5233423709869385, 'timing/data': 0.00017725815996527672, 'timing/model': 0.4578152112662792, 'learning_rate/action_model': 9.027594161350873e-05, 'learning_rate/action_query_proj': 9.027594161350873e-05, 'learning_rate/base': 2.2568985403377184e-05, 'epoch': 0.13}) +[2026-07-26 20:56:01,540][starVLA.training.train_starvla][INFO] - Step 1032, Loss: {'train/loss': 0.4045071601867676, 'train/grad_norm_pre_clip': 4.8859663009643555, 'timing/data': 0.00018113013356924057, 'timing/model': 0.4694063030183315, 'learning_rate/action_model': 9.025773501843045e-05, 'learning_rate/action_query_proj': 9.025773501843045e-05, 'learning_rate/base': 2.2564433754607613e-05, 'epoch': 0.13}) +[2026-07-26 20:56:07,198][starVLA.training.train_starvla][INFO] - Step 1033, Loss: {'train/loss': 0.44094085693359375, 'train/grad_norm_pre_clip': 3.9778528213500977, 'timing/data': 0.00016720406711101532, 'timing/model': 0.4621919598430395, 'learning_rate/action_model': 9.023951331980428e-05, 'learning_rate/action_query_proj': 9.023951331980428e-05, 'learning_rate/base': 2.255987832995107e-05, 'epoch': 0.13}) +[2026-07-26 20:56:12,861][starVLA.training.train_starvla][INFO] - Step 1034, Loss: {'train/loss': 0.5669739246368408, 'train/grad_norm_pre_clip': 5.920747756958008, 'timing/data': 0.00019648298621177673, 'timing/model': 0.46356558706611395, 'learning_rate/action_model': 9.022127652482386e-05, 'learning_rate/action_query_proj': 9.022127652482386e-05, 'learning_rate/base': 2.2555319131205965e-05, 'epoch': 0.13}) +[2026-07-26 20:56:18,519][starVLA.training.train_starvla][INFO] - Step 1035, Loss: {'train/loss': 0.4889775216579437, 'train/grad_norm_pre_clip': 6.890129566192627, 'timing/data': 0.00017583277076482773, 'timing/model': 0.4659306318499148, 'learning_rate/action_model': 9.020302464068876e-05, 'learning_rate/action_query_proj': 9.020302464068876e-05, 'learning_rate/base': 2.255075616017219e-05, 'epoch': 0.13}) +[2026-07-26 20:56:24,181][starVLA.training.train_starvla][INFO] - Step 1036, Loss: {'train/loss': 0.47424864768981934, 'train/grad_norm_pre_clip': 3.8840417861938477, 'timing/data': 0.00018250476568937302, 'timing/model': 0.46513146813958883, 'learning_rate/action_model': 9.018475767460456e-05, 'learning_rate/action_query_proj': 9.018475767460456e-05, 'learning_rate/base': 2.254618941865114e-05, 'epoch': 0.13}) +[2026-07-26 20:56:29,823][starVLA.training.train_starvla][INFO] - Step 1037, Loss: {'train/loss': 0.5434539318084717, 'train/grad_norm_pre_clip': 3.0958385467529297, 'timing/data': 0.00017696479335427284, 'timing/model': 0.4654021952301264, 'learning_rate/action_model': 9.016647563378276e-05, 'learning_rate/action_query_proj': 9.016647563378276e-05, 'learning_rate/base': 2.254161890844569e-05, 'epoch': 0.13}) +[2026-07-26 20:56:35,451][starVLA.training.train_starvla][INFO] - Step 1038, Loss: {'train/loss': 0.4122800827026367, 'train/grad_norm_pre_clip': 3.4537107944488525, 'timing/data': 0.0002241954207420349, 'timing/model': 0.4644678169861436, 'learning_rate/action_model': 9.014817852544081e-05, 'learning_rate/action_query_proj': 9.014817852544081e-05, 'learning_rate/base': 2.2537044631360203e-05, 'epoch': 0.13}) +[2026-07-26 20:56:41,070][starVLA.training.train_starvla][INFO] - Step 1039, Loss: {'train/loss': 0.45357444882392883, 'train/grad_norm_pre_clip': 2.912907838821411, 'timing/data': 0.00018674694001674652, 'timing/model': 0.4601561492308974, 'learning_rate/action_model': 9.012986635680214e-05, 'learning_rate/action_query_proj': 9.012986635680214e-05, 'learning_rate/base': 2.2532466589200535e-05, 'epoch': 0.13}) +[2026-07-26 20:56:46,710][starVLA.training.train_starvla][INFO] - Step 1040, Loss: {'train/loss': 0.4291202127933502, 'train/grad_norm_pre_clip': 3.137260913848877, 'timing/data': 0.00017712311819195747, 'timing/model': 0.46223909594118595, 'learning_rate/action_model': 9.01115391350961e-05, 'learning_rate/action_query_proj': 9.01115391350961e-05, 'learning_rate/base': 2.2527884783774024e-05, 'epoch': 0.13}) +[2026-07-26 20:56:52,324][starVLA.training.train_starvla][INFO] - Step 1041, Loss: {'train/loss': 0.37832289934158325, 'train/grad_norm_pre_clip': 3.4175045490264893, 'timing/data': 0.00018124468624591827, 'timing/model': 0.4663727041333914, 'learning_rate/action_model': 9.009319686755797e-05, 'learning_rate/action_query_proj': 9.009319686755797e-05, 'learning_rate/base': 2.2523299216889494e-05, 'epoch': 0.13}) +[2026-07-26 20:56:57,957][starVLA.training.train_starvla][INFO] - Step 1042, Loss: {'train/loss': 0.361141562461853, 'train/grad_norm_pre_clip': 3.3680002689361572, 'timing/data': 0.0001827809028327465, 'timing/model': 0.46608429169282317, 'learning_rate/action_model': 9.007483956142901e-05, 'learning_rate/action_query_proj': 9.007483956142901e-05, 'learning_rate/base': 2.2518709890357252e-05, 'epoch': 0.13}) +[2026-07-26 20:57:03,590][starVLA.training.train_starvla][INFO] - Step 1043, Loss: {'train/loss': 0.35142719745635986, 'train/grad_norm_pre_clip': 3.509747266769409, 'timing/data': 0.00018602004274725914, 'timing/model': 0.46564785204827785, 'learning_rate/action_model': 9.005646722395635e-05, 'learning_rate/action_query_proj': 9.005646722395635e-05, 'learning_rate/base': 2.2514116805989087e-05, 'epoch': 0.13}) +[2026-07-26 20:57:09,217][starVLA.training.train_starvla][INFO] - Step 1044, Loss: {'train/loss': 0.45096442103385925, 'train/grad_norm_pre_clip': 2.778752088546753, 'timing/data': 0.00023412099108099937, 'timing/model': 0.46454997919499874, 'learning_rate/action_model': 9.003807986239315e-05, 'learning_rate/action_query_proj': 9.003807986239315e-05, 'learning_rate/base': 2.250951996559829e-05, 'epoch': 0.13}) +[2026-07-26 20:57:14,867][starVLA.training.train_starvla][INFO] - Step 1045, Loss: {'train/loss': 0.43884149193763733, 'train/grad_norm_pre_clip': 2.8904078006744385, 'timing/data': 0.00016907695680856705, 'timing/model': 0.4644811940379441, 'learning_rate/action_model': 9.001967748399842e-05, 'learning_rate/action_query_proj': 9.001967748399842e-05, 'learning_rate/base': 2.2504919370999605e-05, 'epoch': 0.13}) +[2026-07-26 20:57:20,504][starVLA.training.train_starvla][INFO] - Step 1046, Loss: {'train/loss': 0.5222021341323853, 'train/grad_norm_pre_clip': 3.8182337284088135, 'timing/data': 0.00017436780035495758, 'timing/model': 0.4665738861076534, 'learning_rate/action_model': 9.000126009603714e-05, 'learning_rate/action_query_proj': 9.000126009603714e-05, 'learning_rate/base': 2.2500315024009284e-05, 'epoch': 0.13}) +[2026-07-26 20:57:26,150][starVLA.training.train_starvla][INFO] - Step 1047, Loss: {'train/loss': 0.5937075018882751, 'train/grad_norm_pre_clip': 3.264378309249878, 'timing/data': 0.00017988774925470352, 'timing/model': 0.46806681994348764, 'learning_rate/action_model': 8.99828277057802e-05, 'learning_rate/action_query_proj': 8.99828277057802e-05, 'learning_rate/base': 2.249570692644505e-05, 'epoch': 0.13}) +[2026-07-26 20:57:31,775][starVLA.training.train_starvla][INFO] - Step 1048, Loss: {'train/loss': 0.5857070684432983, 'train/grad_norm_pre_clip': 3.823429822921753, 'timing/data': 0.00017570797353982925, 'timing/model': 0.4665234121493995, 'learning_rate/action_model': 8.99643803205044e-05, 'learning_rate/action_query_proj': 8.99643803205044e-05, 'learning_rate/base': 2.24910950801261e-05, 'epoch': 0.13}) +[2026-07-26 20:57:37,408][starVLA.training.train_starvla][INFO] - Step 1049, Loss: {'train/loss': 0.4942645728588104, 'train/grad_norm_pre_clip': 4.996049880981445, 'timing/data': 0.0001819198951125145, 'timing/model': 0.4644191488623619, 'learning_rate/action_model': 8.994591794749251e-05, 'learning_rate/action_query_proj': 8.994591794749251e-05, 'learning_rate/base': 2.2486479486873127e-05, 'epoch': 0.13}) +[2026-07-26 20:57:43,025][starVLA.training.train_starvla][INFO] - Step 1050, Loss: {'train/loss': 0.4579086899757385, 'train/grad_norm_pre_clip': 3.5592761039733887, 'timing/data': 0.00018502771854400635, 'timing/model': 0.46640247805044055, 'learning_rate/action_model': 8.992744059403314e-05, 'learning_rate/action_query_proj': 8.992744059403314e-05, 'learning_rate/base': 2.2481860148508284e-05, 'epoch': 0.13}) +[2026-07-26 20:57:48,652][starVLA.training.train_starvla][INFO] - Step 1051, Loss: {'train/loss': 0.4579237699508667, 'train/grad_norm_pre_clip': 4.297646999359131, 'timing/data': 0.00018505007028579712, 'timing/model': 0.46447813091799617, 'learning_rate/action_model': 8.990894826742089e-05, 'learning_rate/action_query_proj': 8.990894826742089e-05, 'learning_rate/base': 2.2477237066855223e-05, 'epoch': 0.13}) +[2026-07-26 20:57:54,265][starVLA.training.train_starvla][INFO] - Step 1052, Loss: {'train/loss': 0.43325120210647583, 'train/grad_norm_pre_clip': 2.903346061706543, 'timing/data': 0.00017195474356412888, 'timing/model': 0.4666625768877566, 'learning_rate/action_model': 8.989044097495624e-05, 'learning_rate/action_query_proj': 8.989044097495624e-05, 'learning_rate/base': 2.247261024373906e-05, 'epoch': 0.13}) +[2026-07-26 20:57:59,829][starVLA.training.train_starvla][INFO] - Step 1053, Loss: {'train/loss': 0.4826051592826843, 'train/grad_norm_pre_clip': 4.010021686553955, 'timing/data': 0.00017838040366768837, 'timing/model': 0.4632002799771726, 'learning_rate/action_model': 8.987191872394553e-05, 'learning_rate/action_query_proj': 8.987191872394553e-05, 'learning_rate/base': 2.2467979680986383e-05, 'epoch': 0.13}) +[2026-07-26 20:58:05,517][starVLA.training.train_starvla][INFO] - Step 1054, Loss: {'train/loss': 0.561731219291687, 'train/grad_norm_pre_clip': 4.55634880065918, 'timing/data': 0.00017181877046823502, 'timing/model': 0.4672027579508722, 'learning_rate/action_model': 8.98533815217011e-05, 'learning_rate/action_query_proj': 8.98533815217011e-05, 'learning_rate/base': 2.2463345380425274e-05, 'epoch': 0.13}) +[2026-07-26 20:58:11,116][starVLA.training.train_starvla][INFO] - Step 1055, Loss: {'train/loss': 0.5257011651992798, 'train/grad_norm_pre_clip': 4.173479080200195, 'timing/data': 0.00016964273527264595, 'timing/model': 0.4677319540642202, 'learning_rate/action_model': 8.983482937554113e-05, 'learning_rate/action_query_proj': 8.983482937554113e-05, 'learning_rate/base': 2.245870734388528e-05, 'epoch': 0.13}) +[2026-07-26 20:58:16,724][starVLA.training.train_starvla][INFO] - Step 1056, Loss: {'train/loss': 0.5068184733390808, 'train/grad_norm_pre_clip': 3.689711332321167, 'timing/data': 0.00018785195425152779, 'timing/model': 0.4643585989251733, 'learning_rate/action_model': 8.98162622927897e-05, 'learning_rate/action_query_proj': 8.98162622927897e-05, 'learning_rate/base': 2.2454065573197424e-05, 'epoch': 0.13}) +[2026-07-26 20:58:22,324][starVLA.training.train_starvla][INFO] - Step 1057, Loss: {'train/loss': 0.397384911775589, 'train/grad_norm_pre_clip': 3.3162410259246826, 'timing/data': 0.00017970800399780273, 'timing/model': 0.4601298379711807, 'learning_rate/action_model': 8.979768028077681e-05, 'learning_rate/action_query_proj': 8.979768028077681e-05, 'learning_rate/base': 2.2449420070194203e-05, 'epoch': 0.13}) +[2026-07-26 20:58:27,938][starVLA.training.train_starvla][INFO] - Step 1058, Loss: {'train/loss': 0.5117279887199402, 'train/grad_norm_pre_clip': 4.059201240539551, 'timing/data': 0.00017203297466039658, 'timing/model': 0.46682043792679906, 'learning_rate/action_model': 8.977908334683836e-05, 'learning_rate/action_query_proj': 8.977908334683836e-05, 'learning_rate/base': 2.244477083670959e-05, 'epoch': 0.13}) +[2026-07-26 20:58:33,564][starVLA.training.train_starvla][INFO] - Step 1059, Loss: {'train/loss': 0.46816691756248474, 'train/grad_norm_pre_clip': 3.3365488052368164, 'timing/data': 0.00017215078696608543, 'timing/model': 0.4654009835794568, 'learning_rate/action_model': 8.97604714983161e-05, 'learning_rate/action_query_proj': 8.97604714983161e-05, 'learning_rate/base': 2.2440117874579027e-05, 'epoch': 0.13}) +[2026-07-26 20:58:39,172][starVLA.training.train_starvla][INFO] - Step 1060, Loss: {'train/loss': 0.5450736880302429, 'train/grad_norm_pre_clip': 4.550548076629639, 'timing/data': 0.00017081107944250107, 'timing/model': 0.463929858058691, 'learning_rate/action_model': 8.974184474255772e-05, 'learning_rate/action_query_proj': 8.974184474255772e-05, 'learning_rate/base': 2.243546118563943e-05, 'epoch': 0.13}) +[2026-07-26 20:58:44,777][starVLA.training.train_starvla][INFO] - Step 1061, Loss: {'train/loss': 0.4493308365345001, 'train/grad_norm_pre_clip': 2.2568018436431885, 'timing/data': 0.00017497921362519264, 'timing/model': 0.457133247051388, 'learning_rate/action_model': 8.972320308691672e-05, 'learning_rate/action_query_proj': 8.972320308691672e-05, 'learning_rate/base': 2.243080077172918e-05, 'epoch': 0.13}) +[2026-07-26 20:58:50,389][starVLA.training.train_starvla][INFO] - Step 1062, Loss: {'train/loss': 0.4919554889202118, 'train/grad_norm_pre_clip': 3.04424786567688, 'timing/data': 0.0001855962909758091, 'timing/model': 0.4666130328550935, 'learning_rate/action_model': 8.970454653875258e-05, 'learning_rate/action_query_proj': 8.970454653875258e-05, 'learning_rate/base': 2.2426136634688144e-05, 'epoch': 0.13}) +[2026-07-26 20:58:56,004][starVLA.training.train_starvla][INFO] - Step 1063, Loss: {'train/loss': 0.4339662790298462, 'train/grad_norm_pre_clip': 3.268599510192871, 'timing/data': 0.00017017917707562447, 'timing/model': 0.46658139396458864, 'learning_rate/action_model': 8.96858751054306e-05, 'learning_rate/action_query_proj': 8.96858751054306e-05, 'learning_rate/base': 2.242146877635765e-05, 'epoch': 0.13}) +[2026-07-26 20:59:01,662][starVLA.training.train_starvla][INFO] - Step 1064, Loss: {'train/loss': 0.5096251964569092, 'train/grad_norm_pre_clip': 5.187160968780518, 'timing/data': 0.00018653785809874535, 'timing/model': 0.49076959025114775, 'learning_rate/action_model': 8.966718879432194e-05, 'learning_rate/action_query_proj': 8.966718879432194e-05, 'learning_rate/base': 2.2416797198580485e-05, 'epoch': 0.13}) +[2026-07-26 20:59:07,258][starVLA.training.train_starvla][INFO] - Step 1065, Loss: {'train/loss': 0.4428107738494873, 'train/grad_norm_pre_clip': 4.507356643676758, 'timing/data': 0.000185295008122921, 'timing/model': 0.48026691284030676, 'learning_rate/action_model': 8.964848761280368e-05, 'learning_rate/action_query_proj': 8.964848761280368e-05, 'learning_rate/base': 2.241212190320092e-05, 'epoch': 0.13}) +[2026-07-26 20:59:12,884][starVLA.training.train_starvla][INFO] - Step 1066, Loss: {'train/loss': 0.5570050477981567, 'train/grad_norm_pre_clip': 3.652398109436035, 'timing/data': 0.00017642462626099586, 'timing/model': 0.48176907608285546, 'learning_rate/action_model': 8.962977156825875e-05, 'learning_rate/action_query_proj': 8.962977156825875e-05, 'learning_rate/base': 2.2407442892064688e-05, 'epoch': 0.13}) +[2026-07-26 20:59:18,511][starVLA.training.train_starvla][INFO] - Step 1067, Loss: {'train/loss': 0.4252835512161255, 'train/grad_norm_pre_clip': 6.292324542999268, 'timing/data': 0.00017785700038075447, 'timing/model': 0.4637059783563018, 'learning_rate/action_model': 8.961104066807596e-05, 'learning_rate/action_query_proj': 8.961104066807596e-05, 'learning_rate/base': 2.240276016701899e-05, 'epoch': 0.13}) +[2026-07-26 20:59:24,104][starVLA.training.train_starvla][INFO] - Step 1068, Loss: {'train/loss': 0.5473389029502869, 'train/grad_norm_pre_clip': 4.2613115310668945, 'timing/data': 0.0001683398149907589, 'timing/model': 0.46781404595822096, 'learning_rate/action_model': 8.959229491964995e-05, 'learning_rate/action_query_proj': 8.959229491964995e-05, 'learning_rate/base': 2.2398073729912486e-05, 'epoch': 0.13}) +[2026-07-26 20:59:29,702][starVLA.training.train_starvla][INFO] - Step 1069, Loss: {'train/loss': 0.44460320472717285, 'train/grad_norm_pre_clip': 6.035994529724121, 'timing/data': 0.00018194504082202911, 'timing/model': 0.46444353088736534, 'learning_rate/action_model': 8.957353433038124e-05, 'learning_rate/action_query_proj': 8.957353433038124e-05, 'learning_rate/base': 2.239338358259531e-05, 'epoch': 0.13}) +[2026-07-26 20:59:35,320][starVLA.training.train_starvla][INFO] - Step 1070, Loss: {'train/loss': 0.2929668426513672, 'train/grad_norm_pre_clip': 2.4675865173339844, 'timing/data': 0.00017964188009500504, 'timing/model': 0.46593901375308633, 'learning_rate/action_model': 8.955475890767623e-05, 'learning_rate/action_query_proj': 8.955475890767623e-05, 'learning_rate/base': 2.238868972691906e-05, 'epoch': 0.13}) +[2026-07-26 20:59:40,977][starVLA.training.train_starvla][INFO] - Step 1071, Loss: {'train/loss': 0.3621455132961273, 'train/grad_norm_pre_clip': 5.380553245544434, 'timing/data': 0.0001864512450993061, 'timing/model': 0.4862206387333572, 'learning_rate/action_model': 8.953596865894715e-05, 'learning_rate/action_query_proj': 8.953596865894715e-05, 'learning_rate/base': 2.2383992164736788e-05, 'epoch': 0.13}) +[2026-07-26 20:59:46,629][starVLA.training.train_starvla][INFO] - Step 1072, Loss: {'train/loss': 0.4757770597934723, 'train/grad_norm_pre_clip': 3.9678070545196533, 'timing/data': 0.00018148915842175484, 'timing/model': 0.48275970993563533, 'learning_rate/action_model': 8.951716359161212e-05, 'learning_rate/action_query_proj': 8.951716359161212e-05, 'learning_rate/base': 2.237929089790303e-05, 'epoch': 0.13}) +[2026-07-26 20:59:52,279][starVLA.training.train_starvla][INFO] - Step 1073, Loss: {'train/loss': 0.4546986520290375, 'train/grad_norm_pre_clip': 5.399389266967773, 'timing/data': 0.0001871609129011631, 'timing/model': 0.4854255737736821, 'learning_rate/action_model': 8.949834371309506e-05, 'learning_rate/action_query_proj': 8.949834371309506e-05, 'learning_rate/base': 2.2374585928273764e-05, 'epoch': 0.13}) +[2026-07-26 20:59:57,919][starVLA.training.train_starvla][INFO] - Step 1074, Loss: {'train/loss': 0.4823768734931946, 'train/grad_norm_pre_clip': 4.64829158782959, 'timing/data': 0.00017020897939801216, 'timing/model': 0.485441030934453, 'learning_rate/action_model': 8.947950903082575e-05, 'learning_rate/action_query_proj': 8.947950903082575e-05, 'learning_rate/base': 2.2369877257706438e-05, 'epoch': 0.13}) +[2026-07-26 21:00:03,566][starVLA.training.train_starvla][INFO] - Step 1075, Loss: {'train/loss': 0.4854695796966553, 'train/grad_norm_pre_clip': 4.153299331665039, 'timing/data': 0.0001835031434893608, 'timing/model': 0.4836520217359066, 'learning_rate/action_model': 8.946065955223984e-05, 'learning_rate/action_query_proj': 8.946065955223984e-05, 'learning_rate/base': 2.236516488805996e-05, 'epoch': 0.13}) +[2026-07-26 21:00:09,210][starVLA.training.train_starvla][INFO] - Step 1076, Loss: {'train/loss': 0.49727925658226013, 'train/grad_norm_pre_clip': 3.9707913398742676, 'timing/data': 0.00017065415158867836, 'timing/model': 0.48371589183807373, 'learning_rate/action_model': 8.94417952847788e-05, 'learning_rate/action_query_proj': 8.94417952847788e-05, 'learning_rate/base': 2.23604488211947e-05, 'epoch': 0.13}) +[2026-07-26 21:00:14,846][starVLA.training.train_starvla][INFO] - Step 1077, Loss: {'train/loss': 0.32760751247406006, 'train/grad_norm_pre_clip': 3.4465324878692627, 'timing/data': 0.00017916690558195114, 'timing/model': 0.48252904368564487, 'learning_rate/action_model': 8.942291623588993e-05, 'learning_rate/action_query_proj': 8.942291623588993e-05, 'learning_rate/base': 2.2355729058972483e-05, 'epoch': 0.13}) +[2026-07-26 21:00:20,495][starVLA.training.train_starvla][INFO] - Step 1078, Loss: {'train/loss': 0.4244843125343323, 'train/grad_norm_pre_clip': 3.3530845642089844, 'timing/data': 0.0001785201020538807, 'timing/model': 0.4936055666767061, 'learning_rate/action_model': 8.940402241302642e-05, 'learning_rate/action_query_proj': 8.940402241302642e-05, 'learning_rate/base': 2.2351005603256604e-05, 'epoch': 0.13}) +[2026-07-26 21:00:26,140][starVLA.training.train_starvla][INFO] - Step 1079, Loss: {'train/loss': 0.4554261863231659, 'train/grad_norm_pre_clip': 3.5382535457611084, 'timing/data': 0.00017192913219332695, 'timing/model': 0.4828036483377218, 'learning_rate/action_model': 8.938511382364722e-05, 'learning_rate/action_query_proj': 8.938511382364722e-05, 'learning_rate/base': 2.2346278455911804e-05, 'epoch': 0.13}) +[2026-07-26 21:00:31,766][starVLA.training.train_starvla][INFO] - Step 1080, Loss: {'train/loss': 0.35640057921409607, 'train/grad_norm_pre_clip': 3.11586594581604, 'timing/data': 0.00018677208572626114, 'timing/model': 0.47926327073946595, 'learning_rate/action_model': 8.936619047521714e-05, 'learning_rate/action_query_proj': 8.936619047521714e-05, 'learning_rate/base': 2.2341547618804285e-05, 'epoch': 0.13}) +[2026-07-26 21:00:37,414][starVLA.training.train_starvla][INFO] - Step 1081, Loss: {'train/loss': 0.6018046140670776, 'train/grad_norm_pre_clip': 5.110367298126221, 'timing/data': 0.0001843390055000782, 'timing/model': 0.4790838910266757, 'learning_rate/action_model': 8.934725237520682e-05, 'learning_rate/action_query_proj': 8.934725237520682e-05, 'learning_rate/base': 2.2336813093801704e-05, 'epoch': 0.13}) +[2026-07-26 21:00:43,059][starVLA.training.train_starvla][INFO] - Step 1082, Loss: {'train/loss': 0.5736315846443176, 'train/grad_norm_pre_clip': 6.567288875579834, 'timing/data': 0.00018020812422037125, 'timing/model': 0.48501566890627146, 'learning_rate/action_model': 8.932829953109274e-05, 'learning_rate/action_query_proj': 8.932829953109274e-05, 'learning_rate/base': 2.2332074882773185e-05, 'epoch': 0.13}) +[2026-07-26 21:00:48,608][starVLA.training.train_starvla][INFO] - Step 1083, Loss: {'train/loss': 0.4932304620742798, 'train/grad_norm_pre_clip': 6.958058834075928, 'timing/data': 0.00017656711861491203, 'timing/model': 0.4692530520260334, 'learning_rate/action_model': 8.930933195035717e-05, 'learning_rate/action_query_proj': 8.930933195035717e-05, 'learning_rate/base': 2.2327332987589293e-05, 'epoch': 0.13}) +[2026-07-26 21:00:54,213][starVLA.training.train_starvla][INFO] - Step 1084, Loss: {'train/loss': 0.35938939452171326, 'train/grad_norm_pre_clip': 4.297143459320068, 'timing/data': 0.00017483672127127647, 'timing/model': 0.46493361378088593, 'learning_rate/action_model': 8.929034964048821e-05, 'learning_rate/action_query_proj': 8.929034964048821e-05, 'learning_rate/base': 2.2322587410122053e-05, 'epoch': 0.13}) +[2026-07-26 21:00:59,841][starVLA.training.train_starvla][INFO] - Step 1085, Loss: {'train/loss': 0.30664634704589844, 'train/grad_norm_pre_clip': 5.241677761077881, 'timing/data': 0.00017122412100434303, 'timing/model': 0.4669757173396647, 'learning_rate/action_model': 8.927135260897978e-05, 'learning_rate/action_query_proj': 8.927135260897978e-05, 'learning_rate/base': 2.2317838152244945e-05, 'epoch': 0.13}) +[2026-07-26 21:01:05,484][starVLA.training.train_starvla][INFO] - Step 1086, Loss: {'train/loss': 0.3615696132183075, 'train/grad_norm_pre_clip': 3.704686403274536, 'timing/data': 0.00018993020057678223, 'timing/model': 0.4654606753028929, 'learning_rate/action_model': 8.92523408633316e-05, 'learning_rate/action_query_proj': 8.92523408633316e-05, 'learning_rate/base': 2.23130852158329e-05, 'epoch': 0.13}) +[2026-07-26 21:01:11,171][starVLA.training.train_starvla][INFO] - Step 1087, Loss: {'train/loss': 0.4673784673213959, 'train/grad_norm_pre_clip': 4.268793106079102, 'timing/data': 0.00018138065934181213, 'timing/model': 0.4916286342777312, 'learning_rate/action_model': 8.92333144110492e-05, 'learning_rate/action_query_proj': 8.92333144110492e-05, 'learning_rate/base': 2.23083286027623e-05, 'epoch': 0.13}) +[2026-07-26 21:01:16,826][starVLA.training.train_starvla][INFO] - Step 1088, Loss: {'train/loss': 0.4288475513458252, 'train/grad_norm_pre_clip': 5.962397575378418, 'timing/data': 0.00017271889373660088, 'timing/model': 0.4872570913285017, 'learning_rate/action_model': 8.921427325964396e-05, 'learning_rate/action_query_proj': 8.921427325964396e-05, 'learning_rate/base': 2.230356831491099e-05, 'epoch': 0.13}) +[2026-07-26 21:01:22,480][starVLA.training.train_starvla][INFO] - Step 1089, Loss: {'train/loss': 0.4294436275959015, 'train/grad_norm_pre_clip': 4.908320426940918, 'timing/data': 0.00017275428399443626, 'timing/model': 0.48065188294276595, 'learning_rate/action_model': 8.9195217416633e-05, 'learning_rate/action_query_proj': 8.9195217416633e-05, 'learning_rate/base': 2.229880435415825e-05, 'epoch': 0.13}) +[2026-07-26 21:01:28,120][starVLA.training.train_starvla][INFO] - Step 1090, Loss: {'train/loss': 0.5751986503601074, 'train/grad_norm_pre_clip': 3.2551074028015137, 'timing/data': 0.0001689656637609005, 'timing/model': 0.4819373758509755, 'learning_rate/action_model': 8.917614688953923e-05, 'learning_rate/action_query_proj': 8.917614688953923e-05, 'learning_rate/base': 2.2294036722384807e-05, 'epoch': 0.13}) +[2026-07-26 21:01:33,784][starVLA.training.train_starvla][INFO] - Step 1091, Loss: {'train/loss': 0.517829954624176, 'train/grad_norm_pre_clip': 3.228795051574707, 'timing/data': 0.00016837380826473236, 'timing/model': 0.48551088012754917, 'learning_rate/action_model': 8.915706168589143e-05, 'learning_rate/action_query_proj': 8.915706168589143e-05, 'learning_rate/base': 2.228926542147286e-05, 'epoch': 0.13}) +[2026-07-26 21:01:39,393][starVLA.training.train_starvla][INFO] - Step 1092, Loss: {'train/loss': 0.543106198310852, 'train/grad_norm_pre_clip': 4.853926658630371, 'timing/data': 0.00016811396926641464, 'timing/model': 0.46695954306051135, 'learning_rate/action_model': 8.913796181322416e-05, 'learning_rate/action_query_proj': 8.913796181322416e-05, 'learning_rate/base': 2.228449045330604e-05, 'epoch': 0.13}) +[2026-07-26 21:01:45,014][starVLA.training.train_starvla][INFO] - Step 1093, Loss: {'train/loss': 0.47308194637298584, 'train/grad_norm_pre_clip': 3.3041751384735107, 'timing/data': 0.00016740383580327034, 'timing/model': 0.46745456801727414, 'learning_rate/action_model': 8.911884727907769e-05, 'learning_rate/action_query_proj': 8.911884727907769e-05, 'learning_rate/base': 2.2279711819769423e-05, 'epoch': 0.13}) +[2026-07-26 21:01:50,667][starVLA.training.train_starvla][INFO] - Step 1094, Loss: {'train/loss': 0.473687082529068, 'train/grad_norm_pre_clip': 3.9166157245635986, 'timing/data': 0.00018067099153995514, 'timing/model': 0.4680902138352394, 'learning_rate/action_model': 8.909971809099817e-05, 'learning_rate/action_query_proj': 8.909971809099817e-05, 'learning_rate/base': 2.2274929522749543e-05, 'epoch': 0.13}) +[2026-07-26 21:01:56,346][starVLA.training.train_starvla][INFO] - Step 1095, Loss: {'train/loss': 0.43584394454956055, 'train/grad_norm_pre_clip': 4.382892608642578, 'timing/data': 0.00017487118020653725, 'timing/model': 0.4688464212231338, 'learning_rate/action_model': 8.90805742565375e-05, 'learning_rate/action_query_proj': 8.90805742565375e-05, 'learning_rate/base': 2.2270143564134375e-05, 'epoch': 0.13}) +[2026-07-26 21:02:01,987][starVLA.training.train_starvla][INFO] - Step 1096, Loss: {'train/loss': 0.4448595643043518, 'train/grad_norm_pre_clip': 4.411208152770996, 'timing/data': 0.00017281295731663704, 'timing/model': 0.4614783492870629, 'learning_rate/action_model': 8.906141578325336e-05, 'learning_rate/action_query_proj': 8.906141578325336e-05, 'learning_rate/base': 2.226535394581334e-05, 'epoch': 0.13}) +[2026-07-26 21:02:07,632][starVLA.training.train_starvla][INFO] - Step 1097, Loss: {'train/loss': 0.5094318389892578, 'train/grad_norm_pre_clip': 6.468245506286621, 'timing/data': 0.00016970140859484673, 'timing/model': 0.4678353169001639, 'learning_rate/action_model': 8.904224267870919e-05, 'learning_rate/action_query_proj': 8.904224267870919e-05, 'learning_rate/base': 2.2260560669677298e-05, 'epoch': 0.13}) +[2026-07-26 21:02:13,311][starVLA.training.train_starvla][INFO] - Step 1098, Loss: {'train/loss': 0.3655443787574768, 'train/grad_norm_pre_clip': 3.594649076461792, 'timing/data': 0.00018472503870725632, 'timing/model': 0.46669918205589056, 'learning_rate/action_model': 8.902305495047426e-05, 'learning_rate/action_query_proj': 8.902305495047426e-05, 'learning_rate/base': 2.2255763737618564e-05, 'epoch': 0.13}) +[2026-07-26 21:02:18,948][starVLA.training.train_starvla][INFO] - Step 1099, Loss: {'train/loss': 0.4319874942302704, 'train/grad_norm_pre_clip': 3.8661794662475586, 'timing/data': 0.0001721722073853016, 'timing/model': 0.46757691306993365, 'learning_rate/action_model': 8.900385260612356e-05, 'learning_rate/action_query_proj': 8.900385260612356e-05, 'learning_rate/base': 2.225096315153089e-05, 'epoch': 0.13}) +[2026-07-26 21:02:24,595][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 1100 +[2026-07-26 21:02:24,596][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 1100 +[2026-07-26 21:02:24,597][starVLA.training.train_starvla][INFO] - Step 1100, Loss: {'train/loss': 0.4075506031513214, 'train/grad_norm_pre_clip': 4.321938991546631, 'timing/data': 0.00017836922779679298, 'timing/model': 0.46585480496287346, 'learning_rate/action_model': 8.898463565323789e-05, 'learning_rate/action_query_proj': 8.898463565323789e-05, 'learning_rate/base': 2.2246158913309473e-05, 'epoch': 0.13}) +[2026-07-26 21:02:30,235][starVLA.training.train_starvla][INFO] - Step 1101, Loss: {'train/loss': 0.38605451583862305, 'train/grad_norm_pre_clip': 2.2677762508392334, 'timing/data': 0.00018339278176426888, 'timing/model': 0.46739922277629375, 'learning_rate/action_model': 8.896540409940377e-05, 'learning_rate/action_query_proj': 8.896540409940377e-05, 'learning_rate/base': 2.2241351024850943e-05, 'epoch': 0.13}) +[2026-07-26 21:02:35,904][starVLA.training.train_starvla][INFO] - Step 1102, Loss: {'train/loss': 0.4293520450592041, 'train/grad_norm_pre_clip': 3.8802640438079834, 'timing/data': 0.00017703324556350708, 'timing/model': 0.46646321238949895, 'learning_rate/action_model': 8.894615795221356e-05, 'learning_rate/action_query_proj': 8.894615795221356e-05, 'learning_rate/base': 2.223653948805339e-05, 'epoch': 0.13}) +[2026-07-26 21:02:41,549][starVLA.training.train_starvla][INFO] - Step 1103, Loss: {'train/loss': 0.3988286256790161, 'train/grad_norm_pre_clip': 3.7621426582336426, 'timing/data': 0.00017440086230635643, 'timing/model': 0.464136759750545, 'learning_rate/action_model': 8.892689721926528e-05, 'learning_rate/action_query_proj': 8.892689721926528e-05, 'learning_rate/base': 2.223172430481632e-05, 'epoch': 0.13}) +[2026-07-26 21:02:47,195][starVLA.training.train_starvla][INFO] - Step 1104, Loss: {'train/loss': 0.4156560003757477, 'train/grad_norm_pre_clip': 3.514030694961548, 'timing/data': 0.00018463796004652977, 'timing/model': 0.46678383788093925, 'learning_rate/action_model': 8.890762190816279e-05, 'learning_rate/action_query_proj': 8.890762190816279e-05, 'learning_rate/base': 2.2226905477040698e-05, 'epoch': 0.13}) +[2026-07-26 21:02:52,855][starVLA.training.train_starvla][INFO] - Step 1105, Loss: {'train/loss': 0.372858464717865, 'train/grad_norm_pre_clip': 4.249928951263428, 'timing/data': 0.0001780511811375618, 'timing/model': 0.4666841891594231, 'learning_rate/action_model': 8.888833202651569e-05, 'learning_rate/action_query_proj': 8.888833202651569e-05, 'learning_rate/base': 2.2222083006628923e-05, 'epoch': 0.13}) +[2026-07-26 21:02:58,509][starVLA.training.train_starvla][INFO] - Step 1106, Loss: {'train/loss': 0.49110305309295654, 'train/grad_norm_pre_clip': 4.422137260437012, 'timing/data': 0.00018524331972002983, 'timing/model': 0.46680651418864727, 'learning_rate/action_model': 8.886902758193927e-05, 'learning_rate/action_query_proj': 8.886902758193927e-05, 'learning_rate/base': 2.221725689548482e-05, 'epoch': 0.13}) +[2026-07-26 21:03:04,168][starVLA.training.train_starvla][INFO] - Step 1107, Loss: {'train/loss': 0.45247218012809753, 'train/grad_norm_pre_clip': 3.7209126949310303, 'timing/data': 0.00017631379887461662, 'timing/model': 0.4847290781326592, 'learning_rate/action_model': 8.884970858205469e-05, 'learning_rate/action_query_proj': 8.884970858205469e-05, 'learning_rate/base': 2.2212427145513672e-05, 'epoch': 0.13}) +[2026-07-26 21:03:09,840][starVLA.training.train_starvla][INFO] - Step 1108, Loss: {'train/loss': 0.45348021388053894, 'train/grad_norm_pre_clip': 5.4830546379089355, 'timing/data': 0.00016690371558070183, 'timing/model': 0.49054207978770137, 'learning_rate/action_model': 8.883037503448875e-05, 'learning_rate/action_query_proj': 8.883037503448875e-05, 'learning_rate/base': 2.2207593758622187e-05, 'epoch': 0.13}) +[2026-07-26 21:03:15,449][starVLA.training.train_starvla][INFO] - Step 1109, Loss: {'train/loss': 0.49603933095932007, 'train/grad_norm_pre_clip': 5.421006202697754, 'timing/data': 0.00016911886632442474, 'timing/model': 0.4849773198366165, 'learning_rate/action_model': 8.881102694687401e-05, 'learning_rate/action_query_proj': 8.881102694687401e-05, 'learning_rate/base': 2.2202756736718503e-05, 'epoch': 0.13}) +[2026-07-26 21:03:21,251][starVLA.training.train_starvla][INFO] - Step 1110, Loss: {'train/loss': 0.5118276476860046, 'train/grad_norm_pre_clip': 6.702466011047363, 'timing/data': 0.00016979314386844635, 'timing/model': 0.4675643346272409, 'learning_rate/action_model': 8.87916643268488e-05, 'learning_rate/action_query_proj': 8.87916643268488e-05, 'learning_rate/base': 2.21979160817122e-05, 'epoch': 0.13}) +[2026-07-26 21:03:27,040][starVLA.training.train_starvla][INFO] - Step 1111, Loss: {'train/loss': 0.4335884153842926, 'train/grad_norm_pre_clip': 4.428893089294434, 'timing/data': 0.000169496051967144, 'timing/model': 0.48485074611380696, 'learning_rate/action_model': 8.877228718205718e-05, 'learning_rate/action_query_proj': 8.877228718205718e-05, 'learning_rate/base': 2.2193071795514296e-05, 'epoch': 0.13}) +[2026-07-26 21:03:32,847][starVLA.training.train_starvla][INFO] - Step 1112, Loss: {'train/loss': 0.28784874081611633, 'train/grad_norm_pre_clip': 3.2492637634277344, 'timing/data': 0.00016755890101194382, 'timing/model': 0.6316876038908958, 'learning_rate/action_model': 8.875289552014897e-05, 'learning_rate/action_query_proj': 8.875289552014897e-05, 'learning_rate/base': 2.2188223880037242e-05, 'epoch': 0.13}) +[2026-07-26 21:03:38,510][starVLA.training.train_starvla][INFO] - Step 1113, Loss: {'train/loss': 0.5881022810935974, 'train/grad_norm_pre_clip': 7.093707084655762, 'timing/data': 0.00017619691789150238, 'timing/model': 0.46712592616677284, 'learning_rate/action_model': 8.873348934877963e-05, 'learning_rate/action_query_proj': 8.873348934877963e-05, 'learning_rate/base': 2.2183372337194907e-05, 'epoch': 0.14}) +[2026-07-26 21:03:44,193][starVLA.training.train_starvla][INFO] - Step 1114, Loss: {'train/loss': 0.5508747100830078, 'train/grad_norm_pre_clip': 7.235667705535889, 'timing/data': 0.00027752993628382683, 'timing/model': 0.4652288337238133, 'learning_rate/action_model': 8.871406867561045e-05, 'learning_rate/action_query_proj': 8.871406867561045e-05, 'learning_rate/base': 2.2178517168902613e-05, 'epoch': 0.14}) +[2026-07-26 21:03:49,872][starVLA.training.train_starvla][INFO] - Step 1115, Loss: {'train/loss': 0.3992190659046173, 'train/grad_norm_pre_clip': 5.212583065032959, 'timing/data': 0.000182462390512228, 'timing/model': 0.46736829495057464, 'learning_rate/action_model': 8.86946335083084e-05, 'learning_rate/action_query_proj': 8.86946335083084e-05, 'learning_rate/base': 2.21736583770771e-05, 'epoch': 0.14}) +[2026-07-26 21:03:55,575][starVLA.training.train_starvla][INFO] - Step 1116, Loss: {'train/loss': 0.5649503469467163, 'train/grad_norm_pre_clip': 6.148922443389893, 'timing/data': 0.00017723580822348595, 'timing/model': 0.4674643501639366, 'learning_rate/action_model': 8.867518385454616e-05, 'learning_rate/action_query_proj': 8.867518385454616e-05, 'learning_rate/base': 2.216879596363654e-05, 'epoch': 0.14}) +[2026-07-26 21:04:01,229][starVLA.training.train_starvla][INFO] - Step 1117, Loss: {'train/loss': 0.44566071033477783, 'train/grad_norm_pre_clip': 5.177394866943359, 'timing/data': 0.00017701927572488785, 'timing/model': 0.4643184277229011, 'learning_rate/action_model': 8.865571972200218e-05, 'learning_rate/action_query_proj': 8.865571972200218e-05, 'learning_rate/base': 2.2163929930500545e-05, 'epoch': 0.14}) +[2026-07-26 21:04:06,875][starVLA.training.train_starvla][INFO] - Step 1118, Loss: {'train/loss': 0.5827162265777588, 'train/grad_norm_pre_clip': 4.425588607788086, 'timing/data': 0.00017630821093916893, 'timing/model': 0.4663689127191901, 'learning_rate/action_model': 8.863624111836056e-05, 'learning_rate/action_query_proj': 8.863624111836056e-05, 'learning_rate/base': 2.215906027959014e-05, 'epoch': 0.14}) +[2026-07-26 21:04:12,532][starVLA.training.train_starvla][INFO] - Step 1119, Loss: {'train/loss': 0.4401187300682068, 'train/grad_norm_pre_clip': 4.172391414642334, 'timing/data': 0.00018008612096309662, 'timing/model': 0.464279942214489, 'learning_rate/action_model': 8.861674805131115e-05, 'learning_rate/action_query_proj': 8.861674805131115e-05, 'learning_rate/base': 2.215418701282779e-05, 'epoch': 0.14}) +[2026-07-26 21:04:18,181][starVLA.training.train_starvla][INFO] - Step 1120, Loss: {'train/loss': 0.4547514319419861, 'train/grad_norm_pre_clip': 5.808874130249023, 'timing/data': 0.00017524324357509613, 'timing/model': 0.4623491680249572, 'learning_rate/action_model': 8.85972405285495e-05, 'learning_rate/action_query_proj': 8.85972405285495e-05, 'learning_rate/base': 2.2149310132137376e-05, 'epoch': 0.14}) +[2026-07-26 21:04:23,823][starVLA.training.train_starvla][INFO] - Step 1121, Loss: {'train/loss': 0.5018833875656128, 'train/grad_norm_pre_clip': 7.458010673522949, 'timing/data': 0.00018683820962905884, 'timing/model': 0.4674705839715898, 'learning_rate/action_model': 8.857771855777688e-05, 'learning_rate/action_query_proj': 8.857771855777688e-05, 'learning_rate/base': 2.214442963944422e-05, 'epoch': 0.14}) +[2026-07-26 21:04:29,646][starVLA.training.train_starvla][INFO] - Step 1122, Loss: {'train/loss': 0.40741023421287537, 'train/grad_norm_pre_clip': 6.648398399353027, 'timing/data': 0.0001726602204144001, 'timing/model': 0.45854824874550104, 'learning_rate/action_model': 8.855818214670026e-05, 'learning_rate/action_query_proj': 8.855818214670026e-05, 'learning_rate/base': 2.2139545536675064e-05, 'epoch': 0.14}) +[2026-07-26 21:04:35,184][starVLA.training.train_starvla][INFO] - Step 1123, Loss: {'train/loss': 0.4104100465774536, 'train/grad_norm_pre_clip': 3.246403932571411, 'timing/data': 0.00017324509099125862, 'timing/model': 0.4592767022550106, 'learning_rate/action_model': 8.85386313030323e-05, 'learning_rate/action_query_proj': 8.85386313030323e-05, 'learning_rate/base': 2.2134657825758074e-05, 'epoch': 0.14}) +[2026-07-26 21:04:40,683][starVLA.training.train_starvla][INFO] - Step 1124, Loss: {'train/loss': 0.38185054063796997, 'train/grad_norm_pre_clip': 3.9940133094787598, 'timing/data': 0.000176949892193079, 'timing/model': 0.45844903588294983, 'learning_rate/action_model': 8.851906603449136e-05, 'learning_rate/action_query_proj': 8.851906603449136e-05, 'learning_rate/base': 2.212976650862284e-05, 'epoch': 0.14}) +[2026-07-26 21:04:46,204][starVLA.training.train_starvla][INFO] - Step 1125, Loss: {'train/loss': 0.41488033533096313, 'train/grad_norm_pre_clip': 4.53791618347168, 'timing/data': 0.00017261598259210587, 'timing/model': 0.4588222997263074, 'learning_rate/action_model': 8.84994863488015e-05, 'learning_rate/action_query_proj': 8.84994863488015e-05, 'learning_rate/base': 2.2124871587200376e-05, 'epoch': 0.14}) +[2026-07-26 21:04:51,721][starVLA.training.train_starvla][INFO] - Step 1126, Loss: {'train/loss': 0.4709247350692749, 'train/grad_norm_pre_clip': 4.968776702880859, 'timing/data': 0.00017586024478077888, 'timing/model': 0.45924634858965874, 'learning_rate/action_model': 8.847989225369247e-05, 'learning_rate/action_query_proj': 8.847989225369247e-05, 'learning_rate/base': 2.2119973063423118e-05, 'epoch': 0.14}) +[2026-07-26 21:04:57,235][starVLA.training.train_starvla][INFO] - Step 1127, Loss: {'train/loss': 0.5467203855514526, 'train/grad_norm_pre_clip': 7.332501411437988, 'timing/data': 0.00017994502559304237, 'timing/model': 0.460132644046098, 'learning_rate/action_model': 8.84602837568997e-05, 'learning_rate/action_query_proj': 8.84602837568997e-05, 'learning_rate/base': 2.2115070939224924e-05, 'epoch': 0.14}) +[2026-07-26 21:05:02,747][starVLA.training.train_starvla][INFO] - Step 1128, Loss: {'train/loss': 0.4571745991706848, 'train/grad_norm_pre_clip': 5.415983200073242, 'timing/data': 0.00017005903646349907, 'timing/model': 0.45811307104304433, 'learning_rate/action_model': 8.844066086616431e-05, 'learning_rate/action_query_proj': 8.844066086616431e-05, 'learning_rate/base': 2.2110165216541078e-05, 'epoch': 0.14}) +[2026-07-26 21:05:08,285][starVLA.training.train_starvla][INFO] - Step 1129, Loss: {'train/loss': 0.6310124397277832, 'train/grad_norm_pre_clip': 6.227737903594971, 'timing/data': 0.00017049210146069527, 'timing/model': 0.459531235974282, 'learning_rate/action_model': 8.842102358923315e-05, 'learning_rate/action_query_proj': 8.842102358923315e-05, 'learning_rate/base': 2.2105255897308286e-05, 'epoch': 0.14}) +[2026-07-26 21:05:13,833][starVLA.training.train_starvla][INFO] - Step 1130, Loss: {'train/loss': 0.4533877968788147, 'train/grad_norm_pre_clip': 4.576280117034912, 'timing/data': 0.0001719258725643158, 'timing/model': 0.45892356894910336, 'learning_rate/action_model': 8.840137193385865e-05, 'learning_rate/action_query_proj': 8.840137193385865e-05, 'learning_rate/base': 2.2100342983464663e-05, 'epoch': 0.14}) +[2026-07-26 21:05:19,341][starVLA.training.train_starvla][INFO] - Step 1131, Loss: {'train/loss': 0.40525585412979126, 'train/grad_norm_pre_clip': 3.720083475112915, 'timing/data': 0.00018767733126878738, 'timing/model': 0.4577954360283911, 'learning_rate/action_model': 8.8381705907799e-05, 'learning_rate/action_query_proj': 8.8381705907799e-05, 'learning_rate/base': 2.209542647694975e-05, 'epoch': 0.14}) +[2026-07-26 21:05:24,863][starVLA.training.train_starvla][INFO] - Step 1132, Loss: {'train/loss': 0.2995053231716156, 'train/grad_norm_pre_clip': 2.8680896759033203, 'timing/data': 0.0001796460710465908, 'timing/model': 0.45893323980271816, 'learning_rate/action_model': 8.836202551881806e-05, 'learning_rate/action_query_proj': 8.836202551881806e-05, 'learning_rate/base': 2.2090506379704515e-05, 'epoch': 0.14}) +[2026-07-26 21:05:30,375][starVLA.training.train_starvla][INFO] - Step 1133, Loss: {'train/loss': 0.48917102813720703, 'train/grad_norm_pre_clip': 4.098389148712158, 'timing/data': 0.0001695607788860798, 'timing/model': 0.4632120910100639, 'learning_rate/action_model': 8.834233077468527e-05, 'learning_rate/action_query_proj': 8.834233077468527e-05, 'learning_rate/base': 2.2085582693671318e-05, 'epoch': 0.14}) +[2026-07-26 21:05:35,889][starVLA.training.train_starvla][INFO] - Step 1134, Loss: {'train/loss': 0.4782447814941406, 'train/grad_norm_pre_clip': 3.9070751667022705, 'timing/data': 0.00017420295625925064, 'timing/model': 0.4587637111544609, 'learning_rate/action_model': 8.832262168317587e-05, 'learning_rate/action_query_proj': 8.832262168317587e-05, 'learning_rate/base': 2.2080655420793968e-05, 'epoch': 0.14}) +[2026-07-26 21:05:41,580][starVLA.training.train_starvla][INFO] - Step 1135, Loss: {'train/loss': 0.35736632347106934, 'train/grad_norm_pre_clip': 3.1318867206573486, 'timing/data': 0.00016662012785673141, 'timing/model': 0.4573603291064501, 'learning_rate/action_model': 8.830289825207065e-05, 'learning_rate/action_query_proj': 8.830289825207065e-05, 'learning_rate/base': 2.2075724563017662e-05, 'epoch': 0.14}) +[2026-07-26 21:05:47,090][starVLA.training.train_starvla][INFO] - Step 1136, Loss: {'train/loss': 0.5526320338249207, 'train/grad_norm_pre_clip': 8.047642707824707, 'timing/data': 0.00017997482791543007, 'timing/model': 0.4590620528906584, 'learning_rate/action_model': 8.828316048915615e-05, 'learning_rate/action_query_proj': 8.828316048915615e-05, 'learning_rate/base': 2.2070790122289038e-05, 'epoch': 0.14}) +[2026-07-26 21:05:52,598][starVLA.training.train_starvla][INFO] - Step 1137, Loss: {'train/loss': 0.4827609956264496, 'train/grad_norm_pre_clip': 5.1638641357421875, 'timing/data': 0.00017846934497356415, 'timing/model': 0.4590086159296334, 'learning_rate/action_model': 8.826340840222448e-05, 'learning_rate/action_query_proj': 8.826340840222448e-05, 'learning_rate/base': 2.206585210055612e-05, 'epoch': 0.14}) +[2026-07-26 21:05:58,117][starVLA.training.train_starvla][INFO] - Step 1138, Loss: {'train/loss': 0.4356437623500824, 'train/grad_norm_pre_clip': 4.246867656707764, 'timing/data': 0.0001793862320482731, 'timing/model': 0.4597515780478716, 'learning_rate/action_model': 8.824364199907348e-05, 'learning_rate/action_query_proj': 8.824364199907348e-05, 'learning_rate/base': 2.206091049976837e-05, 'epoch': 0.14}) +[2026-07-26 21:06:03,629][starVLA.training.train_starvla][INFO] - Step 1139, Loss: {'train/loss': 0.3126926124095917, 'train/grad_norm_pre_clip': 3.068962335586548, 'timing/data': 0.00016896333545446396, 'timing/model': 0.45821967208757997, 'learning_rate/action_model': 8.822386128750662e-05, 'learning_rate/action_query_proj': 8.822386128750662e-05, 'learning_rate/base': 2.2055965321876655e-05, 'epoch': 0.14}) +[2026-07-26 21:06:09,182][starVLA.training.train_starvla][INFO] - Step 1140, Loss: {'train/loss': 0.44074687361717224, 'train/grad_norm_pre_clip': 5.7320356369018555, 'timing/data': 0.00017069373279809952, 'timing/model': 0.4779545785859227, 'learning_rate/action_model': 8.820406627533298e-05, 'learning_rate/action_query_proj': 8.820406627533298e-05, 'learning_rate/base': 2.2051016568833246e-05, 'epoch': 0.14}) +[2026-07-26 21:06:14,714][starVLA.training.train_starvla][INFO] - Step 1141, Loss: {'train/loss': 0.3981863260269165, 'train/grad_norm_pre_clip': 6.183659553527832, 'timing/data': 0.0001732190139591694, 'timing/model': 0.47099385084584355, 'learning_rate/action_model': 8.818425697036736e-05, 'learning_rate/action_query_proj': 8.818425697036736e-05, 'learning_rate/base': 2.204606424259184e-05, 'epoch': 0.14}) +[2026-07-26 21:06:20,254][starVLA.training.train_starvla][INFO] - Step 1142, Loss: {'train/loss': 0.4014623165130615, 'train/grad_norm_pre_clip': 3.2386186122894287, 'timing/data': 0.00017200270667672157, 'timing/model': 0.46947694988921285, 'learning_rate/action_model': 8.816443338043011e-05, 'learning_rate/action_query_proj': 8.816443338043011e-05, 'learning_rate/base': 2.2041108345107528e-05, 'epoch': 0.14}) +[2026-07-26 21:06:26,029][starVLA.training.train_starvla][INFO] - Step 1143, Loss: {'train/loss': 0.47315341234207153, 'train/grad_norm_pre_clip': 5.094200134277344, 'timing/data': 0.00018279114738106728, 'timing/model': 0.45879670698195696, 'learning_rate/action_model': 8.814459551334732e-05, 'learning_rate/action_query_proj': 8.814459551334732e-05, 'learning_rate/base': 2.203614887833683e-05, 'epoch': 0.14}) +[2026-07-26 21:06:31,801][starVLA.training.train_starvla][INFO] - Step 1144, Loss: {'train/loss': 0.37380629777908325, 'train/grad_norm_pre_clip': 3.547224998474121, 'timing/data': 0.00017412379384040833, 'timing/model': 0.45912073412910104, 'learning_rate/action_model': 8.812474337695062e-05, 'learning_rate/action_query_proj': 8.812474337695062e-05, 'learning_rate/base': 2.2031185844237656e-05, 'epoch': 0.14}) +[2026-07-26 21:06:37,318][starVLA.training.train_starvla][INFO] - Step 1145, Loss: {'train/loss': 0.3531672954559326, 'train/grad_norm_pre_clip': 3.3267018795013428, 'timing/data': 0.00017697829753160477, 'timing/model': 0.4594135438092053, 'learning_rate/action_model': 8.810487697907735e-05, 'learning_rate/action_query_proj': 8.810487697907735e-05, 'learning_rate/base': 2.2026219244769338e-05, 'epoch': 0.14}) +[2026-07-26 21:06:42,835][starVLA.training.train_starvla][INFO] - Step 1146, Loss: {'train/loss': 0.3681913912296295, 'train/grad_norm_pre_clip': 5.7724409103393555, 'timing/data': 0.0001779003068804741, 'timing/model': 0.45947089279070497, 'learning_rate/action_model': 8.808499632757045e-05, 'learning_rate/action_query_proj': 8.808499632757045e-05, 'learning_rate/base': 2.202124908189261e-05, 'epoch': 0.14}) +[2026-07-26 21:06:48,609][starVLA.training.train_starvla][INFO] - Step 1147, Loss: {'train/loss': 0.3838765621185303, 'train/grad_norm_pre_clip': 4.32589054107666, 'timing/data': 0.00017325393855571747, 'timing/model': 0.45962424017488956, 'learning_rate/action_model': 8.806510143027846e-05, 'learning_rate/action_query_proj': 8.806510143027846e-05, 'learning_rate/base': 2.2016275357569615e-05, 'epoch': 0.14}) +[2026-07-26 21:06:54,125][starVLA.training.train_starvla][INFO] - Step 1148, Loss: {'train/loss': 0.4757295846939087, 'train/grad_norm_pre_clip': 4.416137218475342, 'timing/data': 0.00017105834558606148, 'timing/model': 0.46007117768749595, 'learning_rate/action_model': 8.80451922950556e-05, 'learning_rate/action_query_proj': 8.80451922950556e-05, 'learning_rate/base': 2.20112980737639e-05, 'epoch': 0.14}) +[2026-07-26 21:06:59,642][starVLA.training.train_starvla][INFO] - Step 1149, Loss: {'train/loss': 0.4780127704143524, 'train/grad_norm_pre_clip': 5.624264717102051, 'timing/data': 0.00017495173960924149, 'timing/model': 0.45819743489846587, 'learning_rate/action_model': 8.802526892976164e-05, 'learning_rate/action_query_proj': 8.802526892976164e-05, 'learning_rate/base': 2.200631723244041e-05, 'epoch': 0.14}) +[2026-07-26 21:07:05,418][starVLA.training.train_starvla][INFO] - Step 1150, Loss: {'train/loss': 0.2908632457256317, 'train/grad_norm_pre_clip': 3.6717841625213623, 'timing/data': 0.0001721661537885666, 'timing/model': 0.45996615337207913, 'learning_rate/action_model': 8.800533134226207e-05, 'learning_rate/action_query_proj': 8.800533134226207e-05, 'learning_rate/base': 2.2001332835565517e-05, 'epoch': 0.14}) +[2026-07-26 21:07:10,927][starVLA.training.train_starvla][INFO] - Step 1151, Loss: {'train/loss': 0.5774088501930237, 'train/grad_norm_pre_clip': 4.425626277923584, 'timing/data': 0.0001750611700117588, 'timing/model': 0.4590946421958506, 'learning_rate/action_model': 8.798537954042789e-05, 'learning_rate/action_query_proj': 8.798537954042789e-05, 'learning_rate/base': 2.199634488510697e-05, 'epoch': 0.14}) +[2026-07-26 21:07:16,445][starVLA.training.train_starvla][INFO] - Step 1152, Loss: {'train/loss': 0.4529944062232971, 'train/grad_norm_pre_clip': 4.008486270904541, 'timing/data': 0.00018187565729022026, 'timing/model': 0.4577237870544195, 'learning_rate/action_model': 8.796541353213577e-05, 'learning_rate/action_query_proj': 8.796541353213577e-05, 'learning_rate/base': 2.1991353383033942e-05, 'epoch': 0.14}) +[2026-07-26 21:07:21,968][starVLA.training.train_starvla][INFO] - Step 1153, Loss: {'train/loss': 0.4790816009044647, 'train/grad_norm_pre_clip': 4.961630821228027, 'timing/data': 0.00022998033091425896, 'timing/model': 0.4683043360710144, 'learning_rate/action_model': 8.794543332526795e-05, 'learning_rate/action_query_proj': 8.794543332526795e-05, 'learning_rate/base': 2.1986358331316987e-05, 'epoch': 0.14}) +[2026-07-26 21:07:27,482][starVLA.training.train_starvla][INFO] - Step 1154, Loss: {'train/loss': 0.41046634316444397, 'train/grad_norm_pre_clip': 5.785067081451416, 'timing/data': 0.0001849532127380371, 'timing/model': 0.45870361290872097, 'learning_rate/action_model': 8.792543892771233e-05, 'learning_rate/action_query_proj': 8.792543892771233e-05, 'learning_rate/base': 2.1981359731928082e-05, 'epoch': 0.14}) +[2026-07-26 21:07:32,995][starVLA.training.train_starvla][INFO] - Step 1155, Loss: {'train/loss': 0.4535204768180847, 'train/grad_norm_pre_clip': 4.74979305267334, 'timing/data': 0.00017617782577872276, 'timing/model': 0.4589748131111264, 'learning_rate/action_model': 8.790543034736237e-05, 'learning_rate/action_query_proj': 8.790543034736237e-05, 'learning_rate/base': 2.197635758684059e-05, 'epoch': 0.14}) +[2026-07-26 21:07:38,780][starVLA.training.train_starvla][INFO] - Step 1156, Loss: {'train/loss': 0.4705577492713928, 'train/grad_norm_pre_clip': 3.2814559936523438, 'timing/data': 0.00017653871327638626, 'timing/model': 0.7174196387641132, 'learning_rate/action_model': 8.788540759211714e-05, 'learning_rate/action_query_proj': 8.788540759211714e-05, 'learning_rate/base': 2.1971351898029285e-05, 'epoch': 0.14}) +[2026-07-26 21:07:44,298][starVLA.training.train_starvla][INFO] - Step 1157, Loss: {'train/loss': 0.4677059054374695, 'train/grad_norm_pre_clip': 4.924156665802002, 'timing/data': 0.00019622500985860825, 'timing/model': 0.4591437540948391, 'learning_rate/action_model': 8.78653706698813e-05, 'learning_rate/action_query_proj': 8.78653706698813e-05, 'learning_rate/base': 2.1966342667470326e-05, 'epoch': 0.14}) +[2026-07-26 21:07:49,895][starVLA.training.train_starvla][INFO] - Step 1158, Loss: {'train/loss': 0.4534367024898529, 'train/grad_norm_pre_clip': 4.846853256225586, 'timing/data': 0.00023047812283039093, 'timing/model': 0.47158496966585517, 'learning_rate/action_model': 8.784531958856514e-05, 'learning_rate/action_query_proj': 8.784531958856514e-05, 'learning_rate/base': 2.1961329897141284e-05, 'epoch': 0.14}) +[2026-07-26 21:07:55,512][starVLA.training.train_starvla][INFO] - Step 1159, Loss: {'train/loss': 0.42993754148483276, 'train/grad_norm_pre_clip': 5.316492557525635, 'timing/data': 0.00018217088654637337, 'timing/model': 0.45836681593209505, 'learning_rate/action_model': 8.782525435608447e-05, 'learning_rate/action_query_proj': 8.782525435608447e-05, 'learning_rate/base': 2.195631358902112e-05, 'epoch': 0.14}) +[2026-07-26 21:08:01,085][starVLA.training.train_starvla][INFO] - Step 1160, Loss: {'train/loss': 0.386344313621521, 'train/grad_norm_pre_clip': 5.897268295288086, 'timing/data': 0.00017977925017476082, 'timing/model': 0.4585641329176724, 'learning_rate/action_model': 8.780517498036074e-05, 'learning_rate/action_query_proj': 8.780517498036074e-05, 'learning_rate/base': 2.1951293745090186e-05, 'epoch': 0.14}) +[2026-07-26 21:08:06,617][starVLA.training.train_starvla][INFO] - Step 1161, Loss: {'train/loss': 0.4827670753002167, 'train/grad_norm_pre_clip': 4.941498279571533, 'timing/data': 0.00018600188195705414, 'timing/model': 0.45961686270311475, 'learning_rate/action_model': 8.778508146932098e-05, 'learning_rate/action_query_proj': 8.778508146932098e-05, 'learning_rate/base': 2.1946270367330245e-05, 'epoch': 0.14}) +[2026-07-26 21:08:12,163][starVLA.training.train_starvla][INFO] - Step 1162, Loss: {'train/loss': 0.4251757860183716, 'train/grad_norm_pre_clip': 4.064012050628662, 'timing/data': 0.00018162233754992485, 'timing/model': 0.4710814459249377, 'learning_rate/action_model': 8.776497383089779e-05, 'learning_rate/action_query_proj': 8.776497383089779e-05, 'learning_rate/base': 2.1941243457724448e-05, 'epoch': 0.14}) +[2026-07-26 21:08:17,708][starVLA.training.train_starvla][INFO] - Step 1163, Loss: {'train/loss': 0.4211304783821106, 'train/grad_norm_pre_clip': 4.3477396965026855, 'timing/data': 0.00017206324264407158, 'timing/model': 0.46914148703217506, 'learning_rate/action_model': 8.774485207302933e-05, 'learning_rate/action_query_proj': 8.774485207302933e-05, 'learning_rate/base': 2.1936213018257332e-05, 'epoch': 0.14}) +[2026-07-26 21:08:23,269][starVLA.training.train_starvla][INFO] - Step 1164, Loss: {'train/loss': 0.43599849939346313, 'train/grad_norm_pre_clip': 4.623950481414795, 'timing/data': 0.00017126090824604034, 'timing/model': 0.4722283580340445, 'learning_rate/action_model': 8.772471620365937e-05, 'learning_rate/action_query_proj': 8.772471620365937e-05, 'learning_rate/base': 2.1931179050914842e-05, 'epoch': 0.14}) +[2026-07-26 21:08:28,821][starVLA.training.train_starvla][INFO] - Step 1165, Loss: {'train/loss': 0.5184502005577087, 'train/grad_norm_pre_clip': 4.839860916137695, 'timing/data': 0.00018485775217413902, 'timing/model': 0.47152801183983684, 'learning_rate/action_model': 8.770456623073721e-05, 'learning_rate/action_query_proj': 8.770456623073721e-05, 'learning_rate/base': 2.1926141557684303e-05, 'epoch': 0.14}) +[2026-07-26 21:08:34,370][starVLA.training.train_starvla][INFO] - Step 1166, Loss: {'train/loss': 0.5453415513038635, 'train/grad_norm_pre_clip': 4.770151138305664, 'timing/data': 0.000180946197360754, 'timing/model': 0.45954193407669663, 'learning_rate/action_model': 8.768440216221776e-05, 'learning_rate/action_query_proj': 8.768440216221776e-05, 'learning_rate/base': 2.192110054055444e-05, 'epoch': 0.14}) +[2026-07-26 21:08:39,926][starVLA.training.train_starvla][INFO] - Step 1167, Loss: {'train/loss': 0.3623813986778259, 'train/grad_norm_pre_clip': 3.8870019912719727, 'timing/data': 0.0001705540344119072, 'timing/model': 0.4705837410874665, 'learning_rate/action_model': 8.766422400606147e-05, 'learning_rate/action_query_proj': 8.766422400606147e-05, 'learning_rate/base': 2.1916056001515367e-05, 'epoch': 0.14}) +[2026-07-26 21:08:45,477][starVLA.training.train_starvla][INFO] - Step 1168, Loss: {'train/loss': 0.4931830167770386, 'train/grad_norm_pre_clip': 5.1968183517456055, 'timing/data': 0.00018379278481006622, 'timing/model': 0.46924071898683906, 'learning_rate/action_model': 8.764403177023435e-05, 'learning_rate/action_query_proj': 8.764403177023435e-05, 'learning_rate/base': 2.191100794255859e-05, 'epoch': 0.14}) +[2026-07-26 21:08:51,013][starVLA.training.train_starvla][INFO] - Step 1169, Loss: {'train/loss': 0.34994128346443176, 'train/grad_norm_pre_clip': 5.173801898956299, 'timing/data': 0.00017946725711226463, 'timing/model': 0.4590160478837788, 'learning_rate/action_model': 8.762382546270799e-05, 'learning_rate/action_query_proj': 8.762382546270799e-05, 'learning_rate/base': 2.1905956365676998e-05, 'epoch': 0.14}) +[2026-07-26 21:08:56,544][starVLA.training.train_starvla][INFO] - Step 1170, Loss: {'train/loss': 0.38137710094451904, 'train/grad_norm_pre_clip': 2.8816771507263184, 'timing/data': 0.0001746579073369503, 'timing/model': 0.45865244185552, 'learning_rate/action_model': 8.760360509145949e-05, 'learning_rate/action_query_proj': 8.760360509145949e-05, 'learning_rate/base': 2.1900901272864873e-05, 'epoch': 0.14}) +[2026-07-26 21:09:02,110][starVLA.training.train_starvla][INFO] - Step 1171, Loss: {'train/loss': 0.44308149814605713, 'train/grad_norm_pre_clip': 4.447658061981201, 'timing/data': 0.00018813880160450935, 'timing/model': 0.45854128524661064, 'learning_rate/action_model': 8.758337066447157e-05, 'learning_rate/action_query_proj': 8.758337066447157e-05, 'learning_rate/base': 2.1895842666117893e-05, 'epoch': 0.14}) +[2026-07-26 21:09:07,647][starVLA.training.train_starvla][INFO] - Step 1172, Loss: {'train/loss': 0.34260573983192444, 'train/grad_norm_pre_clip': 2.9523515701293945, 'timing/data': 0.00017718086019158363, 'timing/model': 0.471777425147593, 'learning_rate/action_model': 8.756312218973243e-05, 'learning_rate/action_query_proj': 8.756312218973243e-05, 'learning_rate/base': 2.1890780547433107e-05, 'epoch': 0.14}) +[2026-07-26 21:09:13,403][starVLA.training.train_starvla][INFO] - Step 1173, Loss: {'train/loss': 0.5480058193206787, 'train/grad_norm_pre_clip': 5.284971714019775, 'timing/data': 0.00017364602535963058, 'timing/model': 0.47749666310846806, 'learning_rate/action_model': 8.754285967523586e-05, 'learning_rate/action_query_proj': 8.754285967523586e-05, 'learning_rate/base': 2.1885714918808965e-05, 'epoch': 0.14}) +[2026-07-26 21:09:18,961][starVLA.training.train_starvla][INFO] - Step 1174, Loss: {'train/loss': 0.3474012017250061, 'train/grad_norm_pre_clip': 2.5107855796813965, 'timing/data': 0.0001770220696926117, 'timing/model': 0.47727310191839933, 'learning_rate/action_model': 8.75225831289812e-05, 'learning_rate/action_query_proj': 8.75225831289812e-05, 'learning_rate/base': 2.18806457822453e-05, 'epoch': 0.14}) +[2026-07-26 21:09:24,507][starVLA.training.train_starvla][INFO] - Step 1175, Loss: {'train/loss': 0.38604772090911865, 'train/grad_norm_pre_clip': 6.267544269561768, 'timing/data': 0.00018424121662974358, 'timing/model': 0.4740530583076179, 'learning_rate/action_model': 8.750229255897328e-05, 'learning_rate/action_query_proj': 8.750229255897328e-05, 'learning_rate/base': 2.187557313974332e-05, 'epoch': 0.14}) +[2026-07-26 21:09:30,055][starVLA.training.train_starvla][INFO] - Step 1176, Loss: {'train/loss': 0.5466275811195374, 'train/grad_norm_pre_clip': 5.906582832336426, 'timing/data': 0.00017847586423158646, 'timing/model': 0.47320799389854074, 'learning_rate/action_model': 8.74819879732225e-05, 'learning_rate/action_query_proj': 8.74819879732225e-05, 'learning_rate/base': 2.1870496993305626e-05, 'epoch': 0.14}) +[2026-07-26 21:09:35,600][starVLA.training.train_starvla][INFO] - Step 1177, Loss: {'train/loss': 0.41669946908950806, 'train/grad_norm_pre_clip': 5.783977508544922, 'timing/data': 0.0001703370362520218, 'timing/model': 0.47309158788993955, 'learning_rate/action_model': 8.74616693797448e-05, 'learning_rate/action_query_proj': 8.74616693797448e-05, 'learning_rate/base': 2.18654173449362e-05, 'epoch': 0.14}) +[2026-07-26 21:09:41,166][starVLA.training.train_starvla][INFO] - Step 1178, Loss: {'train/loss': 0.44257962703704834, 'train/grad_norm_pre_clip': 3.949960470199585, 'timing/data': 0.00018057413399219513, 'timing/model': 0.4711846779100597, 'learning_rate/action_model': 8.744133678656162e-05, 'learning_rate/action_query_proj': 8.744133678656162e-05, 'learning_rate/base': 2.1860334196640404e-05, 'epoch': 0.14}) +[2026-07-26 21:09:46,724][starVLA.training.train_starvla][INFO] - Step 1179, Loss: {'train/loss': 0.45302724838256836, 'train/grad_norm_pre_clip': 4.8702874183654785, 'timing/data': 0.0001778639853000641, 'timing/model': 0.472447759937495, 'learning_rate/action_model': 8.742099020169997e-05, 'learning_rate/action_query_proj': 8.742099020169997e-05, 'learning_rate/base': 2.1855247550424993e-05, 'epoch': 0.14}) +[2026-07-26 21:09:52,270][starVLA.training.train_starvla][INFO] - Step 1180, Loss: {'train/loss': 0.5121636986732483, 'train/grad_norm_pre_clip': 4.666510105133057, 'timing/data': 0.0001723538152873516, 'timing/model': 0.4723027949221432, 'learning_rate/action_model': 8.740062963319236e-05, 'learning_rate/action_query_proj': 8.740062963319236e-05, 'learning_rate/base': 2.185015740829809e-05, 'epoch': 0.14}) +[2026-07-26 21:09:57,832][starVLA.training.train_starvla][INFO] - Step 1181, Loss: {'train/loss': 0.46073442697525024, 'train/grad_norm_pre_clip': 4.013531684875488, 'timing/data': 0.00017434172332286835, 'timing/model': 0.4705999200232327, 'learning_rate/action_model': 8.73802550890768e-05, 'learning_rate/action_query_proj': 8.73802550890768e-05, 'learning_rate/base': 2.18450637722692e-05, 'epoch': 0.14}) +[2026-07-26 21:10:03,663][starVLA.training.train_starvla][INFO] - Step 1182, Loss: {'train/loss': 0.41038545966148376, 'train/grad_norm_pre_clip': 4.709507942199707, 'timing/data': 0.00017439434304833412, 'timing/model': 0.6525088539347053, 'learning_rate/action_model': 8.735986657739684e-05, 'learning_rate/action_query_proj': 8.735986657739684e-05, 'learning_rate/base': 2.183996664434921e-05, 'epoch': 0.14}) +[2026-07-26 21:10:09,196][starVLA.training.train_starvla][INFO] - Step 1183, Loss: {'train/loss': 0.2475528120994568, 'train/grad_norm_pre_clip': 4.254112243652344, 'timing/data': 0.0001784898340702057, 'timing/model': 0.4613325600512326, 'learning_rate/action_model': 8.733946410620155e-05, 'learning_rate/action_query_proj': 8.733946410620155e-05, 'learning_rate/base': 2.1834866026550387e-05, 'epoch': 0.14}) +[2026-07-26 21:10:14,731][starVLA.training.train_starvla][INFO] - Step 1184, Loss: {'train/loss': 0.3495163917541504, 'train/grad_norm_pre_clip': 3.4955220222473145, 'timing/data': 0.00016622524708509445, 'timing/model': 0.46268027974292636, 'learning_rate/action_model': 8.731904768354549e-05, 'learning_rate/action_query_proj': 8.731904768354549e-05, 'learning_rate/base': 2.1829761920886372e-05, 'epoch': 0.14}) +[2026-07-26 21:10:20,262][starVLA.training.train_starvla][INFO] - Step 1185, Loss: {'train/loss': 0.3660782277584076, 'train/grad_norm_pre_clip': 4.719862937927246, 'timing/data': 0.00016458891332149506, 'timing/model': 0.4625433050096035, 'learning_rate/action_model': 8.729861731748877e-05, 'learning_rate/action_query_proj': 8.729861731748877e-05, 'learning_rate/base': 2.1824654329372192e-05, 'epoch': 0.14}) +[2026-07-26 21:10:25,770][starVLA.training.train_starvla][INFO] - Step 1186, Loss: {'train/loss': 0.4288941025733948, 'train/grad_norm_pre_clip': 3.7395577430725098, 'timing/data': 0.00016673095524311066, 'timing/model': 0.4607869409956038, 'learning_rate/action_model': 8.727817301609695e-05, 'learning_rate/action_query_proj': 8.727817301609695e-05, 'learning_rate/base': 2.1819543254024237e-05, 'epoch': 0.14}) +[2026-07-26 21:10:31,283][starVLA.training.train_starvla][INFO] - Step 1187, Loss: {'train/loss': 0.33535656332969666, 'train/grad_norm_pre_clip': 2.848670721054077, 'timing/data': 0.00017023971304297447, 'timing/model': 0.4582712100818753, 'learning_rate/action_model': 8.725771478744112e-05, 'learning_rate/action_query_proj': 8.725771478744112e-05, 'learning_rate/base': 2.181442869686028e-05, 'epoch': 0.14}) +[2026-07-26 21:10:36,812][starVLA.training.train_starvla][INFO] - Step 1188, Loss: {'train/loss': 0.5859885215759277, 'train/grad_norm_pre_clip': 5.056640625, 'timing/data': 0.0001753130927681923, 'timing/model': 0.4610273758880794, 'learning_rate/action_model': 8.723724263959785e-05, 'learning_rate/action_query_proj': 8.723724263959785e-05, 'learning_rate/base': 2.180931065989946e-05, 'epoch': 0.14}) +[2026-07-26 21:10:42,324][starVLA.training.train_starvla][INFO] - Step 1189, Loss: {'train/loss': 0.45421406626701355, 'train/grad_norm_pre_clip': 4.367008686065674, 'timing/data': 0.0001764572225511074, 'timing/model': 0.4576040981337428, 'learning_rate/action_model': 8.721675658064925e-05, 'learning_rate/action_query_proj': 8.721675658064925e-05, 'learning_rate/base': 2.180418914516231e-05, 'epoch': 0.14}) +[2026-07-26 21:10:47,861][starVLA.training.train_starvla][INFO] - Step 1190, Loss: {'train/loss': 0.34538498520851135, 'train/grad_norm_pre_clip': 3.179083824157715, 'timing/data': 0.00016624713316559792, 'timing/model': 0.45874560298398137, 'learning_rate/action_model': 8.71962566186829e-05, 'learning_rate/action_query_proj': 8.71962566186829e-05, 'learning_rate/base': 2.1799064154670724e-05, 'epoch': 0.14}) +[2026-07-26 21:10:53,400][starVLA.training.train_starvla][INFO] - Step 1191, Loss: {'train/loss': 0.41087350249290466, 'train/grad_norm_pre_clip': 3.3700573444366455, 'timing/data': 0.00016969768330454826, 'timing/model': 0.45811316510662436, 'learning_rate/action_model': 8.71757427617918e-05, 'learning_rate/action_query_proj': 8.71757427617918e-05, 'learning_rate/base': 2.179393569044795e-05, 'epoch': 0.14}) +[2026-07-26 21:10:58,948][starVLA.training.train_starvla][INFO] - Step 1192, Loss: {'train/loss': 0.5376790165901184, 'train/grad_norm_pre_clip': 4.668105125427246, 'timing/data': 0.0001704641617834568, 'timing/model': 0.4578417809680104, 'learning_rate/action_model': 8.715521501807457e-05, 'learning_rate/action_query_proj': 8.715521501807457e-05, 'learning_rate/base': 2.1788803754518642e-05, 'epoch': 0.14}) +[2026-07-26 21:11:04,483][starVLA.training.train_starvla][INFO] - Step 1193, Loss: {'train/loss': 0.5564272999763489, 'train/grad_norm_pre_clip': 5.445946216583252, 'timing/data': 0.00016838405281305313, 'timing/model': 0.4567187991924584, 'learning_rate/action_model': 8.713467339563518e-05, 'learning_rate/action_query_proj': 8.713467339563518e-05, 'learning_rate/base': 2.1783668348908794e-05, 'epoch': 0.14}) +[2026-07-26 21:11:10,025][starVLA.training.train_starvla][INFO] - Step 1194, Loss: {'train/loss': 0.5504035949707031, 'train/grad_norm_pre_clip': 4.010425567626953, 'timing/data': 0.0001666788011789322, 'timing/model': 0.4591287951916456, 'learning_rate/action_model': 8.711411790258314e-05, 'learning_rate/action_query_proj': 8.711411790258314e-05, 'learning_rate/base': 2.1778529475645786e-05, 'epoch': 0.14}) +[2026-07-26 21:11:15,562][starVLA.training.train_starvla][INFO] - Step 1195, Loss: {'train/loss': 0.38875502347946167, 'train/grad_norm_pre_clip': 3.243417739868164, 'timing/data': 0.00017117103561758995, 'timing/model': 0.45795934507623315, 'learning_rate/action_model': 8.709354854703348e-05, 'learning_rate/action_query_proj': 8.709354854703348e-05, 'learning_rate/base': 2.177338713675837e-05, 'epoch': 0.14}) +[2026-07-26 21:11:21,113][starVLA.training.train_starvla][INFO] - Step 1196, Loss: {'train/loss': 0.5075548887252808, 'train/grad_norm_pre_clip': 4.711744785308838, 'timing/data': 0.00017517199739813805, 'timing/model': 0.45851863687857985, 'learning_rate/action_model': 8.707296533710663e-05, 'learning_rate/action_query_proj': 8.707296533710663e-05, 'learning_rate/base': 2.176824133427666e-05, 'epoch': 0.15}) +[2026-07-26 21:11:26,658][starVLA.training.train_starvla][INFO] - Step 1197, Loss: {'train/loss': 0.5426375865936279, 'train/grad_norm_pre_clip': 5.02165412902832, 'timing/data': 0.00016787415370345116, 'timing/model': 0.45696441596373916, 'learning_rate/action_model': 8.705236828092849e-05, 'learning_rate/action_query_proj': 8.705236828092849e-05, 'learning_rate/base': 2.1763092070232123e-05, 'epoch': 0.15}) +[2026-07-26 21:11:32,199][starVLA.training.train_starvla][INFO] - Step 1198, Loss: {'train/loss': 0.4332035779953003, 'train/grad_norm_pre_clip': 3.0030384063720703, 'timing/data': 0.00017743930220603943, 'timing/model': 0.4578816876746714, 'learning_rate/action_model': 8.70317573866305e-05, 'learning_rate/action_query_proj': 8.70317573866305e-05, 'learning_rate/base': 2.1757939346657626e-05, 'epoch': 0.15}) +[2026-07-26 21:11:37,742][starVLA.training.train_starvla][INFO] - Step 1199, Loss: {'train/loss': 0.4617270529270172, 'train/grad_norm_pre_clip': 3.3066718578338623, 'timing/data': 0.00017040781676769257, 'timing/model': 0.45880521833896637, 'learning_rate/action_model': 8.701113266234949e-05, 'learning_rate/action_query_proj': 8.701113266234949e-05, 'learning_rate/base': 2.1752783165587372e-05, 'epoch': 0.15}) +[2026-07-26 21:11:43,267][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 1200 +[2026-07-26 21:11:43,268][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 1200 +[2026-07-26 21:11:43,269][starVLA.training.train_starvla][INFO] - Step 1200, Loss: {'train/loss': 0.3741632401943207, 'train/grad_norm_pre_clip': 3.934730291366577, 'timing/data': 0.00016834912821650505, 'timing/model': 0.4569156849756837, 'learning_rate/action_model': 8.699049411622776e-05, 'learning_rate/action_query_proj': 8.699049411622776e-05, 'learning_rate/base': 2.174762352905694e-05, 'epoch': 0.15}) +[2026-07-26 21:11:48,810][starVLA.training.train_starvla][INFO] - Step 1201, Loss: {'train/loss': 0.3165486752986908, 'train/grad_norm_pre_clip': 3.2297351360321045, 'timing/data': 0.00016884785145521164, 'timing/model': 0.4587973183952272, 'learning_rate/action_model': 8.69698417564131e-05, 'learning_rate/action_query_proj': 8.69698417564131e-05, 'learning_rate/base': 2.1742460439103274e-05, 'epoch': 0.15}) +[2026-07-26 21:11:54,348][starVLA.training.train_starvla][INFO] - Step 1202, Loss: {'train/loss': 0.3909187912940979, 'train/grad_norm_pre_clip': 3.976025104522705, 'timing/data': 0.00017059314996004105, 'timing/model': 0.4589609960094094, 'learning_rate/action_model': 8.694917559105873e-05, 'learning_rate/action_query_proj': 8.694917559105873e-05, 'learning_rate/base': 2.173729389776468e-05, 'epoch': 0.15}) +[2026-07-26 21:11:59,897][starVLA.training.train_starvla][INFO] - Step 1203, Loss: {'train/loss': 0.33626165986061096, 'train/grad_norm_pre_clip': 3.850226879119873, 'timing/data': 0.0001740916632115841, 'timing/model': 0.45972183626145124, 'learning_rate/action_model': 8.692849562832331e-05, 'learning_rate/action_query_proj': 8.692849562832331e-05, 'learning_rate/base': 2.173212390708083e-05, 'epoch': 0.15}) +[2026-07-26 21:12:05,499][starVLA.training.train_starvla][INFO] - Step 1204, Loss: {'train/loss': 0.3928745687007904, 'train/grad_norm_pre_clip': 3.091398239135742, 'timing/data': 0.00017374195158481598, 'timing/model': 0.493248478975147, 'learning_rate/action_model': 8.6907801876371e-05, 'learning_rate/action_query_proj': 8.6907801876371e-05, 'learning_rate/base': 2.172695046909275e-05, 'epoch': 0.15}) +[2026-07-26 21:12:11,049][starVLA.training.train_starvla][INFO] - Step 1205, Loss: {'train/loss': 0.42205747961997986, 'train/grad_norm_pre_clip': 4.116116046905518, 'timing/data': 0.000246529933065176, 'timing/model': 0.45807383907958865, 'learning_rate/action_model': 8.688709434337134e-05, 'learning_rate/action_query_proj': 8.688709434337134e-05, 'learning_rate/base': 2.1721773585842835e-05, 'epoch': 0.15}) +[2026-07-26 21:12:16,578][starVLA.training.train_starvla][INFO] - Step 1206, Loss: {'train/loss': 0.4456266462802887, 'train/grad_norm_pre_clip': 3.696434497833252, 'timing/data': 0.00018536485731601715, 'timing/model': 0.45838401606306434, 'learning_rate/action_model': 8.686637303749933e-05, 'learning_rate/action_query_proj': 8.686637303749933e-05, 'learning_rate/base': 2.1716593259374833e-05, 'epoch': 0.15}) +[2026-07-26 21:12:22,113][starVLA.training.train_starvla][INFO] - Step 1207, Loss: {'train/loss': 0.25664716958999634, 'train/grad_norm_pre_clip': 2.691321849822998, 'timing/data': 0.00017007067799568176, 'timing/model': 0.45819871220737696, 'learning_rate/action_model': 8.684563796693544e-05, 'learning_rate/action_query_proj': 8.684563796693544e-05, 'learning_rate/base': 2.171140949173386e-05, 'epoch': 0.15}) +[2026-07-26 21:12:27,644][starVLA.training.train_starvla][INFO] - Step 1208, Loss: {'train/loss': 0.46025922894477844, 'train/grad_norm_pre_clip': 3.257934093475342, 'timing/data': 0.00018332060426473618, 'timing/model': 0.458481898996979, 'learning_rate/action_model': 8.68248891398655e-05, 'learning_rate/action_query_proj': 8.68248891398655e-05, 'learning_rate/base': 2.1706222284966375e-05, 'epoch': 0.15}) +[2026-07-26 21:12:33,179][starVLA.training.train_starvla][INFO] - Step 1209, Loss: {'train/loss': 0.4346911311149597, 'train/grad_norm_pre_clip': 4.416379928588867, 'timing/data': 0.00016785692423582077, 'timing/model': 0.45876577869057655, 'learning_rate/action_model': 8.680412656448086e-05, 'learning_rate/action_query_proj': 8.680412656448086e-05, 'learning_rate/base': 2.1701031641120216e-05, 'epoch': 0.15}) +[2026-07-26 21:12:38,724][starVLA.training.train_starvla][INFO] - Step 1210, Loss: {'train/loss': 0.40066611766815186, 'train/grad_norm_pre_clip': 3.81870698928833, 'timing/data': 0.00017242087051272392, 'timing/model': 0.45797021267935634, 'learning_rate/action_model': 8.678335024897824e-05, 'learning_rate/action_query_proj': 8.678335024897824e-05, 'learning_rate/base': 2.169583756224456e-05, 'epoch': 0.15}) +[2026-07-26 21:12:44,251][starVLA.training.train_starvla][INFO] - Step 1211, Loss: {'train/loss': 0.40450403094291687, 'train/grad_norm_pre_clip': 3.464843988418579, 'timing/data': 0.00017265928909182549, 'timing/model': 0.4573394521139562, 'learning_rate/action_model': 8.676256020155982e-05, 'learning_rate/action_query_proj': 8.676256020155982e-05, 'learning_rate/base': 2.1690640050389954e-05, 'epoch': 0.15}) +[2026-07-26 21:12:49,772][starVLA.training.train_starvla][INFO] - Step 1212, Loss: {'train/loss': 0.42354702949523926, 'train/grad_norm_pre_clip': 4.571228504180908, 'timing/data': 0.00016907509416341782, 'timing/model': 0.4585240841843188, 'learning_rate/action_model': 8.674175643043314e-05, 'learning_rate/action_query_proj': 8.674175643043314e-05, 'learning_rate/base': 2.1685439107608286e-05, 'epoch': 0.15}) +[2026-07-26 21:12:55,295][starVLA.training.train_starvla][INFO] - Step 1213, Loss: {'train/loss': 0.44929394125938416, 'train/grad_norm_pre_clip': 3.758378744125366, 'timing/data': 0.00017206091433763504, 'timing/model': 0.45720832608640194, 'learning_rate/action_model': 8.672093894381125e-05, 'learning_rate/action_query_proj': 8.672093894381125e-05, 'learning_rate/base': 2.1680234735952812e-05, 'epoch': 0.15}) +[2026-07-26 21:13:00,819][starVLA.training.train_starvla][INFO] - Step 1214, Loss: {'train/loss': 0.3770529329776764, 'train/grad_norm_pre_clip': 2.5526998043060303, 'timing/data': 0.00024168193340301514, 'timing/model': 0.4585452270694077, 'learning_rate/action_model': 8.670010774991251e-05, 'learning_rate/action_query_proj': 8.670010774991251e-05, 'learning_rate/base': 2.167502693747813e-05, 'epoch': 0.15}) +[2026-07-26 21:13:06,346][starVLA.training.train_starvla][INFO] - Step 1215, Loss: {'train/loss': 0.4540404677391052, 'train/grad_norm_pre_clip': 3.105731964111328, 'timing/data': 0.0001760050654411316, 'timing/model': 0.4586708229035139, 'learning_rate/action_model': 8.66792628569608e-05, 'learning_rate/action_query_proj': 8.66792628569608e-05, 'learning_rate/base': 2.16698157142402e-05, 'epoch': 0.15}) +[2026-07-26 21:13:11,913][starVLA.training.train_starvla][INFO] - Step 1216, Loss: {'train/loss': 0.29515305161476135, 'train/grad_norm_pre_clip': 4.771399021148682, 'timing/data': 0.0001731840893626213, 'timing/model': 0.4575985986739397, 'learning_rate/action_model': 8.665840427318532e-05, 'learning_rate/action_query_proj': 8.665840427318532e-05, 'learning_rate/base': 2.166460106829633e-05, 'epoch': 0.15}) +[2026-07-26 21:13:17,508][starVLA.training.train_starvla][INFO] - Step 1217, Loss: {'train/loss': 0.615744411945343, 'train/grad_norm_pre_clip': 6.267367839813232, 'timing/data': 0.00017041480168700218, 'timing/model': 0.45733398804441094, 'learning_rate/action_model': 8.663753200682071e-05, 'learning_rate/action_query_proj': 8.663753200682071e-05, 'learning_rate/base': 2.1659383001705177e-05, 'epoch': 0.15}) +[2026-07-26 21:13:23,085][starVLA.training.train_starvla][INFO] - Step 1218, Loss: {'train/loss': 0.4813538193702698, 'train/grad_norm_pre_clip': 5.6142258644104, 'timing/data': 0.00017013493925333023, 'timing/model': 0.45805643405765295, 'learning_rate/action_model': 8.661664606610702e-05, 'learning_rate/action_query_proj': 8.661664606610702e-05, 'learning_rate/base': 2.1654161516526756e-05, 'epoch': 0.15}) +[2026-07-26 21:13:28,656][starVLA.training.train_starvla][INFO] - Step 1219, Loss: {'train/loss': 0.4438188672065735, 'train/grad_norm_pre_clip': 3.4337878227233887, 'timing/data': 0.0001743687316775322, 'timing/model': 0.458642543759197, 'learning_rate/action_model': 8.659574645928969e-05, 'learning_rate/action_query_proj': 8.659574645928969e-05, 'learning_rate/base': 2.1648936614822423e-05, 'epoch': 0.15}) +[2026-07-26 21:13:34,243][starVLA.training.train_starvla][INFO] - Step 1220, Loss: {'train/loss': 0.5038639903068542, 'train/grad_norm_pre_clip': 7.652440547943115, 'timing/data': 0.00016996590420603752, 'timing/model': 0.4571651089936495, 'learning_rate/action_model': 8.657483319461954e-05, 'learning_rate/action_query_proj': 8.657483319461954e-05, 'learning_rate/base': 2.1643708298654885e-05, 'epoch': 0.15}) +[2026-07-26 21:13:39,829][starVLA.training.train_starvla][INFO] - Step 1221, Loss: {'train/loss': 0.5042536854743958, 'train/grad_norm_pre_clip': 5.581185817718506, 'timing/data': 0.00017237896099686623, 'timing/model': 0.4582705646753311, 'learning_rate/action_model': 8.65539062803528e-05, 'learning_rate/action_query_proj': 8.65539062803528e-05, 'learning_rate/base': 2.16384765700882e-05, 'epoch': 0.15}) +[2026-07-26 21:13:45,404][starVLA.training.train_starvla][INFO] - Step 1222, Loss: {'train/loss': 0.411485493183136, 'train/grad_norm_pre_clip': 3.548438787460327, 'timing/data': 0.0001727081835269928, 'timing/model': 0.4588311817497015, 'learning_rate/action_model': 8.653296572475111e-05, 'learning_rate/action_query_proj': 8.653296572475111e-05, 'learning_rate/base': 2.1633241431187777e-05, 'epoch': 0.15}) +[2026-07-26 21:13:51,000][starVLA.training.train_starvla][INFO] - Step 1223, Loss: {'train/loss': 0.4768461585044861, 'train/grad_norm_pre_clip': 4.8163275718688965, 'timing/data': 0.00017070118337869644, 'timing/model': 0.46309347776696086, 'learning_rate/action_model': 8.651201153608142e-05, 'learning_rate/action_query_proj': 8.651201153608142e-05, 'learning_rate/base': 2.1628002884020354e-05, 'epoch': 0.15}) +[2026-07-26 21:13:56,556][starVLA.training.train_starvla][INFO] - Step 1224, Loss: {'train/loss': 0.4227175712585449, 'train/grad_norm_pre_clip': 5.5888543128967285, 'timing/data': 0.00017932290211319923, 'timing/model': 0.45739894872531295, 'learning_rate/action_model': 8.649104372261617e-05, 'learning_rate/action_query_proj': 8.649104372261617e-05, 'learning_rate/base': 2.1622760930654042e-05, 'epoch': 0.15}) +[2026-07-26 21:14:02,107][starVLA.training.train_starvla][INFO] - Step 1225, Loss: {'train/loss': 0.30959364771842957, 'train/grad_norm_pre_clip': 3.7801268100738525, 'timing/data': 0.0001721791923046112, 'timing/model': 0.4590412420220673, 'learning_rate/action_model': 8.647006229263306e-05, 'learning_rate/action_query_proj': 8.647006229263306e-05, 'learning_rate/base': 2.1617515573158266e-05, 'epoch': 0.15}) +[2026-07-26 21:14:07,647][starVLA.training.train_starvla][INFO] - Step 1226, Loss: {'train/loss': 0.47936245799064636, 'train/grad_norm_pre_clip': 4.476667881011963, 'timing/data': 0.00017849495634436607, 'timing/model': 0.45785458106547594, 'learning_rate/action_model': 8.644906725441528e-05, 'learning_rate/action_query_proj': 8.644906725441528e-05, 'learning_rate/base': 2.161226681360382e-05, 'epoch': 0.15}) +[2026-07-26 21:14:13,187][starVLA.training.train_starvla][INFO] - Step 1227, Loss: {'train/loss': 0.35624098777770996, 'train/grad_norm_pre_clip': 3.7103917598724365, 'timing/data': 0.00024209823459386826, 'timing/model': 0.45713180489838123, 'learning_rate/action_model': 8.64280586162513e-05, 'learning_rate/action_query_proj': 8.64280586162513e-05, 'learning_rate/base': 2.1607014654062826e-05, 'epoch': 0.15}) +[2026-07-26 21:14:18,740][starVLA.training.train_starvla][INFO] - Step 1228, Loss: {'train/loss': 0.35629335045814514, 'train/grad_norm_pre_clip': 5.063233375549316, 'timing/data': 0.00016968371346592903, 'timing/model': 0.4572589839808643, 'learning_rate/action_model': 8.640703638643503e-05, 'learning_rate/action_query_proj': 8.640703638643503e-05, 'learning_rate/base': 2.1601759096608758e-05, 'epoch': 0.15}) +[2026-07-26 21:14:24,301][starVLA.training.train_starvla][INFO] - Step 1229, Loss: {'train/loss': 0.5185204744338989, 'train/grad_norm_pre_clip': 3.6048784255981445, 'timing/data': 0.00017352215945720673, 'timing/model': 0.45835409266874194, 'learning_rate/action_model': 8.638600057326569e-05, 'learning_rate/action_query_proj': 8.638600057326569e-05, 'learning_rate/base': 2.1596500143316422e-05, 'epoch': 0.15}) +[2026-07-26 21:14:29,854][starVLA.training.train_starvla][INFO] - Step 1230, Loss: {'train/loss': 0.4799131751060486, 'train/grad_norm_pre_clip': 3.460094928741455, 'timing/data': 0.00017264112830162048, 'timing/model': 0.4569157329387963, 'learning_rate/action_model': 8.63649511850479e-05, 'learning_rate/action_query_proj': 8.63649511850479e-05, 'learning_rate/base': 2.1591237796261974e-05, 'epoch': 0.15}) +[2026-07-26 21:14:35,404][starVLA.training.train_starvla][INFO] - Step 1231, Loss: {'train/loss': 0.3378523886203766, 'train/grad_norm_pre_clip': 3.2047839164733887, 'timing/data': 0.00017090095207095146, 'timing/model': 0.45867878291755915, 'learning_rate/action_model': 8.63438882300916e-05, 'learning_rate/action_query_proj': 8.63438882300916e-05, 'learning_rate/base': 2.15859720575229e-05, 'epoch': 0.15}) +[2026-07-26 21:14:40,952][starVLA.training.train_starvla][INFO] - Step 1232, Loss: {'train/loss': 0.37403297424316406, 'train/grad_norm_pre_clip': 4.417442321777344, 'timing/data': 0.000170096755027771, 'timing/model': 0.45756527688354254, 'learning_rate/action_model': 8.632281171671215e-05, 'learning_rate/action_query_proj': 8.632281171671215e-05, 'learning_rate/base': 2.1580702929178037e-05, 'epoch': 0.15}) +[2026-07-26 21:14:46,522][starVLA.training.train_starvla][INFO] - Step 1233, Loss: {'train/loss': 0.29681751132011414, 'train/grad_norm_pre_clip': 5.087827682495117, 'timing/data': 0.00016848091036081314, 'timing/model': 0.4572671512141824, 'learning_rate/action_model': 8.630172165323019e-05, 'learning_rate/action_query_proj': 8.630172165323019e-05, 'learning_rate/base': 2.1575430413307547e-05, 'epoch': 0.15}) +[2026-07-26 21:14:52,099][starVLA.training.train_starvla][INFO] - Step 1234, Loss: {'train/loss': 0.4931623339653015, 'train/grad_norm_pre_clip': 5.800286293029785, 'timing/data': 0.0002690856344997883, 'timing/model': 0.4678210821002722, 'learning_rate/action_model': 8.628061804797178e-05, 'learning_rate/action_query_proj': 8.628061804797178e-05, 'learning_rate/base': 2.1570154511992944e-05, 'epoch': 0.15}) +[2026-07-26 21:14:57,926][starVLA.training.train_starvla][INFO] - Step 1235, Loss: {'train/loss': 0.3829668462276459, 'train/grad_norm_pre_clip': 3.5297598838806152, 'timing/data': 0.00017936760559678078, 'timing/model': 0.45766007993370295, 'learning_rate/action_model': 8.625950090926824e-05, 'learning_rate/action_query_proj': 8.625950090926824e-05, 'learning_rate/base': 2.156487522731706e-05, 'epoch': 0.15}) +[2026-07-26 21:15:03,486][starVLA.training.train_starvla][INFO] - Step 1236, Loss: {'train/loss': 0.3735823333263397, 'train/grad_norm_pre_clip': 3.7763636112213135, 'timing/data': 0.0001764749176800251, 'timing/model': 0.4581696237437427, 'learning_rate/action_model': 8.623837024545629e-05, 'learning_rate/action_query_proj': 8.623837024545629e-05, 'learning_rate/base': 2.1559592561364073e-05, 'epoch': 0.15}) +[2026-07-26 21:15:09,068][starVLA.training.train_starvla][INFO] - Step 1237, Loss: {'train/loss': 0.6174337863922119, 'train/grad_norm_pre_clip': 4.976559162139893, 'timing/data': 0.0001778220757842064, 'timing/model': 0.45740401092916727, 'learning_rate/action_model': 8.621722606487803e-05, 'learning_rate/action_query_proj': 8.621722606487803e-05, 'learning_rate/base': 2.1554306516219508e-05, 'epoch': 0.15}) +[2026-07-26 21:15:14,644][starVLA.training.train_starvla][INFO] - Step 1238, Loss: {'train/loss': 0.5852090716362, 'train/grad_norm_pre_clip': 4.396416664123535, 'timing/data': 0.00018004700541496277, 'timing/model': 0.4569654748775065, 'learning_rate/action_model': 8.61960683758808e-05, 'learning_rate/action_query_proj': 8.61960683758808e-05, 'learning_rate/base': 2.15490170939702e-05, 'epoch': 0.15}) +[2026-07-26 21:15:20,196][starVLA.training.train_starvla][INFO] - Step 1239, Loss: {'train/loss': 0.5108342170715332, 'train/grad_norm_pre_clip': 4.311384677886963, 'timing/data': 0.00018055085092782974, 'timing/model': 0.4574794862419367, 'learning_rate/action_model': 8.617489718681734e-05, 'learning_rate/action_query_proj': 8.617489718681734e-05, 'learning_rate/base': 2.1543724296704336e-05, 'epoch': 0.15}) +[2026-07-26 21:15:25,748][starVLA.training.train_starvla][INFO] - Step 1240, Loss: {'train/loss': 0.4723881185054779, 'train/grad_norm_pre_clip': 3.854858636856079, 'timing/data': 0.00018194084987044334, 'timing/model': 0.45788958575576544, 'learning_rate/action_model': 8.615371250604571e-05, 'learning_rate/action_query_proj': 8.615371250604571e-05, 'learning_rate/base': 2.153842812651143e-05, 'epoch': 0.15}) +[2026-07-26 21:15:31,305][starVLA.training.train_starvla][INFO] - Step 1241, Loss: {'train/loss': 0.6289830803871155, 'train/grad_norm_pre_clip': 3.829456090927124, 'timing/data': 0.00016963528469204903, 'timing/model': 0.45642076106742024, 'learning_rate/action_model': 8.613251434192924e-05, 'learning_rate/action_query_proj': 8.613251434192924e-05, 'learning_rate/base': 2.153312858548231e-05, 'epoch': 0.15}) +[2026-07-26 21:15:36,853][starVLA.training.train_starvla][INFO] - Step 1242, Loss: {'train/loss': 0.43601739406585693, 'train/grad_norm_pre_clip': 3.969346523284912, 'timing/data': 0.00018468964844942093, 'timing/model': 0.4582692668773234, 'learning_rate/action_model': 8.611130270283669e-05, 'learning_rate/action_query_proj': 8.611130270283669e-05, 'learning_rate/base': 2.1527825675709172e-05, 'epoch': 0.15}) +[2026-07-26 21:15:42,418][starVLA.training.train_starvla][INFO] - Step 1243, Loss: {'train/loss': 0.3999672532081604, 'train/grad_norm_pre_clip': 4.370663642883301, 'timing/data': 0.00017385371029376984, 'timing/model': 0.4581567901186645, 'learning_rate/action_model': 8.609007759714206e-05, 'learning_rate/action_query_proj': 8.609007759714206e-05, 'learning_rate/base': 2.1522519399285515e-05, 'epoch': 0.15}) +[2026-07-26 21:15:47,984][starVLA.training.train_starvla][INFO] - Step 1244, Loss: {'train/loss': 0.44202911853790283, 'train/grad_norm_pre_clip': 5.105381488800049, 'timing/data': 0.00017793383449316025, 'timing/model': 0.4605753063224256, 'learning_rate/action_model': 8.606883903322466e-05, 'learning_rate/action_query_proj': 8.606883903322466e-05, 'learning_rate/base': 2.1517209758306164e-05, 'epoch': 0.15}) +[2026-07-26 21:15:53,549][starVLA.training.train_starvla][INFO] - Step 1245, Loss: {'train/loss': 0.3097914457321167, 'train/grad_norm_pre_clip': 5.150757789611816, 'timing/data': 0.0001735626719892025, 'timing/model': 0.4579085223376751, 'learning_rate/action_model': 8.604758701946915e-05, 'learning_rate/action_query_proj': 8.604758701946915e-05, 'learning_rate/base': 2.1511896754867288e-05, 'epoch': 0.15}) +[2026-07-26 21:15:59,112][starVLA.training.train_starvla][INFO] - Step 1246, Loss: {'train/loss': 0.591406524181366, 'train/grad_norm_pre_clip': 6.571680068969727, 'timing/data': 0.0001765289343893528, 'timing/model': 0.457657468970865, 'learning_rate/action_model': 8.60263215642655e-05, 'learning_rate/action_query_proj': 8.60263215642655e-05, 'learning_rate/base': 2.1506580391066374e-05, 'epoch': 0.15}) +[2026-07-26 21:16:04,715][starVLA.training.train_starvla][INFO] - Step 1247, Loss: {'train/loss': 0.38666749000549316, 'train/grad_norm_pre_clip': 3.9142746925354004, 'timing/data': 0.0001722630113363266, 'timing/model': 0.45781574910506606, 'learning_rate/action_model': 8.600504267600897e-05, 'learning_rate/action_query_proj': 8.600504267600897e-05, 'learning_rate/base': 2.1501260669002242e-05, 'epoch': 0.15}) +[2026-07-26 21:16:10,297][starVLA.training.train_starvla][INFO] - Step 1248, Loss: {'train/loss': 0.6051545739173889, 'train/grad_norm_pre_clip': 6.76198148727417, 'timing/data': 0.0001814630813896656, 'timing/model': 0.4585018320940435, 'learning_rate/action_model': 8.598375036310014e-05, 'learning_rate/action_query_proj': 8.598375036310014e-05, 'learning_rate/base': 2.1495937590775035e-05, 'epoch': 0.15}) +[2026-07-26 21:16:15,894][starVLA.training.train_starvla][INFO] - Step 1249, Loss: {'train/loss': 0.5379209518432617, 'train/grad_norm_pre_clip': 7.348114490509033, 'timing/data': 0.00017354823648929596, 'timing/model': 0.45724708866328, 'learning_rate/action_model': 8.596244463394486e-05, 'learning_rate/action_query_proj': 8.596244463394486e-05, 'learning_rate/base': 2.1490611158486214e-05, 'epoch': 0.15}) +[2026-07-26 21:16:21,464][starVLA.training.train_starvla][INFO] - Step 1250, Loss: {'train/loss': 0.46331480145454407, 'train/grad_norm_pre_clip': 8.444259643554688, 'timing/data': 0.00017344672232866287, 'timing/model': 0.45726517913863063, 'learning_rate/action_model': 8.594112549695428e-05, 'learning_rate/action_query_proj': 8.594112549695428e-05, 'learning_rate/base': 2.148528137423857e-05, 'epoch': 0.15}) +[2026-07-26 21:16:27,048][starVLA.training.train_starvla][INFO] - Step 1251, Loss: {'train/loss': 0.3229350745677948, 'train/grad_norm_pre_clip': 2.812548875808716, 'timing/data': 0.0001800782047212124, 'timing/model': 0.4574696999043226, 'learning_rate/action_model': 8.591979296054491e-05, 'learning_rate/action_query_proj': 8.591979296054491e-05, 'learning_rate/base': 2.1479948240136228e-05, 'epoch': 0.15}) +[2026-07-26 21:16:32,634][starVLA.training.train_starvla][INFO] - Step 1252, Loss: {'train/loss': 0.4131978452205658, 'train/grad_norm_pre_clip': 4.510601043701172, 'timing/data': 0.00018337275832891464, 'timing/model': 0.4575287336483598, 'learning_rate/action_model': 8.589844703313844e-05, 'learning_rate/action_query_proj': 8.589844703313844e-05, 'learning_rate/base': 2.147461175828461e-05, 'epoch': 0.15}) +[2026-07-26 21:16:38,218][starVLA.training.train_starvla][INFO] - Step 1253, Loss: {'train/loss': 0.5703350901603699, 'train/grad_norm_pre_clip': 4.561155796051025, 'timing/data': 0.00018233060836791992, 'timing/model': 0.45707838609814644, 'learning_rate/action_model': 8.587708772316194e-05, 'learning_rate/action_query_proj': 8.587708772316194e-05, 'learning_rate/base': 2.1469271930790484e-05, 'epoch': 0.15}) +[2026-07-26 21:16:43,817][starVLA.training.train_starvla][INFO] - Step 1254, Loss: {'train/loss': 0.49610066413879395, 'train/grad_norm_pre_clip': 5.261361122131348, 'timing/data': 0.00018362002447247505, 'timing/model': 0.47173733077943325, 'learning_rate/action_model': 8.58557150390477e-05, 'learning_rate/action_query_proj': 8.58557150390477e-05, 'learning_rate/base': 2.1463928759761926e-05, 'epoch': 0.15}) +[2026-07-26 21:16:49,407][starVLA.training.train_starvla][INFO] - Step 1255, Loss: {'train/loss': 0.4586200416088104, 'train/grad_norm_pre_clip': 5.751350402832031, 'timing/data': 0.00019571511074900627, 'timing/model': 0.46023889631032944, 'learning_rate/action_model': 8.583432898923335e-05, 'learning_rate/action_query_proj': 8.583432898923335e-05, 'learning_rate/base': 2.1458582247308337e-05, 'epoch': 0.15}) +[2026-07-26 21:16:54,989][starVLA.training.train_starvla][INFO] - Step 1256, Loss: {'train/loss': 0.39759528636932373, 'train/grad_norm_pre_clip': 5.9151692390441895, 'timing/data': 0.0001678522676229477, 'timing/model': 0.4614137033931911, 'learning_rate/action_model': 8.581292958216175e-05, 'learning_rate/action_query_proj': 8.581292958216175e-05, 'learning_rate/base': 2.1453232395540436e-05, 'epoch': 0.15}) +[2026-07-26 21:17:00,605][starVLA.training.train_starvla][INFO] - Step 1257, Loss: {'train/loss': 0.4322744607925415, 'train/grad_norm_pre_clip': 6.070643901824951, 'timing/data': 0.0001718602143228054, 'timing/model': 0.45722738094627857, 'learning_rate/action_model': 8.579151682628104e-05, 'learning_rate/action_query_proj': 8.579151682628104e-05, 'learning_rate/base': 2.144787920657026e-05, 'epoch': 0.15}) +[2026-07-26 21:17:06,184][starVLA.training.train_starvla][INFO] - Step 1258, Loss: {'train/loss': 0.5545583367347717, 'train/grad_norm_pre_clip': 6.302320957183838, 'timing/data': 0.00017923396080732346, 'timing/model': 0.45843383111059666, 'learning_rate/action_model': 8.577009073004464e-05, 'learning_rate/action_query_proj': 8.577009073004464e-05, 'learning_rate/base': 2.144252268251116e-05, 'epoch': 0.15}) +[2026-07-26 21:17:11,762][starVLA.training.train_starvla][INFO] - Step 1259, Loss: {'train/loss': 0.4231579303741455, 'train/grad_norm_pre_clip': 4.274067401885986, 'timing/data': 0.00017272494733333588, 'timing/model': 0.45694911293685436, 'learning_rate/action_model': 8.574865130191123e-05, 'learning_rate/action_query_proj': 8.574865130191123e-05, 'learning_rate/base': 2.1437162825477807e-05, 'epoch': 0.15}) +[2026-07-26 21:17:17,332][starVLA.training.train_starvla][INFO] - Step 1260, Loss: {'train/loss': 0.4044872522354126, 'train/grad_norm_pre_clip': 3.3596625328063965, 'timing/data': 0.00017096800729632378, 'timing/model': 0.4576209899969399, 'learning_rate/action_model': 8.572719855034477e-05, 'learning_rate/action_query_proj': 8.572719855034477e-05, 'learning_rate/base': 2.1431799637586193e-05, 'epoch': 0.15}) +[2026-07-26 21:17:22,877][starVLA.training.train_starvla][INFO] - Step 1261, Loss: {'train/loss': 0.4528115689754486, 'train/grad_norm_pre_clip': 6.674079418182373, 'timing/data': 0.0001715286634862423, 'timing/model': 0.45767922373488545, 'learning_rate/action_model': 8.570573248381445e-05, 'learning_rate/action_query_proj': 8.570573248381445e-05, 'learning_rate/base': 2.1426433120953614e-05, 'epoch': 0.15}) +[2026-07-26 21:17:28,432][starVLA.training.train_starvla][INFO] - Step 1262, Loss: {'train/loss': 0.5110308527946472, 'train/grad_norm_pre_clip': 7.1567463874816895, 'timing/data': 0.00017117196694016457, 'timing/model': 0.4576965728774667, 'learning_rate/action_model': 8.568425311079475e-05, 'learning_rate/action_query_proj': 8.568425311079475e-05, 'learning_rate/base': 2.1421063277698687e-05, 'epoch': 0.15}) +[2026-07-26 21:17:33,992][starVLA.training.train_starvla][INFO] - Step 1263, Loss: {'train/loss': 0.5216255187988281, 'train/grad_norm_pre_clip': 8.114669799804688, 'timing/data': 0.00016646180301904678, 'timing/model': 0.45885506412014365, 'learning_rate/action_model': 8.566276043976536e-05, 'learning_rate/action_query_proj': 8.566276043976536e-05, 'learning_rate/base': 2.141569010994134e-05, 'epoch': 0.15}) +[2026-07-26 21:17:39,566][starVLA.training.train_starvla][INFO] - Step 1264, Loss: {'train/loss': 0.4833879768848419, 'train/grad_norm_pre_clip': 4.4769697189331055, 'timing/data': 0.00017293402925133705, 'timing/model': 0.4590229280292988, 'learning_rate/action_model': 8.564125447921129e-05, 'learning_rate/action_query_proj': 8.564125447921129e-05, 'learning_rate/base': 2.1410313619802823e-05, 'epoch': 0.15}) +[2026-07-26 21:17:45,112][starVLA.training.train_starvla][INFO] - Step 1265, Loss: {'train/loss': 0.5229105353355408, 'train/grad_norm_pre_clip': 3.472094774246216, 'timing/data': 0.00016965623944997787, 'timing/model': 0.45893892692402005, 'learning_rate/action_model': 8.56197352376227e-05, 'learning_rate/action_query_proj': 8.56197352376227e-05, 'learning_rate/base': 2.1404933809405676e-05, 'epoch': 0.15}) +[2026-07-26 21:17:50,893][starVLA.training.train_starvla][INFO] - Step 1266, Loss: {'train/loss': 0.3420816659927368, 'train/grad_norm_pre_clip': 3.1364786624908447, 'timing/data': 0.00017100665718317032, 'timing/model': 0.46684753987938166, 'learning_rate/action_model': 8.55982027234951e-05, 'learning_rate/action_query_proj': 8.55982027234951e-05, 'learning_rate/base': 2.1399550680873775e-05, 'epoch': 0.15}) +[2026-07-26 21:17:56,544][starVLA.training.train_starvla][INFO] - Step 1267, Loss: {'train/loss': 0.4656662046909332, 'train/grad_norm_pre_clip': 5.626478672027588, 'timing/data': 0.00017646094784140587, 'timing/model': 0.47818822087720037, 'learning_rate/action_model': 8.557665694532913e-05, 'learning_rate/action_query_proj': 8.557665694532913e-05, 'learning_rate/base': 2.1394164236332283e-05, 'epoch': 0.15}) +[2026-07-26 21:18:02,218][starVLA.training.train_starvla][INFO] - Step 1268, Loss: {'train/loss': 0.45249873399734497, 'train/grad_norm_pre_clip': 6.397235870361328, 'timing/data': 0.00018145889043807983, 'timing/model': 0.4721786887384951, 'learning_rate/action_model': 8.555509791163078e-05, 'learning_rate/action_query_proj': 8.555509791163078e-05, 'learning_rate/base': 2.1388774477907695e-05, 'epoch': 0.15}) +[2026-07-26 21:18:07,814][starVLA.training.train_starvla][INFO] - Step 1269, Loss: {'train/loss': 0.37673601508140564, 'train/grad_norm_pre_clip': 4.679316520690918, 'timing/data': 0.00017465511336922646, 'timing/model': 0.4760949849151075, 'learning_rate/action_model': 8.553352563091116e-05, 'learning_rate/action_query_proj': 8.553352563091116e-05, 'learning_rate/base': 2.138338140772779e-05, 'epoch': 0.15}) +[2026-07-26 21:18:13,425][starVLA.training.train_starvla][INFO] - Step 1270, Loss: {'train/loss': 0.4600452780723572, 'train/grad_norm_pre_clip': 6.436844348907471, 'timing/data': 0.0001767450012266636, 'timing/model': 0.46088039595633745, 'learning_rate/action_model': 8.55119401116867e-05, 'learning_rate/action_query_proj': 8.55119401116867e-05, 'learning_rate/base': 2.1377985027921675e-05, 'epoch': 0.15}) +[2026-07-26 21:18:19,034][starVLA.training.train_starvla][INFO] - Step 1271, Loss: {'train/loss': 0.48657435178756714, 'train/grad_norm_pre_clip': 5.280015468597412, 'timing/data': 0.00017487211152911186, 'timing/model': 0.4715446992777288, 'learning_rate/action_model': 8.549034136247901e-05, 'learning_rate/action_query_proj': 8.549034136247901e-05, 'learning_rate/base': 2.1372585340619753e-05, 'epoch': 0.15}) +[2026-07-26 21:18:24,685][starVLA.training.train_starvla][INFO] - Step 1272, Loss: {'train/loss': 0.49382391571998596, 'train/grad_norm_pre_clip': 4.238423824310303, 'timing/data': 0.00018627382814884186, 'timing/model': 0.4703984959051013, 'learning_rate/action_model': 8.546872939181492e-05, 'learning_rate/action_query_proj': 8.546872939181492e-05, 'learning_rate/base': 2.136718234795373e-05, 'epoch': 0.15}) +[2026-07-26 21:18:30,294][starVLA.training.train_starvla][INFO] - Step 1273, Loss: {'train/loss': 0.42371731996536255, 'train/grad_norm_pre_clip': 4.798404693603516, 'timing/data': 0.00017796875908970833, 'timing/model': 0.46807669196277857, 'learning_rate/action_model': 8.544710420822653e-05, 'learning_rate/action_query_proj': 8.544710420822653e-05, 'learning_rate/base': 2.1361776052056633e-05, 'epoch': 0.15}) +[2026-07-26 21:18:35,889][starVLA.training.train_starvla][INFO] - Step 1274, Loss: {'train/loss': 0.4549334645271301, 'train/grad_norm_pre_clip': 5.560477256774902, 'timing/data': 0.0001752469688653946, 'timing/model': 0.45882235607132316, 'learning_rate/action_model': 8.542546582025108e-05, 'learning_rate/action_query_proj': 8.542546582025108e-05, 'learning_rate/base': 2.135636645506277e-05, 'epoch': 0.15}) +[2026-07-26 21:18:41,495][starVLA.training.train_starvla][INFO] - Step 1275, Loss: {'train/loss': 0.4855412542819977, 'train/grad_norm_pre_clip': 6.222863674163818, 'timing/data': 0.00017500482499599457, 'timing/model': 0.45739390328526497, 'learning_rate/action_model': 8.54038142364311e-05, 'learning_rate/action_query_proj': 8.54038142364311e-05, 'learning_rate/base': 2.1350953559107774e-05, 'epoch': 0.15}) +[2026-07-26 21:18:47,275][starVLA.training.train_starvla][INFO] - Step 1276, Loss: {'train/loss': 0.39945873618125916, 'train/grad_norm_pre_clip': 4.613713264465332, 'timing/data': 0.00018813740462064743, 'timing/model': 0.6176950894296169, 'learning_rate/action_model': 8.538214946531426e-05, 'learning_rate/action_query_proj': 8.538214946531426e-05, 'learning_rate/base': 2.1345537366328565e-05, 'epoch': 0.15}) +[2026-07-26 21:18:52,864][starVLA.training.train_starvla][INFO] - Step 1277, Loss: {'train/loss': 0.5231313109397888, 'train/grad_norm_pre_clip': 7.3495049476623535, 'timing/data': 0.00018287170678377151, 'timing/model': 0.45735436491668224, 'learning_rate/action_model': 8.53604715154535e-05, 'learning_rate/action_query_proj': 8.53604715154535e-05, 'learning_rate/base': 2.1340117878863374e-05, 'epoch': 0.15}) +[2026-07-26 21:18:58,463][starVLA.training.train_starvla][INFO] - Step 1278, Loss: {'train/loss': 0.4814035892486572, 'train/grad_norm_pre_clip': 5.442375183105469, 'timing/data': 0.00017675478011369705, 'timing/model': 0.45862586703151464, 'learning_rate/action_model': 8.53387803954069e-05, 'learning_rate/action_query_proj': 8.53387803954069e-05, 'learning_rate/base': 2.1334695098851724e-05, 'epoch': 0.16}) +[2026-07-26 21:19:04,094][starVLA.training.train_starvla][INFO] - Step 1279, Loss: {'train/loss': 0.4123707711696625, 'train/grad_norm_pre_clip': 7.096485614776611, 'timing/data': 0.00022907089442014694, 'timing/model': 0.47024098690599203, 'learning_rate/action_model': 8.531707611373776e-05, 'learning_rate/action_query_proj': 8.531707611373776e-05, 'learning_rate/base': 2.132926902843444e-05, 'epoch': 0.16}) +[2026-07-26 21:19:09,729][starVLA.training.train_starvla][INFO] - Step 1280, Loss: {'train/loss': 0.46597957611083984, 'train/grad_norm_pre_clip': 4.506432056427002, 'timing/data': 0.00017641205340623856, 'timing/model': 0.46947132190689445, 'learning_rate/action_model': 8.529535867901463e-05, 'learning_rate/action_query_proj': 8.529535867901463e-05, 'learning_rate/base': 2.1323839669753658e-05, 'epoch': 0.16}) +[2026-07-26 21:19:15,349][starVLA.training.train_starvla][INFO] - Step 1281, Loss: {'train/loss': 0.43201661109924316, 'train/grad_norm_pre_clip': 4.429759502410889, 'timing/data': 0.0001802169717848301, 'timing/model': 0.45944866724312305, 'learning_rate/action_model': 8.527362809981121e-05, 'learning_rate/action_query_proj': 8.527362809981121e-05, 'learning_rate/base': 2.1318407024952803e-05, 'epoch': 0.16}) +[2026-07-26 21:19:20,954][starVLA.training.train_starvla][INFO] - Step 1282, Loss: {'train/loss': 0.35588809847831726, 'train/grad_norm_pre_clip': 2.870100975036621, 'timing/data': 0.00017196033149957657, 'timing/model': 0.45889768516644835, 'learning_rate/action_model': 8.525188438470636e-05, 'learning_rate/action_query_proj': 8.525188438470636e-05, 'learning_rate/base': 2.131297109617659e-05, 'epoch': 0.16}) +[2026-07-26 21:19:26,560][starVLA.training.train_starvla][INFO] - Step 1283, Loss: {'train/loss': 0.4026115834712982, 'train/grad_norm_pre_clip': 4.878795146942139, 'timing/data': 0.00017357338219881058, 'timing/model': 0.45813414826989174, 'learning_rate/action_model': 8.523012754228416e-05, 'learning_rate/action_query_proj': 8.523012754228416e-05, 'learning_rate/base': 2.130753188557104e-05, 'epoch': 0.16}) +[2026-07-26 21:19:32,710][starVLA.training.train_starvla][INFO] - Step 1284, Loss: {'train/loss': 0.45334628224372864, 'train/grad_norm_pre_clip': 4.512337684631348, 'timing/data': 0.0001717819832265377, 'timing/model': 0.4581438312307, 'learning_rate/action_model': 8.520835758113385e-05, 'learning_rate/action_query_proj': 8.520835758113385e-05, 'learning_rate/base': 2.1302089395283463e-05, 'epoch': 0.16}) +[2026-07-26 21:19:38,581][starVLA.training.train_starvla][INFO] - Step 1285, Loss: {'train/loss': 0.45166608691215515, 'train/grad_norm_pre_clip': 5.008653163909912, 'timing/data': 0.00017321761697530746, 'timing/model': 0.45937418518587947, 'learning_rate/action_model': 8.518657450984991e-05, 'learning_rate/action_query_proj': 8.518657450984991e-05, 'learning_rate/base': 2.1296643627462478e-05, 'epoch': 0.16}) +[2026-07-26 21:19:44,192][starVLA.training.train_starvla][INFO] - Step 1286, Loss: {'train/loss': 0.4155532121658325, 'train/grad_norm_pre_clip': 4.269199848175049, 'timing/data': 0.00017432402819395065, 'timing/model': 0.458388427272439, 'learning_rate/action_model': 8.516477833703192e-05, 'learning_rate/action_query_proj': 8.516477833703192e-05, 'learning_rate/base': 2.129119458425798e-05, 'epoch': 0.16}) +[2026-07-26 21:19:49,786][starVLA.training.train_starvla][INFO] - Step 1287, Loss: {'train/loss': 0.373618483543396, 'train/grad_norm_pre_clip': 2.684422254562378, 'timing/data': 0.00017545511946082115, 'timing/model': 0.45808228477835655, 'learning_rate/action_model': 8.514296907128468e-05, 'learning_rate/action_query_proj': 8.514296907128468e-05, 'learning_rate/base': 2.128574226782117e-05, 'epoch': 0.16}) +[2026-07-26 21:19:55,646][starVLA.training.train_starvla][INFO] - Step 1288, Loss: {'train/loss': 0.3149108588695526, 'train/grad_norm_pre_clip': 3.321753740310669, 'timing/data': 0.0001742839813232422, 'timing/model': 0.459678762126714, 'learning_rate/action_model': 8.512114672121813e-05, 'learning_rate/action_query_proj': 8.512114672121813e-05, 'learning_rate/base': 2.1280286680304532e-05, 'epoch': 0.16}) +[2026-07-26 21:20:01,273][starVLA.training.train_starvla][INFO] - Step 1289, Loss: {'train/loss': 0.4320352375507355, 'train/grad_norm_pre_clip': 4.121015548706055, 'timing/data': 0.0001851213164627552, 'timing/model': 0.4586752587929368, 'learning_rate/action_model': 8.509931129544739e-05, 'learning_rate/action_query_proj': 8.509931129544739e-05, 'learning_rate/base': 2.1274827823861848e-05, 'epoch': 0.16}) +[2026-07-26 21:20:06,875][starVLA.training.train_starvla][INFO] - Step 1290, Loss: {'train/loss': 0.4263142943382263, 'train/grad_norm_pre_clip': 3.6950337886810303, 'timing/data': 0.000176349189132452, 'timing/model': 0.4584045512601733, 'learning_rate/action_model': 8.507746280259273e-05, 'learning_rate/action_query_proj': 8.507746280259273e-05, 'learning_rate/base': 2.1269365700648182e-05, 'epoch': 0.16}) +[2026-07-26 21:20:12,480][starVLA.training.train_starvla][INFO] - Step 1291, Loss: {'train/loss': 0.4205324947834015, 'train/grad_norm_pre_clip': 5.13672399520874, 'timing/data': 0.000173899345099926, 'timing/model': 0.45760085014626384, 'learning_rate/action_model': 8.505560125127962e-05, 'learning_rate/action_query_proj': 8.505560125127962e-05, 'learning_rate/base': 2.1263900312819904e-05, 'epoch': 0.16}) +[2026-07-26 21:20:18,087][starVLA.training.train_starvla][INFO] - Step 1292, Loss: {'train/loss': 0.4141707122325897, 'train/grad_norm_pre_clip': 3.3166065216064453, 'timing/data': 0.00017756689339876175, 'timing/model': 0.4575057541951537, 'learning_rate/action_model': 8.503372665013862e-05, 'learning_rate/action_query_proj': 8.503372665013862e-05, 'learning_rate/base': 2.1258431662534654e-05, 'epoch': 0.16}) +[2026-07-26 21:20:23,713][starVLA.training.train_starvla][INFO] - Step 1293, Loss: {'train/loss': 0.4430716335773468, 'train/grad_norm_pre_clip': 3.2380144596099854, 'timing/data': 0.0001764260232448578, 'timing/model': 0.4677310208790004, 'learning_rate/action_model': 8.501183900780551e-05, 'learning_rate/action_query_proj': 8.501183900780551e-05, 'learning_rate/base': 2.1252959751951377e-05, 'epoch': 0.16}) +[2026-07-26 21:20:29,425][starVLA.training.train_starvla][INFO] - Step 1294, Loss: {'train/loss': 0.2893844246864319, 'train/grad_norm_pre_clip': 3.4067904949188232, 'timing/data': 0.00017614662647247314, 'timing/model': 0.4710252759978175, 'learning_rate/action_model': 8.498993833292115e-05, 'learning_rate/action_query_proj': 8.498993833292115e-05, 'learning_rate/base': 2.1247484583230288e-05, 'epoch': 0.16}) +[2026-07-26 21:20:35,073][starVLA.training.train_starvla][INFO] - Step 1295, Loss: {'train/loss': 0.35323241353034973, 'train/grad_norm_pre_clip': 4.216679096221924, 'timing/data': 0.000170776154845953, 'timing/model': 0.4582146699540317, 'learning_rate/action_model': 8.49680246341316e-05, 'learning_rate/action_query_proj': 8.49680246341316e-05, 'learning_rate/base': 2.12420061585329e-05, 'epoch': 0.16}) +[2026-07-26 21:20:40,736][starVLA.training.train_starvla][INFO] - Step 1296, Loss: {'train/loss': 0.32490304112434387, 'train/grad_norm_pre_clip': 3.0796258449554443, 'timing/data': 0.00018654484301805496, 'timing/model': 0.45866290712729096, 'learning_rate/action_model': 8.494609792008804e-05, 'learning_rate/action_query_proj': 8.494609792008804e-05, 'learning_rate/base': 2.123652448002201e-05, 'epoch': 0.16}) +[2026-07-26 21:20:46,395][starVLA.training.train_starvla][INFO] - Step 1297, Loss: {'train/loss': 0.37318965792655945, 'train/grad_norm_pre_clip': 4.090183734893799, 'timing/data': 0.0001801210455596447, 'timing/model': 0.4687446327880025, 'learning_rate/action_model': 8.492415819944678e-05, 'learning_rate/action_query_proj': 8.492415819944678e-05, 'learning_rate/base': 2.1231039549861694e-05, 'epoch': 0.16}) +[2026-07-26 21:20:52,019][starVLA.training.train_starvla][INFO] - Step 1298, Loss: {'train/loss': 0.430228590965271, 'train/grad_norm_pre_clip': 5.635390281677246, 'timing/data': 0.00018207821995019913, 'timing/model': 0.47010172298178077, 'learning_rate/action_model': 8.49022054808693e-05, 'learning_rate/action_query_proj': 8.49022054808693e-05, 'learning_rate/base': 2.1225551370217323e-05, 'epoch': 0.16}) +[2026-07-26 21:20:57,603][starVLA.training.train_starvla][INFO] - Step 1299, Loss: {'train/loss': 0.35857343673706055, 'train/grad_norm_pre_clip': 3.358820676803589, 'timing/data': 0.00018027471378445625, 'timing/model': 0.47112606978043914, 'learning_rate/action_model': 8.488023977302216e-05, 'learning_rate/action_query_proj': 8.488023977302216e-05, 'learning_rate/base': 2.122005994325554e-05, 'epoch': 0.16}) +[2026-07-26 21:21:03,183][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 1300 +[2026-07-26 21:21:03,183][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 1300 +[2026-07-26 21:21:03,184][starVLA.training.train_starvla][INFO] - Step 1300, Loss: {'train/loss': 0.25384756922721863, 'train/grad_norm_pre_clip': 3.243488311767578, 'timing/data': 0.0001874500885605812, 'timing/model': 0.4696156387217343, 'learning_rate/action_model': 8.485826108457706e-05, 'learning_rate/action_query_proj': 8.485826108457706e-05, 'learning_rate/base': 2.1214565271144265e-05, 'epoch': 0.16}) +[2026-07-26 21:21:08,768][starVLA.training.train_starvla][INFO] - Step 1301, Loss: {'train/loss': 0.35291242599487305, 'train/grad_norm_pre_clip': 3.9823665618896484, 'timing/data': 0.0001791110262274742, 'timing/model': 0.470847699791193, 'learning_rate/action_model': 8.483626942421087e-05, 'learning_rate/action_query_proj': 8.483626942421087e-05, 'learning_rate/base': 2.1209067356052718e-05, 'epoch': 0.16}) +[2026-07-26 21:21:14,365][starVLA.training.train_starvla][INFO] - Step 1302, Loss: {'train/loss': 0.36902812123298645, 'train/grad_norm_pre_clip': 3.3898415565490723, 'timing/data': 0.0001723896712064743, 'timing/model': 0.47498193476349115, 'learning_rate/action_model': 8.481426480060553e-05, 'learning_rate/action_query_proj': 8.481426480060553e-05, 'learning_rate/base': 2.1203566200151383e-05, 'epoch': 0.16}) +[2026-07-26 21:21:19,974][starVLA.training.train_starvla][INFO] - Step 1303, Loss: {'train/loss': 0.5272031426429749, 'train/grad_norm_pre_clip': 4.976366996765137, 'timing/data': 0.00017582392320036888, 'timing/model': 0.46962055610492826, 'learning_rate/action_model': 8.479224722244814e-05, 'learning_rate/action_query_proj': 8.479224722244814e-05, 'learning_rate/base': 2.1198061805612036e-05, 'epoch': 0.16}) +[2026-07-26 21:21:25,565][starVLA.training.train_starvla][INFO] - Step 1304, Loss: {'train/loss': 0.37354275584220886, 'train/grad_norm_pre_clip': 4.489303112030029, 'timing/data': 0.0001749405637383461, 'timing/model': 0.4702744041569531, 'learning_rate/action_model': 8.477021669843088e-05, 'learning_rate/action_query_proj': 8.477021669843088e-05, 'learning_rate/base': 2.119255417460772e-05, 'epoch': 0.16}) +[2026-07-26 21:21:31,155][starVLA.training.train_starvla][INFO] - Step 1305, Loss: {'train/loss': 0.5312796831130981, 'train/grad_norm_pre_clip': 4.5702104568481445, 'timing/data': 0.00018121767789125443, 'timing/model': 0.47072337241843343, 'learning_rate/action_model': 8.474817323725104e-05, 'learning_rate/action_query_proj': 8.474817323725104e-05, 'learning_rate/base': 2.118704330931276e-05, 'epoch': 0.16}) +[2026-07-26 21:21:36,754][starVLA.training.train_starvla][INFO] - Step 1306, Loss: {'train/loss': 0.5823954343795776, 'train/grad_norm_pre_clip': 6.743046760559082, 'timing/data': 0.00018015503883361816, 'timing/model': 0.47667186334729195, 'learning_rate/action_model': 8.472611684761103e-05, 'learning_rate/action_query_proj': 8.472611684761103e-05, 'learning_rate/base': 2.1181529211902757e-05, 'epoch': 0.16}) +[2026-07-26 21:21:42,366][starVLA.training.train_starvla][INFO] - Step 1307, Loss: {'train/loss': 0.5134978294372559, 'train/grad_norm_pre_clip': 6.049795627593994, 'timing/data': 0.00017263414338231087, 'timing/model': 0.47667642403393984, 'learning_rate/action_model': 8.470404753821836e-05, 'learning_rate/action_query_proj': 8.470404753821836e-05, 'learning_rate/base': 2.117601188455459e-05, 'epoch': 0.16}) +[2026-07-26 21:21:47,987][starVLA.training.train_starvla][INFO] - Step 1308, Loss: {'train/loss': 0.3404964506626129, 'train/grad_norm_pre_clip': 3.813868761062622, 'timing/data': 0.00018619326874613762, 'timing/model': 0.48363409703597426, 'learning_rate/action_model': 8.468196531778568e-05, 'learning_rate/action_query_proj': 8.468196531778568e-05, 'learning_rate/base': 2.117049132944642e-05, 'epoch': 0.16}) +[2026-07-26 21:21:53,619][starVLA.training.train_starvla][INFO] - Step 1309, Loss: {'train/loss': 0.544768214225769, 'train/grad_norm_pre_clip': 5.415402412414551, 'timing/data': 0.0001731780357658863, 'timing/model': 0.479750731959939, 'learning_rate/action_model': 8.465987019503066e-05, 'learning_rate/action_query_proj': 8.465987019503066e-05, 'learning_rate/base': 2.1164967548757665e-05, 'epoch': 0.16}) +[2026-07-26 21:21:59,180][starVLA.training.train_starvla][INFO] - Step 1310, Loss: {'train/loss': 0.4595460295677185, 'train/grad_norm_pre_clip': 5.209269046783447, 'timing/data': 0.00020060501992702484, 'timing/model': 0.4691421678289771, 'learning_rate/action_model': 8.463776217867613e-05, 'learning_rate/action_query_proj': 8.463776217867613e-05, 'learning_rate/base': 2.115944054466903e-05, 'epoch': 0.16}) +[2026-07-26 21:22:04,733][starVLA.training.train_starvla][INFO] - Step 1311, Loss: {'train/loss': 0.35227251052856445, 'train/grad_norm_pre_clip': 3.242476224899292, 'timing/data': 0.00018213503062725067, 'timing/model': 0.4689549747854471, 'learning_rate/action_model': 8.461564127744998e-05, 'learning_rate/action_query_proj': 8.461564127744998e-05, 'learning_rate/base': 2.1153910319362495e-05, 'epoch': 0.16}) +[2026-07-26 21:22:10,336][starVLA.training.train_starvla][INFO] - Step 1312, Loss: {'train/loss': 0.3701210021972656, 'train/grad_norm_pre_clip': 3.664424419403076, 'timing/data': 0.00016995426267385483, 'timing/model': 0.46982274297624826, 'learning_rate/action_model': 8.459350750008515e-05, 'learning_rate/action_query_proj': 8.459350750008515e-05, 'learning_rate/base': 2.1148376875021288e-05, 'epoch': 0.16}) +[2026-07-26 21:22:15,925][starVLA.training.train_starvla][INFO] - Step 1313, Loss: {'train/loss': 0.5691807270050049, 'train/grad_norm_pre_clip': 3.4035232067108154, 'timing/data': 0.00018375273793935776, 'timing/model': 0.4698326801881194, 'learning_rate/action_model': 8.457136085531977e-05, 'learning_rate/action_query_proj': 8.457136085531977e-05, 'learning_rate/base': 2.1142840213829944e-05, 'epoch': 0.16}) +[2026-07-26 21:22:21,593][starVLA.training.train_starvla][INFO] - Step 1314, Loss: {'train/loss': 0.31371793150901794, 'train/grad_norm_pre_clip': 2.4731647968292236, 'timing/data': 0.00017484277486801147, 'timing/model': 0.4761457503773272, 'learning_rate/action_model': 8.454920135189694e-05, 'learning_rate/action_query_proj': 8.454920135189694e-05, 'learning_rate/base': 2.1137300337974235e-05, 'epoch': 0.16}) +[2026-07-26 21:22:27,211][starVLA.training.train_starvla][INFO] - Step 1315, Loss: {'train/loss': 0.35329917073249817, 'train/grad_norm_pre_clip': 3.798959732055664, 'timing/data': 0.00017818016931414604, 'timing/model': 0.4700102210044861, 'learning_rate/action_model': 8.452702899856491e-05, 'learning_rate/action_query_proj': 8.452702899856491e-05, 'learning_rate/base': 2.113175724964123e-05, 'epoch': 0.16}) +[2026-07-26 21:22:32,817][starVLA.training.train_starvla][INFO] - Step 1316, Loss: {'train/loss': 0.3195453882217407, 'train/grad_norm_pre_clip': 2.817089080810547, 'timing/data': 0.00017196405678987503, 'timing/model': 0.47076035011559725, 'learning_rate/action_model': 8.450484380407696e-05, 'learning_rate/action_query_proj': 8.450484380407696e-05, 'learning_rate/base': 2.112621095101924e-05, 'epoch': 0.16}) +[2026-07-26 21:22:38,416][starVLA.training.train_starvla][INFO] - Step 1317, Loss: {'train/loss': 0.30784872174263, 'train/grad_norm_pre_clip': 2.8808960914611816, 'timing/data': 0.00017664628103375435, 'timing/model': 0.4699222599156201, 'learning_rate/action_model': 8.448264577719146e-05, 'learning_rate/action_query_proj': 8.448264577719146e-05, 'learning_rate/base': 2.1120661444297864e-05, 'epoch': 0.16}) +[2026-07-26 21:22:44,046][starVLA.training.train_starvla][INFO] - Step 1318, Loss: {'train/loss': 0.48326873779296875, 'train/grad_norm_pre_clip': 5.190037250518799, 'timing/data': 0.00017424626275897026, 'timing/model': 0.4690764113329351, 'learning_rate/action_model': 8.446043492667181e-05, 'learning_rate/action_query_proj': 8.446043492667181e-05, 'learning_rate/base': 2.1115108731667953e-05, 'epoch': 0.16}) +[2026-07-26 21:22:49,709][starVLA.training.train_starvla][INFO] - Step 1319, Loss: {'train/loss': 0.3199401795864105, 'train/grad_norm_pre_clip': 4.104295253753662, 'timing/data': 0.00017332099378108978, 'timing/model': 0.46918274834752083, 'learning_rate/action_model': 8.443821126128655e-05, 'learning_rate/action_query_proj': 8.443821126128655e-05, 'learning_rate/base': 2.1109552815321637e-05, 'epoch': 0.16}) +[2026-07-26 21:22:55,321][starVLA.training.train_starvla][INFO] - Step 1320, Loss: {'train/loss': 0.39423707127571106, 'train/grad_norm_pre_clip': 3.767544746398926, 'timing/data': 0.00017463788390159607, 'timing/model': 0.4798005041666329, 'learning_rate/action_model': 8.441597478980917e-05, 'learning_rate/action_query_proj': 8.441597478980917e-05, 'learning_rate/base': 2.1103993697452293e-05, 'epoch': 0.16}) +[2026-07-26 21:23:00,939][starVLA.training.train_starvla][INFO] - Step 1321, Loss: {'train/loss': 0.503587007522583, 'train/grad_norm_pre_clip': 3.638540506362915, 'timing/data': 0.00017535081133246422, 'timing/model': 0.4805321400053799, 'learning_rate/action_model': 8.439372552101833e-05, 'learning_rate/action_query_proj': 8.439372552101833e-05, 'learning_rate/base': 2.1098431380254584e-05, 'epoch': 0.16}) +[2026-07-26 21:23:06,555][starVLA.training.train_starvla][INFO] - Step 1322, Loss: {'train/loss': 0.34541085362434387, 'train/grad_norm_pre_clip': 3.477458953857422, 'timing/data': 0.000169308390468359, 'timing/model': 0.4702179366722703, 'learning_rate/action_model': 8.437146346369769e-05, 'learning_rate/action_query_proj': 8.437146346369769e-05, 'learning_rate/base': 2.109286586592442e-05, 'epoch': 0.16}) +[2026-07-26 21:23:12,169][starVLA.training.train_starvla][INFO] - Step 1323, Loss: {'train/loss': 0.5651432275772095, 'train/grad_norm_pre_clip': 3.6736578941345215, 'timing/data': 0.00017220014706254005, 'timing/model': 0.4708211636170745, 'learning_rate/action_model': 8.434918862663593e-05, 'learning_rate/action_query_proj': 8.434918862663593e-05, 'learning_rate/base': 2.1087297156658983e-05, 'epoch': 0.16}) +[2026-07-26 21:23:17,773][starVLA.training.train_starvla][INFO] - Step 1324, Loss: {'train/loss': 0.3393269181251526, 'train/grad_norm_pre_clip': 3.2591140270233154, 'timing/data': 0.00017801905050873756, 'timing/model': 0.4710340350866318, 'learning_rate/action_model': 8.432690101862681e-05, 'learning_rate/action_query_proj': 8.432690101862681e-05, 'learning_rate/base': 2.1081725254656702e-05, 'epoch': 0.16}) +[2026-07-26 21:23:23,391][starVLA.training.train_starvla][INFO] - Step 1325, Loss: {'train/loss': 0.5333691239356995, 'train/grad_norm_pre_clip': 3.726531744003296, 'timing/data': 0.00017806515097618103, 'timing/model': 0.46721226582303643, 'learning_rate/action_model': 8.430460064846912e-05, 'learning_rate/action_query_proj': 8.430460064846912e-05, 'learning_rate/base': 2.107615016211728e-05, 'epoch': 0.16}) +[2026-07-26 21:23:29,007][starVLA.training.train_starvla][INFO] - Step 1326, Loss: {'train/loss': 0.3369107246398926, 'train/grad_norm_pre_clip': 2.41677188873291, 'timing/data': 0.0001806383952498436, 'timing/model': 0.47789089707657695, 'learning_rate/action_model': 8.428228752496672e-05, 'learning_rate/action_query_proj': 8.428228752496672e-05, 'learning_rate/base': 2.107057188124168e-05, 'epoch': 0.16}) +[2026-07-26 21:23:34,640][starVLA.training.train_starvla][INFO] - Step 1327, Loss: {'train/loss': 0.3772878646850586, 'train/grad_norm_pre_clip': 3.8836536407470703, 'timing/data': 0.00017861602827906609, 'timing/model': 0.47838655672967434, 'learning_rate/action_model': 8.425996165692843e-05, 'learning_rate/action_query_proj': 8.425996165692843e-05, 'learning_rate/base': 2.1064990414232107e-05, 'epoch': 0.16}) +[2026-07-26 21:23:40,254][starVLA.training.train_starvla][INFO] - Step 1328, Loss: {'train/loss': 0.30224037170410156, 'train/grad_norm_pre_clip': 2.553534746170044, 'timing/data': 0.0001750793308019638, 'timing/model': 0.4680579053238034, 'learning_rate/action_model': 8.423762305316821e-05, 'learning_rate/action_query_proj': 8.423762305316821e-05, 'learning_rate/base': 2.1059405763292052e-05, 'epoch': 0.16}) +[2026-07-26 21:23:45,865][starVLA.training.train_starvla][INFO] - Step 1329, Loss: {'train/loss': 0.41004133224487305, 'train/grad_norm_pre_clip': 4.77367639541626, 'timing/data': 0.0001710830256342888, 'timing/model': 0.47058270778506994, 'learning_rate/action_model': 8.421527172250494e-05, 'learning_rate/action_query_proj': 8.421527172250494e-05, 'learning_rate/base': 2.1053817930626234e-05, 'epoch': 0.16}) +[2026-07-26 21:23:51,469][starVLA.training.train_starvla][INFO] - Step 1330, Loss: {'train/loss': 0.3604047894477844, 'train/grad_norm_pre_clip': 4.158430099487305, 'timing/data': 0.00018594041466712952, 'timing/model': 0.47704586619511247, 'learning_rate/action_model': 8.419290767376255e-05, 'learning_rate/action_query_proj': 8.419290767376255e-05, 'learning_rate/base': 2.1048226918440637e-05, 'epoch': 0.16}) +[2026-07-26 21:23:57,080][starVLA.training.train_starvla][INFO] - Step 1331, Loss: {'train/loss': 0.4488084614276886, 'train/grad_norm_pre_clip': 4.433672904968262, 'timing/data': 0.0001741102896630764, 'timing/model': 0.468872576020658, 'learning_rate/action_model': 8.417053091577009e-05, 'learning_rate/action_query_proj': 8.417053091577009e-05, 'learning_rate/base': 2.1042632728942522e-05, 'epoch': 0.16}) +[2026-07-26 21:24:02,642][starVLA.training.train_starvla][INFO] - Step 1332, Loss: {'train/loss': 0.34261155128479004, 'train/grad_norm_pre_clip': 3.045851230621338, 'timing/data': 0.00018580397590994835, 'timing/model': 0.459216870367527, 'learning_rate/action_model': 8.414814145736151e-05, 'learning_rate/action_query_proj': 8.414814145736151e-05, 'learning_rate/base': 2.1037035364340378e-05, 'epoch': 0.16}) +[2026-07-26 21:24:08,180][starVLA.training.train_starvla][INFO] - Step 1333, Loss: {'train/loss': 0.40138453245162964, 'train/grad_norm_pre_clip': 2.7111685276031494, 'timing/data': 0.00017167581245303154, 'timing/model': 0.4635088429786265, 'learning_rate/action_model': 8.412573930737579e-05, 'learning_rate/action_query_proj': 8.412573930737579e-05, 'learning_rate/base': 2.1031434826843947e-05, 'epoch': 0.16}) +[2026-07-26 21:24:13,711][starVLA.training.train_starvla][INFO] - Step 1334, Loss: {'train/loss': 0.39087754487991333, 'train/grad_norm_pre_clip': 4.906322002410889, 'timing/data': 0.0001830938272178173, 'timing/model': 0.4588033873587847, 'learning_rate/action_model': 8.410332447465697e-05, 'learning_rate/action_query_proj': 8.410332447465697e-05, 'learning_rate/base': 2.1025831118664243e-05, 'epoch': 0.16}) +[2026-07-26 21:24:19,224][starVLA.training.train_starvla][INFO] - Step 1335, Loss: {'train/loss': 0.48780274391174316, 'train/grad_norm_pre_clip': 3.22536039352417, 'timing/data': 0.00018085213378071785, 'timing/model': 0.4596521910279989, 'learning_rate/action_model': 8.408089696805407e-05, 'learning_rate/action_query_proj': 8.408089696805407e-05, 'learning_rate/base': 2.1020224242013517e-05, 'epoch': 0.16}) +[2026-07-26 21:24:24,753][starVLA.training.train_starvla][INFO] - Step 1336, Loss: {'train/loss': 0.4395866394042969, 'train/grad_norm_pre_clip': 3.1561429500579834, 'timing/data': 0.00017505697906017303, 'timing/model': 0.45861663296818733, 'learning_rate/action_model': 8.405845679642111e-05, 'learning_rate/action_query_proj': 8.405845679642111e-05, 'learning_rate/base': 2.1014614199105278e-05, 'epoch': 0.16}) +[2026-07-26 21:24:30,249][starVLA.training.train_starvla][INFO] - Step 1337, Loss: {'train/loss': 0.2879573106765747, 'train/grad_norm_pre_clip': 3.3812763690948486, 'timing/data': 0.00017717713490128517, 'timing/model': 0.4580996809527278, 'learning_rate/action_model': 8.403600396861712e-05, 'learning_rate/action_query_proj': 8.403600396861712e-05, 'learning_rate/base': 2.100900099215428e-05, 'epoch': 0.16}) +[2026-07-26 21:24:35,747][starVLA.training.train_starvla][INFO] - Step 1338, Loss: {'train/loss': 0.27362120151519775, 'train/grad_norm_pre_clip': 2.5785887241363525, 'timing/data': 0.00017218571156263351, 'timing/model': 0.45858617685735226, 'learning_rate/action_model': 8.40135384935061e-05, 'learning_rate/action_query_proj': 8.40135384935061e-05, 'learning_rate/base': 2.1003384623376526e-05, 'epoch': 0.16}) +[2026-07-26 21:24:41,240][starVLA.training.train_starvla][INFO] - Step 1339, Loss: {'train/loss': 0.3511243164539337, 'train/grad_norm_pre_clip': 3.0385773181915283, 'timing/data': 0.0001720469444990158, 'timing/model': 0.45888545736670494, 'learning_rate/action_model': 8.39910603799571e-05, 'learning_rate/action_query_proj': 8.39910603799571e-05, 'learning_rate/base': 2.0997765094989275e-05, 'epoch': 0.16}) +[2026-07-26 21:24:46,737][starVLA.training.train_starvla][INFO] - Step 1340, Loss: {'train/loss': 0.522072434425354, 'train/grad_norm_pre_clip': 4.973697662353516, 'timing/data': 0.00017590029165148735, 'timing/model': 0.45951593900099397, 'learning_rate/action_model': 8.396856963684409e-05, 'learning_rate/action_query_proj': 8.396856963684409e-05, 'learning_rate/base': 2.0992142409211022e-05, 'epoch': 0.16}) +[2026-07-26 21:24:52,231][starVLA.training.train_starvla][INFO] - Step 1341, Loss: {'train/loss': 0.34229975938796997, 'train/grad_norm_pre_clip': 2.7845425605773926, 'timing/data': 0.00017195427790284157, 'timing/model': 0.4587483792565763, 'learning_rate/action_model': 8.394606627304608e-05, 'learning_rate/action_query_proj': 8.394606627304608e-05, 'learning_rate/base': 2.098651656826152e-05, 'epoch': 0.16}) +[2026-07-26 21:24:57,736][starVLA.training.train_starvla][INFO] - Step 1342, Loss: {'train/loss': 0.43731796741485596, 'train/grad_norm_pre_clip': 5.188492298126221, 'timing/data': 0.00018092291429638863, 'timing/model': 0.45923382276669145, 'learning_rate/action_model': 8.392355029744702e-05, 'learning_rate/action_query_proj': 8.392355029744702e-05, 'learning_rate/base': 2.0980887574361754e-05, 'epoch': 0.16}) +[2026-07-26 21:25:03,231][starVLA.training.train_starvla][INFO] - Step 1343, Loss: {'train/loss': 0.5542243719100952, 'train/grad_norm_pre_clip': 4.877976417541504, 'timing/data': 0.00017360271885991096, 'timing/model': 0.4584628031589091, 'learning_rate/action_model': 8.390102171893586e-05, 'learning_rate/action_query_proj': 8.390102171893586e-05, 'learning_rate/base': 2.0975255429733966e-05, 'epoch': 0.16}) +[2026-07-26 21:25:08,728][starVLA.training.train_starvla][INFO] - Step 1344, Loss: {'train/loss': 0.3826291263103485, 'train/grad_norm_pre_clip': 4.382683753967285, 'timing/data': 0.00017218710854649544, 'timing/model': 0.4585320116020739, 'learning_rate/action_model': 8.387848054640658e-05, 'learning_rate/action_query_proj': 8.387848054640658e-05, 'learning_rate/base': 2.0969620136601645e-05, 'epoch': 0.16}) +[2026-07-26 21:25:14,218][starVLA.training.train_starvla][INFO] - Step 1345, Loss: {'train/loss': 0.3289773166179657, 'train/grad_norm_pre_clip': 3.4647130966186523, 'timing/data': 0.00017145881429314613, 'timing/model': 0.4583294219337404, 'learning_rate/action_model': 8.385592678875802e-05, 'learning_rate/action_query_proj': 8.385592678875802e-05, 'learning_rate/base': 2.0963981697189505e-05, 'epoch': 0.16}) +[2026-07-26 21:25:19,711][starVLA.training.train_starvla][INFO] - Step 1346, Loss: {'train/loss': 0.41621872782707214, 'train/grad_norm_pre_clip': 3.7291572093963623, 'timing/data': 0.00017285719513893127, 'timing/model': 0.45904994290322065, 'learning_rate/action_model': 8.383336045489406e-05, 'learning_rate/action_query_proj': 8.383336045489406e-05, 'learning_rate/base': 2.0958340113723516e-05, 'epoch': 0.16}) +[2026-07-26 21:25:25,230][starVLA.training.train_starvla][INFO] - Step 1347, Loss: {'train/loss': 0.4894275367259979, 'train/grad_norm_pre_clip': 3.9814963340759277, 'timing/data': 0.00018401024863123894, 'timing/model': 0.4653738532215357, 'learning_rate/action_model': 8.381078155372354e-05, 'learning_rate/action_query_proj': 8.381078155372354e-05, 'learning_rate/base': 2.0952695388430885e-05, 'epoch': 0.16}) +[2026-07-26 21:25:30,855][starVLA.training.train_starvla][INFO] - Step 1348, Loss: {'train/loss': 0.346808522939682, 'train/grad_norm_pre_clip': 3.7795350551605225, 'timing/data': 0.0001856749877333641, 'timing/model': 0.4674391229636967, 'learning_rate/action_model': 8.378819009416025e-05, 'learning_rate/action_query_proj': 8.378819009416025e-05, 'learning_rate/base': 2.0947047523540063e-05, 'epoch': 0.16}) +[2026-07-26 21:25:36,437][starVLA.training.train_starvla][INFO] - Step 1349, Loss: {'train/loss': 0.33570194244384766, 'train/grad_norm_pre_clip': 2.668761730194092, 'timing/data': 0.00023674266412854195, 'timing/model': 0.45888463594019413, 'learning_rate/action_model': 8.376558608512293e-05, 'learning_rate/action_query_proj': 8.376558608512293e-05, 'learning_rate/base': 2.0941396521280733e-05, 'epoch': 0.16}) +[2026-07-26 21:25:41,995][starVLA.training.train_starvla][INFO] - Step 1350, Loss: {'train/loss': 0.3683558702468872, 'train/grad_norm_pre_clip': 3.0702691078186035, 'timing/data': 0.00024264119565486908, 'timing/model': 0.4606384998187423, 'learning_rate/action_model': 8.374296953553528e-05, 'learning_rate/action_query_proj': 8.374296953553528e-05, 'learning_rate/base': 2.093574238388382e-05, 'epoch': 0.16}) +[2026-07-26 21:25:47,552][starVLA.training.train_starvla][INFO] - Step 1351, Loss: {'train/loss': 0.2776769697666168, 'train/grad_norm_pre_clip': 4.703361511230469, 'timing/data': 0.00017370795831084251, 'timing/model': 0.45946100214496255, 'learning_rate/action_model': 8.372034045432599e-05, 'learning_rate/action_query_proj': 8.372034045432599e-05, 'learning_rate/base': 2.0930085113581498e-05, 'epoch': 0.16}) +[2026-07-26 21:25:53,123][starVLA.training.train_starvla][INFO] - Step 1352, Loss: {'train/loss': 0.4454585611820221, 'train/grad_norm_pre_clip': 4.546487331390381, 'timing/data': 0.00017174705862998962, 'timing/model': 0.4601945299655199, 'learning_rate/action_model': 8.369769885042867e-05, 'learning_rate/action_query_proj': 8.369769885042867e-05, 'learning_rate/base': 2.0924424712607167e-05, 'epoch': 0.16}) +[2026-07-26 21:25:58,715][starVLA.training.train_starvla][INFO] - Step 1353, Loss: {'train/loss': 0.3338016867637634, 'train/grad_norm_pre_clip': 4.802387714385986, 'timing/data': 0.00017239386215806007, 'timing/model': 0.46030574617907405, 'learning_rate/action_model': 8.367504473278178e-05, 'learning_rate/action_query_proj': 8.367504473278178e-05, 'learning_rate/base': 2.0918761183195446e-05, 'epoch': 0.16}) +[2026-07-26 21:26:04,322][starVLA.training.train_starvla][INFO] - Step 1354, Loss: {'train/loss': 0.47505998611450195, 'train/grad_norm_pre_clip': 4.774620532989502, 'timing/data': 0.00017530610784888268, 'timing/model': 0.4601780967786908, 'learning_rate/action_model': 8.36523781103289e-05, 'learning_rate/action_query_proj': 8.36523781103289e-05, 'learning_rate/base': 2.0913094527582225e-05, 'epoch': 0.16}) +[2026-07-26 21:26:09,870][starVLA.training.train_starvla][INFO] - Step 1355, Loss: {'train/loss': 0.35310664772987366, 'train/grad_norm_pre_clip': 3.207005262374878, 'timing/data': 0.00017439620569348335, 'timing/model': 0.46029296005144715, 'learning_rate/action_model': 8.362969899201842e-05, 'learning_rate/action_query_proj': 8.362969899201842e-05, 'learning_rate/base': 2.0907424748004606e-05, 'epoch': 0.16}) +[2026-07-26 21:26:15,409][starVLA.training.train_starvla][INFO] - Step 1356, Loss: {'train/loss': 0.6390330195426941, 'train/grad_norm_pre_clip': 7.660232067108154, 'timing/data': 0.0001755659468472004, 'timing/model': 0.45817726617679, 'learning_rate/action_model': 8.360700738680368e-05, 'learning_rate/action_query_proj': 8.360700738680368e-05, 'learning_rate/base': 2.090175184670092e-05, 'epoch': 0.16}) +[2026-07-26 21:26:21,229][starVLA.training.train_starvla][INFO] - Step 1357, Loss: {'train/loss': 0.368303507566452, 'train/grad_norm_pre_clip': 3.7240664958953857, 'timing/data': 0.00017266999930143356, 'timing/model': 0.458829065784812, 'learning_rate/action_model': 8.3584303303643e-05, 'learning_rate/action_query_proj': 8.3584303303643e-05, 'learning_rate/base': 2.089607582591075e-05, 'epoch': 0.16}) +[2026-07-26 21:26:26,752][starVLA.training.train_starvla][INFO] - Step 1358, Loss: {'train/loss': 0.43474340438842773, 'train/grad_norm_pre_clip': 4.394076824188232, 'timing/data': 0.00017780624330043793, 'timing/model': 0.4568023970350623, 'learning_rate/action_model': 8.356158675149957e-05, 'learning_rate/action_query_proj': 8.356158675149957e-05, 'learning_rate/base': 2.0890396687874892e-05, 'epoch': 0.16}) +[2026-07-26 21:26:32,274][starVLA.training.train_starvla][INFO] - Step 1359, Loss: {'train/loss': 0.4850707948207855, 'train/grad_norm_pre_clip': 3.2194600105285645, 'timing/data': 0.00017185136675834656, 'timing/model': 0.4583135163411498, 'learning_rate/action_model': 8.353885773934152e-05, 'learning_rate/action_query_proj': 8.353885773934152e-05, 'learning_rate/base': 2.088471443483538e-05, 'epoch': 0.16}) +[2026-07-26 21:26:37,785][starVLA.training.train_starvla][INFO] - Step 1360, Loss: {'train/loss': 0.4609483480453491, 'train/grad_norm_pre_clip': 3.7765252590179443, 'timing/data': 0.00017418107017874718, 'timing/model': 0.45800461806356907, 'learning_rate/action_model': 8.35161162761419e-05, 'learning_rate/action_query_proj': 8.35161162761419e-05, 'learning_rate/base': 2.0879029069035476e-05, 'epoch': 0.16}) +[2026-07-26 21:26:43,311][starVLA.training.train_starvla][INFO] - Step 1361, Loss: {'train/loss': 0.36091816425323486, 'train/grad_norm_pre_clip': 2.7718329429626465, 'timing/data': 0.00018173642456531525, 'timing/model': 0.4583747051656246, 'learning_rate/action_model': 8.349336237087873e-05, 'learning_rate/action_query_proj': 8.349336237087873e-05, 'learning_rate/base': 2.0873340592719682e-05, 'epoch': 0.17}) +[2026-07-26 21:26:48,852][starVLA.training.train_starvla][INFO] - Step 1362, Loss: {'train/loss': 0.3273014426231384, 'train/grad_norm_pre_clip': 3.365699291229248, 'timing/data': 0.0001737377606332302, 'timing/model': 0.45957082509994507, 'learning_rate/action_model': 8.347059603253484e-05, 'learning_rate/action_query_proj': 8.347059603253484e-05, 'learning_rate/base': 2.086764900813371e-05, 'epoch': 0.17}) +[2026-07-26 21:26:54,433][starVLA.training.train_starvla][INFO] - Step 1363, Loss: {'train/loss': 0.32628557085990906, 'train/grad_norm_pre_clip': 4.939011573791504, 'timing/data': 0.00017046090215444565, 'timing/model': 0.4578184369020164, 'learning_rate/action_model': 8.344781727009802e-05, 'learning_rate/action_query_proj': 8.344781727009802e-05, 'learning_rate/base': 2.0861954317524505e-05, 'epoch': 0.17}) +[2026-07-26 21:26:59,982][starVLA.training.train_starvla][INFO] - Step 1364, Loss: {'train/loss': 0.48251378536224365, 'train/grad_norm_pre_clip': 5.715364456176758, 'timing/data': 0.00016524596139788628, 'timing/model': 0.4590029609389603, 'learning_rate/action_model': 8.3425026092561e-05, 'learning_rate/action_query_proj': 8.3425026092561e-05, 'learning_rate/base': 2.085625652314025e-05, 'epoch': 0.17}) +[2026-07-26 21:27:05,481][starVLA.training.train_starvla][INFO] - Step 1365, Loss: {'train/loss': 0.3317102789878845, 'train/grad_norm_pre_clip': 3.9102346897125244, 'timing/data': 0.00016845902428030968, 'timing/model': 0.45759054366499186, 'learning_rate/action_model': 8.340222250892133e-05, 'learning_rate/action_query_proj': 8.340222250892133e-05, 'learning_rate/base': 2.0850555627230334e-05, 'epoch': 0.17}) +[2026-07-26 21:27:10,988][starVLA.training.train_starvla][INFO] - Step 1366, Loss: {'train/loss': 0.3943599462509155, 'train/grad_norm_pre_clip': 2.9527335166931152, 'timing/data': 0.00017407583072781563, 'timing/model': 0.4586994247511029, 'learning_rate/action_model': 8.337940652818155e-05, 'learning_rate/action_query_proj': 8.337940652818155e-05, 'learning_rate/base': 2.0844851632045387e-05, 'epoch': 0.17}) +[2026-07-26 21:27:16,494][starVLA.training.train_starvla][INFO] - Step 1367, Loss: {'train/loss': 0.4885132312774658, 'train/grad_norm_pre_clip': 3.992016553878784, 'timing/data': 0.00017066765576601028, 'timing/model': 0.45858138613402843, 'learning_rate/action_model': 8.335657815934902e-05, 'learning_rate/action_query_proj': 8.335657815934902e-05, 'learning_rate/base': 2.0839144539837254e-05, 'epoch': 0.17}) +[2026-07-26 21:27:21,999][starVLA.training.train_starvla][INFO] - Step 1368, Loss: {'train/loss': 0.4417804777622223, 'train/grad_norm_pre_clip': 5.574484825134277, 'timing/data': 0.00018730619922280312, 'timing/model': 0.45692538982257247, 'learning_rate/action_model': 8.333373741143601e-05, 'learning_rate/action_query_proj': 8.333373741143601e-05, 'learning_rate/base': 2.0833434352859004e-05, 'epoch': 0.17}) +[2026-07-26 21:27:27,524][starVLA.training.train_starvla][INFO] - Step 1369, Loss: {'train/loss': 0.4744587242603302, 'train/grad_norm_pre_clip': 3.609982490539551, 'timing/data': 0.00016985787078738213, 'timing/model': 0.4583818791434169, 'learning_rate/action_model': 8.331088429345973e-05, 'learning_rate/action_query_proj': 8.331088429345973e-05, 'learning_rate/base': 2.0827721073364933e-05, 'epoch': 0.17}) +[2026-07-26 21:27:33,034][starVLA.training.train_starvla][INFO] - Step 1370, Loss: {'train/loss': 0.4298068881034851, 'train/grad_norm_pre_clip': 6.135280609130859, 'timing/data': 0.00018051499500870705, 'timing/model': 0.4582030214369297, 'learning_rate/action_model': 8.328801881444218e-05, 'learning_rate/action_query_proj': 8.328801881444218e-05, 'learning_rate/base': 2.0822004703610546e-05, 'epoch': 0.17}) +[2026-07-26 21:27:38,690][starVLA.training.train_starvla][INFO] - Step 1371, Loss: {'train/loss': 0.3591362237930298, 'train/grad_norm_pre_clip': 3.092350482940674, 'timing/data': 0.00018721772357821465, 'timing/model': 0.47374109691008925, 'learning_rate/action_model': 8.326514098341031e-05, 'learning_rate/action_query_proj': 8.326514098341031e-05, 'learning_rate/base': 2.0816285245852578e-05, 'epoch': 0.17}) +[2026-07-26 21:27:44,208][starVLA.training.train_starvla][INFO] - Step 1372, Loss: {'train/loss': 0.515313446521759, 'train/grad_norm_pre_clip': 4.136053085327148, 'timing/data': 0.00018170708790421486, 'timing/model': 0.4587220340035856, 'learning_rate/action_model': 8.324225080939594e-05, 'learning_rate/action_query_proj': 8.324225080939594e-05, 'learning_rate/base': 2.0810562702348986e-05, 'epoch': 0.17}) +[2026-07-26 21:27:49,759][starVLA.training.train_starvla][INFO] - Step 1373, Loss: {'train/loss': 0.4173317849636078, 'train/grad_norm_pre_clip': 3.4161341190338135, 'timing/data': 0.0001821611076593399, 'timing/model': 0.4596648858860135, 'learning_rate/action_model': 8.321934830143571e-05, 'learning_rate/action_query_proj': 8.321934830143571e-05, 'learning_rate/base': 2.0804837075358928e-05, 'epoch': 0.17}) +[2026-07-26 21:27:55,299][starVLA.training.train_starvla][INFO] - Step 1374, Loss: {'train/loss': 0.3661973476409912, 'train/grad_norm_pre_clip': 2.763244867324829, 'timing/data': 0.00017989100888371468, 'timing/model': 0.45765461307018995, 'learning_rate/action_model': 8.319643346857121e-05, 'learning_rate/action_query_proj': 8.319643346857121e-05, 'learning_rate/base': 2.0799108367142803e-05, 'epoch': 0.17}) +[2026-07-26 21:28:00,876][starVLA.training.train_starvla][INFO] - Step 1375, Loss: {'train/loss': 0.479305237531662, 'train/grad_norm_pre_clip': 4.482635498046875, 'timing/data': 0.00017413869500160217, 'timing/model': 0.4588297540321946, 'learning_rate/action_model': 8.31735063198488e-05, 'learning_rate/action_query_proj': 8.31735063198488e-05, 'learning_rate/base': 2.07933765799622e-05, 'epoch': 0.17}) +[2026-07-26 21:28:06,453][starVLA.training.train_starvla][INFO] - Step 1376, Loss: {'train/loss': 0.4424443542957306, 'train/grad_norm_pre_clip': 5.154755115509033, 'timing/data': 0.00017936108633875847, 'timing/model': 0.45770331006497145, 'learning_rate/action_model': 8.315056686431982e-05, 'learning_rate/action_query_proj': 8.315056686431982e-05, 'learning_rate/base': 2.0787641716079956e-05, 'epoch': 0.17}) +[2026-07-26 21:28:12,023][starVLA.training.train_starvla][INFO] - Step 1377, Loss: {'train/loss': 0.36223194003105164, 'train/grad_norm_pre_clip': 4.646178722381592, 'timing/data': 0.00017655687406659126, 'timing/model': 0.4606060958467424, 'learning_rate/action_model': 8.312761511104038e-05, 'learning_rate/action_query_proj': 8.312761511104038e-05, 'learning_rate/base': 2.0781903777760096e-05, 'epoch': 0.17}) +[2026-07-26 21:28:17,627][starVLA.training.train_starvla][INFO] - Step 1378, Loss: {'train/loss': 0.3117588758468628, 'train/grad_norm_pre_clip': 2.7137250900268555, 'timing/data': 0.00018257508054375648, 'timing/model': 0.4577183248475194, 'learning_rate/action_model': 8.310465106907144e-05, 'learning_rate/action_query_proj': 8.310465106907144e-05, 'learning_rate/base': 2.077616276726786e-05, 'epoch': 0.17}) +[2026-07-26 21:28:23,207][starVLA.training.train_starvla][INFO] - Step 1379, Loss: {'train/loss': 0.31503498554229736, 'train/grad_norm_pre_clip': 2.5189552307128906, 'timing/data': 0.0001834309659898281, 'timing/model': 0.4579582060687244, 'learning_rate/action_model': 8.308167474747885e-05, 'learning_rate/action_query_proj': 8.308167474747885e-05, 'learning_rate/base': 2.0770418686869713e-05, 'epoch': 0.17}) +[2026-07-26 21:28:28,777][starVLA.training.train_starvla][INFO] - Step 1380, Loss: {'train/loss': 0.3902755677700043, 'train/grad_norm_pre_clip': 4.403914928436279, 'timing/data': 0.00017745327204465866, 'timing/model': 0.45862571336328983, 'learning_rate/action_model': 8.305868615533335e-05, 'learning_rate/action_query_proj': 8.305868615533335e-05, 'learning_rate/base': 2.0764671538833337e-05, 'epoch': 0.17}) +[2026-07-26 21:28:34,301][starVLA.training.train_starvla][INFO] - Step 1381, Loss: {'train/loss': 0.45464688539505005, 'train/grad_norm_pre_clip': 4.501677513122559, 'timing/data': 0.0001758909784257412, 'timing/model': 0.4583758171647787, 'learning_rate/action_model': 8.303568530171038e-05, 'learning_rate/action_query_proj': 8.303568530171038e-05, 'learning_rate/base': 2.0758921325427595e-05, 'epoch': 0.17}) +[2026-07-26 21:28:39,822][starVLA.training.train_starvla][INFO] - Step 1382, Loss: {'train/loss': 0.34135693311691284, 'train/grad_norm_pre_clip': 3.590158224105835, 'timing/data': 0.0001712101511657238, 'timing/model': 0.45797387417405844, 'learning_rate/action_model': 8.301267219569038e-05, 'learning_rate/action_query_proj': 8.301267219569038e-05, 'learning_rate/base': 2.0753168048922596e-05, 'epoch': 0.17}) +[2026-07-26 21:28:45,345][starVLA.training.train_starvla][INFO] - Step 1383, Loss: {'train/loss': 0.4274137020111084, 'train/grad_norm_pre_clip': 6.355277061462402, 'timing/data': 0.00017605023458600044, 'timing/model': 0.45886089699342847, 'learning_rate/action_model': 8.298964684635855e-05, 'learning_rate/action_query_proj': 8.298964684635855e-05, 'learning_rate/base': 2.074741171158964e-05, 'epoch': 0.17}) +[2026-07-26 21:28:50,872][starVLA.training.train_starvla][INFO] - Step 1384, Loss: {'train/loss': 0.48507362604141235, 'train/grad_norm_pre_clip': 3.749882459640503, 'timing/data': 0.00017682788893580437, 'timing/model': 0.4582113428041339, 'learning_rate/action_model': 8.296660926280494e-05, 'learning_rate/action_query_proj': 8.296660926280494e-05, 'learning_rate/base': 2.0741652315701235e-05, 'epoch': 0.17}) +[2026-07-26 21:28:56,418][starVLA.training.train_starvla][INFO] - Step 1385, Loss: {'train/loss': 0.2698003053665161, 'train/grad_norm_pre_clip': 2.2507638931274414, 'timing/data': 0.00017812754958868027, 'timing/model': 0.45850767008960247, 'learning_rate/action_model': 8.294355945412439e-05, 'learning_rate/action_query_proj': 8.294355945412439e-05, 'learning_rate/base': 2.0735889863531098e-05, 'epoch': 0.17}) +[2026-07-26 21:29:01,950][starVLA.training.train_starvla][INFO] - Step 1386, Loss: {'train/loss': 0.3575294315814972, 'train/grad_norm_pre_clip': 2.9570658206939697, 'timing/data': 0.0001702411100268364, 'timing/model': 0.4571353318169713, 'learning_rate/action_model': 8.292049742941664e-05, 'learning_rate/action_query_proj': 8.292049742941664e-05, 'learning_rate/base': 2.073012435735416e-05, 'epoch': 0.17}) +[2026-07-26 21:29:07,437][starVLA.training.train_starvla][INFO] - Step 1387, Loss: {'train/loss': 0.329999178647995, 'train/grad_norm_pre_clip': 3.17926287651062, 'timing/data': 0.0001748977228999138, 'timing/model': 0.4573744470253587, 'learning_rate/action_model': 8.289742319778616e-05, 'learning_rate/action_query_proj': 8.289742319778616e-05, 'learning_rate/base': 2.072435579944654e-05, 'epoch': 0.17}) +[2026-07-26 21:29:12,918][starVLA.training.train_starvla][INFO] - Step 1388, Loss: {'train/loss': 0.35277363657951355, 'train/grad_norm_pre_clip': 2.932115077972412, 'timing/data': 0.00017576618120074272, 'timing/model': 0.4574801428243518, 'learning_rate/action_model': 8.287433676834233e-05, 'learning_rate/action_query_proj': 8.287433676834233e-05, 'learning_rate/base': 2.0718584192085583e-05, 'epoch': 0.17}) +[2026-07-26 21:29:18,405][starVLA.training.train_starvla][INFO] - Step 1389, Loss: {'train/loss': 0.5355370044708252, 'train/grad_norm_pre_clip': 4.990432262420654, 'timing/data': 0.0001734062097966671, 'timing/model': 0.45758476620540023, 'learning_rate/action_model': 8.285123815019932e-05, 'learning_rate/action_query_proj': 8.285123815019932e-05, 'learning_rate/base': 2.071280953754983e-05, 'epoch': 0.17}) +[2026-07-26 21:29:23,902][starVLA.training.train_starvla][INFO] - Step 1390, Loss: {'train/loss': 0.27623429894447327, 'train/grad_norm_pre_clip': 3.376889228820801, 'timing/data': 0.00018305284902453423, 'timing/model': 0.45767764607444406, 'learning_rate/action_model': 8.282812735247606e-05, 'learning_rate/action_query_proj': 8.282812735247606e-05, 'learning_rate/base': 2.0707031838119015e-05, 'epoch': 0.17}) +[2026-07-26 21:29:29,397][starVLA.training.train_starvla][INFO] - Step 1391, Loss: {'train/loss': 0.414898544549942, 'train/grad_norm_pre_clip': 4.607906818389893, 'timing/data': 0.00017393799498677254, 'timing/model': 0.4591032746247947, 'learning_rate/action_model': 8.280500438429634e-05, 'learning_rate/action_query_proj': 8.280500438429634e-05, 'learning_rate/base': 2.0701251096074086e-05, 'epoch': 0.17}) +[2026-07-26 21:29:34,936][starVLA.training.train_starvla][INFO] - Step 1392, Loss: {'train/loss': 0.4643213450908661, 'train/grad_norm_pre_clip': 6.037848949432373, 'timing/data': 0.0001733819954097271, 'timing/model': 0.4590798672288656, 'learning_rate/action_model': 8.278186925478876e-05, 'learning_rate/action_query_proj': 8.278186925478876e-05, 'learning_rate/base': 2.069546731369719e-05, 'epoch': 0.17}) +[2026-07-26 21:29:40,469][starVLA.training.train_starvla][INFO] - Step 1393, Loss: {'train/loss': 0.3475516736507416, 'train/grad_norm_pre_clip': 3.1949315071105957, 'timing/data': 0.00019645784050226212, 'timing/model': 0.459851523861289, 'learning_rate/action_model': 8.275872197308668e-05, 'learning_rate/action_query_proj': 8.275872197308668e-05, 'learning_rate/base': 2.068968049327167e-05, 'epoch': 0.17}) +[2026-07-26 21:29:45,998][starVLA.training.train_starvla][INFO] - Step 1394, Loss: {'train/loss': 0.3775484263896942, 'train/grad_norm_pre_clip': 4.112362384796143, 'timing/data': 0.00024317530915141106, 'timing/model': 0.4584111301228404, 'learning_rate/action_model': 8.27355625483283e-05, 'learning_rate/action_query_proj': 8.27355625483283e-05, 'learning_rate/base': 2.0683890637082075e-05, 'epoch': 0.17}) +[2026-07-26 21:29:51,530][starVLA.training.train_starvla][INFO] - Step 1395, Loss: {'train/loss': 0.3602578938007355, 'train/grad_norm_pre_clip': 2.668386459350586, 'timing/data': 0.00017766840755939484, 'timing/model': 0.45907895313575864, 'learning_rate/action_model': 8.271239098965656e-05, 'learning_rate/action_query_proj': 8.271239098965656e-05, 'learning_rate/base': 2.067809774741414e-05, 'epoch': 0.17}) +[2026-07-26 21:29:57,063][starVLA.training.train_starvla][INFO] - Step 1396, Loss: {'train/loss': 0.45827341079711914, 'train/grad_norm_pre_clip': 5.398652076721191, 'timing/data': 0.0001651928760111332, 'timing/model': 0.4593211067840457, 'learning_rate/action_model': 8.268920730621928e-05, 'learning_rate/action_query_proj': 8.268920730621928e-05, 'learning_rate/base': 2.067230182655482e-05, 'epoch': 0.17}) +[2026-07-26 21:30:02,608][starVLA.training.train_starvla][INFO] - Step 1397, Loss: {'train/loss': 0.3346793055534363, 'train/grad_norm_pre_clip': 4.123870372772217, 'timing/data': 0.00016848789528012276, 'timing/model': 0.4599380400031805, 'learning_rate/action_model': 8.266601150716897e-05, 'learning_rate/action_query_proj': 8.266601150716897e-05, 'learning_rate/base': 2.0666502876792242e-05, 'epoch': 0.17}) +[2026-07-26 21:30:08,143][starVLA.training.train_starvla][INFO] - Step 1398, Loss: {'train/loss': 0.33618757128715515, 'train/grad_norm_pre_clip': 4.156859874725342, 'timing/data': 0.00017306115478277206, 'timing/model': 0.45963389007374644, 'learning_rate/action_model': 8.264280360166295e-05, 'learning_rate/action_query_proj': 8.264280360166295e-05, 'learning_rate/base': 2.066070090041574e-05, 'epoch': 0.17}) +[2026-07-26 21:30:13,697][starVLA.training.train_starvla][INFO] - Step 1399, Loss: {'train/loss': 0.3085475564002991, 'train/grad_norm_pre_clip': 3.7901604175567627, 'timing/data': 0.00017012469470500946, 'timing/model': 0.4638897976838052, 'learning_rate/action_model': 8.261958359886337e-05, 'learning_rate/action_query_proj': 8.261958359886337e-05, 'learning_rate/base': 2.0654895899715843e-05, 'epoch': 0.17}) +[2026-07-26 21:30:19,243][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 1400 +[2026-07-26 21:30:19,244][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 1400 +[2026-07-26 21:30:19,245][starVLA.training.train_starvla][INFO] - Step 1400, Loss: {'train/loss': 0.3622515797615051, 'train/grad_norm_pre_clip': 3.1614139080047607, 'timing/data': 0.0001736050471663475, 'timing/model': 0.4581443341448903, 'learning_rate/action_model': 8.25963515079371e-05, 'learning_rate/action_query_proj': 8.25963515079371e-05, 'learning_rate/base': 2.0649087876984276e-05, 'epoch': 0.17}) +[2026-07-26 21:30:24,785][starVLA.training.train_starvla][INFO] - Step 1401, Loss: {'train/loss': 0.39044255018234253, 'train/grad_norm_pre_clip': 4.552657127380371, 'timing/data': 0.00017925305292010307, 'timing/model': 0.4596921280026436, 'learning_rate/action_model': 8.257310733805583e-05, 'learning_rate/action_query_proj': 8.257310733805583e-05, 'learning_rate/base': 2.0643276834513957e-05, 'epoch': 0.17}) +[2026-07-26 21:30:30,309][starVLA.training.train_starvla][INFO] - Step 1402, Loss: {'train/loss': 0.3202682435512543, 'train/grad_norm_pre_clip': 3.517164945602417, 'timing/data': 0.00016887392848730087, 'timing/model': 0.458275961689651, 'learning_rate/action_model': 8.254985109839594e-05, 'learning_rate/action_query_proj': 8.254985109839594e-05, 'learning_rate/base': 2.0637462774598985e-05, 'epoch': 0.17}) +[2026-07-26 21:30:36,150][starVLA.training.train_starvla][INFO] - Step 1403, Loss: {'train/loss': 0.36453622579574585, 'train/grad_norm_pre_clip': 5.218937397003174, 'timing/data': 0.00017106812447309494, 'timing/model': 0.460877840872854, 'learning_rate/action_model': 8.252658279813868e-05, 'learning_rate/action_query_proj': 8.252658279813868e-05, 'learning_rate/base': 2.063164569953467e-05, 'epoch': 0.17}) +[2026-07-26 21:30:41,672][starVLA.training.train_starvla][INFO] - Step 1404, Loss: {'train/loss': 0.27472415566444397, 'train/grad_norm_pre_clip': 2.6762828826904297, 'timing/data': 0.00017302809283137321, 'timing/model': 0.45843560295179486, 'learning_rate/action_model': 8.250330244646996e-05, 'learning_rate/action_query_proj': 8.250330244646996e-05, 'learning_rate/base': 2.062582561161749e-05, 'epoch': 0.17}) +[2026-07-26 21:30:47,221][starVLA.training.train_starvla][INFO] - Step 1405, Loss: {'train/loss': 0.4100026786327362, 'train/grad_norm_pre_clip': 3.5022976398468018, 'timing/data': 0.00017100106924772263, 'timing/model': 0.4621462970972061, 'learning_rate/action_model': 8.248001005258052e-05, 'learning_rate/action_query_proj': 8.248001005258052e-05, 'learning_rate/base': 2.062000251314513e-05, 'epoch': 0.17}) +[2026-07-26 21:30:52,770][starVLA.training.train_starvla][INFO] - Step 1406, Loss: {'train/loss': 0.4418923556804657, 'train/grad_norm_pre_clip': 5.273209095001221, 'timing/data': 0.00017052702605724335, 'timing/model': 0.4606821136549115, 'learning_rate/action_model': 8.24567056256658e-05, 'learning_rate/action_query_proj': 8.24567056256658e-05, 'learning_rate/base': 2.061417640641645e-05, 'epoch': 0.17}) +[2026-07-26 21:30:58,310][starVLA.training.train_starvla][INFO] - Step 1407, Loss: {'train/loss': 0.37627726793289185, 'train/grad_norm_pre_clip': 6.17742395401001, 'timing/data': 0.00017142901197075844, 'timing/model': 0.4700390649959445, 'learning_rate/action_model': 8.243338917492607e-05, 'learning_rate/action_query_proj': 8.243338917492607e-05, 'learning_rate/base': 2.0608347293731516e-05, 'epoch': 0.17}) +[2026-07-26 21:31:03,906][starVLA.training.train_starvla][INFO] - Step 1408, Loss: {'train/loss': 0.4144428074359894, 'train/grad_norm_pre_clip': 5.718090057373047, 'timing/data': 0.00018653692677617073, 'timing/model': 0.4710159949027002, 'learning_rate/action_model': 8.241006070956626e-05, 'learning_rate/action_query_proj': 8.241006070956626e-05, 'learning_rate/base': 2.0602515177391565e-05, 'epoch': 0.17}) +[2026-07-26 21:31:09,496][starVLA.training.train_starvla][INFO] - Step 1409, Loss: {'train/loss': 0.5095453858375549, 'train/grad_norm_pre_clip': 3.9519386291503906, 'timing/data': 0.00016653211787343025, 'timing/model': 0.49529182724654675, 'learning_rate/action_model': 8.238672023879607e-05, 'learning_rate/action_query_proj': 8.238672023879607e-05, 'learning_rate/base': 2.059668005969902e-05, 'epoch': 0.17}) +[2026-07-26 21:31:15,287][starVLA.training.train_starvla][INFO] - Step 1410, Loss: {'train/loss': 0.34591978788375854, 'train/grad_norm_pre_clip': 3.060091018676758, 'timing/data': 0.00016846973448991776, 'timing/model': 0.45971895568072796, 'learning_rate/action_model': 8.236336777182998e-05, 'learning_rate/action_query_proj': 8.236336777182998e-05, 'learning_rate/base': 2.0590841942957496e-05, 'epoch': 0.17}) +[2026-07-26 21:31:21,103][starVLA.training.train_starvla][INFO] - Step 1411, Loss: {'train/loss': 0.316672682762146, 'train/grad_norm_pre_clip': 3.349278450012207, 'timing/data': 0.0001663840375840664, 'timing/model': 0.46041935682296753, 'learning_rate/action_model': 8.234000331788714e-05, 'learning_rate/action_query_proj': 8.234000331788714e-05, 'learning_rate/base': 2.0585000829471786e-05, 'epoch': 0.17}) +[2026-07-26 21:31:26,646][starVLA.training.train_starvla][INFO] - Step 1412, Loss: {'train/loss': 0.392322301864624, 'train/grad_norm_pre_clip': 4.295277118682861, 'timing/data': 0.00017237337306141853, 'timing/model': 0.4602508437819779, 'learning_rate/action_model': 8.231662688619149e-05, 'learning_rate/action_query_proj': 8.231662688619149e-05, 'learning_rate/base': 2.0579156721547873e-05, 'epoch': 0.17}) +[2026-07-26 21:31:32,203][starVLA.training.train_starvla][INFO] - Step 1413, Loss: {'train/loss': 0.4083191156387329, 'train/grad_norm_pre_clip': 5.944623947143555, 'timing/data': 0.00016939686611294746, 'timing/model': 0.4608746888116002, 'learning_rate/action_model': 8.229323848597169e-05, 'learning_rate/action_query_proj': 8.229323848597169e-05, 'learning_rate/base': 2.057330962149292e-05, 'epoch': 0.17}) +[2026-07-26 21:31:37,742][starVLA.training.train_starvla][INFO] - Step 1414, Loss: {'train/loss': 0.39067837595939636, 'train/grad_norm_pre_clip': 3.095592975616455, 'timing/data': 0.00016473094001412392, 'timing/model': 0.4615629827603698, 'learning_rate/action_model': 8.226983812646106e-05, 'learning_rate/action_query_proj': 8.226983812646106e-05, 'learning_rate/base': 2.0567459531615266e-05, 'epoch': 0.17}) +[2026-07-26 21:31:43,285][starVLA.training.train_starvla][INFO] - Step 1415, Loss: {'train/loss': 0.3569673001766205, 'train/grad_norm_pre_clip': 5.243497371673584, 'timing/data': 0.00017122086137533188, 'timing/model': 0.4575765081681311, 'learning_rate/action_model': 8.224642581689773e-05, 'learning_rate/action_query_proj': 8.224642581689773e-05, 'learning_rate/base': 2.0561606454224433e-05, 'epoch': 0.17}) +[2026-07-26 21:31:48,842][starVLA.training.train_starvla][INFO] - Step 1416, Loss: {'train/loss': 0.39989951252937317, 'train/grad_norm_pre_clip': 3.4242191314697266, 'timing/data': 0.00017729075625538826, 'timing/model': 0.4618597533553839, 'learning_rate/action_model': 8.22230015665245e-05, 'learning_rate/action_query_proj': 8.22230015665245e-05, 'learning_rate/base': 2.0555750391631125e-05, 'epoch': 0.17}) +[2026-07-26 21:31:54,384][starVLA.training.train_starvla][INFO] - Step 1417, Loss: {'train/loss': 0.39077895879745483, 'train/grad_norm_pre_clip': 3.2943787574768066, 'timing/data': 0.0001698029227554798, 'timing/model': 0.46044796984642744, 'learning_rate/action_model': 8.219956538458887e-05, 'learning_rate/action_query_proj': 8.219956538458887e-05, 'learning_rate/base': 2.0549891346147217e-05, 'epoch': 0.17}) +[2026-07-26 21:31:59,926][starVLA.training.train_starvla][INFO] - Step 1418, Loss: {'train/loss': 0.30410635471343994, 'train/grad_norm_pre_clip': 3.1602463722229004, 'timing/data': 0.00016968324780464172, 'timing/model': 0.4602286610752344, 'learning_rate/action_model': 8.217611728034312e-05, 'learning_rate/action_query_proj': 8.217611728034312e-05, 'learning_rate/base': 2.054402932008578e-05, 'epoch': 0.17}) +[2026-07-26 21:32:05,484][starVLA.training.train_starvla][INFO] - Step 1419, Loss: {'train/loss': 0.38854271173477173, 'train/grad_norm_pre_clip': 5.629455089569092, 'timing/data': 0.0001789778470993042, 'timing/model': 0.45775796798989177, 'learning_rate/action_model': 8.215265726304417e-05, 'learning_rate/action_query_proj': 8.215265726304417e-05, 'learning_rate/base': 2.0538164315761043e-05, 'epoch': 0.17}) +[2026-07-26 21:32:11,026][starVLA.training.train_starvla][INFO] - Step 1420, Loss: {'train/loss': 0.3896652162075043, 'train/grad_norm_pre_clip': 3.784677743911743, 'timing/data': 0.0001832982525229454, 'timing/model': 0.4579886058345437, 'learning_rate/action_model': 8.212918534195363e-05, 'learning_rate/action_query_proj': 8.212918534195363e-05, 'learning_rate/base': 2.0532296335488408e-05, 'epoch': 0.17}) +[2026-07-26 21:32:16,584][starVLA.training.train_starvla][INFO] - Step 1421, Loss: {'train/loss': 0.3353220820426941, 'train/grad_norm_pre_clip': 4.298649311065674, 'timing/data': 0.00017179129645228386, 'timing/model': 0.4604273922741413, 'learning_rate/action_model': 8.210570152633788e-05, 'learning_rate/action_query_proj': 8.210570152633788e-05, 'learning_rate/base': 2.052642538158447e-05, 'epoch': 0.17}) +[2026-07-26 21:32:22,151][starVLA.training.train_starvla][INFO] - Step 1422, Loss: {'train/loss': 0.3806453049182892, 'train/grad_norm_pre_clip': 4.176231384277344, 'timing/data': 0.00018159020692110062, 'timing/model': 0.46376575576141477, 'learning_rate/action_model': 8.208220582546796e-05, 'learning_rate/action_query_proj': 8.208220582546796e-05, 'learning_rate/base': 2.052055145636699e-05, 'epoch': 0.17}) +[2026-07-26 21:32:27,826][starVLA.training.train_starvla][INFO] - Step 1423, Loss: {'train/loss': 0.3972342014312744, 'train/grad_norm_pre_clip': 3.9485788345336914, 'timing/data': 0.00017083808779716492, 'timing/model': 0.5912617268040776, 'learning_rate/action_model': 8.205869824861957e-05, 'learning_rate/action_query_proj': 8.205869824861957e-05, 'learning_rate/base': 2.0514674562154894e-05, 'epoch': 0.17}) +[2026-07-26 21:32:33,366][starVLA.training.train_starvla][INFO] - Step 1424, Loss: {'train/loss': 0.3070485591888428, 'train/grad_norm_pre_clip': 5.258230686187744, 'timing/data': 0.00016947416588664055, 'timing/model': 0.4598728618584573, 'learning_rate/action_model': 8.203517880507319e-05, 'learning_rate/action_query_proj': 8.203517880507319e-05, 'learning_rate/base': 2.0508794701268297e-05, 'epoch': 0.17}) +[2026-07-26 21:32:39,186][starVLA.training.train_starvla][INFO] - Step 1425, Loss: {'train/loss': 0.2872981131076813, 'train/grad_norm_pre_clip': 2.944812297821045, 'timing/data': 0.00017367210239171982, 'timing/model': 0.4605518691241741, 'learning_rate/action_model': 8.201164750411387e-05, 'learning_rate/action_query_proj': 8.201164750411387e-05, 'learning_rate/base': 2.0502911876028467e-05, 'epoch': 0.17}) +[2026-07-26 21:32:44,978][starVLA.training.train_starvla][INFO] - Step 1426, Loss: {'train/loss': 0.402308851480484, 'train/grad_norm_pre_clip': 4.498889446258545, 'timing/data': 0.0001720278523862362, 'timing/model': 0.46018514409661293, 'learning_rate/action_model': 8.198810435503139e-05, 'learning_rate/action_query_proj': 8.198810435503139e-05, 'learning_rate/base': 2.0497026088757847e-05, 'epoch': 0.17}) +[2026-07-26 21:32:50,515][starVLA.training.train_starvla][INFO] - Step 1427, Loss: {'train/loss': 0.39858531951904297, 'train/grad_norm_pre_clip': 6.975167274475098, 'timing/data': 0.00016911188140511513, 'timing/model': 0.4602990997955203, 'learning_rate/action_model': 8.196454936712023e-05, 'learning_rate/action_query_proj': 8.196454936712023e-05, 'learning_rate/base': 2.0491137341780056e-05, 'epoch': 0.17}) +[2026-07-26 21:32:56,088][starVLA.training.train_starvla][INFO] - Step 1428, Loss: {'train/loss': 0.42863839864730835, 'train/grad_norm_pre_clip': 3.489229202270508, 'timing/data': 0.00017083389684557915, 'timing/model': 0.46047935681417584, 'learning_rate/action_model': 8.194098254967954e-05, 'learning_rate/action_query_proj': 8.194098254967954e-05, 'learning_rate/base': 2.0485245637419884e-05, 'epoch': 0.17}) +[2026-07-26 21:33:01,655][starVLA.training.train_starvla][INFO] - Step 1429, Loss: {'train/loss': 0.3807205557823181, 'train/grad_norm_pre_clip': 2.920198440551758, 'timing/data': 0.00016919942572712898, 'timing/model': 0.4589814939536154, 'learning_rate/action_model': 8.19174039120131e-05, 'learning_rate/action_query_proj': 8.19174039120131e-05, 'learning_rate/base': 2.0479350978003274e-05, 'epoch': 0.17}) +[2026-07-26 21:33:07,416][starVLA.training.train_starvla][INFO] - Step 1430, Loss: {'train/loss': 0.27586787939071655, 'train/grad_norm_pre_clip': 3.9887263774871826, 'timing/data': 0.0001709870994091034, 'timing/model': 0.45840504625812173, 'learning_rate/action_model': 8.18938134634294e-05, 'learning_rate/action_query_proj': 8.18938134634294e-05, 'learning_rate/base': 2.047345336585735e-05, 'epoch': 0.17}) +[2026-07-26 21:33:12,931][starVLA.training.train_starvla][INFO] - Step 1431, Loss: {'train/loss': 0.3567427694797516, 'train/grad_norm_pre_clip': 3.7478020191192627, 'timing/data': 0.00017126789316534996, 'timing/model': 0.45936473505571485, 'learning_rate/action_model': 8.187021121324157e-05, 'learning_rate/action_query_proj': 8.187021121324157e-05, 'learning_rate/base': 2.0467552803310393e-05, 'epoch': 0.17}) +[2026-07-26 21:33:18,443][starVLA.training.train_starvla][INFO] - Step 1432, Loss: {'train/loss': 0.3191695511341095, 'train/grad_norm_pre_clip': 3.6692612171173096, 'timing/data': 0.00018057692795991898, 'timing/model': 0.4585212799720466, 'learning_rate/action_model': 8.184659717076741e-05, 'learning_rate/action_query_proj': 8.184659717076741e-05, 'learning_rate/base': 2.0461649292691854e-05, 'epoch': 0.17}) +[2026-07-26 21:33:23,958][starVLA.training.train_starvla][INFO] - Step 1433, Loss: {'train/loss': 0.4756792187690735, 'train/grad_norm_pre_clip': 3.5810089111328125, 'timing/data': 0.00017078733071684837, 'timing/model': 0.45687603671103716, 'learning_rate/action_model': 8.182297134532938e-05, 'learning_rate/action_query_proj': 8.182297134532938e-05, 'learning_rate/base': 2.0455742836332346e-05, 'epoch': 0.17}) +[2026-07-26 21:33:29,503][starVLA.training.train_starvla][INFO] - Step 1434, Loss: {'train/loss': 0.4166451692581177, 'train/grad_norm_pre_clip': 3.3907854557037354, 'timing/data': 0.00016872398555278778, 'timing/model': 0.4589449497871101, 'learning_rate/action_model': 8.179933374625454e-05, 'learning_rate/action_query_proj': 8.179933374625454e-05, 'learning_rate/base': 2.0449833436563636e-05, 'epoch': 0.17}) +[2026-07-26 21:33:35,068][starVLA.training.train_starvla][INFO] - Step 1435, Loss: {'train/loss': 0.2945256531238556, 'train/grad_norm_pre_clip': 3.210094690322876, 'timing/data': 0.00016639893874526024, 'timing/model': 0.460394490044564, 'learning_rate/action_model': 8.17756843828747e-05, 'learning_rate/action_query_proj': 8.17756843828747e-05, 'learning_rate/base': 2.0443921095718674e-05, 'epoch': 0.17}) +[2026-07-26 21:33:40,636][starVLA.training.train_starvla][INFO] - Step 1436, Loss: {'train/loss': 0.2559013366699219, 'train/grad_norm_pre_clip': 3.71869158744812, 'timing/data': 0.00017280131578445435, 'timing/model': 0.45912804966792464, 'learning_rate/action_model': 8.17520232645262e-05, 'learning_rate/action_query_proj': 8.17520232645262e-05, 'learning_rate/base': 2.043800581613155e-05, 'epoch': 0.17}) +[2026-07-26 21:33:46,194][starVLA.training.train_starvla][INFO] - Step 1437, Loss: {'train/loss': 0.32066869735717773, 'train/grad_norm_pre_clip': 4.3468708992004395, 'timing/data': 0.00016484875231981277, 'timing/model': 0.458786535076797, 'learning_rate/action_model': 8.17283504005501e-05, 'learning_rate/action_query_proj': 8.17283504005501e-05, 'learning_rate/base': 2.0432087600137525e-05, 'epoch': 0.17}) +[2026-07-26 21:33:51,762][starVLA.training.train_starvla][INFO] - Step 1438, Loss: {'train/loss': 0.47634458541870117, 'train/grad_norm_pre_clip': 4.879021167755127, 'timing/data': 0.00017451774328947067, 'timing/model': 0.45971178682520986, 'learning_rate/action_model': 8.170466580029207e-05, 'learning_rate/action_query_proj': 8.170466580029207e-05, 'learning_rate/base': 2.0426166450073018e-05, 'epoch': 0.17}) +[2026-07-26 21:33:57,330][starVLA.training.train_starvla][INFO] - Step 1439, Loss: {'train/loss': 0.4059036672115326, 'train/grad_norm_pre_clip': 3.1992883682250977, 'timing/data': 0.00017113890498876572, 'timing/model': 0.4598886137828231, 'learning_rate/action_model': 8.168096947310241e-05, 'learning_rate/action_query_proj': 8.168096947310241e-05, 'learning_rate/base': 2.0420242368275603e-05, 'epoch': 0.17}) +[2026-07-26 21:34:02,844][starVLA.training.train_starvla][INFO] - Step 1440, Loss: {'train/loss': 0.24113242328166962, 'train/grad_norm_pre_clip': 3.04097318649292, 'timing/data': 0.00017474917694926262, 'timing/model': 0.46223300602287054, 'learning_rate/action_model': 8.165726142833606e-05, 'learning_rate/action_query_proj': 8.165726142833606e-05, 'learning_rate/base': 2.0414315357084015e-05, 'epoch': 0.17}) +[2026-07-26 21:34:08,336][starVLA.training.train_starvla][INFO] - Step 1441, Loss: {'train/loss': 0.39525121450424194, 'train/grad_norm_pre_clip': 4.1833624839782715, 'timing/data': 0.0001740441657602787, 'timing/model': 0.45809831423684955, 'learning_rate/action_model': 8.163354167535257e-05, 'learning_rate/action_query_proj': 8.163354167535257e-05, 'learning_rate/base': 2.0408385418838143e-05, 'epoch': 0.17}) +[2026-07-26 21:34:13,829][starVLA.training.train_starvla][INFO] - Step 1442, Loss: {'train/loss': 0.4131643772125244, 'train/grad_norm_pre_clip': 5.782276153564453, 'timing/data': 0.00017432495951652527, 'timing/model': 0.45859692664816976, 'learning_rate/action_model': 8.160981022351615e-05, 'learning_rate/action_query_proj': 8.160981022351615e-05, 'learning_rate/base': 2.0402452555879038e-05, 'epoch': 0.17}) +[2026-07-26 21:34:19,327][starVLA.training.train_starvla][INFO] - Step 1443, Loss: {'train/loss': 0.3188043236732483, 'train/grad_norm_pre_clip': 2.6440584659576416, 'timing/data': 0.00020576594397425652, 'timing/model': 0.45832995092496276, 'learning_rate/action_model': 8.158606708219555e-05, 'learning_rate/action_query_proj': 8.158606708219555e-05, 'learning_rate/base': 2.0396516770548888e-05, 'epoch': 0.18}) +[2026-07-26 21:34:24,816][starVLA.training.train_starvla][INFO] - Step 1444, Loss: {'train/loss': 0.27709296345710754, 'train/grad_norm_pre_clip': 3.1157162189483643, 'timing/data': 0.00018069008365273476, 'timing/model': 0.4589483249001205, 'learning_rate/action_model': 8.156231226076425e-05, 'learning_rate/action_query_proj': 8.156231226076425e-05, 'learning_rate/base': 2.039057806519106e-05, 'epoch': 0.18}) +[2026-07-26 21:34:30,312][starVLA.training.train_starvla][INFO] - Step 1445, Loss: {'train/loss': 0.4700380861759186, 'train/grad_norm_pre_clip': 3.9089808464050293, 'timing/data': 0.00017850985750555992, 'timing/model': 0.4581377641297877, 'learning_rate/action_model': 8.153854576860024e-05, 'learning_rate/action_query_proj': 8.153854576860024e-05, 'learning_rate/base': 2.038463644215006e-05, 'epoch': 0.18}) +[2026-07-26 21:34:35,807][starVLA.training.train_starvla][INFO] - Step 1446, Loss: {'train/loss': 0.31759709119796753, 'train/grad_norm_pre_clip': 2.9259846210479736, 'timing/data': 0.00019122567027807236, 'timing/model': 0.4593752110376954, 'learning_rate/action_model': 8.151476761508615e-05, 'learning_rate/action_query_proj': 8.151476761508615e-05, 'learning_rate/base': 2.0378691903771538e-05, 'epoch': 0.18}) +[2026-07-26 21:34:41,300][starVLA.training.train_starvla][INFO] - Step 1447, Loss: {'train/loss': 0.3436287045478821, 'train/grad_norm_pre_clip': 3.2654290199279785, 'timing/data': 0.00017812009900808334, 'timing/model': 0.4583597769960761, 'learning_rate/action_model': 8.149097780960924e-05, 'learning_rate/action_query_proj': 8.149097780960924e-05, 'learning_rate/base': 2.037274445240231e-05, 'epoch': 0.18}) +[2026-07-26 21:34:46,801][starVLA.training.train_starvla][INFO] - Step 1448, Loss: {'train/loss': 0.3702239990234375, 'train/grad_norm_pre_clip': 4.274439334869385, 'timing/data': 0.0001727202907204628, 'timing/model': 0.45916373608633876, 'learning_rate/action_model': 8.146717636156133e-05, 'learning_rate/action_query_proj': 8.146717636156133e-05, 'learning_rate/base': 2.036679409039033e-05, 'epoch': 0.18}) +[2026-07-26 21:34:52,295][starVLA.training.train_starvla][INFO] - Step 1449, Loss: {'train/loss': 0.3391251564025879, 'train/grad_norm_pre_clip': 3.812770366668701, 'timing/data': 0.00017956411466002464, 'timing/model': 0.45949608692899346, 'learning_rate/action_model': 8.144336328033886e-05, 'learning_rate/action_query_proj': 8.144336328033886e-05, 'learning_rate/base': 2.0360840820084715e-05, 'epoch': 0.18}) +[2026-07-26 21:34:57,801][starVLA.training.train_starvla][INFO] - Step 1450, Loss: {'train/loss': 0.36756372451782227, 'train/grad_norm_pre_clip': 2.731671094894409, 'timing/data': 0.00017688190564513206, 'timing/model': 0.45940582267940044, 'learning_rate/action_model': 8.141953857534288e-05, 'learning_rate/action_query_proj': 8.141953857534288e-05, 'learning_rate/base': 2.035488464383572e-05, 'epoch': 0.18}) +[2026-07-26 21:35:03,299][starVLA.training.train_starvla][INFO] - Step 1451, Loss: {'train/loss': 0.27992263436317444, 'train/grad_norm_pre_clip': 4.1306352615356445, 'timing/data': 0.00017095822840929031, 'timing/model': 0.459453874733299, 'learning_rate/action_model': 8.139570225597897e-05, 'learning_rate/action_query_proj': 8.139570225597897e-05, 'learning_rate/base': 2.0348925563994743e-05, 'epoch': 0.18}) +[2026-07-26 21:35:08,798][starVLA.training.train_starvla][INFO] - Step 1452, Loss: {'train/loss': 0.5090072154998779, 'train/grad_norm_pre_clip': 4.159453868865967, 'timing/data': 0.00017910171300172806, 'timing/model': 0.45921526616439223, 'learning_rate/action_model': 8.137185433165734e-05, 'learning_rate/action_query_proj': 8.137185433165734e-05, 'learning_rate/base': 2.0342963582914336e-05, 'epoch': 0.18}) +[2026-07-26 21:35:14,306][starVLA.training.train_starvla][INFO] - Step 1453, Loss: {'train/loss': 0.3689953088760376, 'train/grad_norm_pre_clip': 4.960443019866943, 'timing/data': 0.00018961075693368912, 'timing/model': 0.45826270477846265, 'learning_rate/action_model': 8.13479948117928e-05, 'learning_rate/action_query_proj': 8.13479948117928e-05, 'learning_rate/base': 2.03369987029482e-05, 'epoch': 0.18}) +[2026-07-26 21:35:19,828][starVLA.training.train_starvla][INFO] - Step 1454, Loss: {'train/loss': 0.38268959522247314, 'train/grad_norm_pre_clip': 3.243074655532837, 'timing/data': 0.00018787290900945663, 'timing/model': 0.4590895897708833, 'learning_rate/action_model': 8.132412370580468e-05, 'learning_rate/action_query_proj': 8.132412370580468e-05, 'learning_rate/base': 2.033103092645117e-05, 'epoch': 0.18}) +[2026-07-26 21:35:25,331][starVLA.training.train_starvla][INFO] - Step 1455, Loss: {'train/loss': 0.28552284836769104, 'train/grad_norm_pre_clip': 3.741192102432251, 'timing/data': 0.00018139276653528214, 'timing/model': 0.4592648050747812, 'learning_rate/action_model': 8.130024102311692e-05, 'learning_rate/action_query_proj': 8.130024102311692e-05, 'learning_rate/base': 2.032506025577923e-05, 'epoch': 0.18}) +[2026-07-26 21:35:30,891][starVLA.training.train_starvla][INFO] - Step 1456, Loss: {'train/loss': 0.46527037024497986, 'train/grad_norm_pre_clip': 5.215806484222412, 'timing/data': 0.00018413318321108818, 'timing/model': 0.4592095999978483, 'learning_rate/action_model': 8.127634677315804e-05, 'learning_rate/action_query_proj': 8.127634677315804e-05, 'learning_rate/base': 2.031908669328951e-05, 'epoch': 0.18}) +[2026-07-26 21:35:36,447][starVLA.training.train_starvla][INFO] - Step 1457, Loss: {'train/loss': 0.3578125536441803, 'train/grad_norm_pre_clip': 4.9433794021606445, 'timing/data': 0.00018745707347989082, 'timing/model': 0.4590328773483634, 'learning_rate/action_model': 8.125244096536111e-05, 'learning_rate/action_query_proj': 8.125244096536111e-05, 'learning_rate/base': 2.0313110241340277e-05, 'epoch': 0.18}) +[2026-07-26 21:35:41,988][starVLA.training.train_starvla][INFO] - Step 1458, Loss: {'train/loss': 0.33734068274497986, 'train/grad_norm_pre_clip': 4.897422790527344, 'timing/data': 0.00018425891175866127, 'timing/model': 0.4599157958291471, 'learning_rate/action_model': 8.122852360916373e-05, 'learning_rate/action_query_proj': 8.122852360916373e-05, 'learning_rate/base': 2.0307130902290933e-05, 'epoch': 0.18}) +[2026-07-26 21:35:47,513][starVLA.training.train_starvla][INFO] - Step 1459, Loss: {'train/loss': 0.41865992546081543, 'train/grad_norm_pre_clip': 4.117283821105957, 'timing/data': 0.00019014626741409302, 'timing/model': 0.4594059302471578, 'learning_rate/action_model': 8.120459471400815e-05, 'learning_rate/action_query_proj': 8.120459471400815e-05, 'learning_rate/base': 2.0301148678502037e-05, 'epoch': 0.18}) +[2026-07-26 21:35:53,041][starVLA.training.train_starvla][INFO] - Step 1460, Loss: {'train/loss': 0.33886128664016724, 'train/grad_norm_pre_clip': 5.543848514556885, 'timing/data': 0.0001855781301856041, 'timing/model': 0.45942571805790067, 'learning_rate/action_model': 8.118065428934107e-05, 'learning_rate/action_query_proj': 8.118065428934107e-05, 'learning_rate/base': 2.0295163572335267e-05, 'epoch': 0.18}) +[2026-07-26 21:35:58,566][starVLA.training.train_starvla][INFO] - Step 1461, Loss: {'train/loss': 0.4349317252635956, 'train/grad_norm_pre_clip': 4.895069599151611, 'timing/data': 0.00017789332196116447, 'timing/model': 0.4582685362547636, 'learning_rate/action_model': 8.11567023446138e-05, 'learning_rate/action_query_proj': 8.11567023446138e-05, 'learning_rate/base': 2.028917558615345e-05, 'epoch': 0.18}) +[2026-07-26 21:36:04,139][starVLA.training.train_starvla][INFO] - Step 1462, Loss: {'train/loss': 0.4020538926124573, 'train/grad_norm_pre_clip': 3.745105028152466, 'timing/data': 0.00017471099272370338, 'timing/model': 0.45842587016522884, 'learning_rate/action_model': 8.11327388892822e-05, 'learning_rate/action_query_proj': 8.11327388892822e-05, 'learning_rate/base': 2.028318472232055e-05, 'epoch': 0.18}) +[2026-07-26 21:36:09,682][starVLA.training.train_starvla][INFO] - Step 1463, Loss: {'train/loss': 0.30064257979393005, 'train/grad_norm_pre_clip': 3.481287717819214, 'timing/data': 0.00017187511548399925, 'timing/model': 0.45831948379054666, 'learning_rate/action_model': 8.110876393280667e-05, 'learning_rate/action_query_proj': 8.110876393280667e-05, 'learning_rate/base': 2.0277190983201668e-05, 'epoch': 0.18}) +[2026-07-26 21:36:15,217][starVLA.training.train_starvla][INFO] - Step 1464, Loss: {'train/loss': 0.4241155982017517, 'train/grad_norm_pre_clip': 5.0375518798828125, 'timing/data': 0.00017749937251210213, 'timing/model': 0.4594285637140274, 'learning_rate/action_model': 8.108477748465214e-05, 'learning_rate/action_query_proj': 8.108477748465214e-05, 'learning_rate/base': 2.0271194371163034e-05, 'epoch': 0.18}) +[2026-07-26 21:36:20,743][starVLA.training.train_starvla][INFO] - Step 1465, Loss: {'train/loss': 0.38515445590019226, 'train/grad_norm_pre_clip': 3.172482490539551, 'timing/data': 0.00016845576465129852, 'timing/model': 0.45810195710510015, 'learning_rate/action_model': 8.106077955428806e-05, 'learning_rate/action_query_proj': 8.106077955428806e-05, 'learning_rate/base': 2.0265194888572016e-05, 'epoch': 0.18}) +[2026-07-26 21:36:26,287][starVLA.training.train_starvla][INFO] - Step 1466, Loss: {'train/loss': 0.35710838437080383, 'train/grad_norm_pre_clip': 3.123338222503662, 'timing/data': 0.0001932918094098568, 'timing/model': 0.4600912439636886, 'learning_rate/action_model': 8.103677015118847e-05, 'learning_rate/action_query_proj': 8.103677015118847e-05, 'learning_rate/base': 2.0259192537797118e-05, 'epoch': 0.18}) +[2026-07-26 21:36:31,827][starVLA.training.train_starvla][INFO] - Step 1467, Loss: {'train/loss': 0.328105628490448, 'train/grad_norm_pre_clip': 3.760448694229126, 'timing/data': 0.00017732009291648865, 'timing/model': 0.45783189265057445, 'learning_rate/action_model': 8.101274928483186e-05, 'learning_rate/action_query_proj': 8.101274928483186e-05, 'learning_rate/base': 2.0253187321207964e-05, 'epoch': 0.18}) +[2026-07-26 21:36:37,350][starVLA.training.train_starvla][INFO] - Step 1468, Loss: {'train/loss': 0.45048680901527405, 'train/grad_norm_pre_clip': 5.22537088394165, 'timing/data': 0.00019020214676856995, 'timing/model': 0.45756296068429947, 'learning_rate/action_model': 8.098871696470128e-05, 'learning_rate/action_query_proj': 8.098871696470128e-05, 'learning_rate/base': 2.024717924117532e-05, 'epoch': 0.18}) +[2026-07-26 21:36:42,879][starVLA.training.train_starvla][INFO] - Step 1469, Loss: {'train/loss': 0.35458120703697205, 'train/grad_norm_pre_clip': 4.777708053588867, 'timing/data': 0.0001764860935509205, 'timing/model': 0.45813177805393934, 'learning_rate/action_model': 8.096467320028438e-05, 'learning_rate/action_query_proj': 8.096467320028438e-05, 'learning_rate/base': 2.0241168300071096e-05, 'epoch': 0.18}) +[2026-07-26 21:36:48,441][starVLA.training.train_starvla][INFO] - Step 1470, Loss: {'train/loss': 0.26890134811401367, 'train/grad_norm_pre_clip': 3.3659307956695557, 'timing/data': 0.00019026873633265495, 'timing/model': 0.4592627203091979, 'learning_rate/action_model': 8.09406180010732e-05, 'learning_rate/action_query_proj': 8.09406180010732e-05, 'learning_rate/base': 2.02351545002683e-05, 'epoch': 0.18}) +[2026-07-26 21:36:54,345][starVLA.training.train_starvla][INFO] - Step 1471, Loss: {'train/loss': 0.3875579535961151, 'train/grad_norm_pre_clip': 3.088031530380249, 'timing/data': 0.0001853080466389656, 'timing/model': 0.5960133410990238, 'learning_rate/action_model': 8.091655137656434e-05, 'learning_rate/action_query_proj': 8.091655137656434e-05, 'learning_rate/base': 2.0229137844141086e-05, 'epoch': 0.18}) +[2026-07-26 21:36:59,940][starVLA.training.train_starvla][INFO] - Step 1472, Loss: {'train/loss': 0.5325100421905518, 'train/grad_norm_pre_clip': 2.8607330322265625, 'timing/data': 0.00018674088642001152, 'timing/model': 0.4584208922460675, 'learning_rate/action_model': 8.089247333625897e-05, 'learning_rate/action_query_proj': 8.089247333625897e-05, 'learning_rate/base': 2.022311833406474e-05, 'epoch': 0.18}) +[2026-07-26 21:37:05,506][starVLA.training.train_starvla][INFO] - Step 1473, Loss: {'train/loss': 0.39501336216926575, 'train/grad_norm_pre_clip': 2.9817607402801514, 'timing/data': 0.00017806189134716988, 'timing/model': 0.4592765960842371, 'learning_rate/action_model': 8.08683838896627e-05, 'learning_rate/action_query_proj': 8.08683838896627e-05, 'learning_rate/base': 2.0217095972415676e-05, 'epoch': 0.18}) +[2026-07-26 21:37:11,046][starVLA.training.train_starvla][INFO] - Step 1474, Loss: {'train/loss': 0.4713748097419739, 'train/grad_norm_pre_clip': 4.775321960449219, 'timing/data': 0.0001774309203028679, 'timing/model': 0.4591151848435402, 'learning_rate/action_model': 8.084428304628563e-05, 'learning_rate/action_query_proj': 8.084428304628563e-05, 'learning_rate/base': 2.0211070761571407e-05, 'epoch': 0.18}) +[2026-07-26 21:37:16,565][starVLA.training.train_starvla][INFO] - Step 1475, Loss: {'train/loss': 0.3653515577316284, 'train/grad_norm_pre_clip': 3.6173338890075684, 'timing/data': 0.00017820997163653374, 'timing/model': 0.45865203673020005, 'learning_rate/action_model': 8.082017081564244e-05, 'learning_rate/action_query_proj': 8.082017081564244e-05, 'learning_rate/base': 2.020504270391061e-05, 'epoch': 0.18}) +[2026-07-26 21:37:22,106][starVLA.training.train_starvla][INFO] - Step 1476, Loss: {'train/loss': 0.3133578896522522, 'train/grad_norm_pre_clip': 2.8016161918640137, 'timing/data': 0.00017667189240455627, 'timing/model': 0.45880602300167084, 'learning_rate/action_model': 8.079604720725223e-05, 'learning_rate/action_query_proj': 8.079604720725223e-05, 'learning_rate/base': 2.0199011801813058e-05, 'epoch': 0.18}) +[2026-07-26 21:37:27,628][starVLA.training.train_starvla][INFO] - Step 1477, Loss: {'train/loss': 0.34349948167800903, 'train/grad_norm_pre_clip': 4.698951244354248, 'timing/data': 0.00017243437469005585, 'timing/model': 0.4590443233028054, 'learning_rate/action_model': 8.077191223063862e-05, 'learning_rate/action_query_proj': 8.077191223063862e-05, 'learning_rate/base': 2.0192978057659655e-05, 'epoch': 0.18}) +[2026-07-26 21:37:33,154][starVLA.training.train_starvla][INFO] - Step 1478, Loss: {'train/loss': 0.434215247631073, 'train/grad_norm_pre_clip': 4.263153076171875, 'timing/data': 0.00017155101522803307, 'timing/model': 0.45816100714728236, 'learning_rate/action_model': 8.074776589532973e-05, 'learning_rate/action_query_proj': 8.074776589532973e-05, 'learning_rate/base': 2.0186941473832433e-05, 'epoch': 0.18}) +[2026-07-26 21:37:38,946][starVLA.training.train_starvla][INFO] - Step 1479, Loss: {'train/loss': 0.43567585945129395, 'train/grad_norm_pre_clip': 7.966265678405762, 'timing/data': 0.00016975216567516327, 'timing/model': 0.461907307151705, 'learning_rate/action_model': 8.072360821085813e-05, 'learning_rate/action_query_proj': 8.072360821085813e-05, 'learning_rate/base': 2.0180902052714534e-05, 'epoch': 0.18}) +[2026-07-26 21:37:44,471][starVLA.training.train_starvla][INFO] - Step 1480, Loss: {'train/loss': 0.22614574432373047, 'train/grad_norm_pre_clip': 3.6359739303588867, 'timing/data': 0.00022124731913208961, 'timing/model': 0.4586719712242484, 'learning_rate/action_model': 8.069943918676091e-05, 'learning_rate/action_query_proj': 8.069943918676091e-05, 'learning_rate/base': 2.017485979669023e-05, 'epoch': 0.18}) +[2026-07-26 21:37:49,994][starVLA.training.train_starvla][INFO] - Step 1481, Loss: {'train/loss': 0.30885592103004456, 'train/grad_norm_pre_clip': 2.7536001205444336, 'timing/data': 0.00018468406051397324, 'timing/model': 0.4588636038824916, 'learning_rate/action_model': 8.067525883257962e-05, 'learning_rate/action_query_proj': 8.067525883257962e-05, 'learning_rate/base': 2.0168814708144905e-05, 'epoch': 0.18}) +[2026-07-26 21:37:55,506][starVLA.training.train_starvla][INFO] - Step 1482, Loss: {'train/loss': 0.2850794196128845, 'train/grad_norm_pre_clip': 3.1507744789123535, 'timing/data': 0.00018132105469703674, 'timing/model': 0.45803498895838857, 'learning_rate/action_model': 8.065106715786024e-05, 'learning_rate/action_query_proj': 8.065106715786024e-05, 'learning_rate/base': 2.016276678946506e-05, 'epoch': 0.18}) +[2026-07-26 21:38:01,080][starVLA.training.train_starvla][INFO] - Step 1483, Loss: {'train/loss': 0.3968949317932129, 'train/grad_norm_pre_clip': 2.922966718673706, 'timing/data': 0.0001713908277451992, 'timing/model': 0.45850028097629547, 'learning_rate/action_model': 8.062686417215332e-05, 'learning_rate/action_query_proj': 8.062686417215332e-05, 'learning_rate/base': 2.015671604303833e-05, 'epoch': 0.18}) +[2026-07-26 21:38:06,605][starVLA.training.train_starvla][INFO] - Step 1484, Loss: {'train/loss': 0.35180267691612244, 'train/grad_norm_pre_clip': 5.274099349975586, 'timing/data': 0.00017578108236193657, 'timing/model': 0.45903912791982293, 'learning_rate/action_model': 8.060264988501378e-05, 'learning_rate/action_query_proj': 8.060264988501378e-05, 'learning_rate/base': 2.0150662471253444e-05, 'epoch': 0.18}) +[2026-07-26 21:38:12,124][starVLA.training.train_starvla][INFO] - Step 1485, Loss: {'train/loss': 0.38289469480514526, 'train/grad_norm_pre_clip': 5.169043064117432, 'timing/data': 0.00023443205282092094, 'timing/model': 0.4577396661043167, 'learning_rate/action_model': 8.057842430600105e-05, 'learning_rate/action_query_proj': 8.057842430600105e-05, 'learning_rate/base': 2.0144606076500262e-05, 'epoch': 0.18}) +[2026-07-26 21:38:17,642][starVLA.training.train_starvla][INFO] - Step 1486, Loss: {'train/loss': 0.39922428131103516, 'train/grad_norm_pre_clip': 8.20051097869873, 'timing/data': 0.00017033889889717102, 'timing/model': 0.4596026046201587, 'learning_rate/action_model': 8.055418744467899e-05, 'learning_rate/action_query_proj': 8.055418744467899e-05, 'learning_rate/base': 2.0138546861169747e-05, 'epoch': 0.18}) +[2026-07-26 21:38:23,166][starVLA.training.train_starvla][INFO] - Step 1487, Loss: {'train/loss': 0.27102163434028625, 'train/grad_norm_pre_clip': 4.121608734130859, 'timing/data': 0.00017426582053303719, 'timing/model': 0.45868227584287524, 'learning_rate/action_model': 8.052993931061594e-05, 'learning_rate/action_query_proj': 8.052993931061594e-05, 'learning_rate/base': 2.0132484827653986e-05, 'epoch': 0.18}) +[2026-07-26 21:38:28,704][starVLA.training.train_starvla][INFO] - Step 1488, Loss: {'train/loss': 0.3667188882827759, 'train/grad_norm_pre_clip': 3.7418949604034424, 'timing/data': 0.0001709391362965107, 'timing/model': 0.45977391116321087, 'learning_rate/action_model': 8.050567991338467e-05, 'learning_rate/action_query_proj': 8.050567991338467e-05, 'learning_rate/base': 2.0126419978346168e-05, 'epoch': 0.18}) +[2026-07-26 21:38:34,249][starVLA.training.train_starvla][INFO] - Step 1489, Loss: {'train/loss': 0.40028369426727295, 'train/grad_norm_pre_clip': 3.76208233833313, 'timing/data': 0.00017368514090776443, 'timing/model': 0.458962120115757, 'learning_rate/action_model': 8.048140926256242e-05, 'learning_rate/action_query_proj': 8.048140926256242e-05, 'learning_rate/base': 2.0120352315640604e-05, 'epoch': 0.18}) +[2026-07-26 21:38:39,771][starVLA.training.train_starvla][INFO] - Step 1490, Loss: {'train/loss': 0.33277028799057007, 'train/grad_norm_pre_clip': 2.878720998764038, 'timing/data': 0.00018375320360064507, 'timing/model': 0.45782403787598014, 'learning_rate/action_model': 8.045712736773086e-05, 'learning_rate/action_query_proj': 8.045712736773086e-05, 'learning_rate/base': 2.0114281841932714e-05, 'epoch': 0.18}) +[2026-07-26 21:38:45,288][starVLA.training.train_starvla][INFO] - Step 1491, Loss: {'train/loss': 0.2986007034778595, 'train/grad_norm_pre_clip': 3.733888864517212, 'timing/data': 0.00018826499581336975, 'timing/model': 0.45971623295918107, 'learning_rate/action_model': 8.043283423847606e-05, 'learning_rate/action_query_proj': 8.043283423847606e-05, 'learning_rate/base': 2.0108208559619015e-05, 'epoch': 0.18}) +[2026-07-26 21:38:50,807][starVLA.training.train_starvla][INFO] - Step 1492, Loss: {'train/loss': 0.4114035964012146, 'train/grad_norm_pre_clip': 4.509680271148682, 'timing/data': 0.00017443625256419182, 'timing/model': 0.4613554961979389, 'learning_rate/action_model': 8.040852988438861e-05, 'learning_rate/action_query_proj': 8.040852988438861e-05, 'learning_rate/base': 2.0102132471097153e-05, 'epoch': 0.18}) +[2026-07-26 21:38:56,337][starVLA.training.train_starvla][INFO] - Step 1493, Loss: {'train/loss': 0.3975406587123871, 'train/grad_norm_pre_clip': 7.1356682777404785, 'timing/data': 0.000173098873347044, 'timing/model': 0.47030480904504657, 'learning_rate/action_model': 8.038421431506348e-05, 'learning_rate/action_query_proj': 8.038421431506348e-05, 'learning_rate/base': 2.009605357876587e-05, 'epoch': 0.18}) +[2026-07-26 21:39:01,906][starVLA.training.train_starvla][INFO] - Step 1494, Loss: {'train/loss': 0.38667675852775574, 'train/grad_norm_pre_clip': 4.499229907989502, 'timing/data': 0.0001721610315144062, 'timing/model': 0.4709098697640002, 'learning_rate/action_model': 8.035988754010004e-05, 'learning_rate/action_query_proj': 8.035988754010004e-05, 'learning_rate/base': 2.008997188502501e-05, 'epoch': 0.18}) +[2026-07-26 21:39:07,473][starVLA.training.train_starvla][INFO] - Step 1495, Loss: {'train/loss': 0.32564693689346313, 'train/grad_norm_pre_clip': 4.211777687072754, 'timing/data': 0.00017083995044231415, 'timing/model': 0.47179923113435507, 'learning_rate/action_model': 8.033554956910214e-05, 'learning_rate/action_query_proj': 8.033554956910214e-05, 'learning_rate/base': 2.0083887392275534e-05, 'epoch': 0.18}) +[2026-07-26 21:39:13,031][starVLA.training.train_starvla][INFO] - Step 1496, Loss: {'train/loss': 0.3078159689903259, 'train/grad_norm_pre_clip': 3.9127426147460938, 'timing/data': 0.00017699971795082092, 'timing/model': 0.47002400318160653, 'learning_rate/action_model': 8.031120041167801e-05, 'learning_rate/action_query_proj': 8.031120041167801e-05, 'learning_rate/base': 2.0077800102919503e-05, 'epoch': 0.18}) +[2026-07-26 21:39:18,559][starVLA.training.train_starvla][INFO] - Step 1497, Loss: {'train/loss': 0.3753955662250519, 'train/grad_norm_pre_clip': 3.743534803390503, 'timing/data': 0.00018372293561697006, 'timing/model': 0.4774553822353482, 'learning_rate/action_model': 8.028684007744033e-05, 'learning_rate/action_query_proj': 8.028684007744033e-05, 'learning_rate/base': 2.0071710019360084e-05, 'epoch': 0.18}) +[2026-07-26 21:39:24,109][starVLA.training.train_starvla][INFO] - Step 1498, Loss: {'train/loss': 0.33130478858947754, 'train/grad_norm_pre_clip': 3.812182664871216, 'timing/data': 0.00018360884860157967, 'timing/model': 0.4587295716628432, 'learning_rate/action_model': 8.026246857600616e-05, 'learning_rate/action_query_proj': 8.026246857600616e-05, 'learning_rate/base': 2.006561714400154e-05, 'epoch': 0.18}) +[2026-07-26 21:39:29,669][starVLA.training.train_starvla][INFO] - Step 1499, Loss: {'train/loss': 0.4044131636619568, 'train/grad_norm_pre_clip': 5.119479656219482, 'timing/data': 0.00017069512978196144, 'timing/model': 0.4591481131501496, 'learning_rate/action_model': 8.0238085916997e-05, 'learning_rate/action_query_proj': 8.0238085916997e-05, 'learning_rate/base': 2.005952147924925e-05, 'epoch': 0.18}) +[2026-07-26 21:39:35,226][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 1500 +[2026-07-26 21:39:35,227][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 1500 +[2026-07-26 21:39:35,227][starVLA.training.train_starvla][INFO] - Step 1500, Loss: {'train/loss': 0.36449670791625977, 'train/grad_norm_pre_clip': 4.902956485748291, 'timing/data': 0.00017393706366419792, 'timing/model': 0.4592835530638695, 'learning_rate/action_model': 8.021369211003871e-05, 'learning_rate/action_query_proj': 8.021369211003871e-05, 'learning_rate/base': 2.0053423027509678e-05, 'epoch': 0.18}) +[2026-07-26 21:39:35,231][accelerate.accelerator][INFO] - Saving current state to /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_1500_state +[2026-07-26 21:39:35,231][accelerate.accelerator][INFO] - Saving DeepSpeed Model and Optimizer +[2026-07-26 21:40:21,433][accelerate.accelerator][INFO] - DeepSpeed Model and Optimizer saved to output dir /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_1500_state/pytorch_model +[2026-07-26 21:40:21,433][accelerate.checkpointing][INFO] - Sampler state for dataloader 0 saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_1500_state/sampler.bin +[2026-07-26 21:40:21,441][accelerate.checkpointing][INFO] - Random states saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_1500_state/random_states_0.pkl +[2026-07-26 21:40:54,236][starVLA.training.rl_games.checkpoint_sync][INFO] - HF checkpoint sync disabled; skipping upload for step 1500 +[2026-07-26 21:40:54,237][starVLA.training.train_starvla][INFO] - 📊 Saving accessed configuration... +[2026-07-26 21:40:54,251][starVLA.training.train_starvla][INFO] - ✅ Configuration files saved +[2026-07-26 21:40:59,945][starVLA.training.train_starvla][INFO] - Step 1501, Loss: {'train/loss': 0.3066575825214386, 'train/grad_norm_pre_clip': 4.8040008544921875, 'timing/data': 0.00017740577459335327, 'timing/model': 0.47070631198585033, 'learning_rate/action_model': 8.018928716476159e-05, 'learning_rate/action_query_proj': 8.018928716476159e-05, 'learning_rate/base': 2.0047321791190397e-05, 'epoch': 0.18}) +[2026-07-26 21:41:05,585][starVLA.training.train_starvla][INFO] - Step 1502, Loss: {'train/loss': 0.41128045320510864, 'train/grad_norm_pre_clip': 6.028574466705322, 'timing/data': 0.00017733825370669365, 'timing/model': 0.47070200787857175, 'learning_rate/action_model': 8.016487109080034e-05, 'learning_rate/action_query_proj': 8.016487109080034e-05, 'learning_rate/base': 2.0041217772700084e-05, 'epoch': 0.18}) +[2026-07-26 21:41:11,157][starVLA.training.train_starvla][INFO] - Step 1503, Loss: {'train/loss': 0.4518645405769348, 'train/grad_norm_pre_clip': 4.5518598556518555, 'timing/data': 0.00017679110169410706, 'timing/model': 0.46966957207769156, 'learning_rate/action_model': 8.014044389779404e-05, 'learning_rate/action_query_proj': 8.014044389779404e-05, 'learning_rate/base': 2.003511097444851e-05, 'epoch': 0.18}) +[2026-07-26 21:41:16,818][starVLA.training.train_starvla][INFO] - Step 1504, Loss: {'train/loss': 0.41955822706222534, 'train/grad_norm_pre_clip': 3.631714344024658, 'timing/data': 0.00017408467829227448, 'timing/model': 0.47817416302859783, 'learning_rate/action_model': 8.011600559538614e-05, 'learning_rate/action_query_proj': 8.011600559538614e-05, 'learning_rate/base': 2.0029001398846534e-05, 'epoch': 0.18}) +[2026-07-26 21:41:22,526][starVLA.training.train_starvla][INFO] - Step 1505, Loss: {'train/loss': 0.42842021584510803, 'train/grad_norm_pre_clip': 5.497223854064941, 'timing/data': 0.00017775315791368484, 'timing/model': 0.46597420098260045, 'learning_rate/action_model': 8.00915561932245e-05, 'learning_rate/action_query_proj': 8.00915561932245e-05, 'learning_rate/base': 2.0022889048306124e-05, 'epoch': 0.18}) +[2026-07-26 21:41:28,168][starVLA.training.train_starvla][INFO] - Step 1506, Loss: {'train/loss': 0.39477285742759705, 'train/grad_norm_pre_clip': 6.030727863311768, 'timing/data': 0.00017694104462862015, 'timing/model': 0.4680635267868638, 'learning_rate/action_model': 8.006709570096135e-05, 'learning_rate/action_query_proj': 8.006709570096135e-05, 'learning_rate/base': 2.0016773925240337e-05, 'epoch': 0.18}) +[2026-07-26 21:41:33,820][starVLA.training.train_starvla][INFO] - Step 1507, Loss: {'train/loss': 0.2825489938259125, 'train/grad_norm_pre_clip': 4.569980621337891, 'timing/data': 0.00021771667525172234, 'timing/model': 0.4663458871655166, 'learning_rate/action_model': 8.004262412825331e-05, 'learning_rate/action_query_proj': 8.004262412825331e-05, 'learning_rate/base': 2.001065603206333e-05, 'epoch': 0.18}) +[2026-07-26 21:41:39,481][starVLA.training.train_starvla][INFO] - Step 1508, Loss: {'train/loss': 0.4163304567337036, 'train/grad_norm_pre_clip': 4.00604248046875, 'timing/data': 0.0002060113474726677, 'timing/model': 0.48251445684581995, 'learning_rate/action_model': 8.001814148476138e-05, 'learning_rate/action_query_proj': 8.001814148476138e-05, 'learning_rate/base': 2.0004535371190346e-05, 'epoch': 0.18}) +[2026-07-26 21:41:45,164][starVLA.training.train_starvla][INFO] - Step 1509, Loss: {'train/loss': 0.2564347982406616, 'train/grad_norm_pre_clip': 2.7302308082580566, 'timing/data': 0.00018064212054014206, 'timing/model': 0.48792166030034423, 'learning_rate/action_model': 7.999364778015092e-05, 'learning_rate/action_query_proj': 7.999364778015092e-05, 'learning_rate/base': 1.999841194503773e-05, 'epoch': 0.18}) +[2026-07-26 21:41:50,800][starVLA.training.train_starvla][INFO] - Step 1510, Loss: {'train/loss': 0.3222109377384186, 'train/grad_norm_pre_clip': 2.006301164627075, 'timing/data': 0.00017976528033614159, 'timing/model': 0.4671370987780392, 'learning_rate/action_model': 7.996914302409167e-05, 'learning_rate/action_query_proj': 7.996914302409167e-05, 'learning_rate/base': 1.9992285756022917e-05, 'epoch': 0.18}) +[2026-07-26 21:41:56,418][starVLA.training.train_starvla][INFO] - Step 1511, Loss: {'train/loss': 0.3966909945011139, 'train/grad_norm_pre_clip': 4.600602149963379, 'timing/data': 0.0001774141564965248, 'timing/model': 0.4601458329707384, 'learning_rate/action_model': 7.994462722625766e-05, 'learning_rate/action_query_proj': 7.994462722625766e-05, 'learning_rate/base': 1.9986156806564415e-05, 'epoch': 0.18}) +[2026-07-26 21:42:02,064][starVLA.training.train_starvla][INFO] - Step 1512, Loss: {'train/loss': 0.34570232033729553, 'train/grad_norm_pre_clip': 2.394831418991089, 'timing/data': 0.00018641306087374687, 'timing/model': 0.46741120191290975, 'learning_rate/action_model': 7.992010039632741e-05, 'learning_rate/action_query_proj': 7.992010039632741e-05, 'learning_rate/base': 1.9980025099081852e-05, 'epoch': 0.18}) +[2026-07-26 21:42:07,699][starVLA.training.train_starvla][INFO] - Step 1513, Loss: {'train/loss': 0.378338098526001, 'train/grad_norm_pre_clip': 4.034554481506348, 'timing/data': 0.00016910210251808167, 'timing/model': 0.4659595503471792, 'learning_rate/action_model': 7.989556254398367e-05, 'learning_rate/action_query_proj': 7.989556254398367e-05, 'learning_rate/base': 1.9973890635995916e-05, 'epoch': 0.18}) +[2026-07-26 21:42:13,340][starVLA.training.train_starvla][INFO] - Step 1514, Loss: {'train/loss': 0.19230809807777405, 'train/grad_norm_pre_clip': 2.173089027404785, 'timing/data': 0.00023676175624132156, 'timing/model': 0.4682553010061383, 'learning_rate/action_model': 7.987101367891363e-05, 'learning_rate/action_query_proj': 7.987101367891363e-05, 'learning_rate/base': 1.9967753419728407e-05, 'epoch': 0.18}) +[2026-07-26 21:42:18,981][starVLA.training.train_starvla][INFO] - Step 1515, Loss: {'train/loss': 0.4960755705833435, 'train/grad_norm_pre_clip': 4.334486484527588, 'timing/data': 0.0001811198890209198, 'timing/model': 0.4668435691855848, 'learning_rate/action_model': 7.984645381080878e-05, 'learning_rate/action_query_proj': 7.984645381080878e-05, 'learning_rate/base': 1.9961613452702194e-05, 'epoch': 0.18}) +[2026-07-26 21:42:24,626][starVLA.training.train_starvla][INFO] - Step 1516, Loss: {'train/loss': 0.3093582093715668, 'train/grad_norm_pre_clip': 3.9360811710357666, 'timing/data': 0.00017300201579928398, 'timing/model': 0.46642244700342417, 'learning_rate/action_model': 7.982188294936496e-05, 'learning_rate/action_query_proj': 7.982188294936496e-05, 'learning_rate/base': 1.995547073734124e-05, 'epoch': 0.18}) +[2026-07-26 21:42:30,303][starVLA.training.train_starvla][INFO] - Step 1517, Loss: {'train/loss': 0.30951201915740967, 'train/grad_norm_pre_clip': 4.8765034675598145, 'timing/data': 0.00022244080901145935, 'timing/model': 0.46674510603770614, 'learning_rate/action_model': 7.979730110428239e-05, 'learning_rate/action_query_proj': 7.979730110428239e-05, 'learning_rate/base': 1.9949325276070596e-05, 'epoch': 0.18}) +[2026-07-26 21:42:36,004][starVLA.training.train_starvla][INFO] - Step 1518, Loss: {'train/loss': 0.3700726330280304, 'train/grad_norm_pre_clip': 2.716010093688965, 'timing/data': 0.00017422297969460487, 'timing/model': 0.4594647288322449, 'learning_rate/action_model': 7.977270828526554e-05, 'learning_rate/action_query_proj': 7.977270828526554e-05, 'learning_rate/base': 1.9943177071316386e-05, 'epoch': 0.18}) +[2026-07-26 21:42:41,684][starVLA.training.train_starvla][INFO] - Step 1519, Loss: {'train/loss': 0.35646241903305054, 'train/grad_norm_pre_clip': 3.4791009426116943, 'timing/data': 0.00017452798783779144, 'timing/model': 0.4663338749669492, 'learning_rate/action_model': 7.97481045020233e-05, 'learning_rate/action_query_proj': 7.97481045020233e-05, 'learning_rate/base': 1.9937026125505824e-05, 'epoch': 0.18}) +[2026-07-26 21:42:47,335][starVLA.training.train_starvla][INFO] - Step 1520, Loss: {'train/loss': 0.5090841054916382, 'train/grad_norm_pre_clip': 4.116921424865723, 'timing/data': 0.00017357897013425827, 'timing/model': 0.46421891590580344, 'learning_rate/action_model': 7.972348976426885e-05, 'learning_rate/action_query_proj': 7.972348976426885e-05, 'learning_rate/base': 1.9930872441067212e-05, 'epoch': 0.18}) +[2026-07-26 21:42:52,948][starVLA.training.train_starvla][INFO] - Step 1521, Loss: {'train/loss': 0.30592939257621765, 'train/grad_norm_pre_clip': 3.939645528793335, 'timing/data': 0.00018014712259173393, 'timing/model': 0.46494533820077777, 'learning_rate/action_model': 7.969886408171969e-05, 'learning_rate/action_query_proj': 7.969886408171969e-05, 'learning_rate/base': 1.9924716020429923e-05, 'epoch': 0.18}) +[2026-07-26 21:42:58,554][starVLA.training.train_starvla][INFO] - Step 1522, Loss: {'train/loss': 0.3929615914821625, 'train/grad_norm_pre_clip': 5.106079578399658, 'timing/data': 0.000174802727997303, 'timing/model': 0.4636962837539613, 'learning_rate/action_model': 7.967422746409766e-05, 'learning_rate/action_query_proj': 7.967422746409766e-05, 'learning_rate/base': 1.9918556866024414e-05, 'epoch': 0.18}) +[2026-07-26 21:43:04,176][starVLA.training.train_starvla][INFO] - Step 1523, Loss: {'train/loss': 0.42011138796806335, 'train/grad_norm_pre_clip': 4.860906600952148, 'timing/data': 0.0001743868924677372, 'timing/model': 0.46564651606604457, 'learning_rate/action_model': 7.964957992112891e-05, 'learning_rate/action_query_proj': 7.964957992112891e-05, 'learning_rate/base': 1.9912394980282227e-05, 'epoch': 0.18}) +[2026-07-26 21:43:09,841][starVLA.training.train_starvla][INFO] - Step 1524, Loss: {'train/loss': 0.3085387349128723, 'train/grad_norm_pre_clip': 3.5256593227386475, 'timing/data': 0.0001756688579916954, 'timing/model': 0.46819566609337926, 'learning_rate/action_model': 7.96249214625439e-05, 'learning_rate/action_query_proj': 7.96249214625439e-05, 'learning_rate/base': 1.9906230365635976e-05, 'epoch': 0.18}) +[2026-07-26 21:43:15,516][starVLA.training.train_starvla][INFO] - Step 1525, Loss: {'train/loss': 0.3839193284511566, 'train/grad_norm_pre_clip': 5.906778812408447, 'timing/data': 0.00018591294065117836, 'timing/model': 0.4681241288781166, 'learning_rate/action_model': 7.960025209807738e-05, 'learning_rate/action_query_proj': 7.960025209807738e-05, 'learning_rate/base': 1.9900063024519346e-05, 'epoch': 0.18}) +[2026-07-26 21:43:21,157][starVLA.training.train_starvla][INFO] - Step 1526, Loss: {'train/loss': 0.23977430164813995, 'train/grad_norm_pre_clip': 3.7589173316955566, 'timing/data': 0.00017728470265865326, 'timing/model': 0.46776620810851455, 'learning_rate/action_model': 7.957557183746843e-05, 'learning_rate/action_query_proj': 7.957557183746843e-05, 'learning_rate/base': 1.9893892959367108e-05, 'epoch': 0.19}) +[2026-07-26 21:43:26,787][starVLA.training.train_starvla][INFO] - Step 1527, Loss: {'train/loss': 0.32622942328453064, 'train/grad_norm_pre_clip': 3.463233709335327, 'timing/data': 0.0001774379052221775, 'timing/model': 0.4650915269739926, 'learning_rate/action_model': 7.955088069046044e-05, 'learning_rate/action_query_proj': 7.955088069046044e-05, 'learning_rate/base': 1.988772017261511e-05, 'epoch': 0.19}) +[2026-07-26 21:43:32,428][starVLA.training.train_starvla][INFO] - Step 1528, Loss: {'train/loss': 0.4710720181465149, 'train/grad_norm_pre_clip': 4.6668925285339355, 'timing/data': 0.00017076171934604645, 'timing/model': 0.46375169372186065, 'learning_rate/action_model': 7.952617866680106e-05, 'learning_rate/action_query_proj': 7.952617866680106e-05, 'learning_rate/base': 1.9881544666700266e-05, 'epoch': 0.19}) +[2026-07-26 21:43:38,311][starVLA.training.train_starvla][INFO] - Step 1529, Loss: {'train/loss': 0.41520172357559204, 'train/grad_norm_pre_clip': 4.42694091796875, 'timing/data': 0.00017616618424654007, 'timing/model': 0.4645639890804887, 'learning_rate/action_model': 7.950146577624229e-05, 'learning_rate/action_query_proj': 7.950146577624229e-05, 'learning_rate/base': 1.9875366444060573e-05, 'epoch': 0.19}) +[2026-07-26 21:43:43,963][starVLA.training.train_starvla][INFO] - Step 1530, Loss: {'train/loss': 0.35259371995925903, 'train/grad_norm_pre_clip': 3.5272114276885986, 'timing/data': 0.00016991933807730675, 'timing/model': 0.4668634762056172, 'learning_rate/action_model': 7.947674202854037e-05, 'learning_rate/action_query_proj': 7.947674202854037e-05, 'learning_rate/base': 1.9869185507135094e-05, 'epoch': 0.19}) +[2026-07-26 21:43:49,612][starVLA.training.train_starvla][INFO] - Step 1531, Loss: {'train/loss': 0.38675570487976074, 'train/grad_norm_pre_clip': 3.9455654621124268, 'timing/data': 0.00017767073586583138, 'timing/model': 0.46776233380660415, 'learning_rate/action_model': 7.945200743345584e-05, 'learning_rate/action_query_proj': 7.945200743345584e-05, 'learning_rate/base': 1.986300185836396e-05, 'epoch': 0.19}) +[2026-07-26 21:43:55,239][starVLA.training.train_starvla][INFO] - Step 1532, Loss: {'train/loss': 0.4160884618759155, 'train/grad_norm_pre_clip': 4.48257303237915, 'timing/data': 0.00018857000395655632, 'timing/model': 0.462755274027586, 'learning_rate/action_model': 7.942726200075353e-05, 'learning_rate/action_query_proj': 7.942726200075353e-05, 'learning_rate/base': 1.9856815500188382e-05, 'epoch': 0.19}) +[2026-07-26 21:44:00,852][starVLA.training.train_starvla][INFO] - Step 1533, Loss: {'train/loss': 0.43864235281944275, 'train/grad_norm_pre_clip': 5.5726213455200195, 'timing/data': 0.00017493683844804764, 'timing/model': 0.4637572839856148, 'learning_rate/action_model': 7.940250574020256e-05, 'learning_rate/action_query_proj': 7.940250574020256e-05, 'learning_rate/base': 1.985062643505064e-05, 'epoch': 0.19}) +[2026-07-26 21:44:06,481][starVLA.training.train_starvla][INFO] - Step 1534, Loss: {'train/loss': 0.310987263917923, 'train/grad_norm_pre_clip': 3.4418835639953613, 'timing/data': 0.00017895828932523727, 'timing/model': 0.46755698090419173, 'learning_rate/action_model': 7.937773866157626e-05, 'learning_rate/action_query_proj': 7.937773866157626e-05, 'learning_rate/base': 1.9844434665394066e-05, 'epoch': 0.19}) +[2026-07-26 21:44:12,091][starVLA.training.train_starvla][INFO] - Step 1535, Loss: {'train/loss': 0.256195992231369, 'train/grad_norm_pre_clip': 5.121704578399658, 'timing/data': 0.00019095418974757195, 'timing/model': 0.4687189608812332, 'learning_rate/action_model': 7.935296077465235e-05, 'learning_rate/action_query_proj': 7.935296077465235e-05, 'learning_rate/base': 1.9838240193663088e-05, 'epoch': 0.19}) +[2026-07-26 21:44:17,758][starVLA.training.train_starvla][INFO] - Step 1536, Loss: {'train/loss': 0.3764612674713135, 'train/grad_norm_pre_clip': 2.7182843685150146, 'timing/data': 0.00017491495236754417, 'timing/model': 0.46581319998949766, 'learning_rate/action_model': 7.932817208921271e-05, 'learning_rate/action_query_proj': 7.932817208921271e-05, 'learning_rate/base': 1.9832043022303177e-05, 'epoch': 0.19}) +[2026-07-26 21:44:23,632][starVLA.training.train_starvla][INFO] - Step 1537, Loss: {'train/loss': 0.3441321551799774, 'train/grad_norm_pre_clip': 3.5126898288726807, 'timing/data': 0.00017182808369398117, 'timing/model': 0.7197887701913714, 'learning_rate/action_model': 7.93033726150435e-05, 'learning_rate/action_query_proj': 7.93033726150435e-05, 'learning_rate/base': 1.9825843153760875e-05, 'epoch': 0.19}) +[2026-07-26 21:44:29,244][starVLA.training.train_starvla][INFO] - Step 1538, Loss: {'train/loss': 0.27056294679641724, 'train/grad_norm_pre_clip': 3.9074084758758545, 'timing/data': 0.00018000509589910507, 'timing/model': 0.46341906581074, 'learning_rate/action_model': 7.92785623619352e-05, 'learning_rate/action_query_proj': 7.92785623619352e-05, 'learning_rate/base': 1.98196405904838e-05, 'epoch': 0.19}) +[2026-07-26 21:44:34,853][starVLA.training.train_starvla][INFO] - Step 1539, Loss: {'train/loss': 0.36730265617370605, 'train/grad_norm_pre_clip': 3.541358709335327, 'timing/data': 0.0001828409731388092, 'timing/model': 0.457922350615263, 'learning_rate/action_model': 7.925374133968248e-05, 'learning_rate/action_query_proj': 7.925374133968248e-05, 'learning_rate/base': 1.981343533492062e-05, 'epoch': 0.19}) +[2026-07-26 21:44:40,479][starVLA.training.train_starvla][INFO] - Step 1540, Loss: {'train/loss': 0.3278339207172394, 'train/grad_norm_pre_clip': 4.584775447845459, 'timing/data': 0.0001745680347084999, 'timing/model': 0.4670920050702989, 'learning_rate/action_model': 7.922890955808432e-05, 'learning_rate/action_query_proj': 7.922890955808432e-05, 'learning_rate/base': 1.980722738952108e-05, 'epoch': 0.19}) +[2026-07-26 21:44:46,093][starVLA.training.train_starvla][INFO] - Step 1541, Loss: {'train/loss': 0.40492117404937744, 'train/grad_norm_pre_clip': 3.35416579246521, 'timing/data': 0.00017667701467871666, 'timing/model': 0.4664942151866853, 'learning_rate/action_model': 7.920406702694387e-05, 'learning_rate/action_query_proj': 7.920406702694387e-05, 'learning_rate/base': 1.980101675673597e-05, 'epoch': 0.19}) +[2026-07-26 21:44:51,690][starVLA.training.train_starvla][INFO] - Step 1542, Loss: {'train/loss': 0.4043692648410797, 'train/grad_norm_pre_clip': 3.9821298122406006, 'timing/data': 0.00019134674221277237, 'timing/model': 0.4637412470765412, 'learning_rate/action_model': 7.91792137560686e-05, 'learning_rate/action_query_proj': 7.91792137560686e-05, 'learning_rate/base': 1.979480343901715e-05, 'epoch': 0.19}) +[2026-07-26 21:44:57,310][starVLA.training.train_starvla][INFO] - Step 1543, Loss: {'train/loss': 0.4040696322917938, 'train/grad_norm_pre_clip': 3.3649208545684814, 'timing/data': 0.00019165221601724625, 'timing/model': 0.46883082017302513, 'learning_rate/action_model': 7.915434975527015e-05, 'learning_rate/action_query_proj': 7.915434975527015e-05, 'learning_rate/base': 1.9788587438817538e-05, 'epoch': 0.19}) +[2026-07-26 21:45:02,982][starVLA.training.train_starvla][INFO] - Step 1544, Loss: {'train/loss': 0.45096632838249207, 'train/grad_norm_pre_clip': 4.47758674621582, 'timing/data': 0.00017069093883037567, 'timing/model': 0.4659945797175169, 'learning_rate/action_model': 7.912947503436447e-05, 'learning_rate/action_query_proj': 7.912947503436447e-05, 'learning_rate/base': 1.9782368758591118e-05, 'epoch': 0.19}) +[2026-07-26 21:45:08,864][starVLA.training.train_starvla][INFO] - Step 1545, Loss: {'train/loss': 0.43690916895866394, 'train/grad_norm_pre_clip': 3.2386999130249023, 'timing/data': 0.0001779911108314991, 'timing/model': 0.4576594727113843, 'learning_rate/action_model': 7.910458960317171e-05, 'learning_rate/action_query_proj': 7.910458960317171e-05, 'learning_rate/base': 1.9776147400792928e-05, 'epoch': 0.19}) +[2026-07-26 21:45:14,429][starVLA.training.train_starvla][INFO] - Step 1546, Loss: {'train/loss': 0.3433073163032532, 'train/grad_norm_pre_clip': 3.824920654296875, 'timing/data': 0.00019174301996827126, 'timing/model': 0.4576607160270214, 'learning_rate/action_model': 7.907969347151622e-05, 'learning_rate/action_query_proj': 7.907969347151622e-05, 'learning_rate/base': 1.9769923367879055e-05, 'epoch': 0.19}) +[2026-07-26 21:45:20,002][starVLA.training.train_starvla][INFO] - Step 1547, Loss: {'train/loss': 0.24766266345977783, 'train/grad_norm_pre_clip': 3.175758123397827, 'timing/data': 0.00017160829156637192, 'timing/model': 0.45878556929528713, 'learning_rate/action_model': 7.90547866492266e-05, 'learning_rate/action_query_proj': 7.90547866492266e-05, 'learning_rate/base': 1.976369666230665e-05, 'epoch': 0.19}) +[2026-07-26 21:45:25,570][starVLA.training.train_starvla][INFO] - Step 1548, Loss: {'train/loss': 0.2865687906742096, 'train/grad_norm_pre_clip': 2.5495991706848145, 'timing/data': 0.0001690196804702282, 'timing/model': 0.457840281073004, 'learning_rate/action_model': 7.902986914613568e-05, 'learning_rate/action_query_proj': 7.902986914613568e-05, 'learning_rate/base': 1.975746728653392e-05, 'epoch': 0.19}) +[2026-07-26 21:45:31,077][starVLA.training.train_starvla][INFO] - Step 1549, Loss: {'train/loss': 0.28862395882606506, 'train/grad_norm_pre_clip': 3.000865936279297, 'timing/data': 0.00017854897305369377, 'timing/model': 0.45740553084760904, 'learning_rate/action_model': 7.900494097208049e-05, 'learning_rate/action_query_proj': 7.900494097208049e-05, 'learning_rate/base': 1.9751235243020123e-05, 'epoch': 0.19}) +[2026-07-26 21:45:36,592][starVLA.training.train_starvla][INFO] - Step 1550, Loss: {'train/loss': 0.3194741904735565, 'train/grad_norm_pre_clip': 4.119007110595703, 'timing/data': 0.00017767399549484253, 'timing/model': 0.4584514959715307, 'learning_rate/action_model': 7.898000213690227e-05, 'learning_rate/action_query_proj': 7.898000213690227e-05, 'learning_rate/base': 1.974500053422557e-05, 'epoch': 0.19}) +[2026-07-26 21:45:42,102][starVLA.training.train_starvla][INFO] - Step 1551, Loss: {'train/loss': 0.35632002353668213, 'train/grad_norm_pre_clip': 3.7072107791900635, 'timing/data': 0.00018490804359316826, 'timing/model': 0.4585756459273398, 'learning_rate/action_model': 7.895505265044651e-05, 'learning_rate/action_query_proj': 7.895505265044651e-05, 'learning_rate/base': 1.9738763162611627e-05, 'epoch': 0.19}) +[2026-07-26 21:45:47,728][starVLA.training.train_starvla][INFO] - Step 1552, Loss: {'train/loss': 0.3487575650215149, 'train/grad_norm_pre_clip': 2.8795390129089355, 'timing/data': 0.0001672622747719288, 'timing/model': 0.45847424725070596, 'learning_rate/action_model': 7.893009252256283e-05, 'learning_rate/action_query_proj': 7.893009252256283e-05, 'learning_rate/base': 1.9732523130640708e-05, 'epoch': 0.19}) +[2026-07-26 21:45:53,242][starVLA.training.train_starvla][INFO] - Step 1553, Loss: {'train/loss': 0.41184985637664795, 'train/grad_norm_pre_clip': 5.763419151306152, 'timing/data': 0.0001719328574836254, 'timing/model': 0.45692212972790003, 'learning_rate/action_model': 7.890512176310511e-05, 'learning_rate/action_query_proj': 7.890512176310511e-05, 'learning_rate/base': 1.9726280440776277e-05, 'epoch': 0.19}) +[2026-07-26 21:45:58,766][starVLA.training.train_starvla][INFO] - Step 1554, Loss: {'train/loss': 0.31158357858657837, 'train/grad_norm_pre_clip': 3.2824692726135254, 'timing/data': 0.00017395475879311562, 'timing/model': 0.4589228960685432, 'learning_rate/action_model': 7.888014038193144e-05, 'learning_rate/action_query_proj': 7.888014038193144e-05, 'learning_rate/base': 1.972003509548286e-05, 'epoch': 0.19}) +[2026-07-26 21:46:04,309][starVLA.training.train_starvla][INFO] - Step 1555, Loss: {'train/loss': 0.4495713412761688, 'train/grad_norm_pre_clip': 3.572486639022827, 'timing/data': 0.0001894477754831314, 'timing/model': 0.4583103507757187, 'learning_rate/action_model': 7.885514838890402e-05, 'learning_rate/action_query_proj': 7.885514838890402e-05, 'learning_rate/base': 1.9713787097226005e-05, 'epoch': 0.19}) +[2026-07-26 21:46:09,836][starVLA.training.train_starvla][INFO] - Step 1556, Loss: {'train/loss': 0.2767128646373749, 'train/grad_norm_pre_clip': 3.0215964317321777, 'timing/data': 0.00016804691404104233, 'timing/model': 0.45743685495108366, 'learning_rate/action_model': 7.883014579388933e-05, 'learning_rate/action_query_proj': 7.883014579388933e-05, 'learning_rate/base': 1.9707536448472333e-05, 'epoch': 0.19}) +[2026-07-26 21:46:15,438][starVLA.training.train_starvla][INFO] - Step 1557, Loss: {'train/loss': 0.2917976975440979, 'train/grad_norm_pre_clip': 4.405160427093506, 'timing/data': 0.0001710657961666584, 'timing/model': 0.4589095050469041, 'learning_rate/action_model': 7.880513260675799e-05, 'learning_rate/action_query_proj': 7.880513260675799e-05, 'learning_rate/base': 1.9701283151689497e-05, 'epoch': 0.19}) +[2026-07-26 21:46:20,960][starVLA.training.train_starvla][INFO] - Step 1558, Loss: {'train/loss': 0.31652891635894775, 'train/grad_norm_pre_clip': 3.7991607189178467, 'timing/data': 0.00016943691298365593, 'timing/model': 0.45850055664777756, 'learning_rate/action_model': 7.87801088373848e-05, 'learning_rate/action_query_proj': 7.87801088373848e-05, 'learning_rate/base': 1.96950272093462e-05, 'epoch': 0.19}) +[2026-07-26 21:46:26,479][starVLA.training.train_starvla][INFO] - Step 1559, Loss: {'train/loss': 0.35172492265701294, 'train/grad_norm_pre_clip': 3.8032243251800537, 'timing/data': 0.00019158096984028816, 'timing/model': 0.45862527983263135, 'learning_rate/action_model': 7.875507449564876e-05, 'learning_rate/action_query_proj': 7.875507449564876e-05, 'learning_rate/base': 1.968876862391219e-05, 'epoch': 0.19}) +[2026-07-26 21:46:32,003][starVLA.training.train_starvla][INFO] - Step 1560, Loss: {'train/loss': 0.25704967975616455, 'train/grad_norm_pre_clip': 2.505272150039673, 'timing/data': 0.00017429934814572334, 'timing/model': 0.4584832820110023, 'learning_rate/action_model': 7.873002959143304e-05, 'learning_rate/action_query_proj': 7.873002959143304e-05, 'learning_rate/base': 1.968250739785826e-05, 'epoch': 0.19}) +[2026-07-26 21:46:37,519][starVLA.training.train_starvla][INFO] - Step 1561, Loss: {'train/loss': 0.4687654972076416, 'train/grad_norm_pre_clip': 4.484109878540039, 'timing/data': 0.0002022092230618, 'timing/model': 0.45789498602971435, 'learning_rate/action_model': 7.870497413462495e-05, 'learning_rate/action_query_proj': 7.870497413462495e-05, 'learning_rate/base': 1.9676243533656236e-05, 'epoch': 0.19}) +[2026-07-26 21:46:43,037][starVLA.training.train_starvla][INFO] - Step 1562, Loss: {'train/loss': 0.373716801404953, 'train/grad_norm_pre_clip': 3.876325845718384, 'timing/data': 0.00018407218158245087, 'timing/model': 0.4574036216363311, 'learning_rate/action_model': 7.867990813511597e-05, 'learning_rate/action_query_proj': 7.867990813511597e-05, 'learning_rate/base': 1.9669977033778993e-05, 'epoch': 0.19}) +[2026-07-26 21:46:48,552][starVLA.training.train_starvla][INFO] - Step 1563, Loss: {'train/loss': 0.29270318150520325, 'train/grad_norm_pre_clip': 2.5737380981445312, 'timing/data': 0.00017428305000066757, 'timing/model': 0.45950479293242097, 'learning_rate/action_model': 7.865483160280182e-05, 'learning_rate/action_query_proj': 7.865483160280182e-05, 'learning_rate/base': 1.9663707900700455e-05, 'epoch': 0.19}) +[2026-07-26 21:46:54,079][starVLA.training.train_starvla][INFO] - Step 1564, Loss: {'train/loss': 0.34269270300865173, 'train/grad_norm_pre_clip': 2.763359308242798, 'timing/data': 0.00018196506425738335, 'timing/model': 0.4585233088582754, 'learning_rate/action_model': 7.862974454758227e-05, 'learning_rate/action_query_proj': 7.862974454758227e-05, 'learning_rate/base': 1.965743613689557e-05, 'epoch': 0.19}) +[2026-07-26 21:46:59,595][starVLA.training.train_starvla][INFO] - Step 1565, Loss: {'train/loss': 0.4048021137714386, 'train/grad_norm_pre_clip': 4.375768184661865, 'timing/data': 0.0001775221899151802, 'timing/model': 0.45727713592350483, 'learning_rate/action_model': 7.860464697936132e-05, 'learning_rate/action_query_proj': 7.860464697936132e-05, 'learning_rate/base': 1.965116174484033e-05, 'epoch': 0.19}) +[2026-07-26 21:47:05,380][starVLA.training.train_starvla][INFO] - Step 1566, Loss: {'train/loss': 0.31814631819725037, 'train/grad_norm_pre_clip': 2.8868050575256348, 'timing/data': 0.00017851870507001877, 'timing/model': 0.45798323303461075, 'learning_rate/action_model': 7.857953890804707e-05, 'learning_rate/action_query_proj': 7.857953890804707e-05, 'learning_rate/base': 1.964488472701177e-05, 'epoch': 0.19}) +[2026-07-26 21:47:11,163][starVLA.training.train_starvla][INFO] - Step 1567, Loss: {'train/loss': 0.2724476456642151, 'train/grad_norm_pre_clip': 3.2548069953918457, 'timing/data': 0.0001810290850698948, 'timing/model': 0.45850588101893663, 'learning_rate/action_model': 7.855442034355179e-05, 'learning_rate/action_query_proj': 7.855442034355179e-05, 'learning_rate/base': 1.9638605085887947e-05, 'epoch': 0.19}) +[2026-07-26 21:47:16,675][starVLA.training.train_starvla][INFO] - Step 1568, Loss: {'train/loss': 0.34112951159477234, 'train/grad_norm_pre_clip': 4.242225170135498, 'timing/data': 0.00018381793051958084, 'timing/model': 0.4586116336286068, 'learning_rate/action_model': 7.852929129579192e-05, 'learning_rate/action_query_proj': 7.852929129579192e-05, 'learning_rate/base': 1.963232282394798e-05, 'epoch': 0.19}) +[2026-07-26 21:47:22,210][starVLA.training.train_starvla][INFO] - Step 1569, Loss: {'train/loss': 0.35230553150177, 'train/grad_norm_pre_clip': 3.0482168197631836, 'timing/data': 0.00021690968424081802, 'timing/model': 0.46091587701812387, 'learning_rate/action_model': 7.850415177468797e-05, 'learning_rate/action_query_proj': 7.850415177468797e-05, 'learning_rate/base': 1.9626037943671993e-05, 'epoch': 0.19}) +[2026-07-26 21:47:27,732][starVLA.training.train_starvla][INFO] - Step 1570, Loss: {'train/loss': 0.20457807183265686, 'train/grad_norm_pre_clip': 3.032503843307495, 'timing/data': 0.00017990916967391968, 'timing/model': 0.45891362614929676, 'learning_rate/action_model': 7.847900179016466e-05, 'learning_rate/action_query_proj': 7.847900179016466e-05, 'learning_rate/base': 1.9619750447541165e-05, 'epoch': 0.19}) +[2026-07-26 21:47:33,467][starVLA.training.train_starvla][INFO] - Step 1571, Loss: {'train/loss': 0.3559455871582031, 'train/grad_norm_pre_clip': 2.930182933807373, 'timing/data': 0.00018054572865366936, 'timing/model': 0.45856162579730153, 'learning_rate/action_model': 7.845384135215077e-05, 'learning_rate/action_query_proj': 7.845384135215077e-05, 'learning_rate/base': 1.961346033803769e-05, 'epoch': 0.19}) +[2026-07-26 21:47:38,993][starVLA.training.train_starvla][INFO] - Step 1572, Loss: {'train/loss': 0.23956456780433655, 'train/grad_norm_pre_clip': 2.2438621520996094, 'timing/data': 0.00018145889043807983, 'timing/model': 0.45911039505153894, 'learning_rate/action_model': 7.842867047057929e-05, 'learning_rate/action_query_proj': 7.842867047057929e-05, 'learning_rate/base': 1.960716761764482e-05, 'epoch': 0.19}) +[2026-07-26 21:47:44,520][starVLA.training.train_starvla][INFO] - Step 1573, Loss: {'train/loss': 0.35520535707473755, 'train/grad_norm_pre_clip': 4.769901275634766, 'timing/data': 0.00017869891598820686, 'timing/model': 0.4582189260981977, 'learning_rate/action_model': 7.840348915538722e-05, 'learning_rate/action_query_proj': 7.840348915538722e-05, 'learning_rate/base': 1.9600872288846804e-05, 'epoch': 0.19}) +[2026-07-26 21:47:50,060][starVLA.training.train_starvla][INFO] - Step 1574, Loss: {'train/loss': 0.30579429864883423, 'train/grad_norm_pre_clip': 3.4182584285736084, 'timing/data': 0.00018205493688583374, 'timing/model': 0.45833448972553015, 'learning_rate/action_model': 7.837829741651581e-05, 'learning_rate/action_query_proj': 7.837829741651581e-05, 'learning_rate/base': 1.9594574354128953e-05, 'epoch': 0.19}) +[2026-07-26 21:47:55,605][starVLA.training.train_starvla][INFO] - Step 1575, Loss: {'train/loss': 0.1865113079547882, 'train/grad_norm_pre_clip': 2.1748597621917725, 'timing/data': 0.00018389616161584854, 'timing/model': 0.45856666984036565, 'learning_rate/action_model': 7.835309526391033e-05, 'learning_rate/action_query_proj': 7.835309526391033e-05, 'learning_rate/base': 1.958827381597758e-05, 'epoch': 0.19}) +[2026-07-26 21:48:01,163][starVLA.training.train_starvla][INFO] - Step 1576, Loss: {'train/loss': 0.4678044319152832, 'train/grad_norm_pre_clip': 4.429747104644775, 'timing/data': 0.0001788581721484661, 'timing/model': 0.45759151922538877, 'learning_rate/action_model': 7.832788270752018e-05, 'learning_rate/action_query_proj': 7.832788270752018e-05, 'learning_rate/base': 1.9581970676880045e-05, 'epoch': 0.19}) +[2026-07-26 21:48:06,727][starVLA.training.train_starvla][INFO] - Step 1577, Loss: {'train/loss': 0.2861069142818451, 'train/grad_norm_pre_clip': 4.300632476806641, 'timing/data': 0.00017302483320236206, 'timing/model': 0.4582437709905207, 'learning_rate/action_model': 7.83026597572989e-05, 'learning_rate/action_query_proj': 7.83026597572989e-05, 'learning_rate/base': 1.9575664939324727e-05, 'epoch': 0.19}) +[2026-07-26 21:48:12,279][starVLA.training.train_starvla][INFO] - Step 1578, Loss: {'train/loss': 0.5255876779556274, 'train/grad_norm_pre_clip': 6.515117645263672, 'timing/data': 0.00018264306709170341, 'timing/model': 0.4587640492245555, 'learning_rate/action_model': 7.82774264232041e-05, 'learning_rate/action_query_proj': 7.82774264232041e-05, 'learning_rate/base': 1.9569356605801026e-05, 'epoch': 0.19}) +[2026-07-26 21:48:17,856][starVLA.training.train_starvla][INFO] - Step 1579, Loss: {'train/loss': 0.33213067054748535, 'train/grad_norm_pre_clip': 3.632901668548584, 'timing/data': 0.00016804179176688194, 'timing/model': 0.45802890323102474, 'learning_rate/action_model': 7.82521827151975e-05, 'learning_rate/action_query_proj': 7.82521827151975e-05, 'learning_rate/base': 1.9563045678799375e-05, 'epoch': 0.19}) +[2026-07-26 21:48:23,404][starVLA.training.train_starvla][INFO] - Step 1580, Loss: {'train/loss': 0.2722266614437103, 'train/grad_norm_pre_clip': 3.9705862998962402, 'timing/data': 0.00017474358901381493, 'timing/model': 0.45879153814166784, 'learning_rate/action_model': 7.822692864324492e-05, 'learning_rate/action_query_proj': 7.822692864324492e-05, 'learning_rate/base': 1.955673216081123e-05, 'epoch': 0.19}) +[2026-07-26 21:48:28,971][starVLA.training.train_starvla][INFO] - Step 1581, Loss: {'train/loss': 0.2708667516708374, 'train/grad_norm_pre_clip': 4.061947345733643, 'timing/data': 0.000176883302628994, 'timing/model': 0.4658547737635672, 'learning_rate/action_model': 7.820166421731627e-05, 'learning_rate/action_query_proj': 7.820166421731627e-05, 'learning_rate/base': 1.9550416054329068e-05, 'epoch': 0.19}) +[2026-07-26 21:48:34,528][starVLA.training.train_starvla][INFO] - Step 1582, Loss: {'train/loss': 0.31346940994262695, 'train/grad_norm_pre_clip': 3.6257762908935547, 'timing/data': 0.00017683999612927437, 'timing/model': 0.45926560228690505, 'learning_rate/action_model': 7.817638944738553e-05, 'learning_rate/action_query_proj': 7.817638944738553e-05, 'learning_rate/base': 1.9544097361846383e-05, 'epoch': 0.19}) +[2026-07-26 21:48:40,069][starVLA.training.train_starvla][INFO] - Step 1583, Loss: {'train/loss': 0.29694807529449463, 'train/grad_norm_pre_clip': 3.46449613571167, 'timing/data': 0.00017759529873728752, 'timing/model': 0.4585274909622967, 'learning_rate/action_model': 7.81511043434308e-05, 'learning_rate/action_query_proj': 7.81511043434308e-05, 'learning_rate/base': 1.95377760858577e-05, 'epoch': 0.19}) +[2026-07-26 21:48:45,592][starVLA.training.train_starvla][INFO] - Step 1584, Loss: {'train/loss': 0.3860743045806885, 'train/grad_norm_pre_clip': 3.683180809020996, 'timing/data': 0.00017574802041053772, 'timing/model': 0.46065722312778234, 'learning_rate/action_model': 7.812580891543422e-05, 'learning_rate/action_query_proj': 7.812580891543422e-05, 'learning_rate/base': 1.9531452228858554e-05, 'epoch': 0.19}) +[2026-07-26 21:48:51,118][starVLA.training.train_starvla][INFO] - Step 1585, Loss: {'train/loss': 0.3398994207382202, 'train/grad_norm_pre_clip': 6.0947980880737305, 'timing/data': 0.00017510633915662766, 'timing/model': 0.4589633229188621, 'learning_rate/action_model': 7.810050317338204e-05, 'learning_rate/action_query_proj': 7.810050317338204e-05, 'learning_rate/base': 1.952512579334551e-05, 'epoch': 0.19}) +[2026-07-26 21:48:56,637][starVLA.training.train_starvla][INFO] - Step 1586, Loss: {'train/loss': 0.3532281517982483, 'train/grad_norm_pre_clip': 4.105500221252441, 'timing/data': 0.00017310399562120438, 'timing/model': 0.4585020951926708, 'learning_rate/action_model': 7.807518712726457e-05, 'learning_rate/action_query_proj': 7.807518712726457e-05, 'learning_rate/base': 1.9518796781816143e-05, 'epoch': 0.19}) +[2026-07-26 21:49:02,168][starVLA.training.train_starvla][INFO] - Step 1587, Loss: {'train/loss': 0.36864909529685974, 'train/grad_norm_pre_clip': 5.088592529296875, 'timing/data': 0.00019251881167292595, 'timing/model': 0.45868382696062326, 'learning_rate/action_model': 7.804986078707615e-05, 'learning_rate/action_query_proj': 7.804986078707615e-05, 'learning_rate/base': 1.9512465196769038e-05, 'epoch': 0.19}) +[2026-07-26 21:49:07,687][starVLA.training.train_starvla][INFO] - Step 1588, Loss: {'train/loss': 0.3637593686580658, 'train/grad_norm_pre_clip': 4.065125942230225, 'timing/data': 0.00019867299124598503, 'timing/model': 0.458776808809489, 'learning_rate/action_model': 7.802452416281525e-05, 'learning_rate/action_query_proj': 7.802452416281525e-05, 'learning_rate/base': 1.9506131040703813e-05, 'epoch': 0.19}) +[2026-07-26 21:49:13,203][starVLA.training.train_starvla][INFO] - Step 1589, Loss: {'train/loss': 0.284471720457077, 'train/grad_norm_pre_clip': 2.8042314052581787, 'timing/data': 0.00017749378457665443, 'timing/model': 0.45808123890310526, 'learning_rate/action_model': 7.799917726448436e-05, 'learning_rate/action_query_proj': 7.799917726448436e-05, 'learning_rate/base': 1.949979431612109e-05, 'epoch': 0.19}) +[2026-07-26 21:49:18,716][starVLA.training.train_starvla][INFO] - Step 1590, Loss: {'train/loss': 0.24543824791908264, 'train/grad_norm_pre_clip': 2.8212649822235107, 'timing/data': 0.0001758919097483158, 'timing/model': 0.45948938140645623, 'learning_rate/action_model': 7.797382010209005e-05, 'learning_rate/action_query_proj': 7.797382010209005e-05, 'learning_rate/base': 1.949345502552251e-05, 'epoch': 0.19}) +[2026-07-26 21:49:24,240][starVLA.training.train_starvla][INFO] - Step 1591, Loss: {'train/loss': 0.2914124131202698, 'train/grad_norm_pre_clip': 3.53704833984375, 'timing/data': 0.00017517991364002228, 'timing/model': 0.4584701433777809, 'learning_rate/action_model': 7.79484526856429e-05, 'learning_rate/action_query_proj': 7.79484526856429e-05, 'learning_rate/base': 1.9487113171410724e-05, 'epoch': 0.19}) +[2026-07-26 21:49:29,759][starVLA.training.train_starvla][INFO] - Step 1592, Loss: {'train/loss': 0.33027076721191406, 'train/grad_norm_pre_clip': 3.605717420578003, 'timing/data': 0.0001724380999803543, 'timing/model': 0.45851310808211565, 'learning_rate/action_model': 7.792307502515756e-05, 'learning_rate/action_query_proj': 7.792307502515756e-05, 'learning_rate/base': 1.948076875628939e-05, 'epoch': 0.19}) +[2026-07-26 21:49:35,273][starVLA.training.train_starvla][INFO] - Step 1593, Loss: {'train/loss': 0.43925726413726807, 'train/grad_norm_pre_clip': 6.182380676269531, 'timing/data': 0.00017668027430772781, 'timing/model': 0.45876856008544564, 'learning_rate/action_model': 7.789768713065277e-05, 'learning_rate/action_query_proj': 7.789768713065277e-05, 'learning_rate/base': 1.9474421782663192e-05, 'epoch': 0.19}) +[2026-07-26 21:49:40,788][starVLA.training.train_starvla][INFO] - Step 1594, Loss: {'train/loss': 0.42994534969329834, 'train/grad_norm_pre_clip': 4.6298041343688965, 'timing/data': 0.00017405487596988678, 'timing/model': 0.4598314817994833, 'learning_rate/action_model': 7.78722890121512e-05, 'learning_rate/action_query_proj': 7.78722890121512e-05, 'learning_rate/base': 1.94680722530378e-05, 'epoch': 0.19}) +[2026-07-26 21:49:46,327][starVLA.training.train_starvla][INFO] - Step 1595, Loss: {'train/loss': 0.32878923416137695, 'train/grad_norm_pre_clip': 3.3889341354370117, 'timing/data': 0.00017437804490327835, 'timing/model': 0.4580318918451667, 'learning_rate/action_model': 7.78468806796797e-05, 'learning_rate/action_query_proj': 7.78468806796797e-05, 'learning_rate/base': 1.9461720169919924e-05, 'epoch': 0.19}) +[2026-07-26 21:49:51,853][starVLA.training.train_starvla][INFO] - Step 1596, Loss: {'train/loss': 0.3846382200717926, 'train/grad_norm_pre_clip': 4.98623514175415, 'timing/data': 0.00017807027325034142, 'timing/model': 0.4586447160691023, 'learning_rate/action_model': 7.782146214326902e-05, 'learning_rate/action_query_proj': 7.782146214326902e-05, 'learning_rate/base': 1.9455365535817255e-05, 'epoch': 0.19}) +[2026-07-26 21:49:57,446][starVLA.training.train_starvla][INFO] - Step 1597, Loss: {'train/loss': 0.3709949851036072, 'train/grad_norm_pre_clip': 3.81115984916687, 'timing/data': 0.00017738807946443558, 'timing/model': 0.49685387685894966, 'learning_rate/action_model': 7.779603341295403e-05, 'learning_rate/action_query_proj': 7.779603341295403e-05, 'learning_rate/base': 1.9449008353238507e-05, 'epoch': 0.19}) +[2026-07-26 21:50:03,020][starVLA.training.train_starvla][INFO] - Step 1598, Loss: {'train/loss': 0.3775676488876343, 'train/grad_norm_pre_clip': 4.597434997558594, 'timing/data': 0.00017120875418186188, 'timing/model': 0.4584840959869325, 'learning_rate/action_model': 7.77705944987736e-05, 'learning_rate/action_query_proj': 7.77705944987736e-05, 'learning_rate/base': 1.94426486246934e-05, 'epoch': 0.19}) +[2026-07-26 21:50:08,534][starVLA.training.train_starvla][INFO] - Step 1599, Loss: {'train/loss': 0.31651216745376587, 'train/grad_norm_pre_clip': 3.5778512954711914, 'timing/data': 0.00018518511205911636, 'timing/model': 0.45737613504752517, 'learning_rate/action_model': 7.774514541077056e-05, 'learning_rate/action_query_proj': 7.774514541077056e-05, 'learning_rate/base': 1.943628635269264e-05, 'epoch': 0.19}) +[2026-07-26 21:50:14,308][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 1600 +[2026-07-26 21:50:14,309][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 1600 +[2026-07-26 21:50:14,310][starVLA.training.train_starvla][INFO] - Step 1600, Loss: {'train/loss': 0.2951088845729828, 'train/grad_norm_pre_clip': 3.268442153930664, 'timing/data': 0.0001796525903046131, 'timing/model': 0.4584723967127502, 'learning_rate/action_model': 7.771968615899183e-05, 'learning_rate/action_query_proj': 7.771968615899183e-05, 'learning_rate/base': 1.9429921539747957e-05, 'epoch': 0.19}) +[2026-07-26 21:50:19,828][starVLA.training.train_starvla][INFO] - Step 1601, Loss: {'train/loss': 0.4829314351081848, 'train/grad_norm_pre_clip': 4.282720565795898, 'timing/data': 0.00019202614203095436, 'timing/model': 0.4578954176977277, 'learning_rate/action_model': 7.769421675348836e-05, 'learning_rate/action_query_proj': 7.769421675348836e-05, 'learning_rate/base': 1.942355418837209e-05, 'epoch': 0.19}) +[2026-07-26 21:50:25,358][starVLA.training.train_starvla][INFO] - Step 1602, Loss: {'train/loss': 0.40294021368026733, 'train/grad_norm_pre_clip': 6.756217956542969, 'timing/data': 0.00017577502876520157, 'timing/model': 0.458648718893528, 'learning_rate/action_model': 7.7668737204315e-05, 'learning_rate/action_query_proj': 7.7668737204315e-05, 'learning_rate/base': 1.941718430107875e-05, 'epoch': 0.19}) +[2026-07-26 21:50:30,920][starVLA.training.train_starvla][INFO] - Step 1603, Loss: {'train/loss': 0.41364389657974243, 'train/grad_norm_pre_clip': 4.169053077697754, 'timing/data': 0.00018232036381959915, 'timing/model': 0.45811373135074973, 'learning_rate/action_model': 7.764324752153073e-05, 'learning_rate/action_query_proj': 7.764324752153073e-05, 'learning_rate/base': 1.941081188038268e-05, 'epoch': 0.19}) +[2026-07-26 21:50:36,431][starVLA.training.train_starvla][INFO] - Step 1604, Loss: {'train/loss': 0.3907545208930969, 'train/grad_norm_pre_clip': 6.026463508605957, 'timing/data': 0.00018631620332598686, 'timing/model': 0.45848559821024537, 'learning_rate/action_model': 7.761774771519844e-05, 'learning_rate/action_query_proj': 7.761774771519844e-05, 'learning_rate/base': 1.940443692879961e-05, 'epoch': 0.19}) +[2026-07-26 21:50:41,944][starVLA.training.train_starvla][INFO] - Step 1605, Loss: {'train/loss': 0.2654413878917694, 'train/grad_norm_pre_clip': 4.014255523681641, 'timing/data': 0.00017622020095586777, 'timing/model': 0.45725600700825453, 'learning_rate/action_model': 7.759223779538505e-05, 'learning_rate/action_query_proj': 7.759223779538505e-05, 'learning_rate/base': 1.9398059448846263e-05, 'epoch': 0.19}) +[2026-07-26 21:50:47,455][starVLA.training.train_starvla][INFO] - Step 1606, Loss: {'train/loss': 0.2591259777545929, 'train/grad_norm_pre_clip': 3.2079644203186035, 'timing/data': 0.00017975131049752235, 'timing/model': 0.45629713125526905, 'learning_rate/action_model': 7.756671777216149e-05, 'learning_rate/action_query_proj': 7.756671777216149e-05, 'learning_rate/base': 1.939167944304037e-05, 'epoch': 0.19}) +[2026-07-26 21:50:52,980][starVLA.training.train_starvla][INFO] - Step 1607, Loss: {'train/loss': 0.2242026925086975, 'train/grad_norm_pre_clip': 3.1388349533081055, 'timing/data': 0.00017264671623706818, 'timing/model': 0.45829156367108226, 'learning_rate/action_model': 7.754118765560265e-05, 'learning_rate/action_query_proj': 7.754118765560265e-05, 'learning_rate/base': 1.9385296913900664e-05, 'epoch': 0.19}) +[2026-07-26 21:50:58,525][starVLA.training.train_starvla][INFO] - Step 1608, Loss: {'train/loss': 0.2632942795753479, 'train/grad_norm_pre_clip': 3.7123053073883057, 'timing/data': 0.0001730392687022686, 'timing/model': 0.4573998968116939, 'learning_rate/action_model': 7.751564745578744e-05, 'learning_rate/action_query_proj': 7.751564745578744e-05, 'learning_rate/base': 1.937891186394686e-05, 'epoch': 0.2}) +[2026-07-26 21:51:04,048][starVLA.training.train_starvla][INFO] - Step 1609, Loss: {'train/loss': 0.49468475580215454, 'train/grad_norm_pre_clip': 6.8789286613464355, 'timing/data': 0.00017967307940125465, 'timing/model': 0.45848329877480865, 'learning_rate/action_model': 7.749009718279867e-05, 'learning_rate/action_query_proj': 7.749009718279867e-05, 'learning_rate/base': 1.9372524295699666e-05, 'epoch': 0.2}) +[2026-07-26 21:51:09,558][starVLA.training.train_starvla][INFO] - Step 1610, Loss: {'train/loss': 0.2781240940093994, 'train/grad_norm_pre_clip': 4.701544761657715, 'timing/data': 0.000173086766153574, 'timing/model': 0.4583445666357875, 'learning_rate/action_model': 7.746453684672323e-05, 'learning_rate/action_query_proj': 7.746453684672323e-05, 'learning_rate/base': 1.936613421168081e-05, 'epoch': 0.2}) +[2026-07-26 21:51:15,067][starVLA.training.train_starvla][INFO] - Step 1611, Loss: {'train/loss': 0.22238689661026, 'train/grad_norm_pre_clip': 2.6217293739318848, 'timing/data': 0.00017246929928660393, 'timing/model': 0.45745705999433994, 'learning_rate/action_model': 7.743896645765193e-05, 'learning_rate/action_query_proj': 7.743896645765193e-05, 'learning_rate/base': 1.9359741614412983e-05, 'epoch': 0.2}) +[2026-07-26 21:51:20,581][starVLA.training.train_starvla][INFO] - Step 1612, Loss: {'train/loss': 0.2817617356777191, 'train/grad_norm_pre_clip': 3.0989410877227783, 'timing/data': 0.00017341133207082748, 'timing/model': 0.4577647019177675, 'learning_rate/action_model': 7.741338602567956e-05, 'learning_rate/action_query_proj': 7.741338602567956e-05, 'learning_rate/base': 1.935334650641989e-05, 'epoch': 0.2}) +[2026-07-26 21:51:26,088][starVLA.training.train_starvla][INFO] - Step 1613, Loss: {'train/loss': 0.3355133831501007, 'train/grad_norm_pre_clip': 5.420110702514648, 'timing/data': 0.00018666312098503113, 'timing/model': 0.45790976332500577, 'learning_rate/action_model': 7.738779556090484e-05, 'learning_rate/action_query_proj': 7.738779556090484e-05, 'learning_rate/base': 1.934694889022621e-05, 'epoch': 0.2}) +[2026-07-26 21:51:31,592][starVLA.training.train_starvla][INFO] - Step 1614, Loss: {'train/loss': 0.2625511586666107, 'train/grad_norm_pre_clip': 3.19366192817688, 'timing/data': 0.00018437393009662628, 'timing/model': 0.4572176272049546, 'learning_rate/action_model': 7.736219507343048e-05, 'learning_rate/action_query_proj': 7.736219507343048e-05, 'learning_rate/base': 1.934054876835762e-05, 'epoch': 0.2}) +[2026-07-26 21:51:37,103][starVLA.training.train_starvla][INFO] - Step 1615, Loss: {'train/loss': 0.27634692192077637, 'train/grad_norm_pre_clip': 3.7278409004211426, 'timing/data': 0.0001766621135175228, 'timing/model': 0.4573112912476063, 'learning_rate/action_model': 7.733658457336319e-05, 'learning_rate/action_query_proj': 7.733658457336319e-05, 'learning_rate/base': 1.9334146143340798e-05, 'epoch': 0.2}) +[2026-07-26 21:51:42,631][starVLA.training.train_starvla][INFO] - Step 1616, Loss: {'train/loss': 0.2883407771587372, 'train/grad_norm_pre_clip': 2.8147780895233154, 'timing/data': 0.00017230398952960968, 'timing/model': 0.45783856604248285, 'learning_rate/action_model': 7.731096407081357e-05, 'learning_rate/action_query_proj': 7.731096407081357e-05, 'learning_rate/base': 1.9327741017703392e-05, 'epoch': 0.2}) +[2026-07-26 21:51:48,140][starVLA.training.train_starvla][INFO] - Step 1617, Loss: {'train/loss': 0.3528186082839966, 'train/grad_norm_pre_clip': 3.172192096710205, 'timing/data': 0.00017283670604228973, 'timing/model': 0.4585856981575489, 'learning_rate/action_model': 7.728533357589616e-05, 'learning_rate/action_query_proj': 7.728533357589616e-05, 'learning_rate/base': 1.932133339397404e-05, 'epoch': 0.2}) +[2026-07-26 21:51:53,647][starVLA.training.train_starvla][INFO] - Step 1618, Loss: {'train/loss': 0.2531866133213043, 'train/grad_norm_pre_clip': 4.672346591949463, 'timing/data': 0.0001772330142557621, 'timing/model': 0.4580919537693262, 'learning_rate/action_model': 7.725969309872952e-05, 'learning_rate/action_query_proj': 7.725969309872952e-05, 'learning_rate/base': 1.931492327468238e-05, 'epoch': 0.2}) +[2026-07-26 21:51:59,164][starVLA.training.train_starvla][INFO] - Step 1619, Loss: {'train/loss': 0.44516557455062866, 'train/grad_norm_pre_clip': 5.169576644897461, 'timing/data': 0.00018371501937508583, 'timing/model': 0.4573043929412961, 'learning_rate/action_model': 7.723404264943607e-05, 'learning_rate/action_query_proj': 7.723404264943607e-05, 'learning_rate/base': 1.9308510662359016e-05, 'epoch': 0.2}) +[2026-07-26 21:52:04,690][starVLA.training.train_starvla][INFO] - Step 1620, Loss: {'train/loss': 0.2688594460487366, 'train/grad_norm_pre_clip': 3.4787487983703613, 'timing/data': 0.0001801750622689724, 'timing/model': 0.4572444758377969, 'learning_rate/action_model': 7.72083822381422e-05, 'learning_rate/action_query_proj': 7.72083822381422e-05, 'learning_rate/base': 1.930209555953555e-05, 'epoch': 0.2}) +[2026-07-26 21:52:10,201][starVLA.training.train_starvla][INFO] - Step 1621, Loss: {'train/loss': 0.4242594540119171, 'train/grad_norm_pre_clip': 5.474217414855957, 'timing/data': 0.00016988487914204597, 'timing/model': 0.45706805819645524, 'learning_rate/action_model': 7.718271187497827e-05, 'learning_rate/action_query_proj': 7.718271187497827e-05, 'learning_rate/base': 1.9295677968744568e-05, 'epoch': 0.2}) +[2026-07-26 21:52:15,711][starVLA.training.train_starvla][INFO] - Step 1622, Loss: {'train/loss': 0.3455570936203003, 'train/grad_norm_pre_clip': 4.321257591247559, 'timing/data': 0.0001718178391456604, 'timing/model': 0.45734543818980455, 'learning_rate/action_model': 7.715703157007848e-05, 'learning_rate/action_query_proj': 7.715703157007848e-05, 'learning_rate/base': 1.928925789251962e-05, 'epoch': 0.2}) +[2026-07-26 21:52:21,215][starVLA.training.train_starvla][INFO] - Step 1623, Loss: {'train/loss': 0.2919343411922455, 'train/grad_norm_pre_clip': 3.0514259338378906, 'timing/data': 0.00017286790534853935, 'timing/model': 0.4581351960077882, 'learning_rate/action_model': 7.713134133358106e-05, 'learning_rate/action_query_proj': 7.713134133358106e-05, 'learning_rate/base': 1.9282835333395265e-05, 'epoch': 0.2}) +[2026-07-26 21:52:26,752][starVLA.training.train_starvla][INFO] - Step 1624, Loss: {'train/loss': 0.40444305539131165, 'train/grad_norm_pre_clip': 4.19366979598999, 'timing/data': 0.00018307799473404884, 'timing/model': 0.457595394924283, 'learning_rate/action_model': 7.710564117562808e-05, 'learning_rate/action_query_proj': 7.710564117562808e-05, 'learning_rate/base': 1.927641029390702e-05, 'epoch': 0.2}) +[2026-07-26 21:52:32,276][starVLA.training.train_starvla][INFO] - Step 1625, Loss: {'train/loss': 0.39993932843208313, 'train/grad_norm_pre_clip': 4.037374973297119, 'timing/data': 0.00017501506954431534, 'timing/model': 0.45790086314082146, 'learning_rate/action_model': 7.707993110636554e-05, 'learning_rate/action_query_proj': 7.707993110636554e-05, 'learning_rate/base': 1.9269982776591384e-05, 'epoch': 0.2}) +[2026-07-26 21:52:37,789][starVLA.training.train_starvla][INFO] - Step 1626, Loss: {'train/loss': 0.35261446237564087, 'train/grad_norm_pre_clip': 3.6754226684570312, 'timing/data': 0.00018599210307002068, 'timing/model': 0.4576538363471627, 'learning_rate/action_model': 7.705421113594342e-05, 'learning_rate/action_query_proj': 7.705421113594342e-05, 'learning_rate/base': 1.9263552783985854e-05, 'epoch': 0.2}) +[2026-07-26 21:52:43,310][starVLA.training.train_starvla][INFO] - Step 1627, Loss: {'train/loss': 0.35909444093704224, 'train/grad_norm_pre_clip': 4.687363624572754, 'timing/data': 0.0001777680590748787, 'timing/model': 0.4578234259970486, 'learning_rate/action_model': 7.70284812745155e-05, 'learning_rate/action_query_proj': 7.70284812745155e-05, 'learning_rate/base': 1.9257120318628875e-05, 'epoch': 0.2}) +[2026-07-26 21:52:48,826][starVLA.training.train_starvla][INFO] - Step 1628, Loss: {'train/loss': 0.4118138551712036, 'train/grad_norm_pre_clip': 3.2184526920318604, 'timing/data': 0.0001761135645210743, 'timing/model': 0.45834064204245806, 'learning_rate/action_model': 7.700274153223958e-05, 'learning_rate/action_query_proj': 7.700274153223958e-05, 'learning_rate/base': 1.9250685383059894e-05, 'epoch': 0.2}) +[2026-07-26 21:52:54,352][starVLA.training.train_starvla][INFO] - Step 1629, Loss: {'train/loss': 0.3543907701969147, 'train/grad_norm_pre_clip': 5.121155261993408, 'timing/data': 0.00017812708392739296, 'timing/model': 0.46063338685780764, 'learning_rate/action_model': 7.697699191927726e-05, 'learning_rate/action_query_proj': 7.697699191927726e-05, 'learning_rate/base': 1.9244247979819314e-05, 'epoch': 0.2}) +[2026-07-26 21:52:59,862][starVLA.training.train_starvla][INFO] - Step 1630, Loss: {'train/loss': 0.2451319396495819, 'train/grad_norm_pre_clip': 4.130297660827637, 'timing/data': 0.00018463609740138054, 'timing/model': 0.4577984921634197, 'learning_rate/action_model': 7.695123244579405e-05, 'learning_rate/action_query_proj': 7.695123244579405e-05, 'learning_rate/base': 1.9237808111448512e-05, 'epoch': 0.2}) +[2026-07-26 21:53:05,373][starVLA.training.train_starvla][INFO] - Step 1631, Loss: {'train/loss': 0.4351969361305237, 'train/grad_norm_pre_clip': 7.107354640960693, 'timing/data': 0.00019155209884047508, 'timing/model': 0.4609827818349004, 'learning_rate/action_model': 7.692546312195947e-05, 'learning_rate/action_query_proj': 7.692546312195947e-05, 'learning_rate/base': 1.9231365780489867e-05, 'epoch': 0.2}) +[2026-07-26 21:53:10,884][starVLA.training.train_starvla][INFO] - Step 1632, Loss: {'train/loss': 0.3736136257648468, 'train/grad_norm_pre_clip': 4.275711536407471, 'timing/data': 0.0001773596741259098, 'timing/model': 0.4581050709821284, 'learning_rate/action_model': 7.689968395794677e-05, 'learning_rate/action_query_proj': 7.689968395794677e-05, 'learning_rate/base': 1.9224920989486692e-05, 'epoch': 0.2}) +[2026-07-26 21:53:16,397][starVLA.training.train_starvla][INFO] - Step 1633, Loss: {'train/loss': 0.3349786102771759, 'train/grad_norm_pre_clip': 3.5659432411193848, 'timing/data': 0.00017702113837003708, 'timing/model': 0.4615988093428314, 'learning_rate/action_model': 7.68738949639332e-05, 'learning_rate/action_query_proj': 7.68738949639332e-05, 'learning_rate/base': 1.92184737409833e-05, 'epoch': 0.2}) +[2026-07-26 21:53:21,944][starVLA.training.train_starvla][INFO] - Step 1634, Loss: {'train/loss': 0.3243110179901123, 'train/grad_norm_pre_clip': 3.420065402984619, 'timing/data': 0.00018678884953260422, 'timing/model': 0.47372493287548423, 'learning_rate/action_model': 7.684809615009978e-05, 'learning_rate/action_query_proj': 7.684809615009978e-05, 'learning_rate/base': 1.9212024037524946e-05, 'epoch': 0.2}) +[2026-07-26 21:53:27,490][starVLA.training.train_starvla][INFO] - Step 1635, Loss: {'train/loss': 0.347912073135376, 'train/grad_norm_pre_clip': 3.4182016849517822, 'timing/data': 0.00017387187108397484, 'timing/model': 0.4563993541523814, 'learning_rate/action_model': 7.682228752663154e-05, 'learning_rate/action_query_proj': 7.682228752663154e-05, 'learning_rate/base': 1.9205571881657884e-05, 'epoch': 0.2}) +[2026-07-26 21:53:33,023][starVLA.training.train_starvla][INFO] - Step 1636, Loss: {'train/loss': 0.3273756504058838, 'train/grad_norm_pre_clip': 3.240675926208496, 'timing/data': 0.00018582679331302643, 'timing/model': 0.4585951790213585, 'learning_rate/action_model': 7.679646910371731e-05, 'learning_rate/action_query_proj': 7.679646910371731e-05, 'learning_rate/base': 1.9199117275929328e-05, 'epoch': 0.2}) +[2026-07-26 21:53:38,542][starVLA.training.train_starvla][INFO] - Step 1637, Loss: {'train/loss': 0.3575693964958191, 'train/grad_norm_pre_clip': 3.6772584915161133, 'timing/data': 0.00018402980640530586, 'timing/model': 0.4576089661568403, 'learning_rate/action_model': 7.677064089154976e-05, 'learning_rate/action_query_proj': 7.677064089154976e-05, 'learning_rate/base': 1.919266022288744e-05, 'epoch': 0.2}) +[2026-07-26 21:53:44,049][starVLA.training.train_starvla][INFO] - Step 1638, Loss: {'train/loss': 0.3293161392211914, 'train/grad_norm_pre_clip': 3.272334098815918, 'timing/data': 0.00018456624820828438, 'timing/model': 0.45789396995678544, 'learning_rate/action_model': 7.674480290032549e-05, 'learning_rate/action_query_proj': 7.674480290032549e-05, 'learning_rate/base': 1.918620072508137e-05, 'epoch': 0.2}) +[2026-07-26 21:53:49,556][starVLA.training.train_starvla][INFO] - Step 1639, Loss: {'train/loss': 0.36355096101760864, 'train/grad_norm_pre_clip': 4.027158260345459, 'timing/data': 0.00017928797751665115, 'timing/model': 0.4577321573160589, 'learning_rate/action_model': 7.671895514024492e-05, 'learning_rate/action_query_proj': 7.671895514024492e-05, 'learning_rate/base': 1.917973878506123e-05, 'epoch': 0.2}) +[2026-07-26 21:53:55,068][starVLA.training.train_starvla][INFO] - Step 1640, Loss: {'train/loss': 0.344630628824234, 'train/grad_norm_pre_clip': 3.0343120098114014, 'timing/data': 0.00017857039347290993, 'timing/model': 0.457118087913841, 'learning_rate/action_model': 7.66930976215123e-05, 'learning_rate/action_query_proj': 7.66930976215123e-05, 'learning_rate/base': 1.9173274405378077e-05, 'epoch': 0.2}) +[2026-07-26 21:54:00,596][starVLA.training.train_starvla][INFO] - Step 1641, Loss: {'train/loss': 0.2811349630355835, 'train/grad_norm_pre_clip': 3.272455930709839, 'timing/data': 0.00018249498680233955, 'timing/model': 0.4648772357031703, 'learning_rate/action_model': 7.666723035433584e-05, 'learning_rate/action_query_proj': 7.666723035433584e-05, 'learning_rate/base': 1.916680758858396e-05, 'epoch': 0.2}) +[2026-07-26 21:54:06,096][starVLA.training.train_starvla][INFO] - Step 1642, Loss: {'train/loss': 0.24790969491004944, 'train/grad_norm_pre_clip': 3.0553646087646484, 'timing/data': 0.00018156832084059715, 'timing/model': 0.4580546380020678, 'learning_rate/action_model': 7.664135334892747e-05, 'learning_rate/action_query_proj': 7.664135334892747e-05, 'learning_rate/base': 1.9160338337231867e-05, 'epoch': 0.2}) +[2026-07-26 21:54:11,600][starVLA.training.train_starvla][INFO] - Step 1643, Loss: {'train/loss': 0.33007436990737915, 'train/grad_norm_pre_clip': 4.427035808563232, 'timing/data': 0.0001774318516254425, 'timing/model': 0.45879686111584306, 'learning_rate/action_model': 7.661546661550306e-05, 'learning_rate/action_query_proj': 7.661546661550306e-05, 'learning_rate/base': 1.9153866653875764e-05, 'epoch': 0.2}) +[2026-07-26 21:54:17,114][starVLA.training.train_starvla][INFO] - Step 1644, Loss: {'train/loss': 0.24369673430919647, 'train/grad_norm_pre_clip': 4.367572784423828, 'timing/data': 0.00017971592023968697, 'timing/model': 0.45767759112641215, 'learning_rate/action_model': 7.658957016428225e-05, 'learning_rate/action_query_proj': 7.658957016428225e-05, 'learning_rate/base': 1.9147392541070563e-05, 'epoch': 0.2}) +[2026-07-26 21:54:22,643][starVLA.training.train_starvla][INFO] - Step 1645, Loss: {'train/loss': 0.3223894536495209, 'train/grad_norm_pre_clip': 3.8482718467712402, 'timing/data': 0.00017677200958132744, 'timing/model': 0.4582408326677978, 'learning_rate/action_model': 7.656366400548857e-05, 'learning_rate/action_query_proj': 7.656366400548857e-05, 'learning_rate/base': 1.914091600137214e-05, 'epoch': 0.2}) +[2026-07-26 21:54:28,159][starVLA.training.train_starvla][INFO] - Step 1646, Loss: {'train/loss': 0.22319477796554565, 'train/grad_norm_pre_clip': 2.537386178970337, 'timing/data': 0.0001818779855966568, 'timing/model': 0.4574746647849679, 'learning_rate/action_model': 7.653774814934935e-05, 'learning_rate/action_query_proj': 7.653774814934935e-05, 'learning_rate/base': 1.9134437037337336e-05, 'epoch': 0.2}) +[2026-07-26 21:54:33,679][starVLA.training.train_starvla][INFO] - Step 1647, Loss: {'train/loss': 0.37670913338661194, 'train/grad_norm_pre_clip': 4.129435062408447, 'timing/data': 0.00017594220116734505, 'timing/model': 0.45729488180950284, 'learning_rate/action_model': 7.651182260609575e-05, 'learning_rate/action_query_proj': 7.651182260609575e-05, 'learning_rate/base': 1.9127955651523937e-05, 'epoch': 0.2}) +[2026-07-26 21:54:39,201][starVLA.training.train_starvla][INFO] - Step 1648, Loss: {'train/loss': 0.3251338601112366, 'train/grad_norm_pre_clip': 2.8141398429870605, 'timing/data': 0.00018100440502166748, 'timing/model': 0.45778011390939355, 'learning_rate/action_model': 7.648588738596279e-05, 'learning_rate/action_query_proj': 7.648588738596279e-05, 'learning_rate/base': 1.9121471846490698e-05, 'epoch': 0.2}) +[2026-07-26 21:54:44,730][starVLA.training.train_starvla][INFO] - Step 1649, Loss: {'train/loss': 0.43224862217903137, 'train/grad_norm_pre_clip': 3.6006977558135986, 'timing/data': 0.00018745195120573044, 'timing/model': 0.45891444897279143, 'learning_rate/action_model': 7.645994249918927e-05, 'learning_rate/action_query_proj': 7.645994249918927e-05, 'learning_rate/base': 1.9114985624797318e-05, 'epoch': 0.2}) +[2026-07-26 21:54:50,268][starVLA.training.train_starvla][INFO] - Step 1650, Loss: {'train/loss': 0.2479177564382553, 'train/grad_norm_pre_clip': 3.1904616355895996, 'timing/data': 0.00018120789900422096, 'timing/model': 0.45731680002063513, 'learning_rate/action_model': 7.643398795601782e-05, 'learning_rate/action_query_proj': 7.643398795601782e-05, 'learning_rate/base': 1.9108496989004455e-05, 'epoch': 0.2}) +[2026-07-26 21:54:55,788][starVLA.training.train_starvla][INFO] - Step 1651, Loss: {'train/loss': 0.3752060830593109, 'train/grad_norm_pre_clip': 3.775282144546509, 'timing/data': 0.00017667515203356743, 'timing/model': 0.4573949361220002, 'learning_rate/action_model': 7.640802376669489e-05, 'learning_rate/action_query_proj': 7.640802376669489e-05, 'learning_rate/base': 1.9102005941673722e-05, 'epoch': 0.2}) +[2026-07-26 21:55:01,324][starVLA.training.train_starvla][INFO] - Step 1652, Loss: {'train/loss': 0.36353933811187744, 'train/grad_norm_pre_clip': 4.084232330322266, 'timing/data': 0.00017888285219669342, 'timing/model': 0.45829856721684337, 'learning_rate/action_model': 7.63820499414707e-05, 'learning_rate/action_query_proj': 7.63820499414707e-05, 'learning_rate/base': 1.9095512485367677e-05, 'epoch': 0.2}) +[2026-07-26 21:55:06,837][starVLA.training.train_starvla][INFO] - Step 1653, Loss: {'train/loss': 0.4967253506183624, 'train/grad_norm_pre_clip': 5.546100616455078, 'timing/data': 0.00017547979950904846, 'timing/model': 0.45788864605128765, 'learning_rate/action_model': 7.635606649059939e-05, 'learning_rate/action_query_proj': 7.635606649059939e-05, 'learning_rate/base': 1.9089016622649847e-05, 'epoch': 0.2}) +[2026-07-26 21:55:12,355][starVLA.training.train_starvla][INFO] - Step 1654, Loss: {'train/loss': 0.3384837508201599, 'train/grad_norm_pre_clip': 5.3672943115234375, 'timing/data': 0.00018062302842736244, 'timing/model': 0.45833665784448385, 'learning_rate/action_model': 7.633007342433872e-05, 'learning_rate/action_query_proj': 7.633007342433872e-05, 'learning_rate/base': 1.908251835608468e-05, 'epoch': 0.2}) +[2026-07-26 21:55:18,119][starVLA.training.train_starvla][INFO] - Step 1655, Loss: {'train/loss': 0.3345193862915039, 'train/grad_norm_pre_clip': 3.65627384185791, 'timing/data': 0.0001805960200726986, 'timing/model': 0.4580388097092509, 'learning_rate/action_model': 7.630407075295037e-05, 'learning_rate/action_query_proj': 7.630407075295037e-05, 'learning_rate/base': 1.907601768823759e-05, 'epoch': 0.2}) +[2026-07-26 21:55:23,673][starVLA.training.train_starvla][INFO] - Step 1656, Loss: {'train/loss': 0.2850620150566101, 'train/grad_norm_pre_clip': 3.8920867443084717, 'timing/data': 0.00017588306218385696, 'timing/model': 0.46034295903518796, 'learning_rate/action_model': 7.62780584866998e-05, 'learning_rate/action_query_proj': 7.62780584866998e-05, 'learning_rate/base': 1.906951462167495e-05, 'epoch': 0.2}) +[2026-07-26 21:55:29,203][starVLA.training.train_starvla][INFO] - Step 1657, Loss: {'train/loss': 0.286410391330719, 'train/grad_norm_pre_clip': 4.211836338043213, 'timing/data': 0.0001873238943517208, 'timing/model': 0.4581167153082788, 'learning_rate/action_model': 7.625203663585622e-05, 'learning_rate/action_query_proj': 7.625203663585622e-05, 'learning_rate/base': 1.9063009158964054e-05, 'epoch': 0.2}) +[2026-07-26 21:55:34,734][starVLA.training.train_starvla][INFO] - Step 1658, Loss: {'train/loss': 0.2819734811782837, 'train/grad_norm_pre_clip': 3.319209337234497, 'timing/data': 0.00017552915960550308, 'timing/model': 0.45856077410280704, 'learning_rate/action_model': 7.622600521069266e-05, 'learning_rate/action_query_proj': 7.622600521069266e-05, 'learning_rate/base': 1.9056501302673165e-05, 'epoch': 0.2}) +[2026-07-26 21:55:40,259][starVLA.training.train_starvla][INFO] - Step 1659, Loss: {'train/loss': 0.16241592168807983, 'train/grad_norm_pre_clip': 2.491602897644043, 'timing/data': 0.00018268870189785957, 'timing/model': 0.45698859402909875, 'learning_rate/action_model': 7.619996422148589e-05, 'learning_rate/action_query_proj': 7.619996422148589e-05, 'learning_rate/base': 1.9049991055371473e-05, 'epoch': 0.2}) +[2026-07-26 21:55:45,797][starVLA.training.train_starvla][INFO] - Step 1660, Loss: {'train/loss': 0.3656441867351532, 'train/grad_norm_pre_clip': 4.476451873779297, 'timing/data': 0.00017854804173111916, 'timing/model': 0.4600718249566853, 'learning_rate/action_model': 7.617391367851653e-05, 'learning_rate/action_query_proj': 7.617391367851653e-05, 'learning_rate/base': 1.9043478419629132e-05, 'epoch': 0.2}) +[2026-07-26 21:55:51,352][starVLA.training.train_starvla][INFO] - Step 1661, Loss: {'train/loss': 0.24937386810779572, 'train/grad_norm_pre_clip': 3.4631147384643555, 'timing/data': 0.00017811870202422142, 'timing/model': 0.4799009347334504, 'learning_rate/action_model': 7.614785359206888e-05, 'learning_rate/action_query_proj': 7.614785359206888e-05, 'learning_rate/base': 1.903696339801722e-05, 'epoch': 0.2}) +[2026-07-26 21:55:56,911][starVLA.training.train_starvla][INFO] - Step 1662, Loss: {'train/loss': 0.166117861866951, 'train/grad_norm_pre_clip': 3.1753997802734375, 'timing/data': 0.00017772288993000984, 'timing/model': 0.47431590501219034, 'learning_rate/action_model': 7.612178397243105e-05, 'learning_rate/action_query_proj': 7.612178397243105e-05, 'learning_rate/base': 1.9030445993107763e-05, 'epoch': 0.2}) +[2026-07-26 21:56:02,534][starVLA.training.train_starvla][INFO] - Step 1663, Loss: {'train/loss': 0.22919303178787231, 'train/grad_norm_pre_clip': 2.6586074829101562, 'timing/data': 0.00017810193821787834, 'timing/model': 0.4751607640646398, 'learning_rate/action_model': 7.609570482989494e-05, 'learning_rate/action_query_proj': 7.609570482989494e-05, 'learning_rate/base': 1.9023926207473734e-05, 'epoch': 0.2}) +[2026-07-26 21:56:08,115][starVLA.training.train_starvla][INFO] - Step 1664, Loss: {'train/loss': 0.3076300024986267, 'train/grad_norm_pre_clip': 4.245794296264648, 'timing/data': 0.00017543509602546692, 'timing/model': 0.47312749410048127, 'learning_rate/action_model': 7.606961617475615e-05, 'learning_rate/action_query_proj': 7.606961617475615e-05, 'learning_rate/base': 1.9017404043689037e-05, 'epoch': 0.2}) +[2026-07-26 21:56:13,928][starVLA.training.train_starvla][INFO] - Step 1665, Loss: {'train/loss': 0.36571449041366577, 'train/grad_norm_pre_clip': 4.005121231079102, 'timing/data': 0.00017330097034573555, 'timing/model': 0.4742608149535954, 'learning_rate/action_model': 7.604351801731409e-05, 'learning_rate/action_query_proj': 7.604351801731409e-05, 'learning_rate/base': 1.9010879504328523e-05, 'epoch': 0.2}) +[2026-07-26 21:56:19,495][starVLA.training.train_starvla][INFO] - Step 1666, Loss: {'train/loss': 0.4068508744239807, 'train/grad_norm_pre_clip': 4.0260491371154785, 'timing/data': 0.0001752781681716442, 'timing/model': 0.47177153220400214, 'learning_rate/action_model': 7.601741036787187e-05, 'learning_rate/action_query_proj': 7.601741036787187e-05, 'learning_rate/base': 1.9004352591967968e-05, 'epoch': 0.2}) +[2026-07-26 21:56:25,076][starVLA.training.train_starvla][INFO] - Step 1667, Loss: {'train/loss': 0.296061635017395, 'train/grad_norm_pre_clip': 3.1664648056030273, 'timing/data': 0.00018151989206671715, 'timing/model': 0.4747399198822677, 'learning_rate/action_model': 7.599129323673643e-05, 'learning_rate/action_query_proj': 7.599129323673643e-05, 'learning_rate/base': 1.8997823309184108e-05, 'epoch': 0.2}) +[2026-07-26 21:56:30,641][starVLA.training.train_starvla][INFO] - Step 1668, Loss: {'train/loss': 0.4596761167049408, 'train/grad_norm_pre_clip': 4.239711761474609, 'timing/data': 0.0001707230694591999, 'timing/model': 0.4686401220969856, 'learning_rate/action_model': 7.596516663421837e-05, 'learning_rate/action_query_proj': 7.596516663421837e-05, 'learning_rate/base': 1.8991291658554592e-05, 'epoch': 0.2}) +[2026-07-26 21:56:36,208][starVLA.training.train_starvla][INFO] - Step 1669, Loss: {'train/loss': 0.3255872130393982, 'train/grad_norm_pre_clip': 3.290769100189209, 'timing/data': 0.00017636502161622047, 'timing/model': 0.4752941392362118, 'learning_rate/action_model': 7.593903057063204e-05, 'learning_rate/action_query_proj': 7.593903057063204e-05, 'learning_rate/base': 1.898475764265801e-05, 'epoch': 0.2}) +[2026-07-26 21:56:41,774][starVLA.training.train_starvla][INFO] - Step 1670, Loss: {'train/loss': 0.4379886984825134, 'train/grad_norm_pre_clip': 4.000573635101318, 'timing/data': 0.00017225230112671852, 'timing/model': 0.4746112353168428, 'learning_rate/action_model': 7.591288505629556e-05, 'learning_rate/action_query_proj': 7.591288505629556e-05, 'learning_rate/base': 1.897822126407389e-05, 'epoch': 0.2}) +[2026-07-26 21:56:47,338][starVLA.training.train_starvla][INFO] - Step 1671, Loss: {'train/loss': 0.18195170164108276, 'train/grad_norm_pre_clip': 2.383955240249634, 'timing/data': 0.00018458999693393707, 'timing/model': 0.47363219503313303, 'learning_rate/action_model': 7.588673010153079e-05, 'learning_rate/action_query_proj': 7.588673010153079e-05, 'learning_rate/base': 1.8971682525382696e-05, 'epoch': 0.2}) +[2026-07-26 21:56:52,873][starVLA.training.train_starvla][INFO] - Step 1672, Loss: {'train/loss': 0.31507590413093567, 'train/grad_norm_pre_clip': 3.4943883419036865, 'timing/data': 0.00019789254292845726, 'timing/model': 0.45891851000487804, 'learning_rate/action_model': 7.586056571666326e-05, 'learning_rate/action_query_proj': 7.586056571666326e-05, 'learning_rate/base': 1.8965141429165815e-05, 'epoch': 0.2}) +[2026-07-26 21:56:58,407][starVLA.training.train_starvla][INFO] - Step 1673, Loss: {'train/loss': 0.3016739785671234, 'train/grad_norm_pre_clip': 3.757875919342041, 'timing/data': 0.00017442693933844566, 'timing/model': 0.4608297157101333, 'learning_rate/action_model': 7.583439191202224e-05, 'learning_rate/action_query_proj': 7.583439191202224e-05, 'learning_rate/base': 1.895859797800556e-05, 'epoch': 0.2}) +[2026-07-26 21:57:03,933][starVLA.training.train_starvla][INFO] - Step 1674, Loss: {'train/loss': 0.43590790033340454, 'train/grad_norm_pre_clip': 5.165084362030029, 'timing/data': 0.0001731710508465767, 'timing/model': 0.4601645260117948, 'learning_rate/action_model': 7.580820869794077e-05, 'learning_rate/action_query_proj': 7.580820869794077e-05, 'learning_rate/base': 1.8952052174485192e-05, 'epoch': 0.2}) +[2026-07-26 21:57:09,464][starVLA.training.train_starvla][INFO] - Step 1675, Loss: {'train/loss': 0.48928773403167725, 'train/grad_norm_pre_clip': 6.6977996826171875, 'timing/data': 0.000174736138433218, 'timing/model': 0.4587563811801374, 'learning_rate/action_model': 7.578201608475557e-05, 'learning_rate/action_query_proj': 7.578201608475557e-05, 'learning_rate/base': 1.8945504021188893e-05, 'epoch': 0.2}) +[2026-07-26 21:57:14,986][starVLA.training.train_starvla][INFO] - Step 1676, Loss: {'train/loss': 0.318539559841156, 'train/grad_norm_pre_clip': 4.665047645568848, 'timing/data': 0.00017832079902291298, 'timing/model': 0.45867320569232106, 'learning_rate/action_model': 7.575581408280705e-05, 'learning_rate/action_query_proj': 7.575581408280705e-05, 'learning_rate/base': 1.8938953520701762e-05, 'epoch': 0.2}) +[2026-07-26 21:57:20,522][starVLA.training.train_starvla][INFO] - Step 1677, Loss: {'train/loss': 0.34711670875549316, 'train/grad_norm_pre_clip': 3.873016119003296, 'timing/data': 0.00017353100702166557, 'timing/model': 0.4594981479458511, 'learning_rate/action_model': 7.572960270243934e-05, 'learning_rate/action_query_proj': 7.572960270243934e-05, 'learning_rate/base': 1.8932400675609835e-05, 'epoch': 0.2}) +[2026-07-26 21:57:26,055][starVLA.training.train_starvla][INFO] - Step 1678, Loss: {'train/loss': 0.315134733915329, 'train/grad_norm_pre_clip': 4.450930595397949, 'timing/data': 0.00017417734488844872, 'timing/model': 0.45761325815692544, 'learning_rate/action_model': 7.570338195400029e-05, 'learning_rate/action_query_proj': 7.570338195400029e-05, 'learning_rate/base': 1.8925845488500073e-05, 'epoch': 0.2}) +[2026-07-26 21:57:31,585][starVLA.training.train_starvla][INFO] - Step 1679, Loss: {'train/loss': 0.4486294388771057, 'train/grad_norm_pre_clip': 3.7661166191101074, 'timing/data': 0.00017263693735003471, 'timing/model': 0.4571907860226929, 'learning_rate/action_model': 7.567715184784144e-05, 'learning_rate/action_query_proj': 7.567715184784144e-05, 'learning_rate/base': 1.891928796196036e-05, 'epoch': 0.2}) +[2026-07-26 21:57:37,127][starVLA.training.train_starvla][INFO] - Step 1680, Loss: {'train/loss': 0.2751386761665344, 'train/grad_norm_pre_clip': 5.367060661315918, 'timing/data': 0.0001749699003994465, 'timing/model': 0.4580014883540571, 'learning_rate/action_model': 7.5650912394318e-05, 'learning_rate/action_query_proj': 7.5650912394318e-05, 'learning_rate/base': 1.89127280985795e-05, 'epoch': 0.2}) +[2026-07-26 21:57:42,682][starVLA.training.train_starvla][INFO] - Step 1681, Loss: {'train/loss': 0.3042943775653839, 'train/grad_norm_pre_clip': 3.4229040145874023, 'timing/data': 0.00017090141773223877, 'timing/model': 0.4590169438160956, 'learning_rate/action_model': 7.562466360378891e-05, 'learning_rate/action_query_proj': 7.562466360378891e-05, 'learning_rate/base': 1.8906165900947228e-05, 'epoch': 0.2}) +[2026-07-26 21:57:48,229][starVLA.training.train_starvla][INFO] - Step 1682, Loss: {'train/loss': 0.28787699341773987, 'train/grad_norm_pre_clip': 3.9270846843719482, 'timing/data': 0.00017051119357347488, 'timing/model': 0.4580933041870594, 'learning_rate/action_model': 7.559840548661678e-05, 'learning_rate/action_query_proj': 7.559840548661678e-05, 'learning_rate/base': 1.8899601371654195e-05, 'epoch': 0.2}) +[2026-07-26 21:57:53,770][starVLA.training.train_starvla][INFO] - Step 1683, Loss: {'train/loss': 0.3632681369781494, 'train/grad_norm_pre_clip': 5.503645420074463, 'timing/data': 0.00018335599452257156, 'timing/model': 0.4580252142623067, 'learning_rate/action_model': 7.557213805316788e-05, 'learning_rate/action_query_proj': 7.557213805316788e-05, 'learning_rate/base': 1.889303451329197e-05, 'epoch': 0.2}) +[2026-07-26 21:57:59,319][starVLA.training.train_starvla][INFO] - Step 1684, Loss: {'train/loss': 0.45144134759902954, 'train/grad_norm_pre_clip': 6.885928630828857, 'timing/data': 0.00017405906692147255, 'timing/model': 0.45827159797772765, 'learning_rate/action_model': 7.55458613138122e-05, 'learning_rate/action_query_proj': 7.55458613138122e-05, 'learning_rate/base': 1.888646532845305e-05, 'epoch': 0.2}) +[2026-07-26 21:58:04,910][starVLA.training.train_starvla][INFO] - Step 1685, Loss: {'train/loss': 0.3484678566455841, 'train/grad_norm_pre_clip': 3.55454421043396, 'timing/data': 0.00016965670511126518, 'timing/model': 0.45866564381867647, 'learning_rate/action_model': 7.551957527892335e-05, 'learning_rate/action_query_proj': 7.551957527892335e-05, 'learning_rate/base': 1.887989381973084e-05, 'epoch': 0.2}) +[2026-07-26 21:58:10,444][starVLA.training.train_starvla][INFO] - Step 1686, Loss: {'train/loss': 0.5113692283630371, 'train/grad_norm_pre_clip': 6.42655611038208, 'timing/data': 0.00017581740394234657, 'timing/model': 0.45824895007535815, 'learning_rate/action_model': 7.549327995887869e-05, 'learning_rate/action_query_proj': 7.549327995887869e-05, 'learning_rate/base': 1.8873319989719672e-05, 'epoch': 0.2}) +[2026-07-26 21:58:15,969][starVLA.training.train_starvla][INFO] - Step 1687, Loss: {'train/loss': 0.4101889729499817, 'train/grad_norm_pre_clip': 4.988023281097412, 'timing/data': 0.0001748139038681984, 'timing/model': 0.45942834997549653, 'learning_rate/action_model': 7.546697536405914e-05, 'learning_rate/action_query_proj': 7.546697536405914e-05, 'learning_rate/base': 1.8866743841014786e-05, 'epoch': 0.2}) +[2026-07-26 21:58:21,494][starVLA.training.train_starvla][INFO] - Step 1688, Loss: {'train/loss': 0.2907160222530365, 'train/grad_norm_pre_clip': 3.5329976081848145, 'timing/data': 0.0001720227301120758, 'timing/model': 0.458637862931937, 'learning_rate/action_model': 7.544066150484936e-05, 'learning_rate/action_query_proj': 7.544066150484936e-05, 'learning_rate/base': 1.886016537621234e-05, 'epoch': 0.2}) +[2026-07-26 21:58:27,225][starVLA.training.train_starvla][INFO] - Step 1689, Loss: {'train/loss': 0.3682255148887634, 'train/grad_norm_pre_clip': 4.736027717590332, 'timing/data': 0.00017181690782308578, 'timing/model': 0.45836108503863215, 'learning_rate/action_model': 7.541433839163765e-05, 'learning_rate/action_query_proj': 7.541433839163765e-05, 'learning_rate/base': 1.8853584597909412e-05, 'epoch': 0.2}) +[2026-07-26 21:58:32,755][starVLA.training.train_starvla][INFO] - Step 1690, Loss: {'train/loss': 0.27136510610580444, 'train/grad_norm_pre_clip': 3.2597899436950684, 'timing/data': 0.0001723901368677616, 'timing/model': 0.45764591777697206, 'learning_rate/action_model': 7.538800603481596e-05, 'learning_rate/action_query_proj': 7.538800603481596e-05, 'learning_rate/base': 1.884700150870399e-05, 'epoch': 0.21}) +[2026-07-26 21:58:38,287][starVLA.training.train_starvla][INFO] - Step 1691, Loss: {'train/loss': 0.4911830425262451, 'train/grad_norm_pre_clip': 5.32211446762085, 'timing/data': 0.0001771962270140648, 'timing/model': 0.4587445077486336, 'learning_rate/action_model': 7.536166444477986e-05, 'learning_rate/action_query_proj': 7.536166444477986e-05, 'learning_rate/base': 1.8840416111194966e-05, 'epoch': 0.21}) +[2026-07-26 21:58:44,054][starVLA.training.train_starvla][INFO] - Step 1692, Loss: {'train/loss': 0.38119661808013916, 'train/grad_norm_pre_clip': 2.8550925254821777, 'timing/data': 0.00017485395073890686, 'timing/model': 0.47864518966525793, 'learning_rate/action_model': 7.533531363192865e-05, 'learning_rate/action_query_proj': 7.533531363192865e-05, 'learning_rate/base': 1.8833828407982163e-05, 'epoch': 0.21}) +[2026-07-26 21:58:49,636][starVLA.training.train_starvla][INFO] - Step 1693, Loss: {'train/loss': 0.27372488379478455, 'train/grad_norm_pre_clip': 3.3053476810455322, 'timing/data': 0.00018846523016691208, 'timing/model': 0.4715523258782923, 'learning_rate/action_model': 7.530895360666515e-05, 'learning_rate/action_query_proj': 7.530895360666515e-05, 'learning_rate/base': 1.882723840166629e-05, 'epoch': 0.21}) +[2026-07-26 21:58:55,199][starVLA.training.train_starvla][INFO] - Step 1694, Loss: {'train/loss': 0.39748334884643555, 'train/grad_norm_pre_clip': 4.861843109130859, 'timing/data': 0.00019159121438860893, 'timing/model': 0.47077974397689104, 'learning_rate/action_model': 7.528258437939592e-05, 'learning_rate/action_query_proj': 7.528258437939592e-05, 'learning_rate/base': 1.882064609484898e-05, 'epoch': 0.21}) +[2026-07-26 21:59:00,757][starVLA.training.train_starvla][INFO] - Step 1695, Loss: {'train/loss': 0.3257148563861847, 'train/grad_norm_pre_clip': 4.2210774421691895, 'timing/data': 0.00017581600695848465, 'timing/model': 0.46979104820638895, 'learning_rate/action_model': 7.52562059605311e-05, 'learning_rate/action_query_proj': 7.52562059605311e-05, 'learning_rate/base': 1.8814051490132775e-05, 'epoch': 0.21}) +[2026-07-26 21:59:06,311][starVLA.training.train_starvla][INFO] - Step 1696, Loss: {'train/loss': 0.2632201313972473, 'train/grad_norm_pre_clip': 4.193467617034912, 'timing/data': 0.00017968937754631042, 'timing/model': 0.4687484889291227, 'learning_rate/action_model': 7.522981836048447e-05, 'learning_rate/action_query_proj': 7.522981836048447e-05, 'learning_rate/base': 1.880745459012112e-05, 'epoch': 0.21}) +[2026-07-26 21:59:11,878][starVLA.training.train_starvla][INFO] - Step 1697, Loss: {'train/loss': 0.2840319275856018, 'train/grad_norm_pre_clip': 2.7562005519866943, 'timing/data': 0.00017661694437265396, 'timing/model': 0.47602683771401644, 'learning_rate/action_model': 7.520342158967347e-05, 'learning_rate/action_query_proj': 7.520342158967347e-05, 'learning_rate/base': 1.8800855397418367e-05, 'epoch': 0.21}) +[2026-07-26 21:59:17,409][starVLA.training.train_starvla][INFO] - Step 1698, Loss: {'train/loss': 0.2637438476085663, 'train/grad_norm_pre_clip': 4.548277854919434, 'timing/data': 0.0001782807521522045, 'timing/model': 0.45844437135383487, 'learning_rate/action_model': 7.517701565851905e-05, 'learning_rate/action_query_proj': 7.517701565851905e-05, 'learning_rate/base': 1.8794253914629763e-05, 'epoch': 0.21}) +[2026-07-26 21:59:22,956][starVLA.training.train_starvla][INFO] - Step 1699, Loss: {'train/loss': 0.3850322365760803, 'train/grad_norm_pre_clip': 4.499848365783691, 'timing/data': 0.00017888005822896957, 'timing/model': 0.4586729588918388, 'learning_rate/action_model': 7.515060057744594e-05, 'learning_rate/action_query_proj': 7.515060057744594e-05, 'learning_rate/base': 1.8787650144361485e-05, 'epoch': 0.21}) +[2026-07-26 21:59:28,517][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 1700 +[2026-07-26 21:59:28,517][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 1700 +[2026-07-26 21:59:28,518][starVLA.training.train_starvla][INFO] - Step 1700, Loss: {'train/loss': 0.2854008078575134, 'train/grad_norm_pre_clip': 2.6605637073516846, 'timing/data': 0.00017849216237664223, 'timing/model': 0.4592313230969012, 'learning_rate/action_model': 7.512417635688234e-05, 'learning_rate/action_query_proj': 7.512417635688234e-05, 'learning_rate/base': 1.8781044089220585e-05, 'epoch': 0.21}) +[2026-07-26 21:59:34,060][starVLA.training.train_starvla][INFO] - Step 1701, Loss: {'train/loss': 0.2869011461734772, 'train/grad_norm_pre_clip': 3.5697803497314453, 'timing/data': 0.0001877150498330593, 'timing/model': 0.4587791943922639, 'learning_rate/action_model': 7.509774300726013e-05, 'learning_rate/action_query_proj': 7.509774300726013e-05, 'learning_rate/base': 1.8774435751815033e-05, 'epoch': 0.21}) +[2026-07-26 21:59:39,621][starVLA.training.train_starvla][INFO] - Step 1702, Loss: {'train/loss': 0.3655678629875183, 'train/grad_norm_pre_clip': 3.5884287357330322, 'timing/data': 0.00017163017764687538, 'timing/model': 0.4602766647003591, 'learning_rate/action_model': 7.507130053901479e-05, 'learning_rate/action_query_proj': 7.507130053901479e-05, 'learning_rate/base': 1.8767825134753698e-05, 'epoch': 0.21}) +[2026-07-26 21:59:45,186][starVLA.training.train_starvla][INFO] - Step 1703, Loss: {'train/loss': 0.3039998710155487, 'train/grad_norm_pre_clip': 3.6856443881988525, 'timing/data': 0.00017325300723314285, 'timing/model': 0.45788817293941975, 'learning_rate/action_model': 7.504484896258534e-05, 'learning_rate/action_query_proj': 7.504484896258534e-05, 'learning_rate/base': 1.8761212240646335e-05, 'epoch': 0.21}) +[2026-07-26 21:59:50,740][starVLA.training.train_starvla][INFO] - Step 1704, Loss: {'train/loss': 0.3752077519893646, 'train/grad_norm_pre_clip': 5.350024223327637, 'timing/data': 0.000170260202139616, 'timing/model': 0.4590380294248462, 'learning_rate/action_model': 7.501838828841452e-05, 'learning_rate/action_query_proj': 7.501838828841452e-05, 'learning_rate/base': 1.875459707210363e-05, 'epoch': 0.21}) +[2026-07-26 21:59:56,304][starVLA.training.train_starvla][INFO] - Step 1705, Loss: {'train/loss': 0.24591860175132751, 'train/grad_norm_pre_clip': 3.4576187133789062, 'timing/data': 0.0001774020493030548, 'timing/model': 0.45786532294005156, 'learning_rate/action_model': 7.499191852694854e-05, 'learning_rate/action_query_proj': 7.499191852694854e-05, 'learning_rate/base': 1.8747979631737135e-05, 'epoch': 0.21}) +[2026-07-26 22:00:01,915][starVLA.training.train_starvla][INFO] - Step 1706, Loss: {'train/loss': 0.2836267948150635, 'train/grad_norm_pre_clip': 3.6384472846984863, 'timing/data': 0.00017315195873379707, 'timing/model': 0.45829150965437293, 'learning_rate/action_model': 7.496543968863722e-05, 'learning_rate/action_query_proj': 7.496543968863722e-05, 'learning_rate/base': 1.8741359922159306e-05, 'epoch': 0.21}) +[2026-07-26 22:00:07,709][starVLA.training.train_starvla][INFO] - Step 1707, Loss: {'train/loss': 0.24187301099300385, 'train/grad_norm_pre_clip': 3.430443286895752, 'timing/data': 0.00017940206453204155, 'timing/model': 0.45820092828944325, 'learning_rate/action_model': 7.493895178393404e-05, 'learning_rate/action_query_proj': 7.493895178393404e-05, 'learning_rate/base': 1.873473794598351e-05, 'epoch': 0.21}) +[2026-07-26 22:00:13,535][starVLA.training.train_starvla][INFO] - Step 1708, Loss: {'train/loss': 0.25629550218582153, 'train/grad_norm_pre_clip': 3.005014181137085, 'timing/data': 0.00017617084085941315, 'timing/model': 0.4588959631510079, 'learning_rate/action_model': 7.491245482329597e-05, 'learning_rate/action_query_proj': 7.491245482329597e-05, 'learning_rate/base': 1.8728113705823993e-05, 'epoch': 0.21}) +[2026-07-26 22:00:19,132][starVLA.training.train_starvla][INFO] - Step 1709, Loss: {'train/loss': 0.3409797251224518, 'train/grad_norm_pre_clip': 3.397395133972168, 'timing/data': 0.00017161201685667038, 'timing/model': 0.459518579300493, 'learning_rate/action_model': 7.488594881718362e-05, 'learning_rate/action_query_proj': 7.488594881718362e-05, 'learning_rate/base': 1.8721487204295905e-05, 'epoch': 0.21}) +[2026-07-26 22:00:24,697][starVLA.training.train_starvla][INFO] - Step 1710, Loss: {'train/loss': 0.22137752175331116, 'train/grad_norm_pre_clip': 2.911022901535034, 'timing/data': 0.0001725936308503151, 'timing/model': 0.45922430511564016, 'learning_rate/action_model': 7.485943377606109e-05, 'learning_rate/action_query_proj': 7.485943377606109e-05, 'learning_rate/base': 1.8714858444015272e-05, 'epoch': 0.21}) +[2026-07-26 22:00:30,256][starVLA.training.train_starvla][INFO] - Step 1711, Loss: {'train/loss': 0.3171176612377167, 'train/grad_norm_pre_clip': 3.7755680084228516, 'timing/data': 0.00017271703109145164, 'timing/model': 0.45846419921144843, 'learning_rate/action_model': 7.483290971039614e-05, 'learning_rate/action_query_proj': 7.483290971039614e-05, 'learning_rate/base': 1.8708227427599036e-05, 'epoch': 0.21}) +[2026-07-26 22:00:35,848][starVLA.training.train_starvla][INFO] - Step 1712, Loss: {'train/loss': 0.29956379532814026, 'train/grad_norm_pre_clip': 4.442272663116455, 'timing/data': 0.00016996124759316444, 'timing/model': 0.4579744338989258, 'learning_rate/action_model': 7.480637663066004e-05, 'learning_rate/action_query_proj': 7.480637663066004e-05, 'learning_rate/base': 1.870159415766501e-05, 'epoch': 0.21}) +[2026-07-26 22:00:41,640][starVLA.training.train_starvla][INFO] - Step 1713, Loss: {'train/loss': 0.4023542106151581, 'train/grad_norm_pre_clip': 6.48110818862915, 'timing/data': 0.00017023785039782524, 'timing/model': 0.45858172699809074, 'learning_rate/action_model': 7.477983454732762e-05, 'learning_rate/action_query_proj': 7.477983454732762e-05, 'learning_rate/base': 1.8694958636831904e-05, 'epoch': 0.21}) +[2026-07-26 22:00:47,211][starVLA.training.train_starvla][INFO] - Step 1714, Loss: {'train/loss': 0.3546319901943207, 'train/grad_norm_pre_clip': 4.6879563331604, 'timing/data': 0.000174814835190773, 'timing/model': 0.4583167051896453, 'learning_rate/action_model': 7.475328347087729e-05, 'learning_rate/action_query_proj': 7.475328347087729e-05, 'learning_rate/base': 1.868832086771932e-05, 'epoch': 0.21}) +[2026-07-26 22:00:52,786][starVLA.training.train_starvla][INFO] - Step 1715, Loss: {'train/loss': 0.34779036045074463, 'train/grad_norm_pre_clip': 4.739287376403809, 'timing/data': 0.0001705610193312168, 'timing/model': 0.4586733691394329, 'learning_rate/action_model': 7.472672341179099e-05, 'learning_rate/action_query_proj': 7.472672341179099e-05, 'learning_rate/base': 1.8681680852947747e-05, 'epoch': 0.21}) +[2026-07-26 22:00:58,358][starVLA.training.train_starvla][INFO] - Step 1716, Loss: {'train/loss': 0.47042351961135864, 'train/grad_norm_pre_clip': 6.20383358001709, 'timing/data': 0.00017543509602546692, 'timing/model': 0.45845578238368034, 'learning_rate/action_model': 7.470015438055421e-05, 'learning_rate/action_query_proj': 7.470015438055421e-05, 'learning_rate/base': 1.8675038595138553e-05, 'epoch': 0.21}) +[2026-07-26 22:01:03,939][starVLA.training.train_starvla][INFO] - Step 1717, Loss: {'train/loss': 0.3831205368041992, 'train/grad_norm_pre_clip': 5.700804233551025, 'timing/data': 0.00019031018018722534, 'timing/model': 0.458254337310791, 'learning_rate/action_model': 7.467357638765598e-05, 'learning_rate/action_query_proj': 7.467357638765598e-05, 'learning_rate/base': 1.8668394096913996e-05, 'epoch': 0.21}) +[2026-07-26 22:01:09,500][starVLA.training.train_starvla][INFO] - Step 1718, Loss: {'train/loss': 0.2958759665489197, 'train/grad_norm_pre_clip': 3.70961856842041, 'timing/data': 0.00017526885494589806, 'timing/model': 0.45819473871961236, 'learning_rate/action_model': 7.464698944358887e-05, 'learning_rate/action_query_proj': 7.464698944358887e-05, 'learning_rate/base': 1.8661747360897218e-05, 'epoch': 0.21}) +[2026-07-26 22:01:15,049][starVLA.training.train_starvla][INFO] - Step 1719, Loss: {'train/loss': 0.3954399824142456, 'train/grad_norm_pre_clip': 5.970126152038574, 'timing/data': 0.0001806868240237236, 'timing/model': 0.45834818994626403, 'learning_rate/action_model': 7.462039355884899e-05, 'learning_rate/action_query_proj': 7.462039355884899e-05, 'learning_rate/base': 1.8655098389712247e-05, 'epoch': 0.21}) +[2026-07-26 22:01:20,612][starVLA.training.train_starvla][INFO] - Step 1720, Loss: {'train/loss': 0.32032468914985657, 'train/grad_norm_pre_clip': 4.0564165115356445, 'timing/data': 0.00017845723778009415, 'timing/model': 0.4589624390937388, 'learning_rate/action_model': 7.459378874393598e-05, 'learning_rate/action_query_proj': 7.459378874393598e-05, 'learning_rate/base': 1.8648447185983994e-05, 'epoch': 0.21}) +[2026-07-26 22:01:26,187][starVLA.training.train_starvla][INFO] - Step 1721, Loss: {'train/loss': 0.4013996720314026, 'train/grad_norm_pre_clip': 4.029879570007324, 'timing/data': 0.0001729186624288559, 'timing/model': 0.46021703677251935, 'learning_rate/action_model': 7.456717500935298e-05, 'learning_rate/action_query_proj': 7.456717500935298e-05, 'learning_rate/base': 1.8641793752338244e-05, 'epoch': 0.21}) +[2026-07-26 22:01:32,005][starVLA.training.train_starvla][INFO] - Step 1722, Loss: {'train/loss': 0.3539692461490631, 'train/grad_norm_pre_clip': 4.247800827026367, 'timing/data': 0.00017581693828105927, 'timing/model': 0.45782187627628446, 'learning_rate/action_model': 7.454055236560668e-05, 'learning_rate/action_query_proj': 7.454055236560668e-05, 'learning_rate/base': 1.863513809140167e-05, 'epoch': 0.21}) +[2026-07-26 22:01:37,578][starVLA.training.train_starvla][INFO] - Step 1723, Loss: {'train/loss': 0.37261807918548584, 'train/grad_norm_pre_clip': 4.420726776123047, 'timing/data': 0.0001759398728609085, 'timing/model': 0.4579480569809675, 'learning_rate/action_model': 7.451392082320727e-05, 'learning_rate/action_query_proj': 7.451392082320727e-05, 'learning_rate/base': 1.8628480205801818e-05, 'epoch': 0.21}) +[2026-07-26 22:01:43,150][starVLA.training.train_starvla][INFO] - Step 1724, Loss: {'train/loss': 0.4412310719490051, 'train/grad_norm_pre_clip': 6.239474296569824, 'timing/data': 0.0001745428889989853, 'timing/model': 0.4577496307902038, 'learning_rate/action_model': 7.44872803926685e-05, 'learning_rate/action_query_proj': 7.44872803926685e-05, 'learning_rate/base': 1.8621820098167124e-05, 'epoch': 0.21}) +[2026-07-26 22:01:48,721][starVLA.training.train_starvla][INFO] - Step 1725, Loss: {'train/loss': 0.18172737956047058, 'train/grad_norm_pre_clip': 2.4597244262695312, 'timing/data': 0.00017955387011170387, 'timing/model': 0.4580133422277868, 'learning_rate/action_model': 7.446063108450753e-05, 'learning_rate/action_query_proj': 7.446063108450753e-05, 'learning_rate/base': 1.8615157771126882e-05, 'epoch': 0.21}) +[2026-07-26 22:01:54,303][starVLA.training.train_starvla][INFO] - Step 1726, Loss: {'train/loss': 0.3000146746635437, 'train/grad_norm_pre_clip': 3.685150384902954, 'timing/data': 0.00017240410670638084, 'timing/model': 0.4585379809141159, 'learning_rate/action_model': 7.443397290924513e-05, 'learning_rate/action_query_proj': 7.443397290924513e-05, 'learning_rate/base': 1.8608493227311284e-05, 'epoch': 0.21}) +[2026-07-26 22:01:59,887][starVLA.training.train_starvla][INFO] - Step 1727, Loss: {'train/loss': 0.21908704936504364, 'train/grad_norm_pre_clip': 2.6650373935699463, 'timing/data': 0.00017932523041963577, 'timing/model': 0.45871065417304635, 'learning_rate/action_model': 7.440730587740551e-05, 'learning_rate/action_query_proj': 7.440730587740551e-05, 'learning_rate/base': 1.8601826469351378e-05, 'epoch': 0.21}) +[2026-07-26 22:02:05,457][starVLA.training.train_starvla][INFO] - Step 1728, Loss: {'train/loss': 0.36399906873703003, 'train/grad_norm_pre_clip': 3.4137885570526123, 'timing/data': 0.000175348948687315, 'timing/model': 0.45738541474565864, 'learning_rate/action_model': 7.43806299995164e-05, 'learning_rate/action_query_proj': 7.43806299995164e-05, 'learning_rate/base': 1.85951574998791e-05, 'epoch': 0.21}) +[2026-07-26 22:02:11,027][starVLA.training.train_starvla][INFO] - Step 1729, Loss: {'train/loss': 0.43604835867881775, 'train/grad_norm_pre_clip': 5.617831707000732, 'timing/data': 0.0001743631437420845, 'timing/model': 0.4578045541420579, 'learning_rate/action_model': 7.435394528610899e-05, 'learning_rate/action_query_proj': 7.435394528610899e-05, 'learning_rate/base': 1.8588486321527247e-05, 'epoch': 0.21}) +[2026-07-26 22:02:16,593][starVLA.training.train_starvla][INFO] - Step 1730, Loss: {'train/loss': 0.28844118118286133, 'train/grad_norm_pre_clip': 3.536938190460205, 'timing/data': 0.00019185198470950127, 'timing/model': 0.4586353818885982, 'learning_rate/action_model': 7.4327251747718e-05, 'learning_rate/action_query_proj': 7.4327251747718e-05, 'learning_rate/base': 1.85818129369295e-05, 'epoch': 0.21}) +[2026-07-26 22:02:22,164][starVLA.training.train_starvla][INFO] - Step 1731, Loss: {'train/loss': 0.262404203414917, 'train/grad_norm_pre_clip': 2.8486533164978027, 'timing/data': 0.00019177095964550972, 'timing/model': 0.4586653606966138, 'learning_rate/action_model': 7.430054939488163e-05, 'learning_rate/action_query_proj': 7.430054939488163e-05, 'learning_rate/base': 1.8575137348720407e-05, 'epoch': 0.21}) +[2026-07-26 22:02:27,739][starVLA.training.train_starvla][INFO] - Step 1732, Loss: {'train/loss': 0.4272526204586029, 'train/grad_norm_pre_clip': 5.285976409912109, 'timing/data': 0.0001900182105600834, 'timing/model': 0.4590044217184186, 'learning_rate/action_model': 7.427383823814152e-05, 'learning_rate/action_query_proj': 7.427383823814152e-05, 'learning_rate/base': 1.856845955953538e-05, 'epoch': 0.21}) +[2026-07-26 22:02:33,316][starVLA.training.train_starvla][INFO] - Step 1733, Loss: {'train/loss': 0.2771416902542114, 'train/grad_norm_pre_clip': 3.6818015575408936, 'timing/data': 0.00017795292660593987, 'timing/model': 0.45802306989207864, 'learning_rate/action_model': 7.424711828804282e-05, 'learning_rate/action_query_proj': 7.424711828804282e-05, 'learning_rate/base': 1.8561779572010706e-05, 'epoch': 0.21}) +[2026-07-26 22:02:38,877][starVLA.training.train_starvla][INFO] - Step 1734, Loss: {'train/loss': 0.38361406326293945, 'train/grad_norm_pre_clip': 5.1580023765563965, 'timing/data': 0.00017936574295163155, 'timing/model': 0.45853427005931735, 'learning_rate/action_model': 7.422038955513417e-05, 'learning_rate/action_query_proj': 7.422038955513417e-05, 'learning_rate/base': 1.8555097388783542e-05, 'epoch': 0.21}) +[2026-07-26 22:02:44,436][starVLA.training.train_starvla][INFO] - Step 1735, Loss: {'train/loss': 0.20620200037956238, 'train/grad_norm_pre_clip': 3.018303394317627, 'timing/data': 0.00018301419913768768, 'timing/model': 0.45879434375092387, 'learning_rate/action_model': 7.419365204996761e-05, 'learning_rate/action_query_proj': 7.419365204996761e-05, 'learning_rate/base': 1.8548413012491902e-05, 'epoch': 0.21}) +[2026-07-26 22:02:49,980][starVLA.training.train_starvla][INFO] - Step 1736, Loss: {'train/loss': 0.31200310587882996, 'train/grad_norm_pre_clip': 2.893216609954834, 'timing/data': 0.00018076784908771515, 'timing/model': 0.45792424213141203, 'learning_rate/action_model': 7.416690578309871e-05, 'learning_rate/action_query_proj': 7.416690578309871e-05, 'learning_rate/base': 1.8541726445774677e-05, 'epoch': 0.21}) +[2026-07-26 22:02:55,573][starVLA.training.train_starvla][INFO] - Step 1737, Loss: {'train/loss': 0.25520795583724976, 'train/grad_norm_pre_clip': 2.9101216793060303, 'timing/data': 0.00018066773191094398, 'timing/model': 0.4578499519266188, 'learning_rate/action_model': 7.414015076508644e-05, 'learning_rate/action_query_proj': 7.414015076508644e-05, 'learning_rate/base': 1.853503769127161e-05, 'epoch': 0.21}) +[2026-07-26 22:03:01,195][starVLA.training.train_starvla][INFO] - Step 1738, Loss: {'train/loss': 0.3725200593471527, 'train/grad_norm_pre_clip': 3.9793384075164795, 'timing/data': 0.0001828651875257492, 'timing/model': 0.4648252110928297, 'learning_rate/action_model': 7.41133870064933e-05, 'learning_rate/action_query_proj': 7.41133870064933e-05, 'learning_rate/base': 1.8528346751623325e-05, 'epoch': 0.21}) +[2026-07-26 22:03:06,812][starVLA.training.train_starvla][INFO] - Step 1739, Loss: {'train/loss': 0.2865212857723236, 'train/grad_norm_pre_clip': 3.2971692085266113, 'timing/data': 0.00018375413492321968, 'timing/model': 0.45978997414931655, 'learning_rate/action_model': 7.408661451788518e-05, 'learning_rate/action_query_proj': 7.408661451788518e-05, 'learning_rate/base': 1.8521653629471295e-05, 'epoch': 0.21}) +[2026-07-26 22:03:12,492][starVLA.training.train_starvla][INFO] - Step 1740, Loss: {'train/loss': 0.2909202575683594, 'train/grad_norm_pre_clip': 3.290743350982666, 'timing/data': 0.00018061278387904167, 'timing/model': 0.4628965216688812, 'learning_rate/action_model': 7.405983330983143e-05, 'learning_rate/action_query_proj': 7.405983330983143e-05, 'learning_rate/base': 1.851495832745786e-05, 'epoch': 0.21}) +[2026-07-26 22:03:18,166][starVLA.training.train_starvla][INFO] - Step 1741, Loss: {'train/loss': 0.29061660170555115, 'train/grad_norm_pre_clip': 2.6607401371002197, 'timing/data': 0.00018170801922678947, 'timing/model': 0.46255091996863484, 'learning_rate/action_model': 7.403304339290484e-05, 'learning_rate/action_query_proj': 7.403304339290484e-05, 'learning_rate/base': 1.850826084822621e-05, 'epoch': 0.21}) +[2026-07-26 22:03:23,783][starVLA.training.train_starvla][INFO] - Step 1742, Loss: {'train/loss': 0.2692049443721771, 'train/grad_norm_pre_clip': 3.8024327754974365, 'timing/data': 0.00017973408102989197, 'timing/model': 0.4606159678660333, 'learning_rate/action_model': 7.400624477768167e-05, 'learning_rate/action_query_proj': 7.400624477768167e-05, 'learning_rate/base': 1.8501561194420417e-05, 'epoch': 0.21}) +[2026-07-26 22:03:29,428][starVLA.training.train_starvla][INFO] - Step 1743, Loss: {'train/loss': 0.23703834414482117, 'train/grad_norm_pre_clip': 2.5608596801757812, 'timing/data': 0.00017869379371404648, 'timing/model': 0.46276090294122696, 'learning_rate/action_model': 7.397943747474155e-05, 'learning_rate/action_query_proj': 7.397943747474155e-05, 'learning_rate/base': 1.8494859368685387e-05, 'epoch': 0.21}) +[2026-07-26 22:03:35,039][starVLA.training.train_starvla][INFO] - Step 1744, Loss: {'train/loss': 0.29726487398147583, 'train/grad_norm_pre_clip': 3.655745029449463, 'timing/data': 0.00017735594883561134, 'timing/model': 0.4617802076973021, 'learning_rate/action_model': 7.395262149466762e-05, 'learning_rate/action_query_proj': 7.395262149466762e-05, 'learning_rate/base': 1.8488155373666905e-05, 'epoch': 0.21}) +[2026-07-26 22:03:40,678][starVLA.training.train_starvla][INFO] - Step 1745, Loss: {'train/loss': 0.38381022214889526, 'train/grad_norm_pre_clip': 2.9483485221862793, 'timing/data': 0.0001704334281384945, 'timing/model': 0.4605147368274629, 'learning_rate/action_model': 7.392579684804638e-05, 'learning_rate/action_query_proj': 7.392579684804638e-05, 'learning_rate/base': 1.8481449212011594e-05, 'epoch': 0.21}) +[2026-07-26 22:03:46,294][starVLA.training.train_starvla][INFO] - Step 1746, Loss: {'train/loss': 0.20591090619564056, 'train/grad_norm_pre_clip': 3.016584634780884, 'timing/data': 0.00017847400158643723, 'timing/model': 0.4608403746969998, 'learning_rate/action_model': 7.389896354546778e-05, 'learning_rate/action_query_proj': 7.389896354546778e-05, 'learning_rate/base': 1.8474740886366945e-05, 'epoch': 0.21}) +[2026-07-26 22:03:51,881][starVLA.training.train_starvla][INFO] - Step 1747, Loss: {'train/loss': 0.40192484855651855, 'train/grad_norm_pre_clip': 3.012300491333008, 'timing/data': 0.00019007781520485878, 'timing/model': 0.46155548095703125, 'learning_rate/action_model': 7.38721215975252e-05, 'learning_rate/action_query_proj': 7.38721215975252e-05, 'learning_rate/base': 1.84680303993813e-05, 'epoch': 0.21}) +[2026-07-26 22:03:57,497][starVLA.training.train_starvla][INFO] - Step 1748, Loss: {'train/loss': 0.48210352659225464, 'train/grad_norm_pre_clip': 4.311460494995117, 'timing/data': 0.00017456570640206337, 'timing/model': 0.4635745957493782, 'learning_rate/action_model': 7.384527101481539e-05, 'learning_rate/action_query_proj': 7.384527101481539e-05, 'learning_rate/base': 1.8461317753703847e-05, 'epoch': 0.21}) +[2026-07-26 22:04:03,119][starVLA.training.train_starvla][INFO] - Step 1749, Loss: {'train/loss': 0.2611396908760071, 'train/grad_norm_pre_clip': 4.695193290710449, 'timing/data': 0.00017801066860556602, 'timing/model': 0.46210521925240755, 'learning_rate/action_model': 7.381841180793854e-05, 'learning_rate/action_query_proj': 7.381841180793854e-05, 'learning_rate/base': 1.8454602951984636e-05, 'epoch': 0.21}) +[2026-07-26 22:04:08,717][starVLA.training.train_starvla][INFO] - Step 1750, Loss: {'train/loss': 0.33742663264274597, 'train/grad_norm_pre_clip': 2.91915225982666, 'timing/data': 0.00018038786947727203, 'timing/model': 0.4605848449282348, 'learning_rate/action_model': 7.379154398749825e-05, 'learning_rate/action_query_proj': 7.379154398749825e-05, 'learning_rate/base': 1.8447885996874562e-05, 'epoch': 0.21}) +[2026-07-26 22:04:14,350][starVLA.training.train_starvla][INFO] - Step 1751, Loss: {'train/loss': 0.31046345829963684, 'train/grad_norm_pre_clip': 5.961197853088379, 'timing/data': 0.00017807399854063988, 'timing/model': 0.4615115732885897, 'learning_rate/action_model': 7.37646675641015e-05, 'learning_rate/action_query_proj': 7.37646675641015e-05, 'learning_rate/base': 1.8441166891025375e-05, 'epoch': 0.21}) +[2026-07-26 22:04:19,940][starVLA.training.train_starvla][INFO] - Step 1752, Loss: {'train/loss': 0.37717127799987793, 'train/grad_norm_pre_clip': 4.374416828155518, 'timing/data': 0.0001833043061196804, 'timing/model': 0.4634978901594877, 'learning_rate/action_model': 7.37377825483587e-05, 'learning_rate/action_query_proj': 7.37377825483587e-05, 'learning_rate/base': 1.8434445637089676e-05, 'epoch': 0.21}) +[2026-07-26 22:04:25,503][starVLA.training.train_starvla][INFO] - Step 1753, Loss: {'train/loss': 0.3728596866130829, 'train/grad_norm_pre_clip': 4.074063301086426, 'timing/data': 0.00017954129725694656, 'timing/model': 0.460196727886796, 'learning_rate/action_model': 7.371088895088359e-05, 'learning_rate/action_query_proj': 7.371088895088359e-05, 'learning_rate/base': 1.8427722237720898e-05, 'epoch': 0.21}) +[2026-07-26 22:04:31,064][starVLA.training.train_starvla][INFO] - Step 1754, Loss: {'train/loss': 0.3547295331954956, 'train/grad_norm_pre_clip': 6.526339530944824, 'timing/data': 0.00017880089581012726, 'timing/model': 0.461152883246541, 'learning_rate/action_model': 7.368398678229336e-05, 'learning_rate/action_query_proj': 7.368398678229336e-05, 'learning_rate/base': 1.842099669557334e-05, 'epoch': 0.21}) +[2026-07-26 22:04:36,638][starVLA.training.train_starvla][INFO] - Step 1755, Loss: {'train/loss': 0.318559467792511, 'train/grad_norm_pre_clip': 4.363874435424805, 'timing/data': 0.0001783878542482853, 'timing/model': 0.4619449069723487, 'learning_rate/action_model': 7.365707605320857e-05, 'learning_rate/action_query_proj': 7.365707605320857e-05, 'learning_rate/base': 1.8414269013302144e-05, 'epoch': 0.21}) +[2026-07-26 22:04:42,215][starVLA.training.train_starvla][INFO] - Step 1756, Loss: {'train/loss': 0.33007296919822693, 'train/grad_norm_pre_clip': 3.614008903503418, 'timing/data': 0.00017412472516298294, 'timing/model': 0.46383386105298996, 'learning_rate/action_model': 7.363015677425312e-05, 'learning_rate/action_query_proj': 7.363015677425312e-05, 'learning_rate/base': 1.840753919356328e-05, 'epoch': 0.21}) +[2026-07-26 22:04:47,787][starVLA.training.train_starvla][INFO] - Step 1757, Loss: {'train/loss': 0.3074548542499542, 'train/grad_norm_pre_clip': 3.7722666263580322, 'timing/data': 0.00017848098650574684, 'timing/model': 0.46425224374979734, 'learning_rate/action_model': 7.360322895605434e-05, 'learning_rate/action_query_proj': 7.360322895605434e-05, 'learning_rate/base': 1.8400807239013586e-05, 'epoch': 0.21}) +[2026-07-26 22:04:53,353][starVLA.training.train_starvla][INFO] - Step 1758, Loss: {'train/loss': 0.3167453408241272, 'train/grad_norm_pre_clip': 2.497270107269287, 'timing/data': 0.0001833941787481308, 'timing/model': 0.4616130399517715, 'learning_rate/action_model': 7.357629260924291e-05, 'learning_rate/action_query_proj': 7.357629260924291e-05, 'learning_rate/base': 1.8394073152310727e-05, 'epoch': 0.21}) +[2026-07-26 22:04:58,924][starVLA.training.train_starvla][INFO] - Step 1759, Loss: {'train/loss': 0.2985840141773224, 'train/grad_norm_pre_clip': 3.308553457260132, 'timing/data': 0.00017873523756861687, 'timing/model': 0.46164021408185363, 'learning_rate/action_model': 7.354934774445285e-05, 'learning_rate/action_query_proj': 7.354934774445285e-05, 'learning_rate/base': 1.838733693611321e-05, 'epoch': 0.21}) +[2026-07-26 22:05:04,491][starVLA.training.train_starvla][INFO] - Step 1760, Loss: {'train/loss': 0.29921501874923706, 'train/grad_norm_pre_clip': 3.2283012866973877, 'timing/data': 0.00018362421542406082, 'timing/model': 0.4601866723969579, 'learning_rate/action_model': 7.352239437232156e-05, 'learning_rate/action_query_proj': 7.352239437232156e-05, 'learning_rate/base': 1.838059859308039e-05, 'epoch': 0.21}) +[2026-07-26 22:05:10,061][starVLA.training.train_starvla][INFO] - Step 1761, Loss: {'train/loss': 0.24814721941947937, 'train/grad_norm_pre_clip': 4.323275089263916, 'timing/data': 0.00017891498282551765, 'timing/model': 0.46032913215458393, 'learning_rate/action_model': 7.349543250348984e-05, 'learning_rate/action_query_proj': 7.349543250348984e-05, 'learning_rate/base': 1.837385812587246e-05, 'epoch': 0.21}) +[2026-07-26 22:05:15,618][starVLA.training.train_starvla][INFO] - Step 1762, Loss: {'train/loss': 0.25262749195098877, 'train/grad_norm_pre_clip': 3.1724536418914795, 'timing/data': 0.00017059128731489182, 'timing/model': 0.4602208803407848, 'learning_rate/action_model': 7.346846214860179e-05, 'learning_rate/action_query_proj': 7.346846214860179e-05, 'learning_rate/base': 1.8367115537150446e-05, 'epoch': 0.21}) +[2026-07-26 22:05:21,189][starVLA.training.train_starvla][INFO] - Step 1763, Loss: {'train/loss': 0.369088739156723, 'train/grad_norm_pre_clip': 3.7221381664276123, 'timing/data': 0.00024506310001015663, 'timing/model': 0.4616306400857866, 'learning_rate/action_model': 7.344148331830484e-05, 'learning_rate/action_query_proj': 7.344148331830484e-05, 'learning_rate/base': 1.836037082957621e-05, 'epoch': 0.21}) +[2026-07-26 22:05:26,772][starVLA.training.train_starvla][INFO] - Step 1764, Loss: {'train/loss': 0.20484352111816406, 'train/grad_norm_pre_clip': 3.2395527362823486, 'timing/data': 0.00017515802755951881, 'timing/model': 0.46152623277157545, 'learning_rate/action_model': 7.341449602324988e-05, 'learning_rate/action_query_proj': 7.341449602324988e-05, 'learning_rate/base': 1.835362400581247e-05, 'epoch': 0.21}) +[2026-07-26 22:05:32,357][starVLA.training.train_starvla][INFO] - Step 1765, Loss: {'train/loss': 0.36985284090042114, 'train/grad_norm_pre_clip': 3.4234986305236816, 'timing/data': 0.00017383601516485214, 'timing/model': 0.46038419008255005, 'learning_rate/action_model': 7.338750027409104e-05, 'learning_rate/action_query_proj': 7.338750027409104e-05, 'learning_rate/base': 1.834687506852276e-05, 'epoch': 0.21}) +[2026-07-26 22:05:37,947][starVLA.training.train_starvla][INFO] - Step 1766, Loss: {'train/loss': 0.20173443853855133, 'train/grad_norm_pre_clip': 2.2188568115234375, 'timing/data': 0.00017886236310005188, 'timing/model': 0.46134333312511444, 'learning_rate/action_model': 7.336049608148577e-05, 'learning_rate/action_query_proj': 7.336049608148577e-05, 'learning_rate/base': 1.8340124020371444e-05, 'epoch': 0.21}) +[2026-07-26 22:05:43,566][starVLA.training.train_starvla][INFO] - Step 1767, Loss: {'train/loss': 0.25992071628570557, 'train/grad_norm_pre_clip': 4.754784107208252, 'timing/data': 0.0001788209192454815, 'timing/model': 0.4627536120824516, 'learning_rate/action_model': 7.333348345609497e-05, 'learning_rate/action_query_proj': 7.333348345609497e-05, 'learning_rate/base': 1.833337086402374e-05, 'epoch': 0.21}) +[2026-07-26 22:05:49,188][starVLA.training.train_starvla][INFO] - Step 1768, Loss: {'train/loss': 0.3385602831840515, 'train/grad_norm_pre_clip': 3.6695303916931152, 'timing/data': 0.00017936574295163155, 'timing/model': 0.4650241690687835, 'learning_rate/action_model': 7.330646240858272e-05, 'learning_rate/action_query_proj': 7.330646240858272e-05, 'learning_rate/base': 1.832661560214568e-05, 'epoch': 0.21}) +[2026-07-26 22:05:54,779][starVLA.training.train_starvla][INFO] - Step 1769, Loss: {'train/loss': 0.2913339138031006, 'train/grad_norm_pre_clip': 3.2226767539978027, 'timing/data': 0.0001922929659485817, 'timing/model': 0.46274242363870144, 'learning_rate/action_model': 7.327943294961656e-05, 'learning_rate/action_query_proj': 7.327943294961656e-05, 'learning_rate/base': 1.831985823740414e-05, 'epoch': 0.21}) +[2026-07-26 22:06:00,347][starVLA.training.train_starvla][INFO] - Step 1770, Loss: {'train/loss': 0.32273033261299133, 'train/grad_norm_pre_clip': 3.821836471557617, 'timing/data': 0.00019236095249652863, 'timing/model': 0.46145109087228775, 'learning_rate/action_model': 7.325239508986729e-05, 'learning_rate/action_query_proj': 7.325239508986729e-05, 'learning_rate/base': 1.831309877246682e-05, 'epoch': 0.21}) +[2026-07-26 22:06:05,897][starVLA.training.train_starvla][INFO] - Step 1771, Loss: {'train/loss': 0.27562081813812256, 'train/grad_norm_pre_clip': 3.8301117420196533, 'timing/data': 0.00018977094441652298, 'timing/model': 0.45980673329904675, 'learning_rate/action_model': 7.3225348840009e-05, 'learning_rate/action_query_proj': 7.3225348840009e-05, 'learning_rate/base': 1.830633721000225e-05, 'epoch': 0.21}) +[2026-07-26 22:06:11,463][starVLA.training.train_starvla][INFO] - Step 1772, Loss: {'train/loss': 0.3307400941848755, 'train/grad_norm_pre_clip': 3.5898261070251465, 'timing/data': 0.00018254481256008148, 'timing/model': 0.46456643706187606, 'learning_rate/action_model': 7.319829421071911e-05, 'learning_rate/action_query_proj': 7.319829421071911e-05, 'learning_rate/base': 1.829957355267978e-05, 'epoch': 0.21}) +[2026-07-26 22:06:17,034][starVLA.training.train_starvla][INFO] - Step 1773, Loss: {'train/loss': 0.3432629406452179, 'train/grad_norm_pre_clip': 3.338848114013672, 'timing/data': 0.0001750006340444088, 'timing/model': 0.4606387889944017, 'learning_rate/action_model': 7.317123121267839e-05, 'learning_rate/action_query_proj': 7.317123121267839e-05, 'learning_rate/base': 1.8292807803169598e-05, 'epoch': 0.22}) +[2026-07-26 22:06:22,592][starVLA.training.train_starvla][INFO] - Step 1774, Loss: {'train/loss': 0.4103828966617584, 'train/grad_norm_pre_clip': 5.185588359832764, 'timing/data': 0.00018147379159927368, 'timing/model': 0.46262036729604006, 'learning_rate/action_model': 7.31441598565709e-05, 'learning_rate/action_query_proj': 7.31441598565709e-05, 'learning_rate/base': 1.8286039964142724e-05, 'epoch': 0.22}) +[2026-07-26 22:06:28,335][starVLA.training.train_starvla][INFO] - Step 1775, Loss: {'train/loss': 0.27909064292907715, 'train/grad_norm_pre_clip': 3.66087007522583, 'timing/data': 0.00018389616161584854, 'timing/model': 0.46429059095680714, 'learning_rate/action_model': 7.311708015308394e-05, 'learning_rate/action_query_proj': 7.311708015308394e-05, 'learning_rate/base': 1.8279270038270986e-05, 'epoch': 0.22}) +[2026-07-26 22:06:33,901][starVLA.training.train_starvla][INFO] - Step 1776, Loss: {'train/loss': 0.2171705812215805, 'train/grad_norm_pre_clip': 2.5307631492614746, 'timing/data': 0.00018171686679124832, 'timing/model': 0.46301205828785896, 'learning_rate/action_model': 7.308999211290816e-05, 'learning_rate/action_query_proj': 7.308999211290816e-05, 'learning_rate/base': 1.827249802822704e-05, 'epoch': 0.22}) +[2026-07-26 22:06:39,470][starVLA.training.train_starvla][INFO] - Step 1777, Loss: {'train/loss': 0.31689345836639404, 'train/grad_norm_pre_clip': 2.852571725845337, 'timing/data': 0.00018244097009301186, 'timing/model': 0.4623785116709769, 'learning_rate/action_model': 7.30628957467375e-05, 'learning_rate/action_query_proj': 7.30628957467375e-05, 'learning_rate/base': 1.8265723936684375e-05, 'epoch': 0.22}) +[2026-07-26 22:06:45,059][starVLA.training.train_starvla][INFO] - Step 1778, Loss: {'train/loss': 0.1511438488960266, 'train/grad_norm_pre_clip': 2.682110071182251, 'timing/data': 0.0001798570156097412, 'timing/model': 0.4596210429444909, 'learning_rate/action_model': 7.303579106526917e-05, 'learning_rate/action_query_proj': 7.303579106526917e-05, 'learning_rate/base': 1.825894776631729e-05, 'epoch': 0.22}) +[2026-07-26 22:06:50,637][starVLA.training.train_starvla][INFO] - Step 1779, Loss: {'train/loss': 0.26959049701690674, 'train/grad_norm_pre_clip': 2.7550697326660156, 'timing/data': 0.00017809681594371796, 'timing/model': 0.4638382699340582, 'learning_rate/action_model': 7.300867807920368e-05, 'learning_rate/action_query_proj': 7.300867807920368e-05, 'learning_rate/base': 1.825216951980092e-05, 'epoch': 0.22}) +[2026-07-26 22:06:56,202][starVLA.training.train_starvla][INFO] - Step 1780, Loss: {'train/loss': 0.29687777161598206, 'train/grad_norm_pre_clip': 3.841156244277954, 'timing/data': 0.00017700577154755592, 'timing/model': 0.46165896905586123, 'learning_rate/action_model': 7.298155679924478e-05, 'learning_rate/action_query_proj': 7.298155679924478e-05, 'learning_rate/base': 1.8245389199811196e-05, 'epoch': 0.22}) +[2026-07-26 22:07:01,742][starVLA.training.train_starvla][INFO] - Step 1781, Loss: {'train/loss': 0.3388373553752899, 'train/grad_norm_pre_clip': 3.4998269081115723, 'timing/data': 0.0001774430274963379, 'timing/model': 0.4591407780535519, 'learning_rate/action_model': 7.295442723609956e-05, 'learning_rate/action_query_proj': 7.295442723609956e-05, 'learning_rate/base': 1.823860680902489e-05, 'epoch': 0.22}) +[2026-07-26 22:07:07,478][starVLA.training.train_starvla][INFO] - Step 1782, Loss: {'train/loss': 0.33911892771720886, 'train/grad_norm_pre_clip': 3.347933053970337, 'timing/data': 0.0001790742389857769, 'timing/model': 0.4593175589106977, 'learning_rate/action_model': 7.292728940047831e-05, 'learning_rate/action_query_proj': 7.292728940047831e-05, 'learning_rate/base': 1.823182235011958e-05, 'epoch': 0.22}) +[2026-07-26 22:07:13,009][starVLA.training.train_starvla][INFO] - Step 1783, Loss: {'train/loss': 0.3630603849887848, 'train/grad_norm_pre_clip': 4.960601806640625, 'timing/data': 0.00017847632989287376, 'timing/model': 0.45828670216724277, 'learning_rate/action_model': 7.290014330309462e-05, 'learning_rate/action_query_proj': 7.290014330309462e-05, 'learning_rate/base': 1.8225035825773655e-05, 'epoch': 0.22}) +[2026-07-26 22:07:18,524][starVLA.training.train_starvla][INFO] - Step 1784, Loss: {'train/loss': 0.456409215927124, 'train/grad_norm_pre_clip': 4.249692916870117, 'timing/data': 0.00017990637570619583, 'timing/model': 0.45802193507552147, 'learning_rate/action_model': 7.287298895466535e-05, 'learning_rate/action_query_proj': 7.287298895466535e-05, 'learning_rate/base': 1.821824723866634e-05, 'epoch': 0.22}) +[2026-07-26 22:07:24,065][starVLA.training.train_starvla][INFO] - Step 1785, Loss: {'train/loss': 0.19349391758441925, 'train/grad_norm_pre_clip': 3.0311644077301025, 'timing/data': 0.00017800182104110718, 'timing/model': 0.45822747610509396, 'learning_rate/action_model': 7.284582636591063e-05, 'learning_rate/action_query_proj': 7.284582636591063e-05, 'learning_rate/base': 1.821145659147766e-05, 'epoch': 0.22}) +[2026-07-26 22:07:29,600][starVLA.training.train_starvla][INFO] - Step 1786, Loss: {'train/loss': 0.18469493091106415, 'train/grad_norm_pre_clip': 2.44113826751709, 'timing/data': 0.0001795012503862381, 'timing/model': 0.4589864909648895, 'learning_rate/action_model': 7.281865554755377e-05, 'learning_rate/action_query_proj': 7.281865554755377e-05, 'learning_rate/base': 1.8204663886888444e-05, 'epoch': 0.22}) +[2026-07-26 22:07:35,131][starVLA.training.train_starvla][INFO] - Step 1787, Loss: {'train/loss': 0.2107974737882614, 'train/grad_norm_pre_clip': 2.7947909832000732, 'timing/data': 0.0001763598993420601, 'timing/model': 0.4585237498395145, 'learning_rate/action_model': 7.279147651032141e-05, 'learning_rate/action_query_proj': 7.279147651032141e-05, 'learning_rate/base': 1.8197869127580352e-05, 'epoch': 0.22}) +[2026-07-26 22:07:40,647][starVLA.training.train_starvla][INFO] - Step 1788, Loss: {'train/loss': 0.2804087698459625, 'train/grad_norm_pre_clip': 2.702643394470215, 'timing/data': 0.00017753476276993752, 'timing/model': 0.4572040089406073, 'learning_rate/action_model': 7.27642892649434e-05, 'learning_rate/action_query_proj': 7.27642892649434e-05, 'learning_rate/base': 1.819107231623585e-05, 'epoch': 0.22}) +[2026-07-26 22:07:46,169][starVLA.training.train_starvla][INFO] - Step 1789, Loss: {'train/loss': 0.34864291548728943, 'train/grad_norm_pre_clip': 3.778597354888916, 'timing/data': 0.00017662672325968742, 'timing/model': 0.45789171988144517, 'learning_rate/action_model': 7.273709382215284e-05, 'learning_rate/action_query_proj': 7.273709382215284e-05, 'learning_rate/base': 1.818427345553821e-05, 'epoch': 0.22}) +[2026-07-26 22:07:51,697][starVLA.training.train_starvla][INFO] - Step 1790, Loss: {'train/loss': 0.33116117119789124, 'train/grad_norm_pre_clip': 2.9837517738342285, 'timing/data': 0.00018019694834947586, 'timing/model': 0.45701791997998953, 'learning_rate/action_model': 7.270989019268604e-05, 'learning_rate/action_query_proj': 7.270989019268604e-05, 'learning_rate/base': 1.817747254817151e-05, 'epoch': 0.22}) +[2026-07-26 22:07:57,223][starVLA.training.train_starvla][INFO] - Step 1791, Loss: {'train/loss': 0.36769723892211914, 'train/grad_norm_pre_clip': 3.9919095039367676, 'timing/data': 0.0001781350001692772, 'timing/model': 0.4573469259776175, 'learning_rate/action_model': 7.268267838728257e-05, 'learning_rate/action_query_proj': 7.268267838728257e-05, 'learning_rate/base': 1.8170669596820642e-05, 'epoch': 0.22}) +[2026-07-26 22:08:03,014][starVLA.training.train_starvla][INFO] - Step 1792, Loss: {'train/loss': 0.3720855414867401, 'train/grad_norm_pre_clip': 4.659047603607178, 'timing/data': 0.00017342297360301018, 'timing/model': 0.4583402299322188, 'learning_rate/action_model': 7.265545841668523e-05, 'learning_rate/action_query_proj': 7.265545841668523e-05, 'learning_rate/base': 1.8163864604171307e-05, 'epoch': 0.22}) +[2026-07-26 22:08:08,536][starVLA.training.train_starvla][INFO] - Step 1793, Loss: {'train/loss': 0.24342259764671326, 'train/grad_norm_pre_clip': 2.480752944946289, 'timing/data': 0.0001766500063240528, 'timing/model': 0.45752041693776846, 'learning_rate/action_model': 7.262823029164003e-05, 'learning_rate/action_query_proj': 7.262823029164003e-05, 'learning_rate/base': 1.8157057572910007e-05, 'epoch': 0.22}) +[2026-07-26 22:08:14,070][starVLA.training.train_starvla][INFO] - Step 1794, Loss: {'train/loss': 0.2855866849422455, 'train/grad_norm_pre_clip': 4.5680317878723145, 'timing/data': 0.00017762603238224983, 'timing/model': 0.45708519127219915, 'learning_rate/action_model': 7.260099402289618e-05, 'learning_rate/action_query_proj': 7.260099402289618e-05, 'learning_rate/base': 1.8150248505724046e-05, 'epoch': 0.22}) +[2026-07-26 22:08:19,606][starVLA.training.train_starvla][INFO] - Step 1795, Loss: {'train/loss': 0.3937709629535675, 'train/grad_norm_pre_clip': 5.174994468688965, 'timing/data': 0.00018558278679847717, 'timing/model': 0.4574862951412797, 'learning_rate/action_model': 7.257374962120617e-05, 'learning_rate/action_query_proj': 7.257374962120617e-05, 'learning_rate/base': 1.8143437405301543e-05, 'epoch': 0.22}) +[2026-07-26 22:08:25,133][starVLA.training.train_starvla][INFO] - Step 1796, Loss: {'train/loss': 0.34586894512176514, 'train/grad_norm_pre_clip': 3.80531644821167, 'timing/data': 0.00018078181892633438, 'timing/model': 0.45877430867403746, 'learning_rate/action_model': 7.25464970973256e-05, 'learning_rate/action_query_proj': 7.25464970973256e-05, 'learning_rate/base': 1.81366242743314e-05, 'epoch': 0.22}) +[2026-07-26 22:08:30,666][starVLA.training.train_starvla][INFO] - Step 1797, Loss: {'train/loss': 0.30631715059280396, 'train/grad_norm_pre_clip': 4.232253551483154, 'timing/data': 0.00017447303980588913, 'timing/model': 0.45749474316835403, 'learning_rate/action_model': 7.251923646201341e-05, 'learning_rate/action_query_proj': 7.251923646201341e-05, 'learning_rate/base': 1.8129809115503352e-05, 'epoch': 0.22}) +[2026-07-26 22:08:36,186][starVLA.training.train_starvla][INFO] - Step 1798, Loss: {'train/loss': 0.3116895854473114, 'train/grad_norm_pre_clip': 3.7615292072296143, 'timing/data': 0.00016933400183916092, 'timing/model': 0.4586706981062889, 'learning_rate/action_model': 7.249196772603161e-05, 'learning_rate/action_query_proj': 7.249196772603161e-05, 'learning_rate/base': 1.8122991931507903e-05, 'epoch': 0.22}) +[2026-07-26 22:08:41,726][starVLA.training.train_starvla][INFO] - Step 1799, Loss: {'train/loss': 0.37807154655456543, 'train/grad_norm_pre_clip': 3.7546393871307373, 'timing/data': 0.00017513195052742958, 'timing/model': 0.4580742670223117, 'learning_rate/action_model': 7.246469090014549e-05, 'learning_rate/action_query_proj': 7.246469090014549e-05, 'learning_rate/base': 1.8116172725036372e-05, 'epoch': 0.22}) +[2026-07-26 22:08:47,258][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 1800 +[2026-07-26 22:08:47,258][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 1800 +[2026-07-26 22:08:47,259][starVLA.training.train_starvla][INFO] - Step 1800, Loss: {'train/loss': 0.26208534836769104, 'train/grad_norm_pre_clip': 3.9934279918670654, 'timing/data': 0.00017295917496085167, 'timing/model': 0.45787398191168904, 'learning_rate/action_model': 7.243740599512349e-05, 'learning_rate/action_query_proj': 7.243740599512349e-05, 'learning_rate/base': 1.8109351498780873e-05, 'epoch': 0.22}) +[2026-07-26 22:08:52,776][starVLA.training.train_starvla][INFO] - Step 1801, Loss: {'train/loss': 0.14948807656764984, 'train/grad_norm_pre_clip': 3.4259674549102783, 'timing/data': 0.00017141876742243767, 'timing/model': 0.45803267508745193, 'learning_rate/action_model': 7.241011302173728e-05, 'learning_rate/action_query_proj': 7.241011302173728e-05, 'learning_rate/base': 1.810252825543432e-05, 'epoch': 0.22}) +[2026-07-26 22:08:58,284][starVLA.training.train_starvla][INFO] - Step 1802, Loss: {'train/loss': 0.32501569390296936, 'train/grad_norm_pre_clip': 5.018476963043213, 'timing/data': 0.00018008099868893623, 'timing/model': 0.4580356921069324, 'learning_rate/action_model': 7.238281199076167e-05, 'learning_rate/action_query_proj': 7.238281199076167e-05, 'learning_rate/base': 1.8095702997690417e-05, 'epoch': 0.22}) +[2026-07-26 22:09:03,782][starVLA.training.train_starvla][INFO] - Step 1803, Loss: {'train/loss': 0.30208975076675415, 'train/grad_norm_pre_clip': 4.959760665893555, 'timing/data': 0.00018059136345982552, 'timing/model': 0.45849423576146364, 'learning_rate/action_model': 7.235550291297469e-05, 'learning_rate/action_query_proj': 7.235550291297469e-05, 'learning_rate/base': 1.808887572824367e-05, 'epoch': 0.22}) +[2026-07-26 22:09:09,283][starVLA.training.train_starvla][INFO] - Step 1804, Loss: {'train/loss': 0.3205021023750305, 'train/grad_norm_pre_clip': 4.3503737449646, 'timing/data': 0.0001770108938217163, 'timing/model': 0.45795176085084677, 'learning_rate/action_model': 7.232818579915753e-05, 'learning_rate/action_query_proj': 7.232818579915753e-05, 'learning_rate/base': 1.8082046449789382e-05, 'epoch': 0.22}) +[2026-07-26 22:09:14,784][starVLA.training.train_starvla][INFO] - Step 1805, Loss: {'train/loss': 0.2543044984340668, 'train/grad_norm_pre_clip': 3.3094334602355957, 'timing/data': 0.0001770583912730217, 'timing/model': 0.45750623382627964, 'learning_rate/action_model': 7.230086066009455e-05, 'learning_rate/action_query_proj': 7.230086066009455e-05, 'learning_rate/base': 1.8075215165023638e-05, 'epoch': 0.22}) +[2026-07-26 22:09:20,303][starVLA.training.train_starvla][INFO] - Step 1806, Loss: {'train/loss': 0.33287757635116577, 'train/grad_norm_pre_clip': 4.134039878845215, 'timing/data': 0.00017280178144574165, 'timing/model': 0.45895888190716505, 'learning_rate/action_model': 7.22735275065733e-05, 'learning_rate/action_query_proj': 7.22735275065733e-05, 'learning_rate/base': 1.8068381876643324e-05, 'epoch': 0.22}) +[2026-07-26 22:09:25,795][starVLA.training.train_starvla][INFO] - Step 1807, Loss: {'train/loss': 0.2588188648223877, 'train/grad_norm_pre_clip': 3.757550001144409, 'timing/data': 0.00017485488206148148, 'timing/model': 0.45786048797890544, 'learning_rate/action_model': 7.224618634938446e-05, 'learning_rate/action_query_proj': 7.224618634938446e-05, 'learning_rate/base': 1.8061546587346116e-05, 'epoch': 0.22}) +[2026-07-26 22:09:31,286][starVLA.training.train_starvla][INFO] - Step 1808, Loss: {'train/loss': 0.408249169588089, 'train/grad_norm_pre_clip': 5.3756232261657715, 'timing/data': 0.00017609400674700737, 'timing/model': 0.45844673505052924, 'learning_rate/action_model': 7.221883719932189e-05, 'learning_rate/action_query_proj': 7.221883719932189e-05, 'learning_rate/base': 1.8054709299830473e-05, 'epoch': 0.22}) +[2026-07-26 22:09:36,768][starVLA.training.train_starvla][INFO] - Step 1809, Loss: {'train/loss': 0.319148451089859, 'train/grad_norm_pre_clip': 3.7034428119659424, 'timing/data': 0.0001758430153131485, 'timing/model': 0.4572622589766979, 'learning_rate/action_model': 7.219148006718257e-05, 'learning_rate/action_query_proj': 7.219148006718257e-05, 'learning_rate/base': 1.8047870016795642e-05, 'epoch': 0.22}) +[2026-07-26 22:09:42,252][starVLA.training.train_starvla][INFO] - Step 1810, Loss: {'train/loss': 0.3758891224861145, 'train/grad_norm_pre_clip': 5.251133441925049, 'timing/data': 0.0001726178452372551, 'timing/model': 0.4579734946601093, 'learning_rate/action_model': 7.216411496376672e-05, 'learning_rate/action_query_proj': 7.216411496376672e-05, 'learning_rate/base': 1.804102874094168e-05, 'epoch': 0.22}) +[2026-07-26 22:09:47,745][starVLA.training.train_starvla][INFO] - Step 1811, Loss: {'train/loss': 0.34045645594596863, 'train/grad_norm_pre_clip': 6.771354675292969, 'timing/data': 0.000173996202647686, 'timing/model': 0.4583704019896686, 'learning_rate/action_model': 7.21367418998776e-05, 'learning_rate/action_query_proj': 7.21367418998776e-05, 'learning_rate/base': 1.80341854749694e-05, 'epoch': 0.22}) +[2026-07-26 22:09:53,415][starVLA.training.train_starvla][INFO] - Step 1812, Loss: {'train/loss': 0.3472091853618622, 'train/grad_norm_pre_clip': 2.4973745346069336, 'timing/data': 0.000169247854501009, 'timing/model': 0.4578921729698777, 'learning_rate/action_model': 7.210936088632169e-05, 'learning_rate/action_query_proj': 7.210936088632169e-05, 'learning_rate/base': 1.8027340221580423e-05, 'epoch': 0.22}) +[2026-07-26 22:09:58,890][starVLA.training.train_starvla][INFO] - Step 1813, Loss: {'train/loss': 0.28202328085899353, 'train/grad_norm_pre_clip': 2.87981915473938, 'timing/data': 0.00017077289521694183, 'timing/model': 0.4574678470380604, 'learning_rate/action_model': 7.208197193390858e-05, 'learning_rate/action_query_proj': 7.208197193390858e-05, 'learning_rate/base': 1.8020492983477144e-05, 'epoch': 0.22}) +[2026-07-26 22:10:04,380][starVLA.training.train_starvla][INFO] - Step 1814, Loss: {'train/loss': 0.31389254331588745, 'train/grad_norm_pre_clip': 4.589589595794678, 'timing/data': 0.00017578387632966042, 'timing/model': 0.45831936364993453, 'learning_rate/action_model': 7.205457505345097e-05, 'learning_rate/action_query_proj': 7.205457505345097e-05, 'learning_rate/base': 1.8013643763362742e-05, 'epoch': 0.22}) +[2026-07-26 22:10:09,883][starVLA.training.train_starvla][INFO] - Step 1815, Loss: {'train/loss': 0.2637028694152832, 'train/grad_norm_pre_clip': 3.4637153148651123, 'timing/data': 0.00017453311011195183, 'timing/model': 0.4575663669966161, 'learning_rate/action_model': 7.202717025576475e-05, 'learning_rate/action_query_proj': 7.202717025576475e-05, 'learning_rate/base': 1.8006792563941187e-05, 'epoch': 0.22}) +[2026-07-26 22:10:15,390][starVLA.training.train_starvla][INFO] - Step 1816, Loss: {'train/loss': 0.24103713035583496, 'train/grad_norm_pre_clip': 3.320671319961548, 'timing/data': 0.00017470819875597954, 'timing/model': 0.45903706876561046, 'learning_rate/action_model': 7.199975755166887e-05, 'learning_rate/action_query_proj': 7.199975755166887e-05, 'learning_rate/base': 1.7999939387917217e-05, 'epoch': 0.22}) +[2026-07-26 22:10:20,893][starVLA.training.train_starvla][INFO] - Step 1817, Loss: {'train/loss': 0.3566308319568634, 'train/grad_norm_pre_clip': 6.120192050933838, 'timing/data': 0.0001776297576725483, 'timing/model': 0.4582423600368202, 'learning_rate/action_model': 7.197233695198545e-05, 'learning_rate/action_query_proj': 7.197233695198545e-05, 'learning_rate/base': 1.799308423799636e-05, 'epoch': 0.22}) +[2026-07-26 22:10:26,400][starVLA.training.train_starvla][INFO] - Step 1818, Loss: {'train/loss': 0.27081039547920227, 'train/grad_norm_pre_clip': 3.7927441596984863, 'timing/data': 0.0001748749054968357, 'timing/model': 0.4587665549479425, 'learning_rate/action_model': 7.19449084675397e-05, 'learning_rate/action_query_proj': 7.19449084675397e-05, 'learning_rate/base': 1.7986227116884924e-05, 'epoch': 0.22}) +[2026-07-26 22:10:31,906][starVLA.training.train_starvla][INFO] - Step 1819, Loss: {'train/loss': 0.39607036113739014, 'train/grad_norm_pre_clip': 6.533316612243652, 'timing/data': 0.000172480009496212, 'timing/model': 0.4565378222614527, 'learning_rate/action_model': 7.191747210915995e-05, 'learning_rate/action_query_proj': 7.191747210915995e-05, 'learning_rate/base': 1.7979368027289987e-05, 'epoch': 0.22}) +[2026-07-26 22:10:37,421][starVLA.training.train_starvla][INFO] - Step 1820, Loss: {'train/loss': 0.34674587845802307, 'train/grad_norm_pre_clip': 3.5339667797088623, 'timing/data': 0.0001758611761033535, 'timing/model': 0.4595961677841842, 'learning_rate/action_model': 7.189002788767765e-05, 'learning_rate/action_query_proj': 7.189002788767765e-05, 'learning_rate/base': 1.797250697191941e-05, 'epoch': 0.22}) +[2026-07-26 22:10:42,962][starVLA.training.train_starvla][INFO] - Step 1821, Loss: {'train/loss': 0.33598411083221436, 'train/grad_norm_pre_clip': 4.518271446228027, 'timing/data': 0.00017563113942742348, 'timing/model': 0.4568708036094904, 'learning_rate/action_model': 7.186257581392733e-05, 'learning_rate/action_query_proj': 7.186257581392733e-05, 'learning_rate/base': 1.796564395348183e-05, 'epoch': 0.22}) +[2026-07-26 22:10:48,497][starVLA.training.train_starvla][INFO] - Step 1822, Loss: {'train/loss': 0.29415246844291687, 'train/grad_norm_pre_clip': 3.5238821506500244, 'timing/data': 0.0001756027340888977, 'timing/model': 0.4582654102705419, 'learning_rate/action_model': 7.183511589874665e-05, 'learning_rate/action_query_proj': 7.183511589874665e-05, 'learning_rate/base': 1.7958778974686662e-05, 'epoch': 0.22}) +[2026-07-26 22:10:54,029][starVLA.training.train_starvla][INFO] - Step 1823, Loss: {'train/loss': 0.3276268243789673, 'train/grad_norm_pre_clip': 6.103243827819824, 'timing/data': 0.00017263926565647125, 'timing/model': 0.45853334618732333, 'learning_rate/action_model': 7.180764815297633e-05, 'learning_rate/action_query_proj': 7.180764815297633e-05, 'learning_rate/base': 1.7951912038244083e-05, 'epoch': 0.22}) +[2026-07-26 22:10:59,559][starVLA.training.train_starvla][INFO] - Step 1824, Loss: {'train/loss': 0.28016015887260437, 'train/grad_norm_pre_clip': 3.623016119003296, 'timing/data': 0.00017644977197051048, 'timing/model': 0.4583143126219511, 'learning_rate/action_model': 7.178017258746021e-05, 'learning_rate/action_query_proj': 7.178017258746021e-05, 'learning_rate/base': 1.7945043146865053e-05, 'epoch': 0.22}) +[2026-07-26 22:11:05,088][starVLA.training.train_starvla][INFO] - Step 1825, Loss: {'train/loss': 0.49418485164642334, 'train/grad_norm_pre_clip': 5.572820663452148, 'timing/data': 0.0001760600134730339, 'timing/model': 0.45818080101162195, 'learning_rate/action_model': 7.175268921304524e-05, 'learning_rate/action_query_proj': 7.175268921304524e-05, 'learning_rate/base': 1.793817230326131e-05, 'epoch': 0.22}) +[2026-07-26 22:11:10,601][starVLA.training.train_starvla][INFO] - Step 1826, Loss: {'train/loss': 0.34256303310394287, 'train/grad_norm_pre_clip': 5.49285888671875, 'timing/data': 0.00018271198496222496, 'timing/model': 0.45679768826812506, 'learning_rate/action_model': 7.172519804058135e-05, 'learning_rate/action_query_proj': 7.172519804058135e-05, 'learning_rate/base': 1.7931299510145338e-05, 'epoch': 0.22}) +[2026-07-26 22:11:16,115][starVLA.training.train_starvla][INFO] - Step 1827, Loss: {'train/loss': 0.3032870888710022, 'train/grad_norm_pre_clip': 3.4611899852752686, 'timing/data': 0.00017399294301867485, 'timing/model': 0.45788003923371434, 'learning_rate/action_model': 7.169769908092169e-05, 'learning_rate/action_query_proj': 7.169769908092169e-05, 'learning_rate/base': 1.7924424770230423e-05, 'epoch': 0.22}) +[2026-07-26 22:11:21,621][starVLA.training.train_starvla][INFO] - Step 1828, Loss: {'train/loss': 0.2386595904827118, 'train/grad_norm_pre_clip': 3.1991875171661377, 'timing/data': 0.0001767207868397236, 'timing/model': 0.4574101776815951, 'learning_rate/action_model': 7.167019234492238e-05, 'learning_rate/action_query_proj': 7.167019234492238e-05, 'learning_rate/base': 1.7917548086230594e-05, 'epoch': 0.22}) +[2026-07-26 22:11:27,131][starVLA.training.train_starvla][INFO] - Step 1829, Loss: {'train/loss': 0.28837984800338745, 'train/grad_norm_pre_clip': 4.068442344665527, 'timing/data': 0.00016908487305045128, 'timing/model': 0.4573183008469641, 'learning_rate/action_model': 7.164267784344263e-05, 'learning_rate/action_query_proj': 7.164267784344263e-05, 'learning_rate/base': 1.791066946086066e-05, 'epoch': 0.22}) +[2026-07-26 22:11:32,640][starVLA.training.train_starvla][INFO] - Step 1830, Loss: {'train/loss': 0.18307292461395264, 'train/grad_norm_pre_clip': 3.122159481048584, 'timing/data': 0.00017463602125644684, 'timing/model': 0.4568059057928622, 'learning_rate/action_model': 7.161515558734476e-05, 'learning_rate/action_query_proj': 7.161515558734476e-05, 'learning_rate/base': 1.790378889683619e-05, 'epoch': 0.22}) +[2026-07-26 22:11:38,164][starVLA.training.train_starvla][INFO] - Step 1831, Loss: {'train/loss': 0.38541179895401, 'train/grad_norm_pre_clip': 4.900445938110352, 'timing/data': 0.0001736469566822052, 'timing/model': 0.4573945561423898, 'learning_rate/action_model': 7.15876255874941e-05, 'learning_rate/action_query_proj': 7.15876255874941e-05, 'learning_rate/base': 1.7896906396873524e-05, 'epoch': 0.22}) +[2026-07-26 22:11:43,687][starVLA.training.train_starvla][INFO] - Step 1832, Loss: {'train/loss': 0.24684524536132812, 'train/grad_norm_pre_clip': 3.514526605606079, 'timing/data': 0.00017103413119912148, 'timing/model': 0.4586295527406037, 'learning_rate/action_model': 7.156008785475907e-05, 'learning_rate/action_query_proj': 7.156008785475907e-05, 'learning_rate/base': 1.7890021963689768e-05, 'epoch': 0.22}) +[2026-07-26 22:11:49,389][starVLA.training.train_starvla][INFO] - Step 1833, Loss: {'train/loss': 0.26244834065437317, 'train/grad_norm_pre_clip': 2.8426389694213867, 'timing/data': 0.00017301971092820168, 'timing/model': 0.4568081288598478, 'learning_rate/action_model': 7.153254240001116e-05, 'learning_rate/action_query_proj': 7.153254240001116e-05, 'learning_rate/base': 1.788313560000279e-05, 'epoch': 0.22}) +[2026-07-26 22:11:54,909][starVLA.training.train_starvla][INFO] - Step 1834, Loss: {'train/loss': 0.25357916951179504, 'train/grad_norm_pre_clip': 2.5509531497955322, 'timing/data': 0.00016937684267759323, 'timing/model': 0.45821656798943877, 'learning_rate/action_model': 7.150498923412479e-05, 'learning_rate/action_query_proj': 7.150498923412479e-05, 'learning_rate/base': 1.7876247308531197e-05, 'epoch': 0.22}) +[2026-07-26 22:12:00,453][starVLA.training.train_starvla][INFO] - Step 1835, Loss: {'train/loss': 0.30880704522132874, 'train/grad_norm_pre_clip': 3.1113407611846924, 'timing/data': 0.00017021875828504562, 'timing/model': 0.4592126151546836, 'learning_rate/action_model': 7.14774283679776e-05, 'learning_rate/action_query_proj': 7.14774283679776e-05, 'learning_rate/base': 1.78693570919944e-05, 'epoch': 0.22}) +[2026-07-26 22:12:06,010][starVLA.training.train_starvla][INFO] - Step 1836, Loss: {'train/loss': 0.2115958034992218, 'train/grad_norm_pre_clip': 2.3820059299468994, 'timing/data': 0.00017104996368288994, 'timing/model': 0.45785417733713984, 'learning_rate/action_model': 7.144985981245015e-05, 'learning_rate/action_query_proj': 7.144985981245015e-05, 'learning_rate/base': 1.7862464953112537e-05, 'epoch': 0.22}) +[2026-07-26 22:12:11,527][starVLA.training.train_starvla][INFO] - Step 1837, Loss: {'train/loss': 0.26761478185653687, 'train/grad_norm_pre_clip': 2.9306609630584717, 'timing/data': 0.00017042085528373718, 'timing/model': 0.4568089568056166, 'learning_rate/action_model': 7.142228357842608e-05, 'learning_rate/action_query_proj': 7.142228357842608e-05, 'learning_rate/base': 1.785557089460652e-05, 'epoch': 0.22}) +[2026-07-26 22:12:17,052][starVLA.training.train_starvla][INFO] - Step 1838, Loss: {'train/loss': 0.24413558840751648, 'train/grad_norm_pre_clip': 3.2902274131774902, 'timing/data': 0.00017264066264033318, 'timing/model': 0.4577911179512739, 'learning_rate/action_model': 7.139469967679204e-05, 'learning_rate/action_query_proj': 7.139469967679204e-05, 'learning_rate/base': 1.784867491919801e-05, 'epoch': 0.22}) +[2026-07-26 22:12:22,556][starVLA.training.train_starvla][INFO] - Step 1839, Loss: {'train/loss': 0.37459880113601685, 'train/grad_norm_pre_clip': 4.84023904800415, 'timing/data': 0.0001718061976134777, 'timing/model': 0.4580435389652848, 'learning_rate/action_model': 7.13671081184377e-05, 'learning_rate/action_query_proj': 7.13671081184377e-05, 'learning_rate/base': 1.7841777029609425e-05, 'epoch': 0.22}) +[2026-07-26 22:12:28,109][starVLA.training.train_starvla][INFO] - Step 1840, Loss: {'train/loss': 0.16767077147960663, 'train/grad_norm_pre_clip': 2.9135255813598633, 'timing/data': 0.00017047394067049026, 'timing/model': 0.4579969719052315, 'learning_rate/action_model': 7.133950891425582e-05, 'learning_rate/action_query_proj': 7.133950891425582e-05, 'learning_rate/base': 1.7834877228563955e-05, 'epoch': 0.22}) +[2026-07-26 22:12:33,621][starVLA.training.train_starvla][INFO] - Step 1841, Loss: {'train/loss': 0.28719866275787354, 'train/grad_norm_pre_clip': 3.8987252712249756, 'timing/data': 0.00017952127382159233, 'timing/model': 0.457561950199306, 'learning_rate/action_model': 7.131190207514206e-05, 'learning_rate/action_query_proj': 7.131190207514206e-05, 'learning_rate/base': 1.7827975518785516e-05, 'epoch': 0.22}) +[2026-07-26 22:12:39,138][starVLA.training.train_starvla][INFO] - Step 1842, Loss: {'train/loss': 0.23391035199165344, 'train/grad_norm_pre_clip': 2.4858779907226562, 'timing/data': 0.00017760414630174637, 'timing/model': 0.45711873983964324, 'learning_rate/action_model': 7.128428761199523e-05, 'learning_rate/action_query_proj': 7.128428761199523e-05, 'learning_rate/base': 1.7821071902998808e-05, 'epoch': 0.22}) +[2026-07-26 22:12:44,662][starVLA.training.train_starvla][INFO] - Step 1843, Loss: {'train/loss': 0.3469718396663666, 'train/grad_norm_pre_clip': 3.945103883743286, 'timing/data': 0.0001739361323416233, 'timing/model': 0.45956555800512433, 'learning_rate/action_model': 7.125666553571707e-05, 'learning_rate/action_query_proj': 7.125666553571707e-05, 'learning_rate/base': 1.7814166383929267e-05, 'epoch': 0.22}) +[2026-07-26 22:12:50,431][starVLA.training.train_starvla][INFO] - Step 1844, Loss: {'train/loss': 0.2826671004295349, 'train/grad_norm_pre_clip': 3.2020530700683594, 'timing/data': 0.000175433699041605, 'timing/model': 0.7178311641328037, 'learning_rate/action_model': 7.12290358572123e-05, 'learning_rate/action_query_proj': 7.12290358572123e-05, 'learning_rate/base': 1.7807258964303076e-05, 'epoch': 0.22}) +[2026-07-26 22:12:55,942][starVLA.training.train_starvla][INFO] - Step 1845, Loss: {'train/loss': 0.21442092955112457, 'train/grad_norm_pre_clip': 3.0325326919555664, 'timing/data': 0.00017562834545969963, 'timing/model': 0.45780778396874666, 'learning_rate/action_model': 7.12013985873887e-05, 'learning_rate/action_query_proj': 7.12013985873887e-05, 'learning_rate/base': 1.7800349646847176e-05, 'epoch': 0.22}) +[2026-07-26 22:13:01,458][starVLA.training.train_starvla][INFO] - Step 1846, Loss: {'train/loss': 0.2589584290981293, 'train/grad_norm_pre_clip': 4.7186760902404785, 'timing/data': 0.00017828959971666336, 'timing/model': 0.45757313864305615, 'learning_rate/action_model': 7.117375373715704e-05, 'learning_rate/action_query_proj': 7.117375373715704e-05, 'learning_rate/base': 1.779343843428926e-05, 'epoch': 0.22}) +[2026-07-26 22:13:06,967][starVLA.training.train_starvla][INFO] - Step 1847, Loss: {'train/loss': 0.424285888671875, 'train/grad_norm_pre_clip': 5.618386745452881, 'timing/data': 0.00017648423090577126, 'timing/model': 0.45835668686777353, 'learning_rate/action_model': 7.114610131743106e-05, 'learning_rate/action_query_proj': 7.114610131743106e-05, 'learning_rate/base': 1.7786525329357765e-05, 'epoch': 0.22}) +[2026-07-26 22:13:12,702][starVLA.training.train_starvla][INFO] - Step 1848, Loss: {'train/loss': 0.3458713889122009, 'train/grad_norm_pre_clip': 2.924145460128784, 'timing/data': 0.00017334194853901863, 'timing/model': 0.45816056709736586, 'learning_rate/action_model': 7.111844133912751e-05, 'learning_rate/action_query_proj': 7.111844133912751e-05, 'learning_rate/base': 1.7779610334781877e-05, 'epoch': 0.22}) +[2026-07-26 22:13:18,261][starVLA.training.train_starvla][INFO] - Step 1849, Loss: {'train/loss': 0.2445177286863327, 'train/grad_norm_pre_clip': 3.4358108043670654, 'timing/data': 0.0001731892116367817, 'timing/model': 0.4584108339622617, 'learning_rate/action_model': 7.109077381316606e-05, 'learning_rate/action_query_proj': 7.109077381316606e-05, 'learning_rate/base': 1.7772693453291516e-05, 'epoch': 0.22}) +[2026-07-26 22:13:24,080][starVLA.training.train_starvla][INFO] - Step 1850, Loss: {'train/loss': 0.2690647542476654, 'train/grad_norm_pre_clip': 3.9093096256256104, 'timing/data': 0.0001759640872478485, 'timing/model': 0.4574215756729245, 'learning_rate/action_model': 7.106309875046947e-05, 'learning_rate/action_query_proj': 7.106309875046947e-05, 'learning_rate/base': 1.7765774687617366e-05, 'epoch': 0.22}) +[2026-07-26 22:13:29,622][starVLA.training.train_starvla][INFO] - Step 1851, Loss: {'train/loss': 0.33320754766464233, 'train/grad_norm_pre_clip': 4.257226943969727, 'timing/data': 0.00017899787053465843, 'timing/model': 0.45824762899428606, 'learning_rate/action_model': 7.10354161619634e-05, 'learning_rate/action_query_proj': 7.10354161619634e-05, 'learning_rate/base': 1.775885404049085e-05, 'epoch': 0.22}) +[2026-07-26 22:13:35,165][starVLA.training.train_starvla][INFO] - Step 1852, Loss: {'train/loss': 0.16566425561904907, 'train/grad_norm_pre_clip': 2.8032681941986084, 'timing/data': 0.00017643766477704048, 'timing/model': 0.45719358464702964, 'learning_rate/action_model': 7.100772605857648e-05, 'learning_rate/action_query_proj': 7.100772605857648e-05, 'learning_rate/base': 1.775193151464412e-05, 'epoch': 0.22}) +[2026-07-26 22:13:40,704][starVLA.training.train_starvla][INFO] - Step 1853, Loss: {'train/loss': 0.18256355822086334, 'train/grad_norm_pre_clip': 2.019484519958496, 'timing/data': 0.00018383702263236046, 'timing/model': 0.4562747827731073, 'learning_rate/action_model': 7.098002845124033e-05, 'learning_rate/action_query_proj': 7.098002845124033e-05, 'learning_rate/base': 1.7745007112810084e-05, 'epoch': 0.22}) +[2026-07-26 22:13:46,244][starVLA.training.train_starvla][INFO] - Step 1854, Loss: {'train/loss': 0.31470149755477905, 'train/grad_norm_pre_clip': 3.4021685123443604, 'timing/data': 0.00016622990369796753, 'timing/model': 0.4575753868557513, 'learning_rate/action_model': 7.095232335088956e-05, 'learning_rate/action_query_proj': 7.095232335088956e-05, 'learning_rate/base': 1.773808083772239e-05, 'epoch': 0.22}) +[2026-07-26 22:13:52,002][starVLA.training.train_starvla][INFO] - Step 1855, Loss: {'train/loss': 0.3438059091567993, 'train/grad_norm_pre_clip': 5.885262489318848, 'timing/data': 0.00018334807828068733, 'timing/model': 0.4603188196197152, 'learning_rate/action_model': 7.092461076846166e-05, 'learning_rate/action_query_proj': 7.092461076846166e-05, 'learning_rate/base': 1.7731152692115415e-05, 'epoch': 0.23}) +[2026-07-26 22:13:57,549][starVLA.training.train_starvla][INFO] - Step 1856, Loss: {'train/loss': 0.4170600175857544, 'train/grad_norm_pre_clip': 5.959842681884766, 'timing/data': 0.0001826537773013115, 'timing/model': 0.45686594396829605, 'learning_rate/action_model': 7.089689071489714e-05, 'learning_rate/action_query_proj': 7.089689071489714e-05, 'learning_rate/base': 1.7724222678724284e-05, 'epoch': 0.23}) +[2026-07-26 22:14:03,115][starVLA.training.train_starvla][INFO] - Step 1857, Loss: {'train/loss': 0.3460830748081207, 'train/grad_norm_pre_clip': 4.420861721038818, 'timing/data': 0.00018351199105381966, 'timing/model': 0.45768311293795705, 'learning_rate/action_model': 7.086916320113943e-05, 'learning_rate/action_query_proj': 7.086916320113943e-05, 'learning_rate/base': 1.7717290800284857e-05, 'epoch': 0.23}) +[2026-07-26 22:14:08,647][starVLA.training.train_starvla][INFO] - Step 1858, Loss: {'train/loss': 0.21693013608455658, 'train/grad_norm_pre_clip': 3.683321714401245, 'timing/data': 0.00018056202679872513, 'timing/model': 0.45841892901808023, 'learning_rate/action_model': 7.084142823813492e-05, 'learning_rate/action_query_proj': 7.084142823813492e-05, 'learning_rate/base': 1.771035705953373e-05, 'epoch': 0.23}) +[2026-07-26 22:14:14,404][starVLA.training.train_starvla][INFO] - Step 1859, Loss: {'train/loss': 0.21435564756393433, 'train/grad_norm_pre_clip': 1.8927868604660034, 'timing/data': 0.0001687970943748951, 'timing/model': 0.45836005127057433, 'learning_rate/action_model': 7.081368583683292e-05, 'learning_rate/action_query_proj': 7.081368583683292e-05, 'learning_rate/base': 1.770342145920823e-05, 'epoch': 0.23}) +[2026-07-26 22:14:20,152][starVLA.training.train_starvla][INFO] - Step 1860, Loss: {'train/loss': 0.2803483307361603, 'train/grad_norm_pre_clip': 3.9799745082855225, 'timing/data': 0.00031732162460684776, 'timing/model': 0.5550592462532222, 'learning_rate/action_model': 7.078593600818572e-05, 'learning_rate/action_query_proj': 7.078593600818572e-05, 'learning_rate/base': 1.769648400204643e-05, 'epoch': 0.23}) +[2026-07-26 22:14:25,681][starVLA.training.train_starvla][INFO] - Step 1861, Loss: {'train/loss': 0.42777493596076965, 'train/grad_norm_pre_clip': 4.630714416503906, 'timing/data': 0.00017012609168887138, 'timing/model': 0.4569211080670357, 'learning_rate/action_model': 7.075817876314849e-05, 'learning_rate/action_query_proj': 7.075817876314849e-05, 'learning_rate/base': 1.7689544690787123e-05, 'epoch': 0.23}) +[2026-07-26 22:14:31,223][starVLA.training.train_starvla][INFO] - Step 1862, Loss: {'train/loss': 0.20708073675632477, 'train/grad_norm_pre_clip': 2.6159515380859375, 'timing/data': 0.00017437338829040527, 'timing/model': 0.4559501032344997, 'learning_rate/action_model': 7.073041411267935e-05, 'learning_rate/action_query_proj': 7.073041411267935e-05, 'learning_rate/base': 1.7682603528169838e-05, 'epoch': 0.23}) +[2026-07-26 22:14:36,773][starVLA.training.train_starvla][INFO] - Step 1863, Loss: {'train/loss': 0.30275142192840576, 'train/grad_norm_pre_clip': 4.57729434967041, 'timing/data': 0.00017158128321170807, 'timing/model': 0.45858192909508944, 'learning_rate/action_model': 7.070264206773938e-05, 'learning_rate/action_query_proj': 7.070264206773938e-05, 'learning_rate/base': 1.7675660516934844e-05, 'epoch': 0.23}) +[2026-07-26 22:14:42,319][starVLA.training.train_starvla][INFO] - Step 1864, Loss: {'train/loss': 0.27963435649871826, 'train/grad_norm_pre_clip': 4.686438083648682, 'timing/data': 0.00018059788271784782, 'timing/model': 0.45592238707467914, 'learning_rate/action_model': 7.067486263929249e-05, 'learning_rate/action_query_proj': 7.067486263929249e-05, 'learning_rate/base': 1.766871565982312e-05, 'epoch': 0.23}) +[2026-07-26 22:14:47,866][starVLA.training.train_starvla][INFO] - Step 1865, Loss: {'train/loss': 0.17700140178203583, 'train/grad_norm_pre_clip': 2.954854965209961, 'timing/data': 0.00017538107931613922, 'timing/model': 0.45808658096939325, 'learning_rate/action_model': 7.064707583830558e-05, 'learning_rate/action_query_proj': 7.064707583830558e-05, 'learning_rate/base': 1.7661768959576396e-05, 'epoch': 0.23}) +[2026-07-26 22:14:53,404][starVLA.training.train_starvla][INFO] - Step 1866, Loss: {'train/loss': 0.2850612699985504, 'train/grad_norm_pre_clip': 3.2233500480651855, 'timing/data': 0.0001751459203660488, 'timing/model': 0.4568678974173963, 'learning_rate/action_model': 7.061928167574846e-05, 'learning_rate/action_query_proj': 7.061928167574846e-05, 'learning_rate/base': 1.7654820418937116e-05, 'epoch': 0.23}) +[2026-07-26 22:14:58,949][starVLA.training.train_starvla][INFO] - Step 1867, Loss: {'train/loss': 0.2856176197528839, 'train/grad_norm_pre_clip': 3.348350763320923, 'timing/data': 0.00017443625256419182, 'timing/model': 0.4565497920848429, 'learning_rate/action_model': 7.059148016259378e-05, 'learning_rate/action_query_proj': 7.059148016259378e-05, 'learning_rate/base': 1.7647870040648446e-05, 'epoch': 0.23}) +[2026-07-26 22:15:04,497][starVLA.training.train_starvla][INFO] - Step 1868, Loss: {'train/loss': 0.30213090777397156, 'train/grad_norm_pre_clip': 3.8112881183624268, 'timing/data': 0.00017363112419843674, 'timing/model': 0.45738366805016994, 'learning_rate/action_model': 7.056367130981718e-05, 'learning_rate/action_query_proj': 7.056367130981718e-05, 'learning_rate/base': 1.7640917827454295e-05, 'epoch': 0.23}) +[2026-07-26 22:15:10,029][starVLA.training.train_starvla][INFO] - Step 1869, Loss: {'train/loss': 0.31791186332702637, 'train/grad_norm_pre_clip': 3.7700142860412598, 'timing/data': 0.00017831381410360336, 'timing/model': 0.45819302927702665, 'learning_rate/action_model': 7.053585512839713e-05, 'learning_rate/action_query_proj': 7.053585512839713e-05, 'learning_rate/base': 1.7633963782099283e-05, 'epoch': 0.23}) +[2026-07-26 22:15:15,569][starVLA.training.train_starvla][INFO] - Step 1870, Loss: {'train/loss': 0.3031001091003418, 'train/grad_norm_pre_clip': 2.739938974380493, 'timing/data': 0.00018303422257304192, 'timing/model': 0.4575738040730357, 'learning_rate/action_model': 7.050803162931504e-05, 'learning_rate/action_query_proj': 7.050803162931504e-05, 'learning_rate/base': 1.762700790732876e-05, 'epoch': 0.23}) +[2026-07-26 22:15:21,174][starVLA.training.train_starvla][INFO] - Step 1871, Loss: {'train/loss': 0.330319344997406, 'train/grad_norm_pre_clip': 2.9777865409851074, 'timing/data': 0.00017863605171442032, 'timing/model': 0.524245731998235, 'learning_rate/action_model': 7.048020082355518e-05, 'learning_rate/action_query_proj': 7.048020082355518e-05, 'learning_rate/base': 1.7620050205888794e-05, 'epoch': 0.23}) +[2026-07-26 22:15:26,708][starVLA.training.train_starvla][INFO] - Step 1872, Loss: {'train/loss': 0.2504618763923645, 'train/grad_norm_pre_clip': 3.070511817932129, 'timing/data': 0.00017234496772289276, 'timing/model': 0.4583706702105701, 'learning_rate/action_model': 7.045236272210468e-05, 'learning_rate/action_query_proj': 7.045236272210468e-05, 'learning_rate/base': 1.761309068052617e-05, 'epoch': 0.23}) +[2026-07-26 22:15:32,250][starVLA.training.train_starvla][INFO] - Step 1873, Loss: {'train/loss': 0.2976086437702179, 'train/grad_norm_pre_clip': 2.9413836002349854, 'timing/data': 0.00016792584210634232, 'timing/model': 0.45823004888370633, 'learning_rate/action_model': 7.042451733595362e-05, 'learning_rate/action_query_proj': 7.042451733595362e-05, 'learning_rate/base': 1.7606129333988405e-05, 'epoch': 0.23}) +[2026-07-26 22:15:37,798][starVLA.training.train_starvla][INFO] - Step 1874, Loss: {'train/loss': 0.3061135411262512, 'train/grad_norm_pre_clip': 2.9039907455444336, 'timing/data': 0.00017124926671385765, 'timing/model': 0.457901612855494, 'learning_rate/action_model': 7.039666467609489e-05, 'learning_rate/action_query_proj': 7.039666467609489e-05, 'learning_rate/base': 1.7599166169023723e-05, 'epoch': 0.23}) +[2026-07-26 22:15:43,345][starVLA.training.train_starvla][INFO] - Step 1875, Loss: {'train/loss': 0.35481131076812744, 'train/grad_norm_pre_clip': 2.6798512935638428, 'timing/data': 0.0001701568253338337, 'timing/model': 0.4581513833254576, 'learning_rate/action_model': 7.036880475352432e-05, 'learning_rate/action_query_proj': 7.036880475352432e-05, 'learning_rate/base': 1.759220118838108e-05, 'epoch': 0.23}) +[2026-07-26 22:15:48,885][starVLA.training.train_starvla][INFO] - Step 1876, Loss: {'train/loss': 0.33790576457977295, 'train/grad_norm_pre_clip': 3.822296142578125, 'timing/data': 0.0001764087937772274, 'timing/model': 0.4582996368408203, 'learning_rate/action_model': 7.034093757924052e-05, 'learning_rate/action_query_proj': 7.034093757924052e-05, 'learning_rate/base': 1.758523439481013e-05, 'epoch': 0.23}) +[2026-07-26 22:15:54,432][starVLA.training.train_starvla][INFO] - Step 1877, Loss: {'train/loss': 0.27233636379241943, 'train/grad_norm_pre_clip': 3.451622247695923, 'timing/data': 0.0001725521869957447, 'timing/model': 0.4589712470769882, 'learning_rate/action_model': 7.031306316424504e-05, 'learning_rate/action_query_proj': 7.031306316424504e-05, 'learning_rate/base': 1.757826579106126e-05, 'epoch': 0.23}) +[2026-07-26 22:15:59,980][starVLA.training.train_starvla][INFO] - Step 1878, Loss: {'train/loss': 0.43619123101234436, 'train/grad_norm_pre_clip': 3.8849217891693115, 'timing/data': 0.0001801629550755024, 'timing/model': 0.45924213295802474, 'learning_rate/action_model': 7.028518151954222e-05, 'learning_rate/action_query_proj': 7.028518151954222e-05, 'learning_rate/base': 1.7571295379885554e-05, 'epoch': 0.23}) +[2026-07-26 22:16:05,518][starVLA.training.train_starvla][INFO] - Step 1879, Loss: {'train/loss': 0.3638593554496765, 'train/grad_norm_pre_clip': 4.122097492218018, 'timing/data': 0.00017851591110229492, 'timing/model': 0.4581087767146528, 'learning_rate/action_model': 7.025729265613934e-05, 'learning_rate/action_query_proj': 7.025729265613934e-05, 'learning_rate/base': 1.7564323164034835e-05, 'epoch': 0.23}) +[2026-07-26 22:16:11,044][starVLA.training.train_starvla][INFO] - Step 1880, Loss: {'train/loss': 0.24568448960781097, 'train/grad_norm_pre_clip': 4.532832145690918, 'timing/data': 0.00017579132691025734, 'timing/model': 0.4593073199503124, 'learning_rate/action_model': 7.022939658504645e-05, 'learning_rate/action_query_proj': 7.022939658504645e-05, 'learning_rate/base': 1.7557349146261614e-05, 'epoch': 0.23}) +[2026-07-26 22:16:16,584][starVLA.training.train_starvla][INFO] - Step 1881, Loss: {'train/loss': 0.28980737924575806, 'train/grad_norm_pre_clip': 4.575943946838379, 'timing/data': 0.0001730513758957386, 'timing/model': 0.45883142156526446, 'learning_rate/action_model': 7.02014933172765e-05, 'learning_rate/action_query_proj': 7.02014933172765e-05, 'learning_rate/base': 1.7550373329319125e-05, 'epoch': 0.23}) +[2026-07-26 22:16:22,111][starVLA.training.train_starvla][INFO] - Step 1882, Loss: {'train/loss': 0.3253061771392822, 'train/grad_norm_pre_clip': 3.507505178451538, 'timing/data': 0.0001764623448252678, 'timing/model': 0.45826834673061967, 'learning_rate/action_model': 7.017358286384524e-05, 'learning_rate/action_query_proj': 7.017358286384524e-05, 'learning_rate/base': 1.754339571596131e-05, 'epoch': 0.23}) +[2026-07-26 22:16:27,644][starVLA.training.train_starvla][INFO] - Step 1883, Loss: {'train/loss': 0.14938534796237946, 'train/grad_norm_pre_clip': 2.7822277545928955, 'timing/data': 0.0001733577810227871, 'timing/model': 0.45935917599126697, 'learning_rate/action_model': 7.014566523577127e-05, 'learning_rate/action_query_proj': 7.014566523577127e-05, 'learning_rate/base': 1.7536416308942817e-05, 'epoch': 0.23}) +[2026-07-26 22:16:33,159][starVLA.training.train_starvla][INFO] - Step 1884, Loss: {'train/loss': 0.35239627957344055, 'train/grad_norm_pre_clip': 5.364450454711914, 'timing/data': 0.00017493823543190956, 'timing/model': 0.4588983729481697, 'learning_rate/action_model': 7.011774044407603e-05, 'learning_rate/action_query_proj': 7.011774044407603e-05, 'learning_rate/base': 1.7529435111019007e-05, 'epoch': 0.23}) +[2026-07-26 22:16:38,690][starVLA.training.train_starvla][INFO] - Step 1885, Loss: {'train/loss': 0.31299540400505066, 'train/grad_norm_pre_clip': 3.7807393074035645, 'timing/data': 0.00017283018678426743, 'timing/model': 0.46267510391771793, 'learning_rate/action_model': 7.008980849978382e-05, 'learning_rate/action_query_proj': 7.008980849978382e-05, 'learning_rate/base': 1.7522452124945954e-05, 'epoch': 0.23}) +[2026-07-26 22:16:44,202][starVLA.training.train_starvla][INFO] - Step 1886, Loss: {'train/loss': 0.3041129410266876, 'train/grad_norm_pre_clip': 2.725677490234375, 'timing/data': 0.00017513660714030266, 'timing/model': 0.45747658610343933, 'learning_rate/action_model': 7.006186941392168e-05, 'learning_rate/action_query_proj': 7.006186941392168e-05, 'learning_rate/base': 1.751546735348042e-05, 'epoch': 0.23}) +[2026-07-26 22:16:49,709][starVLA.training.train_starvla][INFO] - Step 1887, Loss: {'train/loss': 0.34797337651252747, 'train/grad_norm_pre_clip': 4.723813533782959, 'timing/data': 0.00017458386719226837, 'timing/model': 0.4575185147114098, 'learning_rate/action_model': 7.003392319751954e-05, 'learning_rate/action_query_proj': 7.003392319751954e-05, 'learning_rate/base': 1.7508480799379885e-05, 'epoch': 0.23}) +[2026-07-26 22:16:55,218][starVLA.training.train_starvla][INFO] - Step 1888, Loss: {'train/loss': 0.2637336850166321, 'train/grad_norm_pre_clip': 4.576013088226318, 'timing/data': 0.0001870701089501381, 'timing/model': 0.4578705611638725, 'learning_rate/action_model': 7.000596986161014e-05, 'learning_rate/action_query_proj': 7.000596986161014e-05, 'learning_rate/base': 1.7501492465402534e-05, 'epoch': 0.23}) +[2026-07-26 22:17:00,720][starVLA.training.train_starvla][INFO] - Step 1889, Loss: {'train/loss': 0.2573397159576416, 'train/grad_norm_pre_clip': 5.611774444580078, 'timing/data': 0.00018655182793736458, 'timing/model': 0.4587145708501339, 'learning_rate/action_model': 6.997800941722899e-05, 'learning_rate/action_query_proj': 6.997800941722899e-05, 'learning_rate/base': 1.7494502354307247e-05, 'epoch': 0.23}) +[2026-07-26 22:17:06,226][starVLA.training.train_starvla][INFO] - Step 1890, Loss: {'train/loss': 0.27498385310173035, 'train/grad_norm_pre_clip': 3.879753828048706, 'timing/data': 0.0001707170158624649, 'timing/model': 0.45866067381575704, 'learning_rate/action_model': 6.995004187541442e-05, 'learning_rate/action_query_proj': 6.995004187541442e-05, 'learning_rate/base': 1.7487510468853606e-05, 'epoch': 0.23}) +[2026-07-26 22:17:11,732][starVLA.training.train_starvla][INFO] - Step 1891, Loss: {'train/loss': 0.21825209259986877, 'train/grad_norm_pre_clip': 2.5520942211151123, 'timing/data': 0.00017575686797499657, 'timing/model': 0.4584649163298309, 'learning_rate/action_model': 6.992206724720761e-05, 'learning_rate/action_query_proj': 6.992206724720761e-05, 'learning_rate/base': 1.7480516811801903e-05, 'epoch': 0.23}) +[2026-07-26 22:17:17,228][starVLA.training.train_starvla][INFO] - Step 1892, Loss: {'train/loss': 0.21746818721294403, 'train/grad_norm_pre_clip': 3.4932658672332764, 'timing/data': 0.00017057918012142181, 'timing/model': 0.45858606416732073, 'learning_rate/action_model': 6.989408554365249e-05, 'learning_rate/action_query_proj': 6.989408554365249e-05, 'learning_rate/base': 1.7473521385913122e-05, 'epoch': 0.23}) +[2026-07-26 22:17:22,731][starVLA.training.train_starvla][INFO] - Step 1893, Loss: {'train/loss': 0.252932608127594, 'train/grad_norm_pre_clip': 3.359086513519287, 'timing/data': 0.0001722089946269989, 'timing/model': 0.45991227636113763, 'learning_rate/action_model': 6.986609677579578e-05, 'learning_rate/action_query_proj': 6.986609677579578e-05, 'learning_rate/base': 1.7466524193948944e-05, 'epoch': 0.23}) +[2026-07-26 22:17:28,232][starVLA.training.train_starvla][INFO] - Step 1894, Loss: {'train/loss': 0.27823325991630554, 'train/grad_norm_pre_clip': 3.27077054977417, 'timing/data': 0.00017115194350481033, 'timing/model': 0.4585494799539447, 'learning_rate/action_model': 6.983810095468698e-05, 'learning_rate/action_query_proj': 6.983810095468698e-05, 'learning_rate/base': 1.7459525238671746e-05, 'epoch': 0.23}) +[2026-07-26 22:17:33,741][starVLA.training.train_starvla][INFO] - Step 1895, Loss: {'train/loss': 0.2238878607749939, 'train/grad_norm_pre_clip': 4.012063503265381, 'timing/data': 0.0001726248301565647, 'timing/model': 0.46036452800035477, 'learning_rate/action_model': 6.981009809137846e-05, 'learning_rate/action_query_proj': 6.981009809137846e-05, 'learning_rate/base': 1.7452524522844614e-05, 'epoch': 0.23}) +[2026-07-26 22:17:39,345][starVLA.training.train_starvla][INFO] - Step 1896, Loss: {'train/loss': 0.2998667061328888, 'train/grad_norm_pre_clip': 2.516899824142456, 'timing/data': 0.0001723766326904297, 'timing/model': 0.45728756906464696, 'learning_rate/action_model': 6.978208819692526e-05, 'learning_rate/action_query_proj': 6.978208819692526e-05, 'learning_rate/base': 1.7445522049231314e-05, 'epoch': 0.23}) +[2026-07-26 22:17:44,843][starVLA.training.train_starvla][INFO] - Step 1897, Loss: {'train/loss': 0.285702645778656, 'train/grad_norm_pre_clip': 3.2575299739837646, 'timing/data': 0.00017098477110266685, 'timing/model': 0.45950628304854035, 'learning_rate/action_model': 6.975407128238525e-05, 'learning_rate/action_query_proj': 6.975407128238525e-05, 'learning_rate/base': 1.7438517820596313e-05, 'epoch': 0.23}) +[2026-07-26 22:17:50,346][starVLA.training.train_starvla][INFO] - Step 1898, Loss: {'train/loss': 0.2129157930612564, 'train/grad_norm_pre_clip': 4.7354817390441895, 'timing/data': 0.00017590774223208427, 'timing/model': 0.4591656378470361, 'learning_rate/action_model': 6.972604735881907e-05, 'learning_rate/action_query_proj': 6.972604735881907e-05, 'learning_rate/base': 1.7431511839704768e-05, 'epoch': 0.23}) +[2026-07-26 22:17:55,843][starVLA.training.train_starvla][INFO] - Step 1899, Loss: {'train/loss': 0.2563798427581787, 'train/grad_norm_pre_clip': 2.8159303665161133, 'timing/data': 0.00017446326091885567, 'timing/model': 0.45866046380251646, 'learning_rate/action_model': 6.969801643729011e-05, 'learning_rate/action_query_proj': 6.969801643729011e-05, 'learning_rate/base': 1.7424504109322527e-05, 'epoch': 0.23}) +[2026-07-26 22:18:01,377][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 1900 +[2026-07-26 22:18:01,378][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 1900 +[2026-07-26 22:18:01,379][starVLA.training.train_starvla][INFO] - Step 1900, Loss: {'train/loss': 0.2581680715084076, 'train/grad_norm_pre_clip': 3.490781307220459, 'timing/data': 0.00017151376232504845, 'timing/model': 0.45758231868967414, 'learning_rate/action_model': 6.966997852886456e-05, 'learning_rate/action_query_proj': 6.966997852886456e-05, 'learning_rate/base': 1.741749463221614e-05, 'epoch': 0.23}) +[2026-07-26 22:18:06,881][starVLA.training.train_starvla][INFO] - Step 1901, Loss: {'train/loss': 0.22204303741455078, 'train/grad_norm_pre_clip': 3.626236915588379, 'timing/data': 0.00016927486285567284, 'timing/model': 0.45720227900892496, 'learning_rate/action_model': 6.96419336446113e-05, 'learning_rate/action_query_proj': 6.96419336446113e-05, 'learning_rate/base': 1.7410483411152824e-05, 'epoch': 0.23}) +[2026-07-26 22:18:12,375][starVLA.training.train_starvla][INFO] - Step 1902, Loss: {'train/loss': 0.28279775381088257, 'train/grad_norm_pre_clip': 3.7250313758850098, 'timing/data': 0.0001687486656010151, 'timing/model': 0.4563467036932707, 'learning_rate/action_model': 6.961388179560206e-05, 'learning_rate/action_query_proj': 6.961388179560206e-05, 'learning_rate/base': 1.7403470448900514e-05, 'epoch': 0.23}) +[2026-07-26 22:18:17,879][starVLA.training.train_starvla][INFO] - Step 1903, Loss: {'train/loss': 0.2930116653442383, 'train/grad_norm_pre_clip': 3.384458065032959, 'timing/data': 0.00017094984650611877, 'timing/model': 0.45784664899110794, 'learning_rate/action_model': 6.958582299291123e-05, 'learning_rate/action_query_proj': 6.958582299291123e-05, 'learning_rate/base': 1.7396455748227806e-05, 'epoch': 0.23}) +[2026-07-26 22:18:23,385][starVLA.training.train_starvla][INFO] - Step 1904, Loss: {'train/loss': 0.3340602517127991, 'train/grad_norm_pre_clip': 5.309323787689209, 'timing/data': 0.00016854098066687584, 'timing/model': 0.4578460496850312, 'learning_rate/action_model': 6.955775724761597e-05, 'learning_rate/action_query_proj': 6.955775724761597e-05, 'learning_rate/base': 1.7389439311903992e-05, 'epoch': 0.23}) +[2026-07-26 22:18:28,899][starVLA.training.train_starvla][INFO] - Step 1905, Loss: {'train/loss': 0.21731188893318176, 'train/grad_norm_pre_clip': 3.8302488327026367, 'timing/data': 0.00016984017565846443, 'timing/model': 0.45866136671975255, 'learning_rate/action_model': 6.952968457079623e-05, 'learning_rate/action_query_proj': 6.952968457079623e-05, 'learning_rate/base': 1.7382421142699057e-05, 'epoch': 0.23}) +[2026-07-26 22:18:34,411][starVLA.training.train_starvla][INFO] - Step 1906, Loss: {'train/loss': 0.2675740718841553, 'train/grad_norm_pre_clip': 3.205404043197632, 'timing/data': 0.00017181597650051117, 'timing/model': 0.45913070999085903, 'learning_rate/action_model': 6.950160497353463e-05, 'learning_rate/action_query_proj': 6.950160497353463e-05, 'learning_rate/base': 1.7375401243383658e-05, 'epoch': 0.23}) +[2026-07-26 22:18:39,947][starVLA.training.train_starvla][INFO] - Step 1907, Loss: {'train/loss': 0.4032350778579712, 'train/grad_norm_pre_clip': 4.442027568817139, 'timing/data': 0.00017441995441913605, 'timing/model': 0.4724507168866694, 'learning_rate/action_model': 6.947351846691655e-05, 'learning_rate/action_query_proj': 6.947351846691655e-05, 'learning_rate/base': 1.7368379616729138e-05, 'epoch': 0.23}) +[2026-07-26 22:18:45,668][starVLA.training.train_starvla][INFO] - Step 1908, Loss: {'train/loss': 0.3190003037452698, 'train/grad_norm_pre_clip': 4.042942047119141, 'timing/data': 0.00017869658768177032, 'timing/model': 0.4585262187756598, 'learning_rate/action_model': 6.944542506203011e-05, 'learning_rate/action_query_proj': 6.944542506203011e-05, 'learning_rate/base': 1.7361356265507528e-05, 'epoch': 0.23}) +[2026-07-26 22:18:51,184][starVLA.training.train_starvla][INFO] - Step 1909, Loss: {'train/loss': 0.28456708788871765, 'train/grad_norm_pre_clip': 4.710842132568359, 'timing/data': 0.00017138570547103882, 'timing/model': 0.4593838360160589, 'learning_rate/action_model': 6.941732476996616e-05, 'learning_rate/action_query_proj': 6.941732476996616e-05, 'learning_rate/base': 1.735433119249154e-05, 'epoch': 0.23}) +[2026-07-26 22:18:56,703][starVLA.training.train_starvla][INFO] - Step 1910, Loss: {'train/loss': 0.3786575496196747, 'train/grad_norm_pre_clip': 5.600715637207031, 'timing/data': 0.00016828486695885658, 'timing/model': 0.4590579909272492, 'learning_rate/action_model': 6.93892176018182e-05, 'learning_rate/action_query_proj': 6.93892176018182e-05, 'learning_rate/base': 1.734730440045455e-05, 'epoch': 0.23}) +[2026-07-26 22:19:02,221][starVLA.training.train_starvla][INFO] - Step 1911, Loss: {'train/loss': 0.2899116575717926, 'train/grad_norm_pre_clip': 3.680234909057617, 'timing/data': 0.00017153378576040268, 'timing/model': 0.4585464387200773, 'learning_rate/action_model': 6.936110356868254e-05, 'learning_rate/action_query_proj': 6.936110356868254e-05, 'learning_rate/base': 1.7340275892170634e-05, 'epoch': 0.23}) +[2026-07-26 22:19:07,735][starVLA.training.train_starvla][INFO] - Step 1912, Loss: {'train/loss': 0.171117901802063, 'train/grad_norm_pre_clip': 2.7097184658050537, 'timing/data': 0.0001780628226697445, 'timing/model': 0.45796474115923047, 'learning_rate/action_model': 6.933298268165813e-05, 'learning_rate/action_query_proj': 6.933298268165813e-05, 'learning_rate/base': 1.733324567041453e-05, 'epoch': 0.23}) +[2026-07-26 22:19:13,243][starVLA.training.train_starvla][INFO] - Step 1913, Loss: {'train/loss': 0.2929079234600067, 'train/grad_norm_pre_clip': 3.312246561050415, 'timing/data': 0.00017053401097655296, 'timing/model': 0.4573588012717664, 'learning_rate/action_model': 6.930485495184665e-05, 'learning_rate/action_query_proj': 6.930485495184665e-05, 'learning_rate/base': 1.7326213737961662e-05, 'epoch': 0.23}) +[2026-07-26 22:19:18,778][starVLA.training.train_starvla][INFO] - Step 1914, Loss: {'train/loss': 0.37399527430534363, 'train/grad_norm_pre_clip': 3.3708531856536865, 'timing/data': 0.00017561530694365501, 'timing/model': 0.46812936710193753, 'learning_rate/action_model': 6.92767203903525e-05, 'learning_rate/action_query_proj': 6.92767203903525e-05, 'learning_rate/base': 1.7319180097588127e-05, 'epoch': 0.23}) +[2026-07-26 22:19:24,308][starVLA.training.train_starvla][INFO] - Step 1915, Loss: {'train/loss': 0.24236010015010834, 'train/grad_norm_pre_clip': 4.040602207183838, 'timing/data': 0.00017083389684557915, 'timing/model': 0.45855946792289615, 'learning_rate/action_model': 6.924857900828276e-05, 'learning_rate/action_query_proj': 6.924857900828276e-05, 'learning_rate/base': 1.731214475207069e-05, 'epoch': 0.23}) +[2026-07-26 22:19:29,823][starVLA.training.train_starvla][INFO] - Step 1916, Loss: {'train/loss': 0.3016836941242218, 'train/grad_norm_pre_clip': 3.631263256072998, 'timing/data': 0.0001759761944413185, 'timing/model': 0.4571090769022703, 'learning_rate/action_model': 6.922043081674719e-05, 'learning_rate/action_query_proj': 6.922043081674719e-05, 'learning_rate/base': 1.7305107704186798e-05, 'epoch': 0.23}) +[2026-07-26 22:19:35,340][starVLA.training.train_starvla][INFO] - Step 1917, Loss: {'train/loss': 0.2553468644618988, 'train/grad_norm_pre_clip': 2.961193323135376, 'timing/data': 0.00016609719023108482, 'timing/model': 0.45759057719260454, 'learning_rate/action_model': 6.919227582685823e-05, 'learning_rate/action_query_proj': 6.919227582685823e-05, 'learning_rate/base': 1.7298068956714558e-05, 'epoch': 0.23}) +[2026-07-26 22:19:40,850][starVLA.training.train_starvla][INFO] - Step 1918, Loss: {'train/loss': 0.2962087392807007, 'train/grad_norm_pre_clip': 5.24561882019043, 'timing/data': 0.00017898762598633766, 'timing/model': 0.45684413285925984, 'learning_rate/action_model': 6.916411404973108e-05, 'learning_rate/action_query_proj': 6.916411404973108e-05, 'learning_rate/base': 1.729102851243277e-05, 'epoch': 0.23}) +[2026-07-26 22:19:46,625][starVLA.training.train_starvla][INFO] - Step 1919, Loss: {'train/loss': 0.3059765696525574, 'train/grad_norm_pre_clip': 4.707546234130859, 'timing/data': 0.00018970295786857605, 'timing/model': 0.4580026092007756, 'learning_rate/action_model': 6.913594549648352e-05, 'learning_rate/action_query_proj': 6.913594549648352e-05, 'learning_rate/base': 1.728398637412088e-05, 'epoch': 0.23}) +[2026-07-26 22:19:52,142][starVLA.training.train_starvla][INFO] - Step 1920, Loss: {'train/loss': 0.291474312543869, 'train/grad_norm_pre_clip': 4.435419082641602, 'timing/data': 0.00018291734158992767, 'timing/model': 0.4571442580781877, 'learning_rate/action_model': 6.910777017823603e-05, 'learning_rate/action_query_proj': 6.910777017823603e-05, 'learning_rate/base': 1.727694254455901e-05, 'epoch': 0.23}) +[2026-07-26 22:19:57,671][starVLA.training.train_starvla][INFO] - Step 1921, Loss: {'train/loss': 0.3390499949455261, 'train/grad_norm_pre_clip': 4.198409557342529, 'timing/data': 0.00018388405442237854, 'timing/model': 0.45838175993412733, 'learning_rate/action_model': 6.907958810611183e-05, 'learning_rate/action_query_proj': 6.907958810611183e-05, 'learning_rate/base': 1.7269897026527958e-05, 'epoch': 0.23}) +[2026-07-26 22:20:03,189][starVLA.training.train_starvla][INFO] - Step 1922, Loss: {'train/loss': 0.20647978782653809, 'train/grad_norm_pre_clip': 2.6824448108673096, 'timing/data': 0.00017431098967790604, 'timing/model': 0.45782844023779035, 'learning_rate/action_model': 6.905139929123674e-05, 'learning_rate/action_query_proj': 6.905139929123674e-05, 'learning_rate/base': 1.7262849822809185e-05, 'epoch': 0.23}) +[2026-07-26 22:20:08,701][starVLA.training.train_starvla][INFO] - Step 1923, Loss: {'train/loss': 0.20946332812309265, 'train/grad_norm_pre_clip': 2.6589488983154297, 'timing/data': 0.00017248885706067085, 'timing/model': 0.4572517997585237, 'learning_rate/action_model': 6.902320374473927e-05, 'learning_rate/action_query_proj': 6.902320374473927e-05, 'learning_rate/base': 1.7255800936184817e-05, 'epoch': 0.23}) +[2026-07-26 22:20:14,209][starVLA.training.train_starvla][INFO] - Step 1924, Loss: {'train/loss': 0.30039235949516296, 'train/grad_norm_pre_clip': 3.4968037605285645, 'timing/data': 0.00017138803377747536, 'timing/model': 0.45722964964807034, 'learning_rate/action_model': 6.899500147775052e-05, 'learning_rate/action_query_proj': 6.899500147775052e-05, 'learning_rate/base': 1.724875036943763e-05, 'epoch': 0.23}) +[2026-07-26 22:20:19,713][starVLA.training.train_starvla][INFO] - Step 1925, Loss: {'train/loss': 0.3037785291671753, 'train/grad_norm_pre_clip': 3.9285333156585693, 'timing/data': 0.00017157895490527153, 'timing/model': 0.4580325181595981, 'learning_rate/action_model': 6.896679250140435e-05, 'learning_rate/action_query_proj': 6.896679250140435e-05, 'learning_rate/base': 1.7241698125351087e-05, 'epoch': 0.23}) +[2026-07-26 22:20:25,213][starVLA.training.train_starvla][INFO] - Step 1926, Loss: {'train/loss': 0.24217110872268677, 'train/grad_norm_pre_clip': 2.9806134700775146, 'timing/data': 0.00018276134505867958, 'timing/model': 0.4580432749353349, 'learning_rate/action_model': 6.893857682683721e-05, 'learning_rate/action_query_proj': 6.893857682683721e-05, 'learning_rate/base': 1.7234644206709303e-05, 'epoch': 0.23}) +[2026-07-26 22:20:30,697][starVLA.training.train_starvla][INFO] - Step 1927, Loss: {'train/loss': 0.24227824807167053, 'train/grad_norm_pre_clip': 3.128448247909546, 'timing/data': 0.0001739710569381714, 'timing/model': 0.45646446384489536, 'learning_rate/action_model': 6.891035446518817e-05, 'learning_rate/action_query_proj': 6.891035446518817e-05, 'learning_rate/base': 1.7227588616297044e-05, 'epoch': 0.23}) +[2026-07-26 22:20:36,180][starVLA.training.train_starvla][INFO] - Step 1928, Loss: {'train/loss': 0.15159186720848083, 'train/grad_norm_pre_clip': 3.1872146129608154, 'timing/data': 0.00017988961189985275, 'timing/model': 0.45794308092445135, 'learning_rate/action_model': 6.888212542759902e-05, 'learning_rate/action_query_proj': 6.888212542759902e-05, 'learning_rate/base': 1.7220531356899755e-05, 'epoch': 0.23}) +[2026-07-26 22:20:41,667][starVLA.training.train_starvla][INFO] - Step 1929, Loss: {'train/loss': 0.25417113304138184, 'train/grad_norm_pre_clip': 3.047668933868408, 'timing/data': 0.00017045019194483757, 'timing/model': 0.4572082031518221, 'learning_rate/action_model': 6.885388972521412e-05, 'learning_rate/action_query_proj': 6.885388972521412e-05, 'learning_rate/base': 1.721347243130353e-05, 'epoch': 0.23}) +[2026-07-26 22:20:47,168][starVLA.training.train_starvla][INFO] - Step 1930, Loss: {'train/loss': 0.2922622561454773, 'train/grad_norm_pre_clip': 3.1323697566986084, 'timing/data': 0.00017125578597187996, 'timing/model': 0.45747733023017645, 'learning_rate/action_model': 6.882564736918043e-05, 'learning_rate/action_query_proj': 6.882564736918043e-05, 'learning_rate/base': 1.7206411842295108e-05, 'epoch': 0.23}) +[2026-07-26 22:20:52,656][starVLA.training.train_starvla][INFO] - Step 1931, Loss: {'train/loss': 0.32546618580818176, 'train/grad_norm_pre_clip': 4.210874557495117, 'timing/data': 0.00017376383766531944, 'timing/model': 0.4584404369816184, 'learning_rate/action_model': 6.879739837064765e-05, 'learning_rate/action_query_proj': 6.879739837064765e-05, 'learning_rate/base': 1.7199349592661913e-05, 'epoch': 0.23}) +[2026-07-26 22:20:58,148][starVLA.training.train_starvla][INFO] - Step 1932, Loss: {'train/loss': 0.2986326217651367, 'train/grad_norm_pre_clip': 3.6162352561950684, 'timing/data': 0.00016981596127152443, 'timing/model': 0.4688504720106721, 'learning_rate/action_model': 6.876914274076802e-05, 'learning_rate/action_query_proj': 6.876914274076802e-05, 'learning_rate/base': 1.7192285685192006e-05, 'epoch': 0.23}) +[2026-07-26 22:21:03,727][starVLA.training.train_starvla][INFO] - Step 1933, Loss: {'train/loss': 0.29311051964759827, 'train/grad_norm_pre_clip': 3.033763885498047, 'timing/data': 0.00016971677541732788, 'timing/model': 0.4611425530165434, 'learning_rate/action_model': 6.874088049069641e-05, 'learning_rate/action_query_proj': 6.874088049069641e-05, 'learning_rate/base': 1.7185220122674102e-05, 'epoch': 0.23}) +[2026-07-26 22:21:09,215][starVLA.training.train_starvla][INFO] - Step 1934, Loss: {'train/loss': 0.35403910279273987, 'train/grad_norm_pre_clip': 3.8890419006347656, 'timing/data': 0.00017066113650798798, 'timing/model': 0.4568875846453011, 'learning_rate/action_model': 6.871261163159028e-05, 'learning_rate/action_query_proj': 6.871261163159028e-05, 'learning_rate/base': 1.717815290789757e-05, 'epoch': 0.23}) +[2026-07-26 22:21:14,729][starVLA.training.train_starvla][INFO] - Step 1935, Loss: {'train/loss': 0.35355618596076965, 'train/grad_norm_pre_clip': 3.8002758026123047, 'timing/data': 0.00017579365521669388, 'timing/model': 0.4568873173557222, 'learning_rate/action_model': 6.868433617460978e-05, 'learning_rate/action_query_proj': 6.868433617460978e-05, 'learning_rate/base': 1.7171084043652445e-05, 'epoch': 0.23}) +[2026-07-26 22:21:20,239][starVLA.training.train_starvla][INFO] - Step 1936, Loss: {'train/loss': 0.2146676927804947, 'train/grad_norm_pre_clip': 2.7546274662017822, 'timing/data': 0.00017085717990994453, 'timing/model': 0.4579658699221909, 'learning_rate/action_model': 6.865605413091759e-05, 'learning_rate/action_query_proj': 6.865605413091759e-05, 'learning_rate/base': 1.7164013532729398e-05, 'epoch': 0.23}) +[2026-07-26 22:21:25,738][starVLA.training.train_starvla][INFO] - Step 1937, Loss: {'train/loss': 0.26081758737564087, 'train/grad_norm_pre_clip': 3.7431488037109375, 'timing/data': 0.00017214007675647736, 'timing/model': 0.4556393730454147, 'learning_rate/action_model': 6.862776551167898e-05, 'learning_rate/action_query_proj': 6.862776551167898e-05, 'learning_rate/base': 1.7156941377919745e-05, 'epoch': 0.23}) +[2026-07-26 22:21:31,259][starVLA.training.train_starvla][INFO] - Step 1938, Loss: {'train/loss': 0.20339849591255188, 'train/grad_norm_pre_clip': 2.7337911128997803, 'timing/data': 0.00017043296247720718, 'timing/model': 0.458358995616436, 'learning_rate/action_model': 6.859947032806191e-05, 'learning_rate/action_query_proj': 6.859947032806191e-05, 'learning_rate/base': 1.7149867582015477e-05, 'epoch': 0.24}) +[2026-07-26 22:21:36,774][starVLA.training.train_starvla][INFO] - Step 1939, Loss: {'train/loss': 0.26525217294692993, 'train/grad_norm_pre_clip': 3.9064419269561768, 'timing/data': 0.00017063599079847336, 'timing/model': 0.4585207370109856, 'learning_rate/action_model': 6.857116859123683e-05, 'learning_rate/action_query_proj': 6.857116859123683e-05, 'learning_rate/base': 1.7142792147809207e-05, 'epoch': 0.24}) +[2026-07-26 22:21:42,281][starVLA.training.train_starvla][INFO] - Step 1940, Loss: {'train/loss': 0.2510364055633545, 'train/grad_norm_pre_clip': 5.093713283538818, 'timing/data': 0.00016990117728710175, 'timing/model': 0.45648558996617794, 'learning_rate/action_model': 6.854286031237682e-05, 'learning_rate/action_query_proj': 6.854286031237682e-05, 'learning_rate/base': 1.7135715078094205e-05, 'epoch': 0.24}) +[2026-07-26 22:21:47,793][starVLA.training.train_starvla][INFO] - Step 1941, Loss: {'train/loss': 0.25761303305625916, 'train/grad_norm_pre_clip': 4.494205951690674, 'timing/data': 0.0001719328574836254, 'timing/model': 0.45739370584487915, 'learning_rate/action_model': 6.851454550265756e-05, 'learning_rate/action_query_proj': 6.851454550265756e-05, 'learning_rate/base': 1.712863637566439e-05, 'epoch': 0.24}) +[2026-07-26 22:21:53,308][starVLA.training.train_starvla][INFO] - Step 1942, Loss: {'train/loss': 0.1935195028781891, 'train/grad_norm_pre_clip': 3.189445734024048, 'timing/data': 0.0001720110885798931, 'timing/model': 0.4582655322737992, 'learning_rate/action_model': 6.848622417325725e-05, 'learning_rate/action_query_proj': 6.848622417325725e-05, 'learning_rate/base': 1.7121556043314312e-05, 'epoch': 0.24}) +[2026-07-26 22:21:58,853][starVLA.training.train_starvla][INFO] - Step 1943, Loss: {'train/loss': 0.17660020291805267, 'train/grad_norm_pre_clip': 3.354814291000366, 'timing/data': 0.0001730206422507763, 'timing/model': 0.45975155802443624, 'learning_rate/action_model': 6.845789633535677e-05, 'learning_rate/action_query_proj': 6.845789633535677e-05, 'learning_rate/base': 1.711447408383919e-05, 'epoch': 0.24}) +[2026-07-26 22:22:04,479][starVLA.training.train_starvla][INFO] - Step 1944, Loss: {'train/loss': 0.151957169175148, 'train/grad_norm_pre_clip': 2.384550094604492, 'timing/data': 0.00017182808369398117, 'timing/model': 0.4610186517238617, 'learning_rate/action_model': 6.842956200013942e-05, 'learning_rate/action_query_proj': 6.842956200013942e-05, 'learning_rate/base': 1.7107390500034856e-05, 'epoch': 0.24}) +[2026-07-26 22:22:09,971][starVLA.training.train_starvla][INFO] - Step 1945, Loss: {'train/loss': 0.2399635910987854, 'train/grad_norm_pre_clip': 2.6726794242858887, 'timing/data': 0.00016939174383878708, 'timing/model': 0.45867075491696596, 'learning_rate/action_model': 6.840122117879121e-05, 'learning_rate/action_query_proj': 6.840122117879121e-05, 'learning_rate/base': 1.7100305294697802e-05, 'epoch': 0.24}) +[2026-07-26 22:22:15,460][starVLA.training.train_starvla][INFO] - Step 1946, Loss: {'train/loss': 0.3617386221885681, 'train/grad_norm_pre_clip': 3.915461778640747, 'timing/data': 0.00017360085621476173, 'timing/model': 0.4607109879143536, 'learning_rate/action_model': 6.837287388250061e-05, 'learning_rate/action_query_proj': 6.837287388250061e-05, 'learning_rate/base': 1.7093218470625153e-05, 'epoch': 0.24}) +[2026-07-26 22:22:20,953][starVLA.training.train_starvla][INFO] - Step 1947, Loss: {'train/loss': 0.2359488308429718, 'train/grad_norm_pre_clip': 3.9949374198913574, 'timing/data': 0.00017250282689929008, 'timing/model': 0.4606877928599715, 'learning_rate/action_model': 6.834452012245872e-05, 'learning_rate/action_query_proj': 6.834452012245872e-05, 'learning_rate/base': 1.708613003061468e-05, 'epoch': 0.24}) +[2026-07-26 22:22:26,448][starVLA.training.train_starvla][INFO] - Step 1948, Loss: {'train/loss': 0.42035871744155884, 'train/grad_norm_pre_clip': 5.143797397613525, 'timing/data': 0.000177810899913311, 'timing/model': 0.45914672315120697, 'learning_rate/action_model': 6.831615990985912e-05, 'learning_rate/action_query_proj': 6.831615990985912e-05, 'learning_rate/base': 1.707903997746478e-05, 'epoch': 0.24}) +[2026-07-26 22:22:31,947][starVLA.training.train_starvla][INFO] - Step 1949, Loss: {'train/loss': 0.2063252180814743, 'train/grad_norm_pre_clip': 3.39819598197937, 'timing/data': 0.00016961293295025826, 'timing/model': 0.45966978557407856, 'learning_rate/action_model': 6.828779325589796e-05, 'learning_rate/action_query_proj': 6.828779325589796e-05, 'learning_rate/base': 1.707194831397449e-05, 'epoch': 0.24}) +[2026-07-26 22:22:37,450][starVLA.training.train_starvla][INFO] - Step 1950, Loss: {'train/loss': 0.19825978577136993, 'train/grad_norm_pre_clip': 2.9600932598114014, 'timing/data': 0.00017165299504995346, 'timing/model': 0.4589049923233688, 'learning_rate/action_model': 6.8259420171774e-05, 'learning_rate/action_query_proj': 6.8259420171774e-05, 'learning_rate/base': 1.70648550429435e-05, 'epoch': 0.24}) +[2026-07-26 22:22:42,963][starVLA.training.train_starvla][INFO] - Step 1951, Loss: {'train/loss': 0.29795002937316895, 'train/grad_norm_pre_clip': 3.3861477375030518, 'timing/data': 0.00016973307356238365, 'timing/model': 0.46121223783120513, 'learning_rate/action_model': 6.823104066868843e-05, 'learning_rate/action_query_proj': 6.823104066868843e-05, 'learning_rate/base': 1.7057760167172108e-05, 'epoch': 0.24}) +[2026-07-26 22:22:48,476][starVLA.training.train_starvla][INFO] - Step 1952, Loss: {'train/loss': 0.18528017401695251, 'train/grad_norm_pre_clip': 3.4000749588012695, 'timing/data': 0.00017439620569348335, 'timing/model': 0.459747230168432, 'learning_rate/action_model': 6.820265475784509e-05, 'learning_rate/action_query_proj': 6.820265475784509e-05, 'learning_rate/base': 1.7050663689461273e-05, 'epoch': 0.24}) +[2026-07-26 22:22:53,979][starVLA.training.train_starvla][INFO] - Step 1953, Loss: {'train/loss': 0.28103524446487427, 'train/grad_norm_pre_clip': 3.197748899459839, 'timing/data': 0.00016966182738542557, 'timing/model': 0.45949306804686785, 'learning_rate/action_model': 6.817426245045022e-05, 'learning_rate/action_query_proj': 6.817426245045022e-05, 'learning_rate/base': 1.7043565612612556e-05, 'epoch': 0.24}) +[2026-07-26 22:22:59,476][starVLA.training.train_starvla][INFO] - Step 1954, Loss: {'train/loss': 0.32921069860458374, 'train/grad_norm_pre_clip': 3.340160846710205, 'timing/data': 0.0001818351447582245, 'timing/model': 0.4578802133910358, 'learning_rate/action_model': 6.814586375771271e-05, 'learning_rate/action_query_proj': 6.814586375771271e-05, 'learning_rate/base': 1.7036465939428178e-05, 'epoch': 0.24}) +[2026-07-26 22:23:04,979][starVLA.training.train_starvla][INFO] - Step 1955, Loss: {'train/loss': 0.3014812767505646, 'train/grad_norm_pre_clip': 5.051088809967041, 'timing/data': 0.00017589982599020004, 'timing/model': 0.45981879299506545, 'learning_rate/action_model': 6.811745869084388e-05, 'learning_rate/action_query_proj': 6.811745869084388e-05, 'learning_rate/base': 1.702936467271097e-05, 'epoch': 0.24}) +[2026-07-26 22:23:10,482][starVLA.training.train_starvla][INFO] - Step 1956, Loss: {'train/loss': 0.15195655822753906, 'train/grad_norm_pre_clip': 2.6049373149871826, 'timing/data': 0.0001738937571644783, 'timing/model': 0.4600578648969531, 'learning_rate/action_model': 6.808904726105762e-05, 'learning_rate/action_query_proj': 6.808904726105762e-05, 'learning_rate/base': 1.7022261815264405e-05, 'epoch': 0.24}) +[2026-07-26 22:23:15,989][starVLA.training.train_starvla][INFO] - Step 1957, Loss: {'train/loss': 0.35795819759368896, 'train/grad_norm_pre_clip': 4.26124382019043, 'timing/data': 0.00017849495634436607, 'timing/model': 0.45755851408466697, 'learning_rate/action_model': 6.806062947957028e-05, 'learning_rate/action_query_proj': 6.806062947957028e-05, 'learning_rate/base': 1.701515736989257e-05, 'epoch': 0.24}) +[2026-07-26 22:23:21,485][starVLA.training.train_starvla][INFO] - Step 1958, Loss: {'train/loss': 0.21629387140274048, 'train/grad_norm_pre_clip': 4.275406360626221, 'timing/data': 0.00016949884593486786, 'timing/model': 0.4616829021833837, 'learning_rate/action_model': 6.803220535760079e-05, 'learning_rate/action_query_proj': 6.803220535760079e-05, 'learning_rate/base': 1.7008051339400196e-05, 'epoch': 0.24}) +[2026-07-26 22:23:27,001][starVLA.training.train_starvla][INFO] - Step 1959, Loss: {'train/loss': 0.2959035038948059, 'train/grad_norm_pre_clip': 3.3322649002075195, 'timing/data': 0.00016534607857465744, 'timing/model': 0.46004797937348485, 'learning_rate/action_model': 6.800377490637052e-05, 'learning_rate/action_query_proj': 6.800377490637052e-05, 'learning_rate/base': 1.700094372659263e-05, 'epoch': 0.24}) +[2026-07-26 22:23:32,505][starVLA.training.train_starvla][INFO] - Step 1960, Loss: {'train/loss': 0.2610257863998413, 'train/grad_norm_pre_clip': 3.6824398040771484, 'timing/data': 0.0001726187765598297, 'timing/model': 0.46059456281363964, 'learning_rate/action_model': 6.797533813710336e-05, 'learning_rate/action_query_proj': 6.797533813710336e-05, 'learning_rate/base': 1.699383453427584e-05, 'epoch': 0.24}) +[2026-07-26 22:23:38,001][starVLA.training.train_starvla][INFO] - Step 1961, Loss: {'train/loss': 0.2236250787973404, 'train/grad_norm_pre_clip': 3.7729697227478027, 'timing/data': 0.00017579039558768272, 'timing/model': 0.46040017111226916, 'learning_rate/action_model': 6.794689506102572e-05, 'learning_rate/action_query_proj': 6.794689506102572e-05, 'learning_rate/base': 1.698672376525643e-05, 'epoch': 0.24}) +[2026-07-26 22:23:43,498][starVLA.training.train_starvla][INFO] - Step 1962, Loss: {'train/loss': 0.17200317978858948, 'train/grad_norm_pre_clip': 2.8251912593841553, 'timing/data': 0.00017988774925470352, 'timing/model': 0.45773688703775406, 'learning_rate/action_model': 6.791844568936644e-05, 'learning_rate/action_query_proj': 6.791844568936644e-05, 'learning_rate/base': 1.697961142234161e-05, 'epoch': 0.24}) +[2026-07-26 22:23:48,998][starVLA.training.train_starvla][INFO] - Step 1963, Loss: {'train/loss': 0.1748088300228119, 'train/grad_norm_pre_clip': 3.316396713256836, 'timing/data': 0.0001686951145529747, 'timing/model': 0.46136566903442144, 'learning_rate/action_model': 6.788999003335692e-05, 'learning_rate/action_query_proj': 6.788999003335692e-05, 'learning_rate/base': 1.697249750833923e-05, 'epoch': 0.24}) +[2026-07-26 22:23:54,499][starVLA.training.train_starvla][INFO] - Step 1964, Loss: {'train/loss': 0.17732225358486176, 'train/grad_norm_pre_clip': 2.9081356525421143, 'timing/data': 0.00017126509919762611, 'timing/model': 0.4615599578246474, 'learning_rate/action_model': 6.786152810423099e-05, 'learning_rate/action_query_proj': 6.786152810423099e-05, 'learning_rate/base': 1.6965382026057748e-05, 'epoch': 0.24}) +[2026-07-26 22:24:00,008][starVLA.training.train_starvla][INFO] - Step 1965, Loss: {'train/loss': 0.25940248370170593, 'train/grad_norm_pre_clip': 4.571630477905273, 'timing/data': 0.0001772986724972725, 'timing/model': 0.47022773372009397, 'learning_rate/action_model': 6.783305991322493e-05, 'learning_rate/action_query_proj': 6.783305991322493e-05, 'learning_rate/base': 1.6958264978306233e-05, 'epoch': 0.24}) +[2026-07-26 22:24:05,551][starVLA.training.train_starvla][INFO] - Step 1966, Loss: {'train/loss': 0.32240724563598633, 'train/grad_norm_pre_clip': 4.701593399047852, 'timing/data': 0.0001771613024175167, 'timing/model': 0.4580566198565066, 'learning_rate/action_model': 6.780458547157761e-05, 'learning_rate/action_query_proj': 6.780458547157761e-05, 'learning_rate/base': 1.6951146367894402e-05, 'epoch': 0.24}) +[2026-07-26 22:24:11,379][starVLA.training.train_starvla][INFO] - Step 1967, Loss: {'train/loss': 0.1715661734342575, 'train/grad_norm_pre_clip': 3.2020907402038574, 'timing/data': 0.00018279394134879112, 'timing/model': 0.4574502231553197, 'learning_rate/action_model': 6.77761047905302e-05, 'learning_rate/action_query_proj': 6.77761047905302e-05, 'learning_rate/base': 1.694402619763255e-05, 'epoch': 0.24}) +[2026-07-26 22:24:16,922][starVLA.training.train_starvla][INFO] - Step 1968, Loss: {'train/loss': 0.33432459831237793, 'train/grad_norm_pre_clip': 3.915597438812256, 'timing/data': 0.00017449399456381798, 'timing/model': 0.4570733900181949, 'learning_rate/action_model': 6.774761788132648e-05, 'learning_rate/action_query_proj': 6.774761788132648e-05, 'learning_rate/base': 1.693690447033162e-05, 'epoch': 0.24}) +[2026-07-26 22:24:22,467][starVLA.training.train_starvla][INFO] - Step 1969, Loss: {'train/loss': 0.3357677459716797, 'train/grad_norm_pre_clip': 4.939390182495117, 'timing/data': 0.00017143413424491882, 'timing/model': 0.46046108938753605, 'learning_rate/action_model': 6.771912475521262e-05, 'learning_rate/action_query_proj': 6.771912475521262e-05, 'learning_rate/base': 1.6929781188803156e-05, 'epoch': 0.24}) +[2026-07-26 22:24:28,015][starVLA.training.train_starvla][INFO] - Step 1970, Loss: {'train/loss': 0.2441784143447876, 'train/grad_norm_pre_clip': 3.140249729156494, 'timing/data': 0.00017690705135464668, 'timing/model': 0.4608757686801255, 'learning_rate/action_model': 6.769062542343724e-05, 'learning_rate/action_query_proj': 6.769062542343724e-05, 'learning_rate/base': 1.692265635585931e-05, 'epoch': 0.24}) +[2026-07-26 22:24:33,544][starVLA.training.train_starvla][INFO] - Step 1971, Loss: {'train/loss': 0.22382982075214386, 'train/grad_norm_pre_clip': 3.4124467372894287, 'timing/data': 0.000173238106071949, 'timing/model': 0.4573357254266739, 'learning_rate/action_model': 6.766211989725145e-05, 'learning_rate/action_query_proj': 6.766211989725145e-05, 'learning_rate/base': 1.691552997431286e-05, 'epoch': 0.24}) +[2026-07-26 22:24:39,080][starVLA.training.train_starvla][INFO] - Step 1972, Loss: {'train/loss': 0.3257174491882324, 'train/grad_norm_pre_clip': 3.4929115772247314, 'timing/data': 0.00017488515004515648, 'timing/model': 0.45779933081939816, 'learning_rate/action_model': 6.763360818790875e-05, 'learning_rate/action_query_proj': 6.763360818790875e-05, 'learning_rate/base': 1.6908402046977187e-05, 'epoch': 0.24}) +[2026-07-26 22:24:44,640][starVLA.training.train_starvla][INFO] - Step 1973, Loss: {'train/loss': 0.2208874672651291, 'train/grad_norm_pre_clip': 2.8488404750823975, 'timing/data': 0.00018146494403481483, 'timing/model': 0.4602274149656296, 'learning_rate/action_model': 6.760509030666513e-05, 'learning_rate/action_query_proj': 6.760509030666513e-05, 'learning_rate/base': 1.6901272576666282e-05, 'epoch': 0.24}) +[2026-07-26 22:24:50,202][starVLA.training.train_starvla][INFO] - Step 1974, Loss: {'train/loss': 0.16451244056224823, 'train/grad_norm_pre_clip': 3.238215684890747, 'timing/data': 0.0001694648526608944, 'timing/model': 0.46035989420488477, 'learning_rate/action_model': 6.757656626477898e-05, 'learning_rate/action_query_proj': 6.757656626477898e-05, 'learning_rate/base': 1.6894141566194746e-05, 'epoch': 0.24}) +[2026-07-26 22:24:55,802][starVLA.training.train_starvla][INFO] - Step 1975, Loss: {'train/loss': 0.2992594540119171, 'train/grad_norm_pre_clip': 3.790863275527954, 'timing/data': 0.00017284508794546127, 'timing/model': 0.46008534263819456, 'learning_rate/action_model': 6.754803607351117e-05, 'learning_rate/action_query_proj': 6.754803607351117e-05, 'learning_rate/base': 1.6887009018377793e-05, 'epoch': 0.24}) +[2026-07-26 22:25:01,355][starVLA.training.train_starvla][INFO] - Step 1976, Loss: {'train/loss': 0.41856569051742554, 'train/grad_norm_pre_clip': 6.149964332580566, 'timing/data': 0.000169502105563879, 'timing/model': 0.4594118380919099, 'learning_rate/action_model': 6.751949974412496e-05, 'learning_rate/action_query_proj': 6.751949974412496e-05, 'learning_rate/base': 1.687987493603124e-05, 'epoch': 0.24}) +[2026-07-26 22:25:07,096][starVLA.training.train_starvla][INFO] - Step 1977, Loss: {'train/loss': 0.2698269188404083, 'train/grad_norm_pre_clip': 3.145839214324951, 'timing/data': 0.00016695400699973106, 'timing/model': 0.4606968490406871, 'learning_rate/action_model': 6.749095728788602e-05, 'learning_rate/action_query_proj': 6.749095728788602e-05, 'learning_rate/base': 1.6872739321971506e-05, 'epoch': 0.24}) +[2026-07-26 22:25:12,622][starVLA.training.train_starvla][INFO] - Step 1978, Loss: {'train/loss': 0.22689701616764069, 'train/grad_norm_pre_clip': 3.9064786434173584, 'timing/data': 0.00018317624926567078, 'timing/model': 0.46189907705411315, 'learning_rate/action_model': 6.746240871606247e-05, 'learning_rate/action_query_proj': 6.746240871606247e-05, 'learning_rate/base': 1.6865602179015618e-05, 'epoch': 0.24}) +[2026-07-26 22:25:18,118][starVLA.training.train_starvla][INFO] - Step 1979, Loss: {'train/loss': 0.13973736763000488, 'train/grad_norm_pre_clip': 2.944647789001465, 'timing/data': 0.0001691877841949463, 'timing/model': 0.46070246724411845, 'learning_rate/action_model': 6.743385403992484e-05, 'learning_rate/action_query_proj': 6.743385403992484e-05, 'learning_rate/base': 1.685846350998121e-05, 'epoch': 0.24}) +[2026-07-26 22:25:23,619][starVLA.training.train_starvla][INFO] - Step 1980, Loss: {'train/loss': 0.3042513132095337, 'train/grad_norm_pre_clip': 2.615018606185913, 'timing/data': 0.0001679128035902977, 'timing/model': 0.4603257109411061, 'learning_rate/action_model': 6.740529327074605e-05, 'learning_rate/action_query_proj': 6.740529327074605e-05, 'learning_rate/base': 1.6851323317686512e-05, 'epoch': 0.24}) +[2026-07-26 22:25:29,122][starVLA.training.train_starvla][INFO] - Step 1981, Loss: {'train/loss': 0.30181026458740234, 'train/grad_norm_pre_clip': 4.407649040222168, 'timing/data': 0.00017153611406683922, 'timing/model': 0.4586782078258693, 'learning_rate/action_model': 6.737672641980147e-05, 'learning_rate/action_query_proj': 6.737672641980147e-05, 'learning_rate/base': 1.6844181604950367e-05, 'epoch': 0.24}) +[2026-07-26 22:25:34,628][starVLA.training.train_starvla][INFO] - Step 1982, Loss: {'train/loss': 0.4403478801250458, 'train/grad_norm_pre_clip': 3.979440450668335, 'timing/data': 0.0001755361445248127, 'timing/model': 0.4603947694413364, 'learning_rate/action_model': 6.734815349836882e-05, 'learning_rate/action_query_proj': 6.734815349836882e-05, 'learning_rate/base': 1.6837038374592205e-05, 'epoch': 0.24}) +[2026-07-26 22:25:40,120][starVLA.training.train_starvla][INFO] - Step 1983, Loss: {'train/loss': 0.3409481942653656, 'train/grad_norm_pre_clip': 5.290349960327148, 'timing/data': 0.0001716366969048977, 'timing/model': 0.4596745688468218, 'learning_rate/action_model': 6.731957451772823e-05, 'learning_rate/action_query_proj': 6.731957451772823e-05, 'learning_rate/base': 1.6829893629432057e-05, 'epoch': 0.24}) +[2026-07-26 22:25:45,651][starVLA.training.train_starvla][INFO] - Step 1984, Loss: {'train/loss': 0.29678329825401306, 'train/grad_norm_pre_clip': 3.6913506984710693, 'timing/data': 0.00017224997282028198, 'timing/model': 0.45662081707268953, 'learning_rate/action_model': 6.729098948916221e-05, 'learning_rate/action_query_proj': 6.729098948916221e-05, 'learning_rate/base': 1.6822747372290553e-05, 'epoch': 0.24}) +[2026-07-26 22:25:51,190][starVLA.training.train_starvla][INFO] - Step 1985, Loss: {'train/loss': 0.29360097646713257, 'train/grad_norm_pre_clip': 3.723140001296997, 'timing/data': 0.00018005073070526123, 'timing/model': 0.4567464222200215, 'learning_rate/action_model': 6.726239842395571e-05, 'learning_rate/action_query_proj': 6.726239842395571e-05, 'learning_rate/base': 1.681559960598893e-05, 'epoch': 0.24}) +[2026-07-26 22:25:56,728][starVLA.training.train_starvla][INFO] - Step 1986, Loss: {'train/loss': 0.33626213669776917, 'train/grad_norm_pre_clip': 4.160166263580322, 'timing/data': 0.0001848749816417694, 'timing/model': 0.4584607547149062, 'learning_rate/action_model': 6.723380133339605e-05, 'learning_rate/action_query_proj': 6.723380133339605e-05, 'learning_rate/base': 1.6808450333349013e-05, 'epoch': 0.24}) +[2026-07-26 22:26:02,268][starVLA.training.train_starvla][INFO] - Step 1987, Loss: {'train/loss': 0.17040501534938812, 'train/grad_norm_pre_clip': 2.674884796142578, 'timing/data': 0.00018437020480632782, 'timing/model': 0.45709130726754665, 'learning_rate/action_model': 6.720519822877286e-05, 'learning_rate/action_query_proj': 6.720519822877286e-05, 'learning_rate/base': 1.6801299557193216e-05, 'epoch': 0.24}) +[2026-07-26 22:26:07,800][starVLA.training.train_starvla][INFO] - Step 1988, Loss: {'train/loss': 0.28768718242645264, 'train/grad_norm_pre_clip': 3.5062038898468018, 'timing/data': 0.00019800709560513496, 'timing/model': 0.458494592923671, 'learning_rate/action_model': 6.717658912137824e-05, 'learning_rate/action_query_proj': 6.717658912137824e-05, 'learning_rate/base': 1.679414728034456e-05, 'epoch': 0.24}) +[2026-07-26 22:26:13,542][starVLA.training.train_starvla][INFO] - Step 1989, Loss: {'train/loss': 0.27572834491729736, 'train/grad_norm_pre_clip': 4.203859806060791, 'timing/data': 0.0001732371747493744, 'timing/model': 0.6864682612940669, 'learning_rate/action_model': 6.714797402250656e-05, 'learning_rate/action_query_proj': 6.714797402250656e-05, 'learning_rate/base': 1.678699350562664e-05, 'epoch': 0.24}) +[2026-07-26 22:26:19,067][starVLA.training.train_starvla][INFO] - Step 1990, Loss: {'train/loss': 0.36169975996017456, 'train/grad_norm_pre_clip': 4.16705846786499, 'timing/data': 0.00017825327813625336, 'timing/model': 0.45842663384974003, 'learning_rate/action_model': 6.711935294345463e-05, 'learning_rate/action_query_proj': 6.711935294345463e-05, 'learning_rate/base': 1.6779838235863658e-05, 'epoch': 0.24}) +[2026-07-26 22:26:24,840][starVLA.training.train_starvla][INFO] - Step 1991, Loss: {'train/loss': 0.22277790307998657, 'train/grad_norm_pre_clip': 2.707141399383545, 'timing/data': 0.0001669628545641899, 'timing/model': 0.4568847129121423, 'learning_rate/action_model': 6.709072589552163e-05, 'learning_rate/action_query_proj': 6.709072589552163e-05, 'learning_rate/base': 1.6772681473880406e-05, 'epoch': 0.24}) +[2026-07-26 22:26:30,386][starVLA.training.train_starvla][INFO] - Step 1992, Loss: {'train/loss': 0.33723288774490356, 'train/grad_norm_pre_clip': 5.165767669677734, 'timing/data': 0.00017298897728323936, 'timing/model': 0.4575071493163705, 'learning_rate/action_model': 6.7062092890009e-05, 'learning_rate/action_query_proj': 6.7062092890009e-05, 'learning_rate/base': 1.676552322250225e-05, 'epoch': 0.24}) +[2026-07-26 22:26:35,878][starVLA.training.train_starvla][INFO] - Step 1993, Loss: {'train/loss': 0.3279636800289154, 'train/grad_norm_pre_clip': 3.3598480224609375, 'timing/data': 0.0001781783066689968, 'timing/model': 0.4572805133648217, 'learning_rate/action_model': 6.703345393822066e-05, 'learning_rate/action_query_proj': 6.703345393822066e-05, 'learning_rate/base': 1.6758363484555166e-05, 'epoch': 0.24}) +[2026-07-26 22:26:41,368][starVLA.training.train_starvla][INFO] - Step 1994, Loss: {'train/loss': 0.31846776604652405, 'train/grad_norm_pre_clip': 4.1658735275268555, 'timing/data': 0.0001777438446879387, 'timing/model': 0.4579582028090954, 'learning_rate/action_model': 6.700480905146278e-05, 'learning_rate/action_query_proj': 6.700480905146278e-05, 'learning_rate/base': 1.6751202262865696e-05, 'epoch': 0.24}) +[2026-07-26 22:26:46,856][starVLA.training.train_starvla][INFO] - Step 1995, Loss: {'train/loss': 0.35411015152931213, 'train/grad_norm_pre_clip': 3.2373011112213135, 'timing/data': 0.0001724380999803543, 'timing/model': 0.4572908226400614, 'learning_rate/action_model': 6.697615824104392e-05, 'learning_rate/action_query_proj': 6.697615824104392e-05, 'learning_rate/base': 1.674403956026098e-05, 'epoch': 0.24}) +[2026-07-26 22:26:52,600][starVLA.training.train_starvla][INFO] - Step 1996, Loss: {'train/loss': 0.2961892783641815, 'train/grad_norm_pre_clip': 3.8033807277679443, 'timing/data': 0.00017637480050325394, 'timing/model': 0.46138605009764433, 'learning_rate/action_model': 6.694750151827497e-05, 'learning_rate/action_query_proj': 6.694750151827497e-05, 'learning_rate/base': 1.6736875379568742e-05, 'epoch': 0.24}) +[2026-07-26 22:26:58,159][starVLA.training.train_starvla][INFO] - Step 1997, Loss: {'train/loss': 0.32111284136772156, 'train/grad_norm_pre_clip': 3.6138012409210205, 'timing/data': 0.00017524417489767075, 'timing/model': 0.46090715704485774, 'learning_rate/action_model': 6.691883889446912e-05, 'learning_rate/action_query_proj': 6.691883889446912e-05, 'learning_rate/base': 1.672970972361728e-05, 'epoch': 0.24}) +[2026-07-26 22:27:03,835][starVLA.training.train_starvla][INFO] - Step 1998, Loss: {'train/loss': 0.2151278853416443, 'train/grad_norm_pre_clip': 3.366741180419922, 'timing/data': 0.00017703697085380554, 'timing/model': 0.45863912673667073, 'learning_rate/action_model': 6.689017038094197e-05, 'learning_rate/action_query_proj': 6.689017038094197e-05, 'learning_rate/base': 1.6722542595235493e-05, 'epoch': 0.24}) +[2026-07-26 22:27:09,454][starVLA.training.train_starvla][INFO] - Step 1999, Loss: {'train/loss': 0.1825757622718811, 'train/grad_norm_pre_clip': 2.993551731109619, 'timing/data': 0.00017257872968912125, 'timing/model': 0.46845301473513246, 'learning_rate/action_model': 6.686149598901136e-05, 'learning_rate/action_query_proj': 6.686149598901136e-05, 'learning_rate/base': 1.671537399725284e-05, 'epoch': 0.24}) +[2026-07-26 22:27:15,001][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2000 +[2026-07-26 22:27:15,002][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2000 +[2026-07-26 22:27:15,003][starVLA.training.train_starvla][INFO] - Step 2000, Loss: {'train/loss': 0.3552701473236084, 'train/grad_norm_pre_clip': 3.7772088050842285, 'timing/data': 0.00017000827938318253, 'timing/model': 0.46754340501502156, 'learning_rate/action_model': 6.683281572999748e-05, 'learning_rate/action_query_proj': 6.683281572999748e-05, 'learning_rate/base': 1.670820393249937e-05, 'epoch': 0.24}) +[2026-07-26 22:27:15,006][accelerate.accelerator][INFO] - Saving current state to /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state +[2026-07-26 22:27:15,006][accelerate.accelerator][INFO] - Saving DeepSpeed Model and Optimizer +[2026-07-26 22:28:00,939][accelerate.accelerator][INFO] - DeepSpeed Model and Optimizer saved to output dir /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state/pytorch_model +[2026-07-26 22:28:00,940][accelerate.checkpointing][INFO] - Sampler state for dataloader 0 saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state/sampler.bin +[2026-07-26 22:28:00,943][accelerate.checkpointing][INFO] - Random states saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state/random_states_0.pkl +[2026-07-26 22:28:41,955][starVLA.training.rl_games.checkpoint_sync][INFO] - HF checkpoint sync disabled; skipping upload for step 2000 +[2026-07-26 22:28:41,956][starVLA.training.train_starvla][INFO] - 📊 Saving accessed configuration... +[2026-07-26 22:28:41,970][starVLA.training.train_starvla][INFO] - ✅ Configuration files saved +[2026-07-26 22:28:47,701][starVLA.training.train_starvla][INFO] - Step 2001, Loss: {'train/loss': 0.18349874019622803, 'train/grad_norm_pre_clip': 3.681549310684204, 'timing/data': 0.00018559489399194717, 'timing/model': 0.46375015331432223, 'learning_rate/action_model': 6.680412961522287e-05, 'learning_rate/action_query_proj': 6.680412961522287e-05, 'learning_rate/base': 1.6701032403805718e-05, 'epoch': 0.24}) +[2026-07-26 22:28:53,480][starVLA.training.train_starvla][INFO] - Step 2002, Loss: {'train/loss': 0.2826516926288605, 'train/grad_norm_pre_clip': 2.7734766006469727, 'timing/data': 0.00017737364396452904, 'timing/model': 0.46360240038484335, 'learning_rate/action_model': 6.677543765601234e-05, 'learning_rate/action_query_proj': 6.677543765601234e-05, 'learning_rate/base': 1.6693859414003085e-05, 'epoch': 0.24}) +[2026-07-26 22:28:59,177][starVLA.training.train_starvla][INFO] - Step 2003, Loss: {'train/loss': 0.3929942846298218, 'train/grad_norm_pre_clip': 3.8140902519226074, 'timing/data': 0.00017857691273093224, 'timing/model': 0.461831274908036, 'learning_rate/action_model': 6.6746739863693e-05, 'learning_rate/action_query_proj': 6.6746739863693e-05, 'learning_rate/base': 1.668668496592325e-05, 'epoch': 0.24}) +[2026-07-26 22:29:04,919][starVLA.training.train_starvla][INFO] - Step 2004, Loss: {'train/loss': 0.28445202112197876, 'train/grad_norm_pre_clip': 2.978177547454834, 'timing/data': 0.00016818195581436157, 'timing/model': 0.46662568394094706, 'learning_rate/action_model': 6.671803624959436e-05, 'learning_rate/action_query_proj': 6.671803624959436e-05, 'learning_rate/base': 1.667950906239859e-05, 'epoch': 0.24}) +[2026-07-26 22:29:10,598][starVLA.training.train_starvla][INFO] - Step 2005, Loss: {'train/loss': 0.25135093927383423, 'train/grad_norm_pre_clip': 4.871317386627197, 'timing/data': 0.00017014099285006523, 'timing/model': 0.47343812184408307, 'learning_rate/action_model': 6.668932682504805e-05, 'learning_rate/action_query_proj': 6.668932682504805e-05, 'learning_rate/base': 1.6672331706262012e-05, 'epoch': 0.24}) +[2026-07-26 22:29:16,340][starVLA.training.train_starvla][INFO] - Step 2006, Loss: {'train/loss': 0.2046118527650833, 'train/grad_norm_pre_clip': 2.563415288925171, 'timing/data': 0.00018245680257678032, 'timing/model': 0.4723752811551094, 'learning_rate/action_model': 6.666061160138816e-05, 'learning_rate/action_query_proj': 6.666061160138816e-05, 'learning_rate/base': 1.666515290034704e-05, 'epoch': 0.24}) +[2026-07-26 22:29:22,063][starVLA.training.train_starvla][INFO] - Step 2007, Loss: {'train/loss': 0.1898041069507599, 'train/grad_norm_pre_clip': 2.9674906730651855, 'timing/data': 0.00018022069707512856, 'timing/model': 0.47212624410167336, 'learning_rate/action_model': 6.663189058995098e-05, 'learning_rate/action_query_proj': 6.663189058995098e-05, 'learning_rate/base': 1.6657972647487745e-05, 'epoch': 0.24}) +[2026-07-26 22:29:27,822][starVLA.training.train_starvla][INFO] - Step 2008, Loss: {'train/loss': 0.2289276123046875, 'train/grad_norm_pre_clip': 3.4914495944976807, 'timing/data': 0.00017217593267560005, 'timing/model': 0.47122605983167887, 'learning_rate/action_model': 6.66031638020751e-05, 'learning_rate/action_query_proj': 6.66031638020751e-05, 'learning_rate/base': 1.6650790950518777e-05, 'epoch': 0.24}) +[2026-07-26 22:29:33,580][starVLA.training.train_starvla][INFO] - Step 2009, Loss: {'train/loss': 0.21882663667201996, 'train/grad_norm_pre_clip': 2.467531681060791, 'timing/data': 0.0001692669466137886, 'timing/model': 0.47248759819194674, 'learning_rate/action_model': 6.657443124910146e-05, 'learning_rate/action_query_proj': 6.657443124910146e-05, 'learning_rate/base': 1.6643607812275364e-05, 'epoch': 0.24}) +[2026-07-26 22:29:39,354][starVLA.training.train_starvla][INFO] - Step 2010, Loss: {'train/loss': 0.18568846583366394, 'train/grad_norm_pre_clip': 2.599868059158325, 'timing/data': 0.00017319200560450554, 'timing/model': 0.4718188280239701, 'learning_rate/action_model': 6.654569294237317e-05, 'learning_rate/action_query_proj': 6.654569294237317e-05, 'learning_rate/base': 1.6636423235593292e-05, 'epoch': 0.24}) +[2026-07-26 22:29:45,110][starVLA.training.train_starvla][INFO] - Step 2011, Loss: {'train/loss': 0.2880740463733673, 'train/grad_norm_pre_clip': 3.216049909591675, 'timing/data': 0.0001943390816450119, 'timing/model': 0.48079535411670804, 'learning_rate/action_model': 6.651694889323564e-05, 'learning_rate/action_query_proj': 6.651694889323564e-05, 'learning_rate/base': 1.662923722330891e-05, 'epoch': 0.24}) +[2026-07-26 22:29:50,874][starVLA.training.train_starvla][INFO] - Step 2012, Loss: {'train/loss': 0.25219953060150146, 'train/grad_norm_pre_clip': 4.32688570022583, 'timing/data': 0.00017846794798970222, 'timing/model': 0.46594965318217874, 'learning_rate/action_model': 6.648819911303662e-05, 'learning_rate/action_query_proj': 6.648819911303662e-05, 'learning_rate/base': 1.6622049778259156e-05, 'epoch': 0.24}) +[2026-07-26 22:29:56,473][starVLA.training.train_starvla][INFO] - Step 2013, Loss: {'train/loss': 0.17279097437858582, 'train/grad_norm_pre_clip': 3.4651291370391846, 'timing/data': 0.00016718590632081032, 'timing/model': 0.45929528027772903, 'learning_rate/action_model': 6.645944361312602e-05, 'learning_rate/action_query_proj': 6.645944361312602e-05, 'learning_rate/base': 1.6614860903281505e-05, 'epoch': 0.24}) +[2026-07-26 22:30:02,250][starVLA.training.train_starvla][INFO] - Step 2014, Loss: {'train/loss': 0.17093251645565033, 'train/grad_norm_pre_clip': 3.4858009815216064, 'timing/data': 0.00018123211339116096, 'timing/model': 0.4658937072381377, 'learning_rate/action_model': 6.643068240485608e-05, 'learning_rate/action_query_proj': 6.643068240485608e-05, 'learning_rate/base': 1.660767060121402e-05, 'epoch': 0.24}) +[2026-07-26 22:30:08,010][starVLA.training.train_starvla][INFO] - Step 2015, Loss: {'train/loss': 0.1770099550485611, 'train/grad_norm_pre_clip': 2.8250656127929688, 'timing/data': 0.00017754407599568367, 'timing/model': 0.46425647707656026, 'learning_rate/action_model': 6.640191549958126e-05, 'learning_rate/action_query_proj': 6.640191549958126e-05, 'learning_rate/base': 1.6600478874895315e-05, 'epoch': 0.24}) +[2026-07-26 22:30:13,772][starVLA.training.train_starvla][INFO] - Step 2016, Loss: {'train/loss': 0.2693248987197876, 'train/grad_norm_pre_clip': 2.775421142578125, 'timing/data': 0.00017306674271821976, 'timing/model': 0.4663809770718217, 'learning_rate/action_model': 6.63731429086583e-05, 'learning_rate/action_query_proj': 6.63731429086583e-05, 'learning_rate/base': 1.6593285727164576e-05, 'epoch': 0.24}) +[2026-07-26 22:30:19,460][starVLA.training.train_starvla][INFO] - Step 2017, Loss: {'train/loss': 0.2970277667045593, 'train/grad_norm_pre_clip': 3.540463924407959, 'timing/data': 0.00017297407612204552, 'timing/model': 0.4661192069761455, 'learning_rate/action_model': 6.634436464344615e-05, 'learning_rate/action_query_proj': 6.634436464344615e-05, 'learning_rate/base': 1.6586091160861537e-05, 'epoch': 0.24}) +[2026-07-26 22:30:25,157][starVLA.training.train_starvla][INFO] - Step 2018, Loss: {'train/loss': 0.3592827320098877, 'train/grad_norm_pre_clip': 4.969442367553711, 'timing/data': 0.0001779249869287014, 'timing/model': 0.4654979398474097, 'learning_rate/action_model': 6.631558071530597e-05, 'learning_rate/action_query_proj': 6.631558071530597e-05, 'learning_rate/base': 1.657889517882649e-05, 'epoch': 0.24}) +[2026-07-26 22:30:30,732][starVLA.training.train_starvla][INFO] - Step 2019, Loss: {'train/loss': 0.27872660756111145, 'train/grad_norm_pre_clip': 2.7081475257873535, 'timing/data': 0.00016895076259970665, 'timing/model': 0.45906609715893865, 'learning_rate/action_model': 6.628679113560127e-05, 'learning_rate/action_query_proj': 6.628679113560127e-05, 'learning_rate/base': 1.6571697783900317e-05, 'epoch': 0.24}) +[2026-07-26 22:30:36,437][starVLA.training.train_starvla][INFO] - Step 2020, Loss: {'train/loss': 0.26230666041374207, 'train/grad_norm_pre_clip': 4.72259521484375, 'timing/data': 0.00016940990462899208, 'timing/model': 0.4638251350261271, 'learning_rate/action_model': 6.625799591569767e-05, 'learning_rate/action_query_proj': 6.625799591569767e-05, 'learning_rate/base': 1.656449897892442e-05, 'epoch': 0.25}) +[2026-07-26 22:30:42,127][starVLA.training.train_starvla][INFO] - Step 2021, Loss: {'train/loss': 0.23500460386276245, 'train/grad_norm_pre_clip': 3.172978162765503, 'timing/data': 0.00017338618636131287, 'timing/model': 0.4667349080555141, 'learning_rate/action_model': 6.62291950669631e-05, 'learning_rate/action_query_proj': 6.62291950669631e-05, 'learning_rate/base': 1.6557298766740776e-05, 'epoch': 0.25}) +[2026-07-26 22:30:47,809][starVLA.training.train_starvla][INFO] - Step 2022, Loss: {'train/loss': 0.23055621981620789, 'train/grad_norm_pre_clip': 3.056673288345337, 'timing/data': 0.0001722034066915512, 'timing/model': 0.4635215559974313, 'learning_rate/action_model': 6.620038860076768e-05, 'learning_rate/action_query_proj': 6.620038860076768e-05, 'learning_rate/base': 1.655009715019192e-05, 'epoch': 0.25}) +[2026-07-26 22:30:53,493][starVLA.training.train_starvla][INFO] - Step 2023, Loss: {'train/loss': 0.27253472805023193, 'train/grad_norm_pre_clip': 3.7337136268615723, 'timing/data': 0.0001870221458375454, 'timing/model': 0.46662998106330633, 'learning_rate/action_model': 6.617157652848371e-05, 'learning_rate/action_query_proj': 6.617157652848371e-05, 'learning_rate/base': 1.6542894132120928e-05, 'epoch': 0.25}) +[2026-07-26 22:30:59,215][starVLA.training.train_starvla][INFO] - Step 2024, Loss: {'train/loss': 0.12998689711093903, 'train/grad_norm_pre_clip': 2.754225492477417, 'timing/data': 0.0001838463358581066, 'timing/model': 0.4655669960193336, 'learning_rate/action_model': 6.614275886148575e-05, 'learning_rate/action_query_proj': 6.614275886148575e-05, 'learning_rate/base': 1.653568971537144e-05, 'epoch': 0.25}) +[2026-07-26 22:31:04,929][starVLA.training.train_starvla][INFO] - Step 2025, Loss: {'train/loss': 0.2220359891653061, 'train/grad_norm_pre_clip': 3.739915132522583, 'timing/data': 0.00017574569210410118, 'timing/model': 0.46559797786176205, 'learning_rate/action_model': 6.611393561115059e-05, 'learning_rate/action_query_proj': 6.611393561115059e-05, 'learning_rate/base': 1.6528483902787647e-05, 'epoch': 0.25}) +[2026-07-26 22:31:10,698][starVLA.training.train_starvla][INFO] - Step 2026, Loss: {'train/loss': 0.2669087052345276, 'train/grad_norm_pre_clip': 3.923119306564331, 'timing/data': 0.00017327629029750824, 'timing/model': 0.4777441881597042, 'learning_rate/action_model': 6.608510678885716e-05, 'learning_rate/action_query_proj': 6.608510678885716e-05, 'learning_rate/base': 1.652127669721429e-05, 'epoch': 0.25}) +[2026-07-26 22:31:16,406][starVLA.training.train_starvla][INFO] - Step 2027, Loss: {'train/loss': 0.2265271544456482, 'train/grad_norm_pre_clip': 2.904118061065674, 'timing/data': 0.00017208606004714966, 'timing/model': 0.4635219140909612, 'learning_rate/action_model': 6.605627240598665e-05, 'learning_rate/action_query_proj': 6.605627240598665e-05, 'learning_rate/base': 1.6514068101496662e-05, 'epoch': 0.25}) +[2026-07-26 22:31:22,131][starVLA.training.train_starvla][INFO] - Step 2028, Loss: {'train/loss': 0.472182959318161, 'train/grad_norm_pre_clip': 5.945268154144287, 'timing/data': 0.0001812586560845375, 'timing/model': 0.46322034718468785, 'learning_rate/action_model': 6.60274324739224e-05, 'learning_rate/action_query_proj': 6.60274324739224e-05, 'learning_rate/base': 1.65068581184806e-05, 'epoch': 0.25}) +[2026-07-26 22:31:27,732][starVLA.training.train_starvla][INFO] - Step 2029, Loss: {'train/loss': 0.3444087505340576, 'train/grad_norm_pre_clip': 6.284109592437744, 'timing/data': 0.00017932383343577385, 'timing/model': 0.46408675890415907, 'learning_rate/action_model': 6.599858700404996e-05, 'learning_rate/action_query_proj': 6.599858700404996e-05, 'learning_rate/base': 1.649964675101249e-05, 'epoch': 0.25}) +[2026-07-26 22:31:33,337][starVLA.training.train_starvla][INFO] - Step 2030, Loss: {'train/loss': 0.17855392396450043, 'train/grad_norm_pre_clip': 3.3213584423065186, 'timing/data': 0.00017584813758730888, 'timing/model': 0.46532030776143074, 'learning_rate/action_model': 6.596973600775704e-05, 'learning_rate/action_query_proj': 6.596973600775704e-05, 'learning_rate/base': 1.649243400193926e-05, 'epoch': 0.25}) +[2026-07-26 22:31:38,932][starVLA.training.train_starvla][INFO] - Step 2031, Loss: {'train/loss': 0.12371859699487686, 'train/grad_norm_pre_clip': 2.2299654483795166, 'timing/data': 0.0001834370195865631, 'timing/model': 0.4635208291001618, 'learning_rate/action_model': 6.594087949643362e-05, 'learning_rate/action_query_proj': 6.594087949643362e-05, 'learning_rate/base': 1.6485219874108404e-05, 'epoch': 0.25}) +[2026-07-26 22:31:44,552][starVLA.training.train_starvla][INFO] - Step 2032, Loss: {'train/loss': 0.2382725477218628, 'train/grad_norm_pre_clip': 3.546947479248047, 'timing/data': 0.0001692911610007286, 'timing/model': 0.462716497015208, 'learning_rate/action_model': 6.591201748147173e-05, 'learning_rate/action_query_proj': 6.591201748147173e-05, 'learning_rate/base': 1.6478004370367932e-05, 'epoch': 0.25}) +[2026-07-26 22:31:50,189][starVLA.training.train_starvla][INFO] - Step 2033, Loss: {'train/loss': 0.20202568173408508, 'train/grad_norm_pre_clip': 3.61419677734375, 'timing/data': 0.00017141131684184074, 'timing/model': 0.4673080937936902, 'learning_rate/action_model': 6.588314997426566e-05, 'learning_rate/action_query_proj': 6.588314997426566e-05, 'learning_rate/base': 1.6470787493566416e-05, 'epoch': 0.25}) +[2026-07-26 22:31:56,081][starVLA.training.train_starvla][INFO] - Step 2034, Loss: {'train/loss': 0.1671726554632187, 'train/grad_norm_pre_clip': 2.2378129959106445, 'timing/data': 0.000176919624209404, 'timing/model': 0.4643847569823265, 'learning_rate/action_model': 6.585427698621188e-05, 'learning_rate/action_query_proj': 6.585427698621188e-05, 'learning_rate/base': 1.646356924655297e-05, 'epoch': 0.25}) +[2026-07-26 22:32:01,728][starVLA.training.train_starvla][INFO] - Step 2035, Loss: {'train/loss': 0.28276780247688293, 'train/grad_norm_pre_clip': 5.226228713989258, 'timing/data': 0.00018812483176589012, 'timing/model': 0.4644508929923177, 'learning_rate/action_model': 6.582539852870894e-05, 'learning_rate/action_query_proj': 6.582539852870894e-05, 'learning_rate/base': 1.6456349632177234e-05, 'epoch': 0.25}) +[2026-07-26 22:32:07,388][starVLA.training.train_starvla][INFO] - Step 2036, Loss: {'train/loss': 0.2246597856283188, 'train/grad_norm_pre_clip': 3.6994481086730957, 'timing/data': 0.00017670495435595512, 'timing/model': 0.4637044039554894, 'learning_rate/action_model': 6.579651461315761e-05, 'learning_rate/action_query_proj': 6.579651461315761e-05, 'learning_rate/base': 1.6449128653289402e-05, 'epoch': 0.25}) +[2026-07-26 22:32:13,047][starVLA.training.train_starvla][INFO] - Step 2037, Loss: {'train/loss': 0.248165562748909, 'train/grad_norm_pre_clip': 3.6530468463897705, 'timing/data': 0.00017400877550244331, 'timing/model': 0.4662653598934412, 'learning_rate/action_model': 6.576762525096078e-05, 'learning_rate/action_query_proj': 6.576762525096078e-05, 'learning_rate/base': 1.6441906312740196e-05, 'epoch': 0.25}) +[2026-07-26 22:32:18,709][starVLA.training.train_starvla][INFO] - Step 2038, Loss: {'train/loss': 0.3283029794692993, 'train/grad_norm_pre_clip': 4.956212520599365, 'timing/data': 0.00017985887825489044, 'timing/model': 0.4678718252107501, 'learning_rate/action_model': 6.573873045352357e-05, 'learning_rate/action_query_proj': 6.573873045352357e-05, 'learning_rate/base': 1.6434682613380892e-05, 'epoch': 0.25}) +[2026-07-26 22:32:24,320][starVLA.training.train_starvla][INFO] - Step 2039, Loss: {'train/loss': 0.25309598445892334, 'train/grad_norm_pre_clip': 3.532514810562134, 'timing/data': 0.0001722872257232666, 'timing/model': 0.46736745722591877, 'learning_rate/action_model': 6.570983023225314e-05, 'learning_rate/action_query_proj': 6.570983023225314e-05, 'learning_rate/base': 1.6427457558063284e-05, 'epoch': 0.25}) +[2026-07-26 22:32:29,934][starVLA.training.train_starvla][INFO] - Step 2040, Loss: {'train/loss': 0.19537116587162018, 'train/grad_norm_pre_clip': 3.009972095489502, 'timing/data': 0.00017486466094851494, 'timing/model': 0.4658890049904585, 'learning_rate/action_model': 6.568092459855886e-05, 'learning_rate/action_query_proj': 6.568092459855886e-05, 'learning_rate/base': 1.6420231149639714e-05, 'epoch': 0.25}) +[2026-07-26 22:32:35,568][starVLA.training.train_starvla][INFO] - Step 2041, Loss: {'train/loss': 0.3691011667251587, 'train/grad_norm_pre_clip': 3.814253330230713, 'timing/data': 0.0001737796701490879, 'timing/model': 0.4655582341365516, 'learning_rate/action_model': 6.56520135638522e-05, 'learning_rate/action_query_proj': 6.56520135638522e-05, 'learning_rate/base': 1.641300339096305e-05, 'epoch': 0.25}) +[2026-07-26 22:32:41,291][starVLA.training.train_starvla][INFO] - Step 2042, Loss: {'train/loss': 0.2506028711795807, 'train/grad_norm_pre_clip': 3.32771897315979, 'timing/data': 0.00017096102237701416, 'timing/model': 0.4767702450044453, 'learning_rate/action_model': 6.562309713954682e-05, 'learning_rate/action_query_proj': 6.562309713954682e-05, 'learning_rate/base': 1.6405774284886705e-05, 'epoch': 0.25}) +[2026-07-26 22:32:46,826][starVLA.training.train_starvla][INFO] - Step 2043, Loss: {'train/loss': 0.1686583161354065, 'train/grad_norm_pre_clip': 3.606182813644409, 'timing/data': 0.00018123304471373558, 'timing/model': 0.4601355716586113, 'learning_rate/action_model': 6.559417533705841e-05, 'learning_rate/action_query_proj': 6.559417533705841e-05, 'learning_rate/base': 1.6398543834264603e-05, 'epoch': 0.25}) +[2026-07-26 22:32:52,510][starVLA.training.train_starvla][INFO] - Step 2044, Loss: {'train/loss': 0.2346544712781906, 'train/grad_norm_pre_clip': 3.077282428741455, 'timing/data': 0.00018091918900609016, 'timing/model': 0.46670557791367173, 'learning_rate/action_model': 6.55652481678049e-05, 'learning_rate/action_query_proj': 6.55652481678049e-05, 'learning_rate/base': 1.6391312041951224e-05, 'epoch': 0.25}) +[2026-07-26 22:32:58,137][starVLA.training.train_starvla][INFO] - Step 2045, Loss: {'train/loss': 0.2571074962615967, 'train/grad_norm_pre_clip': 2.4206385612487793, 'timing/data': 0.0001696101389825344, 'timing/model': 0.46379694482311606, 'learning_rate/action_model': 6.553631564320621e-05, 'learning_rate/action_query_proj': 6.553631564320621e-05, 'learning_rate/base': 1.6384078910801553e-05, 'epoch': 0.25}) +[2026-07-26 22:33:04,017][starVLA.training.train_starvla][INFO] - Step 2046, Loss: {'train/loss': 0.25897693634033203, 'train/grad_norm_pre_clip': 4.506300449371338, 'timing/data': 0.00017000176012516022, 'timing/model': 0.4674608358182013, 'learning_rate/action_model': 6.550737777468451e-05, 'learning_rate/action_query_proj': 6.550737777468451e-05, 'learning_rate/base': 1.6376844443671127e-05, 'epoch': 0.25}) +[2026-07-26 22:33:09,633][starVLA.training.train_starvla][INFO] - Step 2047, Loss: {'train/loss': 0.2520427107810974, 'train/grad_norm_pre_clip': 3.4535834789276123, 'timing/data': 0.00017149979248642921, 'timing/model': 0.46086458023637533, 'learning_rate/action_model': 6.547843457366396e-05, 'learning_rate/action_query_proj': 6.547843457366396e-05, 'learning_rate/base': 1.636960864341599e-05, 'epoch': 0.25}) +[2026-07-26 22:33:15,264][starVLA.training.train_starvla][INFO] - Step 2048, Loss: {'train/loss': 0.16079029440879822, 'train/grad_norm_pre_clip': 3.5719738006591797, 'timing/data': 0.00017274683341383934, 'timing/model': 0.4631092520430684, 'learning_rate/action_model': 6.54494860515709e-05, 'learning_rate/action_query_proj': 6.54494860515709e-05, 'learning_rate/base': 1.6362371512892726e-05, 'epoch': 0.25}) +[2026-07-26 22:33:20,893][starVLA.training.train_starvla][INFO] - Step 2049, Loss: {'train/loss': 0.147783100605011, 'train/grad_norm_pre_clip': 2.428157329559326, 'timing/data': 0.0001717209815979004, 'timing/model': 0.46600560937076807, 'learning_rate/action_model': 6.542053221983374e-05, 'learning_rate/action_query_proj': 6.542053221983374e-05, 'learning_rate/base': 1.6355133054958434e-05, 'epoch': 0.25}) +[2026-07-26 22:33:26,513][starVLA.training.train_starvla][INFO] - Step 2050, Loss: {'train/loss': 0.3014124929904938, 'train/grad_norm_pre_clip': 3.1462321281433105, 'timing/data': 0.0001759696751832962, 'timing/model': 0.4669657018966973, 'learning_rate/action_model': 6.539157308988302e-05, 'learning_rate/action_query_proj': 6.539157308988302e-05, 'learning_rate/base': 1.6347893272470754e-05, 'epoch': 0.25}) +[2026-07-26 22:33:32,090][starVLA.training.train_starvla][INFO] - Step 2051, Loss: {'train/loss': 0.3792114853858948, 'train/grad_norm_pre_clip': 3.783531904220581, 'timing/data': 0.00017100293189287186, 'timing/model': 0.4627637518569827, 'learning_rate/action_model': 6.536260867315131e-05, 'learning_rate/action_query_proj': 6.536260867315131e-05, 'learning_rate/base': 1.6340652168287828e-05, 'epoch': 0.25}) +[2026-07-26 22:33:37,723][starVLA.training.train_starvla][INFO] - Step 2052, Loss: {'train/loss': 0.21343325078487396, 'train/grad_norm_pre_clip': 2.767925977706909, 'timing/data': 0.00017856713384389877, 'timing/model': 0.4659473020583391, 'learning_rate/action_model': 6.533363898107333e-05, 'learning_rate/action_query_proj': 6.533363898107333e-05, 'learning_rate/base': 1.6333409745268332e-05, 'epoch': 0.25}) +[2026-07-26 22:33:43,360][starVLA.training.train_starvla][INFO] - Step 2053, Loss: {'train/loss': 0.2052028775215149, 'train/grad_norm_pre_clip': 2.550731658935547, 'timing/data': 0.0001712939701974392, 'timing/model': 0.4665108611807227, 'learning_rate/action_model': 6.530466402508581e-05, 'learning_rate/action_query_proj': 6.530466402508581e-05, 'learning_rate/base': 1.6326166006271452e-05, 'epoch': 0.25}) +[2026-07-26 22:33:49,036][starVLA.training.train_starvla][INFO] - Step 2054, Loss: {'train/loss': 0.21879588067531586, 'train/grad_norm_pre_clip': 2.8038363456726074, 'timing/data': 0.00017424486577510834, 'timing/model': 0.47201696690171957, 'learning_rate/action_model': 6.527568381662769e-05, 'learning_rate/action_query_proj': 6.527568381662769e-05, 'learning_rate/base': 1.631892095415692e-05, 'epoch': 0.25}) +[2026-07-26 22:33:54,733][starVLA.training.train_starvla][INFO] - Step 2055, Loss: {'train/loss': 0.28281369805336, 'train/grad_norm_pre_clip': 3.9393482208251953, 'timing/data': 0.0001701749861240387, 'timing/model': 0.4691255954094231, 'learning_rate/action_model': 6.524669836713981e-05, 'learning_rate/action_query_proj': 6.524669836713981e-05, 'learning_rate/base': 1.6311674591784953e-05, 'epoch': 0.25}) +[2026-07-26 22:34:00,430][starVLA.training.train_starvla][INFO] - Step 2056, Loss: {'train/loss': 0.2510264217853546, 'train/grad_norm_pre_clip': 3.4109151363372803, 'timing/data': 0.00018474506214261055, 'timing/model': 0.46926497062668204, 'learning_rate/action_model': 6.52177076880652e-05, 'learning_rate/action_query_proj': 6.52177076880652e-05, 'learning_rate/base': 1.63044269220163e-05, 'epoch': 0.25}) +[2026-07-26 22:34:06,116][starVLA.training.train_starvla][INFO] - Step 2057, Loss: {'train/loss': 0.28256312012672424, 'train/grad_norm_pre_clip': 3.62039852142334, 'timing/data': 0.00017321715131402016, 'timing/model': 0.46043874928727746, 'learning_rate/action_model': 6.518871179084895e-05, 'learning_rate/action_query_proj': 6.518871179084895e-05, 'learning_rate/base': 1.6297177947712236e-05, 'epoch': 0.25}) +[2026-07-26 22:34:11,808][starVLA.training.train_starvla][INFO] - Step 2058, Loss: {'train/loss': 0.20841635763645172, 'train/grad_norm_pre_clip': 2.2646944522857666, 'timing/data': 0.0001696818508207798, 'timing/model': 0.4648263491690159, 'learning_rate/action_model': 6.515971068693812e-05, 'learning_rate/action_query_proj': 6.515971068693812e-05, 'learning_rate/base': 1.628992767173453e-05, 'epoch': 0.25}) +[2026-07-26 22:34:17,478][starVLA.training.train_starvla][INFO] - Step 2059, Loss: {'train/loss': 0.16457168757915497, 'train/grad_norm_pre_clip': 3.2625129222869873, 'timing/data': 0.00017038080841302872, 'timing/model': 0.48488553520292044, 'learning_rate/action_model': 6.513070438778194e-05, 'learning_rate/action_query_proj': 6.513070438778194e-05, 'learning_rate/base': 1.6282676096945486e-05, 'epoch': 0.25}) +[2026-07-26 22:34:23,163][starVLA.training.train_starvla][INFO] - Step 2060, Loss: {'train/loss': 0.3441409468650818, 'train/grad_norm_pre_clip': 4.144716262817383, 'timing/data': 0.00017587607726454735, 'timing/model': 0.48717962112277746, 'learning_rate/action_model': 6.510169290483163e-05, 'learning_rate/action_query_proj': 6.510169290483163e-05, 'learning_rate/base': 1.6275423226207907e-05, 'epoch': 0.25}) +[2026-07-26 22:34:28,815][starVLA.training.train_starvla][INFO] - Step 2061, Loss: {'train/loss': 0.38751932978630066, 'train/grad_norm_pre_clip': 4.036487102508545, 'timing/data': 0.0001798556186258793, 'timing/model': 0.4703767183236778, 'learning_rate/action_model': 6.507267624954042e-05, 'learning_rate/action_query_proj': 6.507267624954042e-05, 'learning_rate/base': 1.6268169062385105e-05, 'epoch': 0.25}) +[2026-07-26 22:34:34,453][starVLA.training.train_starvla][INFO] - Step 2062, Loss: {'train/loss': 0.3083304762840271, 'train/grad_norm_pre_clip': 3.575446605682373, 'timing/data': 0.00017020106315612793, 'timing/model': 0.4672844083979726, 'learning_rate/action_model': 6.504365443336368e-05, 'learning_rate/action_query_proj': 6.504365443336368e-05, 'learning_rate/base': 1.626091360834092e-05, 'epoch': 0.25}) +[2026-07-26 22:34:40,084][starVLA.training.train_starvla][INFO] - Step 2063, Loss: {'train/loss': 0.30946215987205505, 'train/grad_norm_pre_clip': 4.818874359130859, 'timing/data': 0.0001877383328974247, 'timing/model': 0.46212068386375904, 'learning_rate/action_model': 6.501462746775874e-05, 'learning_rate/action_query_proj': 6.501462746775874e-05, 'learning_rate/base': 1.6253656866939685e-05, 'epoch': 0.25}) +[2026-07-26 22:34:45,710][starVLA.training.train_starvla][INFO] - Step 2064, Loss: {'train/loss': 0.280059278011322, 'train/grad_norm_pre_clip': 3.830662488937378, 'timing/data': 0.0001748679205775261, 'timing/model': 0.46794140292331576, 'learning_rate/action_model': 6.498559536418498e-05, 'learning_rate/action_query_proj': 6.498559536418498e-05, 'learning_rate/base': 1.6246398841046246e-05, 'epoch': 0.25}) +[2026-07-26 22:34:51,343][starVLA.training.train_starvla][INFO] - Step 2065, Loss: {'train/loss': 0.3003559112548828, 'train/grad_norm_pre_clip': 4.332400321960449, 'timing/data': 0.00017405487596988678, 'timing/model': 0.46363276429474354, 'learning_rate/action_model': 6.495655813410384e-05, 'learning_rate/action_query_proj': 6.495655813410384e-05, 'learning_rate/base': 1.623913953352596e-05, 'epoch': 0.25}) +[2026-07-26 22:34:56,964][starVLA.training.train_starvla][INFO] - Step 2066, Loss: {'train/loss': 0.27632009983062744, 'train/grad_norm_pre_clip': 3.6209750175476074, 'timing/data': 0.00016854098066687584, 'timing/model': 0.4630119423381984, 'learning_rate/action_model': 6.49275157889787e-05, 'learning_rate/action_query_proj': 6.49275157889787e-05, 'learning_rate/base': 1.6231878947244676e-05, 'epoch': 0.25}) +[2026-07-26 22:35:02,574][starVLA.training.train_starvla][INFO] - Step 2067, Loss: {'train/loss': 0.1358695924282074, 'train/grad_norm_pre_clip': 2.613140344619751, 'timing/data': 0.00017582019791007042, 'timing/model': 0.461896738037467, 'learning_rate/action_model': 6.48984683402751e-05, 'learning_rate/action_query_proj': 6.48984683402751e-05, 'learning_rate/base': 1.6224617085068776e-05, 'epoch': 0.25}) +[2026-07-26 22:35:08,200][starVLA.training.train_starvla][INFO] - Step 2068, Loss: {'train/loss': 0.1992209404706955, 'train/grad_norm_pre_clip': 3.411864995956421, 'timing/data': 0.00017345137894153595, 'timing/model': 0.46774028055369854, 'learning_rate/action_model': 6.486941579946046e-05, 'learning_rate/action_query_proj': 6.486941579946046e-05, 'learning_rate/base': 1.6217353949865115e-05, 'epoch': 0.25}) +[2026-07-26 22:35:13,848][starVLA.training.train_starvla][INFO] - Step 2069, Loss: {'train/loss': 0.29932233691215515, 'train/grad_norm_pre_clip': 3.206739902496338, 'timing/data': 0.00018035806715488434, 'timing/model': 0.46354062482714653, 'learning_rate/action_model': 6.484035817800427e-05, 'learning_rate/action_query_proj': 6.484035817800427e-05, 'learning_rate/base': 1.621008954450107e-05, 'epoch': 0.25}) +[2026-07-26 22:35:19,489][starVLA.training.train_starvla][INFO] - Step 2070, Loss: {'train/loss': 0.21945597231388092, 'train/grad_norm_pre_clip': 3.4653637409210205, 'timing/data': 0.00017245439812541008, 'timing/model': 0.4667692929506302, 'learning_rate/action_model': 6.481129548737803e-05, 'learning_rate/action_query_proj': 6.481129548737803e-05, 'learning_rate/base': 1.6202823871844507e-05, 'epoch': 0.25}) +[2026-07-26 22:35:25,130][starVLA.training.train_starvla][INFO] - Step 2071, Loss: {'train/loss': 0.238511860370636, 'train/grad_norm_pre_clip': 3.6688499450683594, 'timing/data': 0.00017111003398895264, 'timing/model': 0.46321615809574723, 'learning_rate/action_model': 6.478222773905523e-05, 'learning_rate/action_query_proj': 6.478222773905523e-05, 'learning_rate/base': 1.6195556934763806e-05, 'epoch': 0.25}) +[2026-07-26 22:35:30,797][starVLA.training.train_starvla][INFO] - Step 2072, Loss: {'train/loss': 0.2321075052022934, 'train/grad_norm_pre_clip': 3.501953363418579, 'timing/data': 0.0001714271493256092, 'timing/model': 0.46647503320127726, 'learning_rate/action_model': 6.475315494451133e-05, 'learning_rate/action_query_proj': 6.475315494451133e-05, 'learning_rate/base': 1.6188288736127833e-05, 'epoch': 0.25}) +[2026-07-26 22:35:36,445][starVLA.training.train_starvla][INFO] - Step 2073, Loss: {'train/loss': 0.2624918520450592, 'train/grad_norm_pre_clip': 2.9272208213806152, 'timing/data': 0.00017534801736474037, 'timing/model': 0.46357500087469816, 'learning_rate/action_model': 6.472407711522383e-05, 'learning_rate/action_query_proj': 6.472407711522383e-05, 'learning_rate/base': 1.6181019278805958e-05, 'epoch': 0.25}) +[2026-07-26 22:35:42,113][starVLA.training.train_starvla][INFO] - Step 2074, Loss: {'train/loss': 0.20086322724819183, 'train/grad_norm_pre_clip': 2.7938520908355713, 'timing/data': 0.00017317617312073708, 'timing/model': 0.4636029819957912, 'learning_rate/action_model': 6.469499426267221e-05, 'learning_rate/action_query_proj': 6.469499426267221e-05, 'learning_rate/base': 1.6173748565668052e-05, 'epoch': 0.25}) +[2026-07-26 22:35:47,705][starVLA.training.train_starvla][INFO] - Step 2075, Loss: {'train/loss': 0.19061096012592316, 'train/grad_norm_pre_clip': 3.360142707824707, 'timing/data': 0.0001698569394648075, 'timing/model': 0.4592545246705413, 'learning_rate/action_model': 6.46659063983379e-05, 'learning_rate/action_query_proj': 6.46659063983379e-05, 'learning_rate/base': 1.6166476599584475e-05, 'epoch': 0.25}) +[2026-07-26 22:35:53,359][starVLA.training.train_starvla][INFO] - Step 2076, Loss: {'train/loss': 0.1851157397031784, 'train/grad_norm_pre_clip': 3.0631768703460693, 'timing/data': 0.0001789359375834465, 'timing/model': 0.46626028791069984, 'learning_rate/action_model': 6.463681353370433e-05, 'learning_rate/action_query_proj': 6.463681353370433e-05, 'learning_rate/base': 1.6159203383426083e-05, 'epoch': 0.25}) +[2026-07-26 22:35:59,010][starVLA.training.train_starvla][INFO] - Step 2077, Loss: {'train/loss': 0.22211898863315582, 'train/grad_norm_pre_clip': 3.255807876586914, 'timing/data': 0.00018376484513282776, 'timing/model': 0.46577110700309277, 'learning_rate/action_model': 6.46077156802569e-05, 'learning_rate/action_query_proj': 6.46077156802569e-05, 'learning_rate/base': 1.6151928920064226e-05, 'epoch': 0.25}) +[2026-07-26 22:36:04,641][starVLA.training.train_starvla][INFO] - Step 2078, Loss: {'train/loss': 0.17223995923995972, 'train/grad_norm_pre_clip': 3.073770523071289, 'timing/data': 0.0001760772429406643, 'timing/model': 0.46304995426908135, 'learning_rate/action_model': 6.4578612849483e-05, 'learning_rate/action_query_proj': 6.4578612849483e-05, 'learning_rate/base': 1.614465321237075e-05, 'epoch': 0.25}) +[2026-07-26 22:36:10,274][starVLA.training.train_starvla][INFO] - Step 2079, Loss: {'train/loss': 0.2075919657945633, 'train/grad_norm_pre_clip': 2.729107141494751, 'timing/data': 0.00017496710643172264, 'timing/model': 0.46610902016982436, 'learning_rate/action_model': 6.454950505287196e-05, 'learning_rate/action_query_proj': 6.454950505287196e-05, 'learning_rate/base': 1.613737626321799e-05, 'epoch': 0.25}) +[2026-07-26 22:36:15,916][starVLA.training.train_starvla][INFO] - Step 2080, Loss: {'train/loss': 0.17294514179229736, 'train/grad_norm_pre_clip': 3.2029385566711426, 'timing/data': 0.0001733582466840744, 'timing/model': 0.46625474374741316, 'learning_rate/action_model': 6.452039230191506e-05, 'learning_rate/action_query_proj': 6.452039230191506e-05, 'learning_rate/base': 1.6130098075478765e-05, 'epoch': 0.25}) +[2026-07-26 22:36:21,527][starVLA.training.train_starvla][INFO] - Step 2081, Loss: {'train/loss': 0.25735801458358765, 'train/grad_norm_pre_clip': 4.332840919494629, 'timing/data': 0.00017021503299474716, 'timing/model': 0.4635974024422467, 'learning_rate/action_model': 6.449127460810556e-05, 'learning_rate/action_query_proj': 6.449127460810556e-05, 'learning_rate/base': 1.612281865202639e-05, 'epoch': 0.25}) +[2026-07-26 22:36:27,155][starVLA.training.train_starvla][INFO] - Step 2082, Loss: {'train/loss': 0.2580811083316803, 'train/grad_norm_pre_clip': 3.6409592628479004, 'timing/data': 0.00017376895993947983, 'timing/model': 0.4668644992634654, 'learning_rate/action_model': 6.446215198293868e-05, 'learning_rate/action_query_proj': 6.446215198293868e-05, 'learning_rate/base': 1.611553799573467e-05, 'epoch': 0.25}) +[2026-07-26 22:36:32,710][starVLA.training.train_starvla][INFO] - Step 2083, Loss: {'train/loss': 0.31236597895622253, 'train/grad_norm_pre_clip': 4.055556297302246, 'timing/data': 0.0001769321970641613, 'timing/model': 0.45693489210680127, 'learning_rate/action_model': 6.443302443791153e-05, 'learning_rate/action_query_proj': 6.443302443791153e-05, 'learning_rate/base': 1.6108256109477883e-05, 'epoch': 0.25}) +[2026-07-26 22:36:38,355][starVLA.training.train_starvla][INFO] - Step 2084, Loss: {'train/loss': 0.3192335367202759, 'train/grad_norm_pre_clip': 2.5978970527648926, 'timing/data': 0.00017839903011918068, 'timing/model': 0.4651489779353142, 'learning_rate/action_model': 6.440389198452327e-05, 'learning_rate/action_query_proj': 6.440389198452327e-05, 'learning_rate/base': 1.6100972996130818e-05, 'epoch': 0.25}) +[2026-07-26 22:36:44,020][starVLA.training.train_starvla][INFO] - Step 2085, Loss: {'train/loss': 0.16258540749549866, 'train/grad_norm_pre_clip': 4.410067558288574, 'timing/data': 0.00021863402798771858, 'timing/model': 0.46675388095900416, 'learning_rate/action_model': 6.437475463427489e-05, 'learning_rate/action_query_proj': 6.437475463427489e-05, 'learning_rate/base': 1.609368865856872e-05, 'epoch': 0.25}) +[2026-07-26 22:36:49,684][starVLA.training.train_starvla][INFO] - Step 2086, Loss: {'train/loss': 0.2705256938934326, 'train/grad_norm_pre_clip': 3.426926612854004, 'timing/data': 0.00017769215628504753, 'timing/model': 0.46722642984241247, 'learning_rate/action_model': 6.434561239866933e-05, 'learning_rate/action_query_proj': 6.434561239866933e-05, 'learning_rate/base': 1.608640309966733e-05, 'epoch': 0.25}) +[2026-07-26 22:36:55,371][starVLA.training.train_starvla][INFO] - Step 2087, Loss: {'train/loss': 0.22604002058506012, 'train/grad_norm_pre_clip': 2.918043851852417, 'timing/data': 0.00017212983220815659, 'timing/model': 0.46881969878450036, 'learning_rate/action_model': 6.431646528921154e-05, 'learning_rate/action_query_proj': 6.431646528921154e-05, 'learning_rate/base': 1.6079116322302884e-05, 'epoch': 0.25}) +[2026-07-26 22:37:01,294][starVLA.training.train_starvla][INFO] - Step 2088, Loss: {'train/loss': 0.24419131875038147, 'train/grad_norm_pre_clip': 3.6345648765563965, 'timing/data': 0.00018882332369685173, 'timing/model': 0.7581002698279917, 'learning_rate/action_model': 6.42873133174083e-05, 'learning_rate/action_query_proj': 6.42873133174083e-05, 'learning_rate/base': 1.6071828329352076e-05, 'epoch': 0.25}) +[2026-07-26 22:37:06,909][starVLA.training.train_starvla][INFO] - Step 2089, Loss: {'train/loss': 0.20015853643417358, 'train/grad_norm_pre_clip': 3.4267125129699707, 'timing/data': 0.00017007999122142792, 'timing/model': 0.46136491280049086, 'learning_rate/action_model': 6.425815649476834e-05, 'learning_rate/action_query_proj': 6.425815649476834e-05, 'learning_rate/base': 1.6064539123692084e-05, 'epoch': 0.25}) +[2026-07-26 22:37:12,542][starVLA.training.train_starvla][INFO] - Step 2090, Loss: {'train/loss': 0.19970539212226868, 'train/grad_norm_pre_clip': 2.4086344242095947, 'timing/data': 0.00017447536811232567, 'timing/model': 0.46662697196006775, 'learning_rate/action_model': 6.422899483280234e-05, 'learning_rate/action_query_proj': 6.422899483280234e-05, 'learning_rate/base': 1.6057248708200585e-05, 'epoch': 0.25}) +[2026-07-26 22:37:18,195][starVLA.training.train_starvla][INFO] - Step 2091, Loss: {'train/loss': 0.17542731761932373, 'train/grad_norm_pre_clip': 2.2454612255096436, 'timing/data': 0.00017236312851309776, 'timing/model': 0.4663415881805122, 'learning_rate/action_model': 6.419982834302288e-05, 'learning_rate/action_query_proj': 6.419982834302288e-05, 'learning_rate/base': 1.604995708575572e-05, 'epoch': 0.25}) +[2026-07-26 22:37:23,843][starVLA.training.train_starvla][INFO] - Step 2092, Loss: {'train/loss': 0.18775126338005066, 'train/grad_norm_pre_clip': 3.037130117416382, 'timing/data': 0.00017129303887486458, 'timing/model': 0.46427086275070906, 'learning_rate/action_model': 6.417065703694435e-05, 'learning_rate/action_query_proj': 6.417065703694435e-05, 'learning_rate/base': 1.6042664259236086e-05, 'epoch': 0.25}) +[2026-07-26 22:37:29,481][starVLA.training.train_starvla][INFO] - Step 2093, Loss: {'train/loss': 0.1945936232805252, 'train/grad_norm_pre_clip': 2.764824628829956, 'timing/data': 0.0002112830989062786, 'timing/model': 0.4658152018673718, 'learning_rate/action_model': 6.414148092608319e-05, 'learning_rate/action_query_proj': 6.414148092608319e-05, 'learning_rate/base': 1.6035370231520796e-05, 'epoch': 0.25}) +[2026-07-26 22:37:35,120][starVLA.training.train_starvla][INFO] - Step 2094, Loss: {'train/loss': 0.26398149132728577, 'train/grad_norm_pre_clip': 3.5948567390441895, 'timing/data': 0.0001746751368045807, 'timing/model': 0.4670699620619416, 'learning_rate/action_model': 6.411230002195765e-05, 'learning_rate/action_query_proj': 6.411230002195765e-05, 'learning_rate/base': 1.6028075005489412e-05, 'epoch': 0.25}) +[2026-07-26 22:37:40,770][starVLA.training.train_starvla][INFO] - Step 2095, Loss: {'train/loss': 0.19326215982437134, 'train/grad_norm_pre_clip': 3.8809702396392822, 'timing/data': 0.00017295405268669128, 'timing/model': 0.4638655153103173, 'learning_rate/action_model': 6.408311433608787e-05, 'learning_rate/action_query_proj': 6.408311433608787e-05, 'learning_rate/base': 1.6020778584021967e-05, 'epoch': 0.25}) +[2026-07-26 22:37:46,421][starVLA.training.train_starvla][INFO] - Step 2096, Loss: {'train/loss': 0.19243112206459045, 'train/grad_norm_pre_clip': 2.979013681411743, 'timing/data': 0.00017596594989299774, 'timing/model': 0.4664667909964919, 'learning_rate/action_model': 6.405392387999591e-05, 'learning_rate/action_query_proj': 6.405392387999591e-05, 'learning_rate/base': 1.6013480969998977e-05, 'epoch': 0.25}) +[2026-07-26 22:37:52,089][starVLA.training.train_starvla][INFO] - Step 2097, Loss: {'train/loss': 0.2051171213388443, 'train/grad_norm_pre_clip': 3.154134750366211, 'timing/data': 0.00016980990767478943, 'timing/model': 0.4674374349415302, 'learning_rate/action_model': 6.402472866520571e-05, 'learning_rate/action_query_proj': 6.402472866520571e-05, 'learning_rate/base': 1.6006182166301428e-05, 'epoch': 0.25}) +[2026-07-26 22:37:57,745][starVLA.training.train_starvla][INFO] - Step 2098, Loss: {'train/loss': 0.2856030762195587, 'train/grad_norm_pre_clip': 3.847944974899292, 'timing/data': 0.00017944490537047386, 'timing/model': 0.4660658538341522, 'learning_rate/action_model': 6.399552870324306e-05, 'learning_rate/action_query_proj': 6.399552870324306e-05, 'learning_rate/base': 1.5998882175810766e-05, 'epoch': 0.25}) +[2026-07-26 22:38:03,351][starVLA.training.train_starvla][INFO] - Step 2099, Loss: {'train/loss': 0.20106519758701324, 'train/grad_norm_pre_clip': 3.39911150932312, 'timing/data': 0.00018687685951590538, 'timing/model': 0.4581591938622296, 'learning_rate/action_model': 6.396632400563565e-05, 'learning_rate/action_query_proj': 6.396632400563565e-05, 'learning_rate/base': 1.5991581001408913e-05, 'epoch': 0.25}) +[2026-07-26 22:38:09,033][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2100 +[2026-07-26 22:38:09,034][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2100 +[2026-07-26 22:38:09,035][starVLA.training.train_starvla][INFO] - Step 2100, Loss: {'train/loss': 0.2407473772764206, 'train/grad_norm_pre_clip': 4.080024719238281, 'timing/data': 0.00018250709399580956, 'timing/model': 0.46912275115028024, 'learning_rate/action_model': 6.393711458391304e-05, 'learning_rate/action_query_proj': 6.393711458391304e-05, 'learning_rate/base': 1.598427864597826e-05, 'epoch': 0.25}) +[2026-07-26 22:38:14,700][starVLA.training.train_starvla][INFO] - Step 2101, Loss: {'train/loss': 0.3824580907821655, 'train/grad_norm_pre_clip': 4.232491970062256, 'timing/data': 0.0001780926249921322, 'timing/model': 0.47042464977130294, 'learning_rate/action_model': 6.390790044960663e-05, 'learning_rate/action_query_proj': 6.390790044960663e-05, 'learning_rate/base': 1.5976975112401656e-05, 'epoch': 0.25}) +[2026-07-26 22:38:20,402][starVLA.training.train_starvla][INFO] - Step 2102, Loss: {'train/loss': 0.2453094720840454, 'train/grad_norm_pre_clip': 3.228435516357422, 'timing/data': 0.00017820624634623528, 'timing/model': 0.4642119249328971, 'learning_rate/action_model': 6.387868161424972e-05, 'learning_rate/action_query_proj': 6.387868161424972e-05, 'learning_rate/base': 1.596967040356243e-05, 'epoch': 0.25}) +[2026-07-26 22:38:26,056][starVLA.training.train_starvla][INFO] - Step 2103, Loss: {'train/loss': 0.15054471790790558, 'train/grad_norm_pre_clip': 2.839627742767334, 'timing/data': 0.00017969263717532158, 'timing/model': 0.46640192391350865, 'learning_rate/action_model': 6.384945808937742e-05, 'learning_rate/action_query_proj': 6.384945808937742e-05, 'learning_rate/base': 1.5962364522344354e-05, 'epoch': 0.26}) +[2026-07-26 22:38:31,715][starVLA.training.train_starvla][INFO] - Step 2104, Loss: {'train/loss': 0.1879221796989441, 'train/grad_norm_pre_clip': 4.051975250244141, 'timing/data': 0.00017380109056830406, 'timing/model': 0.46465947572141886, 'learning_rate/action_model': 6.382022988652673e-05, 'learning_rate/action_query_proj': 6.382022988652673e-05, 'learning_rate/base': 1.5955057471631684e-05, 'epoch': 0.26}) +[2026-07-26 22:38:37,362][starVLA.training.train_starvla][INFO] - Step 2105, Loss: {'train/loss': 0.278674840927124, 'train/grad_norm_pre_clip': 4.583571434020996, 'timing/data': 0.0001746336929500103, 'timing/model': 0.463821011595428, 'learning_rate/action_model': 6.379099701723648e-05, 'learning_rate/action_query_proj': 6.379099701723648e-05, 'learning_rate/base': 1.594774925430912e-05, 'epoch': 0.26}) +[2026-07-26 22:38:43,028][starVLA.training.train_starvla][INFO] - Step 2106, Loss: {'train/loss': 0.19361035525798798, 'train/grad_norm_pre_clip': 2.431049108505249, 'timing/data': 0.00018065515905618668, 'timing/model': 0.4642822309397161, 'learning_rate/action_model': 6.376175949304733e-05, 'learning_rate/action_query_proj': 6.376175949304733e-05, 'learning_rate/base': 1.594043987326183e-05, 'epoch': 0.26}) +[2026-07-26 22:38:48,710][starVLA.training.train_starvla][INFO] - Step 2107, Loss: {'train/loss': 0.37232470512390137, 'train/grad_norm_pre_clip': 4.398918151855469, 'timing/data': 0.00018091173842549324, 'timing/model': 0.4652441958896816, 'learning_rate/action_model': 6.373251732550182e-05, 'learning_rate/action_query_proj': 6.373251732550182e-05, 'learning_rate/base': 1.5933129331375455e-05, 'epoch': 0.26}) +[2026-07-26 22:38:54,428][starVLA.training.train_starvla][INFO] - Step 2108, Loss: {'train/loss': 0.21805588901042938, 'train/grad_norm_pre_clip': 3.507882595062256, 'timing/data': 0.00017385371029376984, 'timing/model': 0.4663813980296254, 'learning_rate/action_model': 6.370327052614426e-05, 'learning_rate/action_query_proj': 6.370327052614426e-05, 'learning_rate/base': 1.5925817631536065e-05, 'epoch': 0.26}) +[2026-07-26 22:39:00,064][starVLA.training.train_starvla][INFO] - Step 2109, Loss: {'train/loss': 0.29611971974372864, 'train/grad_norm_pre_clip': 3.4610068798065186, 'timing/data': 0.00017641903832554817, 'timing/model': 0.46350981015712023, 'learning_rate/action_model': 6.367401910652084e-05, 'learning_rate/action_query_proj': 6.367401910652084e-05, 'learning_rate/base': 1.591850477663021e-05, 'epoch': 0.26}) +[2026-07-26 22:39:05,694][starVLA.training.train_starvla][INFO] - Step 2110, Loss: {'train/loss': 0.23937273025512695, 'train/grad_norm_pre_clip': 2.6882221698760986, 'timing/data': 0.00018107611685991287, 'timing/model': 0.46699264412745833, 'learning_rate/action_model': 6.364476307817956e-05, 'learning_rate/action_query_proj': 6.364476307817956e-05, 'learning_rate/base': 1.591119076954489e-05, 'epoch': 0.26}) +[2026-07-26 22:39:11,486][starVLA.training.train_starvla][INFO] - Step 2111, Loss: {'train/loss': 0.2689318060874939, 'train/grad_norm_pre_clip': 3.7690987586975098, 'timing/data': 0.00017178338021039963, 'timing/model': 0.4599353917874396, 'learning_rate/action_model': 6.361550245267024e-05, 'learning_rate/action_query_proj': 6.361550245267024e-05, 'learning_rate/base': 1.590387561316756e-05, 'epoch': 0.26}) +[2026-07-26 22:39:16,990][starVLA.training.train_starvla][INFO] - Step 2112, Loss: {'train/loss': 0.2999340295791626, 'train/grad_norm_pre_clip': 4.694171905517578, 'timing/data': 0.00017360085621476173, 'timing/model': 0.4595360392704606, 'learning_rate/action_model': 6.358623724154451e-05, 'learning_rate/action_query_proj': 6.358623724154451e-05, 'learning_rate/base': 1.5896559310386127e-05, 'epoch': 0.26}) +[2026-07-26 22:39:22,504][starVLA.training.train_starvla][INFO] - Step 2113, Loss: {'train/loss': 0.3452371060848236, 'train/grad_norm_pre_clip': 4.30427885055542, 'timing/data': 0.00017502810806035995, 'timing/model': 0.45846139593049884, 'learning_rate/action_model': 6.35569674563558e-05, 'learning_rate/action_query_proj': 6.35569674563558e-05, 'learning_rate/base': 1.588924186408895e-05, 'epoch': 0.26}) +[2026-07-26 22:39:28,021][starVLA.training.train_starvla][INFO] - Step 2114, Loss: {'train/loss': 0.3404526710510254, 'train/grad_norm_pre_clip': 5.139298439025879, 'timing/data': 0.00017964886501431465, 'timing/model': 0.46058294316753745, 'learning_rate/action_model': 6.352769310865936e-05, 'learning_rate/action_query_proj': 6.352769310865936e-05, 'learning_rate/base': 1.588192327716484e-05, 'epoch': 0.26}) +[2026-07-26 22:39:33,540][starVLA.training.train_starvla][INFO] - Step 2115, Loss: {'train/loss': 0.2711239755153656, 'train/grad_norm_pre_clip': 3.990626811981201, 'timing/data': 0.0001774490810930729, 'timing/model': 0.45984868379309773, 'learning_rate/action_model': 6.349841421001226e-05, 'learning_rate/action_query_proj': 6.349841421001226e-05, 'learning_rate/base': 1.5874603552503065e-05, 'epoch': 0.26}) +[2026-07-26 22:39:39,060][starVLA.training.train_starvla][INFO] - Step 2116, Loss: {'train/loss': 0.28719562292099, 'train/grad_norm_pre_clip': 4.156073093414307, 'timing/data': 0.0001826002262532711, 'timing/model': 0.4602755131199956, 'learning_rate/action_model': 6.346913077197331e-05, 'learning_rate/action_query_proj': 6.346913077197331e-05, 'learning_rate/base': 1.5867282692993328e-05, 'epoch': 0.26}) +[2026-07-26 22:39:44,597][starVLA.training.train_starvla][INFO] - Step 2117, Loss: {'train/loss': 0.1827271729707718, 'train/grad_norm_pre_clip': 3.3635122776031494, 'timing/data': 0.00018846476450562477, 'timing/model': 0.458792211022228, 'learning_rate/action_model': 6.343984280610317e-05, 'learning_rate/action_query_proj': 6.343984280610317e-05, 'learning_rate/base': 1.5859960701525793e-05, 'epoch': 0.26}) +[2026-07-26 22:39:50,126][starVLA.training.train_starvla][INFO] - Step 2118, Loss: {'train/loss': 0.24192601442337036, 'train/grad_norm_pre_clip': 4.053901672363281, 'timing/data': 0.0001827077940106392, 'timing/model': 0.46116588544100523, 'learning_rate/action_model': 6.341055032396427e-05, 'learning_rate/action_query_proj': 6.341055032396427e-05, 'learning_rate/base': 1.585263758099107e-05, 'epoch': 0.26}) +[2026-07-26 22:39:55,651][starVLA.training.train_starvla][INFO] - Step 2119, Loss: {'train/loss': 0.2699313163757324, 'train/grad_norm_pre_clip': 3.4066989421844482, 'timing/data': 0.0001691938377916813, 'timing/model': 0.4615126308053732, 'learning_rate/action_model': 6.338125333712082e-05, 'learning_rate/action_query_proj': 6.338125333712082e-05, 'learning_rate/base': 1.5845313334280205e-05, 'epoch': 0.26}) +[2026-07-26 22:40:01,202][starVLA.training.train_starvla][INFO] - Step 2120, Loss: {'train/loss': 0.15418463945388794, 'train/grad_norm_pre_clip': 2.2832207679748535, 'timing/data': 0.00019355211406946182, 'timing/model': 0.46140180714428425, 'learning_rate/action_model': 6.335195185713879e-05, 'learning_rate/action_query_proj': 6.335195185713879e-05, 'learning_rate/base': 1.5837987964284697e-05, 'epoch': 0.26}) +[2026-07-26 22:40:06,784][starVLA.training.train_starvla][INFO] - Step 2121, Loss: {'train/loss': 0.20699958503246307, 'train/grad_norm_pre_clip': 2.780933380126953, 'timing/data': 0.00018038274720311165, 'timing/model': 0.4628649689257145, 'learning_rate/action_model': 6.332264589558595e-05, 'learning_rate/action_query_proj': 6.332264589558595e-05, 'learning_rate/base': 1.5830661473896486e-05, 'epoch': 0.26}) +[2026-07-26 22:40:12,321][starVLA.training.train_starvla][INFO] - Step 2122, Loss: {'train/loss': 0.17020457983016968, 'train/grad_norm_pre_clip': 3.0745465755462646, 'timing/data': 0.00017320411279797554, 'timing/model': 0.4590088059194386, 'learning_rate/action_model': 6.329333546403182e-05, 'learning_rate/action_query_proj': 6.329333546403182e-05, 'learning_rate/base': 1.5823333866007954e-05, 'epoch': 0.26}) +[2026-07-26 22:40:17,900][starVLA.training.train_starvla][INFO] - Step 2123, Loss: {'train/loss': 0.14238066971302032, 'train/grad_norm_pre_clip': 2.727736234664917, 'timing/data': 0.00017800834029912949, 'timing/model': 0.46044138399884105, 'learning_rate/action_model': 6.32640205740477e-05, 'learning_rate/action_query_proj': 6.32640205740477e-05, 'learning_rate/base': 1.5816005143511924e-05, 'epoch': 0.26}) +[2026-07-26 22:40:23,453][starVLA.training.train_starvla][INFO] - Step 2124, Loss: {'train/loss': 0.26774606108665466, 'train/grad_norm_pre_clip': 4.708238124847412, 'timing/data': 0.00017054984346032143, 'timing/model': 0.4594093351624906, 'learning_rate/action_model': 6.323470123720665e-05, 'learning_rate/action_query_proj': 6.323470123720665e-05, 'learning_rate/base': 1.580867530930166e-05, 'epoch': 0.26}) +[2026-07-26 22:40:28,998][starVLA.training.train_starvla][INFO] - Step 2125, Loss: {'train/loss': 0.22529588639736176, 'train/grad_norm_pre_clip': 4.474598407745361, 'timing/data': 0.0001738998107612133, 'timing/model': 0.4596110531128943, 'learning_rate/action_model': 6.320537746508347e-05, 'learning_rate/action_query_proj': 6.320537746508347e-05, 'learning_rate/base': 1.5801344366270868e-05, 'epoch': 0.26}) +[2026-07-26 22:40:34,554][starVLA.training.train_starvla][INFO] - Step 2126, Loss: {'train/loss': 0.233965665102005, 'train/grad_norm_pre_clip': 3.76442813873291, 'timing/data': 0.0001749466173350811, 'timing/model': 0.4608490481041372, 'learning_rate/action_model': 6.317604926925473e-05, 'learning_rate/action_query_proj': 6.317604926925473e-05, 'learning_rate/base': 1.579401231731368e-05, 'epoch': 0.26}) +[2026-07-26 22:40:40,100][starVLA.training.train_starvla][INFO] - Step 2127, Loss: {'train/loss': 0.2081722766160965, 'train/grad_norm_pre_clip': 3.865180730819702, 'timing/data': 0.00018599117174744606, 'timing/model': 0.45940794330090284, 'learning_rate/action_model': 6.314671666129871e-05, 'learning_rate/action_query_proj': 6.314671666129871e-05, 'learning_rate/base': 1.578667916532468e-05, 'epoch': 0.26}) +[2026-07-26 22:40:45,661][starVLA.training.train_starvla][INFO] - Step 2128, Loss: {'train/loss': 0.29506373405456543, 'train/grad_norm_pre_clip': 4.1734395027160645, 'timing/data': 0.0001816130243241787, 'timing/model': 0.45997487008571625, 'learning_rate/action_model': 6.311737965279551e-05, 'learning_rate/action_query_proj': 6.311737965279551e-05, 'learning_rate/base': 1.577934491319888e-05, 'epoch': 0.26}) +[2026-07-26 22:40:51,232][starVLA.training.train_starvla][INFO] - Step 2129, Loss: {'train/loss': 0.26756760478019714, 'train/grad_norm_pre_clip': 3.959578275680542, 'timing/data': 0.000167052261531353, 'timing/model': 0.45880101062357426, 'learning_rate/action_model': 6.308803825532689e-05, 'learning_rate/action_query_proj': 6.308803825532689e-05, 'learning_rate/base': 1.5772009563831722e-05, 'epoch': 0.26}) +[2026-07-26 22:40:57,013][starVLA.training.train_starvla][INFO] - Step 2130, Loss: {'train/loss': 0.2546534538269043, 'train/grad_norm_pre_clip': 4.202487468719482, 'timing/data': 0.00017411401495337486, 'timing/model': 0.4608520190231502, 'learning_rate/action_model': 6.305869248047635e-05, 'learning_rate/action_query_proj': 6.305869248047635e-05, 'learning_rate/base': 1.576467312011909e-05, 'epoch': 0.26}) +[2026-07-26 22:41:02,808][starVLA.training.train_starvla][INFO] - Step 2131, Loss: {'train/loss': 0.27916228771209717, 'train/grad_norm_pre_clip': 3.6641247272491455, 'timing/data': 0.0001893630251288414, 'timing/model': 0.4568423228338361, 'learning_rate/action_model': 6.302934233982916e-05, 'learning_rate/action_query_proj': 6.302934233982916e-05, 'learning_rate/base': 1.575733558495729e-05, 'epoch': 0.26}) +[2026-07-26 22:41:08,353][starVLA.training.train_starvla][INFO] - Step 2132, Loss: {'train/loss': 0.18443509936332703, 'train/grad_norm_pre_clip': 3.427410125732422, 'timing/data': 0.00023995712399482727, 'timing/model': 0.45674607576802373, 'learning_rate/action_model': 6.29999878449723e-05, 'learning_rate/action_query_proj': 6.29999878449723e-05, 'learning_rate/base': 1.5749996961243074e-05, 'epoch': 0.26}) +[2026-07-26 22:41:13,892][starVLA.training.train_starvla][INFO] - Step 2133, Loss: {'train/loss': 0.16679354012012482, 'train/grad_norm_pre_clip': 2.676295518875122, 'timing/data': 0.0001791459508240223, 'timing/model': 0.45797968888655305, 'learning_rate/action_model': 6.297062900749442e-05, 'learning_rate/action_query_proj': 6.297062900749442e-05, 'learning_rate/base': 1.5742657251873605e-05, 'epoch': 0.26}) +[2026-07-26 22:41:19,416][starVLA.training.train_starvla][INFO] - Step 2134, Loss: {'train/loss': 0.3566405475139618, 'train/grad_norm_pre_clip': 3.4739620685577393, 'timing/data': 0.0001715528778731823, 'timing/model': 0.45920423371717334, 'learning_rate/action_model': 6.294126583898596e-05, 'learning_rate/action_query_proj': 6.294126583898596e-05, 'learning_rate/base': 1.573531645974649e-05, 'epoch': 0.26}) +[2026-07-26 22:41:24,897][starVLA.training.train_starvla][INFO] - Step 2135, Loss: {'train/loss': 0.24538399279117584, 'train/grad_norm_pre_clip': 4.947198390960693, 'timing/data': 0.0001837611198425293, 'timing/model': 0.45768988505005836, 'learning_rate/action_model': 6.291189835103903e-05, 'learning_rate/action_query_proj': 6.291189835103903e-05, 'learning_rate/base': 1.572797458775976e-05, 'epoch': 0.26}) +[2026-07-26 22:41:30,387][starVLA.training.train_starvla][INFO] - Step 2136, Loss: {'train/loss': 0.2455386072397232, 'train/grad_norm_pre_clip': 3.3513193130493164, 'timing/data': 0.0001712101511657238, 'timing/model': 0.458210495300591, 'learning_rate/action_model': 6.288252655524744e-05, 'learning_rate/action_query_proj': 6.288252655524744e-05, 'learning_rate/base': 1.572063163881186e-05, 'epoch': 0.26}) +[2026-07-26 22:41:36,088][starVLA.training.train_starvla][INFO] - Step 2137, Loss: {'train/loss': 0.14920131862163544, 'train/grad_norm_pre_clip': 3.8189761638641357, 'timing/data': 0.0001759640872478485, 'timing/model': 0.45725937793031335, 'learning_rate/action_model': 6.28531504632067e-05, 'learning_rate/action_query_proj': 6.28531504632067e-05, 'learning_rate/base': 1.5713287615801676e-05, 'epoch': 0.26}) +[2026-07-26 22:41:41,568][starVLA.training.train_starvla][INFO] - Step 2138, Loss: {'train/loss': 0.3232533633708954, 'train/grad_norm_pre_clip': 4.210965633392334, 'timing/data': 0.00017416523769497871, 'timing/model': 0.45813869312405586, 'learning_rate/action_model': 6.282377008651405e-05, 'learning_rate/action_query_proj': 6.282377008651405e-05, 'learning_rate/base': 1.5705942521628513e-05, 'epoch': 0.26}) +[2026-07-26 22:41:47,050][starVLA.training.train_starvla][INFO] - Step 2139, Loss: {'train/loss': 0.33389851450920105, 'train/grad_norm_pre_clip': 3.9958159923553467, 'timing/data': 0.00016915518790483475, 'timing/model': 0.4581148470751941, 'learning_rate/action_model': 6.27943854367684e-05, 'learning_rate/action_query_proj': 6.27943854367684e-05, 'learning_rate/base': 1.56985963591921e-05, 'epoch': 0.26}) +[2026-07-26 22:41:52,530][starVLA.training.train_starvla][INFO] - Step 2140, Loss: {'train/loss': 0.32240423560142517, 'train/grad_norm_pre_clip': 4.501708984375, 'timing/data': 0.00016925903037190437, 'timing/model': 0.4581140819936991, 'learning_rate/action_model': 6.276499652557031e-05, 'learning_rate/action_query_proj': 6.276499652557031e-05, 'learning_rate/base': 1.5691249131392578e-05, 'epoch': 0.26}) +[2026-07-26 22:41:58,021][starVLA.training.train_starvla][INFO] - Step 2141, Loss: {'train/loss': 0.2042548954486847, 'train/grad_norm_pre_clip': 3.162964344024658, 'timing/data': 0.00017059920355677605, 'timing/model': 0.4587253979407251, 'learning_rate/action_model': 6.273560336452207e-05, 'learning_rate/action_query_proj': 6.273560336452207e-05, 'learning_rate/base': 1.5683900841130517e-05, 'epoch': 0.26}) +[2026-07-26 22:42:03,505][starVLA.training.train_starvla][INFO] - Step 2142, Loss: {'train/loss': 0.22907790541648865, 'train/grad_norm_pre_clip': 3.4267613887786865, 'timing/data': 0.00017339829355478287, 'timing/model': 0.45744064496830106, 'learning_rate/action_model': 6.270620596522765e-05, 'learning_rate/action_query_proj': 6.270620596522765e-05, 'learning_rate/base': 1.5676551491306913e-05, 'epoch': 0.26}) +[2026-07-26 22:42:09,026][starVLA.training.train_starvla][INFO] - Step 2143, Loss: {'train/loss': 0.43932661414146423, 'train/grad_norm_pre_clip': 4.502662181854248, 'timing/data': 0.00017083296552300453, 'timing/model': 0.46223238483071327, 'learning_rate/action_model': 6.267680433929269e-05, 'learning_rate/action_query_proj': 6.267680433929269e-05, 'learning_rate/base': 1.5669201084823172e-05, 'epoch': 0.26}) +[2026-07-26 22:42:14,550][starVLA.training.train_starvla][INFO] - Step 2144, Loss: {'train/loss': 0.26415759325027466, 'train/grad_norm_pre_clip': 4.843015193939209, 'timing/data': 0.0001782551407814026, 'timing/model': 0.4588072490878403, 'learning_rate/action_model': 6.264739849832441e-05, 'learning_rate/action_query_proj': 6.264739849832441e-05, 'learning_rate/base': 1.5661849624581103e-05, 'epoch': 0.26}) +[2026-07-26 22:42:20,069][starVLA.training.train_starvla][INFO] - Step 2145, Loss: {'train/loss': 0.34202438592910767, 'train/grad_norm_pre_clip': 3.8469152450561523, 'timing/data': 0.00017163017764687538, 'timing/model': 0.4610957521945238, 'learning_rate/action_model': 6.261798845393188e-05, 'learning_rate/action_query_proj': 6.261798845393188e-05, 'learning_rate/base': 1.565449711348297e-05, 'epoch': 0.26}) +[2026-07-26 22:42:25,613][starVLA.training.train_starvla][INFO] - Step 2146, Loss: {'train/loss': 0.27058112621307373, 'train/grad_norm_pre_clip': 3.9456064701080322, 'timing/data': 0.00017151422798633575, 'timing/model': 0.4626275608316064, 'learning_rate/action_model': 6.258857421772563e-05, 'learning_rate/action_query_proj': 6.258857421772563e-05, 'learning_rate/base': 1.5647143554431408e-05, 'epoch': 0.26}) +[2026-07-26 22:42:31,168][starVLA.training.train_starvla][INFO] - Step 2147, Loss: {'train/loss': 0.2317698746919632, 'train/grad_norm_pre_clip': 4.255947113037109, 'timing/data': 0.00017070118337869644, 'timing/model': 0.4600587859749794, 'learning_rate/action_model': 6.255915580131798e-05, 'learning_rate/action_query_proj': 6.255915580131798e-05, 'learning_rate/base': 1.5639788950329495e-05, 'epoch': 0.26}) +[2026-07-26 22:42:36,767][starVLA.training.train_starvla][INFO] - Step 2148, Loss: {'train/loss': 0.2342209368944168, 'train/grad_norm_pre_clip': 2.890021562576294, 'timing/data': 0.0001698145642876625, 'timing/model': 0.45972580276429653, 'learning_rate/action_model': 6.252973321632285e-05, 'learning_rate/action_query_proj': 6.252973321632285e-05, 'learning_rate/base': 1.563243330408071e-05, 'epoch': 0.26}) +[2026-07-26 22:42:42,343][starVLA.training.train_starvla][INFO] - Step 2149, Loss: {'train/loss': 0.29995232820510864, 'train/grad_norm_pre_clip': 4.143825054168701, 'timing/data': 0.00017076591029763222, 'timing/model': 0.4582172390073538, 'learning_rate/action_model': 6.250030647435581e-05, 'learning_rate/action_query_proj': 6.250030647435581e-05, 'learning_rate/base': 1.5625076618588952e-05, 'epoch': 0.26}) +[2026-07-26 22:42:47,910][starVLA.training.train_starvla][INFO] - Step 2150, Loss: {'train/loss': 0.2361360341310501, 'train/grad_norm_pre_clip': 4.00314474105835, 'timing/data': 0.00017406605184078217, 'timing/model': 0.4583782576955855, 'learning_rate/action_model': 6.247087558703405e-05, 'learning_rate/action_query_proj': 6.247087558703405e-05, 'learning_rate/base': 1.561771889675851e-05, 'epoch': 0.26}) +[2026-07-26 22:42:53,482][starVLA.training.train_starvla][INFO] - Step 2151, Loss: {'train/loss': 0.26748165488243103, 'train/grad_norm_pre_clip': 3.3108341693878174, 'timing/data': 0.00017245719209313393, 'timing/model': 0.45750577095896006, 'learning_rate/action_model': 6.244144056597644e-05, 'learning_rate/action_query_proj': 6.244144056597644e-05, 'learning_rate/base': 1.561036014149411e-05, 'epoch': 0.26}) +[2026-07-26 22:42:59,055][starVLA.training.train_starvla][INFO] - Step 2152, Loss: {'train/loss': 0.20634707808494568, 'train/grad_norm_pre_clip': 2.695080280303955, 'timing/data': 0.0001725759357213974, 'timing/model': 0.45771342143416405, 'learning_rate/action_model': 6.241200142280347e-05, 'learning_rate/action_query_proj': 6.241200142280347e-05, 'learning_rate/base': 1.5603000355700867e-05, 'epoch': 0.26}) +[2026-07-26 22:43:04,615][starVLA.training.train_starvla][INFO] - Step 2153, Loss: {'train/loss': 0.2190513014793396, 'train/grad_norm_pre_clip': 2.5926032066345215, 'timing/data': 0.0002197069115936756, 'timing/model': 0.4577629598788917, 'learning_rate/action_model': 6.238255816913721e-05, 'learning_rate/action_query_proj': 6.238255816913721e-05, 'learning_rate/base': 1.5595639542284303e-05, 'epoch': 0.26}) +[2026-07-26 22:43:10,177][starVLA.training.train_starvla][INFO] - Step 2154, Loss: {'train/loss': 0.24909690022468567, 'train/grad_norm_pre_clip': 3.7753467559814453, 'timing/data': 0.0001894109882414341, 'timing/model': 0.4575219275429845, 'learning_rate/action_model': 6.235311081660142e-05, 'learning_rate/action_query_proj': 6.235311081660142e-05, 'learning_rate/base': 1.5588277704150356e-05, 'epoch': 0.26}) +[2026-07-26 22:43:15,743][starVLA.training.train_starvla][INFO] - Step 2155, Loss: {'train/loss': 0.2416883111000061, 'train/grad_norm_pre_clip': 3.1750736236572266, 'timing/data': 0.00017636176198720932, 'timing/model': 0.45849720388650894, 'learning_rate/action_model': 6.232365937682145e-05, 'learning_rate/action_query_proj': 6.232365937682145e-05, 'learning_rate/base': 1.558091484420536e-05, 'epoch': 0.26}) +[2026-07-26 22:43:21,312][starVLA.training.train_starvla][INFO] - Step 2156, Loss: {'train/loss': 0.21173883974552155, 'train/grad_norm_pre_clip': 3.0768990516662598, 'timing/data': 0.00017541879788041115, 'timing/model': 0.4575848658569157, 'learning_rate/action_model': 6.229420386142424e-05, 'learning_rate/action_query_proj': 6.229420386142424e-05, 'learning_rate/base': 1.557355096535606e-05, 'epoch': 0.26}) +[2026-07-26 22:43:26,898][starVLA.training.train_starvla][INFO] - Step 2157, Loss: {'train/loss': 0.3176558315753937, 'train/grad_norm_pre_clip': 3.4038827419281006, 'timing/data': 0.00017208093777298927, 'timing/model': 0.45674921991303563, 'learning_rate/action_model': 6.226474428203838e-05, 'learning_rate/action_query_proj': 6.226474428203838e-05, 'learning_rate/base': 1.5566186070509596e-05, 'epoch': 0.26}) +[2026-07-26 22:43:32,492][starVLA.training.train_starvla][INFO] - Step 2158, Loss: {'train/loss': 0.29980137944221497, 'train/grad_norm_pre_clip': 3.7780680656433105, 'timing/data': 0.00018533272668719292, 'timing/model': 0.4588169762864709, 'learning_rate/action_model': 6.223528065029406e-05, 'learning_rate/action_query_proj': 6.223528065029406e-05, 'learning_rate/base': 1.5558820162573516e-05, 'epoch': 0.26}) +[2026-07-26 22:43:38,070][starVLA.training.train_starvla][INFO] - Step 2159, Loss: {'train/loss': 0.28538617491722107, 'train/grad_norm_pre_clip': 3.2674508094787598, 'timing/data': 0.00018005305901169777, 'timing/model': 0.4583467999473214, 'learning_rate/action_model': 6.2205812977823e-05, 'learning_rate/action_query_proj': 6.2205812977823e-05, 'learning_rate/base': 1.555145324445575e-05, 'epoch': 0.26}) +[2026-07-26 22:43:43,637][starVLA.training.train_starvla][INFO] - Step 2160, Loss: {'train/loss': 0.20512068271636963, 'train/grad_norm_pre_clip': 2.5392794609069824, 'timing/data': 0.0001782323233783245, 'timing/model': 0.45690850308164954, 'learning_rate/action_model': 6.217634127625863e-05, 'learning_rate/action_query_proj': 6.217634127625863e-05, 'learning_rate/base': 1.5544085319064658e-05, 'epoch': 0.26}) +[2026-07-26 22:43:49,414][starVLA.training.train_starvla][INFO] - Step 2161, Loss: {'train/loss': 0.21908307075500488, 'train/grad_norm_pre_clip': 3.285130739212036, 'timing/data': 0.0001777452416718006, 'timing/model': 0.45821937872096896, 'learning_rate/action_model': 6.21468655572359e-05, 'learning_rate/action_query_proj': 6.21468655572359e-05, 'learning_rate/base': 1.5536716389308974e-05, 'epoch': 0.26}) +[2026-07-26 22:43:55,036][starVLA.training.train_starvla][INFO] - Step 2162, Loss: {'train/loss': 0.1530744731426239, 'train/grad_norm_pre_clip': 2.4751532077789307, 'timing/data': 0.00020180270075798035, 'timing/model': 0.4585321699269116, 'learning_rate/action_model': 6.211738583239129e-05, 'learning_rate/action_query_proj': 6.211738583239129e-05, 'learning_rate/base': 1.5529346458097823e-05, 'epoch': 0.26}) +[2026-07-26 22:44:00,650][starVLA.training.train_starvla][INFO] - Step 2163, Loss: {'train/loss': 0.17652711272239685, 'train/grad_norm_pre_clip': 2.8142120838165283, 'timing/data': 0.00019995402544736862, 'timing/model': 0.5017564631998539, 'learning_rate/action_model': 6.208790211336303e-05, 'learning_rate/action_query_proj': 6.208790211336303e-05, 'learning_rate/base': 1.5521975528340758e-05, 'epoch': 0.26}) +[2026-07-26 22:44:06,206][starVLA.training.train_starvla][INFO] - Step 2164, Loss: {'train/loss': 0.307853102684021, 'train/grad_norm_pre_clip': 2.7879490852355957, 'timing/data': 0.0001694709062576294, 'timing/model': 0.45784803479909897, 'learning_rate/action_model': 6.205841441179074e-05, 'learning_rate/action_query_proj': 6.205841441179074e-05, 'learning_rate/base': 1.5514603602947685e-05, 'epoch': 0.26}) +[2026-07-26 22:44:11,822][starVLA.training.train_starvla][INFO] - Step 2165, Loss: {'train/loss': 0.2384513020515442, 'train/grad_norm_pre_clip': 3.372136116027832, 'timing/data': 0.00017461879178881645, 'timing/model': 0.47326521994546056, 'learning_rate/action_model': 6.202892273931577e-05, 'learning_rate/action_query_proj': 6.202892273931577e-05, 'learning_rate/base': 1.550723068482894e-05, 'epoch': 0.26}) +[2026-07-26 22:44:17,412][starVLA.training.train_starvla][INFO] - Step 2166, Loss: {'train/loss': 0.2068793922662735, 'train/grad_norm_pre_clip': 3.00744366645813, 'timing/data': 0.00016856472939252853, 'timing/model': 0.4775150059722364, 'learning_rate/action_model': 6.199942710758092e-05, 'learning_rate/action_query_proj': 6.199942710758092e-05, 'learning_rate/base': 1.549985677689523e-05, 'epoch': 0.26}) +[2026-07-26 22:44:23,078][starVLA.training.train_starvla][INFO] - Step 2167, Loss: {'train/loss': 0.20341777801513672, 'train/grad_norm_pre_clip': 3.647817373275757, 'timing/data': 0.00018246378749608994, 'timing/model': 0.533474599942565, 'learning_rate/action_model': 6.19699275282306e-05, 'learning_rate/action_query_proj': 6.19699275282306e-05, 'learning_rate/base': 1.549248188205765e-05, 'epoch': 0.26}) +[2026-07-26 22:44:28,648][starVLA.training.train_starvla][INFO] - Step 2168, Loss: {'train/loss': 0.32655075192451477, 'train/grad_norm_pre_clip': 3.2491087913513184, 'timing/data': 0.00017608515918254852, 'timing/model': 0.4600503668189049, 'learning_rate/action_model': 6.19404240129108e-05, 'learning_rate/action_query_proj': 6.19404240129108e-05, 'learning_rate/base': 1.54851060032277e-05, 'epoch': 0.26}) +[2026-07-26 22:44:34,234][starVLA.training.train_starvla][INFO] - Step 2169, Loss: {'train/loss': 0.37248650193214417, 'train/grad_norm_pre_clip': 4.36372709274292, 'timing/data': 0.00017233286052942276, 'timing/model': 0.46038719918578863, 'learning_rate/action_model': 6.191091657326899e-05, 'learning_rate/action_query_proj': 6.191091657326899e-05, 'learning_rate/base': 1.5477729143317248e-05, 'epoch': 0.26}) +[2026-07-26 22:44:39,826][starVLA.training.train_starvla][INFO] - Step 2170, Loss: {'train/loss': 0.27357378602027893, 'train/grad_norm_pre_clip': 3.2431068420410156, 'timing/data': 0.000180722214281559, 'timing/model': 0.46051622880622745, 'learning_rate/action_model': 6.188140522095431e-05, 'learning_rate/action_query_proj': 6.188140522095431e-05, 'learning_rate/base': 1.5470351305238578e-05, 'epoch': 0.26}) +[2026-07-26 22:44:45,387][starVLA.training.train_starvla][INFO] - Step 2171, Loss: {'train/loss': 0.23006176948547363, 'train/grad_norm_pre_clip': 2.816004753112793, 'timing/data': 0.00017223460599780083, 'timing/model': 0.45929660415276885, 'learning_rate/action_model': 6.185188996761733e-05, 'learning_rate/action_query_proj': 6.185188996761733e-05, 'learning_rate/base': 1.5462972491904332e-05, 'epoch': 0.26}) +[2026-07-26 22:44:50,960][starVLA.training.train_starvla][INFO] - Step 2172, Loss: {'train/loss': 0.26899898052215576, 'train/grad_norm_pre_clip': 4.547600746154785, 'timing/data': 0.00017235474660992622, 'timing/model': 0.4595770472660661, 'learning_rate/action_model': 6.182237082491021e-05, 'learning_rate/action_query_proj': 6.182237082491021e-05, 'learning_rate/base': 1.5455592706227553e-05, 'epoch': 0.26}) +[2026-07-26 22:44:56,797][starVLA.training.train_starvla][INFO] - Step 2173, Loss: {'train/loss': 0.21137380599975586, 'train/grad_norm_pre_clip': 3.0865442752838135, 'timing/data': 0.00017366092652082443, 'timing/model': 0.4588727680966258, 'learning_rate/action_model': 6.179284780448667e-05, 'learning_rate/action_query_proj': 6.179284780448667e-05, 'learning_rate/base': 1.5448211951121667e-05, 'epoch': 0.26}) +[2026-07-26 22:45:02,367][starVLA.training.train_starvla][INFO] - Step 2174, Loss: {'train/loss': 0.22016791999340057, 'train/grad_norm_pre_clip': 3.0888671875, 'timing/data': 0.00019086012616753578, 'timing/model': 0.45944599620997906, 'learning_rate/action_model': 6.176332091800186e-05, 'learning_rate/action_query_proj': 6.176332091800186e-05, 'learning_rate/base': 1.5440830229500465e-05, 'epoch': 0.26}) +[2026-07-26 22:45:07,948][starVLA.training.train_starvla][INFO] - Step 2175, Loss: {'train/loss': 0.2796729505062103, 'train/grad_norm_pre_clip': 4.199902057647705, 'timing/data': 0.00016743317246437073, 'timing/model': 0.4592976071871817, 'learning_rate/action_model': 6.17337901771126e-05, 'learning_rate/action_query_proj': 6.17337901771126e-05, 'learning_rate/base': 1.543344754427815e-05, 'epoch': 0.26}) +[2026-07-26 22:45:13,510][starVLA.training.train_starvla][INFO] - Step 2176, Loss: {'train/loss': 0.2516143321990967, 'train/grad_norm_pre_clip': 3.375753402709961, 'timing/data': 0.00017303414642810822, 'timing/model': 0.457144892308861, 'learning_rate/action_model': 6.170425559347713e-05, 'learning_rate/action_query_proj': 6.170425559347713e-05, 'learning_rate/base': 1.5426063898369283e-05, 'epoch': 0.26}) +[2026-07-26 22:45:19,070][starVLA.training.train_starvla][INFO] - Step 2177, Loss: {'train/loss': 0.3458893299102783, 'train/grad_norm_pre_clip': 5.479530334472656, 'timing/data': 0.0003125350922346115, 'timing/model': 0.4555821311660111, 'learning_rate/action_model': 6.167471717875523e-05, 'learning_rate/action_query_proj': 6.167471717875523e-05, 'learning_rate/base': 1.5418679294688808e-05, 'epoch': 0.26}) +[2026-07-26 22:45:24,614][starVLA.training.train_starvla][INFO] - Step 2178, Loss: {'train/loss': 0.1915837824344635, 'train/grad_norm_pre_clip': 2.156825065612793, 'timing/data': 0.00016920221969485283, 'timing/model': 0.45758092077448964, 'learning_rate/action_model': 6.164517494460822e-05, 'learning_rate/action_query_proj': 6.164517494460822e-05, 'learning_rate/base': 1.5411293736152055e-05, 'epoch': 0.26}) +[2026-07-26 22:45:30,122][starVLA.training.train_starvla][INFO] - Step 2179, Loss: {'train/loss': 0.28411316871643066, 'train/grad_norm_pre_clip': 4.487966537475586, 'timing/data': 0.00017071189358830452, 'timing/model': 0.45816768798977137, 'learning_rate/action_model': 6.161562890269888e-05, 'learning_rate/action_query_proj': 6.161562890269888e-05, 'learning_rate/base': 1.540390722567472e-05, 'epoch': 0.26}) +[2026-07-26 22:45:35,639][starVLA.training.train_starvla][INFO] - Step 2180, Loss: {'train/loss': 0.3473186194896698, 'train/grad_norm_pre_clip': 4.437093257904053, 'timing/data': 0.0001751095987856388, 'timing/model': 0.4576570917852223, 'learning_rate/action_model': 6.158607906469154e-05, 'learning_rate/action_query_proj': 6.158607906469154e-05, 'learning_rate/base': 1.5396519766172884e-05, 'epoch': 0.26}) +[2026-07-26 22:45:41,172][starVLA.training.train_starvla][INFO] - Step 2181, Loss: {'train/loss': 0.2153560221195221, 'train/grad_norm_pre_clip': 3.4584898948669434, 'timing/data': 0.00017520226538181305, 'timing/model': 0.4582083420827985, 'learning_rate/action_model': 6.1556525442252e-05, 'learning_rate/action_query_proj': 6.1556525442252e-05, 'learning_rate/base': 1.5389131360563e-05, 'epoch': 0.26}) +[2026-07-26 22:45:46,682][starVLA.training.train_starvla][INFO] - Step 2182, Loss: {'train/loss': 0.29039013385772705, 'train/grad_norm_pre_clip': 3.8691020011901855, 'timing/data': 0.00017423368990421295, 'timing/model': 0.45767842698842287, 'learning_rate/action_model': 6.152696804704755e-05, 'learning_rate/action_query_proj': 6.152696804704755e-05, 'learning_rate/base': 1.5381742011761886e-05, 'epoch': 0.26}) +[2026-07-26 22:45:52,195][starVLA.training.train_starvla][INFO] - Step 2183, Loss: {'train/loss': 0.27272921800613403, 'train/grad_norm_pre_clip': 3.771947145462036, 'timing/data': 0.00017321528866887093, 'timing/model': 0.45914177503436804, 'learning_rate/action_model': 6.1497406890747e-05, 'learning_rate/action_query_proj': 6.1497406890747e-05, 'learning_rate/base': 1.537435172268675e-05, 'epoch': 0.26}) +[2026-07-26 22:45:57,713][starVLA.training.train_starvla][INFO] - Step 2184, Loss: {'train/loss': 0.26377320289611816, 'train/grad_norm_pre_clip': 4.5446248054504395, 'timing/data': 0.0001748800277709961, 'timing/model': 0.45792051684111357, 'learning_rate/action_model': 6.146784198502062e-05, 'learning_rate/action_query_proj': 6.146784198502062e-05, 'learning_rate/base': 1.5366960496255155e-05, 'epoch': 0.26}) +[2026-07-26 22:46:03,228][starVLA.training.train_starvla][INFO] - Step 2185, Loss: {'train/loss': 0.2109784036874771, 'train/grad_norm_pre_clip': 3.4204461574554443, 'timing/data': 0.00017340108752250671, 'timing/model': 0.4579630312509835, 'learning_rate/action_model': 6.143827334154016e-05, 'learning_rate/action_query_proj': 6.143827334154016e-05, 'learning_rate/base': 1.535956833538504e-05, 'epoch': 0.27}) +[2026-07-26 22:46:08,746][starVLA.training.train_starvla][INFO] - Step 2186, Loss: {'train/loss': 0.24918988347053528, 'train/grad_norm_pre_clip': 4.205227375030518, 'timing/data': 0.00017270399257540703, 'timing/model': 0.45816662814468145, 'learning_rate/action_model': 6.140870097197887e-05, 'learning_rate/action_query_proj': 6.140870097197887e-05, 'learning_rate/base': 1.5352175242994718e-05, 'epoch': 0.27}) +[2026-07-26 22:46:14,270][starVLA.training.train_starvla][INFO] - Step 2187, Loss: {'train/loss': 0.2973043620586395, 'train/grad_norm_pre_clip': 4.472860813140869, 'timing/data': 0.0001697121188044548, 'timing/model': 0.457894709892571, 'learning_rate/action_model': 6.137912488801144e-05, 'learning_rate/action_query_proj': 6.137912488801144e-05, 'learning_rate/base': 1.534478122200286e-05, 'epoch': 0.27}) +[2026-07-26 22:46:19,789][starVLA.training.train_starvla][INFO] - Step 2188, Loss: {'train/loss': 0.2821444571018219, 'train/grad_norm_pre_clip': 3.824399948120117, 'timing/data': 0.00017106998711824417, 'timing/model': 0.45855070091784, 'learning_rate/action_model': 6.134954510131403e-05, 'learning_rate/action_query_proj': 6.134954510131403e-05, 'learning_rate/base': 1.533738627532851e-05, 'epoch': 0.27}) +[2026-07-26 22:46:25,308][starVLA.training.train_starvla][INFO] - Step 2189, Loss: {'train/loss': 0.2239617109298706, 'train/grad_norm_pre_clip': 3.6192214488983154, 'timing/data': 0.00018299603834748268, 'timing/model': 0.45784122170880437, 'learning_rate/action_model': 6.131996162356428e-05, 'learning_rate/action_query_proj': 6.131996162356428e-05, 'learning_rate/base': 1.532999040589107e-05, 'epoch': 0.27}) +[2026-07-26 22:46:30,807][starVLA.training.train_starvla][INFO] - Step 2190, Loss: {'train/loss': 0.16440854966640472, 'train/grad_norm_pre_clip': 2.7979562282562256, 'timing/data': 0.0001688818447291851, 'timing/model': 0.45878860307857394, 'learning_rate/action_model': 6.12903744664413e-05, 'learning_rate/action_query_proj': 6.12903744664413e-05, 'learning_rate/base': 1.5322593616610325e-05, 'epoch': 0.27}) +[2026-07-26 22:46:36,329][starVLA.training.train_starvla][INFO] - Step 2191, Loss: {'train/loss': 0.2716352939605713, 'train/grad_norm_pre_clip': 4.324864864349365, 'timing/data': 0.0001760050654411316, 'timing/model': 0.4863719968125224, 'learning_rate/action_model': 6.12607836416256e-05, 'learning_rate/action_query_proj': 6.12607836416256e-05, 'learning_rate/base': 1.53151959104064e-05, 'epoch': 0.27}) +[2026-07-26 22:46:42,228][starVLA.training.train_starvla][INFO] - Step 2192, Loss: {'train/loss': 0.22750094532966614, 'train/grad_norm_pre_clip': 3.4710726737976074, 'timing/data': 0.00017210794612765312, 'timing/model': 0.4584872121922672, 'learning_rate/action_model': 6.123118916079919e-05, 'learning_rate/action_query_proj': 6.123118916079919e-05, 'learning_rate/base': 1.5307797290199798e-05, 'epoch': 0.27}) +[2026-07-26 22:46:47,723][starVLA.training.train_starvla][INFO] - Step 2193, Loss: {'train/loss': 0.31518667936325073, 'train/grad_norm_pre_clip': 3.5505435466766357, 'timing/data': 0.00017206603661179543, 'timing/model': 0.4572998001240194, 'learning_rate/action_model': 6.120159103564547e-05, 'learning_rate/action_query_proj': 6.120159103564547e-05, 'learning_rate/base': 1.5300397758911368e-05, 'epoch': 0.27}) +[2026-07-26 22:46:53,211][starVLA.training.train_starvla][INFO] - Step 2194, Loss: {'train/loss': 0.25265786051750183, 'train/grad_norm_pre_clip': 4.210837364196777, 'timing/data': 0.00017553428187966347, 'timing/model': 0.45726380636915565, 'learning_rate/action_model': 6.117198927784936e-05, 'learning_rate/action_query_proj': 6.117198927784936e-05, 'learning_rate/base': 1.529299731946234e-05, 'epoch': 0.27}) +[2026-07-26 22:46:58,721][starVLA.training.train_starvla][INFO] - Step 2195, Loss: {'train/loss': 0.20519182085990906, 'train/grad_norm_pre_clip': 3.1500744819641113, 'timing/data': 0.0001809210516512394, 'timing/model': 0.45884821098297834, 'learning_rate/action_model': 6.114238389909713e-05, 'learning_rate/action_query_proj': 6.114238389909713e-05, 'learning_rate/base': 1.5285595974774282e-05, 'epoch': 0.27}) +[2026-07-26 22:47:04,249][starVLA.training.train_starvla][INFO] - Step 2196, Loss: {'train/loss': 0.24764251708984375, 'train/grad_norm_pre_clip': 3.330477476119995, 'timing/data': 0.00017624301835894585, 'timing/model': 0.4582046796567738, 'learning_rate/action_model': 6.111277491107652e-05, 'learning_rate/action_query_proj': 6.111277491107652e-05, 'learning_rate/base': 1.527819372776913e-05, 'epoch': 0.27}) +[2026-07-26 22:47:09,785][starVLA.training.train_starvla][INFO] - Step 2197, Loss: {'train/loss': 0.2105933576822281, 'train/grad_norm_pre_clip': 3.3336048126220703, 'timing/data': 0.0001706150360405445, 'timing/model': 0.4577745380811393, 'learning_rate/action_model': 6.108316232547668e-05, 'learning_rate/action_query_proj': 6.108316232547668e-05, 'learning_rate/base': 1.527079058136917e-05, 'epoch': 0.27}) +[2026-07-26 22:47:15,312][starVLA.training.train_starvla][INFO] - Step 2198, Loss: {'train/loss': 0.1996040940284729, 'train/grad_norm_pre_clip': 2.8004961013793945, 'timing/data': 0.00017297500744462013, 'timing/model': 0.45697406213730574, 'learning_rate/action_model': 6.105354615398825e-05, 'learning_rate/action_query_proj': 6.105354615398825e-05, 'learning_rate/base': 1.526338653849706e-05, 'epoch': 0.27}) +[2026-07-26 22:47:20,840][starVLA.training.train_starvla][INFO] - Step 2199, Loss: {'train/loss': 0.317861944437027, 'train/grad_norm_pre_clip': 2.9792463779449463, 'timing/data': 0.00017440179362893105, 'timing/model': 0.457064607180655, 'learning_rate/action_model': 6.102392640830312e-05, 'learning_rate/action_query_proj': 6.102392640830312e-05, 'learning_rate/base': 1.525598160207578e-05, 'epoch': 0.27}) +[2026-07-26 22:47:26,372][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2200 +[2026-07-26 22:47:26,373][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2200 +[2026-07-26 22:47:26,374][starVLA.training.train_starvla][INFO] - Step 2200, Loss: {'train/loss': 0.1670370101928711, 'train/grad_norm_pre_clip': 2.819432497024536, 'timing/data': 0.0001696213148534298, 'timing/model': 0.45775745902210474, 'learning_rate/action_model': 6.099430310011479e-05, 'learning_rate/action_query_proj': 6.099430310011479e-05, 'learning_rate/base': 1.5248575775028697e-05, 'epoch': 0.27}) +[2026-07-26 22:47:31,905][starVLA.training.train_starvla][INFO] - Step 2201, Loss: {'train/loss': 0.21274076402187347, 'train/grad_norm_pre_clip': 2.6511592864990234, 'timing/data': 0.000173195730894804, 'timing/model': 0.4578797109425068, 'learning_rate/action_model': 6.0964676241118036e-05, 'learning_rate/action_query_proj': 6.0964676241118036e-05, 'learning_rate/base': 1.5241169060279509e-05, 'epoch': 0.27}) +[2026-07-26 22:47:37,403][starVLA.training.train_starvla][INFO] - Step 2202, Loss: {'train/loss': 0.17053121328353882, 'train/grad_norm_pre_clip': 2.765366315841675, 'timing/data': 0.00017364509403705597, 'timing/model': 0.457662055734545, 'learning_rate/action_model': 6.093504584300906e-05, 'learning_rate/action_query_proj': 6.093504584300906e-05, 'learning_rate/base': 1.5233761460752265e-05, 'epoch': 0.27}) +[2026-07-26 22:47:42,910][starVLA.training.train_starvla][INFO] - Step 2203, Loss: {'train/loss': 0.292240172624588, 'train/grad_norm_pre_clip': 4.063537120819092, 'timing/data': 0.00017428305000066757, 'timing/model': 0.45724238688126206, 'learning_rate/action_model': 6.0905411917485514e-05, 'learning_rate/action_query_proj': 6.0905411917485514e-05, 'learning_rate/base': 1.5226352979371378e-05, 'epoch': 0.27}) +[2026-07-26 22:47:48,413][starVLA.training.train_starvla][INFO] - Step 2204, Loss: {'train/loss': 0.14677435159683228, 'train/grad_norm_pre_clip': 2.2612504959106445, 'timing/data': 0.0001720651052892208, 'timing/model': 0.4571428829804063, 'learning_rate/action_model': 6.087577447624635e-05, 'learning_rate/action_query_proj': 6.087577447624635e-05, 'learning_rate/base': 1.5218943619061587e-05, 'epoch': 0.27}) +[2026-07-26 22:47:53,909][starVLA.training.train_starvla][INFO] - Step 2205, Loss: {'train/loss': 0.14399586617946625, 'train/grad_norm_pre_clip': 3.2621614933013916, 'timing/data': 0.000173110980540514, 'timing/model': 0.4582087597809732, 'learning_rate/action_model': 6.084613353099201e-05, 'learning_rate/action_query_proj': 6.084613353099201e-05, 'learning_rate/base': 1.5211533382748002e-05, 'epoch': 0.27}) +[2026-07-26 22:47:59,407][starVLA.training.train_starvla][INFO] - Step 2206, Loss: {'train/loss': 0.25291845202445984, 'train/grad_norm_pre_clip': 3.7472498416900635, 'timing/data': 0.0001692129299044609, 'timing/model': 0.4565870608203113, 'learning_rate/action_model': 6.081648909342424e-05, 'learning_rate/action_query_proj': 6.081648909342424e-05, 'learning_rate/base': 1.520412227335606e-05, 'epoch': 0.27}) +[2026-07-26 22:48:04,900][starVLA.training.train_starvla][INFO] - Step 2207, Loss: {'train/loss': 0.23086842894554138, 'train/grad_norm_pre_clip': 3.0999045372009277, 'timing/data': 0.00017149187624454498, 'timing/model': 0.45856853434816003, 'learning_rate/action_model': 6.078684117524619e-05, 'learning_rate/action_query_proj': 6.078684117524619e-05, 'learning_rate/base': 1.5196710293811547e-05, 'epoch': 0.27}) +[2026-07-26 22:48:10,393][starVLA.training.train_starvla][INFO] - Step 2208, Loss: {'train/loss': 0.2983979284763336, 'train/grad_norm_pre_clip': 3.667851686477661, 'timing/data': 0.00019044708460569382, 'timing/model': 0.4580193478614092, 'learning_rate/action_model': 6.0757189788162414e-05, 'learning_rate/action_query_proj': 6.0757189788162414e-05, 'learning_rate/base': 1.5189297447040604e-05, 'epoch': 0.27}) +[2026-07-26 22:48:15,881][starVLA.training.train_starvla][INFO] - Step 2209, Loss: {'train/loss': 0.35056552290916443, 'train/grad_norm_pre_clip': 3.5847909450531006, 'timing/data': 0.00017640087753534317, 'timing/model': 0.45731745287775993, 'learning_rate/action_model': 6.0727534943878795e-05, 'learning_rate/action_query_proj': 6.0727534943878795e-05, 'learning_rate/base': 1.5181883735969699e-05, 'epoch': 0.27}) +[2026-07-26 22:48:21,373][starVLA.training.train_starvla][INFO] - Step 2210, Loss: {'train/loss': 0.2462024688720703, 'train/grad_norm_pre_clip': 3.3008341789245605, 'timing/data': 0.00017335079610347748, 'timing/model': 0.45800961926579475, 'learning_rate/action_model': 6.0697876654102594e-05, 'learning_rate/action_query_proj': 6.0697876654102594e-05, 'learning_rate/base': 1.5174469163525649e-05, 'epoch': 0.27}) +[2026-07-26 22:48:27,116][starVLA.training.train_starvla][INFO] - Step 2211, Loss: {'train/loss': 0.30460038781166077, 'train/grad_norm_pre_clip': 3.6745193004608154, 'timing/data': 0.000171746127307415, 'timing/model': 0.45784896379336715, 'learning_rate/action_model': 6.066821493054244e-05, 'learning_rate/action_query_proj': 6.066821493054244e-05, 'learning_rate/base': 1.516705373263561e-05, 'epoch': 0.27}) +[2026-07-26 22:48:32,663][starVLA.training.train_starvla][INFO] - Step 2212, Loss: {'train/loss': 0.220894455909729, 'train/grad_norm_pre_clip': 2.635533332824707, 'timing/data': 0.0001707109622657299, 'timing/model': 0.45786592783406377, 'learning_rate/action_model': 6.063854978490832e-05, 'learning_rate/action_query_proj': 6.063854978490832e-05, 'learning_rate/base': 1.515963744622708e-05, 'epoch': 0.27}) +[2026-07-26 22:48:38,153][starVLA.training.train_starvla][INFO] - Step 2213, Loss: {'train/loss': 0.22878795862197876, 'train/grad_norm_pre_clip': 3.8420121669769287, 'timing/data': 0.0001841220073401928, 'timing/model': 0.4575712997466326, 'learning_rate/action_model': 6.060888122891154e-05, 'learning_rate/action_query_proj': 6.060888122891154e-05, 'learning_rate/base': 1.5152220307227885e-05, 'epoch': 0.27}) +[2026-07-26 22:48:43,638][starVLA.training.train_starvla][INFO] - Step 2214, Loss: {'train/loss': 0.1683567464351654, 'train/grad_norm_pre_clip': 2.860645055770874, 'timing/data': 0.00017201993614435196, 'timing/model': 0.457549499347806, 'learning_rate/action_model': 6.057920927426479e-05, 'learning_rate/action_query_proj': 6.057920927426479e-05, 'learning_rate/base': 1.5144802318566198e-05, 'epoch': 0.27}) +[2026-07-26 22:48:49,152][starVLA.training.train_starvla][INFO] - Step 2215, Loss: {'train/loss': 0.33687296509742737, 'train/grad_norm_pre_clip': 5.023107051849365, 'timing/data': 0.00018168101087212563, 'timing/model': 0.4602854601107538, 'learning_rate/action_model': 6.054953393268209e-05, 'learning_rate/action_query_proj': 6.054953393268209e-05, 'learning_rate/base': 1.5137383483170523e-05, 'epoch': 0.27}) +[2026-07-26 22:48:54,657][starVLA.training.train_starvla][INFO] - Step 2216, Loss: {'train/loss': 0.38814646005630493, 'train/grad_norm_pre_clip': 4.688660144805908, 'timing/data': 0.00017223460599780083, 'timing/model': 0.45722162211313844, 'learning_rate/action_model': 6.0519855215878795e-05, 'learning_rate/action_query_proj': 6.0519855215878795e-05, 'learning_rate/base': 1.5129963803969699e-05, 'epoch': 0.27}) +[2026-07-26 22:49:00,171][starVLA.training.train_starvla][INFO] - Step 2217, Loss: {'train/loss': 0.324382483959198, 'train/grad_norm_pre_clip': 6.5503621101379395, 'timing/data': 0.00017424114048480988, 'timing/model': 0.457845838740468, 'learning_rate/action_model': 6.049017313557158e-05, 'learning_rate/action_query_proj': 6.049017313557158e-05, 'learning_rate/base': 1.5122543283892895e-05, 'epoch': 0.27}) +[2026-07-26 22:49:05,696][starVLA.training.train_starvla][INFO] - Step 2218, Loss: {'train/loss': 0.3131614327430725, 'train/grad_norm_pre_clip': 3.187940835952759, 'timing/data': 0.00018239812925457954, 'timing/model': 0.4581664828583598, 'learning_rate/action_model': 6.046048770347849e-05, 'learning_rate/action_query_proj': 6.046048770347849e-05, 'learning_rate/base': 1.5115121925869622e-05, 'epoch': 0.27}) +[2026-07-26 22:49:11,206][starVLA.training.train_starvla][INFO] - Step 2219, Loss: {'train/loss': 0.19803471863269806, 'train/grad_norm_pre_clip': 2.9802918434143066, 'timing/data': 0.0001765838824212551, 'timing/model': 0.45737649593502283, 'learning_rate/action_model': 6.043079893131882e-05, 'learning_rate/action_query_proj': 6.043079893131882e-05, 'learning_rate/base': 1.5107699732829706e-05, 'epoch': 0.27}) +[2026-07-26 22:49:16,727][starVLA.training.train_starvla][INFO] - Step 2220, Loss: {'train/loss': 0.18721455335617065, 'train/grad_norm_pre_clip': 2.693617820739746, 'timing/data': 0.00018338719382882118, 'timing/model': 0.4578031492419541, 'learning_rate/action_model': 6.040110683081326e-05, 'learning_rate/action_query_proj': 6.040110683081326e-05, 'learning_rate/base': 1.5100276707703315e-05, 'epoch': 0.27}) +[2026-07-26 22:49:22,248][starVLA.training.train_starvla][INFO] - Step 2221, Loss: {'train/loss': 0.26675575971603394, 'train/grad_norm_pre_clip': 3.9964871406555176, 'timing/data': 0.00018002325668931007, 'timing/model': 0.46517511177808046, 'learning_rate/action_model': 6.037141141368376e-05, 'learning_rate/action_query_proj': 6.037141141368376e-05, 'learning_rate/base': 1.509285285342094e-05, 'epoch': 0.27}) +[2026-07-26 22:49:27,775][starVLA.training.train_starvla][INFO] - Step 2222, Loss: {'train/loss': 0.33956843614578247, 'train/grad_norm_pre_clip': 3.633423328399658, 'timing/data': 0.00017853500321507454, 'timing/model': 0.46384035097435117, 'learning_rate/action_model': 6.034171269165362e-05, 'learning_rate/action_query_proj': 6.034171269165362e-05, 'learning_rate/base': 1.5085428172913405e-05, 'epoch': 0.27}) +[2026-07-26 22:49:33,301][starVLA.training.train_starvla][INFO] - Step 2223, Loss: {'train/loss': 0.22789610922336578, 'train/grad_norm_pre_clip': 2.7891945838928223, 'timing/data': 0.0001762588508427143, 'timing/model': 0.46414272021502256, 'learning_rate/action_model': 6.031201067644742e-05, 'learning_rate/action_query_proj': 6.031201067644742e-05, 'learning_rate/base': 1.5078002669111855e-05, 'epoch': 0.27}) +[2026-07-26 22:49:38,822][starVLA.training.train_starvla][INFO] - Step 2224, Loss: {'train/loss': 0.29764777421951294, 'train/grad_norm_pre_clip': 4.164820194244385, 'timing/data': 0.00018804986029863358, 'timing/model': 0.4638087982311845, 'learning_rate/action_model': 6.028230537979105e-05, 'learning_rate/action_query_proj': 6.028230537979105e-05, 'learning_rate/base': 1.5070576344947763e-05, 'epoch': 0.27}) +[2026-07-26 22:49:44,347][starVLA.training.train_starvla][INFO] - Step 2225, Loss: {'train/loss': 0.3098222315311432, 'train/grad_norm_pre_clip': 3.567197561264038, 'timing/data': 0.00018333829939365387, 'timing/model': 0.46436819108203053, 'learning_rate/action_model': 6.025259681341166e-05, 'learning_rate/action_query_proj': 6.025259681341166e-05, 'learning_rate/base': 1.5063149203352914e-05, 'epoch': 0.27}) +[2026-07-26 22:49:49,868][starVLA.training.train_starvla][INFO] - Step 2226, Loss: {'train/loss': 0.18506841361522675, 'train/grad_norm_pre_clip': 1.9312636852264404, 'timing/data': 0.00017793802544474602, 'timing/model': 0.46284073032438755, 'learning_rate/action_model': 6.0222884989037755e-05, 'learning_rate/action_query_proj': 6.0222884989037755e-05, 'learning_rate/base': 1.5055721247259439e-05, 'epoch': 0.27}) +[2026-07-26 22:49:55,358][starVLA.training.train_starvla][INFO] - Step 2227, Loss: {'train/loss': 0.17379117012023926, 'train/grad_norm_pre_clip': 2.464124917984009, 'timing/data': 0.0001790020614862442, 'timing/model': 0.45756162982434034, 'learning_rate/action_model': 6.0193169918399085e-05, 'learning_rate/action_query_proj': 6.0193169918399085e-05, 'learning_rate/base': 1.5048292479599771e-05, 'epoch': 0.27}) +[2026-07-26 22:50:00,851][starVLA.training.train_starvla][INFO] - Step 2228, Loss: {'train/loss': 0.22056128084659576, 'train/grad_norm_pre_clip': 3.318624258041382, 'timing/data': 0.00017334101721644402, 'timing/model': 0.45964477909728885, 'learning_rate/action_model': 6.016345161322669e-05, 'learning_rate/action_query_proj': 6.016345161322669e-05, 'learning_rate/base': 1.5040862903306672e-05, 'epoch': 0.27}) +[2026-07-26 22:50:06,374][starVLA.training.train_starvla][INFO] - Step 2229, Loss: {'train/loss': 0.2533881962299347, 'train/grad_norm_pre_clip': 3.4517829418182373, 'timing/data': 0.00017858203500509262, 'timing/model': 0.45814951602369547, 'learning_rate/action_model': 6.013373008525287e-05, 'learning_rate/action_query_proj': 6.013373008525287e-05, 'learning_rate/base': 1.5033432521313217e-05, 'epoch': 0.27}) +[2026-07-26 22:50:11,933][starVLA.training.train_starvla][INFO] - Step 2230, Loss: {'train/loss': 0.2514254152774811, 'train/grad_norm_pre_clip': 3.1746554374694824, 'timing/data': 0.0001718839630484581, 'timing/model': 0.5098329177126288, 'learning_rate/action_model': 6.0104005346211225e-05, 'learning_rate/action_query_proj': 6.0104005346211225e-05, 'learning_rate/base': 1.5026001336552806e-05, 'epoch': 0.27}) +[2026-07-26 22:50:17,472][starVLA.training.train_starvla][INFO] - Step 2231, Loss: {'train/loss': 0.1241813451051712, 'train/grad_norm_pre_clip': 2.3732900619506836, 'timing/data': 0.0001758011057972908, 'timing/model': 0.45706908591091633, 'learning_rate/action_model': 6.007427740783663e-05, 'learning_rate/action_query_proj': 6.007427740783663e-05, 'learning_rate/base': 1.5018569351959158e-05, 'epoch': 0.27}) +[2026-07-26 22:50:22,997][starVLA.training.train_starvla][INFO] - Step 2232, Loss: {'train/loss': 0.23631726205348969, 'train/grad_norm_pre_clip': 3.099998712539673, 'timing/data': 0.00017836503684520721, 'timing/model': 0.4565858128480613, 'learning_rate/action_model': 6.004454628186516e-05, 'learning_rate/action_query_proj': 6.004454628186516e-05, 'learning_rate/base': 1.501113657046629e-05, 'epoch': 0.27}) +[2026-07-26 22:50:28,526][starVLA.training.train_starvla][INFO] - Step 2233, Loss: {'train/loss': 0.2593008875846863, 'train/grad_norm_pre_clip': 3.7712574005126953, 'timing/data': 0.00017876597121357918, 'timing/model': 0.45780669106170535, 'learning_rate/action_model': 6.001481198003425e-05, 'learning_rate/action_query_proj': 6.001481198003425e-05, 'learning_rate/base': 1.5003702995008562e-05, 'epoch': 0.27}) +[2026-07-26 22:50:34,299][starVLA.training.train_starvla][INFO] - Step 2234, Loss: {'train/loss': 0.2649625539779663, 'train/grad_norm_pre_clip': 4.314619541168213, 'timing/data': 0.00017378386110067368, 'timing/model': 0.45728401094675064, 'learning_rate/action_model': 5.9985074514082475e-05, 'learning_rate/action_query_proj': 5.9985074514082475e-05, 'learning_rate/base': 1.4996268628520619e-05, 'epoch': 0.27}) +[2026-07-26 22:50:39,838][starVLA.training.train_starvla][INFO] - Step 2235, Loss: {'train/loss': 0.27131590247154236, 'train/grad_norm_pre_clip': 3.583848476409912, 'timing/data': 0.00017703091725707054, 'timing/model': 0.45672049280256033, 'learning_rate/action_model': 5.995533389574976e-05, 'learning_rate/action_query_proj': 5.995533389574976e-05, 'learning_rate/base': 1.498883347393744e-05, 'epoch': 0.27}) +[2026-07-26 22:50:45,397][starVLA.training.train_starvla][INFO] - Step 2236, Loss: {'train/loss': 0.19370467960834503, 'train/grad_norm_pre_clip': 3.389202356338501, 'timing/data': 0.00017709191888570786, 'timing/model': 0.45785151282325387, 'learning_rate/action_model': 5.9925590136777187e-05, 'learning_rate/action_query_proj': 5.9925590136777187e-05, 'learning_rate/base': 1.4981397534194297e-05, 'epoch': 0.27}) +[2026-07-26 22:50:50,959][starVLA.training.train_starvla][INFO] - Step 2237, Loss: {'train/loss': 0.21640267968177795, 'train/grad_norm_pre_clip': 3.116694211959839, 'timing/data': 0.00017454568296670914, 'timing/model': 0.457601698115468, 'learning_rate/action_model': 5.989584324890717e-05, 'learning_rate/action_query_proj': 5.989584324890717e-05, 'learning_rate/base': 1.4973960812226793e-05, 'epoch': 0.27}) +[2026-07-26 22:50:56,533][starVLA.training.train_starvla][INFO] - Step 2238, Loss: {'train/loss': 0.22521111369132996, 'train/grad_norm_pre_clip': 2.9540717601776123, 'timing/data': 0.0001721009612083435, 'timing/model': 0.45803603157401085, 'learning_rate/action_model': 5.986609324388327e-05, 'learning_rate/action_query_proj': 5.986609324388327e-05, 'learning_rate/base': 1.4966523310970817e-05, 'epoch': 0.27}) +[2026-07-26 22:51:02,097][starVLA.training.train_starvla][INFO] - Step 2239, Loss: {'train/loss': 0.16220909357070923, 'train/grad_norm_pre_clip': 3.135408639907837, 'timing/data': 0.00017757201567292213, 'timing/model': 0.4583880202844739, 'learning_rate/action_model': 5.983634013345033e-05, 'learning_rate/action_query_proj': 5.983634013345033e-05, 'learning_rate/base': 1.4959085033362582e-05, 'epoch': 0.27}) +[2026-07-26 22:51:07,654][starVLA.training.train_starvla][INFO] - Step 2240, Loss: {'train/loss': 0.3464325964450836, 'train/grad_norm_pre_clip': 3.26676869392395, 'timing/data': 0.0001734970137476921, 'timing/model': 0.4579156790859997, 'learning_rate/action_model': 5.9806583929354424e-05, 'learning_rate/action_query_proj': 5.9806583929354424e-05, 'learning_rate/base': 1.4951645982338606e-05, 'epoch': 0.27}) +[2026-07-26 22:51:13,210][starVLA.training.train_starvla][INFO] - Step 2241, Loss: {'train/loss': 0.17899969220161438, 'train/grad_norm_pre_clip': 3.502164363861084, 'timing/data': 0.0001690131612122059, 'timing/model': 0.4578295210376382, 'learning_rate/action_model': 5.9776824643342813e-05, 'learning_rate/action_query_proj': 5.9776824643342813e-05, 'learning_rate/base': 1.4944206160835703e-05, 'epoch': 0.27}) +[2026-07-26 22:51:18,774][starVLA.training.train_starvla][INFO] - Step 2242, Loss: {'train/loss': 0.24377678334712982, 'train/grad_norm_pre_clip': 3.3895111083984375, 'timing/data': 0.00017751287668943405, 'timing/model': 0.45724346302449703, 'learning_rate/action_model': 5.974706228716398e-05, 'learning_rate/action_query_proj': 5.974706228716398e-05, 'learning_rate/base': 1.4936765571790995e-05, 'epoch': 0.27}) +[2026-07-26 22:51:24,338][starVLA.training.train_starvla][INFO] - Step 2243, Loss: {'train/loss': 0.18974041938781738, 'train/grad_norm_pre_clip': 3.036104679107666, 'timing/data': 0.000176197849214077, 'timing/model': 0.45801408775150776, 'learning_rate/action_model': 5.971729687256765e-05, 'learning_rate/action_query_proj': 5.971729687256765e-05, 'learning_rate/base': 1.4929324218141913e-05, 'epoch': 0.27}) +[2026-07-26 22:51:29,920][starVLA.training.train_starvla][INFO] - Step 2244, Loss: {'train/loss': 0.3081076741218567, 'train/grad_norm_pre_clip': 3.6879024505615234, 'timing/data': 0.00018728524446487427, 'timing/model': 0.45921602193266153, 'learning_rate/action_model': 5.9687528411304736e-05, 'learning_rate/action_query_proj': 5.9687528411304736e-05, 'learning_rate/base': 1.4921882102826184e-05, 'epoch': 0.27}) +[2026-07-26 22:51:35,492][starVLA.training.train_starvla][INFO] - Step 2245, Loss: {'train/loss': 0.16069622337818146, 'train/grad_norm_pre_clip': 3.0344045162200928, 'timing/data': 0.00017723999917507172, 'timing/model': 0.45762093970552087, 'learning_rate/action_model': 5.965775691512735e-05, 'learning_rate/action_query_proj': 5.965775691512735e-05, 'learning_rate/base': 1.4914439228781838e-05, 'epoch': 0.27}) +[2026-07-26 22:51:41,219][starVLA.training.train_starvla][INFO] - Step 2246, Loss: {'train/loss': 0.2981097996234894, 'train/grad_norm_pre_clip': 3.0245859622955322, 'timing/data': 0.0001756018027663231, 'timing/model': 0.45808069221675396, 'learning_rate/action_model': 5.962798239578882e-05, 'learning_rate/action_query_proj': 5.962798239578882e-05, 'learning_rate/base': 1.4906995598947205e-05, 'epoch': 0.27}) +[2026-07-26 22:51:46,757][starVLA.training.train_starvla][INFO] - Step 2247, Loss: {'train/loss': 0.11837376654148102, 'train/grad_norm_pre_clip': 2.641803503036499, 'timing/data': 0.00017504114657640457, 'timing/model': 0.4574551656842232, 'learning_rate/action_model': 5.9598204865043625e-05, 'learning_rate/action_query_proj': 5.9598204865043625e-05, 'learning_rate/base': 1.4899551216260906e-05, 'epoch': 0.27}) +[2026-07-26 22:51:52,313][starVLA.training.train_starvla][INFO] - Step 2248, Loss: {'train/loss': 0.2982531785964966, 'train/grad_norm_pre_clip': 4.107396125793457, 'timing/data': 0.00019316235557198524, 'timing/model': 0.45778732001781464, 'learning_rate/action_model': 5.95684243346475e-05, 'learning_rate/action_query_proj': 5.95684243346475e-05, 'learning_rate/base': 1.4892106083661875e-05, 'epoch': 0.27}) +[2026-07-26 22:51:57,853][starVLA.training.train_starvla][INFO] - Step 2249, Loss: {'train/loss': 0.17343617975711823, 'train/grad_norm_pre_clip': 2.8251631259918213, 'timing/data': 0.00018388591706752777, 'timing/model': 0.45802213810384274, 'learning_rate/action_model': 5.953864081635729e-05, 'learning_rate/action_query_proj': 5.953864081635729e-05, 'learning_rate/base': 1.4884660204089323e-05, 'epoch': 0.27}) +[2026-07-26 22:52:03,393][starVLA.training.train_starvla][INFO] - Step 2250, Loss: {'train/loss': 0.15584538877010345, 'train/grad_norm_pre_clip': 2.286024570465088, 'timing/data': 0.00018020905554294586, 'timing/model': 0.4593327268958092, 'learning_rate/action_model': 5.950885432193108e-05, 'learning_rate/action_query_proj': 5.950885432193108e-05, 'learning_rate/base': 1.487721358048277e-05, 'epoch': 0.27}) +[2026-07-26 22:52:08,932][starVLA.training.train_starvla][INFO] - Step 2251, Loss: {'train/loss': 0.1784980297088623, 'train/grad_norm_pre_clip': 2.870929718017578, 'timing/data': 0.00017445161938667297, 'timing/model': 0.4575647725723684, 'learning_rate/action_model': 5.947906486312812e-05, 'learning_rate/action_query_proj': 5.947906486312812e-05, 'learning_rate/base': 1.486976621578203e-05, 'epoch': 0.27}) +[2026-07-26 22:52:14,475][starVLA.training.train_starvla][INFO] - Step 2252, Loss: {'train/loss': 0.1604962944984436, 'train/grad_norm_pre_clip': 2.8669650554656982, 'timing/data': 0.00017194310203194618, 'timing/model': 0.4578123800456524, 'learning_rate/action_model': 5.944927245170877e-05, 'learning_rate/action_query_proj': 5.944927245170877e-05, 'learning_rate/base': 1.4862318112927192e-05, 'epoch': 0.27}) +[2026-07-26 22:52:19,993][starVLA.training.train_starvla][INFO] - Step 2253, Loss: {'train/loss': 0.19387294352054596, 'train/grad_norm_pre_clip': 3.6095569133758545, 'timing/data': 0.00017020897939801216, 'timing/model': 0.4565847269259393, 'learning_rate/action_model': 5.941947709943465e-05, 'learning_rate/action_query_proj': 5.941947709943465e-05, 'learning_rate/base': 1.4854869274858662e-05, 'epoch': 0.27}) +[2026-07-26 22:52:25,500][starVLA.training.train_starvla][INFO] - Step 2254, Loss: {'train/loss': 0.14266198873519897, 'train/grad_norm_pre_clip': 2.442148447036743, 'timing/data': 0.00017624814063310623, 'timing/model': 0.4573952639475465, 'learning_rate/action_model': 5.938967881806847e-05, 'learning_rate/action_query_proj': 5.938967881806847e-05, 'learning_rate/base': 1.4847419704517118e-05, 'epoch': 0.27}) +[2026-07-26 22:52:31,209][starVLA.training.train_starvla][INFO] - Step 2255, Loss: {'train/loss': 0.2619211673736572, 'train/grad_norm_pre_clip': 4.454577445983887, 'timing/data': 0.00017190678045153618, 'timing/model': 0.4582800497300923, 'learning_rate/action_model': 5.935987761937412e-05, 'learning_rate/action_query_proj': 5.935987761937412e-05, 'learning_rate/base': 1.483996940484353e-05, 'epoch': 0.27}) +[2026-07-26 22:52:36,712][starVLA.training.train_starvla][INFO] - Step 2256, Loss: {'train/loss': 0.15349476039409637, 'train/grad_norm_pre_clip': 2.9547278881073, 'timing/data': 0.00017831986770033836, 'timing/model': 0.45731620490550995, 'learning_rate/action_model': 5.933007351511664e-05, 'learning_rate/action_query_proj': 5.933007351511664e-05, 'learning_rate/base': 1.483251837877916e-05, 'epoch': 0.27}) +[2026-07-26 22:52:42,277][starVLA.training.train_starvla][INFO] - Step 2257, Loss: {'train/loss': 0.1918955147266388, 'train/grad_norm_pre_clip': 2.447387456893921, 'timing/data': 0.00017235102131962776, 'timing/model': 0.4582444201223552, 'learning_rate/action_model': 5.930026651706222e-05, 'learning_rate/action_query_proj': 5.930026651706222e-05, 'learning_rate/base': 1.4825066629265556e-05, 'epoch': 0.27}) +[2026-07-26 22:52:47,776][starVLA.training.train_starvla][INFO] - Step 2258, Loss: {'train/loss': 0.1688024252653122, 'train/grad_norm_pre_clip': 2.4358201026916504, 'timing/data': 0.0001728101633489132, 'timing/model': 0.4578405828215182, 'learning_rate/action_model': 5.92704566369782e-05, 'learning_rate/action_query_proj': 5.92704566369782e-05, 'learning_rate/base': 1.481761415924455e-05, 'epoch': 0.27}) +[2026-07-26 22:52:53,272][starVLA.training.train_starvla][INFO] - Step 2259, Loss: {'train/loss': 0.2488710880279541, 'train/grad_norm_pre_clip': 4.0903778076171875, 'timing/data': 0.00017138198018074036, 'timing/model': 0.4570166156627238, 'learning_rate/action_model': 5.924064388663304e-05, 'learning_rate/action_query_proj': 5.924064388663304e-05, 'learning_rate/base': 1.481016097165826e-05, 'epoch': 0.27}) +[2026-07-26 22:52:58,769][starVLA.training.train_starvla][INFO] - Step 2260, Loss: {'train/loss': 0.3025400936603546, 'train/grad_norm_pre_clip': 3.6957273483276367, 'timing/data': 0.0001770639792084694, 'timing/model': 0.458089258056134, 'learning_rate/action_model': 5.921082827779635e-05, 'learning_rate/action_query_proj': 5.921082827779635e-05, 'learning_rate/base': 1.4802707069449087e-05, 'epoch': 0.27}) +[2026-07-26 22:53:04,289][starVLA.training.train_starvla][INFO] - Step 2261, Loss: {'train/loss': 0.2372487336397171, 'train/grad_norm_pre_clip': 3.6618335247039795, 'timing/data': 0.0001777559518814087, 'timing/model': 0.45869797887280583, 'learning_rate/action_model': 5.918100982223884e-05, 'learning_rate/action_query_proj': 5.918100982223884e-05, 'learning_rate/base': 1.479525245555971e-05, 'epoch': 0.27}) +[2026-07-26 22:53:09,796][starVLA.training.train_starvla][INFO] - Step 2262, Loss: {'train/loss': 0.1770859658718109, 'train/grad_norm_pre_clip': 3.6549184322357178, 'timing/data': 0.00017873011529445648, 'timing/model': 0.458235299680382, 'learning_rate/action_model': 5.9151188531732384e-05, 'learning_rate/action_query_proj': 5.9151188531732384e-05, 'learning_rate/base': 1.4787797132933096e-05, 'epoch': 0.27}) +[2026-07-26 22:53:15,323][starVLA.training.train_starvla][INFO] - Step 2263, Loss: {'train/loss': 0.2969181537628174, 'train/grad_norm_pre_clip': 3.6598258018493652, 'timing/data': 0.0001756078563630581, 'timing/model': 0.45972690312191844, 'learning_rate/action_model': 5.9121364418049954e-05, 'learning_rate/action_query_proj': 5.9121364418049954e-05, 'learning_rate/base': 1.4780341104512489e-05, 'epoch': 0.27}) +[2026-07-26 22:53:20,833][starVLA.training.train_starvla][INFO] - Step 2264, Loss: {'train/loss': 0.2766394019126892, 'train/grad_norm_pre_clip': 6.046956539154053, 'timing/data': 0.00019075116142630577, 'timing/model': 0.45769464736804366, 'learning_rate/action_model': 5.909153749296563e-05, 'learning_rate/action_query_proj': 5.909153749296563e-05, 'learning_rate/base': 1.4772884373241407e-05, 'epoch': 0.27}) +[2026-07-26 22:53:26,345][starVLA.training.train_starvla][INFO] - Step 2265, Loss: {'train/loss': 0.21649983525276184, 'train/grad_norm_pre_clip': 4.550899028778076, 'timing/data': 0.00018358789384365082, 'timing/model': 0.45937957987189293, 'learning_rate/action_model': 5.906170776825459e-05, 'learning_rate/action_query_proj': 5.906170776825459e-05, 'learning_rate/base': 1.4765426942063648e-05, 'epoch': 0.27}) +[2026-07-26 22:53:31,849][starVLA.training.train_starvla][INFO] - Step 2266, Loss: {'train/loss': 0.19705697894096375, 'train/grad_norm_pre_clip': 3.931609630584717, 'timing/data': 0.00017744069918990135, 'timing/model': 0.4583208002150059, 'learning_rate/action_model': 5.903187525569319e-05, 'learning_rate/action_query_proj': 5.903187525569319e-05, 'learning_rate/base': 1.4757968813923298e-05, 'epoch': 0.27}) +[2026-07-26 22:53:37,345][starVLA.training.train_starvla][INFO] - Step 2267, Loss: {'train/loss': 0.24394862353801727, 'train/grad_norm_pre_clip': 3.358581066131592, 'timing/data': 0.00017507094889879227, 'timing/model': 0.45898127974942327, 'learning_rate/action_model': 5.9002039967058785e-05, 'learning_rate/action_query_proj': 5.9002039967058785e-05, 'learning_rate/base': 1.4750509991764696e-05, 'epoch': 0.28}) +[2026-07-26 22:53:42,844][starVLA.training.train_starvla][INFO] - Step 2268, Loss: {'train/loss': 0.192159503698349, 'train/grad_norm_pre_clip': 3.375880718231201, 'timing/data': 0.0001686951145529747, 'timing/model': 0.4582923739217222, 'learning_rate/action_model': 5.89722019141299e-05, 'learning_rate/action_query_proj': 5.89722019141299e-05, 'learning_rate/base': 1.4743050478532474e-05, 'epoch': 0.28}) +[2026-07-26 22:53:48,387][starVLA.training.train_starvla][INFO] - Step 2269, Loss: {'train/loss': 0.24864332377910614, 'train/grad_norm_pre_clip': 3.0454394817352295, 'timing/data': 0.00017912592738866806, 'timing/model': 0.458577036857605, 'learning_rate/action_model': 5.894236110868612e-05, 'learning_rate/action_query_proj': 5.894236110868612e-05, 'learning_rate/base': 1.473559027717153e-05, 'epoch': 0.28}) +[2026-07-26 22:53:53,890][starVLA.training.train_starvla][INFO] - Step 2270, Loss: {'train/loss': 0.22107543051242828, 'train/grad_norm_pre_clip': 3.057678699493408, 'timing/data': 0.000181655865162611, 'timing/model': 0.45871360413730145, 'learning_rate/action_model': 5.8912517562508104e-05, 'learning_rate/action_query_proj': 5.8912517562508104e-05, 'learning_rate/base': 1.4728129390627026e-05, 'epoch': 0.28}) +[2026-07-26 22:53:59,626][starVLA.training.train_starvla][INFO] - Step 2271, Loss: {'train/loss': 0.3467113971710205, 'train/grad_norm_pre_clip': 5.00515079498291, 'timing/data': 0.00017704395577311516, 'timing/model': 0.4583060871809721, 'learning_rate/action_model': 5.8882671287377644e-05, 'learning_rate/action_query_proj': 5.8882671287377644e-05, 'learning_rate/base': 1.4720667821844411e-05, 'epoch': 0.28}) +[2026-07-26 22:54:05,399][starVLA.training.train_starvla][INFO] - Step 2272, Loss: {'train/loss': 0.3031662106513977, 'train/grad_norm_pre_clip': 3.8124337196350098, 'timing/data': 0.00017080968245863914, 'timing/model': 0.4579827939160168, 'learning_rate/action_model': 5.885282229507755e-05, 'learning_rate/action_query_proj': 5.885282229507755e-05, 'learning_rate/base': 1.4713205573769387e-05, 'epoch': 0.28}) +[2026-07-26 22:54:10,899][starVLA.training.train_starvla][INFO] - Step 2273, Loss: {'train/loss': 0.19954736530780792, 'train/grad_norm_pre_clip': 3.448115587234497, 'timing/data': 0.00017653265967965126, 'timing/model': 0.45985690504312515, 'learning_rate/action_model': 5.8822970597391745e-05, 'learning_rate/action_query_proj': 5.8822970597391745e-05, 'learning_rate/base': 1.4705742649347936e-05, 'epoch': 0.28}) +[2026-07-26 22:54:16,379][starVLA.training.train_starvla][INFO] - Step 2274, Loss: {'train/loss': 0.22518108785152435, 'train/grad_norm_pre_clip': 3.2051663398742676, 'timing/data': 0.00017691124230623245, 'timing/model': 0.45803822902962565, 'learning_rate/action_model': 5.8793116206105215e-05, 'learning_rate/action_query_proj': 5.8793116206105215e-05, 'learning_rate/base': 1.4698279051526304e-05, 'epoch': 0.28}) +[2026-07-26 22:54:21,912][starVLA.training.train_starvla][INFO] - Step 2275, Loss: {'train/loss': 0.2277328073978424, 'train/grad_norm_pre_clip': 3.8968820571899414, 'timing/data': 0.0001882081851363182, 'timing/model': 0.45868879882618785, 'learning_rate/action_model': 5.876325913300397e-05, 'learning_rate/action_query_proj': 5.876325913300397e-05, 'learning_rate/base': 1.4690814783250992e-05, 'epoch': 0.28}) +[2026-07-26 22:54:27,441][starVLA.training.train_starvla][INFO] - Step 2276, Loss: {'train/loss': 0.24738040566444397, 'train/grad_norm_pre_clip': 3.156277894973755, 'timing/data': 0.00018438789993524551, 'timing/model': 0.45815844368189573, 'learning_rate/action_model': 5.8733399389875144e-05, 'learning_rate/action_query_proj': 5.8733399389875144e-05, 'learning_rate/base': 1.4683349847468786e-05, 'epoch': 0.28}) +[2026-07-26 22:54:32,956][starVLA.training.train_starvla][INFO] - Step 2277, Loss: {'train/loss': 0.23891650140285492, 'train/grad_norm_pre_clip': 4.063899993896484, 'timing/data': 0.00017578806728124619, 'timing/model': 0.4585099439136684, 'learning_rate/action_model': 5.870353698850686e-05, 'learning_rate/action_query_proj': 5.870353698850686e-05, 'learning_rate/base': 1.4675884247126715e-05, 'epoch': 0.28}) +[2026-07-26 22:54:38,458][starVLA.training.train_starvla][INFO] - Step 2278, Loss: {'train/loss': 0.17991957068443298, 'train/grad_norm_pre_clip': 3.6551108360290527, 'timing/data': 0.00023230817168951035, 'timing/model': 0.45731395576149225, 'learning_rate/action_model': 5.8673671940688344e-05, 'learning_rate/action_query_proj': 5.8673671940688344e-05, 'learning_rate/base': 1.4668417985172086e-05, 'epoch': 0.28}) +[2026-07-26 22:54:44,168][starVLA.training.train_starvla][INFO] - Step 2279, Loss: {'train/loss': 0.15884673595428467, 'train/grad_norm_pre_clip': 2.8924176692962646, 'timing/data': 0.0001693987287580967, 'timing/model': 0.45791929587721825, 'learning_rate/action_model': 5.864380425820984e-05, 'learning_rate/action_query_proj': 5.864380425820984e-05, 'learning_rate/base': 1.466095106455246e-05, 'epoch': 0.28}) +[2026-07-26 22:54:49,658][starVLA.training.train_starvla][INFO] - Step 2280, Loss: {'train/loss': 0.17929480969905853, 'train/grad_norm_pre_clip': 2.9796488285064697, 'timing/data': 0.0001721782609820366, 'timing/model': 0.45803260803222656, 'learning_rate/action_model': 5.8613933952862634e-05, 'learning_rate/action_query_proj': 5.8613933952862634e-05, 'learning_rate/base': 1.4653483488215659e-05, 'epoch': 0.28}) +[2026-07-26 22:54:55,146][starVLA.training.train_starvla][INFO] - Step 2281, Loss: {'train/loss': 0.22384165227413177, 'train/grad_norm_pre_clip': 2.6055245399475098, 'timing/data': 0.00016990816220641136, 'timing/model': 0.4587407731451094, 'learning_rate/action_model': 5.858406103643904e-05, 'learning_rate/action_query_proj': 5.858406103643904e-05, 'learning_rate/base': 1.464601525910976e-05, 'epoch': 0.28}) +[2026-07-26 22:55:00,635][starVLA.training.train_starvla][INFO] - Step 2282, Loss: {'train/loss': 0.1150815486907959, 'train/grad_norm_pre_clip': 2.1604156494140625, 'timing/data': 0.00017061922699213028, 'timing/model': 0.457587247248739, 'learning_rate/action_model': 5.855418552073243e-05, 'learning_rate/action_query_proj': 5.855418552073243e-05, 'learning_rate/base': 1.4638546380183108e-05, 'epoch': 0.28}) +[2026-07-26 22:55:06,113][starVLA.training.train_starvla][INFO] - Step 2283, Loss: {'train/loss': 0.1801997423171997, 'train/grad_norm_pre_clip': 2.465864419937134, 'timing/data': 0.0001734667457640171, 'timing/model': 0.45848936913535, 'learning_rate/action_model': 5.852430741753717e-05, 'learning_rate/action_query_proj': 5.852430741753717e-05, 'learning_rate/base': 1.4631076854384293e-05, 'epoch': 0.28}) +[2026-07-26 22:55:11,595][starVLA.training.train_starvla][INFO] - Step 2284, Loss: {'train/loss': 0.25476571917533875, 'train/grad_norm_pre_clip': 3.4717342853546143, 'timing/data': 0.00017130188643932343, 'timing/model': 0.45696813287213445, 'learning_rate/action_model': 5.8494426738648656e-05, 'learning_rate/action_query_proj': 5.8494426738648656e-05, 'learning_rate/base': 1.4623606684662164e-05, 'epoch': 0.28}) +[2026-07-26 22:55:17,085][starVLA.training.train_starvla][INFO] - Step 2285, Loss: {'train/loss': 0.14934444427490234, 'train/grad_norm_pre_clip': 2.294201374053955, 'timing/data': 0.00017224997282028198, 'timing/model': 0.45652960473671556, 'learning_rate/action_model': 5.846454349586333e-05, 'learning_rate/action_query_proj': 5.846454349586333e-05, 'learning_rate/base': 1.4616135873965833e-05, 'epoch': 0.28}) +[2026-07-26 22:55:22,584][starVLA.training.train_starvla][INFO] - Step 2286, Loss: {'train/loss': 0.2414800524711609, 'train/grad_norm_pre_clip': 3.764364719390869, 'timing/data': 0.0001733638346195221, 'timing/model': 0.4573907838203013, 'learning_rate/action_model': 5.843465770097861e-05, 'learning_rate/action_query_proj': 5.843465770097861e-05, 'learning_rate/base': 1.4608664425244652e-05, 'epoch': 0.28}) +[2026-07-26 22:55:28,312][starVLA.training.train_starvla][INFO] - Step 2287, Loss: {'train/loss': 0.19930385053157806, 'train/grad_norm_pre_clip': 2.745704412460327, 'timing/data': 0.00017100106924772263, 'timing/model': 0.45895856991410255, 'learning_rate/action_model': 5.840476936579292e-05, 'learning_rate/action_query_proj': 5.840476936579292e-05, 'learning_rate/base': 1.460119234144823e-05, 'epoch': 0.28}) +[2026-07-26 22:55:33,827][starVLA.training.train_starvla][INFO] - Step 2288, Loss: {'train/loss': 0.25331345200538635, 'train/grad_norm_pre_clip': 2.9330031871795654, 'timing/data': 0.00017145415768027306, 'timing/model': 0.45853334199637175, 'learning_rate/action_model': 5.8374878502105745e-05, 'learning_rate/action_query_proj': 5.8374878502105745e-05, 'learning_rate/base': 1.4593719625526436e-05, 'epoch': 0.28}) +[2026-07-26 22:55:39,381][starVLA.training.train_starvla][INFO] - Step 2289, Loss: {'train/loss': 0.16747798025608063, 'train/grad_norm_pre_clip': 2.5904722213745117, 'timing/data': 0.000170891173183918, 'timing/model': 0.45794833870604634, 'learning_rate/action_model': 5.834498512171748e-05, 'learning_rate/action_query_proj': 5.834498512171748e-05, 'learning_rate/base': 1.458624628042937e-05, 'epoch': 0.28}) +[2026-07-26 22:55:44,867][starVLA.training.train_starvla][INFO] - Step 2290, Loss: {'train/loss': 0.2579534947872162, 'train/grad_norm_pre_clip': 2.8205478191375732, 'timing/data': 0.0001678350381553173, 'timing/model': 0.4570975168608129, 'learning_rate/action_model': 5.8315089236429566e-05, 'learning_rate/action_query_proj': 5.8315089236429566e-05, 'learning_rate/base': 1.4578772309107391e-05, 'epoch': 0.28}) +[2026-07-26 22:55:50,355][starVLA.training.train_starvla][INFO] - Step 2291, Loss: {'train/loss': 0.1877751350402832, 'train/grad_norm_pre_clip': 3.838621139526367, 'timing/data': 0.00017024576663970947, 'timing/model': 0.4579371828585863, 'learning_rate/action_model': 5.828519085804444e-05, 'learning_rate/action_query_proj': 5.828519085804444e-05, 'learning_rate/base': 1.457129771451111e-05, 'epoch': 0.28}) +[2026-07-26 22:55:55,839][starVLA.training.train_starvla][INFO] - Step 2292, Loss: {'train/loss': 0.15339937806129456, 'train/grad_norm_pre_clip': 3.1273608207702637, 'timing/data': 0.00017329910770058632, 'timing/model': 0.4577591582201421, 'learning_rate/action_model': 5.8255289998365515e-05, 'learning_rate/action_query_proj': 5.8255289998365515e-05, 'learning_rate/base': 1.4563822499591379e-05, 'epoch': 0.28}) +[2026-07-26 22:56:01,329][starVLA.training.train_starvla][INFO] - Step 2293, Loss: {'train/loss': 0.1992143988609314, 'train/grad_norm_pre_clip': 4.066401958465576, 'timing/data': 0.00017959391698241234, 'timing/model': 0.45753730507567525, 'learning_rate/action_model': 5.822538666919715e-05, 'learning_rate/action_query_proj': 5.822538666919715e-05, 'learning_rate/base': 1.4556346667299287e-05, 'epoch': 0.28}) +[2026-07-26 22:56:06,824][starVLA.training.train_starvla][INFO] - Step 2294, Loss: {'train/loss': 0.3234724998474121, 'train/grad_norm_pre_clip': 3.4414777755737305, 'timing/data': 0.00017648795619606972, 'timing/model': 0.4602530808188021, 'learning_rate/action_model': 5.819548088234471e-05, 'learning_rate/action_query_proj': 5.819548088234471e-05, 'learning_rate/base': 1.4548870220586177e-05, 'epoch': 0.28}) +[2026-07-26 22:56:12,321][starVLA.training.train_starvla][INFO] - Step 2295, Loss: {'train/loss': 0.20373226702213287, 'train/grad_norm_pre_clip': 2.7912425994873047, 'timing/data': 0.00017587607726454735, 'timing/model': 0.45706278597936034, 'learning_rate/action_model': 5.816557264961454e-05, 'learning_rate/action_query_proj': 5.816557264961454e-05, 'learning_rate/base': 1.4541393162403635e-05, 'epoch': 0.28}) +[2026-07-26 22:56:17,814][starVLA.training.train_starvla][INFO] - Step 2296, Loss: {'train/loss': 0.16935203969478607, 'train/grad_norm_pre_clip': 3.119920253753662, 'timing/data': 0.0001883888617157936, 'timing/model': 0.4572975314222276, 'learning_rate/action_model': 5.813566198281394e-05, 'learning_rate/action_query_proj': 5.813566198281394e-05, 'learning_rate/base': 1.4533915495703485e-05, 'epoch': 0.28}) +[2026-07-26 22:56:23,304][starVLA.training.train_starvla][INFO] - Step 2297, Loss: {'train/loss': 0.22473499178886414, 'train/grad_norm_pre_clip': 2.774113893508911, 'timing/data': 0.00017692288383841515, 'timing/model': 0.45731639117002487, 'learning_rate/action_model': 5.8105748893751164e-05, 'learning_rate/action_query_proj': 5.8105748893751164e-05, 'learning_rate/base': 1.4526437223437791e-05, 'epoch': 0.28}) +[2026-07-26 22:56:28,811][starVLA.training.train_starvla][INFO] - Step 2298, Loss: {'train/loss': 0.15621492266654968, 'train/grad_norm_pre_clip': 3.4109137058258057, 'timing/data': 0.00017772288993000984, 'timing/model': 0.4721822449937463, 'learning_rate/action_model': 5.80758333942354e-05, 'learning_rate/action_query_proj': 5.80758333942354e-05, 'learning_rate/base': 1.451895834855885e-05, 'epoch': 0.28}) +[2026-07-26 22:56:34,328][starVLA.training.train_starvla][INFO] - Step 2299, Loss: {'train/loss': 0.12697875499725342, 'train/grad_norm_pre_clip': 3.340273141860962, 'timing/data': 0.00018258113414049149, 'timing/model': 0.47052971785888076, 'learning_rate/action_model': 5.8045915496076853e-05, 'learning_rate/action_query_proj': 5.8045915496076853e-05, 'learning_rate/base': 1.4511478874019213e-05, 'epoch': 0.28}) +[2026-07-26 22:56:40,129][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2300 +[2026-07-26 22:56:40,130][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2300 +[2026-07-26 22:56:40,131][starVLA.training.train_starvla][INFO] - Step 2300, Loss: {'train/loss': 0.07959552854299545, 'train/grad_norm_pre_clip': 1.8753827810287476, 'timing/data': 0.00017498619854450226, 'timing/model': 0.47240472910925746, 'learning_rate/action_model': 5.80159952110866e-05, 'learning_rate/action_query_proj': 5.80159952110866e-05, 'learning_rate/base': 1.450399880277165e-05, 'epoch': 0.28}) +[2026-07-26 22:56:45,677][starVLA.training.train_starvla][INFO] - Step 2301, Loss: {'train/loss': 0.22347663342952728, 'train/grad_norm_pre_clip': 3.417371988296509, 'timing/data': 0.00017541786655783653, 'timing/model': 0.47147590573877096, 'learning_rate/action_model': 5.798607255107674e-05, 'learning_rate/action_query_proj': 5.798607255107674e-05, 'learning_rate/base': 1.4496518137769186e-05, 'epoch': 0.28}) +[2026-07-26 22:56:51,201][starVLA.training.train_starvla][INFO] - Step 2302, Loss: {'train/loss': 0.2071150839328766, 'train/grad_norm_pre_clip': 3.884746551513672, 'timing/data': 0.00017301132902503014, 'timing/model': 0.47136043990030885, 'learning_rate/action_model': 5.795614752786023e-05, 'learning_rate/action_query_proj': 5.795614752786023e-05, 'learning_rate/base': 1.4489036881965057e-05, 'epoch': 0.28}) +[2026-07-26 22:56:56,727][starVLA.training.train_starvla][INFO] - Step 2303, Loss: {'train/loss': 0.19613748788833618, 'train/grad_norm_pre_clip': 3.7334048748016357, 'timing/data': 0.0001795380376279354, 'timing/model': 0.47786982310935855, 'learning_rate/action_model': 5.792622015325098e-05, 'learning_rate/action_query_proj': 5.792622015325098e-05, 'learning_rate/base': 1.4481555038312744e-05, 'epoch': 0.28}) +[2026-07-26 22:57:02,248][starVLA.training.train_starvla][INFO] - Step 2304, Loss: {'train/loss': 0.22374358773231506, 'train/grad_norm_pre_clip': 3.1891655921936035, 'timing/data': 0.00017741601914167404, 'timing/model': 0.471298567019403, 'learning_rate/action_model': 5.789629043906388e-05, 'learning_rate/action_query_proj': 5.789629043906388e-05, 'learning_rate/base': 1.447407260976597e-05, 'epoch': 0.28}) +[2026-07-26 22:57:07,773][starVLA.training.train_starvla][INFO] - Step 2305, Loss: {'train/loss': 0.09455349296331406, 'train/grad_norm_pre_clip': 2.228104591369629, 'timing/data': 0.00017560692504048347, 'timing/model': 0.4770902507007122, 'learning_rate/action_model': 5.78663583971147e-05, 'learning_rate/action_query_proj': 5.78663583971147e-05, 'learning_rate/base': 1.4466589599278674e-05, 'epoch': 0.28}) +[2026-07-26 22:57:13,349][starVLA.training.train_starvla][INFO] - Step 2306, Loss: {'train/loss': 0.26786142587661743, 'train/grad_norm_pre_clip': 3.467219829559326, 'timing/data': 0.00018105097115039825, 'timing/model': 0.4728182223625481, 'learning_rate/action_model': 5.7836424039220126e-05, 'learning_rate/action_query_proj': 5.7836424039220126e-05, 'learning_rate/base': 1.4459106009805031e-05, 'epoch': 0.28}) +[2026-07-26 22:57:18,879][starVLA.training.train_starvla][INFO] - Step 2307, Loss: {'train/loss': 0.20864716172218323, 'train/grad_norm_pre_clip': 3.024151563644409, 'timing/data': 0.0001810956746339798, 'timing/model': 0.4702648678794503, 'learning_rate/action_model': 5.7806487377197785e-05, 'learning_rate/action_query_proj': 5.7806487377197785e-05, 'learning_rate/base': 1.4451621844299446e-05, 'epoch': 0.28}) +[2026-07-26 22:57:24,415][starVLA.training.train_starvla][INFO] - Step 2308, Loss: {'train/loss': 0.25575539469718933, 'train/grad_norm_pre_clip': 4.1318488121032715, 'timing/data': 0.00018032081425189972, 'timing/model': 0.4796683918684721, 'learning_rate/action_model': 5.777654842286616e-05, 'learning_rate/action_query_proj': 5.777654842286616e-05, 'learning_rate/base': 1.444413710571654e-05, 'epoch': 0.28}) +[2026-07-26 22:57:29,959][starVLA.training.train_starvla][INFO] - Step 2309, Loss: {'train/loss': 0.3635098934173584, 'train/grad_norm_pre_clip': 4.709985256195068, 'timing/data': 0.00017142901197075844, 'timing/model': 0.4781370749697089, 'learning_rate/action_model': 5.774660718804471e-05, 'learning_rate/action_query_proj': 5.774660718804471e-05, 'learning_rate/base': 1.4436651797011177e-05, 'epoch': 0.28}) +[2026-07-26 22:57:35,497][starVLA.training.train_starvla][INFO] - Step 2310, Loss: {'train/loss': 0.15525572001934052, 'train/grad_norm_pre_clip': 3.1686017513275146, 'timing/data': 0.00017402507364749908, 'timing/model': 0.47113408287987113, 'learning_rate/action_model': 5.7716663684553754e-05, 'learning_rate/action_query_proj': 5.7716663684553754e-05, 'learning_rate/base': 1.4429165921138438e-05, 'epoch': 0.28}) +[2026-07-26 22:57:41,015][starVLA.training.train_starvla][INFO] - Step 2311, Loss: {'train/loss': 0.25293880701065063, 'train/grad_norm_pre_clip': 3.6414759159088135, 'timing/data': 0.00017508817836642265, 'timing/model': 0.45766221871599555, 'learning_rate/action_model': 5.768671792421452e-05, 'learning_rate/action_query_proj': 5.768671792421452e-05, 'learning_rate/base': 1.442167948105363e-05, 'epoch': 0.28}) +[2026-07-26 22:57:46,517][starVLA.training.train_starvla][INFO] - Step 2312, Loss: {'train/loss': 0.19781498610973358, 'train/grad_norm_pre_clip': 3.6324217319488525, 'timing/data': 0.00017275894060730934, 'timing/model': 0.4591669416986406, 'learning_rate/action_model': 5.76567699188491e-05, 'learning_rate/action_query_proj': 5.76567699188491e-05, 'learning_rate/base': 1.4414192479712275e-05, 'epoch': 0.28}) +[2026-07-26 22:57:52,022][starVLA.training.train_starvla][INFO] - Step 2313, Loss: {'train/loss': 0.29803672432899475, 'train/grad_norm_pre_clip': 3.035573959350586, 'timing/data': 0.00017238780856132507, 'timing/model': 0.45779055170714855, 'learning_rate/action_model': 5.7626819680280485e-05, 'learning_rate/action_query_proj': 5.7626819680280485e-05, 'learning_rate/base': 1.4406704920070121e-05, 'epoch': 0.28}) +[2026-07-26 22:57:57,529][starVLA.training.train_starvla][INFO] - Step 2314, Loss: {'train/loss': 0.2840377986431122, 'train/grad_norm_pre_clip': 4.1575541496276855, 'timing/data': 0.00017186393961310387, 'timing/model': 0.4582054750062525, 'learning_rate/action_model': 5.7596867220332596e-05, 'learning_rate/action_query_proj': 5.7596867220332596e-05, 'learning_rate/base': 1.4399216805083149e-05, 'epoch': 0.28}) +[2026-07-26 22:58:03,028][starVLA.training.train_starvla][INFO] - Step 2315, Loss: {'train/loss': 0.30785953998565674, 'train/grad_norm_pre_clip': 4.4160847663879395, 'timing/data': 0.00017064297571778297, 'timing/model': 0.45856833504512906, 'learning_rate/action_model': 5.756691255083015e-05, 'learning_rate/action_query_proj': 5.756691255083015e-05, 'learning_rate/base': 1.4391728137707538e-05, 'epoch': 0.28}) +[2026-07-26 22:58:08,524][starVLA.training.train_starvla][INFO] - Step 2316, Loss: {'train/loss': 0.244438037276268, 'train/grad_norm_pre_clip': 3.39690899848938, 'timing/data': 0.00017211399972438812, 'timing/model': 0.45880703208968043, 'learning_rate/action_model': 5.7536955683598806e-05, 'learning_rate/action_query_proj': 5.7536955683598806e-05, 'learning_rate/base': 1.4384238920899701e-05, 'epoch': 0.28}) +[2026-07-26 22:58:14,066][starVLA.training.train_starvla][INFO] - Step 2317, Loss: {'train/loss': 0.18523602187633514, 'train/grad_norm_pre_clip': 3.348362922668457, 'timing/data': 0.0001741950400173664, 'timing/model': 0.4623671779409051, 'learning_rate/action_model': 5.750699663046504e-05, 'learning_rate/action_query_proj': 5.750699663046504e-05, 'learning_rate/base': 1.437674915761626e-05, 'epoch': 0.28}) +[2026-07-26 22:58:19,618][starVLA.training.train_starvla][INFO] - Step 2318, Loss: {'train/loss': 0.2790777087211609, 'train/grad_norm_pre_clip': 3.7195756435394287, 'timing/data': 0.00017431611195206642, 'timing/model': 0.4717329479753971, 'learning_rate/action_model': 5.747703540325622e-05, 'learning_rate/action_query_proj': 5.747703540325622e-05, 'learning_rate/base': 1.4369258850814055e-05, 'epoch': 0.28}) +[2026-07-26 22:58:25,180][starVLA.training.train_starvla][INFO] - Step 2319, Loss: {'train/loss': 0.205200657248497, 'train/grad_norm_pre_clip': 2.4716241359710693, 'timing/data': 0.00017441902309656143, 'timing/model': 0.4760881750844419, 'learning_rate/action_model': 5.744707201380055e-05, 'learning_rate/action_query_proj': 5.744707201380055e-05, 'learning_rate/base': 1.4361768003450137e-05, 'epoch': 0.28}) +[2026-07-26 22:58:30,783][starVLA.training.train_starvla][INFO] - Step 2320, Loss: {'train/loss': 0.24575649201869965, 'train/grad_norm_pre_clip': 3.708648443222046, 'timing/data': 0.00017446791753172874, 'timing/model': 0.47003832925111055, 'learning_rate/action_model': 5.741710647392712e-05, 'learning_rate/action_query_proj': 5.741710647392712e-05, 'learning_rate/base': 1.435427661848178e-05, 'epoch': 0.28}) +[2026-07-26 22:58:36,375][starVLA.training.train_starvla][INFO] - Step 2321, Loss: {'train/loss': 0.23018673062324524, 'train/grad_norm_pre_clip': 5.006730556488037, 'timing/data': 0.00018030498176813126, 'timing/model': 0.47837233636528254, 'learning_rate/action_model': 5.7387138795465855e-05, 'learning_rate/action_query_proj': 5.7387138795465855e-05, 'learning_rate/base': 1.4346784698866464e-05, 'epoch': 0.28}) +[2026-07-26 22:58:41,962][starVLA.training.train_starvla][INFO] - Step 2322, Loss: {'train/loss': 0.2142900824546814, 'train/grad_norm_pre_clip': 4.566804885864258, 'timing/data': 0.00017719389870762825, 'timing/model': 0.47890115808695555, 'learning_rate/action_model': 5.735716899024751e-05, 'learning_rate/action_query_proj': 5.735716899024751e-05, 'learning_rate/base': 1.4339292247561877e-05, 'epoch': 0.28}) +[2026-07-26 22:58:47,517][starVLA.training.train_starvla][INFO] - Step 2323, Loss: {'train/loss': 0.2328520119190216, 'train/grad_norm_pre_clip': 3.989572525024414, 'timing/data': 0.00017431331798434258, 'timing/model': 0.4697915567085147, 'learning_rate/action_model': 5.732719707010368e-05, 'learning_rate/action_query_proj': 5.732719707010368e-05, 'learning_rate/base': 1.433179926752592e-05, 'epoch': 0.28}) +[2026-07-26 22:58:53,065][starVLA.training.train_starvla][INFO] - Step 2324, Loss: {'train/loss': 0.28620192408561707, 'train/grad_norm_pre_clip': 3.602195978164673, 'timing/data': 0.00017238128930330276, 'timing/model': 0.47098656138405204, 'learning_rate/action_model': 5.729722304686681e-05, 'learning_rate/action_query_proj': 5.729722304686681e-05, 'learning_rate/base': 1.4324305761716702e-05, 'epoch': 0.28}) +[2026-07-26 22:58:58,624][starVLA.training.train_starvla][INFO] - Step 2325, Loss: {'train/loss': 0.11328373849391937, 'train/grad_norm_pre_clip': 1.9219635725021362, 'timing/data': 0.00017509283497929573, 'timing/model': 0.477523370180279, 'learning_rate/action_model': 5.726724693237017e-05, 'learning_rate/action_query_proj': 5.726724693237017e-05, 'learning_rate/base': 1.4316811733092542e-05, 'epoch': 0.28}) +[2026-07-26 22:59:04,181][starVLA.training.train_starvla][INFO] - Step 2326, Loss: {'train/loss': 0.22694149613380432, 'train/grad_norm_pre_clip': 3.3728911876678467, 'timing/data': 0.0001767510548233986, 'timing/model': 0.4777293438091874, 'learning_rate/action_model': 5.723726873844787e-05, 'learning_rate/action_query_proj': 5.723726873844787e-05, 'learning_rate/base': 1.4309317184611968e-05, 'epoch': 0.28}) +[2026-07-26 22:59:09,734][starVLA.training.train_starvla][INFO] - Step 2327, Loss: {'train/loss': 0.20330341160297394, 'train/grad_norm_pre_clip': 3.184485912322998, 'timing/data': 0.0001782737672328949, 'timing/model': 0.47022648295387626, 'learning_rate/action_model': 5.7207288476934814e-05, 'learning_rate/action_query_proj': 5.7207288476934814e-05, 'learning_rate/base': 1.4301822119233703e-05, 'epoch': 0.28}) +[2026-07-26 22:59:15,292][starVLA.training.train_starvla][INFO] - Step 2328, Loss: {'train/loss': 0.13959887623786926, 'train/grad_norm_pre_clip': 3.3448636531829834, 'timing/data': 0.00017369911074638367, 'timing/model': 0.4780313242226839, 'learning_rate/action_model': 5.7177306159666736e-05, 'learning_rate/action_query_proj': 5.7177306159666736e-05, 'learning_rate/base': 1.4294326539916684e-05, 'epoch': 0.28}) +[2026-07-26 22:59:20,842][starVLA.training.train_starvla][INFO] - Step 2329, Loss: {'train/loss': 0.2202109843492508, 'train/grad_norm_pre_clip': 2.945230484008789, 'timing/data': 0.00017567677423357964, 'timing/model': 0.46894816821441054, 'learning_rate/action_model': 5.714732179848017e-05, 'learning_rate/action_query_proj': 5.714732179848017e-05, 'learning_rate/base': 1.4286830449620042e-05, 'epoch': 0.28}) +[2026-07-26 22:59:26,399][starVLA.training.train_starvla][INFO] - Step 2330, Loss: {'train/loss': 0.19234171509742737, 'train/grad_norm_pre_clip': 3.265427827835083, 'timing/data': 0.00017805909737944603, 'timing/model': 0.4688799688592553, 'learning_rate/action_model': 5.711733540521248e-05, 'learning_rate/action_query_proj': 5.711733540521248e-05, 'learning_rate/base': 1.427933385130312e-05, 'epoch': 0.28}) +[2026-07-26 22:59:31,946][starVLA.training.train_starvla][INFO] - Step 2331, Loss: {'train/loss': 0.2832339107990265, 'train/grad_norm_pre_clip': 3.900906801223755, 'timing/data': 0.00017567258328199387, 'timing/model': 0.46981178130954504, 'learning_rate/action_model': 5.708734699170181e-05, 'learning_rate/action_query_proj': 5.708734699170181e-05, 'learning_rate/base': 1.4271836747925452e-05, 'epoch': 0.28}) +[2026-07-26 22:59:37,508][starVLA.training.train_starvla][INFO] - Step 2332, Loss: {'train/loss': 0.2776259183883667, 'train/grad_norm_pre_clip': 4.180500030517578, 'timing/data': 0.0001754038967192173, 'timing/model': 0.4719328177161515, 'learning_rate/action_model': 5.7057356569787124e-05, 'learning_rate/action_query_proj': 5.7057356569787124e-05, 'learning_rate/base': 1.4264339142446781e-05, 'epoch': 0.28}) +[2026-07-26 22:59:43,322][starVLA.training.train_starvla][INFO] - Step 2333, Loss: {'train/loss': 0.28772205114364624, 'train/grad_norm_pre_clip': 3.8951048851013184, 'timing/data': 0.00017951009795069695, 'timing/model': 0.4691576389595866, 'learning_rate/action_model': 5.702736415130816e-05, 'learning_rate/action_query_proj': 5.702736415130816e-05, 'learning_rate/base': 1.425684103782704e-05, 'epoch': 0.28}) +[2026-07-26 22:59:48,892][starVLA.training.train_starvla][INFO] - Step 2334, Loss: {'train/loss': 0.18442757427692413, 'train/grad_norm_pre_clip': 3.6040775775909424, 'timing/data': 0.0001739002764225006, 'timing/model': 0.4770884569734335, 'learning_rate/action_model': 5.699736974810545e-05, 'learning_rate/action_query_proj': 5.699736974810545e-05, 'learning_rate/base': 1.4249342437026362e-05, 'epoch': 0.28}) +[2026-07-26 22:59:54,450][starVLA.training.train_starvla][INFO] - Step 2335, Loss: {'train/loss': 0.20490731298923492, 'train/grad_norm_pre_clip': 3.8748538494110107, 'timing/data': 0.00017109233886003494, 'timing/model': 0.47126621985808015, 'learning_rate/action_model': 5.6967373372020285e-05, 'learning_rate/action_query_proj': 5.6967373372020285e-05, 'learning_rate/base': 1.4241843343005071e-05, 'epoch': 0.28}) +[2026-07-26 23:00:00,011][starVLA.training.train_starvla][INFO] - Step 2336, Loss: {'train/loss': 0.23979611694812775, 'train/grad_norm_pre_clip': 2.9355204105377197, 'timing/data': 0.00017553800716996193, 'timing/model': 0.4725077631883323, 'learning_rate/action_model': 5.69373750348948e-05, 'learning_rate/action_query_proj': 5.69373750348948e-05, 'learning_rate/base': 1.42343437587237e-05, 'epoch': 0.28}) +[2026-07-26 23:00:05,628][starVLA.training.train_starvla][INFO] - Step 2337, Loss: {'train/loss': 0.22153371572494507, 'train/grad_norm_pre_clip': 3.319375991821289, 'timing/data': 0.00018906407058238983, 'timing/model': 0.4760105670429766, 'learning_rate/action_model': 5.690737474857184e-05, 'learning_rate/action_query_proj': 5.690737474857184e-05, 'learning_rate/base': 1.422684368714296e-05, 'epoch': 0.28}) +[2026-07-26 23:00:11,193][starVLA.training.train_starvla][INFO] - Step 2338, Loss: {'train/loss': 0.26037704944610596, 'train/grad_norm_pre_clip': 4.055980682373047, 'timing/data': 0.00017383182421326637, 'timing/model': 0.47058145701885223, 'learning_rate/action_model': 5.6877372524895044e-05, 'learning_rate/action_query_proj': 5.6877372524895044e-05, 'learning_rate/base': 1.4219343131223761e-05, 'epoch': 0.28}) +[2026-07-26 23:00:16,749][starVLA.training.train_starvla][INFO] - Step 2339, Loss: {'train/loss': 0.2990935742855072, 'train/grad_norm_pre_clip': 5.3588738441467285, 'timing/data': 0.0001749340444803238, 'timing/model': 0.4724520272575319, 'learning_rate/action_model': 5.684736837570882e-05, 'learning_rate/action_query_proj': 5.684736837570882e-05, 'learning_rate/base': 1.4211842093927206e-05, 'epoch': 0.28}) +[2026-07-26 23:00:22,303][starVLA.training.train_starvla][INFO] - Step 2340, Loss: {'train/loss': 0.2661445736885071, 'train/grad_norm_pre_clip': 3.4518189430236816, 'timing/data': 0.0001731780357658863, 'timing/model': 0.47100304812192917, 'learning_rate/action_model': 5.681736231285831e-05, 'learning_rate/action_query_proj': 5.681736231285831e-05, 'learning_rate/base': 1.4204340578214578e-05, 'epoch': 0.28}) +[2026-07-26 23:00:27,854][starVLA.training.train_starvla][INFO] - Step 2341, Loss: {'train/loss': 0.11622123420238495, 'train/grad_norm_pre_clip': 2.937994956970215, 'timing/data': 0.00017121341079473495, 'timing/model': 0.47098510013893247, 'learning_rate/action_model': 5.678735434818948e-05, 'learning_rate/action_query_proj': 5.678735434818948e-05, 'learning_rate/base': 1.419683858704737e-05, 'epoch': 0.28}) +[2026-07-26 23:00:33,415][starVLA.training.train_starvla][INFO] - Step 2342, Loss: {'train/loss': 0.18964837491512299, 'train/grad_norm_pre_clip': 2.87560772895813, 'timing/data': 0.0001714080572128296, 'timing/model': 0.47136479476466775, 'learning_rate/action_model': 5.675734449354896e-05, 'learning_rate/action_query_proj': 5.675734449354896e-05, 'learning_rate/base': 1.418933612338724e-05, 'epoch': 0.28}) +[2026-07-26 23:00:38,969][starVLA.training.train_starvla][INFO] - Step 2343, Loss: {'train/loss': 0.2319331169128418, 'train/grad_norm_pre_clip': 3.935122013092041, 'timing/data': 0.00017731031402945518, 'timing/model': 0.4697273811325431, 'learning_rate/action_model': 5.6727332760784165e-05, 'learning_rate/action_query_proj': 5.6727332760784165e-05, 'learning_rate/base': 1.4181833190196041e-05, 'epoch': 0.28}) +[2026-07-26 23:00:44,531][starVLA.training.train_starvla][INFO] - Step 2344, Loss: {'train/loss': 0.21899013221263885, 'train/grad_norm_pre_clip': 2.870990514755249, 'timing/data': 0.00017280690371990204, 'timing/model': 0.4677127990871668, 'learning_rate/action_model': 5.669731916174329e-05, 'learning_rate/action_query_proj': 5.669731916174329e-05, 'learning_rate/base': 1.4174329790435822e-05, 'epoch': 0.28}) +[2026-07-26 23:00:50,079][starVLA.training.train_starvla][INFO] - Step 2345, Loss: {'train/loss': 0.28124019503593445, 'train/grad_norm_pre_clip': 4.147287368774414, 'timing/data': 0.0001784777268767357, 'timing/model': 0.4756414941512048, 'learning_rate/action_model': 5.666730370827519e-05, 'learning_rate/action_query_proj': 5.666730370827519e-05, 'learning_rate/base': 1.4166825927068797e-05, 'epoch': 0.28}) +[2026-07-26 23:00:55,655][starVLA.training.train_starvla][INFO] - Step 2346, Loss: {'train/loss': 0.15859726071357727, 'train/grad_norm_pre_clip': 3.3306572437286377, 'timing/data': 0.00017455127090215683, 'timing/model': 0.471762013155967, 'learning_rate/action_model': 5.663728641222947e-05, 'learning_rate/action_query_proj': 5.663728641222947e-05, 'learning_rate/base': 1.4159321603057368e-05, 'epoch': 0.28}) +[2026-07-26 23:01:01,209][starVLA.training.train_starvla][INFO] - Step 2347, Loss: {'train/loss': 0.20181837677955627, 'train/grad_norm_pre_clip': 3.3177435398101807, 'timing/data': 0.00017902301624417305, 'timing/model': 0.4682116433978081, 'learning_rate/action_model': 5.660726728545655e-05, 'learning_rate/action_query_proj': 5.660726728545655e-05, 'learning_rate/base': 1.4151816821364138e-05, 'epoch': 0.28}) +[2026-07-26 23:01:06,795][starVLA.training.train_starvla][INFO] - Step 2348, Loss: {'train/loss': 0.23683400452136993, 'train/grad_norm_pre_clip': 4.925920486450195, 'timing/data': 0.0001857466995716095, 'timing/model': 0.46929234219715, 'learning_rate/action_model': 5.657724633980746e-05, 'learning_rate/action_query_proj': 5.657724633980746e-05, 'learning_rate/base': 1.4144311584951864e-05, 'epoch': 0.28}) +[2026-07-26 23:01:12,354][starVLA.training.train_starvla][INFO] - Step 2349, Loss: {'train/loss': 0.23314885795116425, 'train/grad_norm_pre_clip': 3.3869965076446533, 'timing/data': 0.00017730286344885826, 'timing/model': 0.4705249550752342, 'learning_rate/action_model': 5.6547223587134016e-05, 'learning_rate/action_query_proj': 5.6547223587134016e-05, 'learning_rate/base': 1.4136805896783504e-05, 'epoch': 0.28}) +[2026-07-26 23:01:17,916][starVLA.training.train_starvla][INFO] - Step 2350, Loss: {'train/loss': 0.1744914948940277, 'train/grad_norm_pre_clip': 2.36037015914917, 'timing/data': 0.00017971685156226158, 'timing/model': 0.4709297763183713, 'learning_rate/action_model': 5.651719903928871e-05, 'learning_rate/action_query_proj': 5.651719903928871e-05, 'learning_rate/base': 1.4129299759822177e-05, 'epoch': 0.29}) +[2026-07-26 23:01:23,478][starVLA.training.train_starvla][INFO] - Step 2351, Loss: {'train/loss': 0.1583574414253235, 'train/grad_norm_pre_clip': 2.04132080078125, 'timing/data': 0.0001749102957546711, 'timing/model': 0.4681565002538264, 'learning_rate/action_model': 5.6487172708124735e-05, 'learning_rate/action_query_proj': 5.6487172708124735e-05, 'learning_rate/base': 1.4121793177031184e-05, 'epoch': 0.29}) +[2026-07-26 23:01:29,067][starVLA.training.train_starvla][INFO] - Step 2352, Loss: {'train/loss': 0.14672672748565674, 'train/grad_norm_pre_clip': 2.5309994220733643, 'timing/data': 0.00017892662435770035, 'timing/model': 0.45804069098085165, 'learning_rate/action_model': 5.645714460549606e-05, 'learning_rate/action_query_proj': 5.645714460549606e-05, 'learning_rate/base': 1.4114286151374015e-05, 'epoch': 0.29}) +[2026-07-26 23:01:34,606][starVLA.training.train_starvla][INFO] - Step 2353, Loss: {'train/loss': 0.23213912546634674, 'train/grad_norm_pre_clip': 3.3200955390930176, 'timing/data': 0.00017766840755939484, 'timing/model': 0.4584002420306206, 'learning_rate/action_model': 5.642711474325728e-05, 'learning_rate/action_query_proj': 5.642711474325728e-05, 'learning_rate/base': 1.410677868581432e-05, 'epoch': 0.29}) +[2026-07-26 23:01:40,134][starVLA.training.train_starvla][INFO] - Step 2354, Loss: {'train/loss': 0.12114714086055756, 'train/grad_norm_pre_clip': 2.614590883255005, 'timing/data': 0.0001836949959397316, 'timing/model': 0.4574724491685629, 'learning_rate/action_model': 5.6397083133263717e-05, 'learning_rate/action_query_proj': 5.6397083133263717e-05, 'learning_rate/base': 1.4099270783315929e-05, 'epoch': 0.29}) +[2026-07-26 23:01:45,666][starVLA.training.train_starvla][INFO] - Step 2355, Loss: {'train/loss': 0.20459558069705963, 'train/grad_norm_pre_clip': 3.025175094604492, 'timing/data': 0.00018447311595082283, 'timing/model': 0.458847944624722, 'learning_rate/action_model': 5.6367049787371373e-05, 'learning_rate/action_query_proj': 5.6367049787371373e-05, 'learning_rate/base': 1.4091762446842843e-05, 'epoch': 0.29}) +[2026-07-26 23:01:51,201][starVLA.training.train_starvla][INFO] - Step 2356, Loss: {'train/loss': 0.28948473930358887, 'train/grad_norm_pre_clip': 3.5199508666992188, 'timing/data': 0.00017460715025663376, 'timing/model': 0.4582911911420524, 'learning_rate/action_model': 5.633701471743691e-05, 'learning_rate/action_query_proj': 5.633701471743691e-05, 'learning_rate/base': 1.4084253679359228e-05, 'epoch': 0.29}) +[2026-07-26 23:01:56,730][starVLA.training.train_starvla][INFO] - Step 2357, Loss: {'train/loss': 0.1759069859981537, 'train/grad_norm_pre_clip': 2.8502330780029297, 'timing/data': 0.00017584487795829773, 'timing/model': 0.45931609673425555, 'learning_rate/action_model': 5.630697793531774e-05, 'learning_rate/action_query_proj': 5.630697793531774e-05, 'learning_rate/base': 1.4076744483829435e-05, 'epoch': 0.29}) +[2026-07-26 23:02:02,267][starVLA.training.train_starvla][INFO] - Step 2358, Loss: {'train/loss': 0.3451343774795532, 'train/grad_norm_pre_clip': 4.409091472625732, 'timing/data': 0.000177701935172081, 'timing/model': 0.45852163061499596, 'learning_rate/action_model': 5.627693945287189e-05, 'learning_rate/action_query_proj': 5.627693945287189e-05, 'learning_rate/base': 1.4069234863217972e-05, 'epoch': 0.29}) +[2026-07-26 23:02:07,785][starVLA.training.train_starvla][INFO] - Step 2359, Loss: {'train/loss': 0.22645381093025208, 'train/grad_norm_pre_clip': 3.4544410705566406, 'timing/data': 0.00017587188631296158, 'timing/model': 0.458078111987561, 'learning_rate/action_model': 5.6246899281958073e-05, 'learning_rate/action_query_proj': 5.6246899281958073e-05, 'learning_rate/base': 1.4061724820489518e-05, 'epoch': 0.29}) +[2026-07-26 23:02:13,312][starVLA.training.train_starvla][INFO] - Step 2360, Loss: {'train/loss': 0.1483067274093628, 'train/grad_norm_pre_clip': 3.082249879837036, 'timing/data': 0.00017706817016005516, 'timing/model': 0.45859318412840366, 'learning_rate/action_model': 5.6216857434435687e-05, 'learning_rate/action_query_proj': 5.6216857434435687e-05, 'learning_rate/base': 1.4054214358608922e-05, 'epoch': 0.29}) +[2026-07-26 23:02:18,852][starVLA.training.train_starvla][INFO] - Step 2361, Loss: {'train/loss': 0.21778705716133118, 'train/grad_norm_pre_clip': 2.9427239894866943, 'timing/data': 0.0001850132830440998, 'timing/model': 0.4578727940097451, 'learning_rate/action_model': 5.618681392216475e-05, 'learning_rate/action_query_proj': 5.618681392216475e-05, 'learning_rate/base': 1.4046703480541187e-05, 'epoch': 0.29}) +[2026-07-26 23:02:24,383][starVLA.training.train_starvla][INFO] - Step 2362, Loss: {'train/loss': 0.2981642484664917, 'train/grad_norm_pre_clip': 3.617002487182617, 'timing/data': 0.00017450517043471336, 'timing/model': 0.4585931939072907, 'learning_rate/action_model': 5.615676875700599e-05, 'learning_rate/action_query_proj': 5.615676875700599e-05, 'learning_rate/base': 1.4039192189251498e-05, 'epoch': 0.29}) +[2026-07-26 23:02:29,911][starVLA.training.train_starvla][INFO] - Step 2363, Loss: {'train/loss': 0.23407313227653503, 'train/grad_norm_pre_clip': 4.196963310241699, 'timing/data': 0.00017632078379392624, 'timing/model': 0.45747453114017844, 'learning_rate/action_model': 5.612672195082076e-05, 'learning_rate/action_query_proj': 5.612672195082076e-05, 'learning_rate/base': 1.403168048770519e-05, 'epoch': 0.29}) +[2026-07-26 23:02:35,439][starVLA.training.train_starvla][INFO] - Step 2364, Loss: {'train/loss': 0.23304183781147003, 'train/grad_norm_pre_clip': 3.1980607509613037, 'timing/data': 0.00017827097326517105, 'timing/model': 0.45814717281609774, 'learning_rate/action_model': 5.609667351547106e-05, 'learning_rate/action_query_proj': 5.609667351547106e-05, 'learning_rate/base': 1.4024168378867766e-05, 'epoch': 0.29}) +[2026-07-26 23:02:41,015][starVLA.training.train_starvla][INFO] - Step 2365, Loss: {'train/loss': 0.16131910681724548, 'train/grad_norm_pre_clip': 2.563765048980713, 'timing/data': 0.00017458805814385414, 'timing/model': 0.4585036230273545, 'learning_rate/action_model': 5.606662346281953e-05, 'learning_rate/action_query_proj': 5.606662346281953e-05, 'learning_rate/base': 1.4016655865704883e-05, 'epoch': 0.29}) +[2026-07-26 23:02:46,566][starVLA.training.train_starvla][INFO] - Step 2366, Loss: {'train/loss': 0.1900104284286499, 'train/grad_norm_pre_clip': 4.38438606262207, 'timing/data': 0.00017595291137695312, 'timing/model': 0.4575612349435687, 'learning_rate/action_model': 5.603657180472945e-05, 'learning_rate/action_query_proj': 5.603657180472945e-05, 'learning_rate/base': 1.4009142951182363e-05, 'epoch': 0.29}) +[2026-07-26 23:02:52,142][starVLA.training.train_starvla][INFO] - Step 2367, Loss: {'train/loss': 0.17580567300319672, 'train/grad_norm_pre_clip': 2.9265213012695312, 'timing/data': 0.00018608104437589645, 'timing/model': 0.4596969713456929, 'learning_rate/action_model': 5.600651855306477e-05, 'learning_rate/action_query_proj': 5.600651855306477e-05, 'learning_rate/base': 1.4001629638266193e-05, 'epoch': 0.29}) +[2026-07-26 23:02:57,662][starVLA.training.train_starvla][INFO] - Step 2368, Loss: {'train/loss': 0.22987720370292664, 'train/grad_norm_pre_clip': 3.115062952041626, 'timing/data': 0.00017373869195580482, 'timing/model': 0.45842498634010553, 'learning_rate/action_model': 5.597646371969e-05, 'learning_rate/action_query_proj': 5.597646371969e-05, 'learning_rate/base': 1.39941159299225e-05, 'epoch': 0.29}) +[2026-07-26 23:03:03,207][starVLA.training.train_starvla][INFO] - Step 2369, Loss: {'train/loss': 0.22036010026931763, 'train/grad_norm_pre_clip': 3.548333168029785, 'timing/data': 0.00017902767285704613, 'timing/model': 0.4716990450397134, 'learning_rate/action_model': 5.5946407316470336e-05, 'learning_rate/action_query_proj': 5.5946407316470336e-05, 'learning_rate/base': 1.3986601829117584e-05, 'epoch': 0.29}) +[2026-07-26 23:03:08,755][starVLA.training.train_starvla][INFO] - Step 2370, Loss: {'train/loss': 0.1722429096698761, 'train/grad_norm_pre_clip': 3.2577128410339355, 'timing/data': 0.00017612287774682045, 'timing/model': 0.4787009381689131, 'learning_rate/action_model': 5.591634935527158e-05, 'learning_rate/action_query_proj': 5.591634935527158e-05, 'learning_rate/base': 1.3979087338817894e-05, 'epoch': 0.29}) +[2026-07-26 23:03:14,335][starVLA.training.train_starvla][INFO] - Step 2371, Loss: {'train/loss': 0.24947012960910797, 'train/grad_norm_pre_clip': 2.8693134784698486, 'timing/data': 0.00017182622104883194, 'timing/model': 0.4708417900837958, 'learning_rate/action_model': 5.588628984796008e-05, 'learning_rate/action_query_proj': 5.588628984796008e-05, 'learning_rate/base': 1.397157246199002e-05, 'epoch': 0.29}) +[2026-07-26 23:03:19,902][starVLA.training.train_starvla][INFO] - Step 2372, Loss: {'train/loss': 0.1826924979686737, 'train/grad_norm_pre_clip': 3.434530019760132, 'timing/data': 0.00018173595890402794, 'timing/model': 0.47159091802313924, 'learning_rate/action_model': 5.585622880640293e-05, 'learning_rate/action_query_proj': 5.585622880640293e-05, 'learning_rate/base': 1.3964057201600733e-05, 'epoch': 0.29}) +[2026-07-26 23:03:25,495][starVLA.training.train_starvla][INFO] - Step 2373, Loss: {'train/loss': 0.216034933924675, 'train/grad_norm_pre_clip': 4.244793891906738, 'timing/data': 0.00018138810992240906, 'timing/model': 0.4729922991245985, 'learning_rate/action_model': 5.582616624246769e-05, 'learning_rate/action_query_proj': 5.582616624246769e-05, 'learning_rate/base': 1.3956541560616923e-05, 'epoch': 0.29}) +[2026-07-26 23:03:31,132][starVLA.training.train_starvla][INFO] - Step 2374, Loss: {'train/loss': 0.2537946105003357, 'train/grad_norm_pre_clip': 3.7177696228027344, 'timing/data': 0.0001780390739440918, 'timing/model': 0.47160165337845683, 'learning_rate/action_model': 5.579610216802264e-05, 'learning_rate/action_query_proj': 5.579610216802264e-05, 'learning_rate/base': 1.394902554200566e-05, 'epoch': 0.29}) +[2026-07-26 23:03:36,806][starVLA.training.train_starvla][INFO] - Step 2375, Loss: {'train/loss': 0.26299840211868286, 'train/grad_norm_pre_clip': 4.836269855499268, 'timing/data': 0.00017963116988539696, 'timing/model': 0.4724382711574435, 'learning_rate/action_model': 5.576603659493657e-05, 'learning_rate/action_query_proj': 5.576603659493657e-05, 'learning_rate/base': 1.3941509148734142e-05, 'epoch': 0.29}) +[2026-07-26 23:03:42,449][starVLA.training.train_starvla][INFO] - Step 2376, Loss: {'train/loss': 0.24172334372997284, 'train/grad_norm_pre_clip': 3.530593156814575, 'timing/data': 0.0001778402365744114, 'timing/model': 0.46778375608846545, 'learning_rate/action_model': 5.573596953507887e-05, 'learning_rate/action_query_proj': 5.573596953507887e-05, 'learning_rate/base': 1.3933992383769717e-05, 'epoch': 0.29}) +[2026-07-26 23:03:48,090][starVLA.training.train_starvla][INFO] - Step 2377, Loss: {'train/loss': 0.1836998015642166, 'train/grad_norm_pre_clip': 2.781864881515503, 'timing/data': 0.000191589817404747, 'timing/model': 0.4697295371443033, 'learning_rate/action_model': 5.570590100031958e-05, 'learning_rate/action_query_proj': 5.570590100031958e-05, 'learning_rate/base': 1.3926475250079896e-05, 'epoch': 0.29}) +[2026-07-26 23:03:53,732][starVLA.training.train_starvla][INFO] - Step 2378, Loss: {'train/loss': 0.22273261845111847, 'train/grad_norm_pre_clip': 3.6741373538970947, 'timing/data': 0.0001729968935251236, 'timing/model': 0.4759826851077378, 'learning_rate/action_model': 5.567583100252928e-05, 'learning_rate/action_query_proj': 5.567583100252928e-05, 'learning_rate/base': 1.391895775063232e-05, 'epoch': 0.29}) +[2026-07-26 23:03:59,369][starVLA.training.train_starvla][INFO] - Step 2379, Loss: {'train/loss': 0.20515045523643494, 'train/grad_norm_pre_clip': 3.7060744762420654, 'timing/data': 0.0001888517290353775, 'timing/model': 0.4699365342967212, 'learning_rate/action_model': 5.564575955357909e-05, 'learning_rate/action_query_proj': 5.564575955357909e-05, 'learning_rate/base': 1.3911439888394773e-05, 'epoch': 0.29}) +[2026-07-26 23:04:04,973][starVLA.training.train_starvla][INFO] - Step 2380, Loss: {'train/loss': 0.22137990593910217, 'train/grad_norm_pre_clip': 3.403907299041748, 'timing/data': 0.0001840321347117424, 'timing/model': 0.4715156042948365, 'learning_rate/action_model': 5.561568666534078e-05, 'learning_rate/action_query_proj': 5.561568666534078e-05, 'learning_rate/base': 1.3903921666335195e-05, 'epoch': 0.29}) +[2026-07-26 23:04:10,575][starVLA.training.train_starvla][INFO] - Step 2381, Loss: {'train/loss': 0.21794238686561584, 'train/grad_norm_pre_clip': 3.3824069499969482, 'timing/data': 0.00017958367243409157, 'timing/model': 0.4717623353935778, 'learning_rate/action_model': 5.5585612349686634e-05, 'learning_rate/action_query_proj': 5.5585612349686634e-05, 'learning_rate/base': 1.3896403087421658e-05, 'epoch': 0.29}) +[2026-07-26 23:04:16,191][starVLA.training.train_starvla][INFO] - Step 2382, Loss: {'train/loss': 0.24543461203575134, 'train/grad_norm_pre_clip': 3.494267225265503, 'timing/data': 0.00017666397616267204, 'timing/model': 0.47155942395329475, 'learning_rate/action_model': 5.555553661848951e-05, 'learning_rate/action_query_proj': 5.555553661848951e-05, 'learning_rate/base': 1.3888884154622378e-05, 'epoch': 0.29}) +[2026-07-26 23:04:21,823][starVLA.training.train_starvla][INFO] - Step 2383, Loss: {'train/loss': 0.1385117918252945, 'train/grad_norm_pre_clip': 3.37214732170105, 'timing/data': 0.0001819320023059845, 'timing/model': 0.4703155788592994, 'learning_rate/action_model': 5.552545948362283e-05, 'learning_rate/action_query_proj': 5.552545948362283e-05, 'learning_rate/base': 1.3881364870905707e-05, 'epoch': 0.29}) +[2026-07-26 23:04:27,443][starVLA.training.train_starvla][INFO] - Step 2384, Loss: {'train/loss': 0.1580272912979126, 'train/grad_norm_pre_clip': 4.369729042053223, 'timing/data': 0.00018686288967728615, 'timing/model': 0.470186113845557, 'learning_rate/action_model': 5.549538095696061e-05, 'learning_rate/action_query_proj': 5.549538095696061e-05, 'learning_rate/base': 1.3873845239240152e-05, 'epoch': 0.29}) +[2026-07-26 23:04:33,064][starVLA.training.train_starvla][INFO] - Step 2385, Loss: {'train/loss': 0.16572342813014984, 'train/grad_norm_pre_clip': 2.932272434234619, 'timing/data': 0.0001924913376569748, 'timing/model': 0.4694977579638362, 'learning_rate/action_model': 5.546530105037733e-05, 'learning_rate/action_query_proj': 5.546530105037733e-05, 'learning_rate/base': 1.3866325262594332e-05, 'epoch': 0.29}) +[2026-07-26 23:04:38,662][starVLA.training.train_starvla][INFO] - Step 2386, Loss: {'train/loss': 0.12314058840274811, 'train/grad_norm_pre_clip': 3.173642158508301, 'timing/data': 0.00018341979011893272, 'timing/model': 0.4719800688326359, 'learning_rate/action_model': 5.5435219775748056e-05, 'learning_rate/action_query_proj': 5.5435219775748056e-05, 'learning_rate/base': 1.3858804943937014e-05, 'epoch': 0.29}) +[2026-07-26 23:04:44,288][starVLA.training.train_starvla][INFO] - Step 2387, Loss: {'train/loss': 0.2579779028892517, 'train/grad_norm_pre_clip': 3.616936445236206, 'timing/data': 0.00017855409532785416, 'timing/model': 0.47089950181543827, 'learning_rate/action_model': 5.5405137144948436e-05, 'learning_rate/action_query_proj': 5.5405137144948436e-05, 'learning_rate/base': 1.3851284286237109e-05, 'epoch': 0.29}) +[2026-07-26 23:04:49,910][starVLA.training.train_starvla][INFO] - Step 2388, Loss: {'train/loss': 0.20515483617782593, 'train/grad_norm_pre_clip': 2.6045544147491455, 'timing/data': 0.00018456997349858284, 'timing/model': 0.4702977519482374, 'learning_rate/action_model': 5.53750531698546e-05, 'learning_rate/action_query_proj': 5.53750531698546e-05, 'learning_rate/base': 1.384376329246365e-05, 'epoch': 0.29}) +[2026-07-26 23:04:55,513][starVLA.training.train_starvla][INFO] - Step 2389, Loss: {'train/loss': 0.3082676827907562, 'train/grad_norm_pre_clip': 3.6885035037994385, 'timing/data': 0.00017545185983181, 'timing/model': 0.4700746717862785, 'learning_rate/action_model': 5.534496786234321e-05, 'learning_rate/action_query_proj': 5.534496786234321e-05, 'learning_rate/base': 1.3836241965585803e-05, 'epoch': 0.29}) +[2026-07-26 23:05:01,136][starVLA.training.train_starvla][INFO] - Step 2390, Loss: {'train/loss': 0.30668866634368896, 'train/grad_norm_pre_clip': 3.473858594894409, 'timing/data': 0.00017991289496421814, 'timing/model': 0.4714204999618232, 'learning_rate/action_model': 5.531488123429149e-05, 'learning_rate/action_query_proj': 5.531488123429149e-05, 'learning_rate/base': 1.3828720308572873e-05, 'epoch': 0.29}) +[2026-07-26 23:05:06,939][starVLA.training.train_starvla][INFO] - Step 2391, Loss: {'train/loss': 0.2037883847951889, 'train/grad_norm_pre_clip': 2.976463556289673, 'timing/data': 0.00018402887508273125, 'timing/model': 0.458975768648088, 'learning_rate/action_model': 5.528479329757715e-05, 'learning_rate/action_query_proj': 5.528479329757715e-05, 'learning_rate/base': 1.3821198324394288e-05, 'epoch': 0.29}) +[2026-07-26 23:05:12,518][starVLA.training.train_starvla][INFO] - Step 2392, Loss: {'train/loss': 0.2307334542274475, 'train/grad_norm_pre_clip': 2.963852643966675, 'timing/data': 0.00018194690346717834, 'timing/model': 0.4712291290052235, 'learning_rate/action_model': 5.5254704064078445e-05, 'learning_rate/action_query_proj': 5.5254704064078445e-05, 'learning_rate/base': 1.3813676016019611e-05, 'epoch': 0.29}) +[2026-07-26 23:05:18,133][starVLA.training.train_starvla][INFO] - Step 2393, Loss: {'train/loss': 0.23008809983730316, 'train/grad_norm_pre_clip': 4.5497846603393555, 'timing/data': 0.0001775757409632206, 'timing/model': 0.4684577672742307, 'learning_rate/action_model': 5.522461354567412e-05, 'learning_rate/action_query_proj': 5.522461354567412e-05, 'learning_rate/base': 1.380615338641853e-05, 'epoch': 0.29}) +[2026-07-26 23:05:23,731][starVLA.training.train_starvla][INFO] - Step 2394, Loss: {'train/loss': 0.2996556758880615, 'train/grad_norm_pre_clip': 3.3560397624969482, 'timing/data': 0.00018586823716759682, 'timing/model': 0.4705448509193957, 'learning_rate/action_model': 5.5194521754243434e-05, 'learning_rate/action_query_proj': 5.5194521754243434e-05, 'learning_rate/base': 1.3798630438560859e-05, 'epoch': 0.29}) +[2026-07-26 23:05:29,340][starVLA.training.train_starvla][INFO] - Step 2395, Loss: {'train/loss': 0.20296673476696014, 'train/grad_norm_pre_clip': 4.22550106048584, 'timing/data': 0.00017394497990608215, 'timing/model': 0.4715819279663265, 'learning_rate/action_model': 5.516442870166615e-05, 'learning_rate/action_query_proj': 5.516442870166615e-05, 'learning_rate/base': 1.3791107175416537e-05, 'epoch': 0.29}) +[2026-07-26 23:05:34,936][starVLA.training.train_starvla][INFO] - Step 2396, Loss: {'train/loss': 0.18940655887126923, 'train/grad_norm_pre_clip': 3.8480989933013916, 'timing/data': 0.00018513621762394905, 'timing/model': 0.4695135438814759, 'learning_rate/action_model': 5.513433439982252e-05, 'learning_rate/action_query_proj': 5.513433439982252e-05, 'learning_rate/base': 1.378358359995563e-05, 'epoch': 0.29}) +[2026-07-26 23:05:40,555][starVLA.training.train_starvla][INFO] - Step 2397, Loss: {'train/loss': 0.1966058611869812, 'train/grad_norm_pre_clip': 3.5116326808929443, 'timing/data': 0.00018086889758706093, 'timing/model': 0.4704889669083059, 'learning_rate/action_model': 5.5104238860593325e-05, 'learning_rate/action_query_proj': 5.5104238860593325e-05, 'learning_rate/base': 1.3776059715148331e-05, 'epoch': 0.29}) +[2026-07-26 23:05:46,178][starVLA.training.train_starvla][INFO] - Step 2398, Loss: {'train/loss': 0.1671166867017746, 'train/grad_norm_pre_clip': 2.4999334812164307, 'timing/data': 0.00017111701890826225, 'timing/model': 0.4780635233037174, 'learning_rate/action_model': 5.507414209585977e-05, 'learning_rate/action_query_proj': 5.507414209585977e-05, 'learning_rate/base': 1.3768535523964943e-05, 'epoch': 0.29}) +[2026-07-26 23:05:51,970][starVLA.training.train_starvla][INFO] - Step 2399, Loss: {'train/loss': 0.16713367402553558, 'train/grad_norm_pre_clip': 2.489609956741333, 'timing/data': 0.00017404090613126755, 'timing/model': 0.46843707421794534, 'learning_rate/action_model': 5.504404411750361e-05, 'learning_rate/action_query_proj': 5.504404411750361e-05, 'learning_rate/base': 1.3761011029375903e-05, 'epoch': 0.29}) +[2026-07-26 23:05:57,566][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2400 +[2026-07-26 23:05:57,567][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2400 +[2026-07-26 23:05:57,567][starVLA.training.train_starvla][INFO] - Step 2400, Loss: {'train/loss': 0.3396926820278168, 'train/grad_norm_pre_clip': 3.840892791748047, 'timing/data': 0.00017293216660618782, 'timing/model': 0.46896588196977973, 'learning_rate/action_model': 5.5013944937407045e-05, 'learning_rate/action_query_proj': 5.5013944937407045e-05, 'learning_rate/base': 1.3753486234351761e-05, 'epoch': 0.29}) +[2026-07-26 23:06:03,175][starVLA.training.train_starvla][INFO] - Step 2401, Loss: {'train/loss': 0.2266591638326645, 'train/grad_norm_pre_clip': 3.4795756340026855, 'timing/data': 0.00017550773918628693, 'timing/model': 0.470515969209373, 'learning_rate/action_model': 5.498384456745275e-05, 'learning_rate/action_query_proj': 5.498384456745275e-05, 'learning_rate/base': 1.3745961141863187e-05, 'epoch': 0.29}) +[2026-07-26 23:06:08,777][starVLA.training.train_starvla][INFO] - Step 2402, Loss: {'train/loss': 0.22431275248527527, 'train/grad_norm_pre_clip': 3.466226100921631, 'timing/data': 0.00018453598022460938, 'timing/model': 0.47182373236864805, 'learning_rate/action_model': 5.495374301952387e-05, 'learning_rate/action_query_proj': 5.495374301952387e-05, 'learning_rate/base': 1.3738435754880968e-05, 'epoch': 0.29}) +[2026-07-26 23:06:14,421][starVLA.training.train_starvla][INFO] - Step 2403, Loss: {'train/loss': 0.17931388318538666, 'train/grad_norm_pre_clip': 2.7119059562683105, 'timing/data': 0.00017287582159042358, 'timing/model': 0.45805555395781994, 'learning_rate/action_model': 5.492364030550403e-05, 'learning_rate/action_query_proj': 5.492364030550403e-05, 'learning_rate/base': 1.3730910076376007e-05, 'epoch': 0.29}) +[2026-07-26 23:06:20,005][starVLA.training.train_starvla][INFO] - Step 2404, Loss: {'train/loss': 0.15157432854175568, 'train/grad_norm_pre_clip': 2.535856246948242, 'timing/data': 0.0002522990107536316, 'timing/model': 0.45915118185803294, 'learning_rate/action_model': 5.489353643727731e-05, 'learning_rate/action_query_proj': 5.489353643727731e-05, 'learning_rate/base': 1.3723384109319327e-05, 'epoch': 0.29}) +[2026-07-26 23:06:25,612][starVLA.training.train_starvla][INFO] - Step 2405, Loss: {'train/loss': 0.20187300443649292, 'train/grad_norm_pre_clip': 3.2456324100494385, 'timing/data': 0.00020600203424692154, 'timing/model': 0.46074686478823423, 'learning_rate/action_model': 5.4863431426728204e-05, 'learning_rate/action_query_proj': 5.4863431426728204e-05, 'learning_rate/base': 1.3715857856682051e-05, 'epoch': 0.29}) +[2026-07-26 23:06:31,239][starVLA.training.train_starvla][INFO] - Step 2406, Loss: {'train/loss': 0.15112867951393127, 'train/grad_norm_pre_clip': 2.6495447158813477, 'timing/data': 0.00017937598749995232, 'timing/model': 0.4762513590976596, 'learning_rate/action_model': 5.4833325285741724e-05, 'learning_rate/action_query_proj': 5.4833325285741724e-05, 'learning_rate/base': 1.3708331321435431e-05, 'epoch': 0.29}) +[2026-07-26 23:06:36,859][starVLA.training.train_starvla][INFO] - Step 2407, Loss: {'train/loss': 0.2166222631931305, 'train/grad_norm_pre_clip': 3.813829183578491, 'timing/data': 0.00017382390797138214, 'timing/model': 0.4702542438171804, 'learning_rate/action_model': 5.4803218026203296e-05, 'learning_rate/action_query_proj': 5.4803218026203296e-05, 'learning_rate/base': 1.3700804506550824e-05, 'epoch': 0.29}) +[2026-07-26 23:06:42,542][starVLA.training.train_starvla][INFO] - Step 2408, Loss: {'train/loss': 0.21846260130405426, 'train/grad_norm_pre_clip': 3.7630393505096436, 'timing/data': 0.00017539411783218384, 'timing/model': 0.46655239211395383, 'learning_rate/action_model': 5.4773109659998786e-05, 'learning_rate/action_query_proj': 5.4773109659998786e-05, 'learning_rate/base': 1.3693277414999697e-05, 'epoch': 0.29}) +[2026-07-26 23:06:48,183][starVLA.training.train_starvla][INFO] - Step 2409, Loss: {'train/loss': 0.17031875252723694, 'train/grad_norm_pre_clip': 3.7380192279815674, 'timing/data': 0.00018488988280296326, 'timing/model': 0.4586566761136055, 'learning_rate/action_model': 5.4743000199014505e-05, 'learning_rate/action_query_proj': 5.4743000199014505e-05, 'learning_rate/base': 1.3685750049753626e-05, 'epoch': 0.29}) +[2026-07-26 23:06:53,787][starVLA.training.train_starvla][INFO] - Step 2410, Loss: {'train/loss': 0.28591978549957275, 'train/grad_norm_pre_clip': 4.797059059143066, 'timing/data': 0.00017410004511475563, 'timing/model': 0.4586173971183598, 'learning_rate/action_model': 5.471288965513719e-05, 'learning_rate/action_query_proj': 5.471288965513719e-05, 'learning_rate/base': 1.3678222413784298e-05, 'epoch': 0.29}) +[2026-07-26 23:06:59,378][starVLA.training.train_starvla][INFO] - Step 2411, Loss: {'train/loss': 0.22123068571090698, 'train/grad_norm_pre_clip': 4.010922431945801, 'timing/data': 0.00017668120563030243, 'timing/model': 0.4580300711095333, 'learning_rate/action_model': 5.468277804025398e-05, 'learning_rate/action_query_proj': 5.468277804025398e-05, 'learning_rate/base': 1.3670694510063494e-05, 'epoch': 0.29}) +[2026-07-26 23:07:05,201][starVLA.training.train_starvla][INFO] - Step 2412, Loss: {'train/loss': 0.2285294532775879, 'train/grad_norm_pre_clip': 3.381662130355835, 'timing/data': 0.00017350073903799057, 'timing/model': 0.45914873760193586, 'learning_rate/action_model': 5.465266536625251e-05, 'learning_rate/action_query_proj': 5.465266536625251e-05, 'learning_rate/base': 1.3663166341563127e-05, 'epoch': 0.29}) +[2026-07-26 23:07:10,909][starVLA.training.train_starvla][INFO] - Step 2413, Loss: {'train/loss': 0.2851531207561493, 'train/grad_norm_pre_clip': 3.3231394290924072, 'timing/data': 0.0001733396202325821, 'timing/model': 0.6325722080655396, 'learning_rate/action_model': 5.462255164502076e-05, 'learning_rate/action_query_proj': 5.462255164502076e-05, 'learning_rate/base': 1.365563791125519e-05, 'epoch': 0.29}) +[2026-07-26 23:07:16,454][starVLA.training.train_starvla][INFO] - Step 2414, Loss: {'train/loss': 0.22485090792179108, 'train/grad_norm_pre_clip': 3.068135976791382, 'timing/data': 0.0001775813288986683, 'timing/model': 0.47151435213163495, 'learning_rate/action_model': 5.459243688844714e-05, 'learning_rate/action_query_proj': 5.459243688844714e-05, 'learning_rate/base': 1.3648109222111785e-05, 'epoch': 0.29}) +[2026-07-26 23:07:21,986][starVLA.training.train_starvla][INFO] - Step 2415, Loss: {'train/loss': 0.2088489830493927, 'train/grad_norm_pre_clip': 4.035843849182129, 'timing/data': 0.000193761195987463, 'timing/model': 0.4713878696784377, 'learning_rate/action_model': 5.456232110842051e-05, 'learning_rate/action_query_proj': 5.456232110842051e-05, 'learning_rate/base': 1.3640580277105128e-05, 'epoch': 0.29}) +[2026-07-27 02:54:14,247][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 02:54:14,248][starVLA.model.framework.share_tools][INFO] - [*] [apply_config_compat] normalised config from version_id=0.21 to '0.21' +[2026-07-27 02:54:14,248][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 02:54:14,251][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 02:54:14,251][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 02:54:14,347][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 02:54:14,350][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 02:54:14,379][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 02:54:14,380][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 02:54:14,382][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 02:54:14,383][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 02:54:14,388][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 02:54:14,391][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 02:54:14,413][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 02:54:14,417][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 02:54:14,435][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 02:54:14,499][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 02:54:15,324][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 02:54:15,340][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 02:54:15,377][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 02:54:15,387][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 02:54:15,393][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 02:54:15,403][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 02:54:15,437][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 02:54:15,453][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 02:54:15,460][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 02:54:15,462][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 02:54:15,476][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 02:54:15,478][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 02:54:15,501][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 02:54:15,523][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 02:54:15,796][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 02:54:15,813][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 02:54:18,557][starVLA.model.modules.world_model.Wan2][INFO] - [*] Loading Wan2.2-TI2V from /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers +[2026-07-27 02:56:16,095][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 02:56:16,269][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 02:56:16,271][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 02:56:16,271][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 02:56:16,271][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 02:56:16,271][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 02:56:16,272][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 02:56:16,276][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 02:56:19,014][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 02:56:19,014][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 02:56:19,014][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 02:56:19,014][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 02:56:19,014][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 02:56:19,014][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 02:56:19,014][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 02:56:19,016][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 02:56:19,018][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 02:56:19,018][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 02:56:19,018][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 02:56:19,018][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 02:56:19,019][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 02:56:19,020][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 02:56:19,020][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 02:56:19,020][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 02:56:19,020][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 02:56:19,020][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 02:56:19,021][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,023][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 02:56:19,025][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 02:56:19,028][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 02:56:19,030][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 02:56:19,032][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 02:56:19,032][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 02:56:19,032][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 02:56:19,032][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 02:56:19,032][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 02:56:19,032][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 02:56:19,032][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 02:56:19,032][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 02:56:19,032][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 02:56:19,032][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 02:56:19,033][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 02:56:19,033][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 02:56:19,033][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 02:56:19,033][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 02:56:19,033][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 02:56:19,033][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 02:56:19,033][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 02:56:19,033][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 02:56:19,033][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 02:56:19,033][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 02:56:19,033][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 02:56:19,035][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,037][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 02:56:19,042][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 02:56:19,043][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 02:56:19,043][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 02:56:19,043][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 02:56:19,044][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 02:56:19,044][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 02:56:19,044][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 02:56:19,044][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 02:56:19,044][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 02:56:19,044][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 02:56:19,045][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,045][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 02:56:19,045][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 02:56:19,046][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 02:56:19,046][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 02:56:19,046][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 02:56:19,047][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 02:56:19,047][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 02:56:19,047][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 02:56:19,047][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 02:56:19,047][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 02:56:19,047][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 02:56:19,048][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 02:56:19,048][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 02:56:19,048][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 02:56:19,049][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 02:56:19,049][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 02:56:19,049][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 02:56:19,050][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,050][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 02:56:19,050][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 02:56:27,025][starVLA.dataloader][INFO] - Created train VLA dataloader with num_workers=8, persistent_workers=True, cpu_only_workers=True +[2026-07-27 02:56:27,065][starVLA.training.train_starvla][INFO] - LR Group action_model: lr=0.0001, num_params=16 +[2026-07-27 02:56:27,066][starVLA.training.train_starvla][INFO] - LR Group action_query_proj: lr=0.0001, num_params=2 +[2026-07-27 02:56:27,066][starVLA.training.train_starvla][INFO] - LR Group base: lr=2.5e-05, num_params=1263 +[2026-07-27 02:56:27,085][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state, steps: 2000 +[2026-07-27 02:56:27,085][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state, steps: 2000 +[2026-07-27 02:56:27,085][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state, steps: 2000 +[2026-07-27 02:56:27,085][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state, steps: 2000 +[2026-07-27 02:56:27,085][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state, steps: 2000 +[2026-07-27 02:56:27,085][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state, steps: 2000 +[2026-07-27 02:56:27,087][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state, steps: 2000 +[2026-07-27 02:56:27,097][starVLA.training.train_starvla][INFO] - 📝 Full config saved at /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/config.full.yaml +[2026-07-27 02:56:27,108][starVLA.training.train_starvla][INFO] - 📊 Accessed config snapshot saved at /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/config.yaml +[2026-07-27 02:56:27,109][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state, steps: 2000 +[2026-07-27 02:57:26,901][accelerate.accelerator][INFO] - Loading states from /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state +[2026-07-27 02:57:26,901][accelerate.accelerator][INFO] - Loading DeepSpeed Model and Optimizer +[2026-07-27 02:58:11,365][accelerate.accelerator][INFO] - DeepSpeed Model and Optimizer loaded from input dir /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2000_state/pytorch_model +[2026-07-27 02:58:11,365][accelerate.checkpointing][INFO] - All model weights loaded successfully +[2026-07-27 02:58:11,365][accelerate.checkpointing][INFO] - All optimizer states loaded successfully +[2026-07-27 02:58:11,366][accelerate.checkpointing][INFO] - All scheduler states loaded successfully +[2026-07-27 02:58:11,366][accelerate.checkpointing][INFO] - All dataloader sampler states loaded successfully +[2026-07-27 02:58:11,370][accelerate.checkpointing][INFO] - All random states loaded successfully +[2026-07-27 02:58:11,371][accelerate.accelerator][INFO] - Loading in 0 custom states +[2026-07-27 02:58:14,596][starVLA.training.train_starvla][INFO] - ***** Training Configuration ***** +[2026-07-27 02:58:14,596][starVLA.training.train_starvla][INFO] - Total optimization steps = 5000 +[2026-07-27 02:58:14,597][starVLA.training.train_starvla][INFO] - Per device batch size = 1 +[2026-07-27 02:58:14,597][starVLA.training.train_starvla][INFO] - Gradient accumulation steps = 16 +[2026-07-27 02:58:14,597][starVLA.training.train_starvla][INFO] - Total batch size = 128 +[2026-07-27 02:59:31,996][starVLA.training.train_starvla][INFO] - Step 2001, Loss: {'train/loss': 0.30492424964904785, 'train/grad_norm_pre_clip': 4.530391216278076, 'timing/data': 0.00025221100077033043, 'timing/model': 1.1579434629529715, 'learning_rate/action_model': 9.999999052518008e-05, 'learning_rate/action_query_proj': 9.999999052518008e-05, 'learning_rate/base': 2.499999763129502e-05, 'epoch': 0.24}) +[2026-07-27 02:59:37,700][starVLA.training.train_starvla][INFO] - Step 2002, Loss: {'train/loss': 0.2718087434768677, 'train/grad_norm_pre_clip': 4.753889560699463, 'timing/data': 0.00019133929163217545, 'timing/model': 0.4713647896423936, 'learning_rate/action_model': 9.99999621007241e-05, 'learning_rate/action_query_proj': 9.99999621007241e-05, 'learning_rate/base': 2.4999990525181024e-05, 'epoch': 0.24}) +[2026-07-27 02:59:43,388][starVLA.training.train_starvla][INFO] - Step 2003, Loss: {'train/loss': 0.19344207644462585, 'train/grad_norm_pre_clip': 3.6515846252441406, 'timing/data': 0.0003075692802667618, 'timing/model': 0.46777754509821534, 'learning_rate/action_model': 9.999991472664323e-05, 'learning_rate/action_query_proj': 9.999991472664323e-05, 'learning_rate/base': 2.4999978681660807e-05, 'epoch': 0.24}) +[2026-07-27 02:59:49,104][starVLA.training.train_starvla][INFO] - Step 2004, Loss: {'train/loss': 0.31530097126960754, 'train/grad_norm_pre_clip': 3.610041379928589, 'timing/data': 0.00039263488724827766, 'timing/model': 0.46310587879270315, 'learning_rate/action_model': 9.99998484029562e-05, 'learning_rate/action_query_proj': 9.99998484029562e-05, 'learning_rate/base': 2.499996210073905e-05, 'epoch': 0.24}) +[2026-07-27 02:59:54,811][starVLA.training.train_starvla][INFO] - Step 2005, Loss: {'train/loss': 0.2392587661743164, 'train/grad_norm_pre_clip': 3.033553123474121, 'timing/data': 0.0002846112474799156, 'timing/model': 0.4644236979074776, 'learning_rate/action_model': 9.99997631296892e-05, 'learning_rate/action_query_proj': 9.99997631296892e-05, 'learning_rate/base': 2.49999407824223e-05, 'epoch': 0.24}) +[2026-07-27 03:00:00,536][starVLA.training.train_starvla][INFO] - Step 2006, Loss: {'train/loss': 0.37332436442375183, 'train/grad_norm_pre_clip': 3.5844953060150146, 'timing/data': 0.0002830773591995239, 'timing/model': 0.4700932432897389, 'learning_rate/action_model': 9.999965890687587e-05, 'learning_rate/action_query_proj': 9.999965890687587e-05, 'learning_rate/base': 2.4999914726718967e-05, 'epoch': 0.24}) +[2026-07-27 03:00:06,248][starVLA.training.train_starvla][INFO] - Step 2007, Loss: {'train/loss': 0.22804097831249237, 'train/grad_norm_pre_clip': 4.601352691650391, 'timing/data': 0.0002171131782233715, 'timing/model': 0.47331053111702204, 'learning_rate/action_model': 9.999953573455739e-05, 'learning_rate/action_query_proj': 9.999953573455739e-05, 'learning_rate/base': 2.4999883933639347e-05, 'epoch': 0.24}) +[2026-07-27 03:00:12,250][starVLA.training.train_starvla][INFO] - Step 2008, Loss: {'train/loss': 0.36512264609336853, 'train/grad_norm_pre_clip': 5.051891803741455, 'timing/data': 0.0002805553376674652, 'timing/model': 0.46700935903936625, 'learning_rate/action_model': 9.999939361278237e-05, 'learning_rate/action_query_proj': 9.999939361278237e-05, 'learning_rate/base': 2.4999848403195593e-05, 'epoch': 0.24}) +[2026-07-27 03:00:18,051][starVLA.training.train_starvla][INFO] - Step 2009, Loss: {'train/loss': 0.20775948464870453, 'train/grad_norm_pre_clip': 3.343083620071411, 'timing/data': 0.0002778470516204834, 'timing/model': 0.668667078949511, 'learning_rate/action_model': 9.999923254160689e-05, 'learning_rate/action_query_proj': 9.999923254160689e-05, 'learning_rate/base': 2.4999808135401723e-05, 'epoch': 0.24}) +[2026-07-27 03:00:24,240][starVLA.training.train_starvla][INFO] - Step 2010, Loss: {'train/loss': 0.28345298767089844, 'train/grad_norm_pre_clip': 3.197277545928955, 'timing/data': 0.0002210470847785473, 'timing/model': 1.03821704024449, 'learning_rate/action_model': 9.999905252109459e-05, 'learning_rate/action_query_proj': 9.999905252109459e-05, 'learning_rate/base': 2.4999763130273646e-05, 'epoch': 0.24}) +[2026-07-27 03:00:29,875][starVLA.training.train_starvla][INFO] - Step 2011, Loss: {'train/loss': 0.3221764862537384, 'train/grad_norm_pre_clip': 4.329913139343262, 'timing/data': 0.0002810000441968441, 'timing/model': 0.4675499969162047, 'learning_rate/action_model': 9.99988535513165e-05, 'learning_rate/action_query_proj': 9.99988535513165e-05, 'learning_rate/base': 2.4999713387829125e-05, 'epoch': 0.24}) +[2026-07-27 03:00:35,481][starVLA.training.train_starvla][INFO] - Step 2012, Loss: {'train/loss': 0.2473716139793396, 'train/grad_norm_pre_clip': 4.155468940734863, 'timing/data': 0.0002636881545186043, 'timing/model': 0.4685832392424345, 'learning_rate/action_model': 9.999863563235118e-05, 'learning_rate/action_query_proj': 9.999863563235118e-05, 'learning_rate/base': 2.4999658908087796e-05, 'epoch': 0.24}) +[2026-07-27 03:00:41,117][starVLA.training.train_starvla][INFO] - Step 2013, Loss: {'train/loss': 0.24096152186393738, 'train/grad_norm_pre_clip': 2.6964657306671143, 'timing/data': 0.00028193695470690727, 'timing/model': 0.4831263069063425, 'learning_rate/action_model': 9.999839876428467e-05, 'learning_rate/action_query_proj': 9.999839876428467e-05, 'learning_rate/base': 2.4999599691071167e-05, 'epoch': 0.24}) +[2026-07-27 03:00:46,715][starVLA.training.train_starvla][INFO] - Step 2014, Loss: {'train/loss': 0.17682139575481415, 'train/grad_norm_pre_clip': 4.355631351470947, 'timing/data': 0.00027387216687202454, 'timing/model': 0.4684271328151226, 'learning_rate/action_model': 9.999814294721048e-05, 'learning_rate/action_query_proj': 9.999814294721048e-05, 'learning_rate/base': 2.499953573680262e-05, 'epoch': 0.24}) +[2026-07-27 03:00:52,330][starVLA.training.train_starvla][INFO] - Step 2015, Loss: {'train/loss': 0.2790055274963379, 'train/grad_norm_pre_clip': 4.537757396697998, 'timing/data': 0.00026576220989227295, 'timing/model': 0.46522931614890695, 'learning_rate/action_model': 9.99978681812296e-05, 'learning_rate/action_query_proj': 9.99978681812296e-05, 'learning_rate/base': 2.49994670453074e-05, 'epoch': 0.24}) +[2026-07-27 03:00:57,951][starVLA.training.train_starvla][INFO] - Step 2016, Loss: {'train/loss': 0.25714558362960815, 'train/grad_norm_pre_clip': 3.2515344619750977, 'timing/data': 0.0002631363458931446, 'timing/model': 0.46866720682010055, 'learning_rate/action_model': 9.999757446645048e-05, 'learning_rate/action_query_proj': 9.999757446645048e-05, 'learning_rate/base': 2.499939361661262e-05, 'epoch': 0.24}) +[2026-07-27 03:01:03,566][starVLA.training.train_starvla][INFO] - Step 2017, Loss: {'train/loss': 0.2366626262664795, 'train/grad_norm_pre_clip': 3.4032816886901855, 'timing/data': 0.00027521513402462006, 'timing/model': 0.46948727825656533, 'learning_rate/action_model': 9.999726180298913e-05, 'learning_rate/action_query_proj': 9.999726180298913e-05, 'learning_rate/base': 2.4999315450747283e-05, 'epoch': 0.24}) +[2026-07-27 03:01:09,171][starVLA.training.train_starvla][INFO] - Step 2018, Loss: {'train/loss': 0.27587780356407166, 'train/grad_norm_pre_clip': 5.806060791015625, 'timing/data': 0.00028106430545449257, 'timing/model': 0.46393256494775414, 'learning_rate/action_model': 9.999693019096892e-05, 'learning_rate/action_query_proj': 9.999693019096892e-05, 'learning_rate/base': 2.499923254774223e-05, 'epoch': 0.24}) +[2026-07-27 03:01:14,777][starVLA.training.train_starvla][INFO] - Step 2019, Loss: {'train/loss': 0.20707224309444427, 'train/grad_norm_pre_clip': 4.4196553230285645, 'timing/data': 0.0002682306803762913, 'timing/model': 0.4656222560442984, 'learning_rate/action_model': 9.999657963052081e-05, 'learning_rate/action_query_proj': 9.999657963052081e-05, 'learning_rate/base': 2.4999144907630202e-05, 'epoch': 0.24}) +[2026-07-27 03:01:20,374][starVLA.training.train_starvla][INFO] - Step 2020, Loss: {'train/loss': 0.3089151680469513, 'train/grad_norm_pre_clip': 4.654731273651123, 'timing/data': 0.00026494497433304787, 'timing/model': 0.4616031884215772, 'learning_rate/action_model': 9.999621012178318e-05, 'learning_rate/action_query_proj': 9.999621012178318e-05, 'learning_rate/base': 2.4999052530445796e-05, 'epoch': 0.25}) +[2026-07-27 03:01:26,030][starVLA.training.train_starvla][INFO] - Step 2021, Loss: {'train/loss': 0.32768431305885315, 'train/grad_norm_pre_clip': 4.370153427124023, 'timing/data': 0.0002788160927593708, 'timing/model': 0.4694507601670921, 'learning_rate/action_model': 9.999582166490191e-05, 'learning_rate/action_query_proj': 9.999582166490191e-05, 'learning_rate/base': 2.4998955416225478e-05, 'epoch': 0.25}) +[2026-07-27 03:01:31,631][starVLA.training.train_starvla][INFO] - Step 2022, Loss: {'train/loss': 0.32122349739074707, 'train/grad_norm_pre_clip': 4.243355751037598, 'timing/data': 0.00027268799021840096, 'timing/model': 0.46353359101340175, 'learning_rate/action_model': 9.999541426003034e-05, 'learning_rate/action_query_proj': 9.999541426003034e-05, 'learning_rate/base': 2.4998853565007585e-05, 'epoch': 0.25}) +[2026-07-27 03:01:37,198][starVLA.training.train_starvla][INFO] - Step 2023, Loss: {'train/loss': 0.3680116534233093, 'train/grad_norm_pre_clip': 3.5059103965759277, 'timing/data': 0.000196726992726326, 'timing/model': 0.4667869289405644, 'learning_rate/action_model': 9.999498790732934e-05, 'learning_rate/action_query_proj': 9.999498790732934e-05, 'learning_rate/base': 2.4998746976832335e-05, 'epoch': 0.25}) +[2026-07-27 03:01:42,782][starVLA.training.train_starvla][INFO] - Step 2024, Loss: {'train/loss': 0.2579055428504944, 'train/grad_norm_pre_clip': 3.2332842350006104, 'timing/data': 0.0002023722045123577, 'timing/model': 0.46533246291801333, 'learning_rate/action_model': 9.999454260696719e-05, 'learning_rate/action_query_proj': 9.999454260696719e-05, 'learning_rate/base': 2.4998635651741797e-05, 'epoch': 0.25}) +[2026-07-27 03:01:48,410][starVLA.training.train_starvla][INFO] - Step 2025, Loss: {'train/loss': 0.22752505540847778, 'train/grad_norm_pre_clip': 3.8822202682495117, 'timing/data': 0.00035975873470306396, 'timing/model': 0.4680205970071256, 'learning_rate/action_model': 9.999407835911971e-05, 'learning_rate/action_query_proj': 9.999407835911971e-05, 'learning_rate/base': 2.4998519589779927e-05, 'epoch': 0.25}) +[2026-07-27 03:01:54,008][starVLA.training.train_starvla][INFO] - Step 2026, Loss: {'train/loss': 0.3448287546634674, 'train/grad_norm_pre_clip': 4.28146505355835, 'timing/data': 0.000306909903883934, 'timing/model': 0.4677054900676012, 'learning_rate/action_model': 9.999359516397018e-05, 'learning_rate/action_query_proj': 9.999359516397018e-05, 'learning_rate/base': 2.4998398790992545e-05, 'epoch': 0.25}) +[2026-07-27 03:01:59,625][starVLA.training.train_starvla][INFO] - Step 2027, Loss: {'train/loss': 0.23657894134521484, 'train/grad_norm_pre_clip': 2.7763030529022217, 'timing/data': 0.000269297044724226, 'timing/model': 0.4656338570639491, 'learning_rate/action_model': 9.999309302170934e-05, 'learning_rate/action_query_proj': 9.999309302170934e-05, 'learning_rate/base': 2.4998273255427336e-05, 'epoch': 0.25}) +[2026-07-27 03:02:05,236][starVLA.training.train_starvla][INFO] - Step 2028, Loss: {'train/loss': 0.2990310490131378, 'train/grad_norm_pre_clip': 4.608770847320557, 'timing/data': 0.00025609880685806274, 'timing/model': 0.4681827798485756, 'learning_rate/action_model': 9.999257193253546e-05, 'learning_rate/action_query_proj': 9.999257193253546e-05, 'learning_rate/base': 2.4998142983133864e-05, 'epoch': 0.25}) +[2026-07-27 03:02:10,848][starVLA.training.train_starvla][INFO] - Step 2029, Loss: {'train/loss': 0.23621466755867004, 'train/grad_norm_pre_clip': 3.5739901065826416, 'timing/data': 0.0002655657008290291, 'timing/model': 0.4673802242614329, 'learning_rate/action_model': 9.999203189665421e-05, 'learning_rate/action_query_proj': 9.999203189665421e-05, 'learning_rate/base': 2.4998007974163552e-05, 'epoch': 0.25}) +[2026-07-27 03:02:16,482][starVLA.training.train_starvla][INFO] - Step 2030, Loss: {'train/loss': 0.18883489072322845, 'train/grad_norm_pre_clip': 2.863689661026001, 'timing/data': 0.0002724486403167248, 'timing/model': 0.46717455703765154, 'learning_rate/action_model': 9.999147291427884e-05, 'learning_rate/action_query_proj': 9.999147291427884e-05, 'learning_rate/base': 2.499786822856971e-05, 'epoch': 0.25}) +[2026-07-27 03:02:22,094][starVLA.training.train_starvla][INFO] - Step 2031, Loss: {'train/loss': 0.3739858865737915, 'train/grad_norm_pre_clip': 4.6118011474609375, 'timing/data': 0.0002702060155570507, 'timing/model': 0.46849059872329235, 'learning_rate/action_model': 9.999089498562998e-05, 'learning_rate/action_query_proj': 9.999089498562998e-05, 'learning_rate/base': 2.4997723746407496e-05, 'epoch': 0.25}) +[2026-07-27 03:02:27,688][starVLA.training.train_starvla][INFO] - Step 2032, Loss: {'train/loss': 0.2273687720298767, 'train/grad_norm_pre_clip': 2.8902220726013184, 'timing/data': 0.0002586459740996361, 'timing/model': 0.46362554421648383, 'learning_rate/action_model': 9.999029811093582e-05, 'learning_rate/action_query_proj': 9.999029811093582e-05, 'learning_rate/base': 2.4997574527733956e-05, 'epoch': 0.25}) +[2026-07-27 03:02:33,307][starVLA.training.train_starvla][INFO] - Step 2033, Loss: {'train/loss': 0.30290037393569946, 'train/grad_norm_pre_clip': 4.192659378051758, 'timing/data': 0.0002642842009663582, 'timing/model': 0.4662059540860355, 'learning_rate/action_model': 9.998968229043199e-05, 'learning_rate/action_query_proj': 9.998968229043199e-05, 'learning_rate/base': 2.4997420572607998e-05, 'epoch': 0.25}) +[2026-07-27 03:02:39,012][starVLA.training.train_starvla][INFO] - Step 2034, Loss: {'train/loss': 0.2277963012456894, 'train/grad_norm_pre_clip': 3.554258108139038, 'timing/data': 0.0002612052485346794, 'timing/model': 0.4825506270863116, 'learning_rate/action_model': 9.99890475243616e-05, 'learning_rate/action_query_proj': 9.99890475243616e-05, 'learning_rate/base': 2.49972618810904e-05, 'epoch': 0.25}) +[2026-07-27 03:02:44,636][starVLA.training.train_starvla][INFO] - Step 2035, Loss: {'train/loss': 0.19976875185966492, 'train/grad_norm_pre_clip': 3.199070930480957, 'timing/data': 0.0002597537823021412, 'timing/model': 0.46895112562924623, 'learning_rate/action_model': 9.998839381297525e-05, 'learning_rate/action_query_proj': 9.998839381297525e-05, 'learning_rate/base': 2.4997098453243813e-05, 'epoch': 0.25}) +[2026-07-27 03:02:50,238][starVLA.training.train_starvla][INFO] - Step 2036, Loss: {'train/loss': 0.26735055446624756, 'train/grad_norm_pre_clip': 3.2548553943634033, 'timing/data': 0.00020663486793637276, 'timing/model': 0.47544795321300626, 'learning_rate/action_model': 9.998772115653099e-05, 'learning_rate/action_query_proj': 9.998772115653099e-05, 'learning_rate/base': 2.4996930289132748e-05, 'epoch': 0.25}) +[2026-07-27 03:02:55,829][starVLA.training.train_starvla][INFO] - Step 2037, Loss: {'train/loss': 0.2622382342815399, 'train/grad_norm_pre_clip': 4.681552410125732, 'timing/data': 0.00020558899268507957, 'timing/model': 0.4684530030936003, 'learning_rate/action_model': 9.998702955529441e-05, 'learning_rate/action_query_proj': 9.998702955529441e-05, 'learning_rate/base': 2.4996757388823603e-05, 'epoch': 0.25}) +[2026-07-27 03:03:01,425][starVLA.training.train_starvla][INFO] - Step 2038, Loss: {'train/loss': 0.3052414357662201, 'train/grad_norm_pre_clip': 3.40633225440979, 'timing/data': 0.00019443640485405922, 'timing/model': 0.473732179030776, 'learning_rate/action_model': 9.998631900953854e-05, 'learning_rate/action_query_proj': 9.998631900953854e-05, 'learning_rate/base': 2.4996579752384635e-05, 'epoch': 0.25}) +[2026-07-27 03:03:07,034][starVLA.training.train_starvla][INFO] - Step 2039, Loss: {'train/loss': 0.21358783543109894, 'train/grad_norm_pre_clip': 3.8886139392852783, 'timing/data': 0.00020041875541210175, 'timing/model': 0.474409612827003, 'learning_rate/action_model': 9.998558951954387e-05, 'learning_rate/action_query_proj': 9.998558951954387e-05, 'learning_rate/base': 2.4996397379885968e-05, 'epoch': 0.25}) +[2026-07-27 03:03:12,624][starVLA.training.train_starvla][INFO] - Step 2040, Loss: {'train/loss': 0.2677229046821594, 'train/grad_norm_pre_clip': 4.6182122230529785, 'timing/data': 0.0001985267736017704, 'timing/model': 0.46846170304343104, 'learning_rate/action_model': 9.99848410855984e-05, 'learning_rate/action_query_proj': 9.99848410855984e-05, 'learning_rate/base': 2.49962102713996e-05, 'epoch': 0.25}) +[2026-07-27 03:03:18,198][starVLA.training.train_starvla][INFO] - Step 2041, Loss: {'train/loss': 0.3402461111545563, 'train/grad_norm_pre_clip': 4.5700602531433105, 'timing/data': 0.00019954098388552666, 'timing/model': 0.4687960552982986, 'learning_rate/action_model': 9.99840737079976e-05, 'learning_rate/action_query_proj': 9.99840737079976e-05, 'learning_rate/base': 2.49960184269994e-05, 'epoch': 0.25}) +[2026-07-27 03:03:23,778][starVLA.training.train_starvla][INFO] - Step 2042, Loss: {'train/loss': 0.24368761479854584, 'train/grad_norm_pre_clip': 2.726195812225342, 'timing/data': 0.0001977812498807907, 'timing/model': 0.46668713772669435, 'learning_rate/action_model': 9.998328738704444e-05, 'learning_rate/action_query_proj': 9.998328738704444e-05, 'learning_rate/base': 2.499582184676111e-05, 'epoch': 0.25}) +[2026-07-27 03:03:29,358][starVLA.training.train_starvla][INFO] - Step 2043, Loss: {'train/loss': 0.4237922728061676, 'train/grad_norm_pre_clip': 3.6641876697540283, 'timing/data': 0.00019771791994571686, 'timing/model': 0.46807763492688537, 'learning_rate/action_model': 9.998248212304932e-05, 'learning_rate/action_query_proj': 9.998248212304932e-05, 'learning_rate/base': 2.499562053076233e-05, 'epoch': 0.25}) +[2026-07-27 03:03:34,949][starVLA.training.train_starvla][INFO] - Step 2044, Loss: {'train/loss': 0.2458878755569458, 'train/grad_norm_pre_clip': 3.574191093444824, 'timing/data': 0.00020951218903064728, 'timing/model': 0.4699824620038271, 'learning_rate/action_model': 9.998165791633016e-05, 'learning_rate/action_query_proj': 9.998165791633016e-05, 'learning_rate/base': 2.499541447908254e-05, 'epoch': 0.25}) +[2026-07-27 03:03:40,525][starVLA.training.train_starvla][INFO] - Step 2045, Loss: {'train/loss': 0.22175471484661102, 'train/grad_norm_pre_clip': 5.492667198181152, 'timing/data': 0.00020877690985798836, 'timing/model': 0.4690219610929489, 'learning_rate/action_model': 9.998081476721232e-05, 'learning_rate/action_query_proj': 9.998081476721232e-05, 'learning_rate/base': 2.499520369180308e-05, 'epoch': 0.25}) +[2026-07-27 03:03:46,106][starVLA.training.train_starvla][INFO] - Step 2046, Loss: {'train/loss': 0.2746722996234894, 'train/grad_norm_pre_clip': 4.0851149559021, 'timing/data': 0.00020787492394447327, 'timing/model': 0.4707118137739599, 'learning_rate/action_model': 9.997995267602868e-05, 'learning_rate/action_query_proj': 9.997995267602868e-05, 'learning_rate/base': 2.499498816900717e-05, 'epoch': 0.25}) +[2026-07-27 03:03:51,696][starVLA.training.train_starvla][INFO] - Step 2047, Loss: {'train/loss': 0.3630552589893341, 'train/grad_norm_pre_clip': 4.413190841674805, 'timing/data': 0.00019921595230698586, 'timing/model': 0.4686639402061701, 'learning_rate/action_model': 9.997907164311958e-05, 'learning_rate/action_query_proj': 9.997907164311958e-05, 'learning_rate/base': 2.4994767910779894e-05, 'epoch': 0.25}) +[2026-07-27 03:03:57,287][starVLA.training.train_starvla][INFO] - Step 2048, Loss: {'train/loss': 0.2447838932275772, 'train/grad_norm_pre_clip': 3.5497286319732666, 'timing/data': 0.0002517816610634327, 'timing/model': 0.46984513429924846, 'learning_rate/action_model': 9.997817166883286e-05, 'learning_rate/action_query_proj': 9.997817166883286e-05, 'learning_rate/base': 2.4994542917208215e-05, 'epoch': 0.25}) +[2026-07-27 03:04:02,902][starVLA.training.train_starvla][INFO] - Step 2049, Loss: {'train/loss': 0.356301486492157, 'train/grad_norm_pre_clip': 5.1537604331970215, 'timing/data': 0.00019603082910180092, 'timing/model': 0.46796579798683524, 'learning_rate/action_model': 9.997725275352378e-05, 'learning_rate/action_query_proj': 9.997725275352378e-05, 'learning_rate/base': 2.4994313188380945e-05, 'epoch': 0.25}) +[2026-07-27 03:04:08,527][starVLA.training.train_starvla][INFO] - Step 2050, Loss: {'train/loss': 0.3086010813713074, 'train/grad_norm_pre_clip': 4.144663333892822, 'timing/data': 0.00024166982620954514, 'timing/model': 0.46789388498291373, 'learning_rate/action_model': 9.997631489755513e-05, 'learning_rate/action_query_proj': 9.997631489755513e-05, 'learning_rate/base': 2.4994078724388782e-05, 'epoch': 0.25}) +[2026-07-27 03:04:14,175][starVLA.training.train_starvla][INFO] - Step 2051, Loss: {'train/loss': 0.27447161078453064, 'train/grad_norm_pre_clip': 3.715524435043335, 'timing/data': 0.00020112795755267143, 'timing/model': 0.4728397261351347, 'learning_rate/action_model': 9.997535810129714e-05, 'learning_rate/action_query_proj': 9.997535810129714e-05, 'learning_rate/base': 2.4993839525324285e-05, 'epoch': 0.25}) +[2026-07-27 03:04:19,760][starVLA.training.train_starvla][INFO] - Step 2052, Loss: {'train/loss': 0.22153542935848236, 'train/grad_norm_pre_clip': 3.088841438293457, 'timing/data': 0.00019689509645104408, 'timing/model': 0.468830653000623, 'learning_rate/action_model': 9.997438236512756e-05, 'learning_rate/action_query_proj': 9.997438236512756e-05, 'learning_rate/base': 2.499359559128189e-05, 'epoch': 0.25}) +[2026-07-27 03:04:25,353][starVLA.training.train_starvla][INFO] - Step 2053, Loss: {'train/loss': 0.2816239595413208, 'train/grad_norm_pre_clip': 3.0932350158691406, 'timing/data': 0.00030683819204568863, 'timing/model': 0.4637121590785682, 'learning_rate/action_model': 9.99733876894316e-05, 'learning_rate/action_query_proj': 9.99733876894316e-05, 'learning_rate/base': 2.49933469223579e-05, 'epoch': 0.25}) +[2026-07-27 03:04:30,949][starVLA.training.train_starvla][INFO] - Step 2054, Loss: {'train/loss': 0.3453499376773834, 'train/grad_norm_pre_clip': 4.4790143966674805, 'timing/data': 0.00019796518608927727, 'timing/model': 0.46123427618294954, 'learning_rate/action_model': 9.997237407460191e-05, 'learning_rate/action_query_proj': 9.997237407460191e-05, 'learning_rate/base': 2.4993093518650478e-05, 'epoch': 0.25}) +[2026-07-27 03:04:36,543][starVLA.training.train_starvla][INFO] - Step 2055, Loss: {'train/loss': 0.207271546125412, 'train/grad_norm_pre_clip': 3.144592761993408, 'timing/data': 0.00019851373508572578, 'timing/model': 0.4595073889940977, 'learning_rate/action_model': 9.997134152103871e-05, 'learning_rate/action_query_proj': 9.997134152103871e-05, 'learning_rate/base': 2.4992835380259678e-05, 'epoch': 0.25}) +[2026-07-27 03:04:42,153][starVLA.training.train_starvla][INFO] - Step 2056, Loss: {'train/loss': 0.43569278717041016, 'train/grad_norm_pre_clip': 5.574852466583252, 'timing/data': 0.0001974431797862053, 'timing/model': 0.46325422916561365, 'learning_rate/action_model': 9.997029002914957e-05, 'learning_rate/action_query_proj': 9.997029002914957e-05, 'learning_rate/base': 2.4992572507287394e-05, 'epoch': 0.25}) +[2026-07-27 03:04:47,714][starVLA.training.train_starvla][INFO] - Step 2057, Loss: {'train/loss': 0.3488563895225525, 'train/grad_norm_pre_clip': 5.205839157104492, 'timing/data': 0.0001949341967701912, 'timing/model': 0.4636557758785784, 'learning_rate/action_model': 9.996921959934963e-05, 'learning_rate/action_query_proj': 9.996921959934963e-05, 'learning_rate/base': 2.4992304899837407e-05, 'epoch': 0.25}) +[2026-07-27 03:04:53,294][starVLA.training.train_starvla][INFO] - Step 2058, Loss: {'train/loss': 0.40924617648124695, 'train/grad_norm_pre_clip': 4.090874671936035, 'timing/data': 0.00019722199067473412, 'timing/model': 0.4625067999586463, 'learning_rate/action_model': 9.996813023206148e-05, 'learning_rate/action_query_proj': 9.996813023206148e-05, 'learning_rate/base': 2.499203255801537e-05, 'epoch': 0.25}) +[2026-07-27 03:04:58,869][starVLA.training.train_starvla][INFO] - Step 2059, Loss: {'train/loss': 0.21637600660324097, 'train/grad_norm_pre_clip': 3.3024611473083496, 'timing/data': 0.0001899171620607376, 'timing/model': 0.46206832537427545, 'learning_rate/action_model': 9.996702192771519e-05, 'learning_rate/action_query_proj': 9.996702192771519e-05, 'learning_rate/base': 2.4991755481928798e-05, 'epoch': 0.25}) +[2026-07-27 03:05:04,457][starVLA.training.train_starvla][INFO] - Step 2060, Loss: {'train/loss': 0.16632167994976044, 'train/grad_norm_pre_clip': 3.927302837371826, 'timing/data': 0.0001894719898700714, 'timing/model': 0.46306442003697157, 'learning_rate/action_model': 9.996589468674828e-05, 'learning_rate/action_query_proj': 9.996589468674828e-05, 'learning_rate/base': 2.499147367168707e-05, 'epoch': 0.25}) +[2026-07-27 03:05:10,048][starVLA.training.train_starvla][INFO] - Step 2061, Loss: {'train/loss': 0.27404698729515076, 'train/grad_norm_pre_clip': 3.4844446182250977, 'timing/data': 0.0001975339837372303, 'timing/model': 0.463816633913666, 'learning_rate/action_model': 9.99647485096058e-05, 'learning_rate/action_query_proj': 9.99647485096058e-05, 'learning_rate/base': 2.499118712740145e-05, 'epoch': 0.25}) +[2026-07-27 03:05:15,645][starVLA.training.train_starvla][INFO] - Step 2062, Loss: {'train/loss': 0.2970985770225525, 'train/grad_norm_pre_clip': 3.8529460430145264, 'timing/data': 0.00019229203462600708, 'timing/model': 0.4669628441333771, 'learning_rate/action_model': 9.996358339674021e-05, 'learning_rate/action_query_proj': 9.996358339674021e-05, 'learning_rate/base': 2.4990895849185053e-05, 'epoch': 0.25}) +[2026-07-27 03:05:21,241][starVLA.training.train_starvla][INFO] - Step 2063, Loss: {'train/loss': 0.2687875032424927, 'train/grad_norm_pre_clip': 5.007481098175049, 'timing/data': 0.0002034660428762436, 'timing/model': 0.46628356957808137, 'learning_rate/action_model': 9.99623993486115e-05, 'learning_rate/action_query_proj': 9.99623993486115e-05, 'learning_rate/base': 2.4990599837152875e-05, 'epoch': 0.25}) +[2026-07-27 03:05:26,812][starVLA.training.train_starvla][INFO] - Step 2064, Loss: {'train/loss': 0.2948267161846161, 'train/grad_norm_pre_clip': 4.167128086090088, 'timing/data': 0.00020202621817588806, 'timing/model': 0.4623871520161629, 'learning_rate/action_model': 9.99611963656871e-05, 'learning_rate/action_query_proj': 9.99611963656871e-05, 'learning_rate/base': 2.4990299091421775e-05, 'epoch': 0.25}) +[2026-07-27 03:05:32,367][starVLA.training.train_starvla][INFO] - Step 2065, Loss: {'train/loss': 0.3461796045303345, 'train/grad_norm_pre_clip': 5.872561454772949, 'timing/data': 0.00019487738609313965, 'timing/model': 0.46098286006599665, 'learning_rate/action_model': 9.995997444844192e-05, 'learning_rate/action_query_proj': 9.995997444844192e-05, 'learning_rate/base': 2.498999361211048e-05, 'epoch': 0.25}) +[2026-07-27 03:05:37,955][starVLA.training.train_starvla][INFO] - Step 2066, Loss: {'train/loss': 0.37768417596817017, 'train/grad_norm_pre_clip': 5.296987533569336, 'timing/data': 0.0001896698959171772, 'timing/model': 0.46208438323810697, 'learning_rate/action_model': 9.995873359735839e-05, 'learning_rate/action_query_proj': 9.995873359735839e-05, 'learning_rate/base': 2.4989683399339598e-05, 'epoch': 0.25}) +[2026-07-27 03:05:43,557][starVLA.training.train_starvla][INFO] - Step 2067, Loss: {'train/loss': 0.24982509016990662, 'train/grad_norm_pre_clip': 3.1058430671691895, 'timing/data': 0.00018571782857179642, 'timing/model': 0.466948748100549, 'learning_rate/action_model': 9.995747381292634e-05, 'learning_rate/action_query_proj': 9.995747381292634e-05, 'learning_rate/base': 2.4989368453231586e-05, 'epoch': 0.25}) +[2026-07-27 03:05:49,150][starVLA.training.train_starvla][INFO] - Step 2068, Loss: {'train/loss': 0.21082594990730286, 'train/grad_norm_pre_clip': 3.284000873565674, 'timing/data': 0.00018977699801325798, 'timing/model': 0.46086919819936156, 'learning_rate/action_model': 9.995619509564315e-05, 'learning_rate/action_query_proj': 9.995619509564315e-05, 'learning_rate/base': 2.4989048773910787e-05, 'epoch': 0.25}) +[2026-07-27 03:05:54,757][starVLA.training.train_starvla][INFO] - Step 2069, Loss: {'train/loss': 0.25893688201904297, 'train/grad_norm_pre_clip': 2.652263879776001, 'timing/data': 0.0001900061033666134, 'timing/model': 0.46147884195670485, 'learning_rate/action_model': 9.995489744601361e-05, 'learning_rate/action_query_proj': 9.995489744601361e-05, 'learning_rate/base': 2.4988724361503402e-05, 'epoch': 0.25}) +[2026-07-27 03:06:00,353][starVLA.training.train_starvla][INFO] - Step 2070, Loss: {'train/loss': 0.27146419882774353, 'train/grad_norm_pre_clip': 4.163395881652832, 'timing/data': 0.00018616020679473877, 'timing/model': 0.46646779030561447, 'learning_rate/action_model': 9.995358086455e-05, 'learning_rate/action_query_proj': 9.995358086455e-05, 'learning_rate/base': 2.49883952161375e-05, 'epoch': 0.25}) +[2026-07-27 03:06:05,932][starVLA.training.train_starvla][INFO] - Step 2071, Loss: {'train/loss': 0.19225578010082245, 'train/grad_norm_pre_clip': 3.4085254669189453, 'timing/data': 0.0001972327008843422, 'timing/model': 0.4636666919104755, 'learning_rate/action_model': 9.99522453517721e-05, 'learning_rate/action_query_proj': 9.99522453517721e-05, 'learning_rate/base': 2.4988061337943024e-05, 'epoch': 0.25}) +[2026-07-27 03:06:11,498][starVLA.training.train_starvla][INFO] - Step 2072, Loss: {'train/loss': 0.2128138542175293, 'train/grad_norm_pre_clip': 3.395841121673584, 'timing/data': 0.0001864028163254261, 'timing/model': 0.46656494215130806, 'learning_rate/action_model': 9.995089090820716e-05, 'learning_rate/action_query_proj': 9.995089090820716e-05, 'learning_rate/base': 2.498772272705179e-05, 'epoch': 0.25}) +[2026-07-27 03:06:17,045][starVLA.training.train_starvla][INFO] - Step 2073, Loss: {'train/loss': 0.36951008439064026, 'train/grad_norm_pre_clip': 5.729607105255127, 'timing/data': 0.00018594739958643913, 'timing/model': 0.4654520498588681, 'learning_rate/action_model': 9.99495175343899e-05, 'learning_rate/action_query_proj': 9.99495175343899e-05, 'learning_rate/base': 2.4987379383597474e-05, 'epoch': 0.25}) +[2026-07-27 03:06:22,602][starVLA.training.train_starvla][INFO] - Step 2074, Loss: {'train/loss': 0.22737643122673035, 'train/grad_norm_pre_clip': 4.608994483947754, 'timing/data': 0.00020443368703126907, 'timing/model': 0.463042045943439, 'learning_rate/action_model': 9.994812523086248e-05, 'learning_rate/action_query_proj': 9.994812523086248e-05, 'learning_rate/base': 2.498703130771562e-05, 'epoch': 0.25}) +[2026-07-27 03:06:28,216][starVLA.training.train_starvla][INFO] - Step 2075, Loss: {'train/loss': 0.31999048590660095, 'train/grad_norm_pre_clip': 5.1972975730896, 'timing/data': 0.00019197724759578705, 'timing/model': 0.4563202098943293, 'learning_rate/action_model': 9.994671399817457e-05, 'learning_rate/action_query_proj': 9.994671399817457e-05, 'learning_rate/base': 2.4986678499543643e-05, 'epoch': 0.25}) +[2026-07-27 03:06:33,795][starVLA.training.train_starvla][INFO] - Step 2076, Loss: {'train/loss': 0.2440374195575714, 'train/grad_norm_pre_clip': 4.138142108917236, 'timing/data': 0.00018802983686327934, 'timing/model': 0.46318119298666716, 'learning_rate/action_model': 9.994528383688328e-05, 'learning_rate/action_query_proj': 9.994528383688328e-05, 'learning_rate/base': 2.498632095922082e-05, 'epoch': 0.25}) +[2026-07-27 03:06:39,355][starVLA.training.train_starvla][INFO] - Step 2077, Loss: {'train/loss': 0.26307252049446106, 'train/grad_norm_pre_clip': 4.302169322967529, 'timing/data': 0.0001863599754869938, 'timing/model': 0.45620319806039333, 'learning_rate/action_model': 9.994383474755328e-05, 'learning_rate/action_query_proj': 9.994383474755328e-05, 'learning_rate/base': 2.498595868688832e-05, 'epoch': 0.25}) +[2026-07-27 03:06:44,935][starVLA.training.train_starvla][INFO] - Step 2078, Loss: {'train/loss': 0.2598411738872528, 'train/grad_norm_pre_clip': 4.456933498382568, 'timing/data': 0.00018579792231321335, 'timing/model': 0.4661600198596716, 'learning_rate/action_model': 9.994236673075659e-05, 'learning_rate/action_query_proj': 9.994236673075659e-05, 'learning_rate/base': 2.4985591682689147e-05, 'epoch': 0.25}) +[2026-07-27 03:06:50,519][starVLA.training.train_starvla][INFO] - Step 2079, Loss: {'train/loss': 0.29432228207588196, 'train/grad_norm_pre_clip': 5.341826915740967, 'timing/data': 0.00018675671890377998, 'timing/model': 0.4649866847321391, 'learning_rate/action_model': 9.994087978707277e-05, 'learning_rate/action_query_proj': 9.994087978707277e-05, 'learning_rate/base': 2.498521994676819e-05, 'epoch': 0.25}) +[2026-07-27 03:06:56,079][starVLA.training.train_starvla][INFO] - Step 2080, Loss: {'train/loss': 0.318938672542572, 'train/grad_norm_pre_clip': 5.369421482086182, 'timing/data': 0.00019001495093107224, 'timing/model': 0.45544051518663764, 'learning_rate/action_model': 9.993937391708885e-05, 'learning_rate/action_query_proj': 9.993937391708885e-05, 'learning_rate/base': 2.4984843479272213e-05, 'epoch': 0.25}) +[2026-07-27 03:07:01,661][starVLA.training.train_starvla][INFO] - Step 2081, Loss: {'train/loss': 0.2487647831439972, 'train/grad_norm_pre_clip': 3.7518198490142822, 'timing/data': 0.0001912708394229412, 'timing/model': 0.46558965230360627, 'learning_rate/action_model': 9.993784912139931e-05, 'learning_rate/action_query_proj': 9.993784912139931e-05, 'learning_rate/base': 2.4984462280349827e-05, 'epoch': 0.25}) +[2026-07-27 03:07:07,233][starVLA.training.train_starvla][INFO] - Step 2082, Loss: {'train/loss': 0.2578240931034088, 'train/grad_norm_pre_clip': 3.0643131732940674, 'timing/data': 0.00018484331667423248, 'timing/model': 0.4638523799367249, 'learning_rate/action_model': 9.993630540060613e-05, 'learning_rate/action_query_proj': 9.993630540060613e-05, 'learning_rate/base': 2.4984076350151533e-05, 'epoch': 0.25}) +[2026-07-27 03:07:12,820][starVLA.training.train_starvla][INFO] - Step 2083, Loss: {'train/loss': 0.4091237783432007, 'train/grad_norm_pre_clip': 4.644161224365234, 'timing/data': 0.00018839258700609207, 'timing/model': 0.46529987594112754, 'learning_rate/action_model': 9.993474275531877e-05, 'learning_rate/action_query_proj': 9.993474275531877e-05, 'learning_rate/base': 2.498368568882969e-05, 'epoch': 0.25}) +[2026-07-27 03:07:18,415][starVLA.training.train_starvla][INFO] - Step 2084, Loss: {'train/loss': 0.28829705715179443, 'train/grad_norm_pre_clip': 4.458441257476807, 'timing/data': 0.00018507987260818481, 'timing/model': 0.4627481191419065, 'learning_rate/action_model': 9.993316118615408e-05, 'learning_rate/action_query_proj': 9.993316118615408e-05, 'learning_rate/base': 2.498329029653852e-05, 'epoch': 0.25}) +[2026-07-27 03:07:24,019][starVLA.training.train_starvla][INFO] - Step 2085, Loss: {'train/loss': 0.18078108131885529, 'train/grad_norm_pre_clip': 2.9427545070648193, 'timing/data': 0.00020185671746730804, 'timing/model': 0.4660169151611626, 'learning_rate/action_model': 9.993156069373646e-05, 'learning_rate/action_query_proj': 9.993156069373646e-05, 'learning_rate/base': 2.4982890173434116e-05, 'epoch': 0.25}) +[2026-07-27 03:07:29,625][starVLA.training.train_starvla][INFO] - Step 2086, Loss: {'train/loss': 0.18273216485977173, 'train/grad_norm_pre_clip': 3.3675639629364014, 'timing/data': 0.00019403500482439995, 'timing/model': 0.4664616547524929, 'learning_rate/action_model': 9.992994127869779e-05, 'learning_rate/action_query_proj': 9.992994127869779e-05, 'learning_rate/base': 2.4982485319674448e-05, 'epoch': 0.25}) +[2026-07-27 03:07:35,207][starVLA.training.train_starvla][INFO] - Step 2087, Loss: {'train/loss': 0.21507662534713745, 'train/grad_norm_pre_clip': 3.8213257789611816, 'timing/data': 0.00019058678299188614, 'timing/model': 0.46116224583238363, 'learning_rate/action_model': 9.992830294167737e-05, 'learning_rate/action_query_proj': 9.992830294167737e-05, 'learning_rate/base': 2.4982075735419342e-05, 'epoch': 0.25}) +[2026-07-27 03:07:40,808][starVLA.training.train_starvla][INFO] - Step 2088, Loss: {'train/loss': 0.22124572098255157, 'train/grad_norm_pre_clip': 2.9516987800598145, 'timing/data': 0.00020042667165398598, 'timing/model': 0.4627164537087083, 'learning_rate/action_model': 9.992664568332197e-05, 'learning_rate/action_query_proj': 9.992664568332197e-05, 'learning_rate/base': 2.4981661420830493e-05, 'epoch': 0.25}) +[2026-07-27 03:07:46,422][starVLA.training.train_starvla][INFO] - Step 2089, Loss: {'train/loss': 0.2952151298522949, 'train/grad_norm_pre_clip': 3.5863261222839355, 'timing/data': 0.00019191531464457512, 'timing/model': 0.4659609040245414, 'learning_rate/action_model': 9.992496950428587e-05, 'learning_rate/action_query_proj': 9.992496950428587e-05, 'learning_rate/base': 2.4981242376071467e-05, 'epoch': 0.25}) +[2026-07-27 03:07:52,002][starVLA.training.train_starvla][INFO] - Step 2090, Loss: {'train/loss': 0.2800738513469696, 'train/grad_norm_pre_clip': 5.021015167236328, 'timing/data': 0.00018588081002235413, 'timing/model': 0.4566171448677778, 'learning_rate/action_model': 9.992327440523081e-05, 'learning_rate/action_query_proj': 9.992327440523081e-05, 'learning_rate/base': 2.4980818601307702e-05, 'epoch': 0.25}) +[2026-07-27 03:07:57,615][starVLA.training.train_starvla][INFO] - Step 2091, Loss: {'train/loss': 0.33074551820755005, 'train/grad_norm_pre_clip': 4.409263610839844, 'timing/data': 0.00024534203112125397, 'timing/model': 0.46557424683123827, 'learning_rate/action_model': 9.992156038682597e-05, 'learning_rate/action_query_proj': 9.992156038682597e-05, 'learning_rate/base': 2.4980390096706492e-05, 'epoch': 0.25}) +[2026-07-27 03:08:03,217][starVLA.training.train_starvla][INFO] - Step 2092, Loss: {'train/loss': 0.2710435092449188, 'train/grad_norm_pre_clip': 4.754846572875977, 'timing/data': 0.0002421122044324875, 'timing/model': 0.4664245005697012, 'learning_rate/action_model': 9.991982744974799e-05, 'learning_rate/action_query_proj': 9.991982744974799e-05, 'learning_rate/base': 2.4979956862436998e-05, 'epoch': 0.25}) +[2026-07-27 03:08:08,813][starVLA.training.train_starvla][INFO] - Step 2093, Loss: {'train/loss': 0.2904133200645447, 'train/grad_norm_pre_clip': 4.3754987716674805, 'timing/data': 0.00019378634169697762, 'timing/model': 0.457739997189492, 'learning_rate/action_model': 9.991807559468107e-05, 'learning_rate/action_query_proj': 9.991807559468107e-05, 'learning_rate/base': 2.4979518898670267e-05, 'epoch': 0.25}) +[2026-07-27 03:08:14,441][starVLA.training.train_starvla][INFO] - Step 2094, Loss: {'train/loss': 0.22090847790241241, 'train/grad_norm_pre_clip': 4.402039051055908, 'timing/data': 0.00019641639664769173, 'timing/model': 0.46141067100688815, 'learning_rate/action_model': 9.991630482231677e-05, 'learning_rate/action_query_proj': 9.991630482231677e-05, 'learning_rate/base': 2.4979076205579193e-05, 'epoch': 0.25}) +[2026-07-27 03:08:20,067][starVLA.training.train_starvla][INFO] - Step 2095, Loss: {'train/loss': 0.3226405084133148, 'train/grad_norm_pre_clip': 3.7072393894195557, 'timing/data': 0.00019800011068582535, 'timing/model': 0.4623202420771122, 'learning_rate/action_model': 9.991451513335418e-05, 'learning_rate/action_query_proj': 9.991451513335418e-05, 'learning_rate/base': 2.4978628783338545e-05, 'epoch': 0.25}) +[2026-07-27 03:08:25,691][starVLA.training.train_starvla][INFO] - Step 2096, Loss: {'train/loss': 0.285351037979126, 'train/grad_norm_pre_clip': 3.24772310256958, 'timing/data': 0.00019236421212553978, 'timing/model': 0.4630621559917927, 'learning_rate/action_model': 9.991270652849981e-05, 'learning_rate/action_query_proj': 9.991270652849981e-05, 'learning_rate/base': 2.4978176632124953e-05, 'epoch': 0.25}) +[2026-07-27 03:08:31,308][starVLA.training.train_starvla][INFO] - Step 2097, Loss: {'train/loss': 0.305053174495697, 'train/grad_norm_pre_clip': 3.0223124027252197, 'timing/data': 0.0001908969134092331, 'timing/model': 0.457677467726171, 'learning_rate/action_model': 9.991087900846772e-05, 'learning_rate/action_query_proj': 9.991087900846772e-05, 'learning_rate/base': 2.497771975211693e-05, 'epoch': 0.25}) +[2026-07-27 03:08:36,951][starVLA.training.train_starvla][INFO] - Step 2098, Loss: {'train/loss': 0.25072014331817627, 'train/grad_norm_pre_clip': 4.914848804473877, 'timing/data': 0.00019856775179505348, 'timing/model': 0.4618930481374264, 'learning_rate/action_model': 9.990903257397934e-05, 'learning_rate/action_query_proj': 9.990903257397934e-05, 'learning_rate/base': 2.4977258143494836e-05, 'epoch': 0.25}) +[2026-07-27 03:08:42,750][starVLA.training.train_starvla][INFO] - Step 2099, Loss: {'train/loss': 0.26878172159194946, 'train/grad_norm_pre_clip': 3.7652854919433594, 'timing/data': 0.00018715392798185349, 'timing/model': 0.46567560406401753, 'learning_rate/action_model': 9.990716722576365e-05, 'learning_rate/action_query_proj': 9.990716722576365e-05, 'learning_rate/base': 2.4976791806440912e-05, 'epoch': 0.25}) +[2026-07-27 03:08:48,387][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2100 +[2026-07-27 03:08:48,388][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2100 +[2026-07-27 03:08:48,389][starVLA.training.train_starvla][INFO] - Step 2100, Loss: {'train/loss': 0.2883679270744324, 'train/grad_norm_pre_clip': 4.522176265716553, 'timing/data': 0.0001908848062157631, 'timing/model': 0.4615168278105557, 'learning_rate/action_model': 9.990528296455703e-05, 'learning_rate/action_query_proj': 9.990528296455703e-05, 'learning_rate/base': 2.4976320741139258e-05, 'epoch': 0.25}) +[2026-07-27 03:08:54,032][starVLA.training.train_starvla][INFO] - Step 2101, Loss: {'train/loss': 0.24818888306617737, 'train/grad_norm_pre_clip': 3.4227428436279297, 'timing/data': 0.00018947385251522064, 'timing/model': 0.4589228010736406, 'learning_rate/action_model': 9.990337979110337e-05, 'learning_rate/action_query_proj': 9.990337979110337e-05, 'learning_rate/base': 2.4975844947775844e-05, 'epoch': 0.25}) +[2026-07-27 03:08:59,669][starVLA.training.train_starvla][INFO] - Step 2102, Loss: {'train/loss': 0.2594144344329834, 'train/grad_norm_pre_clip': 3.326479911804199, 'timing/data': 0.00018556276336312294, 'timing/model': 0.4632357149384916, 'learning_rate/action_model': 9.990145770615403e-05, 'learning_rate/action_query_proj': 9.990145770615403e-05, 'learning_rate/base': 2.4975364426538507e-05, 'epoch': 0.25}) +[2026-07-27 03:09:05,274][starVLA.training.train_starvla][INFO] - Step 2103, Loss: {'train/loss': 0.15805691480636597, 'train/grad_norm_pre_clip': 3.0898351669311523, 'timing/data': 0.00019467109814286232, 'timing/model': 0.4621782978065312, 'learning_rate/action_model': 9.989951671046779e-05, 'learning_rate/action_query_proj': 9.989951671046779e-05, 'learning_rate/base': 2.4974879177616947e-05, 'epoch': 0.26}) +[2026-07-27 03:09:10,889][starVLA.training.train_starvla][INFO] - Step 2104, Loss: {'train/loss': 0.20510371029376984, 'train/grad_norm_pre_clip': 3.339071750640869, 'timing/data': 0.00020579202100634575, 'timing/model': 0.46103304577991366, 'learning_rate/action_model': 9.989755680481093e-05, 'learning_rate/action_query_proj': 9.989755680481093e-05, 'learning_rate/base': 2.497438920120273e-05, 'epoch': 0.26}) +[2026-07-27 03:09:16,508][starVLA.training.train_starvla][INFO] - Step 2105, Loss: {'train/loss': 0.2060329020023346, 'train/grad_norm_pre_clip': 2.9278738498687744, 'timing/data': 0.00019759777933359146, 'timing/model': 0.4663991560228169, 'learning_rate/action_model': 9.98955779899572e-05, 'learning_rate/action_query_proj': 9.98955779899572e-05, 'learning_rate/base': 2.49738944974893e-05, 'epoch': 0.26}) +[2026-07-27 03:09:22,121][starVLA.training.train_starvla][INFO] - Step 2106, Loss: {'train/loss': 0.2998088300228119, 'train/grad_norm_pre_clip': 5.0302581787109375, 'timing/data': 0.00019208528101444244, 'timing/model': 0.45848514698445797, 'learning_rate/action_model': 9.98935802666878e-05, 'learning_rate/action_query_proj': 9.98935802666878e-05, 'learning_rate/base': 2.497339506667195e-05, 'epoch': 0.26}) +[2026-07-27 03:09:27,748][starVLA.training.train_starvla][INFO] - Step 2107, Loss: {'train/loss': 0.30954280495643616, 'train/grad_norm_pre_clip': 4.1204400062561035, 'timing/data': 0.00018575182184576988, 'timing/model': 0.46611219411715865, 'learning_rate/action_model': 9.989156363579138e-05, 'learning_rate/action_query_proj': 9.989156363579138e-05, 'learning_rate/base': 2.4972890908947846e-05, 'epoch': 0.26}) +[2026-07-27 03:09:33,379][starVLA.training.train_starvla][INFO] - Step 2108, Loss: {'train/loss': 0.38651299476623535, 'train/grad_norm_pre_clip': 4.125433921813965, 'timing/data': 0.00018730014562606812, 'timing/model': 0.46601275727152824, 'learning_rate/action_model': 9.98895280980641e-05, 'learning_rate/action_query_proj': 9.98895280980641e-05, 'learning_rate/base': 2.4972382024516026e-05, 'epoch': 0.26}) +[2026-07-27 03:09:39,003][starVLA.training.train_starvla][INFO] - Step 2109, Loss: {'train/loss': 0.352714478969574, 'train/grad_norm_pre_clip': 4.010198593139648, 'timing/data': 0.00018807407468557358, 'timing/model': 0.46524739265441895, 'learning_rate/action_model': 9.988747365430957e-05, 'learning_rate/action_query_proj': 9.988747365430957e-05, 'learning_rate/base': 2.4971868413577392e-05, 'epoch': 0.26}) +[2026-07-27 03:09:44,618][starVLA.training.train_starvla][INFO] - Step 2110, Loss: {'train/loss': 0.18103425204753876, 'train/grad_norm_pre_clip': 2.4946343898773193, 'timing/data': 0.00019200798124074936, 'timing/model': 0.4622247563675046, 'learning_rate/action_model': 9.98854003053388e-05, 'learning_rate/action_query_proj': 9.98854003053388e-05, 'learning_rate/base': 2.49713500763347e-05, 'epoch': 0.26}) +[2026-07-27 03:09:50,598][starVLA.training.train_starvla][INFO] - Step 2111, Loss: {'train/loss': 0.19195277988910675, 'train/grad_norm_pre_clip': 3.0358774662017822, 'timing/data': 0.00019036000594496727, 'timing/model': 0.4964580535888672, 'learning_rate/action_model': 9.988330805197039e-05, 'learning_rate/action_query_proj': 9.988330805197039e-05, 'learning_rate/base': 2.4970827012992596e-05, 'epoch': 0.26}) +[2026-07-27 03:09:56,277][starVLA.training.train_starvla][INFO] - Step 2112, Loss: {'train/loss': 0.4047733545303345, 'train/grad_norm_pre_clip': 4.557254791259766, 'timing/data': 0.0001916247420012951, 'timing/model': 0.4617673298344016, 'learning_rate/action_model': 9.988119689503026e-05, 'learning_rate/action_query_proj': 9.988119689503026e-05, 'learning_rate/base': 2.4970299223757564e-05, 'epoch': 0.26}) +[2026-07-27 03:10:01,891][starVLA.training.train_starvla][INFO] - Step 2113, Loss: {'train/loss': 0.31376752257347107, 'train/grad_norm_pre_clip': 3.9782543182373047, 'timing/data': 0.00018834881484508514, 'timing/model': 0.48119120579212904, 'learning_rate/action_model': 9.987906683535189e-05, 'learning_rate/action_query_proj': 9.987906683535189e-05, 'learning_rate/base': 2.4969766708837973e-05, 'epoch': 0.26}) +[2026-07-27 03:10:07,512][starVLA.training.train_starvla][INFO] - Step 2114, Loss: {'train/loss': 0.3536487817764282, 'train/grad_norm_pre_clip': 5.743139743804932, 'timing/data': 0.00019383011385798454, 'timing/model': 0.46590132219716907, 'learning_rate/action_model': 9.987691787377619e-05, 'learning_rate/action_query_proj': 9.987691787377619e-05, 'learning_rate/base': 2.4969229468444047e-05, 'epoch': 0.26}) +[2026-07-27 03:10:13,110][starVLA.training.train_starvla][INFO] - Step 2115, Loss: {'train/loss': 0.2014693021774292, 'train/grad_norm_pre_clip': 2.7559053897857666, 'timing/data': 0.0001925393007695675, 'timing/model': 0.4623765111900866, 'learning_rate/action_model': 9.987475001115155e-05, 'learning_rate/action_query_proj': 9.987475001115155e-05, 'learning_rate/base': 2.4968687502787886e-05, 'epoch': 0.26}) +[2026-07-27 03:10:18,785][starVLA.training.train_starvla][INFO] - Step 2116, Loss: {'train/loss': 0.24626296758651733, 'train/grad_norm_pre_clip': 3.6014297008514404, 'timing/data': 0.0001943511888384819, 'timing/model': 0.46930518420413136, 'learning_rate/action_model': 9.987256324833378e-05, 'learning_rate/action_query_proj': 9.987256324833378e-05, 'learning_rate/base': 2.4968140812083445e-05, 'epoch': 0.26}) +[2026-07-27 03:10:24,417][starVLA.training.train_starvla][INFO] - Step 2117, Loss: {'train/loss': 0.40241605043411255, 'train/grad_norm_pre_clip': 3.5659236907958984, 'timing/data': 0.00018487870693206787, 'timing/model': 0.4633255018852651, 'learning_rate/action_model': 9.98703575861862e-05, 'learning_rate/action_query_proj': 9.98703575861862e-05, 'learning_rate/base': 2.496758939654655e-05, 'epoch': 0.26}) +[2026-07-27 03:10:30,081][starVLA.training.train_starvla][INFO] - Step 2118, Loss: {'train/loss': 0.28087541460990906, 'train/grad_norm_pre_clip': 4.5750956535339355, 'timing/data': 0.00018770573660731316, 'timing/model': 0.47016376024112105, 'learning_rate/action_model': 9.986813302557955e-05, 'learning_rate/action_query_proj': 9.986813302557955e-05, 'learning_rate/base': 2.4967033256394888e-05, 'epoch': 0.26}) +[2026-07-27 03:10:35,734][starVLA.training.train_starvla][INFO] - Step 2119, Loss: {'train/loss': 0.28377020359039307, 'train/grad_norm_pre_clip': 4.048264503479004, 'timing/data': 0.00018496299162507057, 'timing/model': 0.4715224811807275, 'learning_rate/action_model': 9.98658895673921e-05, 'learning_rate/action_query_proj': 9.98658895673921e-05, 'learning_rate/base': 2.4966472391848025e-05, 'epoch': 0.26}) +[2026-07-27 03:10:41,399][starVLA.training.train_starvla][INFO] - Step 2120, Loss: {'train/loss': 0.19443626701831818, 'train/grad_norm_pre_clip': 3.434213161468506, 'timing/data': 0.00018617277964949608, 'timing/model': 0.4681444368325174, 'learning_rate/action_model': 9.986362721250947e-05, 'learning_rate/action_query_proj': 9.986362721250947e-05, 'learning_rate/base': 2.4965906803127368e-05, 'epoch': 0.26}) +[2026-07-27 03:10:47,275][starVLA.training.train_starvla][INFO] - Step 2121, Loss: {'train/loss': 0.18340826034545898, 'train/grad_norm_pre_clip': 2.6895647048950195, 'timing/data': 0.0002261567860841751, 'timing/model': 0.4582196562550962, 'learning_rate/action_model': 9.986134596182483e-05, 'learning_rate/action_query_proj': 9.986134596182483e-05, 'learning_rate/base': 2.4965336490456208e-05, 'epoch': 0.26}) +[2026-07-27 03:10:52,937][starVLA.training.train_starvla][INFO] - Step 2122, Loss: {'train/loss': 0.31357961893081665, 'train/grad_norm_pre_clip': 3.765921115875244, 'timing/data': 0.00019939569756388664, 'timing/model': 0.4658122709952295, 'learning_rate/action_model': 9.98590458162388e-05, 'learning_rate/action_query_proj': 9.98590458162388e-05, 'learning_rate/base': 2.49647614540597e-05, 'epoch': 0.26}) +[2026-07-27 03:10:58,591][starVLA.training.train_starvla][INFO] - Step 2123, Loss: {'train/loss': 0.30089113116264343, 'train/grad_norm_pre_clip': 4.465490341186523, 'timing/data': 0.0002041817642748356, 'timing/model': 0.4678981676697731, 'learning_rate/action_model': 9.985672677665942e-05, 'learning_rate/action_query_proj': 9.985672677665942e-05, 'learning_rate/base': 2.4964181694164854e-05, 'epoch': 0.26}) +[2026-07-27 03:11:04,255][starVLA.training.train_starvla][INFO] - Step 2124, Loss: {'train/loss': 0.20887073874473572, 'train/grad_norm_pre_clip': 4.203181743621826, 'timing/data': 0.0001881048083305359, 'timing/model': 0.464642520993948, 'learning_rate/action_model': 9.985438884400221e-05, 'learning_rate/action_query_proj': 9.985438884400221e-05, 'learning_rate/base': 2.4963597211000553e-05, 'epoch': 0.26}) +[2026-07-27 03:11:09,917][starVLA.training.train_starvla][INFO] - Step 2125, Loss: {'train/loss': 0.3167745769023895, 'train/grad_norm_pre_clip': 4.259637832641602, 'timing/data': 0.000194622203707695, 'timing/model': 0.46728873485699296, 'learning_rate/action_model': 9.985203201919016e-05, 'learning_rate/action_query_proj': 9.985203201919016e-05, 'learning_rate/base': 2.496300800479754e-05, 'epoch': 0.26}) +[2026-07-27 03:11:15,596][starVLA.training.train_starvla][INFO] - Step 2126, Loss: {'train/loss': 0.35351496934890747, 'train/grad_norm_pre_clip': 3.9190139770507812, 'timing/data': 0.0001883460208773613, 'timing/model': 0.4630087409168482, 'learning_rate/action_model': 9.984965630315367e-05, 'learning_rate/action_query_proj': 9.984965630315367e-05, 'learning_rate/base': 2.4962414075788417e-05, 'epoch': 0.26}) +[2026-07-27 03:11:21,230][starVLA.training.train_starvla][INFO] - Step 2127, Loss: {'train/loss': 0.24673011898994446, 'train/grad_norm_pre_clip': 4.098334789276123, 'timing/data': 0.00019203312695026398, 'timing/model': 0.459329130128026, 'learning_rate/action_model': 9.984726169683069e-05, 'learning_rate/action_query_proj': 9.984726169683069e-05, 'learning_rate/base': 2.4961815424207673e-05, 'epoch': 0.26}) +[2026-07-27 03:11:26,892][starVLA.training.train_starvla][INFO] - Step 2128, Loss: {'train/loss': 0.24368104338645935, 'train/grad_norm_pre_clip': 3.5870847702026367, 'timing/data': 0.00018872320652008057, 'timing/model': 0.46794611075893044, 'learning_rate/action_model': 9.984484820116655e-05, 'learning_rate/action_query_proj': 9.984484820116655e-05, 'learning_rate/base': 2.4961212050291636e-05, 'epoch': 0.26}) +[2026-07-27 03:11:32,555][starVLA.training.train_starvla][INFO] - Step 2129, Loss: {'train/loss': 0.263272225856781, 'train/grad_norm_pre_clip': 4.3747406005859375, 'timing/data': 0.00019337376579642296, 'timing/model': 0.4690187182277441, 'learning_rate/action_model': 9.984241581711403e-05, 'learning_rate/action_query_proj': 9.984241581711403e-05, 'learning_rate/base': 2.4960603954278507e-05, 'epoch': 0.26}) +[2026-07-27 03:11:38,158][starVLA.training.train_starvla][INFO] - Step 2130, Loss: {'train/loss': 0.39841198921203613, 'train/grad_norm_pre_clip': 4.439051628112793, 'timing/data': 0.00019835121929645538, 'timing/model': 0.4683915697969496, 'learning_rate/action_model': 9.983996454563343e-05, 'learning_rate/action_query_proj': 9.983996454563343e-05, 'learning_rate/base': 2.4959991136408358e-05, 'epoch': 0.26}) +[2026-07-27 03:11:44,045][starVLA.training.train_starvla][INFO] - Step 2131, Loss: {'train/loss': 0.2286672294139862, 'train/grad_norm_pre_clip': 2.3900530338287354, 'timing/data': 0.00018886569887399673, 'timing/model': 0.468537837266922, 'learning_rate/action_model': 9.983749438769247e-05, 'learning_rate/action_query_proj': 9.983749438769247e-05, 'learning_rate/base': 2.4959373596923118e-05, 'epoch': 0.26}) +[2026-07-27 03:11:49,731][starVLA.training.train_starvla][INFO] - Step 2132, Loss: {'train/loss': 0.22493815422058105, 'train/grad_norm_pre_clip': 3.8754217624664307, 'timing/data': 0.0001884191296994686, 'timing/model': 0.4631997817195952, 'learning_rate/action_model': 9.983500534426635e-05, 'learning_rate/action_query_proj': 9.983500534426635e-05, 'learning_rate/base': 2.4958751336066588e-05, 'epoch': 0.26}) +[2026-07-27 03:11:55,399][starVLA.training.train_starvla][INFO] - Step 2133, Loss: {'train/loss': 0.24035832285881042, 'train/grad_norm_pre_clip': 3.0982470512390137, 'timing/data': 0.00019546691328287125, 'timing/model': 0.4659893470816314, 'learning_rate/action_model': 9.983249741633765e-05, 'learning_rate/action_query_proj': 9.983249741633765e-05, 'learning_rate/base': 2.4958124354084414e-05, 'epoch': 0.26}) +[2026-07-27 03:12:01,138][starVLA.training.train_starvla][INFO] - Step 2134, Loss: {'train/loss': 0.27097007632255554, 'train/grad_norm_pre_clip': 3.4580063819885254, 'timing/data': 0.00019045639783143997, 'timing/model': 0.46797346975654364, 'learning_rate/action_model': 9.98299706048965e-05, 'learning_rate/action_query_proj': 9.98299706048965e-05, 'learning_rate/base': 2.4957492651224125e-05, 'epoch': 0.26}) +[2026-07-27 03:12:06,816][starVLA.training.train_starvla][INFO] - Step 2135, Loss: {'train/loss': 0.19827434420585632, 'train/grad_norm_pre_clip': 4.1249494552612305, 'timing/data': 0.00018545426428318024, 'timing/model': 0.46106173237785697, 'learning_rate/action_model': 9.982742491094044e-05, 'learning_rate/action_query_proj': 9.982742491094044e-05, 'learning_rate/base': 2.495685622773511e-05, 'epoch': 0.26}) +[2026-07-27 03:12:12,747][starVLA.training.train_starvla][INFO] - Step 2136, Loss: {'train/loss': 0.3604881763458252, 'train/grad_norm_pre_clip': 6.481802463531494, 'timing/data': 0.00018627382814884186, 'timing/model': 0.4685954418964684, 'learning_rate/action_model': 9.982486033547446e-05, 'learning_rate/action_query_proj': 9.982486033547446e-05, 'learning_rate/base': 2.4956215083868616e-05, 'epoch': 0.26}) +[2026-07-27 03:12:18,687][starVLA.training.train_starvla][INFO] - Step 2137, Loss: {'train/loss': 0.4123150408267975, 'train/grad_norm_pre_clip': 7.184659004211426, 'timing/data': 0.00018779980018734932, 'timing/model': 0.46841190243139863, 'learning_rate/action_model': 9.982227687951103e-05, 'learning_rate/action_query_proj': 9.982227687951103e-05, 'learning_rate/base': 2.4955569219877756e-05, 'epoch': 0.26}) +[2026-07-27 03:12:24,322][starVLA.training.train_starvla][INFO] - Step 2138, Loss: {'train/loss': 0.276203989982605, 'train/grad_norm_pre_clip': 4.044956684112549, 'timing/data': 0.00018662819638848305, 'timing/model': 0.46790648717433214, 'learning_rate/action_model': 9.981967454407004e-05, 'learning_rate/action_query_proj': 9.981967454407004e-05, 'learning_rate/base': 2.495491863601751e-05, 'epoch': 0.26}) +[2026-07-27 03:12:29,941][starVLA.training.train_starvla][INFO] - Step 2139, Loss: {'train/loss': 0.2709347605705261, 'train/grad_norm_pre_clip': 4.23813009262085, 'timing/data': 0.00019480008631944656, 'timing/model': 0.462657384108752, 'learning_rate/action_model': 9.981705333017884e-05, 'learning_rate/action_query_proj': 9.981705333017884e-05, 'learning_rate/base': 2.495426333254471e-05, 'epoch': 0.26}) +[2026-07-27 03:12:35,621][starVLA.training.train_starvla][INFO] - Step 2140, Loss: {'train/loss': 0.28881970047950745, 'train/grad_norm_pre_clip': 3.540468215942383, 'timing/data': 0.00018890295177698135, 'timing/model': 0.45618403796106577, 'learning_rate/action_model': 9.981441323887228e-05, 'learning_rate/action_query_proj': 9.981441323887228e-05, 'learning_rate/base': 2.495360330971807e-05, 'epoch': 0.26}) +[2026-07-27 03:12:41,257][starVLA.training.train_starvla][INFO] - Step 2141, Loss: {'train/loss': 0.18299229443073273, 'train/grad_norm_pre_clip': 4.977637767791748, 'timing/data': 0.00019187107682228088, 'timing/model': 0.46640765108168125, 'learning_rate/action_model': 9.981175427119261e-05, 'learning_rate/action_query_proj': 9.981175427119261e-05, 'learning_rate/base': 2.4952938567798152e-05, 'epoch': 0.26}) +[2026-07-27 03:12:46,887][starVLA.training.train_starvla][INFO] - Step 2142, Loss: {'train/loss': 0.25214818120002747, 'train/grad_norm_pre_clip': 4.743141174316406, 'timing/data': 0.0001864451915025711, 'timing/model': 0.46805131109431386, 'learning_rate/action_model': 9.980907642818953e-05, 'learning_rate/action_query_proj': 9.980907642818953e-05, 'learning_rate/base': 2.4952269107047384e-05, 'epoch': 0.26}) +[2026-07-27 03:12:52,517][starVLA.training.train_starvla][INFO] - Step 2143, Loss: {'train/loss': 0.24404984712600708, 'train/grad_norm_pre_clip': 3.0149216651916504, 'timing/data': 0.0001978711225092411, 'timing/model': 0.4670914257876575, 'learning_rate/action_model': 9.980637971092024e-05, 'learning_rate/action_query_proj': 9.980637971092024e-05, 'learning_rate/base': 2.495159492773006e-05, 'epoch': 0.26}) +[2026-07-27 03:12:58,118][starVLA.training.train_starvla][INFO] - Step 2144, Loss: {'train/loss': 0.24869957566261292, 'train/grad_norm_pre_clip': 3.8387601375579834, 'timing/data': 0.00018845312297344208, 'timing/model': 0.45810213312506676, 'learning_rate/action_model': 9.980366412044934e-05, 'learning_rate/action_query_proj': 9.980366412044934e-05, 'learning_rate/base': 2.4950916030112335e-05, 'epoch': 0.26}) +[2026-07-27 03:13:03,731][starVLA.training.train_starvla][INFO] - Step 2145, Loss: {'train/loss': 0.26377740502357483, 'train/grad_norm_pre_clip': 3.8961470127105713, 'timing/data': 0.0002012699842453003, 'timing/model': 0.4665922042913735, 'learning_rate/action_model': 9.980092965784891e-05, 'learning_rate/action_query_proj': 9.980092965784891e-05, 'learning_rate/base': 2.4950232414462228e-05, 'epoch': 0.26}) +[2026-07-27 03:13:09,360][starVLA.training.train_starvla][INFO] - Step 2146, Loss: {'train/loss': 0.240034282207489, 'train/grad_norm_pre_clip': 4.110159397125244, 'timing/data': 0.00020291702821850777, 'timing/model': 0.46766772493720055, 'learning_rate/action_model': 9.979817632419848e-05, 'learning_rate/action_query_proj': 9.979817632419848e-05, 'learning_rate/base': 2.494954408104962e-05, 'epoch': 0.26}) +[2026-07-27 03:13:14,969][starVLA.training.train_starvla][INFO] - Step 2147, Loss: {'train/loss': 0.21396006643772125, 'train/grad_norm_pre_clip': 4.320291996002197, 'timing/data': 0.0002021072432398796, 'timing/model': 0.46661274693906307, 'learning_rate/action_model': 9.979540412058501e-05, 'learning_rate/action_query_proj': 9.979540412058501e-05, 'learning_rate/base': 2.4948851030146252e-05, 'epoch': 0.26}) +[2026-07-27 03:13:20,586][starVLA.training.train_starvla][INFO] - Step 2148, Loss: {'train/loss': 0.2699183523654938, 'train/grad_norm_pre_clip': 5.121222496032715, 'timing/data': 0.00019123172387480736, 'timing/model': 0.46728281071409583, 'learning_rate/action_model': 9.979261304810292e-05, 'learning_rate/action_query_proj': 9.979261304810292e-05, 'learning_rate/base': 2.494815326202573e-05, 'epoch': 0.26}) +[2026-07-27 03:13:26,193][starVLA.training.train_starvla][INFO] - Step 2149, Loss: {'train/loss': 0.23333865404129028, 'train/grad_norm_pre_clip': 3.621720790863037, 'timing/data': 0.0001876302994787693, 'timing/model': 0.4668868728913367, 'learning_rate/action_model': 9.978980310785408e-05, 'learning_rate/action_query_proj': 9.978980310785408e-05, 'learning_rate/base': 2.494745077696352e-05, 'epoch': 0.26}) +[2026-07-27 03:13:31,809][starVLA.training.train_starvla][INFO] - Step 2150, Loss: {'train/loss': 0.31860777735710144, 'train/grad_norm_pre_clip': 3.2793519496917725, 'timing/data': 0.00019436003640294075, 'timing/model': 0.46282468689605594, 'learning_rate/action_model': 9.978697430094785e-05, 'learning_rate/action_query_proj': 9.978697430094785e-05, 'learning_rate/base': 2.494674357523696e-05, 'epoch': 0.26}) +[2026-07-27 03:13:37,454][starVLA.training.train_starvla][INFO] - Step 2151, Loss: {'train/loss': 0.23484832048416138, 'train/grad_norm_pre_clip': 3.961519241333008, 'timing/data': 0.00019267713651061058, 'timing/model': 0.46246375935152173, 'learning_rate/action_model': 9.978412662850094e-05, 'learning_rate/action_query_proj': 9.978412662850094e-05, 'learning_rate/base': 2.4946031657125236e-05, 'epoch': 0.26}) +[2026-07-27 03:13:44,001][starVLA.training.train_starvla][INFO] - Step 2152, Loss: {'train/loss': 0.22356417775154114, 'train/grad_norm_pre_clip': 2.963737726211548, 'timing/data': 0.00019110413268208504, 'timing/model': 0.7416486223228276, 'learning_rate/action_model': 9.97812600916376e-05, 'learning_rate/action_query_proj': 9.97812600916376e-05, 'learning_rate/base': 2.49453150229094e-05, 'epoch': 0.26}) +[2026-07-27 03:13:49,620][starVLA.training.train_starvla][INFO] - Step 2153, Loss: {'train/loss': 0.23958224058151245, 'train/grad_norm_pre_clip': 3.142085313796997, 'timing/data': 0.00019642803817987442, 'timing/model': 0.4570903521962464, 'learning_rate/action_model': 9.977837469148947e-05, 'learning_rate/action_query_proj': 9.977837469148947e-05, 'learning_rate/base': 2.4944593672872368e-05, 'epoch': 0.26}) +[2026-07-27 03:13:55,230][starVLA.training.train_starvla][INFO] - Step 2154, Loss: {'train/loss': 0.2110249549150467, 'train/grad_norm_pre_clip': 3.130504846572876, 'timing/data': 0.00018089869990944862, 'timing/model': 0.46236713184043765, 'learning_rate/action_model': 9.977547042919569e-05, 'learning_rate/action_query_proj': 9.977547042919569e-05, 'learning_rate/base': 2.4943867607298923e-05, 'epoch': 0.26}) +[2026-07-27 03:14:00,831][starVLA.training.train_starvla][INFO] - Step 2155, Loss: {'train/loss': 0.25749364495277405, 'train/grad_norm_pre_clip': 3.917614698410034, 'timing/data': 0.00019095977768301964, 'timing/model': 0.458402241114527, 'learning_rate/action_model': 9.977254730590281e-05, 'learning_rate/action_query_proj': 9.977254730590281e-05, 'learning_rate/base': 2.4943136826475702e-05, 'epoch': 0.26}) +[2026-07-27 03:14:06,462][starVLA.training.train_starvla][INFO] - Step 2156, Loss: {'train/loss': 0.2690034806728363, 'train/grad_norm_pre_clip': 2.77679705619812, 'timing/data': 0.00018581096082925797, 'timing/model': 0.46201654989272356, 'learning_rate/action_model': 9.97696053227648e-05, 'learning_rate/action_query_proj': 9.97696053227648e-05, 'learning_rate/base': 2.49424013306912e-05, 'epoch': 0.26}) +[2026-07-27 03:14:12,066][starVLA.training.train_starvla][INFO] - Step 2157, Loss: {'train/loss': 0.1564897745847702, 'train/grad_norm_pre_clip': 2.855476140975952, 'timing/data': 0.00018206285312771797, 'timing/model': 0.46435094671323895, 'learning_rate/action_model': 9.976664448094316e-05, 'learning_rate/action_query_proj': 9.976664448094316e-05, 'learning_rate/base': 2.494166112023579e-05, 'epoch': 0.26}) +[2026-07-27 03:14:17,652][starVLA.training.train_starvla][INFO] - Step 2158, Loss: {'train/loss': 0.31020739674568176, 'train/grad_norm_pre_clip': 3.268448829650879, 'timing/data': 0.00018835300579667091, 'timing/model': 0.4667787398211658, 'learning_rate/action_model': 9.976366478160673e-05, 'learning_rate/action_query_proj': 9.976366478160673e-05, 'learning_rate/base': 2.4940916195401682e-05, 'epoch': 0.26}) +[2026-07-27 03:14:23,252][starVLA.training.train_starvla][INFO] - Step 2159, Loss: {'train/loss': 0.2963376045227051, 'train/grad_norm_pre_clip': 4.560788154602051, 'timing/data': 0.00018819887191057205, 'timing/model': 0.4668752336874604, 'learning_rate/action_model': 9.97606662259319e-05, 'learning_rate/action_query_proj': 9.97606662259319e-05, 'learning_rate/base': 2.4940166556482976e-05, 'epoch': 0.26}) +[2026-07-27 03:14:28,885][starVLA.training.train_starvla][INFO] - Step 2160, Loss: {'train/loss': 0.23405659198760986, 'train/grad_norm_pre_clip': 2.360422134399414, 'timing/data': 0.00018728803843259811, 'timing/model': 0.4645640361122787, 'learning_rate/action_model': 9.975764881510242e-05, 'learning_rate/action_query_proj': 9.975764881510242e-05, 'learning_rate/base': 2.4939412203775605e-05, 'epoch': 0.26}) +[2026-07-27 03:14:34,510][starVLA.training.train_starvla][INFO] - Step 2161, Loss: {'train/loss': 0.23514394462108612, 'train/grad_norm_pre_clip': 3.7245261669158936, 'timing/data': 0.00018720002844929695, 'timing/model': 0.4674325338564813, 'learning_rate/action_model': 9.975461255030951e-05, 'learning_rate/action_query_proj': 9.975461255030951e-05, 'learning_rate/base': 2.493865313757738e-05, 'epoch': 0.26}) +[2026-07-27 03:14:40,126][starVLA.training.train_starvla][INFO] - Step 2162, Loss: {'train/loss': 0.21968524158000946, 'train/grad_norm_pre_clip': 3.937648296356201, 'timing/data': 0.0001851939596235752, 'timing/model': 0.46066502342000604, 'learning_rate/action_model': 9.975155743275187e-05, 'learning_rate/action_query_proj': 9.975155743275187e-05, 'learning_rate/base': 2.4937889358187967e-05, 'epoch': 0.26}) +[2026-07-27 03:14:45,732][starVLA.training.train_starvla][INFO] - Step 2163, Loss: {'train/loss': 0.3001726269721985, 'train/grad_norm_pre_clip': 4.182757377624512, 'timing/data': 0.00019381195306777954, 'timing/model': 0.4627909488044679, 'learning_rate/action_model': 9.974848346363557e-05, 'learning_rate/action_query_proj': 9.974848346363557e-05, 'learning_rate/base': 2.4937120865908894e-05, 'epoch': 0.26}) +[2026-07-27 03:14:51,332][starVLA.training.train_starvla][INFO] - Step 2164, Loss: {'train/loss': 0.45363864302635193, 'train/grad_norm_pre_clip': 5.439469814300537, 'timing/data': 0.00018545286729931831, 'timing/model': 0.4573912392370403, 'learning_rate/action_model': 9.974539064417421e-05, 'learning_rate/action_query_proj': 9.974539064417421e-05, 'learning_rate/base': 2.4936347661043552e-05, 'epoch': 0.26}) +[2026-07-27 03:14:56,955][starVLA.training.train_starvla][INFO] - Step 2165, Loss: {'train/loss': 0.19969090819358826, 'train/grad_norm_pre_clip': 3.166811466217041, 'timing/data': 0.00019940407946705818, 'timing/model': 0.46787133906036615, 'learning_rate/action_model': 9.974227897558876e-05, 'learning_rate/action_query_proj': 9.974227897558876e-05, 'learning_rate/base': 2.493556974389719e-05, 'epoch': 0.26}) +[2026-07-27 03:15:02,569][starVLA.training.train_starvla][INFO] - Step 2166, Loss: {'train/loss': 0.2821216285228729, 'train/grad_norm_pre_clip': 4.079124450683594, 'timing/data': 0.0001916307955980301, 'timing/model': 0.4667769898660481, 'learning_rate/action_model': 9.973914845910765e-05, 'learning_rate/action_query_proj': 9.973914845910765e-05, 'learning_rate/base': 2.4934787114776913e-05, 'epoch': 0.26}) +[2026-07-27 03:15:08,183][starVLA.training.train_starvla][INFO] - Step 2167, Loss: {'train/loss': 0.24432729184627533, 'train/grad_norm_pre_clip': 4.387979984283447, 'timing/data': 0.00018930435180664062, 'timing/model': 0.4642271311022341, 'learning_rate/action_model': 9.973599909596679e-05, 'learning_rate/action_query_proj': 9.973599909596679e-05, 'learning_rate/base': 2.4933999773991696e-05, 'epoch': 0.26}) +[2026-07-27 03:15:13,810][starVLA.training.train_starvla][INFO] - Step 2168, Loss: {'train/loss': 0.22171278297901154, 'train/grad_norm_pre_clip': 4.898635387420654, 'timing/data': 0.00019038887694478035, 'timing/model': 0.4667592463083565, 'learning_rate/action_model': 9.973283088740948e-05, 'learning_rate/action_query_proj': 9.973283088740948e-05, 'learning_rate/base': 2.493320772185237e-05, 'epoch': 0.26}) +[2026-07-27 03:15:19,427][starVLA.training.train_starvla][INFO] - Step 2169, Loss: {'train/loss': 0.2732614576816559, 'train/grad_norm_pre_clip': 3.596067190170288, 'timing/data': 0.00018694903701543808, 'timing/model': 0.46846636198461056, 'learning_rate/action_model': 9.972964383468646e-05, 'learning_rate/action_query_proj': 9.972964383468646e-05, 'learning_rate/base': 2.4932410958671615e-05, 'epoch': 0.26}) +[2026-07-27 03:15:25,035][starVLA.training.train_starvla][INFO] - Step 2170, Loss: {'train/loss': 0.2059105783700943, 'train/grad_norm_pre_clip': 3.327669382095337, 'timing/data': 0.00018642377108335495, 'timing/model': 0.4639128069393337, 'learning_rate/action_model': 9.972643793905595e-05, 'learning_rate/action_query_proj': 9.972643793905595e-05, 'learning_rate/base': 2.4931609484763988e-05, 'epoch': 0.26}) +[2026-07-27 03:15:30,634][starVLA.training.train_starvla][INFO] - Step 2171, Loss: {'train/loss': 0.23907065391540527, 'train/grad_norm_pre_clip': 2.927591323852539, 'timing/data': 0.0002400190569460392, 'timing/model': 0.4630509978160262, 'learning_rate/action_model': 9.972321320178359e-05, 'learning_rate/action_query_proj': 9.972321320178359e-05, 'learning_rate/base': 2.4930803300445897e-05, 'epoch': 0.26}) +[2026-07-27 03:15:36,261][starVLA.training.train_starvla][INFO] - Step 2172, Loss: {'train/loss': 0.2934689521789551, 'train/grad_norm_pre_clip': 3.4474520683288574, 'timing/data': 0.0001955782063305378, 'timing/model': 0.4620669218711555, 'learning_rate/action_model': 9.971996962414244e-05, 'learning_rate/action_query_proj': 9.971996962414244e-05, 'learning_rate/base': 2.492999240603561e-05, 'epoch': 0.26}) +[2026-07-27 03:15:41,851][starVLA.training.train_starvla][INFO] - Step 2173, Loss: {'train/loss': 0.22877392172813416, 'train/grad_norm_pre_clip': 2.911316156387329, 'timing/data': 0.0002570180222392082, 'timing/model': 0.45804981980472803, 'learning_rate/action_model': 9.971670720741304e-05, 'learning_rate/action_query_proj': 9.971670720741304e-05, 'learning_rate/base': 2.492917680185326e-05, 'epoch': 0.26}) +[2026-07-27 03:15:47,417][starVLA.training.train_starvla][INFO] - Step 2174, Loss: {'train/loss': 0.22876155376434326, 'train/grad_norm_pre_clip': 3.5377631187438965, 'timing/data': 0.00018547195941209793, 'timing/model': 0.4569954057224095, 'learning_rate/action_model': 9.97134259528833e-05, 'learning_rate/action_query_proj': 9.97134259528833e-05, 'learning_rate/base': 2.4928356488220825e-05, 'epoch': 0.26}) +[2026-07-27 03:15:53,277][starVLA.training.train_starvla][INFO] - Step 2175, Loss: {'train/loss': 0.2919447720050812, 'train/grad_norm_pre_clip': 3.9325509071350098, 'timing/data': 0.00018554413691163063, 'timing/model': 0.4677102477289736, 'learning_rate/action_model': 9.971012586184863e-05, 'learning_rate/action_query_proj': 9.971012586184863e-05, 'learning_rate/base': 2.4927531465462158e-05, 'epoch': 0.26}) +[2026-07-27 03:15:58,887][starVLA.training.train_starvla][INFO] - Step 2176, Loss: {'train/loss': 0.2965652346611023, 'train/grad_norm_pre_clip': 4.206953048706055, 'timing/data': 0.00018962519243359566, 'timing/model': 0.46680149203166366, 'learning_rate/action_model': 9.970680693561186e-05, 'learning_rate/action_query_proj': 9.970680693561186e-05, 'learning_rate/base': 2.4926701733902965e-05, 'epoch': 0.26}) +[2026-07-27 03:16:04,515][starVLA.training.train_starvla][INFO] - Step 2177, Loss: {'train/loss': 0.2569063901901245, 'train/grad_norm_pre_clip': 4.096540451049805, 'timing/data': 0.00018682843074202538, 'timing/model': 0.460758144967258, 'learning_rate/action_model': 9.970346917548323e-05, 'learning_rate/action_query_proj': 9.970346917548323e-05, 'learning_rate/base': 2.4925867293870808e-05, 'epoch': 0.26}) +[2026-07-27 03:16:10,115][starVLA.training.train_starvla][INFO] - Step 2178, Loss: {'train/loss': 0.2244826853275299, 'train/grad_norm_pre_clip': 4.036859512329102, 'timing/data': 0.00019003311172127724, 'timing/model': 0.4639644189737737, 'learning_rate/action_model': 9.970011258278047e-05, 'learning_rate/action_query_proj': 9.970011258278047e-05, 'learning_rate/base': 2.4925028145695118e-05, 'epoch': 0.26}) +[2026-07-27 03:16:15,731][starVLA.training.train_starvla][INFO] - Step 2179, Loss: {'train/loss': 0.3001983165740967, 'train/grad_norm_pre_clip': 4.747781753540039, 'timing/data': 0.00019759219139814377, 'timing/model': 0.4667407777160406, 'learning_rate/action_model': 9.969673715882866e-05, 'learning_rate/action_query_proj': 9.969673715882866e-05, 'learning_rate/base': 2.4924184289707166e-05, 'epoch': 0.26}) +[2026-07-27 03:16:21,341][starVLA.training.train_starvla][INFO] - Step 2180, Loss: {'train/loss': 0.13954223692417145, 'train/grad_norm_pre_clip': 2.542057752609253, 'timing/data': 0.00018809596076607704, 'timing/model': 0.4663611790165305, 'learning_rate/action_model': 9.96933429049604e-05, 'learning_rate/action_query_proj': 9.96933429049604e-05, 'learning_rate/base': 2.49233357262401e-05, 'epoch': 0.26}) +[2026-07-27 03:16:26,954][starVLA.training.train_starvla][INFO] - Step 2181, Loss: {'train/loss': 0.2303023487329483, 'train/grad_norm_pre_clip': 2.985524892807007, 'timing/data': 0.00019099097698926926, 'timing/model': 0.4664813722483814, 'learning_rate/action_model': 9.968992982251568e-05, 'learning_rate/action_query_proj': 9.968992982251568e-05, 'learning_rate/base': 2.492248245562892e-05, 'epoch': 0.26}) +[2026-07-27 03:16:32,557][starVLA.training.train_starvla][INFO] - Step 2182, Loss: {'train/loss': 0.2868817150592804, 'train/grad_norm_pre_clip': 3.8896965980529785, 'timing/data': 0.00018897512927651405, 'timing/model': 0.4630770920775831, 'learning_rate/action_model': 9.968649791284193e-05, 'learning_rate/action_query_proj': 9.968649791284193e-05, 'learning_rate/base': 2.4921624478210483e-05, 'epoch': 0.26}) +[2026-07-27 03:16:38,168][starVLA.training.train_starvla][INFO] - Step 2183, Loss: {'train/loss': 0.21791386604309082, 'train/grad_norm_pre_clip': 4.176706314086914, 'timing/data': 0.0001883888617157936, 'timing/model': 0.46648654295131564, 'learning_rate/action_model': 9.968304717729401e-05, 'learning_rate/action_query_proj': 9.968304717729401e-05, 'learning_rate/base': 2.4920761794323503e-05, 'epoch': 0.26}) +[2026-07-27 03:16:43,784][starVLA.training.train_starvla][INFO] - Step 2184, Loss: {'train/loss': 0.22902855277061462, 'train/grad_norm_pre_clip': 3.648218870162964, 'timing/data': 0.0001897909678518772, 'timing/model': 0.46750181587412953, 'learning_rate/action_model': 9.967957761723423e-05, 'learning_rate/action_query_proj': 9.967957761723423e-05, 'learning_rate/base': 2.4919894404308557e-05, 'epoch': 0.26}) +[2026-07-27 03:16:49,374][starVLA.training.train_starvla][INFO] - Step 2185, Loss: {'train/loss': 0.18622809648513794, 'train/grad_norm_pre_clip': 3.189586877822876, 'timing/data': 0.00018974626436829567, 'timing/model': 0.4561167578212917, 'learning_rate/action_model': 9.96760892340323e-05, 'learning_rate/action_query_proj': 9.96760892340323e-05, 'learning_rate/base': 2.4919022308508075e-05, 'epoch': 0.27}) +[2026-07-27 03:16:54,988][starVLA.training.train_starvla][INFO] - Step 2186, Loss: {'train/loss': 0.1948443204164505, 'train/grad_norm_pre_clip': 2.7682363986968994, 'timing/data': 0.00019038096070289612, 'timing/model': 0.45644679106771946, 'learning_rate/action_model': 9.967258202906537e-05, 'learning_rate/action_query_proj': 9.967258202906537e-05, 'learning_rate/base': 2.4918145507266342e-05, 'epoch': 0.27}) +[2026-07-27 03:17:00,553][starVLA.training.train_starvla][INFO] - Step 2187, Loss: {'train/loss': 0.21332524716854095, 'train/grad_norm_pre_clip': 3.4573323726654053, 'timing/data': 0.00018703890964388847, 'timing/model': 0.4640443972311914, 'learning_rate/action_model': 9.966905600371806e-05, 'learning_rate/action_query_proj': 9.966905600371806e-05, 'learning_rate/base': 2.4917264000929515e-05, 'epoch': 0.27}) +[2026-07-27 03:17:06,158][starVLA.training.train_starvla][INFO] - Step 2188, Loss: {'train/loss': 0.31181010603904724, 'train/grad_norm_pre_clip': 4.973203659057617, 'timing/data': 0.00019208015874028206, 'timing/model': 0.4625093531794846, 'learning_rate/action_model': 9.966551115938236e-05, 'learning_rate/action_query_proj': 9.966551115938236e-05, 'learning_rate/base': 2.491637778984559e-05, 'epoch': 0.27}) +[2026-07-27 03:17:11,728][starVLA.training.train_starvla][INFO] - Step 2189, Loss: {'train/loss': 0.1702386438846588, 'train/grad_norm_pre_clip': 4.071613311767578, 'timing/data': 0.00018996186554431915, 'timing/model': 0.4638282139785588, 'learning_rate/action_model': 9.966194749745774e-05, 'learning_rate/action_query_proj': 9.966194749745774e-05, 'learning_rate/base': 2.4915486874364434e-05, 'epoch': 0.27}) +[2026-07-27 03:17:17,310][starVLA.training.train_starvla][INFO] - Step 2190, Loss: {'train/loss': 0.2514895796775818, 'train/grad_norm_pre_clip': 4.015397548675537, 'timing/data': 0.00019587529823184013, 'timing/model': 0.4671387691050768, 'learning_rate/action_model': 9.965836501935105e-05, 'learning_rate/action_query_proj': 9.965836501935105e-05, 'learning_rate/base': 2.4914591254837762e-05, 'epoch': 0.27}) +[2026-07-27 03:17:22,887][starVLA.training.train_starvla][INFO] - Step 2191, Loss: {'train/loss': 0.17743439972400665, 'train/grad_norm_pre_clip': 2.891700267791748, 'timing/data': 0.000185416080057621, 'timing/model': 0.46668544178828597, 'learning_rate/action_model': 9.965476372647662e-05, 'learning_rate/action_query_proj': 9.965476372647662e-05, 'learning_rate/base': 2.4913690931619156e-05, 'epoch': 0.27}) +[2026-07-27 03:17:28,467][starVLA.training.train_starvla][INFO] - Step 2192, Loss: {'train/loss': 0.33189982175827026, 'train/grad_norm_pre_clip': 4.292404651641846, 'timing/data': 0.0001881001517176628, 'timing/model': 0.46070586098358035, 'learning_rate/action_model': 9.96511436202562e-05, 'learning_rate/action_query_proj': 9.96511436202562e-05, 'learning_rate/base': 2.491278590506405e-05, 'epoch': 0.27}) +[2026-07-27 03:17:34,059][starVLA.training.train_starvla][INFO] - Step 2193, Loss: {'train/loss': 0.12245529890060425, 'train/grad_norm_pre_clip': 2.8685288429260254, 'timing/data': 0.0001925700344145298, 'timing/model': 0.4642019630409777, 'learning_rate/action_model': 9.964750470211891e-05, 'learning_rate/action_query_proj': 9.964750470211891e-05, 'learning_rate/base': 2.491187617552973e-05, 'epoch': 0.27}) +[2026-07-27 03:17:39,646][starVLA.training.train_starvla][INFO] - Step 2194, Loss: {'train/loss': 0.27233803272247314, 'train/grad_norm_pre_clip': 3.285645008087158, 'timing/data': 0.00018669990822672844, 'timing/model': 0.4640974919311702, 'learning_rate/action_model': 9.964384697350134e-05, 'learning_rate/action_query_proj': 9.964384697350134e-05, 'learning_rate/base': 2.4910961743375335e-05, 'epoch': 0.27}) +[2026-07-27 03:17:45,230][starVLA.training.train_starvla][INFO] - Step 2195, Loss: {'train/loss': 0.37856072187423706, 'train/grad_norm_pre_clip': 4.98137092590332, 'timing/data': 0.00018696533516049385, 'timing/model': 0.45613533491268754, 'learning_rate/action_model': 9.964017043584755e-05, 'learning_rate/action_query_proj': 9.964017043584755e-05, 'learning_rate/base': 2.4910042608961888e-05, 'epoch': 0.27}) +[2026-07-27 03:17:50,822][starVLA.training.train_starvla][INFO] - Step 2196, Loss: {'train/loss': 0.3325539827346802, 'train/grad_norm_pre_clip': 3.776118278503418, 'timing/data': 0.0001937849447131157, 'timing/model': 0.46385273803025484, 'learning_rate/action_model': 9.963647509060892e-05, 'learning_rate/action_query_proj': 9.963647509060892e-05, 'learning_rate/base': 2.490911877265223e-05, 'epoch': 0.27}) +[2026-07-27 03:17:56,413][starVLA.training.train_starvla][INFO] - Step 2197, Loss: {'train/loss': 0.26098912954330444, 'train/grad_norm_pre_clip': 4.554856300354004, 'timing/data': 0.00018930668011307716, 'timing/model': 0.4670731909573078, 'learning_rate/action_model': 9.963276093924435e-05, 'learning_rate/action_query_proj': 9.963276093924435e-05, 'learning_rate/base': 2.4908190234811088e-05, 'epoch': 0.27}) +[2026-07-27 03:18:02,011][starVLA.training.train_starvla][INFO] - Step 2198, Loss: {'train/loss': 0.22533875703811646, 'train/grad_norm_pre_clip': 3.2707912921905518, 'timing/data': 0.00019194185733795166, 'timing/model': 0.463386386167258, 'learning_rate/action_model': 9.962902798322013e-05, 'learning_rate/action_query_proj': 9.962902798322013e-05, 'learning_rate/base': 2.4907256995805032e-05, 'epoch': 0.27}) +[2026-07-27 03:18:07,610][starVLA.training.train_starvla][INFO] - Step 2199, Loss: {'train/loss': 0.2664867341518402, 'train/grad_norm_pre_clip': 4.154898643493652, 'timing/data': 0.00018927501514554024, 'timing/model': 0.46145682595670223, 'learning_rate/action_model': 9.962527622400994e-05, 'learning_rate/action_query_proj': 9.962527622400994e-05, 'learning_rate/base': 2.4906319056002486e-05, 'epoch': 0.27}) +[2026-07-27 03:18:13,185][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2200 +[2026-07-27 03:18:13,185][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2200 +[2026-07-27 03:18:13,186][starVLA.training.train_starvla][INFO] - Step 2200, Loss: {'train/loss': 0.25008919835090637, 'train/grad_norm_pre_clip': 4.90110969543457, 'timing/data': 0.00019016116857528687, 'timing/model': 0.4626182387582958, 'learning_rate/action_model': 9.962150566309495e-05, 'learning_rate/action_query_proj': 9.962150566309495e-05, 'learning_rate/base': 2.4905376415773737e-05, 'epoch': 0.27}) +[2026-07-27 03:18:18,764][starVLA.training.train_starvla][INFO] - Step 2201, Loss: {'train/loss': 0.22662512958049774, 'train/grad_norm_pre_clip': 3.2456700801849365, 'timing/data': 0.00019013788551092148, 'timing/model': 0.4583572172559798, 'learning_rate/action_model': 9.961771630196369e-05, 'learning_rate/action_query_proj': 9.961771630196369e-05, 'learning_rate/base': 2.490442907549092e-05, 'epoch': 0.27}) +[2026-07-27 03:18:24,327][starVLA.training.train_starvla][INFO] - Step 2202, Loss: {'train/loss': 0.4072307050228119, 'train/grad_norm_pre_clip': 6.107918739318848, 'timing/data': 0.00019365502521395683, 'timing/model': 0.4685821612365544, 'learning_rate/action_model': 9.961390814211215e-05, 'learning_rate/action_query_proj': 9.961390814211215e-05, 'learning_rate/base': 2.4903477035528038e-05, 'epoch': 0.27}) +[2026-07-27 03:18:29,905][starVLA.training.train_starvla][INFO] - Step 2203, Loss: {'train/loss': 0.2851889133453369, 'train/grad_norm_pre_clip': 3.6459367275238037, 'timing/data': 0.00019976217299699783, 'timing/model': 0.46661103842779994, 'learning_rate/action_model': 9.961008118504374e-05, 'learning_rate/action_query_proj': 9.961008118504374e-05, 'learning_rate/base': 2.4902520296260936e-05, 'epoch': 0.27}) +[2026-07-27 03:18:35,479][starVLA.training.train_starvla][INFO] - Step 2204, Loss: {'train/loss': 0.2789309322834015, 'train/grad_norm_pre_clip': 4.319817066192627, 'timing/data': 0.00019897287711501122, 'timing/model': 0.46431757789105177, 'learning_rate/action_model': 9.96062354322693e-05, 'learning_rate/action_query_proj': 9.96062354322693e-05, 'learning_rate/base': 2.4901558858067324e-05, 'epoch': 0.27}) +[2026-07-27 03:18:41,057][starVLA.training.train_starvla][INFO] - Step 2205, Loss: {'train/loss': 0.20126692950725555, 'train/grad_norm_pre_clip': 3.283952236175537, 'timing/data': 0.00019590184092521667, 'timing/model': 0.46642856393009424, 'learning_rate/action_model': 9.960237088530703e-05, 'learning_rate/action_query_proj': 9.960237088530703e-05, 'learning_rate/base': 2.4900592721326758e-05, 'epoch': 0.27}) +[2026-07-27 03:18:46,652][starVLA.training.train_starvla][INFO] - Step 2206, Loss: {'train/loss': 0.24701370298862457, 'train/grad_norm_pre_clip': 3.9944264888763428, 'timing/data': 0.00019331229850649834, 'timing/model': 0.46185881784185767, 'learning_rate/action_model': 9.959848754568261e-05, 'learning_rate/action_query_proj': 9.959848754568261e-05, 'learning_rate/base': 2.4899621886420652e-05, 'epoch': 0.27}) +[2026-07-27 03:18:52,257][starVLA.training.train_starvla][INFO] - Step 2207, Loss: {'train/loss': 0.3851924538612366, 'train/grad_norm_pre_clip': 6.865060806274414, 'timing/data': 0.00018566381186246872, 'timing/model': 0.46396465925499797, 'learning_rate/action_model': 9.959458541492912e-05, 'learning_rate/action_query_proj': 9.959458541492912e-05, 'learning_rate/base': 2.489864635373228e-05, 'epoch': 0.27}) +[2026-07-27 03:18:57,852][starVLA.training.train_starvla][INFO] - Step 2208, Loss: {'train/loss': 0.28619319200515747, 'train/grad_norm_pre_clip': 4.91138219833374, 'timing/data': 0.00018980307504534721, 'timing/model': 0.4631433440372348, 'learning_rate/action_model': 9.959066449458705e-05, 'learning_rate/action_query_proj': 9.959066449458705e-05, 'learning_rate/base': 2.4897666123646764e-05, 'epoch': 0.27}) +[2026-07-27 03:19:03,471][starVLA.training.train_starvla][INFO] - Step 2209, Loss: {'train/loss': 0.348938912153244, 'train/grad_norm_pre_clip': 4.995481014251709, 'timing/data': 0.00019420217722654343, 'timing/model': 0.4677561791613698, 'learning_rate/action_model': 9.958672478620435e-05, 'learning_rate/action_query_proj': 9.958672478620435e-05, 'learning_rate/base': 2.4896681196551088e-05, 'epoch': 0.27}) +[2026-07-27 03:19:09,068][starVLA.training.train_starvla][INFO] - Step 2210, Loss: {'train/loss': 0.32010093331336975, 'train/grad_norm_pre_clip': 3.4996073246002197, 'timing/data': 0.00019289599731564522, 'timing/model': 0.46194361289963126, 'learning_rate/action_model': 9.958276629133632e-05, 'learning_rate/action_query_proj': 9.958276629133632e-05, 'learning_rate/base': 2.489569157283408e-05, 'epoch': 0.27}) +[2026-07-27 03:19:14,664][starVLA.training.train_starvla][INFO] - Step 2211, Loss: {'train/loss': 0.20403741300106049, 'train/grad_norm_pre_clip': 3.732102632522583, 'timing/data': 0.00018996791914105415, 'timing/model': 0.4581730882637203, 'learning_rate/action_model': 9.957878901154573e-05, 'learning_rate/action_query_proj': 9.957878901154573e-05, 'learning_rate/base': 2.4894697252886432e-05, 'epoch': 0.27}) +[2026-07-27 03:19:20,568][starVLA.training.train_starvla][INFO] - Step 2212, Loss: {'train/loss': 0.2266998291015625, 'train/grad_norm_pre_clip': 3.494574785232544, 'timing/data': 0.00019067060202360153, 'timing/model': 0.4666413739323616, 'learning_rate/action_model': 9.957479294840275e-05, 'learning_rate/action_query_proj': 9.957479294840275e-05, 'learning_rate/base': 2.4893698237100686e-05, 'epoch': 0.27}) +[2026-07-27 03:19:26,162][starVLA.training.train_starvla][INFO] - Step 2213, Loss: {'train/loss': 0.23661832511425018, 'train/grad_norm_pre_clip': 4.298208236694336, 'timing/data': 0.00018565496429800987, 'timing/model': 0.46804818511009216, 'learning_rate/action_model': 9.957077810348493e-05, 'learning_rate/action_query_proj': 9.957077810348493e-05, 'learning_rate/base': 2.4892694525871234e-05, 'epoch': 0.27}) +[2026-07-27 03:19:31,781][starVLA.training.train_starvla][INFO] - Step 2214, Loss: {'train/loss': 0.17360323667526245, 'train/grad_norm_pre_clip': 3.677891731262207, 'timing/data': 0.00020063482224941254, 'timing/model': 0.46261103823781013, 'learning_rate/action_model': 9.95667444783773e-05, 'learning_rate/action_query_proj': 9.95667444783773e-05, 'learning_rate/base': 2.4891686119594326e-05, 'epoch': 0.27}) +[2026-07-27 03:19:37,395][starVLA.training.train_starvla][INFO] - Step 2215, Loss: {'train/loss': 0.17652767896652222, 'train/grad_norm_pre_clip': 3.6062610149383545, 'timing/data': 0.00018406705930829048, 'timing/model': 0.466402777004987, 'learning_rate/action_model': 9.956269207467226e-05, 'learning_rate/action_query_proj': 9.956269207467226e-05, 'learning_rate/base': 2.4890673018668066e-05, 'epoch': 0.27}) +[2026-07-27 03:19:42,996][starVLA.training.train_starvla][INFO] - Step 2216, Loss: {'train/loss': 0.3398360013961792, 'train/grad_norm_pre_clip': 3.864658832550049, 'timing/data': 0.00018835021182894707, 'timing/model': 0.46727029606699944, 'learning_rate/action_model': 9.955862089396965e-05, 'learning_rate/action_query_proj': 9.955862089396965e-05, 'learning_rate/base': 2.488965522349241e-05, 'epoch': 0.27}) +[2026-07-27 03:19:48,594][starVLA.training.train_starvla][INFO] - Step 2217, Loss: {'train/loss': 0.3222202956676483, 'train/grad_norm_pre_clip': 3.7060720920562744, 'timing/data': 0.000191486906260252, 'timing/model': 0.4580848589539528, 'learning_rate/action_model': 9.955453093787667e-05, 'learning_rate/action_query_proj': 9.955453093787667e-05, 'learning_rate/base': 2.488863273446917e-05, 'epoch': 0.27}) +[2026-07-27 03:19:54,206][starVLA.training.train_starvla][INFO] - Step 2218, Loss: {'train/loss': 0.24257145822048187, 'train/grad_norm_pre_clip': 4.17234468460083, 'timing/data': 0.0001864987425506115, 'timing/model': 0.4672657959163189, 'learning_rate/action_model': 9.955042220800802e-05, 'learning_rate/action_query_proj': 9.955042220800802e-05, 'learning_rate/base': 2.4887605552002006e-05, 'epoch': 0.27}) +[2026-07-27 03:19:59,768][starVLA.training.train_starvla][INFO] - Step 2219, Loss: {'train/loss': 0.19248202443122864, 'train/grad_norm_pre_clip': 3.0829873085021973, 'timing/data': 0.00019043823704123497, 'timing/model': 0.46339562721550465, 'learning_rate/action_model': 9.954629470598571e-05, 'learning_rate/action_query_proj': 9.954629470598571e-05, 'learning_rate/base': 2.488657367649643e-05, 'epoch': 0.27}) +[2026-07-27 03:20:05,355][starVLA.training.train_starvla][INFO] - Step 2220, Loss: {'train/loss': 0.26741474866867065, 'train/grad_norm_pre_clip': 3.9488277435302734, 'timing/data': 0.00018859189003705978, 'timing/model': 0.4618999590165913, 'learning_rate/action_model': 9.954214843343925e-05, 'learning_rate/action_query_proj': 9.954214843343925e-05, 'learning_rate/base': 2.4885537108359812e-05, 'epoch': 0.27}) +[2026-07-27 03:20:10,946][starVLA.training.train_starvla][INFO] - Step 2221, Loss: {'train/loss': 0.2737247049808502, 'train/grad_norm_pre_clip': 3.028815269470215, 'timing/data': 0.00019120704382658005, 'timing/model': 0.46330715669319034, 'learning_rate/action_model': 9.953798339200553e-05, 'learning_rate/action_query_proj': 9.953798339200553e-05, 'learning_rate/base': 2.4884495848001382e-05, 'epoch': 0.27}) +[2026-07-27 03:20:16,541][starVLA.training.train_starvla][INFO] - Step 2222, Loss: {'train/loss': 0.14692097902297974, 'train/grad_norm_pre_clip': 1.8941758871078491, 'timing/data': 0.0001998869702219963, 'timing/model': 0.4622822287492454, 'learning_rate/action_model': 9.95337995833288e-05, 'learning_rate/action_query_proj': 9.95337995833288e-05, 'learning_rate/base': 2.48834498958322e-05, 'epoch': 0.27}) +[2026-07-27 03:20:22,134][starVLA.training.train_starvla][INFO] - Step 2223, Loss: {'train/loss': 0.2960427403450012, 'train/grad_norm_pre_clip': 4.589844703674316, 'timing/data': 0.00018883869051933289, 'timing/model': 0.46229832619428635, 'learning_rate/action_model': 9.952959700906079e-05, 'learning_rate/action_query_proj': 9.952959700906079e-05, 'learning_rate/base': 2.4882399252265197e-05, 'epoch': 0.27}) +[2026-07-27 03:20:27,972][starVLA.training.train_starvla][INFO] - Step 2224, Loss: {'train/loss': 0.1506652981042862, 'train/grad_norm_pre_clip': 3.0736043453216553, 'timing/data': 0.00019058585166931152, 'timing/model': 0.4623874509707093, 'learning_rate/action_model': 9.952537567086062e-05, 'learning_rate/action_query_proj': 9.952537567086062e-05, 'learning_rate/base': 2.4881343917715156e-05, 'epoch': 0.27}) +[2026-07-27 03:20:33,580][starVLA.training.train_starvla][INFO] - Step 2225, Loss: {'train/loss': 0.24210083484649658, 'train/grad_norm_pre_clip': 3.3404064178466797, 'timing/data': 0.00018754880875349045, 'timing/model': 0.4642028701491654, 'learning_rate/action_model': 9.952113557039477e-05, 'learning_rate/action_query_proj': 9.952113557039477e-05, 'learning_rate/base': 2.488028389259869e-05, 'epoch': 0.27}) +[2026-07-27 03:20:39,230][starVLA.training.train_starvla][INFO] - Step 2226, Loss: {'train/loss': 0.2630731463432312, 'train/grad_norm_pre_clip': 3.143303155899048, 'timing/data': 0.00019002333283424377, 'timing/model': 0.4628776554018259, 'learning_rate/action_model': 9.95168767093372e-05, 'learning_rate/action_query_proj': 9.95168767093372e-05, 'learning_rate/base': 2.48792191773343e-05, 'epoch': 0.27}) +[2026-07-27 03:20:44,838][starVLA.training.train_starvla][INFO] - Step 2227, Loss: {'train/loss': 0.28059035539627075, 'train/grad_norm_pre_clip': 3.1173858642578125, 'timing/data': 0.00018926290795207024, 'timing/model': 0.46625961689278483, 'learning_rate/action_model': 9.951259908936921e-05, 'learning_rate/action_query_proj': 9.951259908936921e-05, 'learning_rate/base': 2.4878149772342303e-05, 'epoch': 0.27}) +[2026-07-27 03:20:50,438][starVLA.training.train_starvla][INFO] - Step 2228, Loss: {'train/loss': 0.14199352264404297, 'train/grad_norm_pre_clip': 2.3555710315704346, 'timing/data': 0.00018661702051758766, 'timing/model': 0.46499274391680956, 'learning_rate/action_model': 9.950830271217957e-05, 'learning_rate/action_query_proj': 9.950830271217957e-05, 'learning_rate/base': 2.487707567804489e-05, 'epoch': 0.27}) +[2026-07-27 03:20:56,044][starVLA.training.train_starvla][INFO] - Step 2229, Loss: {'train/loss': 0.1816282868385315, 'train/grad_norm_pre_clip': 3.482314109802246, 'timing/data': 0.00018841493874788284, 'timing/model': 0.46733022201806307, 'learning_rate/action_model': 9.95039875794644e-05, 'learning_rate/action_query_proj': 9.95039875794644e-05, 'learning_rate/base': 2.48759968948661e-05, 'epoch': 0.27}) +[2026-07-27 03:21:01,638][starVLA.training.train_starvla][INFO] - Step 2230, Loss: {'train/loss': 0.16101327538490295, 'train/grad_norm_pre_clip': 3.173042058944702, 'timing/data': 0.00018880004063248634, 'timing/model': 0.4580089170485735, 'learning_rate/action_model': 9.949965369292724e-05, 'learning_rate/action_query_proj': 9.949965369292724e-05, 'learning_rate/base': 2.487491342323181e-05, 'epoch': 0.27}) +[2026-07-27 03:21:07,246][starVLA.training.train_starvla][INFO] - Step 2231, Loss: {'train/loss': 0.21981438994407654, 'train/grad_norm_pre_clip': 3.7609424591064453, 'timing/data': 0.00019310228526592255, 'timing/model': 0.46102402871474624, 'learning_rate/action_model': 9.949530105427908e-05, 'learning_rate/action_query_proj': 9.949530105427908e-05, 'learning_rate/base': 2.487382526356977e-05, 'epoch': 0.27}) +[2026-07-27 03:21:12,834][starVLA.training.train_starvla][INFO] - Step 2232, Loss: {'train/loss': 0.2106638252735138, 'train/grad_norm_pre_clip': 3.519085645675659, 'timing/data': 0.0001913853920996189, 'timing/model': 0.4592494289390743, 'learning_rate/action_model': 9.949092966523822e-05, 'learning_rate/action_query_proj': 9.949092966523822e-05, 'learning_rate/base': 2.4872732416309556e-05, 'epoch': 0.27}) +[2026-07-27 03:21:18,426][starVLA.training.train_starvla][INFO] - Step 2233, Loss: {'train/loss': 0.2542301118373871, 'train/grad_norm_pre_clip': 2.424020767211914, 'timing/data': 0.00018691876903176308, 'timing/model': 0.45579725597053766, 'learning_rate/action_model': 9.948653952753044e-05, 'learning_rate/action_query_proj': 9.948653952753044e-05, 'learning_rate/base': 2.487163488188261e-05, 'epoch': 0.27}) +[2026-07-27 03:21:24,049][starVLA.training.train_starvla][INFO] - Step 2234, Loss: {'train/loss': 0.12158455699682236, 'train/grad_norm_pre_clip': 3.2440645694732666, 'timing/data': 0.00018532434478402138, 'timing/model': 0.4618927170522511, 'learning_rate/action_model': 9.948213064288892e-05, 'learning_rate/action_query_proj': 9.948213064288892e-05, 'learning_rate/base': 2.487053266072223e-05, 'epoch': 0.27}) +[2026-07-27 03:21:29,663][starVLA.training.train_starvla][INFO] - Step 2235, Loss: {'train/loss': 0.12220703065395355, 'train/grad_norm_pre_clip': 3.261909246444702, 'timing/data': 0.00019614584743976593, 'timing/model': 0.46505898609757423, 'learning_rate/action_model': 9.947770301305417e-05, 'learning_rate/action_query_proj': 9.947770301305417e-05, 'learning_rate/base': 2.486942575326354e-05, 'epoch': 0.27}) +[2026-07-27 03:21:35,279][starVLA.training.train_starvla][INFO] - Step 2236, Loss: {'train/loss': 0.2811441123485565, 'train/grad_norm_pre_clip': 4.544694900512695, 'timing/data': 0.00018957164138555527, 'timing/model': 0.46285896468907595, 'learning_rate/action_model': 9.947325663977418e-05, 'learning_rate/action_query_proj': 9.947325663977418e-05, 'learning_rate/base': 2.4868314159943546e-05, 'epoch': 0.27}) +[2026-07-27 03:21:40,890][starVLA.training.train_starvla][INFO] - Step 2237, Loss: {'train/loss': 0.2919125556945801, 'train/grad_norm_pre_clip': 4.109127521514893, 'timing/data': 0.0002032080665230751, 'timing/model': 0.4656901489943266, 'learning_rate/action_model': 9.946879152480431e-05, 'learning_rate/action_query_proj': 9.946879152480431e-05, 'learning_rate/base': 2.4867197881201077e-05, 'epoch': 0.27}) +[2026-07-27 03:21:46,513][starVLA.training.train_starvla][INFO] - Step 2238, Loss: {'train/loss': 0.2486453354358673, 'train/grad_norm_pre_clip': 4.224859714508057, 'timing/data': 0.0002067871391773224, 'timing/model': 0.4659418221563101, 'learning_rate/action_model': 9.946430766990729e-05, 'learning_rate/action_query_proj': 9.946430766990729e-05, 'learning_rate/base': 2.4866076917476822e-05, 'epoch': 0.27}) +[2026-07-27 03:21:52,113][starVLA.training.train_starvla][INFO] - Step 2239, Loss: {'train/loss': 0.27758488059043884, 'train/grad_norm_pre_clip': 5.246476650238037, 'timing/data': 0.00019345898181200027, 'timing/model': 0.45767213264480233, 'learning_rate/action_model': 9.94598050768533e-05, 'learning_rate/action_query_proj': 9.94598050768533e-05, 'learning_rate/base': 2.4864951269213325e-05, 'epoch': 0.27}) +[2026-07-27 03:21:57,733][starVLA.training.train_starvla][INFO] - Step 2240, Loss: {'train/loss': 0.17284390330314636, 'train/grad_norm_pre_clip': 3.331005811691284, 'timing/data': 0.00020242901518940926, 'timing/model': 0.46276495419442654, 'learning_rate/action_model': 9.945528374741986e-05, 'learning_rate/action_query_proj': 9.945528374741986e-05, 'learning_rate/base': 2.4863820936854966e-05, 'epoch': 0.27}) +[2026-07-27 03:22:03,359][starVLA.training.train_starvla][INFO] - Step 2241, Loss: {'train/loss': 0.26441553235054016, 'train/grad_norm_pre_clip': 5.0065836906433105, 'timing/data': 0.0001887069083750248, 'timing/model': 0.4622055487707257, 'learning_rate/action_model': 9.945074368339197e-05, 'learning_rate/action_query_proj': 9.945074368339197e-05, 'learning_rate/base': 2.4862685920847993e-05, 'epoch': 0.27}) +[2026-07-27 03:22:08,967][starVLA.training.train_starvla][INFO] - Step 2242, Loss: {'train/loss': 0.26816028356552124, 'train/grad_norm_pre_clip': 3.4982693195343018, 'timing/data': 0.0001902407966554165, 'timing/model': 0.46710856491699815, 'learning_rate/action_model': 9.944618488656196e-05, 'learning_rate/action_query_proj': 9.944618488656196e-05, 'learning_rate/base': 2.486154622164049e-05, 'epoch': 0.27}) +[2026-07-27 03:22:14,580][starVLA.training.train_starvla][INFO] - Step 2243, Loss: {'train/loss': 0.16739250719547272, 'train/grad_norm_pre_clip': 3.1934614181518555, 'timing/data': 0.00019087782129645348, 'timing/model': 0.46707711881026626, 'learning_rate/action_model': 9.944160735872952e-05, 'learning_rate/action_query_proj': 9.944160735872952e-05, 'learning_rate/base': 2.486040183968238e-05, 'epoch': 0.27}) +[2026-07-27 03:22:20,201][starVLA.training.train_starvla][INFO] - Step 2244, Loss: {'train/loss': 0.19326059520244598, 'train/grad_norm_pre_clip': 3.6636173725128174, 'timing/data': 0.00018560606986284256, 'timing/model': 0.4673977307975292, 'learning_rate/action_model': 9.943701110170186e-05, 'learning_rate/action_query_proj': 9.943701110170186e-05, 'learning_rate/base': 2.4859252775425466e-05, 'epoch': 0.27}) +[2026-07-27 03:22:25,809][starVLA.training.train_starvla][INFO] - Step 2245, Loss: {'train/loss': 0.29597944021224976, 'train/grad_norm_pre_clip': 4.57321310043335, 'timing/data': 0.00019210530444979668, 'timing/model': 0.4569066413678229, 'learning_rate/action_model': 9.943239611729349e-05, 'learning_rate/action_query_proj': 9.943239611729349e-05, 'learning_rate/base': 2.485809902932337e-05, 'epoch': 0.27}) +[2026-07-27 03:22:31,414][starVLA.training.train_starvla][INFO] - Step 2246, Loss: {'train/loss': 0.1395130306482315, 'train/grad_norm_pre_clip': 2.683138847351074, 'timing/data': 0.00019109435379505157, 'timing/model': 0.4668713826686144, 'learning_rate/action_model': 9.942776240732626e-05, 'learning_rate/action_query_proj': 9.942776240732626e-05, 'learning_rate/base': 2.4856940601831565e-05, 'epoch': 0.27}) +[2026-07-27 03:22:37,032][starVLA.training.train_starvla][INFO] - Step 2247, Loss: {'train/loss': 0.20158958435058594, 'train/grad_norm_pre_clip': 3.7307469844818115, 'timing/data': 0.0001909038983285427, 'timing/model': 0.46680998615920544, 'learning_rate/action_model': 9.942310997362958e-05, 'learning_rate/action_query_proj': 9.942310997362958e-05, 'learning_rate/base': 2.4855777493407395e-05, 'epoch': 0.27}) +[2026-07-27 03:22:42,685][starVLA.training.train_starvla][INFO] - Step 2248, Loss: {'train/loss': 0.18453240394592285, 'train/grad_norm_pre_clip': 3.4886929988861084, 'timing/data': 0.00018693506717681885, 'timing/model': 0.46334198536351323, 'learning_rate/action_model': 9.941843881804011e-05, 'learning_rate/action_query_proj': 9.941843881804011e-05, 'learning_rate/base': 2.4854609704510027e-05, 'epoch': 0.27}) +[2026-07-27 03:22:48,333][starVLA.training.train_starvla][INFO] - Step 2249, Loss: {'train/loss': 0.2960679531097412, 'train/grad_norm_pre_clip': 4.525446891784668, 'timing/data': 0.00019095884636044502, 'timing/model': 0.4657949358224869, 'learning_rate/action_model': 9.941374894240196e-05, 'learning_rate/action_query_proj': 9.941374894240196e-05, 'learning_rate/base': 2.485343723560049e-05, 'epoch': 0.27}) +[2026-07-27 03:22:53,971][starVLA.training.train_starvla][INFO] - Step 2250, Loss: {'train/loss': 0.40712466835975647, 'train/grad_norm_pre_clip': 4.594310283660889, 'timing/data': 0.00022398727014660835, 'timing/model': 0.46371916169300675, 'learning_rate/action_model': 9.940904034856662e-05, 'learning_rate/action_query_proj': 9.940904034856662e-05, 'learning_rate/base': 2.4852260087141655e-05, 'epoch': 0.27}) +[2026-07-27 03:22:59,588][starVLA.training.train_starvla][INFO] - Step 2251, Loss: {'train/loss': 0.29253044724464417, 'train/grad_norm_pre_clip': 4.4827375411987305, 'timing/data': 0.00019060680642724037, 'timing/model': 0.46484976075589657, 'learning_rate/action_model': 9.940431303839296e-05, 'learning_rate/action_query_proj': 9.940431303839296e-05, 'learning_rate/base': 2.485107825959824e-05, 'epoch': 0.27}) +[2026-07-27 03:23:05,223][starVLA.training.train_starvla][INFO] - Step 2252, Loss: {'train/loss': 0.27904731035232544, 'train/grad_norm_pre_clip': 4.387750625610352, 'timing/data': 0.00018919305875897408, 'timing/model': 0.45940787298604846, 'learning_rate/action_model': 9.939956701374724e-05, 'learning_rate/action_query_proj': 9.939956701374724e-05, 'learning_rate/base': 2.484989175343681e-05, 'epoch': 0.27}) +[2026-07-27 03:23:11,097][starVLA.training.train_starvla][INFO] - Step 2253, Loss: {'train/loss': 0.2128877490758896, 'train/grad_norm_pre_clip': 4.492863178253174, 'timing/data': 0.0001938152126967907, 'timing/model': 0.4592828298918903, 'learning_rate/action_model': 9.939480227650314e-05, 'learning_rate/action_query_proj': 9.939480227650314e-05, 'learning_rate/base': 2.4848700569125786e-05, 'epoch': 0.27}) +[2026-07-27 03:23:16,718][starVLA.training.train_starvla][INFO] - Step 2254, Loss: {'train/loss': 0.32564491033554077, 'train/grad_norm_pre_clip': 4.55303430557251, 'timing/data': 0.00018821703270077705, 'timing/model': 0.46906341426074505, 'learning_rate/action_model': 9.93900188285417e-05, 'learning_rate/action_query_proj': 9.93900188285417e-05, 'learning_rate/base': 2.4847504707135424e-05, 'epoch': 0.27}) +[2026-07-27 03:23:22,341][starVLA.training.train_starvla][INFO] - Step 2255, Loss: {'train/loss': 0.24613308906555176, 'train/grad_norm_pre_clip': 3.3231937885284424, 'timing/data': 0.00025221891701221466, 'timing/model': 0.46396002639085054, 'learning_rate/action_model': 9.938521667175133e-05, 'learning_rate/action_query_proj': 9.938521667175133e-05, 'learning_rate/base': 2.484630416793783e-05, 'epoch': 0.27}) +[2026-07-27 03:23:27,979][starVLA.training.train_starvla][INFO] - Step 2256, Loss: {'train/loss': 0.19093544781208038, 'train/grad_norm_pre_clip': 4.190287113189697, 'timing/data': 0.00019218679517507553, 'timing/model': 0.46263219229876995, 'learning_rate/action_model': 9.938039580802785e-05, 'learning_rate/action_query_proj': 9.938039580802785e-05, 'learning_rate/base': 2.4845098952006962e-05, 'epoch': 0.27}) +[2026-07-27 03:23:33,584][starVLA.training.train_starvla][INFO] - Step 2257, Loss: {'train/loss': 0.2794482707977295, 'train/grad_norm_pre_clip': 5.9566426277160645, 'timing/data': 0.00018977094441652298, 'timing/model': 0.46228569792583585, 'learning_rate/action_model': 9.937555623927447e-05, 'learning_rate/action_query_proj': 9.937555623927447e-05, 'learning_rate/base': 2.4843889059818616e-05, 'epoch': 0.27}) +[2026-07-27 03:23:39,194][starVLA.training.train_starvla][INFO] - Step 2258, Loss: {'train/loss': 0.25358065962791443, 'train/grad_norm_pre_clip': 3.992607355117798, 'timing/data': 0.0002014380879700184, 'timing/model': 0.4671351849101484, 'learning_rate/action_model': 9.937069796740176e-05, 'learning_rate/action_query_proj': 9.937069796740176e-05, 'learning_rate/base': 2.484267449185044e-05, 'epoch': 0.27}) +[2026-07-27 03:23:44,814][starVLA.training.train_starvla][INFO] - Step 2259, Loss: {'train/loss': 0.2159493863582611, 'train/grad_norm_pre_clip': 3.3837151527404785, 'timing/data': 0.0001962520182132721, 'timing/model': 0.4666077080182731, 'learning_rate/action_model': 9.936582099432772e-05, 'learning_rate/action_query_proj': 9.936582099432772e-05, 'learning_rate/base': 2.484145524858193e-05, 'epoch': 0.27}) +[2026-07-27 03:23:50,433][starVLA.training.train_starvla][INFO] - Step 2260, Loss: {'train/loss': 0.3506486713886261, 'train/grad_norm_pre_clip': 5.911502361297607, 'timing/data': 0.00019537797197699547, 'timing/model': 0.46599604515358806, 'learning_rate/action_model': 9.936092532197766e-05, 'learning_rate/action_query_proj': 9.936092532197766e-05, 'learning_rate/base': 2.4840231330494415e-05, 'epoch': 0.27}) +[2026-07-27 03:23:56,032][starVLA.training.train_starvla][INFO] - Step 2261, Loss: {'train/loss': 0.315119206905365, 'train/grad_norm_pre_clip': 4.4805121421813965, 'timing/data': 0.0001891050487756729, 'timing/model': 0.46438561379909515, 'learning_rate/action_model': 9.935601095228436e-05, 'learning_rate/action_query_proj': 9.935601095228436e-05, 'learning_rate/base': 2.483900273807109e-05, 'epoch': 0.27}) +[2026-07-27 03:24:01,908][starVLA.training.train_starvla][INFO] - Step 2262, Loss: {'train/loss': 0.28536325693130493, 'train/grad_norm_pre_clip': 3.4392764568328857, 'timing/data': 0.0001930566504597664, 'timing/model': 0.46755049377679825, 'learning_rate/action_model': 9.935107788718789e-05, 'learning_rate/action_query_proj': 9.935107788718789e-05, 'learning_rate/base': 2.4837769471796972e-05, 'epoch': 0.27}) +[2026-07-27 03:24:07,520][starVLA.training.train_starvla][INFO] - Step 2263, Loss: {'train/loss': 0.18733610212802887, 'train/grad_norm_pre_clip': 4.449254035949707, 'timing/data': 0.00019121216610074043, 'timing/model': 0.45633599907159805, 'learning_rate/action_model': 9.934612612863578e-05, 'learning_rate/action_query_proj': 9.934612612863578e-05, 'learning_rate/base': 2.4836531532158945e-05, 'epoch': 0.27}) +[2026-07-27 03:24:13,417][starVLA.training.train_starvla][INFO] - Step 2264, Loss: {'train/loss': 0.16593267023563385, 'train/grad_norm_pre_clip': 3.0090506076812744, 'timing/data': 0.00019658636301755905, 'timing/model': 0.4575049509294331, 'learning_rate/action_model': 9.934115567858288e-05, 'learning_rate/action_query_proj': 9.934115567858288e-05, 'learning_rate/base': 2.483528891964572e-05, 'epoch': 0.27}) +[2026-07-27 03:24:19,271][starVLA.training.train_starvla][INFO] - Step 2265, Loss: {'train/loss': 0.23043063282966614, 'train/grad_norm_pre_clip': 4.262088298797607, 'timing/data': 0.00018626125529408455, 'timing/model': 0.46437060460448265, 'learning_rate/action_model': 9.933616653899147e-05, 'learning_rate/action_query_proj': 9.933616653899147e-05, 'learning_rate/base': 2.4834041634747868e-05, 'epoch': 0.27}) +[2026-07-27 03:24:24,894][starVLA.training.train_starvla][INFO] - Step 2266, Loss: {'train/loss': 0.14677569270133972, 'train/grad_norm_pre_clip': 3.0138533115386963, 'timing/data': 0.00019154231995344162, 'timing/model': 0.46421994687989354, 'learning_rate/action_model': 9.933115871183117e-05, 'learning_rate/action_query_proj': 9.933115871183117e-05, 'learning_rate/base': 2.4832789677957792e-05, 'epoch': 0.27}) +[2026-07-27 03:24:30,538][starVLA.training.train_starvla][INFO] - Step 2267, Loss: {'train/loss': 0.1898641139268875, 'train/grad_norm_pre_clip': 3.5510685443878174, 'timing/data': 0.00018966617062687874, 'timing/model': 0.47464111214503646, 'learning_rate/action_model': 9.932613219907899e-05, 'learning_rate/action_query_proj': 9.932613219907899e-05, 'learning_rate/base': 2.4831533049769746e-05, 'epoch': 0.28}) +[2026-07-27 03:24:36,179][starVLA.training.train_starvla][INFO] - Step 2268, Loss: {'train/loss': 0.23532544076442719, 'train/grad_norm_pre_clip': 3.6650118827819824, 'timing/data': 0.0001879427582025528, 'timing/model': 0.4664428438991308, 'learning_rate/action_model': 9.93210870027193e-05, 'learning_rate/action_query_proj': 9.93210870027193e-05, 'learning_rate/base': 2.4830271750679825e-05, 'epoch': 0.28}) +[2026-07-27 03:24:41,796][starVLA.training.train_starvla][INFO] - Step 2269, Loss: {'train/loss': 0.2148975282907486, 'train/grad_norm_pre_clip': 4.899641036987305, 'timing/data': 0.00018823007121682167, 'timing/model': 0.4574937750585377, 'learning_rate/action_model': 9.931602312474391e-05, 'learning_rate/action_query_proj': 9.931602312474391e-05, 'learning_rate/base': 2.4829005781185977e-05, 'epoch': 0.28}) +[2026-07-27 03:24:47,417][starVLA.training.train_starvla][INFO] - Step 2270, Loss: {'train/loss': 0.2622995972633362, 'train/grad_norm_pre_clip': 4.835476875305176, 'timing/data': 0.00018652621656656265, 'timing/model': 0.46839627996087074, 'learning_rate/action_model': 9.931094056715191e-05, 'learning_rate/action_query_proj': 9.931094056715191e-05, 'learning_rate/base': 2.4827735141787978e-05, 'epoch': 0.28}) +[2026-07-27 03:24:53,007][starVLA.training.train_starvla][INFO] - Step 2271, Loss: {'train/loss': 0.3732190430164337, 'train/grad_norm_pre_clip': 5.622563362121582, 'timing/data': 0.00018727779388427734, 'timing/model': 0.4578838590532541, 'learning_rate/action_model': 9.930583933194983e-05, 'learning_rate/action_query_proj': 9.930583933194983e-05, 'learning_rate/base': 2.482645983298746e-05, 'epoch': 0.28}) +[2026-07-27 03:24:58,613][starVLA.training.train_starvla][INFO] - Step 2272, Loss: {'train/loss': 0.238499253988266, 'train/grad_norm_pre_clip': 3.50724720954895, 'timing/data': 0.00018839910626411438, 'timing/model': 0.46380172623321414, 'learning_rate/action_model': 9.930071942115159e-05, 'learning_rate/action_query_proj': 9.930071942115159e-05, 'learning_rate/base': 2.4825179855287897e-05, 'epoch': 0.28}) +[2026-07-27 03:25:04,228][starVLA.training.train_starvla][INFO] - Step 2273, Loss: {'train/loss': 0.20396645367145538, 'train/grad_norm_pre_clip': 2.9714667797088623, 'timing/data': 0.00019913725554943085, 'timing/model': 0.466630008071661, 'learning_rate/action_model': 9.92955808367784e-05, 'learning_rate/action_query_proj': 9.92955808367784e-05, 'learning_rate/base': 2.48238952091946e-05, 'epoch': 0.28}) +[2026-07-27 03:25:09,835][starVLA.training.train_starvla][INFO] - Step 2274, Loss: {'train/loss': 0.2435978651046753, 'train/grad_norm_pre_clip': 3.227418899536133, 'timing/data': 0.00020785629749298096, 'timing/model': 0.4670214750804007, 'learning_rate/action_model': 9.929042358085894e-05, 'learning_rate/action_query_proj': 9.929042358085894e-05, 'learning_rate/base': 2.4822605895214735e-05, 'epoch': 0.28}) +[2026-07-27 03:25:15,435][starVLA.training.train_starvla][INFO] - Step 2275, Loss: {'train/loss': 0.28820109367370605, 'train/grad_norm_pre_clip': 3.6949615478515625, 'timing/data': 0.00036581000313162804, 'timing/model': 0.46554419584572315, 'learning_rate/action_model': 9.928524765542915e-05, 'learning_rate/action_query_proj': 9.928524765542915e-05, 'learning_rate/base': 2.4821311913857286e-05, 'epoch': 0.28}) +[2026-07-27 03:25:21,085][starVLA.training.train_starvla][INFO] - Step 2276, Loss: {'train/loss': 0.19861340522766113, 'train/grad_norm_pre_clip': 3.195754289627075, 'timing/data': 0.00019910000264644623, 'timing/model': 0.46969708474352956, 'learning_rate/action_model': 9.928005306253245e-05, 'learning_rate/action_query_proj': 9.928005306253245e-05, 'learning_rate/base': 2.4820013265633112e-05, 'epoch': 0.28}) +[2026-07-27 03:25:26,732][starVLA.training.train_starvla][INFO] - Step 2277, Loss: {'train/loss': 0.16427302360534668, 'train/grad_norm_pre_clip': 5.259099006652832, 'timing/data': 0.00019828276708722115, 'timing/model': 0.4583347109146416, 'learning_rate/action_model': 9.927483980421959e-05, 'learning_rate/action_query_proj': 9.927483980421959e-05, 'learning_rate/base': 2.4818709951054896e-05, 'epoch': 0.28}) +[2026-07-27 03:25:32,339][starVLA.training.train_starvla][INFO] - Step 2278, Loss: {'train/loss': 0.3887770175933838, 'train/grad_norm_pre_clip': 6.435734748840332, 'timing/data': 0.00019655795767903328, 'timing/model': 0.4678192650899291, 'learning_rate/action_model': 9.926960788254865e-05, 'learning_rate/action_query_proj': 9.926960788254865e-05, 'learning_rate/base': 2.4817401970637162e-05, 'epoch': 0.28}) +[2026-07-27 03:25:37,948][starVLA.training.train_starvla][INFO] - Step 2279, Loss: {'train/loss': 0.3679119646549225, 'train/grad_norm_pre_clip': 5.911397457122803, 'timing/data': 0.00019394885748624802, 'timing/model': 0.46373689407482743, 'learning_rate/action_model': 9.926435729958512e-05, 'learning_rate/action_query_proj': 9.926435729958512e-05, 'learning_rate/base': 2.481608932489628e-05, 'epoch': 0.28}) +[2026-07-27 03:25:43,546][starVLA.training.train_starvla][INFO] - Step 2280, Loss: {'train/loss': 0.3003896474838257, 'train/grad_norm_pre_clip': 4.358699321746826, 'timing/data': 0.00019403593614697456, 'timing/model': 0.4643993489444256, 'learning_rate/action_model': 9.925908805740186e-05, 'learning_rate/action_query_proj': 9.925908805740186e-05, 'learning_rate/base': 2.4814772014350464e-05, 'epoch': 0.28}) +[2026-07-27 03:25:49,153][starVLA.training.train_starvla][INFO] - Step 2281, Loss: {'train/loss': 0.3305360674858093, 'train/grad_norm_pre_clip': 4.599392890930176, 'timing/data': 0.0001926911063492298, 'timing/model': 0.4569316660054028, 'learning_rate/action_model': 9.925380015807908e-05, 'learning_rate/action_query_proj': 9.925380015807908e-05, 'learning_rate/base': 2.481345003951977e-05, 'epoch': 0.28}) +[2026-07-27 03:25:54,765][starVLA.training.train_starvla][INFO] - Step 2282, Loss: {'train/loss': 0.16089887917041779, 'train/grad_norm_pre_clip': 3.4811413288116455, 'timing/data': 0.00018943427130579948, 'timing/model': 0.4661964876577258, 'learning_rate/action_model': 9.924849360370433e-05, 'learning_rate/action_query_proj': 9.924849360370433e-05, 'learning_rate/base': 2.4812123400926083e-05, 'epoch': 0.28}) +[2026-07-27 03:26:00,375][starVLA.training.train_starvla][INFO] - Step 2283, Loss: {'train/loss': 0.1893719881772995, 'train/grad_norm_pre_clip': 4.453360080718994, 'timing/data': 0.00018814485520124435, 'timing/model': 0.4671088410541415, 'learning_rate/action_model': 9.924316839637261e-05, 'learning_rate/action_query_proj': 9.924316839637261e-05, 'learning_rate/base': 2.4810792099093152e-05, 'epoch': 0.28}) +[2026-07-27 03:26:05,987][starVLA.training.train_starvla][INFO] - Step 2284, Loss: {'train/loss': 0.2324550598859787, 'train/grad_norm_pre_clip': 4.070430278778076, 'timing/data': 0.0001903320662677288, 'timing/model': 0.4633654928766191, 'learning_rate/action_model': 9.923782453818617e-05, 'learning_rate/action_query_proj': 9.923782453818617e-05, 'learning_rate/base': 2.4809456134546542e-05, 'epoch': 0.28}) +[2026-07-27 03:26:11,565][starVLA.training.train_starvla][INFO] - Step 2285, Loss: {'train/loss': 0.28090235590934753, 'train/grad_norm_pre_clip': 5.289968013763428, 'timing/data': 0.00019042659550905228, 'timing/model': 0.46788819320499897, 'learning_rate/action_model': 9.923246203125471e-05, 'learning_rate/action_query_proj': 9.923246203125471e-05, 'learning_rate/base': 2.480811550781368e-05, 'epoch': 0.28}) +[2026-07-27 03:26:17,170][starVLA.training.train_starvla][INFO] - Step 2286, Loss: {'train/loss': 0.33398428559303284, 'train/grad_norm_pre_clip': 3.3942055702209473, 'timing/data': 0.00019037816673517227, 'timing/model': 0.4659490492194891, 'learning_rate/action_model': 9.922708087769526e-05, 'learning_rate/action_query_proj': 9.922708087769526e-05, 'learning_rate/base': 2.4806770219423816e-05, 'epoch': 0.28}) +[2026-07-27 03:26:22,766][starVLA.training.train_starvla][INFO] - Step 2287, Loss: {'train/loss': 0.21699579060077667, 'train/grad_norm_pre_clip': 2.569662570953369, 'timing/data': 0.00018926477059721947, 'timing/model': 0.4635943239554763, 'learning_rate/action_model': 9.922168107963222e-05, 'learning_rate/action_query_proj': 9.922168107963222e-05, 'learning_rate/base': 2.4805420269908054e-05, 'epoch': 0.28}) +[2026-07-27 03:26:28,362][starVLA.training.train_starvla][INFO] - Step 2288, Loss: {'train/loss': 0.24616491794586182, 'train/grad_norm_pre_clip': 3.001389980316162, 'timing/data': 0.0001873420551419258, 'timing/model': 0.4621118432842195, 'learning_rate/action_model': 9.921626263919733e-05, 'learning_rate/action_query_proj': 9.921626263919733e-05, 'learning_rate/base': 2.4804065659799333e-05, 'epoch': 0.28}) +[2026-07-27 03:26:33,955][starVLA.training.train_starvla][INFO] - Step 2289, Loss: {'train/loss': 0.1688632369041443, 'train/grad_norm_pre_clip': 4.005153179168701, 'timing/data': 0.000187611673027277, 'timing/model': 0.46175488410517573, 'learning_rate/action_model': 9.921082555852971e-05, 'learning_rate/action_query_proj': 9.921082555852971e-05, 'learning_rate/base': 2.4802706389632427e-05, 'epoch': 0.28}) +[2026-07-27 03:26:39,558][starVLA.training.train_starvla][INFO] - Step 2290, Loss: {'train/loss': 0.16776959598064423, 'train/grad_norm_pre_clip': 3.041289806365967, 'timing/data': 0.000185301061719656, 'timing/model': 0.46179875591769814, 'learning_rate/action_model': 9.920536983977583e-05, 'learning_rate/action_query_proj': 9.920536983977583e-05, 'learning_rate/base': 2.4801342459943956e-05, 'epoch': 0.28}) +[2026-07-27 03:26:45,160][starVLA.training.train_starvla][INFO] - Step 2291, Loss: {'train/loss': 0.19514238834381104, 'train/grad_norm_pre_clip': 2.8111228942871094, 'timing/data': 0.00019000796601176262, 'timing/model': 0.45637284126132727, 'learning_rate/action_model': 9.919989548508953e-05, 'learning_rate/action_query_proj': 9.919989548508953e-05, 'learning_rate/base': 2.4799973871272383e-05, 'epoch': 0.28}) +[2026-07-27 03:26:50,785][starVLA.training.train_starvla][INFO] - Step 2292, Loss: {'train/loss': 0.24158240854740143, 'train/grad_norm_pre_clip': 4.164824485778809, 'timing/data': 0.00018938584253191948, 'timing/model': 0.46532816905528307, 'learning_rate/action_model': 9.919440249663198e-05, 'learning_rate/action_query_proj': 9.919440249663198e-05, 'learning_rate/base': 2.4798600624157996e-05, 'epoch': 0.28}) +[2026-07-27 03:26:56,676][starVLA.training.train_starvla][INFO] - Step 2293, Loss: {'train/loss': 0.31279999017715454, 'train/grad_norm_pre_clip': 5.474593162536621, 'timing/data': 0.0001943442039191723, 'timing/model': 0.4616644140332937, 'learning_rate/action_model': 9.918889087657177e-05, 'learning_rate/action_query_proj': 9.918889087657177e-05, 'learning_rate/base': 2.4797222719142943e-05, 'epoch': 0.28}) +[2026-07-27 03:27:02,541][starVLA.training.train_starvla][INFO] - Step 2294, Loss: {'train/loss': 0.37243399024009705, 'train/grad_norm_pre_clip': 4.527698040008545, 'timing/data': 0.00018747104331851006, 'timing/model': 0.4682074370793998, 'learning_rate/action_model': 9.918336062708476e-05, 'learning_rate/action_query_proj': 9.918336062708476e-05, 'learning_rate/base': 2.479584015677119e-05, 'epoch': 0.28}) +[2026-07-27 03:27:08,162][starVLA.training.train_starvla][INFO] - Step 2295, Loss: {'train/loss': 0.20011752843856812, 'train/grad_norm_pre_clip': 3.605135202407837, 'timing/data': 0.00019661709666252136, 'timing/model': 0.4618043899536133, 'learning_rate/action_model': 9.91778117503542e-05, 'learning_rate/action_query_proj': 9.91778117503542e-05, 'learning_rate/base': 2.479445293758855e-05, 'epoch': 0.28}) +[2026-07-27 03:27:13,795][starVLA.training.train_starvla][INFO] - Step 2296, Loss: {'train/loss': 0.22569270431995392, 'train/grad_norm_pre_clip': 3.4456121921539307, 'timing/data': 0.00018683681264519691, 'timing/model': 0.46383632998913527, 'learning_rate/action_model': 9.917224424857073e-05, 'learning_rate/action_query_proj': 9.917224424857073e-05, 'learning_rate/base': 2.4793061062142682e-05, 'epoch': 0.28}) +[2026-07-27 03:27:19,418][starVLA.training.train_starvla][INFO] - Step 2297, Loss: {'train/loss': 0.25750190019607544, 'train/grad_norm_pre_clip': 3.69659686088562, 'timing/data': 0.0001867162063717842, 'timing/model': 0.46707315370440483, 'learning_rate/action_model': 9.916665812393228e-05, 'learning_rate/action_query_proj': 9.916665812393228e-05, 'learning_rate/base': 2.479166453098307e-05, 'epoch': 0.28}) +[2026-07-27 03:27:25,051][starVLA.training.train_starvla][INFO] - Step 2298, Loss: {'train/loss': 0.3283126950263977, 'train/grad_norm_pre_clip': 5.1020402908325195, 'timing/data': 0.00018870597705245018, 'timing/model': 0.4628740409389138, 'learning_rate/action_model': 9.916105337864419e-05, 'learning_rate/action_query_proj': 9.916105337864419e-05, 'learning_rate/base': 2.4790263344661048e-05, 'epoch': 0.28}) +[2026-07-27 03:27:30,677][starVLA.training.train_starvla][INFO] - Step 2299, Loss: {'train/loss': 0.19332672655582428, 'train/grad_norm_pre_clip': 4.0628981590271, 'timing/data': 0.00018748827278614044, 'timing/model': 0.45920783607289195, 'learning_rate/action_model': 9.915543001491912e-05, 'learning_rate/action_query_proj': 9.915543001491912e-05, 'learning_rate/base': 2.478885750372978e-05, 'epoch': 0.28}) +[2026-07-27 03:27:36,301][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2300 +[2026-07-27 03:27:36,302][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2300 +[2026-07-27 03:27:36,302][starVLA.training.train_starvla][INFO] - Step 2300, Loss: {'train/loss': 0.305708646774292, 'train/grad_norm_pre_clip': 5.191511631011963, 'timing/data': 0.00018693506717681885, 'timing/model': 0.4623767379671335, 'learning_rate/action_model': 9.914978803497707e-05, 'learning_rate/action_query_proj': 9.914978803497707e-05, 'learning_rate/base': 2.4787447008744268e-05, 'epoch': 0.28}) +[2026-07-27 03:27:41,910][starVLA.training.train_starvla][INFO] - Step 2301, Loss: {'train/loss': 0.25702691078186035, 'train/grad_norm_pre_clip': 2.9012908935546875, 'timing/data': 0.00019580498337745667, 'timing/model': 0.457291005179286, 'learning_rate/action_model': 9.91441274410454e-05, 'learning_rate/action_query_proj': 9.91441274410454e-05, 'learning_rate/base': 2.478603186026135e-05, 'epoch': 0.28}) +[2026-07-27 03:27:47,530][starVLA.training.train_starvla][INFO] - Step 2302, Loss: {'train/loss': 0.20330487191677094, 'train/grad_norm_pre_clip': 3.629068613052368, 'timing/data': 0.00019216490909457207, 'timing/model': 0.4668382368981838, 'learning_rate/action_model': 9.913844823535884e-05, 'learning_rate/action_query_proj': 9.913844823535884e-05, 'learning_rate/base': 2.478461205883971e-05, 'epoch': 0.28}) +[2026-07-27 03:27:53,140][starVLA.training.train_starvla][INFO] - Step 2303, Loss: {'train/loss': 0.2203073501586914, 'train/grad_norm_pre_clip': 2.6505930423736572, 'timing/data': 0.0001884368248283863, 'timing/model': 0.46474097296595573, 'learning_rate/action_model': 9.913275042015944e-05, 'learning_rate/action_query_proj': 9.913275042015944e-05, 'learning_rate/base': 2.478318760503986e-05, 'epoch': 0.28}) +[2026-07-27 03:27:58,756][starVLA.training.train_starvla][INFO] - Step 2304, Loss: {'train/loss': 0.24316921830177307, 'train/grad_norm_pre_clip': 3.644693374633789, 'timing/data': 0.00018481677398085594, 'timing/model': 0.4627858907915652, 'learning_rate/action_model': 9.912703399769664e-05, 'learning_rate/action_query_proj': 9.912703399769664e-05, 'learning_rate/base': 2.478175849942416e-05, 'epoch': 0.28}) +[2026-07-27 03:28:04,374][starVLA.training.train_starvla][INFO] - Step 2305, Loss: {'train/loss': 0.28327855467796326, 'train/grad_norm_pre_clip': 4.3246002197265625, 'timing/data': 0.00018980726599693298, 'timing/model': 0.4622709909453988, 'learning_rate/action_model': 9.912129897022714e-05, 'learning_rate/action_query_proj': 9.912129897022714e-05, 'learning_rate/base': 2.4780324742556786e-05, 'epoch': 0.28}) +[2026-07-27 03:28:09,997][starVLA.training.train_starvla][INFO] - Step 2306, Loss: {'train/loss': 0.2714264690876007, 'train/grad_norm_pre_clip': 5.238894939422607, 'timing/data': 0.00021211709827184677, 'timing/model': 0.4621485131792724, 'learning_rate/action_model': 9.911554534001508e-05, 'learning_rate/action_query_proj': 9.911554534001508e-05, 'learning_rate/base': 2.477888633500377e-05, 'epoch': 0.28}) +[2026-07-27 03:28:15,621][starVLA.training.train_starvla][INFO] - Step 2307, Loss: {'train/loss': 0.20917898416519165, 'train/grad_norm_pre_clip': 3.0855329036712646, 'timing/data': 0.00020008813589811325, 'timing/model': 0.46596301440149546, 'learning_rate/action_model': 9.910977310933189e-05, 'learning_rate/action_query_proj': 9.910977310933189e-05, 'learning_rate/base': 2.477744327733297e-05, 'epoch': 0.28}) +[2026-07-27 03:28:21,233][starVLA.training.train_starvla][INFO] - Step 2308, Loss: {'train/loss': 0.2456827312707901, 'train/grad_norm_pre_clip': 4.007587432861328, 'timing/data': 0.000196775421500206, 'timing/model': 0.4610610418021679, 'learning_rate/action_model': 9.910398228045635e-05, 'learning_rate/action_query_proj': 9.910398228045635e-05, 'learning_rate/base': 2.4775995570114086e-05, 'epoch': 0.28}) +[2026-07-27 03:28:26,853][starVLA.training.train_starvla][INFO] - Step 2309, Loss: {'train/loss': 0.33530640602111816, 'train/grad_norm_pre_clip': 3.990896701812744, 'timing/data': 0.00018671993166208267, 'timing/model': 0.46772150602191687, 'learning_rate/action_model': 9.909817285567456e-05, 'learning_rate/action_query_proj': 9.909817285567456e-05, 'learning_rate/base': 2.477454321391864e-05, 'epoch': 0.28}) +[2026-07-27 03:28:32,463][starVLA.training.train_starvla][INFO] - Step 2310, Loss: {'train/loss': 0.2714337110519409, 'train/grad_norm_pre_clip': 3.496729850769043, 'timing/data': 0.00018670875579118729, 'timing/model': 0.4620977551676333, 'learning_rate/action_model': 9.909234483728003e-05, 'learning_rate/action_query_proj': 9.909234483728003e-05, 'learning_rate/base': 2.477308620932001e-05, 'epoch': 0.28}) +[2026-07-27 03:28:38,080][starVLA.training.train_starvla][INFO] - Step 2311, Loss: {'train/loss': 0.170247882604599, 'train/grad_norm_pre_clip': 3.3432223796844482, 'timing/data': 0.00018607499077916145, 'timing/model': 0.46703853690996766, 'learning_rate/action_model': 9.908649822757358e-05, 'learning_rate/action_query_proj': 9.908649822757358e-05, 'learning_rate/base': 2.4771624556893396e-05, 'epoch': 0.28}) +[2026-07-27 03:28:43,696][starVLA.training.train_starvla][INFO] - Step 2312, Loss: {'train/loss': 0.2598098814487457, 'train/grad_norm_pre_clip': 5.0045552253723145, 'timing/data': 0.00019305571913719177, 'timing/model': 0.4658308778889477, 'learning_rate/action_model': 9.908063302886332e-05, 'learning_rate/action_query_proj': 9.908063302886332e-05, 'learning_rate/base': 2.477015825721583e-05, 'epoch': 0.28}) +[2026-07-27 03:28:49,313][starVLA.training.train_starvla][INFO] - Step 2313, Loss: {'train/loss': 0.25572457909584045, 'train/grad_norm_pre_clip': 3.945657968521118, 'timing/data': 0.00018936535343527794, 'timing/model': 0.46472026174888015, 'learning_rate/action_model': 9.907474924346476e-05, 'learning_rate/action_query_proj': 9.907474924346476e-05, 'learning_rate/base': 2.476868731086619e-05, 'epoch': 0.28}) +[2026-07-27 03:28:54,932][starVLA.training.train_starvla][INFO] - Step 2314, Loss: {'train/loss': 0.2440732717514038, 'train/grad_norm_pre_clip': 3.5186216831207275, 'timing/data': 0.0001885499805212021, 'timing/model': 0.46134759206324816, 'learning_rate/action_model': 9.906884687370069e-05, 'learning_rate/action_query_proj': 9.906884687370069e-05, 'learning_rate/base': 2.4767211718425173e-05, 'epoch': 0.28}) +[2026-07-27 03:29:00,542][starVLA.training.train_starvla][INFO] - Step 2315, Loss: {'train/loss': 0.25404152274131775, 'train/grad_norm_pre_clip': 4.913512706756592, 'timing/data': 0.00018733274191617966, 'timing/model': 0.4581218780949712, 'learning_rate/action_model': 9.906292592190133e-05, 'learning_rate/action_query_proj': 9.906292592190133e-05, 'learning_rate/base': 2.4765731480475333e-05, 'epoch': 0.28}) +[2026-07-27 03:29:06,135][starVLA.training.train_starvla][INFO] - Step 2316, Loss: {'train/loss': 0.3445369005203247, 'train/grad_norm_pre_clip': 4.728456974029541, 'timing/data': 0.0001897537149488926, 'timing/model': 0.4655982097610831, 'learning_rate/action_model': 9.905698639040415e-05, 'learning_rate/action_query_proj': 9.905698639040415e-05, 'learning_rate/base': 2.4764246597601038e-05, 'epoch': 0.28}) +[2026-07-27 03:29:11,736][starVLA.training.train_starvla][INFO] - Step 2317, Loss: {'train/loss': 0.2971358001232147, 'train/grad_norm_pre_clip': 4.785398006439209, 'timing/data': 0.0001866137608885765, 'timing/model': 0.4677881780080497, 'learning_rate/action_model': 9.905102828155398e-05, 'learning_rate/action_query_proj': 9.905102828155398e-05, 'learning_rate/base': 2.4762757070388494e-05, 'epoch': 0.28}) +[2026-07-27 03:29:17,315][starVLA.training.train_starvla][INFO] - Step 2318, Loss: {'train/loss': 0.19490039348602295, 'train/grad_norm_pre_clip': 3.3853752613067627, 'timing/data': 0.0001876060850918293, 'timing/model': 0.4655097438953817, 'learning_rate/action_model': 9.904505159770298e-05, 'learning_rate/action_query_proj': 9.904505159770298e-05, 'learning_rate/base': 2.4761262899425746e-05, 'epoch': 0.28}) +[2026-07-27 03:29:22,920][starVLA.training.train_starvla][INFO] - Step 2319, Loss: {'train/loss': 0.17494243383407593, 'train/grad_norm_pre_clip': 3.05271053314209, 'timing/data': 0.0001913909800350666, 'timing/model': 0.4665187238715589, 'learning_rate/action_model': 9.903905634121067e-05, 'learning_rate/action_query_proj': 9.903905634121067e-05, 'learning_rate/base': 2.4759764085302667e-05, 'epoch': 0.28}) +[2026-07-27 03:29:28,533][starVLA.training.train_starvla][INFO] - Step 2320, Loss: {'train/loss': 0.24067875742912292, 'train/grad_norm_pre_clip': 3.978475570678711, 'timing/data': 0.00021748291328549385, 'timing/model': 0.4633606937713921, 'learning_rate/action_model': 9.903304251444385e-05, 'learning_rate/action_query_proj': 9.903304251444385e-05, 'learning_rate/base': 2.4758260628610964e-05, 'epoch': 0.28}) +[2026-07-27 03:29:34,143][starVLA.training.train_starvla][INFO] - Step 2321, Loss: {'train/loss': 0.248243510723114, 'train/grad_norm_pre_clip': 4.125966548919678, 'timing/data': 0.0001911502331495285, 'timing/model': 0.46171040274202824, 'learning_rate/action_model': 9.902701011977672e-05, 'learning_rate/action_query_proj': 9.902701011977672e-05, 'learning_rate/base': 2.475675252994418e-05, 'epoch': 0.28}) +[2026-07-27 03:29:39,760][starVLA.training.train_starvla][INFO] - Step 2322, Loss: {'train/loss': 0.2778070569038391, 'train/grad_norm_pre_clip': 3.7686567306518555, 'timing/data': 0.00018573133274912834, 'timing/model': 0.46256446512416005, 'learning_rate/action_model': 9.902095915959077e-05, 'learning_rate/action_query_proj': 9.902095915959077e-05, 'learning_rate/base': 2.475523978989769e-05, 'epoch': 0.28}) +[2026-07-27 03:29:45,389][starVLA.training.train_starvla][INFO] - Step 2323, Loss: {'train/loss': 0.15675044059753418, 'train/grad_norm_pre_clip': 2.368377208709717, 'timing/data': 0.00019079633057117462, 'timing/model': 0.46357879973948, 'learning_rate/action_model': 9.901488963627479e-05, 'learning_rate/action_query_proj': 9.901488963627479e-05, 'learning_rate/base': 2.4753722409068697e-05, 'epoch': 0.28}) +[2026-07-27 03:29:50,985][starVLA.training.train_starvla][INFO] - Step 2324, Loss: {'train/loss': 0.24164889752864838, 'train/grad_norm_pre_clip': 4.384181499481201, 'timing/data': 0.00018753483891487122, 'timing/model': 0.46488543087616563, 'learning_rate/action_model': 9.900880155222496e-05, 'learning_rate/action_query_proj': 9.900880155222496e-05, 'learning_rate/base': 2.475220038805624e-05, 'epoch': 0.28}) +[2026-07-27 03:29:56,585][starVLA.training.train_starvla][INFO] - Step 2325, Loss: {'train/loss': 0.2587219774723053, 'train/grad_norm_pre_clip': 5.198971271514893, 'timing/data': 0.00018705986440181732, 'timing/model': 0.46230674209073186, 'learning_rate/action_model': 9.900269490984477e-05, 'learning_rate/action_query_proj': 9.900269490984477e-05, 'learning_rate/base': 2.4750673727461192e-05, 'epoch': 0.28}) +[2026-07-27 03:30:02,193][starVLA.training.train_starvla][INFO] - Step 2326, Loss: {'train/loss': 0.22139300405979156, 'train/grad_norm_pre_clip': 3.8653359413146973, 'timing/data': 0.00018639490008354187, 'timing/model': 0.4620160898193717, 'learning_rate/action_model': 9.899656971154499e-05, 'learning_rate/action_query_proj': 9.899656971154499e-05, 'learning_rate/base': 2.4749142427886247e-05, 'epoch': 0.28}) +[2026-07-27 03:30:07,778][starVLA.training.train_starvla][INFO] - Step 2327, Loss: {'train/loss': 0.15653565526008606, 'train/grad_norm_pre_clip': 2.522362232208252, 'timing/data': 0.00018903007730841637, 'timing/model': 0.4670134102925658, 'learning_rate/action_model': 9.899042595974377e-05, 'learning_rate/action_query_proj': 9.899042595974377e-05, 'learning_rate/base': 2.4747606489935942e-05, 'epoch': 0.28}) +[2026-07-27 03:30:13,371][starVLA.training.train_starvla][INFO] - Step 2328, Loss: {'train/loss': 0.19923484325408936, 'train/grad_norm_pre_clip': 3.8430356979370117, 'timing/data': 0.00019970489665865898, 'timing/model': 0.46406619157642126, 'learning_rate/action_model': 9.898426365686659e-05, 'learning_rate/action_query_proj': 9.898426365686659e-05, 'learning_rate/base': 2.4746065914216647e-05, 'epoch': 0.28}) +[2026-07-27 03:30:18,982][starVLA.training.train_starvla][INFO] - Step 2329, Loss: {'train/loss': 0.14487120509147644, 'train/grad_norm_pre_clip': 2.628873348236084, 'timing/data': 0.00019618868827819824, 'timing/model': 0.4620434599928558, 'learning_rate/action_model': 9.897808280534616e-05, 'learning_rate/action_query_proj': 9.897808280534616e-05, 'learning_rate/base': 2.474452070133654e-05, 'epoch': 0.28}) +[2026-07-27 03:30:24,578][starVLA.training.train_starvla][INFO] - Step 2330, Loss: {'train/loss': 0.2357882559299469, 'train/grad_norm_pre_clip': 4.401565074920654, 'timing/data': 0.00019397586584091187, 'timing/model': 0.4632628308609128, 'learning_rate/action_model': 9.897188340762267e-05, 'learning_rate/action_query_proj': 9.897188340762267e-05, 'learning_rate/base': 2.4742970851905668e-05, 'epoch': 0.28}) +[2026-07-27 03:30:30,160][starVLA.training.train_starvla][INFO] - Step 2331, Loss: {'train/loss': 0.09004118293523788, 'train/grad_norm_pre_clip': 1.932321548461914, 'timing/data': 0.00019000796601176262, 'timing/model': 0.465145954862237, 'learning_rate/action_model': 9.896566546614349e-05, 'learning_rate/action_query_proj': 9.896566546614349e-05, 'learning_rate/base': 2.4741416366535873e-05, 'epoch': 0.28}) +[2026-07-27 03:30:35,755][starVLA.training.train_starvla][INFO] - Step 2332, Loss: {'train/loss': 0.28156256675720215, 'train/grad_norm_pre_clip': 3.6399731636047363, 'timing/data': 0.00019845226779580116, 'timing/model': 0.4618791122920811, 'learning_rate/action_model': 9.895942898336337e-05, 'learning_rate/action_query_proj': 9.895942898336337e-05, 'learning_rate/base': 2.4739857245840843e-05, 'epoch': 0.28}) +[2026-07-27 03:30:41,359][starVLA.training.train_starvla][INFO] - Step 2333, Loss: {'train/loss': 0.17584848403930664, 'train/grad_norm_pre_clip': 4.027921199798584, 'timing/data': 0.00019115908071398735, 'timing/model': 0.46438937820494175, 'learning_rate/action_model': 9.895317396174437e-05, 'learning_rate/action_query_proj': 9.895317396174437e-05, 'learning_rate/base': 2.4738293490436092e-05, 'epoch': 0.28}) +[2026-07-27 03:30:46,949][starVLA.training.train_starvla][INFO] - Step 2334, Loss: {'train/loss': 0.27549731731414795, 'train/grad_norm_pre_clip': 3.4232702255249023, 'timing/data': 0.00019080191850662231, 'timing/model': 0.4603964393027127, 'learning_rate/action_model': 9.89469004037559e-05, 'learning_rate/action_query_proj': 9.89469004037559e-05, 'learning_rate/base': 2.4736725100938977e-05, 'epoch': 0.28}) +[2026-07-27 03:30:52,545][starVLA.training.train_starvla][INFO] - Step 2335, Loss: {'train/loss': 0.1681809425354004, 'train/grad_norm_pre_clip': 3.48408579826355, 'timing/data': 0.00019129179418087006, 'timing/model': 0.4650884959846735, 'learning_rate/action_model': 9.894060831187465e-05, 'learning_rate/action_query_proj': 9.894060831187465e-05, 'learning_rate/base': 2.4735152077968663e-05, 'epoch': 0.28}) +[2026-07-27 03:30:58,192][starVLA.training.train_starvla][INFO] - Step 2336, Loss: {'train/loss': 0.21161723136901855, 'train/grad_norm_pre_clip': 4.526143550872803, 'timing/data': 0.00019974308088421822, 'timing/model': 0.46708686789497733, 'learning_rate/action_model': 9.893429768858464e-05, 'learning_rate/action_query_proj': 9.893429768858464e-05, 'learning_rate/base': 2.473357442214616e-05, 'epoch': 0.28}) +[2026-07-27 03:31:03,782][starVLA.training.train_starvla][INFO] - Step 2337, Loss: {'train/loss': 0.26770302653312683, 'train/grad_norm_pre_clip': 4.152843952178955, 'timing/data': 0.00021317973732948303, 'timing/model': 0.46233963733538985, 'learning_rate/action_model': 9.892796853637718e-05, 'learning_rate/action_query_proj': 9.892796853637718e-05, 'learning_rate/base': 2.4731992134094295e-05, 'epoch': 0.28}) +[2026-07-27 03:31:09,450][starVLA.training.train_starvla][INFO] - Step 2338, Loss: {'train/loss': 0.35951414704322815, 'train/grad_norm_pre_clip': 3.7869040966033936, 'timing/data': 0.0002195020206272602, 'timing/model': 0.46572784380987287, 'learning_rate/action_model': 9.892162085775094e-05, 'learning_rate/action_query_proj': 9.892162085775094e-05, 'learning_rate/base': 2.4730405214437734e-05, 'epoch': 0.28}) +[2026-07-27 03:31:15,095][starVLA.training.train_starvla][INFO] - Step 2339, Loss: {'train/loss': 0.35505515336990356, 'train/grad_norm_pre_clip': 5.680398941040039, 'timing/data': 0.00020311493426561356, 'timing/model': 0.47362338239327073, 'learning_rate/action_model': 9.89152546552119e-05, 'learning_rate/action_query_proj': 9.89152546552119e-05, 'learning_rate/base': 2.4728813663802975e-05, 'epoch': 0.28}) +[2026-07-27 03:31:20,733][starVLA.training.train_starvla][INFO] - Step 2340, Loss: {'train/loss': 0.23472781479358673, 'train/grad_norm_pre_clip': 4.3059163093566895, 'timing/data': 0.00019824225455522537, 'timing/model': 0.4821919007226825, 'learning_rate/action_model': 9.89088699312733e-05, 'learning_rate/action_query_proj': 9.89088699312733e-05, 'learning_rate/base': 2.4727217482818323e-05, 'epoch': 0.28}) +[2026-07-27 03:31:26,326][starVLA.training.train_starvla][INFO] - Step 2341, Loss: {'train/loss': 0.3206535875797272, 'train/grad_norm_pre_clip': 6.11910343170166, 'timing/data': 0.00020061805844306946, 'timing/model': 0.4753660596907139, 'learning_rate/action_model': 9.890246668845574e-05, 'learning_rate/action_query_proj': 9.890246668845574e-05, 'learning_rate/base': 2.4725616672113935e-05, 'epoch': 0.28}) +[2026-07-27 03:31:31,942][starVLA.training.train_starvla][INFO] - Step 2342, Loss: {'train/loss': 0.4697914719581604, 'train/grad_norm_pre_clip': 6.459118843078613, 'timing/data': 0.00019221287220716476, 'timing/model': 0.47061786986887455, 'learning_rate/action_model': 9.889604492928712e-05, 'learning_rate/action_query_proj': 9.889604492928712e-05, 'learning_rate/base': 2.472401123232178e-05, 'epoch': 0.28}) +[2026-07-27 03:31:37,562][starVLA.training.train_starvla][INFO] - Step 2343, Loss: {'train/loss': 0.3170461356639862, 'train/grad_norm_pre_clip': 5.591163635253906, 'timing/data': 0.00018890714272856712, 'timing/model': 0.48023034492507577, 'learning_rate/action_model': 9.888960465630267e-05, 'learning_rate/action_query_proj': 9.888960465630267e-05, 'learning_rate/base': 2.4722401164075667e-05, 'epoch': 0.28}) +[2026-07-27 03:31:43,182][starVLA.training.train_starvla][INFO] - Step 2344, Loss: {'train/loss': 0.2567053437232971, 'train/grad_norm_pre_clip': 3.5998668670654297, 'timing/data': 0.00019002193585038185, 'timing/model': 0.48212609998881817, 'learning_rate/action_model': 9.888314587204488e-05, 'learning_rate/action_query_proj': 9.888314587204488e-05, 'learning_rate/base': 2.472078646801122e-05, 'epoch': 0.28}) +[2026-07-27 03:31:48,783][starVLA.training.train_starvla][INFO] - Step 2345, Loss: {'train/loss': 0.3103611469268799, 'train/grad_norm_pre_clip': 5.40421199798584, 'timing/data': 0.0001858258619904518, 'timing/model': 0.46977041894569993, 'learning_rate/action_model': 9.887666857906358e-05, 'learning_rate/action_query_proj': 9.887666857906358e-05, 'learning_rate/base': 2.4719167144765895e-05, 'epoch': 0.28}) +[2026-07-27 03:31:54,424][starVLA.training.train_starvla][INFO] - Step 2346, Loss: {'train/loss': 0.23014293611049652, 'train/grad_norm_pre_clip': 4.983258247375488, 'timing/data': 0.00019239401444792747, 'timing/model': 0.48135658586397767, 'learning_rate/action_model': 9.887017277991591e-05, 'learning_rate/action_query_proj': 9.887017277991591e-05, 'learning_rate/base': 2.4717543194978978e-05, 'epoch': 0.28}) +[2026-07-27 03:32:00,055][starVLA.training.train_starvla][INFO] - Step 2347, Loss: {'train/loss': 0.21442484855651855, 'train/grad_norm_pre_clip': 5.822146892547607, 'timing/data': 0.00021592481061816216, 'timing/model': 0.4712897604331374, 'learning_rate/action_model': 9.886365847716633e-05, 'learning_rate/action_query_proj': 9.886365847716633e-05, 'learning_rate/base': 2.471591461929158e-05, 'epoch': 0.28}) +[2026-07-27 03:32:05,704][starVLA.training.train_starvla][INFO] - Step 2348, Loss: {'train/loss': 0.16048987209796906, 'train/grad_norm_pre_clip': 4.692098140716553, 'timing/data': 0.00018950318917632103, 'timing/model': 0.4704428822733462, 'learning_rate/action_model': 9.885712567338654e-05, 'learning_rate/action_query_proj': 9.885712567338654e-05, 'learning_rate/base': 2.4714281418346635e-05, 'epoch': 0.28}) +[2026-07-27 03:32:11,358][starVLA.training.train_starvla][INFO] - Step 2349, Loss: {'train/loss': 0.16447651386260986, 'train/grad_norm_pre_clip': 3.4675159454345703, 'timing/data': 0.00018806708976626396, 'timing/model': 0.4817647482268512, 'learning_rate/action_model': 9.885057437115561e-05, 'learning_rate/action_query_proj': 9.885057437115561e-05, 'learning_rate/base': 2.4712643592788902e-05, 'epoch': 0.28}) +[2026-07-27 03:32:16,968][starVLA.training.train_starvla][INFO] - Step 2350, Loss: {'train/loss': 0.14273110032081604, 'train/grad_norm_pre_clip': 2.933169364929199, 'timing/data': 0.00019156187772750854, 'timing/model': 0.46244170190766454, 'learning_rate/action_model': 9.884400457305988e-05, 'learning_rate/action_query_proj': 9.884400457305988e-05, 'learning_rate/base': 2.471100114326497e-05, 'epoch': 0.29}) +[2026-07-27 03:32:22,602][starVLA.training.train_starvla][INFO] - Step 2351, Loss: {'train/loss': 0.18715572357177734, 'train/grad_norm_pre_clip': 3.6414945125579834, 'timing/data': 0.0001867269165813923, 'timing/model': 0.4633452417328954, 'learning_rate/action_model': 9.883741628169302e-05, 'learning_rate/action_query_proj': 9.883741628169302e-05, 'learning_rate/base': 2.4709354070423256e-05, 'epoch': 0.29}) +[2026-07-27 03:32:28,229][starVLA.training.train_starvla][INFO] - Step 2352, Loss: {'train/loss': 0.17672349512577057, 'train/grad_norm_pre_clip': 3.4534542560577393, 'timing/data': 0.0001889299601316452, 'timing/model': 0.46263562934473157, 'learning_rate/action_model': 9.883080949965597e-05, 'learning_rate/action_query_proj': 9.883080949965597e-05, 'learning_rate/base': 2.4707702374913994e-05, 'epoch': 0.29}) +[2026-07-27 03:32:33,828][starVLA.training.train_starvla][INFO] - Step 2353, Loss: {'train/loss': 0.20732925832271576, 'train/grad_norm_pre_clip': 4.7143330574035645, 'timing/data': 0.00019301613792777061, 'timing/model': 0.46597274113446474, 'learning_rate/action_model': 9.882418422955699e-05, 'learning_rate/action_query_proj': 9.882418422955699e-05, 'learning_rate/base': 2.4706046057389246e-05, 'epoch': 0.29}) +[2026-07-27 03:32:39,439][starVLA.training.train_starvla][INFO] - Step 2354, Loss: {'train/loss': 0.13225479423999786, 'train/grad_norm_pre_clip': 3.943617105484009, 'timing/data': 0.0001845918595790863, 'timing/model': 0.46246357867494226, 'learning_rate/action_model': 9.881754047401163e-05, 'learning_rate/action_query_proj': 9.881754047401163e-05, 'learning_rate/base': 2.4704385118502907e-05, 'epoch': 0.29}) +[2026-07-27 03:32:45,056][starVLA.training.train_starvla][INFO] - Step 2355, Loss: {'train/loss': 0.11624317616224289, 'train/grad_norm_pre_clip': 3.212150812149048, 'timing/data': 0.00019044382497668266, 'timing/model': 0.46582522615790367, 'learning_rate/action_model': 9.881087823564272e-05, 'learning_rate/action_query_proj': 9.881087823564272e-05, 'learning_rate/base': 2.470271955891068e-05, 'epoch': 0.29}) +[2026-07-27 03:32:50,667][starVLA.training.train_starvla][INFO] - Step 2356, Loss: {'train/loss': 0.11918064206838608, 'train/grad_norm_pre_clip': 2.6575803756713867, 'timing/data': 0.00019328389316797256, 'timing/model': 0.4613155350089073, 'learning_rate/action_model': 9.880419751708045e-05, 'learning_rate/action_query_proj': 9.880419751708045e-05, 'learning_rate/base': 2.4701049379270112e-05, 'epoch': 0.29}) +[2026-07-27 03:32:56,283][starVLA.training.train_starvla][INFO] - Step 2357, Loss: {'train/loss': 0.1942322552204132, 'train/grad_norm_pre_clip': 4.467930793762207, 'timing/data': 0.0001892540603876114, 'timing/model': 0.4666597479954362, 'learning_rate/action_model': 9.879749832096221e-05, 'learning_rate/action_query_proj': 9.879749832096221e-05, 'learning_rate/base': 2.4699374580240552e-05, 'epoch': 0.29}) +[2026-07-27 03:33:01,916][starVLA.training.train_starvla][INFO] - Step 2358, Loss: {'train/loss': 0.10118785500526428, 'train/grad_norm_pre_clip': 2.3031299114227295, 'timing/data': 0.0001925458200275898, 'timing/model': 0.4642051560804248, 'learning_rate/action_model': 9.87907806499328e-05, 'learning_rate/action_query_proj': 9.87907806499328e-05, 'learning_rate/base': 2.46976951624832e-05, 'epoch': 0.29}) +[2026-07-27 03:33:07,528][starVLA.training.train_starvla][INFO] - Step 2359, Loss: {'train/loss': 0.1993967592716217, 'train/grad_norm_pre_clip': 2.989645481109619, 'timing/data': 0.00020273681730031967, 'timing/model': 0.4623807370662689, 'learning_rate/action_model': 9.878404450664417e-05, 'learning_rate/action_query_proj': 9.878404450664417e-05, 'learning_rate/base': 2.4696011126661043e-05, 'epoch': 0.29}) +[2026-07-27 03:33:13,120][starVLA.training.train_starvla][INFO] - Step 2360, Loss: {'train/loss': 0.27074185013771057, 'train/grad_norm_pre_clip': 4.259048938751221, 'timing/data': 0.0001899409107863903, 'timing/model': 0.46151492092758417, 'learning_rate/action_model': 9.877728989375571e-05, 'learning_rate/action_query_proj': 9.877728989375571e-05, 'learning_rate/base': 2.4694322473438927e-05, 'epoch': 0.29}) +[2026-07-27 03:33:18,716][starVLA.training.train_starvla][INFO] - Step 2361, Loss: {'train/loss': 0.1510443240404129, 'train/grad_norm_pre_clip': 3.3209950923919678, 'timing/data': 0.00018877023831009865, 'timing/model': 0.4655112009495497, 'learning_rate/action_model': 9.8770516813934e-05, 'learning_rate/action_query_proj': 9.8770516813934e-05, 'learning_rate/base': 2.46926292034835e-05, 'epoch': 0.29}) +[2026-07-27 03:33:24,325][starVLA.training.train_starvla][INFO] - Step 2362, Loss: {'train/loss': 0.14682096242904663, 'train/grad_norm_pre_clip': 2.718283176422119, 'timing/data': 0.0001866794191300869, 'timing/model': 0.46164296194911003, 'learning_rate/action_model': 9.876372526985295e-05, 'learning_rate/action_query_proj': 9.876372526985295e-05, 'learning_rate/base': 2.4690931317463238e-05, 'epoch': 0.29}) +[2026-07-27 03:33:29,915][starVLA.training.train_starvla][INFO] - Step 2363, Loss: {'train/loss': 0.23579417169094086, 'train/grad_norm_pre_clip': 5.857855796813965, 'timing/data': 0.00019972585141658783, 'timing/model': 0.45917539298534393, 'learning_rate/action_model': 9.875691526419377e-05, 'learning_rate/action_query_proj': 9.875691526419377e-05, 'learning_rate/base': 2.4689228816048442e-05, 'epoch': 0.29}) +[2026-07-27 03:33:35,523][starVLA.training.train_starvla][INFO] - Step 2364, Loss: {'train/loss': 0.19896116852760315, 'train/grad_norm_pre_clip': 3.4015541076660156, 'timing/data': 0.00018568476662039757, 'timing/model': 0.46219334099441767, 'learning_rate/action_model': 9.875008679964492e-05, 'learning_rate/action_query_proj': 9.875008679964492e-05, 'learning_rate/base': 2.468752169991123e-05, 'epoch': 0.29}) +[2026-07-27 03:33:41,125][starVLA.training.train_starvla][INFO] - Step 2365, Loss: {'train/loss': 0.1631447970867157, 'train/grad_norm_pre_clip': 3.2224152088165283, 'timing/data': 0.0001895260065793991, 'timing/model': 0.46665332093834877, 'learning_rate/action_model': 9.874323987890218e-05, 'learning_rate/action_query_proj': 9.874323987890218e-05, 'learning_rate/base': 2.4685809969725546e-05, 'epoch': 0.29}) +[2026-07-27 03:33:46,724][starVLA.training.train_starvla][INFO] - Step 2366, Loss: {'train/loss': 0.22837069630622864, 'train/grad_norm_pre_clip': 2.9879119396209717, 'timing/data': 0.00018678093329071999, 'timing/model': 0.45871981978416443, 'learning_rate/action_model': 9.873637450466862e-05, 'learning_rate/action_query_proj': 9.873637450466862e-05, 'learning_rate/base': 2.4684093626167155e-05, 'epoch': 0.29}) +[2026-07-27 03:33:52,420][starVLA.training.train_starvla][INFO] - Step 2367, Loss: {'train/loss': 0.11841720342636108, 'train/grad_norm_pre_clip': 2.4929323196411133, 'timing/data': 0.0001875641755759716, 'timing/model': 0.4666620730422437, 'learning_rate/action_model': 9.872949067965455e-05, 'learning_rate/action_query_proj': 9.872949067965455e-05, 'learning_rate/base': 2.4682372669913638e-05, 'epoch': 0.29}) +[2026-07-27 03:33:58,021][starVLA.training.train_starvla][INFO] - Step 2368, Loss: {'train/loss': 0.14455372095108032, 'train/grad_norm_pre_clip': 2.909788131713867, 'timing/data': 0.0003634607419371605, 'timing/model': 0.4665422858670354, 'learning_rate/action_model': 9.872258840657762e-05, 'learning_rate/action_query_proj': 9.872258840657762e-05, 'learning_rate/base': 2.4680647101644405e-05, 'epoch': 0.29}) +[2026-07-27 03:34:03,650][starVLA.training.train_starvla][INFO] - Step 2369, Loss: {'train/loss': 0.23734159767627716, 'train/grad_norm_pre_clip': 3.2095491886138916, 'timing/data': 0.0002198871225118637, 'timing/model': 0.4613513043150306, 'learning_rate/action_model': 9.871566768816274e-05, 'learning_rate/action_query_proj': 9.871566768816274e-05, 'learning_rate/base': 2.4678916922040685e-05, 'epoch': 0.29}) +[2026-07-27 03:34:09,258][starVLA.training.train_starvla][INFO] - Step 2370, Loss: {'train/loss': 0.2293662130832672, 'train/grad_norm_pre_clip': 4.061336040496826, 'timing/data': 0.00019181380048394203, 'timing/model': 0.4592980230227113, 'learning_rate/action_model': 9.870872852714209e-05, 'learning_rate/action_query_proj': 9.870872852714209e-05, 'learning_rate/base': 2.4677182131785522e-05, 'epoch': 0.29}) +[2026-07-27 03:34:14,862][starVLA.training.train_starvla][INFO] - Step 2371, Loss: {'train/loss': 0.19181688129901886, 'train/grad_norm_pre_clip': 3.457718849182129, 'timing/data': 0.000201439019292593, 'timing/model': 0.45907485485076904, 'learning_rate/action_model': 9.870177092625513e-05, 'learning_rate/action_query_proj': 9.870177092625513e-05, 'learning_rate/base': 2.4675442731563782e-05, 'epoch': 0.29}) +[2026-07-27 03:34:20,479][starVLA.training.train_starvla][INFO] - Step 2372, Loss: {'train/loss': 0.22030186653137207, 'train/grad_norm_pre_clip': 4.147365570068359, 'timing/data': 0.00018964800983667374, 'timing/model': 0.4590246048755944, 'learning_rate/action_model': 9.869479488824861e-05, 'learning_rate/action_query_proj': 9.869479488824861e-05, 'learning_rate/base': 2.4673698722062152e-05, 'epoch': 0.29}) +[2026-07-27 03:34:26,083][starVLA.training.train_starvla][INFO] - Step 2373, Loss: {'train/loss': 0.1483345627784729, 'train/grad_norm_pre_clip': 2.6758809089660645, 'timing/data': 0.00019280193373560905, 'timing/model': 0.46396431839093566, 'learning_rate/action_model': 9.868780041587659e-05, 'learning_rate/action_query_proj': 9.868780041587659e-05, 'learning_rate/base': 2.4671950103969147e-05, 'epoch': 0.29}) +[2026-07-27 03:34:31,681][starVLA.training.train_starvla][INFO] - Step 2374, Loss: {'train/loss': 0.33604493737220764, 'train/grad_norm_pre_clip': 3.866079807281494, 'timing/data': 0.00019110878929495811, 'timing/model': 0.46456254087388515, 'learning_rate/action_model': 9.868078751190035e-05, 'learning_rate/action_query_proj': 9.868078751190035e-05, 'learning_rate/base': 2.4670196877975087e-05, 'epoch': 0.29}) +[2026-07-27 03:34:37,531][starVLA.training.train_starvla][INFO] - Step 2375, Loss: {'train/loss': 0.17232772707939148, 'train/grad_norm_pre_clip': 3.23531174659729, 'timing/data': 0.00018918514251708984, 'timing/model': 0.4623435130342841, 'learning_rate/action_model': 9.867375617908848e-05, 'learning_rate/action_query_proj': 9.867375617908848e-05, 'learning_rate/base': 2.466843904477212e-05, 'epoch': 0.29}) +[2026-07-27 03:34:43,137][starVLA.training.train_starvla][INFO] - Step 2376, Loss: {'train/loss': 0.2071288675069809, 'train/grad_norm_pre_clip': 3.1199867725372314, 'timing/data': 0.00019182218238711357, 'timing/model': 0.4600230036303401, 'learning_rate/action_model': 9.866670642021684e-05, 'learning_rate/action_query_proj': 9.866670642021684e-05, 'learning_rate/base': 2.466667660505421e-05, 'epoch': 0.29}) +[2026-07-27 03:34:48,742][starVLA.training.train_starvla][INFO] - Step 2377, Loss: {'train/loss': 0.14633119106292725, 'train/grad_norm_pre_clip': 2.4124438762664795, 'timing/data': 0.00019562989473342896, 'timing/model': 0.4656262840144336, 'learning_rate/action_model': 9.865963823806857e-05, 'learning_rate/action_query_proj': 9.865963823806857e-05, 'learning_rate/base': 2.4664909559517144e-05, 'epoch': 0.29}) +[2026-07-27 03:34:54,324][starVLA.training.train_starvla][INFO] - Step 2378, Loss: {'train/loss': 0.243750661611557, 'train/grad_norm_pre_clip': 4.2069268226623535, 'timing/data': 0.0001916489563882351, 'timing/model': 0.46359378565102816, 'learning_rate/action_model': 9.865255163543406e-05, 'learning_rate/action_query_proj': 9.865255163543406e-05, 'learning_rate/base': 2.4663137908858515e-05, 'epoch': 0.29}) +[2026-07-27 03:34:59,889][starVLA.training.train_starvla][INFO] - Step 2379, Loss: {'train/loss': 0.1919359713792801, 'train/grad_norm_pre_clip': 4.444068908691406, 'timing/data': 0.000189152080565691, 'timing/model': 0.46144472900778055, 'learning_rate/action_model': 9.864544661511101e-05, 'learning_rate/action_query_proj': 9.864544661511101e-05, 'learning_rate/base': 2.4661361653777753e-05, 'epoch': 0.29}) +[2026-07-27 03:35:05,479][starVLA.training.train_starvla][INFO] - Step 2380, Loss: {'train/loss': 0.18137992918491364, 'train/grad_norm_pre_clip': 2.746415138244629, 'timing/data': 0.00018762703984975815, 'timing/model': 0.4672923949547112, 'learning_rate/action_model': 9.863832317990436e-05, 'learning_rate/action_query_proj': 9.863832317990436e-05, 'learning_rate/base': 2.465958079497609e-05, 'epoch': 0.29}) +[2026-07-27 03:35:11,067][starVLA.training.train_starvla][INFO] - Step 2381, Loss: {'train/loss': 0.24335819482803345, 'train/grad_norm_pre_clip': 4.008073329925537, 'timing/data': 0.00019790185615420341, 'timing/model': 0.46409487491473556, 'learning_rate/action_model': 9.863118133262632e-05, 'learning_rate/action_query_proj': 9.863118133262632e-05, 'learning_rate/base': 2.465779533315658e-05, 'epoch': 0.29}) +[2026-07-27 03:35:16,657][starVLA.training.train_starvla][INFO] - Step 2382, Loss: {'train/loss': 0.2311909794807434, 'train/grad_norm_pre_clip': 3.599381923675537, 'timing/data': 0.0002406020648777485, 'timing/model': 0.46784609043970704, 'learning_rate/action_model': 9.862402107609638e-05, 'learning_rate/action_query_proj': 9.862402107609638e-05, 'learning_rate/base': 2.4656005269024094e-05, 'epoch': 0.29}) +[2026-07-27 03:35:22,264][starVLA.training.train_starvla][INFO] - Step 2383, Loss: {'train/loss': 0.10680685937404633, 'train/grad_norm_pre_clip': 1.7540467977523804, 'timing/data': 0.0001875460147857666, 'timing/model': 0.46200435189530253, 'learning_rate/action_model': 9.86168424131413e-05, 'learning_rate/action_query_proj': 9.86168424131413e-05, 'learning_rate/base': 2.4654210603285325e-05, 'epoch': 0.29}) +[2026-07-27 03:35:27,869][starVLA.training.train_starvla][INFO] - Step 2384, Loss: {'train/loss': 0.19933241605758667, 'train/grad_norm_pre_clip': 3.2757623195648193, 'timing/data': 0.00020498502999544144, 'timing/model': 0.46243106480687857, 'learning_rate/action_model': 9.860964534659511e-05, 'learning_rate/action_query_proj': 9.860964534659511e-05, 'learning_rate/base': 2.4652411336648777e-05, 'epoch': 0.29}) +[2026-07-27 03:35:33,481][starVLA.training.train_starvla][INFO] - Step 2385, Loss: {'train/loss': 0.23532673716545105, 'train/grad_norm_pre_clip': 3.2046399116516113, 'timing/data': 0.00019245781004428864, 'timing/model': 0.4588644281029701, 'learning_rate/action_model': 9.86024298792991e-05, 'learning_rate/action_query_proj': 9.86024298792991e-05, 'learning_rate/base': 2.4650607469824774e-05, 'epoch': 0.29}) +[2026-07-27 03:35:39,089][starVLA.training.train_starvla][INFO] - Step 2386, Loss: {'train/loss': 0.2645812928676605, 'train/grad_norm_pre_clip': 4.275042533874512, 'timing/data': 0.0001895497553050518, 'timing/model': 0.46544138388708234, 'learning_rate/action_model': 9.85951960141018e-05, 'learning_rate/action_query_proj': 9.85951960141018e-05, 'learning_rate/base': 2.464879900352545e-05, 'epoch': 0.29}) +[2026-07-27 03:35:44,691][starVLA.training.train_starvla][INFO] - Step 2387, Loss: {'train/loss': 0.21932880580425262, 'train/grad_norm_pre_clip': 3.1876449584960938, 'timing/data': 0.00018909433856606483, 'timing/model': 0.46671648183837533, 'learning_rate/action_model': 9.858794375385903e-05, 'learning_rate/action_query_proj': 9.858794375385903e-05, 'learning_rate/base': 2.464698593846476e-05, 'epoch': 0.29}) +[2026-07-27 03:35:50,318][starVLA.training.train_starvla][INFO] - Step 2388, Loss: {'train/loss': 0.16284266114234924, 'train/grad_norm_pre_clip': 3.8626222610473633, 'timing/data': 0.0001878282055258751, 'timing/model': 0.4659057459793985, 'learning_rate/action_model': 9.85806731014339e-05, 'learning_rate/action_query_proj': 9.85806731014339e-05, 'learning_rate/base': 2.4645168275358476e-05, 'epoch': 0.29}) +[2026-07-27 03:35:56,175][starVLA.training.train_starvla][INFO] - Step 2389, Loss: {'train/loss': 0.11953994631767273, 'train/grad_norm_pre_clip': 2.7565407752990723, 'timing/data': 0.00019071483984589577, 'timing/model': 0.45980417961254716, 'learning_rate/action_model': 9.857338405969672e-05, 'learning_rate/action_query_proj': 9.857338405969672e-05, 'learning_rate/base': 2.464334601492418e-05, 'epoch': 0.29}) +[2026-07-27 03:36:01,765][starVLA.training.train_starvla][INFO] - Step 2390, Loss: {'train/loss': 0.17294539511203766, 'train/grad_norm_pre_clip': 2.5529353618621826, 'timing/data': 0.0001888331025838852, 'timing/model': 0.46550060668960214, 'learning_rate/action_model': 9.856607663152508e-05, 'learning_rate/action_query_proj': 9.856607663152508e-05, 'learning_rate/base': 2.464151915788127e-05, 'epoch': 0.29}) +[2026-07-27 03:36:07,821][starVLA.training.train_starvla][INFO] - Step 2391, Loss: {'train/loss': 0.22247497737407684, 'train/grad_norm_pre_clip': 3.442385196685791, 'timing/data': 0.00018878793343901634, 'timing/model': 0.46553716994822025, 'learning_rate/action_model': 9.855875081980387e-05, 'learning_rate/action_query_proj': 9.855875081980387e-05, 'learning_rate/base': 2.4639687704950968e-05, 'epoch': 0.29}) +[2026-07-27 03:36:13,387][starVLA.training.train_starvla][INFO] - Step 2392, Loss: {'train/loss': 0.37569698691368103, 'train/grad_norm_pre_clip': 4.729377269744873, 'timing/data': 0.00019254814833402634, 'timing/model': 0.45795577485114336, 'learning_rate/action_model': 9.855140662742517e-05, 'learning_rate/action_query_proj': 9.855140662742517e-05, 'learning_rate/base': 2.4637851656856293e-05, 'epoch': 0.29}) +[2026-07-27 03:36:18,948][starVLA.training.train_starvla][INFO] - Step 2393, Loss: {'train/loss': 0.29664766788482666, 'train/grad_norm_pre_clip': 4.180397033691406, 'timing/data': 0.0001873658038675785, 'timing/model': 0.4581713262014091, 'learning_rate/action_model': 9.854404405728837e-05, 'learning_rate/action_query_proj': 9.854404405728837e-05, 'learning_rate/base': 2.4636011014322093e-05, 'epoch': 0.29}) +[2026-07-27 03:36:24,536][starVLA.training.train_starvla][INFO] - Step 2394, Loss: {'train/loss': 0.19167083501815796, 'train/grad_norm_pre_clip': 3.7120485305786133, 'timing/data': 0.00018623005598783493, 'timing/model': 0.4672089829109609, 'learning_rate/action_model': 9.85366631123001e-05, 'learning_rate/action_query_proj': 9.85366631123001e-05, 'learning_rate/base': 2.4634165778075026e-05, 'epoch': 0.29}) +[2026-07-27 03:36:30,153][starVLA.training.train_starvla][INFO] - Step 2395, Loss: {'train/loss': 0.17565667629241943, 'train/grad_norm_pre_clip': 2.624898672103882, 'timing/data': 0.0002035810612142086, 'timing/model': 0.4661081191152334, 'learning_rate/action_model': 9.852926379537421e-05, 'learning_rate/action_query_proj': 9.852926379537421e-05, 'learning_rate/base': 2.4632315948843552e-05, 'epoch': 0.29}) +[2026-07-27 03:36:35,750][starVLA.training.train_starvla][INFO] - Step 2396, Loss: {'train/loss': 0.11659274250268936, 'train/grad_norm_pre_clip': 2.408367872238159, 'timing/data': 0.00018808618187904358, 'timing/model': 0.46252431022003293, 'learning_rate/action_model': 9.852184610943185e-05, 'learning_rate/action_query_proj': 9.852184610943185e-05, 'learning_rate/base': 2.4630461527357964e-05, 'epoch': 0.29}) +[2026-07-27 03:36:41,331][starVLA.training.train_starvla][INFO] - Step 2397, Loss: {'train/loss': 0.21118591725826263, 'train/grad_norm_pre_clip': 4.707210063934326, 'timing/data': 0.00018428824841976166, 'timing/model': 0.4580882443115115, 'learning_rate/action_model': 9.851441005740144e-05, 'learning_rate/action_query_proj': 9.851441005740144e-05, 'learning_rate/base': 2.462860251435036e-05, 'epoch': 0.29}) +[2026-07-27 03:36:46,924][starVLA.training.train_starvla][INFO] - Step 2398, Loss: {'train/loss': 0.10648225247859955, 'train/grad_norm_pre_clip': 2.134885311126709, 'timing/data': 0.0001860302872955799, 'timing/model': 0.466066082008183, 'learning_rate/action_model': 9.850695564221858e-05, 'learning_rate/action_query_proj': 9.850695564221858e-05, 'learning_rate/base': 2.4626738910554645e-05, 'epoch': 0.29}) +[2026-07-27 03:36:52,499][starVLA.training.train_starvla][INFO] - Step 2399, Loss: {'train/loss': 0.27155226469039917, 'train/grad_norm_pre_clip': 4.01578950881958, 'timing/data': 0.00019064685329794884, 'timing/model': 0.46310933819040656, 'learning_rate/action_model': 9.849948286682615e-05, 'learning_rate/action_query_proj': 9.849948286682615e-05, 'learning_rate/base': 2.4624870716706537e-05, 'epoch': 0.29}) +[2026-07-27 03:36:58,084][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2400 +[2026-07-27 03:36:58,084][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2400 +[2026-07-27 03:36:58,085][starVLA.training.train_starvla][INFO] - Step 2400, Loss: {'train/loss': 0.2387504279613495, 'train/grad_norm_pre_clip': 5.783323764801025, 'timing/data': 0.00020728306844830513, 'timing/model': 0.465685801114887, 'learning_rate/action_model': 9.849199173417429e-05, 'learning_rate/action_query_proj': 9.849199173417429e-05, 'learning_rate/base': 2.4622997933543573e-05, 'epoch': 0.29}) +[2026-07-27 03:37:03,674][starVLA.training.train_starvla][INFO] - Step 2401, Loss: {'train/loss': 0.20218196511268616, 'train/grad_norm_pre_clip': 4.725001811981201, 'timing/data': 0.00019377702847123146, 'timing/model': 0.4639833807013929, 'learning_rate/action_model': 9.84844822472204e-05, 'learning_rate/action_query_proj': 9.84844822472204e-05, 'learning_rate/base': 2.46211205618051e-05, 'epoch': 0.29}) +[2026-07-27 03:37:09,281][starVLA.training.train_starvla][INFO] - Step 2402, Loss: {'train/loss': 0.12392614781856537, 'train/grad_norm_pre_clip': 2.632174253463745, 'timing/data': 0.0001855962909758091, 'timing/model': 0.4644091110676527, 'learning_rate/action_model': 9.847695440892908e-05, 'learning_rate/action_query_proj': 9.847695440892908e-05, 'learning_rate/base': 2.461923860223227e-05, 'epoch': 0.29}) +[2026-07-27 03:37:14,859][starVLA.training.train_starvla][INFO] - Step 2403, Loss: {'train/loss': 0.2832515835762024, 'train/grad_norm_pre_clip': 3.5460920333862305, 'timing/data': 0.00019541708752512932, 'timing/model': 0.4566331459209323, 'learning_rate/action_model': 9.846940822227222e-05, 'learning_rate/action_query_proj': 9.846940822227222e-05, 'learning_rate/base': 2.4617352055568056e-05, 'epoch': 0.29}) +[2026-07-27 03:37:20,435][starVLA.training.train_starvla][INFO] - Step 2404, Loss: {'train/loss': 0.1176992654800415, 'train/grad_norm_pre_clip': 2.886476993560791, 'timing/data': 0.00018869014456868172, 'timing/model': 0.4631498069502413, 'learning_rate/action_model': 9.846184369022893e-05, 'learning_rate/action_query_proj': 9.846184369022893e-05, 'learning_rate/base': 2.4615460922557233e-05, 'epoch': 0.29}) +[2026-07-27 03:37:26,009][starVLA.training.train_starvla][INFO] - Step 2405, Loss: {'train/loss': 0.4083491265773773, 'train/grad_norm_pre_clip': 4.667464733123779, 'timing/data': 0.00018711574375629425, 'timing/model': 0.46623659087345004, 'learning_rate/action_model': 9.845426081578554e-05, 'learning_rate/action_query_proj': 9.845426081578554e-05, 'learning_rate/base': 2.4613565203946386e-05, 'epoch': 0.29}) +[2026-07-27 03:37:31,599][starVLA.training.train_starvla][INFO] - Step 2406, Loss: {'train/loss': 0.09494051337242126, 'train/grad_norm_pre_clip': 2.4153385162353516, 'timing/data': 0.00021154526621103287, 'timing/model': 0.4601489366032183, 'learning_rate/action_model': 9.844665960193569e-05, 'learning_rate/action_query_proj': 9.844665960193569e-05, 'learning_rate/base': 2.4611664900483923e-05, 'epoch': 0.29}) +[2026-07-27 03:37:37,180][starVLA.training.train_starvla][INFO] - Step 2407, Loss: {'train/loss': 0.2687217593193054, 'train/grad_norm_pre_clip': 5.524029731750488, 'timing/data': 0.00019941013306379318, 'timing/model': 0.4621945028193295, 'learning_rate/action_model': 9.84390400516802e-05, 'learning_rate/action_query_proj': 9.84390400516802e-05, 'learning_rate/base': 2.460976001292005e-05, 'epoch': 0.29}) +[2026-07-27 03:37:43,017][starVLA.training.train_starvla][INFO] - Step 2408, Loss: {'train/loss': 0.14390070736408234, 'train/grad_norm_pre_clip': 2.6871771812438965, 'timing/data': 0.00018927408382296562, 'timing/model': 0.46378521621227264, 'learning_rate/action_model': 9.843140216802716e-05, 'learning_rate/action_query_proj': 9.843140216802716e-05, 'learning_rate/base': 2.460785054200679e-05, 'epoch': 0.29}) +[2026-07-27 03:37:48,608][starVLA.training.train_starvla][INFO] - Step 2409, Loss: {'train/loss': 0.26077407598495483, 'train/grad_norm_pre_clip': 3.7205848693847656, 'timing/data': 0.00019023707136511803, 'timing/model': 0.4599796449765563, 'learning_rate/action_model': 9.842374595399187e-05, 'learning_rate/action_query_proj': 9.842374595399187e-05, 'learning_rate/base': 2.4605936488497968e-05, 'epoch': 0.29}) +[2026-07-27 03:37:54,192][starVLA.training.train_starvla][INFO] - Step 2410, Loss: {'train/loss': 0.19224458932876587, 'train/grad_norm_pre_clip': 3.4907450675964355, 'timing/data': 0.00018787896260619164, 'timing/model': 0.4669899079017341, 'learning_rate/action_model': 9.841607141259689e-05, 'learning_rate/action_query_proj': 9.841607141259689e-05, 'learning_rate/base': 2.4604017853149223e-05, 'epoch': 0.29}) +[2026-07-27 03:37:59,759][starVLA.training.train_starvla][INFO] - Step 2411, Loss: {'train/loss': 0.1522945761680603, 'train/grad_norm_pre_clip': 2.7979798316955566, 'timing/data': 0.00019168108701705933, 'timing/model': 0.4566713301464915, 'learning_rate/action_model': 9.840837854687199e-05, 'learning_rate/action_query_proj': 9.840837854687199e-05, 'learning_rate/base': 2.4602094636717997e-05, 'epoch': 0.29}) +[2026-07-27 03:38:05,374][starVLA.training.train_starvla][INFO] - Step 2412, Loss: {'train/loss': 0.30553102493286133, 'train/grad_norm_pre_clip': 4.323787689208984, 'timing/data': 0.00018502306193113327, 'timing/model': 0.4628322836942971, 'learning_rate/action_model': 9.840066735985422e-05, 'learning_rate/action_query_proj': 9.840066735985422e-05, 'learning_rate/base': 2.4600166839963555e-05, 'epoch': 0.29}) +[2026-07-27 03:38:10,945][starVLA.training.train_starvla][INFO] - Step 2413, Loss: {'train/loss': 0.17879138886928558, 'train/grad_norm_pre_clip': 4.002136707305908, 'timing/data': 0.00018143514171242714, 'timing/model': 0.45714865578338504, 'learning_rate/action_model': 9.839293785458783e-05, 'learning_rate/action_query_proj': 9.839293785458783e-05, 'learning_rate/base': 2.4598234463646957e-05, 'epoch': 0.29}) +[2026-07-27 03:38:16,536][starVLA.training.train_starvla][INFO] - Step 2414, Loss: {'train/loss': 0.34421178698539734, 'train/grad_norm_pre_clip': 4.316072463989258, 'timing/data': 0.0001852228306233883, 'timing/model': 0.465147138107568, 'learning_rate/action_model': 9.838519003412427e-05, 'learning_rate/action_query_proj': 9.838519003412427e-05, 'learning_rate/base': 2.459629750853107e-05, 'epoch': 0.29}) +[2026-07-27 03:38:22,125][starVLA.training.train_starvla][INFO] - Step 2415, Loss: {'train/loss': 0.2757198214530945, 'train/grad_norm_pre_clip': 4.994760990142822, 'timing/data': 0.00018364796414971352, 'timing/model': 0.4625166761688888, 'learning_rate/action_model': 9.837742390152232e-05, 'learning_rate/action_query_proj': 9.837742390152232e-05, 'learning_rate/base': 2.459435597538058e-05, 'epoch': 0.29}) +[2026-07-27 03:38:27,697][starVLA.training.train_starvla][INFO] - Step 2416, Loss: {'train/loss': 0.15293395519256592, 'train/grad_norm_pre_clip': 2.8103015422821045, 'timing/data': 0.0001805000938475132, 'timing/model': 0.4660426019690931, 'learning_rate/action_model': 9.836963945984786e-05, 'learning_rate/action_query_proj': 9.836963945984786e-05, 'learning_rate/base': 2.4592409864961965e-05, 'epoch': 0.29}) +[2026-07-27 03:38:33,274][starVLA.training.train_starvla][INFO] - Step 2417, Loss: {'train/loss': 0.1903855949640274, 'train/grad_norm_pre_clip': 3.271235942840576, 'timing/data': 0.000185276847332716, 'timing/model': 0.46333983493968844, 'learning_rate/action_model': 9.83618367121741e-05, 'learning_rate/action_query_proj': 9.83618367121741e-05, 'learning_rate/base': 2.4590459178043526e-05, 'epoch': 0.29}) +[2026-07-27 03:38:38,815][starVLA.training.train_starvla][INFO] - Step 2418, Loss: {'train/loss': 0.15752540528774261, 'train/grad_norm_pre_clip': 2.7051751613616943, 'timing/data': 0.0001821061596274376, 'timing/model': 0.4571445141918957, 'learning_rate/action_model': 9.835401566158145e-05, 'learning_rate/action_query_proj': 9.835401566158145e-05, 'learning_rate/base': 2.4588503915395362e-05, 'epoch': 0.29}) +[2026-07-27 03:38:44,411][starVLA.training.train_starvla][INFO] - Step 2419, Loss: {'train/loss': 0.1966932713985443, 'train/grad_norm_pre_clip': 3.4856207370758057, 'timing/data': 0.0001949341967701912, 'timing/model': 0.45649549597874284, 'learning_rate/action_model': 9.834617631115751e-05, 'learning_rate/action_query_proj': 9.834617631115751e-05, 'learning_rate/base': 2.4586544077789378e-05, 'epoch': 0.29}) +[2026-07-27 03:38:50,002][starVLA.training.train_starvla][INFO] - Step 2420, Loss: {'train/loss': 0.14461049437522888, 'train/grad_norm_pre_clip': 2.479722261428833, 'timing/data': 0.00018660491332411766, 'timing/model': 0.46726563619449735, 'learning_rate/action_model': 9.833831866399716e-05, 'learning_rate/action_query_proj': 9.833831866399716e-05, 'learning_rate/base': 2.458457966599929e-05, 'epoch': 0.29}) +[2026-07-27 03:38:55,562][starVLA.training.train_starvla][INFO] - Step 2421, Loss: {'train/loss': 0.2621167004108429, 'train/grad_norm_pre_clip': 3.7588987350463867, 'timing/data': 0.00018342304974794388, 'timing/model': 0.45728679839521646, 'learning_rate/action_model': 9.833044272320245e-05, 'learning_rate/action_query_proj': 9.833044272320245e-05, 'learning_rate/base': 2.4582610680800612e-05, 'epoch': 0.29}) +[2026-07-27 03:39:01,150][starVLA.training.train_starvla][INFO] - Step 2422, Loss: {'train/loss': 0.24798926711082458, 'train/grad_norm_pre_clip': 4.7401909828186035, 'timing/data': 0.00018791481852531433, 'timing/model': 0.46366382809355855, 'learning_rate/action_model': 9.832254849188268e-05, 'learning_rate/action_query_proj': 9.832254849188268e-05, 'learning_rate/base': 2.458063712297067e-05, 'epoch': 0.29}) +[2026-07-27 03:39:06,731][starVLA.training.train_starvla][INFO] - Step 2423, Loss: {'train/loss': 0.31706365942955017, 'train/grad_norm_pre_clip': 5.228954792022705, 'timing/data': 0.0001834840513765812, 'timing/model': 0.46153777791187167, 'learning_rate/action_model': 9.831463597315437e-05, 'learning_rate/action_query_proj': 9.831463597315437e-05, 'learning_rate/base': 2.4578658993288592e-05, 'epoch': 0.29}) +[2026-07-27 03:39:12,320][starVLA.training.train_starvla][INFO] - Step 2424, Loss: {'train/loss': 0.25217506289482117, 'train/grad_norm_pre_clip': 4.231448650360107, 'timing/data': 0.0001892847940325737, 'timing/model': 0.46204806584864855, 'learning_rate/action_model': 9.830670517014126e-05, 'learning_rate/action_query_proj': 9.830670517014126e-05, 'learning_rate/base': 2.4576676292535316e-05, 'epoch': 0.29}) +[2026-07-27 03:39:17,902][starVLA.training.train_starvla][INFO] - Step 2425, Loss: {'train/loss': 0.22622200846672058, 'train/grad_norm_pre_clip': 3.207397699356079, 'timing/data': 0.00018315017223358154, 'timing/model': 0.4616106366738677, 'learning_rate/action_model': 9.82987560859743e-05, 'learning_rate/action_query_proj': 9.82987560859743e-05, 'learning_rate/base': 2.4574689021493577e-05, 'epoch': 0.29}) +[2026-07-27 03:39:23,477][starVLA.training.train_starvla][INFO] - Step 2426, Loss: {'train/loss': 0.21556001901626587, 'train/grad_norm_pre_clip': 4.210697174072266, 'timing/data': 0.00018629292026162148, 'timing/model': 0.46604969818145037, 'learning_rate/action_model': 9.829078872379169e-05, 'learning_rate/action_query_proj': 9.829078872379169e-05, 'learning_rate/base': 2.4572697180947923e-05, 'epoch': 0.29}) +[2026-07-27 03:39:29,057][starVLA.training.train_starvla][INFO] - Step 2427, Loss: {'train/loss': 0.14349481463432312, 'train/grad_norm_pre_clip': 3.53054141998291, 'timing/data': 0.00018471106886863708, 'timing/model': 0.4639092618599534, 'learning_rate/action_model': 9.828280308673878e-05, 'learning_rate/action_query_proj': 9.828280308673878e-05, 'learning_rate/base': 2.4570700771684696e-05, 'epoch': 0.29}) +[2026-07-27 03:39:34,639][starVLA.training.train_starvla][INFO] - Step 2428, Loss: {'train/loss': 0.23419249057769775, 'train/grad_norm_pre_clip': 3.3025267124176025, 'timing/data': 0.0001859758049249649, 'timing/model': 0.46060638315975666, 'learning_rate/action_model': 9.82747991779682e-05, 'learning_rate/action_query_proj': 9.82747991779682e-05, 'learning_rate/base': 2.456869979449205e-05, 'epoch': 0.29}) +[2026-07-27 03:39:40,229][starVLA.training.train_starvla][INFO] - Step 2429, Loss: {'train/loss': 0.3769146502017975, 'train/grad_norm_pre_clip': 6.756432056427002, 'timing/data': 0.0001829727552831173, 'timing/model': 0.4660649448633194, 'learning_rate/action_model': 9.826677700063977e-05, 'learning_rate/action_query_proj': 9.826677700063977e-05, 'learning_rate/base': 2.4566694250159943e-05, 'epoch': 0.29}) +[2026-07-27 03:39:45,813][starVLA.training.train_starvla][INFO] - Step 2430, Loss: {'train/loss': 0.2865307927131653, 'train/grad_norm_pre_clip': 5.290785312652588, 'timing/data': 0.0001841159537434578, 'timing/model': 0.4610716081224382, 'learning_rate/action_model': 9.825873655792047e-05, 'learning_rate/action_query_proj': 9.825873655792047e-05, 'learning_rate/base': 2.4564684139480118e-05, 'epoch': 0.29}) +[2026-07-27 03:39:51,424][starVLA.training.train_starvla][INFO] - Step 2431, Loss: {'train/loss': 0.16217836737632751, 'train/grad_norm_pre_clip': 3.1343252658843994, 'timing/data': 0.00018461188301444054, 'timing/model': 0.46332506462931633, 'learning_rate/action_model': 9.825067785298459e-05, 'learning_rate/action_query_proj': 9.825067785298459e-05, 'learning_rate/base': 2.4562669463246147e-05, 'epoch': 0.29}) +[2026-07-27 03:39:57,047][starVLA.training.train_starvla][INFO] - Step 2432, Loss: {'train/loss': 0.11587054282426834, 'train/grad_norm_pre_clip': 2.429161787033081, 'timing/data': 0.00018339883536100388, 'timing/model': 0.4634138219989836, 'learning_rate/action_model': 9.824260088901355e-05, 'learning_rate/action_query_proj': 9.824260088901355e-05, 'learning_rate/base': 2.456065022225339e-05, 'epoch': 0.3}) +[2026-07-27 03:40:02,618][starVLA.training.train_starvla][INFO] - Step 2433, Loss: {'train/loss': 0.1933886855840683, 'train/grad_norm_pre_clip': 3.8315062522888184, 'timing/data': 0.00018532108515501022, 'timing/model': 0.4655606811866164, 'learning_rate/action_model': 9.823450566919606e-05, 'learning_rate/action_query_proj': 9.823450566919606e-05, 'learning_rate/base': 2.4558626417299015e-05, 'epoch': 0.3}) +[2026-07-27 03:40:08,470][starVLA.training.train_starvla][INFO] - Step 2434, Loss: {'train/loss': 0.22956952452659607, 'train/grad_norm_pre_clip': 3.339138984680176, 'timing/data': 0.00018323585391044617, 'timing/model': 0.46382816415280104, 'learning_rate/action_model': 9.82263921967279e-05, 'learning_rate/action_query_proj': 9.82263921967279e-05, 'learning_rate/base': 2.4556598049181975e-05, 'epoch': 0.3}) +[2026-07-27 03:40:14,063][starVLA.training.train_starvla][INFO] - Step 2435, Loss: {'train/loss': 0.45042383670806885, 'train/grad_norm_pre_clip': 7.528350353240967, 'timing/data': 0.00018442096188664436, 'timing/model': 0.46320964582264423, 'learning_rate/action_model': 9.821826047481222e-05, 'learning_rate/action_query_proj': 9.821826047481222e-05, 'learning_rate/base': 2.4554565118703056e-05, 'epoch': 0.3}) +[2026-07-27 03:40:19,882][starVLA.training.train_starvla][INFO] - Step 2436, Loss: {'train/loss': 0.12052882462739944, 'train/grad_norm_pre_clip': 3.305377960205078, 'timing/data': 0.00019499706104397774, 'timing/model': 0.46336392499506474, 'learning_rate/action_model': 9.821011050665924e-05, 'learning_rate/action_query_proj': 9.821011050665924e-05, 'learning_rate/base': 2.455252762666481e-05, 'epoch': 0.3}) +[2026-07-27 03:40:25,486][starVLA.training.train_starvla][INFO] - Step 2437, Loss: {'train/loss': 0.18468628823757172, 'train/grad_norm_pre_clip': 4.285468101501465, 'timing/data': 0.00019478192552924156, 'timing/model': 0.4637320190668106, 'learning_rate/action_model': 9.820194229548645e-05, 'learning_rate/action_query_proj': 9.820194229548645e-05, 'learning_rate/base': 2.4550485573871612e-05, 'epoch': 0.3}) +[2026-07-27 03:40:31,058][starVLA.training.train_starvla][INFO] - Step 2438, Loss: {'train/loss': 0.22412337362766266, 'train/grad_norm_pre_clip': 4.7580156326293945, 'timing/data': 0.00018286798149347305, 'timing/model': 0.4640075140632689, 'learning_rate/action_model': 9.819375584451857e-05, 'learning_rate/action_query_proj': 9.819375584451857e-05, 'learning_rate/base': 2.454843896112964e-05, 'epoch': 0.3}) +[2026-07-27 03:40:36,640][starVLA.training.train_starvla][INFO] - Step 2439, Loss: {'train/loss': 0.19680485129356384, 'train/grad_norm_pre_clip': 3.375469446182251, 'timing/data': 0.00018614763393998146, 'timing/model': 0.45973210874944925, 'learning_rate/action_model': 9.818555115698742e-05, 'learning_rate/action_query_proj': 9.818555115698742e-05, 'learning_rate/base': 2.4546387789246856e-05, 'epoch': 0.3}) +[2026-07-27 03:40:42,238][starVLA.training.train_starvla][INFO] - Step 2440, Loss: {'train/loss': 0.2443690001964569, 'train/grad_norm_pre_clip': 5.051225185394287, 'timing/data': 0.000186992809176445, 'timing/model': 0.4621042679063976, 'learning_rate/action_model': 9.817732823613213e-05, 'learning_rate/action_query_proj': 9.817732823613213e-05, 'learning_rate/base': 2.4544332059033032e-05, 'epoch': 0.3}) +[2026-07-27 03:40:47,823][starVLA.training.train_starvla][INFO] - Step 2441, Loss: {'train/loss': 0.18451711535453796, 'train/grad_norm_pre_clip': 3.5459702014923096, 'timing/data': 0.00018529407680034637, 'timing/model': 0.46269877161830664, 'learning_rate/action_model': 9.816908708519896e-05, 'learning_rate/action_query_proj': 9.816908708519896e-05, 'learning_rate/base': 2.454227177129974e-05, 'epoch': 0.3}) +[2026-07-27 03:40:53,405][starVLA.training.train_starvla][INFO] - Step 2442, Loss: {'train/loss': 0.3085916042327881, 'train/grad_norm_pre_clip': 7.0142292976379395, 'timing/data': 0.0001946217380464077, 'timing/model': 0.45724978391081095, 'learning_rate/action_model': 9.816082770744137e-05, 'learning_rate/action_query_proj': 9.816082770744137e-05, 'learning_rate/base': 2.4540206926860343e-05, 'epoch': 0.3}) +[2026-07-27 03:40:58,987][starVLA.training.train_starvla][INFO] - Step 2443, Loss: {'train/loss': 0.11521648615598679, 'train/grad_norm_pre_clip': 2.867901563644409, 'timing/data': 0.00019259005784988403, 'timing/model': 0.46444441098719835, 'learning_rate/action_model': 9.815255010612007e-05, 'learning_rate/action_query_proj': 9.815255010612007e-05, 'learning_rate/base': 2.4538137526530018e-05, 'epoch': 0.3}) +[2026-07-27 03:41:04,562][starVLA.training.train_starvla][INFO] - Step 2444, Loss: {'train/loss': 0.28719663619995117, 'train/grad_norm_pre_clip': 4.550296783447266, 'timing/data': 0.0001844479702413082, 'timing/model': 0.4620598270557821, 'learning_rate/action_model': 9.814425428450289e-05, 'learning_rate/action_query_proj': 9.814425428450289e-05, 'learning_rate/base': 2.4536063571125723e-05, 'epoch': 0.3}) +[2026-07-27 03:41:10,142][starVLA.training.train_starvla][INFO] - Step 2445, Loss: {'train/loss': 0.29853570461273193, 'train/grad_norm_pre_clip': 3.5767393112182617, 'timing/data': 0.0001849103718996048, 'timing/model': 0.45607998594641685, 'learning_rate/action_model': 9.81359402458649e-05, 'learning_rate/action_query_proj': 9.81359402458649e-05, 'learning_rate/base': 2.4533985061466225e-05, 'epoch': 0.3}) +[2026-07-27 03:41:15,725][starVLA.training.train_starvla][INFO] - Step 2446, Loss: {'train/loss': 0.1884097307920456, 'train/grad_norm_pre_clip': 3.637521743774414, 'timing/data': 0.00018417881801724434, 'timing/model': 0.4619174343533814, 'learning_rate/action_model': 9.812760799348835e-05, 'learning_rate/action_query_proj': 9.812760799348835e-05, 'learning_rate/base': 2.4531901998372088e-05, 'epoch': 0.3}) +[2026-07-27 03:41:21,319][starVLA.training.train_starvla][INFO] - Step 2447, Loss: {'train/loss': 0.16049163043498993, 'train/grad_norm_pre_clip': 3.804647922515869, 'timing/data': 0.00019203685224056244, 'timing/model': 0.4653878384269774, 'learning_rate/action_model': 9.811925753066269e-05, 'learning_rate/action_query_proj': 9.811925753066269e-05, 'learning_rate/base': 2.4529814382665672e-05, 'epoch': 0.3}) +[2026-07-27 03:41:26,893][starVLA.training.train_starvla][INFO] - Step 2448, Loss: {'train/loss': 0.23312784731388092, 'train/grad_norm_pre_clip': 4.743290424346924, 'timing/data': 0.0001878039911389351, 'timing/model': 0.4673729110509157, 'learning_rate/action_model': 9.811088886068454e-05, 'learning_rate/action_query_proj': 9.811088886068454e-05, 'learning_rate/base': 2.4527722215171135e-05, 'epoch': 0.3}) +[2026-07-27 03:41:32,489][starVLA.training.train_starvla][INFO] - Step 2449, Loss: {'train/loss': 0.19680103659629822, 'train/grad_norm_pre_clip': 5.096949577331543, 'timing/data': 0.00018797721713781357, 'timing/model': 0.4723692140541971, 'learning_rate/action_model': 9.810250198685774e-05, 'learning_rate/action_query_proj': 9.810250198685774e-05, 'learning_rate/base': 2.4525625496714435e-05, 'epoch': 0.3}) +[2026-07-27 03:41:38,200][starVLA.training.train_starvla][INFO] - Step 2450, Loss: {'train/loss': 0.27923741936683655, 'train/grad_norm_pre_clip': 4.211532115936279, 'timing/data': 0.00018354272469878197, 'timing/model': 0.4819979681633413, 'learning_rate/action_model': 9.809409691249328e-05, 'learning_rate/action_query_proj': 9.809409691249328e-05, 'learning_rate/base': 2.452352422812332e-05, 'epoch': 0.3}) +[2026-07-27 03:41:43,853][starVLA.training.train_starvla][INFO] - Step 2451, Loss: {'train/loss': 0.16103799641132355, 'train/grad_norm_pre_clip': 3.1987171173095703, 'timing/data': 0.00018405262380838394, 'timing/model': 0.47428834112361073, 'learning_rate/action_model': 9.808567364090932e-05, 'learning_rate/action_query_proj': 9.808567364090932e-05, 'learning_rate/base': 2.452141841022733e-05, 'epoch': 0.3}) +[2026-07-27 03:41:49,483][starVLA.training.train_starvla][INFO] - Step 2452, Loss: {'train/loss': 0.24687831103801727, 'train/grad_norm_pre_clip': 3.938410758972168, 'timing/data': 0.00018136296421289444, 'timing/model': 0.4743743697181344, 'learning_rate/action_model': 9.80772321754313e-05, 'learning_rate/action_query_proj': 9.80772321754313e-05, 'learning_rate/base': 2.4519308043857824e-05, 'epoch': 0.3}) +[2026-07-27 03:41:55,101][starVLA.training.train_starvla][INFO] - Step 2453, Loss: {'train/loss': 0.18712118268013, 'train/grad_norm_pre_clip': 3.0836198329925537, 'timing/data': 0.0001888819970190525, 'timing/model': 0.47456273809075356, 'learning_rate/action_model': 9.80687725193917e-05, 'learning_rate/action_query_proj': 9.80687725193917e-05, 'learning_rate/base': 2.4517193129847925e-05, 'epoch': 0.3}) +[2026-07-27 03:42:00,736][starVLA.training.train_starvla][INFO] - Step 2454, Loss: {'train/loss': 0.13887061178684235, 'train/grad_norm_pre_clip': 2.2674996852874756, 'timing/data': 0.00020177429541945457, 'timing/model': 0.47818322805687785, 'learning_rate/action_model': 9.806029467613033e-05, 'learning_rate/action_query_proj': 9.806029467613033e-05, 'learning_rate/base': 2.4515073669032583e-05, 'epoch': 0.3}) +[2026-07-27 03:42:06,332][starVLA.training.train_starvla][INFO] - Step 2455, Loss: {'train/loss': 0.09946014732122421, 'train/grad_norm_pre_clip': 2.4251670837402344, 'timing/data': 0.00018690433353185654, 'timing/model': 0.46594689320772886, 'learning_rate/action_model': 9.805179864899407e-05, 'learning_rate/action_query_proj': 9.805179864899407e-05, 'learning_rate/base': 2.4512949662248516e-05, 'epoch': 0.3}) +[2026-07-27 03:42:11,939][starVLA.training.train_starvla][INFO] - Step 2456, Loss: {'train/loss': 0.1659347116947174, 'train/grad_norm_pre_clip': 3.7847344875335693, 'timing/data': 0.0001890501007437706, 'timing/model': 0.4655400770716369, 'learning_rate/action_model': 9.804328444133702e-05, 'learning_rate/action_query_proj': 9.804328444133702e-05, 'learning_rate/base': 2.4510821110334254e-05, 'epoch': 0.3}) +[2026-07-27 03:42:17,557][starVLA.training.train_starvla][INFO] - Step 2457, Loss: {'train/loss': 0.2775987982749939, 'train/grad_norm_pre_clip': 4.129715442657471, 'timing/data': 0.00018694298341870308, 'timing/model': 0.46551910834386945, 'learning_rate/action_model': 9.803475205652044e-05, 'learning_rate/action_query_proj': 9.803475205652044e-05, 'learning_rate/base': 2.450868801413011e-05, 'epoch': 0.3}) +[2026-07-27 03:42:23,166][starVLA.training.train_starvla][INFO] - Step 2458, Loss: {'train/loss': 0.13849782943725586, 'train/grad_norm_pre_clip': 2.390232801437378, 'timing/data': 0.00018505286425352097, 'timing/model': 0.4642911087721586, 'learning_rate/action_model': 9.802620149791282e-05, 'learning_rate/action_query_proj': 9.802620149791282e-05, 'learning_rate/base': 2.4506550374478206e-05, 'epoch': 0.3}) +[2026-07-27 03:42:28,761][starVLA.training.train_starvla][INFO] - Step 2459, Loss: {'train/loss': 0.1265987902879715, 'train/grad_norm_pre_clip': 2.841783046722412, 'timing/data': 0.00018813088536262512, 'timing/model': 0.4601295366883278, 'learning_rate/action_model': 9.801763276888974e-05, 'learning_rate/action_query_proj': 9.801763276888974e-05, 'learning_rate/base': 2.4504408192222436e-05, 'epoch': 0.3}) +[2026-07-27 03:42:34,377][starVLA.training.train_starvla][INFO] - Step 2460, Loss: {'train/loss': 0.23409231007099152, 'train/grad_norm_pre_clip': 3.7056214809417725, 'timing/data': 0.00018584588542580605, 'timing/model': 0.465413314756006, 'learning_rate/action_model': 9.800904587283404e-05, 'learning_rate/action_query_proj': 9.800904587283404e-05, 'learning_rate/base': 2.450226146820851e-05, 'epoch': 0.3}) +[2026-07-27 03:42:40,075][starVLA.training.train_starvla][INFO] - Step 2461, Loss: {'train/loss': 0.11950813233852386, 'train/grad_norm_pre_clip': 3.298816680908203, 'timing/data': 0.0001850249245762825, 'timing/model': 0.6008654227480292, 'learning_rate/action_model': 9.800044081313569e-05, 'learning_rate/action_query_proj': 9.800044081313569e-05, 'learning_rate/base': 2.4500110203283923e-05, 'epoch': 0.3}) +[2026-07-27 03:42:45,859][starVLA.training.train_starvla][INFO] - Step 2462, Loss: {'train/loss': 0.1330844759941101, 'train/grad_norm_pre_clip': 3.1861159801483154, 'timing/data': 0.00024017412215471268, 'timing/model': 0.46687003457918763, 'learning_rate/action_model': 9.799181759319177e-05, 'learning_rate/action_query_proj': 9.799181759319177e-05, 'learning_rate/base': 2.4497954398297944e-05, 'epoch': 0.3}) +[2026-07-27 03:42:51,443][starVLA.training.train_starvla][INFO] - Step 2463, Loss: {'train/loss': 0.20498597621917725, 'train/grad_norm_pre_clip': 3.244576930999756, 'timing/data': 0.00018807407468557358, 'timing/model': 0.4615133968181908, 'learning_rate/action_model': 9.798317621640667e-05, 'learning_rate/action_query_proj': 9.798317621640667e-05, 'learning_rate/base': 2.449579405410167e-05, 'epoch': 0.3}) +[2026-07-27 03:42:57,030][starVLA.training.train_starvla][INFO] - Step 2464, Loss: {'train/loss': 0.15021051466464996, 'train/grad_norm_pre_clip': 2.560408353805542, 'timing/data': 0.00018838513642549515, 'timing/model': 0.4668160378932953, 'learning_rate/action_model': 9.797451668619182e-05, 'learning_rate/action_query_proj': 9.797451668619182e-05, 'learning_rate/base': 2.4493629171547955e-05, 'epoch': 0.3}) +[2026-07-27 03:43:02,597][starVLA.training.train_starvla][INFO] - Step 2465, Loss: {'train/loss': 0.19472050666809082, 'train/grad_norm_pre_clip': 3.5860543251037598, 'timing/data': 0.00018619606271386147, 'timing/model': 0.4606235711835325, 'learning_rate/action_model': 9.796583900596586e-05, 'learning_rate/action_query_proj': 9.796583900596586e-05, 'learning_rate/base': 2.4491459751491465e-05, 'epoch': 0.3}) +[2026-07-27 03:43:08,171][starVLA.training.train_starvla][INFO] - Step 2466, Loss: {'train/loss': 0.2659691870212555, 'train/grad_norm_pre_clip': 2.9547085762023926, 'timing/data': 0.00018600886687636375, 'timing/model': 0.4661188586615026, 'learning_rate/action_model': 9.795714317915465e-05, 'learning_rate/action_query_proj': 9.795714317915465e-05, 'learning_rate/base': 2.448928579478866e-05, 'epoch': 0.3}) +[2026-07-27 03:43:13,744][starVLA.training.train_starvla][INFO] - Step 2467, Loss: {'train/loss': 0.11195226013660431, 'train/grad_norm_pre_clip': 3.035519599914551, 'timing/data': 0.00019174814224243164, 'timing/model': 0.4662362337112427, 'learning_rate/action_model': 9.794842920919113e-05, 'learning_rate/action_query_proj': 9.794842920919113e-05, 'learning_rate/base': 2.4487107302297782e-05, 'epoch': 0.3}) +[2026-07-27 03:43:19,331][starVLA.training.train_starvla][INFO] - Step 2468, Loss: {'train/loss': 0.1980637013912201, 'train/grad_norm_pre_clip': 3.444706678390503, 'timing/data': 0.0002044658176600933, 'timing/model': 0.45968413492664695, 'learning_rate/action_model': 9.793969709951543e-05, 'learning_rate/action_query_proj': 9.793969709951543e-05, 'learning_rate/base': 2.4484924274878857e-05, 'epoch': 0.3}) +[2026-07-27 03:43:24,914][starVLA.training.train_starvla][INFO] - Step 2469, Loss: {'train/loss': 0.10679267346858978, 'train/grad_norm_pre_clip': 2.003603458404541, 'timing/data': 0.0001862109638750553, 'timing/model': 0.46110636088997126, 'learning_rate/action_model': 9.793094685357484e-05, 'learning_rate/action_query_proj': 9.793094685357484e-05, 'learning_rate/base': 2.448273671339371e-05, 'epoch': 0.3}) +[2026-07-27 03:43:30,493][starVLA.training.train_starvla][INFO] - Step 2470, Loss: {'train/loss': 0.23126503825187683, 'train/grad_norm_pre_clip': 5.179784774780273, 'timing/data': 0.00018923310562968254, 'timing/model': 0.4613408837467432, 'learning_rate/action_model': 9.792217847482387e-05, 'learning_rate/action_query_proj': 9.792217847482387e-05, 'learning_rate/base': 2.4480544618705968e-05, 'epoch': 0.3}) +[2026-07-27 03:43:36,075][starVLA.training.train_starvla][INFO] - Step 2471, Loss: {'train/loss': 0.23445294797420502, 'train/grad_norm_pre_clip': 4.431254863739014, 'timing/data': 0.00019678007811307907, 'timing/model': 0.45899439323693514, 'learning_rate/action_model': 9.791339196672409e-05, 'learning_rate/action_query_proj': 9.791339196672409e-05, 'learning_rate/base': 2.4478347991681022e-05, 'epoch': 0.3}) +[2026-07-27 03:43:41,672][starVLA.training.train_starvla][INFO] - Step 2472, Loss: {'train/loss': 0.20374761521816254, 'train/grad_norm_pre_clip': 3.536231756210327, 'timing/data': 0.00018421001732349396, 'timing/model': 0.46584377670660615, 'learning_rate/action_model': 9.79045873327443e-05, 'learning_rate/action_query_proj': 9.79045873327443e-05, 'learning_rate/base': 2.4476146833186076e-05, 'epoch': 0.3}) +[2026-07-27 03:43:47,239][starVLA.training.train_starvla][INFO] - Step 2473, Loss: {'train/loss': 0.2712915539741516, 'train/grad_norm_pre_clip': 4.506248950958252, 'timing/data': 0.00018956419080495834, 'timing/model': 0.46647615684196353, 'learning_rate/action_model': 9.789576457636042e-05, 'learning_rate/action_query_proj': 9.789576457636042e-05, 'learning_rate/base': 2.4473941144090105e-05, 'epoch': 0.3}) +[2026-07-27 03:43:53,072][starVLA.training.train_starvla][INFO] - Step 2474, Loss: {'train/loss': 0.23139342665672302, 'train/grad_norm_pre_clip': 4.4003586769104, 'timing/data': 0.00018562795594334602, 'timing/model': 0.5877568288706243, 'learning_rate/action_model': 9.788692370105551e-05, 'learning_rate/action_query_proj': 9.788692370105551e-05, 'learning_rate/base': 2.4471730925263877e-05, 'epoch': 0.3}) +[2026-07-27 03:43:58,732][starVLA.training.train_starvla][INFO] - Step 2475, Loss: {'train/loss': 0.3223162293434143, 'train/grad_norm_pre_clip': 5.767147064208984, 'timing/data': 0.00018456578254699707, 'timing/model': 0.4610683936625719, 'learning_rate/action_model': 9.787806471031985e-05, 'learning_rate/action_query_proj': 9.787806471031985e-05, 'learning_rate/base': 2.4469516177579963e-05, 'epoch': 0.3}) +[2026-07-27 03:44:04,344][starVLA.training.train_starvla][INFO] - Step 2476, Loss: {'train/loss': 0.16269506514072418, 'train/grad_norm_pre_clip': 3.8401403427124023, 'timing/data': 0.00020165089517831802, 'timing/model': 0.4632146288640797, 'learning_rate/action_model': 9.786918760765082e-05, 'learning_rate/action_query_proj': 9.786918760765082e-05, 'learning_rate/base': 2.4467296901912704e-05, 'epoch': 0.3}) +[2026-07-27 03:44:09,899][starVLA.training.train_starvla][INFO] - Step 2477, Loss: {'train/loss': 0.29070523381233215, 'train/grad_norm_pre_clip': 3.8513145446777344, 'timing/data': 0.0001798029989004135, 'timing/model': 0.46645657904446125, 'learning_rate/action_model': 9.786029239655294e-05, 'learning_rate/action_query_proj': 9.786029239655294e-05, 'learning_rate/base': 2.4465073099138234e-05, 'epoch': 0.3}) +[2026-07-27 03:44:15,443][starVLA.training.train_starvla][INFO] - Step 2478, Loss: {'train/loss': 0.1222527027130127, 'train/grad_norm_pre_clip': 2.969423294067383, 'timing/data': 0.0001883767545223236, 'timing/model': 0.46147063467651606, 'learning_rate/action_model': 9.78513790805379e-05, 'learning_rate/action_query_proj': 9.78513790805379e-05, 'learning_rate/base': 2.4462844770134474e-05, 'epoch': 0.3}) +[2026-07-27 03:44:21,011][starVLA.training.train_starvla][INFO] - Step 2479, Loss: {'train/loss': 0.20408140122890472, 'train/grad_norm_pre_clip': 3.246509552001953, 'timing/data': 0.0001927027478814125, 'timing/model': 0.46536709321662784, 'learning_rate/action_model': 9.784244766312455e-05, 'learning_rate/action_query_proj': 9.784244766312455e-05, 'learning_rate/base': 2.4460611915781137e-05, 'epoch': 0.3}) +[2026-07-27 03:44:26,584][starVLA.training.train_starvla][INFO] - Step 2480, Loss: {'train/loss': 0.12736675143241882, 'train/grad_norm_pre_clip': 2.876723527908325, 'timing/data': 0.00018454482778906822, 'timing/model': 0.46441452810540795, 'learning_rate/action_model': 9.783349814783888e-05, 'learning_rate/action_query_proj': 9.783349814783888e-05, 'learning_rate/base': 2.445837453695972e-05, 'epoch': 0.3}) +[2026-07-27 03:44:32,175][starVLA.training.train_starvla][INFO] - Step 2481, Loss: {'train/loss': 0.18660926818847656, 'train/grad_norm_pre_clip': 4.084866523742676, 'timing/data': 0.0001874561421573162, 'timing/model': 0.46361498115584254, 'learning_rate/action_model': 9.782453053821398e-05, 'learning_rate/action_query_proj': 9.782453053821398e-05, 'learning_rate/base': 2.4456132634553494e-05, 'epoch': 0.3}) +[2026-07-27 03:44:37,762][starVLA.training.train_starvla][INFO] - Step 2482, Loss: {'train/loss': 0.19626547396183014, 'train/grad_norm_pre_clip': 3.120903491973877, 'timing/data': 0.00018478231504559517, 'timing/model': 0.4653332307934761, 'learning_rate/action_model': 9.781554483779016e-05, 'learning_rate/action_query_proj': 9.781554483779016e-05, 'learning_rate/base': 2.445388620944754e-05, 'epoch': 0.3}) +[2026-07-27 03:44:43,345][starVLA.training.train_starvla][INFO] - Step 2483, Loss: {'train/loss': 0.2923397123813629, 'train/grad_norm_pre_clip': 3.8720462322235107, 'timing/data': 0.00018255691975355148, 'timing/model': 0.46266222884878516, 'learning_rate/action_model': 9.78065410501148e-05, 'learning_rate/action_query_proj': 9.78065410501148e-05, 'learning_rate/base': 2.44516352625287e-05, 'epoch': 0.3}) +[2026-07-27 03:44:48,918][starVLA.training.train_starvla][INFO] - Step 2484, Loss: {'train/loss': 0.13894346356391907, 'train/grad_norm_pre_clip': 3.7934980392456055, 'timing/data': 0.0001842719502747059, 'timing/model': 0.46508268220350146, 'learning_rate/action_model': 9.779751917874249e-05, 'learning_rate/action_query_proj': 9.779751917874249e-05, 'learning_rate/base': 2.4449379794685623e-05, 'epoch': 0.3}) +[2026-07-27 03:44:54,487][starVLA.training.train_starvla][INFO] - Step 2485, Loss: {'train/loss': 0.13516825437545776, 'train/grad_norm_pre_clip': 2.973731279373169, 'timing/data': 0.00018295599147677422, 'timing/model': 0.46608794992789626, 'learning_rate/action_model': 9.77884792272349e-05, 'learning_rate/action_query_proj': 9.77884792272349e-05, 'learning_rate/base': 2.4447119806808725e-05, 'epoch': 0.3}) +[2026-07-27 03:45:00,040][starVLA.training.train_starvla][INFO] - Step 2486, Loss: {'train/loss': 0.15674570202827454, 'train/grad_norm_pre_clip': 3.3602678775787354, 'timing/data': 0.00019294489175081253, 'timing/model': 0.46503372490406036, 'learning_rate/action_model': 9.777942119916085e-05, 'learning_rate/action_query_proj': 9.777942119916085e-05, 'learning_rate/base': 2.4444855299790212e-05, 'epoch': 0.3}) +[2026-07-27 03:45:05,600][starVLA.training.train_starvla][INFO] - Step 2487, Loss: {'train/loss': 0.17125357687473297, 'train/grad_norm_pre_clip': 3.3462860584259033, 'timing/data': 0.00018189707770943642, 'timing/model': 0.46732659777626395, 'learning_rate/action_model': 9.777034509809633e-05, 'learning_rate/action_query_proj': 9.777034509809633e-05, 'learning_rate/base': 2.4442586274524083e-05, 'epoch': 0.3}) +[2026-07-27 03:45:11,178][starVLA.training.train_starvla][INFO] - Step 2488, Loss: {'train/loss': 0.1205001175403595, 'train/grad_norm_pre_clip': 2.805556058883667, 'timing/data': 0.0002576191909611225, 'timing/model': 0.4646283220499754, 'learning_rate/action_model': 9.776125092762441e-05, 'learning_rate/action_query_proj': 9.776125092762441e-05, 'learning_rate/base': 2.4440312731906103e-05, 'epoch': 0.3}) +[2026-07-27 03:45:16,754][starVLA.training.train_starvla][INFO] - Step 2489, Loss: {'train/loss': 0.17397813498973846, 'train/grad_norm_pre_clip': 2.699315071105957, 'timing/data': 0.00018129125237464905, 'timing/model': 0.4670492368750274, 'learning_rate/action_model': 9.775213869133535e-05, 'learning_rate/action_query_proj': 9.775213869133535e-05, 'learning_rate/base': 2.4438034672833837e-05, 'epoch': 0.3}) +[2026-07-27 03:45:22,302][starVLA.training.train_starvla][INFO] - Step 2490, Loss: {'train/loss': 0.1231437548995018, 'train/grad_norm_pre_clip': 2.073394775390625, 'timing/data': 0.00018478184938430786, 'timing/model': 0.4648878597654402, 'learning_rate/action_model': 9.774300839282652e-05, 'learning_rate/action_query_proj': 9.774300839282652e-05, 'learning_rate/base': 2.443575209820663e-05, 'epoch': 0.3}) +[2026-07-27 03:45:27,875][starVLA.training.train_starvla][INFO] - Step 2491, Loss: {'train/loss': 0.14585812389850616, 'train/grad_norm_pre_clip': 2.4601614475250244, 'timing/data': 0.00019123824313282967, 'timing/model': 0.4622647697106004, 'learning_rate/action_model': 9.773386003570238e-05, 'learning_rate/action_query_proj': 9.773386003570238e-05, 'learning_rate/base': 2.4433465008925596e-05, 'epoch': 0.3}) +[2026-07-27 03:45:33,436][starVLA.training.train_starvla][INFO] - Step 2492, Loss: {'train/loss': 0.176840677857399, 'train/grad_norm_pre_clip': 3.4399445056915283, 'timing/data': 0.00018376391381025314, 'timing/model': 0.46526018204167485, 'learning_rate/action_model': 9.772469362357461e-05, 'learning_rate/action_query_proj': 9.772469362357461e-05, 'learning_rate/base': 2.4431173405893652e-05, 'epoch': 0.3}) +[2026-07-27 03:45:38,992][starVLA.training.train_starvla][INFO] - Step 2493, Loss: {'train/loss': 0.17850381135940552, 'train/grad_norm_pre_clip': 3.496520757675171, 'timing/data': 0.00018575973808765411, 'timing/model': 0.4587253709323704, 'learning_rate/action_model': 9.771550916006191e-05, 'learning_rate/action_query_proj': 9.771550916006191e-05, 'learning_rate/base': 2.4428877290015478e-05, 'epoch': 0.3}) +[2026-07-27 03:45:44,554][starVLA.training.train_starvla][INFO] - Step 2494, Loss: {'train/loss': 0.11933941394090652, 'train/grad_norm_pre_clip': 3.228297710418701, 'timing/data': 0.00018424168229103088, 'timing/model': 0.4647234841249883, 'learning_rate/action_model': 9.770630664879021e-05, 'learning_rate/action_query_proj': 9.770630664879021e-05, 'learning_rate/base': 2.4426576662197553e-05, 'epoch': 0.3}) +[2026-07-27 03:45:50,113][starVLA.training.train_starvla][INFO] - Step 2495, Loss: {'train/loss': 0.12571892142295837, 'train/grad_norm_pre_clip': 3.0645945072174072, 'timing/data': 0.00018030591309070587, 'timing/model': 0.45668463595211506, 'learning_rate/action_model': 9.769708609339249e-05, 'learning_rate/action_query_proj': 9.769708609339249e-05, 'learning_rate/base': 2.4424271523348122e-05, 'epoch': 0.3}) +[2026-07-27 03:45:55,707][starVLA.training.train_starvla][INFO] - Step 2496, Loss: {'train/loss': 0.19208019971847534, 'train/grad_norm_pre_clip': 3.7276785373687744, 'timing/data': 0.00021888595074415207, 'timing/model': 0.4653836409561336, 'learning_rate/action_model': 9.768784749750887e-05, 'learning_rate/action_query_proj': 9.768784749750887e-05, 'learning_rate/base': 2.4421961874377218e-05, 'epoch': 0.3}) +[2026-07-27 03:46:01,517][starVLA.training.train_starvla][INFO] - Step 2497, Loss: {'train/loss': 0.20921234786510468, 'train/grad_norm_pre_clip': 3.4536139965057373, 'timing/data': 0.00018188916146755219, 'timing/model': 0.46218826435506344, 'learning_rate/action_model': 9.767859086478662e-05, 'learning_rate/action_query_proj': 9.767859086478662e-05, 'learning_rate/base': 2.4419647716196655e-05, 'epoch': 0.3}) +[2026-07-27 03:46:07,171][starVLA.training.train_starvla][INFO] - Step 2498, Loss: {'train/loss': 0.1676938533782959, 'train/grad_norm_pre_clip': 3.9995691776275635, 'timing/data': 0.00020004110410809517, 'timing/model': 0.46262652473524213, 'learning_rate/action_model': 9.766931619888011e-05, 'learning_rate/action_query_proj': 9.766931619888011e-05, 'learning_rate/base': 2.4417329049720028e-05, 'epoch': 0.3}) +[2026-07-27 03:46:12,737][starVLA.training.train_starvla][INFO] - Step 2499, Loss: {'train/loss': 0.2660384774208069, 'train/grad_norm_pre_clip': 4.153954982757568, 'timing/data': 0.00018255412578582764, 'timing/model': 0.46075055794790387, 'learning_rate/action_model': 9.766002350345082e-05, 'learning_rate/action_query_proj': 9.766002350345082e-05, 'learning_rate/base': 2.4415005875862706e-05, 'epoch': 0.3}) +[2026-07-27 03:46:18,307][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2500 +[2026-07-27 03:46:18,307][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2500 +[2026-07-27 03:46:18,308][starVLA.training.train_starvla][INFO] - Step 2500, Loss: {'train/loss': 0.11806732416152954, 'train/grad_norm_pre_clip': 2.3192758560180664, 'timing/data': 0.00018565403297543526, 'timing/model': 0.46536875888705254, 'learning_rate/action_model': 9.765071278216737e-05, 'learning_rate/action_query_proj': 9.765071278216737e-05, 'learning_rate/base': 2.4412678195541843e-05, 'epoch': 0.3}) +[2026-07-27 03:46:18,312][accelerate.accelerator][INFO] - Saving current state to /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2500_state +[2026-07-27 03:46:18,313][accelerate.accelerator][INFO] - Saving DeepSpeed Model and Optimizer +[2026-07-27 03:47:05,020][accelerate.accelerator][INFO] - DeepSpeed Model and Optimizer saved to output dir /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2500_state/pytorch_model +[2026-07-27 03:47:05,020][accelerate.checkpointing][INFO] - Sampler state for dataloader 0 saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2500_state/sampler.bin +[2026-07-27 03:47:05,023][accelerate.checkpointing][INFO] - Random states saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_2500_state/random_states_0.pkl +[2026-07-27 03:47:46,183][starVLA.training.rl_games.checkpoint_sync][INFO] - HF checkpoint sync disabled; skipping upload for step 2500 +[2026-07-27 03:47:46,183][starVLA.training.train_starvla][INFO] - 📊 Saving accessed configuration... +[2026-07-27 03:47:46,198][starVLA.training.train_starvla][INFO] - ✅ Configuration files saved +[2026-07-27 03:47:51,908][starVLA.training.train_starvla][INFO] - Step 2501, Loss: {'train/loss': 0.16070032119750977, 'train/grad_norm_pre_clip': 2.9930319786071777, 'timing/data': 0.0001921001821756363, 'timing/model': 0.47973410319536924, 'learning_rate/action_model': 9.764138403870548e-05, 'learning_rate/action_query_proj': 9.764138403870548e-05, 'learning_rate/base': 2.441034600967637e-05, 'epoch': 0.3}) +[2026-07-27 03:47:57,570][starVLA.training.train_starvla][INFO] - Step 2502, Loss: {'train/loss': 0.20854565501213074, 'train/grad_norm_pre_clip': 4.172630310058594, 'timing/data': 0.00020115496590733528, 'timing/model': 0.47247378807514906, 'learning_rate/action_model': 9.7632037276748e-05, 'learning_rate/action_query_proj': 9.7632037276748e-05, 'learning_rate/base': 2.4408009319187e-05, 'epoch': 0.3}) +[2026-07-27 03:48:03,182][starVLA.training.train_starvla][INFO] - Step 2503, Loss: {'train/loss': 0.12140122801065445, 'train/grad_norm_pre_clip': 4.100634574890137, 'timing/data': 0.00018344074487686157, 'timing/model': 0.4675928680226207, 'learning_rate/action_model': 9.762267249998487e-05, 'learning_rate/action_query_proj': 9.762267249998487e-05, 'learning_rate/base': 2.4405668124996217e-05, 'epoch': 0.3}) +[2026-07-27 03:48:08,822][starVLA.training.train_starvla][INFO] - Step 2504, Loss: {'train/loss': 0.09392575919628143, 'train/grad_norm_pre_clip': 2.2421417236328125, 'timing/data': 0.00018416205421090126, 'timing/model': 0.4682430108077824, 'learning_rate/action_model': 9.761328971211315e-05, 'learning_rate/action_query_proj': 9.761328971211315e-05, 'learning_rate/base': 2.4403322428028287e-05, 'epoch': 0.3}) +[2026-07-27 03:48:14,468][starVLA.training.train_starvla][INFO] - Step 2505, Loss: {'train/loss': 0.1627683788537979, 'train/grad_norm_pre_clip': 3.761631488800049, 'timing/data': 0.0002041351981461048, 'timing/model': 0.46367446333169937, 'learning_rate/action_model': 9.760388891683704e-05, 'learning_rate/action_query_proj': 9.760388891683704e-05, 'learning_rate/base': 2.440097222920926e-05, 'epoch': 0.3}) +[2026-07-27 03:48:20,172][starVLA.training.train_starvla][INFO] - Step 2506, Loss: {'train/loss': 0.25176382064819336, 'train/grad_norm_pre_clip': 3.4392170906066895, 'timing/data': 0.00019198190420866013, 'timing/model': 0.4667679718695581, 'learning_rate/action_model': 9.759447011786783e-05, 'learning_rate/action_query_proj': 9.759447011786783e-05, 'learning_rate/base': 2.4398617529466957e-05, 'epoch': 0.3}) +[2026-07-27 03:48:25,862][starVLA.training.train_starvla][INFO] - Step 2507, Loss: {'train/loss': 0.2372249960899353, 'train/grad_norm_pre_clip': 4.0456862449646, 'timing/data': 0.0002076597884297371, 'timing/model': 0.4667108650319278, 'learning_rate/action_model': 9.758503331892385e-05, 'learning_rate/action_query_proj': 9.758503331892385e-05, 'learning_rate/base': 2.4396258329730964e-05, 'epoch': 0.3}) +[2026-07-27 03:48:31,568][starVLA.training.train_starvla][INFO] - Step 2508, Loss: {'train/loss': 0.23877207934856415, 'train/grad_norm_pre_clip': 5.109228134155273, 'timing/data': 0.00019180122762918472, 'timing/model': 0.4668052992783487, 'learning_rate/action_model': 9.757557852373067e-05, 'learning_rate/action_query_proj': 9.757557852373067e-05, 'learning_rate/base': 2.4393894630932668e-05, 'epoch': 0.3}) +[2026-07-27 03:48:37,236][starVLA.training.train_starvla][INFO] - Step 2509, Loss: {'train/loss': 0.24104152619838715, 'train/grad_norm_pre_clip': 4.42243766784668, 'timing/data': 0.00019811280071735382, 'timing/model': 0.46624123910441995, 'learning_rate/action_model': 9.756610573602087e-05, 'learning_rate/action_query_proj': 9.756610573602087e-05, 'learning_rate/base': 2.4391526434005218e-05, 'epoch': 0.3}) +[2026-07-27 03:48:42,885][starVLA.training.train_starvla][INFO] - Step 2510, Loss: {'train/loss': 0.22636327147483826, 'train/grad_norm_pre_clip': 4.427290439605713, 'timing/data': 0.00020434986799955368, 'timing/model': 0.4676861581392586, 'learning_rate/action_model': 9.755661495953414e-05, 'learning_rate/action_query_proj': 9.755661495953414e-05, 'learning_rate/base': 2.4389153739883535e-05, 'epoch': 0.3}) +[2026-07-27 03:48:48,530][starVLA.training.train_starvla][INFO] - Step 2511, Loss: {'train/loss': 0.24869602918624878, 'train/grad_norm_pre_clip': 3.51058030128479, 'timing/data': 0.00019833119586110115, 'timing/model': 0.4661254920065403, 'learning_rate/action_model': 9.754710619801732e-05, 'learning_rate/action_query_proj': 9.754710619801732e-05, 'learning_rate/base': 2.438677654950433e-05, 'epoch': 0.3}) +[2026-07-27 03:48:54,183][starVLA.training.train_starvla][INFO] - Step 2512, Loss: {'train/loss': 0.30311691761016846, 'train/grad_norm_pre_clip': 4.75082540512085, 'timing/data': 0.0001917337067425251, 'timing/model': 0.46493868017569184, 'learning_rate/action_model': 9.753757945522428e-05, 'learning_rate/action_query_proj': 9.753757945522428e-05, 'learning_rate/base': 2.438439486380607e-05, 'epoch': 0.3}) +[2026-07-27 03:48:59,838][starVLA.training.train_starvla][INFO] - Step 2513, Loss: {'train/loss': 0.26023322343826294, 'train/grad_norm_pre_clip': 3.780088186264038, 'timing/data': 0.0002025873400270939, 'timing/model': 0.465391815174371, 'learning_rate/action_model': 9.752803473491605e-05, 'learning_rate/action_query_proj': 9.752803473491605e-05, 'learning_rate/base': 2.4382008683729013e-05, 'epoch': 0.3}) +[2026-07-27 03:49:05,489][starVLA.training.train_starvla][INFO] - Step 2514, Loss: {'train/loss': 0.15927787125110626, 'train/grad_norm_pre_clip': 2.748853921890259, 'timing/data': 0.00019929418340325356, 'timing/model': 0.4672742821276188, 'learning_rate/action_model': 9.751847204086074e-05, 'learning_rate/action_query_proj': 9.751847204086074e-05, 'learning_rate/base': 2.4379618010215186e-05, 'epoch': 0.3}) +[2026-07-27 03:49:11,323][starVLA.training.train_starvla][INFO] - Step 2515, Loss: {'train/loss': 0.336088627576828, 'train/grad_norm_pre_clip': 4.3149590492248535, 'timing/data': 0.00018996186554431915, 'timing/model': 0.6480067982338369, 'learning_rate/action_model': 9.750889137683354e-05, 'learning_rate/action_query_proj': 9.750889137683354e-05, 'learning_rate/base': 2.4377222844208385e-05, 'epoch': 0.31}) +[2026-07-27 03:49:16,997][starVLA.training.train_starvla][INFO] - Step 2516, Loss: {'train/loss': 0.1481218934059143, 'train/grad_norm_pre_clip': 2.4939167499542236, 'timing/data': 0.000220464076846838, 'timing/model': 0.4669916848652065, 'learning_rate/action_model': 9.749929274661674e-05, 'learning_rate/action_query_proj': 9.749929274661674e-05, 'learning_rate/base': 2.4374823186654185e-05, 'epoch': 0.31}) +[2026-07-27 03:49:22,645][starVLA.training.train_starvla][INFO] - Step 2517, Loss: {'train/loss': 0.17285306751728058, 'train/grad_norm_pre_clip': 2.5178232192993164, 'timing/data': 0.00020809471607208252, 'timing/model': 0.46509016724303365, 'learning_rate/action_model': 9.748967615399975e-05, 'learning_rate/action_query_proj': 9.748967615399975e-05, 'learning_rate/base': 2.4372419038499937e-05, 'epoch': 0.31}) +[2026-07-27 03:49:28,554][starVLA.training.train_starvla][INFO] - Step 2518, Loss: {'train/loss': 0.15143023431301117, 'train/grad_norm_pre_clip': 2.940401554107666, 'timing/data': 0.0001825038343667984, 'timing/model': 0.4658828992396593, 'learning_rate/action_model': 9.748004160277901e-05, 'learning_rate/action_query_proj': 9.748004160277901e-05, 'learning_rate/base': 2.4370010400694753e-05, 'epoch': 0.31}) +[2026-07-27 03:49:34,186][starVLA.training.train_starvla][INFO] - Step 2519, Loss: {'train/loss': 0.16308097541332245, 'train/grad_norm_pre_clip': 3.3086233139038086, 'timing/data': 0.00018282607197761536, 'timing/model': 0.4650388490408659, 'learning_rate/action_model': 9.747038909675812e-05, 'learning_rate/action_query_proj': 9.747038909675812e-05, 'learning_rate/base': 2.436759727418953e-05, 'epoch': 0.31}) +[2026-07-27 03:49:39,835][starVLA.training.train_starvla][INFO] - Step 2520, Loss: {'train/loss': 0.1464400738477707, 'train/grad_norm_pre_clip': 3.2269415855407715, 'timing/data': 0.000308220274746418, 'timing/model': 0.4677530899643898, 'learning_rate/action_model': 9.746071863974773e-05, 'learning_rate/action_query_proj': 9.746071863974773e-05, 'learning_rate/base': 2.4365179659936933e-05, 'epoch': 0.31}) +[2026-07-27 03:49:45,471][starVLA.training.train_starvla][INFO] - Step 2521, Loss: {'train/loss': 0.18112216889858246, 'train/grad_norm_pre_clip': 2.5230050086975098, 'timing/data': 0.00019493699073791504, 'timing/model': 0.46517689898610115, 'learning_rate/action_model': 9.745103023556558e-05, 'learning_rate/action_query_proj': 9.745103023556558e-05, 'learning_rate/base': 2.4362757558891396e-05, 'epoch': 0.31}) +[2026-07-27 03:49:51,119][starVLA.training.train_starvla][INFO] - Step 2522, Loss: {'train/loss': 0.289028525352478, 'train/grad_norm_pre_clip': 5.204047679901123, 'timing/data': 0.00018251407891511917, 'timing/model': 0.46480926079675555, 'learning_rate/action_model': 9.74413238880365e-05, 'learning_rate/action_query_proj': 9.74413238880365e-05, 'learning_rate/base': 2.4360330972009125e-05, 'epoch': 0.31}) +[2026-07-27 03:49:56,770][starVLA.training.train_starvla][INFO] - Step 2523, Loss: {'train/loss': 0.19952264428138733, 'train/grad_norm_pre_clip': 3.5946240425109863, 'timing/data': 0.00017941603437066078, 'timing/model': 0.46612138487398624, 'learning_rate/action_model': 9.743159960099239e-05, 'learning_rate/action_query_proj': 9.743159960099239e-05, 'learning_rate/base': 2.4357899900248097e-05, 'epoch': 0.31}) +[2026-07-27 03:50:02,410][starVLA.training.train_starvla][INFO] - Step 2524, Loss: {'train/loss': 0.15245485305786133, 'train/grad_norm_pre_clip': 3.1238863468170166, 'timing/data': 0.00018511386588215828, 'timing/model': 0.4661024990491569, 'learning_rate/action_model': 9.742185737827226e-05, 'learning_rate/action_query_proj': 9.742185737827226e-05, 'learning_rate/base': 2.4355464344568065e-05, 'epoch': 0.31}) +[2026-07-27 03:50:08,059][starVLA.training.train_starvla][INFO] - Step 2525, Loss: {'train/loss': 0.09864699095487595, 'train/grad_norm_pre_clip': 1.7658021450042725, 'timing/data': 0.00019416259601712227, 'timing/model': 0.46733154775574803, 'learning_rate/action_model': 9.741209722372218e-05, 'learning_rate/action_query_proj': 9.741209722372218e-05, 'learning_rate/base': 2.4353024305930544e-05, 'epoch': 0.31}) +[2026-07-27 03:50:13,716][starVLA.training.train_starvla][INFO] - Step 2526, Loss: {'train/loss': 0.1499514877796173, 'train/grad_norm_pre_clip': 2.557790994644165, 'timing/data': 0.00018627289682626724, 'timing/model': 0.46630728989839554, 'learning_rate/action_model': 9.740231914119531e-05, 'learning_rate/action_query_proj': 9.740231914119531e-05, 'learning_rate/base': 2.4350579785298827e-05, 'epoch': 0.31}) +[2026-07-27 03:50:19,369][starVLA.training.train_starvla][INFO] - Step 2527, Loss: {'train/loss': 0.17906104028224945, 'train/grad_norm_pre_clip': 3.1699790954589844, 'timing/data': 0.00018931832164525986, 'timing/model': 0.46055271476507187, 'learning_rate/action_model': 9.739252313455186e-05, 'learning_rate/action_query_proj': 9.739252313455186e-05, 'learning_rate/base': 2.4348130783637966e-05, 'epoch': 0.31}) +[2026-07-27 03:50:25,003][starVLA.training.train_starvla][INFO] - Step 2528, Loss: {'train/loss': 0.11009789258241653, 'train/grad_norm_pre_clip': 2.4758405685424805, 'timing/data': 0.00018726196140050888, 'timing/model': 0.4655327405780554, 'learning_rate/action_model': 9.738270920765918e-05, 'learning_rate/action_query_proj': 9.738270920765918e-05, 'learning_rate/base': 2.4345677301914794e-05, 'epoch': 0.31}) +[2026-07-27 03:50:30,596][starVLA.training.train_starvla][INFO] - Step 2529, Loss: {'train/loss': 0.1892739236354828, 'train/grad_norm_pre_clip': 3.33994197845459, 'timing/data': 0.00019434327259659767, 'timing/model': 0.4651350579224527, 'learning_rate/action_model': 9.737287736439162e-05, 'learning_rate/action_query_proj': 9.737287736439162e-05, 'learning_rate/base': 2.4343219341097904e-05, 'epoch': 0.31}) +[2026-07-27 03:50:36,244][starVLA.training.train_starvla][INFO] - Step 2530, Loss: {'train/loss': 0.1950380504131317, 'train/grad_norm_pre_clip': 4.008814811706543, 'timing/data': 0.00020175520330667496, 'timing/model': 0.46509421104565263, 'learning_rate/action_model': 9.736302760863063e-05, 'learning_rate/action_query_proj': 9.736302760863063e-05, 'learning_rate/base': 2.4340756902157657e-05, 'epoch': 0.31}) +[2026-07-27 03:50:41,892][starVLA.training.train_starvla][INFO] - Step 2531, Loss: {'train/loss': 0.32969462871551514, 'train/grad_norm_pre_clip': 5.962156295776367, 'timing/data': 0.00020062178373336792, 'timing/model': 0.46430405881255865, 'learning_rate/action_model': 9.735315994426476e-05, 'learning_rate/action_query_proj': 9.735315994426476e-05, 'learning_rate/base': 2.433828998606619e-05, 'epoch': 0.31}) +[2026-07-27 03:50:47,552][starVLA.training.train_starvla][INFO] - Step 2532, Loss: {'train/loss': 0.31447455286979675, 'train/grad_norm_pre_clip': 4.345524311065674, 'timing/data': 0.0001935390755534172, 'timing/model': 0.4655970889143646, 'learning_rate/action_model': 9.734327437518961e-05, 'learning_rate/action_query_proj': 9.734327437518961e-05, 'learning_rate/base': 2.4335818593797402e-05, 'epoch': 0.31}) +[2026-07-27 03:50:53,217][starVLA.training.train_starvla][INFO] - Step 2533, Loss: {'train/loss': 0.3061295449733734, 'train/grad_norm_pre_clip': 4.710183143615723, 'timing/data': 0.00019596191123127937, 'timing/model': 0.46637226594612, 'learning_rate/action_model': 9.733337090530783e-05, 'learning_rate/action_query_proj': 9.733337090530783e-05, 'learning_rate/base': 2.433334272632696e-05, 'epoch': 0.31}) +[2026-07-27 03:50:58,871][starVLA.training.train_starvla][INFO] - Step 2534, Loss: {'train/loss': 0.20304274559020996, 'train/grad_norm_pre_clip': 5.093832015991211, 'timing/data': 0.00019253278151154518, 'timing/model': 0.4656762550584972, 'learning_rate/action_model': 9.732344953852915e-05, 'learning_rate/action_query_proj': 9.732344953852915e-05, 'learning_rate/base': 2.4330862384632288e-05, 'epoch': 0.31}) +[2026-07-27 03:51:04,531][starVLA.training.train_starvla][INFO] - Step 2535, Loss: {'train/loss': 0.41419219970703125, 'train/grad_norm_pre_clip': 6.224934101104736, 'timing/data': 0.000195325817912817, 'timing/model': 0.4644167823716998, 'learning_rate/action_model': 9.73135102787704e-05, 'learning_rate/action_query_proj': 9.73135102787704e-05, 'learning_rate/base': 2.43283775696926e-05, 'epoch': 0.31}) +[2026-07-27 03:51:10,189][starVLA.training.train_starvla][INFO] - Step 2536, Loss: {'train/loss': 0.23787535727024078, 'train/grad_norm_pre_clip': 4.382106304168701, 'timing/data': 0.0003286702558398247, 'timing/model': 0.46593469101935625, 'learning_rate/action_model': 9.73035531299554e-05, 'learning_rate/action_query_proj': 9.73035531299554e-05, 'learning_rate/base': 2.432588828248885e-05, 'epoch': 0.31}) +[2026-07-27 03:51:15,856][starVLA.training.train_starvla][INFO] - Step 2537, Loss: {'train/loss': 0.12526868283748627, 'train/grad_norm_pre_clip': 3.604201078414917, 'timing/data': 0.00018002791330218315, 'timing/model': 0.4664912689477205, 'learning_rate/action_model': 9.72935780960151e-05, 'learning_rate/action_query_proj': 9.72935780960151e-05, 'learning_rate/base': 2.4323394524003775e-05, 'epoch': 0.31}) +[2026-07-27 03:51:21,515][starVLA.training.train_starvla][INFO] - Step 2538, Loss: {'train/loss': 0.12793338298797607, 'train/grad_norm_pre_clip': 2.8832614421844482, 'timing/data': 0.00019035395234823227, 'timing/model': 0.4683937430381775, 'learning_rate/action_model': 9.728358518088747e-05, 'learning_rate/action_query_proj': 9.728358518088747e-05, 'learning_rate/base': 2.4320896295221867e-05, 'epoch': 0.31}) +[2026-07-27 03:51:27,152][starVLA.training.train_starvla][INFO] - Step 2539, Loss: {'train/loss': 0.18749076128005981, 'train/grad_norm_pre_clip': 4.019662380218506, 'timing/data': 0.00018860213458538055, 'timing/model': 0.4627863368950784, 'learning_rate/action_model': 9.727357438851757e-05, 'learning_rate/action_query_proj': 9.727357438851757e-05, 'learning_rate/base': 2.4318393597129393e-05, 'epoch': 0.31}) +[2026-07-27 03:51:32,808][starVLA.training.train_starvla][INFO] - Step 2540, Loss: {'train/loss': 0.28738901019096375, 'train/grad_norm_pre_clip': 5.4722771644592285, 'timing/data': 0.00019097235053777695, 'timing/model': 0.46597607200965285, 'learning_rate/action_model': 9.72635457228575e-05, 'learning_rate/action_query_proj': 9.72635457228575e-05, 'learning_rate/base': 2.4315886430714374e-05, 'epoch': 0.31}) +[2026-07-27 03:51:38,450][starVLA.training.train_starvla][INFO] - Step 2541, Loss: {'train/loss': 0.21254944801330566, 'train/grad_norm_pre_clip': 4.29258394241333, 'timing/data': 0.0001980392262339592, 'timing/model': 0.46409764094278216, 'learning_rate/action_model': 9.72534991878664e-05, 'learning_rate/action_query_proj': 9.72534991878664e-05, 'learning_rate/base': 2.43133747969666e-05, 'epoch': 0.31}) +[2026-07-27 03:51:44,399][starVLA.training.train_starvla][INFO] - Step 2542, Loss: {'train/loss': 0.1554737687110901, 'train/grad_norm_pre_clip': 5.347346782684326, 'timing/data': 0.00025398097932338715, 'timing/model': 0.4642951227724552, 'learning_rate/action_model': 9.724343478751052e-05, 'learning_rate/action_query_proj': 9.724343478751052e-05, 'learning_rate/base': 2.431085869687763e-05, 'epoch': 0.31}) +[2026-07-27 03:51:50,021][starVLA.training.train_starvla][INFO] - Step 2543, Loss: {'train/loss': 0.1290014535188675, 'train/grad_norm_pre_clip': 3.5475308895111084, 'timing/data': 0.00019762804731726646, 'timing/model': 0.4652328002266586, 'learning_rate/action_model': 9.723335252576309e-05, 'learning_rate/action_query_proj': 9.723335252576309e-05, 'learning_rate/base': 2.4308338131440773e-05, 'epoch': 0.31}) +[2026-07-27 03:51:55,627][starVLA.training.train_starvla][INFO] - Step 2544, Loss: {'train/loss': 0.20622481405735016, 'train/grad_norm_pre_clip': 3.6613447666168213, 'timing/data': 0.00018780212849378586, 'timing/model': 0.4625845090486109, 'learning_rate/action_model': 9.722325240660445e-05, 'learning_rate/action_query_proj': 9.722325240660445e-05, 'learning_rate/base': 2.4305813101651112e-05, 'epoch': 0.31}) +[2026-07-27 03:52:01,234][starVLA.training.train_starvla][INFO] - Step 2545, Loss: {'train/loss': 0.24459603428840637, 'train/grad_norm_pre_clip': 3.978708267211914, 'timing/data': 0.00018330197781324387, 'timing/model': 0.45973056834191084, 'learning_rate/action_model': 9.721313443402194e-05, 'learning_rate/action_query_proj': 9.721313443402194e-05, 'learning_rate/base': 2.4303283608505486e-05, 'epoch': 0.31}) +[2026-07-27 03:52:06,847][starVLA.training.train_starvla][INFO] - Step 2546, Loss: {'train/loss': 0.08415649831295013, 'train/grad_norm_pre_clip': 2.438141345977783, 'timing/data': 0.00033592013642191887, 'timing/model': 0.4634182183071971, 'learning_rate/action_model': 9.720299861201003e-05, 'learning_rate/action_query_proj': 9.720299861201003e-05, 'learning_rate/base': 2.4300749653002507e-05, 'epoch': 0.31}) +[2026-07-27 03:52:12,454][starVLA.training.train_starvla][INFO] - Step 2547, Loss: {'train/loss': 0.2053668349981308, 'train/grad_norm_pre_clip': 4.759463787078857, 'timing/data': 0.0001969980075955391, 'timing/model': 0.4652158818207681, 'learning_rate/action_model': 9.719284494457012e-05, 'learning_rate/action_query_proj': 9.719284494457012e-05, 'learning_rate/base': 2.429821123614253e-05, 'epoch': 0.31}) +[2026-07-27 03:52:18,098][starVLA.training.train_starvla][INFO] - Step 2548, Loss: {'train/loss': 0.21594655513763428, 'train/grad_norm_pre_clip': 3.92502760887146, 'timing/data': 0.00019925367087125778, 'timing/model': 0.4659012369811535, 'learning_rate/action_model': 9.718267343571073e-05, 'learning_rate/action_query_proj': 9.718267343571073e-05, 'learning_rate/base': 2.429566835892768e-05, 'epoch': 0.31}) +[2026-07-27 03:52:23,756][starVLA.training.train_starvla][INFO] - Step 2549, Loss: {'train/loss': 0.10486629605293274, 'train/grad_norm_pre_clip': 3.294542074203491, 'timing/data': 0.0001971968449652195, 'timing/model': 0.46567759197205305, 'learning_rate/action_model': 9.717248408944745e-05, 'learning_rate/action_query_proj': 9.717248408944745e-05, 'learning_rate/base': 2.4293121022361863e-05, 'epoch': 0.31}) +[2026-07-27 03:52:29,456][starVLA.training.train_starvla][INFO] - Step 2550, Loss: {'train/loss': 0.2030380666255951, 'train/grad_norm_pre_clip': 4.270969390869141, 'timing/data': 0.0002825232222676277, 'timing/model': 0.4670022539794445, 'learning_rate/action_model': 9.716227690980283e-05, 'learning_rate/action_query_proj': 9.716227690980283e-05, 'learning_rate/base': 2.4290569227450707e-05, 'epoch': 0.31}) +[2026-07-27 03:52:35,077][starVLA.training.train_starvla][INFO] - Step 2551, Loss: {'train/loss': 0.21133936941623688, 'train/grad_norm_pre_clip': 4.493725299835205, 'timing/data': 0.00019943108782172203, 'timing/model': 0.47127058170735836, 'learning_rate/action_model': 9.715205190080652e-05, 'learning_rate/action_query_proj': 9.715205190080652e-05, 'learning_rate/base': 2.428801297520163e-05, 'epoch': 0.31}) +[2026-07-27 03:52:40,729][starVLA.training.train_starvla][INFO] - Step 2552, Loss: {'train/loss': 0.20121699571609497, 'train/grad_norm_pre_clip': 3.2349627017974854, 'timing/data': 0.0001836717128753662, 'timing/model': 0.4705491168424487, 'learning_rate/action_model': 9.71418090664952e-05, 'learning_rate/action_query_proj': 9.71418090664952e-05, 'learning_rate/base': 2.42854522666238e-05, 'epoch': 0.31}) +[2026-07-27 03:52:46,342][starVLA.training.train_starvla][INFO] - Step 2553, Loss: {'train/loss': 0.10311493277549744, 'train/grad_norm_pre_clip': 3.271859645843506, 'timing/data': 0.0001992490142583847, 'timing/model': 0.462790350895375, 'learning_rate/action_model': 9.713154841091254e-05, 'learning_rate/action_query_proj': 9.713154841091254e-05, 'learning_rate/base': 2.4282887102728134e-05, 'epoch': 0.31}) +[2026-07-27 03:52:51,981][starVLA.training.train_starvla][INFO] - Step 2554, Loss: {'train/loss': 0.16765150427818298, 'train/grad_norm_pre_clip': 3.6684038639068604, 'timing/data': 0.00020155496895313263, 'timing/model': 0.4624408697709441, 'learning_rate/action_model': 9.712126993810933e-05, 'learning_rate/action_query_proj': 9.712126993810933e-05, 'learning_rate/base': 2.4280317484527334e-05, 'epoch': 0.31}) +[2026-07-27 03:52:57,621][starVLA.training.train_starvla][INFO] - Step 2555, Loss: {'train/loss': 0.11256252974271774, 'train/grad_norm_pre_clip': 2.16933536529541, 'timing/data': 0.00019161030650138855, 'timing/model': 0.46852996526286006, 'learning_rate/action_model': 9.711097365214335e-05, 'learning_rate/action_query_proj': 9.711097365214335e-05, 'learning_rate/base': 2.4277743413035837e-05, 'epoch': 0.31}) +[2026-07-27 03:53:03,267][starVLA.training.train_starvla][INFO] - Step 2556, Loss: {'train/loss': 0.15465876460075378, 'train/grad_norm_pre_clip': 3.53898549079895, 'timing/data': 0.0002033407799899578, 'timing/model': 0.4651856068521738, 'learning_rate/action_model': 9.710065955707938e-05, 'learning_rate/action_query_proj': 9.710065955707938e-05, 'learning_rate/base': 2.4275164889269844e-05, 'epoch': 0.31}) +[2026-07-27 03:53:08,904][starVLA.training.train_starvla][INFO] - Step 2557, Loss: {'train/loss': 0.15987122058868408, 'train/grad_norm_pre_clip': 4.137704849243164, 'timing/data': 0.00019296491518616676, 'timing/model': 0.46351751685142517, 'learning_rate/action_model': 9.709032765698926e-05, 'learning_rate/action_query_proj': 9.709032765698926e-05, 'learning_rate/base': 2.4272581914247316e-05, 'epoch': 0.31}) +[2026-07-27 03:53:14,524][starVLA.training.train_starvla][INFO] - Step 2558, Loss: {'train/loss': 0.1511511653661728, 'train/grad_norm_pre_clip': 2.687795877456665, 'timing/data': 0.00021355506032705307, 'timing/model': 0.46684370609000325, 'learning_rate/action_model': 9.70799779559519e-05, 'learning_rate/action_query_proj': 9.70799779559519e-05, 'learning_rate/base': 2.4269994488987973e-05, 'epoch': 0.31}) +[2026-07-27 03:53:20,166][starVLA.training.train_starvla][INFO] - Step 2559, Loss: {'train/loss': 0.13621830940246582, 'train/grad_norm_pre_clip': 2.570896625518799, 'timing/data': 0.00018848106265068054, 'timing/model': 0.4678963012993336, 'learning_rate/action_model': 9.706961045805315e-05, 'learning_rate/action_query_proj': 9.706961045805315e-05, 'learning_rate/base': 2.426740261451329e-05, 'epoch': 0.31}) +[2026-07-27 03:53:25,792][starVLA.training.train_starvla][INFO] - Step 2560, Loss: {'train/loss': 0.15350382030010223, 'train/grad_norm_pre_clip': 2.932623863220215, 'timing/data': 0.0001765056513249874, 'timing/model': 0.46267803898081183, 'learning_rate/action_model': 9.705922516738596e-05, 'learning_rate/action_query_proj': 9.705922516738596e-05, 'learning_rate/base': 2.426480629184649e-05, 'epoch': 0.31}) +[2026-07-27 03:53:31,417][starVLA.training.train_starvla][INFO] - Step 2561, Loss: {'train/loss': 0.13808190822601318, 'train/grad_norm_pre_clip': 2.5066146850585938, 'timing/data': 0.0001794886775314808, 'timing/model': 0.4648016248829663, 'learning_rate/action_model': 9.704882208805029e-05, 'learning_rate/action_query_proj': 9.704882208805029e-05, 'learning_rate/base': 2.426220552201257e-05, 'epoch': 0.31}) +[2026-07-27 03:53:37,042][starVLA.training.train_starvla][INFO] - Step 2562, Loss: {'train/loss': 0.2325320988893509, 'train/grad_norm_pre_clip': 4.216452121734619, 'timing/data': 0.00017670495435595512, 'timing/model': 0.4636075827293098, 'learning_rate/action_model': 9.703840122415306e-05, 'learning_rate/action_query_proj': 9.703840122415306e-05, 'learning_rate/base': 2.4259600306038266e-05, 'epoch': 0.31}) +[2026-07-27 03:53:42,694][starVLA.training.train_starvla][INFO] - Step 2563, Loss: {'train/loss': 0.14233514666557312, 'train/grad_norm_pre_clip': 4.141111850738525, 'timing/data': 0.00018313294276595116, 'timing/model': 0.4616168988868594, 'learning_rate/action_model': 9.702796257980835e-05, 'learning_rate/action_query_proj': 9.702796257980835e-05, 'learning_rate/base': 2.4256990644952087e-05, 'epoch': 0.31}) +[2026-07-27 03:53:48,292][starVLA.training.train_starvla][INFO] - Step 2564, Loss: {'train/loss': 0.16781745851039886, 'train/grad_norm_pre_clip': 3.5971033573150635, 'timing/data': 0.00018319720402359962, 'timing/model': 0.4579635001718998, 'learning_rate/action_model': 9.701750615913707e-05, 'learning_rate/action_query_proj': 9.701750615913707e-05, 'learning_rate/base': 2.425437653978427e-05, 'epoch': 0.31}) +[2026-07-27 03:53:53,929][starVLA.training.train_starvla][INFO] - Step 2565, Loss: {'train/loss': 0.14691030979156494, 'train/grad_norm_pre_clip': 2.9884934425354004, 'timing/data': 0.00017902906984090805, 'timing/model': 0.46069164108484983, 'learning_rate/action_model': 9.700703196626731e-05, 'learning_rate/action_query_proj': 9.700703196626731e-05, 'learning_rate/base': 2.4251757991566827e-05, 'epoch': 0.31}) +[2026-07-27 03:53:59,528][starVLA.training.train_starvla][INFO] - Step 2566, Loss: {'train/loss': 0.21293388307094574, 'train/grad_norm_pre_clip': 4.339851379394531, 'timing/data': 0.0001928592100739479, 'timing/model': 0.4635317358188331, 'learning_rate/action_model': 9.699654000533413e-05, 'learning_rate/action_query_proj': 9.699654000533413e-05, 'learning_rate/base': 2.4249135001333532e-05, 'epoch': 0.31}) +[2026-07-27 03:54:05,161][starVLA.training.train_starvla][INFO] - Step 2567, Loss: {'train/loss': 0.08870607614517212, 'train/grad_norm_pre_clip': 2.093310594558716, 'timing/data': 0.00018898490816354752, 'timing/model': 0.46495679719373584, 'learning_rate/action_model': 9.698603028047954e-05, 'learning_rate/action_query_proj': 9.698603028047954e-05, 'learning_rate/base': 2.4246507570119884e-05, 'epoch': 0.31}) +[2026-07-27 03:54:10,783][starVLA.training.train_starvla][INFO] - Step 2568, Loss: {'train/loss': 0.29405471682548523, 'train/grad_norm_pre_clip': 4.409173965454102, 'timing/data': 0.00017623836174607277, 'timing/model': 0.4658000501804054, 'learning_rate/action_model': 9.697550279585263e-05, 'learning_rate/action_query_proj': 9.697550279585263e-05, 'learning_rate/base': 2.4243875698963157e-05, 'epoch': 0.31}) +[2026-07-27 03:54:16,388][starVLA.training.train_starvla][INFO] - Step 2569, Loss: {'train/loss': 0.17094701528549194, 'train/grad_norm_pre_clip': 3.1064059734344482, 'timing/data': 0.0001836349256336689, 'timing/model': 0.4679938149638474, 'learning_rate/action_model': 9.69649575556095e-05, 'learning_rate/action_query_proj': 9.69649575556095e-05, 'learning_rate/base': 2.4241239388902375e-05, 'epoch': 0.31}) +[2026-07-27 03:54:21,997][starVLA.training.train_starvla][INFO] - Step 2570, Loss: {'train/loss': 0.2385863959789276, 'train/grad_norm_pre_clip': 4.354260444641113, 'timing/data': 0.0001937681809067726, 'timing/model': 0.46841369895264506, 'learning_rate/action_model': 9.695439456391323e-05, 'learning_rate/action_query_proj': 9.695439456391323e-05, 'learning_rate/base': 2.4238598640978308e-05, 'epoch': 0.31}) +[2026-07-27 03:54:27,601][starVLA.training.train_starvla][INFO] - Step 2571, Loss: {'train/loss': 0.27869921922683716, 'train/grad_norm_pre_clip': 4.25577449798584, 'timing/data': 0.00019381800666451454, 'timing/model': 0.456203771289438, 'learning_rate/action_model': 9.694381382493394e-05, 'learning_rate/action_query_proj': 9.694381382493394e-05, 'learning_rate/base': 2.4235953456233485e-05, 'epoch': 0.31}) +[2026-07-27 03:54:33,197][starVLA.training.train_starvla][INFO] - Step 2572, Loss: {'train/loss': 0.16815315186977386, 'train/grad_norm_pre_clip': 2.4355628490448, 'timing/data': 0.00019018026068806648, 'timing/model': 0.4677359866909683, 'learning_rate/action_model': 9.693321534284872e-05, 'learning_rate/action_query_proj': 9.693321534284872e-05, 'learning_rate/base': 2.423330383571218e-05, 'epoch': 0.31}) +[2026-07-27 03:54:38,789][starVLA.training.train_starvla][INFO] - Step 2573, Loss: {'train/loss': 0.22337982058525085, 'train/grad_norm_pre_clip': 3.5836148262023926, 'timing/data': 0.00018009589985013008, 'timing/model': 0.45832954766228795, 'learning_rate/action_model': 9.692259912184169e-05, 'learning_rate/action_query_proj': 9.692259912184169e-05, 'learning_rate/base': 2.4230649780460422e-05, 'epoch': 0.31}) +[2026-07-27 03:54:44,375][starVLA.training.train_starvla][INFO] - Step 2574, Loss: {'train/loss': 0.14669522643089294, 'train/grad_norm_pre_clip': 3.046785593032837, 'timing/data': 0.00018650107085704803, 'timing/model': 0.4606528007425368, 'learning_rate/action_model': 9.691196516610395e-05, 'learning_rate/action_query_proj': 9.691196516610395e-05, 'learning_rate/base': 2.4227991291525987e-05, 'epoch': 0.31}) +[2026-07-27 03:54:50,258][starVLA.training.train_starvla][INFO] - Step 2575, Loss: {'train/loss': 0.1980358213186264, 'train/grad_norm_pre_clip': 2.690335512161255, 'timing/data': 0.00018412014469504356, 'timing/model': 0.4606762151233852, 'learning_rate/action_model': 9.690131347983364e-05, 'learning_rate/action_query_proj': 9.690131347983364e-05, 'learning_rate/base': 2.422532836995841e-05, 'epoch': 0.31}) +[2026-07-27 03:54:55,874][starVLA.training.train_starvla][INFO] - Step 2576, Loss: {'train/loss': 0.25169944763183594, 'train/grad_norm_pre_clip': 5.004843711853027, 'timing/data': 0.0001870100386440754, 'timing/model': 0.46321326307952404, 'learning_rate/action_model': 9.689064406723585e-05, 'learning_rate/action_query_proj': 9.689064406723585e-05, 'learning_rate/base': 2.4222661016808963e-05, 'epoch': 0.31}) +[2026-07-27 03:55:01,758][starVLA.training.train_starvla][INFO] - Step 2577, Loss: {'train/loss': 0.1667952984571457, 'train/grad_norm_pre_clip': 2.9722211360931396, 'timing/data': 0.0001878701150417328, 'timing/model': 0.4846832281909883, 'learning_rate/action_model': 9.687995693252274e-05, 'learning_rate/action_query_proj': 9.687995693252274e-05, 'learning_rate/base': 2.4219989233130686e-05, 'epoch': 0.31}) +[2026-07-27 03:55:07,721][starVLA.training.train_starvla][INFO] - Step 2578, Loss: {'train/loss': 0.2981374263763428, 'train/grad_norm_pre_clip': 5.677104949951172, 'timing/data': 0.00018671108409762383, 'timing/model': 0.4807674321345985, 'learning_rate/action_model': 9.686925207991339e-05, 'learning_rate/action_query_proj': 9.686925207991339e-05, 'learning_rate/base': 2.4217313019978348e-05, 'epoch': 0.31}) +[2026-07-27 03:55:13,430][starVLA.training.train_starvla][INFO] - Step 2579, Loss: {'train/loss': 0.21571436524391174, 'train/grad_norm_pre_clip': 5.0374674797058105, 'timing/data': 0.00018689781427383423, 'timing/model': 0.476944066118449, 'learning_rate/action_model': 9.68585295136339e-05, 'learning_rate/action_query_proj': 9.68585295136339e-05, 'learning_rate/base': 2.4214632378408474e-05, 'epoch': 0.31}) +[2026-07-27 03:55:19,110][starVLA.training.train_starvla][INFO] - Step 2580, Loss: {'train/loss': 0.06055155023932457, 'train/grad_norm_pre_clip': 1.6331233978271484, 'timing/data': 0.00018023187294602394, 'timing/model': 0.4888653657399118, 'learning_rate/action_model': 9.684778923791739e-05, 'learning_rate/action_query_proj': 9.684778923791739e-05, 'learning_rate/base': 2.4211947309479347e-05, 'epoch': 0.31}) +[2026-07-27 03:55:24,768][starVLA.training.train_starvla][INFO] - Step 2581, Loss: {'train/loss': 0.17304696142673492, 'train/grad_norm_pre_clip': 3.4874353408813477, 'timing/data': 0.0001823478378355503, 'timing/model': 0.4779817839153111, 'learning_rate/action_model': 9.683703125700392e-05, 'learning_rate/action_query_proj': 9.683703125700392e-05, 'learning_rate/base': 2.420925781425098e-05, 'epoch': 0.31}) +[2026-07-27 03:55:30,352][starVLA.training.train_starvla][INFO] - Step 2582, Loss: {'train/loss': 0.25307488441467285, 'train/grad_norm_pre_clip': 4.39441442489624, 'timing/data': 0.00019672606140375137, 'timing/model': 0.4633615599013865, 'learning_rate/action_model': 9.682625557514062e-05, 'learning_rate/action_query_proj': 9.682625557514062e-05, 'learning_rate/base': 2.4206563893785156e-05, 'epoch': 0.31}) +[2026-07-27 03:55:36,014][starVLA.training.train_starvla][INFO] - Step 2583, Loss: {'train/loss': 0.27482059597969055, 'train/grad_norm_pre_clip': 3.270766496658325, 'timing/data': 0.00018382584676146507, 'timing/model': 0.4635333977639675, 'learning_rate/action_model': 9.68154621965815e-05, 'learning_rate/action_query_proj': 9.68154621965815e-05, 'learning_rate/base': 2.4203865549145376e-05, 'epoch': 0.31}) +[2026-07-27 03:55:41,658][starVLA.training.train_starvla][INFO] - Step 2584, Loss: {'train/loss': 0.07310272753238678, 'train/grad_norm_pre_clip': 1.7198307514190674, 'timing/data': 0.00018756603822112083, 'timing/model': 0.4592284308746457, 'learning_rate/action_model': 9.680465112558767e-05, 'learning_rate/action_query_proj': 9.680465112558767e-05, 'learning_rate/base': 2.4201162781396917e-05, 'epoch': 0.31}) +[2026-07-27 03:55:47,302][starVLA.training.train_starvla][INFO] - Step 2585, Loss: {'train/loss': 0.215586856007576, 'train/grad_norm_pre_clip': 3.8890912532806396, 'timing/data': 0.00018559396266937256, 'timing/model': 0.4622437618672848, 'learning_rate/action_model': 9.679382236642713e-05, 'learning_rate/action_query_proj': 9.679382236642713e-05, 'learning_rate/base': 2.4198455591606783e-05, 'epoch': 0.31}) +[2026-07-27 03:55:52,943][starVLA.training.train_starvla][INFO] - Step 2586, Loss: {'train/loss': 0.15791261196136475, 'train/grad_norm_pre_clip': 2.544268846511841, 'timing/data': 0.0002446286380290985, 'timing/model': 0.46321969386190176, 'learning_rate/action_model': 9.678297592337493e-05, 'learning_rate/action_query_proj': 9.678297592337493e-05, 'learning_rate/base': 2.4195743980843733e-05, 'epoch': 0.31}) +[2026-07-27 03:55:58,576][starVLA.training.train_starvla][INFO] - Step 2587, Loss: {'train/loss': 0.2691813111305237, 'train/grad_norm_pre_clip': 4.850619792938232, 'timing/data': 0.0002939892001450062, 'timing/model': 0.4664784357883036, 'learning_rate/action_model': 9.677211180071304e-05, 'learning_rate/action_query_proj': 9.677211180071304e-05, 'learning_rate/base': 2.419302795017826e-05, 'epoch': 0.31}) +[2026-07-27 03:56:04,215][starVLA.training.train_starvla][INFO] - Step 2588, Loss: {'train/loss': 0.13121819496154785, 'train/grad_norm_pre_clip': 2.438832998275757, 'timing/data': 0.00017712078988552094, 'timing/model': 0.4693601750768721, 'learning_rate/action_model': 9.676123000273049e-05, 'learning_rate/action_query_proj': 9.676123000273049e-05, 'learning_rate/base': 2.4190307500682622e-05, 'epoch': 0.31}) +[2026-07-27 03:56:09,878][starVLA.training.train_starvla][INFO] - Step 2589, Loss: {'train/loss': 0.16715341806411743, 'train/grad_norm_pre_clip': 3.5594229698181152, 'timing/data': 0.00018973788246512413, 'timing/model': 0.4669959251768887, 'learning_rate/action_model': 9.675033053372322e-05, 'learning_rate/action_query_proj': 9.675033053372322e-05, 'learning_rate/base': 2.4187582633430804e-05, 'epoch': 0.31}) +[2026-07-27 03:56:15,521][starVLA.training.train_starvla][INFO] - Step 2590, Loss: {'train/loss': 0.16413956880569458, 'train/grad_norm_pre_clip': 3.2415473461151123, 'timing/data': 0.00025494908913969994, 'timing/model': 0.46637409878894687, 'learning_rate/action_model': 9.673941339799412e-05, 'learning_rate/action_query_proj': 9.673941339799412e-05, 'learning_rate/base': 2.418485334949853e-05, 'epoch': 0.31}) +[2026-07-27 03:56:21,123][starVLA.training.train_starvla][INFO] - Step 2591, Loss: {'train/loss': 0.18729731440544128, 'train/grad_norm_pre_clip': 4.392409324645996, 'timing/data': 0.00018793903291225433, 'timing/model': 0.45624805660918355, 'learning_rate/action_model': 9.672847859985318e-05, 'learning_rate/action_query_proj': 9.672847859985318e-05, 'learning_rate/base': 2.4182119649963294e-05, 'epoch': 0.31}) +[2026-07-27 03:56:26,779][starVLA.training.train_starvla][INFO] - Step 2592, Loss: {'train/loss': 0.2845258116722107, 'train/grad_norm_pre_clip': 4.619822025299072, 'timing/data': 0.0001858607865869999, 'timing/model': 0.4601094056852162, 'learning_rate/action_model': 9.671752614361726e-05, 'learning_rate/action_query_proj': 9.671752614361726e-05, 'learning_rate/base': 2.4179381535904314e-05, 'epoch': 0.31}) +[2026-07-27 03:56:32,405][starVLA.training.train_starvla][INFO] - Step 2593, Loss: {'train/loss': 0.17378437519073486, 'train/grad_norm_pre_clip': 3.2627596855163574, 'timing/data': 0.00017909426242113113, 'timing/model': 0.4582673339173198, 'learning_rate/action_model': 9.670655603361018e-05, 'learning_rate/action_query_proj': 9.670655603361018e-05, 'learning_rate/base': 2.4176639008402545e-05, 'epoch': 0.31}) +[2026-07-27 03:56:38,042][starVLA.training.train_starvla][INFO] - Step 2594, Loss: {'train/loss': 0.13650986552238464, 'train/grad_norm_pre_clip': 3.2004554271698, 'timing/data': 0.00019629066810011864, 'timing/model': 0.4569749590009451, 'learning_rate/action_model': 9.669556827416282e-05, 'learning_rate/action_query_proj': 9.669556827416282e-05, 'learning_rate/base': 2.4173892068540704e-05, 'epoch': 0.31}) +[2026-07-27 03:56:43,685][starVLA.training.train_starvla][INFO] - Step 2595, Loss: {'train/loss': 0.1459631770849228, 'train/grad_norm_pre_clip': 3.3460168838500977, 'timing/data': 0.00020831963047385216, 'timing/model': 0.464806682895869, 'learning_rate/action_model': 9.668456286961291e-05, 'learning_rate/action_query_proj': 9.668456286961291e-05, 'learning_rate/base': 2.4171140717403227e-05, 'epoch': 0.31}) +[2026-07-27 03:56:49,273][starVLA.training.train_starvla][INFO] - Step 2596, Loss: {'train/loss': 0.22125878930091858, 'train/grad_norm_pre_clip': 4.4421162605285645, 'timing/data': 0.00018495135009288788, 'timing/model': 0.46307537192478776, 'learning_rate/action_model': 9.667353982430528e-05, 'learning_rate/action_query_proj': 9.667353982430528e-05, 'learning_rate/base': 2.416838495607632e-05, 'epoch': 0.31}) +[2026-07-27 03:56:54,943][starVLA.training.train_starvla][INFO] - Step 2597, Loss: {'train/loss': 0.23675265908241272, 'train/grad_norm_pre_clip': 4.704843521118164, 'timing/data': 0.00018262816593050957, 'timing/model': 0.5253351251594722, 'learning_rate/action_model': 9.666249914259162e-05, 'learning_rate/action_query_proj': 9.666249914259162e-05, 'learning_rate/base': 2.4165624785647904e-05, 'epoch': 0.32}) +[2026-07-27 03:57:00,551][starVLA.training.train_starvla][INFO] - Step 2598, Loss: {'train/loss': 0.2223881483078003, 'train/grad_norm_pre_clip': 3.8578786849975586, 'timing/data': 0.000177058856934309, 'timing/model': 0.4665369647555053, 'learning_rate/action_model': 9.665144082883059e-05, 'learning_rate/action_query_proj': 9.665144082883059e-05, 'learning_rate/base': 2.4162860207207646e-05, 'epoch': 0.32}) +[2026-07-27 03:57:06,149][starVLA.training.train_starvla][INFO] - Step 2599, Loss: {'train/loss': 0.2391093671321869, 'train/grad_norm_pre_clip': 4.173878192901611, 'timing/data': 0.0001743989996612072, 'timing/model': 0.4626524238847196, 'learning_rate/action_model': 9.664036488738788e-05, 'learning_rate/action_query_proj': 9.664036488738788e-05, 'learning_rate/base': 2.416009122184697e-05, 'epoch': 0.32}) +[2026-07-27 03:57:11,740][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2600 +[2026-07-27 03:57:11,741][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2600 +[2026-07-27 03:57:11,742][starVLA.training.train_starvla][INFO] - Step 2600, Loss: {'train/loss': 0.1250026375055313, 'train/grad_norm_pre_clip': 3.2496073246002197, 'timing/data': 0.00018299883231520653, 'timing/model': 0.4565254612825811, 'learning_rate/action_model': 9.662927132263607e-05, 'learning_rate/action_query_proj': 9.662927132263607e-05, 'learning_rate/base': 2.4157317830659017e-05, 'epoch': 0.32}) +[2026-07-27 03:57:17,440][starVLA.training.train_starvla][INFO] - Step 2601, Loss: {'train/loss': 0.19090302288532257, 'train/grad_norm_pre_clip': 3.602036952972412, 'timing/data': 0.00019138632342219353, 'timing/model': 0.45753475232049823, 'learning_rate/action_model': 9.661816013895474e-05, 'learning_rate/action_query_proj': 9.661816013895474e-05, 'learning_rate/base': 2.4154540034738685e-05, 'epoch': 0.32}) +[2026-07-27 03:57:23,027][starVLA.training.train_starvla][INFO] - Step 2602, Loss: {'train/loss': 0.15412582457065582, 'train/grad_norm_pre_clip': 3.0412657260894775, 'timing/data': 0.00017082178965210915, 'timing/model': 0.4619091982021928, 'learning_rate/action_model': 9.66070313407304e-05, 'learning_rate/action_query_proj': 9.66070313407304e-05, 'learning_rate/base': 2.41517578351826e-05, 'epoch': 0.32}) +[2026-07-27 03:57:28,605][starVLA.training.train_starvla][INFO] - Step 2603, Loss: {'train/loss': 0.28295445442199707, 'train/grad_norm_pre_clip': 3.711397886276245, 'timing/data': 0.00017220107838511467, 'timing/model': 0.4631156511604786, 'learning_rate/action_model': 9.659588493235653e-05, 'learning_rate/action_query_proj': 9.659588493235653e-05, 'learning_rate/base': 2.414897123308913e-05, 'epoch': 0.32}) +[2026-07-27 03:57:34,197][starVLA.training.train_starvla][INFO] - Step 2604, Loss: {'train/loss': 0.15107646584510803, 'train/grad_norm_pre_clip': 3.6705429553985596, 'timing/data': 0.0001788819208741188, 'timing/model': 0.46477316739037633, 'learning_rate/action_model': 9.658472091823355e-05, 'learning_rate/action_query_proj': 9.658472091823355e-05, 'learning_rate/base': 2.4146180229558388e-05, 'epoch': 0.32}) +[2026-07-27 03:57:39,783][starVLA.training.train_starvla][INFO] - Step 2605, Loss: {'train/loss': 0.22945964336395264, 'train/grad_norm_pre_clip': 4.060090065002441, 'timing/data': 0.000173869077116251, 'timing/model': 0.4649896891787648, 'learning_rate/action_model': 9.657353930276884e-05, 'learning_rate/action_query_proj': 9.657353930276884e-05, 'learning_rate/base': 2.414338482569221e-05, 'epoch': 0.32}) +[2026-07-27 03:57:45,366][starVLA.training.train_starvla][INFO] - Step 2606, Loss: {'train/loss': 0.19654664397239685, 'train/grad_norm_pre_clip': 3.2178685665130615, 'timing/data': 0.00017354590818285942, 'timing/model': 0.45611312380060554, 'learning_rate/action_model': 9.656234009037672e-05, 'learning_rate/action_query_proj': 9.656234009037672e-05, 'learning_rate/base': 2.414058502259418e-05, 'epoch': 0.32}) +[2026-07-27 03:57:50,954][starVLA.training.train_starvla][INFO] - Step 2607, Loss: {'train/loss': 0.1470174789428711, 'train/grad_norm_pre_clip': 2.893085241317749, 'timing/data': 0.0001739109866321087, 'timing/model': 0.45678920997306705, 'learning_rate/action_model': 9.655112328547846e-05, 'learning_rate/action_query_proj': 9.655112328547846e-05, 'learning_rate/base': 2.4137780821369614e-05, 'epoch': 0.32}) +[2026-07-27 03:57:56,564][starVLA.training.train_starvla][INFO] - Step 2608, Loss: {'train/loss': 0.31611379981040955, 'train/grad_norm_pre_clip': 4.861012935638428, 'timing/data': 0.00017508398741483688, 'timing/model': 0.46552639082074165, 'learning_rate/action_model': 9.653988889250227e-05, 'learning_rate/action_query_proj': 9.653988889250227e-05, 'learning_rate/base': 2.4134972223125567e-05, 'epoch': 0.32}) +[2026-07-27 03:58:02,197][starVLA.training.train_starvla][INFO] - Step 2609, Loss: {'train/loss': 0.2696470320224762, 'train/grad_norm_pre_clip': 5.5898027420043945, 'timing/data': 0.00017278222367167473, 'timing/model': 0.46424547815695405, 'learning_rate/action_model': 9.652863691588334e-05, 'learning_rate/action_query_proj': 9.652863691588334e-05, 'learning_rate/base': 2.4132159228970834e-05, 'epoch': 0.32}) +[2026-07-27 03:58:07,806][starVLA.training.train_starvla][INFO] - Step 2610, Loss: {'train/loss': 0.17728832364082336, 'train/grad_norm_pre_clip': 4.083207607269287, 'timing/data': 0.00017169490456581116, 'timing/model': 0.46103693870827556, 'learning_rate/action_model': 9.651736736006375e-05, 'learning_rate/action_query_proj': 9.651736736006375e-05, 'learning_rate/base': 2.4129341840015938e-05, 'epoch': 0.32}) +[2026-07-27 03:58:13,430][starVLA.training.train_starvla][INFO] - Step 2611, Loss: {'train/loss': 0.1371496021747589, 'train/grad_norm_pre_clip': 3.232600450515747, 'timing/data': 0.00017449911683797836, 'timing/model': 0.46475013019517064, 'learning_rate/action_model': 9.650608022949255e-05, 'learning_rate/action_query_proj': 9.650608022949255e-05, 'learning_rate/base': 2.4126520057373138e-05, 'epoch': 0.32}) +[2026-07-27 03:58:19,041][starVLA.training.train_starvla][INFO] - Step 2612, Loss: {'train/loss': 0.21476686000823975, 'train/grad_norm_pre_clip': 5.145824432373047, 'timing/data': 0.00017339596524834633, 'timing/model': 0.4624561984091997, 'learning_rate/action_model': 9.64947755286257e-05, 'learning_rate/action_query_proj': 9.64947755286257e-05, 'learning_rate/base': 2.4123693882156424e-05, 'epoch': 0.32}) +[2026-07-27 03:58:24,739][starVLA.training.train_starvla][INFO] - Step 2613, Loss: {'train/loss': 0.21031175553798676, 'train/grad_norm_pre_clip': 2.7362003326416016, 'timing/data': 0.00017990963533520699, 'timing/model': 0.46620479319244623, 'learning_rate/action_model': 9.648345326192614e-05, 'learning_rate/action_query_proj': 9.648345326192614e-05, 'learning_rate/base': 2.4120863315481535e-05, 'epoch': 0.32}) +[2026-07-27 03:58:30,564][starVLA.training.train_starvla][INFO] - Step 2614, Loss: {'train/loss': 0.14382892847061157, 'train/grad_norm_pre_clip': 2.4396116733551025, 'timing/data': 0.00017802882939577103, 'timing/model': 0.47074150387197733, 'learning_rate/action_model': 9.647211343386371e-05, 'learning_rate/action_query_proj': 9.647211343386371e-05, 'learning_rate/base': 2.4118028358465927e-05, 'epoch': 0.32}) +[2026-07-27 03:58:36,223][starVLA.training.train_starvla][INFO] - Step 2615, Loss: {'train/loss': 0.10077853500843048, 'train/grad_norm_pre_clip': 2.8075456619262695, 'timing/data': 0.00017342297360301018, 'timing/model': 0.4698343500494957, 'learning_rate/action_model': 9.64607560489152e-05, 'learning_rate/action_query_proj': 9.64607560489152e-05, 'learning_rate/base': 2.41151890122288e-05, 'epoch': 0.32}) +[2026-07-27 03:58:41,928][starVLA.training.train_starvla][INFO] - Step 2616, Loss: {'train/loss': 0.2325534075498581, 'train/grad_norm_pre_clip': 3.600684642791748, 'timing/data': 0.00017856992781162262, 'timing/model': 0.47009875997900963, 'learning_rate/action_model': 9.644938111156433e-05, 'learning_rate/action_query_proj': 9.644938111156433e-05, 'learning_rate/base': 2.4112345277891082e-05, 'epoch': 0.32}) +[2026-07-27 03:58:47,587][starVLA.training.train_starvla][INFO] - Step 2617, Loss: {'train/loss': 0.20756961405277252, 'train/grad_norm_pre_clip': 4.948137283325195, 'timing/data': 0.0002175699919462204, 'timing/model': 0.4788691569119692, 'learning_rate/action_model': 9.643798862630174e-05, 'learning_rate/action_query_proj': 9.643798862630174e-05, 'learning_rate/base': 2.4109497156575435e-05, 'epoch': 0.32}) +[2026-07-27 03:58:53,503][starVLA.training.train_starvla][INFO] - Step 2618, Loss: {'train/loss': 0.17210644483566284, 'train/grad_norm_pre_clip': 5.058842182159424, 'timing/data': 0.0001750001683831215, 'timing/model': 0.7476928192190826, 'learning_rate/action_model': 9.6426578597625e-05, 'learning_rate/action_query_proj': 9.6426578597625e-05, 'learning_rate/base': 2.410664464940625e-05, 'epoch': 0.32}) +[2026-07-27 03:58:59,149][starVLA.training.train_starvla][INFO] - Step 2619, Loss: {'train/loss': 0.1271229386329651, 'train/grad_norm_pre_clip': 3.003187656402588, 'timing/data': 0.00017205532640218735, 'timing/model': 0.4747002301737666, 'learning_rate/action_model': 9.64151510300386e-05, 'learning_rate/action_query_proj': 9.64151510300386e-05, 'learning_rate/base': 2.410378775750965e-05, 'epoch': 0.32}) +[2026-07-27 03:59:04,807][starVLA.training.train_starvla][INFO] - Step 2620, Loss: {'train/loss': 0.09679079055786133, 'train/grad_norm_pre_clip': 3.3790271282196045, 'timing/data': 0.00017198733985424042, 'timing/model': 0.46908987406641245, 'learning_rate/action_model': 9.640370592805399e-05, 'learning_rate/action_query_proj': 9.640370592805399e-05, 'learning_rate/base': 2.4100926482013497e-05, 'epoch': 0.32}) +[2026-07-27 03:59:10,444][starVLA.training.train_starvla][INFO] - Step 2621, Loss: {'train/loss': 0.12464897334575653, 'train/grad_norm_pre_clip': 2.737140417098999, 'timing/data': 0.0001801508478820324, 'timing/model': 0.4654179038479924, 'learning_rate/action_model': 9.63922432961895e-05, 'learning_rate/action_query_proj': 9.63922432961895e-05, 'learning_rate/base': 2.4098060824047376e-05, 'epoch': 0.32}) +[2026-07-27 03:59:16,078][starVLA.training.train_starvla][INFO] - Step 2622, Loss: {'train/loss': 0.22755756974220276, 'train/grad_norm_pre_clip': 3.2006139755249023, 'timing/data': 0.0001689358614385128, 'timing/model': 0.4734779680147767, 'learning_rate/action_model': 9.638076313897037e-05, 'learning_rate/action_query_proj': 9.638076313897037e-05, 'learning_rate/base': 2.4095190784742594e-05, 'epoch': 0.32}) +[2026-07-27 03:59:21,690][starVLA.training.train_starvla][INFO] - Step 2623, Loss: {'train/loss': 0.06692583113908768, 'train/grad_norm_pre_clip': 2.267298460006714, 'timing/data': 0.00016680872067809105, 'timing/model': 0.46946538565680385, 'learning_rate/action_model': 9.636926546092883e-05, 'learning_rate/action_query_proj': 9.636926546092883e-05, 'learning_rate/base': 2.4092316365232208e-05, 'epoch': 0.32}) +[2026-07-27 03:59:27,317][starVLA.training.train_starvla][INFO] - Step 2624, Loss: {'train/loss': 0.21950551867485046, 'train/grad_norm_pre_clip': 4.773797988891602, 'timing/data': 0.00017141876742243767, 'timing/model': 0.46835045190528035, 'learning_rate/action_model': 9.635775026660396e-05, 'learning_rate/action_query_proj': 9.635775026660396e-05, 'learning_rate/base': 2.408943756665099e-05, 'epoch': 0.32}) +[2026-07-27 03:59:32,968][starVLA.training.train_starvla][INFO] - Step 2625, Loss: {'train/loss': 0.22256684303283691, 'train/grad_norm_pre_clip': 5.032703399658203, 'timing/data': 0.0001766188070178032, 'timing/model': 0.478208898101002, 'learning_rate/action_model': 9.634621756054177e-05, 'learning_rate/action_query_proj': 9.634621756054177e-05, 'learning_rate/base': 2.4086554390135442e-05, 'epoch': 0.32}) +[2026-07-27 03:59:38,611][starVLA.training.train_starvla][INFO] - Step 2626, Loss: {'train/loss': 0.1775323748588562, 'train/grad_norm_pre_clip': 3.6819467544555664, 'timing/data': 0.00018358509987592697, 'timing/model': 0.469601240940392, 'learning_rate/action_model': 9.63346673472952e-05, 'learning_rate/action_query_proj': 9.63346673472952e-05, 'learning_rate/base': 2.40836668368238e-05, 'epoch': 0.32}) +[2026-07-27 03:59:44,229][starVLA.training.train_starvla][INFO] - Step 2627, Loss: {'train/loss': 0.1766093671321869, 'train/grad_norm_pre_clip': 3.5093185901641846, 'timing/data': 0.0001706080511212349, 'timing/model': 0.46818040404468775, 'learning_rate/action_model': 9.632309963142407e-05, 'learning_rate/action_query_proj': 9.632309963142407e-05, 'learning_rate/base': 2.408077490785602e-05, 'epoch': 0.32}) +[2026-07-27 03:59:49,836][starVLA.training.train_starvla][INFO] - Step 2628, Loss: {'train/loss': 0.1399623602628708, 'train/grad_norm_pre_clip': 3.385573625564575, 'timing/data': 0.00017801392823457718, 'timing/model': 0.47172666201367974, 'learning_rate/action_model': 9.631151441749517e-05, 'learning_rate/action_query_proj': 9.631151441749517e-05, 'learning_rate/base': 2.407787860437379e-05, 'epoch': 0.32}) +[2026-07-27 03:59:55,435][starVLA.training.train_starvla][INFO] - Step 2629, Loss: {'train/loss': 0.1633109152317047, 'train/grad_norm_pre_clip': 4.058245658874512, 'timing/data': 0.00017054425552487373, 'timing/model': 0.46831239107996225, 'learning_rate/action_model': 9.629991171008213e-05, 'learning_rate/action_query_proj': 9.629991171008213e-05, 'learning_rate/base': 2.407497792752053e-05, 'epoch': 0.32}) +[2026-07-27 04:00:01,046][starVLA.training.train_starvla][INFO] - Step 2630, Loss: {'train/loss': 0.2059381753206253, 'train/grad_norm_pre_clip': 3.2755544185638428, 'timing/data': 0.00017687678337097168, 'timing/model': 0.4694269639439881, 'learning_rate/action_model': 9.628829151376552e-05, 'learning_rate/action_query_proj': 9.628829151376552e-05, 'learning_rate/base': 2.407207287844138e-05, 'epoch': 0.32}) +[2026-07-27 04:00:06,674][starVLA.training.train_starvla][INFO] - Step 2631, Loss: {'train/loss': 0.15929660201072693, 'train/grad_norm_pre_clip': 3.043081521987915, 'timing/data': 0.00017437292262911797, 'timing/model': 0.47041207179427147, 'learning_rate/action_model': 9.62766538331328e-05, 'learning_rate/action_query_proj': 9.62766538331328e-05, 'learning_rate/base': 2.40691634582832e-05, 'epoch': 0.32}) +[2026-07-27 04:00:12,288][starVLA.training.train_starvla][INFO] - Step 2632, Loss: {'train/loss': 0.2605583071708679, 'train/grad_norm_pre_clip': 3.4613044261932373, 'timing/data': 0.00017591379582881927, 'timing/model': 0.4695942811667919, 'learning_rate/action_model': 9.626499867277837e-05, 'learning_rate/action_query_proj': 9.626499867277837e-05, 'learning_rate/base': 2.4066249668194593e-05, 'epoch': 0.32}) +[2026-07-27 04:00:17,907][starVLA.training.train_starvla][INFO] - Step 2633, Loss: {'train/loss': 0.16771310567855835, 'train/grad_norm_pre_clip': 4.07485818862915, 'timing/data': 0.00017369305714964867, 'timing/model': 0.467427727766335, 'learning_rate/action_model': 9.62533260373035e-05, 'learning_rate/action_query_proj': 9.62533260373035e-05, 'learning_rate/base': 2.4063331509325873e-05, 'epoch': 0.32}) +[2026-07-27 04:00:23,528][starVLA.training.train_starvla][INFO] - Step 2634, Loss: {'train/loss': 0.13431890308856964, 'train/grad_norm_pre_clip': 2.7673821449279785, 'timing/data': 0.00017221085727214813, 'timing/model': 0.46799510857090354, 'learning_rate/action_model': 9.624163593131632e-05, 'learning_rate/action_query_proj': 9.624163593131632e-05, 'learning_rate/base': 2.406040898282908e-05, 'epoch': 0.32}) +[2026-07-27 04:00:29,135][starVLA.training.train_starvla][INFO] - Step 2635, Loss: {'train/loss': 0.14701879024505615, 'train/grad_norm_pre_clip': 3.6993825435638428, 'timing/data': 0.0001735081896185875, 'timing/model': 0.46945728408172727, 'learning_rate/action_model': 9.622992835943193e-05, 'learning_rate/action_query_proj': 9.622992835943193e-05, 'learning_rate/base': 2.4057482089857984e-05, 'epoch': 0.32}) +[2026-07-27 04:00:34,743][starVLA.training.train_starvla][INFO] - Step 2636, Loss: {'train/loss': 0.3980456292629242, 'train/grad_norm_pre_clip': 5.9216628074646, 'timing/data': 0.000170235987752676, 'timing/model': 0.4708886658772826, 'learning_rate/action_model': 9.621820332627229e-05, 'learning_rate/action_query_proj': 9.621820332627229e-05, 'learning_rate/base': 2.4054550831568072e-05, 'epoch': 0.32}) +[2026-07-27 04:00:40,341][starVLA.training.train_starvla][INFO] - Step 2637, Loss: {'train/loss': 0.13818399608135223, 'train/grad_norm_pre_clip': 3.8129024505615234, 'timing/data': 0.00017580296844244003, 'timing/model': 0.46071614930406213, 'learning_rate/action_model': 9.620646083646627e-05, 'learning_rate/action_query_proj': 9.620646083646627e-05, 'learning_rate/base': 2.4051615209116568e-05, 'epoch': 0.32}) +[2026-07-27 04:00:45,929][starVLA.training.train_starvla][INFO] - Step 2638, Loss: {'train/loss': 0.2152939885854721, 'train/grad_norm_pre_clip': 3.934718132019043, 'timing/data': 0.00017442088574171066, 'timing/model': 0.46377191320061684, 'learning_rate/action_model': 9.61947008946496e-05, 'learning_rate/action_query_proj': 9.61947008946496e-05, 'learning_rate/base': 2.40486752236624e-05, 'epoch': 0.32}) +[2026-07-27 04:00:51,521][starVLA.training.train_starvla][INFO] - Step 2639, Loss: {'train/loss': 0.17499111592769623, 'train/grad_norm_pre_clip': 3.2986605167388916, 'timing/data': 0.0001745559275150299, 'timing/model': 0.4663294409401715, 'learning_rate/action_model': 9.618292350546494e-05, 'learning_rate/action_query_proj': 9.618292350546494e-05, 'learning_rate/base': 2.4045730876366235e-05, 'epoch': 0.32}) +[2026-07-27 04:00:57,119][starVLA.training.train_starvla][INFO] - Step 2640, Loss: {'train/loss': 0.10911302268505096, 'train/grad_norm_pre_clip': 2.3409500122070312, 'timing/data': 0.00018179602921009064, 'timing/model': 0.45717810187488794, 'learning_rate/action_model': 9.617112867356178e-05, 'learning_rate/action_query_proj': 9.617112867356178e-05, 'learning_rate/base': 2.4042782168390445e-05, 'epoch': 0.32}) +[2026-07-27 04:01:02,740][starVLA.training.train_starvla][INFO] - Step 2641, Loss: {'train/loss': 0.24885636568069458, 'train/grad_norm_pre_clip': 3.3007211685180664, 'timing/data': 0.00017610099166631699, 'timing/model': 0.4657834321260452, 'learning_rate/action_model': 9.615931640359656e-05, 'learning_rate/action_query_proj': 9.615931640359656e-05, 'learning_rate/base': 2.403982910089914e-05, 'epoch': 0.32}) +[2026-07-27 04:01:08,622][starVLA.training.train_starvla][INFO] - Step 2642, Loss: {'train/loss': 0.08239886164665222, 'train/grad_norm_pre_clip': 1.7517764568328857, 'timing/data': 0.00017730100080370903, 'timing/model': 0.459691371768713, 'learning_rate/action_model': 9.614748670023258e-05, 'learning_rate/action_query_proj': 9.614748670023258e-05, 'learning_rate/base': 2.4036871675058145e-05, 'epoch': 0.32}) +[2026-07-27 04:01:14,227][starVLA.training.train_starvla][INFO] - Step 2643, Loss: {'train/loss': 0.14969390630722046, 'train/grad_norm_pre_clip': 3.6498758792877197, 'timing/data': 0.00017264112830162048, 'timing/model': 0.45669656805694103, 'learning_rate/action_model': 9.613563956814003e-05, 'learning_rate/action_query_proj': 9.613563956814003e-05, 'learning_rate/base': 2.4033909892035006e-05, 'epoch': 0.32}) +[2026-07-27 04:01:19,851][starVLA.training.train_starvla][INFO] - Step 2644, Loss: {'train/loss': 0.1455087512731552, 'train/grad_norm_pre_clip': 3.0089480876922607, 'timing/data': 0.0001837369054555893, 'timing/model': 0.4666757071390748, 'learning_rate/action_model': 9.612377501199592e-05, 'learning_rate/action_query_proj': 9.612377501199592e-05, 'learning_rate/base': 2.403094375299898e-05, 'epoch': 0.32}) +[2026-07-27 04:01:25,777][starVLA.training.train_starvla][INFO] - Step 2645, Loss: {'train/loss': 0.23336994647979736, 'train/grad_norm_pre_clip': 3.291815757751465, 'timing/data': 0.0001727500930428505, 'timing/model': 0.46236756769940257, 'learning_rate/action_model': 9.611189303648423e-05, 'learning_rate/action_query_proj': 9.611189303648423e-05, 'learning_rate/base': 2.4027973259121057e-05, 'epoch': 0.32}) +[2026-07-27 04:01:31,389][starVLA.training.train_starvla][INFO] - Step 2646, Loss: {'train/loss': 0.12397310882806778, 'train/grad_norm_pre_clip': 2.8545045852661133, 'timing/data': 0.00017442088574171066, 'timing/model': 0.46452261274680495, 'learning_rate/action_model': 9.609999364629577e-05, 'learning_rate/action_query_proj': 9.609999364629577e-05, 'learning_rate/base': 2.4024998411573942e-05, 'epoch': 0.32}) +[2026-07-27 04:01:36,961][starVLA.training.train_starvla][INFO] - Step 2647, Loss: {'train/loss': 0.20629553496837616, 'train/grad_norm_pre_clip': 3.8648595809936523, 'timing/data': 0.00017574196681380272, 'timing/model': 0.4614849700592458, 'learning_rate/action_model': 9.608807684612822e-05, 'learning_rate/action_query_proj': 9.608807684612822e-05, 'learning_rate/base': 2.4022019211532055e-05, 'epoch': 0.32}) +[2026-07-27 04:01:42,568][starVLA.training.train_starvla][INFO] - Step 2648, Loss: {'train/loss': 0.18852072954177856, 'train/grad_norm_pre_clip': 2.6784331798553467, 'timing/data': 0.0001751626841723919, 'timing/model': 0.45987054985016584, 'learning_rate/action_model': 9.607614264068618e-05, 'learning_rate/action_query_proj': 9.607614264068618e-05, 'learning_rate/base': 2.4019035660171544e-05, 'epoch': 0.32}) +[2026-07-27 04:01:48,219][starVLA.training.train_starvla][INFO] - Step 2649, Loss: {'train/loss': 0.17676414549350739, 'train/grad_norm_pre_clip': 2.8240699768066406, 'timing/data': 0.00017720507457852364, 'timing/model': 0.4652603860013187, 'learning_rate/action_model': 9.606419103468103e-05, 'learning_rate/action_query_proj': 9.606419103468103e-05, 'learning_rate/base': 2.4016047758670257e-05, 'epoch': 0.32}) +[2026-07-27 04:01:53,817][starVLA.training.train_starvla][INFO] - Step 2650, Loss: {'train/loss': 0.10224374383687973, 'train/grad_norm_pre_clip': 2.470132350921631, 'timing/data': 0.000218201894313097, 'timing/model': 0.46109415125101805, 'learning_rate/action_model': 9.60522220328311e-05, 'learning_rate/action_query_proj': 9.60522220328311e-05, 'learning_rate/base': 2.4013055508207773e-05, 'epoch': 0.32}) +[2026-07-27 04:01:59,429][starVLA.training.train_starvla][INFO] - Step 2651, Loss: {'train/loss': 0.14574606716632843, 'train/grad_norm_pre_clip': 2.8680577278137207, 'timing/data': 0.00017818063497543335, 'timing/model': 0.46178684988990426, 'learning_rate/action_model': 9.604023563986157e-05, 'learning_rate/action_query_proj': 9.604023563986157e-05, 'learning_rate/base': 2.4010058909965392e-05, 'epoch': 0.32}) +[2026-07-27 04:02:05,029][starVLA.training.train_starvla][INFO] - Step 2652, Loss: {'train/loss': 0.11478494107723236, 'train/grad_norm_pre_clip': 2.590336561203003, 'timing/data': 0.00017364602535963058, 'timing/model': 0.4659013687632978, 'learning_rate/action_model': 9.602823186050448e-05, 'learning_rate/action_query_proj': 9.602823186050448e-05, 'learning_rate/base': 2.400705796512612e-05, 'epoch': 0.32}) +[2026-07-27 04:02:10,637][starVLA.training.train_starvla][INFO] - Step 2653, Loss: {'train/loss': 0.11685492843389511, 'train/grad_norm_pre_clip': 2.7609200477600098, 'timing/data': 0.0001705428585410118, 'timing/model': 0.45839593512937427, 'learning_rate/action_model': 9.601621069949873e-05, 'learning_rate/action_query_proj': 9.601621069949873e-05, 'learning_rate/base': 2.400405267487468e-05, 'epoch': 0.32}) +[2026-07-27 04:02:16,224][starVLA.training.train_starvla][INFO] - Step 2654, Loss: {'train/loss': 0.21664151549339294, 'train/grad_norm_pre_clip': 3.012319326400757, 'timing/data': 0.0001828949898481369, 'timing/model': 0.46462204260751605, 'learning_rate/action_model': 9.600417216159006e-05, 'learning_rate/action_query_proj': 9.600417216159006e-05, 'learning_rate/base': 2.4001043040397516e-05, 'epoch': 0.32}) +[2026-07-27 04:02:21,816][starVLA.training.train_starvla][INFO] - Step 2655, Loss: {'train/loss': 0.1784079223871231, 'train/grad_norm_pre_clip': 3.6100220680236816, 'timing/data': 0.00017215684056282043, 'timing/model': 0.45723046688362956, 'learning_rate/action_model': 9.59921162515311e-05, 'learning_rate/action_query_proj': 9.59921162515311e-05, 'learning_rate/base': 2.3998029062882776e-05, 'epoch': 0.32}) +[2026-07-27 04:02:27,393][starVLA.training.train_starvla][INFO] - Step 2656, Loss: {'train/loss': 0.2039172351360321, 'train/grad_norm_pre_clip': 4.450573444366455, 'timing/data': 0.00017871707677841187, 'timing/model': 0.458087848033756, 'learning_rate/action_model': 9.598004297408138e-05, 'learning_rate/action_query_proj': 9.598004297408138e-05, 'learning_rate/base': 2.3995010743520345e-05, 'epoch': 0.32}) +[2026-07-27 04:02:32,977][starVLA.training.train_starvla][INFO] - Step 2657, Loss: {'train/loss': 0.0952487364411354, 'train/grad_norm_pre_clip': 2.6700963973999023, 'timing/data': 0.0001727622002363205, 'timing/model': 0.46208441257476807, 'learning_rate/action_model': 9.596795233400718e-05, 'learning_rate/action_query_proj': 9.596795233400718e-05, 'learning_rate/base': 2.3991988083501796e-05, 'epoch': 0.32}) +[2026-07-27 04:02:38,581][starVLA.training.train_starvla][INFO] - Step 2658, Loss: {'train/loss': 0.2113836109638214, 'train/grad_norm_pre_clip': 4.859818458557129, 'timing/data': 0.00017239106819033623, 'timing/model': 0.45848511811345816, 'learning_rate/action_model': 9.595584433608172e-05, 'learning_rate/action_query_proj': 9.595584433608172e-05, 'learning_rate/base': 2.398896108402043e-05, 'epoch': 0.32}) +[2026-07-27 04:02:44,190][starVLA.training.train_starvla][INFO] - Step 2659, Loss: {'train/loss': 0.06507042050361633, 'train/grad_norm_pre_clip': 1.6376405954360962, 'timing/data': 0.00017166510224342346, 'timing/model': 0.4633109071291983, 'learning_rate/action_model': 9.594371898508504e-05, 'learning_rate/action_query_proj': 9.594371898508504e-05, 'learning_rate/base': 2.398592974627126e-05, 'epoch': 0.32}) +[2026-07-27 04:02:49,801][starVLA.training.train_starvla][INFO] - Step 2660, Loss: {'train/loss': 0.2309562712907791, 'train/grad_norm_pre_clip': 4.010066032409668, 'timing/data': 0.0001861858181655407, 'timing/model': 0.46701036812737584, 'learning_rate/action_model': 9.593157628580404e-05, 'learning_rate/action_query_proj': 9.593157628580404e-05, 'learning_rate/base': 2.398289407145101e-05, 'epoch': 0.32}) +[2026-07-27 04:02:55,393][starVLA.training.train_starvla][INFO] - Step 2661, Loss: {'train/loss': 0.1974165439605713, 'train/grad_norm_pre_clip': 3.1157867908477783, 'timing/data': 0.00017771311104297638, 'timing/model': 0.4651793111115694, 'learning_rate/action_model': 9.591941624303247e-05, 'learning_rate/action_query_proj': 9.591941624303247e-05, 'learning_rate/base': 2.397985406075812e-05, 'epoch': 0.32}) +[2026-07-27 04:03:00,946][starVLA.training.train_starvla][INFO] - Step 2662, Loss: {'train/loss': 0.23176494240760803, 'train/grad_norm_pre_clip': 3.8764522075653076, 'timing/data': 0.0001698979176580906, 'timing/model': 0.4649136778898537, 'learning_rate/action_model': 9.590723886157092e-05, 'learning_rate/action_query_proj': 9.590723886157092e-05, 'learning_rate/base': 2.397680971539273e-05, 'epoch': 0.32}) +[2026-07-27 04:03:06,505][starVLA.training.train_starvla][INFO] - Step 2663, Loss: {'train/loss': 0.10211626440286636, 'train/grad_norm_pre_clip': 2.509493350982666, 'timing/data': 0.00017298804596066475, 'timing/model': 0.4666425408795476, 'learning_rate/action_model': 9.589504414622682e-05, 'learning_rate/action_query_proj': 9.589504414622682e-05, 'learning_rate/base': 2.3973761036556706e-05, 'epoch': 0.32}) +[2026-07-27 04:03:12,074][starVLA.training.train_starvla][INFO] - Step 2664, Loss: {'train/loss': 0.31117382645606995, 'train/grad_norm_pre_clip': 6.644608020782471, 'timing/data': 0.00017357198521494865, 'timing/model': 0.46165675204247236, 'learning_rate/action_model': 9.588283210181446e-05, 'learning_rate/action_query_proj': 9.588283210181446e-05, 'learning_rate/base': 2.3970708025453614e-05, 'epoch': 0.32}) +[2026-07-27 04:03:17,651][starVLA.training.train_starvla][INFO] - Step 2665, Loss: {'train/loss': 0.0804944634437561, 'train/grad_norm_pre_clip': 2.4706501960754395, 'timing/data': 0.00017093494534492493, 'timing/model': 0.46544486191123724, 'learning_rate/action_model': 9.587060273315493e-05, 'learning_rate/action_query_proj': 9.587060273315493e-05, 'learning_rate/base': 2.3967650683288733e-05, 'epoch': 0.32}) +[2026-07-27 04:03:23,228][starVLA.training.train_starvla][INFO] - Step 2666, Loss: {'train/loss': 0.21599207818508148, 'train/grad_norm_pre_clip': 3.4617180824279785, 'timing/data': 0.0001767883077263832, 'timing/model': 0.4606853718869388, 'learning_rate/action_model': 9.585835604507626e-05, 'learning_rate/action_query_proj': 9.585835604507626e-05, 'learning_rate/base': 2.3964589011269066e-05, 'epoch': 0.32}) +[2026-07-27 04:03:28,809][starVLA.training.train_starvla][INFO] - Step 2667, Loss: {'train/loss': 0.10667815059423447, 'train/grad_norm_pre_clip': 3.496469736099243, 'timing/data': 0.00017165113240480423, 'timing/model': 0.4628666406497359, 'learning_rate/action_model': 9.584609204241318e-05, 'learning_rate/action_query_proj': 9.584609204241318e-05, 'learning_rate/base': 2.3961523010603294e-05, 'epoch': 0.32}) +[2026-07-27 04:03:34,387][starVLA.training.train_starvla][INFO] - Step 2668, Loss: {'train/loss': 0.09568938612937927, 'train/grad_norm_pre_clip': 1.9458292722702026, 'timing/data': 0.00017125997692346573, 'timing/model': 0.46057163504883647, 'learning_rate/action_model': 9.583381073000734e-05, 'learning_rate/action_query_proj': 9.583381073000734e-05, 'learning_rate/base': 2.3958452682501835e-05, 'epoch': 0.32}) +[2026-07-27 04:03:39,940][starVLA.training.train_starvla][INFO] - Step 2669, Loss: {'train/loss': 0.1912384033203125, 'train/grad_norm_pre_clip': 4.070225238800049, 'timing/data': 0.00019547296687960625, 'timing/model': 0.46289307391270995, 'learning_rate/action_model': 9.582151211270724e-05, 'learning_rate/action_query_proj': 9.582151211270724e-05, 'learning_rate/base': 2.395537802817681e-05, 'epoch': 0.32}) +[2026-07-27 04:03:45,527][starVLA.training.train_starvla][INFO] - Step 2670, Loss: {'train/loss': 0.07330052554607391, 'train/grad_norm_pre_clip': 2.6441121101379395, 'timing/data': 0.00019276374951004982, 'timing/model': 0.4665110451169312, 'learning_rate/action_model': 9.580919619536814e-05, 'learning_rate/action_query_proj': 9.580919619536814e-05, 'learning_rate/base': 2.3952299048842036e-05, 'epoch': 0.32}) +[2026-07-27 04:03:51,123][starVLA.training.train_starvla][INFO] - Step 2671, Loss: {'train/loss': 0.271639883518219, 'train/grad_norm_pre_clip': 5.278334140777588, 'timing/data': 0.00018211407586932182, 'timing/model': 0.46457080636173487, 'learning_rate/action_model': 9.579686298285219e-05, 'learning_rate/action_query_proj': 9.579686298285219e-05, 'learning_rate/base': 2.3949215745713047e-05, 'epoch': 0.32}) +[2026-07-27 04:03:56,697][starVLA.training.train_starvla][INFO] - Step 2672, Loss: {'train/loss': 0.2593889534473419, 'train/grad_norm_pre_clip': 5.266485214233398, 'timing/data': 0.0001742732711136341, 'timing/model': 0.46072053303942084, 'learning_rate/action_model': 9.578451248002835e-05, 'learning_rate/action_query_proj': 9.578451248002835e-05, 'learning_rate/base': 2.3946128120007087e-05, 'epoch': 0.32}) +[2026-07-27 04:04:02,282][starVLA.training.train_starvla][INFO] - Step 2673, Loss: {'train/loss': 0.14083126187324524, 'train/grad_norm_pre_clip': 3.5819051265716553, 'timing/data': 0.00019368622452020645, 'timing/model': 0.468934825155884, 'learning_rate/action_model': 9.577214469177239e-05, 'learning_rate/action_query_proj': 9.577214469177239e-05, 'learning_rate/base': 2.3943036172943097e-05, 'epoch': 0.32}) +[2026-07-27 04:04:07,856][starVLA.training.train_starvla][INFO] - Step 2674, Loss: {'train/loss': 0.14133912324905396, 'train/grad_norm_pre_clip': 2.8880562782287598, 'timing/data': 0.0001804521307349205, 'timing/model': 0.464313886128366, 'learning_rate/action_model': 9.575975962296692e-05, 'learning_rate/action_query_proj': 9.575975962296692e-05, 'learning_rate/base': 2.393993990574173e-05, 'epoch': 0.32}) +[2026-07-27 04:04:13,426][starVLA.training.train_starvla][INFO] - Step 2675, Loss: {'train/loss': 0.3401780426502228, 'train/grad_norm_pre_clip': 5.16826057434082, 'timing/data': 0.00017332378774881363, 'timing/model': 0.45786247588694096, 'learning_rate/action_model': 9.574735727850137e-05, 'learning_rate/action_query_proj': 9.574735727850137e-05, 'learning_rate/base': 2.3936839319625343e-05, 'epoch': 0.32}) +[2026-07-27 04:04:19,033][starVLA.training.train_starvla][INFO] - Step 2676, Loss: {'train/loss': 0.13905741274356842, 'train/grad_norm_pre_clip': 3.6922607421875, 'timing/data': 0.00019058817997574806, 'timing/model': 0.4821899998933077, 'learning_rate/action_model': 9.573493766327201e-05, 'learning_rate/action_query_proj': 9.573493766327201e-05, 'learning_rate/base': 2.3933734415818002e-05, 'epoch': 0.32}) +[2026-07-27 04:04:24,845][starVLA.training.train_starvla][INFO] - Step 2677, Loss: {'train/loss': 0.342013418674469, 'train/grad_norm_pre_clip': 5.536310195922852, 'timing/data': 0.0001707039773464203, 'timing/model': 0.476459126919508, 'learning_rate/action_model': 9.572250078218187e-05, 'learning_rate/action_query_proj': 9.572250078218187e-05, 'learning_rate/base': 2.3930625195545466e-05, 'epoch': 0.32}) +[2026-07-27 04:04:30,554][starVLA.training.train_starvla][INFO] - Step 2678, Loss: {'train/loss': 0.15136846899986267, 'train/grad_norm_pre_clip': 3.5138933658599854, 'timing/data': 0.00020589865744113922, 'timing/model': 0.4693629960529506, 'learning_rate/action_model': 9.571004664014085e-05, 'learning_rate/action_query_proj': 9.571004664014085e-05, 'learning_rate/base': 2.3927511660035212e-05, 'epoch': 0.32}) +[2026-07-27 04:04:36,172][starVLA.training.train_starvla][INFO] - Step 2679, Loss: {'train/loss': 0.11458897590637207, 'train/grad_norm_pre_clip': 2.9009804725646973, 'timing/data': 0.00018664030358195305, 'timing/model': 0.4648844231851399, 'learning_rate/action_model': 9.569757524206567e-05, 'learning_rate/action_query_proj': 9.569757524206567e-05, 'learning_rate/base': 2.3924393810516417e-05, 'epoch': 0.32}) +[2026-07-27 04:04:41,759][starVLA.training.train_starvla][INFO] - Step 2680, Loss: {'train/loss': 0.09673234075307846, 'train/grad_norm_pre_clip': 3.1429009437561035, 'timing/data': 0.0001959577202796936, 'timing/model': 0.4666468193754554, 'learning_rate/action_model': 9.568508659287979e-05, 'learning_rate/action_query_proj': 9.568508659287979e-05, 'learning_rate/base': 2.3921271648219947e-05, 'epoch': 0.33}) +[2026-07-27 04:04:47,320][starVLA.training.train_starvla][INFO] - Step 2681, Loss: {'train/loss': 0.1502845138311386, 'train/grad_norm_pre_clip': 2.6319403648376465, 'timing/data': 0.00017406325787305832, 'timing/model': 0.4599629039876163, 'learning_rate/action_model': 9.567258069751358e-05, 'learning_rate/action_query_proj': 9.567258069751358e-05, 'learning_rate/base': 2.3918145174378395e-05, 'epoch': 0.33}) +[2026-07-27 04:04:52,926][starVLA.training.train_starvla][INFO] - Step 2682, Loss: {'train/loss': 0.21887674927711487, 'train/grad_norm_pre_clip': 3.7759788036346436, 'timing/data': 0.00018336577340960503, 'timing/model': 0.4661698150448501, 'learning_rate/action_model': 9.566005756090417e-05, 'learning_rate/action_query_proj': 9.566005756090417e-05, 'learning_rate/base': 2.391501439022604e-05, 'epoch': 0.33}) +[2026-07-27 04:04:58,541][starVLA.training.train_starvla][INFO] - Step 2683, Loss: {'train/loss': 0.3311273753643036, 'train/grad_norm_pre_clip': 5.648040771484375, 'timing/data': 0.00017231376841664314, 'timing/model': 0.46250517293810844, 'learning_rate/action_model': 9.564751718799543e-05, 'learning_rate/action_query_proj': 9.564751718799543e-05, 'learning_rate/base': 2.391187929699886e-05, 'epoch': 0.33}) +[2026-07-27 04:05:04,286][starVLA.training.train_starvla][INFO] - Step 2684, Loss: {'train/loss': 0.09410012513399124, 'train/grad_norm_pre_clip': 2.861985683441162, 'timing/data': 0.0001880507916212082, 'timing/model': 0.4669203753583133, 'learning_rate/action_model': 9.563495958373818e-05, 'learning_rate/action_query_proj': 9.563495958373818e-05, 'learning_rate/base': 2.3908739895934545e-05, 'epoch': 0.33}) +[2026-07-27 04:05:09,904][starVLA.training.train_starvla][INFO] - Step 2685, Loss: {'train/loss': 0.1453430950641632, 'train/grad_norm_pre_clip': 2.7552242279052734, 'timing/data': 0.0001726788468658924, 'timing/model': 0.4657486220821738, 'learning_rate/action_model': 9.562238475308993e-05, 'learning_rate/action_query_proj': 9.562238475308993e-05, 'learning_rate/base': 2.3905596188272482e-05, 'epoch': 0.33}) +[2026-07-27 04:05:15,791][starVLA.training.train_starvla][INFO] - Step 2686, Loss: {'train/loss': 0.20808929204940796, 'train/grad_norm_pre_clip': 3.4752228260040283, 'timing/data': 0.0001734062097966671, 'timing/model': 0.4662702428176999, 'learning_rate/action_model': 9.560979270101502e-05, 'learning_rate/action_query_proj': 9.560979270101502e-05, 'learning_rate/base': 2.3902448175253754e-05, 'epoch': 0.33}) +[2026-07-27 04:05:21,368][starVLA.training.train_starvla][INFO] - Step 2687, Loss: {'train/loss': 0.2673814594745636, 'train/grad_norm_pre_clip': 3.8875644207000732, 'timing/data': 0.00018986407667398453, 'timing/model': 0.4625293677672744, 'learning_rate/action_model': 9.559718343248459e-05, 'learning_rate/action_query_proj': 9.559718343248459e-05, 'learning_rate/base': 2.3899295858121147e-05, 'epoch': 0.33}) +[2026-07-27 04:05:26,945][starVLA.training.train_starvla][INFO] - Step 2688, Loss: {'train/loss': 0.16400320827960968, 'train/grad_norm_pre_clip': 2.5466392040252686, 'timing/data': 0.00019088201224803925, 'timing/model': 0.4631931600160897, 'learning_rate/action_model': 9.55845569524766e-05, 'learning_rate/action_query_proj': 9.55845569524766e-05, 'learning_rate/base': 2.389613923811915e-05, 'epoch': 0.33}) +[2026-07-27 04:05:32,510][starVLA.training.train_starvla][INFO] - Step 2689, Loss: {'train/loss': 0.17889562249183655, 'train/grad_norm_pre_clip': 2.981558084487915, 'timing/data': 0.00018316088244318962, 'timing/model': 0.459868841804564, 'learning_rate/action_model': 9.557191326597575e-05, 'learning_rate/action_query_proj': 9.557191326597575e-05, 'learning_rate/base': 2.3892978316493938e-05, 'epoch': 0.33}) +[2026-07-27 04:05:38,084][starVLA.training.train_starvla][INFO] - Step 2690, Loss: {'train/loss': 0.13866281509399414, 'train/grad_norm_pre_clip': 3.028350830078125, 'timing/data': 0.00017736107110977173, 'timing/model': 0.4657915788702667, 'learning_rate/action_model': 9.555925237797362e-05, 'learning_rate/action_query_proj': 9.555925237797362e-05, 'learning_rate/base': 2.3889813094493405e-05, 'epoch': 0.33}) +[2026-07-27 04:05:43,649][starVLA.training.train_starvla][INFO] - Step 2691, Loss: {'train/loss': 0.1299295276403427, 'train/grad_norm_pre_clip': 3.7210512161254883, 'timing/data': 0.00018290989100933075, 'timing/model': 0.4613408828154206, 'learning_rate/action_model': 9.554657429346848e-05, 'learning_rate/action_query_proj': 9.554657429346848e-05, 'learning_rate/base': 2.388664357336712e-05, 'epoch': 0.33}) +[2026-07-27 04:05:49,246][starVLA.training.train_starvla][INFO] - Step 2692, Loss: {'train/loss': 0.13667245209217072, 'train/grad_norm_pre_clip': 2.5848588943481445, 'timing/data': 0.00018624169752001762, 'timing/model': 0.4657364781014621, 'learning_rate/action_model': 9.553387901746546e-05, 'learning_rate/action_query_proj': 9.553387901746546e-05, 'learning_rate/base': 2.3883469754366365e-05, 'epoch': 0.33}) +[2026-07-27 04:05:54,834][starVLA.training.train_starvla][INFO] - Step 2693, Loss: {'train/loss': 0.1580120325088501, 'train/grad_norm_pre_clip': 3.4827311038970947, 'timing/data': 0.0001755962148308754, 'timing/model': 0.4665881269611418, 'learning_rate/action_model': 9.552116655497644e-05, 'learning_rate/action_query_proj': 9.552116655497644e-05, 'learning_rate/base': 2.388029163874411e-05, 'epoch': 0.33}) +[2026-07-27 04:06:00,455][starVLA.training.train_starvla][INFO] - Step 2694, Loss: {'train/loss': 0.0816204696893692, 'train/grad_norm_pre_clip': 2.297563076019287, 'timing/data': 0.00017163297161459923, 'timing/model': 0.4666723790578544, 'learning_rate/action_model': 9.550843691102011e-05, 'learning_rate/action_query_proj': 9.550843691102011e-05, 'learning_rate/base': 2.3877109227755027e-05, 'epoch': 0.33}) +[2026-07-27 04:06:06,033][starVLA.training.train_starvla][INFO] - Step 2695, Loss: {'train/loss': 0.0651819035410881, 'train/grad_norm_pre_clip': 1.8249447345733643, 'timing/data': 0.0001702709123492241, 'timing/model': 0.46592205530032516, 'learning_rate/action_model': 9.549569009062191e-05, 'learning_rate/action_query_proj': 9.549569009062191e-05, 'learning_rate/base': 2.387392252265548e-05, 'epoch': 0.33}) +[2026-07-27 04:06:11,621][starVLA.training.train_starvla][INFO] - Step 2696, Loss: {'train/loss': 0.0925258994102478, 'train/grad_norm_pre_clip': 3.014991044998169, 'timing/data': 0.00017684884369373322, 'timing/model': 0.46552587393671274, 'learning_rate/action_model': 9.548292609881412e-05, 'learning_rate/action_query_proj': 9.548292609881412e-05, 'learning_rate/base': 2.387073152470353e-05, 'epoch': 0.33}) +[2026-07-27 04:06:17,211][starVLA.training.train_starvla][INFO] - Step 2697, Loss: {'train/loss': 0.18611031770706177, 'train/grad_norm_pre_clip': 5.300108432769775, 'timing/data': 0.00017359713092446327, 'timing/model': 0.46728060580790043, 'learning_rate/action_model': 9.547014494063574e-05, 'learning_rate/action_query_proj': 9.547014494063574e-05, 'learning_rate/base': 2.3867536235158935e-05, 'epoch': 0.33}) +[2026-07-27 04:06:22,784][starVLA.training.train_starvla][INFO] - Step 2698, Loss: {'train/loss': 0.10944005101919174, 'train/grad_norm_pre_clip': 2.830214500427246, 'timing/data': 0.00017726095393300056, 'timing/model': 0.4599087256938219, 'learning_rate/action_model': 9.545734662113257e-05, 'learning_rate/action_query_proj': 9.545734662113257e-05, 'learning_rate/base': 2.3864336655283143e-05, 'epoch': 0.33}) +[2026-07-27 04:06:28,373][starVLA.training.train_starvla][INFO] - Step 2699, Loss: {'train/loss': 0.07870390266180038, 'train/grad_norm_pre_clip': 2.433523416519165, 'timing/data': 0.0001750430092215538, 'timing/model': 0.46654736809432507, 'learning_rate/action_model': 9.544453114535719e-05, 'learning_rate/action_query_proj': 9.544453114535719e-05, 'learning_rate/base': 2.3861132786339298e-05, 'epoch': 0.33}) +[2026-07-27 04:06:33,981][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2700 +[2026-07-27 04:06:33,981][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2700 +[2026-07-27 04:06:33,982][starVLA.training.train_starvla][INFO] - Step 2700, Loss: {'train/loss': 0.14794136583805084, 'train/grad_norm_pre_clip': 3.2302732467651367, 'timing/data': 0.0001772092655301094, 'timing/model': 0.4713046057149768, 'learning_rate/action_model': 9.543169851836894e-05, 'learning_rate/action_query_proj': 9.543169851836894e-05, 'learning_rate/base': 2.3857924629592234e-05, 'epoch': 0.33}) +[2026-07-27 04:06:39,600][starVLA.training.train_starvla][INFO] - Step 2701, Loss: {'train/loss': 0.11026692390441895, 'train/grad_norm_pre_clip': 2.921719551086426, 'timing/data': 0.00017549702897667885, 'timing/model': 0.47320779599249363, 'learning_rate/action_model': 9.541884874523394e-05, 'learning_rate/action_query_proj': 9.541884874523394e-05, 'learning_rate/base': 2.3854712186308485e-05, 'epoch': 0.33}) +[2026-07-27 04:06:45,214][starVLA.training.train_starvla][INFO] - Step 2702, Loss: {'train/loss': 0.08381839096546173, 'train/grad_norm_pre_clip': 2.5907511711120605, 'timing/data': 0.0001895260065793991, 'timing/model': 0.4673949000425637, 'learning_rate/action_model': 9.540598183102508e-05, 'learning_rate/action_query_proj': 9.540598183102508e-05, 'learning_rate/base': 2.385149545775627e-05, 'epoch': 0.33}) +[2026-07-27 04:06:50,779][starVLA.training.train_starvla][INFO] - Step 2703, Loss: {'train/loss': 0.14304478466510773, 'train/grad_norm_pre_clip': 2.9509170055389404, 'timing/data': 0.00017839577049016953, 'timing/model': 0.46142995823174715, 'learning_rate/action_model': 9.5393097780822e-05, 'learning_rate/action_query_proj': 9.5393097780822e-05, 'learning_rate/base': 2.38482744452055e-05, 'epoch': 0.33}) +[2026-07-27 04:06:56,386][starVLA.training.train_starvla][INFO] - Step 2704, Loss: {'train/loss': 0.08096665143966675, 'train/grad_norm_pre_clip': 2.7725892066955566, 'timing/data': 0.00017795106396079063, 'timing/model': 0.4608563152141869, 'learning_rate/action_model': 9.538019659971116e-05, 'learning_rate/action_query_proj': 9.538019659971116e-05, 'learning_rate/base': 2.384504914992779e-05, 'epoch': 0.33}) +[2026-07-27 04:07:01,991][starVLA.training.train_starvla][INFO] - Step 2705, Loss: {'train/loss': 0.09006591886281967, 'train/grad_norm_pre_clip': 2.0175492763519287, 'timing/data': 0.00018176808953285217, 'timing/model': 0.459883461240679, 'learning_rate/action_model': 9.536727829278568e-05, 'learning_rate/action_query_proj': 9.536727829278568e-05, 'learning_rate/base': 2.384181957319642e-05, 'epoch': 0.33}) +[2026-07-27 04:07:07,595][starVLA.training.train_starvla][INFO] - Step 2706, Loss: {'train/loss': 0.22798128426074982, 'train/grad_norm_pre_clip': 4.409328460693359, 'timing/data': 0.00018378207460045815, 'timing/model': 0.4626525561325252, 'learning_rate/action_model': 9.535434286514555e-05, 'learning_rate/action_query_proj': 9.535434286514555e-05, 'learning_rate/base': 2.3838585716286386e-05, 'epoch': 0.33}) +[2026-07-27 04:07:13,194][starVLA.training.train_starvla][INFO] - Step 2707, Loss: {'train/loss': 0.14278946816921234, 'train/grad_norm_pre_clip': 3.68723726272583, 'timing/data': 0.00017520133405923843, 'timing/model': 0.4656186797656119, 'learning_rate/action_model': 9.534139032189744e-05, 'learning_rate/action_query_proj': 9.534139032189744e-05, 'learning_rate/base': 2.383534758047436e-05, 'epoch': 0.33}) +[2026-07-27 04:07:18,930][starVLA.training.train_starvla][INFO] - Step 2708, Loss: {'train/loss': 0.2658950090408325, 'train/grad_norm_pre_clip': 5.057244300842285, 'timing/data': 0.00017398176714777946, 'timing/model': 0.46115132281556726, 'learning_rate/action_model': 9.532842066815484e-05, 'learning_rate/action_query_proj': 9.532842066815484e-05, 'learning_rate/base': 2.383210516703871e-05, 'epoch': 0.33}) +[2026-07-27 04:07:24,554][starVLA.training.train_starvla][INFO] - Step 2709, Loss: {'train/loss': 0.1000680923461914, 'train/grad_norm_pre_clip': 3.3191077709198, 'timing/data': 0.00017431797459721565, 'timing/model': 0.4582677851431072, 'learning_rate/action_model': 9.531543390903796e-05, 'learning_rate/action_query_proj': 9.531543390903796e-05, 'learning_rate/base': 2.382885847725949e-05, 'epoch': 0.33}) +[2026-07-27 04:07:30,220][starVLA.training.train_starvla][INFO] - Step 2710, Loss: {'train/loss': 0.1529625952243805, 'train/grad_norm_pre_clip': 2.497868537902832, 'timing/data': 0.00018614809960126877, 'timing/model': 0.4662837372161448, 'learning_rate/action_model': 9.530243004967375e-05, 'learning_rate/action_query_proj': 9.530243004967375e-05, 'learning_rate/base': 2.3825607512418436e-05, 'epoch': 0.33}) +[2026-07-27 04:07:35,870][starVLA.training.train_starvla][INFO] - Step 2711, Loss: {'train/loss': 0.15075619518756866, 'train/grad_norm_pre_clip': 2.8097469806671143, 'timing/data': 0.00017687398940324783, 'timing/model': 0.46453624311834574, 'learning_rate/action_model': 9.528940909519591e-05, 'learning_rate/action_query_proj': 9.528940909519591e-05, 'learning_rate/base': 2.3822352273798978e-05, 'epoch': 0.33}) +[2026-07-27 04:07:41,533][starVLA.training.train_starvla][INFO] - Step 2712, Loss: {'train/loss': 0.08751844614744186, 'train/grad_norm_pre_clip': 2.636967658996582, 'timing/data': 0.00017604418098926544, 'timing/model': 0.46396301593631506, 'learning_rate/action_model': 9.527637105074497e-05, 'learning_rate/action_query_proj': 9.527637105074497e-05, 'learning_rate/base': 2.381909276268624e-05, 'epoch': 0.33}) +[2026-07-27 04:07:47,212][starVLA.training.train_starvla][INFO] - Step 2713, Loss: {'train/loss': 0.14733079075813293, 'train/grad_norm_pre_clip': 3.7901811599731445, 'timing/data': 0.00017867889255285263, 'timing/model': 0.4622202618047595, 'learning_rate/action_model': 9.526331592146808e-05, 'learning_rate/action_query_proj': 9.526331592146808e-05, 'learning_rate/base': 2.381582898036702e-05, 'epoch': 0.33}) +[2026-07-27 04:07:52,839][starVLA.training.train_starvla][INFO] - Step 2714, Loss: {'train/loss': 0.2949451506137848, 'train/grad_norm_pre_clip': 4.650285243988037, 'timing/data': 0.00017586303874850273, 'timing/model': 0.4607665650546551, 'learning_rate/action_model': 9.525024371251923e-05, 'learning_rate/action_query_proj': 9.525024371251923e-05, 'learning_rate/base': 2.3812560928129806e-05, 'epoch': 0.33}) +[2026-07-27 04:07:58,510][starVLA.training.train_starvla][INFO] - Step 2715, Loss: {'train/loss': 0.28089243173599243, 'train/grad_norm_pre_clip': 4.324635982513428, 'timing/data': 0.00017509469762444496, 'timing/model': 0.47641551308333874, 'learning_rate/action_model': 9.523715442905912e-05, 'learning_rate/action_query_proj': 9.523715442905912e-05, 'learning_rate/base': 2.380928860726478e-05, 'epoch': 0.33}) +[2026-07-27 04:08:04,458][starVLA.training.train_starvla][INFO] - Step 2716, Loss: {'train/loss': 0.14658847451210022, 'train/grad_norm_pre_clip': 4.076557159423828, 'timing/data': 0.00017416290938854218, 'timing/model': 0.4775944612920284, 'learning_rate/action_model': 9.522404807625518e-05, 'learning_rate/action_query_proj': 9.522404807625518e-05, 'learning_rate/base': 2.3806012019063796e-05, 'epoch': 0.33}) +[2026-07-27 04:08:10,111][starVLA.training.train_starvla][INFO] - Step 2717, Loss: {'train/loss': 0.11948010325431824, 'train/grad_norm_pre_clip': 2.5456595420837402, 'timing/data': 0.00017605023458600044, 'timing/model': 0.47128629917278886, 'learning_rate/action_model': 9.52109246592816e-05, 'learning_rate/action_query_proj': 9.52109246592816e-05, 'learning_rate/base': 2.38027311648204e-05, 'epoch': 0.33}) +[2026-07-27 04:08:15,761][starVLA.training.train_starvla][INFO] - Step 2718, Loss: {'train/loss': 0.13208144903182983, 'train/grad_norm_pre_clip': 3.325253963470459, 'timing/data': 0.0001787617802619934, 'timing/model': 0.4708205838687718, 'learning_rate/action_model': 9.519778418331928e-05, 'learning_rate/action_query_proj': 9.519778418331928e-05, 'learning_rate/base': 2.379944604582982e-05, 'epoch': 0.33}) +[2026-07-27 04:08:21,411][starVLA.training.train_starvla][INFO] - Step 2719, Loss: {'train/loss': 0.20879212021827698, 'train/grad_norm_pre_clip': 3.811842918395996, 'timing/data': 0.00017483392730355263, 'timing/model': 0.4712846358306706, 'learning_rate/action_model': 9.518462665355588e-05, 'learning_rate/action_query_proj': 9.518462665355588e-05, 'learning_rate/base': 2.379615666338897e-05, 'epoch': 0.33}) +[2026-07-27 04:08:27,345][starVLA.training.train_starvla][INFO] - Step 2720, Loss: {'train/loss': 0.14943629503250122, 'train/grad_norm_pre_clip': 2.8714957237243652, 'timing/data': 0.00017688237130641937, 'timing/model': 0.47712422581389546, 'learning_rate/action_model': 9.517145207518581e-05, 'learning_rate/action_query_proj': 9.517145207518581e-05, 'learning_rate/base': 2.3792863018796453e-05, 'epoch': 0.33}) +[2026-07-27 04:08:32,993][starVLA.training.train_starvla][INFO] - Step 2721, Loss: {'train/loss': 0.14592161774635315, 'train/grad_norm_pre_clip': 3.080425500869751, 'timing/data': 0.00017385603860020638, 'timing/model': 0.46180430706590414, 'learning_rate/action_model': 9.515826045341017e-05, 'learning_rate/action_query_proj': 9.515826045341017e-05, 'learning_rate/base': 2.3789565113352542e-05, 'epoch': 0.33}) +[2026-07-27 04:08:38,622][starVLA.training.train_starvla][INFO] - Step 2722, Loss: {'train/loss': 0.2222272902727127, 'train/grad_norm_pre_clip': 5.358524799346924, 'timing/data': 0.00019890209659934044, 'timing/model': 0.46205918909981847, 'learning_rate/action_model': 9.514505179343678e-05, 'learning_rate/action_query_proj': 9.514505179343678e-05, 'learning_rate/base': 2.3786262948359195e-05, 'epoch': 0.33}) +[2026-07-27 04:08:44,243][starVLA.training.train_starvla][INFO] - Step 2723, Loss: {'train/loss': 0.19221735000610352, 'train/grad_norm_pre_clip': 5.057590007781982, 'timing/data': 0.00017713569104671478, 'timing/model': 0.46400010399520397, 'learning_rate/action_model': 9.513182610048024e-05, 'learning_rate/action_query_proj': 9.513182610048024e-05, 'learning_rate/base': 2.378295652512006e-05, 'epoch': 0.33}) +[2026-07-27 04:08:49,855][starVLA.training.train_starvla][INFO] - Step 2724, Loss: {'train/loss': 0.1819077581167221, 'train/grad_norm_pre_clip': 5.001282215118408, 'timing/data': 0.00017683114856481552, 'timing/model': 0.4620614149607718, 'learning_rate/action_model': 9.511858337976182e-05, 'learning_rate/action_query_proj': 9.511858337976182e-05, 'learning_rate/base': 2.3779645844940456e-05, 'epoch': 0.33}) +[2026-07-27 04:08:55,478][starVLA.training.train_starvla][INFO] - Step 2725, Loss: {'train/loss': 0.2773507237434387, 'train/grad_norm_pre_clip': 5.873976230621338, 'timing/data': 0.00018009310588240623, 'timing/model': 0.4652413190342486, 'learning_rate/action_model': 9.510532363650955e-05, 'learning_rate/action_query_proj': 9.510532363650955e-05, 'learning_rate/base': 2.3776330909127388e-05, 'epoch': 0.33}) +[2026-07-27 04:09:01,107][starVLA.training.train_starvla][INFO] - Step 2726, Loss: {'train/loss': 0.15645743906497955, 'train/grad_norm_pre_clip': 3.207012414932251, 'timing/data': 0.00017397012561559677, 'timing/model': 0.46544354408979416, 'learning_rate/action_model': 9.509204687595817e-05, 'learning_rate/action_query_proj': 9.509204687595817e-05, 'learning_rate/base': 2.3773011718989542e-05, 'epoch': 0.33}) +[2026-07-27 04:09:06,746][starVLA.training.train_starvla][INFO] - Step 2727, Loss: {'train/loss': 0.20536576211452484, 'train/grad_norm_pre_clip': 4.188419818878174, 'timing/data': 0.00017224624752998352, 'timing/model': 0.4616118767298758, 'learning_rate/action_model': 9.507875310334913e-05, 'learning_rate/action_query_proj': 9.507875310334913e-05, 'learning_rate/base': 2.3769688275837283e-05, 'epoch': 0.33}) +[2026-07-27 04:09:12,417][starVLA.training.train_starvla][INFO] - Step 2728, Loss: {'train/loss': 0.1730356514453888, 'train/grad_norm_pre_clip': 4.944821834564209, 'timing/data': 0.00017733918502926826, 'timing/model': 0.4598505599424243, 'learning_rate/action_model': 9.506544232393061e-05, 'learning_rate/action_query_proj': 9.506544232393061e-05, 'learning_rate/base': 2.3766360580982654e-05, 'epoch': 0.33}) +[2026-07-27 04:09:18,041][starVLA.training.train_starvla][INFO] - Step 2729, Loss: {'train/loss': 0.3151843249797821, 'train/grad_norm_pre_clip': 4.515359878540039, 'timing/data': 0.0001713312231004238, 'timing/model': 0.46188285015523434, 'learning_rate/action_model': 9.505211454295747e-05, 'learning_rate/action_query_proj': 9.505211454295747e-05, 'learning_rate/base': 2.3763028635739368e-05, 'epoch': 0.33}) +[2026-07-27 04:09:23,661][starVLA.training.train_starvla][INFO] - Step 2730, Loss: {'train/loss': 0.23567792773246765, 'train/grad_norm_pre_clip': 4.620734691619873, 'timing/data': 0.00018019787967205048, 'timing/model': 0.46312360605224967, 'learning_rate/action_model': 9.503876976569133e-05, 'learning_rate/action_query_proj': 9.503876976569133e-05, 'learning_rate/base': 2.3759692441422832e-05, 'epoch': 0.33}) +[2026-07-27 04:09:29,287][starVLA.training.train_starvla][INFO] - Step 2731, Loss: {'train/loss': 0.19237306714057922, 'train/grad_norm_pre_clip': 4.64211893081665, 'timing/data': 0.00018630828708410263, 'timing/model': 0.465179409366101, 'learning_rate/action_model': 9.502540799740048e-05, 'learning_rate/action_query_proj': 9.502540799740048e-05, 'learning_rate/base': 2.375635199935012e-05, 'epoch': 0.33}) +[2026-07-27 04:09:34,897][starVLA.training.train_starvla][INFO] - Step 2732, Loss: {'train/loss': 0.24275588989257812, 'train/grad_norm_pre_clip': 4.976065635681152, 'timing/data': 0.00017466116696596146, 'timing/model': 0.461778512224555, 'learning_rate/action_model': 9.501202924335996e-05, 'learning_rate/action_query_proj': 9.501202924335996e-05, 'learning_rate/base': 2.375300731083999e-05, 'epoch': 0.33}) +[2026-07-27 04:09:40,496][starVLA.training.train_starvla][INFO] - Step 2733, Loss: {'train/loss': 0.2059483528137207, 'train/grad_norm_pre_clip': 4.2257771492004395, 'timing/data': 0.00017853127792477608, 'timing/model': 0.46128447633236647, 'learning_rate/action_model': 9.499863350885146e-05, 'learning_rate/action_query_proj': 9.499863350885146e-05, 'learning_rate/base': 2.3749658377212864e-05, 'epoch': 0.33}) +[2026-07-27 04:09:46,089][starVLA.training.train_starvla][INFO] - Step 2734, Loss: {'train/loss': 0.15653282403945923, 'train/grad_norm_pre_clip': 3.23382568359375, 'timing/data': 0.00017141597345471382, 'timing/model': 0.46111511904746294, 'learning_rate/action_model': 9.498522079916342e-05, 'learning_rate/action_query_proj': 9.498522079916342e-05, 'learning_rate/base': 2.3746305199790854e-05, 'epoch': 0.33}) +[2026-07-27 04:09:51,699][starVLA.training.train_starvla][INFO] - Step 2735, Loss: {'train/loss': 0.09972679615020752, 'train/grad_norm_pre_clip': 2.1207737922668457, 'timing/data': 0.0001727202907204628, 'timing/model': 0.4619304877705872, 'learning_rate/action_model': 9.497179111959098e-05, 'learning_rate/action_query_proj': 9.497179111959098e-05, 'learning_rate/base': 2.3742947779897744e-05, 'epoch': 0.33}) +[2026-07-27 04:09:57,336][starVLA.training.train_starvla][INFO] - Step 2736, Loss: {'train/loss': 0.30578386783599854, 'train/grad_norm_pre_clip': 5.317631244659424, 'timing/data': 0.00017632078379392624, 'timing/model': 0.4643656210973859, 'learning_rate/action_model': 9.495834447543591e-05, 'learning_rate/action_query_proj': 9.495834447543591e-05, 'learning_rate/base': 2.3739586118858977e-05, 'epoch': 0.33}) +[2026-07-27 04:10:02,959][starVLA.training.train_starvla][INFO] - Step 2737, Loss: {'train/loss': 0.20607969164848328, 'train/grad_norm_pre_clip': 4.384097576141357, 'timing/data': 0.00017530983313918114, 'timing/model': 0.4644521400332451, 'learning_rate/action_model': 9.49448808720068e-05, 'learning_rate/action_query_proj': 9.49448808720068e-05, 'learning_rate/base': 2.37362202180017e-05, 'epoch': 0.33}) +[2026-07-27 04:10:08,573][starVLA.training.train_starvla][INFO] - Step 2738, Loss: {'train/loss': 0.0983748733997345, 'train/grad_norm_pre_clip': 2.8655753135681152, 'timing/data': 0.00017333123832941055, 'timing/model': 0.46361520793288946, 'learning_rate/action_model': 9.493140031461883e-05, 'learning_rate/action_query_proj': 9.493140031461883e-05, 'learning_rate/base': 2.3732850078654708e-05, 'epoch': 0.33}) +[2026-07-27 04:10:14,187][starVLA.training.train_starvla][INFO] - Step 2739, Loss: {'train/loss': 0.20568743348121643, 'train/grad_norm_pre_clip': 4.441051006317139, 'timing/data': 0.00017079804092645645, 'timing/model': 0.4596271039918065, 'learning_rate/action_model': 9.491790280859393e-05, 'learning_rate/action_query_proj': 9.491790280859393e-05, 'learning_rate/base': 2.3729475702148482e-05, 'epoch': 0.33}) +[2026-07-27 04:10:19,811][starVLA.training.train_starvla][INFO] - Step 2740, Loss: {'train/loss': 0.13724850118160248, 'train/grad_norm_pre_clip': 3.038409948348999, 'timing/data': 0.00017172005027532578, 'timing/model': 0.46268884371966124, 'learning_rate/action_model': 9.490438835926067e-05, 'learning_rate/action_query_proj': 9.490438835926067e-05, 'learning_rate/base': 2.3726097089815167e-05, 'epoch': 0.33}) +[2026-07-27 04:10:25,677][starVLA.training.train_starvla][INFO] - Step 2741, Loss: {'train/loss': 0.1863643378019333, 'train/grad_norm_pre_clip': 3.2678284645080566, 'timing/data': 0.0001774011179804802, 'timing/model': 0.46206900384277105, 'learning_rate/action_model': 9.489085697195437e-05, 'learning_rate/action_query_proj': 9.489085697195437e-05, 'learning_rate/base': 2.3722714242988593e-05, 'epoch': 0.33}) +[2026-07-27 04:10:31,297][starVLA.training.train_starvla][INFO] - Step 2742, Loss: {'train/loss': 0.38265562057495117, 'train/grad_norm_pre_clip': 6.894699573516846, 'timing/data': 0.00017683906480669975, 'timing/model': 0.46171514596790075, 'learning_rate/action_model': 9.4877308652017e-05, 'learning_rate/action_query_proj': 9.4877308652017e-05, 'learning_rate/base': 2.371932716300425e-05, 'epoch': 0.33}) +[2026-07-27 04:10:36,920][starVLA.training.train_starvla][INFO] - Step 2743, Loss: {'train/loss': 0.20274819433689117, 'train/grad_norm_pre_clip': 5.885848522186279, 'timing/data': 0.00018072593957185745, 'timing/model': 0.4641289305873215, 'learning_rate/action_model': 9.48637434047972e-05, 'learning_rate/action_query_proj': 9.48637434047972e-05, 'learning_rate/base': 2.37159358511993e-05, 'epoch': 0.33}) +[2026-07-27 04:10:42,530][starVLA.training.train_starvla][INFO] - Step 2744, Loss: {'train/loss': 0.2572678327560425, 'train/grad_norm_pre_clip': 7.169898986816406, 'timing/data': 0.00018241256475448608, 'timing/model': 0.4614051072858274, 'learning_rate/action_model': 9.485016123565036e-05, 'learning_rate/action_query_proj': 9.485016123565036e-05, 'learning_rate/base': 2.371254030891259e-05, 'epoch': 0.33}) +[2026-07-27 04:10:48,156][starVLA.training.train_starvla][INFO] - Step 2745, Loss: {'train/loss': 0.1512279212474823, 'train/grad_norm_pre_clip': 4.920431613922119, 'timing/data': 0.0001750602386891842, 'timing/model': 0.4630776420235634, 'learning_rate/action_model': 9.483656214993847e-05, 'learning_rate/action_query_proj': 9.483656214993847e-05, 'learning_rate/base': 2.3709140537484617e-05, 'epoch': 0.33}) +[2026-07-27 04:10:53,828][starVLA.training.train_starvla][INFO] - Step 2746, Loss: {'train/loss': 0.2425616830587387, 'train/grad_norm_pre_clip': 3.228111743927002, 'timing/data': 0.00017052097246050835, 'timing/model': 0.4617003430612385, 'learning_rate/action_model': 9.482294615303024e-05, 'learning_rate/action_query_proj': 9.482294615303024e-05, 'learning_rate/base': 2.370573653825756e-05, 'epoch': 0.33}) +[2026-07-27 04:10:59,470][starVLA.training.train_starvla][INFO] - Step 2747, Loss: {'train/loss': 0.14558550715446472, 'train/grad_norm_pre_clip': 3.418215036392212, 'timing/data': 0.00017432263121008873, 'timing/model': 0.4633717997930944, 'learning_rate/action_model': 9.480931325030104e-05, 'learning_rate/action_query_proj': 9.480931325030104e-05, 'learning_rate/base': 2.370232831257526e-05, 'epoch': 0.33}) +[2026-07-27 04:11:05,099][starVLA.training.train_starvla][INFO] - Step 2748, Loss: {'train/loss': 0.12343141436576843, 'train/grad_norm_pre_clip': 2.5002384185791016, 'timing/data': 0.00017409911379218102, 'timing/model': 0.4659912879578769, 'learning_rate/action_model': 9.479566344713298e-05, 'learning_rate/action_query_proj': 9.479566344713298e-05, 'learning_rate/base': 2.3698915861783245e-05, 'epoch': 0.33}) +[2026-07-27 04:11:10,720][starVLA.training.train_starvla][INFO] - Step 2749, Loss: {'train/loss': 0.0997815653681755, 'train/grad_norm_pre_clip': 2.893702268600464, 'timing/data': 0.00017378898337483406, 'timing/model': 0.4626953578554094, 'learning_rate/action_model': 9.478199674891471e-05, 'learning_rate/action_query_proj': 9.478199674891471e-05, 'learning_rate/base': 2.369549918722868e-05, 'epoch': 0.33}) +[2026-07-27 04:11:16,364][starVLA.training.train_starvla][INFO] - Step 2750, Loss: {'train/loss': 0.19983583688735962, 'train/grad_norm_pre_clip': 4.113654136657715, 'timing/data': 0.00017060479149222374, 'timing/model': 0.46592229697853327, 'learning_rate/action_model': 9.476831316104165e-05, 'learning_rate/action_query_proj': 9.476831316104165e-05, 'learning_rate/base': 2.3692078290260413e-05, 'epoch': 0.33}) +[2026-07-27 04:11:22,007][starVLA.training.train_starvla][INFO] - Step 2751, Loss: {'train/loss': 0.14735393226146698, 'train/grad_norm_pre_clip': 2.6589930057525635, 'timing/data': 0.00017408328130841255, 'timing/model': 0.4623815040104091, 'learning_rate/action_model': 9.475461268891591e-05, 'learning_rate/action_query_proj': 9.475461268891591e-05, 'learning_rate/base': 2.3688653172228978e-05, 'epoch': 0.33}) +[2026-07-27 04:11:27,651][starVLA.training.train_starvla][INFO] - Step 2752, Loss: {'train/loss': 0.1881178766489029, 'train/grad_norm_pre_clip': 4.875403881072998, 'timing/data': 0.00017730286344885826, 'timing/model': 0.4696744126267731, 'learning_rate/action_model': 9.474089533794616e-05, 'learning_rate/action_query_proj': 9.474089533794616e-05, 'learning_rate/base': 2.368522383448654e-05, 'epoch': 0.33}) +[2026-07-27 04:11:33,249][starVLA.training.train_starvla][INFO] - Step 2753, Loss: {'train/loss': 0.13098594546318054, 'train/grad_norm_pre_clip': 3.3618905544281006, 'timing/data': 0.0001747352071106434, 'timing/model': 0.4604400182142854, 'learning_rate/action_model': 9.472716111354781e-05, 'learning_rate/action_query_proj': 9.472716111354781e-05, 'learning_rate/base': 2.3681790278386953e-05, 'epoch': 0.33}) +[2026-07-27 04:11:38,892][starVLA.training.train_starvla][INFO] - Step 2754, Loss: {'train/loss': 0.11659155040979385, 'train/grad_norm_pre_clip': 2.4984145164489746, 'timing/data': 0.00017618807032704353, 'timing/model': 0.4637310542166233, 'learning_rate/action_model': 9.471341002114293e-05, 'learning_rate/action_query_proj': 9.471341002114293e-05, 'learning_rate/base': 2.3678352505285733e-05, 'epoch': 0.33}) +[2026-07-27 04:11:44,620][starVLA.training.train_starvla][INFO] - Step 2755, Loss: {'train/loss': 0.13866229355335236, 'train/grad_norm_pre_clip': 2.560044050216675, 'timing/data': 0.00017616525292396545, 'timing/model': 0.46080490993335843, 'learning_rate/action_model': 9.469964206616023e-05, 'learning_rate/action_query_proj': 9.469964206616023e-05, 'learning_rate/base': 2.3674910516540058e-05, 'epoch': 0.33}) +[2026-07-27 04:11:50,239][starVLA.training.train_starvla][INFO] - Step 2756, Loss: {'train/loss': 0.16590018570423126, 'train/grad_norm_pre_clip': 4.264873027801514, 'timing/data': 0.00017329305410385132, 'timing/model': 0.459608918055892, 'learning_rate/action_model': 9.468585725403506e-05, 'learning_rate/action_query_proj': 9.468585725403506e-05, 'learning_rate/base': 2.3671464313508764e-05, 'epoch': 0.33}) +[2026-07-27 04:11:55,823][starVLA.training.train_starvla][INFO] - Step 2757, Loss: {'train/loss': 0.15861383080482483, 'train/grad_norm_pre_clip': 2.6708688735961914, 'timing/data': 0.00017804699018597603, 'timing/model': 0.46089733205735683, 'learning_rate/action_model': 9.467205559020947e-05, 'learning_rate/action_query_proj': 9.467205559020947e-05, 'learning_rate/base': 2.3668013897552367e-05, 'epoch': 0.33}) +[2026-07-27 04:12:01,484][starVLA.training.train_starvla][INFO] - Step 2758, Loss: {'train/loss': 0.10411539673805237, 'train/grad_norm_pre_clip': 2.8688642978668213, 'timing/data': 0.00017713196575641632, 'timing/model': 0.46560552809387445, 'learning_rate/action_model': 9.465823708013211e-05, 'learning_rate/action_query_proj': 9.465823708013211e-05, 'learning_rate/base': 2.3664559270033028e-05, 'epoch': 0.33}) +[2026-07-27 04:12:07,108][starVLA.training.train_starvla][INFO] - Step 2759, Loss: {'train/loss': 0.13136668503284454, 'train/grad_norm_pre_clip': 2.165229558944702, 'timing/data': 0.00017511798068881035, 'timing/model': 0.459793530870229, 'learning_rate/action_model': 9.464440172925835e-05, 'learning_rate/action_query_proj': 9.464440172925835e-05, 'learning_rate/base': 2.3661100432314587e-05, 'epoch': 0.33}) +[2026-07-27 04:12:12,731][starVLA.training.train_starvla][INFO] - Step 2760, Loss: {'train/loss': 0.172181636095047, 'train/grad_norm_pre_clip': 2.4741623401641846, 'timing/data': 0.00017632264643907547, 'timing/model': 0.4618087629787624, 'learning_rate/action_model': 9.463054954305014e-05, 'learning_rate/action_query_proj': 9.463054954305014e-05, 'learning_rate/base': 2.3657637385762534e-05, 'epoch': 0.33}) +[2026-07-27 04:12:18,349][starVLA.training.train_starvla][INFO] - Step 2761, Loss: {'train/loss': 0.05105793848633766, 'train/grad_norm_pre_clip': 1.5401341915130615, 'timing/data': 0.00018031615763902664, 'timing/model': 0.46232675295323133, 'learning_rate/action_model': 9.461668052697611e-05, 'learning_rate/action_query_proj': 9.461668052697611e-05, 'learning_rate/base': 2.3654170131744028e-05, 'epoch': 0.33}) +[2026-07-27 04:12:23,958][starVLA.training.train_starvla][INFO] - Step 2762, Loss: {'train/loss': 0.20864862203598022, 'train/grad_norm_pre_clip': 3.6743693351745605, 'timing/data': 0.00020981580018997192, 'timing/model': 0.46572916116565466, 'learning_rate/action_model': 9.460279468651152e-05, 'learning_rate/action_query_proj': 9.460279468651152e-05, 'learning_rate/base': 2.365069867162788e-05, 'epoch': 0.34}) +[2026-07-27 04:12:29,575][starVLA.training.train_starvla][INFO] - Step 2763, Loss: {'train/loss': 0.11921446025371552, 'train/grad_norm_pre_clip': 2.323408842086792, 'timing/data': 0.00017691310495138168, 'timing/model': 0.46617908077314496, 'learning_rate/action_model': 9.458889202713828e-05, 'learning_rate/action_query_proj': 9.458889202713828e-05, 'learning_rate/base': 2.364722300678457e-05, 'epoch': 0.34}) +[2026-07-27 04:12:35,189][starVLA.training.train_starvla][INFO] - Step 2764, Loss: {'train/loss': 0.1285601556301117, 'train/grad_norm_pre_clip': 3.10537052154541, 'timing/data': 0.0001711808145046234, 'timing/model': 0.4664508909918368, 'learning_rate/action_model': 9.457497255434495e-05, 'learning_rate/action_query_proj': 9.457497255434495e-05, 'learning_rate/base': 2.3643743138586238e-05, 'epoch': 0.34}) +[2026-07-27 04:12:40,801][starVLA.training.train_starvla][INFO] - Step 2765, Loss: {'train/loss': 0.23968343436717987, 'train/grad_norm_pre_clip': 3.9147121906280518, 'timing/data': 0.00018607312813401222, 'timing/model': 0.4652030561119318, 'learning_rate/action_model': 9.456103627362673e-05, 'learning_rate/action_query_proj': 9.456103627362673e-05, 'learning_rate/base': 2.364025906840668e-05, 'epoch': 0.34}) +[2026-07-27 04:12:46,429][starVLA.training.train_starvla][INFO] - Step 2766, Loss: {'train/loss': 0.12541130185127258, 'train/grad_norm_pre_clip': 2.9685163497924805, 'timing/data': 0.0001710299402475357, 'timing/model': 0.46499930461868644, 'learning_rate/action_model': 9.45470831904854e-05, 'learning_rate/action_query_proj': 9.45470831904854e-05, 'learning_rate/base': 2.363677079762135e-05, 'epoch': 0.34}) +[2026-07-27 04:12:52,061][starVLA.training.train_starvla][INFO] - Step 2767, Loss: {'train/loss': 0.19032984972000122, 'train/grad_norm_pre_clip': 2.7845916748046875, 'timing/data': 0.0001696520484983921, 'timing/model': 0.4633169691078365, 'learning_rate/action_model': 9.453311331042945e-05, 'learning_rate/action_query_proj': 9.453311331042945e-05, 'learning_rate/base': 2.3633278327607363e-05, 'epoch': 0.34}) +[2026-07-27 04:12:57,941][starVLA.training.train_starvla][INFO] - Step 2768, Loss: {'train/loss': 0.11915495991706848, 'train/grad_norm_pre_clip': 3.5776400566101074, 'timing/data': 0.00017489399760961533, 'timing/model': 0.4611979080364108, 'learning_rate/action_model': 9.451912663897396e-05, 'learning_rate/action_query_proj': 9.451912663897396e-05, 'learning_rate/base': 2.362978165974349e-05, 'epoch': 0.34}) +[2026-07-27 04:13:03,571][starVLA.training.train_starvla][INFO] - Step 2769, Loss: {'train/loss': 0.13611552119255066, 'train/grad_norm_pre_clip': 3.1720402240753174, 'timing/data': 0.00017205998301506042, 'timing/model': 0.4580849576741457, 'learning_rate/action_model': 9.450512318164065e-05, 'learning_rate/action_query_proj': 9.450512318164065e-05, 'learning_rate/base': 2.362628079541016e-05, 'epoch': 0.34}) +[2026-07-27 04:13:09,199][starVLA.training.train_starvla][INFO] - Step 2770, Loss: {'train/loss': 0.14968201518058777, 'train/grad_norm_pre_clip': 4.142294406890869, 'timing/data': 0.0001748078502714634, 'timing/model': 0.46316096605733037, 'learning_rate/action_model': 9.449110294395786e-05, 'learning_rate/action_query_proj': 9.449110294395786e-05, 'learning_rate/base': 2.3622775735989464e-05, 'epoch': 0.34}) +[2026-07-27 04:13:14,821][starVLA.training.train_starvla][INFO] - Step 2771, Loss: {'train/loss': 0.11802957952022552, 'train/grad_norm_pre_clip': 2.8179352283477783, 'timing/data': 0.00017201807349920273, 'timing/model': 0.46340272203087807, 'learning_rate/action_model': 9.447706593146055e-05, 'learning_rate/action_query_proj': 9.447706593146055e-05, 'learning_rate/base': 2.3619266482865138e-05, 'epoch': 0.34}) +[2026-07-27 04:13:20,724][starVLA.training.train_starvla][INFO] - Step 2772, Loss: {'train/loss': 0.10682061314582825, 'train/grad_norm_pre_clip': 2.96126651763916, 'timing/data': 0.0001789592206478119, 'timing/model': 0.465132846031338, 'learning_rate/action_model': 9.446301214969032e-05, 'learning_rate/action_query_proj': 9.446301214969032e-05, 'learning_rate/base': 2.361575303742258e-05, 'epoch': 0.34}) +[2026-07-27 04:13:26,354][starVLA.training.train_starvla][INFO] - Step 2773, Loss: {'train/loss': 0.08222601562738419, 'train/grad_norm_pre_clip': 2.4175453186035156, 'timing/data': 0.000174615066498518, 'timing/model': 0.46495458763092756, 'learning_rate/action_model': 9.444894160419539e-05, 'learning_rate/action_query_proj': 9.444894160419539e-05, 'learning_rate/base': 2.3612235401048847e-05, 'epoch': 0.34}) +[2026-07-27 04:13:31,969][starVLA.training.train_starvla][INFO] - Step 2774, Loss: {'train/loss': 0.28384825587272644, 'train/grad_norm_pre_clip': 4.289488792419434, 'timing/data': 0.00017312495037913322, 'timing/model': 0.46370491618290544, 'learning_rate/action_model': 9.443485430053056e-05, 'learning_rate/action_query_proj': 9.443485430053056e-05, 'learning_rate/base': 2.360871357513264e-05, 'epoch': 0.34}) +[2026-07-27 04:13:37,576][starVLA.training.train_starvla][INFO] - Step 2775, Loss: {'train/loss': 0.14012473821640015, 'train/grad_norm_pre_clip': 3.5588796138763428, 'timing/data': 0.0001749172806739807, 'timing/model': 0.4651201101951301, 'learning_rate/action_model': 9.44207502442573e-05, 'learning_rate/action_query_proj': 9.44207502442573e-05, 'learning_rate/base': 2.3605187561064324e-05, 'epoch': 0.34}) +[2026-07-27 04:13:43,192][starVLA.training.train_starvla][INFO] - Step 2776, Loss: {'train/loss': 0.087169349193573, 'train/grad_norm_pre_clip': 2.4130284786224365, 'timing/data': 0.00017523206770420074, 'timing/model': 0.4611818199045956, 'learning_rate/action_model': 9.440662944094364e-05, 'learning_rate/action_query_proj': 9.440662944094364e-05, 'learning_rate/base': 2.360165736023591e-05, 'epoch': 0.34}) +[2026-07-27 04:13:48,815][starVLA.training.train_starvla][INFO] - Step 2777, Loss: {'train/loss': 0.2725300192832947, 'train/grad_norm_pre_clip': 4.509618759155273, 'timing/data': 0.0001747608184814453, 'timing/model': 0.4650059724226594, 'learning_rate/action_model': 9.439249189616428e-05, 'learning_rate/action_query_proj': 9.439249189616428e-05, 'learning_rate/base': 2.359812297404107e-05, 'epoch': 0.34}) +[2026-07-27 04:13:54,446][starVLA.training.train_starvla][INFO] - Step 2778, Loss: {'train/loss': 0.1209758073091507, 'train/grad_norm_pre_clip': 4.195541858673096, 'timing/data': 0.00017614290118217468, 'timing/model': 0.4653377220965922, 'learning_rate/action_model': 9.43783376155005e-05, 'learning_rate/action_query_proj': 9.43783376155005e-05, 'learning_rate/base': 2.3594584403875124e-05, 'epoch': 0.34}) +[2026-07-27 04:14:00,081][starVLA.training.train_starvla][INFO] - Step 2779, Loss: {'train/loss': 0.2105036973953247, 'train/grad_norm_pre_clip': 4.2643656730651855, 'timing/data': 0.00018581561744213104, 'timing/model': 0.46241198712959886, 'learning_rate/action_model': 9.436416660454016e-05, 'learning_rate/action_query_proj': 9.436416660454016e-05, 'learning_rate/base': 2.359104165113504e-05, 'epoch': 0.34}) +[2026-07-27 04:14:05,698][starVLA.training.train_starvla][INFO] - Step 2780, Loss: {'train/loss': 0.10539958626031876, 'train/grad_norm_pre_clip': 2.372826099395752, 'timing/data': 0.00018781516700983047, 'timing/model': 0.46518715703859925, 'learning_rate/action_model': 9.434997886887776e-05, 'learning_rate/action_query_proj': 9.434997886887776e-05, 'learning_rate/base': 2.358749471721944e-05, 'epoch': 0.34}) +[2026-07-27 04:14:11,315][starVLA.training.train_starvla][INFO] - Step 2781, Loss: {'train/loss': 0.16867183148860931, 'train/grad_norm_pre_clip': 3.8418800830841064, 'timing/data': 0.00017603999003767967, 'timing/model': 0.4610207946971059, 'learning_rate/action_model': 9.43357744141144e-05, 'learning_rate/action_query_proj': 9.43357744141144e-05, 'learning_rate/base': 2.35839436035286e-05, 'epoch': 0.34}) +[2026-07-27 04:14:16,933][starVLA.training.train_starvla][INFO] - Step 2782, Loss: {'train/loss': 0.22430114448070526, 'train/grad_norm_pre_clip': 3.3889174461364746, 'timing/data': 0.0001716199330985546, 'timing/model': 0.4628498596139252, 'learning_rate/action_model': 9.432155324585776e-05, 'learning_rate/action_query_proj': 9.432155324585776e-05, 'learning_rate/base': 2.358038831146444e-05, 'epoch': 0.34}) +[2026-07-27 04:14:22,547][starVLA.training.train_starvla][INFO] - Step 2783, Loss: {'train/loss': 0.1855449080467224, 'train/grad_norm_pre_clip': 3.495323419570923, 'timing/data': 0.0001750001683831215, 'timing/model': 0.46107225585728884, 'learning_rate/action_model': 9.430731536972218e-05, 'learning_rate/action_query_proj': 9.430731536972218e-05, 'learning_rate/base': 2.3576828842430544e-05, 'epoch': 0.34}) +[2026-07-27 04:14:28,180][starVLA.training.train_starvla][INFO] - Step 2784, Loss: {'train/loss': 0.13701626658439636, 'train/grad_norm_pre_clip': 2.9226632118225098, 'timing/data': 0.0001735449768602848, 'timing/model': 0.4654464232735336, 'learning_rate/action_model': 9.429306079132849e-05, 'learning_rate/action_query_proj': 9.429306079132849e-05, 'learning_rate/base': 2.3573265197832122e-05, 'epoch': 0.34}) +[2026-07-27 04:14:33,793][starVLA.training.train_starvla][INFO] - Step 2785, Loss: {'train/loss': 0.08501920849084854, 'train/grad_norm_pre_clip': 2.9586100578308105, 'timing/data': 0.00017599528655409813, 'timing/model': 0.46062858728691936, 'learning_rate/action_model': 9.427878951630418e-05, 'learning_rate/action_query_proj': 9.427878951630418e-05, 'learning_rate/base': 2.3569697379076044e-05, 'epoch': 0.34}) +[2026-07-27 04:14:39,392][starVLA.training.train_starvla][INFO] - Step 2786, Loss: {'train/loss': 0.20315197110176086, 'train/grad_norm_pre_clip': 4.135983467102051, 'timing/data': 0.00017654988914728165, 'timing/model': 0.46380932815372944, 'learning_rate/action_model': 9.426450155028334e-05, 'learning_rate/action_query_proj': 9.426450155028334e-05, 'learning_rate/base': 2.3566125387570834e-05, 'epoch': 0.34}) +[2026-07-27 04:14:44,992][starVLA.training.train_starvla][INFO] - Step 2787, Loss: {'train/loss': 0.18950815498828888, 'train/grad_norm_pre_clip': 2.9746625423431396, 'timing/data': 0.0001755119301378727, 'timing/model': 0.4631994068622589, 'learning_rate/action_model': 9.425019689890664e-05, 'learning_rate/action_query_proj': 9.425019689890664e-05, 'learning_rate/base': 2.356254922472666e-05, 'epoch': 0.34}) +[2026-07-27 04:14:50,594][starVLA.training.train_starvla][INFO] - Step 2788, Loss: {'train/loss': 0.12187248468399048, 'train/grad_norm_pre_clip': 3.014862537384033, 'timing/data': 0.00017390400171279907, 'timing/model': 0.4612670741043985, 'learning_rate/action_model': 9.42358755678213e-05, 'learning_rate/action_query_proj': 9.42358755678213e-05, 'learning_rate/base': 2.3558968891955324e-05, 'epoch': 0.34}) +[2026-07-27 04:14:56,209][starVLA.training.train_starvla][INFO] - Step 2789, Loss: {'train/loss': 0.07608512789011002, 'train/grad_norm_pre_clip': 1.898163080215454, 'timing/data': 0.00018798187375068665, 'timing/model': 0.4620055821724236, 'learning_rate/action_model': 9.42215375626812e-05, 'learning_rate/action_query_proj': 9.42215375626812e-05, 'learning_rate/base': 2.35553843906703e-05, 'epoch': 0.34}) +[2026-07-27 04:15:01,814][starVLA.training.train_starvla][INFO] - Step 2790, Loss: {'train/loss': 0.21764494478702545, 'train/grad_norm_pre_clip': 4.103318214416504, 'timing/data': 0.00017872871831059456, 'timing/model': 0.46047353791072965, 'learning_rate/action_model': 9.42071828891467e-05, 'learning_rate/action_query_proj': 9.42071828891467e-05, 'learning_rate/base': 2.3551795722286675e-05, 'epoch': 0.34}) +[2026-07-27 04:15:07,428][starVLA.training.train_starvla][INFO] - Step 2791, Loss: {'train/loss': 0.15601235628128052, 'train/grad_norm_pre_clip': 3.0562446117401123, 'timing/data': 0.00017428770661354065, 'timing/model': 0.46044732816517353, 'learning_rate/action_model': 9.419281155288484e-05, 'learning_rate/action_query_proj': 9.419281155288484e-05, 'learning_rate/base': 2.354820288822121e-05, 'epoch': 0.34}) +[2026-07-27 04:15:13,031][starVLA.training.train_starvla][INFO] - Step 2792, Loss: {'train/loss': 0.1942186802625656, 'train/grad_norm_pre_clip': 3.7874457836151123, 'timing/data': 0.00017659692093729973, 'timing/model': 0.46215675631538033, 'learning_rate/action_model': 9.417842355956918e-05, 'learning_rate/action_query_proj': 9.417842355956918e-05, 'learning_rate/base': 2.3544605889892295e-05, 'epoch': 0.34}) +[2026-07-27 04:15:18,616][starVLA.training.train_starvla][INFO] - Step 2793, Loss: {'train/loss': 0.14215213060379028, 'train/grad_norm_pre_clip': 3.6424033641815186, 'timing/data': 0.00018791109323501587, 'timing/model': 0.46331999404355884, 'learning_rate/action_model': 9.416401891487989e-05, 'learning_rate/action_query_proj': 9.416401891487989e-05, 'learning_rate/base': 2.3541004728719973e-05, 'epoch': 0.34}) +[2026-07-27 04:15:24,172][starVLA.training.train_starvla][INFO] - Step 2794, Loss: {'train/loss': 0.20891813933849335, 'train/grad_norm_pre_clip': 3.1995034217834473, 'timing/data': 0.00017659272998571396, 'timing/model': 0.4627968901768327, 'learning_rate/action_model': 9.414959762450369e-05, 'learning_rate/action_query_proj': 9.414959762450369e-05, 'learning_rate/base': 2.353739940612592e-05, 'epoch': 0.34}) +[2026-07-27 04:15:29,730][starVLA.training.train_starvla][INFO] - Step 2795, Loss: {'train/loss': 0.22626911103725433, 'train/grad_norm_pre_clip': 4.699852466583252, 'timing/data': 0.00018710410222411156, 'timing/model': 0.4651590660214424, 'learning_rate/action_model': 9.413515969413386e-05, 'learning_rate/action_query_proj': 9.413515969413386e-05, 'learning_rate/base': 2.3533789923533465e-05, 'epoch': 0.34}) +[2026-07-27 04:15:35,290][starVLA.training.train_starvla][INFO] - Step 2796, Loss: {'train/loss': 0.11670335382223129, 'train/grad_norm_pre_clip': 3.2051029205322266, 'timing/data': 0.0001742248423397541, 'timing/model': 0.46496514277532697, 'learning_rate/action_model': 9.412070512947025e-05, 'learning_rate/action_query_proj': 9.412070512947025e-05, 'learning_rate/base': 2.3530176282367562e-05, 'epoch': 0.34}) +[2026-07-27 04:15:40,966][starVLA.training.train_starvla][INFO] - Step 2797, Loss: {'train/loss': 0.16420966386795044, 'train/grad_norm_pre_clip': 4.5039448738098145, 'timing/data': 0.0001738937571644783, 'timing/model': 0.4613213720731437, 'learning_rate/action_model': 9.410623393621935e-05, 'learning_rate/action_query_proj': 9.410623393621935e-05, 'learning_rate/base': 2.3526558484054838e-05, 'epoch': 0.34}) +[2026-07-27 04:15:46,531][starVLA.training.train_starvla][INFO] - Step 2798, Loss: {'train/loss': 0.13861083984375, 'train/grad_norm_pre_clip': 2.692836046218872, 'timing/data': 0.00017521390691399574, 'timing/model': 0.46121141081675887, 'learning_rate/action_model': 9.40917461200941e-05, 'learning_rate/action_query_proj': 9.40917461200941e-05, 'learning_rate/base': 2.3522936530023525e-05, 'epoch': 0.34}) +[2026-07-27 04:15:52,091][starVLA.training.train_starvla][INFO] - Step 2799, Loss: {'train/loss': 0.14139780402183533, 'train/grad_norm_pre_clip': 2.7667946815490723, 'timing/data': 0.00018074270337820053, 'timing/model': 0.46192310005426407, 'learning_rate/action_model': 9.40772416868141e-05, 'learning_rate/action_query_proj': 9.40772416868141e-05, 'learning_rate/base': 2.3519310421703526e-05, 'epoch': 0.34}) +[2026-07-27 04:15:57,734][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2800 +[2026-07-27 04:15:57,734][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2800 +[2026-07-27 04:15:57,735][starVLA.training.train_starvla][INFO] - Step 2800, Loss: {'train/loss': 0.22263051569461823, 'train/grad_norm_pre_clip': 4.137203693389893, 'timing/data': 0.00016916124150156975, 'timing/model': 0.46239069290459156, 'learning_rate/action_model': 9.406272064210545e-05, 'learning_rate/action_query_proj': 9.406272064210545e-05, 'learning_rate/base': 2.351568016052636e-05, 'epoch': 0.34}) +[2026-07-27 04:16:03,346][starVLA.training.train_starvla][INFO] - Step 2801, Loss: {'train/loss': 0.17215946316719055, 'train/grad_norm_pre_clip': 2.6828255653381348, 'timing/data': 0.00017327303066849709, 'timing/model': 0.45580650167539716, 'learning_rate/action_model': 9.404818299170084e-05, 'learning_rate/action_query_proj': 9.404818299170084e-05, 'learning_rate/base': 2.351204574792521e-05, 'epoch': 0.34}) +[2026-07-27 04:16:08,915][starVLA.training.train_starvla][INFO] - Step 2802, Loss: {'train/loss': 0.039351899176836014, 'train/grad_norm_pre_clip': 1.2688465118408203, 'timing/data': 0.00017576804384589195, 'timing/model': 0.4629092449322343, 'learning_rate/action_model': 9.403362874133952e-05, 'learning_rate/action_query_proj': 9.403362874133952e-05, 'learning_rate/base': 2.350840718533488e-05, 'epoch': 0.34}) +[2026-07-27 04:16:14,479][starVLA.training.train_starvla][INFO] - Step 2803, Loss: {'train/loss': 0.09317374229431152, 'train/grad_norm_pre_clip': 2.387613534927368, 'timing/data': 0.00017271796241402626, 'timing/model': 0.45692753698676825, 'learning_rate/action_model': 9.401905789676722e-05, 'learning_rate/action_query_proj': 9.401905789676722e-05, 'learning_rate/base': 2.3504764474191806e-05, 'epoch': 0.34}) +[2026-07-27 04:16:20,052][starVLA.training.train_starvla][INFO] - Step 2804, Loss: {'train/loss': 0.13552258908748627, 'train/grad_norm_pre_clip': 2.5279345512390137, 'timing/data': 0.00017106300219893456, 'timing/model': 0.46529631968587637, 'learning_rate/action_model': 9.400447046373634e-05, 'learning_rate/action_query_proj': 9.400447046373634e-05, 'learning_rate/base': 2.3501117615934086e-05, 'epoch': 0.34}) +[2026-07-27 04:16:25,647][starVLA.training.train_starvla][INFO] - Step 2805, Loss: {'train/loss': 0.16673240065574646, 'train/grad_norm_pre_clip': 3.4371416568756104, 'timing/data': 0.00017117289826273918, 'timing/model': 0.46541885612532496, 'learning_rate/action_model': 9.398986644800573e-05, 'learning_rate/action_query_proj': 9.398986644800573e-05, 'learning_rate/base': 2.3497466612001434e-05, 'epoch': 0.34}) +[2026-07-27 04:16:31,258][starVLA.training.train_starvla][INFO] - Step 2806, Loss: {'train/loss': 0.13936938345432281, 'train/grad_norm_pre_clip': 3.763366937637329, 'timing/data': 0.00017632218077778816, 'timing/model': 0.46501661092042923, 'learning_rate/action_model': 9.397524585534085e-05, 'learning_rate/action_query_proj': 9.397524585534085e-05, 'learning_rate/base': 2.3493811463835213e-05, 'epoch': 0.34}) +[2026-07-27 04:16:36,858][starVLA.training.train_starvla][INFO] - Step 2807, Loss: {'train/loss': 0.12412933260202408, 'train/grad_norm_pre_clip': 2.905160427093506, 'timing/data': 0.00017610285431146622, 'timing/model': 0.46294480189681053, 'learning_rate/action_model': 9.396060869151366e-05, 'learning_rate/action_query_proj': 9.396060869151366e-05, 'learning_rate/base': 2.3490152172878414e-05, 'epoch': 0.34}) +[2026-07-27 04:16:42,443][starVLA.training.train_starvla][INFO] - Step 2808, Loss: {'train/loss': 0.14689168334007263, 'train/grad_norm_pre_clip': 2.856593608856201, 'timing/data': 0.0001789359375834465, 'timing/model': 0.4637060877867043, 'learning_rate/action_model': 9.39459549623027e-05, 'learning_rate/action_query_proj': 9.39459549623027e-05, 'learning_rate/base': 2.3486488740575675e-05, 'epoch': 0.34}) +[2026-07-27 04:16:48,365][starVLA.training.train_starvla][INFO] - Step 2809, Loss: {'train/loss': 0.10755768418312073, 'train/grad_norm_pre_clip': 3.697031259536743, 'timing/data': 0.0001712767407298088, 'timing/model': 0.4628705019131303, 'learning_rate/action_model': 9.393128467349301e-05, 'learning_rate/action_query_proj': 9.393128467349301e-05, 'learning_rate/base': 2.3482821168373252e-05, 'epoch': 0.34}) +[2026-07-27 04:16:53,988][starVLA.training.train_starvla][INFO] - Step 2810, Loss: {'train/loss': 0.07650217413902283, 'train/grad_norm_pre_clip': 1.8218178749084473, 'timing/data': 0.0001781121827661991, 'timing/model': 0.4691078523173928, 'learning_rate/action_model': 9.391659783087618e-05, 'learning_rate/action_query_proj': 9.391659783087618e-05, 'learning_rate/base': 2.3479149457719045e-05, 'epoch': 0.34}) +[2026-07-27 04:16:59,620][starVLA.training.train_starvla][INFO] - Step 2811, Loss: {'train/loss': 0.12173932045698166, 'train/grad_norm_pre_clip': 2.869860887527466, 'timing/data': 0.00017503509297966957, 'timing/model': 0.4623617809265852, 'learning_rate/action_model': 9.390189444025036e-05, 'learning_rate/action_query_proj': 9.390189444025036e-05, 'learning_rate/base': 2.347547361006259e-05, 'epoch': 0.34}) +[2026-07-27 04:17:05,241][starVLA.training.train_starvla][INFO] - Step 2812, Loss: {'train/loss': 0.15128542482852936, 'train/grad_norm_pre_clip': 3.514294385910034, 'timing/data': 0.00017978576943278313, 'timing/model': 0.46325570065528154, 'learning_rate/action_model': 9.388717450742021e-05, 'learning_rate/action_query_proj': 9.388717450742021e-05, 'learning_rate/base': 2.3471793626855053e-05, 'epoch': 0.34}) +[2026-07-27 04:17:10,834][starVLA.training.train_starvla][INFO] - Step 2813, Loss: {'train/loss': 0.21842798590660095, 'train/grad_norm_pre_clip': 3.820063591003418, 'timing/data': 0.000170102808624506, 'timing/model': 0.4674538793042302, 'learning_rate/action_model': 9.387243803819694e-05, 'learning_rate/action_query_proj': 9.387243803819694e-05, 'learning_rate/base': 2.3468109509549235e-05, 'epoch': 0.34}) +[2026-07-27 04:17:16,473][starVLA.training.train_starvla][INFO] - Step 2814, Loss: {'train/loss': 0.09778331220149994, 'train/grad_norm_pre_clip': 3.1638951301574707, 'timing/data': 0.00017435196787118912, 'timing/model': 0.46480928594246507, 'learning_rate/action_model': 9.385768503839827e-05, 'learning_rate/action_query_proj': 9.385768503839827e-05, 'learning_rate/base': 2.346442125959957e-05, 'epoch': 0.34}) +[2026-07-27 04:17:22,120][starVLA.training.train_starvla][INFO] - Step 2815, Loss: {'train/loss': 0.10304255783557892, 'train/grad_norm_pre_clip': 1.7083021402359009, 'timing/data': 0.00018027517944574356, 'timing/model': 0.46355460677295923, 'learning_rate/action_model': 9.384291551384843e-05, 'learning_rate/action_query_proj': 9.384291551384843e-05, 'learning_rate/base': 2.346072887846211e-05, 'epoch': 0.34}) +[2026-07-27 04:17:27,777][starVLA.training.train_starvla][INFO] - Step 2816, Loss: {'train/loss': 0.19126570224761963, 'train/grad_norm_pre_clip': 4.786315441131592, 'timing/data': 0.0001744409091770649, 'timing/model': 0.4670162503607571, 'learning_rate/action_model': 9.382812947037821e-05, 'learning_rate/action_query_proj': 9.382812947037821e-05, 'learning_rate/base': 2.3457032367594552e-05, 'epoch': 0.34}) +[2026-07-27 04:17:33,460][starVLA.training.train_starvla][INFO] - Step 2817, Loss: {'train/loss': 0.24914336204528809, 'train/grad_norm_pre_clip': 4.575440406799316, 'timing/data': 0.00017341412603855133, 'timing/model': 0.4663580069318414, 'learning_rate/action_model': 9.381332691382491e-05, 'learning_rate/action_query_proj': 9.381332691382491e-05, 'learning_rate/base': 2.345333172845623e-05, 'epoch': 0.34}) +[2026-07-27 04:17:39,108][starVLA.training.train_starvla][INFO] - Step 2818, Loss: {'train/loss': 0.21067257225513458, 'train/grad_norm_pre_clip': 4.559476375579834, 'timing/data': 0.00018661189824342728, 'timing/model': 0.4640758787281811, 'learning_rate/action_model': 9.379850785003234e-05, 'learning_rate/action_query_proj': 9.379850785003234e-05, 'learning_rate/base': 2.3449626962508086e-05, 'epoch': 0.34}) +[2026-07-27 04:17:44,791][starVLA.training.train_starvla][INFO] - Step 2819, Loss: {'train/loss': 0.12583130598068237, 'train/grad_norm_pre_clip': 2.5579333305358887, 'timing/data': 0.00017553707584738731, 'timing/model': 0.46609594067558646, 'learning_rate/action_model': 9.378367228485083e-05, 'learning_rate/action_query_proj': 9.378367228485083e-05, 'learning_rate/base': 2.3445918071212707e-05, 'epoch': 0.34}) +[2026-07-27 04:17:50,397][starVLA.training.train_starvla][INFO] - Step 2820, Loss: {'train/loss': 0.11407067626714706, 'train/grad_norm_pre_clip': 2.5186779499053955, 'timing/data': 0.00018544495105743408, 'timing/model': 0.464373872615397, 'learning_rate/action_model': 9.376882022413723e-05, 'learning_rate/action_query_proj': 9.376882022413723e-05, 'learning_rate/base': 2.3442205056034307e-05, 'epoch': 0.34}) +[2026-07-27 04:17:55,994][starVLA.training.train_starvla][INFO] - Step 2821, Loss: {'train/loss': 0.21428273618221283, 'train/grad_norm_pre_clip': 4.437380790710449, 'timing/data': 0.00017287908121943474, 'timing/model': 0.46596750570461154, 'learning_rate/action_model': 9.375395167375489e-05, 'learning_rate/action_query_proj': 9.375395167375489e-05, 'learning_rate/base': 2.3438487918438723e-05, 'epoch': 0.34}) +[2026-07-27 04:18:01,594][starVLA.training.train_starvla][INFO] - Step 2822, Loss: {'train/loss': 0.203127920627594, 'train/grad_norm_pre_clip': 3.4900240898132324, 'timing/data': 0.00017468398436903954, 'timing/model': 0.46423392882570624, 'learning_rate/action_model': 9.37390666395737e-05, 'learning_rate/action_query_proj': 9.37390666395737e-05, 'learning_rate/base': 2.3434766659893427e-05, 'epoch': 0.34}) +[2026-07-27 04:18:07,213][starVLA.training.train_starvla][INFO] - Step 2823, Loss: {'train/loss': 0.21564702689647675, 'train/grad_norm_pre_clip': 5.361258029937744, 'timing/data': 0.00017846934497356415, 'timing/model': 0.4630627939477563, 'learning_rate/action_model': 9.372416512747e-05, 'learning_rate/action_query_proj': 9.372416512747e-05, 'learning_rate/base': 2.34310412818675e-05, 'epoch': 0.34}) +[2026-07-27 04:18:12,836][starVLA.training.train_starvla][INFO] - Step 2824, Loss: {'train/loss': 0.1878410130739212, 'train/grad_norm_pre_clip': 4.921347141265869, 'timing/data': 0.0001728581264615059, 'timing/model': 0.4657299406826496, 'learning_rate/action_model': 9.370924714332671e-05, 'learning_rate/action_query_proj': 9.370924714332671e-05, 'learning_rate/base': 2.3427311785831678e-05, 'epoch': 0.34}) +[2026-07-27 04:18:18,427][starVLA.training.train_starvla][INFO] - Step 2825, Loss: {'train/loss': 0.20226015150547028, 'train/grad_norm_pre_clip': 3.1208159923553467, 'timing/data': 0.00017432775348424911, 'timing/model': 0.46249267971143126, 'learning_rate/action_model': 9.36943126930332e-05, 'learning_rate/action_query_proj': 9.36943126930332e-05, 'learning_rate/base': 2.34235781732583e-05, 'epoch': 0.34}) +[2026-07-27 04:18:24,051][starVLA.training.train_starvla][INFO] - Step 2826, Loss: {'train/loss': 0.10533993691205978, 'train/grad_norm_pre_clip': 3.236482620239258, 'timing/data': 0.00018314318731427193, 'timing/model': 0.46597752161324024, 'learning_rate/action_model': 9.367936178248533e-05, 'learning_rate/action_query_proj': 9.367936178248533e-05, 'learning_rate/base': 2.341984044562133e-05, 'epoch': 0.34}) +[2026-07-27 04:18:29,665][starVLA.training.train_starvla][INFO] - Step 2827, Loss: {'train/loss': 0.1278623342514038, 'train/grad_norm_pre_clip': 2.430636405944824, 'timing/data': 0.00017235008999705315, 'timing/model': 0.4614902166649699, 'learning_rate/action_model': 9.36643944175855e-05, 'learning_rate/action_query_proj': 9.36643944175855e-05, 'learning_rate/base': 2.3416098604396374e-05, 'epoch': 0.34}) +[2026-07-27 04:18:35,297][starVLA.training.train_starvla][INFO] - Step 2828, Loss: {'train/loss': 0.13022400438785553, 'train/grad_norm_pre_clip': 2.082693338394165, 'timing/data': 0.00017439574003219604, 'timing/model': 0.46376753225922585, 'learning_rate/action_model': 9.364941060424258e-05, 'learning_rate/action_query_proj': 9.364941060424258e-05, 'learning_rate/base': 2.3412352651060645e-05, 'epoch': 0.34}) +[2026-07-27 04:18:40,907][starVLA.training.train_starvla][INFO] - Step 2829, Loss: {'train/loss': 0.03202605992555618, 'train/grad_norm_pre_clip': 1.2868252992630005, 'timing/data': 0.00017177406698465347, 'timing/model': 0.46781474398449063, 'learning_rate/action_model': 9.363441034837199e-05, 'learning_rate/action_query_proj': 9.363441034837199e-05, 'learning_rate/base': 2.3408602587092997e-05, 'epoch': 0.34}) +[2026-07-27 04:18:46,711][starVLA.training.train_starvla][INFO] - Step 2830, Loss: {'train/loss': 0.13415269553661346, 'train/grad_norm_pre_clip': 5.172083377838135, 'timing/data': 0.00017189979553222656, 'timing/model': 0.46558846114203334, 'learning_rate/action_model': 9.361939365589553e-05, 'learning_rate/action_query_proj': 9.361939365589553e-05, 'learning_rate/base': 2.3404848413973883e-05, 'epoch': 0.34}) +[2026-07-27 04:18:52,337][starVLA.training.train_starvla][INFO] - Step 2831, Loss: {'train/loss': 0.11004824936389923, 'train/grad_norm_pre_clip': 3.6121904850006104, 'timing/data': 0.00017388304695487022, 'timing/model': 0.46374322893097997, 'learning_rate/action_model': 9.360436053274158e-05, 'learning_rate/action_query_proj': 9.360436053274158e-05, 'learning_rate/base': 2.3401090133185395e-05, 'epoch': 0.34}) +[2026-07-27 04:18:57,984][starVLA.training.train_starvla][INFO] - Step 2832, Loss: {'train/loss': 0.30171138048171997, 'train/grad_norm_pre_clip': 5.519800662994385, 'timing/data': 0.00017788074910640717, 'timing/model': 0.4631296223960817, 'learning_rate/action_model': 9.358931098484499e-05, 'learning_rate/action_query_proj': 9.358931098484499e-05, 'learning_rate/base': 2.3397327746211247e-05, 'epoch': 0.34}) +[2026-07-27 04:19:03,591][starVLA.training.train_starvla][INFO] - Step 2833, Loss: {'train/loss': 0.22392675280570984, 'train/grad_norm_pre_clip': 5.122239112854004, 'timing/data': 0.0001741349697113037, 'timing/model': 0.4662397438660264, 'learning_rate/action_model': 9.357424501814706e-05, 'learning_rate/action_query_proj': 9.357424501814706e-05, 'learning_rate/base': 2.3393561254536764e-05, 'epoch': 0.34}) +[2026-07-27 04:19:09,239][starVLA.training.train_starvla][INFO] - Step 2834, Loss: {'train/loss': 0.11409717798233032, 'train/grad_norm_pre_clip': 3.6113901138305664, 'timing/data': 0.0001736413687467575, 'timing/model': 0.46335409209132195, 'learning_rate/action_model': 9.355916263859561e-05, 'learning_rate/action_query_proj': 9.355916263859561e-05, 'learning_rate/base': 2.3389790659648904e-05, 'epoch': 0.34}) +[2026-07-27 04:19:14,841][starVLA.training.train_starvla][INFO] - Step 2835, Loss: {'train/loss': 0.044945668429136276, 'train/grad_norm_pre_clip': 1.3957756757736206, 'timing/data': 0.00017271284013986588, 'timing/model': 0.4626760659739375, 'learning_rate/action_model': 9.354406385214491e-05, 'learning_rate/action_query_proj': 9.354406385214491e-05, 'learning_rate/base': 2.3386015963036227e-05, 'epoch': 0.34}) +[2026-07-27 04:19:20,473][starVLA.training.train_starvla][INFO] - Step 2836, Loss: {'train/loss': 0.126336470246315, 'train/grad_norm_pre_clip': 3.46384334564209, 'timing/data': 0.00017467420548200607, 'timing/model': 0.4659071508795023, 'learning_rate/action_model': 9.352894866475575e-05, 'learning_rate/action_query_proj': 9.352894866475575e-05, 'learning_rate/base': 2.3382237166188937e-05, 'epoch': 0.34}) +[2026-07-27 04:19:26,120][starVLA.training.train_starvla][INFO] - Step 2837, Loss: {'train/loss': 0.0945490151643753, 'train/grad_norm_pre_clip': 2.738891839981079, 'timing/data': 0.00018164003267884254, 'timing/model': 0.46665366599336267, 'learning_rate/action_model': 9.351381708239534e-05, 'learning_rate/action_query_proj': 9.351381708239534e-05, 'learning_rate/base': 2.3378454270598835e-05, 'epoch': 0.34}) +[2026-07-27 04:19:31,724][starVLA.training.train_starvla][INFO] - Step 2838, Loss: {'train/loss': 0.15215636789798737, 'train/grad_norm_pre_clip': 2.616151809692383, 'timing/data': 0.0001763841137290001, 'timing/model': 0.4642991409637034, 'learning_rate/action_model': 9.34986691110374e-05, 'learning_rate/action_query_proj': 9.34986691110374e-05, 'learning_rate/base': 2.337466727775935e-05, 'epoch': 0.34}) +[2026-07-27 04:19:37,309][starVLA.training.train_starvla][INFO] - Step 2839, Loss: {'train/loss': 0.15254926681518555, 'train/grad_norm_pre_clip': 4.173856258392334, 'timing/data': 0.00017732568085193634, 'timing/model': 0.46308236476033926, 'learning_rate/action_model': 9.34835047566621e-05, 'learning_rate/action_query_proj': 9.34835047566621e-05, 'learning_rate/base': 2.3370876189165525e-05, 'epoch': 0.34}) +[2026-07-27 04:19:42,933][starVLA.training.train_starvla][INFO] - Step 2840, Loss: {'train/loss': 0.1614297479391098, 'train/grad_norm_pre_clip': 3.634267568588257, 'timing/data': 0.00017176056280732155, 'timing/model': 0.45975814294070005, 'learning_rate/action_model': 9.34683240252561e-05, 'learning_rate/action_query_proj': 9.34683240252561e-05, 'learning_rate/base': 2.3367081006314024e-05, 'epoch': 0.34}) +[2026-07-27 04:19:48,536][starVLA.training.train_starvla][INFO] - Step 2841, Loss: {'train/loss': 0.11461078375577927, 'train/grad_norm_pre_clip': 4.129837512969971, 'timing/data': 0.00017617782577872276, 'timing/model': 0.4616772159934044, 'learning_rate/action_model': 9.345312692281251e-05, 'learning_rate/action_query_proj': 9.345312692281251e-05, 'learning_rate/base': 2.3363281730703128e-05, 'epoch': 0.34}) +[2026-07-27 04:19:54,153][starVLA.training.train_starvla][INFO] - Step 2842, Loss: {'train/loss': 0.12796540558338165, 'train/grad_norm_pre_clip': 3.368720769882202, 'timing/data': 0.00017509888857603073, 'timing/model': 0.46615938609465957, 'learning_rate/action_model': 9.34379134553309e-05, 'learning_rate/action_query_proj': 9.34379134553309e-05, 'learning_rate/base': 2.3359478363832725e-05, 'epoch': 0.34}) +[2026-07-27 04:19:59,766][starVLA.training.train_starvla][INFO] - Step 2843, Loss: {'train/loss': 0.18128755688667297, 'train/grad_norm_pre_clip': 3.986640214920044, 'timing/data': 0.00017339922487735748, 'timing/model': 0.45981664303690195, 'learning_rate/action_model': 9.342268362881729e-05, 'learning_rate/action_query_proj': 9.342268362881729e-05, 'learning_rate/base': 2.3355670907204323e-05, 'epoch': 0.34}) +[2026-07-27 04:20:05,383][starVLA.training.train_starvla][INFO] - Step 2844, Loss: {'train/loss': 0.07866573333740234, 'train/grad_norm_pre_clip': 2.8471028804779053, 'timing/data': 0.00017285998910665512, 'timing/model': 0.4621023559011519, 'learning_rate/action_model': 9.340743744928422e-05, 'learning_rate/action_query_proj': 9.340743744928422e-05, 'learning_rate/base': 2.3351859362321054e-05, 'epoch': 0.35}) +[2026-07-27 04:20:11,007][starVLA.training.train_starvla][INFO] - Step 2845, Loss: {'train/loss': 0.1963626891374588, 'train/grad_norm_pre_clip': 4.668315410614014, 'timing/data': 0.00018519628793001175, 'timing/model': 0.4660913650877774, 'learning_rate/action_model': 9.33921749227506e-05, 'learning_rate/action_query_proj': 9.33921749227506e-05, 'learning_rate/base': 2.334804373068765e-05, 'epoch': 0.35}) +[2026-07-27 04:20:16,624][starVLA.training.train_starvla][INFO] - Step 2846, Loss: {'train/loss': 0.12221221625804901, 'train/grad_norm_pre_clip': 3.1455767154693604, 'timing/data': 0.00017294008284807205, 'timing/model': 0.4621335254050791, 'learning_rate/action_model': 9.337689605524184e-05, 'learning_rate/action_query_proj': 9.337689605524184e-05, 'learning_rate/base': 2.334422401381046e-05, 'epoch': 0.35}) +[2026-07-27 04:20:22,263][starVLA.training.train_starvla][INFO] - Step 2847, Loss: {'train/loss': 0.137944296002388, 'train/grad_norm_pre_clip': 3.9244229793548584, 'timing/data': 0.0001774197444319725, 'timing/model': 0.4628795040771365, 'learning_rate/action_model': 9.336160085278981e-05, 'learning_rate/action_query_proj': 9.336160085278981e-05, 'learning_rate/base': 2.3340400213197452e-05, 'epoch': 0.35}) +[2026-07-27 04:20:27,894][starVLA.training.train_starvla][INFO] - Step 2848, Loss: {'train/loss': 0.17395111918449402, 'train/grad_norm_pre_clip': 3.489337682723999, 'timing/data': 0.00018789293244481087, 'timing/model': 0.4641728540882468, 'learning_rate/action_model': 9.33462893214328e-05, 'learning_rate/action_query_proj': 9.33462893214328e-05, 'learning_rate/base': 2.33365723303582e-05, 'epoch': 0.35}) +[2026-07-27 04:20:33,480][starVLA.training.train_starvla][INFO] - Step 2849, Loss: {'train/loss': 0.12171079963445663, 'train/grad_norm_pre_clip': 2.3341314792633057, 'timing/data': 0.0001729782670736313, 'timing/model': 0.46514999493956566, 'learning_rate/action_model': 9.333096146721557e-05, 'learning_rate/action_query_proj': 9.333096146721557e-05, 'learning_rate/base': 2.333274036680389e-05, 'epoch': 0.35}) +[2026-07-27 04:20:39,047][starVLA.training.train_starvla][INFO] - Step 2850, Loss: {'train/loss': 0.319965124130249, 'train/grad_norm_pre_clip': 5.726029396057129, 'timing/data': 0.0001791650429368019, 'timing/model': 0.46273966087028384, 'learning_rate/action_model': 9.33156172961893e-05, 'learning_rate/action_query_proj': 9.33156172961893e-05, 'learning_rate/base': 2.3328904324047325e-05, 'epoch': 0.35}) +[2026-07-27 04:20:44,632][starVLA.training.train_starvla][INFO] - Step 2851, Loss: {'train/loss': 0.1375240981578827, 'train/grad_norm_pre_clip': 3.1437063217163086, 'timing/data': 0.00017420761287212372, 'timing/model': 0.464455493260175, 'learning_rate/action_model': 9.330025681441163e-05, 'learning_rate/action_query_proj': 9.330025681441163e-05, 'learning_rate/base': 2.3325064203602908e-05, 'epoch': 0.35}) +[2026-07-27 04:20:50,241][starVLA.training.train_starvla][INFO] - Step 2852, Loss: {'train/loss': 0.23892253637313843, 'train/grad_norm_pre_clip': 4.578263282775879, 'timing/data': 0.00017027882859110832, 'timing/model': 0.4653418269008398, 'learning_rate/action_model': 9.328488002794666e-05, 'learning_rate/action_query_proj': 9.328488002794666e-05, 'learning_rate/base': 2.3321220006986664e-05, 'epoch': 0.35}) +[2026-07-27 04:20:55,827][starVLA.training.train_starvla][INFO] - Step 2853, Loss: {'train/loss': 0.2538332939147949, 'train/grad_norm_pre_clip': 3.047414779663086, 'timing/data': 0.00017416710034012794, 'timing/model': 0.4666296080686152, 'learning_rate/action_model': 9.326948694286486e-05, 'learning_rate/action_query_proj': 9.326948694286486e-05, 'learning_rate/base': 2.3317371735716215e-05, 'epoch': 0.35}) +[2026-07-27 04:21:01,412][starVLA.training.train_starvla][INFO] - Step 2854, Loss: {'train/loss': 0.18260665237903595, 'train/grad_norm_pre_clip': 3.3622732162475586, 'timing/data': 0.00017608702182769775, 'timing/model': 0.46330871107056737, 'learning_rate/action_model': 9.325407756524321e-05, 'learning_rate/action_query_proj': 9.325407756524321e-05, 'learning_rate/base': 2.3313519391310802e-05, 'epoch': 0.35}) +[2026-07-27 04:21:06,994][starVLA.training.train_starvla][INFO] - Step 2855, Loss: {'train/loss': 0.28194567561149597, 'train/grad_norm_pre_clip': 4.0381340980529785, 'timing/data': 0.00022272998467087746, 'timing/model': 0.46627160301432014, 'learning_rate/action_model': 9.323865190116508e-05, 'learning_rate/action_query_proj': 9.323865190116508e-05, 'learning_rate/base': 2.330966297529127e-05, 'epoch': 0.35}) +[2026-07-27 04:21:12,601][starVLA.training.train_starvla][INFO] - Step 2856, Loss: {'train/loss': 0.09089729934930801, 'train/grad_norm_pre_clip': 2.517850637435913, 'timing/data': 0.00017529679462313652, 'timing/model': 0.46172708505764604, 'learning_rate/action_model': 9.322320995672028e-05, 'learning_rate/action_query_proj': 9.322320995672028e-05, 'learning_rate/base': 2.330580248918007e-05, 'epoch': 0.35}) +[2026-07-27 04:21:18,366][starVLA.training.train_starvla][INFO] - Step 2857, Loss: {'train/loss': 0.14080515503883362, 'train/grad_norm_pre_clip': 2.803861618041992, 'timing/data': 0.00018203910440206528, 'timing/model': 0.6317439428530633, 'learning_rate/action_model': 9.3207751738005e-05, 'learning_rate/action_query_proj': 9.3207751738005e-05, 'learning_rate/base': 2.330193793450125e-05, 'epoch': 0.35}) +[2026-07-27 04:21:23,950][starVLA.training.train_starvla][INFO] - Step 2858, Loss: {'train/loss': 0.07963484525680542, 'train/grad_norm_pre_clip': 2.472947359085083, 'timing/data': 0.00021547917276620865, 'timing/model': 0.46367216715589166, 'learning_rate/action_model': 9.319227725112199e-05, 'learning_rate/action_query_proj': 9.319227725112199e-05, 'learning_rate/base': 2.3298069312780497e-05, 'epoch': 0.35}) +[2026-07-27 04:21:29,549][starVLA.training.train_starvla][INFO] - Step 2859, Loss: {'train/loss': 0.20869570970535278, 'train/grad_norm_pre_clip': 3.37740421295166, 'timing/data': 0.00018762517720460892, 'timing/model': 0.46646026102826, 'learning_rate/action_model': 9.317678650218024e-05, 'learning_rate/action_query_proj': 9.317678650218024e-05, 'learning_rate/base': 2.329419662554506e-05, 'epoch': 0.35}) +[2026-07-27 04:21:35,133][starVLA.training.train_starvla][INFO] - Step 2860, Loss: {'train/loss': 0.24594585597515106, 'train/grad_norm_pre_clip': 4.324487686157227, 'timing/data': 0.00017980393022298813, 'timing/model': 0.46116500394418836, 'learning_rate/action_model': 9.316127949729531e-05, 'learning_rate/action_query_proj': 9.316127949729531e-05, 'learning_rate/base': 2.329031987432383e-05, 'epoch': 0.35}) +[2026-07-27 04:21:40,716][starVLA.training.train_starvla][INFO] - Step 2861, Loss: {'train/loss': 0.11854086071252823, 'train/grad_norm_pre_clip': 3.048657178878784, 'timing/data': 0.00017743604257702827, 'timing/model': 0.4653532588854432, 'learning_rate/action_model': 9.314575624258912e-05, 'learning_rate/action_query_proj': 9.314575624258912e-05, 'learning_rate/base': 2.328643906064728e-05, 'epoch': 0.35}) +[2026-07-27 04:21:46,540][starVLA.training.train_starvla][INFO] - Step 2862, Loss: {'train/loss': 0.1135767251253128, 'train/grad_norm_pre_clip': 2.429252862930298, 'timing/data': 0.0001743561588227749, 'timing/model': 0.46721016708761454, 'learning_rate/action_model': 9.313021674418996e-05, 'learning_rate/action_query_proj': 9.313021674418996e-05, 'learning_rate/base': 2.328255418604749e-05, 'epoch': 0.35}) +[2026-07-27 04:21:52,385][starVLA.training.train_starvla][INFO] - Step 2863, Loss: {'train/loss': 0.10361144691705704, 'train/grad_norm_pre_clip': 2.735741138458252, 'timing/data': 0.00018308497965335846, 'timing/model': 0.46259603882208467, 'learning_rate/action_model': 9.311466100823261e-05, 'learning_rate/action_query_proj': 9.311466100823261e-05, 'learning_rate/base': 2.3278665252058152e-05, 'epoch': 0.35}) +[2026-07-27 04:21:57,958][starVLA.training.train_starvla][INFO] - Step 2864, Loss: {'train/loss': 0.0810168907046318, 'train/grad_norm_pre_clip': 1.840619444847107, 'timing/data': 0.00017412565648555756, 'timing/model': 0.4613435887731612, 'learning_rate/action_model': 9.309908904085823e-05, 'learning_rate/action_query_proj': 9.309908904085823e-05, 'learning_rate/base': 2.327477226021456e-05, 'epoch': 0.35}) +[2026-07-27 04:22:03,537][starVLA.training.train_starvla][INFO] - Step 2865, Loss: {'train/loss': 0.06012710928916931, 'train/grad_norm_pre_clip': 1.9942609071731567, 'timing/data': 0.00017850985750555992, 'timing/model': 0.4654726181179285, 'learning_rate/action_model': 9.308350084821439e-05, 'learning_rate/action_query_proj': 9.308350084821439e-05, 'learning_rate/base': 2.3270875212053597e-05, 'epoch': 0.35}) +[2026-07-27 04:22:09,125][starVLA.training.train_starvla][INFO] - Step 2866, Loss: {'train/loss': 0.1481286734342575, 'train/grad_norm_pre_clip': 2.7818779945373535, 'timing/data': 0.00018322886899113655, 'timing/model': 0.4628041032701731, 'learning_rate/action_model': 9.306789643645505e-05, 'learning_rate/action_query_proj': 9.306789643645505e-05, 'learning_rate/base': 2.3266974109113763e-05, 'epoch': 0.35}) +[2026-07-27 04:22:14,704][starVLA.training.train_starvla][INFO] - Step 2867, Loss: {'train/loss': 0.07799771428108215, 'train/grad_norm_pre_clip': 1.9271007776260376, 'timing/data': 0.00017325440421700478, 'timing/model': 0.46572077088057995, 'learning_rate/action_model': 9.305227581174057e-05, 'learning_rate/action_query_proj': 9.305227581174057e-05, 'learning_rate/base': 2.3263068952935142e-05, 'epoch': 0.35}) +[2026-07-27 04:22:20,286][starVLA.training.train_starvla][INFO] - Step 2868, Loss: {'train/loss': 0.13676518201828003, 'train/grad_norm_pre_clip': 3.7208523750305176, 'timing/data': 0.0001762108877301216, 'timing/model': 0.46315213292837143, 'learning_rate/action_model': 9.303663898023776e-05, 'learning_rate/action_query_proj': 9.303663898023776e-05, 'learning_rate/base': 2.325915974505944e-05, 'epoch': 0.35}) +[2026-07-27 04:22:25,853][starVLA.training.train_starvla][INFO] - Step 2869, Loss: {'train/loss': 0.11503250151872635, 'train/grad_norm_pre_clip': 3.287376642227173, 'timing/data': 0.00017978204414248466, 'timing/model': 0.46272827172651887, 'learning_rate/action_model': 9.302098594811976e-05, 'learning_rate/action_query_proj': 9.302098594811976e-05, 'learning_rate/base': 2.325524648702994e-05, 'epoch': 0.35}) +[2026-07-27 04:22:31,444][starVLA.training.train_starvla][INFO] - Step 2870, Loss: {'train/loss': 0.17844325304031372, 'train/grad_norm_pre_clip': 3.582319736480713, 'timing/data': 0.00017292704433202744, 'timing/model': 0.4632521993480623, 'learning_rate/action_model': 9.300531672156618e-05, 'learning_rate/action_query_proj': 9.300531672156618e-05, 'learning_rate/base': 2.3251329180391544e-05, 'epoch': 0.35}) +[2026-07-27 04:22:37,025][starVLA.training.train_starvla][INFO] - Step 2871, Loss: {'train/loss': 0.11875321716070175, 'train/grad_norm_pre_clip': 3.6461079120635986, 'timing/data': 0.00017191143706440926, 'timing/model': 0.46248108008876443, 'learning_rate/action_model': 9.298963130676294e-05, 'learning_rate/action_query_proj': 9.298963130676294e-05, 'learning_rate/base': 2.3247407826690736e-05, 'epoch': 0.35}) +[2026-07-27 04:22:42,631][starVLA.training.train_starvla][INFO] - Step 2872, Loss: {'train/loss': 0.12188342213630676, 'train/grad_norm_pre_clip': 2.8739101886749268, 'timing/data': 0.0001834849826991558, 'timing/model': 0.46310618380084634, 'learning_rate/action_model': 9.297392970990241e-05, 'learning_rate/action_query_proj': 9.297392970990241e-05, 'learning_rate/base': 2.3243482427475603e-05, 'epoch': 0.35}) +[2026-07-27 04:22:48,236][starVLA.training.train_starvla][INFO] - Step 2873, Loss: {'train/loss': 0.17160840332508087, 'train/grad_norm_pre_clip': 3.5973567962646484, 'timing/data': 0.0001773769035935402, 'timing/model': 0.4660294121131301, 'learning_rate/action_model': 9.295821193718334e-05, 'learning_rate/action_query_proj': 9.295821193718334e-05, 'learning_rate/base': 2.3239552984295835e-05, 'epoch': 0.35}) +[2026-07-27 04:22:53,840][starVLA.training.train_starvla][INFO] - Step 2874, Loss: {'train/loss': 0.11599276959896088, 'train/grad_norm_pre_clip': 2.6667237281799316, 'timing/data': 0.00018560094758868217, 'timing/model': 0.4622296611778438, 'learning_rate/action_model': 9.294247799481083e-05, 'learning_rate/action_query_proj': 9.294247799481083e-05, 'learning_rate/base': 2.3235619498702706e-05, 'epoch': 0.35}) +[2026-07-27 04:22:59,449][starVLA.training.train_starvla][INFO] - Step 2875, Loss: {'train/loss': 0.2737025022506714, 'train/grad_norm_pre_clip': 5.760605812072754, 'timing/data': 0.00018741097301244736, 'timing/model': 0.46217177575454116, 'learning_rate/action_model': 9.292672788899643e-05, 'learning_rate/action_query_proj': 9.292672788899643e-05, 'learning_rate/base': 2.3231681972249107e-05, 'epoch': 0.35}) +[2026-07-27 04:23:05,047][starVLA.training.train_starvla][INFO] - Step 2876, Loss: {'train/loss': 0.0742611438035965, 'train/grad_norm_pre_clip': 2.625760316848755, 'timing/data': 0.0001841099001467228, 'timing/model': 0.4622768424451351, 'learning_rate/action_model': 9.291096162595801e-05, 'learning_rate/action_query_proj': 9.291096162595801e-05, 'learning_rate/base': 2.3227740406489503e-05, 'epoch': 0.35}) +[2026-07-27 04:23:10,646][starVLA.training.train_starvla][INFO] - Step 2877, Loss: {'train/loss': 0.10538189113140106, 'train/grad_norm_pre_clip': 3.6518232822418213, 'timing/data': 0.00017970893532037735, 'timing/model': 0.46310616703704, 'learning_rate/action_model': 9.289517921191985e-05, 'learning_rate/action_query_proj': 9.289517921191985e-05, 'learning_rate/base': 2.3223794802979963e-05, 'epoch': 0.35}) +[2026-07-27 04:23:16,253][starVLA.training.train_starvla][INFO] - Step 2878, Loss: {'train/loss': 0.10353266447782516, 'train/grad_norm_pre_clip': 2.8458199501037598, 'timing/data': 0.00017480971291661263, 'timing/model': 0.4659920618869364, 'learning_rate/action_model': 9.287938065311258e-05, 'learning_rate/action_query_proj': 9.287938065311258e-05, 'learning_rate/base': 2.3219845163278144e-05, 'epoch': 0.35}) +[2026-07-27 04:23:21,838][starVLA.training.train_starvla][INFO] - Step 2879, Loss: {'train/loss': 0.3157505691051483, 'train/grad_norm_pre_clip': 4.745258331298828, 'timing/data': 0.00017521902918815613, 'timing/model': 0.4614001726731658, 'learning_rate/action_model': 9.286356595577325e-05, 'learning_rate/action_query_proj': 9.286356595577325e-05, 'learning_rate/base': 2.3215891488943312e-05, 'epoch': 0.35}) +[2026-07-27 04:23:27,442][starVLA.training.train_starvla][INFO] - Step 2880, Loss: {'train/loss': 0.11395850032567978, 'train/grad_norm_pre_clip': 2.7202861309051514, 'timing/data': 0.0001798979938030243, 'timing/model': 0.46314792800694704, 'learning_rate/action_model': 9.284773512614522e-05, 'learning_rate/action_query_proj': 9.284773512614522e-05, 'learning_rate/base': 2.3211933781536305e-05, 'epoch': 0.35}) +[2026-07-27 04:23:33,037][starVLA.training.train_starvla][INFO] - Step 2881, Loss: {'train/loss': 0.07935447245836258, 'train/grad_norm_pre_clip': 2.785930633544922, 'timing/data': 0.00017501134425401688, 'timing/model': 0.462454651016742, 'learning_rate/action_model': 9.283188817047826e-05, 'learning_rate/action_query_proj': 9.283188817047826e-05, 'learning_rate/base': 2.3207972042619566e-05, 'epoch': 0.35}) +[2026-07-27 04:23:38,620][starVLA.training.train_starvla][INFO] - Step 2882, Loss: {'train/loss': 0.16120676696300507, 'train/grad_norm_pre_clip': 4.585208892822266, 'timing/data': 0.0001771370880305767, 'timing/model': 0.4656112929806113, 'learning_rate/action_model': 9.281602509502851e-05, 'learning_rate/action_query_proj': 9.281602509502851e-05, 'learning_rate/base': 2.320400627375713e-05, 'epoch': 0.35}) +[2026-07-27 04:23:44,223][starVLA.training.train_starvla][INFO] - Step 2883, Loss: {'train/loss': 0.15534262359142303, 'train/grad_norm_pre_clip': 3.793060064315796, 'timing/data': 0.00017207814380526543, 'timing/model': 0.4655770258978009, 'learning_rate/action_model': 9.280014590605847e-05, 'learning_rate/action_query_proj': 9.280014590605847e-05, 'learning_rate/base': 2.3200036476514617e-05, 'epoch': 0.35}) +[2026-07-27 04:23:49,824][starVLA.training.train_starvla][INFO] - Step 2884, Loss: {'train/loss': 0.12075863778591156, 'train/grad_norm_pre_clip': 3.0583183765411377, 'timing/data': 0.00017488421872258186, 'timing/model': 0.46626773895695806, 'learning_rate/action_model': 9.278425060983696e-05, 'learning_rate/action_query_proj': 9.278425060983696e-05, 'learning_rate/base': 2.319606265245924e-05, 'epoch': 0.35}) +[2026-07-27 04:23:55,423][starVLA.training.train_starvla][INFO] - Step 2885, Loss: {'train/loss': 0.1788911074399948, 'train/grad_norm_pre_clip': 4.26277494430542, 'timing/data': 0.00018026959151029587, 'timing/model': 0.4619930717162788, 'learning_rate/action_model': 9.27683392126392e-05, 'learning_rate/action_query_proj': 9.27683392126392e-05, 'learning_rate/base': 2.31920848031598e-05, 'epoch': 0.35}) +[2026-07-27 04:24:01,000][starVLA.training.train_starvla][INFO] - Step 2886, Loss: {'train/loss': 0.11600086092948914, 'train/grad_norm_pre_clip': 2.6764135360717773, 'timing/data': 0.00017185229808092117, 'timing/model': 0.46067152125760913, 'learning_rate/action_model': 9.275241172074677e-05, 'learning_rate/action_query_proj': 9.275241172074677e-05, 'learning_rate/base': 2.318810293018669e-05, 'epoch': 0.35}) +[2026-07-27 04:24:06,583][starVLA.training.train_starvla][INFO] - Step 2887, Loss: {'train/loss': 0.06436999142169952, 'train/grad_norm_pre_clip': 2.158522129058838, 'timing/data': 0.00017410097643733025, 'timing/model': 0.46256790217012167, 'learning_rate/action_model': 9.273646814044759e-05, 'learning_rate/action_query_proj': 9.273646814044759e-05, 'learning_rate/base': 2.3184117035111898e-05, 'epoch': 0.35}) +[2026-07-27 04:24:12,175][starVLA.training.train_starvla][INFO] - Step 2888, Loss: {'train/loss': 0.0976749062538147, 'train/grad_norm_pre_clip': 2.356187343597412, 'timing/data': 0.0001806439831852913, 'timing/model': 0.46227311668917537, 'learning_rate/action_model': 9.272050847803593e-05, 'learning_rate/action_query_proj': 9.272050847803593e-05, 'learning_rate/base': 2.3180127119508982e-05, 'epoch': 0.35}) +[2026-07-27 04:24:17,766][starVLA.training.train_starvla][INFO] - Step 2889, Loss: {'train/loss': 0.14825737476348877, 'train/grad_norm_pre_clip': 3.639577865600586, 'timing/data': 0.00017230631783604622, 'timing/model': 0.4658693321980536, 'learning_rate/action_model': 9.270453273981241e-05, 'learning_rate/action_query_proj': 9.270453273981241e-05, 'learning_rate/base': 2.3176133184953103e-05, 'epoch': 0.35}) +[2026-07-27 04:24:23,364][starVLA.training.train_starvla][INFO] - Step 2890, Loss: {'train/loss': 0.1339881271123886, 'train/grad_norm_pre_clip': 3.306617021560669, 'timing/data': 0.00017083296552300453, 'timing/model': 0.4686990319751203, 'learning_rate/action_model': 9.2688540932084e-05, 'learning_rate/action_query_proj': 9.2688540932084e-05, 'learning_rate/base': 2.3172135233021e-05, 'epoch': 0.35}) +[2026-07-27 04:24:28,994][starVLA.training.train_starvla][INFO] - Step 2891, Loss: {'train/loss': 0.23958435654640198, 'train/grad_norm_pre_clip': 5.663854122161865, 'timing/data': 0.00017580995336174965, 'timing/model': 0.46420800825580955, 'learning_rate/action_model': 9.267253306116401e-05, 'learning_rate/action_query_proj': 9.267253306116401e-05, 'learning_rate/base': 2.3168133265291003e-05, 'epoch': 0.35}) +[2026-07-27 04:24:34,618][starVLA.training.train_starvla][INFO] - Step 2892, Loss: {'train/loss': 0.18382343649864197, 'train/grad_norm_pre_clip': 4.952252388000488, 'timing/data': 0.00017346907407045364, 'timing/model': 0.4657418392598629, 'learning_rate/action_model': 9.265650913337209e-05, 'learning_rate/action_query_proj': 9.265650913337209e-05, 'learning_rate/base': 2.3164127283343022e-05, 'epoch': 0.35}) +[2026-07-27 04:24:40,257][starVLA.training.train_starvla][INFO] - Step 2893, Loss: {'train/loss': 0.21043217182159424, 'train/grad_norm_pre_clip': 4.509117126464844, 'timing/data': 0.000170903280377388, 'timing/model': 0.46612629713490605, 'learning_rate/action_model': 9.264046915503425e-05, 'learning_rate/action_query_proj': 9.264046915503425e-05, 'learning_rate/base': 2.316011728875856e-05, 'epoch': 0.35}) +[2026-07-27 04:24:45,894][starVLA.training.train_starvla][INFO] - Step 2894, Loss: {'train/loss': 0.13389788568019867, 'train/grad_norm_pre_clip': 3.4481253623962402, 'timing/data': 0.00016984809190034866, 'timing/model': 0.46180262323468924, 'learning_rate/action_model': 9.262441313248281e-05, 'learning_rate/action_query_proj': 9.262441313248281e-05, 'learning_rate/base': 2.3156103283120703e-05, 'epoch': 0.35}) +[2026-07-27 04:24:51,767][starVLA.training.train_starvla][INFO] - Step 2895, Loss: {'train/loss': 0.23761491477489471, 'train/grad_norm_pre_clip': 3.5205225944519043, 'timing/data': 0.0001705489121377468, 'timing/model': 0.4597476888448, 'learning_rate/action_model': 9.260834107205643e-05, 'learning_rate/action_query_proj': 9.260834107205643e-05, 'learning_rate/base': 2.3152085268014107e-05, 'epoch': 0.35}) +[2026-07-27 04:24:57,418][starVLA.training.train_starvla][INFO] - Step 2896, Loss: {'train/loss': 0.2129109501838684, 'train/grad_norm_pre_clip': 4.439271926879883, 'timing/data': 0.0001753740943968296, 'timing/model': 0.463066890835762, 'learning_rate/action_model': 9.259225298010011e-05, 'learning_rate/action_query_proj': 9.259225298010011e-05, 'learning_rate/base': 2.3148063245025027e-05, 'epoch': 0.35}) +[2026-07-27 04:25:03,039][starVLA.training.train_starvla][INFO] - Step 2897, Loss: {'train/loss': 0.13450060784816742, 'train/grad_norm_pre_clip': 3.2933402061462402, 'timing/data': 0.00016714772209525108, 'timing/model': 0.46694821398705244, 'learning_rate/action_model': 9.257614886296516e-05, 'learning_rate/action_query_proj': 9.257614886296516e-05, 'learning_rate/base': 2.314403721574129e-05, 'epoch': 0.35}) +[2026-07-27 04:25:08,646][starVLA.training.train_starvla][INFO] - Step 2898, Loss: {'train/loss': 0.07360263913869858, 'train/grad_norm_pre_clip': 3.341092109680176, 'timing/data': 0.00016894424334168434, 'timing/model': 0.46729362988844514, 'learning_rate/action_model': 9.256002872700924e-05, 'learning_rate/action_query_proj': 9.256002872700924e-05, 'learning_rate/base': 2.314000718175231e-05, 'epoch': 0.35}) +[2026-07-27 04:25:14,538][starVLA.training.train_starvla][INFO] - Step 2899, Loss: {'train/loss': 0.12885227799415588, 'train/grad_norm_pre_clip': 2.7306101322174072, 'timing/data': 0.00017371727153658867, 'timing/model': 0.4654345507733524, 'learning_rate/action_model': 9.254389257859633e-05, 'learning_rate/action_query_proj': 9.254389257859633e-05, 'learning_rate/base': 2.3135973144649083e-05, 'epoch': 0.35}) +[2026-07-27 04:25:20,176][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 2900 +[2026-07-27 04:25:20,176][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 2900 +[2026-07-27 04:25:20,177][starVLA.training.train_starvla][INFO] - Step 2900, Loss: {'train/loss': 0.20320427417755127, 'train/grad_norm_pre_clip': 4.843314170837402, 'timing/data': 0.00017258478328585625, 'timing/model': 0.46564496494829655, 'learning_rate/action_model': 9.252774042409673e-05, 'learning_rate/action_query_proj': 9.252774042409673e-05, 'learning_rate/base': 2.313193510602418e-05, 'epoch': 0.35}) +[2026-07-27 04:25:25,800][starVLA.training.train_starvla][INFO] - Step 2901, Loss: {'train/loss': 0.25437822937965393, 'train/grad_norm_pre_clip': 4.850813388824463, 'timing/data': 0.00017272122204303741, 'timing/model': 0.46104843681678176, 'learning_rate/action_model': 9.251157226988703e-05, 'learning_rate/action_query_proj': 9.251157226988703e-05, 'learning_rate/base': 2.3127893067471758e-05, 'epoch': 0.35}) +[2026-07-27 04:25:31,441][starVLA.training.train_starvla][INFO] - Step 2902, Loss: {'train/loss': 0.3442308008670807, 'train/grad_norm_pre_clip': 4.832738399505615, 'timing/data': 0.00017151329666376114, 'timing/model': 0.46319736214354634, 'learning_rate/action_model': 9.249538812235019e-05, 'learning_rate/action_query_proj': 9.249538812235019e-05, 'learning_rate/base': 2.3123847030587548e-05, 'epoch': 0.35}) +[2026-07-27 04:25:37,064][starVLA.training.train_starvla][INFO] - Step 2903, Loss: {'train/loss': 0.21064360439777374, 'train/grad_norm_pre_clip': 4.159329414367676, 'timing/data': 0.00017459411174058914, 'timing/model': 0.45878570806235075, 'learning_rate/action_model': 9.247918798787544e-05, 'learning_rate/action_query_proj': 9.247918798787544e-05, 'learning_rate/base': 2.311979699696886e-05, 'epoch': 0.35}) +[2026-07-27 04:25:42,992][starVLA.training.train_starvla][INFO] - Step 2904, Loss: {'train/loss': 0.1187295913696289, 'train/grad_norm_pre_clip': 3.122791290283203, 'timing/data': 0.00017227325588464737, 'timing/model': 0.46493047196418047, 'learning_rate/action_model': 9.246297187285834e-05, 'learning_rate/action_query_proj': 9.246297187285834e-05, 'learning_rate/base': 2.3115742968214584e-05, 'epoch': 0.35}) +[2026-07-27 04:25:48,643][starVLA.training.train_starvla][INFO] - Step 2905, Loss: {'train/loss': 0.17299439013004303, 'train/grad_norm_pre_clip': 4.3901166915893555, 'timing/data': 0.00017176475375890732, 'timing/model': 0.4851099541410804, 'learning_rate/action_model': 9.244673978370076e-05, 'learning_rate/action_query_proj': 9.244673978370076e-05, 'learning_rate/base': 2.311168494592519e-05, 'epoch': 0.35}) +[2026-07-27 04:25:54,270][starVLA.training.train_starvla][INFO] - Step 2906, Loss: {'train/loss': 0.1278267651796341, 'train/grad_norm_pre_clip': 3.1703736782073975, 'timing/data': 0.0001777750439941883, 'timing/model': 0.49200676335021853, 'learning_rate/action_model': 9.243049172681085e-05, 'learning_rate/action_query_proj': 9.243049172681085e-05, 'learning_rate/base': 2.3107622931702712e-05, 'epoch': 0.35}) +[2026-07-27 04:25:59,926][starVLA.training.train_starvla][INFO] - Step 2907, Loss: {'train/loss': 0.2033393234014511, 'train/grad_norm_pre_clip': 5.0604071617126465, 'timing/data': 0.00017605023458600044, 'timing/model': 0.4720048657618463, 'learning_rate/action_model': 9.241422770860311e-05, 'learning_rate/action_query_proj': 9.241422770860311e-05, 'learning_rate/base': 2.3103556927150778e-05, 'epoch': 0.35}) +[2026-07-27 04:26:05,589][starVLA.training.train_starvla][INFO] - Step 2908, Loss: {'train/loss': 0.19179049134254456, 'train/grad_norm_pre_clip': 3.301880359649658, 'timing/data': 0.00017169630154967308, 'timing/model': 0.4719775547273457, 'learning_rate/action_model': 9.239794773549832e-05, 'learning_rate/action_query_proj': 9.239794773549832e-05, 'learning_rate/base': 2.309948693387458e-05, 'epoch': 0.35}) +[2026-07-27 04:26:11,222][starVLA.training.train_starvla][INFO] - Step 2909, Loss: {'train/loss': 0.08917759358882904, 'train/grad_norm_pre_clip': 3.3059487342834473, 'timing/data': 0.00018554320558905602, 'timing/model': 0.4627123298123479, 'learning_rate/action_model': 9.238165181392354e-05, 'learning_rate/action_query_proj': 9.238165181392354e-05, 'learning_rate/base': 2.3095412953480884e-05, 'epoch': 0.35}) +[2026-07-27 04:26:16,826][starVLA.training.train_starvla][INFO] - Step 2910, Loss: {'train/loss': 0.13411958515644073, 'train/grad_norm_pre_clip': 3.710158586502075, 'timing/data': 0.00017434265464544296, 'timing/model': 0.47223009122535586, 'learning_rate/action_model': 9.236533995031212e-05, 'learning_rate/action_query_proj': 9.236533995031212e-05, 'learning_rate/base': 2.309133498757803e-05, 'epoch': 0.35}) +[2026-07-27 04:26:22,436][starVLA.training.train_starvla][INFO] - Step 2911, Loss: {'train/loss': 0.1574878990650177, 'train/grad_norm_pre_clip': 3.797213554382324, 'timing/data': 0.00017161713913083076, 'timing/model': 0.46948101092129946, 'learning_rate/action_model': 9.234901215110378e-05, 'learning_rate/action_query_proj': 9.234901215110378e-05, 'learning_rate/base': 2.3087253037775945e-05, 'epoch': 0.35}) +[2026-07-27 04:26:28,067][starVLA.training.train_starvla][INFO] - Step 2912, Loss: {'train/loss': 0.22368906438350677, 'train/grad_norm_pre_clip': 4.390694618225098, 'timing/data': 0.00017516594380140305, 'timing/model': 0.4693452939391136, 'learning_rate/action_model': 9.233266842274442e-05, 'learning_rate/action_query_proj': 9.233266842274442e-05, 'learning_rate/base': 2.3083167105686106e-05, 'epoch': 0.35}) +[2026-07-27 04:26:33,680][starVLA.training.train_starvla][INFO] - Step 2913, Loss: {'train/loss': 0.1583487093448639, 'train/grad_norm_pre_clip': 3.318202495574951, 'timing/data': 0.00017263181507587433, 'timing/model': 0.4715564367361367, 'learning_rate/action_model': 9.231630877168634e-05, 'learning_rate/action_query_proj': 9.231630877168634e-05, 'learning_rate/base': 2.3079077192921584e-05, 'epoch': 0.35}) +[2026-07-27 04:26:39,286][starVLA.training.train_starvla][INFO] - Step 2914, Loss: {'train/loss': 0.18314297497272491, 'train/grad_norm_pre_clip': 3.958677291870117, 'timing/data': 0.0001787012442946434, 'timing/model': 0.46069207321852446, 'learning_rate/action_model': 9.229993320438804e-05, 'learning_rate/action_query_proj': 9.229993320438804e-05, 'learning_rate/base': 2.307498330109701e-05, 'epoch': 0.35}) +[2026-07-27 04:26:44,909][starVLA.training.train_starvla][INFO] - Step 2915, Loss: {'train/loss': 0.1339908242225647, 'train/grad_norm_pre_clip': 2.8083224296569824, 'timing/data': 0.00017584674060344696, 'timing/model': 0.4632714572362602, 'learning_rate/action_model': 9.228354172731432e-05, 'learning_rate/action_query_proj': 9.228354172731432e-05, 'learning_rate/base': 2.307088543182858e-05, 'epoch': 0.35}) +[2026-07-27 04:26:50,548][starVLA.training.train_starvla][INFO] - Step 2916, Loss: {'train/loss': 0.12628309428691864, 'train/grad_norm_pre_clip': 3.7536401748657227, 'timing/data': 0.00017377780750393867, 'timing/model': 0.4601592682301998, 'learning_rate/action_model': 9.226713434693632e-05, 'learning_rate/action_query_proj': 9.226713434693632e-05, 'learning_rate/base': 2.306678358673408e-05, 'epoch': 0.35}) +[2026-07-27 04:26:56,181][starVLA.training.train_starvla][INFO] - Step 2917, Loss: {'train/loss': 0.19992059469223022, 'train/grad_norm_pre_clip': 4.561664581298828, 'timing/data': 0.00016755610704421997, 'timing/model': 0.46169411204755306, 'learning_rate/action_model': 9.225071106973137e-05, 'learning_rate/action_query_proj': 9.225071106973137e-05, 'learning_rate/base': 2.3062677767432842e-05, 'epoch': 0.35}) +[2026-07-27 04:27:01,802][starVLA.training.train_starvla][INFO] - Step 2918, Loss: {'train/loss': 0.17880241572856903, 'train/grad_norm_pre_clip': 4.2363362312316895, 'timing/data': 0.00017209211364388466, 'timing/model': 0.4617950520478189, 'learning_rate/action_model': 9.223427190218314e-05, 'learning_rate/action_query_proj': 9.223427190218314e-05, 'learning_rate/base': 2.3058567975545785e-05, 'epoch': 0.35}) +[2026-07-27 04:27:07,416][starVLA.training.train_starvla][INFO] - Step 2919, Loss: {'train/loss': 0.24377146363258362, 'train/grad_norm_pre_clip': 3.8680801391601562, 'timing/data': 0.0001714141108095646, 'timing/model': 0.460002978798002, 'learning_rate/action_model': 9.221781685078157e-05, 'learning_rate/action_query_proj': 9.221781685078157e-05, 'learning_rate/base': 2.3054454212695392e-05, 'epoch': 0.35}) +[2026-07-27 04:27:13,031][starVLA.training.train_starvla][INFO] - Step 2920, Loss: {'train/loss': 0.11057015508413315, 'train/grad_norm_pre_clip': 2.6282567977905273, 'timing/data': 0.00017533684149384499, 'timing/model': 0.4685000451281667, 'learning_rate/action_model': 9.220134592202282e-05, 'learning_rate/action_query_proj': 9.220134592202282e-05, 'learning_rate/base': 2.3050336480505704e-05, 'epoch': 0.35}) +[2026-07-27 04:27:18,647][starVLA.training.train_starvla][INFO] - Step 2921, Loss: {'train/loss': 0.15531575679779053, 'train/grad_norm_pre_clip': 2.824176549911499, 'timing/data': 0.0001772451214492321, 'timing/model': 0.4674627431668341, 'learning_rate/action_model': 9.218485912240935e-05, 'learning_rate/action_query_proj': 9.218485912240935e-05, 'learning_rate/base': 2.3046214780602336e-05, 'epoch': 0.35}) +[2026-07-27 04:27:24,262][starVLA.training.train_starvla][INFO] - Step 2922, Loss: {'train/loss': 0.08817090094089508, 'train/grad_norm_pre_clip': 2.385047435760498, 'timing/data': 0.00017332891002297401, 'timing/model': 0.4623469221405685, 'learning_rate/action_model': 9.216835645844992e-05, 'learning_rate/action_query_proj': 9.216835645844992e-05, 'learning_rate/base': 2.304208911461248e-05, 'epoch': 0.35}) +[2026-07-27 04:27:29,855][starVLA.training.train_starvla][INFO] - Step 2923, Loss: {'train/loss': 0.30565014481544495, 'train/grad_norm_pre_clip': 4.534396648406982, 'timing/data': 0.0001761200837790966, 'timing/model': 0.4593749828636646, 'learning_rate/action_model': 9.215183793665952e-05, 'learning_rate/action_query_proj': 9.215183793665952e-05, 'learning_rate/base': 2.303795948416488e-05, 'epoch': 0.35}) +[2026-07-27 04:27:35,436][starVLA.training.train_starvla][INFO] - Step 2924, Loss: {'train/loss': 0.23851169645786285, 'train/grad_norm_pre_clip': 4.457359313964844, 'timing/data': 0.0001708674244582653, 'timing/model': 0.46112212305888534, 'learning_rate/action_model': 9.213530356355935e-05, 'learning_rate/action_query_proj': 9.213530356355935e-05, 'learning_rate/base': 2.3033825890889838e-05, 'epoch': 0.35}) +[2026-07-27 04:27:41,041][starVLA.training.train_starvla][INFO] - Step 2925, Loss: {'train/loss': 0.11252465844154358, 'train/grad_norm_pre_clip': 3.360712766647339, 'timing/data': 0.00017507700249552727, 'timing/model': 0.4670791868120432, 'learning_rate/action_model': 9.211875334567698e-05, 'learning_rate/action_query_proj': 9.211875334567698e-05, 'learning_rate/base': 2.3029688336419245e-05, 'epoch': 0.35}) +[2026-07-27 04:27:46,647][starVLA.training.train_starvla][INFO] - Step 2926, Loss: {'train/loss': 0.13405735790729523, 'train/grad_norm_pre_clip': 3.1374545097351074, 'timing/data': 0.00017271889373660088, 'timing/model': 0.46575021371245384, 'learning_rate/action_model': 9.210218728954614e-05, 'learning_rate/action_query_proj': 9.210218728954614e-05, 'learning_rate/base': 2.3025546822386536e-05, 'epoch': 0.35}) +[2026-07-27 04:27:52,238][starVLA.training.train_starvla][INFO] - Step 2927, Loss: {'train/loss': 0.0782044380903244, 'train/grad_norm_pre_clip': 2.177683115005493, 'timing/data': 0.0001743929460644722, 'timing/model': 0.4678801097907126, 'learning_rate/action_model': 9.208560540170686e-05, 'learning_rate/action_query_proj': 9.208560540170686e-05, 'learning_rate/base': 2.3021401350426714e-05, 'epoch': 0.36}) +[2026-07-27 04:27:57,821][starVLA.training.train_starvla][INFO] - Step 2928, Loss: {'train/loss': 0.11909102648496628, 'train/grad_norm_pre_clip': 2.9405500888824463, 'timing/data': 0.0001753503456711769, 'timing/model': 0.4677861277014017, 'learning_rate/action_model': 9.20690076887054e-05, 'learning_rate/action_query_proj': 9.20690076887054e-05, 'learning_rate/base': 2.301725192217635e-05, 'epoch': 0.36}) +[2026-07-27 04:28:03,442][starVLA.training.train_starvla][INFO] - Step 2929, Loss: {'train/loss': 0.06801418960094452, 'train/grad_norm_pre_clip': 2.576794385910034, 'timing/data': 0.00017269514501094818, 'timing/model': 0.4661355749703944, 'learning_rate/action_model': 9.205239415709426e-05, 'learning_rate/action_query_proj': 9.205239415709426e-05, 'learning_rate/base': 2.3013098539273564e-05, 'epoch': 0.36}) +[2026-07-27 04:28:09,030][starVLA.training.train_starvla][INFO] - Step 2930, Loss: {'train/loss': 0.15410813689231873, 'train/grad_norm_pre_clip': 3.4568676948547363, 'timing/data': 0.00017691077664494514, 'timing/model': 0.46745232678949833, 'learning_rate/action_model': 9.203576481343223e-05, 'learning_rate/action_query_proj': 9.203576481343223e-05, 'learning_rate/base': 2.3008941203358057e-05, 'epoch': 0.36}) +[2026-07-27 04:28:14,632][starVLA.training.train_starvla][INFO] - Step 2931, Loss: {'train/loss': 0.12304441630840302, 'train/grad_norm_pre_clip': 3.72135591506958, 'timing/data': 0.0001763962209224701, 'timing/model': 0.46942570013925433, 'learning_rate/action_model': 9.201911966428429e-05, 'learning_rate/action_query_proj': 9.201911966428429e-05, 'learning_rate/base': 2.3004779916071072e-05, 'epoch': 0.36}) +[2026-07-27 04:28:20,239][starVLA.training.train_starvla][INFO] - Step 2932, Loss: {'train/loss': 0.138996422290802, 'train/grad_norm_pre_clip': 3.540285110473633, 'timing/data': 0.00017471099272370338, 'timing/model': 0.4601343357935548, 'learning_rate/action_model': 9.200245871622167e-05, 'learning_rate/action_query_proj': 9.200245871622167e-05, 'learning_rate/base': 2.3000614679055417e-05, 'epoch': 0.36}) +[2026-07-27 04:28:25,829][starVLA.training.train_starvla][INFO] - Step 2933, Loss: {'train/loss': 0.08292598277330399, 'train/grad_norm_pre_clip': 2.1360116004943848, 'timing/data': 0.00017449166625738144, 'timing/model': 0.46712980000302196, 'learning_rate/action_model': 9.19857819758219e-05, 'learning_rate/action_query_proj': 9.19857819758219e-05, 'learning_rate/base': 2.2996445493955475e-05, 'epoch': 0.36}) +[2026-07-27 04:28:31,446][starVLA.training.train_starvla][INFO] - Step 2934, Loss: {'train/loss': 0.1419370472431183, 'train/grad_norm_pre_clip': 3.267162561416626, 'timing/data': 0.00017708586528897285, 'timing/model': 0.46253203600645065, 'learning_rate/action_model': 9.196908944966863e-05, 'learning_rate/action_query_proj': 9.196908944966863e-05, 'learning_rate/base': 2.2992272362417158e-05, 'epoch': 0.36}) +[2026-07-27 04:28:37,035][starVLA.training.train_starvla][INFO] - Step 2935, Loss: {'train/loss': 0.19069378077983856, 'train/grad_norm_pre_clip': 4.25821590423584, 'timing/data': 0.00018259696662425995, 'timing/model': 0.46289713913574815, 'learning_rate/action_model': 9.195238114435186e-05, 'learning_rate/action_query_proj': 9.195238114435186e-05, 'learning_rate/base': 2.2988095286087964e-05, 'epoch': 0.36}) +[2026-07-27 04:28:42,629][starVLA.training.train_starvla][INFO] - Step 2936, Loss: {'train/loss': 0.25102314352989197, 'train/grad_norm_pre_clip': 3.4501194953918457, 'timing/data': 0.00017473287880420685, 'timing/model': 0.4627391779795289, 'learning_rate/action_model': 9.193565706646772e-05, 'learning_rate/action_query_proj': 9.193565706646772e-05, 'learning_rate/base': 2.298391426661693e-05, 'epoch': 0.36}) +[2026-07-27 04:28:48,224][starVLA.training.train_starvla][INFO] - Step 2937, Loss: {'train/loss': 0.12105192989110947, 'train/grad_norm_pre_clip': 3.5180108547210693, 'timing/data': 0.0001820041798055172, 'timing/model': 0.4587262808345258, 'learning_rate/action_model': 9.191891722261861e-05, 'learning_rate/action_query_proj': 9.191891722261861e-05, 'learning_rate/base': 2.2979729305654653e-05, 'epoch': 0.36}) +[2026-07-27 04:28:53,834][starVLA.training.train_starvla][INFO] - Step 2938, Loss: {'train/loss': 0.17172524333000183, 'train/grad_norm_pre_clip': 4.1944804191589355, 'timing/data': 0.00017121387645602226, 'timing/model': 0.4671784667298198, 'learning_rate/action_model': 9.190216161941321e-05, 'learning_rate/action_query_proj': 9.190216161941321e-05, 'learning_rate/base': 2.2975540404853302e-05, 'epoch': 0.36}) +[2026-07-27 04:28:59,447][starVLA.training.train_starvla][INFO] - Step 2939, Loss: {'train/loss': 0.19080382585525513, 'train/grad_norm_pre_clip': 4.211899280548096, 'timing/data': 0.00017248187214136124, 'timing/model': 0.46356419287621975, 'learning_rate/action_model': 9.188539026346632e-05, 'learning_rate/action_query_proj': 9.188539026346632e-05, 'learning_rate/base': 2.297134756586658e-05, 'epoch': 0.36}) +[2026-07-27 04:29:05,049][starVLA.training.train_starvla][INFO] - Step 2940, Loss: {'train/loss': 0.05149035528302193, 'train/grad_norm_pre_clip': 1.7489359378814697, 'timing/data': 0.00017596129328012466, 'timing/model': 0.4668264565989375, 'learning_rate/action_model': 9.186860316139901e-05, 'learning_rate/action_query_proj': 9.186860316139901e-05, 'learning_rate/base': 2.2967150790349752e-05, 'epoch': 0.36}) +[2026-07-27 04:29:10,657][starVLA.training.train_starvla][INFO] - Step 2941, Loss: {'train/loss': 0.2067621648311615, 'train/grad_norm_pre_clip': 3.9836888313293457, 'timing/data': 0.00017257314175367355, 'timing/model': 0.4628767790272832, 'learning_rate/action_model': 9.185180031983857e-05, 'learning_rate/action_query_proj': 9.185180031983857e-05, 'learning_rate/base': 2.2962950079959643e-05, 'epoch': 0.36}) +[2026-07-27 04:29:16,252][starVLA.training.train_starvla][INFO] - Step 2942, Loss: {'train/loss': 0.12236766517162323, 'train/grad_norm_pre_clip': 2.9620954990386963, 'timing/data': 0.0001720278523862362, 'timing/model': 0.463477311655879, 'learning_rate/action_model': 9.18349817454185e-05, 'learning_rate/action_query_proj': 9.18349817454185e-05, 'learning_rate/base': 2.2958745436354624e-05, 'epoch': 0.36}) +[2026-07-27 04:29:21,855][starVLA.training.train_starvla][INFO] - Step 2943, Loss: {'train/loss': 0.11757977306842804, 'train/grad_norm_pre_clip': 4.318047046661377, 'timing/data': 0.0001766071654856205, 'timing/model': 0.4622155507095158, 'learning_rate/action_model': 9.181814744477851e-05, 'learning_rate/action_query_proj': 9.181814744477851e-05, 'learning_rate/base': 2.2954536861194627e-05, 'epoch': 0.36}) +[2026-07-27 04:29:27,467][starVLA.training.train_starvla][INFO] - Step 2944, Loss: {'train/loss': 0.16016128659248352, 'train/grad_norm_pre_clip': 3.3513293266296387, 'timing/data': 0.00017555616796016693, 'timing/model': 0.4606494680047035, 'learning_rate/action_model': 9.180129742456448e-05, 'learning_rate/action_query_proj': 9.180129742456448e-05, 'learning_rate/base': 2.295032435614112e-05, 'epoch': 0.36}) +[2026-07-27 04:29:33,080][starVLA.training.train_starvla][INFO] - Step 2945, Loss: {'train/loss': 0.21247372031211853, 'train/grad_norm_pre_clip': 3.3055078983306885, 'timing/data': 0.00017249304801225662, 'timing/model': 0.4647685019299388, 'learning_rate/action_model': 9.178443169142858e-05, 'learning_rate/action_query_proj': 9.178443169142858e-05, 'learning_rate/base': 2.2946107922857144e-05, 'epoch': 0.36}) +[2026-07-27 04:29:38,662][starVLA.training.train_starvla][INFO] - Step 2946, Loss: {'train/loss': 0.12745849788188934, 'train/grad_norm_pre_clip': 2.609654188156128, 'timing/data': 0.0001734178513288498, 'timing/model': 0.46163076302036643, 'learning_rate/action_model': 9.176755025202911e-05, 'learning_rate/action_query_proj': 9.176755025202911e-05, 'learning_rate/base': 2.2941887563007278e-05, 'epoch': 0.36}) +[2026-07-27 04:29:44,265][starVLA.training.train_starvla][INFO] - Step 2947, Loss: {'train/loss': 0.12698933482170105, 'train/grad_norm_pre_clip': 3.1262402534484863, 'timing/data': 0.0001789531670510769, 'timing/model': 0.46586893405765295, 'learning_rate/action_model': 9.175065311303058e-05, 'learning_rate/action_query_proj': 9.175065311303058e-05, 'learning_rate/base': 2.2937663278257646e-05, 'epoch': 0.36}) +[2026-07-27 04:29:49,882][starVLA.training.train_starvla][INFO] - Step 2948, Loss: {'train/loss': 0.20755700767040253, 'train/grad_norm_pre_clip': 4.7353105545043945, 'timing/data': 0.0001758909784257412, 'timing/model': 0.4623593967407942, 'learning_rate/action_model': 9.173374028110373e-05, 'learning_rate/action_query_proj': 9.173374028110373e-05, 'learning_rate/base': 2.2933435070275934e-05, 'epoch': 0.36}) +[2026-07-27 04:29:55,488][starVLA.training.train_starvla][INFO] - Step 2949, Loss: {'train/loss': 0.12128482758998871, 'train/grad_norm_pre_clip': 3.434697151184082, 'timing/data': 0.00017799483612179756, 'timing/model': 0.46775661408901215, 'learning_rate/action_model': 9.17168117629255e-05, 'learning_rate/action_query_proj': 9.17168117629255e-05, 'learning_rate/base': 2.2929202940731376e-05, 'epoch': 0.36}) +[2026-07-27 04:30:01,082][starVLA.training.train_starvla][INFO] - Step 2950, Loss: {'train/loss': 0.12189573049545288, 'train/grad_norm_pre_clip': 4.086886405944824, 'timing/data': 0.00017541786655783653, 'timing/model': 0.4619744890369475, 'learning_rate/action_model': 9.169986756517896e-05, 'learning_rate/action_query_proj': 9.169986756517896e-05, 'learning_rate/base': 2.292496689129474e-05, 'epoch': 0.36}) +[2026-07-27 04:30:06,676][starVLA.training.train_starvla][INFO] - Step 2951, Loss: {'train/loss': 0.17417091131210327, 'train/grad_norm_pre_clip': 3.1373651027679443, 'timing/data': 0.00017612427473068237, 'timing/model': 0.46448312094435096, 'learning_rate/action_model': 9.168290769455344e-05, 'learning_rate/action_query_proj': 9.168290769455344e-05, 'learning_rate/base': 2.292072692363836e-05, 'epoch': 0.36}) +[2026-07-27 04:30:12,287][starVLA.training.train_starvla][INFO] - Step 2952, Loss: {'train/loss': 0.1990385204553604, 'train/grad_norm_pre_clip': 3.0156073570251465, 'timing/data': 0.00017508072778582573, 'timing/model': 0.4653413137421012, 'learning_rate/action_model': 9.166593215774442e-05, 'learning_rate/action_query_proj': 9.166593215774442e-05, 'learning_rate/base': 2.2916483039436106e-05, 'epoch': 0.36}) +[2026-07-27 04:30:17,884][starVLA.training.train_starvla][INFO] - Step 2953, Loss: {'train/loss': 0.0685381069779396, 'train/grad_norm_pre_clip': 1.8559565544128418, 'timing/data': 0.00017050886526703835, 'timing/model': 0.4634547149762511, 'learning_rate/action_model': 9.164894096145357e-05, 'learning_rate/action_query_proj': 9.164894096145357e-05, 'learning_rate/base': 2.2912235240363393e-05, 'epoch': 0.36}) +[2026-07-27 04:30:23,470][starVLA.training.train_starvla][INFO] - Step 2954, Loss: {'train/loss': 0.21953903138637543, 'train/grad_norm_pre_clip': 3.6823501586914062, 'timing/data': 0.00017786677926778793, 'timing/model': 0.4597765249200165, 'learning_rate/action_model': 9.163193411238875e-05, 'learning_rate/action_query_proj': 9.163193411238875e-05, 'learning_rate/base': 2.2907983528097187e-05, 'epoch': 0.36}) +[2026-07-27 04:30:29,074][starVLA.training.train_starvla][INFO] - Step 2955, Loss: {'train/loss': 0.1470285952091217, 'train/grad_norm_pre_clip': 3.404750347137451, 'timing/data': 0.00017171911895275116, 'timing/model': 0.4619765947572887, 'learning_rate/action_model': 9.161491161726398e-05, 'learning_rate/action_query_proj': 9.161491161726398e-05, 'learning_rate/base': 2.2903727904315996e-05, 'epoch': 0.36}) +[2026-07-27 04:30:34,669][starVLA.training.train_starvla][INFO] - Step 2956, Loss: {'train/loss': 0.0705806165933609, 'train/grad_norm_pre_clip': 2.1454262733459473, 'timing/data': 0.00016872910782694817, 'timing/model': 0.46656464878469706, 'learning_rate/action_model': 9.15978734827995e-05, 'learning_rate/action_query_proj': 9.15978734827995e-05, 'learning_rate/base': 2.2899468370699875e-05, 'epoch': 0.36}) +[2026-07-27 04:30:40,209][starVLA.training.train_starvla][INFO] - Step 2957, Loss: {'train/loss': 0.16616493463516235, 'train/grad_norm_pre_clip': 3.880962610244751, 'timing/data': 0.00017217686399817467, 'timing/model': 0.4636667971499264, 'learning_rate/action_model': 9.158081971572165e-05, 'learning_rate/action_query_proj': 9.158081971572165e-05, 'learning_rate/base': 2.2895204928930413e-05, 'epoch': 0.36}) +[2026-07-27 04:30:45,805][starVLA.training.train_starvla][INFO] - Step 2958, Loss: {'train/loss': 0.07666198909282684, 'train/grad_norm_pre_clip': 3.3774681091308594, 'timing/data': 0.00017162319272756577, 'timing/model': 0.45979760494083166, 'learning_rate/action_model': 9.156375032276305e-05, 'learning_rate/action_query_proj': 9.156375032276305e-05, 'learning_rate/base': 2.289093758069076e-05, 'epoch': 0.36}) +[2026-07-27 04:30:51,377][starVLA.training.train_starvla][INFO] - Step 2959, Loss: {'train/loss': 0.18464818596839905, 'train/grad_norm_pre_clip': 5.375093936920166, 'timing/data': 0.0001726909540593624, 'timing/model': 0.4641552292741835, 'learning_rate/action_model': 9.154666531066236e-05, 'learning_rate/action_query_proj': 9.154666531066236e-05, 'learning_rate/base': 2.288666632766559e-05, 'epoch': 0.36}) +[2026-07-27 04:30:56,967][starVLA.training.train_starvla][INFO] - Step 2960, Loss: {'train/loss': 0.147513285279274, 'train/grad_norm_pre_clip': 3.1821110248565674, 'timing/data': 0.00017514405772089958, 'timing/model': 0.46347086876630783, 'learning_rate/action_model': 9.152956468616451e-05, 'learning_rate/action_query_proj': 9.152956468616451e-05, 'learning_rate/base': 2.2882391171541128e-05, 'epoch': 0.36}) +[2026-07-27 04:31:02,596][starVLA.training.train_starvla][INFO] - Step 2961, Loss: {'train/loss': 0.0776311606168747, 'train/grad_norm_pre_clip': 2.849656820297241, 'timing/data': 0.00018321489915251732, 'timing/model': 0.46403892803937197, 'learning_rate/action_model': 9.151244845602056e-05, 'learning_rate/action_query_proj': 9.151244845602056e-05, 'learning_rate/base': 2.287811211400514e-05, 'epoch': 0.36}) +[2026-07-27 04:31:08,197][starVLA.training.train_starvla][INFO] - Step 2962, Loss: {'train/loss': 0.13829489052295685, 'train/grad_norm_pre_clip': 4.228906154632568, 'timing/data': 0.00016848696395754814, 'timing/model': 0.4648065138608217, 'learning_rate/action_model': 9.149531662698772e-05, 'learning_rate/action_query_proj': 9.149531662698772e-05, 'learning_rate/base': 2.287382915674693e-05, 'epoch': 0.36}) +[2026-07-27 04:31:13,772][starVLA.training.train_starvla][INFO] - Step 2963, Loss: {'train/loss': 0.21471013128757477, 'train/grad_norm_pre_clip': 4.465731143951416, 'timing/data': 0.0021223891526460648, 'timing/model': 0.46397635992616415, 'learning_rate/action_model': 9.147816920582935e-05, 'learning_rate/action_query_proj': 9.147816920582935e-05, 'learning_rate/base': 2.286954230145734e-05, 'epoch': 0.36}) +[2026-07-27 04:31:19,339][starVLA.training.train_starvla][INFO] - Step 2964, Loss: {'train/loss': 0.048762768507003784, 'train/grad_norm_pre_clip': 1.962533712387085, 'timing/data': 0.00017288792878389359, 'timing/model': 0.46371072717010975, 'learning_rate/action_model': 9.1461006199315e-05, 'learning_rate/action_query_proj': 9.1461006199315e-05, 'learning_rate/base': 2.286525154982875e-05, 'epoch': 0.36}) +[2026-07-27 04:31:24,886][starVLA.training.train_starvla][INFO] - Step 2965, Loss: {'train/loss': 0.08819219470024109, 'train/grad_norm_pre_clip': 2.3022584915161133, 'timing/data': 0.00017666583880782127, 'timing/model': 0.458469910081476, 'learning_rate/action_model': 9.144382761422033e-05, 'learning_rate/action_query_proj': 9.144382761422033e-05, 'learning_rate/base': 2.2860956903555083e-05, 'epoch': 0.36}) +[2026-07-27 04:31:30,447][starVLA.training.train_starvla][INFO] - Step 2966, Loss: {'train/loss': 0.16993483901023865, 'train/grad_norm_pre_clip': 3.518857717514038, 'timing/data': 0.00017364928498864174, 'timing/model': 0.4679585541598499, 'learning_rate/action_model': 9.14266334573272e-05, 'learning_rate/action_query_proj': 9.14266334573272e-05, 'learning_rate/base': 2.28566583643318e-05, 'epoch': 0.36}) +[2026-07-27 04:31:36,014][starVLA.training.train_starvla][INFO] - Step 2967, Loss: {'train/loss': 0.13076382875442505, 'train/grad_norm_pre_clip': 3.2426986694335938, 'timing/data': 0.00017325719818472862, 'timing/model': 0.46348636876791716, 'learning_rate/action_model': 9.140942373542359e-05, 'learning_rate/action_query_proj': 9.140942373542359e-05, 'learning_rate/base': 2.2852355933855896e-05, 'epoch': 0.36}) +[2026-07-27 04:31:41,591][starVLA.training.train_starvla][INFO] - Step 2968, Loss: {'train/loss': 0.11753164231777191, 'train/grad_norm_pre_clip': 2.8967387676239014, 'timing/data': 0.00018295086920261383, 'timing/model': 0.46626812871545553, 'learning_rate/action_model': 9.139219845530359e-05, 'learning_rate/action_query_proj': 9.139219845530359e-05, 'learning_rate/base': 2.2848049613825898e-05, 'epoch': 0.36}) +[2026-07-27 04:31:47,154][starVLA.training.train_starvla][INFO] - Step 2969, Loss: {'train/loss': 0.04975377395749092, 'train/grad_norm_pre_clip': 2.118032217025757, 'timing/data': 0.00017715990543365479, 'timing/model': 0.46310799289494753, 'learning_rate/action_model': 9.13749576237675e-05, 'learning_rate/action_query_proj': 9.13749576237675e-05, 'learning_rate/base': 2.2843739405941874e-05, 'epoch': 0.36}) +[2026-07-27 04:31:52,736][starVLA.training.train_starvla][INFO] - Step 2970, Loss: {'train/loss': 0.06658127158880234, 'train/grad_norm_pre_clip': 2.6852304935455322, 'timing/data': 0.00017531216144561768, 'timing/model': 0.463761642575264, 'learning_rate/action_model': 9.135770124762172e-05, 'learning_rate/action_query_proj': 9.135770124762172e-05, 'learning_rate/base': 2.283942531190543e-05, 'epoch': 0.36}) +[2026-07-27 04:31:58,296][starVLA.training.train_starvla][INFO] - Step 2971, Loss: {'train/loss': 0.10629034042358398, 'train/grad_norm_pre_clip': 3.0930376052856445, 'timing/data': 0.00017097406089305878, 'timing/model': 0.46302540972828865, 'learning_rate/action_model': 9.134042933367879e-05, 'learning_rate/action_query_proj': 9.134042933367879e-05, 'learning_rate/base': 2.2835107333419697e-05, 'epoch': 0.36}) +[2026-07-27 04:32:03,945][starVLA.training.train_starvla][INFO] - Step 2972, Loss: {'train/loss': 0.16236469149589539, 'train/grad_norm_pre_clip': 4.520678997039795, 'timing/data': 0.00017413171008229256, 'timing/model': 0.4625298921018839, 'learning_rate/action_model': 9.13231418887574e-05, 'learning_rate/action_query_proj': 9.13231418887574e-05, 'learning_rate/base': 2.283078547218935e-05, 'epoch': 0.36}) +[2026-07-27 04:32:09,528][starVLA.training.train_starvla][INFO] - Step 2973, Loss: {'train/loss': 0.12122412025928497, 'train/grad_norm_pre_clip': 4.25188684463501, 'timing/data': 0.00018314318731427193, 'timing/model': 0.46333765471354127, 'learning_rate/action_model': 9.130583891968233e-05, 'learning_rate/action_query_proj': 9.130583891968233e-05, 'learning_rate/base': 2.2826459729920583e-05, 'epoch': 0.36}) +[2026-07-27 04:32:15,302][starVLA.training.train_starvla][INFO] - Step 2974, Loss: {'train/loss': 0.2975386381149292, 'train/grad_norm_pre_clip': 5.574340343475342, 'timing/data': 0.0001780209131538868, 'timing/model': 0.4675206309184432, 'learning_rate/action_model': 9.128852043328456e-05, 'learning_rate/action_query_proj': 9.128852043328456e-05, 'learning_rate/base': 2.282213010832114e-05, 'epoch': 0.36}) +[2026-07-27 04:32:21,029][starVLA.training.train_starvla][INFO] - Step 2975, Loss: {'train/loss': 0.107136070728302, 'train/grad_norm_pre_clip': 2.994215726852417, 'timing/data': 0.00017404276877641678, 'timing/model': 0.48065167386084795, 'learning_rate/action_model': 9.127118643640112e-05, 'learning_rate/action_query_proj': 9.127118643640112e-05, 'learning_rate/base': 2.281779660910028e-05, 'epoch': 0.36}) +[2026-07-27 04:32:26,669][starVLA.training.train_starvla][INFO] - Step 2976, Loss: {'train/loss': 0.1300186663866043, 'train/grad_norm_pre_clip': 3.516226053237915, 'timing/data': 0.00017088884487748146, 'timing/model': 0.46600141609087586, 'learning_rate/action_model': 9.125383693587523e-05, 'learning_rate/action_query_proj': 9.125383693587523e-05, 'learning_rate/base': 2.281345923396881e-05, 'epoch': 0.36}) +[2026-07-27 04:32:32,296][starVLA.training.train_starvla][INFO] - Step 2977, Loss: {'train/loss': 0.14942814409732819, 'train/grad_norm_pre_clip': 3.562164545059204, 'timing/data': 0.00016976101323962212, 'timing/model': 0.4665011097677052, 'learning_rate/action_model': 9.123647193855617e-05, 'learning_rate/action_query_proj': 9.123647193855617e-05, 'learning_rate/base': 2.280911798463904e-05, 'epoch': 0.36}) +[2026-07-27 04:32:37,945][starVLA.training.train_starvla][INFO] - Step 2978, Loss: {'train/loss': 0.15541094541549683, 'train/grad_norm_pre_clip': 3.3197882175445557, 'timing/data': 0.00017339596524834633, 'timing/model': 0.46175987366586924, 'learning_rate/action_model': 9.121909145129937e-05, 'learning_rate/action_query_proj': 9.121909145129937e-05, 'learning_rate/base': 2.2804772862824842e-05, 'epoch': 0.36}) +[2026-07-27 04:32:43,569][starVLA.training.train_starvla][INFO] - Step 2979, Loss: {'train/loss': 0.10951288044452667, 'train/grad_norm_pre_clip': 3.9384191036224365, 'timing/data': 0.00017385510727763176, 'timing/model': 0.46524956077337265, 'learning_rate/action_model': 9.120169548096637e-05, 'learning_rate/action_query_proj': 9.120169548096637e-05, 'learning_rate/base': 2.280042387024159e-05, 'epoch': 0.36}) +[2026-07-27 04:32:49,161][starVLA.training.train_starvla][INFO] - Step 2980, Loss: {'train/loss': 0.15602411329746246, 'train/grad_norm_pre_clip': 4.218347549438477, 'timing/data': 0.00017736898735165596, 'timing/model': 0.466850477270782, 'learning_rate/action_model': 9.118428403442483e-05, 'learning_rate/action_query_proj': 9.118428403442483e-05, 'learning_rate/base': 2.2796071008606208e-05, 'epoch': 0.36}) +[2026-07-27 04:32:54,734][starVLA.training.train_starvla][INFO] - Step 2981, Loss: {'train/loss': 0.1316107213497162, 'train/grad_norm_pre_clip': 4.624538898468018, 'timing/data': 0.00017302995547652245, 'timing/model': 0.4615519247017801, 'learning_rate/action_model': 9.116685711854853e-05, 'learning_rate/action_query_proj': 9.116685711854853e-05, 'learning_rate/base': 2.2791714279637132e-05, 'epoch': 0.36}) +[2026-07-27 04:33:00,314][starVLA.training.train_starvla][INFO] - Step 2982, Loss: {'train/loss': 0.07819123566150665, 'train/grad_norm_pre_clip': 2.556825637817383, 'timing/data': 0.00017132097855210304, 'timing/model': 0.46629039105027914, 'learning_rate/action_model': 9.11494147402173e-05, 'learning_rate/action_query_proj': 9.11494147402173e-05, 'learning_rate/base': 2.2787353685054325e-05, 'epoch': 0.36}) +[2026-07-27 04:33:05,886][starVLA.training.train_starvla][INFO] - Step 2983, Loss: {'train/loss': 0.191290020942688, 'train/grad_norm_pre_clip': 3.952331066131592, 'timing/data': 0.00017680972814559937, 'timing/model': 0.4601611662656069, 'learning_rate/action_model': 9.113195690631716e-05, 'learning_rate/action_query_proj': 9.113195690631716e-05, 'learning_rate/base': 2.278298922657929e-05, 'epoch': 0.36}) +[2026-07-27 04:33:11,465][starVLA.training.train_starvla][INFO] - Step 2984, Loss: {'train/loss': 0.11166608333587646, 'train/grad_norm_pre_clip': 2.814452648162842, 'timing/data': 0.00017358968034386635, 'timing/model': 0.46593293407931924, 'learning_rate/action_model': 9.111448362374014e-05, 'learning_rate/action_query_proj': 9.111448362374014e-05, 'learning_rate/base': 2.2778620905935036e-05, 'epoch': 0.36}) +[2026-07-27 04:33:17,288][starVLA.training.train_starvla][INFO] - Step 2985, Loss: {'train/loss': 0.09421806782484055, 'train/grad_norm_pre_clip': 2.351241111755371, 'timing/data': 0.00016934378072619438, 'timing/model': 0.46252908557653427, 'learning_rate/action_model': 9.109699489938446e-05, 'learning_rate/action_query_proj': 9.109699489938446e-05, 'learning_rate/base': 2.2774248724846114e-05, 'epoch': 0.36}) +[2026-07-27 04:33:22,861][starVLA.training.train_starvla][INFO] - Step 2986, Loss: {'train/loss': 0.07069282978773117, 'train/grad_norm_pre_clip': 2.728841543197632, 'timing/data': 0.00016766414046287537, 'timing/model': 0.4621918830089271, 'learning_rate/action_model': 9.107949074015435e-05, 'learning_rate/action_query_proj': 9.107949074015435e-05, 'learning_rate/base': 2.2769872685038588e-05, 'epoch': 0.36}) +[2026-07-27 04:33:28,617][starVLA.training.train_starvla][INFO] - Step 2987, Loss: {'train/loss': 0.10936453193426132, 'train/grad_norm_pre_clip': 2.852649688720703, 'timing/data': 0.00016917800530791283, 'timing/model': 0.46185355028137565, 'learning_rate/action_model': 9.106197115296022e-05, 'learning_rate/action_query_proj': 9.106197115296022e-05, 'learning_rate/base': 2.2765492788240054e-05, 'epoch': 0.36}) +[2026-07-27 04:33:34,201][starVLA.training.train_starvla][INFO] - Step 2988, Loss: {'train/loss': 0.10452897101640701, 'train/grad_norm_pre_clip': 3.4048099517822266, 'timing/data': 0.00017160503193736076, 'timing/model': 0.47192761208862066, 'learning_rate/action_model': 9.104443614471848e-05, 'learning_rate/action_query_proj': 9.104443614471848e-05, 'learning_rate/base': 2.276110903617962e-05, 'epoch': 0.36}) +[2026-07-27 04:33:39,812][starVLA.training.train_starvla][INFO] - Step 2989, Loss: {'train/loss': 0.18087679147720337, 'train/grad_norm_pre_clip': 4.291153907775879, 'timing/data': 0.00017264392226934433, 'timing/model': 0.4730337648652494, 'learning_rate/action_model': 9.102688572235171e-05, 'learning_rate/action_query_proj': 9.102688572235171e-05, 'learning_rate/base': 2.2756721430587927e-05, 'epoch': 0.36}) +[2026-07-27 04:33:45,431][starVLA.training.train_starvla][INFO] - Step 2990, Loss: {'train/loss': 0.13186827301979065, 'train/grad_norm_pre_clip': 3.747231960296631, 'timing/data': 0.00017428584396839142, 'timing/model': 0.468745409976691, 'learning_rate/action_model': 9.100931989278851e-05, 'learning_rate/action_query_proj': 9.100931989278851e-05, 'learning_rate/base': 2.2752329973197127e-05, 'epoch': 0.36}) +[2026-07-27 04:33:51,047][starVLA.training.train_starvla][INFO] - Step 2991, Loss: {'train/loss': 0.08351356536149979, 'train/grad_norm_pre_clip': 2.319566488265991, 'timing/data': 0.0001768292859196663, 'timing/model': 0.47573503106832504, 'learning_rate/action_model': 9.099173866296361e-05, 'learning_rate/action_query_proj': 9.099173866296361e-05, 'learning_rate/base': 2.2747934665740902e-05, 'epoch': 0.36}) +[2026-07-27 04:33:56,631][starVLA.training.train_starvla][INFO] - Step 2992, Loss: {'train/loss': 0.047804683446884155, 'train/grad_norm_pre_clip': 1.813862681388855, 'timing/data': 0.0001719449646770954, 'timing/model': 0.4673056798055768, 'learning_rate/action_model': 9.097414203981781e-05, 'learning_rate/action_query_proj': 9.097414203981781e-05, 'learning_rate/base': 2.2743535509954454e-05, 'epoch': 0.36}) +[2026-07-27 04:34:02,248][starVLA.training.train_starvla][INFO] - Step 2993, Loss: {'train/loss': 0.16282252967357635, 'train/grad_norm_pre_clip': 3.7423763275146484, 'timing/data': 0.00017233798280358315, 'timing/model': 0.4696231782436371, 'learning_rate/action_model': 9.095653003029793e-05, 'learning_rate/action_query_proj': 9.095653003029793e-05, 'learning_rate/base': 2.2739132507574483e-05, 'epoch': 0.36}) +[2026-07-27 04:34:07,871][starVLA.training.train_starvla][INFO] - Step 2994, Loss: {'train/loss': 0.14723877608776093, 'train/grad_norm_pre_clip': 3.4102962017059326, 'timing/data': 0.00017239386215806007, 'timing/model': 0.4627363667823374, 'learning_rate/action_model': 9.093890264135698e-05, 'learning_rate/action_query_proj': 9.093890264135698e-05, 'learning_rate/base': 2.2734725660339245e-05, 'epoch': 0.36}) +[2026-07-27 04:34:13,487][starVLA.training.train_starvla][INFO] - Step 2995, Loss: {'train/loss': 0.1398075968027115, 'train/grad_norm_pre_clip': 3.8151676654815674, 'timing/data': 0.00017798412591218948, 'timing/model': 0.4695769539102912, 'learning_rate/action_model': 9.092125987995393e-05, 'learning_rate/action_query_proj': 9.092125987995393e-05, 'learning_rate/base': 2.2730314969988483e-05, 'epoch': 0.36}) +[2026-07-27 04:34:19,118][starVLA.training.train_starvla][INFO] - Step 2996, Loss: {'train/loss': 0.09045512229204178, 'train/grad_norm_pre_clip': 2.830613613128662, 'timing/data': 0.0001812037080526352, 'timing/model': 0.46949753584340215, 'learning_rate/action_model': 9.090360175305387e-05, 'learning_rate/action_query_proj': 9.090360175305387e-05, 'learning_rate/base': 2.272590043826347e-05, 'epoch': 0.36}) +[2026-07-27 04:34:24,743][starVLA.training.train_starvla][INFO] - Step 2997, Loss: {'train/loss': 0.11990152299404144, 'train/grad_norm_pre_clip': 2.93888258934021, 'timing/data': 0.0001687011681497097, 'timing/model': 0.4699476547539234, 'learning_rate/action_model': 9.088592826762795e-05, 'learning_rate/action_query_proj': 9.088592826762795e-05, 'learning_rate/base': 2.2721482066906987e-05, 'epoch': 0.36}) +[2026-07-27 04:34:30,593][starVLA.training.train_starvla][INFO] - Step 2998, Loss: {'train/loss': 0.16467827558517456, 'train/grad_norm_pre_clip': 3.5093939304351807, 'timing/data': 0.00019751815125346184, 'timing/model': 0.4679286489263177, 'learning_rate/action_model': 9.08682394306534e-05, 'learning_rate/action_query_proj': 9.08682394306534e-05, 'learning_rate/base': 2.271705985766335e-05, 'epoch': 0.36}) +[2026-07-27 04:34:36,487][starVLA.training.train_starvla][INFO] - Step 2999, Loss: {'train/loss': 0.06523583829402924, 'train/grad_norm_pre_clip': 2.2902674674987793, 'timing/data': 0.0001702350564301014, 'timing/model': 0.5088865598663688, 'learning_rate/action_model': 9.085053524911345e-05, 'learning_rate/action_query_proj': 9.085053524911345e-05, 'learning_rate/base': 2.2712633812278362e-05, 'epoch': 0.36}) +[2026-07-27 04:34:42,236][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 3000 +[2026-07-27 04:34:42,236][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 3000 +[2026-07-27 04:34:42,237][starVLA.training.train_starvla][INFO] - Step 3000, Loss: {'train/loss': 0.11679266393184662, 'train/grad_norm_pre_clip': 3.303331136703491, 'timing/data': 0.00018153805285692215, 'timing/model': 0.4730224939994514, 'learning_rate/action_model': 9.083281572999748e-05, 'learning_rate/action_query_proj': 9.083281572999748e-05, 'learning_rate/base': 2.270820393249937e-05, 'epoch': 0.36}) +[2026-07-27 04:34:42,241][accelerate.accelerator][INFO] - Saving current state to /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_3000_state +[2026-07-27 04:34:42,241][accelerate.accelerator][INFO] - Saving DeepSpeed Model and Optimizer +[2026-07-27 04:35:28,558][accelerate.accelerator][INFO] - DeepSpeed Model and Optimizer saved to output dir /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_3000_state/pytorch_model +[2026-07-27 04:35:28,558][accelerate.checkpointing][INFO] - Sampler state for dataloader 0 saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_3000_state/sampler.bin +[2026-07-27 04:35:28,563][accelerate.checkpointing][INFO] - Random states saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_3000_state/random_states_0.pkl +[2026-07-27 04:35:57,377][starVLA.training.rl_games.checkpoint_sync][INFO] - HF checkpoint sync disabled; skipping upload for step 3000 +[2026-07-27 04:35:57,378][starVLA.training.train_starvla][INFO] - 📊 Saving accessed configuration... +[2026-07-27 04:35:57,392][starVLA.training.train_starvla][INFO] - ✅ Configuration files saved +[2026-07-27 04:36:03,101][starVLA.training.train_starvla][INFO] - Step 3001, Loss: {'train/loss': 0.193370521068573, 'train/grad_norm_pre_clip': 3.7433903217315674, 'timing/data': 0.00017491495236754417, 'timing/model': 0.4670475129969418, 'learning_rate/action_model': 9.081508088030085e-05, 'learning_rate/action_query_proj': 9.081508088030085e-05, 'learning_rate/base': 2.270377022007521e-05, 'epoch': 0.36}) +[2026-07-27 04:36:08,995][starVLA.training.train_starvla][INFO] - Step 3002, Loss: {'train/loss': 0.09071145951747894, 'train/grad_norm_pre_clip': 3.141143321990967, 'timing/data': 0.00017027929425239563, 'timing/model': 0.46281301602721214, 'learning_rate/action_model': 9.079733070702499e-05, 'learning_rate/action_query_proj': 9.079733070702499e-05, 'learning_rate/base': 2.2699332676756247e-05, 'epoch': 0.36}) +[2026-07-27 04:36:14,676][starVLA.training.train_starvla][INFO] - Step 3003, Loss: {'train/loss': 0.13925981521606445, 'train/grad_norm_pre_clip': 3.2355709075927734, 'timing/data': 0.0001707528717815876, 'timing/model': 0.46619176492094994, 'learning_rate/action_model': 9.07795652171774e-05, 'learning_rate/action_query_proj': 9.07795652171774e-05, 'learning_rate/base': 2.269489130429435e-05, 'epoch': 0.36}) +[2026-07-27 04:36:20,324][starVLA.training.train_starvla][INFO] - Step 3004, Loss: {'train/loss': 0.06362313777208328, 'train/grad_norm_pre_clip': 1.9433704614639282, 'timing/data': 0.00017291726544499397, 'timing/model': 0.46446547098457813, 'learning_rate/action_model': 9.076178441777162e-05, 'learning_rate/action_query_proj': 9.076178441777162e-05, 'learning_rate/base': 2.2690446104442904e-05, 'epoch': 0.36}) +[2026-07-27 04:36:25,993][starVLA.training.train_starvla][INFO] - Step 3005, Loss: {'train/loss': 0.1408124417066574, 'train/grad_norm_pre_clip': 3.2585513591766357, 'timing/data': 0.00017113098874688148, 'timing/model': 0.47058406099677086, 'learning_rate/action_model': 9.074398831582722e-05, 'learning_rate/action_query_proj': 9.074398831582722e-05, 'learning_rate/base': 2.2685997078956804e-05, 'epoch': 0.36}) +[2026-07-27 04:36:31,694][starVLA.training.train_starvla][INFO] - Step 3006, Loss: {'train/loss': 0.20919999480247498, 'train/grad_norm_pre_clip': 3.8658254146575928, 'timing/data': 0.0001676836982369423, 'timing/model': 0.47034994373098016, 'learning_rate/action_model': 9.072617691836982e-05, 'learning_rate/action_query_proj': 9.072617691836982e-05, 'learning_rate/base': 2.2681544229592454e-05, 'epoch': 0.36}) +[2026-07-27 04:36:37,412][starVLA.training.train_starvla][INFO] - Step 3007, Loss: {'train/loss': 0.12976764142513275, 'train/grad_norm_pre_clip': 4.629542827606201, 'timing/data': 0.00017747282981872559, 'timing/model': 0.47043114714324474, 'learning_rate/action_model': 9.070835023243107e-05, 'learning_rate/action_query_proj': 9.070835023243107e-05, 'learning_rate/base': 2.2677087558107767e-05, 'epoch': 0.36}) +[2026-07-27 04:36:43,113][starVLA.training.train_starvla][INFO] - Step 3008, Loss: {'train/loss': 0.06051969528198242, 'train/grad_norm_pre_clip': 2.6464409828186035, 'timing/data': 0.00017030071467161179, 'timing/model': 0.4715428492054343, 'learning_rate/action_model': 9.069050826504866e-05, 'learning_rate/action_query_proj': 9.069050826504866e-05, 'learning_rate/base': 2.2672627066262165e-05, 'epoch': 0.36}) +[2026-07-27 04:36:48,826][starVLA.training.train_starvla][INFO] - Step 3009, Loss: {'train/loss': 0.06091349944472313, 'train/grad_norm_pre_clip': 1.970380425453186, 'timing/data': 0.00017248094081878662, 'timing/model': 0.47249773889780045, 'learning_rate/action_model': 9.067265102326634e-05, 'learning_rate/action_query_proj': 9.067265102326634e-05, 'learning_rate/base': 2.2668162755816586e-05, 'epoch': 0.37}) +[2026-07-27 04:36:54,746][starVLA.training.train_starvla][INFO] - Step 3010, Loss: {'train/loss': 0.13512374460697174, 'train/grad_norm_pre_clip': 3.085681915283203, 'timing/data': 0.00017649726942181587, 'timing/model': 0.4715513177216053, 'learning_rate/action_model': 9.065477851413386e-05, 'learning_rate/action_query_proj': 9.065477851413386e-05, 'learning_rate/base': 2.2663694628533465e-05, 'epoch': 0.37}) +[2026-07-27 04:37:00,441][starVLA.training.train_starvla][INFO] - Step 3011, Loss: {'train/loss': 0.11940523982048035, 'train/grad_norm_pre_clip': 2.9346461296081543, 'timing/data': 0.00017469003796577454, 'timing/model': 0.4728699899278581, 'learning_rate/action_model': 9.063689074470699e-05, 'learning_rate/action_query_proj': 9.063689074470699e-05, 'learning_rate/base': 2.2659222686176747e-05, 'epoch': 0.37}) +[2026-07-27 04:37:06,115][starVLA.training.train_starvla][INFO] - Step 3012, Loss: {'train/loss': 0.10610555112361908, 'train/grad_norm_pre_clip': 2.8021399974823, 'timing/data': 0.00017536897212266922, 'timing/model': 0.4641622598282993, 'learning_rate/action_model': 9.061898772204755e-05, 'learning_rate/action_query_proj': 9.061898772204755e-05, 'learning_rate/base': 2.2654746930511887e-05, 'epoch': 0.37}) +[2026-07-27 04:37:11,791][starVLA.training.train_starvla][INFO] - Step 3013, Loss: {'train/loss': 0.18470419943332672, 'train/grad_norm_pre_clip': 4.333393096923828, 'timing/data': 0.00017045019194483757, 'timing/model': 0.46529526310041547, 'learning_rate/action_model': 9.060106945322335e-05, 'learning_rate/action_query_proj': 9.060106945322335e-05, 'learning_rate/base': 2.2650267363305837e-05, 'epoch': 0.37}) +[2026-07-27 04:37:17,481][starVLA.training.train_starvla][INFO] - Step 3014, Loss: {'train/loss': 0.09812702238559723, 'train/grad_norm_pre_clip': 3.143655776977539, 'timing/data': 0.0001734960824251175, 'timing/model': 0.46244854340329766, 'learning_rate/action_model': 9.058313594530826e-05, 'learning_rate/action_query_proj': 9.058313594530826e-05, 'learning_rate/base': 2.2645783986327064e-05, 'epoch': 0.37}) +[2026-07-27 04:37:23,127][starVLA.training.train_starvla][INFO] - Step 3015, Loss: {'train/loss': 0.2155281901359558, 'train/grad_norm_pre_clip': 3.6760237216949463, 'timing/data': 0.00017430121079087257, 'timing/model': 0.4662459222599864, 'learning_rate/action_model': 9.056518720538213e-05, 'learning_rate/action_query_proj': 9.056518720538213e-05, 'learning_rate/base': 2.2641296801345534e-05, 'epoch': 0.37}) +[2026-07-27 04:37:28,795][starVLA.training.train_starvla][INFO] - Step 3016, Loss: {'train/loss': 0.10759111493825912, 'train/grad_norm_pre_clip': 2.9454293251037598, 'timing/data': 0.00017508398741483688, 'timing/model': 0.46560395788401365, 'learning_rate/action_model': 9.054722324053085e-05, 'learning_rate/action_query_proj': 9.054722324053085e-05, 'learning_rate/base': 2.2636805810132713e-05, 'epoch': 0.37}) +[2026-07-27 04:37:34,426][starVLA.training.train_starvla][INFO] - Step 3017, Loss: {'train/loss': 0.10756891220808029, 'train/grad_norm_pre_clip': 2.586949110031128, 'timing/data': 0.00016967998817563057, 'timing/model': 0.4628964150324464, 'learning_rate/action_model': 9.05292440578463e-05, 'learning_rate/action_query_proj': 9.05292440578463e-05, 'learning_rate/base': 2.2632311014461577e-05, 'epoch': 0.37}) +[2026-07-27 04:37:40,096][starVLA.training.train_starvla][INFO] - Step 3018, Loss: {'train/loss': 0.11216586083173752, 'train/grad_norm_pre_clip': 3.080369472503662, 'timing/data': 0.0001732311211526394, 'timing/model': 0.46534230513498187, 'learning_rate/action_model': 9.05112496644264e-05, 'learning_rate/action_query_proj': 9.05112496644264e-05, 'learning_rate/base': 2.26278124161066e-05, 'epoch': 0.37}) +[2026-07-27 04:37:45,764][starVLA.training.train_starvla][INFO] - Step 3019, Loss: {'train/loss': 0.20719745755195618, 'train/grad_norm_pre_clip': 3.5230307579040527, 'timing/data': 0.00017373869195580482, 'timing/model': 0.4599567982368171, 'learning_rate/action_model': 9.049324006737501e-05, 'learning_rate/action_query_proj': 9.049324006737501e-05, 'learning_rate/base': 2.2623310016843753e-05, 'epoch': 0.37}) +[2026-07-27 04:37:51,443][starVLA.training.train_starvla][INFO] - Step 3020, Loss: {'train/loss': 0.14053620398044586, 'train/grad_norm_pre_clip': 3.9063339233398438, 'timing/data': 0.00016940385103225708, 'timing/model': 0.46557018579915166, 'learning_rate/action_model': 9.047521527380208e-05, 'learning_rate/action_query_proj': 9.047521527380208e-05, 'learning_rate/base': 2.261880381845052e-05, 'epoch': 0.37}) +[2026-07-27 04:37:57,307][starVLA.training.train_starvla][INFO] - Step 3021, Loss: {'train/loss': 0.25848305225372314, 'train/grad_norm_pre_clip': 5.5280232429504395, 'timing/data': 0.00018116319552063942, 'timing/model': 0.6359123839065433, 'learning_rate/action_model': 9.045717529082349e-05, 'learning_rate/action_query_proj': 9.045717529082349e-05, 'learning_rate/base': 2.2614293822705872e-05, 'epoch': 0.37}) +[2026-07-27 04:38:03,006][starVLA.training.train_starvla][INFO] - Step 3022, Loss: {'train/loss': 0.3696337640285492, 'train/grad_norm_pre_clip': 5.650859355926514, 'timing/data': 0.00017166603356599808, 'timing/model': 0.4663603249937296, 'learning_rate/action_model': 9.043912012556112e-05, 'learning_rate/action_query_proj': 9.043912012556112e-05, 'learning_rate/base': 2.260978003139028e-05, 'epoch': 0.37}) +[2026-07-27 04:38:08,669][starVLA.training.train_starvla][INFO] - Step 3023, Loss: {'train/loss': 0.14443151652812958, 'train/grad_norm_pre_clip': 3.428555488586426, 'timing/data': 0.0001707170158624649, 'timing/model': 0.46406327933073044, 'learning_rate/action_model': 9.042104978514288e-05, 'learning_rate/action_query_proj': 9.042104978514288e-05, 'learning_rate/base': 2.260526244628572e-05, 'epoch': 0.37}) +[2026-07-27 04:38:14,345][starVLA.training.train_starvla][INFO] - Step 3024, Loss: {'train/loss': 0.1199830174446106, 'train/grad_norm_pre_clip': 2.9157984256744385, 'timing/data': 0.0001752721145749092, 'timing/model': 0.46541741909459233, 'learning_rate/action_model': 9.040296427670267e-05, 'learning_rate/action_query_proj': 9.040296427670267e-05, 'learning_rate/base': 2.2600741069175667e-05, 'epoch': 0.37}) +[2026-07-27 04:38:20,035][starVLA.training.train_starvla][INFO] - Step 3025, Loss: {'train/loss': 0.08144578337669373, 'train/grad_norm_pre_clip': 2.7377376556396484, 'timing/data': 0.00018086005002260208, 'timing/model': 0.4665522528812289, 'learning_rate/action_model': 9.038486360738036e-05, 'learning_rate/action_query_proj': 9.038486360738036e-05, 'learning_rate/base': 2.259621590184509e-05, 'epoch': 0.37}) +[2026-07-27 04:38:25,973][starVLA.training.train_starvla][INFO] - Step 3026, Loss: {'train/loss': 0.039420824497938156, 'train/grad_norm_pre_clip': 1.525091528892517, 'timing/data': 0.00017315102741122246, 'timing/model': 0.46669733989983797, 'learning_rate/action_model': 9.036674778432178e-05, 'learning_rate/action_query_proj': 9.036674778432178e-05, 'learning_rate/base': 2.2591686946080444e-05, 'epoch': 0.37}) +[2026-07-27 04:38:31,656][starVLA.training.train_starvla][INFO] - Step 3027, Loss: {'train/loss': 0.11246047168970108, 'train/grad_norm_pre_clip': 2.888051748275757, 'timing/data': 0.0001802481710910797, 'timing/model': 0.4780267160385847, 'learning_rate/action_model': 9.034861681467878e-05, 'learning_rate/action_query_proj': 9.034861681467878e-05, 'learning_rate/base': 2.2587154203669696e-05, 'epoch': 0.37}) +[2026-07-27 04:38:37,312][starVLA.training.train_starvla][INFO] - Step 3028, Loss: {'train/loss': 0.14693854749202728, 'train/grad_norm_pre_clip': 3.318403720855713, 'timing/data': 0.0001769321970641613, 'timing/model': 0.4691975568421185, 'learning_rate/action_model': 9.03304707056092e-05, 'learning_rate/action_query_proj': 9.03304707056092e-05, 'learning_rate/base': 2.25826176764023e-05, 'epoch': 0.37}) +[2026-07-27 04:38:42,992][starVLA.training.train_starvla][INFO] - Step 3029, Loss: {'train/loss': 0.05769043415784836, 'train/grad_norm_pre_clip': 2.446078300476074, 'timing/data': 0.000174596905708313, 'timing/model': 0.46879872772842646, 'learning_rate/action_model': 9.031230946427681e-05, 'learning_rate/action_query_proj': 9.031230946427681e-05, 'learning_rate/base': 2.2578077366069202e-05, 'epoch': 0.37}) +[2026-07-27 04:38:48,678][starVLA.training.train_starvla][INFO] - Step 3030, Loss: {'train/loss': 0.0768037885427475, 'train/grad_norm_pre_clip': 2.4703991413116455, 'timing/data': 0.00017854617908596992, 'timing/model': 0.47918400494381785, 'learning_rate/action_model': 9.029413309785141e-05, 'learning_rate/action_query_proj': 9.029413309785141e-05, 'learning_rate/base': 2.2573533274462853e-05, 'epoch': 0.37}) +[2026-07-27 04:38:54,344][starVLA.training.train_starvla][INFO] - Step 3031, Loss: {'train/loss': 0.08561315387487411, 'train/grad_norm_pre_clip': 2.5194849967956543, 'timing/data': 0.0002055480144917965, 'timing/model': 0.47281220089644194, 'learning_rate/action_model': 9.027594161350873e-05, 'learning_rate/action_query_proj': 9.027594161350873e-05, 'learning_rate/base': 2.2568985403377184e-05, 'epoch': 0.37}) +[2026-07-27 04:39:00,039][starVLA.training.train_starvla][INFO] - Step 3032, Loss: {'train/loss': 0.16750271618366241, 'train/grad_norm_pre_clip': 4.533550262451172, 'timing/data': 0.00017419084906578064, 'timing/model': 0.4714630860835314, 'learning_rate/action_model': 9.025773501843045e-05, 'learning_rate/action_query_proj': 9.025773501843045e-05, 'learning_rate/base': 2.2564433754607613e-05, 'epoch': 0.37}) +[2026-07-27 04:39:05,711][starVLA.training.train_starvla][INFO] - Step 3033, Loss: {'train/loss': 0.15391141176223755, 'train/grad_norm_pre_clip': 3.5346617698669434, 'timing/data': 0.00019582081586122513, 'timing/model': 0.4625264420174062, 'learning_rate/action_model': 9.023951331980428e-05, 'learning_rate/action_query_proj': 9.023951331980428e-05, 'learning_rate/base': 2.255987832995107e-05, 'epoch': 0.37}) +[2026-07-27 04:39:11,381][starVLA.training.train_starvla][INFO] - Step 3034, Loss: {'train/loss': 0.19427894055843353, 'train/grad_norm_pre_clip': 3.2493038177490234, 'timing/data': 0.00017472589388489723, 'timing/model': 0.4653500239364803, 'learning_rate/action_model': 9.022127652482386e-05, 'learning_rate/action_query_proj': 9.022127652482386e-05, 'learning_rate/base': 2.2555319131205965e-05, 'epoch': 0.37}) +[2026-07-27 04:39:17,051][starVLA.training.train_starvla][INFO] - Step 3035, Loss: {'train/loss': 0.11498484760522842, 'train/grad_norm_pre_clip': 3.2497522830963135, 'timing/data': 0.0002058912068605423, 'timing/model': 0.46225708769634366, 'learning_rate/action_model': 9.020302464068876e-05, 'learning_rate/action_query_proj': 9.020302464068876e-05, 'learning_rate/base': 2.255075616017219e-05, 'epoch': 0.37}) +[2026-07-27 04:39:22,749][starVLA.training.train_starvla][INFO] - Step 3036, Loss: {'train/loss': 0.12301618605852127, 'train/grad_norm_pre_clip': 2.933520555496216, 'timing/data': 0.00017400598153471947, 'timing/model': 0.49088680325075984, 'learning_rate/action_model': 9.018475767460456e-05, 'learning_rate/action_query_proj': 9.018475767460456e-05, 'learning_rate/base': 2.254618941865114e-05, 'epoch': 0.37}) +[2026-07-27 04:39:28,437][starVLA.training.train_starvla][INFO] - Step 3037, Loss: {'train/loss': 0.08180225640535355, 'train/grad_norm_pre_clip': 3.0212671756744385, 'timing/data': 0.0001711496151983738, 'timing/model': 0.4753923541866243, 'learning_rate/action_model': 9.016647563378276e-05, 'learning_rate/action_query_proj': 9.016647563378276e-05, 'learning_rate/base': 2.254161890844569e-05, 'epoch': 0.37}) +[2026-07-27 04:39:34,140][starVLA.training.train_starvla][INFO] - Step 3038, Loss: {'train/loss': 0.09441424906253815, 'train/grad_norm_pre_clip': 3.2413198947906494, 'timing/data': 0.0001717992126941681, 'timing/model': 0.4820079132914543, 'learning_rate/action_model': 9.014817852544081e-05, 'learning_rate/action_query_proj': 9.014817852544081e-05, 'learning_rate/base': 2.2537044631360203e-05, 'epoch': 0.37}) +[2026-07-27 04:39:39,843][starVLA.training.train_starvla][INFO] - Step 3039, Loss: {'train/loss': 0.040846213698387146, 'train/grad_norm_pre_clip': 1.5501036643981934, 'timing/data': 0.00017093028873205185, 'timing/model': 0.4809916620142758, 'learning_rate/action_model': 9.012986635680214e-05, 'learning_rate/action_query_proj': 9.012986635680214e-05, 'learning_rate/base': 2.2532466589200535e-05, 'epoch': 0.37}) +[2026-07-27 04:39:45,546][starVLA.training.train_starvla][INFO] - Step 3040, Loss: {'train/loss': 0.12421182543039322, 'train/grad_norm_pre_clip': 3.3350751399993896, 'timing/data': 0.00020521599799394608, 'timing/model': 0.48341710306704044, 'learning_rate/action_model': 9.01115391350961e-05, 'learning_rate/action_query_proj': 9.01115391350961e-05, 'learning_rate/base': 2.2527884783774024e-05, 'epoch': 0.37}) +[2026-07-27 04:39:51,243][starVLA.training.train_starvla][INFO] - Step 3041, Loss: {'train/loss': 0.23461394011974335, 'train/grad_norm_pre_clip': 4.470423221588135, 'timing/data': 0.0001741405576467514, 'timing/model': 0.46628012508153915, 'learning_rate/action_model': 9.009319686755797e-05, 'learning_rate/action_query_proj': 9.009319686755797e-05, 'learning_rate/base': 2.2523299216889494e-05, 'epoch': 0.37}) +[2026-07-27 04:39:56,928][starVLA.training.train_starvla][INFO] - Step 3042, Loss: {'train/loss': 0.15077531337738037, 'train/grad_norm_pre_clip': 3.08383846282959, 'timing/data': 0.00017579132691025734, 'timing/model': 0.46540492586791515, 'learning_rate/action_model': 9.007483956142901e-05, 'learning_rate/action_query_proj': 9.007483956142901e-05, 'learning_rate/base': 2.2518709890357252e-05, 'epoch': 0.37}) +[2026-07-27 04:40:02,619][starVLA.training.train_starvla][INFO] - Step 3043, Loss: {'train/loss': 0.08152421563863754, 'train/grad_norm_pre_clip': 2.8553502559661865, 'timing/data': 0.00018241116777062416, 'timing/model': 0.4905469510704279, 'learning_rate/action_model': 9.005646722395635e-05, 'learning_rate/action_query_proj': 9.005646722395635e-05, 'learning_rate/base': 2.2514116805989087e-05, 'epoch': 0.37}) +[2026-07-27 04:40:08,295][starVLA.training.train_starvla][INFO] - Step 3044, Loss: {'train/loss': 0.12946544587612152, 'train/grad_norm_pre_clip': 2.944086790084839, 'timing/data': 0.00018236413598060608, 'timing/model': 0.4651476121507585, 'learning_rate/action_model': 9.003807986239315e-05, 'learning_rate/action_query_proj': 9.003807986239315e-05, 'learning_rate/base': 2.250951996559829e-05, 'epoch': 0.37}) +[2026-07-27 04:40:13,965][starVLA.training.train_starvla][INFO] - Step 3045, Loss: {'train/loss': 0.12470930069684982, 'train/grad_norm_pre_clip': 3.812366247177124, 'timing/data': 0.0001763780601322651, 'timing/model': 0.46426215628162026, 'learning_rate/action_model': 9.001967748399842e-05, 'learning_rate/action_query_proj': 9.001967748399842e-05, 'learning_rate/base': 2.2504919370999605e-05, 'epoch': 0.37}) +[2026-07-27 04:40:19,658][starVLA.training.train_starvla][INFO] - Step 3046, Loss: {'train/loss': 0.16031460464000702, 'train/grad_norm_pre_clip': 3.63138484954834, 'timing/data': 0.0001812288537621498, 'timing/model': 0.4784800447523594, 'learning_rate/action_model': 9.000126009603714e-05, 'learning_rate/action_query_proj': 9.000126009603714e-05, 'learning_rate/base': 2.2500315024009284e-05, 'epoch': 0.37}) +[2026-07-27 04:40:25,362][starVLA.training.train_starvla][INFO] - Step 3047, Loss: {'train/loss': 0.06812319904565811, 'train/grad_norm_pre_clip': 2.630568504333496, 'timing/data': 0.00019373511895537376, 'timing/model': 0.4771419120952487, 'learning_rate/action_model': 8.99828277057802e-05, 'learning_rate/action_query_proj': 8.99828277057802e-05, 'learning_rate/base': 2.249570692644505e-05, 'epoch': 0.37}) +[2026-07-27 04:40:31,050][starVLA.training.train_starvla][INFO] - Step 3048, Loss: {'train/loss': 0.16127456724643707, 'train/grad_norm_pre_clip': 3.808006525039673, 'timing/data': 0.00017669377848505974, 'timing/model': 0.4843899952247739, 'learning_rate/action_model': 8.99643803205044e-05, 'learning_rate/action_query_proj': 8.99643803205044e-05, 'learning_rate/base': 2.24910950801261e-05, 'epoch': 0.37}) +[2026-07-27 04:40:36,741][starVLA.training.train_starvla][INFO] - Step 3049, Loss: {'train/loss': 0.08543836325407028, 'train/grad_norm_pre_clip': 2.4352846145629883, 'timing/data': 0.00017283158376812935, 'timing/model': 0.48374941293150187, 'learning_rate/action_model': 8.994591794749251e-05, 'learning_rate/action_query_proj': 8.994591794749251e-05, 'learning_rate/base': 2.2486479486873127e-05, 'epoch': 0.37}) +[2026-07-27 04:40:42,444][starVLA.training.train_starvla][INFO] - Step 3050, Loss: {'train/loss': 0.09137126058340073, 'train/grad_norm_pre_clip': 2.962721109390259, 'timing/data': 0.00017393240705132484, 'timing/model': 0.4816768066957593, 'learning_rate/action_model': 8.992744059403314e-05, 'learning_rate/action_query_proj': 8.992744059403314e-05, 'learning_rate/base': 2.2481860148508284e-05, 'epoch': 0.37}) +[2026-07-27 04:40:48,149][starVLA.training.train_starvla][INFO] - Step 3051, Loss: {'train/loss': 0.22839531302452087, 'train/grad_norm_pre_clip': 4.616447448730469, 'timing/data': 0.00017245998606085777, 'timing/model': 0.4795082570053637, 'learning_rate/action_model': 8.990894826742089e-05, 'learning_rate/action_query_proj': 8.990894826742089e-05, 'learning_rate/base': 2.2477237066855223e-05, 'epoch': 0.37}) +[2026-07-27 04:40:53,828][starVLA.training.train_starvla][INFO] - Step 3052, Loss: {'train/loss': 0.08046498894691467, 'train/grad_norm_pre_clip': 2.5325429439544678, 'timing/data': 0.0001714751124382019, 'timing/model': 0.4789307750761509, 'learning_rate/action_model': 8.989044097495624e-05, 'learning_rate/action_query_proj': 8.989044097495624e-05, 'learning_rate/base': 2.247261024373906e-05, 'epoch': 0.37}) +[2026-07-27 04:40:59,499][starVLA.training.train_starvla][INFO] - Step 3053, Loss: {'train/loss': 0.16380760073661804, 'train/grad_norm_pre_clip': 4.103827953338623, 'timing/data': 0.00017233612015843391, 'timing/model': 0.47848716331645846, 'learning_rate/action_model': 8.987191872394553e-05, 'learning_rate/action_query_proj': 8.987191872394553e-05, 'learning_rate/base': 2.2467979680986383e-05, 'epoch': 0.37}) +[2026-07-27 04:41:05,167][starVLA.training.train_starvla][INFO] - Step 3054, Loss: {'train/loss': 0.14358605444431305, 'train/grad_norm_pre_clip': 3.2596731185913086, 'timing/data': 0.00017458386719226837, 'timing/model': 0.4777149669826031, 'learning_rate/action_model': 8.98533815217011e-05, 'learning_rate/action_query_proj': 8.98533815217011e-05, 'learning_rate/base': 2.2463345380425274e-05, 'epoch': 0.37}) +[2026-07-27 04:41:10,827][starVLA.training.train_starvla][INFO] - Step 3055, Loss: {'train/loss': 0.13340750336647034, 'train/grad_norm_pre_clip': 3.6831247806549072, 'timing/data': 0.00017336569726467133, 'timing/model': 0.48344144504517317, 'learning_rate/action_model': 8.983482937554113e-05, 'learning_rate/action_query_proj': 8.983482937554113e-05, 'learning_rate/base': 2.245870734388528e-05, 'epoch': 0.37}) +[2026-07-27 04:41:16,502][starVLA.training.train_starvla][INFO] - Step 3056, Loss: {'train/loss': 0.08398960530757904, 'train/grad_norm_pre_clip': 2.812748432159424, 'timing/data': 0.000170981977134943, 'timing/model': 0.4829687690362334, 'learning_rate/action_model': 8.98162622927897e-05, 'learning_rate/action_query_proj': 8.98162622927897e-05, 'learning_rate/base': 2.2454065573197424e-05, 'epoch': 0.37}) +[2026-07-27 04:41:22,156][starVLA.training.train_starvla][INFO] - Step 3057, Loss: {'train/loss': 0.07746216654777527, 'train/grad_norm_pre_clip': 2.615117311477661, 'timing/data': 0.00017661694437265396, 'timing/model': 0.4782316689379513, 'learning_rate/action_model': 8.979768028077681e-05, 'learning_rate/action_query_proj': 8.979768028077681e-05, 'learning_rate/base': 2.2449420070194203e-05, 'epoch': 0.37}) +[2026-07-27 04:41:27,849][starVLA.training.train_starvla][INFO] - Step 3058, Loss: {'train/loss': 0.21098914742469788, 'train/grad_norm_pre_clip': 4.752718925476074, 'timing/data': 0.00018137088045477867, 'timing/model': 0.4810564098879695, 'learning_rate/action_model': 8.977908334683836e-05, 'learning_rate/action_query_proj': 8.977908334683836e-05, 'learning_rate/base': 2.244477083670959e-05, 'epoch': 0.37}) +[2026-07-27 04:41:33,524][starVLA.training.train_starvla][INFO] - Step 3059, Loss: {'train/loss': 0.054327670484781265, 'train/grad_norm_pre_clip': 1.9128433465957642, 'timing/data': 0.00017476920038461685, 'timing/model': 0.4790059756487608, 'learning_rate/action_model': 8.97604714983161e-05, 'learning_rate/action_query_proj': 8.97604714983161e-05, 'learning_rate/base': 2.2440117874579027e-05, 'epoch': 0.37}) +[2026-07-27 04:41:39,215][starVLA.training.train_starvla][INFO] - Step 3060, Loss: {'train/loss': 0.0923265665769577, 'train/grad_norm_pre_clip': 2.825349807739258, 'timing/data': 0.00017778202891349792, 'timing/model': 0.487017631996423, 'learning_rate/action_model': 8.974184474255772e-05, 'learning_rate/action_query_proj': 8.974184474255772e-05, 'learning_rate/base': 2.243546118563943e-05, 'epoch': 0.37}) +[2026-07-27 04:41:44,905][starVLA.training.train_starvla][INFO] - Step 3061, Loss: {'train/loss': 0.057006023824214935, 'train/grad_norm_pre_clip': 2.34407377243042, 'timing/data': 0.00017188070341944695, 'timing/model': 0.4825322972610593, 'learning_rate/action_model': 8.972320308691672e-05, 'learning_rate/action_query_proj': 8.972320308691672e-05, 'learning_rate/base': 2.243080077172918e-05, 'epoch': 0.37}) +[2026-07-27 04:41:50,577][starVLA.training.train_starvla][INFO] - Step 3062, Loss: {'train/loss': 0.1435442715883255, 'train/grad_norm_pre_clip': 4.310849189758301, 'timing/data': 0.00016983924433588982, 'timing/model': 0.48516492918133736, 'learning_rate/action_model': 8.970454653875258e-05, 'learning_rate/action_query_proj': 8.970454653875258e-05, 'learning_rate/base': 2.2426136634688144e-05, 'epoch': 0.37}) +[2026-07-27 04:41:56,259][starVLA.training.train_starvla][INFO] - Step 3063, Loss: {'train/loss': 0.055944204330444336, 'train/grad_norm_pre_clip': 3.0739948749542236, 'timing/data': 0.00017549190670251846, 'timing/model': 0.4797296589240432, 'learning_rate/action_model': 8.96858751054306e-05, 'learning_rate/action_query_proj': 8.96858751054306e-05, 'learning_rate/base': 2.242146877635765e-05, 'epoch': 0.37}) +[2026-07-27 04:42:01,955][starVLA.training.train_starvla][INFO] - Step 3064, Loss: {'train/loss': 0.17222638428211212, 'train/grad_norm_pre_clip': 4.258438587188721, 'timing/data': 0.0001737968996167183, 'timing/model': 0.4821592881344259, 'learning_rate/action_model': 8.966718879432194e-05, 'learning_rate/action_query_proj': 8.966718879432194e-05, 'learning_rate/base': 2.2416797198580485e-05, 'epoch': 0.37}) +[2026-07-27 04:42:07,651][starVLA.training.train_starvla][INFO] - Step 3065, Loss: {'train/loss': 0.1662760078907013, 'train/grad_norm_pre_clip': 3.902217388153076, 'timing/data': 0.0001736772246658802, 'timing/model': 0.48245357209816575, 'learning_rate/action_model': 8.964848761280368e-05, 'learning_rate/action_query_proj': 8.964848761280368e-05, 'learning_rate/base': 2.241212190320092e-05, 'epoch': 0.37}) +[2026-07-27 04:42:13,359][starVLA.training.train_starvla][INFO] - Step 3066, Loss: {'train/loss': 0.154453307390213, 'train/grad_norm_pre_clip': 4.557680606842041, 'timing/data': 0.00017067696899175644, 'timing/model': 0.4811432110145688, 'learning_rate/action_model': 8.962977156825875e-05, 'learning_rate/action_query_proj': 8.962977156825875e-05, 'learning_rate/base': 2.2407442892064688e-05, 'epoch': 0.37}) +[2026-07-27 04:42:19,051][starVLA.training.train_starvla][INFO] - Step 3067, Loss: {'train/loss': 0.13297146558761597, 'train/grad_norm_pre_clip': 4.0189666748046875, 'timing/data': 0.00017434777691960335, 'timing/model': 0.4855212983675301, 'learning_rate/action_model': 8.961104066807596e-05, 'learning_rate/action_query_proj': 8.961104066807596e-05, 'learning_rate/base': 2.240276016701899e-05, 'epoch': 0.37}) +[2026-07-27 04:42:24,753][starVLA.training.train_starvla][INFO] - Step 3068, Loss: {'train/loss': 0.2550070583820343, 'train/grad_norm_pre_clip': 5.467522144317627, 'timing/data': 0.0001755058765411377, 'timing/model': 0.4832579023204744, 'learning_rate/action_model': 8.959229491964995e-05, 'learning_rate/action_query_proj': 8.959229491964995e-05, 'learning_rate/base': 2.2398073729912486e-05, 'epoch': 0.37}) +[2026-07-27 04:42:30,460][starVLA.training.train_starvla][INFO] - Step 3069, Loss: {'train/loss': 0.10631006211042404, 'train/grad_norm_pre_clip': 4.051225662231445, 'timing/data': 0.00017519015818834305, 'timing/model': 0.4786176858469844, 'learning_rate/action_model': 8.957353433038124e-05, 'learning_rate/action_query_proj': 8.957353433038124e-05, 'learning_rate/base': 2.239338358259531e-05, 'epoch': 0.37}) +[2026-07-27 04:42:36,177][starVLA.training.train_starvla][INFO] - Step 3070, Loss: {'train/loss': 0.02735595591366291, 'train/grad_norm_pre_clip': 1.5384209156036377, 'timing/data': 0.00017348909750580788, 'timing/model': 0.48230268666520715, 'learning_rate/action_model': 8.955475890767623e-05, 'learning_rate/action_query_proj': 8.955475890767623e-05, 'learning_rate/base': 2.238868972691906e-05, 'epoch': 0.37}) +[2026-07-27 04:42:41,856][starVLA.training.train_starvla][INFO] - Step 3071, Loss: {'train/loss': 0.09906014800071716, 'train/grad_norm_pre_clip': 3.2896056175231934, 'timing/data': 0.00017284229397773743, 'timing/model': 0.478836421854794, 'learning_rate/action_model': 8.953596865894715e-05, 'learning_rate/action_query_proj': 8.953596865894715e-05, 'learning_rate/base': 2.2383992164736788e-05, 'epoch': 0.37}) +[2026-07-27 04:42:47,574][starVLA.training.train_starvla][INFO] - Step 3072, Loss: {'train/loss': 0.1342277079820633, 'train/grad_norm_pre_clip': 3.9773082733154297, 'timing/data': 0.00017313100397586823, 'timing/model': 0.48517865408211946, 'learning_rate/action_model': 8.951716359161212e-05, 'learning_rate/action_query_proj': 8.951716359161212e-05, 'learning_rate/base': 2.237929089790303e-05, 'epoch': 0.37}) +[2026-07-27 04:42:53,269][starVLA.training.train_starvla][INFO] - Step 3073, Loss: {'train/loss': 0.042337171733379364, 'train/grad_norm_pre_clip': 1.490054726600647, 'timing/data': 0.00017804093658924103, 'timing/model': 0.4897628789767623, 'learning_rate/action_model': 8.949834371309506e-05, 'learning_rate/action_query_proj': 8.949834371309506e-05, 'learning_rate/base': 2.2374585928273764e-05, 'epoch': 0.37}) +[2026-07-27 04:42:58,963][starVLA.training.train_starvla][INFO] - Step 3074, Loss: {'train/loss': 0.09582556039094925, 'train/grad_norm_pre_clip': 3.2107632160186768, 'timing/data': 0.00022401893511414528, 'timing/model': 0.4802862317301333, 'learning_rate/action_model': 8.947950903082575e-05, 'learning_rate/action_query_proj': 8.947950903082575e-05, 'learning_rate/base': 2.2369877257706438e-05, 'epoch': 0.37}) +[2026-07-27 04:43:04,647][starVLA.training.train_starvla][INFO] - Step 3075, Loss: {'train/loss': 0.15300127863883972, 'train/grad_norm_pre_clip': 2.776597261428833, 'timing/data': 0.0001753680408000946, 'timing/model': 0.48410117207095027, 'learning_rate/action_model': 8.946065955223984e-05, 'learning_rate/action_query_proj': 8.946065955223984e-05, 'learning_rate/base': 2.236516488805996e-05, 'epoch': 0.37}) +[2026-07-27 04:43:10,351][starVLA.training.train_starvla][INFO] - Step 3076, Loss: {'train/loss': 0.11026375740766525, 'train/grad_norm_pre_clip': 2.7888967990875244, 'timing/data': 0.00017896387726068497, 'timing/model': 0.4827908221632242, 'learning_rate/action_model': 8.94417952847788e-05, 'learning_rate/action_query_proj': 8.94417952847788e-05, 'learning_rate/base': 2.23604488211947e-05, 'epoch': 0.37}) +[2026-07-27 04:43:16,076][starVLA.training.train_starvla][INFO] - Step 3077, Loss: {'train/loss': 0.05319027602672577, 'train/grad_norm_pre_clip': 2.3066976070404053, 'timing/data': 0.00017235707491636276, 'timing/model': 0.47795655811205506, 'learning_rate/action_model': 8.942291623588993e-05, 'learning_rate/action_query_proj': 8.942291623588993e-05, 'learning_rate/base': 2.2355729058972483e-05, 'epoch': 0.37}) +[2026-07-27 04:43:21,784][starVLA.training.train_starvla][INFO] - Step 3078, Loss: {'train/loss': 0.11951273679733276, 'train/grad_norm_pre_clip': 3.836937427520752, 'timing/data': 0.00016951467841863632, 'timing/model': 0.4829461597837508, 'learning_rate/action_model': 8.940402241302642e-05, 'learning_rate/action_query_proj': 8.940402241302642e-05, 'learning_rate/base': 2.2351005603256604e-05, 'epoch': 0.37}) +[2026-07-27 04:43:27,494][starVLA.training.train_starvla][INFO] - Step 3079, Loss: {'train/loss': 0.09775439649820328, 'train/grad_norm_pre_clip': 3.541475534439087, 'timing/data': 0.00017052190378308296, 'timing/model': 0.4835604280233383, 'learning_rate/action_model': 8.938511382364722e-05, 'learning_rate/action_query_proj': 8.938511382364722e-05, 'learning_rate/base': 2.2346278455911804e-05, 'epoch': 0.37}) +[2026-07-27 04:43:33,437][starVLA.training.train_starvla][INFO] - Step 3080, Loss: {'train/loss': 0.06755228340625763, 'train/grad_norm_pre_clip': 2.645307779312134, 'timing/data': 0.00017334381118416786, 'timing/model': 0.4852641331963241, 'learning_rate/action_model': 8.936619047521714e-05, 'learning_rate/action_query_proj': 8.936619047521714e-05, 'learning_rate/base': 2.2341547618804285e-05, 'epoch': 0.37}) +[2026-07-27 04:43:39,144][starVLA.training.train_starvla][INFO] - Step 3081, Loss: {'train/loss': 0.24124184250831604, 'train/grad_norm_pre_clip': 5.4754958152771, 'timing/data': 0.0001914510503411293, 'timing/model': 0.4827316850423813, 'learning_rate/action_model': 8.934725237520682e-05, 'learning_rate/action_query_proj': 8.934725237520682e-05, 'learning_rate/base': 2.2336813093801704e-05, 'epoch': 0.37}) +[2026-07-27 04:43:44,860][starVLA.training.train_starvla][INFO] - Step 3082, Loss: {'train/loss': 0.24198578298091888, 'train/grad_norm_pre_clip': 5.19355583190918, 'timing/data': 0.00016978289932012558, 'timing/model': 0.48253718111664057, 'learning_rate/action_model': 8.932829953109274e-05, 'learning_rate/action_query_proj': 8.932829953109274e-05, 'learning_rate/base': 2.2332074882773185e-05, 'epoch': 0.37}) +[2026-07-27 04:43:50,584][starVLA.training.train_starvla][INFO] - Step 3083, Loss: {'train/loss': 0.2626470625400543, 'train/grad_norm_pre_clip': 4.904425621032715, 'timing/data': 0.00017041200771927834, 'timing/model': 0.4854012937285006, 'learning_rate/action_model': 8.930933195035717e-05, 'learning_rate/action_query_proj': 8.930933195035717e-05, 'learning_rate/base': 2.2327332987589293e-05, 'epoch': 0.37}) +[2026-07-27 04:43:56,266][starVLA.training.train_starvla][INFO] - Step 3084, Loss: {'train/loss': 0.052148785442113876, 'train/grad_norm_pre_clip': 2.5722250938415527, 'timing/data': 0.00017898902297019958, 'timing/model': 0.4826478660106659, 'learning_rate/action_model': 8.929034964048821e-05, 'learning_rate/action_query_proj': 8.929034964048821e-05, 'learning_rate/base': 2.2322587410122053e-05, 'epoch': 0.37}) +[2026-07-27 04:44:01,996][starVLA.training.train_starvla][INFO] - Step 3085, Loss: {'train/loss': 0.08816804736852646, 'train/grad_norm_pre_clip': 2.8309266567230225, 'timing/data': 0.00017251307144761086, 'timing/model': 0.4856425649486482, 'learning_rate/action_model': 8.927135260897978e-05, 'learning_rate/action_query_proj': 8.927135260897978e-05, 'learning_rate/base': 2.2317838152244945e-05, 'epoch': 0.37}) +[2026-07-27 04:44:07,649][starVLA.training.train_starvla][INFO] - Step 3086, Loss: {'train/loss': 0.07270164042711258, 'train/grad_norm_pre_clip': 3.165635108947754, 'timing/data': 0.00017123203724622726, 'timing/model': 0.4825525810010731, 'learning_rate/action_model': 8.92523408633316e-05, 'learning_rate/action_query_proj': 8.92523408633316e-05, 'learning_rate/base': 2.23130852158329e-05, 'epoch': 0.37}) +[2026-07-27 04:44:13,324][starVLA.training.train_starvla][INFO] - Step 3087, Loss: {'train/loss': 0.16347509622573853, 'train/grad_norm_pre_clip': 4.024873733520508, 'timing/data': 0.00017260201275348663, 'timing/model': 0.4812741791829467, 'learning_rate/action_model': 8.92333144110492e-05, 'learning_rate/action_query_proj': 8.92333144110492e-05, 'learning_rate/base': 2.23083286027623e-05, 'epoch': 0.37}) +[2026-07-27 04:44:19,004][starVLA.training.train_starvla][INFO] - Step 3088, Loss: {'train/loss': 0.16094468533992767, 'train/grad_norm_pre_clip': 3.096188545227051, 'timing/data': 0.00018745381385087967, 'timing/model': 0.48380297515541315, 'learning_rate/action_model': 8.921427325964396e-05, 'learning_rate/action_query_proj': 8.921427325964396e-05, 'learning_rate/base': 2.230356831491099e-05, 'epoch': 0.37}) +[2026-07-27 04:44:24,673][starVLA.training.train_starvla][INFO] - Step 3089, Loss: {'train/loss': 0.13403625786304474, 'train/grad_norm_pre_clip': 4.320026397705078, 'timing/data': 0.0001766500063240528, 'timing/model': 0.4779552221298218, 'learning_rate/action_model': 8.9195217416633e-05, 'learning_rate/action_query_proj': 8.9195217416633e-05, 'learning_rate/base': 2.229880435415825e-05, 'epoch': 0.37}) +[2026-07-27 04:44:30,353][starVLA.training.train_starvla][INFO] - Step 3090, Loss: {'train/loss': 0.10322131216526031, 'train/grad_norm_pre_clip': 2.0409059524536133, 'timing/data': 0.00017388397827744484, 'timing/model': 0.48322329903021455, 'learning_rate/action_model': 8.917614688953923e-05, 'learning_rate/action_query_proj': 8.917614688953923e-05, 'learning_rate/base': 2.2294036722384807e-05, 'epoch': 0.37}) +[2026-07-27 04:44:36,030][starVLA.training.train_starvla][INFO] - Step 3091, Loss: {'train/loss': 0.2389059066772461, 'train/grad_norm_pre_clip': 5.095106601715088, 'timing/data': 0.00017733406275510788, 'timing/model': 0.4829253260977566, 'learning_rate/action_model': 8.915706168589143e-05, 'learning_rate/action_query_proj': 8.915706168589143e-05, 'learning_rate/base': 2.228926542147286e-05, 'epoch': 0.37}) +[2026-07-27 04:44:41,691][starVLA.training.train_starvla][INFO] - Step 3092, Loss: {'train/loss': 0.2355038970708847, 'train/grad_norm_pre_clip': 6.5291829109191895, 'timing/data': 0.0001752292737364769, 'timing/model': 0.48646129108965397, 'learning_rate/action_model': 8.913796181322416e-05, 'learning_rate/action_query_proj': 8.913796181322416e-05, 'learning_rate/base': 2.228449045330604e-05, 'epoch': 0.38}) +[2026-07-27 04:44:47,366][starVLA.training.train_starvla][INFO] - Step 3093, Loss: {'train/loss': 0.19284352660179138, 'train/grad_norm_pre_clip': 5.168195724487305, 'timing/data': 0.0001713428646326065, 'timing/model': 0.4843386788852513, 'learning_rate/action_model': 8.911884727907769e-05, 'learning_rate/action_query_proj': 8.911884727907769e-05, 'learning_rate/base': 2.2279711819769423e-05, 'epoch': 0.38}) +[2026-07-27 04:44:53,047][starVLA.training.train_starvla][INFO] - Step 3094, Loss: {'train/loss': 0.15694546699523926, 'train/grad_norm_pre_clip': 3.5596137046813965, 'timing/data': 0.0001743561588227749, 'timing/model': 0.47863468527793884, 'learning_rate/action_model': 8.909971809099817e-05, 'learning_rate/action_query_proj': 8.909971809099817e-05, 'learning_rate/base': 2.2274929522749543e-05, 'epoch': 0.38}) +[2026-07-27 04:44:58,739][starVLA.training.train_starvla][INFO] - Step 3095, Loss: {'train/loss': 0.05476146191358566, 'train/grad_norm_pre_clip': 2.1442155838012695, 'timing/data': 0.00021851714700460434, 'timing/model': 0.4789610616862774, 'learning_rate/action_model': 8.90805742565375e-05, 'learning_rate/action_query_proj': 8.90805742565375e-05, 'learning_rate/base': 2.2270143564134375e-05, 'epoch': 0.38}) +[2026-07-27 04:45:04,409][starVLA.training.train_starvla][INFO] - Step 3096, Loss: {'train/loss': 0.10156657546758652, 'train/grad_norm_pre_clip': 2.978506326675415, 'timing/data': 0.00017348816618323326, 'timing/model': 0.48165380815044045, 'learning_rate/action_model': 8.906141578325336e-05, 'learning_rate/action_query_proj': 8.906141578325336e-05, 'learning_rate/base': 2.226535394581334e-05, 'epoch': 0.38}) +[2026-07-27 04:45:10,089][starVLA.training.train_starvla][INFO] - Step 3097, Loss: {'train/loss': 0.24137264490127563, 'train/grad_norm_pre_clip': 5.554185390472412, 'timing/data': 0.00016877520829439163, 'timing/model': 0.490507451351732, 'learning_rate/action_model': 8.904224267870919e-05, 'learning_rate/action_query_proj': 8.904224267870919e-05, 'learning_rate/base': 2.2260560669677298e-05, 'epoch': 0.38}) +[2026-07-27 04:45:15,751][starVLA.training.train_starvla][INFO] - Step 3098, Loss: {'train/loss': 0.18411141633987427, 'train/grad_norm_pre_clip': 3.697023391723633, 'timing/data': 0.00017282506451010704, 'timing/model': 0.4835737138055265, 'learning_rate/action_model': 8.902305495047426e-05, 'learning_rate/action_query_proj': 8.902305495047426e-05, 'learning_rate/base': 2.2255763737618564e-05, 'epoch': 0.38}) +[2026-07-27 04:45:21,406][starVLA.training.train_starvla][INFO] - Step 3099, Loss: {'train/loss': 0.24871894717216492, 'train/grad_norm_pre_clip': 5.705197334289551, 'timing/data': 0.00017626723274588585, 'timing/model': 0.48291225684806705, 'learning_rate/action_model': 8.900385260612356e-05, 'learning_rate/action_query_proj': 8.900385260612356e-05, 'learning_rate/base': 2.225096315153089e-05, 'epoch': 0.38}) +[2026-07-27 04:45:27,068][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 3100 +[2026-07-27 04:45:27,068][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 3100 +[2026-07-27 04:45:27,069][starVLA.training.train_starvla][INFO] - Step 3100, Loss: {'train/loss': 0.1260673999786377, 'train/grad_norm_pre_clip': 2.795837163925171, 'timing/data': 0.00017300806939601898, 'timing/model': 0.4824036513455212, 'learning_rate/action_model': 8.898463565323789e-05, 'learning_rate/action_query_proj': 8.898463565323789e-05, 'learning_rate/base': 2.2246158913309473e-05, 'epoch': 0.38}) +[2026-07-27 04:45:32,740][starVLA.training.train_starvla][INFO] - Step 3101, Loss: {'train/loss': 0.06877772510051727, 'train/grad_norm_pre_clip': 2.6103286743164062, 'timing/data': 0.00017391890287399292, 'timing/model': 0.4897865420207381, 'learning_rate/action_model': 8.896540409940377e-05, 'learning_rate/action_query_proj': 8.896540409940377e-05, 'learning_rate/base': 2.2241351024850943e-05, 'epoch': 0.38}) +[2026-07-27 04:45:38,395][starVLA.training.train_starvla][INFO] - Step 3102, Loss: {'train/loss': 0.1449618637561798, 'train/grad_norm_pre_clip': 2.8107969760894775, 'timing/data': 0.00017762184143066406, 'timing/model': 0.4841471207328141, 'learning_rate/action_model': 8.894615795221356e-05, 'learning_rate/action_query_proj': 8.894615795221356e-05, 'learning_rate/base': 2.223653948805339e-05, 'epoch': 0.38}) +[2026-07-27 04:45:44,041][starVLA.training.train_starvla][INFO] - Step 3103, Loss: {'train/loss': 0.11521686613559723, 'train/grad_norm_pre_clip': 3.1741273403167725, 'timing/data': 0.00017698900774121284, 'timing/model': 0.4625061331316829, 'learning_rate/action_model': 8.892689721926528e-05, 'learning_rate/action_query_proj': 8.892689721926528e-05, 'learning_rate/base': 2.223172430481632e-05, 'epoch': 0.38}) +[2026-07-27 04:45:49,707][starVLA.training.train_starvla][INFO] - Step 3104, Loss: {'train/loss': 0.0920603796839714, 'train/grad_norm_pre_clip': 3.288586139678955, 'timing/data': 0.0001720050349831581, 'timing/model': 0.4841726799495518, 'learning_rate/action_model': 8.890762190816279e-05, 'learning_rate/action_query_proj': 8.890762190816279e-05, 'learning_rate/base': 2.2226905477040698e-05, 'epoch': 0.38}) +[2026-07-27 04:45:55,337][starVLA.training.train_starvla][INFO] - Step 3105, Loss: {'train/loss': 0.15898071229457855, 'train/grad_norm_pre_clip': 4.290168285369873, 'timing/data': 0.00016973121091723442, 'timing/model': 0.47780052199959755, 'learning_rate/action_model': 8.888833202651569e-05, 'learning_rate/action_query_proj': 8.888833202651569e-05, 'learning_rate/base': 2.2222083006628923e-05, 'epoch': 0.38}) +[2026-07-27 04:46:00,985][starVLA.training.train_starvla][INFO] - Step 3106, Loss: {'train/loss': 0.1462075114250183, 'train/grad_norm_pre_clip': 4.453856945037842, 'timing/data': 0.00017111562192440033, 'timing/model': 0.47857637284323573, 'learning_rate/action_model': 8.886902758193927e-05, 'learning_rate/action_query_proj': 8.886902758193927e-05, 'learning_rate/base': 2.221725689548482e-05, 'epoch': 0.38}) +[2026-07-27 04:46:06,891][starVLA.training.train_starvla][INFO] - Step 3107, Loss: {'train/loss': 0.21894577145576477, 'train/grad_norm_pre_clip': 5.334443092346191, 'timing/data': 0.0001716921105980873, 'timing/model': 0.4657950079999864, 'learning_rate/action_model': 8.884970858205469e-05, 'learning_rate/action_query_proj': 8.884970858205469e-05, 'learning_rate/base': 2.2212427145513672e-05, 'epoch': 0.38}) +[2026-07-27 04:46:12,756][starVLA.training.train_starvla][INFO] - Step 3108, Loss: {'train/loss': 0.10838104039430618, 'train/grad_norm_pre_clip': 3.430270195007324, 'timing/data': 0.00019093183800578117, 'timing/model': 0.45587127516046166, 'learning_rate/action_model': 8.883037503448875e-05, 'learning_rate/action_query_proj': 8.883037503448875e-05, 'learning_rate/base': 2.2207593758622187e-05, 'epoch': 0.38}) +[2026-07-27 04:46:18,349][starVLA.training.train_starvla][INFO] - Step 3109, Loss: {'train/loss': 0.17242854833602905, 'train/grad_norm_pre_clip': 4.047755241394043, 'timing/data': 0.00017616990953683853, 'timing/model': 0.4663221947848797, 'learning_rate/action_model': 8.881102694687401e-05, 'learning_rate/action_query_proj': 8.881102694687401e-05, 'learning_rate/base': 2.2202756736718503e-05, 'epoch': 0.38}) +[2026-07-27 04:46:23,959][starVLA.training.train_starvla][INFO] - Step 3110, Loss: {'train/loss': 0.13820427656173706, 'train/grad_norm_pre_clip': 3.640498638153076, 'timing/data': 0.00017535872757434845, 'timing/model': 0.47403300693258643, 'learning_rate/action_model': 8.87916643268488e-05, 'learning_rate/action_query_proj': 8.87916643268488e-05, 'learning_rate/base': 2.21979160817122e-05, 'epoch': 0.38}) +[2026-07-27 04:46:29,578][starVLA.training.train_starvla][INFO] - Step 3111, Loss: {'train/loss': 0.11289998143911362, 'train/grad_norm_pre_clip': 3.4125497341156006, 'timing/data': 0.00018411502242088318, 'timing/model': 0.46831330144777894, 'learning_rate/action_model': 8.877228718205718e-05, 'learning_rate/action_query_proj': 8.877228718205718e-05, 'learning_rate/base': 2.2193071795514296e-05, 'epoch': 0.38}) +[2026-07-27 04:46:35,215][starVLA.training.train_starvla][INFO] - Step 3112, Loss: {'train/loss': 0.07805194705724716, 'train/grad_norm_pre_clip': 3.674146890640259, 'timing/data': 0.00017548585310578346, 'timing/model': 0.4656618610024452, 'learning_rate/action_model': 8.875289552014897e-05, 'learning_rate/action_query_proj': 8.875289552014897e-05, 'learning_rate/base': 2.2188223880037242e-05, 'epoch': 0.38}) +[2026-07-27 04:46:40,832][starVLA.training.train_starvla][INFO] - Step 3113, Loss: {'train/loss': 0.23525038361549377, 'train/grad_norm_pre_clip': 5.602841854095459, 'timing/data': 0.00018140999600291252, 'timing/model': 0.47540059918537736, 'learning_rate/action_model': 8.873348934877963e-05, 'learning_rate/action_query_proj': 8.873348934877963e-05, 'learning_rate/base': 2.2183372337194907e-05, 'epoch': 0.38}) +[2026-07-27 04:46:46,463][starVLA.training.train_starvla][INFO] - Step 3114, Loss: {'train/loss': 0.17448799312114716, 'train/grad_norm_pre_clip': 4.3293538093566895, 'timing/data': 0.0001739421859383583, 'timing/model': 0.47070916928350925, 'learning_rate/action_model': 8.871406867561045e-05, 'learning_rate/action_query_proj': 8.871406867561045e-05, 'learning_rate/base': 2.2178517168902613e-05, 'epoch': 0.38}) +[2026-07-27 04:46:52,105][starVLA.training.train_starvla][INFO] - Step 3115, Loss: {'train/loss': 0.17474417388439178, 'train/grad_norm_pre_clip': 4.191941738128662, 'timing/data': 0.00018736813217401505, 'timing/model': 0.4684964776970446, 'learning_rate/action_model': 8.86946335083084e-05, 'learning_rate/action_query_proj': 8.86946335083084e-05, 'learning_rate/base': 2.21736583770771e-05, 'epoch': 0.38}) +[2026-07-27 04:46:57,725][starVLA.training.train_starvla][INFO] - Step 3116, Loss: {'train/loss': 0.14656555652618408, 'train/grad_norm_pre_clip': 3.326704740524292, 'timing/data': 0.00017108116298913956, 'timing/model': 0.46806615591049194, 'learning_rate/action_model': 8.867518385454616e-05, 'learning_rate/action_query_proj': 8.867518385454616e-05, 'learning_rate/base': 2.216879596363654e-05, 'epoch': 0.38}) +[2026-07-27 04:47:03,363][starVLA.training.train_starvla][INFO] - Step 3117, Loss: {'train/loss': 0.13709402084350586, 'train/grad_norm_pre_clip': 4.13066291809082, 'timing/data': 0.00017453869804739952, 'timing/model': 0.47045899322256446, 'learning_rate/action_model': 8.865571972200218e-05, 'learning_rate/action_query_proj': 8.865571972200218e-05, 'learning_rate/base': 2.2163929930500545e-05, 'epoch': 0.38}) +[2026-07-27 04:47:08,980][starVLA.training.train_starvla][INFO] - Step 3118, Loss: {'train/loss': 0.124188132584095, 'train/grad_norm_pre_clip': 2.8711724281311035, 'timing/data': 0.00017502577975392342, 'timing/model': 0.46881215181201696, 'learning_rate/action_model': 8.863624111836056e-05, 'learning_rate/action_query_proj': 8.863624111836056e-05, 'learning_rate/base': 2.215906027959014e-05, 'epoch': 0.38}) +[2026-07-27 04:47:14,595][starVLA.training.train_starvla][INFO] - Step 3119, Loss: {'train/loss': 0.08204393088817596, 'train/grad_norm_pre_clip': 2.4698500633239746, 'timing/data': 0.00018644798547029495, 'timing/model': 0.46741781383752823, 'learning_rate/action_model': 8.861674805131115e-05, 'learning_rate/action_query_proj': 8.861674805131115e-05, 'learning_rate/base': 2.215418701282779e-05, 'epoch': 0.38}) +[2026-07-27 04:47:20,193][starVLA.training.train_starvla][INFO] - Step 3120, Loss: {'train/loss': 0.11857207119464874, 'train/grad_norm_pre_clip': 2.756730794906616, 'timing/data': 0.00017868122085928917, 'timing/model': 0.47020596638321877, 'learning_rate/action_model': 8.85972405285495e-05, 'learning_rate/action_query_proj': 8.85972405285495e-05, 'learning_rate/base': 2.2149310132137376e-05, 'epoch': 0.38}) +[2026-07-27 04:47:25,822][starVLA.training.train_starvla][INFO] - Step 3121, Loss: {'train/loss': 0.15427710115909576, 'train/grad_norm_pre_clip': 3.76114559173584, 'timing/data': 0.0001717512495815754, 'timing/model': 0.4758722041733563, 'learning_rate/action_model': 8.857771855777688e-05, 'learning_rate/action_query_proj': 8.857771855777688e-05, 'learning_rate/base': 2.214442963944422e-05, 'epoch': 0.38}) +[2026-07-27 04:47:31,426][starVLA.training.train_starvla][INFO] - Step 3122, Loss: {'train/loss': 0.14222939312458038, 'train/grad_norm_pre_clip': 3.6295223236083984, 'timing/data': 0.00018501514568924904, 'timing/model': 0.4570118822157383, 'learning_rate/action_model': 8.855818214670026e-05, 'learning_rate/action_query_proj': 8.855818214670026e-05, 'learning_rate/base': 2.2139545536675064e-05, 'epoch': 0.38}) +[2026-07-27 04:47:37,049][starVLA.training.train_starvla][INFO] - Step 3123, Loss: {'train/loss': 0.11867498606443405, 'train/grad_norm_pre_clip': 3.5884451866149902, 'timing/data': 0.00019341986626386642, 'timing/model': 0.4585619140416384, 'learning_rate/action_model': 8.85386313030323e-05, 'learning_rate/action_query_proj': 8.85386313030323e-05, 'learning_rate/base': 2.2134657825758074e-05, 'epoch': 0.38}) +[2026-07-27 04:47:42,647][starVLA.training.train_starvla][INFO] - Step 3124, Loss: {'train/loss': 0.08742532879114151, 'train/grad_norm_pre_clip': 2.4405698776245117, 'timing/data': 0.00017884187400341034, 'timing/model': 0.4650097442790866, 'learning_rate/action_model': 8.851906603449136e-05, 'learning_rate/action_query_proj': 8.851906603449136e-05, 'learning_rate/base': 2.212976650862284e-05, 'epoch': 0.38}) +[2026-07-27 04:47:48,269][starVLA.training.train_starvla][INFO] - Step 3125, Loss: {'train/loss': 0.12895911931991577, 'train/grad_norm_pre_clip': 3.3032665252685547, 'timing/data': 0.00018046796321868896, 'timing/model': 0.46515432791784406, 'learning_rate/action_model': 8.84994863488015e-05, 'learning_rate/action_query_proj': 8.84994863488015e-05, 'learning_rate/base': 2.2124871587200376e-05, 'epoch': 0.38}) +[2026-07-27 04:47:53,891][starVLA.training.train_starvla][INFO] - Step 3126, Loss: {'train/loss': 0.10415774583816528, 'train/grad_norm_pre_clip': 2.516430616378784, 'timing/data': 0.0001753191463649273, 'timing/model': 0.46699582366272807, 'learning_rate/action_model': 8.847989225369247e-05, 'learning_rate/action_query_proj': 8.847989225369247e-05, 'learning_rate/base': 2.2119973063423118e-05, 'epoch': 0.38}) +[2026-07-27 04:47:59,500][starVLA.training.train_starvla][INFO] - Step 3127, Loss: {'train/loss': 0.1106993779540062, 'train/grad_norm_pre_clip': 3.016425371170044, 'timing/data': 0.00019284896552562714, 'timing/model': 0.4573819190263748, 'learning_rate/action_model': 8.84602837568997e-05, 'learning_rate/action_query_proj': 8.84602837568997e-05, 'learning_rate/base': 2.2115070939224924e-05, 'epoch': 0.38}) +[2026-07-27 04:48:05,116][starVLA.training.train_starvla][INFO] - Step 3128, Loss: {'train/loss': 0.120897077023983, 'train/grad_norm_pre_clip': 2.3080177307128906, 'timing/data': 0.00017130887135863304, 'timing/model': 0.45967714907601476, 'learning_rate/action_model': 8.844066086616431e-05, 'learning_rate/action_query_proj': 8.844066086616431e-05, 'learning_rate/base': 2.2110165216541078e-05, 'epoch': 0.38}) +[2026-07-27 04:48:10,773][starVLA.training.train_starvla][INFO] - Step 3129, Loss: {'train/loss': 0.19443587958812714, 'train/grad_norm_pre_clip': 3.493830919265747, 'timing/data': 0.00017401203513145447, 'timing/model': 0.4638659367337823, 'learning_rate/action_model': 8.842102358923315e-05, 'learning_rate/action_query_proj': 8.842102358923315e-05, 'learning_rate/base': 2.2105255897308286e-05, 'epoch': 0.38}) +[2026-07-27 04:48:16,380][starVLA.training.train_starvla][INFO] - Step 3130, Loss: {'train/loss': 0.15001150965690613, 'train/grad_norm_pre_clip': 3.0763988494873047, 'timing/data': 0.0001848321408033371, 'timing/model': 0.46387312607839704, 'learning_rate/action_model': 8.840137193385865e-05, 'learning_rate/action_query_proj': 8.840137193385865e-05, 'learning_rate/base': 2.2100342983464663e-05, 'epoch': 0.38}) +[2026-07-27 04:48:22,004][starVLA.training.train_starvla][INFO] - Step 3131, Loss: {'train/loss': 0.09570950269699097, 'train/grad_norm_pre_clip': 2.9686572551727295, 'timing/data': 0.00018368102610111237, 'timing/model': 0.46277811890468, 'learning_rate/action_model': 8.8381705907799e-05, 'learning_rate/action_query_proj': 8.8381705907799e-05, 'learning_rate/base': 2.209542647694975e-05, 'epoch': 0.38}) +[2026-07-27 04:48:27,607][starVLA.training.train_starvla][INFO] - Step 3132, Loss: {'train/loss': 0.04624796658754349, 'train/grad_norm_pre_clip': 1.9417450428009033, 'timing/data': 0.0001891818828880787, 'timing/model': 0.4623060147278011, 'learning_rate/action_model': 8.836202551881806e-05, 'learning_rate/action_query_proj': 8.836202551881806e-05, 'learning_rate/base': 2.2090506379704515e-05, 'epoch': 0.38}) +[2026-07-27 04:48:33,226][starVLA.training.train_starvla][INFO] - Step 3133, Loss: {'train/loss': 0.09564796090126038, 'train/grad_norm_pre_clip': 2.548809051513672, 'timing/data': 0.00018127402290701866, 'timing/model': 0.46424496080726385, 'learning_rate/action_model': 8.834233077468527e-05, 'learning_rate/action_query_proj': 8.834233077468527e-05, 'learning_rate/base': 2.2085582693671318e-05, 'epoch': 0.38}) +[2026-07-27 04:48:38,840][starVLA.training.train_starvla][INFO] - Step 3134, Loss: {'train/loss': 0.11264820396900177, 'train/grad_norm_pre_clip': 3.1843695640563965, 'timing/data': 0.00019926298409700394, 'timing/model': 0.4621297768317163, 'learning_rate/action_model': 8.832262168317587e-05, 'learning_rate/action_query_proj': 8.832262168317587e-05, 'learning_rate/base': 2.2080655420793968e-05, 'epoch': 0.38}) +[2026-07-27 04:48:44,465][starVLA.training.train_starvla][INFO] - Step 3135, Loss: {'train/loss': 0.11318562924861908, 'train/grad_norm_pre_clip': 3.207915782928467, 'timing/data': 0.00018869293853640556, 'timing/model': 0.46300046890974045, 'learning_rate/action_model': 8.830289825207065e-05, 'learning_rate/action_query_proj': 8.830289825207065e-05, 'learning_rate/base': 2.2075724563017662e-05, 'epoch': 0.38}) +[2026-07-27 04:48:50,096][starVLA.training.train_starvla][INFO] - Step 3136, Loss: {'train/loss': 0.15573017299175262, 'train/grad_norm_pre_clip': 4.447930335998535, 'timing/data': 0.0001731961965560913, 'timing/model': 0.4562042481265962, 'learning_rate/action_model': 8.828316048915615e-05, 'learning_rate/action_query_proj': 8.828316048915615e-05, 'learning_rate/base': 2.2070790122289038e-05, 'epoch': 0.38}) +[2026-07-27 04:48:55,710][starVLA.training.train_starvla][INFO] - Step 3137, Loss: {'train/loss': 0.16329745948314667, 'train/grad_norm_pre_clip': 3.634544610977173, 'timing/data': 0.00026022130623459816, 'timing/model': 0.46089416882023215, 'learning_rate/action_model': 8.826340840222448e-05, 'learning_rate/action_query_proj': 8.826340840222448e-05, 'learning_rate/base': 2.206585210055612e-05, 'epoch': 0.38}) +[2026-07-27 04:49:01,590][starVLA.training.train_starvla][INFO] - Step 3138, Loss: {'train/loss': 0.16217243671417236, 'train/grad_norm_pre_clip': 3.6337180137634277, 'timing/data': 0.00018615974113345146, 'timing/model': 0.4646348711103201, 'learning_rate/action_model': 8.824364199907348e-05, 'learning_rate/action_query_proj': 8.824364199907348e-05, 'learning_rate/base': 2.206091049976837e-05, 'epoch': 0.38}) +[2026-07-27 04:49:07,203][starVLA.training.train_starvla][INFO] - Step 3139, Loss: {'train/loss': 0.09898456931114197, 'train/grad_norm_pre_clip': 2.1808369159698486, 'timing/data': 0.00018386729061603546, 'timing/model': 0.4602306713350117, 'learning_rate/action_model': 8.822386128750662e-05, 'learning_rate/action_query_proj': 8.822386128750662e-05, 'learning_rate/base': 2.2055965321876655e-05, 'epoch': 0.38}) +[2026-07-27 04:49:12,832][starVLA.training.train_starvla][INFO] - Step 3140, Loss: {'train/loss': 0.10653276741504669, 'train/grad_norm_pre_clip': 3.031313180923462, 'timing/data': 0.00017283717170357704, 'timing/model': 0.4609789368696511, 'learning_rate/action_model': 8.820406627533298e-05, 'learning_rate/action_query_proj': 8.820406627533298e-05, 'learning_rate/base': 2.2051016568833246e-05, 'epoch': 0.38}) +[2026-07-27 04:49:18,478][starVLA.training.train_starvla][INFO] - Step 3141, Loss: {'train/loss': 0.17163601517677307, 'train/grad_norm_pre_clip': 3.4794130325317383, 'timing/data': 0.00017633195966482162, 'timing/model': 0.46073919301852584, 'learning_rate/action_model': 8.818425697036736e-05, 'learning_rate/action_query_proj': 8.818425697036736e-05, 'learning_rate/base': 2.204606424259184e-05, 'epoch': 0.38}) +[2026-07-27 04:49:24,108][starVLA.training.train_starvla][INFO] - Step 3142, Loss: {'train/loss': 0.06802845746278763, 'train/grad_norm_pre_clip': 2.115661382675171, 'timing/data': 0.00017083808779716492, 'timing/model': 0.46578290639445186, 'learning_rate/action_model': 8.816443338043011e-05, 'learning_rate/action_query_proj': 8.816443338043011e-05, 'learning_rate/base': 2.2041108345107528e-05, 'epoch': 0.38}) +[2026-07-27 04:49:29,742][starVLA.training.train_starvla][INFO] - Step 3143, Loss: {'train/loss': 0.02669905126094818, 'train/grad_norm_pre_clip': 1.0032333135604858, 'timing/data': 0.000175348948687315, 'timing/model': 0.4626738652586937, 'learning_rate/action_model': 8.814459551334732e-05, 'learning_rate/action_query_proj': 8.814459551334732e-05, 'learning_rate/base': 2.203614887833683e-05, 'epoch': 0.38}) +[2026-07-27 04:49:35,618][starVLA.training.train_starvla][INFO] - Step 3144, Loss: {'train/loss': 0.07245391607284546, 'train/grad_norm_pre_clip': 2.363624095916748, 'timing/data': 0.0001798742450773716, 'timing/model': 0.4602689319290221, 'learning_rate/action_model': 8.812474337695062e-05, 'learning_rate/action_query_proj': 8.812474337695062e-05, 'learning_rate/base': 2.2031185844237656e-05, 'epoch': 0.38}) +[2026-07-27 04:49:41,251][starVLA.training.train_starvla][INFO] - Step 3145, Loss: {'train/loss': 0.10676316916942596, 'train/grad_norm_pre_clip': 3.2417781352996826, 'timing/data': 0.0001730090007185936, 'timing/model': 0.46047506015747786, 'learning_rate/action_model': 8.810487697907735e-05, 'learning_rate/action_query_proj': 8.810487697907735e-05, 'learning_rate/base': 2.2026219244769338e-05, 'epoch': 0.38}) +[2026-07-27 04:49:46,904][starVLA.training.train_starvla][INFO] - Step 3146, Loss: {'train/loss': 0.10042603313922882, 'train/grad_norm_pre_clip': 3.389564037322998, 'timing/data': 0.00016774283722043037, 'timing/model': 0.4617855651304126, 'learning_rate/action_model': 8.808499632757045e-05, 'learning_rate/action_query_proj': 8.808499632757045e-05, 'learning_rate/base': 2.202124908189261e-05, 'epoch': 0.38}) +[2026-07-27 04:49:52,590][starVLA.training.train_starvla][INFO] - Step 3147, Loss: {'train/loss': 0.11612331122159958, 'train/grad_norm_pre_clip': 3.053734064102173, 'timing/data': 0.00018594181165099144, 'timing/model': 0.4671411351300776, 'learning_rate/action_model': 8.806510143027846e-05, 'learning_rate/action_query_proj': 8.806510143027846e-05, 'learning_rate/base': 2.2016275357569615e-05, 'epoch': 0.38}) +[2026-07-27 04:49:58,493][starVLA.training.train_starvla][INFO] - Step 3148, Loss: {'train/loss': 0.13080258667469025, 'train/grad_norm_pre_clip': 3.670896530151367, 'timing/data': 0.00016885576769709587, 'timing/model': 0.46595986606553197, 'learning_rate/action_model': 8.80451922950556e-05, 'learning_rate/action_query_proj': 8.80451922950556e-05, 'learning_rate/base': 2.20112980737639e-05, 'epoch': 0.38}) +[2026-07-27 04:50:04,154][starVLA.training.train_starvla][INFO] - Step 3149, Loss: {'train/loss': 0.036667268723249435, 'train/grad_norm_pre_clip': 1.6459732055664062, 'timing/data': 0.00016994494944810867, 'timing/model': 0.46048005297780037, 'learning_rate/action_model': 8.802526892976164e-05, 'learning_rate/action_query_proj': 8.802526892976164e-05, 'learning_rate/base': 2.200631723244041e-05, 'epoch': 0.38}) +[2026-07-27 04:50:09,814][starVLA.training.train_starvla][INFO] - Step 3150, Loss: {'train/loss': 0.051325779408216476, 'train/grad_norm_pre_clip': 2.027021884918213, 'timing/data': 0.00018465518951416016, 'timing/model': 0.4610561770386994, 'learning_rate/action_model': 8.800533134226207e-05, 'learning_rate/action_query_proj': 8.800533134226207e-05, 'learning_rate/base': 2.2001332835565517e-05, 'epoch': 0.38}) +[2026-07-27 04:50:15,519][starVLA.training.train_starvla][INFO] - Step 3151, Loss: {'train/loss': 0.19111332297325134, 'train/grad_norm_pre_clip': 4.013418674468994, 'timing/data': 0.00018360372632741928, 'timing/model': 0.5130864498205483, 'learning_rate/action_model': 8.798537954042789e-05, 'learning_rate/action_query_proj': 8.798537954042789e-05, 'learning_rate/base': 2.199634488510697e-05, 'epoch': 0.38}) +[2026-07-27 04:50:21,183][starVLA.training.train_starvla][INFO] - Step 3152, Loss: {'train/loss': 0.13313335180282593, 'train/grad_norm_pre_clip': 3.8319036960601807, 'timing/data': 0.00017758412286639214, 'timing/model': 0.46445946022868156, 'learning_rate/action_model': 8.796541353213577e-05, 'learning_rate/action_query_proj': 8.796541353213577e-05, 'learning_rate/base': 2.1991353383033942e-05, 'epoch': 0.38}) +[2026-07-27 04:50:27,071][starVLA.training.train_starvla][INFO] - Step 3153, Loss: {'train/loss': 0.1476304829120636, 'train/grad_norm_pre_clip': 3.8895955085754395, 'timing/data': 0.00017034541815519333, 'timing/model': 0.4655675473622978, 'learning_rate/action_model': 8.794543332526795e-05, 'learning_rate/action_query_proj': 8.794543332526795e-05, 'learning_rate/base': 2.1986358331316987e-05, 'epoch': 0.38}) +[2026-07-27 04:50:32,708][starVLA.training.train_starvla][INFO] - Step 3154, Loss: {'train/loss': 0.16892732679843903, 'train/grad_norm_pre_clip': 4.621691703796387, 'timing/data': 0.0001734429970383644, 'timing/model': 0.4660181333310902, 'learning_rate/action_model': 8.792543892771233e-05, 'learning_rate/action_query_proj': 8.792543892771233e-05, 'learning_rate/base': 2.1981359731928082e-05, 'epoch': 0.38}) +[2026-07-27 04:50:38,329][starVLA.training.train_starvla][INFO] - Step 3155, Loss: {'train/loss': 0.07860079407691956, 'train/grad_norm_pre_clip': 3.0708694458007812, 'timing/data': 0.00017579970881342888, 'timing/model': 0.4655108363367617, 'learning_rate/action_model': 8.790543034736237e-05, 'learning_rate/action_query_proj': 8.790543034736237e-05, 'learning_rate/base': 2.197635758684059e-05, 'epoch': 0.38}) +[2026-07-27 04:50:43,945][starVLA.training.train_starvla][INFO] - Step 3156, Loss: {'train/loss': 0.1631714254617691, 'train/grad_norm_pre_clip': 4.194677352905273, 'timing/data': 0.00018011732026934624, 'timing/model': 0.46244013914838433, 'learning_rate/action_model': 8.788540759211714e-05, 'learning_rate/action_query_proj': 8.788540759211714e-05, 'learning_rate/base': 2.1971351898029285e-05, 'epoch': 0.38}) +[2026-07-27 04:50:49,568][starVLA.training.train_starvla][INFO] - Step 3157, Loss: {'train/loss': 0.24090924859046936, 'train/grad_norm_pre_clip': 5.618234634399414, 'timing/data': 0.0001716017723083496, 'timing/model': 0.4624073808081448, 'learning_rate/action_model': 8.78653706698813e-05, 'learning_rate/action_query_proj': 8.78653706698813e-05, 'learning_rate/base': 2.1966342667470326e-05, 'epoch': 0.38}) +[2026-07-27 04:50:55,208][starVLA.training.train_starvla][INFO] - Step 3158, Loss: {'train/loss': 0.2258676439523697, 'train/grad_norm_pre_clip': 4.879017353057861, 'timing/data': 0.00018164562061429024, 'timing/model': 0.46455291798338294, 'learning_rate/action_model': 8.784531958856514e-05, 'learning_rate/action_query_proj': 8.784531958856514e-05, 'learning_rate/base': 2.1961329897141284e-05, 'epoch': 0.38}) +[2026-07-27 04:51:00,796][starVLA.training.train_starvla][INFO] - Step 3159, Loss: {'train/loss': 0.1216903030872345, 'train/grad_norm_pre_clip': 4.223363876342773, 'timing/data': 0.00017406325787305832, 'timing/model': 0.45839420799165964, 'learning_rate/action_model': 8.782525435608447e-05, 'learning_rate/action_query_proj': 8.782525435608447e-05, 'learning_rate/base': 2.195631358902112e-05, 'epoch': 0.38}) +[2026-07-27 04:51:06,390][starVLA.training.train_starvla][INFO] - Step 3160, Loss: {'train/loss': 0.1505661904811859, 'train/grad_norm_pre_clip': 4.200697422027588, 'timing/data': 0.00017772801220417023, 'timing/model': 0.4631770313717425, 'learning_rate/action_model': 8.780517498036074e-05, 'learning_rate/action_query_proj': 8.780517498036074e-05, 'learning_rate/base': 2.1951293745090186e-05, 'epoch': 0.38}) +[2026-07-27 04:51:11,991][starVLA.training.train_starvla][INFO] - Step 3161, Loss: {'train/loss': 0.1410156488418579, 'train/grad_norm_pre_clip': 3.609820604324341, 'timing/data': 0.0001710113137960434, 'timing/model': 0.4639614508487284, 'learning_rate/action_model': 8.778508146932098e-05, 'learning_rate/action_query_proj': 8.778508146932098e-05, 'learning_rate/base': 2.1946270367330245e-05, 'epoch': 0.38}) +[2026-07-27 04:51:17,567][starVLA.training.train_starvla][INFO] - Step 3162, Loss: {'train/loss': 0.10139469802379608, 'train/grad_norm_pre_clip': 3.367234945297241, 'timing/data': 0.00018650991842150688, 'timing/model': 0.46066525112837553, 'learning_rate/action_model': 8.776497383089779e-05, 'learning_rate/action_query_proj': 8.776497383089779e-05, 'learning_rate/base': 2.1941243457724448e-05, 'epoch': 0.38}) +[2026-07-27 04:51:23,167][starVLA.training.train_starvla][INFO] - Step 3163, Loss: {'train/loss': 0.1413881629705429, 'train/grad_norm_pre_clip': 3.994492530822754, 'timing/data': 0.0001711798831820488, 'timing/model': 0.4590623630210757, 'learning_rate/action_model': 8.774485207302933e-05, 'learning_rate/action_query_proj': 8.774485207302933e-05, 'learning_rate/base': 2.1936213018257332e-05, 'epoch': 0.38}) +[2026-07-27 04:51:28,787][starVLA.training.train_starvla][INFO] - Step 3164, Loss: {'train/loss': 0.1605559140443802, 'train/grad_norm_pre_clip': 3.727656126022339, 'timing/data': 0.00017345603555440903, 'timing/model': 0.46489616110920906, 'learning_rate/action_model': 8.772471620365937e-05, 'learning_rate/action_query_proj': 8.772471620365937e-05, 'learning_rate/base': 2.1931179050914842e-05, 'epoch': 0.38}) +[2026-07-27 04:51:34,403][starVLA.training.train_starvla][INFO] - Step 3165, Loss: {'train/loss': 0.25025251507759094, 'train/grad_norm_pre_clip': 5.124671459197998, 'timing/data': 0.00017869286239147186, 'timing/model': 0.4627712690271437, 'learning_rate/action_model': 8.770456623073721e-05, 'learning_rate/action_query_proj': 8.770456623073721e-05, 'learning_rate/base': 2.1926141557684303e-05, 'epoch': 0.38}) +[2026-07-27 04:51:40,040][starVLA.training.train_starvla][INFO] - Step 3166, Loss: {'train/loss': 0.2926017940044403, 'train/grad_norm_pre_clip': 5.44130802154541, 'timing/data': 0.00018185703083872795, 'timing/model': 0.466038275975734, 'learning_rate/action_model': 8.768440216221776e-05, 'learning_rate/action_query_proj': 8.768440216221776e-05, 'learning_rate/base': 2.192110054055444e-05, 'epoch': 0.38}) +[2026-07-27 04:51:45,685][starVLA.training.train_starvla][INFO] - Step 3167, Loss: {'train/loss': 0.17601388692855835, 'train/grad_norm_pre_clip': 3.951967716217041, 'timing/data': 0.00017439015209674835, 'timing/model': 0.46279266104102135, 'learning_rate/action_model': 8.766422400606147e-05, 'learning_rate/action_query_proj': 8.766422400606147e-05, 'learning_rate/base': 2.1916056001515367e-05, 'epoch': 0.38}) +[2026-07-27 04:51:51,301][starVLA.training.train_starvla][INFO] - Step 3168, Loss: {'train/loss': 0.10886548459529877, 'train/grad_norm_pre_clip': 3.3548901081085205, 'timing/data': 0.0001781228929758072, 'timing/model': 0.4635523990727961, 'learning_rate/action_model': 8.764403177023435e-05, 'learning_rate/action_query_proj': 8.764403177023435e-05, 'learning_rate/base': 2.191100794255859e-05, 'epoch': 0.38}) +[2026-07-27 04:51:56,959][starVLA.training.train_starvla][INFO] - Step 3169, Loss: {'train/loss': 0.12625105679035187, 'train/grad_norm_pre_clip': 3.9075849056243896, 'timing/data': 0.00019177375361323357, 'timing/model': 0.4650360648520291, 'learning_rate/action_model': 8.762382546270799e-05, 'learning_rate/action_query_proj': 8.762382546270799e-05, 'learning_rate/base': 2.1905956365676998e-05, 'epoch': 0.38}) +[2026-07-27 04:52:02,575][starVLA.training.train_starvla][INFO] - Step 3170, Loss: {'train/loss': 0.12889732420444489, 'train/grad_norm_pre_clip': 4.580338001251221, 'timing/data': 0.0001736111007630825, 'timing/model': 0.4568999451585114, 'learning_rate/action_model': 8.760360509145949e-05, 'learning_rate/action_query_proj': 8.760360509145949e-05, 'learning_rate/base': 2.1900901272864873e-05, 'epoch': 0.38}) +[2026-07-27 04:52:08,178][starVLA.training.train_starvla][INFO] - Step 3171, Loss: {'train/loss': 0.12310944497585297, 'train/grad_norm_pre_clip': 3.974271535873413, 'timing/data': 0.0001748381182551384, 'timing/model': 0.45759437792003155, 'learning_rate/action_model': 8.758337066447157e-05, 'learning_rate/action_query_proj': 8.758337066447157e-05, 'learning_rate/base': 2.1895842666117893e-05, 'epoch': 0.38}) +[2026-07-27 04:52:13,785][starVLA.training.train_starvla][INFO] - Step 3172, Loss: {'train/loss': 0.09581827372312546, 'train/grad_norm_pre_clip': 2.8876307010650635, 'timing/data': 0.00017509795725345612, 'timing/model': 0.45618935814127326, 'learning_rate/action_model': 8.756312218973243e-05, 'learning_rate/action_query_proj': 8.756312218973243e-05, 'learning_rate/base': 2.1890780547433107e-05, 'epoch': 0.38}) +[2026-07-27 04:52:19,380][starVLA.training.train_starvla][INFO] - Step 3173, Loss: {'train/loss': 0.10914198309183121, 'train/grad_norm_pre_clip': 3.0943002700805664, 'timing/data': 0.0001758122816681862, 'timing/model': 0.45593067817389965, 'learning_rate/action_model': 8.754285967523586e-05, 'learning_rate/action_query_proj': 8.754285967523586e-05, 'learning_rate/base': 2.1885714918808965e-05, 'epoch': 0.38}) +[2026-07-27 04:52:24,975][starVLA.training.train_starvla][INFO] - Step 3174, Loss: {'train/loss': 0.049789201468229294, 'train/grad_norm_pre_clip': 1.7206255197525024, 'timing/data': 0.0001757279969751835, 'timing/model': 0.46633219439536333, 'learning_rate/action_model': 8.75225831289812e-05, 'learning_rate/action_query_proj': 8.75225831289812e-05, 'learning_rate/base': 2.18806457822453e-05, 'epoch': 0.39}) +[2026-07-27 04:52:30,528][starVLA.training.train_starvla][INFO] - Step 3175, Loss: {'train/loss': 0.09873101115226746, 'train/grad_norm_pre_clip': 2.7683780193328857, 'timing/data': 0.0005788621492683887, 'timing/model': 0.4628591169603169, 'learning_rate/action_model': 8.750229255897328e-05, 'learning_rate/action_query_proj': 8.750229255897328e-05, 'learning_rate/base': 2.187557313974332e-05, 'epoch': 0.39}) +[2026-07-27 04:52:36,101][starVLA.training.train_starvla][INFO] - Step 3176, Loss: {'train/loss': 0.18245664238929749, 'train/grad_norm_pre_clip': 4.503842830657959, 'timing/data': 0.0001905309036374092, 'timing/model': 0.46067663794383407, 'learning_rate/action_model': 8.74819879732225e-05, 'learning_rate/action_query_proj': 8.74819879732225e-05, 'learning_rate/base': 2.1870496993305626e-05, 'epoch': 0.39}) +[2026-07-27 04:52:41,676][starVLA.training.train_starvla][INFO] - Step 3177, Loss: {'train/loss': 0.25580546259880066, 'train/grad_norm_pre_clip': 5.692604064941406, 'timing/data': 0.00018452294170856476, 'timing/model': 0.4651447986252606, 'learning_rate/action_model': 8.74616693797448e-05, 'learning_rate/action_query_proj': 8.74616693797448e-05, 'learning_rate/base': 2.18654173449362e-05, 'epoch': 0.39}) +[2026-07-27 04:52:47,251][starVLA.training.train_starvla][INFO] - Step 3178, Loss: {'train/loss': 0.11761990189552307, 'train/grad_norm_pre_clip': 2.5568227767944336, 'timing/data': 0.00018042605370283127, 'timing/model': 0.45687602600082755, 'learning_rate/action_model': 8.744133678656162e-05, 'learning_rate/action_query_proj': 8.744133678656162e-05, 'learning_rate/base': 2.1860334196640404e-05, 'epoch': 0.39}) +[2026-07-27 04:52:52,828][starVLA.training.train_starvla][INFO] - Step 3179, Loss: {'train/loss': 0.1551247239112854, 'train/grad_norm_pre_clip': 4.221070766448975, 'timing/data': 0.00018405867740511894, 'timing/model': 0.46535656275227666, 'learning_rate/action_model': 8.742099020169997e-05, 'learning_rate/action_query_proj': 8.742099020169997e-05, 'learning_rate/base': 2.1855247550424993e-05, 'epoch': 0.39}) +[2026-07-27 04:52:58,424][starVLA.training.train_starvla][INFO] - Step 3180, Loss: {'train/loss': 0.11934216320514679, 'train/grad_norm_pre_clip': 3.644912004470825, 'timing/data': 0.0001824069768190384, 'timing/model': 0.4619215917773545, 'learning_rate/action_model': 8.740062963319236e-05, 'learning_rate/action_query_proj': 8.740062963319236e-05, 'learning_rate/base': 2.185015740829809e-05, 'epoch': 0.39}) +[2026-07-27 04:53:04,001][starVLA.training.train_starvla][INFO] - Step 3181, Loss: {'train/loss': 0.09846267104148865, 'train/grad_norm_pre_clip': 3.6689677238464355, 'timing/data': 0.0001892009750008583, 'timing/model': 0.4634068659506738, 'learning_rate/action_model': 8.73802550890768e-05, 'learning_rate/action_query_proj': 8.73802550890768e-05, 'learning_rate/base': 2.18450637722692e-05, 'epoch': 0.39}) +[2026-07-27 04:53:09,580][starVLA.training.train_starvla][INFO] - Step 3182, Loss: {'train/loss': 0.16962990164756775, 'train/grad_norm_pre_clip': 4.375161170959473, 'timing/data': 0.00017935922369360924, 'timing/model': 0.46240791492164135, 'learning_rate/action_model': 8.735986657739684e-05, 'learning_rate/action_query_proj': 8.735986657739684e-05, 'learning_rate/base': 2.183996664434921e-05, 'epoch': 0.39}) +[2026-07-27 04:53:15,155][starVLA.training.train_starvla][INFO] - Step 3183, Loss: {'train/loss': 0.05902007594704628, 'train/grad_norm_pre_clip': 2.1990888118743896, 'timing/data': 0.00024390686303377151, 'timing/model': 0.46359886694699526, 'learning_rate/action_model': 8.733946410620155e-05, 'learning_rate/action_query_proj': 8.733946410620155e-05, 'learning_rate/base': 2.1834866026550387e-05, 'epoch': 0.39}) +[2026-07-27 04:53:20,727][starVLA.training.train_starvla][INFO] - Step 3184, Loss: {'train/loss': 0.08073848485946655, 'train/grad_norm_pre_clip': 3.0141499042510986, 'timing/data': 0.00018045958131551743, 'timing/model': 0.46356375608593225, 'learning_rate/action_model': 8.731904768354549e-05, 'learning_rate/action_query_proj': 8.731904768354549e-05, 'learning_rate/base': 2.1829761920886372e-05, 'epoch': 0.39}) +[2026-07-27 04:53:26,305][starVLA.training.train_starvla][INFO] - Step 3185, Loss: {'train/loss': 0.11780036985874176, 'train/grad_norm_pre_clip': 3.074038505554199, 'timing/data': 0.00019575702026486397, 'timing/model': 0.46575339790433645, 'learning_rate/action_model': 8.729861731748877e-05, 'learning_rate/action_query_proj': 8.729861731748877e-05, 'learning_rate/base': 2.1824654329372192e-05, 'epoch': 0.39}) +[2026-07-27 04:53:31,899][starVLA.training.train_starvla][INFO] - Step 3186, Loss: {'train/loss': 0.11048299074172974, 'train/grad_norm_pre_clip': 3.061340093612671, 'timing/data': 0.00017233891412615776, 'timing/model': 0.4587689423933625, 'learning_rate/action_model': 8.727817301609695e-05, 'learning_rate/action_query_proj': 8.727817301609695e-05, 'learning_rate/base': 2.1819543254024237e-05, 'epoch': 0.39}) +[2026-07-27 04:53:37,500][starVLA.training.train_starvla][INFO] - Step 3187, Loss: {'train/loss': 0.05241839587688446, 'train/grad_norm_pre_clip': 1.8155971765518188, 'timing/data': 0.00018290383741259575, 'timing/model': 0.4607160370796919, 'learning_rate/action_model': 8.725771478744112e-05, 'learning_rate/action_query_proj': 8.725771478744112e-05, 'learning_rate/base': 2.181442869686028e-05, 'epoch': 0.39}) +[2026-07-27 04:53:43,089][starVLA.training.train_starvla][INFO] - Step 3188, Loss: {'train/loss': 0.245112806558609, 'train/grad_norm_pre_clip': 6.687007904052734, 'timing/data': 0.00017193611711263657, 'timing/model': 0.4629434263333678, 'learning_rate/action_model': 8.723724263959785e-05, 'learning_rate/action_query_proj': 8.723724263959785e-05, 'learning_rate/base': 2.180931065989946e-05, 'epoch': 0.39}) +[2026-07-27 04:53:48,697][starVLA.training.train_starvla][INFO] - Step 3189, Loss: {'train/loss': 0.15412497520446777, 'train/grad_norm_pre_clip': 4.763065814971924, 'timing/data': 0.00017398223280906677, 'timing/model': 0.46274051582440734, 'learning_rate/action_model': 8.721675658064925e-05, 'learning_rate/action_query_proj': 8.721675658064925e-05, 'learning_rate/base': 2.180418914516231e-05, 'epoch': 0.39}) +[2026-07-27 04:53:54,316][starVLA.training.train_starvla][INFO] - Step 3190, Loss: {'train/loss': 0.11456357687711716, 'train/grad_norm_pre_clip': 2.5272014141082764, 'timing/data': 0.00019280007109045982, 'timing/model': 0.4616326643154025, 'learning_rate/action_model': 8.71962566186829e-05, 'learning_rate/action_query_proj': 8.71962566186829e-05, 'learning_rate/base': 2.1799064154670724e-05, 'epoch': 0.39}) +[2026-07-27 04:54:00,004][starVLA.training.train_starvla][INFO] - Step 3191, Loss: {'train/loss': 0.06687602400779724, 'train/grad_norm_pre_clip': 2.383258819580078, 'timing/data': 0.0001872689463198185, 'timing/model': 0.4660400371067226, 'learning_rate/action_model': 8.71757427617918e-05, 'learning_rate/action_query_proj': 8.71757427617918e-05, 'learning_rate/base': 2.179393569044795e-05, 'epoch': 0.39}) +[2026-07-27 04:54:05,664][starVLA.training.train_starvla][INFO] - Step 3192, Loss: {'train/loss': 0.152387797832489, 'train/grad_norm_pre_clip': 3.620131254196167, 'timing/data': 0.0001697842963039875, 'timing/model': 0.46623126277700067, 'learning_rate/action_model': 8.715521501807457e-05, 'learning_rate/action_query_proj': 8.715521501807457e-05, 'learning_rate/base': 2.1788803754518642e-05, 'epoch': 0.39}) +[2026-07-27 04:54:11,342][starVLA.training.train_starvla][INFO] - Step 3193, Loss: {'train/loss': 0.20301465690135956, 'train/grad_norm_pre_clip': 4.134619235992432, 'timing/data': 0.00022179866209626198, 'timing/model': 0.46397495782002807, 'learning_rate/action_model': 8.713467339563518e-05, 'learning_rate/action_query_proj': 8.713467339563518e-05, 'learning_rate/base': 2.1783668348908794e-05, 'epoch': 0.39}) +[2026-07-27 04:54:17,020][starVLA.training.train_starvla][INFO] - Step 3194, Loss: {'train/loss': 0.1669815182685852, 'train/grad_norm_pre_clip': 3.4698140621185303, 'timing/data': 0.00022110389545559883, 'timing/model': 0.46358919236809015, 'learning_rate/action_model': 8.711411790258314e-05, 'learning_rate/action_query_proj': 8.711411790258314e-05, 'learning_rate/base': 2.1778529475645786e-05, 'epoch': 0.39}) +[2026-07-27 04:54:22,698][starVLA.training.train_starvla][INFO] - Step 3195, Loss: {'train/loss': 0.07031385600566864, 'train/grad_norm_pre_clip': 3.104813575744629, 'timing/data': 0.0002065710723400116, 'timing/model': 0.463475838303566, 'learning_rate/action_model': 8.709354854703348e-05, 'learning_rate/action_query_proj': 8.709354854703348e-05, 'learning_rate/base': 2.177338713675837e-05, 'epoch': 0.39}) +[2026-07-27 04:54:28,405][starVLA.training.train_starvla][INFO] - Step 3196, Loss: {'train/loss': 0.2331840842962265, 'train/grad_norm_pre_clip': 6.390850067138672, 'timing/data': 0.0001870943233370781, 'timing/model': 0.462518815882504, 'learning_rate/action_model': 8.707296533710663e-05, 'learning_rate/action_query_proj': 8.707296533710663e-05, 'learning_rate/base': 2.176824133427666e-05, 'epoch': 0.39}) +[2026-07-27 04:54:34,112][starVLA.training.train_starvla][INFO] - Step 3197, Loss: {'train/loss': 0.14391262829303741, 'train/grad_norm_pre_clip': 3.360273599624634, 'timing/data': 0.00017484603449702263, 'timing/model': 0.46669648867100477, 'learning_rate/action_model': 8.705236828092849e-05, 'learning_rate/action_query_proj': 8.705236828092849e-05, 'learning_rate/base': 2.1763092070232123e-05, 'epoch': 0.39}) +[2026-07-27 04:54:39,822][starVLA.training.train_starvla][INFO] - Step 3198, Loss: {'train/loss': 0.0668807327747345, 'train/grad_norm_pre_clip': 2.6193149089813232, 'timing/data': 0.00017254985868930817, 'timing/model': 0.4660336161032319, 'learning_rate/action_model': 8.70317573866305e-05, 'learning_rate/action_query_proj': 8.70317573866305e-05, 'learning_rate/base': 2.1757939346657626e-05, 'epoch': 0.39}) +[2026-07-27 04:54:45,456][starVLA.training.train_starvla][INFO] - Step 3199, Loss: {'train/loss': 0.10623740404844284, 'train/grad_norm_pre_clip': 2.634101152420044, 'timing/data': 0.00020314007997512817, 'timing/model': 0.46595662273466587, 'learning_rate/action_model': 8.701113266234949e-05, 'learning_rate/action_query_proj': 8.701113266234949e-05, 'learning_rate/base': 2.1752783165587372e-05, 'epoch': 0.39}) +[2026-07-27 04:54:51,062][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 3200 +[2026-07-27 04:54:51,063][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 3200 +[2026-07-27 04:54:51,064][starVLA.training.train_starvla][INFO] - Step 3200, Loss: {'train/loss': 0.030609559267759323, 'train/grad_norm_pre_clip': 1.702975869178772, 'timing/data': 0.00018889503553509712, 'timing/model': 0.4662593100219965, 'learning_rate/action_model': 8.699049411622776e-05, 'learning_rate/action_query_proj': 8.699049411622776e-05, 'learning_rate/base': 2.174762352905694e-05, 'epoch': 0.39}) +[2026-07-27 04:54:56,670][starVLA.training.train_starvla][INFO] - Step 3201, Loss: {'train/loss': 0.04608258977532387, 'train/grad_norm_pre_clip': 1.9778313636779785, 'timing/data': 0.0001922091469168663, 'timing/model': 0.46306010568514466, 'learning_rate/action_model': 8.69698417564131e-05, 'learning_rate/action_query_proj': 8.69698417564131e-05, 'learning_rate/base': 2.1742460439103274e-05, 'epoch': 0.39}) +[2026-07-27 04:55:02,287][starVLA.training.train_starvla][INFO] - Step 3202, Loss: {'train/loss': 0.10982274264097214, 'train/grad_norm_pre_clip': 3.1685497760772705, 'timing/data': 0.00017467886209487915, 'timing/model': 0.46414025500416756, 'learning_rate/action_model': 8.694917559105873e-05, 'learning_rate/action_query_proj': 8.694917559105873e-05, 'learning_rate/base': 2.173729389776468e-05, 'epoch': 0.39}) +[2026-07-27 04:55:07,906][starVLA.training.train_starvla][INFO] - Step 3203, Loss: {'train/loss': 0.08835922926664352, 'train/grad_norm_pre_clip': 2.647414445877075, 'timing/data': 0.00017663929611444473, 'timing/model': 0.46413744799792767, 'learning_rate/action_model': 8.692849562832331e-05, 'learning_rate/action_query_proj': 8.692849562832331e-05, 'learning_rate/base': 2.173212390708083e-05, 'epoch': 0.39}) +[2026-07-27 04:55:13,504][starVLA.training.train_starvla][INFO] - Step 3204, Loss: {'train/loss': 0.11181864887475967, 'train/grad_norm_pre_clip': 3.5020782947540283, 'timing/data': 0.00018695788457989693, 'timing/model': 0.4657379360869527, 'learning_rate/action_model': 8.6907801876371e-05, 'learning_rate/action_query_proj': 8.6907801876371e-05, 'learning_rate/base': 2.172695046909275e-05, 'epoch': 0.39}) +[2026-07-27 04:55:19,133][starVLA.training.train_starvla][INFO] - Step 3205, Loss: {'train/loss': 0.13212350010871887, 'train/grad_norm_pre_clip': 4.2317633628845215, 'timing/data': 0.00019872095435857773, 'timing/model': 0.4604170862585306, 'learning_rate/action_model': 8.688709434337134e-05, 'learning_rate/action_query_proj': 8.688709434337134e-05, 'learning_rate/base': 2.1721773585842835e-05, 'epoch': 0.39}) +[2026-07-27 04:55:24,749][starVLA.training.train_starvla][INFO] - Step 3206, Loss: {'train/loss': 0.10776513814926147, 'train/grad_norm_pre_clip': 3.406797409057617, 'timing/data': 0.0002327561378479004, 'timing/model': 0.4614729839377105, 'learning_rate/action_model': 8.686637303749933e-05, 'learning_rate/action_query_proj': 8.686637303749933e-05, 'learning_rate/base': 2.1716593259374833e-05, 'epoch': 0.39}) +[2026-07-27 04:55:30,390][starVLA.training.train_starvla][INFO] - Step 3207, Loss: {'train/loss': 0.04508940875530243, 'train/grad_norm_pre_clip': 2.2865865230560303, 'timing/data': 0.00018264120444655418, 'timing/model': 0.4636834808625281, 'learning_rate/action_model': 8.684563796693544e-05, 'learning_rate/action_query_proj': 8.684563796693544e-05, 'learning_rate/base': 2.171140949173386e-05, 'epoch': 0.39}) +[2026-07-27 04:55:36,010][starVLA.training.train_starvla][INFO] - Step 3208, Loss: {'train/loss': 0.16418758034706116, 'train/grad_norm_pre_clip': 2.955293655395508, 'timing/data': 0.00018498115241527557, 'timing/model': 0.4626390878111124, 'learning_rate/action_model': 8.68248891398655e-05, 'learning_rate/action_query_proj': 8.68248891398655e-05, 'learning_rate/base': 2.1706222284966375e-05, 'epoch': 0.39}) +[2026-07-27 04:55:41,663][starVLA.training.train_starvla][INFO] - Step 3209, Loss: {'train/loss': 0.10550446808338165, 'train/grad_norm_pre_clip': 3.348860502243042, 'timing/data': 0.00017417361959815025, 'timing/model': 0.4840561696328223, 'learning_rate/action_model': 8.680412656448086e-05, 'learning_rate/action_query_proj': 8.680412656448086e-05, 'learning_rate/base': 2.1701031641120216e-05, 'epoch': 0.39}) +[2026-07-27 04:55:47,599][starVLA.training.train_starvla][INFO] - Step 3210, Loss: {'train/loss': 0.06347278505563736, 'train/grad_norm_pre_clip': 2.408169746398926, 'timing/data': 0.00018118415027856827, 'timing/model': 0.48030794505029917, 'learning_rate/action_model': 8.678335024897824e-05, 'learning_rate/action_query_proj': 8.678335024897824e-05, 'learning_rate/base': 2.169583756224456e-05, 'epoch': 0.39}) +[2026-07-27 04:55:53,268][starVLA.training.train_starvla][INFO] - Step 3211, Loss: {'train/loss': 0.06791805475950241, 'train/grad_norm_pre_clip': 2.0152182579040527, 'timing/data': 0.00018925312906503677, 'timing/model': 0.4846260598860681, 'learning_rate/action_model': 8.676256020155982e-05, 'learning_rate/action_query_proj': 8.676256020155982e-05, 'learning_rate/base': 2.1690640050389954e-05, 'epoch': 0.39}) +[2026-07-27 04:55:58,943][starVLA.training.train_starvla][INFO] - Step 3212, Loss: {'train/loss': 0.10724589973688126, 'train/grad_norm_pre_clip': 3.0736916065216064, 'timing/data': 0.00018279394134879112, 'timing/model': 0.47916806396096945, 'learning_rate/action_model': 8.674175643043314e-05, 'learning_rate/action_query_proj': 8.674175643043314e-05, 'learning_rate/base': 2.1685439107608286e-05, 'epoch': 0.39}) +[2026-07-27 04:56:04,638][starVLA.training.train_starvla][INFO] - Step 3213, Loss: {'train/loss': 0.17260581254959106, 'train/grad_norm_pre_clip': 4.765740871429443, 'timing/data': 0.0001764991320669651, 'timing/model': 0.4924767119809985, 'learning_rate/action_model': 8.672093894381125e-05, 'learning_rate/action_query_proj': 8.672093894381125e-05, 'learning_rate/base': 2.1680234735952812e-05, 'epoch': 0.39}) +[2026-07-27 04:56:10,296][starVLA.training.train_starvla][INFO] - Step 3214, Loss: {'train/loss': 0.1445813924074173, 'train/grad_norm_pre_clip': 3.533940315246582, 'timing/data': 0.00019363593310117722, 'timing/model': 0.4830533592030406, 'learning_rate/action_model': 8.670010774991251e-05, 'learning_rate/action_query_proj': 8.670010774991251e-05, 'learning_rate/base': 2.167502693747813e-05, 'epoch': 0.39}) +[2026-07-27 04:56:15,941][starVLA.training.train_starvla][INFO] - Step 3215, Loss: {'train/loss': 0.1282879114151001, 'train/grad_norm_pre_clip': 3.550715684890747, 'timing/data': 0.00017679575830698013, 'timing/model': 0.4847964011132717, 'learning_rate/action_model': 8.66792628569608e-05, 'learning_rate/action_query_proj': 8.66792628569608e-05, 'learning_rate/base': 2.16698157142402e-05, 'epoch': 0.39}) +[2026-07-27 04:56:21,602][starVLA.training.train_starvla][INFO] - Step 3216, Loss: {'train/loss': 0.1556633859872818, 'train/grad_norm_pre_clip': 4.335136890411377, 'timing/data': 0.00018140533939003944, 'timing/model': 0.4706011461094022, 'learning_rate/action_model': 8.665840427318532e-05, 'learning_rate/action_query_proj': 8.665840427318532e-05, 'learning_rate/base': 2.166460106829633e-05, 'epoch': 0.39}) +[2026-07-27 04:56:27,278][starVLA.training.train_starvla][INFO] - Step 3217, Loss: {'train/loss': 0.222798153758049, 'train/grad_norm_pre_clip': 4.083861351013184, 'timing/data': 0.00017855409532785416, 'timing/model': 0.4830993148498237, 'learning_rate/action_model': 8.663753200682071e-05, 'learning_rate/action_query_proj': 8.663753200682071e-05, 'learning_rate/base': 2.1659383001705177e-05, 'epoch': 0.39}) +[2026-07-27 04:56:32,939][starVLA.training.train_starvla][INFO] - Step 3218, Loss: {'train/loss': 0.06747333705425262, 'train/grad_norm_pre_clip': 2.7150654792785645, 'timing/data': 0.00017322786152362823, 'timing/model': 0.472020932007581, 'learning_rate/action_model': 8.661664606610702e-05, 'learning_rate/action_query_proj': 8.661664606610702e-05, 'learning_rate/base': 2.1654161516526756e-05, 'epoch': 0.39}) +[2026-07-27 04:56:38,597][starVLA.training.train_starvla][INFO] - Step 3219, Loss: {'train/loss': 0.0859009176492691, 'train/grad_norm_pre_clip': 2.3485560417175293, 'timing/data': 0.00019019003957509995, 'timing/model': 0.4734730077907443, 'learning_rate/action_model': 8.659574645928969e-05, 'learning_rate/action_query_proj': 8.659574645928969e-05, 'learning_rate/base': 2.1648936614822423e-05, 'epoch': 0.39}) +[2026-07-27 04:56:44,293][starVLA.training.train_starvla][INFO] - Step 3220, Loss: {'train/loss': 0.30593132972717285, 'train/grad_norm_pre_clip': 7.0659098625183105, 'timing/data': 0.0001829727552831173, 'timing/model': 0.4926190981641412, 'learning_rate/action_model': 8.657483319461954e-05, 'learning_rate/action_query_proj': 8.657483319461954e-05, 'learning_rate/base': 2.1643708298654885e-05, 'epoch': 0.39}) +[2026-07-27 04:56:49,991][starVLA.training.train_starvla][INFO] - Step 3221, Loss: {'train/loss': 0.1233815997838974, 'train/grad_norm_pre_clip': 3.271817922592163, 'timing/data': 0.0001774439588189125, 'timing/model': 0.4869539327919483, 'learning_rate/action_model': 8.65539062803528e-05, 'learning_rate/action_query_proj': 8.65539062803528e-05, 'learning_rate/base': 2.16384765700882e-05, 'epoch': 0.39}) +[2026-07-27 04:56:55,660][starVLA.training.train_starvla][INFO] - Step 3222, Loss: {'train/loss': 0.10042864829301834, 'train/grad_norm_pre_clip': 3.4639971256256104, 'timing/data': 0.00017430679872632027, 'timing/model': 0.4816551278345287, 'learning_rate/action_model': 8.653296572475111e-05, 'learning_rate/action_query_proj': 8.653296572475111e-05, 'learning_rate/base': 2.1633241431187777e-05, 'epoch': 0.39}) +[2026-07-27 04:57:01,379][starVLA.training.train_starvla][INFO] - Step 3223, Loss: {'train/loss': 0.2085123211145401, 'train/grad_norm_pre_clip': 5.210677146911621, 'timing/data': 0.0001851152628660202, 'timing/model': 0.46425135899335146, 'learning_rate/action_model': 8.651201153608142e-05, 'learning_rate/action_query_proj': 8.651201153608142e-05, 'learning_rate/base': 2.1628002884020354e-05, 'epoch': 0.39}) +[2026-07-27 04:57:07,018][starVLA.training.train_starvla][INFO] - Step 3224, Loss: {'train/loss': 0.1260923445224762, 'train/grad_norm_pre_clip': 3.1631054878234863, 'timing/data': 0.00018117763102054596, 'timing/model': 0.462116708047688, 'learning_rate/action_model': 8.649104372261617e-05, 'learning_rate/action_query_proj': 8.649104372261617e-05, 'learning_rate/base': 2.1622760930654042e-05, 'epoch': 0.39}) +[2026-07-27 04:57:12,659][starVLA.training.train_starvla][INFO] - Step 3225, Loss: {'train/loss': 0.07722044736146927, 'train/grad_norm_pre_clip': 2.51664137840271, 'timing/data': 0.00017551099881529808, 'timing/model': 0.46273738192394376, 'learning_rate/action_model': 8.647006229263306e-05, 'learning_rate/action_query_proj': 8.647006229263306e-05, 'learning_rate/base': 2.1617515573158266e-05, 'epoch': 0.39}) +[2026-07-27 04:57:18,290][starVLA.training.train_starvla][INFO] - Step 3226, Loss: {'train/loss': 0.09627161175012589, 'train/grad_norm_pre_clip': 2.787872314453125, 'timing/data': 0.00017262576147913933, 'timing/model': 0.465367219876498, 'learning_rate/action_model': 8.644906725441528e-05, 'learning_rate/action_query_proj': 8.644906725441528e-05, 'learning_rate/base': 2.161226681360382e-05, 'epoch': 0.39}) +[2026-07-27 04:57:23,926][starVLA.training.train_starvla][INFO] - Step 3227, Loss: {'train/loss': 0.0739826187491417, 'train/grad_norm_pre_clip': 2.9969754219055176, 'timing/data': 0.00017150910571217537, 'timing/model': 0.463546026032418, 'learning_rate/action_model': 8.64280586162513e-05, 'learning_rate/action_query_proj': 8.64280586162513e-05, 'learning_rate/base': 2.1607014654062826e-05, 'epoch': 0.39}) +[2026-07-27 04:57:29,566][starVLA.training.train_starvla][INFO] - Step 3228, Loss: {'train/loss': 0.1650703102350235, 'train/grad_norm_pre_clip': 5.122146129608154, 'timing/data': 0.00017966795712709427, 'timing/model': 0.4653228987008333, 'learning_rate/action_model': 8.640703638643503e-05, 'learning_rate/action_query_proj': 8.640703638643503e-05, 'learning_rate/base': 2.1601759096608758e-05, 'epoch': 0.39}) +[2026-07-27 04:57:35,457][starVLA.training.train_starvla][INFO] - Step 3229, Loss: {'train/loss': 0.13345570862293243, 'train/grad_norm_pre_clip': 4.343565464019775, 'timing/data': 0.00018408522009849548, 'timing/model': 0.46545660216361284, 'learning_rate/action_model': 8.638600057326569e-05, 'learning_rate/action_query_proj': 8.638600057326569e-05, 'learning_rate/base': 2.1596500143316422e-05, 'epoch': 0.39}) +[2026-07-27 04:57:41,078][starVLA.training.train_starvla][INFO] - Step 3230, Loss: {'train/loss': 0.15617959201335907, 'train/grad_norm_pre_clip': 4.93986701965332, 'timing/data': 0.00017306488007307053, 'timing/model': 0.46222140174359083, 'learning_rate/action_model': 8.63649511850479e-05, 'learning_rate/action_query_proj': 8.63649511850479e-05, 'learning_rate/base': 2.1591237796261974e-05, 'epoch': 0.39}) +[2026-07-27 04:57:46,711][starVLA.training.train_starvla][INFO] - Step 3231, Loss: {'train/loss': 0.13968521356582642, 'train/grad_norm_pre_clip': 4.53883695602417, 'timing/data': 0.00017647212371230125, 'timing/model': 0.4652347583323717, 'learning_rate/action_model': 8.63438882300916e-05, 'learning_rate/action_query_proj': 8.63438882300916e-05, 'learning_rate/base': 2.15859720575229e-05, 'epoch': 0.39}) +[2026-07-27 04:57:52,320][starVLA.training.train_starvla][INFO] - Step 3232, Loss: {'train/loss': 0.08218531310558319, 'train/grad_norm_pre_clip': 2.0636191368103027, 'timing/data': 0.00017515895888209343, 'timing/model': 0.45848766900599003, 'learning_rate/action_model': 8.632281171671215e-05, 'learning_rate/action_query_proj': 8.632281171671215e-05, 'learning_rate/base': 2.1580702929178037e-05, 'epoch': 0.39}) +[2026-07-27 04:57:57,940][starVLA.training.train_starvla][INFO] - Step 3233, Loss: {'train/loss': 0.0954577773809433, 'train/grad_norm_pre_clip': 2.478743314743042, 'timing/data': 0.00018938397988677025, 'timing/model': 0.46306535182520747, 'learning_rate/action_model': 8.630172165323019e-05, 'learning_rate/action_query_proj': 8.630172165323019e-05, 'learning_rate/base': 2.1575430413307547e-05, 'epoch': 0.39}) +[2026-07-27 04:58:03,703][starVLA.training.train_starvla][INFO] - Step 3234, Loss: {'train/loss': 0.22432023286819458, 'train/grad_norm_pre_clip': 3.7974586486816406, 'timing/data': 0.00017940625548362732, 'timing/model': 0.484313793014735, 'learning_rate/action_model': 8.628061804797178e-05, 'learning_rate/action_query_proj': 8.628061804797178e-05, 'learning_rate/base': 2.1570154511992944e-05, 'epoch': 0.39}) +[2026-07-27 04:58:09,369][starVLA.training.train_starvla][INFO] - Step 3235, Loss: {'train/loss': 0.17010217905044556, 'train/grad_norm_pre_clip': 4.136098384857178, 'timing/data': 0.00018469197675585747, 'timing/model': 0.4858983429148793, 'learning_rate/action_model': 8.625950090926824e-05, 'learning_rate/action_query_proj': 8.625950090926824e-05, 'learning_rate/base': 2.156487522731706e-05, 'epoch': 0.39}) +[2026-07-27 04:58:15,042][starVLA.training.train_starvla][INFO] - Step 3236, Loss: {'train/loss': 0.15121786296367645, 'train/grad_norm_pre_clip': 4.6434197425842285, 'timing/data': 0.00020138686522841454, 'timing/model': 0.4649737570434809, 'learning_rate/action_model': 8.623837024545629e-05, 'learning_rate/action_query_proj': 8.623837024545629e-05, 'learning_rate/base': 2.1559592561364073e-05, 'epoch': 0.39}) +[2026-07-27 04:58:20,763][starVLA.training.train_starvla][INFO] - Step 3237, Loss: {'train/loss': 0.11923591047525406, 'train/grad_norm_pre_clip': 3.5832736492156982, 'timing/data': 0.00018023978918790817, 'timing/model': 0.4694263767451048, 'learning_rate/action_model': 8.621722606487803e-05, 'learning_rate/action_query_proj': 8.621722606487803e-05, 'learning_rate/base': 2.1554306516219508e-05, 'epoch': 0.39}) +[2026-07-27 04:58:26,449][starVLA.training.train_starvla][INFO] - Step 3238, Loss: {'train/loss': 0.17751769721508026, 'train/grad_norm_pre_clip': 4.283202648162842, 'timing/data': 0.00017754966393113136, 'timing/model': 0.4630914516746998, 'learning_rate/action_model': 8.61960683758808e-05, 'learning_rate/action_query_proj': 8.61960683758808e-05, 'learning_rate/base': 2.15490170939702e-05, 'epoch': 0.39}) +[2026-07-27 04:58:32,149][starVLA.training.train_starvla][INFO] - Step 3239, Loss: {'train/loss': 0.2285267859697342, 'train/grad_norm_pre_clip': 4.480481147766113, 'timing/data': 0.00017473101615905762, 'timing/model': 0.4661191529594362, 'learning_rate/action_model': 8.617489718681734e-05, 'learning_rate/action_query_proj': 8.617489718681734e-05, 'learning_rate/base': 2.1543724296704336e-05, 'epoch': 0.39}) +[2026-07-27 04:58:37,826][starVLA.training.train_starvla][INFO] - Step 3240, Loss: {'train/loss': 0.09305410832166672, 'train/grad_norm_pre_clip': 3.4476850032806396, 'timing/data': 0.00017528608441352844, 'timing/model': 0.46329370187595487, 'learning_rate/action_model': 8.615371250604571e-05, 'learning_rate/action_query_proj': 8.615371250604571e-05, 'learning_rate/base': 2.153842812651143e-05, 'epoch': 0.39}) +[2026-07-27 04:58:43,528][starVLA.training.train_starvla][INFO] - Step 3241, Loss: {'train/loss': 0.11778441071510315, 'train/grad_norm_pre_clip': 2.7611007690429688, 'timing/data': 0.00018135597929358482, 'timing/model': 0.47003325214609504, 'learning_rate/action_model': 8.613251434192924e-05, 'learning_rate/action_query_proj': 8.613251434192924e-05, 'learning_rate/base': 2.153312858548231e-05, 'epoch': 0.39}) +[2026-07-27 04:58:49,239][starVLA.training.train_starvla][INFO] - Step 3242, Loss: {'train/loss': 0.05641666427254677, 'train/grad_norm_pre_clip': 2.0407841205596924, 'timing/data': 0.00019804062321782112, 'timing/model': 0.46825054520741105, 'learning_rate/action_model': 8.611130270283669e-05, 'learning_rate/action_query_proj': 8.611130270283669e-05, 'learning_rate/base': 2.1527825675709172e-05, 'epoch': 0.39}) +[2026-07-27 04:58:54,949][starVLA.training.train_starvla][INFO] - Step 3243, Loss: {'train/loss': 0.12382536381483078, 'train/grad_norm_pre_clip': 2.381150484085083, 'timing/data': 0.00017205579206347466, 'timing/model': 0.4702842361293733, 'learning_rate/action_model': 8.609007759714206e-05, 'learning_rate/action_query_proj': 8.609007759714206e-05, 'learning_rate/base': 2.1522519399285515e-05, 'epoch': 0.39}) +[2026-07-27 04:59:00,646][starVLA.training.train_starvla][INFO] - Step 3244, Loss: {'train/loss': 0.15868613123893738, 'train/grad_norm_pre_clip': 5.232885360717773, 'timing/data': 0.00017480598762631416, 'timing/model': 0.46232603304088116, 'learning_rate/action_model': 8.606883903322466e-05, 'learning_rate/action_query_proj': 8.606883903322466e-05, 'learning_rate/base': 2.1517209758306164e-05, 'epoch': 0.39}) +[2026-07-27 04:59:06,350][starVLA.training.train_starvla][INFO] - Step 3245, Loss: {'train/loss': 0.042434561997652054, 'train/grad_norm_pre_clip': 1.5868661403656006, 'timing/data': 0.0001735379919409752, 'timing/model': 0.4697199370712042, 'learning_rate/action_model': 8.604758701946915e-05, 'learning_rate/action_query_proj': 8.604758701946915e-05, 'learning_rate/base': 2.1511896754867288e-05, 'epoch': 0.39}) +[2026-07-27 04:59:11,969][starVLA.training.train_starvla][INFO] - Step 3246, Loss: {'train/loss': 0.18718156218528748, 'train/grad_norm_pre_clip': 3.958054542541504, 'timing/data': 0.0001745321787893772, 'timing/model': 0.4616008289158344, 'learning_rate/action_model': 8.60263215642655e-05, 'learning_rate/action_query_proj': 8.60263215642655e-05, 'learning_rate/base': 2.1506580391066374e-05, 'epoch': 0.39}) +[2026-07-27 04:59:17,604][starVLA.training.train_starvla][INFO] - Step 3247, Loss: {'train/loss': 0.10231547802686691, 'train/grad_norm_pre_clip': 3.948617458343506, 'timing/data': 0.00017547793686389923, 'timing/model': 0.4665981628932059, 'learning_rate/action_model': 8.600504267600897e-05, 'learning_rate/action_query_proj': 8.600504267600897e-05, 'learning_rate/base': 2.1501260669002242e-05, 'epoch': 0.39}) +[2026-07-27 04:59:23,228][starVLA.training.train_starvla][INFO] - Step 3248, Loss: {'train/loss': 0.15189750492572784, 'train/grad_norm_pre_clip': 3.8207149505615234, 'timing/data': 0.00017499225214123726, 'timing/model': 0.46305957110598683, 'learning_rate/action_model': 8.598375036310014e-05, 'learning_rate/action_query_proj': 8.598375036310014e-05, 'learning_rate/base': 2.1495937590775035e-05, 'epoch': 0.39}) +[2026-07-27 04:59:28,920][starVLA.training.train_starvla][INFO] - Step 3249, Loss: {'train/loss': 0.1348356008529663, 'train/grad_norm_pre_clip': 4.459719181060791, 'timing/data': 0.00020035495981574059, 'timing/model': 0.4672919721342623, 'learning_rate/action_model': 8.596244463394486e-05, 'learning_rate/action_query_proj': 8.596244463394486e-05, 'learning_rate/base': 2.1490611158486214e-05, 'epoch': 0.39}) +[2026-07-27 04:59:34,562][starVLA.training.train_starvla][INFO] - Step 3250, Loss: {'train/loss': 0.14373677968978882, 'train/grad_norm_pre_clip': 3.712171792984009, 'timing/data': 0.00022513233125209808, 'timing/model': 0.4646181473508477, 'learning_rate/action_model': 8.594112549695428e-05, 'learning_rate/action_query_proj': 8.594112549695428e-05, 'learning_rate/base': 2.148528137423857e-05, 'epoch': 0.39}) +[2026-07-27 04:59:40,238][starVLA.training.train_starvla][INFO] - Step 3251, Loss: {'train/loss': 0.019503630697727203, 'train/grad_norm_pre_clip': 1.0980170965194702, 'timing/data': 0.00017828401178121567, 'timing/model': 0.4659859468229115, 'learning_rate/action_model': 8.591979296054491e-05, 'learning_rate/action_query_proj': 8.591979296054491e-05, 'learning_rate/base': 2.1479948240136228e-05, 'epoch': 0.39}) +[2026-07-27 04:59:46,071][starVLA.training.train_starvla][INFO] - Step 3252, Loss: {'train/loss': 0.07003223150968552, 'train/grad_norm_pre_clip': 2.3111205101013184, 'timing/data': 0.0001762942411005497, 'timing/model': 0.46808687085285783, 'learning_rate/action_model': 8.589844703313844e-05, 'learning_rate/action_query_proj': 8.589844703313844e-05, 'learning_rate/base': 2.147461175828461e-05, 'epoch': 0.39}) +[2026-07-27 04:59:51,685][starVLA.training.train_starvla][INFO] - Step 3253, Loss: {'train/loss': 0.21043840050697327, 'train/grad_norm_pre_clip': 5.580310344696045, 'timing/data': 0.00017147371545433998, 'timing/model': 0.4630384212359786, 'learning_rate/action_model': 8.587708772316194e-05, 'learning_rate/action_query_proj': 8.587708772316194e-05, 'learning_rate/base': 2.1469271930790484e-05, 'epoch': 0.39}) +[2026-07-27 04:59:57,328][starVLA.training.train_starvla][INFO] - Step 3254, Loss: {'train/loss': 0.2752070426940918, 'train/grad_norm_pre_clip': 7.1420769691467285, 'timing/data': 0.00018820911645889282, 'timing/model': 0.46677184803411365, 'learning_rate/action_model': 8.58557150390477e-05, 'learning_rate/action_query_proj': 8.58557150390477e-05, 'learning_rate/base': 2.1463928759761926e-05, 'epoch': 0.39}) +[2026-07-27 05:00:02,978][starVLA.training.train_starvla][INFO] - Step 3255, Loss: {'train/loss': 0.15230047702789307, 'train/grad_norm_pre_clip': 4.607149600982666, 'timing/data': 0.00017563998699188232, 'timing/model': 0.46520052291452885, 'learning_rate/action_model': 8.583432898923335e-05, 'learning_rate/action_query_proj': 8.583432898923335e-05, 'learning_rate/base': 2.1458582247308337e-05, 'epoch': 0.39}) +[2026-07-27 05:00:08,614][starVLA.training.train_starvla][INFO] - Step 3256, Loss: {'train/loss': 0.16111360490322113, 'train/grad_norm_pre_clip': 5.0028276443481445, 'timing/data': 0.00017325719818472862, 'timing/model': 0.46627663308754563, 'learning_rate/action_model': 8.581292958216175e-05, 'learning_rate/action_query_proj': 8.581292958216175e-05, 'learning_rate/base': 2.1453232395540436e-05, 'epoch': 0.39}) +[2026-07-27 05:00:14,248][starVLA.training.train_starvla][INFO] - Step 3257, Loss: {'train/loss': 0.13152514398097992, 'train/grad_norm_pre_clip': 3.368605375289917, 'timing/data': 0.00017228908836841583, 'timing/model': 0.4630396072752774, 'learning_rate/action_model': 8.579151682628104e-05, 'learning_rate/action_query_proj': 8.579151682628104e-05, 'learning_rate/base': 2.144787920657026e-05, 'epoch': 0.4}) +[2026-07-27 05:00:19,909][starVLA.training.train_starvla][INFO] - Step 3258, Loss: {'train/loss': 0.1649022251367569, 'train/grad_norm_pre_clip': 5.072504043579102, 'timing/data': 0.00017830077558755875, 'timing/model': 0.46371664898470044, 'learning_rate/action_model': 8.577009073004464e-05, 'learning_rate/action_query_proj': 8.577009073004464e-05, 'learning_rate/base': 2.144252268251116e-05, 'epoch': 0.4}) +[2026-07-27 05:00:25,569][starVLA.training.train_starvla][INFO] - Step 3259, Loss: {'train/loss': 0.10438023507595062, 'train/grad_norm_pre_clip': 2.8042781352996826, 'timing/data': 0.0001734718680381775, 'timing/model': 0.4640429951250553, 'learning_rate/action_model': 8.574865130191123e-05, 'learning_rate/action_query_proj': 8.574865130191123e-05, 'learning_rate/base': 2.1437162825477807e-05, 'epoch': 0.4}) +[2026-07-27 05:00:31,226][starVLA.training.train_starvla][INFO] - Step 3260, Loss: {'train/loss': 0.10479871928691864, 'train/grad_norm_pre_clip': 4.223623752593994, 'timing/data': 0.00017643999308347702, 'timing/model': 0.4662005319260061, 'learning_rate/action_model': 8.572719855034477e-05, 'learning_rate/action_query_proj': 8.572719855034477e-05, 'learning_rate/base': 2.1431799637586193e-05, 'epoch': 0.4}) +[2026-07-27 05:00:36,887][starVLA.training.train_starvla][INFO] - Step 3261, Loss: {'train/loss': 0.10609932243824005, 'train/grad_norm_pre_clip': 3.778029203414917, 'timing/data': 0.000184524804353714, 'timing/model': 0.4779942878521979, 'learning_rate/action_model': 8.570573248381445e-05, 'learning_rate/action_query_proj': 8.570573248381445e-05, 'learning_rate/base': 2.1426433120953614e-05, 'epoch': 0.4}) +[2026-07-27 05:00:42,528][starVLA.training.train_starvla][INFO] - Step 3262, Loss: {'train/loss': 0.13824720680713654, 'train/grad_norm_pre_clip': 3.7301809787750244, 'timing/data': 0.00017822114750742912, 'timing/model': 0.4696599538438022, 'learning_rate/action_model': 8.568425311079475e-05, 'learning_rate/action_query_proj': 8.568425311079475e-05, 'learning_rate/base': 2.1421063277698687e-05, 'epoch': 0.4}) +[2026-07-27 05:00:48,188][starVLA.training.train_starvla][INFO] - Step 3263, Loss: {'train/loss': 0.12264454364776611, 'train/grad_norm_pre_clip': 2.9101099967956543, 'timing/data': 0.00018812110647559166, 'timing/model': 0.47438149666413665, 'learning_rate/action_model': 8.566276043976536e-05, 'learning_rate/action_query_proj': 8.566276043976536e-05, 'learning_rate/base': 2.141569010994134e-05, 'epoch': 0.4}) +[2026-07-27 05:00:53,834][starVLA.training.train_starvla][INFO] - Step 3264, Loss: {'train/loss': 0.15476344525814056, 'train/grad_norm_pre_clip': 4.673318386077881, 'timing/data': 0.00018097413703799248, 'timing/model': 0.4729329156689346, 'learning_rate/action_model': 8.564125447921129e-05, 'learning_rate/action_query_proj': 8.564125447921129e-05, 'learning_rate/base': 2.1410313619802823e-05, 'epoch': 0.4}) +[2026-07-27 05:00:59,497][starVLA.training.train_starvla][INFO] - Step 3265, Loss: {'train/loss': 0.12038955837488174, 'train/grad_norm_pre_clip': 3.3655478954315186, 'timing/data': 0.00017825793474912643, 'timing/model': 0.46877627074718475, 'learning_rate/action_model': 8.56197352376227e-05, 'learning_rate/action_query_proj': 8.56197352376227e-05, 'learning_rate/base': 2.1404933809405676e-05, 'epoch': 0.4}) +[2026-07-27 05:01:05,134][starVLA.training.train_starvla][INFO] - Step 3266, Loss: {'train/loss': 0.10491585731506348, 'train/grad_norm_pre_clip': 3.3727736473083496, 'timing/data': 0.00017379503697156906, 'timing/model': 0.46889346186071634, 'learning_rate/action_model': 8.55982027234951e-05, 'learning_rate/action_query_proj': 8.55982027234951e-05, 'learning_rate/base': 2.1399550680873775e-05, 'epoch': 0.4}) +[2026-07-27 05:01:10,787][starVLA.training.train_starvla][INFO] - Step 3267, Loss: {'train/loss': 0.21701182425022125, 'train/grad_norm_pre_clip': 4.65149450302124, 'timing/data': 0.00018200231716036797, 'timing/model': 0.468066206201911, 'learning_rate/action_model': 8.557665694532913e-05, 'learning_rate/action_query_proj': 8.557665694532913e-05, 'learning_rate/base': 2.1394164236332283e-05, 'epoch': 0.4}) +[2026-07-27 05:01:16,427][starVLA.training.train_starvla][INFO] - Step 3268, Loss: {'train/loss': 0.12739260494709015, 'train/grad_norm_pre_clip': 3.8230929374694824, 'timing/data': 0.00017505092546343803, 'timing/model': 0.4701638272963464, 'learning_rate/action_model': 8.555509791163078e-05, 'learning_rate/action_query_proj': 8.555509791163078e-05, 'learning_rate/base': 2.1388774477907695e-05, 'epoch': 0.4}) +[2026-07-27 05:01:22,049][starVLA.training.train_starvla][INFO] - Step 3269, Loss: {'train/loss': 0.0885479524731636, 'train/grad_norm_pre_clip': 2.5470409393310547, 'timing/data': 0.00017463462427258492, 'timing/model': 0.47250223672017455, 'learning_rate/action_model': 8.553352563091116e-05, 'learning_rate/action_query_proj': 8.553352563091116e-05, 'learning_rate/base': 2.138338140772779e-05, 'epoch': 0.4}) +[2026-07-27 05:01:27,703][starVLA.training.train_starvla][INFO] - Step 3270, Loss: {'train/loss': 0.0862806886434555, 'train/grad_norm_pre_clip': 2.7165701389312744, 'timing/data': 0.0001741582527756691, 'timing/model': 0.46624642610549927, 'learning_rate/action_model': 8.55119401116867e-05, 'learning_rate/action_query_proj': 8.55119401116867e-05, 'learning_rate/base': 2.1377985027921675e-05, 'epoch': 0.4}) +[2026-07-27 05:01:33,359][starVLA.training.train_starvla][INFO] - Step 3271, Loss: {'train/loss': 0.08570565283298492, 'train/grad_norm_pre_clip': 2.6545023918151855, 'timing/data': 0.00017760787159204483, 'timing/model': 0.46922363108024, 'learning_rate/action_model': 8.549034136247901e-05, 'learning_rate/action_query_proj': 8.549034136247901e-05, 'learning_rate/base': 2.1372585340619753e-05, 'epoch': 0.4}) +[2026-07-27 05:01:38,988][starVLA.training.train_starvla][INFO] - Step 3272, Loss: {'train/loss': 0.09206515550613403, 'train/grad_norm_pre_clip': 3.535620927810669, 'timing/data': 0.00017555616796016693, 'timing/model': 0.4672026210464537, 'learning_rate/action_model': 8.546872939181492e-05, 'learning_rate/action_query_proj': 8.546872939181492e-05, 'learning_rate/base': 2.136718234795373e-05, 'epoch': 0.4}) +[2026-07-27 05:01:44,636][starVLA.training.train_starvla][INFO] - Step 3273, Loss: {'train/loss': 0.11028626561164856, 'train/grad_norm_pre_clip': 2.9976742267608643, 'timing/data': 0.00018083397299051285, 'timing/model': 0.4691053102724254, 'learning_rate/action_model': 8.544710420822653e-05, 'learning_rate/action_query_proj': 8.544710420822653e-05, 'learning_rate/base': 2.1361776052056633e-05, 'epoch': 0.4}) +[2026-07-27 05:01:50,547][starVLA.training.train_starvla][INFO] - Step 3274, Loss: {'train/loss': 0.1323527991771698, 'train/grad_norm_pre_clip': 2.9796786308288574, 'timing/data': 0.00017844978719949722, 'timing/model': 0.46732682874426246, 'learning_rate/action_model': 8.542546582025108e-05, 'learning_rate/action_query_proj': 8.542546582025108e-05, 'learning_rate/base': 2.135636645506277e-05, 'epoch': 0.4}) +[2026-07-27 05:01:56,211][starVLA.training.train_starvla][INFO] - Step 3275, Loss: {'train/loss': 0.16942475736141205, 'train/grad_norm_pre_clip': 3.917395830154419, 'timing/data': 0.00017888983711600304, 'timing/model': 0.46999925188720226, 'learning_rate/action_model': 8.54038142364311e-05, 'learning_rate/action_query_proj': 8.54038142364311e-05, 'learning_rate/base': 2.1350953559107774e-05, 'epoch': 0.4}) +[2026-07-27 05:02:01,955][starVLA.training.train_starvla][INFO] - Step 3276, Loss: {'train/loss': 0.11943195760250092, 'train/grad_norm_pre_clip': 2.4972846508026123, 'timing/data': 0.00017657596617937088, 'timing/model': 0.47256892174482346, 'learning_rate/action_model': 8.538214946531426e-05, 'learning_rate/action_query_proj': 8.538214946531426e-05, 'learning_rate/base': 2.1345537366328565e-05, 'epoch': 0.4}) +[2026-07-27 05:02:07,616][starVLA.training.train_starvla][INFO] - Step 3277, Loss: {'train/loss': 0.1901298463344574, 'train/grad_norm_pre_clip': 4.537492752075195, 'timing/data': 0.00017536478117108345, 'timing/model': 0.46773686027154326, 'learning_rate/action_model': 8.53604715154535e-05, 'learning_rate/action_query_proj': 8.53604715154535e-05, 'learning_rate/base': 2.1340117878863374e-05, 'epoch': 0.4}) +[2026-07-27 05:02:13,286][starVLA.training.train_starvla][INFO] - Step 3278, Loss: {'train/loss': 0.12646512687206268, 'train/grad_norm_pre_clip': 4.083923816680908, 'timing/data': 0.00018191616982221603, 'timing/model': 0.4692953177727759, 'learning_rate/action_model': 8.53387803954069e-05, 'learning_rate/action_query_proj': 8.53387803954069e-05, 'learning_rate/base': 2.1334695098851724e-05, 'epoch': 0.4}) +[2026-07-27 05:02:19,199][starVLA.training.train_starvla][INFO] - Step 3279, Loss: {'train/loss': 0.09595441818237305, 'train/grad_norm_pre_clip': 2.499723196029663, 'timing/data': 0.00018395716324448586, 'timing/model': 0.7040577330626547, 'learning_rate/action_model': 8.531707611373776e-05, 'learning_rate/action_query_proj': 8.531707611373776e-05, 'learning_rate/base': 2.132926902843444e-05, 'epoch': 0.4}) +[2026-07-27 05:02:25,132][starVLA.training.train_starvla][INFO] - Step 3280, Loss: {'train/loss': 0.17255672812461853, 'train/grad_norm_pre_clip': 3.4514689445495605, 'timing/data': 0.00018772901967167854, 'timing/model': 0.4698624680750072, 'learning_rate/action_model': 8.529535867901463e-05, 'learning_rate/action_query_proj': 8.529535867901463e-05, 'learning_rate/base': 2.1323839669753658e-05, 'epoch': 0.4}) +[2026-07-27 05:02:30,782][starVLA.training.train_starvla][INFO] - Step 3281, Loss: {'train/loss': 0.07523512095212936, 'train/grad_norm_pre_clip': 3.0950756072998047, 'timing/data': 0.00018352409824728966, 'timing/model': 0.4685951774008572, 'learning_rate/action_model': 8.527362809981121e-05, 'learning_rate/action_query_proj': 8.527362809981121e-05, 'learning_rate/base': 2.1318407024952803e-05, 'epoch': 0.4}) +[2026-07-27 05:02:36,450][starVLA.training.train_starvla][INFO] - Step 3282, Loss: {'train/loss': 0.08680297434329987, 'train/grad_norm_pre_clip': 3.1745870113372803, 'timing/data': 0.00017773965373635292, 'timing/model': 0.4698269860818982, 'learning_rate/action_model': 8.525188438470636e-05, 'learning_rate/action_query_proj': 8.525188438470636e-05, 'learning_rate/base': 2.131297109617659e-05, 'epoch': 0.4}) +[2026-07-27 05:02:42,132][starVLA.training.train_starvla][INFO] - Step 3283, Loss: {'train/loss': 0.1428215503692627, 'train/grad_norm_pre_clip': 4.845941543579102, 'timing/data': 0.00017535081133246422, 'timing/model': 0.46854585129767656, 'learning_rate/action_model': 8.523012754228416e-05, 'learning_rate/action_query_proj': 8.523012754228416e-05, 'learning_rate/base': 2.130753188557104e-05, 'epoch': 0.4}) +[2026-07-27 05:02:47,785][starVLA.training.train_starvla][INFO] - Step 3284, Loss: {'train/loss': 0.09096281230449677, 'train/grad_norm_pre_clip': 2.4310970306396484, 'timing/data': 0.00018454203382134438, 'timing/model': 0.46878124168142676, 'learning_rate/action_model': 8.520835758113385e-05, 'learning_rate/action_query_proj': 8.520835758113385e-05, 'learning_rate/base': 2.1302089395283463e-05, 'epoch': 0.4}) +[2026-07-27 05:02:53,439][starVLA.training.train_starvla][INFO] - Step 3285, Loss: {'train/loss': 0.11847162246704102, 'train/grad_norm_pre_clip': 3.5368595123291016, 'timing/data': 0.00017691496759653091, 'timing/model': 0.466052059084177, 'learning_rate/action_model': 8.518657450984991e-05, 'learning_rate/action_query_proj': 8.518657450984991e-05, 'learning_rate/base': 2.1296643627462478e-05, 'epoch': 0.4}) +[2026-07-27 05:02:59,352][starVLA.training.train_starvla][INFO] - Step 3286, Loss: {'train/loss': 0.1969156712293625, 'train/grad_norm_pre_clip': 4.121633529663086, 'timing/data': 0.0001759096048772335, 'timing/model': 0.4638433689251542, 'learning_rate/action_model': 8.516477833703192e-05, 'learning_rate/action_query_proj': 8.516477833703192e-05, 'learning_rate/base': 2.129119458425798e-05, 'epoch': 0.4}) +[2026-07-27 05:03:04,973][starVLA.training.train_starvla][INFO] - Step 3287, Loss: {'train/loss': 0.03068206086754799, 'train/grad_norm_pre_clip': 1.4747949838638306, 'timing/data': 0.00017497502267360687, 'timing/model': 0.4656326239928603, 'learning_rate/action_model': 8.514296907128468e-05, 'learning_rate/action_query_proj': 8.514296907128468e-05, 'learning_rate/base': 2.128574226782117e-05, 'epoch': 0.4}) +[2026-07-27 05:03:10,578][starVLA.training.train_starvla][INFO] - Step 3288, Loss: {'train/loss': 0.07849248498678207, 'train/grad_norm_pre_clip': 3.176034688949585, 'timing/data': 0.00017539924010634422, 'timing/model': 0.4618727806955576, 'learning_rate/action_model': 8.512114672121813e-05, 'learning_rate/action_query_proj': 8.512114672121813e-05, 'learning_rate/base': 2.1280286680304532e-05, 'epoch': 0.4}) +[2026-07-27 05:03:16,216][starVLA.training.train_starvla][INFO] - Step 3289, Loss: {'train/loss': 0.10212834179401398, 'train/grad_norm_pre_clip': 3.4047694206237793, 'timing/data': 0.00017534522339701653, 'timing/model': 0.46275986498221755, 'learning_rate/action_model': 8.509931129544739e-05, 'learning_rate/action_query_proj': 8.509931129544739e-05, 'learning_rate/base': 2.1274827823861848e-05, 'epoch': 0.4}) +[2026-07-27 05:03:21,825][starVLA.training.train_starvla][INFO] - Step 3290, Loss: {'train/loss': 0.08943655341863632, 'train/grad_norm_pre_clip': 3.4998390674591064, 'timing/data': 0.00017779599875211716, 'timing/model': 0.45860310923308134, 'learning_rate/action_model': 8.507746280259273e-05, 'learning_rate/action_query_proj': 8.507746280259273e-05, 'learning_rate/base': 2.1269365700648182e-05, 'epoch': 0.4}) +[2026-07-27 05:03:27,465][starVLA.training.train_starvla][INFO] - Step 3291, Loss: {'train/loss': 0.150135800242424, 'train/grad_norm_pre_clip': 5.416585922241211, 'timing/data': 0.0001744949258863926, 'timing/model': 0.4667391749098897, 'learning_rate/action_model': 8.505560125127962e-05, 'learning_rate/action_query_proj': 8.505560125127962e-05, 'learning_rate/base': 2.1263900312819904e-05, 'epoch': 0.4}) +[2026-07-27 05:03:33,079][starVLA.training.train_starvla][INFO] - Step 3292, Loss: {'train/loss': 0.12055467069149017, 'train/grad_norm_pre_clip': 3.1481258869171143, 'timing/data': 0.0001714630052447319, 'timing/model': 0.46446464071050286, 'learning_rate/action_model': 8.503372665013862e-05, 'learning_rate/action_query_proj': 8.503372665013862e-05, 'learning_rate/base': 2.1258431662534654e-05, 'epoch': 0.4}) +[2026-07-27 05:03:38,705][starVLA.training.train_starvla][INFO] - Step 3293, Loss: {'train/loss': 0.08923216164112091, 'train/grad_norm_pre_clip': 2.8200879096984863, 'timing/data': 0.00017668073996901512, 'timing/model': 0.46568658761680126, 'learning_rate/action_model': 8.501183900780551e-05, 'learning_rate/action_query_proj': 8.501183900780551e-05, 'learning_rate/base': 2.1252959751951377e-05, 'epoch': 0.4}) +[2026-07-27 05:03:44,310][starVLA.training.train_starvla][INFO] - Step 3294, Loss: {'train/loss': 0.050977449864149094, 'train/grad_norm_pre_clip': 2.399763822555542, 'timing/data': 0.00017444277182221413, 'timing/model': 0.4677160498686135, 'learning_rate/action_model': 8.498993833292115e-05, 'learning_rate/action_query_proj': 8.498993833292115e-05, 'learning_rate/base': 2.1247484583230288e-05, 'epoch': 0.4}) +[2026-07-27 05:03:49,928][starVLA.training.train_starvla][INFO] - Step 3295, Loss: {'train/loss': 0.18422657251358032, 'train/grad_norm_pre_clip': 5.396913528442383, 'timing/data': 0.00017423275858163834, 'timing/model': 0.46431325376033783, 'learning_rate/action_model': 8.49680246341316e-05, 'learning_rate/action_query_proj': 8.49680246341316e-05, 'learning_rate/base': 2.12420061585329e-05, 'epoch': 0.4}) +[2026-07-27 05:03:55,533][starVLA.training.train_starvla][INFO] - Step 3296, Loss: {'train/loss': 0.06467150896787643, 'train/grad_norm_pre_clip': 2.685730218887329, 'timing/data': 0.00018235854804515839, 'timing/model': 0.46711264085024595, 'learning_rate/action_model': 8.494609792008804e-05, 'learning_rate/action_query_proj': 8.494609792008804e-05, 'learning_rate/base': 2.123652448002201e-05, 'epoch': 0.4}) +[2026-07-27 05:04:01,152][starVLA.training.train_starvla][INFO] - Step 3297, Loss: {'train/loss': 0.0661083236336708, 'train/grad_norm_pre_clip': 2.937713146209717, 'timing/data': 0.00018363865092396736, 'timing/model': 0.45690086111426353, 'learning_rate/action_model': 8.492415819944678e-05, 'learning_rate/action_query_proj': 8.492415819944678e-05, 'learning_rate/base': 2.1231039549861694e-05, 'epoch': 0.4}) +[2026-07-27 05:04:06,738][starVLA.training.train_starvla][INFO] - Step 3298, Loss: {'train/loss': 0.09211964905261993, 'train/grad_norm_pre_clip': 3.117217540740967, 'timing/data': 0.00017579598352313042, 'timing/model': 0.4585531488992274, 'learning_rate/action_model': 8.49022054808693e-05, 'learning_rate/action_query_proj': 8.49022054808693e-05, 'learning_rate/base': 2.1225551370217323e-05, 'epoch': 0.4}) +[2026-07-27 05:04:12,362][starVLA.training.train_starvla][INFO] - Step 3299, Loss: {'train/loss': 0.041526004672050476, 'train/grad_norm_pre_clip': 1.697417974472046, 'timing/data': 0.00017626909539103508, 'timing/model': 0.4639224400743842, 'learning_rate/action_model': 8.488023977302216e-05, 'learning_rate/action_query_proj': 8.488023977302216e-05, 'learning_rate/base': 2.122005994325554e-05, 'epoch': 0.4}) +[2026-07-27 05:04:17,976][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 3300 +[2026-07-27 05:04:17,977][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 3300 +[2026-07-27 05:04:17,978][starVLA.training.train_starvla][INFO] - Step 3300, Loss: {'train/loss': 0.05145113915205002, 'train/grad_norm_pre_clip': 2.110666275024414, 'timing/data': 0.00017654569819569588, 'timing/model': 0.4680853341706097, 'learning_rate/action_model': 8.485826108457706e-05, 'learning_rate/action_query_proj': 8.485826108457706e-05, 'learning_rate/base': 2.1214565271144265e-05, 'epoch': 0.4}) +[2026-07-27 05:04:23,604][starVLA.training.train_starvla][INFO] - Step 3301, Loss: {'train/loss': 0.09071221202611923, 'train/grad_norm_pre_clip': 4.186703681945801, 'timing/data': 0.00017699925228953362, 'timing/model': 0.4625843861140311, 'learning_rate/action_model': 8.483626942421087e-05, 'learning_rate/action_query_proj': 8.483626942421087e-05, 'learning_rate/base': 2.1209067356052718e-05, 'epoch': 0.4}) +[2026-07-27 05:04:29,224][starVLA.training.train_starvla][INFO] - Step 3302, Loss: {'train/loss': 0.12416243553161621, 'train/grad_norm_pre_clip': 3.0027964115142822, 'timing/data': 0.00018520141020417213, 'timing/model': 0.4626762089319527, 'learning_rate/action_model': 8.481426480060553e-05, 'learning_rate/action_query_proj': 8.481426480060553e-05, 'learning_rate/base': 2.1203566200151383e-05, 'epoch': 0.4}) +[2026-07-27 05:04:34,864][starVLA.training.train_starvla][INFO] - Step 3303, Loss: {'train/loss': 0.11403129249811172, 'train/grad_norm_pre_clip': 3.7823445796966553, 'timing/data': 0.0001781722530722618, 'timing/model': 0.46735600801184773, 'learning_rate/action_model': 8.479224722244814e-05, 'learning_rate/action_query_proj': 8.479224722244814e-05, 'learning_rate/base': 2.1198061805612036e-05, 'epoch': 0.4}) +[2026-07-27 05:04:40,465][starVLA.training.train_starvla][INFO] - Step 3304, Loss: {'train/loss': 0.18684172630310059, 'train/grad_norm_pre_clip': 4.5594048500061035, 'timing/data': 0.00017474079504609108, 'timing/model': 0.4665789077989757, 'learning_rate/action_model': 8.477021669843088e-05, 'learning_rate/action_query_proj': 8.477021669843088e-05, 'learning_rate/base': 2.119255417460772e-05, 'epoch': 0.4}) +[2026-07-27 05:04:46,096][starVLA.training.train_starvla][INFO] - Step 3305, Loss: {'train/loss': 0.11946706473827362, 'train/grad_norm_pre_clip': 3.9047842025756836, 'timing/data': 0.00017280969768762589, 'timing/model': 0.4662858550436795, 'learning_rate/action_model': 8.474817323725104e-05, 'learning_rate/action_query_proj': 8.474817323725104e-05, 'learning_rate/base': 2.118704330931276e-05, 'epoch': 0.4}) +[2026-07-27 05:04:51,718][starVLA.training.train_starvla][INFO] - Step 3306, Loss: {'train/loss': 0.17374785244464874, 'train/grad_norm_pre_clip': 3.6159963607788086, 'timing/data': 0.0001748260110616684, 'timing/model': 0.46349580213427544, 'learning_rate/action_model': 8.472611684761103e-05, 'learning_rate/action_query_proj': 8.472611684761103e-05, 'learning_rate/base': 2.1181529211902757e-05, 'epoch': 0.4}) +[2026-07-27 05:04:57,376][starVLA.training.train_starvla][INFO] - Step 3307, Loss: {'train/loss': 0.15218231081962585, 'train/grad_norm_pre_clip': 4.889675617218018, 'timing/data': 0.00017719995230436325, 'timing/model': 0.4785392670892179, 'learning_rate/action_model': 8.470404753821836e-05, 'learning_rate/action_query_proj': 8.470404753821836e-05, 'learning_rate/base': 2.117601188455459e-05, 'epoch': 0.4}) +[2026-07-27 05:05:03,028][starVLA.training.train_starvla][INFO] - Step 3308, Loss: {'train/loss': 0.06508424133062363, 'train/grad_norm_pre_clip': 3.162785053253174, 'timing/data': 0.00017664115875959396, 'timing/model': 0.4695261069573462, 'learning_rate/action_model': 8.468196531778568e-05, 'learning_rate/action_query_proj': 8.468196531778568e-05, 'learning_rate/base': 2.117049132944642e-05, 'epoch': 0.4}) +[2026-07-27 05:05:08,695][starVLA.training.train_starvla][INFO] - Step 3309, Loss: {'train/loss': 0.14429278671741486, 'train/grad_norm_pre_clip': 3.6802818775177, 'timing/data': 0.00017340108752250671, 'timing/model': 0.47779232915490866, 'learning_rate/action_model': 8.465987019503066e-05, 'learning_rate/action_query_proj': 8.465987019503066e-05, 'learning_rate/base': 2.1164967548757665e-05, 'epoch': 0.4}) +[2026-07-27 05:05:14,350][starVLA.training.train_starvla][INFO] - Step 3310, Loss: {'train/loss': 0.096443310379982, 'train/grad_norm_pre_clip': 3.3380813598632812, 'timing/data': 0.00017558876425027847, 'timing/model': 0.47162318602204323, 'learning_rate/action_model': 8.463776217867613e-05, 'learning_rate/action_query_proj': 8.463776217867613e-05, 'learning_rate/base': 2.115944054466903e-05, 'epoch': 0.4}) +[2026-07-27 05:05:19,992][starVLA.training.train_starvla][INFO] - Step 3311, Loss: {'train/loss': 0.07506217062473297, 'train/grad_norm_pre_clip': 2.709185838699341, 'timing/data': 0.000180813018232584, 'timing/model': 0.46800830587744713, 'learning_rate/action_model': 8.461564127744998e-05, 'learning_rate/action_query_proj': 8.461564127744998e-05, 'learning_rate/base': 2.1153910319362495e-05, 'epoch': 0.4}) +[2026-07-27 05:05:25,634][starVLA.training.train_starvla][INFO] - Step 3312, Loss: {'train/loss': 0.1411094069480896, 'train/grad_norm_pre_clip': 3.701918125152588, 'timing/data': 0.0001741340383887291, 'timing/model': 0.4720770069397986, 'learning_rate/action_model': 8.459350750008515e-05, 'learning_rate/action_query_proj': 8.459350750008515e-05, 'learning_rate/base': 2.1148376875021288e-05, 'epoch': 0.4}) +[2026-07-27 05:05:31,287][starVLA.training.train_starvla][INFO] - Step 3313, Loss: {'train/loss': 0.2767281234264374, 'train/grad_norm_pre_clip': 4.55227518081665, 'timing/data': 0.0001813489943742752, 'timing/model': 0.47030111867934465, 'learning_rate/action_model': 8.457136085531977e-05, 'learning_rate/action_query_proj': 8.457136085531977e-05, 'learning_rate/base': 2.1142840213829944e-05, 'epoch': 0.4}) +[2026-07-27 05:05:36,915][starVLA.training.train_starvla][INFO] - Step 3314, Loss: {'train/loss': 0.051057420670986176, 'train/grad_norm_pre_clip': 2.6462113857269287, 'timing/data': 0.00019065290689468384, 'timing/model': 0.46579537726938725, 'learning_rate/action_model': 8.454920135189694e-05, 'learning_rate/action_query_proj': 8.454920135189694e-05, 'learning_rate/base': 2.1137300337974235e-05, 'epoch': 0.4}) +[2026-07-27 05:05:42,543][starVLA.training.train_starvla][INFO] - Step 3315, Loss: {'train/loss': 0.029875777661800385, 'train/grad_norm_pre_clip': 1.5230646133422852, 'timing/data': 0.0002522519789636135, 'timing/model': 0.4641492529772222, 'learning_rate/action_model': 8.452702899856491e-05, 'learning_rate/action_query_proj': 8.452702899856491e-05, 'learning_rate/base': 2.113175724964123e-05, 'epoch': 0.4}) +[2026-07-27 05:05:48,177][starVLA.training.train_starvla][INFO] - Step 3316, Loss: {'train/loss': 0.12744037806987762, 'train/grad_norm_pre_clip': 3.8010988235473633, 'timing/data': 0.00017393240705132484, 'timing/model': 0.4665594408288598, 'learning_rate/action_model': 8.450484380407696e-05, 'learning_rate/action_query_proj': 8.450484380407696e-05, 'learning_rate/base': 2.112621095101924e-05, 'epoch': 0.4}) +[2026-07-27 05:05:53,811][starVLA.training.train_starvla][INFO] - Step 3317, Loss: {'train/loss': 0.06482771784067154, 'train/grad_norm_pre_clip': 1.4907934665679932, 'timing/data': 0.00017147604376077652, 'timing/model': 0.4629346248693764, 'learning_rate/action_model': 8.448264577719146e-05, 'learning_rate/action_query_proj': 8.448264577719146e-05, 'learning_rate/base': 2.1120661444297864e-05, 'epoch': 0.4}) +[2026-07-27 05:05:59,448][starVLA.training.train_starvla][INFO] - Step 3318, Loss: {'train/loss': 0.14407460391521454, 'train/grad_norm_pre_clip': 3.658006429672241, 'timing/data': 0.0001764749176800251, 'timing/model': 0.46633847802877426, 'learning_rate/action_model': 8.446043492667181e-05, 'learning_rate/action_query_proj': 8.446043492667181e-05, 'learning_rate/base': 2.1115108731667953e-05, 'epoch': 0.4}) +[2026-07-27 05:06:05,091][starVLA.training.train_starvla][INFO] - Step 3319, Loss: {'train/loss': 0.09405854344367981, 'train/grad_norm_pre_clip': 3.787843942642212, 'timing/data': 0.0001727449707686901, 'timing/model': 0.46184052899479866, 'learning_rate/action_model': 8.443821126128655e-05, 'learning_rate/action_query_proj': 8.443821126128655e-05, 'learning_rate/base': 2.1109552815321637e-05, 'epoch': 0.4}) +[2026-07-27 05:06:10,725][starVLA.training.train_starvla][INFO] - Step 3320, Loss: {'train/loss': 0.13150714337825775, 'train/grad_norm_pre_clip': 3.6199681758880615, 'timing/data': 0.00017529912292957306, 'timing/model': 0.46613180497661233, 'learning_rate/action_model': 8.441597478980917e-05, 'learning_rate/action_query_proj': 8.441597478980917e-05, 'learning_rate/base': 2.1103993697452293e-05, 'epoch': 0.4}) +[2026-07-27 05:06:16,358][starVLA.training.train_starvla][INFO] - Step 3321, Loss: {'train/loss': 0.16086797416210175, 'train/grad_norm_pre_clip': 5.120069980621338, 'timing/data': 0.00017540762200951576, 'timing/model': 0.4641501549631357, 'learning_rate/action_model': 8.439372552101833e-05, 'learning_rate/action_query_proj': 8.439372552101833e-05, 'learning_rate/base': 2.1098431380254584e-05, 'epoch': 0.4}) +[2026-07-27 05:06:21,980][starVLA.training.train_starvla][INFO] - Step 3322, Loss: {'train/loss': 0.1081380844116211, 'train/grad_norm_pre_clip': 3.5491647720336914, 'timing/data': 0.00017639994621276855, 'timing/model': 0.4671609620563686, 'learning_rate/action_model': 8.437146346369769e-05, 'learning_rate/action_query_proj': 8.437146346369769e-05, 'learning_rate/base': 2.109286586592442e-05, 'epoch': 0.4}) +[2026-07-27 05:06:27,662][starVLA.training.train_starvla][INFO] - Step 3323, Loss: {'train/loss': 0.08831188827753067, 'train/grad_norm_pre_clip': 3.723940134048462, 'timing/data': 0.00017588818445801735, 'timing/model': 0.4702035221271217, 'learning_rate/action_model': 8.434918862663593e-05, 'learning_rate/action_query_proj': 8.434918862663593e-05, 'learning_rate/base': 2.1087297156658983e-05, 'epoch': 0.4}) +[2026-07-27 05:06:33,325][starVLA.training.train_starvla][INFO] - Step 3324, Loss: {'train/loss': 0.18681566417217255, 'train/grad_norm_pre_clip': 4.537040710449219, 'timing/data': 0.000176331028342247, 'timing/model': 0.4717395091429353, 'learning_rate/action_model': 8.432690101862681e-05, 'learning_rate/action_query_proj': 8.432690101862681e-05, 'learning_rate/base': 2.1081725254656702e-05, 'epoch': 0.4}) +[2026-07-27 05:06:38,976][starVLA.training.train_starvla][INFO] - Step 3325, Loss: {'train/loss': 0.08618003129959106, 'train/grad_norm_pre_clip': 3.479414701461792, 'timing/data': 0.00017823278903961182, 'timing/model': 0.47314808797091246, 'learning_rate/action_model': 8.430460064846912e-05, 'learning_rate/action_query_proj': 8.430460064846912e-05, 'learning_rate/base': 2.107615016211728e-05, 'epoch': 0.4}) +[2026-07-27 05:06:44,661][starVLA.training.train_starvla][INFO] - Step 3326, Loss: {'train/loss': 0.1084563285112381, 'train/grad_norm_pre_clip': 3.3365705013275146, 'timing/data': 0.00017453590407967567, 'timing/model': 0.48130101803690195, 'learning_rate/action_model': 8.428228752496672e-05, 'learning_rate/action_query_proj': 8.428228752496672e-05, 'learning_rate/base': 2.107057188124168e-05, 'epoch': 0.4}) +[2026-07-27 05:06:50,300][starVLA.training.train_starvla][INFO] - Step 3327, Loss: {'train/loss': 0.10835100710391998, 'train/grad_norm_pre_clip': 4.405452728271484, 'timing/data': 0.00017570285126566887, 'timing/model': 0.4718745849095285, 'learning_rate/action_model': 8.425996165692843e-05, 'learning_rate/action_query_proj': 8.425996165692843e-05, 'learning_rate/base': 2.1064990414232107e-05, 'epoch': 0.4}) +[2026-07-27 05:06:55,977][starVLA.training.train_starvla][INFO] - Step 3328, Loss: {'train/loss': 0.10760944336652756, 'train/grad_norm_pre_clip': 4.811641693115234, 'timing/data': 0.0001711198128759861, 'timing/model': 0.47337154392153025, 'learning_rate/action_model': 8.423762305316821e-05, 'learning_rate/action_query_proj': 8.423762305316821e-05, 'learning_rate/base': 2.1059405763292052e-05, 'epoch': 0.4}) +[2026-07-27 05:07:01,677][starVLA.training.train_starvla][INFO] - Step 3329, Loss: {'train/loss': 0.1370188593864441, 'train/grad_norm_pre_clip': 4.095864295959473, 'timing/data': 0.00017935503274202347, 'timing/model': 0.4733878578990698, 'learning_rate/action_model': 8.421527172250494e-05, 'learning_rate/action_query_proj': 8.421527172250494e-05, 'learning_rate/base': 2.1053817930626234e-05, 'epoch': 0.4}) +[2026-07-27 05:07:07,351][starVLA.training.train_starvla][INFO] - Step 3330, Loss: {'train/loss': 0.09984488040208817, 'train/grad_norm_pre_clip': 3.641136407852173, 'timing/data': 0.00017492612823843956, 'timing/model': 0.47447879891842604, 'learning_rate/action_model': 8.419290767376255e-05, 'learning_rate/action_query_proj': 8.419290767376255e-05, 'learning_rate/base': 2.1048226918440637e-05, 'epoch': 0.4}) +[2026-07-27 05:07:13,023][starVLA.training.train_starvla][INFO] - Step 3331, Loss: {'train/loss': 0.08448654413223267, 'train/grad_norm_pre_clip': 2.3810877799987793, 'timing/data': 0.000175445806235075, 'timing/model': 0.4800411122851074, 'learning_rate/action_model': 8.417053091577009e-05, 'learning_rate/action_query_proj': 8.417053091577009e-05, 'learning_rate/base': 2.1042632728942522e-05, 'epoch': 0.4}) +[2026-07-27 05:07:18,703][starVLA.training.train_starvla][INFO] - Step 3332, Loss: {'train/loss': 0.06868617236614227, 'train/grad_norm_pre_clip': 2.9175865650177, 'timing/data': 0.00017099268734455109, 'timing/model': 0.4703747630119324, 'learning_rate/action_model': 8.414814145736151e-05, 'learning_rate/action_query_proj': 8.414814145736151e-05, 'learning_rate/base': 2.1037035364340378e-05, 'epoch': 0.4}) +[2026-07-27 05:07:24,369][starVLA.training.train_starvla][INFO] - Step 3333, Loss: {'train/loss': 0.08032059669494629, 'train/grad_norm_pre_clip': 3.483144998550415, 'timing/data': 0.0001749526709318161, 'timing/model': 0.4726494401693344, 'learning_rate/action_model': 8.412573930737579e-05, 'learning_rate/action_query_proj': 8.412573930737579e-05, 'learning_rate/base': 2.1031434826843947e-05, 'epoch': 0.4}) +[2026-07-27 05:07:30,025][starVLA.training.train_starvla][INFO] - Step 3334, Loss: {'train/loss': 0.15378229320049286, 'train/grad_norm_pre_clip': 4.19451904296875, 'timing/data': 0.00019093230366706848, 'timing/model': 0.47278860909864306, 'learning_rate/action_model': 8.410332447465697e-05, 'learning_rate/action_query_proj': 8.410332447465697e-05, 'learning_rate/base': 2.1025831118664243e-05, 'epoch': 0.4}) +[2026-07-27 05:07:35,672][starVLA.training.train_starvla][INFO] - Step 3335, Loss: {'train/loss': 0.06937302649021149, 'train/grad_norm_pre_clip': 2.9316823482513428, 'timing/data': 0.00022612698376178741, 'timing/model': 0.4689134224317968, 'learning_rate/action_model': 8.408089696805407e-05, 'learning_rate/action_query_proj': 8.408089696805407e-05, 'learning_rate/base': 2.1020224242013517e-05, 'epoch': 0.4}) +[2026-07-27 05:07:41,280][starVLA.training.train_starvla][INFO] - Step 3336, Loss: {'train/loss': 0.11209555715322495, 'train/grad_norm_pre_clip': 4.663701057434082, 'timing/data': 0.0001735622063279152, 'timing/model': 0.4685278059914708, 'learning_rate/action_model': 8.405845679642111e-05, 'learning_rate/action_query_proj': 8.405845679642111e-05, 'learning_rate/base': 2.1014614199105278e-05, 'epoch': 0.4}) +[2026-07-27 05:07:46,916][starVLA.training.train_starvla][INFO] - Step 3337, Loss: {'train/loss': 0.07604562491178513, 'train/grad_norm_pre_clip': 3.0422635078430176, 'timing/data': 0.0001753251999616623, 'timing/model': 0.46541422605514526, 'learning_rate/action_model': 8.403600396861712e-05, 'learning_rate/action_query_proj': 8.403600396861712e-05, 'learning_rate/base': 2.100900099215428e-05, 'epoch': 0.4}) +[2026-07-27 05:07:52,615][starVLA.training.train_starvla][INFO] - Step 3338, Loss: {'train/loss': 0.044920664280653, 'train/grad_norm_pre_clip': 2.114388942718506, 'timing/data': 0.00017251865938305855, 'timing/model': 0.46366967912763357, 'learning_rate/action_model': 8.40135384935061e-05, 'learning_rate/action_query_proj': 8.40135384935061e-05, 'learning_rate/base': 2.1003384623376526e-05, 'epoch': 0.4}) +[2026-07-27 05:07:58,314][starVLA.training.train_starvla][INFO] - Step 3339, Loss: {'train/loss': 0.06942187994718552, 'train/grad_norm_pre_clip': 2.5729830265045166, 'timing/data': 0.00017618201673030853, 'timing/model': 0.46247093100100756, 'learning_rate/action_model': 8.39910603799571e-05, 'learning_rate/action_query_proj': 8.39910603799571e-05, 'learning_rate/base': 2.0997765094989275e-05, 'epoch': 0.41}) +[2026-07-27 05:08:04,020][starVLA.training.train_starvla][INFO] - Step 3340, Loss: {'train/loss': 0.2330002784729004, 'train/grad_norm_pre_clip': 4.957706928253174, 'timing/data': 0.00017403392121195793, 'timing/model': 0.4671825421974063, 'learning_rate/action_model': 8.396856963684409e-05, 'learning_rate/action_query_proj': 8.396856963684409e-05, 'learning_rate/base': 2.0992142409211022e-05, 'epoch': 0.41}) +[2026-07-27 05:08:09,731][starVLA.training.train_starvla][INFO] - Step 3341, Loss: {'train/loss': 0.11659478396177292, 'train/grad_norm_pre_clip': 3.4586341381073, 'timing/data': 0.00018280325457453728, 'timing/model': 0.46671949001029134, 'learning_rate/action_model': 8.394606627304608e-05, 'learning_rate/action_query_proj': 8.394606627304608e-05, 'learning_rate/base': 2.098651656826152e-05, 'epoch': 0.41}) +[2026-07-27 05:08:15,413][starVLA.training.train_starvla][INFO] - Step 3342, Loss: {'train/loss': 0.2957873046398163, 'train/grad_norm_pre_clip': 5.795405864715576, 'timing/data': 0.0001700310967862606, 'timing/model': 0.46788547234609723, 'learning_rate/action_model': 8.392355029744702e-05, 'learning_rate/action_query_proj': 8.392355029744702e-05, 'learning_rate/base': 2.0980887574361754e-05, 'epoch': 0.41}) +[2026-07-27 05:08:21,089][starVLA.training.train_starvla][INFO] - Step 3343, Loss: {'train/loss': 0.1395600438117981, 'train/grad_norm_pre_clip': 3.3852434158325195, 'timing/data': 0.00017653685063123703, 'timing/model': 0.46270401403307915, 'learning_rate/action_model': 8.390102171893586e-05, 'learning_rate/action_query_proj': 8.390102171893586e-05, 'learning_rate/base': 2.0975255429733966e-05, 'epoch': 0.41}) +[2026-07-27 05:08:26,774][starVLA.training.train_starvla][INFO] - Step 3344, Loss: {'train/loss': 0.08697472512722015, 'train/grad_norm_pre_clip': 3.669624090194702, 'timing/data': 0.00017333775758743286, 'timing/model': 0.4622877831570804, 'learning_rate/action_model': 8.387848054640658e-05, 'learning_rate/action_query_proj': 8.387848054640658e-05, 'learning_rate/base': 2.0969620136601645e-05, 'epoch': 0.41}) +[2026-07-27 05:08:32,494][starVLA.training.train_starvla][INFO] - Step 3345, Loss: {'train/loss': 0.1050570160150528, 'train/grad_norm_pre_clip': 3.2266151905059814, 'timing/data': 0.00017582997679710388, 'timing/model': 0.4618170689791441, 'learning_rate/action_model': 8.385592678875802e-05, 'learning_rate/action_query_proj': 8.385592678875802e-05, 'learning_rate/base': 2.0963981697189505e-05, 'epoch': 0.41}) +[2026-07-27 05:08:38,188][starVLA.training.train_starvla][INFO] - Step 3346, Loss: {'train/loss': 0.11850322037935257, 'train/grad_norm_pre_clip': 4.028872966766357, 'timing/data': 0.00017460109665989876, 'timing/model': 0.4678475637920201, 'learning_rate/action_model': 8.383336045489406e-05, 'learning_rate/action_query_proj': 8.383336045489406e-05, 'learning_rate/base': 2.0958340113723516e-05, 'epoch': 0.41}) +[2026-07-27 05:08:43,850][starVLA.training.train_starvla][INFO] - Step 3347, Loss: {'train/loss': 0.1274918168783188, 'train/grad_norm_pre_clip': 3.114069700241089, 'timing/data': 0.00017368700355291367, 'timing/model': 0.4634094606153667, 'learning_rate/action_model': 8.381078155372354e-05, 'learning_rate/action_query_proj': 8.381078155372354e-05, 'learning_rate/base': 2.0952695388430885e-05, 'epoch': 0.41}) +[2026-07-27 05:08:49,529][starVLA.training.train_starvla][INFO] - Step 3348, Loss: {'train/loss': 0.09267323464155197, 'train/grad_norm_pre_clip': 2.932739019393921, 'timing/data': 0.00017409073188900948, 'timing/model': 0.4616656540893018, 'learning_rate/action_model': 8.378819009416025e-05, 'learning_rate/action_query_proj': 8.378819009416025e-05, 'learning_rate/base': 2.0947047523540063e-05, 'epoch': 0.41}) +[2026-07-27 05:08:55,220][starVLA.training.train_starvla][INFO] - Step 3349, Loss: {'train/loss': 0.073499895632267, 'train/grad_norm_pre_clip': 3.355649709701538, 'timing/data': 0.00017884699627757072, 'timing/model': 0.4695251169614494, 'learning_rate/action_model': 8.376558608512293e-05, 'learning_rate/action_query_proj': 8.376558608512293e-05, 'learning_rate/base': 2.0941396521280733e-05, 'epoch': 0.41}) +[2026-07-27 05:09:00,915][starVLA.training.train_starvla][INFO] - Step 3350, Loss: {'train/loss': 0.06719660013914108, 'train/grad_norm_pre_clip': 2.694904088973999, 'timing/data': 0.00017133401706814766, 'timing/model': 0.47371830185875297, 'learning_rate/action_model': 8.374296953553528e-05, 'learning_rate/action_query_proj': 8.374296953553528e-05, 'learning_rate/base': 2.093574238388382e-05, 'epoch': 0.41}) +[2026-07-27 05:09:06,872][starVLA.training.train_starvla][INFO] - Step 3351, Loss: {'train/loss': 0.1617061346769333, 'train/grad_norm_pre_clip': 3.8150296211242676, 'timing/data': 0.00017391284927725792, 'timing/model': 0.47133550234138966, 'learning_rate/action_model': 8.372034045432599e-05, 'learning_rate/action_query_proj': 8.372034045432599e-05, 'learning_rate/base': 2.0930085113581498e-05, 'epoch': 0.41}) +[2026-07-27 05:09:12,555][starVLA.training.train_starvla][INFO] - Step 3352, Loss: {'train/loss': 0.10101409256458282, 'train/grad_norm_pre_clip': 3.38240647315979, 'timing/data': 0.00017858901992440224, 'timing/model': 0.4710202133283019, 'learning_rate/action_model': 8.369769885042867e-05, 'learning_rate/action_query_proj': 8.369769885042867e-05, 'learning_rate/base': 2.0924424712607167e-05, 'epoch': 0.41}) +[2026-07-27 05:09:18,230][starVLA.training.train_starvla][INFO] - Step 3353, Loss: {'train/loss': 0.132590651512146, 'train/grad_norm_pre_clip': 3.8155016899108887, 'timing/data': 0.00017761578783392906, 'timing/model': 0.4712341823615134, 'learning_rate/action_model': 8.367504473278178e-05, 'learning_rate/action_query_proj': 8.367504473278178e-05, 'learning_rate/base': 2.0918761183195446e-05, 'epoch': 0.41}) +[2026-07-27 05:09:23,916][starVLA.training.train_starvla][INFO] - Step 3354, Loss: {'train/loss': 0.0965852215886116, 'train/grad_norm_pre_clip': 2.674128532409668, 'timing/data': 0.0001708618365228176, 'timing/model': 0.4728895970620215, 'learning_rate/action_model': 8.36523781103289e-05, 'learning_rate/action_query_proj': 8.36523781103289e-05, 'learning_rate/base': 2.0913094527582225e-05, 'epoch': 0.41}) +[2026-07-27 05:09:29,621][starVLA.training.train_starvla][INFO] - Step 3355, Loss: {'train/loss': 0.08917427062988281, 'train/grad_norm_pre_clip': 2.5846478939056396, 'timing/data': 0.00017815176397562027, 'timing/model': 0.47821590304374695, 'learning_rate/action_model': 8.362969899201842e-05, 'learning_rate/action_query_proj': 8.362969899201842e-05, 'learning_rate/base': 2.0907424748004606e-05, 'epoch': 0.41}) +[2026-07-27 05:09:35,592][starVLA.training.train_starvla][INFO] - Step 3356, Loss: {'train/loss': 0.26649630069732666, 'train/grad_norm_pre_clip': 6.189066410064697, 'timing/data': 0.00017342763021588326, 'timing/model': 0.5835419837385416, 'learning_rate/action_model': 8.360700738680368e-05, 'learning_rate/action_query_proj': 8.360700738680368e-05, 'learning_rate/base': 2.090175184670092e-05, 'epoch': 0.41}) +[2026-07-27 05:09:41,354][starVLA.training.train_starvla][INFO] - Step 3357, Loss: {'train/loss': 0.0700879916548729, 'train/grad_norm_pre_clip': 2.4572274684906006, 'timing/data': 0.00017346395179629326, 'timing/model': 0.47272924333810806, 'learning_rate/action_model': 8.3584303303643e-05, 'learning_rate/action_query_proj': 8.3584303303643e-05, 'learning_rate/base': 2.089607582591075e-05, 'epoch': 0.41}) +[2026-07-27 05:09:47,044][starVLA.training.train_starvla][INFO] - Step 3358, Loss: {'train/loss': 0.10381568968296051, 'train/grad_norm_pre_clip': 3.0979552268981934, 'timing/data': 0.0001764199696481228, 'timing/model': 0.4714917968958616, 'learning_rate/action_model': 8.356158675149957e-05, 'learning_rate/action_query_proj': 8.356158675149957e-05, 'learning_rate/base': 2.0890396687874892e-05, 'epoch': 0.41}) +[2026-07-27 05:09:52,727][starVLA.training.train_starvla][INFO] - Step 3359, Loss: {'train/loss': 0.130960613489151, 'train/grad_norm_pre_clip': 3.2730953693389893, 'timing/data': 0.00017659366130828857, 'timing/model': 0.4717421247623861, 'learning_rate/action_model': 8.353885773934152e-05, 'learning_rate/action_query_proj': 8.353885773934152e-05, 'learning_rate/base': 2.088471443483538e-05, 'epoch': 0.41}) +[2026-07-27 05:09:58,401][starVLA.training.train_starvla][INFO] - Step 3360, Loss: {'train/loss': 0.13462772965431213, 'train/grad_norm_pre_clip': 3.855883836746216, 'timing/data': 0.0001773950643837452, 'timing/model': 0.4787158207036555, 'learning_rate/action_model': 8.35161162761419e-05, 'learning_rate/action_query_proj': 8.35161162761419e-05, 'learning_rate/base': 2.0879029069035476e-05, 'epoch': 0.41}) +[2026-07-27 05:10:04,082][starVLA.training.train_starvla][INFO] - Step 3361, Loss: {'train/loss': 0.11419984698295593, 'train/grad_norm_pre_clip': 3.4442636966705322, 'timing/data': 0.00017185695469379425, 'timing/model': 0.47870176611468196, 'learning_rate/action_model': 8.349336237087873e-05, 'learning_rate/action_query_proj': 8.349336237087873e-05, 'learning_rate/base': 2.0873340592719682e-05, 'epoch': 0.41}) +[2026-07-27 05:10:09,742][starVLA.training.train_starvla][INFO] - Step 3362, Loss: {'train/loss': 0.08746643364429474, 'train/grad_norm_pre_clip': 2.390296220779419, 'timing/data': 0.00017583416774868965, 'timing/model': 0.4700875128619373, 'learning_rate/action_model': 8.347059603253484e-05, 'learning_rate/action_query_proj': 8.347059603253484e-05, 'learning_rate/base': 2.086764900813371e-05, 'epoch': 0.41}) +[2026-07-27 05:10:15,410][starVLA.training.train_starvla][INFO] - Step 3363, Loss: {'train/loss': 0.048307839781045914, 'train/grad_norm_pre_clip': 2.4878084659576416, 'timing/data': 0.00017282087355852127, 'timing/model': 0.46161845000460744, 'learning_rate/action_model': 8.344781727009802e-05, 'learning_rate/action_query_proj': 8.344781727009802e-05, 'learning_rate/base': 2.0861954317524505e-05, 'epoch': 0.41}) +[2026-07-27 05:10:21,175][starVLA.training.train_starvla][INFO] - Step 3364, Loss: {'train/loss': 0.15098565816879272, 'train/grad_norm_pre_clip': 3.934450626373291, 'timing/data': 0.00017395708709955215, 'timing/model': 0.4666333720088005, 'learning_rate/action_model': 8.3425026092561e-05, 'learning_rate/action_query_proj': 8.3425026092561e-05, 'learning_rate/base': 2.085625652314025e-05, 'epoch': 0.41}) +[2026-07-27 05:10:26,823][starVLA.training.train_starvla][INFO] - Step 3365, Loss: {'train/loss': 0.05735102295875549, 'train/grad_norm_pre_clip': 2.310687303543091, 'timing/data': 0.00017818016931414604, 'timing/model': 0.46096705505624413, 'learning_rate/action_model': 8.340222250892133e-05, 'learning_rate/action_query_proj': 8.340222250892133e-05, 'learning_rate/base': 2.0850555627230334e-05, 'epoch': 0.41}) +[2026-07-27 05:10:32,458][starVLA.training.train_starvla][INFO] - Step 3366, Loss: {'train/loss': 0.0448482483625412, 'train/grad_norm_pre_clip': 1.8045350313186646, 'timing/data': 0.00017048465088009834, 'timing/model': 0.4636534838937223, 'learning_rate/action_model': 8.337940652818155e-05, 'learning_rate/action_query_proj': 8.337940652818155e-05, 'learning_rate/base': 2.0844851632045387e-05, 'epoch': 0.41}) +[2026-07-27 05:10:38,122][starVLA.training.train_starvla][INFO] - Step 3367, Loss: {'train/loss': 0.17592866718769073, 'train/grad_norm_pre_clip': 4.846106052398682, 'timing/data': 0.00017860624939203262, 'timing/model': 0.4661323018372059, 'learning_rate/action_model': 8.335657815934902e-05, 'learning_rate/action_query_proj': 8.335657815934902e-05, 'learning_rate/base': 2.0839144539837254e-05, 'epoch': 0.41}) +[2026-07-27 05:10:43,759][starVLA.training.train_starvla][INFO] - Step 3368, Loss: {'train/loss': 0.11538588255643845, 'train/grad_norm_pre_clip': 3.377916097640991, 'timing/data': 0.00017395010218024254, 'timing/model': 0.4665204738266766, 'learning_rate/action_model': 8.333373741143601e-05, 'learning_rate/action_query_proj': 8.333373741143601e-05, 'learning_rate/base': 2.0833434352859004e-05, 'epoch': 0.41}) +[2026-07-27 05:10:49,392][starVLA.training.train_starvla][INFO] - Step 3369, Loss: {'train/loss': 0.15978553891181946, 'train/grad_norm_pre_clip': 3.8733348846435547, 'timing/data': 0.00017514638602733612, 'timing/model': 0.4674056014046073, 'learning_rate/action_model': 8.331088429345973e-05, 'learning_rate/action_query_proj': 8.331088429345973e-05, 'learning_rate/base': 2.0827721073364933e-05, 'epoch': 0.41}) +[2026-07-27 05:10:54,976][starVLA.training.train_starvla][INFO] - Step 3370, Loss: {'train/loss': 0.15884912014007568, 'train/grad_norm_pre_clip': 4.343453407287598, 'timing/data': 0.00017333589494228363, 'timing/model': 0.46148007502779365, 'learning_rate/action_model': 8.328801881444218e-05, 'learning_rate/action_query_proj': 8.328801881444218e-05, 'learning_rate/base': 2.0822004703610546e-05, 'epoch': 0.41}) +[2026-07-27 05:11:00,586][starVLA.training.train_starvla][INFO] - Step 3371, Loss: {'train/loss': 0.0811200886964798, 'train/grad_norm_pre_clip': 2.131730318069458, 'timing/data': 0.000174705870449543, 'timing/model': 0.46382129983976483, 'learning_rate/action_model': 8.326514098341031e-05, 'learning_rate/action_query_proj': 8.326514098341031e-05, 'learning_rate/base': 2.0816285245852578e-05, 'epoch': 0.41}) +[2026-07-27 05:11:06,175][starVLA.training.train_starvla][INFO] - Step 3372, Loss: {'train/loss': 0.14918501675128937, 'train/grad_norm_pre_clip': 5.5916595458984375, 'timing/data': 0.0001809992827475071, 'timing/model': 0.4677637740969658, 'learning_rate/action_model': 8.324225080939594e-05, 'learning_rate/action_query_proj': 8.324225080939594e-05, 'learning_rate/base': 2.0810562702348986e-05, 'epoch': 0.41}) +[2026-07-27 05:11:11,779][starVLA.training.train_starvla][INFO] - Step 3373, Loss: {'train/loss': 0.17699286341667175, 'train/grad_norm_pre_clip': 5.334351062774658, 'timing/data': 0.00017528003081679344, 'timing/model': 0.4635544428601861, 'learning_rate/action_model': 8.321934830143571e-05, 'learning_rate/action_query_proj': 8.321934830143571e-05, 'learning_rate/base': 2.0804837075358928e-05, 'epoch': 0.41}) +[2026-07-27 05:11:17,395][starVLA.training.train_starvla][INFO] - Step 3374, Loss: {'train/loss': 0.0935007631778717, 'train/grad_norm_pre_clip': 3.014073610305786, 'timing/data': 0.00017503462731838226, 'timing/model': 0.4626175449229777, 'learning_rate/action_model': 8.319643346857121e-05, 'learning_rate/action_query_proj': 8.319643346857121e-05, 'learning_rate/base': 2.0799108367142803e-05, 'epoch': 0.41}) +[2026-07-27 05:11:23,002][starVLA.training.train_starvla][INFO] - Step 3375, Loss: {'train/loss': 0.14987300336360931, 'train/grad_norm_pre_clip': 4.5254807472229, 'timing/data': 0.0001773349940776825, 'timing/model': 0.4613270778208971, 'learning_rate/action_model': 8.31735063198488e-05, 'learning_rate/action_query_proj': 8.31735063198488e-05, 'learning_rate/base': 2.07933765799622e-05, 'epoch': 0.41}) +[2026-07-27 05:11:28,625][starVLA.training.train_starvla][INFO] - Step 3376, Loss: {'train/loss': 0.12617743015289307, 'train/grad_norm_pre_clip': 3.625223398208618, 'timing/data': 0.00018260115757584572, 'timing/model': 0.4585600649006665, 'learning_rate/action_model': 8.315056686431982e-05, 'learning_rate/action_query_proj': 8.315056686431982e-05, 'learning_rate/base': 2.0787641716079956e-05, 'epoch': 0.41}) +[2026-07-27 05:11:34,262][starVLA.training.train_starvla][INFO] - Step 3377, Loss: {'train/loss': 0.11146174371242523, 'train/grad_norm_pre_clip': 3.2852296829223633, 'timing/data': 0.00018362421542406082, 'timing/model': 0.465058877132833, 'learning_rate/action_model': 8.312761511104038e-05, 'learning_rate/action_query_proj': 8.312761511104038e-05, 'learning_rate/base': 2.0781903777760096e-05, 'epoch': 0.41}) +[2026-07-27 05:11:39,875][starVLA.training.train_starvla][INFO] - Step 3378, Loss: {'train/loss': 0.04460565745830536, 'train/grad_norm_pre_clip': 1.7104345560073853, 'timing/data': 0.00016921618953347206, 'timing/model': 0.4627321530133486, 'learning_rate/action_model': 8.310465106907144e-05, 'learning_rate/action_query_proj': 8.310465106907144e-05, 'learning_rate/base': 2.077616276726786e-05, 'epoch': 0.41}) +[2026-07-27 05:11:45,495][starVLA.training.train_starvla][INFO] - Step 3379, Loss: {'train/loss': 0.061163462698459625, 'train/grad_norm_pre_clip': 2.4992966651916504, 'timing/data': 0.0001767640933394432, 'timing/model': 0.4622090240009129, 'learning_rate/action_model': 8.308167474747885e-05, 'learning_rate/action_query_proj': 8.308167474747885e-05, 'learning_rate/base': 2.0770418686869713e-05, 'epoch': 0.41}) +[2026-07-27 05:11:51,120][starVLA.training.train_starvla][INFO] - Step 3380, Loss: {'train/loss': 0.13113121688365936, 'train/grad_norm_pre_clip': 3.531586170196533, 'timing/data': 0.00017877575010061264, 'timing/model': 0.4658820149488747, 'learning_rate/action_model': 8.305868615533335e-05, 'learning_rate/action_query_proj': 8.305868615533335e-05, 'learning_rate/base': 2.0764671538833337e-05, 'epoch': 0.41}) +[2026-07-27 05:11:56,729][starVLA.training.train_starvla][INFO] - Step 3381, Loss: {'train/loss': 0.10498081147670746, 'train/grad_norm_pre_clip': 3.429046392440796, 'timing/data': 0.00017415639013051987, 'timing/model': 0.46428559999912977, 'learning_rate/action_model': 8.303568530171038e-05, 'learning_rate/action_query_proj': 8.303568530171038e-05, 'learning_rate/base': 2.0758921325427595e-05, 'epoch': 0.41}) +[2026-07-27 05:12:02,355][starVLA.training.train_starvla][INFO] - Step 3382, Loss: {'train/loss': 0.1660429984331131, 'train/grad_norm_pre_clip': 4.7019548416137695, 'timing/data': 0.00017430493608117104, 'timing/model': 0.4617266431450844, 'learning_rate/action_model': 8.301267219569038e-05, 'learning_rate/action_query_proj': 8.301267219569038e-05, 'learning_rate/base': 2.0753168048922596e-05, 'epoch': 0.41}) +[2026-07-27 05:12:08,013][starVLA.training.train_starvla][INFO] - Step 3383, Loss: {'train/loss': 0.07359763979911804, 'train/grad_norm_pre_clip': 2.744006633758545, 'timing/data': 0.00017332332208752632, 'timing/model': 0.4677647319622338, 'learning_rate/action_model': 8.298964684635855e-05, 'learning_rate/action_query_proj': 8.298964684635855e-05, 'learning_rate/base': 2.074741171158964e-05, 'epoch': 0.41}) +[2026-07-27 05:12:13,632][starVLA.training.train_starvla][INFO] - Step 3384, Loss: {'train/loss': 0.10708959400653839, 'train/grad_norm_pre_clip': 3.088357925415039, 'timing/data': 0.00017685815691947937, 'timing/model': 0.46159962099045515, 'learning_rate/action_model': 8.296660926280494e-05, 'learning_rate/action_query_proj': 8.296660926280494e-05, 'learning_rate/base': 2.0741652315701235e-05, 'epoch': 0.41}) +[2026-07-27 05:12:19,270][starVLA.training.train_starvla][INFO] - Step 3385, Loss: {'train/loss': 0.04727207124233246, 'train/grad_norm_pre_clip': 2.164482593536377, 'timing/data': 0.0001771370880305767, 'timing/model': 0.4684159462340176, 'learning_rate/action_model': 8.294355945412439e-05, 'learning_rate/action_query_proj': 8.294355945412439e-05, 'learning_rate/base': 2.0735889863531098e-05, 'epoch': 0.41}) +[2026-07-27 05:12:24,873][starVLA.training.train_starvla][INFO] - Step 3386, Loss: {'train/loss': 0.04832847788929939, 'train/grad_norm_pre_clip': 1.8776899576187134, 'timing/data': 0.00018625380471348763, 'timing/model': 0.46044816682115197, 'learning_rate/action_model': 8.292049742941664e-05, 'learning_rate/action_query_proj': 8.292049742941664e-05, 'learning_rate/base': 2.073012435735416e-05, 'epoch': 0.41}) +[2026-07-27 05:12:30,490][starVLA.training.train_starvla][INFO] - Step 3387, Loss: {'train/loss': 0.04456578195095062, 'train/grad_norm_pre_clip': 2.349485158920288, 'timing/data': 0.0001811501570045948, 'timing/model': 0.46275536296889186, 'learning_rate/action_model': 8.289742319778616e-05, 'learning_rate/action_query_proj': 8.289742319778616e-05, 'learning_rate/base': 2.072435579944654e-05, 'epoch': 0.41}) +[2026-07-27 05:12:36,226][starVLA.training.train_starvla][INFO] - Step 3388, Loss: {'train/loss': 0.11089467257261276, 'train/grad_norm_pre_clip': 2.92341685295105, 'timing/data': 0.0001733587123453617, 'timing/model': 0.46509994473308325, 'learning_rate/action_model': 8.287433676834233e-05, 'learning_rate/action_query_proj': 8.287433676834233e-05, 'learning_rate/base': 2.0718584192085583e-05, 'epoch': 0.41}) +[2026-07-27 05:12:41,869][starVLA.training.train_starvla][INFO] - Step 3389, Loss: {'train/loss': 0.20426006615161896, 'train/grad_norm_pre_clip': 4.577386379241943, 'timing/data': 0.00017227791249752045, 'timing/model': 0.46532846335321665, 'learning_rate/action_model': 8.285123815019932e-05, 'learning_rate/action_query_proj': 8.285123815019932e-05, 'learning_rate/base': 2.071280953754983e-05, 'epoch': 0.41}) +[2026-07-27 05:12:47,495][starVLA.training.train_starvla][INFO] - Step 3390, Loss: {'train/loss': 0.04471226781606674, 'train/grad_norm_pre_clip': 2.1400582790374756, 'timing/data': 0.00017570704221725464, 'timing/model': 0.4652280109003186, 'learning_rate/action_model': 8.282812735247606e-05, 'learning_rate/action_query_proj': 8.282812735247606e-05, 'learning_rate/base': 2.0707031838119015e-05, 'epoch': 0.41}) +[2026-07-27 05:12:53,143][starVLA.training.train_starvla][INFO] - Step 3391, Loss: {'train/loss': 0.15192493796348572, 'train/grad_norm_pre_clip': 4.170712947845459, 'timing/data': 0.0001760111190378666, 'timing/model': 0.46329725394025445, 'learning_rate/action_model': 8.280500438429634e-05, 'learning_rate/action_query_proj': 8.280500438429634e-05, 'learning_rate/base': 2.0701251096074086e-05, 'epoch': 0.41}) +[2026-07-27 05:12:58,780][starVLA.training.train_starvla][INFO] - Step 3392, Loss: {'train/loss': 0.18516287207603455, 'train/grad_norm_pre_clip': 4.804470539093018, 'timing/data': 0.0001843208447098732, 'timing/model': 0.46401106426492333, 'learning_rate/action_model': 8.278186925478876e-05, 'learning_rate/action_query_proj': 8.278186925478876e-05, 'learning_rate/base': 2.069546731369719e-05, 'epoch': 0.41}) +[2026-07-27 05:13:04,436][starVLA.training.train_starvla][INFO] - Step 3393, Loss: {'train/loss': 0.060154251754283905, 'train/grad_norm_pre_clip': 3.1168315410614014, 'timing/data': 0.00018093781545758247, 'timing/model': 0.4655477022752166, 'learning_rate/action_model': 8.275872197308668e-05, 'learning_rate/action_query_proj': 8.275872197308668e-05, 'learning_rate/base': 2.068968049327167e-05, 'epoch': 0.41}) +[2026-07-27 05:13:10,067][starVLA.training.train_starvla][INFO] - Step 3394, Loss: {'train/loss': 0.16243958473205566, 'train/grad_norm_pre_clip': 4.620058059692383, 'timing/data': 0.00017411401495337486, 'timing/model': 0.46286822902038693, 'learning_rate/action_model': 8.27355625483283e-05, 'learning_rate/action_query_proj': 8.27355625483283e-05, 'learning_rate/base': 2.0683890637082075e-05, 'epoch': 0.41}) +[2026-07-27 05:13:15,716][starVLA.training.train_starvla][INFO] - Step 3395, Loss: {'train/loss': 0.07643067091703415, 'train/grad_norm_pre_clip': 2.92033052444458, 'timing/data': 0.00017697084695100784, 'timing/model': 0.4614941398613155, 'learning_rate/action_model': 8.271239098965656e-05, 'learning_rate/action_query_proj': 8.271239098965656e-05, 'learning_rate/base': 2.067809774741414e-05, 'epoch': 0.41}) +[2026-07-27 05:13:21,600][starVLA.training.train_starvla][INFO] - Step 3396, Loss: {'train/loss': 0.10853268206119537, 'train/grad_norm_pre_clip': 3.252819538116455, 'timing/data': 0.00017736200243234634, 'timing/model': 0.46159444097429514, 'learning_rate/action_model': 8.268920730621928e-05, 'learning_rate/action_query_proj': 8.268920730621928e-05, 'learning_rate/base': 2.067230182655482e-05, 'epoch': 0.41}) +[2026-07-27 05:13:27,259][starVLA.training.train_starvla][INFO] - Step 3397, Loss: {'train/loss': 0.15524619817733765, 'train/grad_norm_pre_clip': 2.6547467708587646, 'timing/data': 0.00017489073798060417, 'timing/model': 0.46536320773884654, 'learning_rate/action_model': 8.266601150716897e-05, 'learning_rate/action_query_proj': 8.266601150716897e-05, 'learning_rate/base': 2.0666502876792242e-05, 'epoch': 0.41}) +[2026-07-27 05:13:32,895][starVLA.training.train_starvla][INFO] - Step 3398, Loss: {'train/loss': 0.1376003921031952, 'train/grad_norm_pre_clip': 4.843024730682373, 'timing/data': 0.00017371401190757751, 'timing/model': 0.4638320878148079, 'learning_rate/action_model': 8.264280360166295e-05, 'learning_rate/action_query_proj': 8.264280360166295e-05, 'learning_rate/base': 2.066070090041574e-05, 'epoch': 0.41}) +[2026-07-27 05:13:38,529][starVLA.training.train_starvla][INFO] - Step 3399, Loss: {'train/loss': 0.037366703152656555, 'train/grad_norm_pre_clip': 1.553544044494629, 'timing/data': 0.00017615826800465584, 'timing/model': 0.4668831401504576, 'learning_rate/action_model': 8.261958359886337e-05, 'learning_rate/action_query_proj': 8.261958359886337e-05, 'learning_rate/base': 2.0654895899715843e-05, 'epoch': 0.41}) +[2026-07-27 05:13:44,164][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 3400 +[2026-07-27 05:13:44,164][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 3400 +[2026-07-27 05:13:44,165][starVLA.training.train_starvla][INFO] - Step 3400, Loss: {'train/loss': 0.06175125390291214, 'train/grad_norm_pre_clip': 2.4081575870513916, 'timing/data': 0.00017302809283137321, 'timing/model': 0.4626988652162254, 'learning_rate/action_model': 8.25963515079371e-05, 'learning_rate/action_query_proj': 8.25963515079371e-05, 'learning_rate/base': 2.0649087876984276e-05, 'epoch': 0.41}) +[2026-07-27 05:13:50,063][starVLA.training.train_starvla][INFO] - Step 3401, Loss: {'train/loss': 0.18265274167060852, 'train/grad_norm_pre_clip': 3.450364112854004, 'timing/data': 0.0001723240129649639, 'timing/model': 0.4631322519853711, 'learning_rate/action_model': 8.257310733805583e-05, 'learning_rate/action_query_proj': 8.257310733805583e-05, 'learning_rate/base': 2.0643276834513957e-05, 'epoch': 0.41}) +[2026-07-27 05:13:55,692][starVLA.training.train_starvla][INFO] - Step 3402, Loss: {'train/loss': 0.1165352612733841, 'train/grad_norm_pre_clip': 2.583347797393799, 'timing/data': 0.00017375685274600983, 'timing/model': 0.46532924473285675, 'learning_rate/action_model': 8.254985109839594e-05, 'learning_rate/action_query_proj': 8.254985109839594e-05, 'learning_rate/base': 2.0637462774598985e-05, 'epoch': 0.41}) +[2026-07-27 05:14:01,343][starVLA.training.train_starvla][INFO] - Step 3403, Loss: {'train/loss': 0.09890524297952652, 'train/grad_norm_pre_clip': 2.652930736541748, 'timing/data': 0.00017291493713855743, 'timing/model': 0.46016696235165, 'learning_rate/action_model': 8.252658279813868e-05, 'learning_rate/action_query_proj': 8.252658279813868e-05, 'learning_rate/base': 2.063164569953467e-05, 'epoch': 0.41}) +[2026-07-27 05:14:07,005][starVLA.training.train_starvla][INFO] - Step 3404, Loss: {'train/loss': 0.05259661003947258, 'train/grad_norm_pre_clip': 2.8297665119171143, 'timing/data': 0.0001771850511431694, 'timing/model': 0.46609802497550845, 'learning_rate/action_model': 8.250330244646996e-05, 'learning_rate/action_query_proj': 8.250330244646996e-05, 'learning_rate/base': 2.062582561161749e-05, 'epoch': 0.41}) +[2026-07-27 05:14:12,683][starVLA.training.train_starvla][INFO] - Step 3405, Loss: {'train/loss': 0.059567295014858246, 'train/grad_norm_pre_clip': 2.6221764087677, 'timing/data': 0.00017820484936237335, 'timing/model': 0.4631885518319905, 'learning_rate/action_model': 8.248001005258052e-05, 'learning_rate/action_query_proj': 8.248001005258052e-05, 'learning_rate/base': 2.062000251314513e-05, 'epoch': 0.41}) +[2026-07-27 05:14:18,342][starVLA.training.train_starvla][INFO] - Step 3406, Loss: {'train/loss': 0.17133568227291107, 'train/grad_norm_pre_clip': 4.504602432250977, 'timing/data': 0.00016662990674376488, 'timing/model': 0.4664297476410866, 'learning_rate/action_model': 8.24567056256658e-05, 'learning_rate/action_query_proj': 8.24567056256658e-05, 'learning_rate/base': 2.061417640641645e-05, 'epoch': 0.41}) +[2026-07-27 05:14:24,259][starVLA.training.train_starvla][INFO] - Step 3407, Loss: {'train/loss': 0.17227159440517426, 'train/grad_norm_pre_clip': 5.531864166259766, 'timing/data': 0.0001784120686352253, 'timing/model': 0.46536693070083857, 'learning_rate/action_model': 8.243338917492607e-05, 'learning_rate/action_query_proj': 8.243338917492607e-05, 'learning_rate/base': 2.0608347293731516e-05, 'epoch': 0.41}) +[2026-07-27 05:14:29,969][starVLA.training.train_starvla][INFO] - Step 3408, Loss: {'train/loss': 0.17867736518383026, 'train/grad_norm_pre_clip': 3.954141616821289, 'timing/data': 0.000185282900929451, 'timing/model': 0.46087409695610404, 'learning_rate/action_model': 8.241006070956626e-05, 'learning_rate/action_query_proj': 8.241006070956626e-05, 'learning_rate/base': 2.0602515177391565e-05, 'epoch': 0.41}) +[2026-07-27 05:14:35,682][starVLA.training.train_starvla][INFO] - Step 3409, Loss: {'train/loss': 0.19206975400447845, 'train/grad_norm_pre_clip': 3.5011789798736572, 'timing/data': 0.00017632870003581047, 'timing/model': 0.46308505022898316, 'learning_rate/action_model': 8.238672023879607e-05, 'learning_rate/action_query_proj': 8.238672023879607e-05, 'learning_rate/base': 2.059668005969902e-05, 'epoch': 0.41}) +[2026-07-27 05:14:41,329][starVLA.training.train_starvla][INFO] - Step 3410, Loss: {'train/loss': 0.06396453082561493, 'train/grad_norm_pre_clip': 2.6860010623931885, 'timing/data': 0.00017485907301306725, 'timing/model': 0.4697354668751359, 'learning_rate/action_model': 8.236336777182998e-05, 'learning_rate/action_query_proj': 8.236336777182998e-05, 'learning_rate/base': 2.0590841942957496e-05, 'epoch': 0.41}) +[2026-07-27 05:14:47,009][starVLA.training.train_starvla][INFO] - Step 3411, Loss: {'train/loss': 0.050363000482320786, 'train/grad_norm_pre_clip': 1.9780057668685913, 'timing/data': 0.00017732195556163788, 'timing/model': 0.47152721183374524, 'learning_rate/action_model': 8.234000331788714e-05, 'learning_rate/action_query_proj': 8.234000331788714e-05, 'learning_rate/base': 2.0585000829471786e-05, 'epoch': 0.41}) +[2026-07-27 05:14:52,674][starVLA.training.train_starvla][INFO] - Step 3412, Loss: {'train/loss': 0.09267272800207138, 'train/grad_norm_pre_clip': 2.8889622688293457, 'timing/data': 0.0001775519922375679, 'timing/model': 0.47169145196676254, 'learning_rate/action_model': 8.231662688619149e-05, 'learning_rate/action_query_proj': 8.231662688619149e-05, 'learning_rate/base': 2.0579156721547873e-05, 'epoch': 0.41}) +[2026-07-27 05:14:58,365][starVLA.training.train_starvla][INFO] - Step 3413, Loss: {'train/loss': 0.09328166395425797, 'train/grad_norm_pre_clip': 3.3426859378814697, 'timing/data': 0.00017250794917345047, 'timing/model': 0.48137520207092166, 'learning_rate/action_model': 8.229323848597169e-05, 'learning_rate/action_query_proj': 8.229323848597169e-05, 'learning_rate/base': 2.057330962149292e-05, 'epoch': 0.41}) +[2026-07-27 05:15:04,059][starVLA.training.train_starvla][INFO] - Step 3414, Loss: {'train/loss': 0.06821902841329575, 'train/grad_norm_pre_clip': 2.961207151412964, 'timing/data': 0.00018076831474900246, 'timing/model': 0.4863665350712836, 'learning_rate/action_model': 8.226983812646106e-05, 'learning_rate/action_query_proj': 8.226983812646106e-05, 'learning_rate/base': 2.0567459531615266e-05, 'epoch': 0.41}) +[2026-07-27 05:15:09,716][starVLA.training.train_starvla][INFO] - Step 3415, Loss: {'train/loss': 0.06847064942121506, 'train/grad_norm_pre_clip': 2.9788291454315186, 'timing/data': 0.0001771911047399044, 'timing/model': 0.4676916068419814, 'learning_rate/action_model': 8.224642581689773e-05, 'learning_rate/action_query_proj': 8.224642581689773e-05, 'learning_rate/base': 2.0561606454224433e-05, 'epoch': 0.41}) +[2026-07-27 05:15:15,388][starVLA.training.train_starvla][INFO] - Step 3416, Loss: {'train/loss': 0.06246274709701538, 'train/grad_norm_pre_clip': 2.6713876724243164, 'timing/data': 0.00017565209418535233, 'timing/model': 0.4729923871345818, 'learning_rate/action_model': 8.22230015665245e-05, 'learning_rate/action_query_proj': 8.22230015665245e-05, 'learning_rate/base': 2.0555750391631125e-05, 'epoch': 0.41}) +[2026-07-27 05:15:21,071][starVLA.training.train_starvla][INFO] - Step 3417, Loss: {'train/loss': 0.17643797397613525, 'train/grad_norm_pre_clip': 3.715951919555664, 'timing/data': 0.00017187092453241348, 'timing/model': 0.47189509123563766, 'learning_rate/action_model': 8.219956538458887e-05, 'learning_rate/action_query_proj': 8.219956538458887e-05, 'learning_rate/base': 2.0549891346147217e-05, 'epoch': 0.41}) +[2026-07-27 05:15:26,736][starVLA.training.train_starvla][INFO] - Step 3418, Loss: {'train/loss': 0.038895390927791595, 'train/grad_norm_pre_clip': 1.8921310901641846, 'timing/data': 0.00017718877643346786, 'timing/model': 0.48633363004773855, 'learning_rate/action_model': 8.217611728034312e-05, 'learning_rate/action_query_proj': 8.217611728034312e-05, 'learning_rate/base': 2.054402932008578e-05, 'epoch': 0.41}) +[2026-07-27 05:15:32,405][starVLA.training.train_starvla][INFO] - Step 3419, Loss: {'train/loss': 0.0766730010509491, 'train/grad_norm_pre_clip': 2.877114772796631, 'timing/data': 0.0001756572164595127, 'timing/model': 0.4652921911329031, 'learning_rate/action_model': 8.215265726304417e-05, 'learning_rate/action_query_proj': 8.215265726304417e-05, 'learning_rate/base': 2.0538164315761043e-05, 'epoch': 0.41}) +[2026-07-27 05:15:38,075][starVLA.training.train_starvla][INFO] - Step 3420, Loss: {'train/loss': 0.03874934837222099, 'train/grad_norm_pre_clip': 1.8959518671035767, 'timing/data': 0.0001777438446879387, 'timing/model': 0.46578195597976446, 'learning_rate/action_model': 8.212918534195363e-05, 'learning_rate/action_query_proj': 8.212918534195363e-05, 'learning_rate/base': 2.0532296335488408e-05, 'epoch': 0.41}) +[2026-07-27 05:15:43,993][starVLA.training.train_starvla][INFO] - Step 3421, Loss: {'train/loss': 0.08954377472400665, 'train/grad_norm_pre_clip': 3.275832176208496, 'timing/data': 0.00017600832507014275, 'timing/model': 0.4783381321467459, 'learning_rate/action_model': 8.210570152633788e-05, 'learning_rate/action_query_proj': 8.210570152633788e-05, 'learning_rate/base': 2.052642538158447e-05, 'epoch': 0.42}) +[2026-07-27 05:15:49,672][starVLA.training.train_starvla][INFO] - Step 3422, Loss: {'train/loss': 0.17828884720802307, 'train/grad_norm_pre_clip': 4.917215347290039, 'timing/data': 0.0001762700267136097, 'timing/model': 0.47540566977113485, 'learning_rate/action_model': 8.208220582546796e-05, 'learning_rate/action_query_proj': 8.208220582546796e-05, 'learning_rate/base': 2.052055145636699e-05, 'epoch': 0.42}) +[2026-07-27 05:15:55,359][starVLA.training.train_starvla][INFO] - Step 3423, Loss: {'train/loss': 0.11394960433244705, 'train/grad_norm_pre_clip': 3.104879379272461, 'timing/data': 0.00017787190154194832, 'timing/model': 0.47138211969286203, 'learning_rate/action_model': 8.205869824861957e-05, 'learning_rate/action_query_proj': 8.205869824861957e-05, 'learning_rate/base': 2.0514674562154894e-05, 'epoch': 0.42}) +[2026-07-27 05:16:01,023][starVLA.training.train_starvla][INFO] - Step 3424, Loss: {'train/loss': 0.055783383548259735, 'train/grad_norm_pre_clip': 2.9208598136901855, 'timing/data': 0.00017432216554880142, 'timing/model': 0.4753601588308811, 'learning_rate/action_model': 8.203517880507319e-05, 'learning_rate/action_query_proj': 8.203517880507319e-05, 'learning_rate/base': 2.0508794701268297e-05, 'epoch': 0.42}) +[2026-07-27 05:16:06,715][starVLA.training.train_starvla][INFO] - Step 3425, Loss: {'train/loss': 0.03631545230746269, 'train/grad_norm_pre_clip': 1.4423775672912598, 'timing/data': 0.00017801765352487564, 'timing/model': 0.4842133051715791, 'learning_rate/action_model': 8.201164750411387e-05, 'learning_rate/action_query_proj': 8.201164750411387e-05, 'learning_rate/base': 2.0502911876028467e-05, 'epoch': 0.42}) +[2026-07-27 05:16:12,377][starVLA.training.train_starvla][INFO] - Step 3426, Loss: {'train/loss': 0.06270492076873779, 'train/grad_norm_pre_clip': 2.3418102264404297, 'timing/data': 0.00017508771270513535, 'timing/model': 0.4728522961959243, 'learning_rate/action_model': 8.198810435503139e-05, 'learning_rate/action_query_proj': 8.198810435503139e-05, 'learning_rate/base': 2.0497026088757847e-05, 'epoch': 0.42}) +[2026-07-27 05:16:18,035][starVLA.training.train_starvla][INFO] - Step 3427, Loss: {'train/loss': 0.1061372235417366, 'train/grad_norm_pre_clip': 4.885290622711182, 'timing/data': 0.0001756078563630581, 'timing/model': 0.4751204811036587, 'learning_rate/action_model': 8.196454936712023e-05, 'learning_rate/action_query_proj': 8.196454936712023e-05, 'learning_rate/base': 2.0491137341780056e-05, 'epoch': 0.42}) +[2026-07-27 05:16:23,922][starVLA.training.train_starvla][INFO] - Step 3428, Loss: {'train/loss': 0.16545197367668152, 'train/grad_norm_pre_clip': 5.325961589813232, 'timing/data': 0.00018050707876682281, 'timing/model': 0.47380832210183144, 'learning_rate/action_model': 8.194098254967954e-05, 'learning_rate/action_query_proj': 8.194098254967954e-05, 'learning_rate/base': 2.0485245637419884e-05, 'epoch': 0.42}) +[2026-07-27 05:16:29,652][starVLA.training.train_starvla][INFO] - Step 3429, Loss: {'train/loss': 0.10843314975500107, 'train/grad_norm_pre_clip': 3.775346517562866, 'timing/data': 0.00017952872440218925, 'timing/model': 0.4708350342698395, 'learning_rate/action_model': 8.19174039120131e-05, 'learning_rate/action_query_proj': 8.19174039120131e-05, 'learning_rate/base': 2.0479350978003274e-05, 'epoch': 0.42}) +[2026-07-27 05:16:35,295][starVLA.training.train_starvla][INFO] - Step 3430, Loss: {'train/loss': 0.06479591876268387, 'train/grad_norm_pre_clip': 3.2682580947875977, 'timing/data': 0.00017771311104297638, 'timing/model': 0.47405573120340705, 'learning_rate/action_model': 8.18938134634294e-05, 'learning_rate/action_query_proj': 8.18938134634294e-05, 'learning_rate/base': 2.047345336585735e-05, 'epoch': 0.42}) +[2026-07-27 05:16:40,955][starVLA.training.train_starvla][INFO] - Step 3431, Loss: {'train/loss': 0.09486173838376999, 'train/grad_norm_pre_clip': 3.3767714500427246, 'timing/data': 0.00018102256581187248, 'timing/model': 0.4745065807364881, 'learning_rate/action_model': 8.187021121324157e-05, 'learning_rate/action_query_proj': 8.187021121324157e-05, 'learning_rate/base': 2.0467552803310393e-05, 'epoch': 0.42}) +[2026-07-27 05:16:46,552][starVLA.training.train_starvla][INFO] - Step 3432, Loss: {'train/loss': 0.07817026227712631, 'train/grad_norm_pre_clip': 4.281098365783691, 'timing/data': 0.00017793895676732063, 'timing/model': 0.4745661118067801, 'learning_rate/action_model': 8.184659717076741e-05, 'learning_rate/action_query_proj': 8.184659717076741e-05, 'learning_rate/base': 2.0461649292691854e-05, 'epoch': 0.42}) +[2026-07-27 05:16:52,152][starVLA.training.train_starvla][INFO] - Step 3433, Loss: {'train/loss': 0.13502828776836395, 'train/grad_norm_pre_clip': 3.9768877029418945, 'timing/data': 0.00017544487491250038, 'timing/model': 0.46913353307172656, 'learning_rate/action_model': 8.182297134532938e-05, 'learning_rate/action_query_proj': 8.182297134532938e-05, 'learning_rate/base': 2.0455742836332346e-05, 'epoch': 0.42}) +[2026-07-27 05:16:57,758][starVLA.training.train_starvla][INFO] - Step 3434, Loss: {'train/loss': 0.06805933266878128, 'train/grad_norm_pre_clip': 2.989788055419922, 'timing/data': 0.00017665186896920204, 'timing/model': 0.4695480139926076, 'learning_rate/action_model': 8.179933374625454e-05, 'learning_rate/action_query_proj': 8.179933374625454e-05, 'learning_rate/base': 2.0449833436563636e-05, 'epoch': 0.42}) +[2026-07-27 05:17:03,372][starVLA.training.train_starvla][INFO] - Step 3435, Loss: {'train/loss': 0.14508824050426483, 'train/grad_norm_pre_clip': 3.5208730697631836, 'timing/data': 0.0001787850633263588, 'timing/model': 0.4683691509999335, 'learning_rate/action_model': 8.17756843828747e-05, 'learning_rate/action_query_proj': 8.17756843828747e-05, 'learning_rate/base': 2.0443921095718674e-05, 'epoch': 0.42}) +[2026-07-27 05:17:09,006][starVLA.training.train_starvla][INFO] - Step 3436, Loss: {'train/loss': 0.08872077614068985, 'train/grad_norm_pre_clip': 4.147454738616943, 'timing/data': 0.00017694616690278053, 'timing/model': 0.4695783080533147, 'learning_rate/action_model': 8.17520232645262e-05, 'learning_rate/action_query_proj': 8.17520232645262e-05, 'learning_rate/base': 2.043800581613155e-05, 'epoch': 0.42}) +[2026-07-27 05:17:14,650][starVLA.training.train_starvla][INFO] - Step 3437, Loss: {'train/loss': 0.08933795988559723, 'train/grad_norm_pre_clip': 3.9724459648132324, 'timing/data': 0.00017334893345832825, 'timing/model': 0.4771125689148903, 'learning_rate/action_model': 8.17283504005501e-05, 'learning_rate/action_query_proj': 8.17283504005501e-05, 'learning_rate/base': 2.0432087600137525e-05, 'epoch': 0.42}) +[2026-07-27 05:17:20,263][starVLA.training.train_starvla][INFO] - Step 3438, Loss: {'train/loss': 0.21314382553100586, 'train/grad_norm_pre_clip': 4.595233917236328, 'timing/data': 0.00017652008682489395, 'timing/model': 0.47650011675432324, 'learning_rate/action_model': 8.170466580029207e-05, 'learning_rate/action_query_proj': 8.170466580029207e-05, 'learning_rate/base': 2.0426166450073018e-05, 'epoch': 0.42}) +[2026-07-27 05:17:25,879][starVLA.training.train_starvla][INFO] - Step 3439, Loss: {'train/loss': 0.0792696624994278, 'train/grad_norm_pre_clip': 2.8609490394592285, 'timing/data': 0.000173238106071949, 'timing/model': 0.4705200847238302, 'learning_rate/action_model': 8.168096947310241e-05, 'learning_rate/action_query_proj': 8.168096947310241e-05, 'learning_rate/base': 2.0420242368275603e-05, 'epoch': 0.42}) +[2026-07-27 05:17:31,501][starVLA.training.train_starvla][INFO] - Step 3440, Loss: {'train/loss': 0.04829647019505501, 'train/grad_norm_pre_clip': 2.144767999649048, 'timing/data': 0.00017332704737782478, 'timing/model': 0.47036023810505867, 'learning_rate/action_model': 8.165726142833606e-05, 'learning_rate/action_query_proj': 8.165726142833606e-05, 'learning_rate/base': 2.0414315357084015e-05, 'epoch': 0.42}) +[2026-07-27 05:17:37,140][starVLA.training.train_starvla][INFO] - Step 3441, Loss: {'train/loss': 0.07833129167556763, 'train/grad_norm_pre_clip': 2.2505879402160645, 'timing/data': 0.00017730379477143288, 'timing/model': 0.4703609421849251, 'learning_rate/action_model': 8.163354167535257e-05, 'learning_rate/action_query_proj': 8.163354167535257e-05, 'learning_rate/base': 2.0408385418838143e-05, 'epoch': 0.42}) +[2026-07-27 05:17:42,792][starVLA.training.train_starvla][INFO] - Step 3442, Loss: {'train/loss': 0.03526850789785385, 'train/grad_norm_pre_clip': 1.9344539642333984, 'timing/data': 0.0001747901551425457, 'timing/model': 0.47100405814126134, 'learning_rate/action_model': 8.160981022351615e-05, 'learning_rate/action_query_proj': 8.160981022351615e-05, 'learning_rate/base': 2.0402452555879038e-05, 'epoch': 0.42}) +[2026-07-27 05:17:48,434][starVLA.training.train_starvla][INFO] - Step 3443, Loss: {'train/loss': 0.07518920302391052, 'train/grad_norm_pre_clip': 2.687105894088745, 'timing/data': 0.00017234822735190392, 'timing/model': 0.4766392409801483, 'learning_rate/action_model': 8.158606708219555e-05, 'learning_rate/action_query_proj': 8.158606708219555e-05, 'learning_rate/base': 2.0396516770548888e-05, 'epoch': 0.42}) +[2026-07-27 05:17:54,078][starVLA.training.train_starvla][INFO] - Step 3444, Loss: {'train/loss': 0.12101639807224274, 'train/grad_norm_pre_clip': 1.732218623161316, 'timing/data': 0.0001805308274924755, 'timing/model': 0.47692203940823674, 'learning_rate/action_model': 8.156231226076425e-05, 'learning_rate/action_query_proj': 8.156231226076425e-05, 'learning_rate/base': 2.039057806519106e-05, 'epoch': 0.42}) +[2026-07-27 05:17:59,716][starVLA.training.train_starvla][INFO] - Step 3445, Loss: {'train/loss': 0.10366703569889069, 'train/grad_norm_pre_clip': 3.5617754459381104, 'timing/data': 0.00017677899450063705, 'timing/model': 0.4695707396604121, 'learning_rate/action_model': 8.153854576860024e-05, 'learning_rate/action_query_proj': 8.153854576860024e-05, 'learning_rate/base': 2.038463644215006e-05, 'epoch': 0.42}) +[2026-07-27 05:18:05,352][starVLA.training.train_starvla][INFO] - Step 3446, Loss: {'train/loss': 0.13279326260089874, 'train/grad_norm_pre_clip': 4.443547248840332, 'timing/data': 0.00018820399418473244, 'timing/model': 0.4637264176271856, 'learning_rate/action_model': 8.151476761508615e-05, 'learning_rate/action_query_proj': 8.151476761508615e-05, 'learning_rate/base': 2.0378691903771538e-05, 'epoch': 0.42}) +[2026-07-27 05:18:10,989][starVLA.training.train_starvla][INFO] - Step 3447, Loss: {'train/loss': 0.07362795621156693, 'train/grad_norm_pre_clip': 2.934753179550171, 'timing/data': 0.00017801625654101372, 'timing/model': 0.4632504526525736, 'learning_rate/action_model': 8.149097780960924e-05, 'learning_rate/action_query_proj': 8.149097780960924e-05, 'learning_rate/base': 2.037274445240231e-05, 'epoch': 0.42}) +[2026-07-27 05:18:16,620][starVLA.training.train_starvla][INFO] - Step 3448, Loss: {'train/loss': 0.030038906261324883, 'train/grad_norm_pre_clip': 1.714049220085144, 'timing/data': 0.00017690425738692284, 'timing/model': 0.4616400869563222, 'learning_rate/action_model': 8.146717636156133e-05, 'learning_rate/action_query_proj': 8.146717636156133e-05, 'learning_rate/base': 2.036679409039033e-05, 'epoch': 0.42}) +[2026-07-27 05:18:22,259][starVLA.training.train_starvla][INFO] - Step 3449, Loss: {'train/loss': 0.1085909828543663, 'train/grad_norm_pre_clip': 2.7581064701080322, 'timing/data': 0.00017198314890265465, 'timing/model': 0.46285084215924144, 'learning_rate/action_model': 8.144336328033886e-05, 'learning_rate/action_query_proj': 8.144336328033886e-05, 'learning_rate/base': 2.0360840820084715e-05, 'epoch': 0.42}) +[2026-07-27 05:18:27,918][starVLA.training.train_starvla][INFO] - Step 3450, Loss: {'train/loss': 0.027679981663823128, 'train/grad_norm_pre_clip': 1.7034306526184082, 'timing/data': 0.00018753623589873314, 'timing/model': 0.462660894729197, 'learning_rate/action_model': 8.141953857534288e-05, 'learning_rate/action_query_proj': 8.141953857534288e-05, 'learning_rate/base': 2.035488464383572e-05, 'epoch': 0.42}) +[2026-07-27 05:18:33,549][starVLA.training.train_starvla][INFO] - Step 3451, Loss: {'train/loss': 0.06309824436903, 'train/grad_norm_pre_clip': 3.319711208343506, 'timing/data': 0.00017855921760201454, 'timing/model': 0.4607496652752161, 'learning_rate/action_model': 8.139570225597897e-05, 'learning_rate/action_query_proj': 8.139570225597897e-05, 'learning_rate/base': 2.0348925563994743e-05, 'epoch': 0.42}) +[2026-07-27 05:18:39,204][starVLA.training.train_starvla][INFO] - Step 3452, Loss: {'train/loss': 0.12468408048152924, 'train/grad_norm_pre_clip': 4.3325700759887695, 'timing/data': 0.00017372379079461098, 'timing/model': 0.4624294522218406, 'learning_rate/action_model': 8.137185433165734e-05, 'learning_rate/action_query_proj': 8.137185433165734e-05, 'learning_rate/base': 2.0342963582914336e-05, 'epoch': 0.42}) +[2026-07-27 05:18:44,886][starVLA.training.train_starvla][INFO] - Step 3453, Loss: {'train/loss': 0.06643470376729965, 'train/grad_norm_pre_clip': 3.029078483581543, 'timing/data': 0.0001766318455338478, 'timing/model': 0.4622148126363754, 'learning_rate/action_model': 8.13479948117928e-05, 'learning_rate/action_query_proj': 8.13479948117928e-05, 'learning_rate/base': 2.03369987029482e-05, 'epoch': 0.42}) +[2026-07-27 05:18:50,546][starVLA.training.train_starvla][INFO] - Step 3454, Loss: {'train/loss': 0.12380287051200867, 'train/grad_norm_pre_clip': 3.5431065559387207, 'timing/data': 0.00017700716853141785, 'timing/model': 0.4601223859935999, 'learning_rate/action_model': 8.132412370580468e-05, 'learning_rate/action_query_proj': 8.132412370580468e-05, 'learning_rate/base': 2.033103092645117e-05, 'epoch': 0.42}) +[2026-07-27 05:18:56,209][starVLA.training.train_starvla][INFO] - Step 3455, Loss: {'train/loss': 0.11358708143234253, 'train/grad_norm_pre_clip': 2.836503028869629, 'timing/data': 0.00017753290012478828, 'timing/model': 0.4639929477125406, 'learning_rate/action_model': 8.130024102311692e-05, 'learning_rate/action_query_proj': 8.130024102311692e-05, 'learning_rate/base': 2.032506025577923e-05, 'epoch': 0.42}) +[2026-07-27 05:19:01,865][starVLA.training.train_starvla][INFO] - Step 3456, Loss: {'train/loss': 0.23339654505252838, 'train/grad_norm_pre_clip': 5.903305530548096, 'timing/data': 0.00018508685752749443, 'timing/model': 0.46498705307021737, 'learning_rate/action_model': 8.127634677315804e-05, 'learning_rate/action_query_proj': 8.127634677315804e-05, 'learning_rate/base': 2.031908669328951e-05, 'epoch': 0.42}) +[2026-07-27 05:19:07,576][starVLA.training.train_starvla][INFO] - Step 3457, Loss: {'train/loss': 0.052043233066797256, 'train/grad_norm_pre_clip': 2.8133325576782227, 'timing/data': 0.00017776619642972946, 'timing/model': 0.46499515138566494, 'learning_rate/action_model': 8.125244096536111e-05, 'learning_rate/action_query_proj': 8.125244096536111e-05, 'learning_rate/base': 2.0313110241340277e-05, 'epoch': 0.42}) +[2026-07-27 05:19:13,260][starVLA.training.train_starvla][INFO] - Step 3458, Loss: {'train/loss': 0.15329642593860626, 'train/grad_norm_pre_clip': 3.9892280101776123, 'timing/data': 0.00017558503895998, 'timing/model': 0.46413325471803546, 'learning_rate/action_model': 8.122852360916373e-05, 'learning_rate/action_query_proj': 8.122852360916373e-05, 'learning_rate/base': 2.0307130902290933e-05, 'epoch': 0.42}) +[2026-07-27 05:19:18,951][starVLA.training.train_starvla][INFO] - Step 3459, Loss: {'train/loss': 0.09528344869613647, 'train/grad_norm_pre_clip': 2.386992931365967, 'timing/data': 0.00017518410459160805, 'timing/model': 0.4625791269354522, 'learning_rate/action_model': 8.120459471400815e-05, 'learning_rate/action_query_proj': 8.120459471400815e-05, 'learning_rate/base': 2.0301148678502037e-05, 'epoch': 0.42}) +[2026-07-27 05:19:24,591][starVLA.training.train_starvla][INFO] - Step 3460, Loss: {'train/loss': 0.05277182534337044, 'train/grad_norm_pre_clip': 3.0551888942718506, 'timing/data': 0.00017285579815506935, 'timing/model': 0.46445817733183503, 'learning_rate/action_model': 8.118065428934107e-05, 'learning_rate/action_query_proj': 8.118065428934107e-05, 'learning_rate/base': 2.0295163572335267e-05, 'epoch': 0.42}) +[2026-07-27 05:19:30,244][starVLA.training.train_starvla][INFO] - Step 3461, Loss: {'train/loss': 0.21794404089450836, 'train/grad_norm_pre_clip': 4.529716491699219, 'timing/data': 0.00017608702182769775, 'timing/model': 0.4619548371993005, 'learning_rate/action_model': 8.11567023446138e-05, 'learning_rate/action_query_proj': 8.11567023446138e-05, 'learning_rate/base': 2.028917558615345e-05, 'epoch': 0.42}) +[2026-07-27 05:19:35,921][starVLA.training.train_starvla][INFO] - Step 3462, Loss: {'train/loss': 0.13779260218143463, 'train/grad_norm_pre_clip': 3.8069028854370117, 'timing/data': 0.00017681298777461052, 'timing/model': 0.4635297558270395, 'learning_rate/action_model': 8.11327388892822e-05, 'learning_rate/action_query_proj': 8.11327388892822e-05, 'learning_rate/base': 2.028318472232055e-05, 'epoch': 0.42}) +[2026-07-27 05:19:41,559][starVLA.training.train_starvla][INFO] - Step 3463, Loss: {'train/loss': 0.0776498094201088, 'train/grad_norm_pre_clip': 3.038693904876709, 'timing/data': 0.00017712730914354324, 'timing/model': 0.46193392807617784, 'learning_rate/action_model': 8.110876393280667e-05, 'learning_rate/action_query_proj': 8.110876393280667e-05, 'learning_rate/base': 2.0277190983201668e-05, 'epoch': 0.42}) +[2026-07-27 05:19:47,214][starVLA.training.train_starvla][INFO] - Step 3464, Loss: {'train/loss': 0.2107764631509781, 'train/grad_norm_pre_clip': 4.401660442352295, 'timing/data': 0.00017560413107275963, 'timing/model': 0.46245405403897166, 'learning_rate/action_model': 8.108477748465214e-05, 'learning_rate/action_query_proj': 8.108477748465214e-05, 'learning_rate/base': 2.0271194371163034e-05, 'epoch': 0.42}) +[2026-07-27 05:19:52,869][starVLA.training.train_starvla][INFO] - Step 3465, Loss: {'train/loss': 0.09410576522350311, 'train/grad_norm_pre_clip': 1.9317364692687988, 'timing/data': 0.0001740981824696064, 'timing/model': 0.4603527090512216, 'learning_rate/action_model': 8.106077955428806e-05, 'learning_rate/action_query_proj': 8.106077955428806e-05, 'learning_rate/base': 2.0265194888572016e-05, 'epoch': 0.42}) +[2026-07-27 05:19:58,509][starVLA.training.train_starvla][INFO] - Step 3466, Loss: {'train/loss': 0.08878491073846817, 'train/grad_norm_pre_clip': 3.706529140472412, 'timing/data': 0.0001760232262313366, 'timing/model': 0.46504806308075786, 'learning_rate/action_model': 8.103677015118847e-05, 'learning_rate/action_query_proj': 8.103677015118847e-05, 'learning_rate/base': 2.0259192537797118e-05, 'epoch': 0.42}) +[2026-07-27 05:20:04,094][starVLA.training.train_starvla][INFO] - Step 3467, Loss: {'train/loss': 0.011110372841358185, 'train/grad_norm_pre_clip': 0.6021820902824402, 'timing/data': 0.0001827678643167019, 'timing/model': 0.46395184379071, 'learning_rate/action_model': 8.101274928483186e-05, 'learning_rate/action_query_proj': 8.101274928483186e-05, 'learning_rate/base': 2.0253187321207964e-05, 'epoch': 0.42}) +[2026-07-27 05:20:09,682][starVLA.training.train_starvla][INFO] - Step 3468, Loss: {'train/loss': 0.1246153712272644, 'train/grad_norm_pre_clip': 3.823570489883423, 'timing/data': 0.00017555290833115578, 'timing/model': 0.464328374247998, 'learning_rate/action_model': 8.098871696470128e-05, 'learning_rate/action_query_proj': 8.098871696470128e-05, 'learning_rate/base': 2.024717924117532e-05, 'epoch': 0.42}) +[2026-07-27 05:20:15,335][starVLA.training.train_starvla][INFO] - Step 3469, Loss: {'train/loss': 0.07068074494600296, 'train/grad_norm_pre_clip': 2.8813633918762207, 'timing/data': 0.0001852288842201233, 'timing/model': 0.46223995415493846, 'learning_rate/action_model': 8.096467320028438e-05, 'learning_rate/action_query_proj': 8.096467320028438e-05, 'learning_rate/base': 2.0241168300071096e-05, 'epoch': 0.42}) +[2026-07-27 05:20:20,973][starVLA.training.train_starvla][INFO] - Step 3470, Loss: {'train/loss': 0.05463471636176109, 'train/grad_norm_pre_clip': 2.3364975452423096, 'timing/data': 0.00017315801233053207, 'timing/model': 0.46219498896971345, 'learning_rate/action_model': 8.09406180010732e-05, 'learning_rate/action_query_proj': 8.09406180010732e-05, 'learning_rate/base': 2.02351545002683e-05, 'epoch': 0.42}) +[2026-07-27 05:20:26,607][starVLA.training.train_starvla][INFO] - Step 3471, Loss: {'train/loss': 0.09024705737829208, 'train/grad_norm_pre_clip': 2.403219223022461, 'timing/data': 0.00017617084085941315, 'timing/model': 0.4616686552762985, 'learning_rate/action_model': 8.091655137656434e-05, 'learning_rate/action_query_proj': 8.091655137656434e-05, 'learning_rate/base': 2.0229137844141086e-05, 'epoch': 0.42}) +[2026-07-27 05:20:32,246][starVLA.training.train_starvla][INFO] - Step 3472, Loss: {'train/loss': 0.08143853396177292, 'train/grad_norm_pre_clip': 2.9964683055877686, 'timing/data': 0.00018176622688770294, 'timing/model': 0.4630071669816971, 'learning_rate/action_model': 8.089247333625897e-05, 'learning_rate/action_query_proj': 8.089247333625897e-05, 'learning_rate/base': 2.022311833406474e-05, 'epoch': 0.42}) +[2026-07-27 05:20:38,071][starVLA.training.train_starvla][INFO] - Step 3473, Loss: {'train/loss': 0.20266272127628326, 'train/grad_norm_pre_clip': 5.233218669891357, 'timing/data': 0.0001756139099597931, 'timing/model': 0.46401377487927675, 'learning_rate/action_model': 8.08683838896627e-05, 'learning_rate/action_query_proj': 8.08683838896627e-05, 'learning_rate/base': 2.0217095972415676e-05, 'epoch': 0.42}) +[2026-07-27 05:20:43,665][starVLA.training.train_starvla][INFO] - Step 3474, Loss: {'train/loss': 0.15001867711544037, 'train/grad_norm_pre_clip': 4.087925910949707, 'timing/data': 0.00017779506742954254, 'timing/model': 0.4657846367917955, 'learning_rate/action_model': 8.084428304628563e-05, 'learning_rate/action_query_proj': 8.084428304628563e-05, 'learning_rate/base': 2.0211070761571407e-05, 'epoch': 0.42}) +[2026-07-27 05:20:49,244][starVLA.training.train_starvla][INFO] - Step 3475, Loss: {'train/loss': 0.04393264278769493, 'train/grad_norm_pre_clip': 2.262026786804199, 'timing/data': 0.00018675904721021652, 'timing/model': 0.4617913910187781, 'learning_rate/action_model': 8.082017081564244e-05, 'learning_rate/action_query_proj': 8.082017081564244e-05, 'learning_rate/base': 2.020504270391061e-05, 'epoch': 0.42}) +[2026-07-27 05:20:54,830][starVLA.training.train_starvla][INFO] - Step 3476, Loss: {'train/loss': 0.07373200356960297, 'train/grad_norm_pre_clip': 2.65696120262146, 'timing/data': 0.00017370516434311867, 'timing/model': 0.4646252989768982, 'learning_rate/action_model': 8.079604720725223e-05, 'learning_rate/action_query_proj': 8.079604720725223e-05, 'learning_rate/base': 2.0199011801813058e-05, 'epoch': 0.42}) +[2026-07-27 05:21:00,421][starVLA.training.train_starvla][INFO] - Step 3477, Loss: {'train/loss': 0.17141783237457275, 'train/grad_norm_pre_clip': 3.8405802249908447, 'timing/data': 0.00017472123727202415, 'timing/model': 0.46318592317402363, 'learning_rate/action_model': 8.077191223063862e-05, 'learning_rate/action_query_proj': 8.077191223063862e-05, 'learning_rate/base': 2.0192978057659655e-05, 'epoch': 0.42}) +[2026-07-27 05:21:06,030][starVLA.training.train_starvla][INFO] - Step 3478, Loss: {'train/loss': 0.08806704729795456, 'train/grad_norm_pre_clip': 2.6386420726776123, 'timing/data': 0.000178581103682518, 'timing/model': 0.461223809979856, 'learning_rate/action_model': 8.074776589532973e-05, 'learning_rate/action_query_proj': 8.074776589532973e-05, 'learning_rate/base': 2.0186941473832433e-05, 'epoch': 0.42}) +[2026-07-27 05:21:11,617][starVLA.training.train_starvla][INFO] - Step 3479, Loss: {'train/loss': 0.12649646401405334, 'train/grad_norm_pre_clip': 3.656421184539795, 'timing/data': 0.00017763115465641022, 'timing/model': 0.4632520698942244, 'learning_rate/action_model': 8.072360821085813e-05, 'learning_rate/action_query_proj': 8.072360821085813e-05, 'learning_rate/base': 2.0180902052714534e-05, 'epoch': 0.42}) +[2026-07-27 05:21:17,195][starVLA.training.train_starvla][INFO] - Step 3480, Loss: {'train/loss': 0.11522095650434494, 'train/grad_norm_pre_clip': 2.6880979537963867, 'timing/data': 0.00017633801326155663, 'timing/model': 0.46400795923545957, 'learning_rate/action_model': 8.069943918676091e-05, 'learning_rate/action_query_proj': 8.069943918676091e-05, 'learning_rate/base': 2.017485979669023e-05, 'epoch': 0.42}) +[2026-07-27 05:21:22,785][starVLA.training.train_starvla][INFO] - Step 3481, Loss: {'train/loss': 0.13706311583518982, 'train/grad_norm_pre_clip': 5.198042869567871, 'timing/data': 0.0001738518476486206, 'timing/model': 0.46427829284220934, 'learning_rate/action_model': 8.067525883257962e-05, 'learning_rate/action_query_proj': 8.067525883257962e-05, 'learning_rate/base': 2.0168814708144905e-05, 'epoch': 0.42}) +[2026-07-27 05:21:28,379][starVLA.training.train_starvla][INFO] - Step 3482, Loss: {'train/loss': 0.11718963831663132, 'train/grad_norm_pre_clip': 3.46201491355896, 'timing/data': 0.00017540529370307922, 'timing/model': 0.45950028812512755, 'learning_rate/action_model': 8.065106715786024e-05, 'learning_rate/action_query_proj': 8.065106715786024e-05, 'learning_rate/base': 2.016276678946506e-05, 'epoch': 0.42}) +[2026-07-27 05:21:33,962][starVLA.training.train_starvla][INFO] - Step 3483, Loss: {'train/loss': 0.04318979009985924, 'train/grad_norm_pre_clip': 2.164336919784546, 'timing/data': 0.00017818110063672066, 'timing/model': 0.46392650017514825, 'learning_rate/action_model': 8.062686417215332e-05, 'learning_rate/action_query_proj': 8.062686417215332e-05, 'learning_rate/base': 2.015671604303833e-05, 'epoch': 0.42}) +[2026-07-27 05:21:39,563][starVLA.training.train_starvla][INFO] - Step 3484, Loss: {'train/loss': 0.14927157759666443, 'train/grad_norm_pre_clip': 4.605392932891846, 'timing/data': 0.00017663929611444473, 'timing/model': 0.463531831279397, 'learning_rate/action_model': 8.060264988501378e-05, 'learning_rate/action_query_proj': 8.060264988501378e-05, 'learning_rate/base': 2.0150662471253444e-05, 'epoch': 0.42}) +[2026-07-27 05:21:45,171][starVLA.training.train_starvla][INFO] - Step 3485, Loss: {'train/loss': 0.08686166256666183, 'train/grad_norm_pre_clip': 2.9922640323638916, 'timing/data': 0.00017719296738505363, 'timing/model': 0.46231167018413544, 'learning_rate/action_model': 8.057842430600105e-05, 'learning_rate/action_query_proj': 8.057842430600105e-05, 'learning_rate/base': 2.0144606076500262e-05, 'epoch': 0.42}) +[2026-07-27 05:21:50,803][starVLA.training.train_starvla][INFO] - Step 3486, Loss: {'train/loss': 0.10251763463020325, 'train/grad_norm_pre_clip': 3.0379860401153564, 'timing/data': 0.00018330803140997887, 'timing/model': 0.4612269802019, 'learning_rate/action_model': 8.055418744467899e-05, 'learning_rate/action_query_proj': 8.055418744467899e-05, 'learning_rate/base': 2.0138546861169747e-05, 'epoch': 0.42}) +[2026-07-27 05:21:56,401][starVLA.training.train_starvla][INFO] - Step 3487, Loss: {'train/loss': 0.059966206550598145, 'train/grad_norm_pre_clip': 2.5165598392486572, 'timing/data': 0.00017694011330604553, 'timing/model': 0.46389494324103, 'learning_rate/action_model': 8.052993931061594e-05, 'learning_rate/action_query_proj': 8.052993931061594e-05, 'learning_rate/base': 2.0132484827653986e-05, 'epoch': 0.42}) +[2026-07-27 05:22:02,035][starVLA.training.train_starvla][INFO] - Step 3488, Loss: {'train/loss': 0.07547419518232346, 'train/grad_norm_pre_clip': 2.7466814517974854, 'timing/data': 0.00017842929810285568, 'timing/model': 0.4646523091942072, 'learning_rate/action_model': 8.050567991338467e-05, 'learning_rate/action_query_proj': 8.050567991338467e-05, 'learning_rate/base': 2.0126419978346168e-05, 'epoch': 0.42}) +[2026-07-27 05:22:07,866][starVLA.training.train_starvla][INFO] - Step 3489, Loss: {'train/loss': 0.2050943374633789, 'train/grad_norm_pre_clip': 3.526909351348877, 'timing/data': 0.00018223561346530914, 'timing/model': 0.47718303091824055, 'learning_rate/action_model': 8.048140926256242e-05, 'learning_rate/action_query_proj': 8.048140926256242e-05, 'learning_rate/base': 2.0120352315640604e-05, 'epoch': 0.42}) +[2026-07-27 05:22:13,537][starVLA.training.train_starvla][INFO] - Step 3490, Loss: {'train/loss': 0.052581608295440674, 'train/grad_norm_pre_clip': 2.55873441696167, 'timing/data': 0.00017716595903038979, 'timing/model': 0.4846116090193391, 'learning_rate/action_model': 8.045712736773086e-05, 'learning_rate/action_query_proj': 8.045712736773086e-05, 'learning_rate/base': 2.0114281841932714e-05, 'epoch': 0.42}) +[2026-07-27 05:22:19,186][starVLA.training.train_starvla][INFO] - Step 3491, Loss: {'train/loss': 0.13002285361289978, 'train/grad_norm_pre_clip': 5.008317947387695, 'timing/data': 0.00017702020704746246, 'timing/model': 0.4656989420764148, 'learning_rate/action_model': 8.043283423847606e-05, 'learning_rate/action_query_proj': 8.043283423847606e-05, 'learning_rate/base': 2.0108208559619015e-05, 'epoch': 0.42}) +[2026-07-27 05:22:24,808][starVLA.training.train_starvla][INFO] - Step 3492, Loss: {'train/loss': 0.2138640582561493, 'train/grad_norm_pre_clip': 4.645137786865234, 'timing/data': 0.0001727505587041378, 'timing/model': 0.46414998499676585, 'learning_rate/action_model': 8.040852988438861e-05, 'learning_rate/action_query_proj': 8.040852988438861e-05, 'learning_rate/base': 2.0102132471097153e-05, 'epoch': 0.42}) +[2026-07-27 05:22:30,433][starVLA.training.train_starvla][INFO] - Step 3493, Loss: {'train/loss': 0.11106009781360626, 'train/grad_norm_pre_clip': 3.294691801071167, 'timing/data': 0.00017383694648742676, 'timing/model': 0.4643195169046521, 'learning_rate/action_model': 8.038421431506348e-05, 'learning_rate/action_query_proj': 8.038421431506348e-05, 'learning_rate/base': 2.009605357876587e-05, 'epoch': 0.42}) +[2026-07-27 05:22:36,041][starVLA.training.train_starvla][INFO] - Step 3494, Loss: {'train/loss': 0.11615157127380371, 'train/grad_norm_pre_clip': 4.0977959632873535, 'timing/data': 0.0001732083037495613, 'timing/model': 0.4598673488944769, 'learning_rate/action_model': 8.035988754010004e-05, 'learning_rate/action_query_proj': 8.035988754010004e-05, 'learning_rate/base': 2.008997188502501e-05, 'epoch': 0.42}) +[2026-07-27 05:22:41,675][starVLA.training.train_starvla][INFO] - Step 3495, Loss: {'train/loss': 0.05853135511279106, 'train/grad_norm_pre_clip': 3.0842254161834717, 'timing/data': 0.00018729595467448235, 'timing/model': 0.4655142491683364, 'learning_rate/action_model': 8.033554956910214e-05, 'learning_rate/action_query_proj': 8.033554956910214e-05, 'learning_rate/base': 2.0083887392275534e-05, 'epoch': 0.42}) +[2026-07-27 05:22:47,324][starVLA.training.train_starvla][INFO] - Step 3496, Loss: {'train/loss': 0.07038387656211853, 'train/grad_norm_pre_clip': 2.299437999725342, 'timing/data': 0.0001885569654405117, 'timing/model': 0.4578330288641155, 'learning_rate/action_model': 8.031120041167801e-05, 'learning_rate/action_query_proj': 8.031120041167801e-05, 'learning_rate/base': 2.0077800102919503e-05, 'epoch': 0.42}) +[2026-07-27 05:22:52,968][starVLA.training.train_starvla][INFO] - Step 3497, Loss: {'train/loss': 0.06836427003145218, 'train/grad_norm_pre_clip': 2.6782617568969727, 'timing/data': 0.0001877979375422001, 'timing/model': 0.4644119939766824, 'learning_rate/action_model': 8.028684007744033e-05, 'learning_rate/action_query_proj': 8.028684007744033e-05, 'learning_rate/base': 2.0071710019360084e-05, 'epoch': 0.42}) +[2026-07-27 05:22:58,701][starVLA.training.train_starvla][INFO] - Step 3498, Loss: {'train/loss': 0.05530105158686638, 'train/grad_norm_pre_clip': 2.5384774208068848, 'timing/data': 0.00018094340339303017, 'timing/model': 0.4717812701128423, 'learning_rate/action_model': 8.026246857600616e-05, 'learning_rate/action_query_proj': 8.026246857600616e-05, 'learning_rate/base': 2.006561714400154e-05, 'epoch': 0.42}) +[2026-07-27 05:23:04,369][starVLA.training.train_starvla][INFO] - Step 3499, Loss: {'train/loss': 0.18207497894763947, 'train/grad_norm_pre_clip': 6.376441955566406, 'timing/data': 0.0001760059967637062, 'timing/model': 0.4680551439523697, 'learning_rate/action_model': 8.0238085916997e-05, 'learning_rate/action_query_proj': 8.0238085916997e-05, 'learning_rate/base': 2.005952147924925e-05, 'epoch': 0.42}) +[2026-07-27 05:23:10,091][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 3500 +[2026-07-27 05:23:10,092][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 3500 +[2026-07-27 05:23:10,093][starVLA.training.train_starvla][INFO] - Step 3500, Loss: {'train/loss': 0.12660586833953857, 'train/grad_norm_pre_clip': 4.217858791351318, 'timing/data': 0.00017793010920286179, 'timing/model': 0.4751365799456835, 'learning_rate/action_model': 8.021369211003871e-05, 'learning_rate/action_query_proj': 8.021369211003871e-05, 'learning_rate/base': 2.0053423027509678e-05, 'epoch': 0.42}) +[2026-07-27 05:23:10,097][accelerate.accelerator][INFO] - Saving current state to /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_3500_state +[2026-07-27 05:23:10,097][accelerate.accelerator][INFO] - Saving DeepSpeed Model and Optimizer +[2026-07-27 05:23:56,490][accelerate.accelerator][INFO] - DeepSpeed Model and Optimizer saved to output dir /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_3500_state/pytorch_model +[2026-07-27 05:23:56,490][accelerate.checkpointing][INFO] - Sampler state for dataloader 0 saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_3500_state/sampler.bin +[2026-07-27 05:23:56,498][accelerate.checkpointing][INFO] - Random states saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_3500_state/random_states_0.pkl +[2026-07-27 05:24:36,228][starVLA.training.rl_games.checkpoint_sync][INFO] - HF checkpoint sync disabled; skipping upload for step 3500 +[2026-07-27 05:24:36,228][starVLA.training.train_starvla][INFO] - 📊 Saving accessed configuration... +[2026-07-27 05:24:36,243][starVLA.training.train_starvla][INFO] - ✅ Configuration files saved +[2026-07-27 05:24:41,951][starVLA.training.train_starvla][INFO] - Step 3501, Loss: {'train/loss': 0.08774793893098831, 'train/grad_norm_pre_clip': 3.382258176803589, 'timing/data': 0.00017395569011569023, 'timing/model': 0.47372547443956137, 'learning_rate/action_model': 8.018928716476159e-05, 'learning_rate/action_query_proj': 8.018928716476159e-05, 'learning_rate/base': 2.0047321791190397e-05, 'epoch': 0.42}) +[2026-07-27 05:24:47,603][starVLA.training.train_starvla][INFO] - Step 3502, Loss: {'train/loss': 0.13443753123283386, 'train/grad_norm_pre_clip': 3.9365100860595703, 'timing/data': 0.00017656292766332626, 'timing/model': 0.4732049508020282, 'learning_rate/action_model': 8.016487109080034e-05, 'learning_rate/action_query_proj': 8.016487109080034e-05, 'learning_rate/base': 2.0041217772700084e-05, 'epoch': 0.42}) +[2026-07-27 05:24:53,263][starVLA.training.train_starvla][INFO] - Step 3503, Loss: {'train/loss': 0.22083932161331177, 'train/grad_norm_pre_clip': 4.580852508544922, 'timing/data': 0.00017296988517045975, 'timing/model': 0.47156945103779435, 'learning_rate/action_model': 8.014044389779404e-05, 'learning_rate/action_query_proj': 8.014044389779404e-05, 'learning_rate/base': 2.003511097444851e-05, 'epoch': 0.42}) +[2026-07-27 05:24:58,912][starVLA.training.train_starvla][INFO] - Step 3504, Loss: {'train/loss': 0.12445342540740967, 'train/grad_norm_pre_clip': 3.556870460510254, 'timing/data': 0.00018526706844568253, 'timing/model': 0.47961154021322727, 'learning_rate/action_model': 8.011600559538614e-05, 'learning_rate/action_query_proj': 8.011600559538614e-05, 'learning_rate/base': 2.0029001398846534e-05, 'epoch': 0.43}) +[2026-07-27 05:25:04,547][starVLA.training.train_starvla][INFO] - Step 3505, Loss: {'train/loss': 0.17079755663871765, 'train/grad_norm_pre_clip': 3.772595167160034, 'timing/data': 0.00017917295917868614, 'timing/model': 0.47915781708434224, 'learning_rate/action_model': 8.00915561932245e-05, 'learning_rate/action_query_proj': 8.00915561932245e-05, 'learning_rate/base': 2.0022889048306124e-05, 'epoch': 0.43}) +[2026-07-27 05:25:10,190][starVLA.training.train_starvla][INFO] - Step 3506, Loss: {'train/loss': 0.09904668480157852, 'train/grad_norm_pre_clip': 3.6966514587402344, 'timing/data': 0.0001707407645881176, 'timing/model': 0.4688344821333885, 'learning_rate/action_model': 8.006709570096135e-05, 'learning_rate/action_query_proj': 8.006709570096135e-05, 'learning_rate/base': 2.0016773925240337e-05, 'epoch': 0.43}) +[2026-07-27 05:25:15,817][starVLA.training.train_starvla][INFO] - Step 3507, Loss: {'train/loss': 0.09127480536699295, 'train/grad_norm_pre_clip': 3.409303665161133, 'timing/data': 0.00017504487186670303, 'timing/model': 0.4718499439768493, 'learning_rate/action_model': 8.004262412825331e-05, 'learning_rate/action_query_proj': 8.004262412825331e-05, 'learning_rate/base': 2.001065603206333e-05, 'epoch': 0.43}) +[2026-07-27 05:25:21,662][starVLA.training.train_starvla][INFO] - Step 3508, Loss: {'train/loss': 0.14811156690120697, 'train/grad_norm_pre_clip': 4.145379066467285, 'timing/data': 0.00017254706472158432, 'timing/model': 0.46907417522743344, 'learning_rate/action_model': 8.001814148476138e-05, 'learning_rate/action_query_proj': 8.001814148476138e-05, 'learning_rate/base': 2.0004535371190346e-05, 'epoch': 0.43}) +[2026-07-27 05:25:27,340][starVLA.training.train_starvla][INFO] - Step 3509, Loss: {'train/loss': 0.08030828833580017, 'train/grad_norm_pre_clip': 3.3000576496124268, 'timing/data': 0.00017423788085579872, 'timing/model': 0.47396167227998376, 'learning_rate/action_model': 7.999364778015092e-05, 'learning_rate/action_query_proj': 7.999364778015092e-05, 'learning_rate/base': 1.999841194503773e-05, 'epoch': 0.43}) +[2026-07-27 05:25:33,044][starVLA.training.train_starvla][INFO] - Step 3510, Loss: {'train/loss': 0.10649634897708893, 'train/grad_norm_pre_clip': 3.7231686115264893, 'timing/data': 0.0001709037460386753, 'timing/model': 0.4766318411566317, 'learning_rate/action_model': 7.996914302409167e-05, 'learning_rate/action_query_proj': 7.996914302409167e-05, 'learning_rate/base': 1.9992285756022917e-05, 'epoch': 0.43}) +[2026-07-27 05:25:38,727][starVLA.training.train_starvla][INFO] - Step 3511, Loss: {'train/loss': 0.08998013287782669, 'train/grad_norm_pre_clip': 2.7154812812805176, 'timing/data': 0.00017322786152362823, 'timing/model': 0.47039780486375093, 'learning_rate/action_model': 7.994462722625766e-05, 'learning_rate/action_query_proj': 7.994462722625766e-05, 'learning_rate/base': 1.9986156806564415e-05, 'epoch': 0.43}) +[2026-07-27 05:25:44,423][starVLA.training.train_starvla][INFO] - Step 3512, Loss: {'train/loss': 0.055935442447662354, 'train/grad_norm_pre_clip': 3.021775484085083, 'timing/data': 0.00017472309991717339, 'timing/model': 0.47027005115523934, 'learning_rate/action_model': 7.992010039632741e-05, 'learning_rate/action_query_proj': 7.992010039632741e-05, 'learning_rate/base': 1.9980025099081852e-05, 'epoch': 0.43}) +[2026-07-27 05:25:50,129][starVLA.training.train_starvla][INFO] - Step 3513, Loss: {'train/loss': 0.13083340227603912, 'train/grad_norm_pre_clip': 3.457622528076172, 'timing/data': 0.00017506303265690804, 'timing/model': 0.4739211010746658, 'learning_rate/action_model': 7.989556254398367e-05, 'learning_rate/action_query_proj': 7.989556254398367e-05, 'learning_rate/base': 1.9973890635995916e-05, 'epoch': 0.43}) +[2026-07-27 05:25:55,805][starVLA.training.train_starvla][INFO] - Step 3514, Loss: {'train/loss': 0.05472802743315697, 'train/grad_norm_pre_clip': 2.223649501800537, 'timing/data': 0.0001764087937772274, 'timing/model': 0.4779787492007017, 'learning_rate/action_model': 7.987101367891363e-05, 'learning_rate/action_query_proj': 7.987101367891363e-05, 'learning_rate/base': 1.9967753419728407e-05, 'epoch': 0.43}) +[2026-07-27 05:26:01,459][starVLA.training.train_starvla][INFO] - Step 3515, Loss: {'train/loss': 0.15269851684570312, 'train/grad_norm_pre_clip': 3.4228954315185547, 'timing/data': 0.00017431098967790604, 'timing/model': 0.4696708652190864, 'learning_rate/action_model': 7.984645381080878e-05, 'learning_rate/action_query_proj': 7.984645381080878e-05, 'learning_rate/base': 1.9961613452702194e-05, 'epoch': 0.43}) +[2026-07-27 05:26:07,128][starVLA.training.train_starvla][INFO] - Step 3516, Loss: {'train/loss': 0.08798287063837051, 'train/grad_norm_pre_clip': 2.6253175735473633, 'timing/data': 0.00017432775348424911, 'timing/model': 0.47165982192382216, 'learning_rate/action_model': 7.982188294936496e-05, 'learning_rate/action_query_proj': 7.982188294936496e-05, 'learning_rate/base': 1.995547073734124e-05, 'epoch': 0.43}) +[2026-07-27 05:26:12,799][starVLA.training.train_starvla][INFO] - Step 3517, Loss: {'train/loss': 0.04105839878320694, 'train/grad_norm_pre_clip': 1.776478886604309, 'timing/data': 0.00017487583681941032, 'timing/model': 0.47902401769533753, 'learning_rate/action_model': 7.979730110428239e-05, 'learning_rate/action_query_proj': 7.979730110428239e-05, 'learning_rate/base': 1.9949325276070596e-05, 'epoch': 0.43}) +[2026-07-27 05:26:18,469][starVLA.training.train_starvla][INFO] - Step 3518, Loss: {'train/loss': 0.10706853866577148, 'train/grad_norm_pre_clip': 3.6852974891662598, 'timing/data': 0.00018506404012441635, 'timing/model': 0.47956578992307186, 'learning_rate/action_model': 7.977270828526554e-05, 'learning_rate/action_query_proj': 7.977270828526554e-05, 'learning_rate/base': 1.9943177071316386e-05, 'epoch': 0.43}) +[2026-07-27 05:26:24,128][starVLA.training.train_starvla][INFO] - Step 3519, Loss: {'train/loss': 0.06846849620342255, 'train/grad_norm_pre_clip': 2.585705041885376, 'timing/data': 0.0001766667701303959, 'timing/model': 0.46934095304459333, 'learning_rate/action_model': 7.97481045020233e-05, 'learning_rate/action_query_proj': 7.97481045020233e-05, 'learning_rate/base': 1.9937026125505824e-05, 'epoch': 0.43}) +[2026-07-27 05:26:29,886][starVLA.training.train_starvla][INFO] - Step 3520, Loss: {'train/loss': 0.11878377944231033, 'train/grad_norm_pre_clip': 3.785775661468506, 'timing/data': 0.00017378618940711021, 'timing/model': 0.46328365057706833, 'learning_rate/action_model': 7.972348976426885e-05, 'learning_rate/action_query_proj': 7.972348976426885e-05, 'learning_rate/base': 1.9930872441067212e-05, 'epoch': 0.43}) +[2026-07-27 05:26:35,611][starVLA.training.train_starvla][INFO] - Step 3521, Loss: {'train/loss': 0.10602094978094101, 'train/grad_norm_pre_clip': 3.145465612411499, 'timing/data': 0.0001746751368045807, 'timing/model': 0.46102834679186344, 'learning_rate/action_model': 7.969886408171969e-05, 'learning_rate/action_query_proj': 7.969886408171969e-05, 'learning_rate/base': 1.9924716020429923e-05, 'epoch': 0.43}) +[2026-07-27 05:26:41,264][starVLA.training.train_starvla][INFO] - Step 3522, Loss: {'train/loss': 0.11180776357650757, 'train/grad_norm_pre_clip': 3.6998953819274902, 'timing/data': 0.00018127216026186943, 'timing/model': 0.4608061881735921, 'learning_rate/action_model': 7.967422746409766e-05, 'learning_rate/action_query_proj': 7.967422746409766e-05, 'learning_rate/base': 1.9918556866024414e-05, 'epoch': 0.43}) +[2026-07-27 05:26:46,915][starVLA.training.train_starvla][INFO] - Step 3523, Loss: {'train/loss': 0.10525953769683838, 'train/grad_norm_pre_clip': 3.090142011642456, 'timing/data': 0.00017168791964650154, 'timing/model': 0.462188224773854, 'learning_rate/action_model': 7.964957992112891e-05, 'learning_rate/action_query_proj': 7.964957992112891e-05, 'learning_rate/base': 1.9912394980282227e-05, 'epoch': 0.43}) +[2026-07-27 05:26:52,582][starVLA.training.train_starvla][INFO] - Step 3524, Loss: {'train/loss': 0.034663207828998566, 'train/grad_norm_pre_clip': 1.5920493602752686, 'timing/data': 0.00017990171909332275, 'timing/model': 0.4634789782576263, 'learning_rate/action_model': 7.96249214625439e-05, 'learning_rate/action_query_proj': 7.96249214625439e-05, 'learning_rate/base': 1.9906230365635976e-05, 'epoch': 0.43}) +[2026-07-27 05:26:58,215][starVLA.training.train_starvla][INFO] - Step 3525, Loss: {'train/loss': 0.19984449446201324, 'train/grad_norm_pre_clip': 5.534652233123779, 'timing/data': 0.00017892802134156227, 'timing/model': 0.4600036023184657, 'learning_rate/action_model': 7.960025209807738e-05, 'learning_rate/action_query_proj': 7.960025209807738e-05, 'learning_rate/base': 1.9900063024519346e-05, 'epoch': 0.43}) +[2026-07-27 05:27:03,878][starVLA.training.train_starvla][INFO] - Step 3526, Loss: {'train/loss': 0.05545283108949661, 'train/grad_norm_pre_clip': 2.5335617065429688, 'timing/data': 0.00019121496006846428, 'timing/model': 0.46348075894638896, 'learning_rate/action_model': 7.957557183746843e-05, 'learning_rate/action_query_proj': 7.957557183746843e-05, 'learning_rate/base': 1.9893892959367108e-05, 'epoch': 0.43}) +[2026-07-27 05:27:09,643][starVLA.training.train_starvla][INFO] - Step 3527, Loss: {'train/loss': 0.10342667996883392, 'train/grad_norm_pre_clip': 4.173034191131592, 'timing/data': 0.00017605070024728775, 'timing/model': 0.6300020199269056, 'learning_rate/action_model': 7.955088069046044e-05, 'learning_rate/action_query_proj': 7.955088069046044e-05, 'learning_rate/base': 1.988772017261511e-05, 'epoch': 0.43}) +[2026-07-27 05:27:15,268][starVLA.training.train_starvla][INFO] - Step 3528, Loss: {'train/loss': 0.2249080091714859, 'train/grad_norm_pre_clip': 3.5246238708496094, 'timing/data': 0.00017327489331364632, 'timing/model': 0.46481957100331783, 'learning_rate/action_model': 7.952617866680106e-05, 'learning_rate/action_query_proj': 7.952617866680106e-05, 'learning_rate/base': 1.9881544666700266e-05, 'epoch': 0.43}) +[2026-07-27 05:27:20,866][starVLA.training.train_starvla][INFO] - Step 3529, Loss: {'train/loss': 0.04079312086105347, 'train/grad_norm_pre_clip': 2.127450942993164, 'timing/data': 0.00017040036618709564, 'timing/model': 0.4650816470384598, 'learning_rate/action_model': 7.950146577624229e-05, 'learning_rate/action_query_proj': 7.950146577624229e-05, 'learning_rate/base': 1.9875366444060573e-05, 'epoch': 0.43}) +[2026-07-27 05:27:26,468][starVLA.training.train_starvla][INFO] - Step 3530, Loss: {'train/loss': 0.03305952250957489, 'train/grad_norm_pre_clip': 1.5773935317993164, 'timing/data': 0.00017439806833863258, 'timing/model': 0.46508894162252545, 'learning_rate/action_model': 7.947674202854037e-05, 'learning_rate/action_query_proj': 7.947674202854037e-05, 'learning_rate/base': 1.9869185507135094e-05, 'epoch': 0.43}) +[2026-07-27 05:27:32,104][starVLA.training.train_starvla][INFO] - Step 3531, Loss: {'train/loss': 0.0969981849193573, 'train/grad_norm_pre_clip': 3.3221118450164795, 'timing/data': 0.0001795860007405281, 'timing/model': 0.46123367408290505, 'learning_rate/action_model': 7.945200743345584e-05, 'learning_rate/action_query_proj': 7.945200743345584e-05, 'learning_rate/base': 1.986300185836396e-05, 'epoch': 0.43}) +[2026-07-27 05:27:37,721][starVLA.training.train_starvla][INFO] - Step 3532, Loss: {'train/loss': 0.16048383712768555, 'train/grad_norm_pre_clip': 4.228559970855713, 'timing/data': 0.00017667701467871666, 'timing/model': 0.457238650880754, 'learning_rate/action_model': 7.942726200075353e-05, 'learning_rate/action_query_proj': 7.942726200075353e-05, 'learning_rate/base': 1.9856815500188382e-05, 'epoch': 0.43}) +[2026-07-27 05:27:43,523][starVLA.training.train_starvla][INFO] - Step 3533, Loss: {'train/loss': 0.2700204849243164, 'train/grad_norm_pre_clip': 6.0945000648498535, 'timing/data': 0.000173984095454216, 'timing/model': 0.46061503887176514, 'learning_rate/action_model': 7.940250574020256e-05, 'learning_rate/action_query_proj': 7.940250574020256e-05, 'learning_rate/base': 1.985062643505064e-05, 'epoch': 0.43}) +[2026-07-27 05:27:49,378][starVLA.training.train_starvla][INFO] - Step 3534, Loss: {'train/loss': 0.024075321853160858, 'train/grad_norm_pre_clip': 1.3267462253570557, 'timing/data': 0.00017682695761322975, 'timing/model': 0.46137503208592534, 'learning_rate/action_model': 7.937773866157626e-05, 'learning_rate/action_query_proj': 7.937773866157626e-05, 'learning_rate/base': 1.9844434665394066e-05, 'epoch': 0.43}) +[2026-07-27 05:27:54,984][starVLA.training.train_starvla][INFO] - Step 3535, Loss: {'train/loss': 0.1196826696395874, 'train/grad_norm_pre_clip': 5.138650894165039, 'timing/data': 0.00017276499420404434, 'timing/model': 0.46247875364497304, 'learning_rate/action_model': 7.935296077465235e-05, 'learning_rate/action_query_proj': 7.935296077465235e-05, 'learning_rate/base': 1.9838240193663088e-05, 'epoch': 0.43}) +[2026-07-27 05:28:00,655][starVLA.training.train_starvla][INFO] - Step 3536, Loss: {'train/loss': 0.060703061521053314, 'train/grad_norm_pre_clip': 2.801912784576416, 'timing/data': 0.0001882142387330532, 'timing/model': 0.4971861778758466, 'learning_rate/action_model': 7.932817208921271e-05, 'learning_rate/action_query_proj': 7.932817208921271e-05, 'learning_rate/base': 1.9832043022303177e-05, 'epoch': 0.43}) +[2026-07-27 05:28:06,274][starVLA.training.train_starvla][INFO] - Step 3537, Loss: {'train/loss': 0.05263770371675491, 'train/grad_norm_pre_clip': 2.6907804012298584, 'timing/data': 0.00017616432160139084, 'timing/model': 0.4586836649104953, 'learning_rate/action_model': 7.93033726150435e-05, 'learning_rate/action_query_proj': 7.93033726150435e-05, 'learning_rate/base': 1.9825843153760875e-05, 'epoch': 0.43}) +[2026-07-27 05:28:11,898][starVLA.training.train_starvla][INFO] - Step 3538, Loss: {'train/loss': 0.07638611644506454, 'train/grad_norm_pre_clip': 2.0880744457244873, 'timing/data': 0.00017471006140112877, 'timing/model': 0.46137750800698996, 'learning_rate/action_model': 7.92785623619352e-05, 'learning_rate/action_query_proj': 7.92785623619352e-05, 'learning_rate/base': 1.98196405904838e-05, 'epoch': 0.43}) +[2026-07-27 05:28:17,524][starVLA.training.train_starvla][INFO] - Step 3539, Loss: {'train/loss': 0.08933898061513901, 'train/grad_norm_pre_clip': 4.285782337188721, 'timing/data': 0.00017929496243596077, 'timing/model': 0.4630006290972233, 'learning_rate/action_model': 7.925374133968248e-05, 'learning_rate/action_query_proj': 7.925374133968248e-05, 'learning_rate/base': 1.981343533492062e-05, 'epoch': 0.43}) +[2026-07-27 05:28:23,133][starVLA.training.train_starvla][INFO] - Step 3540, Loss: {'train/loss': 0.1204654797911644, 'train/grad_norm_pre_clip': 3.1533279418945312, 'timing/data': 0.00017514638602733612, 'timing/model': 0.4647214780561626, 'learning_rate/action_model': 7.922890955808432e-05, 'learning_rate/action_query_proj': 7.922890955808432e-05, 'learning_rate/base': 1.980722738952108e-05, 'epoch': 0.43}) +[2026-07-27 05:28:28,761][starVLA.training.train_starvla][INFO] - Step 3541, Loss: {'train/loss': 0.06761036068201065, 'train/grad_norm_pre_clip': 3.1629652976989746, 'timing/data': 0.00017401622608304024, 'timing/model': 0.46050415886566043, 'learning_rate/action_model': 7.920406702694387e-05, 'learning_rate/action_query_proj': 7.920406702694387e-05, 'learning_rate/base': 1.980101675673597e-05, 'epoch': 0.43}) +[2026-07-27 05:28:34,400][starVLA.training.train_starvla][INFO] - Step 3542, Loss: {'train/loss': 0.06586658954620361, 'train/grad_norm_pre_clip': 2.762118101119995, 'timing/data': 0.00017614476382732391, 'timing/model': 0.4650926128961146, 'learning_rate/action_model': 7.91792137560686e-05, 'learning_rate/action_query_proj': 7.91792137560686e-05, 'learning_rate/base': 1.979480343901715e-05, 'epoch': 0.43}) +[2026-07-27 05:28:39,953][starVLA.training.train_starvla][INFO] - Step 3543, Loss: {'train/loss': 0.07154162228107452, 'train/grad_norm_pre_clip': 2.8069536685943604, 'timing/data': 0.000179193913936615, 'timing/model': 0.4606813979335129, 'learning_rate/action_model': 7.915434975527015e-05, 'learning_rate/action_query_proj': 7.915434975527015e-05, 'learning_rate/base': 1.9788587438817538e-05, 'epoch': 0.43}) +[2026-07-27 05:28:45,534][starVLA.training.train_starvla][INFO] - Step 3544, Loss: {'train/loss': 0.1874164342880249, 'train/grad_norm_pre_clip': 5.151529788970947, 'timing/data': 0.00020292075350880623, 'timing/model': 0.46142263896763325, 'learning_rate/action_model': 7.912947503436447e-05, 'learning_rate/action_query_proj': 7.912947503436447e-05, 'learning_rate/base': 1.9782368758591118e-05, 'epoch': 0.43}) +[2026-07-27 05:28:51,096][starVLA.training.train_starvla][INFO] - Step 3545, Loss: {'train/loss': 0.1153709888458252, 'train/grad_norm_pre_clip': 3.5924770832061768, 'timing/data': 0.00017951102927327156, 'timing/model': 0.46209213929250836, 'learning_rate/action_model': 7.910458960317171e-05, 'learning_rate/action_query_proj': 7.910458960317171e-05, 'learning_rate/base': 1.9776147400792928e-05, 'epoch': 0.43}) +[2026-07-27 05:28:56,747][starVLA.training.train_starvla][INFO] - Step 3546, Loss: {'train/loss': 0.10389480739831924, 'train/grad_norm_pre_clip': 3.9985532760620117, 'timing/data': 0.0001767161302268505, 'timing/model': 0.46475649205967784, 'learning_rate/action_model': 7.907969347151622e-05, 'learning_rate/action_query_proj': 7.907969347151622e-05, 'learning_rate/base': 1.9769923367879055e-05, 'epoch': 0.43}) +[2026-07-27 05:29:02,356][starVLA.training.train_starvla][INFO] - Step 3547, Loss: {'train/loss': 0.0564628466963768, 'train/grad_norm_pre_clip': 2.6528165340423584, 'timing/data': 0.00017257919535040855, 'timing/model': 0.45576145593076944, 'learning_rate/action_model': 7.90547866492266e-05, 'learning_rate/action_query_proj': 7.90547866492266e-05, 'learning_rate/base': 1.976369666230665e-05, 'epoch': 0.43}) +[2026-07-27 05:29:07,963][starVLA.training.train_starvla][INFO] - Step 3548, Loss: {'train/loss': 0.11183075606822968, 'train/grad_norm_pre_clip': 2.452373743057251, 'timing/data': 0.00017331307753920555, 'timing/model': 0.46056746505200863, 'learning_rate/action_model': 7.902986914613568e-05, 'learning_rate/action_query_proj': 7.902986914613568e-05, 'learning_rate/base': 1.975746728653392e-05, 'epoch': 0.43}) +[2026-07-27 05:29:13,590][starVLA.training.train_starvla][INFO] - Step 3549, Loss: {'train/loss': 0.23537056148052216, 'train/grad_norm_pre_clip': 4.483189105987549, 'timing/data': 0.00017396360635757446, 'timing/model': 0.4652476208284497, 'learning_rate/action_model': 7.900494097208049e-05, 'learning_rate/action_query_proj': 7.900494097208049e-05, 'learning_rate/base': 1.9751235243020123e-05, 'epoch': 0.43}) +[2026-07-27 05:29:19,216][starVLA.training.train_starvla][INFO] - Step 3550, Loss: {'train/loss': 0.1506372094154358, 'train/grad_norm_pre_clip': 5.777209281921387, 'timing/data': 0.00018600979819893837, 'timing/model': 0.4600464296527207, 'learning_rate/action_model': 7.898000213690227e-05, 'learning_rate/action_query_proj': 7.898000213690227e-05, 'learning_rate/base': 1.974500053422557e-05, 'epoch': 0.43}) +[2026-07-27 05:29:24,814][starVLA.training.train_starvla][INFO] - Step 3551, Loss: {'train/loss': 0.1704447865486145, 'train/grad_norm_pre_clip': 3.371873617172241, 'timing/data': 0.00017350725829601288, 'timing/model': 0.4637906989082694, 'learning_rate/action_model': 7.895505265044651e-05, 'learning_rate/action_query_proj': 7.895505265044651e-05, 'learning_rate/base': 1.9738763162611627e-05, 'epoch': 0.43}) +[2026-07-27 05:29:30,415][starVLA.training.train_starvla][INFO] - Step 3552, Loss: {'train/loss': 0.12229729443788528, 'train/grad_norm_pre_clip': 4.31481409072876, 'timing/data': 0.00016955891624093056, 'timing/model': 0.4650120078586042, 'learning_rate/action_model': 7.893009252256283e-05, 'learning_rate/action_query_proj': 7.893009252256283e-05, 'learning_rate/base': 1.9732523130640708e-05, 'epoch': 0.43}) +[2026-07-27 05:29:36,033][starVLA.training.train_starvla][INFO] - Step 3553, Loss: {'train/loss': 0.21374982595443726, 'train/grad_norm_pre_clip': 5.594736576080322, 'timing/data': 0.00017444975674152374, 'timing/model': 0.4647374916821718, 'learning_rate/action_model': 7.890512176310511e-05, 'learning_rate/action_query_proj': 7.890512176310511e-05, 'learning_rate/base': 1.9726280440776277e-05, 'epoch': 0.43}) +[2026-07-27 05:29:41,657][starVLA.training.train_starvla][INFO] - Step 3554, Loss: {'train/loss': 0.12551453709602356, 'train/grad_norm_pre_clip': 3.7727813720703125, 'timing/data': 0.0001794900745153427, 'timing/model': 0.46130410488694906, 'learning_rate/action_model': 7.888014038193144e-05, 'learning_rate/action_query_proj': 7.888014038193144e-05, 'learning_rate/base': 1.972003509548286e-05, 'epoch': 0.43}) +[2026-07-27 05:29:47,253][starVLA.training.train_starvla][INFO] - Step 3555, Loss: {'train/loss': 0.04589495435357094, 'train/grad_norm_pre_clip': 1.7070763111114502, 'timing/data': 0.00017546908929944038, 'timing/model': 0.46111794328317046, 'learning_rate/action_model': 7.885514838890402e-05, 'learning_rate/action_query_proj': 7.885514838890402e-05, 'learning_rate/base': 1.9713787097226005e-05, 'epoch': 0.43}) +[2026-07-27 05:29:52,866][starVLA.training.train_starvla][INFO] - Step 3556, Loss: {'train/loss': 0.04242079704999924, 'train/grad_norm_pre_clip': 2.3491005897521973, 'timing/data': 0.00018128380179405212, 'timing/model': 0.4630065839737654, 'learning_rate/action_model': 7.883014579388933e-05, 'learning_rate/action_query_proj': 7.883014579388933e-05, 'learning_rate/base': 1.9707536448472333e-05, 'epoch': 0.43}) +[2026-07-27 05:29:58,473][starVLA.training.train_starvla][INFO] - Step 3557, Loss: {'train/loss': 0.17304787039756775, 'train/grad_norm_pre_clip': 4.377165794372559, 'timing/data': 0.0001796460710465908, 'timing/model': 0.46375468792393804, 'learning_rate/action_model': 7.880513260675799e-05, 'learning_rate/action_query_proj': 7.880513260675799e-05, 'learning_rate/base': 1.9701283151689497e-05, 'epoch': 0.43}) +[2026-07-27 05:30:04,071][starVLA.training.train_starvla][INFO] - Step 3558, Loss: {'train/loss': 0.057539455592632294, 'train/grad_norm_pre_clip': 2.593637704849243, 'timing/data': 0.0001758607104420662, 'timing/model': 0.46315660513937473, 'learning_rate/action_model': 7.87801088373848e-05, 'learning_rate/action_query_proj': 7.87801088373848e-05, 'learning_rate/base': 1.96950272093462e-05, 'epoch': 0.43}) +[2026-07-27 05:30:09,669][starVLA.training.train_starvla][INFO] - Step 3559, Loss: {'train/loss': 0.07442256808280945, 'train/grad_norm_pre_clip': 2.7021636962890625, 'timing/data': 0.0001758430153131485, 'timing/model': 0.46209660917520523, 'learning_rate/action_model': 7.875507449564876e-05, 'learning_rate/action_query_proj': 7.875507449564876e-05, 'learning_rate/base': 1.968876862391219e-05, 'epoch': 0.43}) +[2026-07-27 05:30:15,274][starVLA.training.train_starvla][INFO] - Step 3560, Loss: {'train/loss': 0.047432560473680496, 'train/grad_norm_pre_clip': 2.695249080657959, 'timing/data': 0.00017876829952001572, 'timing/model': 0.4636688190512359, 'learning_rate/action_model': 7.873002959143304e-05, 'learning_rate/action_query_proj': 7.873002959143304e-05, 'learning_rate/base': 1.968250739785826e-05, 'epoch': 0.43}) +[2026-07-27 05:30:20,885][starVLA.training.train_starvla][INFO] - Step 3561, Loss: {'train/loss': 0.11087396740913391, 'train/grad_norm_pre_clip': 3.6128764152526855, 'timing/data': 0.00017914501950144768, 'timing/model': 0.4650685382075608, 'learning_rate/action_model': 7.870497413462495e-05, 'learning_rate/action_query_proj': 7.870497413462495e-05, 'learning_rate/base': 1.9676243533656236e-05, 'epoch': 0.43}) +[2026-07-27 05:30:26,723][starVLA.training.train_starvla][INFO] - Step 3562, Loss: {'train/loss': 0.06895403563976288, 'train/grad_norm_pre_clip': 3.4611287117004395, 'timing/data': 0.00018236786127090454, 'timing/model': 0.46440408378839493, 'learning_rate/action_model': 7.867990813511597e-05, 'learning_rate/action_query_proj': 7.867990813511597e-05, 'learning_rate/base': 1.9669977033778993e-05, 'epoch': 0.43}) +[2026-07-27 05:30:32,353][starVLA.training.train_starvla][INFO] - Step 3563, Loss: {'train/loss': 0.0666976049542427, 'train/grad_norm_pre_clip': 2.4210643768310547, 'timing/data': 0.00018281582742929459, 'timing/model': 0.4699023859575391, 'learning_rate/action_model': 7.865483160280182e-05, 'learning_rate/action_query_proj': 7.865483160280182e-05, 'learning_rate/base': 1.9663707900700455e-05, 'epoch': 0.43}) +[2026-07-27 05:30:37,957][starVLA.training.train_starvla][INFO] - Step 3564, Loss: {'train/loss': 0.05320383608341217, 'train/grad_norm_pre_clip': 2.1213271617889404, 'timing/data': 0.00018165679648518562, 'timing/model': 0.46793573116883636, 'learning_rate/action_model': 7.862974454758227e-05, 'learning_rate/action_query_proj': 7.862974454758227e-05, 'learning_rate/base': 1.965743613689557e-05, 'epoch': 0.43}) +[2026-07-27 05:30:43,569][starVLA.training.train_starvla][INFO] - Step 3565, Loss: {'train/loss': 0.11369924992322922, 'train/grad_norm_pre_clip': 3.1683151721954346, 'timing/data': 0.00017484603449702263, 'timing/model': 0.46942116832360625, 'learning_rate/action_model': 7.860464697936132e-05, 'learning_rate/action_query_proj': 7.860464697936132e-05, 'learning_rate/base': 1.965116174484033e-05, 'epoch': 0.43}) +[2026-07-27 05:30:49,197][starVLA.training.train_starvla][INFO] - Step 3566, Loss: {'train/loss': 0.06205335259437561, 'train/grad_norm_pre_clip': 2.5928688049316406, 'timing/data': 0.0001737968996167183, 'timing/model': 0.4758397410623729, 'learning_rate/action_model': 7.857953890804707e-05, 'learning_rate/action_query_proj': 7.857953890804707e-05, 'learning_rate/base': 1.964488472701177e-05, 'epoch': 0.43}) +[2026-07-27 05:30:54,823][starVLA.training.train_starvla][INFO] - Step 3567, Loss: {'train/loss': 0.038628943264484406, 'train/grad_norm_pre_clip': 2.2305028438568115, 'timing/data': 0.00017532240599393845, 'timing/model': 0.4768010750412941, 'learning_rate/action_model': 7.855442034355179e-05, 'learning_rate/action_query_proj': 7.855442034355179e-05, 'learning_rate/base': 1.9638605085887947e-05, 'epoch': 0.43}) +[2026-07-27 05:31:00,455][starVLA.training.train_starvla][INFO] - Step 3568, Loss: {'train/loss': 0.08950038999319077, 'train/grad_norm_pre_clip': 2.578657865524292, 'timing/data': 0.00017811637371778488, 'timing/model': 0.4754384630359709, 'learning_rate/action_model': 7.852929129579192e-05, 'learning_rate/action_query_proj': 7.852929129579192e-05, 'learning_rate/base': 1.963232282394798e-05, 'epoch': 0.43}) +[2026-07-27 05:31:06,340][starVLA.training.train_starvla][INFO] - Step 3569, Loss: {'train/loss': 0.15916948020458221, 'train/grad_norm_pre_clip': 3.7493481636047363, 'timing/data': 0.00017514871433377266, 'timing/model': 0.47022372484207153, 'learning_rate/action_model': 7.850415177468797e-05, 'learning_rate/action_query_proj': 7.850415177468797e-05, 'learning_rate/base': 1.9626037943671993e-05, 'epoch': 0.43}) +[2026-07-27 05:31:11,969][starVLA.training.train_starvla][INFO] - Step 3570, Loss: {'train/loss': 0.04111703485250473, 'train/grad_norm_pre_clip': 2.8432812690734863, 'timing/data': 0.0001737610436975956, 'timing/model': 0.4669471150264144, 'learning_rate/action_model': 7.847900179016466e-05, 'learning_rate/action_query_proj': 7.847900179016466e-05, 'learning_rate/base': 1.9619750447541165e-05, 'epoch': 0.43}) +[2026-07-27 05:31:17,602][starVLA.training.train_starvla][INFO] - Step 3571, Loss: {'train/loss': 0.0751102864742279, 'train/grad_norm_pre_clip': 3.365089178085327, 'timing/data': 0.00018563074991106987, 'timing/model': 0.46920084301382303, 'learning_rate/action_model': 7.845384135215077e-05, 'learning_rate/action_query_proj': 7.845384135215077e-05, 'learning_rate/base': 1.961346033803769e-05, 'epoch': 0.43}) +[2026-07-27 05:31:23,206][starVLA.training.train_starvla][INFO] - Step 3572, Loss: {'train/loss': 0.04176408424973488, 'train/grad_norm_pre_clip': 2.109438419342041, 'timing/data': 0.00017532287165522575, 'timing/model': 0.47064274037256837, 'learning_rate/action_model': 7.842867047057929e-05, 'learning_rate/action_query_proj': 7.842867047057929e-05, 'learning_rate/base': 1.960716761764482e-05, 'epoch': 0.43}) +[2026-07-27 05:31:28,850][starVLA.training.train_starvla][INFO] - Step 3573, Loss: {'train/loss': 0.018832605332136154, 'train/grad_norm_pre_clip': 1.2764966487884521, 'timing/data': 0.00017675897106528282, 'timing/model': 0.4691619691438973, 'learning_rate/action_model': 7.840348915538722e-05, 'learning_rate/action_query_proj': 7.840348915538722e-05, 'learning_rate/base': 1.9600872288846804e-05, 'epoch': 0.43}) +[2026-07-27 05:31:34,469][starVLA.training.train_starvla][INFO] - Step 3574, Loss: {'train/loss': 0.05318761616945267, 'train/grad_norm_pre_clip': 2.16003155708313, 'timing/data': 0.00017814571037888527, 'timing/model': 0.46878756675869226, 'learning_rate/action_model': 7.837829741651581e-05, 'learning_rate/action_query_proj': 7.837829741651581e-05, 'learning_rate/base': 1.9594574354128953e-05, 'epoch': 0.43}) +[2026-07-27 05:31:40,052][starVLA.training.train_starvla][INFO] - Step 3575, Loss: {'train/loss': 0.04162198305130005, 'train/grad_norm_pre_clip': 2.481128692626953, 'timing/data': 0.00017642928287386894, 'timing/model': 0.4685506313107908, 'learning_rate/action_model': 7.835309526391033e-05, 'learning_rate/action_query_proj': 7.835309526391033e-05, 'learning_rate/base': 1.958827381597758e-05, 'epoch': 0.43}) +[2026-07-27 05:31:45,636][starVLA.training.train_starvla][INFO] - Step 3576, Loss: {'train/loss': 0.08231707662343979, 'train/grad_norm_pre_clip': 2.136993646621704, 'timing/data': 0.00017555197700858116, 'timing/model': 0.4667615476064384, 'learning_rate/action_model': 7.832788270752018e-05, 'learning_rate/action_query_proj': 7.832788270752018e-05, 'learning_rate/base': 1.9581970676880045e-05, 'epoch': 0.43}) +[2026-07-27 05:31:51,215][starVLA.training.train_starvla][INFO] - Step 3577, Loss: {'train/loss': 0.05558934435248375, 'train/grad_norm_pre_clip': 2.915116548538208, 'timing/data': 0.00017976295202970505, 'timing/model': 0.47737855976447463, 'learning_rate/action_model': 7.83026597572989e-05, 'learning_rate/action_query_proj': 7.83026597572989e-05, 'learning_rate/base': 1.9575664939324727e-05, 'epoch': 0.43}) +[2026-07-27 05:31:56,795][starVLA.training.train_starvla][INFO] - Step 3578, Loss: {'train/loss': 0.0868631899356842, 'train/grad_norm_pre_clip': 3.583169460296631, 'timing/data': 0.0001761801540851593, 'timing/model': 0.4761882573366165, 'learning_rate/action_model': 7.82774264232041e-05, 'learning_rate/action_query_proj': 7.82774264232041e-05, 'learning_rate/base': 1.9569356605801026e-05, 'epoch': 0.43}) +[2026-07-27 05:32:02,369][starVLA.training.train_starvla][INFO] - Step 3579, Loss: {'train/loss': 0.17079129815101624, 'train/grad_norm_pre_clip': 3.8142077922821045, 'timing/data': 0.00017535081133246422, 'timing/model': 0.4667735700495541, 'learning_rate/action_model': 7.82521827151975e-05, 'learning_rate/action_query_proj': 7.82521827151975e-05, 'learning_rate/base': 1.9563045678799375e-05, 'epoch': 0.43}) +[2026-07-27 05:32:07,956][starVLA.training.train_starvla][INFO] - Step 3580, Loss: {'train/loss': 0.08406756818294525, 'train/grad_norm_pre_clip': 2.924346446990967, 'timing/data': 0.00017706258222460747, 'timing/model': 0.46833276096731424, 'learning_rate/action_model': 7.822692864324492e-05, 'learning_rate/action_query_proj': 7.822692864324492e-05, 'learning_rate/base': 1.955673216081123e-05, 'epoch': 0.43}) +[2026-07-27 05:32:13,534][starVLA.training.train_starvla][INFO] - Step 3581, Loss: {'train/loss': 0.08133304119110107, 'train/grad_norm_pre_clip': 3.2165229320526123, 'timing/data': 0.00017918506637215614, 'timing/model': 0.4697394329123199, 'learning_rate/action_model': 7.820166421731627e-05, 'learning_rate/action_query_proj': 7.820166421731627e-05, 'learning_rate/base': 1.9550416054329068e-05, 'epoch': 0.43}) +[2026-07-27 05:32:19,125][starVLA.training.train_starvla][INFO] - Step 3582, Loss: {'train/loss': 0.0478009395301342, 'train/grad_norm_pre_clip': 2.233813762664795, 'timing/data': 0.000177689827978611, 'timing/model': 0.4757950622588396, 'learning_rate/action_model': 7.817638944738553e-05, 'learning_rate/action_query_proj': 7.817638944738553e-05, 'learning_rate/base': 1.9544097361846383e-05, 'epoch': 0.43}) +[2026-07-27 05:32:24,686][starVLA.training.train_starvla][INFO] - Step 3583, Loss: {'train/loss': 0.08900929242372513, 'train/grad_norm_pre_clip': 1.7780462503433228, 'timing/data': 0.00017482787370681763, 'timing/model': 0.4698380106128752, 'learning_rate/action_model': 7.81511043434308e-05, 'learning_rate/action_query_proj': 7.81511043434308e-05, 'learning_rate/base': 1.95377760858577e-05, 'epoch': 0.43}) +[2026-07-27 05:32:30,268][starVLA.training.train_starvla][INFO] - Step 3584, Loss: {'train/loss': 0.05939343571662903, 'train/grad_norm_pre_clip': 3.06795334815979, 'timing/data': 0.00019609229639172554, 'timing/model': 0.4703157660551369, 'learning_rate/action_model': 7.812580891543422e-05, 'learning_rate/action_query_proj': 7.812580891543422e-05, 'learning_rate/base': 1.9531452228858554e-05, 'epoch': 0.43}) +[2026-07-27 05:32:35,860][starVLA.training.train_starvla][INFO] - Step 3585, Loss: {'train/loss': 0.12523981928825378, 'train/grad_norm_pre_clip': 3.3474111557006836, 'timing/data': 0.0001744837500154972, 'timing/model': 0.467927438672632, 'learning_rate/action_model': 7.810050317338204e-05, 'learning_rate/action_query_proj': 7.810050317338204e-05, 'learning_rate/base': 1.952512579334551e-05, 'epoch': 0.43}) +[2026-07-27 05:32:41,463][starVLA.training.train_starvla][INFO] - Step 3586, Loss: {'train/loss': 0.11613704264163971, 'train/grad_norm_pre_clip': 4.625372409820557, 'timing/data': 0.00018630316480994225, 'timing/model': 0.46892215171828866, 'learning_rate/action_model': 7.807518712726457e-05, 'learning_rate/action_query_proj': 7.807518712726457e-05, 'learning_rate/base': 1.9518796781816143e-05, 'epoch': 0.44}) +[2026-07-27 05:32:47,035][starVLA.training.train_starvla][INFO] - Step 3587, Loss: {'train/loss': 0.12011121213436127, 'train/grad_norm_pre_clip': 3.9770925045013428, 'timing/data': 0.00017346302047371864, 'timing/model': 0.46924360003322363, 'learning_rate/action_model': 7.804986078707615e-05, 'learning_rate/action_query_proj': 7.804986078707615e-05, 'learning_rate/base': 1.9512465196769038e-05, 'epoch': 0.44}) +[2026-07-27 05:32:52,603][starVLA.training.train_starvla][INFO] - Step 3588, Loss: {'train/loss': 0.1275596022605896, 'train/grad_norm_pre_clip': 3.745199680328369, 'timing/data': 0.00017285486683249474, 'timing/model': 0.4702742318622768, 'learning_rate/action_model': 7.802452416281525e-05, 'learning_rate/action_query_proj': 7.802452416281525e-05, 'learning_rate/base': 1.9506131040703813e-05, 'epoch': 0.44}) +[2026-07-27 05:32:58,158][starVLA.training.train_starvla][INFO] - Step 3589, Loss: {'train/loss': 0.06573452055454254, 'train/grad_norm_pre_clip': 3.7759573459625244, 'timing/data': 0.0001753740943968296, 'timing/model': 0.46826730482280254, 'learning_rate/action_model': 7.799917726448436e-05, 'learning_rate/action_query_proj': 7.799917726448436e-05, 'learning_rate/base': 1.949979431612109e-05, 'epoch': 0.44}) +[2026-07-27 05:33:03,733][starVLA.training.train_starvla][INFO] - Step 3590, Loss: {'train/loss': 0.02634955570101738, 'train/grad_norm_pre_clip': 1.9036517143249512, 'timing/data': 0.00017650285735726357, 'timing/model': 0.47453575395047665, 'learning_rate/action_model': 7.797382010209005e-05, 'learning_rate/action_query_proj': 7.797382010209005e-05, 'learning_rate/base': 1.949345502552251e-05, 'epoch': 0.44}) +[2026-07-27 05:33:09,365][starVLA.training.train_starvla][INFO] - Step 3591, Loss: {'train/loss': 0.048738278448581696, 'train/grad_norm_pre_clip': 2.244849443435669, 'timing/data': 0.0001741042360663414, 'timing/model': 0.48954945895820856, 'learning_rate/action_model': 7.79484526856429e-05, 'learning_rate/action_query_proj': 7.79484526856429e-05, 'learning_rate/base': 1.9487113171410724e-05, 'epoch': 0.44}) +[2026-07-27 05:33:14,956][starVLA.training.train_starvla][INFO] - Step 3592, Loss: {'train/loss': 0.10992488265037537, 'train/grad_norm_pre_clip': 4.38991117477417, 'timing/data': 0.00017319712787866592, 'timing/model': 0.4698872738517821, 'learning_rate/action_model': 7.792307502515756e-05, 'learning_rate/action_query_proj': 7.792307502515756e-05, 'learning_rate/base': 1.948076875628939e-05, 'epoch': 0.44}) +[2026-07-27 05:33:20,542][starVLA.training.train_starvla][INFO] - Step 3593, Loss: {'train/loss': 0.27253326773643494, 'train/grad_norm_pre_clip': 6.156078815460205, 'timing/data': 0.0001738579012453556, 'timing/model': 0.4688538839109242, 'learning_rate/action_model': 7.789768713065277e-05, 'learning_rate/action_query_proj': 7.789768713065277e-05, 'learning_rate/base': 1.9474421782663192e-05, 'epoch': 0.44}) +[2026-07-27 05:33:26,383][starVLA.training.train_starvla][INFO] - Step 3594, Loss: {'train/loss': 0.18647658824920654, 'train/grad_norm_pre_clip': 4.225955486297607, 'timing/data': 0.00017953524366021156, 'timing/model': 0.7112127849832177, 'learning_rate/action_model': 7.78722890121512e-05, 'learning_rate/action_query_proj': 7.78722890121512e-05, 'learning_rate/base': 1.94680722530378e-05, 'epoch': 0.44}) +[2026-07-27 05:33:31,962][starVLA.training.train_starvla][INFO] - Step 3595, Loss: {'train/loss': 0.17257176339626312, 'train/grad_norm_pre_clip': 4.9768195152282715, 'timing/data': 0.00017951196059584618, 'timing/model': 0.4675323236733675, 'learning_rate/action_model': 7.78468806796797e-05, 'learning_rate/action_query_proj': 7.78468806796797e-05, 'learning_rate/base': 1.9461720169919924e-05, 'epoch': 0.44}) +[2026-07-27 05:33:37,619][starVLA.training.train_starvla][INFO] - Step 3596, Loss: {'train/loss': 0.12016814947128296, 'train/grad_norm_pre_clip': 4.591435432434082, 'timing/data': 0.0001785149797797203, 'timing/model': 0.4701109160669148, 'learning_rate/action_model': 7.782146214326902e-05, 'learning_rate/action_query_proj': 7.782146214326902e-05, 'learning_rate/base': 1.9455365535817255e-05, 'epoch': 0.44}) +[2026-07-27 05:33:43,237][starVLA.training.train_starvla][INFO] - Step 3597, Loss: {'train/loss': 0.1162923276424408, 'train/grad_norm_pre_clip': 3.2908313274383545, 'timing/data': 0.00017198314890265465, 'timing/model': 0.470678374171257, 'learning_rate/action_model': 7.779603341295403e-05, 'learning_rate/action_query_proj': 7.779603341295403e-05, 'learning_rate/base': 1.9449008353238507e-05, 'epoch': 0.44}) +[2026-07-27 05:33:48,854][starVLA.training.train_starvla][INFO] - Step 3598, Loss: {'train/loss': 0.03908751532435417, 'train/grad_norm_pre_clip': 2.0280921459198, 'timing/data': 0.00017389096319675446, 'timing/model': 0.4673201600089669, 'learning_rate/action_model': 7.77705944987736e-05, 'learning_rate/action_query_proj': 7.77705944987736e-05, 'learning_rate/base': 1.94426486246934e-05, 'epoch': 0.44}) +[2026-07-27 05:33:54,489][starVLA.training.train_starvla][INFO] - Step 3599, Loss: {'train/loss': 0.08002635836601257, 'train/grad_norm_pre_clip': 3.068337917327881, 'timing/data': 0.00018093036487698555, 'timing/model': 0.47089904826134443, 'learning_rate/action_model': 7.774514541077056e-05, 'learning_rate/action_query_proj': 7.774514541077056e-05, 'learning_rate/base': 1.943628635269264e-05, 'epoch': 0.44}) +[2026-07-27 05:34:00,120][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 3600 +[2026-07-27 05:34:00,120][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 3600 +[2026-07-27 05:34:00,121][starVLA.training.train_starvla][INFO] - Step 3600, Loss: {'train/loss': 0.1331145018339157, 'train/grad_norm_pre_clip': 3.9892547130584717, 'timing/data': 0.00017420388758182526, 'timing/model': 0.4703435688279569, 'learning_rate/action_model': 7.771968615899183e-05, 'learning_rate/action_query_proj': 7.771968615899183e-05, 'learning_rate/base': 1.9429921539747957e-05, 'epoch': 0.44}) +[2026-07-27 05:34:05,729][starVLA.training.train_starvla][INFO] - Step 3601, Loss: {'train/loss': 0.13616718351840973, 'train/grad_norm_pre_clip': 5.014341354370117, 'timing/data': 0.00017711007967591286, 'timing/model': 0.46047326689586043, 'learning_rate/action_model': 7.769421675348836e-05, 'learning_rate/action_query_proj': 7.769421675348836e-05, 'learning_rate/base': 1.942355418837209e-05, 'epoch': 0.44}) +[2026-07-27 05:34:11,335][starVLA.training.train_starvla][INFO] - Step 3602, Loss: {'train/loss': 0.20266319811344147, 'train/grad_norm_pre_clip': 4.788188457489014, 'timing/data': 0.00017963675782084465, 'timing/model': 0.4618977280333638, 'learning_rate/action_model': 7.7668737204315e-05, 'learning_rate/action_query_proj': 7.7668737204315e-05, 'learning_rate/base': 1.941718430107875e-05, 'epoch': 0.44}) +[2026-07-27 05:34:16,951][starVLA.training.train_starvla][INFO] - Step 3603, Loss: {'train/loss': 0.12302307784557343, 'train/grad_norm_pre_clip': 4.058099269866943, 'timing/data': 0.00017477339133620262, 'timing/model': 0.456441103015095, 'learning_rate/action_model': 7.764324752153073e-05, 'learning_rate/action_query_proj': 7.764324752153073e-05, 'learning_rate/base': 1.941081188038268e-05, 'epoch': 0.44}) +[2026-07-27 05:34:22,573][starVLA.training.train_starvla][INFO] - Step 3604, Loss: {'train/loss': 0.12929879128932953, 'train/grad_norm_pre_clip': 5.53308629989624, 'timing/data': 0.00017855409532785416, 'timing/model': 0.4634274346753955, 'learning_rate/action_model': 7.761774771519844e-05, 'learning_rate/action_query_proj': 7.761774771519844e-05, 'learning_rate/base': 1.940443692879961e-05, 'epoch': 0.44}) +[2026-07-27 05:34:28,211][starVLA.training.train_starvla][INFO] - Step 3605, Loss: {'train/loss': 0.07494992762804031, 'train/grad_norm_pre_clip': 3.5277774333953857, 'timing/data': 0.0001811012625694275, 'timing/model': 0.4616144369356334, 'learning_rate/action_model': 7.759223779538505e-05, 'learning_rate/action_query_proj': 7.759223779538505e-05, 'learning_rate/base': 1.9398059448846263e-05, 'epoch': 0.44}) +[2026-07-27 05:34:33,853][starVLA.training.train_starvla][INFO] - Step 3606, Loss: {'train/loss': 0.0701465979218483, 'train/grad_norm_pre_clip': 3.442518711090088, 'timing/data': 0.00018250476568937302, 'timing/model': 0.46428219182416797, 'learning_rate/action_model': 7.756671777216149e-05, 'learning_rate/action_query_proj': 7.756671777216149e-05, 'learning_rate/base': 1.939167944304037e-05, 'epoch': 0.44}) +[2026-07-27 05:34:39,467][starVLA.training.train_starvla][INFO] - Step 3607, Loss: {'train/loss': 0.12100279331207275, 'train/grad_norm_pre_clip': 3.1228389739990234, 'timing/data': 0.0001758909784257412, 'timing/model': 0.46376188192516565, 'learning_rate/action_model': 7.754118765560265e-05, 'learning_rate/action_query_proj': 7.754118765560265e-05, 'learning_rate/base': 1.9385296913900664e-05, 'epoch': 0.44}) +[2026-07-27 05:34:45,069][starVLA.training.train_starvla][INFO] - Step 3608, Loss: {'train/loss': 0.05422110855579376, 'train/grad_norm_pre_clip': 2.3168234825134277, 'timing/data': 0.0001775883138179779, 'timing/model': 0.46257504913955927, 'learning_rate/action_model': 7.751564745578744e-05, 'learning_rate/action_query_proj': 7.751564745578744e-05, 'learning_rate/base': 1.937891186394686e-05, 'epoch': 0.44}) +[2026-07-27 05:34:50,673][starVLA.training.train_starvla][INFO] - Step 3609, Loss: {'train/loss': 0.19216768443584442, 'train/grad_norm_pre_clip': 3.4335429668426514, 'timing/data': 0.00017745792865753174, 'timing/model': 0.46330033196136355, 'learning_rate/action_model': 7.749009718279867e-05, 'learning_rate/action_query_proj': 7.749009718279867e-05, 'learning_rate/base': 1.9372524295699666e-05, 'epoch': 0.44}) +[2026-07-27 05:34:56,298][starVLA.training.train_starvla][INFO] - Step 3610, Loss: {'train/loss': 0.052501872181892395, 'train/grad_norm_pre_clip': 2.7198963165283203, 'timing/data': 0.0001782430335879326, 'timing/model': 0.46388408495113254, 'learning_rate/action_model': 7.746453684672323e-05, 'learning_rate/action_query_proj': 7.746453684672323e-05, 'learning_rate/base': 1.936613421168081e-05, 'epoch': 0.44}) +[2026-07-27 05:35:01,892][starVLA.training.train_starvla][INFO] - Step 3611, Loss: {'train/loss': 0.044760774821043015, 'train/grad_norm_pre_clip': 2.1793055534362793, 'timing/data': 0.0001788451336324215, 'timing/model': 0.46158033702522516, 'learning_rate/action_model': 7.743896645765193e-05, 'learning_rate/action_query_proj': 7.743896645765193e-05, 'learning_rate/base': 1.9359741614412983e-05, 'epoch': 0.44}) +[2026-07-27 05:35:07,520][starVLA.training.train_starvla][INFO] - Step 3612, Loss: {'train/loss': 0.07839758694171906, 'train/grad_norm_pre_clip': 3.0901296138763428, 'timing/data': 0.00018438277766108513, 'timing/model': 0.4644054528325796, 'learning_rate/action_model': 7.741338602567956e-05, 'learning_rate/action_query_proj': 7.741338602567956e-05, 'learning_rate/base': 1.935334650641989e-05, 'epoch': 0.44}) +[2026-07-27 05:35:13,144][starVLA.training.train_starvla][INFO] - Step 3613, Loss: {'train/loss': 0.03340623900294304, 'train/grad_norm_pre_clip': 1.791930079460144, 'timing/data': 0.0001760302111506462, 'timing/model': 0.46248458977788687, 'learning_rate/action_model': 7.738779556090484e-05, 'learning_rate/action_query_proj': 7.738779556090484e-05, 'learning_rate/base': 1.934694889022621e-05, 'epoch': 0.44}) +[2026-07-27 05:35:18,763][starVLA.training.train_starvla][INFO] - Step 3614, Loss: {'train/loss': 0.1106143519282341, 'train/grad_norm_pre_clip': 4.462028503417969, 'timing/data': 0.00018490897491574287, 'timing/model': 0.46162493666633964, 'learning_rate/action_model': 7.736219507343048e-05, 'learning_rate/action_query_proj': 7.736219507343048e-05, 'learning_rate/base': 1.934054876835762e-05, 'epoch': 0.44}) +[2026-07-27 05:35:24,371][starVLA.training.train_starvla][INFO] - Step 3615, Loss: {'train/loss': 0.10219088941812515, 'train/grad_norm_pre_clip': 5.101308345794678, 'timing/data': 0.0001908610574901104, 'timing/model': 0.46304155606776476, 'learning_rate/action_model': 7.733658457336319e-05, 'learning_rate/action_query_proj': 7.733658457336319e-05, 'learning_rate/base': 1.9334146143340798e-05, 'epoch': 0.44}) +[2026-07-27 05:35:30,013][starVLA.training.train_starvla][INFO] - Step 3616, Loss: {'train/loss': 0.048045817762613297, 'train/grad_norm_pre_clip': 2.8745880126953125, 'timing/data': 0.00017794081941246986, 'timing/model': 0.477620598860085, 'learning_rate/action_model': 7.731096407081357e-05, 'learning_rate/action_query_proj': 7.731096407081357e-05, 'learning_rate/base': 1.9327741017703392e-05, 'epoch': 0.44}) +[2026-07-27 05:35:35,633][starVLA.training.train_starvla][INFO] - Step 3617, Loss: {'train/loss': 0.07549817860126495, 'train/grad_norm_pre_clip': 3.920339822769165, 'timing/data': 0.0001753140240907669, 'timing/model': 0.47083411645144224, 'learning_rate/action_model': 7.728533357589616e-05, 'learning_rate/action_query_proj': 7.728533357589616e-05, 'learning_rate/base': 1.932133339397404e-05, 'epoch': 0.44}) +[2026-07-27 05:35:41,243][starVLA.training.train_starvla][INFO] - Step 3618, Loss: {'train/loss': 0.0832093209028244, 'train/grad_norm_pre_clip': 4.410548210144043, 'timing/data': 0.0001859939657151699, 'timing/model': 0.46444972325116396, 'learning_rate/action_model': 7.725969309872952e-05, 'learning_rate/action_query_proj': 7.725969309872952e-05, 'learning_rate/base': 1.931492327468238e-05, 'epoch': 0.44}) +[2026-07-27 05:35:46,862][starVLA.training.train_starvla][INFO] - Step 3619, Loss: {'train/loss': 0.11322825402021408, 'train/grad_norm_pre_clip': 3.8892908096313477, 'timing/data': 0.0001740981824696064, 'timing/model': 0.4633591459132731, 'learning_rate/action_model': 7.723404264943607e-05, 'learning_rate/action_query_proj': 7.723404264943607e-05, 'learning_rate/base': 1.9308510662359016e-05, 'epoch': 0.44}) +[2026-07-27 05:35:52,486][starVLA.training.train_starvla][INFO] - Step 3620, Loss: {'train/loss': 0.053554173558950424, 'train/grad_norm_pre_clip': 2.5047667026519775, 'timing/data': 0.0001766132190823555, 'timing/model': 0.46275171311572194, 'learning_rate/action_model': 7.72083822381422e-05, 'learning_rate/action_query_proj': 7.72083822381422e-05, 'learning_rate/base': 1.930209555953555e-05, 'epoch': 0.44}) +[2026-07-27 05:35:58,094][starVLA.training.train_starvla][INFO] - Step 3621, Loss: {'train/loss': 0.15872003138065338, 'train/grad_norm_pre_clip': 3.8457024097442627, 'timing/data': 0.00018255924805998802, 'timing/model': 0.4617325169965625, 'learning_rate/action_model': 7.718271187497827e-05, 'learning_rate/action_query_proj': 7.718271187497827e-05, 'learning_rate/base': 1.9295677968744568e-05, 'epoch': 0.44}) +[2026-07-27 05:36:03,706][starVLA.training.train_starvla][INFO] - Step 3622, Loss: {'train/loss': 0.122092604637146, 'train/grad_norm_pre_clip': 4.212708473205566, 'timing/data': 0.00017500203102827072, 'timing/model': 0.4615267771296203, 'learning_rate/action_model': 7.715703157007848e-05, 'learning_rate/action_query_proj': 7.715703157007848e-05, 'learning_rate/base': 1.928925789251962e-05, 'epoch': 0.44}) +[2026-07-27 05:36:09,310][starVLA.training.train_starvla][INFO] - Step 3623, Loss: {'train/loss': 0.13334572315216064, 'train/grad_norm_pre_clip': 3.592231512069702, 'timing/data': 0.0001760120503604412, 'timing/model': 0.4602373456582427, 'learning_rate/action_model': 7.713134133358106e-05, 'learning_rate/action_query_proj': 7.713134133358106e-05, 'learning_rate/base': 1.9282835333395265e-05, 'epoch': 0.44}) +[2026-07-27 05:36:14,913][starVLA.training.train_starvla][INFO] - Step 3624, Loss: {'train/loss': 0.11142319440841675, 'train/grad_norm_pre_clip': 3.798901319503784, 'timing/data': 0.0001915469765663147, 'timing/model': 0.4643366620875895, 'learning_rate/action_model': 7.710564117562808e-05, 'learning_rate/action_query_proj': 7.710564117562808e-05, 'learning_rate/base': 1.927641029390702e-05, 'epoch': 0.44}) +[2026-07-27 05:36:20,507][starVLA.training.train_starvla][INFO] - Step 3625, Loss: {'train/loss': 0.10577152669429779, 'train/grad_norm_pre_clip': 3.758693218231201, 'timing/data': 0.00017404509708285332, 'timing/model': 0.45645998464897275, 'learning_rate/action_model': 7.707993110636554e-05, 'learning_rate/action_query_proj': 7.707993110636554e-05, 'learning_rate/base': 1.9269982776591384e-05, 'epoch': 0.44}) +[2026-07-27 05:36:26,121][starVLA.training.train_starvla][INFO] - Step 3626, Loss: {'train/loss': 0.08816488832235336, 'train/grad_norm_pre_clip': 3.847907543182373, 'timing/data': 0.00017439480870962143, 'timing/model': 0.4610227127559483, 'learning_rate/action_model': 7.705421113594342e-05, 'learning_rate/action_query_proj': 7.705421113594342e-05, 'learning_rate/base': 1.9263552783985854e-05, 'epoch': 0.44}) +[2026-07-27 05:36:31,713][starVLA.training.train_starvla][INFO] - Step 3627, Loss: {'train/loss': 0.04917310178279877, 'train/grad_norm_pre_clip': 2.5439391136169434, 'timing/data': 0.00018065189942717552, 'timing/model': 0.4636279521510005, 'learning_rate/action_model': 7.70284812745155e-05, 'learning_rate/action_query_proj': 7.70284812745155e-05, 'learning_rate/base': 1.9257120318628875e-05, 'epoch': 0.44}) +[2026-07-27 05:36:37,537][starVLA.training.train_starvla][INFO] - Step 3628, Loss: {'train/loss': 0.13036119937896729, 'train/grad_norm_pre_clip': 4.786994934082031, 'timing/data': 0.00018191710114479065, 'timing/model': 0.45941170025616884, 'learning_rate/action_model': 7.700274153223958e-05, 'learning_rate/action_query_proj': 7.700274153223958e-05, 'learning_rate/base': 1.9250685383059894e-05, 'epoch': 0.44}) +[2026-07-27 05:36:43,149][starVLA.training.train_starvla][INFO] - Step 3629, Loss: {'train/loss': 0.12668055295944214, 'train/grad_norm_pre_clip': 4.167544841766357, 'timing/data': 0.0001764567568898201, 'timing/model': 0.4648017091676593, 'learning_rate/action_model': 7.697699191927726e-05, 'learning_rate/action_query_proj': 7.697699191927726e-05, 'learning_rate/base': 1.9244247979819314e-05, 'epoch': 0.44}) +[2026-07-27 05:36:48,754][starVLA.training.train_starvla][INFO] - Step 3630, Loss: {'train/loss': 0.09595467150211334, 'train/grad_norm_pre_clip': 3.962810516357422, 'timing/data': 0.0001731780357658863, 'timing/model': 0.45961674116551876, 'learning_rate/action_model': 7.695123244579405e-05, 'learning_rate/action_query_proj': 7.695123244579405e-05, 'learning_rate/base': 1.9237808111448512e-05, 'epoch': 0.44}) +[2026-07-27 05:36:54,358][starVLA.training.train_starvla][INFO] - Step 3631, Loss: {'train/loss': 0.09264180809259415, 'train/grad_norm_pre_clip': 3.8614187240600586, 'timing/data': 0.0001881769858300686, 'timing/model': 0.4601841187104583, 'learning_rate/action_model': 7.692546312195947e-05, 'learning_rate/action_query_proj': 7.692546312195947e-05, 'learning_rate/base': 1.9231365780489867e-05, 'epoch': 0.44}) +[2026-07-27 05:36:59,959][starVLA.training.train_starvla][INFO] - Step 3632, Loss: {'train/loss': 0.19211213290691376, 'train/grad_norm_pre_clip': 4.6133952140808105, 'timing/data': 0.00017461692914366722, 'timing/model': 0.4570509782060981, 'learning_rate/action_model': 7.689968395794677e-05, 'learning_rate/action_query_proj': 7.689968395794677e-05, 'learning_rate/base': 1.9224920989486692e-05, 'epoch': 0.44}) +[2026-07-27 05:37:05,574][starVLA.training.train_starvla][INFO] - Step 3633, Loss: {'train/loss': 0.08709298819303513, 'train/grad_norm_pre_clip': 3.8842759132385254, 'timing/data': 0.00018366798758506775, 'timing/model': 0.4651957559399307, 'learning_rate/action_model': 7.68738949639332e-05, 'learning_rate/action_query_proj': 7.68738949639332e-05, 'learning_rate/base': 1.92184737409833e-05, 'epoch': 0.44}) +[2026-07-27 05:37:11,177][starVLA.training.train_starvla][INFO] - Step 3634, Loss: {'train/loss': 0.07564013451337814, 'train/grad_norm_pre_clip': 3.761894702911377, 'timing/data': 0.00017917901277542114, 'timing/model': 0.4652045429684222, 'learning_rate/action_model': 7.684809615009978e-05, 'learning_rate/action_query_proj': 7.684809615009978e-05, 'learning_rate/base': 1.9212024037524946e-05, 'epoch': 0.44}) +[2026-07-27 05:37:16,778][starVLA.training.train_starvla][INFO] - Step 3635, Loss: {'train/loss': 0.13836169242858887, 'train/grad_norm_pre_clip': 5.671274185180664, 'timing/data': 0.00017671100795269012, 'timing/model': 0.46011618385091424, 'learning_rate/action_model': 7.682228752663154e-05, 'learning_rate/action_query_proj': 7.682228752663154e-05, 'learning_rate/base': 1.9205571881657884e-05, 'epoch': 0.44}) +[2026-07-27 05:37:22,377][starVLA.training.train_starvla][INFO] - Step 3636, Loss: {'train/loss': 0.18047122657299042, 'train/grad_norm_pre_clip': 4.952784538269043, 'timing/data': 0.00017221597954630852, 'timing/model': 0.4631611919030547, 'learning_rate/action_model': 7.679646910371731e-05, 'learning_rate/action_query_proj': 7.679646910371731e-05, 'learning_rate/base': 1.9199117275929328e-05, 'epoch': 0.44}) +[2026-07-27 05:37:28,003][starVLA.training.train_starvla][INFO] - Step 3637, Loss: {'train/loss': 0.10529981553554535, 'train/grad_norm_pre_clip': 3.1841065883636475, 'timing/data': 0.00018814904615283012, 'timing/model': 0.4613007181324065, 'learning_rate/action_model': 7.677064089154976e-05, 'learning_rate/action_query_proj': 7.677064089154976e-05, 'learning_rate/base': 1.919266022288744e-05, 'epoch': 0.44}) +[2026-07-27 05:37:33,621][starVLA.training.train_starvla][INFO] - Step 3638, Loss: {'train/loss': 0.04026225954294205, 'train/grad_norm_pre_clip': 1.762011170387268, 'timing/data': 0.00017219502478837967, 'timing/model': 0.46456324122846127, 'learning_rate/action_model': 7.674480290032549e-05, 'learning_rate/action_query_proj': 7.674480290032549e-05, 'learning_rate/base': 1.918620072508137e-05, 'epoch': 0.44}) +[2026-07-27 05:37:39,241][starVLA.training.train_starvla][INFO] - Step 3639, Loss: {'train/loss': 0.1037486344575882, 'train/grad_norm_pre_clip': 3.8913729190826416, 'timing/data': 0.000183159951120615, 'timing/model': 0.4645979730412364, 'learning_rate/action_model': 7.671895514024492e-05, 'learning_rate/action_query_proj': 7.671895514024492e-05, 'learning_rate/base': 1.917973878506123e-05, 'epoch': 0.44}) +[2026-07-27 05:37:44,853][starVLA.training.train_starvla][INFO] - Step 3640, Loss: {'train/loss': 0.14406079053878784, 'train/grad_norm_pre_clip': 3.0405919551849365, 'timing/data': 0.0001748260110616684, 'timing/model': 0.46020470885559916, 'learning_rate/action_model': 7.66930976215123e-05, 'learning_rate/action_query_proj': 7.66930976215123e-05, 'learning_rate/base': 1.9173274405378077e-05, 'epoch': 0.44}) +[2026-07-27 05:37:50,467][starVLA.training.train_starvla][INFO] - Step 3641, Loss: {'train/loss': 0.08510391414165497, 'train/grad_norm_pre_clip': 3.728868007659912, 'timing/data': 0.00017449725419282913, 'timing/model': 0.46071888599544764, 'learning_rate/action_model': 7.666723035433584e-05, 'learning_rate/action_query_proj': 7.666723035433584e-05, 'learning_rate/base': 1.916680758858396e-05, 'epoch': 0.44}) +[2026-07-27 05:37:56,074][starVLA.training.train_starvla][INFO] - Step 3642, Loss: {'train/loss': 0.10124354064464569, 'train/grad_norm_pre_clip': 3.84665846824646, 'timing/data': 0.00017140572890639305, 'timing/model': 0.4596893088892102, 'learning_rate/action_model': 7.664135334892747e-05, 'learning_rate/action_query_proj': 7.664135334892747e-05, 'learning_rate/base': 1.9160338337231867e-05, 'epoch': 0.44}) +[2026-07-27 05:38:01,663][starVLA.training.train_starvla][INFO] - Step 3643, Loss: {'train/loss': 0.1245037168264389, 'train/grad_norm_pre_clip': 4.599370002746582, 'timing/data': 0.00017717387527227402, 'timing/model': 0.4585260022431612, 'learning_rate/action_model': 7.661546661550306e-05, 'learning_rate/action_query_proj': 7.661546661550306e-05, 'learning_rate/base': 1.9153866653875764e-05, 'epoch': 0.44}) +[2026-07-27 05:38:07,252][starVLA.training.train_starvla][INFO] - Step 3644, Loss: {'train/loss': 0.15659049153327942, 'train/grad_norm_pre_clip': 3.984083652496338, 'timing/data': 0.00020120292901992798, 'timing/model': 0.4628838440403342, 'learning_rate/action_model': 7.658957016428225e-05, 'learning_rate/action_query_proj': 7.658957016428225e-05, 'learning_rate/base': 1.9147392541070563e-05, 'epoch': 0.44}) +[2026-07-27 05:38:12,836][starVLA.training.train_starvla][INFO] - Step 3645, Loss: {'train/loss': 0.14505530893802643, 'train/grad_norm_pre_clip': 3.727832078933716, 'timing/data': 0.00017746025696396828, 'timing/model': 0.46472758520394564, 'learning_rate/action_model': 7.656366400548857e-05, 'learning_rate/action_query_proj': 7.656366400548857e-05, 'learning_rate/base': 1.914091600137214e-05, 'epoch': 0.44}) +[2026-07-27 05:38:18,445][starVLA.training.train_starvla][INFO] - Step 3646, Loss: {'train/loss': 0.06410235166549683, 'train/grad_norm_pre_clip': 2.5905983448028564, 'timing/data': 0.00017837900668382645, 'timing/model': 0.46459770714864135, 'learning_rate/action_model': 7.653774814934935e-05, 'learning_rate/action_query_proj': 7.653774814934935e-05, 'learning_rate/base': 1.9134437037337336e-05, 'epoch': 0.44}) +[2026-07-27 05:38:24,023][starVLA.training.train_starvla][INFO] - Step 3647, Loss: {'train/loss': 0.07938181608915329, 'train/grad_norm_pre_clip': 3.155977725982666, 'timing/data': 0.00017653917893767357, 'timing/model': 0.46072922414168715, 'learning_rate/action_model': 7.651182260609575e-05, 'learning_rate/action_query_proj': 7.651182260609575e-05, 'learning_rate/base': 1.9127955651523937e-05, 'epoch': 0.44}) +[2026-07-27 05:38:29,605][starVLA.training.train_starvla][INFO] - Step 3648, Loss: {'train/loss': 0.07124880701303482, 'train/grad_norm_pre_clip': 1.8833303451538086, 'timing/data': 0.00017860997468233109, 'timing/model': 0.46023618010804057, 'learning_rate/action_model': 7.648588738596279e-05, 'learning_rate/action_query_proj': 7.648588738596279e-05, 'learning_rate/base': 1.9121471846490698e-05, 'epoch': 0.44}) +[2026-07-27 05:38:35,215][starVLA.training.train_starvla][INFO] - Step 3649, Loss: {'train/loss': 0.15174385905265808, 'train/grad_norm_pre_clip': 4.242089748382568, 'timing/data': 0.00017904676496982574, 'timing/model': 0.46372747514396906, 'learning_rate/action_model': 7.645994249918927e-05, 'learning_rate/action_query_proj': 7.645994249918927e-05, 'learning_rate/base': 1.9114985624797318e-05, 'epoch': 0.44}) +[2026-07-27 05:38:40,821][starVLA.training.train_starvla][INFO] - Step 3650, Loss: {'train/loss': 0.07145944237709045, 'train/grad_norm_pre_clip': 3.724456310272217, 'timing/data': 0.0001774737611413002, 'timing/model': 0.46177083207294345, 'learning_rate/action_model': 7.643398795601782e-05, 'learning_rate/action_query_proj': 7.643398795601782e-05, 'learning_rate/base': 1.9108496989004455e-05, 'epoch': 0.44}) +[2026-07-27 05:38:46,451][starVLA.training.train_starvla][INFO] - Step 3651, Loss: {'train/loss': 0.1414863020181656, 'train/grad_norm_pre_clip': 3.7318694591522217, 'timing/data': 0.0001835511066019535, 'timing/model': 0.463856662157923, 'learning_rate/action_model': 7.640802376669489e-05, 'learning_rate/action_query_proj': 7.640802376669489e-05, 'learning_rate/base': 1.9102005941673722e-05, 'epoch': 0.44}) +[2026-07-27 05:38:52,083][starVLA.training.train_starvla][INFO] - Step 3652, Loss: {'train/loss': 0.07202719897031784, 'train/grad_norm_pre_clip': 2.803650379180908, 'timing/data': 0.0001760050654411316, 'timing/model': 0.46522687701508403, 'learning_rate/action_model': 7.63820499414707e-05, 'learning_rate/action_query_proj': 7.63820499414707e-05, 'learning_rate/base': 1.9095512485367677e-05, 'epoch': 0.44}) +[2026-07-27 05:38:57,667][starVLA.training.train_starvla][INFO] - Step 3653, Loss: {'train/loss': 0.1565670520067215, 'train/grad_norm_pre_clip': 2.8593459129333496, 'timing/data': 0.00019160378724336624, 'timing/model': 0.4617185387760401, 'learning_rate/action_model': 7.635606649059939e-05, 'learning_rate/action_query_proj': 7.635606649059939e-05, 'learning_rate/base': 1.9089016622649847e-05, 'epoch': 0.44}) +[2026-07-27 05:39:03,529][starVLA.training.train_starvla][INFO] - Step 3654, Loss: {'train/loss': 0.1640368402004242, 'train/grad_norm_pre_clip': 3.5148367881774902, 'timing/data': 0.00017770612612366676, 'timing/model': 0.46205819491297007, 'learning_rate/action_model': 7.633007342433872e-05, 'learning_rate/action_query_proj': 7.633007342433872e-05, 'learning_rate/base': 1.908251835608468e-05, 'epoch': 0.44}) +[2026-07-27 05:39:09,121][starVLA.training.train_starvla][INFO] - Step 3655, Loss: {'train/loss': 0.1340837925672531, 'train/grad_norm_pre_clip': 2.791545867919922, 'timing/data': 0.00016941409558057785, 'timing/model': 0.45972948195412755, 'learning_rate/action_model': 7.630407075295037e-05, 'learning_rate/action_query_proj': 7.630407075295037e-05, 'learning_rate/base': 1.907601768823759e-05, 'epoch': 0.44}) +[2026-07-27 05:39:14,743][starVLA.training.train_starvla][INFO] - Step 3656, Loss: {'train/loss': 0.09868402034044266, 'train/grad_norm_pre_clip': 3.863969087600708, 'timing/data': 0.00017322180792689323, 'timing/model': 0.4609730700030923, 'learning_rate/action_model': 7.62780584866998e-05, 'learning_rate/action_query_proj': 7.62780584866998e-05, 'learning_rate/base': 1.906951462167495e-05, 'epoch': 0.44}) +[2026-07-27 05:39:20,353][starVLA.training.train_starvla][INFO] - Step 3657, Loss: {'train/loss': 0.1356433928012848, 'train/grad_norm_pre_clip': 2.6306424140930176, 'timing/data': 0.00018046190962195396, 'timing/model': 0.46135845920071006, 'learning_rate/action_model': 7.625203663585622e-05, 'learning_rate/action_query_proj': 7.625203663585622e-05, 'learning_rate/base': 1.9063009158964054e-05, 'epoch': 0.44}) +[2026-07-27 05:39:25,978][starVLA.training.train_starvla][INFO] - Step 3658, Loss: {'train/loss': 0.07151190936565399, 'train/grad_norm_pre_clip': 2.775320291519165, 'timing/data': 0.00017913710325956345, 'timing/model': 0.4649354419670999, 'learning_rate/action_model': 7.622600521069266e-05, 'learning_rate/action_query_proj': 7.622600521069266e-05, 'learning_rate/base': 1.9056501302673165e-05, 'epoch': 0.44}) +[2026-07-27 05:39:31,602][starVLA.training.train_starvla][INFO] - Step 3659, Loss: {'train/loss': 0.027439605444669724, 'train/grad_norm_pre_clip': 1.4654840230941772, 'timing/data': 0.000173117034137249, 'timing/model': 0.46077160397544503, 'learning_rate/action_model': 7.619996422148589e-05, 'learning_rate/action_query_proj': 7.619996422148589e-05, 'learning_rate/base': 1.9049991055371473e-05, 'epoch': 0.44}) +[2026-07-27 05:39:37,246][starVLA.training.train_starvla][INFO] - Step 3660, Loss: {'train/loss': 0.202810138463974, 'train/grad_norm_pre_clip': 4.163593769073486, 'timing/data': 0.00017756503075361252, 'timing/model': 0.4639570009894669, 'learning_rate/action_model': 7.617391367851653e-05, 'learning_rate/action_query_proj': 7.617391367851653e-05, 'learning_rate/base': 1.9043478419629132e-05, 'epoch': 0.44}) +[2026-07-27 05:39:43,091][starVLA.training.train_starvla][INFO] - Step 3661, Loss: {'train/loss': 0.07334896922111511, 'train/grad_norm_pre_clip': 1.9480476379394531, 'timing/data': 0.00017424020916223526, 'timing/model': 0.46081123081967235, 'learning_rate/action_model': 7.614785359206888e-05, 'learning_rate/action_query_proj': 7.614785359206888e-05, 'learning_rate/base': 1.903696339801722e-05, 'epoch': 0.44}) +[2026-07-27 05:39:48,710][starVLA.training.train_starvla][INFO] - Step 3662, Loss: {'train/loss': 0.03002886474132538, 'train/grad_norm_pre_clip': 1.2308908700942993, 'timing/data': 0.0001694769598543644, 'timing/model': 0.46487587690353394, 'learning_rate/action_model': 7.612178397243105e-05, 'learning_rate/action_query_proj': 7.612178397243105e-05, 'learning_rate/base': 1.9030445993107763e-05, 'epoch': 0.44}) +[2026-07-27 05:39:54,299][starVLA.training.train_starvla][INFO] - Step 3663, Loss: {'train/loss': 0.03572066128253937, 'train/grad_norm_pre_clip': 1.9132894277572632, 'timing/data': 0.00017869379371404648, 'timing/model': 0.4621597579680383, 'learning_rate/action_model': 7.609570482989494e-05, 'learning_rate/action_query_proj': 7.609570482989494e-05, 'learning_rate/base': 1.9023926207473734e-05, 'epoch': 0.44}) +[2026-07-27 05:39:59,890][starVLA.training.train_starvla][INFO] - Step 3664, Loss: {'train/loss': 0.07391785830259323, 'train/grad_norm_pre_clip': 2.2389540672302246, 'timing/data': 0.00023788120597600937, 'timing/model': 0.46051735803484917, 'learning_rate/action_model': 7.606961617475615e-05, 'learning_rate/action_query_proj': 7.606961617475615e-05, 'learning_rate/base': 1.9017404043689037e-05, 'epoch': 0.44}) +[2026-07-27 05:40:05,501][starVLA.training.train_starvla][INFO] - Step 3665, Loss: {'train/loss': 0.12619513273239136, 'train/grad_norm_pre_clip': 4.102872371673584, 'timing/data': 0.00016638729721307755, 'timing/model': 0.46233206475153565, 'learning_rate/action_model': 7.604351801731409e-05, 'learning_rate/action_query_proj': 7.604351801731409e-05, 'learning_rate/base': 1.9010879504328523e-05, 'epoch': 0.44}) +[2026-07-27 05:40:11,100][starVLA.training.train_starvla][INFO] - Step 3666, Loss: {'train/loss': 0.06885372847318649, 'train/grad_norm_pre_clip': 3.163702964782715, 'timing/data': 0.00017353007569909096, 'timing/model': 0.4616473838686943, 'learning_rate/action_model': 7.601741036787187e-05, 'learning_rate/action_query_proj': 7.601741036787187e-05, 'learning_rate/base': 1.9004352591967968e-05, 'epoch': 0.44}) +[2026-07-27 05:40:16,705][starVLA.training.train_starvla][INFO] - Step 3667, Loss: {'train/loss': 0.09215099364519119, 'train/grad_norm_pre_clip': 4.48309326171875, 'timing/data': 0.0001724069006741047, 'timing/model': 0.465527699328959, 'learning_rate/action_model': 7.599129323673643e-05, 'learning_rate/action_query_proj': 7.599129323673643e-05, 'learning_rate/base': 1.8997823309184108e-05, 'epoch': 0.44}) +[2026-07-27 05:40:22,315][starVLA.training.train_starvla][INFO] - Step 3668, Loss: {'train/loss': 0.13830098509788513, 'train/grad_norm_pre_clip': 3.515029191970825, 'timing/data': 0.00016997195780277252, 'timing/model': 0.46119694504886866, 'learning_rate/action_model': 7.596516663421837e-05, 'learning_rate/action_query_proj': 7.596516663421837e-05, 'learning_rate/base': 1.8991291658554592e-05, 'epoch': 0.44}) +[2026-07-27 05:40:27,907][starVLA.training.train_starvla][INFO] - Step 3669, Loss: {'train/loss': 0.05012673884630203, 'train/grad_norm_pre_clip': 2.183997392654419, 'timing/data': 0.00018034595996141434, 'timing/model': 0.4653556779958308, 'learning_rate/action_model': 7.593903057063204e-05, 'learning_rate/action_query_proj': 7.593903057063204e-05, 'learning_rate/base': 1.898475764265801e-05, 'epoch': 0.45}) +[2026-07-27 05:40:33,506][starVLA.training.train_starvla][INFO] - Step 3670, Loss: {'train/loss': 0.10597188770771027, 'train/grad_norm_pre_clip': 3.7051889896392822, 'timing/data': 0.0002306508831679821, 'timing/model': 0.46186269307509065, 'learning_rate/action_model': 7.591288505629556e-05, 'learning_rate/action_query_proj': 7.591288505629556e-05, 'learning_rate/base': 1.897822126407389e-05, 'epoch': 0.45}) +[2026-07-27 05:40:39,083][starVLA.training.train_starvla][INFO] - Step 3671, Loss: {'train/loss': 0.053502157330513, 'train/grad_norm_pre_clip': 2.3042078018188477, 'timing/data': 0.0001791883260011673, 'timing/model': 0.46095404494553804, 'learning_rate/action_model': 7.588673010153079e-05, 'learning_rate/action_query_proj': 7.588673010153079e-05, 'learning_rate/base': 1.8971682525382696e-05, 'epoch': 0.45}) +[2026-07-27 05:40:44,659][starVLA.training.train_starvla][INFO] - Step 3672, Loss: {'train/loss': 0.09561128914356232, 'train/grad_norm_pre_clip': 3.3133373260498047, 'timing/data': 0.0001783580519258976, 'timing/model': 0.4624430169351399, 'learning_rate/action_model': 7.586056571666326e-05, 'learning_rate/action_query_proj': 7.586056571666326e-05, 'learning_rate/base': 1.8965141429165815e-05, 'epoch': 0.45}) +[2026-07-27 05:40:50,244][starVLA.training.train_starvla][INFO] - Step 3673, Loss: {'train/loss': 0.04798811674118042, 'train/grad_norm_pre_clip': 2.520341157913208, 'timing/data': 0.0001769019290804863, 'timing/model': 0.461486607324332, 'learning_rate/action_model': 7.583439191202224e-05, 'learning_rate/action_query_proj': 7.583439191202224e-05, 'learning_rate/base': 1.895859797800556e-05, 'epoch': 0.45}) +[2026-07-27 05:40:55,809][starVLA.training.train_starvla][INFO] - Step 3674, Loss: {'train/loss': 0.08218640834093094, 'train/grad_norm_pre_clip': 3.243495464324951, 'timing/data': 0.00017609726637601852, 'timing/model': 0.4642830742523074, 'learning_rate/action_model': 7.580820869794077e-05, 'learning_rate/action_query_proj': 7.580820869794077e-05, 'learning_rate/base': 1.8952052174485192e-05, 'epoch': 0.45}) +[2026-07-27 05:41:01,390][starVLA.training.train_starvla][INFO] - Step 3675, Loss: {'train/loss': 0.16050034761428833, 'train/grad_norm_pre_clip': 5.178158760070801, 'timing/data': 0.0001715593971312046, 'timing/model': 0.4622792820446193, 'learning_rate/action_model': 7.578201608475557e-05, 'learning_rate/action_query_proj': 7.578201608475557e-05, 'learning_rate/base': 1.8945504021188893e-05, 'epoch': 0.45}) +[2026-07-27 05:41:06,987][starVLA.training.train_starvla][INFO] - Step 3676, Loss: {'train/loss': 0.10494469851255417, 'train/grad_norm_pre_clip': 3.5093116760253906, 'timing/data': 0.00017306767404079437, 'timing/model': 0.4645031252875924, 'learning_rate/action_model': 7.575581408280705e-05, 'learning_rate/action_query_proj': 7.575581408280705e-05, 'learning_rate/base': 1.8938953520701762e-05, 'epoch': 0.45}) +[2026-07-27 05:41:12,774][starVLA.training.train_starvla][INFO] - Step 3677, Loss: {'train/loss': 0.14204981923103333, 'train/grad_norm_pre_clip': 3.675689220428467, 'timing/data': 0.00016991281881928444, 'timing/model': 0.4654985419474542, 'learning_rate/action_model': 7.572960270243934e-05, 'learning_rate/action_query_proj': 7.572960270243934e-05, 'learning_rate/base': 1.8932400675609835e-05, 'epoch': 0.45}) +[2026-07-27 05:41:18,353][starVLA.training.train_starvla][INFO] - Step 3678, Loss: {'train/loss': 0.05680132284760475, 'train/grad_norm_pre_clip': 2.5247104167938232, 'timing/data': 0.00017720600590109825, 'timing/model': 0.4648347548209131, 'learning_rate/action_model': 7.570338195400029e-05, 'learning_rate/action_query_proj': 7.570338195400029e-05, 'learning_rate/base': 1.8925845488500073e-05, 'epoch': 0.45}) +[2026-07-27 05:41:23,902][starVLA.training.train_starvla][INFO] - Step 3679, Loss: {'train/loss': 0.12621480226516724, 'train/grad_norm_pre_clip': 3.2680718898773193, 'timing/data': 0.0001717330887913704, 'timing/model': 0.4607378481887281, 'learning_rate/action_model': 7.567715184784144e-05, 'learning_rate/action_query_proj': 7.567715184784144e-05, 'learning_rate/base': 1.891928796196036e-05, 'epoch': 0.45}) +[2026-07-27 05:41:29,468][starVLA.training.train_starvla][INFO] - Step 3680, Loss: {'train/loss': 0.0654151439666748, 'train/grad_norm_pre_clip': 3.3012404441833496, 'timing/data': 0.0002091880887746811, 'timing/model': 0.456603295635432, 'learning_rate/action_model': 7.5650912394318e-05, 'learning_rate/action_query_proj': 7.5650912394318e-05, 'learning_rate/base': 1.89127280985795e-05, 'epoch': 0.45}) +[2026-07-27 05:41:35,034][starVLA.training.train_starvla][INFO] - Step 3681, Loss: {'train/loss': 0.02326534502208233, 'train/grad_norm_pre_clip': 1.3060705661773682, 'timing/data': 0.00017339596524834633, 'timing/model': 0.45745497895404696, 'learning_rate/action_model': 7.562466360378891e-05, 'learning_rate/action_query_proj': 7.562466360378891e-05, 'learning_rate/base': 1.8906165900947228e-05, 'epoch': 0.45}) +[2026-07-27 05:41:40,611][starVLA.training.train_starvla][INFO] - Step 3682, Loss: {'train/loss': 0.05485973879694939, 'train/grad_norm_pre_clip': 2.3915772438049316, 'timing/data': 0.00017041899263858795, 'timing/model': 0.4637846262194216, 'learning_rate/action_model': 7.559840548661678e-05, 'learning_rate/action_query_proj': 7.559840548661678e-05, 'learning_rate/base': 1.8899601371654195e-05, 'epoch': 0.45}) +[2026-07-27 05:41:46,173][starVLA.training.train_starvla][INFO] - Step 3683, Loss: {'train/loss': 0.09213172644376755, 'train/grad_norm_pre_clip': 3.1935768127441406, 'timing/data': 0.00017073098570108414, 'timing/model': 0.4625776042230427, 'learning_rate/action_model': 7.557213805316788e-05, 'learning_rate/action_query_proj': 7.557213805316788e-05, 'learning_rate/base': 1.889303451329197e-05, 'epoch': 0.45}) +[2026-07-27 05:41:51,767][starVLA.training.train_starvla][INFO] - Step 3684, Loss: {'train/loss': 0.18225055932998657, 'train/grad_norm_pre_clip': 5.370419979095459, 'timing/data': 0.00017212796956300735, 'timing/model': 0.464301731903106, 'learning_rate/action_model': 7.55458613138122e-05, 'learning_rate/action_query_proj': 7.55458613138122e-05, 'learning_rate/base': 1.888646532845305e-05, 'epoch': 0.45}) +[2026-07-27 05:41:57,343][starVLA.training.train_starvla][INFO] - Step 3685, Loss: {'train/loss': 0.0332036092877388, 'train/grad_norm_pre_clip': 1.85503089427948, 'timing/data': 0.00017123017460107803, 'timing/model': 0.46109086694195867, 'learning_rate/action_model': 7.551957527892335e-05, 'learning_rate/action_query_proj': 7.551957527892335e-05, 'learning_rate/base': 1.887989381973084e-05, 'epoch': 0.45}) +[2026-07-27 05:42:02,913][starVLA.training.train_starvla][INFO] - Step 3686, Loss: {'train/loss': 0.06867162138223648, 'train/grad_norm_pre_clip': 3.0342910289764404, 'timing/data': 0.00017241109162569046, 'timing/model': 0.46394521137699485, 'learning_rate/action_model': 7.549327995887869e-05, 'learning_rate/action_query_proj': 7.549327995887869e-05, 'learning_rate/base': 1.8873319989719672e-05, 'epoch': 0.45}) +[2026-07-27 05:42:08,654][starVLA.training.train_starvla][INFO] - Step 3687, Loss: {'train/loss': 0.13287325203418732, 'train/grad_norm_pre_clip': 4.459425449371338, 'timing/data': 0.0001705358736217022, 'timing/model': 0.46055577090010047, 'learning_rate/action_model': 7.546697536405914e-05, 'learning_rate/action_query_proj': 7.546697536405914e-05, 'learning_rate/base': 1.8866743841014786e-05, 'epoch': 0.45}) +[2026-07-27 05:42:14,274][starVLA.training.train_starvla][INFO] - Step 3688, Loss: {'train/loss': 0.04648031294345856, 'train/grad_norm_pre_clip': 2.851011037826538, 'timing/data': 0.00019272183999419212, 'timing/model': 0.46593560464680195, 'learning_rate/action_model': 7.544066150484936e-05, 'learning_rate/action_query_proj': 7.544066150484936e-05, 'learning_rate/base': 1.886016537621234e-05, 'epoch': 0.45}) +[2026-07-27 05:42:19,912][starVLA.training.train_starvla][INFO] - Step 3689, Loss: {'train/loss': 0.06261687725782394, 'train/grad_norm_pre_clip': 3.5362143516540527, 'timing/data': 0.00017772195860743523, 'timing/model': 0.46599994879215956, 'learning_rate/action_model': 7.541433839163765e-05, 'learning_rate/action_query_proj': 7.541433839163765e-05, 'learning_rate/base': 1.8853584597909412e-05, 'epoch': 0.45}) +[2026-07-27 05:42:25,564][starVLA.training.train_starvla][INFO] - Step 3690, Loss: {'train/loss': 0.05280112847685814, 'train/grad_norm_pre_clip': 3.7652642726898193, 'timing/data': 0.00018336297944188118, 'timing/model': 0.4644656549207866, 'learning_rate/action_model': 7.538800603481596e-05, 'learning_rate/action_query_proj': 7.538800603481596e-05, 'learning_rate/base': 1.884700150870399e-05, 'epoch': 0.45}) +[2026-07-27 05:42:31,206][starVLA.training.train_starvla][INFO] - Step 3691, Loss: {'train/loss': 0.2374938577413559, 'train/grad_norm_pre_clip': 7.2429022789001465, 'timing/data': 0.00016822805628180504, 'timing/model': 0.4644744610413909, 'learning_rate/action_model': 7.536166444477986e-05, 'learning_rate/action_query_proj': 7.536166444477986e-05, 'learning_rate/base': 1.8840416111194966e-05, 'epoch': 0.45}) +[2026-07-27 05:42:36,807][starVLA.training.train_starvla][INFO] - Step 3692, Loss: {'train/loss': 0.09519585222005844, 'train/grad_norm_pre_clip': 3.6813929080963135, 'timing/data': 0.00016431184485554695, 'timing/model': 0.4651471581310034, 'learning_rate/action_model': 7.533531363192865e-05, 'learning_rate/action_query_proj': 7.533531363192865e-05, 'learning_rate/base': 1.8833828407982163e-05, 'epoch': 0.45}) +[2026-07-27 05:42:42,394][starVLA.training.train_starvla][INFO] - Step 3693, Loss: {'train/loss': 0.06543026864528656, 'train/grad_norm_pre_clip': 2.5592164993286133, 'timing/data': 0.00018212664872407913, 'timing/model': 0.45716852601617575, 'learning_rate/action_model': 7.530895360666515e-05, 'learning_rate/action_query_proj': 7.530895360666515e-05, 'learning_rate/base': 1.882723840166629e-05, 'epoch': 0.45}) +[2026-07-27 05:42:47,991][starVLA.training.train_starvla][INFO] - Step 3694, Loss: {'train/loss': 0.08204615116119385, 'train/grad_norm_pre_clip': 2.586925745010376, 'timing/data': 0.00023661227896809578, 'timing/model': 0.46398097090423107, 'learning_rate/action_model': 7.528258437939592e-05, 'learning_rate/action_query_proj': 7.528258437939592e-05, 'learning_rate/base': 1.882064609484898e-05, 'epoch': 0.45}) +[2026-07-27 05:42:53,591][starVLA.training.train_starvla][INFO] - Step 3695, Loss: {'train/loss': 0.0950477123260498, 'train/grad_norm_pre_clip': 3.6054768562316895, 'timing/data': 0.0001719202846288681, 'timing/model': 0.4634524709545076, 'learning_rate/action_model': 7.52562059605311e-05, 'learning_rate/action_query_proj': 7.52562059605311e-05, 'learning_rate/base': 1.8814051490132775e-05, 'epoch': 0.45}) +[2026-07-27 05:42:59,194][starVLA.training.train_starvla][INFO] - Step 3696, Loss: {'train/loss': 0.05506225302815437, 'train/grad_norm_pre_clip': 3.0729637145996094, 'timing/data': 0.00016937172040343285, 'timing/model': 0.4612603117711842, 'learning_rate/action_model': 7.522981836048447e-05, 'learning_rate/action_query_proj': 7.522981836048447e-05, 'learning_rate/base': 1.880745459012112e-05, 'epoch': 0.45}) +[2026-07-27 05:43:04,796][starVLA.training.train_starvla][INFO] - Step 3697, Loss: {'train/loss': 0.039805006235837936, 'train/grad_norm_pre_clip': 2.18139910697937, 'timing/data': 0.00019072787836194038, 'timing/model': 0.46066595520824194, 'learning_rate/action_model': 7.520342158967347e-05, 'learning_rate/action_query_proj': 7.520342158967347e-05, 'learning_rate/base': 1.8800855397418367e-05, 'epoch': 0.45}) +[2026-07-27 05:43:10,392][starVLA.training.train_starvla][INFO] - Step 3698, Loss: {'train/loss': 0.08106598258018494, 'train/grad_norm_pre_clip': 3.7646970748901367, 'timing/data': 0.00017152214422821999, 'timing/model': 0.4616079810075462, 'learning_rate/action_model': 7.517701565851905e-05, 'learning_rate/action_query_proj': 7.517701565851905e-05, 'learning_rate/base': 1.8794253914629763e-05, 'epoch': 0.45}) +[2026-07-27 05:43:15,995][starVLA.training.train_starvla][INFO] - Step 3699, Loss: {'train/loss': 0.0900522843003273, 'train/grad_norm_pre_clip': 4.156022548675537, 'timing/data': 0.00017087208107113838, 'timing/model': 0.46119763888418674, 'learning_rate/action_model': 7.515060057744594e-05, 'learning_rate/action_query_proj': 7.515060057744594e-05, 'learning_rate/base': 1.8787650144361485e-05, 'epoch': 0.45}) +[2026-07-27 05:43:21,586][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 3700 +[2026-07-27 05:43:21,586][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 3700 +[2026-07-27 05:43:21,587][starVLA.training.train_starvla][INFO] - Step 3700, Loss: {'train/loss': 0.12889741361141205, 'train/grad_norm_pre_clip': 3.272947072982788, 'timing/data': 0.00016884692013263702, 'timing/model': 0.46362031484022737, 'learning_rate/action_model': 7.512417635688234e-05, 'learning_rate/action_query_proj': 7.512417635688234e-05, 'learning_rate/base': 1.8781044089220585e-05, 'epoch': 0.45}) +[2026-07-27 05:43:27,183][starVLA.training.train_starvla][INFO] - Step 3701, Loss: {'train/loss': 0.05728559195995331, 'train/grad_norm_pre_clip': 3.584278106689453, 'timing/data': 0.00017491215839982033, 'timing/model': 0.46214959025382996, 'learning_rate/action_model': 7.509774300726013e-05, 'learning_rate/action_query_proj': 7.509774300726013e-05, 'learning_rate/base': 1.8774435751815033e-05, 'epoch': 0.45}) +[2026-07-27 05:43:32,784][starVLA.training.train_starvla][INFO] - Step 3702, Loss: {'train/loss': 0.09123889356851578, 'train/grad_norm_pre_clip': 3.5465662479400635, 'timing/data': 0.00018381979316473007, 'timing/model': 0.4621042963117361, 'learning_rate/action_model': 7.507130053901479e-05, 'learning_rate/action_query_proj': 7.507130053901479e-05, 'learning_rate/base': 1.8767825134753698e-05, 'epoch': 0.45}) +[2026-07-27 05:43:38,582][starVLA.training.train_starvla][INFO] - Step 3703, Loss: {'train/loss': 0.035088393837213516, 'train/grad_norm_pre_clip': 2.0408029556274414, 'timing/data': 0.00016981316730380058, 'timing/model': 0.46426652977243066, 'learning_rate/action_model': 7.504484896258534e-05, 'learning_rate/action_query_proj': 7.504484896258534e-05, 'learning_rate/base': 1.8761212240646335e-05, 'epoch': 0.45}) +[2026-07-27 05:43:44,166][starVLA.training.train_starvla][INFO] - Step 3704, Loss: {'train/loss': 0.11982917040586472, 'train/grad_norm_pre_clip': 3.775726318359375, 'timing/data': 0.0001742900349199772, 'timing/model': 0.46115897316485643, 'learning_rate/action_model': 7.501838828841452e-05, 'learning_rate/action_query_proj': 7.501838828841452e-05, 'learning_rate/base': 1.875459707210363e-05, 'epoch': 0.45}) +[2026-07-27 05:43:49,774][starVLA.training.train_starvla][INFO] - Step 3705, Loss: {'train/loss': 0.06861565262079239, 'train/grad_norm_pre_clip': 3.197293281555176, 'timing/data': 0.00022536283358931541, 'timing/model': 0.4653005921281874, 'learning_rate/action_model': 7.499191852694854e-05, 'learning_rate/action_query_proj': 7.499191852694854e-05, 'learning_rate/base': 1.8747979631737135e-05, 'epoch': 0.45}) +[2026-07-27 05:43:55,359][starVLA.training.train_starvla][INFO] - Step 3706, Loss: {'train/loss': 0.048092320561409, 'train/grad_norm_pre_clip': 2.3696510791778564, 'timing/data': 0.00017089396715164185, 'timing/model': 0.4615990836173296, 'learning_rate/action_model': 7.496543968863722e-05, 'learning_rate/action_query_proj': 7.496543968863722e-05, 'learning_rate/base': 1.8741359922159306e-05, 'epoch': 0.45}) +[2026-07-27 05:44:00,947][starVLA.training.train_starvla][INFO] - Step 3707, Loss: {'train/loss': 0.043381109833717346, 'train/grad_norm_pre_clip': 2.108398199081421, 'timing/data': 0.00016792304813861847, 'timing/model': 0.4616513019427657, 'learning_rate/action_model': 7.493895178393404e-05, 'learning_rate/action_query_proj': 7.493895178393404e-05, 'learning_rate/base': 1.873473794598351e-05, 'epoch': 0.45}) +[2026-07-27 05:44:06,537][starVLA.training.train_starvla][INFO] - Step 3708, Loss: {'train/loss': 0.14490358531475067, 'train/grad_norm_pre_clip': 2.8535029888153076, 'timing/data': 0.00018089590594172478, 'timing/model': 0.46419404121115804, 'learning_rate/action_model': 7.491245482329597e-05, 'learning_rate/action_query_proj': 7.491245482329597e-05, 'learning_rate/base': 1.8728113705823993e-05, 'epoch': 0.45}) +[2026-07-27 05:44:12,126][starVLA.training.train_starvla][INFO] - Step 3709, Loss: {'train/loss': 0.027423009276390076, 'train/grad_norm_pre_clip': 1.7761996984481812, 'timing/data': 0.0002319030463695526, 'timing/model': 0.4658250827342272, 'learning_rate/action_model': 7.488594881718362e-05, 'learning_rate/action_query_proj': 7.488594881718362e-05, 'learning_rate/base': 1.8721487204295905e-05, 'epoch': 0.45}) +[2026-07-27 05:44:17,693][starVLA.training.train_starvla][INFO] - Step 3710, Loss: {'train/loss': 0.11795983463525772, 'train/grad_norm_pre_clip': 4.099474906921387, 'timing/data': 0.0001691528595983982, 'timing/model': 0.4650859753601253, 'learning_rate/action_model': 7.485943377606109e-05, 'learning_rate/action_query_proj': 7.485943377606109e-05, 'learning_rate/base': 1.8714858444015272e-05, 'epoch': 0.45}) +[2026-07-27 05:44:23,871][starVLA.training.train_starvla][INFO] - Step 3711, Loss: {'train/loss': 0.13765475153923035, 'train/grad_norm_pre_clip': 3.4711380004882812, 'timing/data': 0.00017358176410198212, 'timing/model': 0.4600907377898693, 'learning_rate/action_model': 7.483290971039614e-05, 'learning_rate/action_query_proj': 7.483290971039614e-05, 'learning_rate/base': 1.8708227427599036e-05, 'epoch': 0.45}) +[2026-07-27 05:44:29,474][starVLA.training.train_starvla][INFO] - Step 3712, Loss: {'train/loss': 0.03219117596745491, 'train/grad_norm_pre_clip': 1.931998372077942, 'timing/data': 0.00017631705850362778, 'timing/model': 0.4624718837440014, 'learning_rate/action_model': 7.480637663066004e-05, 'learning_rate/action_query_proj': 7.480637663066004e-05, 'learning_rate/base': 1.870159415766501e-05, 'epoch': 0.45}) +[2026-07-27 05:44:35,071][starVLA.training.train_starvla][INFO] - Step 3713, Loss: {'train/loss': 0.12198133021593094, 'train/grad_norm_pre_clip': 4.477407455444336, 'timing/data': 0.00018702121451497078, 'timing/model': 0.4625282706692815, 'learning_rate/action_model': 7.477983454732762e-05, 'learning_rate/action_query_proj': 7.477983454732762e-05, 'learning_rate/base': 1.8694958636831904e-05, 'epoch': 0.45}) +[2026-07-27 05:44:40,644][starVLA.training.train_starvla][INFO] - Step 3714, Loss: {'train/loss': 0.0747775137424469, 'train/grad_norm_pre_clip': 2.593496084213257, 'timing/data': 0.0001797298900783062, 'timing/model': 0.46097431518137455, 'learning_rate/action_model': 7.475328347087729e-05, 'learning_rate/action_query_proj': 7.475328347087729e-05, 'learning_rate/base': 1.868832086771932e-05, 'epoch': 0.45}) +[2026-07-27 05:44:46,209][starVLA.training.train_starvla][INFO] - Step 3715, Loss: {'train/loss': 0.13284486532211304, 'train/grad_norm_pre_clip': 4.1595964431762695, 'timing/data': 0.0001753191463649273, 'timing/model': 0.4651720463298261, 'learning_rate/action_model': 7.472672341179099e-05, 'learning_rate/action_query_proj': 7.472672341179099e-05, 'learning_rate/base': 1.8681680852947747e-05, 'epoch': 0.45}) +[2026-07-27 05:44:51,799][starVLA.training.train_starvla][INFO] - Step 3716, Loss: {'train/loss': 0.18553437292575836, 'train/grad_norm_pre_clip': 3.3230936527252197, 'timing/data': 0.00017510633915662766, 'timing/model': 0.46484156092628837, 'learning_rate/action_model': 7.470015438055421e-05, 'learning_rate/action_query_proj': 7.470015438055421e-05, 'learning_rate/base': 1.8675038595138553e-05, 'epoch': 0.45}) +[2026-07-27 05:44:57,633][starVLA.training.train_starvla][INFO] - Step 3717, Loss: {'train/loss': 0.1434544026851654, 'train/grad_norm_pre_clip': 5.098775863647461, 'timing/data': 0.00017708959057927132, 'timing/model': 0.46149657387286425, 'learning_rate/action_model': 7.467357638765598e-05, 'learning_rate/action_query_proj': 7.467357638765598e-05, 'learning_rate/base': 1.8668394096913996e-05, 'epoch': 0.45}) +[2026-07-27 05:45:03,224][starVLA.training.train_starvla][INFO] - Step 3718, Loss: {'train/loss': 0.06727857142686844, 'train/grad_norm_pre_clip': 3.3253324031829834, 'timing/data': 0.00018158182501792908, 'timing/model': 0.46080216113477945, 'learning_rate/action_model': 7.464698944358887e-05, 'learning_rate/action_query_proj': 7.464698944358887e-05, 'learning_rate/base': 1.8661747360897218e-05, 'epoch': 0.45}) +[2026-07-27 05:45:08,804][starVLA.training.train_starvla][INFO] - Step 3719, Loss: {'train/loss': 0.18449868261814117, 'train/grad_norm_pre_clip': 5.036194801330566, 'timing/data': 0.00018765591084957123, 'timing/model': 0.46118992008268833, 'learning_rate/action_model': 7.462039355884899e-05, 'learning_rate/action_query_proj': 7.462039355884899e-05, 'learning_rate/base': 1.8655098389712247e-05, 'epoch': 0.45}) +[2026-07-27 05:45:14,391][starVLA.training.train_starvla][INFO] - Step 3720, Loss: {'train/loss': 0.1181800365447998, 'train/grad_norm_pre_clip': 2.71769642829895, 'timing/data': 0.0001786472275853157, 'timing/model': 0.4679305972531438, 'learning_rate/action_model': 7.459378874393598e-05, 'learning_rate/action_query_proj': 7.459378874393598e-05, 'learning_rate/base': 1.8648447185983994e-05, 'epoch': 0.45}) +[2026-07-27 05:45:19,978][starVLA.training.train_starvla][INFO] - Step 3721, Loss: {'train/loss': 0.037574268877506256, 'train/grad_norm_pre_clip': 2.123547077178955, 'timing/data': 0.0001688632182776928, 'timing/model': 0.46298927115276456, 'learning_rate/action_model': 7.456717500935298e-05, 'learning_rate/action_query_proj': 7.456717500935298e-05, 'learning_rate/base': 1.8641793752338244e-05, 'epoch': 0.45}) +[2026-07-27 05:45:25,557][starVLA.training.train_starvla][INFO] - Step 3722, Loss: {'train/loss': 0.13434047996997833, 'train/grad_norm_pre_clip': 4.655871391296387, 'timing/data': 0.00021845195442438126, 'timing/model': 0.4619376817718148, 'learning_rate/action_model': 7.454055236560668e-05, 'learning_rate/action_query_proj': 7.454055236560668e-05, 'learning_rate/base': 1.863513809140167e-05, 'epoch': 0.45}) +[2026-07-27 05:45:31,141][starVLA.training.train_starvla][INFO] - Step 3723, Loss: {'train/loss': 0.10946285724639893, 'train/grad_norm_pre_clip': 3.659105062484741, 'timing/data': 0.00017859973013401031, 'timing/model': 0.46491690538823605, 'learning_rate/action_model': 7.451392082320727e-05, 'learning_rate/action_query_proj': 7.451392082320727e-05, 'learning_rate/base': 1.8628480205801818e-05, 'epoch': 0.45}) +[2026-07-27 05:45:36,712][starVLA.training.train_starvla][INFO] - Step 3724, Loss: {'train/loss': 0.10539926588535309, 'train/grad_norm_pre_clip': 3.2116615772247314, 'timing/data': 0.0001797960139811039, 'timing/model': 0.46119238110259175, 'learning_rate/action_model': 7.44872803926685e-05, 'learning_rate/action_query_proj': 7.44872803926685e-05, 'learning_rate/base': 1.8621820098167124e-05, 'epoch': 0.45}) +[2026-07-27 05:45:42,287][starVLA.training.train_starvla][INFO] - Step 3725, Loss: {'train/loss': 0.017722588032484055, 'train/grad_norm_pre_clip': 1.2989212274551392, 'timing/data': 0.00019023986533284187, 'timing/model': 0.4651890969835222, 'learning_rate/action_model': 7.446063108450753e-05, 'learning_rate/action_query_proj': 7.446063108450753e-05, 'learning_rate/base': 1.8615157771126882e-05, 'epoch': 0.45}) +[2026-07-27 05:45:47,848][starVLA.training.train_starvla][INFO] - Step 3726, Loss: {'train/loss': 0.03218698874115944, 'train/grad_norm_pre_clip': 1.9207804203033447, 'timing/data': 0.00022839801385998726, 'timing/model': 0.4608146562241018, 'learning_rate/action_model': 7.443397290924513e-05, 'learning_rate/action_query_proj': 7.443397290924513e-05, 'learning_rate/base': 1.8608493227311284e-05, 'epoch': 0.45}) +[2026-07-27 05:45:53,419][starVLA.training.train_starvla][INFO] - Step 3727, Loss: {'train/loss': 0.03365892544388771, 'train/grad_norm_pre_clip': 1.8058217763900757, 'timing/data': 0.00017471611499786377, 'timing/model': 0.46563505521044135, 'learning_rate/action_model': 7.440730587740551e-05, 'learning_rate/action_query_proj': 7.440730587740551e-05, 'learning_rate/base': 1.8601826469351378e-05, 'epoch': 0.45}) +[2026-07-27 05:45:58,991][starVLA.training.train_starvla][INFO] - Step 3728, Loss: {'train/loss': 0.12249622493982315, 'train/grad_norm_pre_clip': 4.699121475219727, 'timing/data': 0.0001804279163479805, 'timing/model': 0.4636816601268947, 'learning_rate/action_model': 7.43806299995164e-05, 'learning_rate/action_query_proj': 7.43806299995164e-05, 'learning_rate/base': 1.85951574998791e-05, 'epoch': 0.45}) +[2026-07-27 05:46:04,637][starVLA.training.train_starvla][INFO] - Step 3729, Loss: {'train/loss': 0.22321507334709167, 'train/grad_norm_pre_clip': 5.817509651184082, 'timing/data': 0.00017417361959815025, 'timing/model': 0.46705825673416257, 'learning_rate/action_model': 7.435394528610899e-05, 'learning_rate/action_query_proj': 7.435394528610899e-05, 'learning_rate/base': 1.8588486321527247e-05, 'epoch': 0.45}) +[2026-07-27 05:46:10,233][starVLA.training.train_starvla][INFO] - Step 3730, Loss: {'train/loss': 0.11201655119657516, 'train/grad_norm_pre_clip': 3.3688881397247314, 'timing/data': 0.00017570797353982925, 'timing/model': 0.4637481588870287, 'learning_rate/action_model': 7.4327251747718e-05, 'learning_rate/action_query_proj': 7.4327251747718e-05, 'learning_rate/base': 1.85818129369295e-05, 'epoch': 0.45}) +[2026-07-27 05:46:15,819][starVLA.training.train_starvla][INFO] - Step 3731, Loss: {'train/loss': 0.04012855142354965, 'train/grad_norm_pre_clip': 2.0297298431396484, 'timing/data': 0.00017517060041427612, 'timing/model': 0.4592590699903667, 'learning_rate/action_model': 7.430054939488163e-05, 'learning_rate/action_query_proj': 7.430054939488163e-05, 'learning_rate/base': 1.8575137348720407e-05, 'epoch': 0.45}) +[2026-07-27 05:46:21,407][starVLA.training.train_starvla][INFO] - Step 3732, Loss: {'train/loss': 0.073331817984581, 'train/grad_norm_pre_clip': 2.6272668838500977, 'timing/data': 0.00018379930406808853, 'timing/model': 0.4657041085883975, 'learning_rate/action_model': 7.427383823814152e-05, 'learning_rate/action_query_proj': 7.427383823814152e-05, 'learning_rate/base': 1.856845955953538e-05, 'epoch': 0.45}) +[2026-07-27 05:46:27,001][starVLA.training.train_starvla][INFO] - Step 3733, Loss: {'train/loss': 0.04397905245423317, 'train/grad_norm_pre_clip': 2.026346445083618, 'timing/data': 0.00018047494813799858, 'timing/model': 0.4712021630257368, 'learning_rate/action_model': 7.424711828804282e-05, 'learning_rate/action_query_proj': 7.424711828804282e-05, 'learning_rate/base': 1.8561779572010706e-05, 'epoch': 0.45}) +[2026-07-27 05:46:32,607][starVLA.training.train_starvla][INFO] - Step 3734, Loss: {'train/loss': 0.12838688492774963, 'train/grad_norm_pre_clip': 4.537299633026123, 'timing/data': 0.00018134713172912598, 'timing/model': 0.4690420674160123, 'learning_rate/action_model': 7.422038955513417e-05, 'learning_rate/action_query_proj': 7.422038955513417e-05, 'learning_rate/base': 1.8555097388783542e-05, 'epoch': 0.45}) +[2026-07-27 05:46:38,230][starVLA.training.train_starvla][INFO] - Step 3735, Loss: {'train/loss': 0.047844626009464264, 'train/grad_norm_pre_clip': 2.5762360095977783, 'timing/data': 0.00021643983200192451, 'timing/model': 0.4689580388367176, 'learning_rate/action_model': 7.419365204996761e-05, 'learning_rate/action_query_proj': 7.419365204996761e-05, 'learning_rate/base': 1.8548413012491902e-05, 'epoch': 0.45}) +[2026-07-27 05:46:43,873][starVLA.training.train_starvla][INFO] - Step 3736, Loss: {'train/loss': 0.12065235525369644, 'train/grad_norm_pre_clip': 2.7985241413116455, 'timing/data': 0.00021321605890989304, 'timing/model': 0.4711993271484971, 'learning_rate/action_model': 7.416690578309871e-05, 'learning_rate/action_query_proj': 7.416690578309871e-05, 'learning_rate/base': 1.8541726445774677e-05, 'epoch': 0.45}) +[2026-07-27 05:46:49,496][starVLA.training.train_starvla][INFO] - Step 3737, Loss: {'train/loss': 0.060913849622011185, 'train/grad_norm_pre_clip': 3.2568211555480957, 'timing/data': 0.0001713489182293415, 'timing/model': 0.4689610479399562, 'learning_rate/action_model': 7.414015076508644e-05, 'learning_rate/action_query_proj': 7.414015076508644e-05, 'learning_rate/base': 1.853503769127161e-05, 'epoch': 0.45}) +[2026-07-27 05:46:55,123][starVLA.training.train_starvla][INFO] - Step 3738, Loss: {'train/loss': 0.07718800753355026, 'train/grad_norm_pre_clip': 3.503356456756592, 'timing/data': 0.00022392300888895988, 'timing/model': 0.46865108190104365, 'learning_rate/action_model': 7.41133870064933e-05, 'learning_rate/action_query_proj': 7.41133870064933e-05, 'learning_rate/base': 1.8528346751623325e-05, 'epoch': 0.45}) +[2026-07-27 05:47:00,740][starVLA.training.train_starvla][INFO] - Step 3739, Loss: {'train/loss': 0.0646347850561142, 'train/grad_norm_pre_clip': 1.9455453157424927, 'timing/data': 0.0002242252230644226, 'timing/model': 0.4764247159473598, 'learning_rate/action_model': 7.408661451788518e-05, 'learning_rate/action_query_proj': 7.408661451788518e-05, 'learning_rate/base': 1.8521653629471295e-05, 'epoch': 0.45}) +[2026-07-27 05:47:06,347][starVLA.training.train_starvla][INFO] - Step 3740, Loss: {'train/loss': 0.0764109343290329, 'train/grad_norm_pre_clip': 2.97261381149292, 'timing/data': 0.0002283407375216484, 'timing/model': 0.46764573315158486, 'learning_rate/action_model': 7.405983330983143e-05, 'learning_rate/action_query_proj': 7.405983330983143e-05, 'learning_rate/base': 1.851495832745786e-05, 'epoch': 0.45}) +[2026-07-27 05:47:12,029][starVLA.training.train_starvla][INFO] - Step 3741, Loss: {'train/loss': 0.08592357486486435, 'train/grad_norm_pre_clip': 3.1974217891693115, 'timing/data': 0.00018443213775753975, 'timing/model': 0.4701804472133517, 'learning_rate/action_model': 7.403304339290484e-05, 'learning_rate/action_query_proj': 7.403304339290484e-05, 'learning_rate/base': 1.850826084822621e-05, 'epoch': 0.45}) +[2026-07-27 05:47:17,704][starVLA.training.train_starvla][INFO] - Step 3742, Loss: {'train/loss': 0.07857771217823029, 'train/grad_norm_pre_clip': 3.744835138320923, 'timing/data': 0.00018603075295686722, 'timing/model': 0.4704764876514673, 'learning_rate/action_model': 7.400624477768167e-05, 'learning_rate/action_query_proj': 7.400624477768167e-05, 'learning_rate/base': 1.8501561194420417e-05, 'epoch': 0.45}) +[2026-07-27 05:47:23,350][starVLA.training.train_starvla][INFO] - Step 3743, Loss: {'train/loss': 0.018502499908208847, 'train/grad_norm_pre_clip': 1.5724191665649414, 'timing/data': 0.000218832865357399, 'timing/model': 0.4677320532500744, 'learning_rate/action_model': 7.397943747474155e-05, 'learning_rate/action_query_proj': 7.397943747474155e-05, 'learning_rate/base': 1.8494859368685387e-05, 'epoch': 0.45}) +[2026-07-27 05:47:29,010][starVLA.training.train_starvla][INFO] - Step 3744, Loss: {'train/loss': 0.06762073189020157, 'train/grad_norm_pre_clip': 2.934603214263916, 'timing/data': 0.00017502298578619957, 'timing/model': 0.46976538794115186, 'learning_rate/action_model': 7.395262149466762e-05, 'learning_rate/action_query_proj': 7.395262149466762e-05, 'learning_rate/base': 1.8488155373666905e-05, 'epoch': 0.45}) +[2026-07-27 05:47:34,674][starVLA.training.train_starvla][INFO] - Step 3745, Loss: {'train/loss': 0.08171350508928299, 'train/grad_norm_pre_clip': 2.5716254711151123, 'timing/data': 0.00017789797857403755, 'timing/model': 0.47076504677534103, 'learning_rate/action_model': 7.392579684804638e-05, 'learning_rate/action_query_proj': 7.392579684804638e-05, 'learning_rate/base': 1.8481449212011594e-05, 'epoch': 0.45}) +[2026-07-27 05:47:40,360][starVLA.training.train_starvla][INFO] - Step 3746, Loss: {'train/loss': 0.06330439448356628, 'train/grad_norm_pre_clip': 3.0372555255889893, 'timing/data': 0.00018069101497530937, 'timing/model': 0.4785344176925719, 'learning_rate/action_model': 7.389896354546778e-05, 'learning_rate/action_query_proj': 7.389896354546778e-05, 'learning_rate/base': 1.8474740886366945e-05, 'epoch': 0.45}) +[2026-07-27 05:47:46,137][starVLA.training.train_starvla][INFO] - Step 3747, Loss: {'train/loss': 0.09934354573488235, 'train/grad_norm_pre_clip': 3.030442953109741, 'timing/data': 0.00017731403931975365, 'timing/model': 0.47153980378061533, 'learning_rate/action_model': 7.38721215975252e-05, 'learning_rate/action_query_proj': 7.38721215975252e-05, 'learning_rate/base': 1.84680303993813e-05, 'epoch': 0.45}) +[2026-07-27 05:47:51,794][starVLA.training.train_starvla][INFO] - Step 3748, Loss: {'train/loss': 0.23530831933021545, 'train/grad_norm_pre_clip': 5.351259231567383, 'timing/data': 0.0002020290121436119, 'timing/model': 0.47021902399137616, 'learning_rate/action_model': 7.384527101481539e-05, 'learning_rate/action_query_proj': 7.384527101481539e-05, 'learning_rate/base': 1.8461317753703847e-05, 'epoch': 0.45}) +[2026-07-27 05:47:57,465][starVLA.training.train_starvla][INFO] - Step 3749, Loss: {'train/loss': 0.08131235092878342, 'train/grad_norm_pre_clip': 3.26019287109375, 'timing/data': 0.0001791170798242092, 'timing/model': 0.4704465437680483, 'learning_rate/action_model': 7.381841180793854e-05, 'learning_rate/action_query_proj': 7.381841180793854e-05, 'learning_rate/base': 1.8454602951984636e-05, 'epoch': 0.45}) +[2026-07-27 05:48:03,103][starVLA.training.train_starvla][INFO] - Step 3750, Loss: {'train/loss': 0.04458585008978844, 'train/grad_norm_pre_clip': 1.9798239469528198, 'timing/data': 0.00019478006288409233, 'timing/model': 0.4687208761461079, 'learning_rate/action_model': 7.379154398749825e-05, 'learning_rate/action_query_proj': 7.379154398749825e-05, 'learning_rate/base': 1.8447885996874562e-05, 'epoch': 0.45}) +[2026-07-27 05:48:08,706][starVLA.training.train_starvla][INFO] - Step 3751, Loss: {'train/loss': 0.08522306382656097, 'train/grad_norm_pre_clip': 3.841320753097534, 'timing/data': 0.00017242785543203354, 'timing/model': 0.46982633508741856, 'learning_rate/action_model': 7.37646675641015e-05, 'learning_rate/action_query_proj': 7.37646675641015e-05, 'learning_rate/base': 1.8441166891025375e-05, 'epoch': 0.46}) +[2026-07-27 05:48:14,316][starVLA.training.train_starvla][INFO] - Step 3752, Loss: {'train/loss': 0.10464078187942505, 'train/grad_norm_pre_clip': 3.1600515842437744, 'timing/data': 0.00017607491463422775, 'timing/model': 0.4702949011698365, 'learning_rate/action_model': 7.37377825483587e-05, 'learning_rate/action_query_proj': 7.37377825483587e-05, 'learning_rate/base': 1.8434445637089676e-05, 'epoch': 0.46}) +[2026-07-27 05:48:19,926][starVLA.training.train_starvla][INFO] - Step 3753, Loss: {'train/loss': 0.0700707659125328, 'train/grad_norm_pre_clip': 2.873368978500366, 'timing/data': 0.00017193099483847618, 'timing/model': 0.47045506024733186, 'learning_rate/action_model': 7.371088895088359e-05, 'learning_rate/action_query_proj': 7.371088895088359e-05, 'learning_rate/base': 1.8427722237720898e-05, 'epoch': 0.46}) +[2026-07-27 05:48:25,526][starVLA.training.train_starvla][INFO] - Step 3754, Loss: {'train/loss': 0.07263460755348206, 'train/grad_norm_pre_clip': 2.896481513977051, 'timing/data': 0.00022181589156389236, 'timing/model': 0.46710180304944515, 'learning_rate/action_model': 7.368398678229336e-05, 'learning_rate/action_query_proj': 7.368398678229336e-05, 'learning_rate/base': 1.842099669557334e-05, 'epoch': 0.46}) +[2026-07-27 05:48:31,107][starVLA.training.train_starvla][INFO] - Step 3755, Loss: {'train/loss': 0.18504220247268677, 'train/grad_norm_pre_clip': 5.558029651641846, 'timing/data': 0.0001737009733915329, 'timing/model': 0.4683105400763452, 'learning_rate/action_model': 7.365707605320857e-05, 'learning_rate/action_query_proj': 7.365707605320857e-05, 'learning_rate/base': 1.8414269013302144e-05, 'epoch': 0.46}) +[2026-07-27 05:48:36,698][starVLA.training.train_starvla][INFO] - Step 3756, Loss: {'train/loss': 0.0792483240365982, 'train/grad_norm_pre_clip': 3.2100772857666016, 'timing/data': 0.00018521491438150406, 'timing/model': 0.4693230432458222, 'learning_rate/action_model': 7.363015677425312e-05, 'learning_rate/action_query_proj': 7.363015677425312e-05, 'learning_rate/base': 1.840753919356328e-05, 'epoch': 0.46}) +[2026-07-27 05:48:42,374][starVLA.training.train_starvla][INFO] - Step 3757, Loss: {'train/loss': 0.09753917157649994, 'train/grad_norm_pre_clip': 3.317474126815796, 'timing/data': 0.0001757708378136158, 'timing/model': 0.4699344630353153, 'learning_rate/action_model': 7.360322895605434e-05, 'learning_rate/action_query_proj': 7.360322895605434e-05, 'learning_rate/base': 1.8400807239013586e-05, 'epoch': 0.46}) +[2026-07-27 05:48:47,971][starVLA.training.train_starvla][INFO] - Step 3758, Loss: {'train/loss': 0.1786104291677475, 'train/grad_norm_pre_clip': 3.684190511703491, 'timing/data': 0.00017361389473080635, 'timing/model': 0.4681208860129118, 'learning_rate/action_model': 7.357629260924291e-05, 'learning_rate/action_query_proj': 7.357629260924291e-05, 'learning_rate/base': 1.8394073152310727e-05, 'epoch': 0.46}) +[2026-07-27 05:48:53,584][starVLA.training.train_starvla][INFO] - Step 3759, Loss: {'train/loss': 0.1506175696849823, 'train/grad_norm_pre_clip': 4.339900493621826, 'timing/data': 0.00018109101802110672, 'timing/model': 0.47334389481693506, 'learning_rate/action_model': 7.354934774445285e-05, 'learning_rate/action_query_proj': 7.354934774445285e-05, 'learning_rate/base': 1.838733693611321e-05, 'epoch': 0.46}) +[2026-07-27 05:48:59,193][starVLA.training.train_starvla][INFO] - Step 3760, Loss: {'train/loss': 0.07043907791376114, 'train/grad_norm_pre_clip': 2.882495641708374, 'timing/data': 0.00017189374193549156, 'timing/model': 0.4688400262966752, 'learning_rate/action_model': 7.352239437232156e-05, 'learning_rate/action_query_proj': 7.352239437232156e-05, 'learning_rate/base': 1.838059859308039e-05, 'epoch': 0.46}) +[2026-07-27 05:49:04,829][starVLA.training.train_starvla][INFO] - Step 3761, Loss: {'train/loss': 0.17159472405910492, 'train/grad_norm_pre_clip': 4.112499237060547, 'timing/data': 0.00017452193424105644, 'timing/model': 0.4704748662188649, 'learning_rate/action_model': 7.349543250348984e-05, 'learning_rate/action_query_proj': 7.349543250348984e-05, 'learning_rate/base': 1.837385812587246e-05, 'epoch': 0.46}) +[2026-07-27 05:49:10,431][starVLA.training.train_starvla][INFO] - Step 3762, Loss: {'train/loss': 0.052786678075790405, 'train/grad_norm_pre_clip': 1.9132920503616333, 'timing/data': 0.00017266999930143356, 'timing/model': 0.4716257289983332, 'learning_rate/action_model': 7.346846214860179e-05, 'learning_rate/action_query_proj': 7.346846214860179e-05, 'learning_rate/base': 1.8367115537150446e-05, 'epoch': 0.46}) +[2026-07-27 05:49:16,053][starVLA.training.train_starvla][INFO] - Step 3763, Loss: {'train/loss': 0.08754989504814148, 'train/grad_norm_pre_clip': 3.3822412490844727, 'timing/data': 0.00017443625256419182, 'timing/model': 0.474646236281842, 'learning_rate/action_model': 7.344148331830484e-05, 'learning_rate/action_query_proj': 7.344148331830484e-05, 'learning_rate/base': 1.836037082957621e-05, 'epoch': 0.46}) +[2026-07-27 05:49:21,658][starVLA.training.train_starvla][INFO] - Step 3764, Loss: {'train/loss': 0.03313085436820984, 'train/grad_norm_pre_clip': 2.1698853969573975, 'timing/data': 0.00017777271568775177, 'timing/model': 0.47033431800082326, 'learning_rate/action_model': 7.341449602324988e-05, 'learning_rate/action_query_proj': 7.341449602324988e-05, 'learning_rate/base': 1.835362400581247e-05, 'epoch': 0.46}) +[2026-07-27 05:49:27,278][starVLA.training.train_starvla][INFO] - Step 3765, Loss: {'train/loss': 0.08719252049922943, 'train/grad_norm_pre_clip': 3.5203857421875, 'timing/data': 0.00017369166016578674, 'timing/model': 0.4768026270903647, 'learning_rate/action_model': 7.338750027409104e-05, 'learning_rate/action_query_proj': 7.338750027409104e-05, 'learning_rate/base': 1.834687506852276e-05, 'epoch': 0.46}) +[2026-07-27 05:49:32,881][starVLA.training.train_starvla][INFO] - Step 3766, Loss: {'train/loss': 0.03391328826546669, 'train/grad_norm_pre_clip': 1.9527171850204468, 'timing/data': 0.0001778099685907364, 'timing/model': 0.4687289325520396, 'learning_rate/action_model': 7.336049608148577e-05, 'learning_rate/action_query_proj': 7.336049608148577e-05, 'learning_rate/base': 1.8340124020371444e-05, 'epoch': 0.46}) +[2026-07-27 05:49:38,466][starVLA.training.train_starvla][INFO] - Step 3767, Loss: {'train/loss': 0.07935308665037155, 'train/grad_norm_pre_clip': 3.0163917541503906, 'timing/data': 0.00017286697402596474, 'timing/model': 0.47546112909913063, 'learning_rate/action_model': 7.333348345609497e-05, 'learning_rate/action_query_proj': 7.333348345609497e-05, 'learning_rate/base': 1.833337086402374e-05, 'epoch': 0.46}) +[2026-07-27 05:49:44,058][starVLA.training.train_starvla][INFO] - Step 3768, Loss: {'train/loss': 0.17422249913215637, 'train/grad_norm_pre_clip': 3.960845470428467, 'timing/data': 0.00017880229279398918, 'timing/model': 0.47070844983682036, 'learning_rate/action_model': 7.330646240858272e-05, 'learning_rate/action_query_proj': 7.330646240858272e-05, 'learning_rate/base': 1.832661560214568e-05, 'epoch': 0.46}) +[2026-07-27 05:49:49,663][starVLA.training.train_starvla][INFO] - Step 3769, Loss: {'train/loss': 0.048065200448036194, 'train/grad_norm_pre_clip': 2.812934160232544, 'timing/data': 0.00017804978415369987, 'timing/model': 0.4689406673423946, 'learning_rate/action_model': 7.327943294961656e-05, 'learning_rate/action_query_proj': 7.327943294961656e-05, 'learning_rate/base': 1.831985823740414e-05, 'epoch': 0.46}) +[2026-07-27 05:49:55,291][starVLA.training.train_starvla][INFO] - Step 3770, Loss: {'train/loss': 0.12151789665222168, 'train/grad_norm_pre_clip': 3.9277424812316895, 'timing/data': 0.00018260767683386803, 'timing/model': 0.47047888627275825, 'learning_rate/action_model': 7.325239508986729e-05, 'learning_rate/action_query_proj': 7.325239508986729e-05, 'learning_rate/base': 1.831309877246682e-05, 'epoch': 0.46}) +[2026-07-27 05:50:00,866][starVLA.training.train_starvla][INFO] - Step 3771, Loss: {'train/loss': 0.08644578605890274, 'train/grad_norm_pre_clip': 3.769883871078491, 'timing/data': 0.00017341924831271172, 'timing/model': 0.4780440889298916, 'learning_rate/action_model': 7.3225348840009e-05, 'learning_rate/action_query_proj': 7.3225348840009e-05, 'learning_rate/base': 1.830633721000225e-05, 'epoch': 0.46}) +[2026-07-27 05:50:06,462][starVLA.training.train_starvla][INFO] - Step 3772, Loss: {'train/loss': 0.08614180237054825, 'train/grad_norm_pre_clip': 3.2041921615600586, 'timing/data': 0.00017208699136972427, 'timing/model': 0.4676675219088793, 'learning_rate/action_model': 7.319829421071911e-05, 'learning_rate/action_query_proj': 7.319829421071911e-05, 'learning_rate/base': 1.829957355267978e-05, 'epoch': 0.46}) +[2026-07-27 05:50:12,071][starVLA.training.train_starvla][INFO] - Step 3773, Loss: {'train/loss': 0.09864334017038345, 'train/grad_norm_pre_clip': 2.3132987022399902, 'timing/data': 0.0001821191981434822, 'timing/model': 0.47463224921375513, 'learning_rate/action_model': 7.317123121267839e-05, 'learning_rate/action_query_proj': 7.317123121267839e-05, 'learning_rate/base': 1.8292807803169598e-05, 'epoch': 0.46}) +[2026-07-27 05:50:17,679][starVLA.training.train_starvla][INFO] - Step 3774, Loss: {'train/loss': 0.1842595636844635, 'train/grad_norm_pre_clip': 4.848535537719727, 'timing/data': 0.0001735929399728775, 'timing/model': 0.4705291911959648, 'learning_rate/action_model': 7.31441598565709e-05, 'learning_rate/action_query_proj': 7.31441598565709e-05, 'learning_rate/base': 1.8286039964142724e-05, 'epoch': 0.46}) +[2026-07-27 05:50:23,268][starVLA.training.train_starvla][INFO] - Step 3775, Loss: {'train/loss': 0.08040572702884674, 'train/grad_norm_pre_clip': 3.2524781227111816, 'timing/data': 0.0001936103217303753, 'timing/model': 0.4674118421971798, 'learning_rate/action_model': 7.311708015308394e-05, 'learning_rate/action_query_proj': 7.311708015308394e-05, 'learning_rate/base': 1.8279270038270986e-05, 'epoch': 0.46}) +[2026-07-27 05:50:28,883][starVLA.training.train_starvla][INFO] - Step 3776, Loss: {'train/loss': 0.04152357578277588, 'train/grad_norm_pre_clip': 2.172441005706787, 'timing/data': 0.000179933849722147, 'timing/model': 0.4679909930564463, 'learning_rate/action_model': 7.308999211290816e-05, 'learning_rate/action_query_proj': 7.308999211290816e-05, 'learning_rate/base': 1.827249802822704e-05, 'epoch': 0.46}) +[2026-07-27 05:50:34,477][starVLA.training.train_starvla][INFO] - Step 3777, Loss: {'train/loss': 0.04722575098276138, 'train/grad_norm_pre_clip': 2.7939131259918213, 'timing/data': 0.00017616385594010353, 'timing/model': 0.4614259828813374, 'learning_rate/action_model': 7.30628957467375e-05, 'learning_rate/action_query_proj': 7.30628957467375e-05, 'learning_rate/base': 1.8265723936684375e-05, 'epoch': 0.46}) +[2026-07-27 05:50:40,064][starVLA.training.train_starvla][INFO] - Step 3778, Loss: {'train/loss': 0.02609383873641491, 'train/grad_norm_pre_clip': 1.1260502338409424, 'timing/data': 0.00017582997679710388, 'timing/model': 0.4659011662006378, 'learning_rate/action_model': 7.303579106526917e-05, 'learning_rate/action_query_proj': 7.303579106526917e-05, 'learning_rate/base': 1.825894776631729e-05, 'epoch': 0.46}) +[2026-07-27 05:50:45,627][starVLA.training.train_starvla][INFO] - Step 3779, Loss: {'train/loss': 0.07623986899852753, 'train/grad_norm_pre_clip': 2.103153944015503, 'timing/data': 0.00019547110423445702, 'timing/model': 0.46248508198186755, 'learning_rate/action_model': 7.300867807920368e-05, 'learning_rate/action_query_proj': 7.300867807920368e-05, 'learning_rate/base': 1.825216951980092e-05, 'epoch': 0.46}) +[2026-07-27 05:50:51,478][starVLA.training.train_starvla][INFO] - Step 3780, Loss: {'train/loss': 0.028695182874798775, 'train/grad_norm_pre_clip': 1.5402476787567139, 'timing/data': 0.0001833043061196804, 'timing/model': 0.46029680175706744, 'learning_rate/action_model': 7.298155679924478e-05, 'learning_rate/action_query_proj': 7.298155679924478e-05, 'learning_rate/base': 1.8245389199811196e-05, 'epoch': 0.46}) +[2026-07-27 05:50:57,078][starVLA.training.train_starvla][INFO] - Step 3781, Loss: {'train/loss': 0.19675089418888092, 'train/grad_norm_pre_clip': 3.581012010574341, 'timing/data': 0.0002974509261548519, 'timing/model': 0.46184301981702447, 'learning_rate/action_model': 7.295442723609956e-05, 'learning_rate/action_query_proj': 7.295442723609956e-05, 'learning_rate/base': 1.823860680902489e-05, 'epoch': 0.46}) +[2026-07-27 05:51:02,696][starVLA.training.train_starvla][INFO] - Step 3782, Loss: {'train/loss': 0.11349984258413315, 'train/grad_norm_pre_clip': 3.7981534004211426, 'timing/data': 0.00022609997540712357, 'timing/model': 0.4608781011775136, 'learning_rate/action_model': 7.292728940047831e-05, 'learning_rate/action_query_proj': 7.292728940047831e-05, 'learning_rate/base': 1.823182235011958e-05, 'epoch': 0.46}) +[2026-07-27 05:51:08,302][starVLA.training.train_starvla][INFO] - Step 3783, Loss: {'train/loss': 0.20165744423866272, 'train/grad_norm_pre_clip': 4.258862495422363, 'timing/data': 0.00018350593745708466, 'timing/model': 0.4603141560219228, 'learning_rate/action_model': 7.290014330309462e-05, 'learning_rate/action_query_proj': 7.290014330309462e-05, 'learning_rate/base': 1.8225035825773655e-05, 'epoch': 0.46}) +[2026-07-27 05:51:13,914][starVLA.training.train_starvla][INFO] - Step 3784, Loss: {'train/loss': 0.2423885464668274, 'train/grad_norm_pre_clip': 4.842271327972412, 'timing/data': 0.00017400365322828293, 'timing/model': 0.46062630135565996, 'learning_rate/action_model': 7.287298895466535e-05, 'learning_rate/action_query_proj': 7.287298895466535e-05, 'learning_rate/base': 1.821824723866634e-05, 'epoch': 0.46}) +[2026-07-27 05:51:19,537][starVLA.training.train_starvla][INFO] - Step 3785, Loss: {'train/loss': 0.03812400624155998, 'train/grad_norm_pre_clip': 2.470416784286499, 'timing/data': 0.00019123731181025505, 'timing/model': 0.4711866728030145, 'learning_rate/action_model': 7.284582636591063e-05, 'learning_rate/action_query_proj': 7.284582636591063e-05, 'learning_rate/base': 1.821145659147766e-05, 'epoch': 0.46}) +[2026-07-27 05:51:25,154][starVLA.training.train_starvla][INFO] - Step 3786, Loss: {'train/loss': 0.05978351831436157, 'train/grad_norm_pre_clip': 3.2928342819213867, 'timing/data': 0.00017629284411668777, 'timing/model': 0.4605624908581376, 'learning_rate/action_model': 7.281865554755377e-05, 'learning_rate/action_query_proj': 7.281865554755377e-05, 'learning_rate/base': 1.8204663886888444e-05, 'epoch': 0.46}) +[2026-07-27 05:51:30,758][starVLA.training.train_starvla][INFO] - Step 3787, Loss: {'train/loss': 0.0378916934132576, 'train/grad_norm_pre_clip': 2.301992416381836, 'timing/data': 0.00018111569806933403, 'timing/model': 0.4581138202920556, 'learning_rate/action_model': 7.279147651032141e-05, 'learning_rate/action_query_proj': 7.279147651032141e-05, 'learning_rate/base': 1.8197869127580352e-05, 'epoch': 0.46}) +[2026-07-27 05:51:36,581][starVLA.training.train_starvla][INFO] - Step 3788, Loss: {'train/loss': 0.06982074677944183, 'train/grad_norm_pre_clip': 3.358739137649536, 'timing/data': 0.00017153704538941383, 'timing/model': 0.46441484708338976, 'learning_rate/action_model': 7.27642892649434e-05, 'learning_rate/action_query_proj': 7.27642892649434e-05, 'learning_rate/base': 1.819107231623585e-05, 'epoch': 0.46}) +[2026-07-27 05:51:42,194][starVLA.training.train_starvla][INFO] - Step 3789, Loss: {'train/loss': 0.07646428793668747, 'train/grad_norm_pre_clip': 2.9287168979644775, 'timing/data': 0.0002429676242172718, 'timing/model': 0.46244101878255606, 'learning_rate/action_model': 7.273709382215284e-05, 'learning_rate/action_query_proj': 7.273709382215284e-05, 'learning_rate/base': 1.818427345553821e-05, 'epoch': 0.46}) +[2026-07-27 05:51:47,816][starVLA.training.train_starvla][INFO] - Step 3790, Loss: {'train/loss': 0.05777460336685181, 'train/grad_norm_pre_clip': 2.529541254043579, 'timing/data': 0.00021097110584378242, 'timing/model': 0.4640978849492967, 'learning_rate/action_model': 7.270989019268604e-05, 'learning_rate/action_query_proj': 7.270989019268604e-05, 'learning_rate/base': 1.817747254817151e-05, 'epoch': 0.46}) +[2026-07-27 05:51:53,435][starVLA.training.train_starvla][INFO] - Step 3791, Loss: {'train/loss': 0.09251922369003296, 'train/grad_norm_pre_clip': 3.314297676086426, 'timing/data': 0.00017281295731663704, 'timing/model': 0.4639920019544661, 'learning_rate/action_model': 7.268267838728257e-05, 'learning_rate/action_query_proj': 7.268267838728257e-05, 'learning_rate/base': 1.8170669596820642e-05, 'epoch': 0.46}) +[2026-07-27 05:51:59,047][starVLA.training.train_starvla][INFO] - Step 3792, Loss: {'train/loss': 0.1542118638753891, 'train/grad_norm_pre_clip': 4.250973701477051, 'timing/data': 0.00018120277673006058, 'timing/model': 0.4567907461896539, 'learning_rate/action_model': 7.265545841668523e-05, 'learning_rate/action_query_proj': 7.265545841668523e-05, 'learning_rate/base': 1.8163864604171307e-05, 'epoch': 0.46}) +[2026-07-27 05:52:04,643][starVLA.training.train_starvla][INFO] - Step 3793, Loss: {'train/loss': 0.08537714183330536, 'train/grad_norm_pre_clip': 2.7858238220214844, 'timing/data': 0.00017662113532423973, 'timing/model': 0.46097684698179364, 'learning_rate/action_model': 7.262823029164003e-05, 'learning_rate/action_query_proj': 7.262823029164003e-05, 'learning_rate/base': 1.8157057572910007e-05, 'epoch': 0.46}) +[2026-07-27 05:52:10,228][starVLA.training.train_starvla][INFO] - Step 3794, Loss: {'train/loss': 0.13034412264823914, 'train/grad_norm_pre_clip': 4.724633693695068, 'timing/data': 0.00017939507961273193, 'timing/model': 0.45848551113158464, 'learning_rate/action_model': 7.260099402289618e-05, 'learning_rate/action_query_proj': 7.260099402289618e-05, 'learning_rate/base': 1.8150248505724046e-05, 'epoch': 0.46}) +[2026-07-27 05:52:15,822][starVLA.training.train_starvla][INFO] - Step 3795, Loss: {'train/loss': 0.05040421336889267, 'train/grad_norm_pre_clip': 2.1139233112335205, 'timing/data': 0.0001724548637866974, 'timing/model': 0.465555002912879, 'learning_rate/action_model': 7.257374962120617e-05, 'learning_rate/action_query_proj': 7.257374962120617e-05, 'learning_rate/base': 1.8143437405301543e-05, 'epoch': 0.46}) +[2026-07-27 05:52:21,428][starVLA.training.train_starvla][INFO] - Step 3796, Loss: {'train/loss': 0.12676562368869781, 'train/grad_norm_pre_clip': 3.482969045639038, 'timing/data': 0.00017845816910266876, 'timing/model': 0.46956079034134746, 'learning_rate/action_model': 7.25464970973256e-05, 'learning_rate/action_query_proj': 7.25464970973256e-05, 'learning_rate/base': 1.81366242743314e-05, 'epoch': 0.46}) +[2026-07-27 05:52:27,057][starVLA.training.train_starvla][INFO] - Step 3797, Loss: {'train/loss': 0.11239489912986755, 'train/grad_norm_pre_clip': 3.510619878768921, 'timing/data': 0.00017609726637601852, 'timing/model': 0.4682618291117251, 'learning_rate/action_model': 7.251923646201341e-05, 'learning_rate/action_query_proj': 7.251923646201341e-05, 'learning_rate/base': 1.8129809115503352e-05, 'epoch': 0.46}) +[2026-07-27 05:52:32,679][starVLA.training.train_starvla][INFO] - Step 3798, Loss: {'train/loss': 0.10150725394487381, 'train/grad_norm_pre_clip': 3.1097683906555176, 'timing/data': 0.00017125718295574188, 'timing/model': 0.4677712367847562, 'learning_rate/action_model': 7.249196772603161e-05, 'learning_rate/action_query_proj': 7.249196772603161e-05, 'learning_rate/base': 1.8122991931507903e-05, 'epoch': 0.46}) +[2026-07-27 05:52:38,325][starVLA.training.train_starvla][INFO] - Step 3799, Loss: {'train/loss': 0.22153764963150024, 'train/grad_norm_pre_clip': 4.334367752075195, 'timing/data': 0.00017384998500347137, 'timing/model': 0.46973617281764746, 'learning_rate/action_model': 7.246469090014549e-05, 'learning_rate/action_query_proj': 7.246469090014549e-05, 'learning_rate/base': 1.8116172725036372e-05, 'epoch': 0.46}) +[2026-07-27 05:52:43,982][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 3800 +[2026-07-27 05:52:43,983][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 3800 +[2026-07-27 05:52:43,984][starVLA.training.train_starvla][INFO] - Step 3800, Loss: {'train/loss': 0.09676916152238846, 'train/grad_norm_pre_clip': 3.0286004543304443, 'timing/data': 0.00017425883561372757, 'timing/model': 0.4672836409881711, 'learning_rate/action_model': 7.243740599512349e-05, 'learning_rate/action_query_proj': 7.243740599512349e-05, 'learning_rate/base': 1.8109351498780873e-05, 'epoch': 0.46}) +[2026-07-27 05:52:49,629][starVLA.training.train_starvla][INFO] - Step 3801, Loss: {'train/loss': 0.02305968850851059, 'train/grad_norm_pre_clip': 1.4384047985076904, 'timing/data': 0.00018201908096671104, 'timing/model': 0.4699048101902008, 'learning_rate/action_model': 7.241011302173728e-05, 'learning_rate/action_query_proj': 7.241011302173728e-05, 'learning_rate/base': 1.810252825543432e-05, 'epoch': 0.46}) +[2026-07-27 05:52:55,277][starVLA.training.train_starvla][INFO] - Step 3802, Loss: {'train/loss': 0.043684396892786026, 'train/grad_norm_pre_clip': 2.5463080406188965, 'timing/data': 0.00018666498363018036, 'timing/model': 0.46991920890286565, 'learning_rate/action_model': 7.238281199076167e-05, 'learning_rate/action_query_proj': 7.238281199076167e-05, 'learning_rate/base': 1.8095702997690417e-05, 'epoch': 0.46}) +[2026-07-27 05:53:00,942][starVLA.training.train_starvla][INFO] - Step 3803, Loss: {'train/loss': 0.11871541291475296, 'train/grad_norm_pre_clip': 3.0863776206970215, 'timing/data': 0.00017651217058300972, 'timing/model': 0.47677714098244905, 'learning_rate/action_model': 7.235550291297469e-05, 'learning_rate/action_query_proj': 7.235550291297469e-05, 'learning_rate/base': 1.808887572824367e-05, 'epoch': 0.46}) +[2026-07-27 05:53:06,559][starVLA.training.train_starvla][INFO] - Step 3804, Loss: {'train/loss': 0.04363706707954407, 'train/grad_norm_pre_clip': 1.7868664264678955, 'timing/data': 0.00018395297229290009, 'timing/model': 0.47545181727036834, 'learning_rate/action_model': 7.232818579915753e-05, 'learning_rate/action_query_proj': 7.232818579915753e-05, 'learning_rate/base': 1.8082046449789382e-05, 'epoch': 0.46}) +[2026-07-27 05:53:12,175][starVLA.training.train_starvla][INFO] - Step 3805, Loss: {'train/loss': 0.03533373400568962, 'train/grad_norm_pre_clip': 1.972672700881958, 'timing/data': 0.0001756981946527958, 'timing/model': 0.4685407350771129, 'learning_rate/action_model': 7.230086066009455e-05, 'learning_rate/action_query_proj': 7.230086066009455e-05, 'learning_rate/base': 1.8075215165023638e-05, 'epoch': 0.46}) +[2026-07-27 05:53:17,893][starVLA.training.train_starvla][INFO] - Step 3806, Loss: {'train/loss': 0.1402757465839386, 'train/grad_norm_pre_clip': 4.272590637207031, 'timing/data': 0.0001728762872517109, 'timing/model': 0.4748589526861906, 'learning_rate/action_model': 7.22735275065733e-05, 'learning_rate/action_query_proj': 7.22735275065733e-05, 'learning_rate/base': 1.8068381876643324e-05, 'epoch': 0.46}) +[2026-07-27 05:53:23,522][starVLA.training.train_starvla][INFO] - Step 3807, Loss: {'train/loss': 0.04698249697685242, 'train/grad_norm_pre_clip': 2.344337224960327, 'timing/data': 0.00017427606508135796, 'timing/model': 0.4761276519857347, 'learning_rate/action_model': 7.224618634938446e-05, 'learning_rate/action_query_proj': 7.224618634938446e-05, 'learning_rate/base': 1.8061546587346116e-05, 'epoch': 0.46}) +[2026-07-27 05:53:29,135][starVLA.training.train_starvla][INFO] - Step 3808, Loss: {'train/loss': 0.12065485119819641, 'train/grad_norm_pre_clip': 4.526392459869385, 'timing/data': 0.00017670588567852974, 'timing/model': 0.47039434779435396, 'learning_rate/action_model': 7.221883719932189e-05, 'learning_rate/action_query_proj': 7.221883719932189e-05, 'learning_rate/base': 1.8054709299830473e-05, 'epoch': 0.46}) +[2026-07-27 05:53:34,749][starVLA.training.train_starvla][INFO] - Step 3809, Loss: {'train/loss': 0.022641044110059738, 'train/grad_norm_pre_clip': 1.1053516864776611, 'timing/data': 0.0001877318136394024, 'timing/model': 0.4740038029849529, 'learning_rate/action_model': 7.219148006718257e-05, 'learning_rate/action_query_proj': 7.219148006718257e-05, 'learning_rate/base': 1.8047870016795642e-05, 'epoch': 0.46}) +[2026-07-27 05:53:40,357][starVLA.training.train_starvla][INFO] - Step 3810, Loss: {'train/loss': 0.06025104969739914, 'train/grad_norm_pre_clip': 2.608816385269165, 'timing/data': 0.00018621934577822685, 'timing/model': 0.4688863009214401, 'learning_rate/action_model': 7.216411496376672e-05, 'learning_rate/action_query_proj': 7.216411496376672e-05, 'learning_rate/base': 1.804102874094168e-05, 'epoch': 0.46}) +[2026-07-27 05:53:45,957][starVLA.training.train_starvla][INFO] - Step 3811, Loss: {'train/loss': 0.21604669094085693, 'train/grad_norm_pre_clip': 5.082304954528809, 'timing/data': 0.0001722089946269989, 'timing/model': 0.47080788714811206, 'learning_rate/action_model': 7.21367418998776e-05, 'learning_rate/action_query_proj': 7.21367418998776e-05, 'learning_rate/base': 1.80341854749694e-05, 'epoch': 0.46}) +[2026-07-27 05:53:51,568][starVLA.training.train_starvla][INFO] - Step 3812, Loss: {'train/loss': 0.061964429914951324, 'train/grad_norm_pre_clip': 2.5476956367492676, 'timing/data': 0.00017022807151079178, 'timing/model': 0.4688276541419327, 'learning_rate/action_model': 7.210936088632169e-05, 'learning_rate/action_query_proj': 7.210936088632169e-05, 'learning_rate/base': 1.8027340221580423e-05, 'epoch': 0.46}) +[2026-07-27 05:53:57,176][starVLA.training.train_starvla][INFO] - Step 3813, Loss: {'train/loss': 0.03136582672595978, 'train/grad_norm_pre_clip': 1.6944659948349, 'timing/data': 0.00017730286344885826, 'timing/model': 0.46715793013572693, 'learning_rate/action_model': 7.208197193390858e-05, 'learning_rate/action_query_proj': 7.208197193390858e-05, 'learning_rate/base': 1.8020492983477144e-05, 'epoch': 0.46}) +[2026-07-27 05:54:02,808][starVLA.training.train_starvla][INFO] - Step 3814, Loss: {'train/loss': 0.10446321219205856, 'train/grad_norm_pre_clip': 3.2756738662719727, 'timing/data': 0.00018305378034710884, 'timing/model': 0.46971492609009147, 'learning_rate/action_model': 7.205457505345097e-05, 'learning_rate/action_query_proj': 7.205457505345097e-05, 'learning_rate/base': 1.8013643763362742e-05, 'epoch': 0.46}) +[2026-07-27 05:54:08,401][starVLA.training.train_starvla][INFO] - Step 3815, Loss: {'train/loss': 0.035763513296842575, 'train/grad_norm_pre_clip': 2.2024223804473877, 'timing/data': 0.00017427001148462296, 'timing/model': 0.4695423641242087, 'learning_rate/action_model': 7.202717025576475e-05, 'learning_rate/action_query_proj': 7.202717025576475e-05, 'learning_rate/base': 1.8006792563941187e-05, 'epoch': 0.46}) +[2026-07-27 05:54:14,006][starVLA.training.train_starvla][INFO] - Step 3816, Loss: {'train/loss': 0.04674564301967621, 'train/grad_norm_pre_clip': 2.391554117202759, 'timing/data': 0.00017296895384788513, 'timing/model': 0.4768119570799172, 'learning_rate/action_model': 7.199975755166887e-05, 'learning_rate/action_query_proj': 7.199975755166887e-05, 'learning_rate/base': 1.7999939387917217e-05, 'epoch': 0.46}) +[2026-07-27 05:54:19,613][starVLA.training.train_starvla][INFO] - Step 3817, Loss: {'train/loss': 0.12626191973686218, 'train/grad_norm_pre_clip': 4.2415547370910645, 'timing/data': 0.00018585985526442528, 'timing/model': 0.4749151929281652, 'learning_rate/action_model': 7.197233695198545e-05, 'learning_rate/action_query_proj': 7.197233695198545e-05, 'learning_rate/base': 1.799308423799636e-05, 'epoch': 0.46}) +[2026-07-27 05:54:25,227][starVLA.training.train_starvla][INFO] - Step 3818, Loss: {'train/loss': 0.053634777665138245, 'train/grad_norm_pre_clip': 2.4130842685699463, 'timing/data': 0.00017620855942368507, 'timing/model': 0.4754092418588698, 'learning_rate/action_model': 7.19449084675397e-05, 'learning_rate/action_query_proj': 7.19449084675397e-05, 'learning_rate/base': 1.7986227116884924e-05, 'epoch': 0.46}) +[2026-07-27 05:54:30,845][starVLA.training.train_starvla][INFO] - Step 3819, Loss: {'train/loss': 0.1541903167963028, 'train/grad_norm_pre_clip': 5.039374828338623, 'timing/data': 0.00017244787886738777, 'timing/model': 0.4760976489633322, 'learning_rate/action_model': 7.191747210915995e-05, 'learning_rate/action_query_proj': 7.191747210915995e-05, 'learning_rate/base': 1.7979368027289987e-05, 'epoch': 0.46}) +[2026-07-27 05:54:36,449][starVLA.training.train_starvla][INFO] - Step 3820, Loss: {'train/loss': 0.0697048157453537, 'train/grad_norm_pre_clip': 3.141681671142578, 'timing/data': 0.00017956411466002464, 'timing/model': 0.4695662991143763, 'learning_rate/action_model': 7.189002788767765e-05, 'learning_rate/action_query_proj': 7.189002788767765e-05, 'learning_rate/base': 1.797250697191941e-05, 'epoch': 0.46}) +[2026-07-27 05:54:42,255][starVLA.training.train_starvla][INFO] - Step 3821, Loss: {'train/loss': 0.19160504639148712, 'train/grad_norm_pre_clip': 3.8751068115234375, 'timing/data': 0.00017630495131015778, 'timing/model': 0.4760839231312275, 'learning_rate/action_model': 7.186257581392733e-05, 'learning_rate/action_query_proj': 7.186257581392733e-05, 'learning_rate/base': 1.796564395348183e-05, 'epoch': 0.46}) +[2026-07-27 05:54:47,866][starVLA.training.train_starvla][INFO] - Step 3822, Loss: {'train/loss': 0.022476177662611008, 'train/grad_norm_pre_clip': 1.7009649276733398, 'timing/data': 0.0001825275830924511, 'timing/model': 0.4697608188726008, 'learning_rate/action_model': 7.183511589874665e-05, 'learning_rate/action_query_proj': 7.183511589874665e-05, 'learning_rate/base': 1.7958778974686662e-05, 'epoch': 0.46}) +[2026-07-27 05:54:53,462][starVLA.training.train_starvla][INFO] - Step 3823, Loss: {'train/loss': 0.1544719934463501, 'train/grad_norm_pre_clip': 4.303313255310059, 'timing/data': 0.0001760539598762989, 'timing/model': 0.46923498436808586, 'learning_rate/action_model': 7.180764815297633e-05, 'learning_rate/action_query_proj': 7.180764815297633e-05, 'learning_rate/base': 1.7951912038244083e-05, 'epoch': 0.46}) +[2026-07-27 05:54:59,088][starVLA.training.train_starvla][INFO] - Step 3824, Loss: {'train/loss': 0.061094433069229126, 'train/grad_norm_pre_clip': 3.5247435569763184, 'timing/data': 0.00017983978614211082, 'timing/model': 0.4763708356767893, 'learning_rate/action_model': 7.178017258746021e-05, 'learning_rate/action_query_proj': 7.178017258746021e-05, 'learning_rate/base': 1.7945043146865053e-05, 'epoch': 0.46}) +[2026-07-27 05:55:04,671][starVLA.training.train_starvla][INFO] - Step 3825, Loss: {'train/loss': 0.18165118992328644, 'train/grad_norm_pre_clip': 5.145875930786133, 'timing/data': 0.00018418626859784126, 'timing/model': 0.4703475311398506, 'learning_rate/action_model': 7.175268921304524e-05, 'learning_rate/action_query_proj': 7.175268921304524e-05, 'learning_rate/base': 1.793817230326131e-05, 'epoch': 0.46}) +[2026-07-27 05:55:10,279][starVLA.training.train_starvla][INFO] - Step 3826, Loss: {'train/loss': 0.10085092484951019, 'train/grad_norm_pre_clip': 4.0865044593811035, 'timing/data': 0.00017422670498490334, 'timing/model': 0.46941112726926804, 'learning_rate/action_model': 7.172519804058135e-05, 'learning_rate/action_query_proj': 7.172519804058135e-05, 'learning_rate/base': 1.7931299510145338e-05, 'epoch': 0.46}) +[2026-07-27 05:55:15,864][starVLA.training.train_starvla][INFO] - Step 3827, Loss: {'train/loss': 0.044069331139326096, 'train/grad_norm_pre_clip': 2.1773102283477783, 'timing/data': 0.00017559481784701347, 'timing/model': 0.4703610222786665, 'learning_rate/action_model': 7.169769908092169e-05, 'learning_rate/action_query_proj': 7.169769908092169e-05, 'learning_rate/base': 1.7924424770230423e-05, 'epoch': 0.46}) +[2026-07-27 05:55:21,468][starVLA.training.train_starvla][INFO] - Step 3828, Loss: {'train/loss': 0.07369964569807053, 'train/grad_norm_pre_clip': 3.5205631256103516, 'timing/data': 0.000176337081938982, 'timing/model': 0.4712954889982939, 'learning_rate/action_model': 7.167019234492238e-05, 'learning_rate/action_query_proj': 7.167019234492238e-05, 'learning_rate/base': 1.7917548086230594e-05, 'epoch': 0.46}) +[2026-07-27 05:55:27,060][starVLA.training.train_starvla][INFO] - Step 3829, Loss: {'train/loss': 0.10948404669761658, 'train/grad_norm_pre_clip': 3.743108034133911, 'timing/data': 0.00018250104039907455, 'timing/model': 0.47063265601173043, 'learning_rate/action_model': 7.164267784344263e-05, 'learning_rate/action_query_proj': 7.164267784344263e-05, 'learning_rate/base': 1.791066946086066e-05, 'epoch': 0.46}) +[2026-07-27 05:55:32,657][starVLA.training.train_starvla][INFO] - Step 3830, Loss: {'train/loss': 0.10341691970825195, 'train/grad_norm_pre_clip': 4.026771545410156, 'timing/data': 0.00017735594883561134, 'timing/model': 0.4680083617568016, 'learning_rate/action_model': 7.161515558734476e-05, 'learning_rate/action_query_proj': 7.161515558734476e-05, 'learning_rate/base': 1.790378889683619e-05, 'epoch': 0.46}) +[2026-07-27 05:55:38,263][starVLA.training.train_starvla][INFO] - Step 3831, Loss: {'train/loss': 0.1220303475856781, 'train/grad_norm_pre_clip': 3.8110079765319824, 'timing/data': 0.00017035892233252525, 'timing/model': 0.4685992803424597, 'learning_rate/action_model': 7.15876255874941e-05, 'learning_rate/action_query_proj': 7.15876255874941e-05, 'learning_rate/base': 1.7896906396873524e-05, 'epoch': 0.46}) +[2026-07-27 05:55:43,888][starVLA.training.train_starvla][INFO] - Step 3832, Loss: {'train/loss': 0.020849362015724182, 'train/grad_norm_pre_clip': 1.8733757734298706, 'timing/data': 0.00017485721036791801, 'timing/model': 0.4684269423596561, 'learning_rate/action_model': 7.156008785475907e-05, 'learning_rate/action_query_proj': 7.156008785475907e-05, 'learning_rate/base': 1.7890021963689768e-05, 'epoch': 0.46}) +[2026-07-27 05:55:49,489][starVLA.training.train_starvla][INFO] - Step 3833, Loss: {'train/loss': 0.08828408271074295, 'train/grad_norm_pre_clip': 3.286583185195923, 'timing/data': 0.0002090870402753353, 'timing/model': 0.46929064812138677, 'learning_rate/action_model': 7.153254240001116e-05, 'learning_rate/action_query_proj': 7.153254240001116e-05, 'learning_rate/base': 1.788313560000279e-05, 'epoch': 0.46}) +[2026-07-27 05:55:55,097][starVLA.training.train_starvla][INFO] - Step 3834, Loss: {'train/loss': 0.060926489531993866, 'train/grad_norm_pre_clip': 2.9028398990631104, 'timing/data': 0.00017900997772812843, 'timing/model': 0.4640394551679492, 'learning_rate/action_model': 7.150498923412479e-05, 'learning_rate/action_query_proj': 7.150498923412479e-05, 'learning_rate/base': 1.7876247308531197e-05, 'epoch': 0.47}) +[2026-07-27 05:56:00,699][starVLA.training.train_starvla][INFO] - Step 3835, Loss: {'train/loss': 0.12076783925294876, 'train/grad_norm_pre_clip': 5.154008388519287, 'timing/data': 0.0001804279163479805, 'timing/model': 0.4579099197871983, 'learning_rate/action_model': 7.14774283679776e-05, 'learning_rate/action_query_proj': 7.14774283679776e-05, 'learning_rate/base': 1.78693570919944e-05, 'epoch': 0.47}) +[2026-07-27 05:56:06,332][starVLA.training.train_starvla][INFO] - Step 3836, Loss: {'train/loss': 0.043353255838155746, 'train/grad_norm_pre_clip': 2.4670963287353516, 'timing/data': 0.00018362700939178467, 'timing/model': 0.4727395437657833, 'learning_rate/action_model': 7.144985981245015e-05, 'learning_rate/action_query_proj': 7.144985981245015e-05, 'learning_rate/base': 1.7862464953112537e-05, 'epoch': 0.47}) +[2026-07-27 05:56:11,945][starVLA.training.train_starvla][INFO] - Step 3837, Loss: {'train/loss': 0.055152151733636856, 'train/grad_norm_pre_clip': 3.2457592487335205, 'timing/data': 0.00017453497275710106, 'timing/model': 0.4687148779630661, 'learning_rate/action_model': 7.142228357842608e-05, 'learning_rate/action_query_proj': 7.142228357842608e-05, 'learning_rate/base': 1.785557089460652e-05, 'epoch': 0.47}) +[2026-07-27 05:56:17,562][starVLA.training.train_starvla][INFO] - Step 3838, Loss: {'train/loss': 0.08766844868659973, 'train/grad_norm_pre_clip': 2.748756170272827, 'timing/data': 0.00017965491861104965, 'timing/model': 0.46599493315443397, 'learning_rate/action_model': 7.139469967679204e-05, 'learning_rate/action_query_proj': 7.139469967679204e-05, 'learning_rate/base': 1.784867491919801e-05, 'epoch': 0.47}) +[2026-07-27 05:56:23,389][starVLA.training.train_starvla][INFO] - Step 3839, Loss: {'train/loss': 0.07276361435651779, 'train/grad_norm_pre_clip': 3.029446840286255, 'timing/data': 0.00017569633200764656, 'timing/model': 0.4574858001433313, 'learning_rate/action_model': 7.13671081184377e-05, 'learning_rate/action_query_proj': 7.13671081184377e-05, 'learning_rate/base': 1.7841777029609425e-05, 'epoch': 0.47}) +[2026-07-27 05:56:29,221][starVLA.training.train_starvla][INFO] - Step 3840, Loss: {'train/loss': 0.03238053619861603, 'train/grad_norm_pre_clip': 1.7251168489456177, 'timing/data': 0.00017603766173124313, 'timing/model': 0.4671696168370545, 'learning_rate/action_model': 7.133950891425582e-05, 'learning_rate/action_query_proj': 7.133950891425582e-05, 'learning_rate/base': 1.7834877228563955e-05, 'epoch': 0.47}) +[2026-07-27 05:56:34,827][starVLA.training.train_starvla][INFO] - Step 3841, Loss: {'train/loss': 0.05370357260107994, 'train/grad_norm_pre_clip': 2.605055093765259, 'timing/data': 0.00018441211432218552, 'timing/model': 0.45743991108611226, 'learning_rate/action_model': 7.131190207514206e-05, 'learning_rate/action_query_proj': 7.131190207514206e-05, 'learning_rate/base': 1.7827975518785516e-05, 'epoch': 0.47}) +[2026-07-27 05:56:40,423][starVLA.training.train_starvla][INFO] - Step 3842, Loss: {'train/loss': 0.10207200050354004, 'train/grad_norm_pre_clip': 3.594350576400757, 'timing/data': 0.00018543517217040062, 'timing/model': 0.46133661130443215, 'learning_rate/action_model': 7.128428761199523e-05, 'learning_rate/action_query_proj': 7.128428761199523e-05, 'learning_rate/base': 1.7821071902998808e-05, 'epoch': 0.47}) +[2026-07-27 05:56:46,034][starVLA.training.train_starvla][INFO] - Step 3843, Loss: {'train/loss': 0.09913063049316406, 'train/grad_norm_pre_clip': 3.1145007610321045, 'timing/data': 0.0001688459888100624, 'timing/model': 0.4570276807062328, 'learning_rate/action_model': 7.125666553571707e-05, 'learning_rate/action_query_proj': 7.125666553571707e-05, 'learning_rate/base': 1.7814166383929267e-05, 'epoch': 0.47}) +[2026-07-27 05:56:51,871][starVLA.training.train_starvla][INFO] - Step 3844, Loss: {'train/loss': 0.07913185656070709, 'train/grad_norm_pre_clip': 3.4227609634399414, 'timing/data': 0.0001661139540374279, 'timing/model': 0.4701073067262769, 'learning_rate/action_model': 7.12290358572123e-05, 'learning_rate/action_query_proj': 7.12290358572123e-05, 'learning_rate/base': 1.7807258964303076e-05, 'epoch': 0.47}) +[2026-07-27 05:56:57,502][starVLA.training.train_starvla][INFO] - Step 3845, Loss: {'train/loss': 0.059498634189367294, 'train/grad_norm_pre_clip': 1.7645584344863892, 'timing/data': 0.00017125345766544342, 'timing/model': 0.46938801323994994, 'learning_rate/action_model': 7.12013985873887e-05, 'learning_rate/action_query_proj': 7.12013985873887e-05, 'learning_rate/base': 1.7800349646847176e-05, 'epoch': 0.47}) +[2026-07-27 05:57:03,146][starVLA.training.train_starvla][INFO] - Step 3846, Loss: {'train/loss': 0.029552727937698364, 'train/grad_norm_pre_clip': 1.9541606903076172, 'timing/data': 0.00017387885600328445, 'timing/model': 0.47641931381076574, 'learning_rate/action_model': 7.117375373715704e-05, 'learning_rate/action_query_proj': 7.117375373715704e-05, 'learning_rate/base': 1.779343843428926e-05, 'epoch': 0.47}) +[2026-07-27 05:57:08,774][starVLA.training.train_starvla][INFO] - Step 3847, Loss: {'train/loss': 0.19834856688976288, 'train/grad_norm_pre_clip': 4.732357501983643, 'timing/data': 0.00017523718997836113, 'timing/model': 0.4773658229969442, 'learning_rate/action_model': 7.114610131743106e-05, 'learning_rate/action_query_proj': 7.114610131743106e-05, 'learning_rate/base': 1.7786525329357765e-05, 'epoch': 0.47}) +[2026-07-27 05:57:14,392][starVLA.training.train_starvla][INFO] - Step 3848, Loss: {'train/loss': 0.17042601108551025, 'train/grad_norm_pre_clip': 3.561063528060913, 'timing/data': 0.00018944963812828064, 'timing/model': 0.46175964595749974, 'learning_rate/action_model': 7.111844133912751e-05, 'learning_rate/action_query_proj': 7.111844133912751e-05, 'learning_rate/base': 1.7779610334781877e-05, 'epoch': 0.47}) +[2026-07-27 05:57:20,002][starVLA.training.train_starvla][INFO] - Step 3849, Loss: {'train/loss': 0.06071852520108223, 'train/grad_norm_pre_clip': 3.109225034713745, 'timing/data': 0.00017033005133271217, 'timing/model': 0.466071052942425, 'learning_rate/action_model': 7.109077381316606e-05, 'learning_rate/action_query_proj': 7.109077381316606e-05, 'learning_rate/base': 1.7772693453291516e-05, 'epoch': 0.47}) +[2026-07-27 05:57:25,605][starVLA.training.train_starvla][INFO] - Step 3850, Loss: {'train/loss': 0.03805733844637871, 'train/grad_norm_pre_clip': 1.890393614768982, 'timing/data': 0.00018238462507724762, 'timing/model': 0.4623551480472088, 'learning_rate/action_model': 7.106309875046947e-05, 'learning_rate/action_query_proj': 7.106309875046947e-05, 'learning_rate/base': 1.7765774687617366e-05, 'epoch': 0.47}) +[2026-07-27 05:57:31,198][starVLA.training.train_starvla][INFO] - Step 3851, Loss: {'train/loss': 0.13615798950195312, 'train/grad_norm_pre_clip': 2.0990445613861084, 'timing/data': 0.0002267090603709221, 'timing/model': 0.4645910141989589, 'learning_rate/action_model': 7.10354161619634e-05, 'learning_rate/action_query_proj': 7.10354161619634e-05, 'learning_rate/base': 1.775885404049085e-05, 'epoch': 0.47}) +[2026-07-27 05:57:36,795][starVLA.training.train_starvla][INFO] - Step 3852, Loss: {'train/loss': 0.052804023027420044, 'train/grad_norm_pre_clip': 2.8768351078033447, 'timing/data': 0.0002313060685992241, 'timing/model': 0.463120327796787, 'learning_rate/action_model': 7.100772605857648e-05, 'learning_rate/action_query_proj': 7.100772605857648e-05, 'learning_rate/base': 1.775193151464412e-05, 'epoch': 0.47}) +[2026-07-27 05:57:42,617][starVLA.training.train_starvla][INFO] - Step 3853, Loss: {'train/loss': 0.057560570538043976, 'train/grad_norm_pre_clip': 3.1720688343048096, 'timing/data': 0.00017026998102664948, 'timing/model': 0.4619048200547695, 'learning_rate/action_model': 7.098002845124033e-05, 'learning_rate/action_query_proj': 7.098002845124033e-05, 'learning_rate/base': 1.7745007112810084e-05, 'epoch': 0.47}) +[2026-07-27 05:57:48,217][starVLA.training.train_starvla][INFO] - Step 3854, Loss: {'train/loss': 0.07001547515392303, 'train/grad_norm_pre_clip': 3.0211353302001953, 'timing/data': 0.00017655780538916588, 'timing/model': 0.46587092662230134, 'learning_rate/action_model': 7.095232335088956e-05, 'learning_rate/action_query_proj': 7.095232335088956e-05, 'learning_rate/base': 1.773808083772239e-05, 'epoch': 0.47}) +[2026-07-27 05:57:53,789][starVLA.training.train_starvla][INFO] - Step 3855, Loss: {'train/loss': 0.06960231810808182, 'train/grad_norm_pre_clip': 3.042205333709717, 'timing/data': 0.00017014890909194946, 'timing/model': 0.45739521691575646, 'learning_rate/action_model': 7.092461076846166e-05, 'learning_rate/action_query_proj': 7.092461076846166e-05, 'learning_rate/base': 1.7731152692115415e-05, 'epoch': 0.47}) +[2026-07-27 05:57:59,365][starVLA.training.train_starvla][INFO] - Step 3856, Loss: {'train/loss': 0.14617982506752014, 'train/grad_norm_pre_clip': 4.558994770050049, 'timing/data': 0.00017370004206895828, 'timing/model': 0.46457683108747005, 'learning_rate/action_model': 7.089689071489714e-05, 'learning_rate/action_query_proj': 7.089689071489714e-05, 'learning_rate/base': 1.7724222678724284e-05, 'epoch': 0.47}) +[2026-07-27 05:58:05,007][starVLA.training.train_starvla][INFO] - Step 3857, Loss: {'train/loss': 0.13014261424541473, 'train/grad_norm_pre_clip': 4.133610248565674, 'timing/data': 0.00018841726705431938, 'timing/model': 0.4661378809250891, 'learning_rate/action_model': 7.086916320113943e-05, 'learning_rate/action_query_proj': 7.086916320113943e-05, 'learning_rate/base': 1.7717290800284857e-05, 'epoch': 0.47}) +[2026-07-27 05:58:10,615][starVLA.training.train_starvla][INFO] - Step 3858, Loss: {'train/loss': 0.07319226115942001, 'train/grad_norm_pre_clip': 3.6043877601623535, 'timing/data': 0.0001699649728834629, 'timing/model': 0.46425010496750474, 'learning_rate/action_model': 7.084142823813492e-05, 'learning_rate/action_query_proj': 7.084142823813492e-05, 'learning_rate/base': 1.771035705953373e-05, 'epoch': 0.47}) +[2026-07-27 05:58:16,200][starVLA.training.train_starvla][INFO] - Step 3859, Loss: {'train/loss': 0.05819622799754143, 'train/grad_norm_pre_clip': 2.405719518661499, 'timing/data': 0.00021360814571380615, 'timing/model': 0.45497862389311194, 'learning_rate/action_model': 7.081368583683292e-05, 'learning_rate/action_query_proj': 7.081368583683292e-05, 'learning_rate/base': 1.770342145920823e-05, 'epoch': 0.47}) +[2026-07-27 05:58:21,820][starVLA.training.train_starvla][INFO] - Step 3860, Loss: {'train/loss': 0.08443452417850494, 'train/grad_norm_pre_clip': 3.5724096298217773, 'timing/data': 0.00018906733021140099, 'timing/model': 0.4645469612441957, 'learning_rate/action_model': 7.078593600818572e-05, 'learning_rate/action_query_proj': 7.078593600818572e-05, 'learning_rate/base': 1.769648400204643e-05, 'epoch': 0.47}) +[2026-07-27 05:58:27,423][starVLA.training.train_starvla][INFO] - Step 3861, Loss: {'train/loss': 0.11063700169324875, 'train/grad_norm_pre_clip': 3.0091211795806885, 'timing/data': 0.00017627188935875893, 'timing/model': 0.4560029208660126, 'learning_rate/action_model': 7.075817876314849e-05, 'learning_rate/action_query_proj': 7.075817876314849e-05, 'learning_rate/base': 1.7689544690787123e-05, 'epoch': 0.47}) +[2026-07-27 05:58:33,042][starVLA.training.train_starvla][INFO] - Step 3862, Loss: {'train/loss': 0.06917443126440048, 'train/grad_norm_pre_clip': 3.050689697265625, 'timing/data': 0.0002221362665295601, 'timing/model': 0.4637777619063854, 'learning_rate/action_model': 7.073041411267935e-05, 'learning_rate/action_query_proj': 7.073041411267935e-05, 'learning_rate/base': 1.7682603528169838e-05, 'epoch': 0.47}) +[2026-07-27 05:58:38,668][starVLA.training.train_starvla][INFO] - Step 3863, Loss: {'train/loss': 0.07903248816728592, 'train/grad_norm_pre_clip': 3.7321250438690186, 'timing/data': 0.00017972290515899658, 'timing/model': 0.45988434879109263, 'learning_rate/action_model': 7.070264206773938e-05, 'learning_rate/action_query_proj': 7.070264206773938e-05, 'learning_rate/base': 1.7675660516934844e-05, 'epoch': 0.47}) +[2026-07-27 05:58:44,282][starVLA.training.train_starvla][INFO] - Step 3864, Loss: {'train/loss': 0.08333107084035873, 'train/grad_norm_pre_clip': 2.92114520072937, 'timing/data': 0.00017509795725345612, 'timing/model': 0.4627783508040011, 'learning_rate/action_model': 7.067486263929249e-05, 'learning_rate/action_query_proj': 7.067486263929249e-05, 'learning_rate/base': 1.766871565982312e-05, 'epoch': 0.47}) +[2026-07-27 05:58:49,893][starVLA.training.train_starvla][INFO] - Step 3865, Loss: {'train/loss': 0.0539168119430542, 'train/grad_norm_pre_clip': 2.5946044921875, 'timing/data': 0.0001760050654411316, 'timing/model': 0.4638835908845067, 'learning_rate/action_model': 7.064707583830558e-05, 'learning_rate/action_query_proj': 7.064707583830558e-05, 'learning_rate/base': 1.7661768959576396e-05, 'epoch': 0.47}) +[2026-07-27 05:58:55,502][starVLA.training.train_starvla][INFO] - Step 3866, Loss: {'train/loss': 0.09737826883792877, 'train/grad_norm_pre_clip': 3.282991886138916, 'timing/data': 0.00017525115981698036, 'timing/model': 0.46134966472163796, 'learning_rate/action_model': 7.061928167574846e-05, 'learning_rate/action_query_proj': 7.061928167574846e-05, 'learning_rate/base': 1.7654820418937116e-05, 'epoch': 0.47}) +[2026-07-27 05:59:01,113][starVLA.training.train_starvla][INFO] - Step 3867, Loss: {'train/loss': 0.08342631906270981, 'train/grad_norm_pre_clip': 2.8638765811920166, 'timing/data': 0.00018286192789673805, 'timing/model': 0.46015950897708535, 'learning_rate/action_model': 7.059148016259378e-05, 'learning_rate/action_query_proj': 7.059148016259378e-05, 'learning_rate/base': 1.7647870040648446e-05, 'epoch': 0.47}) +[2026-07-27 05:59:06,730][starVLA.training.train_starvla][INFO] - Step 3868, Loss: {'train/loss': 0.0694519504904747, 'train/grad_norm_pre_clip': 3.318798065185547, 'timing/data': 0.00018342584371566772, 'timing/model': 0.46561460103839636, 'learning_rate/action_model': 7.056367130981718e-05, 'learning_rate/action_query_proj': 7.056367130981718e-05, 'learning_rate/base': 1.7640917827454295e-05, 'epoch': 0.47}) +[2026-07-27 05:59:12,326][starVLA.training.train_starvla][INFO] - Step 3869, Loss: {'train/loss': 0.14355142414569855, 'train/grad_norm_pre_clip': 3.5515952110290527, 'timing/data': 0.0001710723154246807, 'timing/model': 0.46046460373327136, 'learning_rate/action_model': 7.053585512839713e-05, 'learning_rate/action_query_proj': 7.053585512839713e-05, 'learning_rate/base': 1.7633963782099283e-05, 'epoch': 0.47}) +[2026-07-27 05:59:17,931][starVLA.training.train_starvla][INFO] - Step 3870, Loss: {'train/loss': 0.12091819196939468, 'train/grad_norm_pre_clip': 4.153090000152588, 'timing/data': 0.0001698690466582775, 'timing/model': 0.463972105178982, 'learning_rate/action_model': 7.050803162931504e-05, 'learning_rate/action_query_proj': 7.050803162931504e-05, 'learning_rate/base': 1.762700790732876e-05, 'epoch': 0.47}) +[2026-07-27 05:59:23,538][starVLA.training.train_starvla][INFO] - Step 3871, Loss: {'train/loss': 0.17195141315460205, 'train/grad_norm_pre_clip': 4.542648792266846, 'timing/data': 0.00018848199397325516, 'timing/model': 0.46230419632047415, 'learning_rate/action_model': 7.048020082355518e-05, 'learning_rate/action_query_proj': 7.048020082355518e-05, 'learning_rate/base': 1.7620050205888794e-05, 'epoch': 0.47}) +[2026-07-27 05:59:29,207][starVLA.training.train_starvla][INFO] - Step 3872, Loss: {'train/loss': 0.09457430988550186, 'train/grad_norm_pre_clip': 4.362171173095703, 'timing/data': 0.00017020804807543755, 'timing/model': 0.46493590623140335, 'learning_rate/action_model': 7.045236272210468e-05, 'learning_rate/action_query_proj': 7.045236272210468e-05, 'learning_rate/base': 1.761309068052617e-05, 'epoch': 0.47}) +[2026-07-27 05:59:34,863][starVLA.training.train_starvla][INFO] - Step 3873, Loss: {'train/loss': 0.09961985051631927, 'train/grad_norm_pre_clip': 3.109952688217163, 'timing/data': 0.00017105694860219955, 'timing/model': 0.45736209861934185, 'learning_rate/action_model': 7.042451733595362e-05, 'learning_rate/action_query_proj': 7.042451733595362e-05, 'learning_rate/base': 1.7606129333988405e-05, 'epoch': 0.47}) +[2026-07-27 05:59:40,480][starVLA.training.train_starvla][INFO] - Step 3874, Loss: {'train/loss': 0.08098212629556656, 'train/grad_norm_pre_clip': 3.3059520721435547, 'timing/data': 0.00017346534878015518, 'timing/model': 0.46171890292316675, 'learning_rate/action_model': 7.039666467609489e-05, 'learning_rate/action_query_proj': 7.039666467609489e-05, 'learning_rate/base': 1.7599166169023723e-05, 'epoch': 0.47}) +[2026-07-27 05:59:46,089][starVLA.training.train_starvla][INFO] - Step 3875, Loss: {'train/loss': 0.07619549334049225, 'train/grad_norm_pre_clip': 2.732268810272217, 'timing/data': 0.0001761498861014843, 'timing/model': 0.46064483001828194, 'learning_rate/action_model': 7.036880475352432e-05, 'learning_rate/action_query_proj': 7.036880475352432e-05, 'learning_rate/base': 1.759220118838108e-05, 'epoch': 0.47}) +[2026-07-27 05:59:51,713][starVLA.training.train_starvla][INFO] - Step 3876, Loss: {'train/loss': 0.06156955286860466, 'train/grad_norm_pre_clip': 3.0215296745300293, 'timing/data': 0.00019473116844892502, 'timing/model': 0.4612338859587908, 'learning_rate/action_model': 7.034093757924052e-05, 'learning_rate/action_query_proj': 7.034093757924052e-05, 'learning_rate/base': 1.758523439481013e-05, 'epoch': 0.47}) +[2026-07-27 05:59:57,393][starVLA.training.train_starvla][INFO] - Step 3877, Loss: {'train/loss': 0.03768544644117355, 'train/grad_norm_pre_clip': 2.0108511447906494, 'timing/data': 0.00017826305702328682, 'timing/model': 0.4676117040216923, 'learning_rate/action_model': 7.031306316424504e-05, 'learning_rate/action_query_proj': 7.031306316424504e-05, 'learning_rate/base': 1.757826579106126e-05, 'epoch': 0.47}) +[2026-07-27 06:00:03,256][starVLA.training.train_starvla][INFO] - Step 3878, Loss: {'train/loss': 0.15315455198287964, 'train/grad_norm_pre_clip': 4.3667826652526855, 'timing/data': 0.00017529120668768883, 'timing/model': 0.46482320595532656, 'learning_rate/action_model': 7.028518151954222e-05, 'learning_rate/action_query_proj': 7.028518151954222e-05, 'learning_rate/base': 1.7571295379885554e-05, 'epoch': 0.47}) +[2026-07-27 06:00:08,852][starVLA.training.train_starvla][INFO] - Step 3879, Loss: {'train/loss': 0.16949860751628876, 'train/grad_norm_pre_clip': 5.88962459564209, 'timing/data': 0.00017431098967790604, 'timing/model': 0.46202087216079235, 'learning_rate/action_model': 7.025729265613934e-05, 'learning_rate/action_query_proj': 7.025729265613934e-05, 'learning_rate/base': 1.7564323164034835e-05, 'epoch': 0.47}) +[2026-07-27 06:00:14,475][starVLA.training.train_starvla][INFO] - Step 3880, Loss: {'train/loss': 0.06012330949306488, 'train/grad_norm_pre_clip': 2.3377156257629395, 'timing/data': 0.0001730513758957386, 'timing/model': 0.460326069034636, 'learning_rate/action_model': 7.022939658504645e-05, 'learning_rate/action_query_proj': 7.022939658504645e-05, 'learning_rate/base': 1.7557349146261614e-05, 'epoch': 0.47}) +[2026-07-27 06:00:20,084][starVLA.training.train_starvla][INFO] - Step 3881, Loss: {'train/loss': 0.05902675539255142, 'train/grad_norm_pre_clip': 2.4281506538391113, 'timing/data': 0.0001819320023059845, 'timing/model': 0.46535342698916793, 'learning_rate/action_model': 7.02014933172765e-05, 'learning_rate/action_query_proj': 7.02014933172765e-05, 'learning_rate/base': 1.7550373329319125e-05, 'epoch': 0.47}) +[2026-07-27 06:00:25,694][starVLA.training.train_starvla][INFO] - Step 3882, Loss: {'train/loss': 0.1607702374458313, 'train/grad_norm_pre_clip': 3.5415797233581543, 'timing/data': 0.00018430082127451897, 'timing/model': 0.46354264905676246, 'learning_rate/action_model': 7.017358286384524e-05, 'learning_rate/action_query_proj': 7.017358286384524e-05, 'learning_rate/base': 1.754339571596131e-05, 'epoch': 0.47}) +[2026-07-27 06:00:31,302][starVLA.training.train_starvla][INFO] - Step 3883, Loss: {'train/loss': 0.09037519991397858, 'train/grad_norm_pre_clip': 4.865150451660156, 'timing/data': 0.00017469516023993492, 'timing/model': 0.46554302610456944, 'learning_rate/action_model': 7.014566523577127e-05, 'learning_rate/action_query_proj': 7.014566523577127e-05, 'learning_rate/base': 1.7536416308942817e-05, 'epoch': 0.47}) +[2026-07-27 06:00:36,916][starVLA.training.train_starvla][INFO] - Step 3884, Loss: {'train/loss': 0.1739199161529541, 'train/grad_norm_pre_clip': 6.106669902801514, 'timing/data': 0.0001782318577170372, 'timing/model': 0.46628467785194516, 'learning_rate/action_model': 7.011774044407603e-05, 'learning_rate/action_query_proj': 7.011774044407603e-05, 'learning_rate/base': 1.7529435111019007e-05, 'epoch': 0.47}) +[2026-07-27 06:00:42,505][starVLA.training.train_starvla][INFO] - Step 3885, Loss: {'train/loss': 0.08786113560199738, 'train/grad_norm_pre_clip': 3.724494218826294, 'timing/data': 0.00017295032739639282, 'timing/model': 0.45609991904348135, 'learning_rate/action_model': 7.008980849978382e-05, 'learning_rate/action_query_proj': 7.008980849978382e-05, 'learning_rate/base': 1.7522452124945954e-05, 'epoch': 0.47}) +[2026-07-27 06:00:48,098][starVLA.training.train_starvla][INFO] - Step 3886, Loss: {'train/loss': 0.11742226034402847, 'train/grad_norm_pre_clip': 3.4469239711761475, 'timing/data': 0.00017461832612752914, 'timing/model': 0.464812271296978, 'learning_rate/action_model': 7.006186941392168e-05, 'learning_rate/action_query_proj': 7.006186941392168e-05, 'learning_rate/base': 1.751546735348042e-05, 'epoch': 0.47}) +[2026-07-27 06:00:53,718][starVLA.training.train_starvla][INFO] - Step 3887, Loss: {'train/loss': 0.06317699700593948, 'train/grad_norm_pre_clip': 2.707125663757324, 'timing/data': 0.00017878226935863495, 'timing/model': 0.46179627208039165, 'learning_rate/action_model': 7.003392319751954e-05, 'learning_rate/action_query_proj': 7.003392319751954e-05, 'learning_rate/base': 1.7508480799379885e-05, 'epoch': 0.47}) +[2026-07-27 06:00:59,367][starVLA.training.train_starvla][INFO] - Step 3888, Loss: {'train/loss': 0.14406156539916992, 'train/grad_norm_pre_clip': 4.462434768676758, 'timing/data': 0.00018906686455011368, 'timing/model': 0.4639302436262369, 'learning_rate/action_model': 7.000596986161014e-05, 'learning_rate/action_query_proj': 7.000596986161014e-05, 'learning_rate/base': 1.7501492465402534e-05, 'epoch': 0.47}) +[2026-07-27 06:01:05,056][starVLA.training.train_starvla][INFO] - Step 3889, Loss: {'train/loss': 0.10511821508407593, 'train/grad_norm_pre_clip': 4.3209123611450195, 'timing/data': 0.00017870217561721802, 'timing/model': 0.4624879229813814, 'learning_rate/action_model': 6.997800941722899e-05, 'learning_rate/action_query_proj': 6.997800941722899e-05, 'learning_rate/base': 1.7494502354307247e-05, 'epoch': 0.47}) +[2026-07-27 06:01:10,720][starVLA.training.train_starvla][INFO] - Step 3890, Loss: {'train/loss': 0.08545949310064316, 'train/grad_norm_pre_clip': 2.4570705890655518, 'timing/data': 0.00017190398648381233, 'timing/model': 0.4605874139815569, 'learning_rate/action_model': 6.995004187541442e-05, 'learning_rate/action_query_proj': 6.995004187541442e-05, 'learning_rate/base': 1.7487510468853606e-05, 'epoch': 0.47}) +[2026-07-27 06:01:16,379][starVLA.training.train_starvla][INFO] - Step 3891, Loss: {'train/loss': 0.14019563794136047, 'train/grad_norm_pre_clip': 4.233628749847412, 'timing/data': 0.00017386581748723984, 'timing/model': 0.46467009326443076, 'learning_rate/action_model': 6.992206724720761e-05, 'learning_rate/action_query_proj': 6.992206724720761e-05, 'learning_rate/base': 1.7480516811801903e-05, 'epoch': 0.47}) +[2026-07-27 06:01:22,027][starVLA.training.train_starvla][INFO] - Step 3892, Loss: {'train/loss': 0.06553147733211517, 'train/grad_norm_pre_clip': 3.3070061206817627, 'timing/data': 0.0001736227422952652, 'timing/model': 0.4603705839253962, 'learning_rate/action_model': 6.989408554365249e-05, 'learning_rate/action_query_proj': 6.989408554365249e-05, 'learning_rate/base': 1.7473521385913122e-05, 'epoch': 0.47}) +[2026-07-27 06:01:27,678][starVLA.training.train_starvla][INFO] - Step 3893, Loss: {'train/loss': 0.06380918622016907, 'train/grad_norm_pre_clip': 2.5708835124969482, 'timing/data': 0.00018311571329832077, 'timing/model': 0.4569227029569447, 'learning_rate/action_model': 6.986609677579578e-05, 'learning_rate/action_query_proj': 6.986609677579578e-05, 'learning_rate/base': 1.7466524193948944e-05, 'epoch': 0.47}) +[2026-07-27 06:01:33,326][starVLA.training.train_starvla][INFO] - Step 3894, Loss: {'train/loss': 0.029987819492816925, 'train/grad_norm_pre_clip': 1.6100211143493652, 'timing/data': 0.00017429376021027565, 'timing/model': 0.4642560100182891, 'learning_rate/action_model': 6.983810095468698e-05, 'learning_rate/action_query_proj': 6.983810095468698e-05, 'learning_rate/base': 1.7459525238671746e-05, 'epoch': 0.47}) +[2026-07-27 06:01:38,989][starVLA.training.train_starvla][INFO] - Step 3895, Loss: {'train/loss': 0.021650485694408417, 'train/grad_norm_pre_clip': 1.158370852470398, 'timing/data': 0.0001907413825392723, 'timing/model': 0.4581228229217231, 'learning_rate/action_model': 6.981009809137846e-05, 'learning_rate/action_query_proj': 6.981009809137846e-05, 'learning_rate/base': 1.7452524522844614e-05, 'epoch': 0.47}) +[2026-07-27 06:01:44,648][starVLA.training.train_starvla][INFO] - Step 3896, Loss: {'train/loss': 0.060897909104824066, 'train/grad_norm_pre_clip': 2.6612772941589355, 'timing/data': 0.00018531735986471176, 'timing/model': 0.4612842118367553, 'learning_rate/action_model': 6.978208819692526e-05, 'learning_rate/action_query_proj': 6.978208819692526e-05, 'learning_rate/base': 1.7445522049231314e-05, 'epoch': 0.47}) +[2026-07-27 06:01:50,294][starVLA.training.train_starvla][INFO] - Step 3897, Loss: {'train/loss': 0.04137150198221207, 'train/grad_norm_pre_clip': 1.9506025314331055, 'timing/data': 0.00017621507868170738, 'timing/model': 0.46596666472032666, 'learning_rate/action_model': 6.975407128238525e-05, 'learning_rate/action_query_proj': 6.975407128238525e-05, 'learning_rate/base': 1.7438517820596313e-05, 'epoch': 0.47}) +[2026-07-27 06:01:55,952][starVLA.training.train_starvla][INFO] - Step 3898, Loss: {'train/loss': 0.02941766008734703, 'train/grad_norm_pre_clip': 1.7779064178466797, 'timing/data': 0.00017776386812329292, 'timing/model': 0.46082620695233345, 'learning_rate/action_model': 6.972604735881907e-05, 'learning_rate/action_query_proj': 6.972604735881907e-05, 'learning_rate/base': 1.7431511839704768e-05, 'epoch': 0.47}) +[2026-07-27 06:02:01,613][starVLA.training.train_starvla][INFO] - Step 3899, Loss: {'train/loss': 0.06778176873922348, 'train/grad_norm_pre_clip': 2.553325891494751, 'timing/data': 0.00018765125423669815, 'timing/model': 0.4655395280569792, 'learning_rate/action_model': 6.969801643729011e-05, 'learning_rate/action_query_proj': 6.969801643729011e-05, 'learning_rate/base': 1.7424504109322527e-05, 'epoch': 0.47}) +[2026-07-27 06:02:07,248][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 3900 +[2026-07-27 06:02:07,249][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 3900 +[2026-07-27 06:02:07,250][starVLA.training.train_starvla][INFO] - Step 3900, Loss: {'train/loss': 0.08970041573047638, 'train/grad_norm_pre_clip': 3.252711296081543, 'timing/data': 0.00017320364713668823, 'timing/model': 0.46158658899366856, 'learning_rate/action_model': 6.966997852886456e-05, 'learning_rate/action_query_proj': 6.966997852886456e-05, 'learning_rate/base': 1.741749463221614e-05, 'epoch': 0.47}) +[2026-07-27 06:02:12,886][starVLA.training.train_starvla][INFO] - Step 3901, Loss: {'train/loss': 0.04187662526965141, 'train/grad_norm_pre_clip': 1.8020309209823608, 'timing/data': 0.00017471099272370338, 'timing/model': 0.46649455185979605, 'learning_rate/action_model': 6.96419336446113e-05, 'learning_rate/action_query_proj': 6.96419336446113e-05, 'learning_rate/base': 1.7410483411152824e-05, 'epoch': 0.47}) +[2026-07-27 06:02:18,540][starVLA.training.train_starvla][INFO] - Step 3902, Loss: {'train/loss': 0.10988438129425049, 'train/grad_norm_pre_clip': 3.3178365230560303, 'timing/data': 0.00017966004088521004, 'timing/model': 0.4698117030784488, 'learning_rate/action_model': 6.961388179560206e-05, 'learning_rate/action_query_proj': 6.961388179560206e-05, 'learning_rate/base': 1.7403470448900514e-05, 'epoch': 0.47}) +[2026-07-27 06:02:24,200][starVLA.training.train_starvla][INFO] - Step 3903, Loss: {'train/loss': 0.18183310329914093, 'train/grad_norm_pre_clip': 3.20276141166687, 'timing/data': 0.000181540846824646, 'timing/model': 0.46870932215824723, 'learning_rate/action_model': 6.958582299291123e-05, 'learning_rate/action_query_proj': 6.958582299291123e-05, 'learning_rate/base': 1.7396455748227806e-05, 'epoch': 0.47}) +[2026-07-27 06:02:29,866][starVLA.training.train_starvla][INFO] - Step 3904, Loss: {'train/loss': 0.14794856309890747, 'train/grad_norm_pre_clip': 3.684751272201538, 'timing/data': 0.00018406473100185394, 'timing/model': 0.46915871324017644, 'learning_rate/action_model': 6.955775724761597e-05, 'learning_rate/action_query_proj': 6.955775724761597e-05, 'learning_rate/base': 1.7389439311903992e-05, 'epoch': 0.47}) +[2026-07-27 06:02:35,552][starVLA.training.train_starvla][INFO] - Step 3905, Loss: {'train/loss': 0.07687205076217651, 'train/grad_norm_pre_clip': 3.1083121299743652, 'timing/data': 0.00017650611698627472, 'timing/model': 0.46993155404925346, 'learning_rate/action_model': 6.952968457079623e-05, 'learning_rate/action_query_proj': 6.952968457079623e-05, 'learning_rate/base': 1.7382421142699057e-05, 'epoch': 0.47}) +[2026-07-27 06:02:41,224][starVLA.training.train_starvla][INFO] - Step 3906, Loss: {'train/loss': 0.11491666734218597, 'train/grad_norm_pre_clip': 3.332044839859009, 'timing/data': 0.0001775636337697506, 'timing/model': 0.4695132481865585, 'learning_rate/action_model': 6.950160497353463e-05, 'learning_rate/action_query_proj': 6.950160497353463e-05, 'learning_rate/base': 1.7375401243383658e-05, 'epoch': 0.47}) +[2026-07-27 06:02:47,135][starVLA.training.train_starvla][INFO] - Step 3907, Loss: {'train/loss': 0.08972734957933426, 'train/grad_norm_pre_clip': 3.5019469261169434, 'timing/data': 0.0002922890707850456, 'timing/model': 0.45792439626529813, 'learning_rate/action_model': 6.947351846691655e-05, 'learning_rate/action_query_proj': 6.947351846691655e-05, 'learning_rate/base': 1.7368379616729138e-05, 'epoch': 0.47}) +[2026-07-27 06:02:52,791][starVLA.training.train_starvla][INFO] - Step 3908, Loss: {'train/loss': 0.17430104315280914, 'train/grad_norm_pre_clip': 4.002719402313232, 'timing/data': 0.00019794516265392303, 'timing/model': 0.4650145969353616, 'learning_rate/action_model': 6.944542506203011e-05, 'learning_rate/action_query_proj': 6.944542506203011e-05, 'learning_rate/base': 1.7361356265507528e-05, 'epoch': 0.47}) +[2026-07-27 06:02:58,496][starVLA.training.train_starvla][INFO] - Step 3909, Loss: {'train/loss': 0.09344977140426636, 'train/grad_norm_pre_clip': 2.919607400894165, 'timing/data': 0.0001752828247845173, 'timing/model': 0.4656744599342346, 'learning_rate/action_model': 6.941732476996616e-05, 'learning_rate/action_query_proj': 6.941732476996616e-05, 'learning_rate/base': 1.735433119249154e-05, 'epoch': 0.47}) +[2026-07-27 06:03:04,124][starVLA.training.train_starvla][INFO] - Step 3910, Loss: {'train/loss': 0.10546138137578964, 'train/grad_norm_pre_clip': 4.0549139976501465, 'timing/data': 0.0001721666194498539, 'timing/model': 0.46192854968830943, 'learning_rate/action_model': 6.93892176018182e-05, 'learning_rate/action_query_proj': 6.93892176018182e-05, 'learning_rate/base': 1.734730440045455e-05, 'epoch': 0.47}) +[2026-07-27 06:03:09,730][starVLA.training.train_starvla][INFO] - Step 3911, Loss: {'train/loss': 0.18921935558319092, 'train/grad_norm_pre_clip': 6.713536262512207, 'timing/data': 0.00017844699323177338, 'timing/model': 0.4647250398993492, 'learning_rate/action_model': 6.936110356868254e-05, 'learning_rate/action_query_proj': 6.936110356868254e-05, 'learning_rate/base': 1.7340275892170634e-05, 'epoch': 0.47}) +[2026-07-27 06:03:15,305][starVLA.training.train_starvla][INFO] - Step 3912, Loss: {'train/loss': 0.07202963531017303, 'train/grad_norm_pre_clip': 3.274545907974243, 'timing/data': 0.00017943698912858963, 'timing/model': 0.4641223531216383, 'learning_rate/action_model': 6.933298268165813e-05, 'learning_rate/action_query_proj': 6.933298268165813e-05, 'learning_rate/base': 1.733324567041453e-05, 'epoch': 0.47}) +[2026-07-27 06:03:20,875][starVLA.training.train_starvla][INFO] - Step 3913, Loss: {'train/loss': 0.04533172398805618, 'train/grad_norm_pre_clip': 2.430779218673706, 'timing/data': 0.00021727103739976883, 'timing/model': 0.46578456787392497, 'learning_rate/action_model': 6.930485495184665e-05, 'learning_rate/action_query_proj': 6.930485495184665e-05, 'learning_rate/base': 1.7326213737961662e-05, 'epoch': 0.47}) +[2026-07-27 06:03:26,439][starVLA.training.train_starvla][INFO] - Step 3914, Loss: {'train/loss': 0.10960197448730469, 'train/grad_norm_pre_clip': 2.441690683364868, 'timing/data': 0.0001798449084162712, 'timing/model': 0.4622281491756439, 'learning_rate/action_model': 6.92767203903525e-05, 'learning_rate/action_query_proj': 6.92767203903525e-05, 'learning_rate/base': 1.7319180097588127e-05, 'epoch': 0.47}) +[2026-07-27 06:03:32,233][starVLA.training.train_starvla][INFO] - Step 3915, Loss: {'train/loss': 0.11340728402137756, 'train/grad_norm_pre_clip': 3.2739412784576416, 'timing/data': 0.00017645163461565971, 'timing/model': 0.465623342897743, 'learning_rate/action_model': 6.924857900828276e-05, 'learning_rate/action_query_proj': 6.924857900828276e-05, 'learning_rate/base': 1.731214475207069e-05, 'epoch': 0.47}) +[2026-07-27 06:03:37,807][starVLA.training.train_starvla][INFO] - Step 3916, Loss: {'train/loss': 0.09485913813114166, 'train/grad_norm_pre_clip': 3.518024444580078, 'timing/data': 0.0002887677401304245, 'timing/model': 0.459895184263587, 'learning_rate/action_model': 6.922043081674719e-05, 'learning_rate/action_query_proj': 6.922043081674719e-05, 'learning_rate/base': 1.7305107704186798e-05, 'epoch': 0.48}) +[2026-07-27 06:03:43,367][starVLA.training.train_starvla][INFO] - Step 3917, Loss: {'train/loss': 0.056873220950365067, 'train/grad_norm_pre_clip': 2.5617799758911133, 'timing/data': 0.00017467886209487915, 'timing/model': 0.4624341740272939, 'learning_rate/action_model': 6.919227582685823e-05, 'learning_rate/action_query_proj': 6.919227582685823e-05, 'learning_rate/base': 1.7298068956714558e-05, 'epoch': 0.48}) +[2026-07-27 06:03:48,957][starVLA.training.train_starvla][INFO] - Step 3918, Loss: {'train/loss': 0.12776075303554535, 'train/grad_norm_pre_clip': 4.462833881378174, 'timing/data': 0.00017397291958332062, 'timing/model': 0.4652273249812424, 'learning_rate/action_model': 6.916411404973108e-05, 'learning_rate/action_query_proj': 6.916411404973108e-05, 'learning_rate/base': 1.729102851243277e-05, 'epoch': 0.48}) +[2026-07-27 06:03:54,526][starVLA.training.train_starvla][INFO] - Step 3919, Loss: {'train/loss': 0.13562361896038055, 'train/grad_norm_pre_clip': 4.748934268951416, 'timing/data': 0.0001854640431702137, 'timing/model': 0.462121426127851, 'learning_rate/action_model': 6.913594549648352e-05, 'learning_rate/action_query_proj': 6.913594549648352e-05, 'learning_rate/base': 1.728398637412088e-05, 'epoch': 0.48}) +[2026-07-27 06:04:00,155][starVLA.training.train_starvla][INFO] - Step 3920, Loss: {'train/loss': 0.06620362401008606, 'train/grad_norm_pre_clip': 3.3922574520111084, 'timing/data': 0.0001829550601541996, 'timing/model': 0.4637548406608403, 'learning_rate/action_model': 6.910777017823603e-05, 'learning_rate/action_query_proj': 6.910777017823603e-05, 'learning_rate/base': 1.727694254455901e-05, 'epoch': 0.48}) +[2026-07-27 06:04:05,778][starVLA.training.train_starvla][INFO] - Step 3921, Loss: {'train/loss': 0.08835045993328094, 'train/grad_norm_pre_clip': 2.8742032051086426, 'timing/data': 0.00017240410670638084, 'timing/model': 0.4598325383849442, 'learning_rate/action_model': 6.907958810611183e-05, 'learning_rate/action_query_proj': 6.907958810611183e-05, 'learning_rate/base': 1.7269897026527958e-05, 'epoch': 0.48}) +[2026-07-27 06:04:11,381][starVLA.training.train_starvla][INFO] - Step 3922, Loss: {'train/loss': 0.0543033592402935, 'train/grad_norm_pre_clip': 2.831930160522461, 'timing/data': 0.00021354109048843384, 'timing/model': 0.46358625032007694, 'learning_rate/action_model': 6.905139929123674e-05, 'learning_rate/action_query_proj': 6.905139929123674e-05, 'learning_rate/base': 1.7262849822809185e-05, 'epoch': 0.48}) +[2026-07-27 06:04:17,011][starVLA.training.train_starvla][INFO] - Step 3923, Loss: {'train/loss': 0.06788908690214157, 'train/grad_norm_pre_clip': 2.8119497299194336, 'timing/data': 0.00016814982518553734, 'timing/model': 0.46509040193632245, 'learning_rate/action_model': 6.902320374473927e-05, 'learning_rate/action_query_proj': 6.902320374473927e-05, 'learning_rate/base': 1.7255800936184817e-05, 'epoch': 0.48}) +[2026-07-27 06:04:22,631][starVLA.training.train_starvla][INFO] - Step 3924, Loss: {'train/loss': 0.1511649191379547, 'train/grad_norm_pre_clip': 4.3775954246521, 'timing/data': 0.00016809534281492233, 'timing/model': 0.4635713850148022, 'learning_rate/action_model': 6.899500147775052e-05, 'learning_rate/action_query_proj': 6.899500147775052e-05, 'learning_rate/base': 1.724875036943763e-05, 'epoch': 0.48}) +[2026-07-27 06:04:28,254][starVLA.training.train_starvla][INFO] - Step 3925, Loss: {'train/loss': 0.1329907476902008, 'train/grad_norm_pre_clip': 3.957674026489258, 'timing/data': 0.00021689524874091148, 'timing/model': 0.4635851248167455, 'learning_rate/action_model': 6.896679250140435e-05, 'learning_rate/action_query_proj': 6.896679250140435e-05, 'learning_rate/base': 1.7241698125351087e-05, 'epoch': 0.48}) +[2026-07-27 06:04:33,875][starVLA.training.train_starvla][INFO] - Step 3926, Loss: {'train/loss': 0.09220179915428162, 'train/grad_norm_pre_clip': 2.9343554973602295, 'timing/data': 0.00016493909060955048, 'timing/model': 0.4608934409916401, 'learning_rate/action_model': 6.893857682683721e-05, 'learning_rate/action_query_proj': 6.893857682683721e-05, 'learning_rate/base': 1.7234644206709303e-05, 'epoch': 0.48}) +[2026-07-27 06:04:39,500][starVLA.training.train_starvla][INFO] - Step 3927, Loss: {'train/loss': 0.0376131497323513, 'train/grad_norm_pre_clip': 2.1379055976867676, 'timing/data': 0.0002199402078986168, 'timing/model': 0.4618644779548049, 'learning_rate/action_model': 6.891035446518817e-05, 'learning_rate/action_query_proj': 6.891035446518817e-05, 'learning_rate/base': 1.7227588616297044e-05, 'epoch': 0.48}) +[2026-07-27 06:04:45,102][starVLA.training.train_starvla][INFO] - Step 3928, Loss: {'train/loss': 0.01676284894347191, 'train/grad_norm_pre_clip': 1.4323763847351074, 'timing/data': 0.00016922783106565475, 'timing/model': 0.4664108562283218, 'learning_rate/action_model': 6.888212542759902e-05, 'learning_rate/action_query_proj': 6.888212542759902e-05, 'learning_rate/base': 1.7220531356899755e-05, 'epoch': 0.48}) +[2026-07-27 06:04:50,700][starVLA.training.train_starvla][INFO] - Step 3929, Loss: {'train/loss': 0.14802922308444977, 'train/grad_norm_pre_clip': 4.4682393074035645, 'timing/data': 0.00016828719526529312, 'timing/model': 0.4593369527719915, 'learning_rate/action_model': 6.885388972521412e-05, 'learning_rate/action_query_proj': 6.885388972521412e-05, 'learning_rate/base': 1.721347243130353e-05, 'epoch': 0.48}) +[2026-07-27 06:04:56,304][starVLA.training.train_starvla][INFO] - Step 3930, Loss: {'train/loss': 0.042486581951379776, 'train/grad_norm_pre_clip': 2.1240780353546143, 'timing/data': 0.00016926182433962822, 'timing/model': 0.4656692328862846, 'learning_rate/action_model': 6.882564736918043e-05, 'learning_rate/action_query_proj': 6.882564736918043e-05, 'learning_rate/base': 1.7206411842295108e-05, 'epoch': 0.48}) +[2026-07-27 06:05:01,944][starVLA.training.train_starvla][INFO] - Step 3931, Loss: {'train/loss': 0.21079856157302856, 'train/grad_norm_pre_clip': 4.815554141998291, 'timing/data': 0.000169296283274889, 'timing/model': 0.46429057186469436, 'learning_rate/action_model': 6.879739837064765e-05, 'learning_rate/action_query_proj': 6.879739837064765e-05, 'learning_rate/base': 1.7199349592661913e-05, 'epoch': 0.48}) +[2026-07-27 06:05:07,531][starVLA.training.train_starvla][INFO] - Step 3932, Loss: {'train/loss': 0.056816551834344864, 'train/grad_norm_pre_clip': 2.5298328399658203, 'timing/data': 0.00016473094001412392, 'timing/model': 0.46484383195638657, 'learning_rate/action_model': 6.876914274076802e-05, 'learning_rate/action_query_proj': 6.876914274076802e-05, 'learning_rate/base': 1.7192285685192006e-05, 'epoch': 0.48}) +[2026-07-27 06:05:13,195][starVLA.training.train_starvla][INFO] - Step 3933, Loss: {'train/loss': 0.03762632608413696, 'train/grad_norm_pre_clip': 2.2656402587890625, 'timing/data': 0.00021359417587518692, 'timing/model': 0.46661313297227025, 'learning_rate/action_model': 6.874088049069641e-05, 'learning_rate/action_query_proj': 6.874088049069641e-05, 'learning_rate/base': 1.7185220122674102e-05, 'epoch': 0.48}) +[2026-07-27 06:05:18,914][starVLA.training.train_starvla][INFO] - Step 3934, Loss: {'train/loss': 0.12921614944934845, 'train/grad_norm_pre_clip': 3.0310983657836914, 'timing/data': 0.0001878160983324051, 'timing/model': 0.463036532048136, 'learning_rate/action_model': 6.871261163159028e-05, 'learning_rate/action_query_proj': 6.871261163159028e-05, 'learning_rate/base': 1.717815290789757e-05, 'epoch': 0.48}) +[2026-07-27 06:05:24,519][starVLA.training.train_starvla][INFO] - Step 3935, Loss: {'train/loss': 0.05248900130391121, 'train/grad_norm_pre_clip': 2.7353885173797607, 'timing/data': 0.00017176615074276924, 'timing/model': 0.464732738211751, 'learning_rate/action_model': 6.868433617460978e-05, 'learning_rate/action_query_proj': 6.868433617460978e-05, 'learning_rate/base': 1.7171084043652445e-05, 'epoch': 0.48}) +[2026-07-27 06:05:30,172][starVLA.training.train_starvla][INFO] - Step 3936, Loss: {'train/loss': 0.028733402490615845, 'train/grad_norm_pre_clip': 1.9133274555206299, 'timing/data': 0.00016492512077093124, 'timing/model': 0.4663452892564237, 'learning_rate/action_model': 6.865605413091759e-05, 'learning_rate/action_query_proj': 6.865605413091759e-05, 'learning_rate/base': 1.7164013532729398e-05, 'epoch': 0.48}) +[2026-07-27 06:05:35,781][starVLA.training.train_starvla][INFO] - Step 3937, Loss: {'train/loss': 0.10956867784261703, 'train/grad_norm_pre_clip': 3.086493492126465, 'timing/data': 0.00017017731443047523, 'timing/model': 0.4556345739401877, 'learning_rate/action_model': 6.862776551167898e-05, 'learning_rate/action_query_proj': 6.862776551167898e-05, 'learning_rate/base': 1.7156941377919745e-05, 'epoch': 0.48}) +[2026-07-27 06:05:41,382][starVLA.training.train_starvla][INFO] - Step 3938, Loss: {'train/loss': 0.07341093569993973, 'train/grad_norm_pre_clip': 2.1029417514801025, 'timing/data': 0.00016673794016242027, 'timing/model': 0.4659125912003219, 'learning_rate/action_model': 6.859947032806191e-05, 'learning_rate/action_query_proj': 6.859947032806191e-05, 'learning_rate/base': 1.7149867582015477e-05, 'epoch': 0.48}) +[2026-07-27 06:05:46,998][starVLA.training.train_starvla][INFO] - Step 3939, Loss: {'train/loss': 0.12106994539499283, 'train/grad_norm_pre_clip': 3.753962755203247, 'timing/data': 0.00017679110169410706, 'timing/model': 0.4595222380012274, 'learning_rate/action_model': 6.857116859123683e-05, 'learning_rate/action_query_proj': 6.857116859123683e-05, 'learning_rate/base': 1.7142792147809207e-05, 'epoch': 0.48}) +[2026-07-27 06:05:52,618][starVLA.training.train_starvla][INFO] - Step 3940, Loss: {'train/loss': 0.08268297463655472, 'train/grad_norm_pre_clip': 4.129905700683594, 'timing/data': 0.00017205579206347466, 'timing/model': 0.4644739259965718, 'learning_rate/action_model': 6.854286031237682e-05, 'learning_rate/action_query_proj': 6.854286031237682e-05, 'learning_rate/base': 1.7135715078094205e-05, 'epoch': 0.48}) +[2026-07-27 06:05:58,244][starVLA.training.train_starvla][INFO] - Step 3941, Loss: {'train/loss': 0.10785701125860214, 'train/grad_norm_pre_clip': 3.9190175533294678, 'timing/data': 0.00017129676416516304, 'timing/model': 0.46587032778188586, 'learning_rate/action_model': 6.851454550265756e-05, 'learning_rate/action_query_proj': 6.851454550265756e-05, 'learning_rate/base': 1.712863637566439e-05, 'epoch': 0.48}) +[2026-07-27 06:06:03,861][starVLA.training.train_starvla][INFO] - Step 3942, Loss: {'train/loss': 0.07872506976127625, 'train/grad_norm_pre_clip': 3.507852077484131, 'timing/data': 0.0001771547831594944, 'timing/model': 0.4637737930752337, 'learning_rate/action_model': 6.848622417325725e-05, 'learning_rate/action_query_proj': 6.848622417325725e-05, 'learning_rate/base': 1.7121556043314312e-05, 'epoch': 0.48}) +[2026-07-27 06:06:09,493][starVLA.training.train_starvla][INFO] - Step 3943, Loss: {'train/loss': 0.06035945564508438, 'train/grad_norm_pre_clip': 1.9993001222610474, 'timing/data': 0.00017271609976887703, 'timing/model': 0.46530417213216424, 'learning_rate/action_model': 6.845789633535677e-05, 'learning_rate/action_query_proj': 6.845789633535677e-05, 'learning_rate/base': 1.711447408383919e-05, 'epoch': 0.48}) +[2026-07-27 06:06:15,144][starVLA.training.train_starvla][INFO] - Step 3944, Loss: {'train/loss': 0.01671910658478737, 'train/grad_norm_pre_clip': 1.1145164966583252, 'timing/data': 0.0001725279726088047, 'timing/model': 0.4617844237945974, 'learning_rate/action_model': 6.842956200013942e-05, 'learning_rate/action_query_proj': 6.842956200013942e-05, 'learning_rate/base': 1.7107390500034856e-05, 'epoch': 0.48}) +[2026-07-27 06:06:20,810][starVLA.training.train_starvla][INFO] - Step 3945, Loss: {'train/loss': 0.11102232336997986, 'train/grad_norm_pre_clip': 3.221982717514038, 'timing/data': 0.00016992166638374329, 'timing/model': 0.46493474394083023, 'learning_rate/action_model': 6.840122117879121e-05, 'learning_rate/action_query_proj': 6.840122117879121e-05, 'learning_rate/base': 1.7100305294697802e-05, 'epoch': 0.48}) +[2026-07-27 06:06:26,459][starVLA.training.train_starvla][INFO] - Step 3946, Loss: {'train/loss': 0.06334152072668076, 'train/grad_norm_pre_clip': 3.028059482574463, 'timing/data': 0.00017911987379193306, 'timing/model': 0.4610592359676957, 'learning_rate/action_model': 6.837287388250061e-05, 'learning_rate/action_query_proj': 6.837287388250061e-05, 'learning_rate/base': 1.7093218470625153e-05, 'epoch': 0.48}) +[2026-07-27 06:06:32,142][starVLA.training.train_starvla][INFO] - Step 3947, Loss: {'train/loss': 0.1342381089925766, 'train/grad_norm_pre_clip': 4.018625259399414, 'timing/data': 0.00017612706869840622, 'timing/model': 0.46545589808374643, 'learning_rate/action_model': 6.834452012245872e-05, 'learning_rate/action_query_proj': 6.834452012245872e-05, 'learning_rate/base': 1.708613003061468e-05, 'epoch': 0.48}) +[2026-07-27 06:06:37,808][starVLA.training.train_starvla][INFO] - Step 3948, Loss: {'train/loss': 0.15472380816936493, 'train/grad_norm_pre_clip': 4.658592700958252, 'timing/data': 0.00017324602231383324, 'timing/model': 0.46047204406931996, 'learning_rate/action_model': 6.831615990985912e-05, 'learning_rate/action_query_proj': 6.831615990985912e-05, 'learning_rate/base': 1.707903997746478e-05, 'epoch': 0.48}) +[2026-07-27 06:06:43,615][starVLA.training.train_starvla][INFO] - Step 3949, Loss: {'train/loss': 0.037762343883514404, 'train/grad_norm_pre_clip': 1.3385555744171143, 'timing/data': 0.0001720460131764412, 'timing/model': 0.46594334207475185, 'learning_rate/action_model': 6.828779325589796e-05, 'learning_rate/action_query_proj': 6.828779325589796e-05, 'learning_rate/base': 1.707194831397449e-05, 'epoch': 0.48}) +[2026-07-27 06:06:49,232][starVLA.training.train_starvla][INFO] - Step 3950, Loss: {'train/loss': 0.030548132956027985, 'train/grad_norm_pre_clip': 2.3939595222473145, 'timing/data': 0.0001705177128314972, 'timing/model': 0.4650936177931726, 'learning_rate/action_model': 6.8259420171774e-05, 'learning_rate/action_query_proj': 6.8259420171774e-05, 'learning_rate/base': 1.70648550429435e-05, 'epoch': 0.48}) +[2026-07-27 06:06:54,854][starVLA.training.train_starvla][INFO] - Step 3951, Loss: {'train/loss': 0.04474566876888275, 'train/grad_norm_pre_clip': 2.845883369445801, 'timing/data': 0.000173298642039299, 'timing/model': 0.467619223985821, 'learning_rate/action_model': 6.823104066868843e-05, 'learning_rate/action_query_proj': 6.823104066868843e-05, 'learning_rate/base': 1.7057760167172108e-05, 'epoch': 0.48}) +[2026-07-27 06:07:00,491][starVLA.training.train_starvla][INFO] - Step 3952, Loss: {'train/loss': 0.029511960223317146, 'train/grad_norm_pre_clip': 1.7165242433547974, 'timing/data': 0.0001719500869512558, 'timing/model': 0.4646895658224821, 'learning_rate/action_model': 6.820265475784509e-05, 'learning_rate/action_query_proj': 6.820265475784509e-05, 'learning_rate/base': 1.7050663689461273e-05, 'epoch': 0.48}) +[2026-07-27 06:07:06,099][starVLA.training.train_starvla][INFO] - Step 3953, Loss: {'train/loss': 0.10460732132196426, 'train/grad_norm_pre_clip': 3.6008105278015137, 'timing/data': 0.00018161442130804062, 'timing/model': 0.4557754439301789, 'learning_rate/action_model': 6.817426245045022e-05, 'learning_rate/action_query_proj': 6.817426245045022e-05, 'learning_rate/base': 1.7043565612612556e-05, 'epoch': 0.48}) +[2026-07-27 06:07:11,731][starVLA.training.train_starvla][INFO] - Step 3954, Loss: {'train/loss': 0.06828434020280838, 'train/grad_norm_pre_clip': 3.145739793777466, 'timing/data': 0.0001696692779660225, 'timing/model': 0.4616747838445008, 'learning_rate/action_model': 6.814586375771271e-05, 'learning_rate/action_query_proj': 6.814586375771271e-05, 'learning_rate/base': 1.7036465939428178e-05, 'epoch': 0.48}) +[2026-07-27 06:07:17,351][starVLA.training.train_starvla][INFO] - Step 3955, Loss: {'train/loss': 0.11732898652553558, 'train/grad_norm_pre_clip': 3.7133736610412598, 'timing/data': 0.00017798598855733871, 'timing/model': 0.4677771320566535, 'learning_rate/action_model': 6.811745869084388e-05, 'learning_rate/action_query_proj': 6.811745869084388e-05, 'learning_rate/base': 1.702936467271097e-05, 'epoch': 0.48}) +[2026-07-27 06:07:22,977][starVLA.training.train_starvla][INFO] - Step 3956, Loss: {'train/loss': 0.025753548368811607, 'train/grad_norm_pre_clip': 1.9570952653884888, 'timing/data': 0.00016975495964288712, 'timing/model': 0.46596142277121544, 'learning_rate/action_model': 6.808904726105762e-05, 'learning_rate/action_query_proj': 6.808904726105762e-05, 'learning_rate/base': 1.7022261815264405e-05, 'epoch': 0.48}) +[2026-07-27 06:07:28,608][starVLA.training.train_starvla][INFO] - Step 3957, Loss: {'train/loss': 0.044933173805475235, 'train/grad_norm_pre_clip': 2.774048089981079, 'timing/data': 0.00016963202506303787, 'timing/model': 0.46497992891818285, 'learning_rate/action_model': 6.806062947957028e-05, 'learning_rate/action_query_proj': 6.806062947957028e-05, 'learning_rate/base': 1.701515736989257e-05, 'epoch': 0.48}) +[2026-07-27 06:07:34,246][starVLA.training.train_starvla][INFO] - Step 3958, Loss: {'train/loss': 0.06675993651151657, 'train/grad_norm_pre_clip': 3.063868522644043, 'timing/data': 0.00017068302258849144, 'timing/model': 0.4662885502912104, 'learning_rate/action_model': 6.803220535760079e-05, 'learning_rate/action_query_proj': 6.803220535760079e-05, 'learning_rate/base': 1.7008051339400196e-05, 'epoch': 0.48}) +[2026-07-27 06:07:39,844][starVLA.training.train_starvla][INFO] - Step 3959, Loss: {'train/loss': 0.05800924822688103, 'train/grad_norm_pre_clip': 3.1321916580200195, 'timing/data': 0.0001713782548904419, 'timing/model': 0.46015140414237976, 'learning_rate/action_model': 6.800377490637052e-05, 'learning_rate/action_query_proj': 6.800377490637052e-05, 'learning_rate/base': 1.700094372659263e-05, 'epoch': 0.48}) +[2026-07-27 06:07:45,462][starVLA.training.train_starvla][INFO] - Step 3960, Loss: {'train/loss': 0.0564444325864315, 'train/grad_norm_pre_clip': 2.7717010974884033, 'timing/data': 0.00017761066555976868, 'timing/model': 0.4637482399120927, 'learning_rate/action_model': 6.797533813710336e-05, 'learning_rate/action_query_proj': 6.797533813710336e-05, 'learning_rate/base': 1.699383453427584e-05, 'epoch': 0.48}) +[2026-07-27 06:07:51,282][starVLA.training.train_starvla][INFO] - Step 3961, Loss: {'train/loss': 0.0469883568584919, 'train/grad_norm_pre_clip': 3.6810479164123535, 'timing/data': 0.0001689121127128601, 'timing/model': 0.4608958098106086, 'learning_rate/action_model': 6.794689506102572e-05, 'learning_rate/action_query_proj': 6.794689506102572e-05, 'learning_rate/base': 1.698672376525643e-05, 'epoch': 0.48}) +[2026-07-27 06:07:56,877][starVLA.training.train_starvla][INFO] - Step 3962, Loss: {'train/loss': 0.037518035620450974, 'train/grad_norm_pre_clip': 2.2190985679626465, 'timing/data': 0.00017534708604216576, 'timing/model': 0.4626226229593158, 'learning_rate/action_model': 6.791844568936644e-05, 'learning_rate/action_query_proj': 6.791844568936644e-05, 'learning_rate/base': 1.697961142234161e-05, 'epoch': 0.48}) +[2026-07-27 06:08:02,464][starVLA.training.train_starvla][INFO] - Step 3963, Loss: {'train/loss': 0.13858336210250854, 'train/grad_norm_pre_clip': 3.0125067234039307, 'timing/data': 0.00017027324065566063, 'timing/model': 0.4628699030727148, 'learning_rate/action_model': 6.788999003335692e-05, 'learning_rate/action_query_proj': 6.788999003335692e-05, 'learning_rate/base': 1.697249750833923e-05, 'epoch': 0.48}) +[2026-07-27 06:08:08,067][starVLA.training.train_starvla][INFO] - Step 3964, Loss: {'train/loss': 0.0728524923324585, 'train/grad_norm_pre_clip': 3.4700560569763184, 'timing/data': 0.0001729670912027359, 'timing/model': 0.4567337650805712, 'learning_rate/action_model': 6.786152810423099e-05, 'learning_rate/action_query_proj': 6.786152810423099e-05, 'learning_rate/base': 1.6965382026057748e-05, 'epoch': 0.48}) +[2026-07-27 06:08:13,853][starVLA.training.train_starvla][INFO] - Step 3965, Loss: {'train/loss': 0.06702248752117157, 'train/grad_norm_pre_clip': 2.8405063152313232, 'timing/data': 0.00017495080828666687, 'timing/model': 0.46297627594321966, 'learning_rate/action_model': 6.783305991322493e-05, 'learning_rate/action_query_proj': 6.783305991322493e-05, 'learning_rate/base': 1.6958264978306233e-05, 'epoch': 0.48}) +[2026-07-27 06:08:19,453][starVLA.training.train_starvla][INFO] - Step 3966, Loss: {'train/loss': 0.03241143003106117, 'train/grad_norm_pre_clip': 1.5460268259048462, 'timing/data': 0.00017558084800839424, 'timing/model': 0.46234103525057435, 'learning_rate/action_model': 6.780458547157761e-05, 'learning_rate/action_query_proj': 6.780458547157761e-05, 'learning_rate/base': 1.6951146367894402e-05, 'epoch': 0.48}) +[2026-07-27 06:08:25,042][starVLA.training.train_starvla][INFO] - Step 3967, Loss: {'train/loss': 0.04157257080078125, 'train/grad_norm_pre_clip': 2.4611732959747314, 'timing/data': 0.00017605070024728775, 'timing/model': 0.46488264575600624, 'learning_rate/action_model': 6.77761047905302e-05, 'learning_rate/action_query_proj': 6.77761047905302e-05, 'learning_rate/base': 1.694402619763255e-05, 'epoch': 0.48}) +[2026-07-27 06:08:30,633][starVLA.training.train_starvla][INFO] - Step 3968, Loss: {'train/loss': 0.10717611759901047, 'train/grad_norm_pre_clip': 3.959099054336548, 'timing/data': 0.00016981270164251328, 'timing/model': 0.46138033689931035, 'learning_rate/action_model': 6.774761788132648e-05, 'learning_rate/action_query_proj': 6.774761788132648e-05, 'learning_rate/base': 1.693690447033162e-05, 'epoch': 0.48}) +[2026-07-27 06:08:36,223][starVLA.training.train_starvla][INFO] - Step 3969, Loss: {'train/loss': 0.05830434709787369, 'train/grad_norm_pre_clip': 2.072838068008423, 'timing/data': 0.0001773959957063198, 'timing/model': 0.4652111120522022, 'learning_rate/action_model': 6.771912475521262e-05, 'learning_rate/action_query_proj': 6.771912475521262e-05, 'learning_rate/base': 1.6929781188803156e-05, 'epoch': 0.48}) +[2026-07-27 06:08:41,807][starVLA.training.train_starvla][INFO] - Step 3970, Loss: {'train/loss': 0.04502146691083908, 'train/grad_norm_pre_clip': 2.546316146850586, 'timing/data': 0.00017653964459896088, 'timing/model': 0.46129093458876014, 'learning_rate/action_model': 6.769062542343724e-05, 'learning_rate/action_query_proj': 6.769062542343724e-05, 'learning_rate/base': 1.692265635585931e-05, 'epoch': 0.48}) +[2026-07-27 06:08:47,403][starVLA.training.train_starvla][INFO] - Step 3971, Loss: {'train/loss': 0.05722294747829437, 'train/grad_norm_pre_clip': 3.2447245121002197, 'timing/data': 0.00017735827714204788, 'timing/model': 0.46529523003846407, 'learning_rate/action_model': 6.766211989725145e-05, 'learning_rate/action_query_proj': 6.766211989725145e-05, 'learning_rate/base': 1.691552997431286e-05, 'epoch': 0.48}) +[2026-07-27 06:08:52,988][starVLA.training.train_starvla][INFO] - Step 3972, Loss: {'train/loss': 0.15458382666110992, 'train/grad_norm_pre_clip': 4.335369110107422, 'timing/data': 0.00017636409029364586, 'timing/model': 0.46646151691675186, 'learning_rate/action_model': 6.763360818790875e-05, 'learning_rate/action_query_proj': 6.763360818790875e-05, 'learning_rate/base': 1.6908402046977187e-05, 'epoch': 0.48}) +[2026-07-27 06:08:58,566][starVLA.training.train_starvla][INFO] - Step 3973, Loss: {'train/loss': 0.05387701094150543, 'train/grad_norm_pre_clip': 2.650055408477783, 'timing/data': 0.0001733461394906044, 'timing/model': 0.46555784484371543, 'learning_rate/action_model': 6.760509030666513e-05, 'learning_rate/action_query_proj': 6.760509030666513e-05, 'learning_rate/base': 1.6901272576666282e-05, 'epoch': 0.48}) +[2026-07-27 06:09:04,163][starVLA.training.train_starvla][INFO] - Step 3974, Loss: {'train/loss': 0.1716080754995346, 'train/grad_norm_pre_clip': 5.303683280944824, 'timing/data': 0.000172480009496212, 'timing/model': 0.4599641510285437, 'learning_rate/action_model': 6.757656626477898e-05, 'learning_rate/action_query_proj': 6.757656626477898e-05, 'learning_rate/base': 1.6894141566194746e-05, 'epoch': 0.48}) +[2026-07-27 06:09:09,777][starVLA.training.train_starvla][INFO] - Step 3975, Loss: {'train/loss': 0.07046430557966232, 'train/grad_norm_pre_clip': 3.0847010612487793, 'timing/data': 0.0001704166643321514, 'timing/model': 0.46471456717699766, 'learning_rate/action_model': 6.754803607351117e-05, 'learning_rate/action_query_proj': 6.754803607351117e-05, 'learning_rate/base': 1.6887009018377793e-05, 'epoch': 0.48}) +[2026-07-27 06:09:15,372][starVLA.training.train_starvla][INFO] - Step 3976, Loss: {'train/loss': 0.1174372136592865, 'train/grad_norm_pre_clip': 4.843085289001465, 'timing/data': 0.00017004786059260368, 'timing/model': 0.46069917315617204, 'learning_rate/action_model': 6.751949974412496e-05, 'learning_rate/action_query_proj': 6.751949974412496e-05, 'learning_rate/base': 1.687987493603124e-05, 'epoch': 0.48}) +[2026-07-27 06:09:20,963][starVLA.training.train_starvla][INFO] - Step 3977, Loss: {'train/loss': 0.07863657921552658, 'train/grad_norm_pre_clip': 3.4850850105285645, 'timing/data': 0.00017311517149209976, 'timing/model': 0.4597677453421056, 'learning_rate/action_model': 6.749095728788602e-05, 'learning_rate/action_query_proj': 6.749095728788602e-05, 'learning_rate/base': 1.6872739321971506e-05, 'epoch': 0.48}) +[2026-07-27 06:09:26,561][starVLA.training.train_starvla][INFO] - Step 3978, Loss: {'train/loss': 0.05249892920255661, 'train/grad_norm_pre_clip': 3.0249903202056885, 'timing/data': 0.00017345603555440903, 'timing/model': 0.46527455281466246, 'learning_rate/action_model': 6.746240871606247e-05, 'learning_rate/action_query_proj': 6.746240871606247e-05, 'learning_rate/base': 1.6865602179015618e-05, 'epoch': 0.48}) +[2026-07-27 06:09:32,154][starVLA.training.train_starvla][INFO] - Step 3979, Loss: {'train/loss': 0.036674778908491135, 'train/grad_norm_pre_clip': 2.5358362197875977, 'timing/data': 0.0001872330904006958, 'timing/model': 0.45595395285636187, 'learning_rate/action_model': 6.743385403992484e-05, 'learning_rate/action_query_proj': 6.743385403992484e-05, 'learning_rate/base': 1.685846350998121e-05, 'epoch': 0.48}) +[2026-07-27 06:09:37,805][starVLA.training.train_starvla][INFO] - Step 3980, Loss: {'train/loss': 0.04993075132369995, 'train/grad_norm_pre_clip': 2.1862547397613525, 'timing/data': 0.00022719381377100945, 'timing/model': 0.4714745720848441, 'learning_rate/action_model': 6.740529327074605e-05, 'learning_rate/action_query_proj': 6.740529327074605e-05, 'learning_rate/base': 1.6851323317686512e-05, 'epoch': 0.48}) +[2026-07-27 06:09:43,403][starVLA.training.train_starvla][INFO] - Step 3981, Loss: {'train/loss': 0.05301167815923691, 'train/grad_norm_pre_clip': 2.94323468208313, 'timing/data': 0.00017108209431171417, 'timing/model': 0.47182249184697866, 'learning_rate/action_model': 6.737672641980147e-05, 'learning_rate/action_query_proj': 6.737672641980147e-05, 'learning_rate/base': 1.6844181604950367e-05, 'epoch': 0.48}) +[2026-07-27 06:09:49,009][starVLA.training.train_starvla][INFO] - Step 3982, Loss: {'train/loss': 0.12168313562870026, 'train/grad_norm_pre_clip': 3.1903014183044434, 'timing/data': 0.00017130514606833458, 'timing/model': 0.4625553507357836, 'learning_rate/action_model': 6.734815349836882e-05, 'learning_rate/action_query_proj': 6.734815349836882e-05, 'learning_rate/base': 1.6837038374592205e-05, 'epoch': 0.48}) +[2026-07-27 06:09:54,582][starVLA.training.train_starvla][INFO] - Step 3983, Loss: {'train/loss': 0.21561183035373688, 'train/grad_norm_pre_clip': 3.900972366333008, 'timing/data': 0.0001681721769273281, 'timing/model': 0.4547746148891747, 'learning_rate/action_model': 6.731957451772823e-05, 'learning_rate/action_query_proj': 6.731957451772823e-05, 'learning_rate/base': 1.6829893629432057e-05, 'epoch': 0.48}) +[2026-07-27 06:10:00,182][starVLA.training.train_starvla][INFO] - Step 3984, Loss: {'train/loss': 0.15179987251758575, 'train/grad_norm_pre_clip': 4.401974201202393, 'timing/data': 0.00016715191304683685, 'timing/model': 0.4617217960767448, 'learning_rate/action_model': 6.729098948916221e-05, 'learning_rate/action_query_proj': 6.729098948916221e-05, 'learning_rate/base': 1.6822747372290553e-05, 'epoch': 0.48}) +[2026-07-27 06:10:06,003][starVLA.training.train_starvla][INFO] - Step 3985, Loss: {'train/loss': 0.06029799208045006, 'train/grad_norm_pre_clip': 2.894728660583496, 'timing/data': 0.000165517907589674, 'timing/model': 0.463881959207356, 'learning_rate/action_model': 6.726239842395571e-05, 'learning_rate/action_query_proj': 6.726239842395571e-05, 'learning_rate/base': 1.681559960598893e-05, 'epoch': 0.48}) +[2026-07-27 06:10:11,583][starVLA.training.train_starvla][INFO] - Step 3986, Loss: {'train/loss': 0.09714081138372421, 'train/grad_norm_pre_clip': 2.8861660957336426, 'timing/data': 0.00017064018175005913, 'timing/model': 0.4608384952880442, 'learning_rate/action_model': 6.723380133339605e-05, 'learning_rate/action_query_proj': 6.723380133339605e-05, 'learning_rate/base': 1.6808450333349013e-05, 'epoch': 0.48}) +[2026-07-27 06:10:17,193][starVLA.training.train_starvla][INFO] - Step 3987, Loss: {'train/loss': 0.02365177497267723, 'train/grad_norm_pre_clip': 1.9357713460922241, 'timing/data': 0.00017389841377735138, 'timing/model': 0.4602709258906543, 'learning_rate/action_model': 6.720519822877286e-05, 'learning_rate/action_query_proj': 6.720519822877286e-05, 'learning_rate/base': 1.6801299557193216e-05, 'epoch': 0.48}) +[2026-07-27 06:10:22,799][starVLA.training.train_starvla][INFO] - Step 3988, Loss: {'train/loss': 0.050753992050886154, 'train/grad_norm_pre_clip': 2.6565206050872803, 'timing/data': 0.00017218571156263351, 'timing/model': 0.4654679587110877, 'learning_rate/action_model': 6.717658912137824e-05, 'learning_rate/action_query_proj': 6.717658912137824e-05, 'learning_rate/base': 1.679414728034456e-05, 'epoch': 0.48}) +[2026-07-27 06:10:28,391][starVLA.training.train_starvla][INFO] - Step 3989, Loss: {'train/loss': 0.12655703723430634, 'train/grad_norm_pre_clip': 3.209348440170288, 'timing/data': 0.00017548119649291039, 'timing/model': 0.4642545459792018, 'learning_rate/action_model': 6.714797402250656e-05, 'learning_rate/action_query_proj': 6.714797402250656e-05, 'learning_rate/base': 1.678699350562664e-05, 'epoch': 0.48}) +[2026-07-27 06:10:33,995][starVLA.training.train_starvla][INFO] - Step 3990, Loss: {'train/loss': 0.08556784689426422, 'train/grad_norm_pre_clip': 2.763991117477417, 'timing/data': 0.00017280597239732742, 'timing/model': 0.4600338712334633, 'learning_rate/action_model': 6.711935294345463e-05, 'learning_rate/action_query_proj': 6.711935294345463e-05, 'learning_rate/base': 1.6779838235863658e-05, 'epoch': 0.48}) +[2026-07-27 06:10:39,577][starVLA.training.train_starvla][INFO] - Step 3991, Loss: {'train/loss': 0.07010754942893982, 'train/grad_norm_pre_clip': 3.007589817047119, 'timing/data': 0.00017125625163316727, 'timing/model': 0.4640237959101796, 'learning_rate/action_model': 6.709072589552163e-05, 'learning_rate/action_query_proj': 6.709072589552163e-05, 'learning_rate/base': 1.6772681473880406e-05, 'epoch': 0.48}) +[2026-07-27 06:10:45,202][starVLA.training.train_starvla][INFO] - Step 3992, Loss: {'train/loss': 0.16373011469841003, 'train/grad_norm_pre_clip': 4.606662273406982, 'timing/data': 0.00018106075003743172, 'timing/model': 0.46517752297222614, 'learning_rate/action_model': 6.7062092890009e-05, 'learning_rate/action_query_proj': 6.7062092890009e-05, 'learning_rate/base': 1.676552322250225e-05, 'epoch': 0.48}) +[2026-07-27 06:10:50,791][starVLA.training.train_starvla][INFO] - Step 3993, Loss: {'train/loss': 0.06344043463468552, 'train/grad_norm_pre_clip': 1.9321935176849365, 'timing/data': 0.0002254289574921131, 'timing/model': 0.46242851996794343, 'learning_rate/action_model': 6.703345393822066e-05, 'learning_rate/action_query_proj': 6.703345393822066e-05, 'learning_rate/base': 1.6758363484555166e-05, 'epoch': 0.48}) +[2026-07-27 06:10:56,399][starVLA.training.train_starvla][INFO] - Step 3994, Loss: {'train/loss': 0.03583521395921707, 'train/grad_norm_pre_clip': 1.6617989540100098, 'timing/data': 0.0001711072400212288, 'timing/model': 0.4622669252566993, 'learning_rate/action_model': 6.700480905146278e-05, 'learning_rate/action_query_proj': 6.700480905146278e-05, 'learning_rate/base': 1.6751202262865696e-05, 'epoch': 0.48}) +[2026-07-27 06:11:02,251][starVLA.training.train_starvla][INFO] - Step 3995, Loss: {'train/loss': 0.057956013828516006, 'train/grad_norm_pre_clip': 2.589043617248535, 'timing/data': 0.000168731901794672, 'timing/model': 0.46424558525905013, 'learning_rate/action_model': 6.697615824104392e-05, 'learning_rate/action_query_proj': 6.697615824104392e-05, 'learning_rate/base': 1.674403956026098e-05, 'epoch': 0.48}) +[2026-07-27 06:11:07,865][starVLA.training.train_starvla][INFO] - Step 3996, Loss: {'train/loss': 0.10767523944377899, 'train/grad_norm_pre_clip': 2.8030786514282227, 'timing/data': 0.00017432216554880142, 'timing/model': 0.4604739723727107, 'learning_rate/action_model': 6.694750151827497e-05, 'learning_rate/action_query_proj': 6.694750151827497e-05, 'learning_rate/base': 1.6736875379568742e-05, 'epoch': 0.48}) +[2026-07-27 06:11:13,595][starVLA.training.train_starvla][INFO] - Step 3997, Loss: {'train/loss': 0.09230130165815353, 'train/grad_norm_pre_clip': 2.376394748687744, 'timing/data': 0.0001798570156097412, 'timing/model': 0.4684448759071529, 'learning_rate/action_model': 6.691883889446912e-05, 'learning_rate/action_query_proj': 6.691883889446912e-05, 'learning_rate/base': 1.672970972361728e-05, 'epoch': 0.48}) +[2026-07-27 06:11:19,318][starVLA.training.train_starvla][INFO] - Step 3998, Loss: {'train/loss': 0.029455404728651047, 'train/grad_norm_pre_clip': 2.035553455352783, 'timing/data': 0.00021264422684907913, 'timing/model': 0.4651750889606774, 'learning_rate/action_model': 6.689017038094197e-05, 'learning_rate/action_query_proj': 6.689017038094197e-05, 'learning_rate/base': 1.6722542595235493e-05, 'epoch': 0.49}) +[2026-07-27 06:11:24,883][starVLA.training.train_starvla][INFO] - Step 3999, Loss: {'train/loss': 0.01768425852060318, 'train/grad_norm_pre_clip': 1.8429343700408936, 'timing/data': 0.00018641026690602303, 'timing/model': 0.4560074587352574, 'learning_rate/action_model': 6.686149598901136e-05, 'learning_rate/action_query_proj': 6.686149598901136e-05, 'learning_rate/base': 1.671537399725284e-05, 'epoch': 0.49}) +[2026-07-27 06:11:30,472][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 4000 +[2026-07-27 06:11:30,473][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 4000 +[2026-07-27 06:11:30,473][starVLA.training.train_starvla][INFO] - Step 4000, Loss: {'train/loss': 0.06767380237579346, 'train/grad_norm_pre_clip': 2.7827541828155518, 'timing/data': 0.00017762836068868637, 'timing/model': 0.4614355228841305, 'learning_rate/action_model': 6.683281572999748e-05, 'learning_rate/action_query_proj': 6.683281572999748e-05, 'learning_rate/base': 1.670820393249937e-05, 'epoch': 0.49}) +[2026-07-27 06:11:30,477][accelerate.accelerator][INFO] - Saving current state to /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state +[2026-07-27 06:11:30,477][accelerate.accelerator][INFO] - Saving DeepSpeed Model and Optimizer +[2026-07-27 06:12:17,152][accelerate.accelerator][INFO] - DeepSpeed Model and Optimizer saved to output dir /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state/pytorch_model +[2026-07-27 06:12:17,152][accelerate.checkpointing][INFO] - Sampler state for dataloader 0 saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state/sampler.bin +[2026-07-27 06:12:17,158][accelerate.checkpointing][INFO] - Random states saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state/random_states_0.pkl +[2026-07-27 06:13:03,539][starVLA.training.rl_games.checkpoint_sync][INFO] - HF checkpoint sync disabled; skipping upload for step 4000 +[2026-07-27 06:13:03,540][starVLA.training.train_starvla][INFO] - 📊 Saving accessed configuration... +[2026-07-27 06:13:03,553][starVLA.training.train_starvla][INFO] - ✅ Configuration files saved +[2026-07-27 06:13:09,208][starVLA.training.train_starvla][INFO] - Step 4001, Loss: {'train/loss': 0.17248815298080444, 'train/grad_norm_pre_clip': 4.143019676208496, 'timing/data': 0.00017005391418933868, 'timing/model': 0.463431513402611, 'learning_rate/action_model': 6.680412961522287e-05, 'learning_rate/action_query_proj': 6.680412961522287e-05, 'learning_rate/base': 1.6701032403805718e-05, 'epoch': 0.49}) +[2026-07-27 06:13:14,865][starVLA.training.train_starvla][INFO] - Step 4002, Loss: {'train/loss': 0.24621380865573883, 'train/grad_norm_pre_clip': 5.216230392456055, 'timing/data': 0.00017529074102640152, 'timing/model': 0.4667379823513329, 'learning_rate/action_model': 6.677543765601234e-05, 'learning_rate/action_query_proj': 6.677543765601234e-05, 'learning_rate/base': 1.6693859414003085e-05, 'epoch': 0.49}) +[2026-07-27 06:13:20,529][starVLA.training.train_starvla][INFO] - Step 4003, Loss: {'train/loss': 0.3633016347885132, 'train/grad_norm_pre_clip': 3.965766668319702, 'timing/data': 0.00017017684876918793, 'timing/model': 0.46792099019512534, 'learning_rate/action_model': 6.6746739863693e-05, 'learning_rate/action_query_proj': 6.6746739863693e-05, 'learning_rate/base': 1.668668496592325e-05, 'epoch': 0.49}) +[2026-07-27 06:13:26,189][starVLA.training.train_starvla][INFO] - Step 4004, Loss: {'train/loss': 0.20576642453670502, 'train/grad_norm_pre_clip': 4.866938591003418, 'timing/data': 0.000177798792719841, 'timing/model': 0.46908540185540915, 'learning_rate/action_model': 6.671803624959436e-05, 'learning_rate/action_query_proj': 6.671803624959436e-05, 'learning_rate/base': 1.667950906239859e-05, 'epoch': 0.49}) +[2026-07-27 06:13:31,860][starVLA.training.train_starvla][INFO] - Step 4005, Loss: {'train/loss': 0.16932959854602814, 'train/grad_norm_pre_clip': 3.1796693801879883, 'timing/data': 0.0001710178330540657, 'timing/model': 0.4682580870576203, 'learning_rate/action_model': 6.668932682504805e-05, 'learning_rate/action_query_proj': 6.668932682504805e-05, 'learning_rate/base': 1.6672331706262012e-05, 'epoch': 0.49}) +[2026-07-27 06:13:37,521][starVLA.training.train_starvla][INFO] - Step 4006, Loss: {'train/loss': 0.08644936978816986, 'train/grad_norm_pre_clip': 3.5030229091644287, 'timing/data': 0.0001772632822394371, 'timing/model': 0.4700774531811476, 'learning_rate/action_model': 6.666061160138816e-05, 'learning_rate/action_query_proj': 6.666061160138816e-05, 'learning_rate/base': 1.666515290034704e-05, 'epoch': 0.49}) +[2026-07-27 06:13:43,205][starVLA.training.train_starvla][INFO] - Step 4007, Loss: {'train/loss': 0.10955062508583069, 'train/grad_norm_pre_clip': 3.8284857273101807, 'timing/data': 0.00022812280803918839, 'timing/model': 0.474785921163857, 'learning_rate/action_model': 6.663189058995098e-05, 'learning_rate/action_query_proj': 6.663189058995098e-05, 'learning_rate/base': 1.6657972647487745e-05, 'epoch': 0.49}) +[2026-07-27 06:13:48,884][starVLA.training.train_starvla][INFO] - Step 4008, Loss: {'train/loss': 0.2296915203332901, 'train/grad_norm_pre_clip': 4.716300010681152, 'timing/data': 0.00017896760255098343, 'timing/model': 0.47776171611621976, 'learning_rate/action_model': 6.66031638020751e-05, 'learning_rate/action_query_proj': 6.66031638020751e-05, 'learning_rate/base': 1.6650790950518777e-05, 'epoch': 0.49}) +[2026-07-27 06:13:54,558][starVLA.training.train_starvla][INFO] - Step 4009, Loss: {'train/loss': 0.24096651375293732, 'train/grad_norm_pre_clip': 4.646292686462402, 'timing/data': 0.00017370004206895828, 'timing/model': 0.479814728256315, 'learning_rate/action_model': 6.657443124910146e-05, 'learning_rate/action_query_proj': 6.657443124910146e-05, 'learning_rate/base': 1.6643607812275364e-05, 'epoch': 0.49}) +[2026-07-27 06:14:00,248][starVLA.training.train_starvla][INFO] - Step 4010, Loss: {'train/loss': 0.2522292137145996, 'train/grad_norm_pre_clip': 5.078022003173828, 'timing/data': 0.0001737191341817379, 'timing/model': 0.481791574973613, 'learning_rate/action_model': 6.654569294237317e-05, 'learning_rate/action_query_proj': 6.654569294237317e-05, 'learning_rate/base': 1.6636423235593292e-05, 'epoch': 0.49}) +[2026-07-27 06:14:05,926][starVLA.training.train_starvla][INFO] - Step 4011, Loss: {'train/loss': 0.2367638647556305, 'train/grad_norm_pre_clip': 4.650909900665283, 'timing/data': 0.0001758979633450508, 'timing/model': 0.49119975604116917, 'learning_rate/action_model': 6.651694889323564e-05, 'learning_rate/action_query_proj': 6.651694889323564e-05, 'learning_rate/base': 1.662923722330891e-05, 'epoch': 0.49}) +[2026-07-27 06:14:11,590][starVLA.training.train_starvla][INFO] - Step 4012, Loss: {'train/loss': 0.21313904225826263, 'train/grad_norm_pre_clip': 4.383981704711914, 'timing/data': 0.0001790989190340042, 'timing/model': 0.48284399416297674, 'learning_rate/action_model': 6.648819911303662e-05, 'learning_rate/action_query_proj': 6.648819911303662e-05, 'learning_rate/base': 1.6622049778259156e-05, 'epoch': 0.49}) +[2026-07-27 06:14:17,262][starVLA.training.train_starvla][INFO] - Step 4013, Loss: {'train/loss': 0.1580139845609665, 'train/grad_norm_pre_clip': 3.5599913597106934, 'timing/data': 0.00025867391377687454, 'timing/model': 0.48391392128542066, 'learning_rate/action_model': 6.645944361312602e-05, 'learning_rate/action_query_proj': 6.645944361312602e-05, 'learning_rate/base': 1.6614860903281505e-05, 'epoch': 0.49}) +[2026-07-27 06:14:22,931][starVLA.training.train_starvla][INFO] - Step 4014, Loss: {'train/loss': 0.12800203263759613, 'train/grad_norm_pre_clip': 3.2752292156219482, 'timing/data': 0.00016883434727787971, 'timing/model': 0.49151923693716526, 'learning_rate/action_model': 6.643068240485608e-05, 'learning_rate/action_query_proj': 6.643068240485608e-05, 'learning_rate/base': 1.660767060121402e-05, 'epoch': 0.49}) +[2026-07-27 06:14:28,628][starVLA.training.train_starvla][INFO] - Step 4015, Loss: {'train/loss': 0.10740043222904205, 'train/grad_norm_pre_clip': 3.2312426567077637, 'timing/data': 0.00017565302550792694, 'timing/model': 0.4870835696347058, 'learning_rate/action_model': 6.640191549958126e-05, 'learning_rate/action_query_proj': 6.640191549958126e-05, 'learning_rate/base': 1.6600478874895315e-05, 'epoch': 0.49}) +[2026-07-27 06:14:34,327][starVLA.training.train_starvla][INFO] - Step 4016, Loss: {'train/loss': 0.13981851935386658, 'train/grad_norm_pre_clip': 4.744570255279541, 'timing/data': 0.00017205625772476196, 'timing/model': 0.4782636142335832, 'learning_rate/action_model': 6.63731429086583e-05, 'learning_rate/action_query_proj': 6.63731429086583e-05, 'learning_rate/base': 1.6593285727164576e-05, 'epoch': 0.49}) +[2026-07-27 06:14:40,071][starVLA.training.train_starvla][INFO] - Step 4017, Loss: {'train/loss': 0.13716599345207214, 'train/grad_norm_pre_clip': 3.5188236236572266, 'timing/data': 0.00023373588919639587, 'timing/model': 0.4666591491550207, 'learning_rate/action_model': 6.634436464344615e-05, 'learning_rate/action_query_proj': 6.634436464344615e-05, 'learning_rate/base': 1.6586091160861537e-05, 'epoch': 0.49}) +[2026-07-27 06:14:45,771][starVLA.training.train_starvla][INFO] - Step 4018, Loss: {'train/loss': 0.2098374217748642, 'train/grad_norm_pre_clip': 3.358170509338379, 'timing/data': 0.00017632916569709778, 'timing/model': 0.46523802215233445, 'learning_rate/action_model': 6.631558071530597e-05, 'learning_rate/action_query_proj': 6.631558071530597e-05, 'learning_rate/base': 1.657889517882649e-05, 'epoch': 0.49}) +[2026-07-27 06:14:51,462][starVLA.training.train_starvla][INFO] - Step 4019, Loss: {'train/loss': 0.19879187643527985, 'train/grad_norm_pre_clip': 4.168957233428955, 'timing/data': 0.00018452899530529976, 'timing/model': 0.4809431601315737, 'learning_rate/action_model': 6.628679113560127e-05, 'learning_rate/action_query_proj': 6.628679113560127e-05, 'learning_rate/base': 1.6571697783900317e-05, 'epoch': 0.49}) +[2026-07-27 06:14:57,127][starVLA.training.train_starvla][INFO] - Step 4020, Loss: {'train/loss': 0.18914654850959778, 'train/grad_norm_pre_clip': 2.3528554439544678, 'timing/data': 0.00018240977078676224, 'timing/model': 0.4863730762153864, 'learning_rate/action_model': 6.625799591569767e-05, 'learning_rate/action_query_proj': 6.625799591569767e-05, 'learning_rate/base': 1.656449897892442e-05, 'epoch': 0.49}) +[2026-07-27 06:15:02,804][starVLA.training.train_starvla][INFO] - Step 4021, Loss: {'train/loss': 0.21583259105682373, 'train/grad_norm_pre_clip': 4.4786787033081055, 'timing/data': 0.0001741941086947918, 'timing/model': 0.48313048714771867, 'learning_rate/action_model': 6.62291950669631e-05, 'learning_rate/action_query_proj': 6.62291950669631e-05, 'learning_rate/base': 1.6557298766740776e-05, 'epoch': 0.49}) +[2026-07-27 06:15:08,470][starVLA.training.train_starvla][INFO] - Step 4022, Loss: {'train/loss': 0.19960108399391174, 'train/grad_norm_pre_clip': 3.8325610160827637, 'timing/data': 0.00017770705744624138, 'timing/model': 0.4832889619283378, 'learning_rate/action_model': 6.620038860076768e-05, 'learning_rate/action_query_proj': 6.620038860076768e-05, 'learning_rate/base': 1.655009715019192e-05, 'epoch': 0.49}) +[2026-07-27 06:15:14,158][starVLA.training.train_starvla][INFO] - Step 4023, Loss: {'train/loss': 0.10544891655445099, 'train/grad_norm_pre_clip': 3.2023203372955322, 'timing/data': 0.00017354311421513557, 'timing/model': 0.4851978160440922, 'learning_rate/action_model': 6.617157652848371e-05, 'learning_rate/action_query_proj': 6.617157652848371e-05, 'learning_rate/base': 1.6542894132120928e-05, 'epoch': 0.49}) +[2026-07-27 06:15:19,809][starVLA.training.train_starvla][INFO] - Step 4024, Loss: {'train/loss': 0.09391649067401886, 'train/grad_norm_pre_clip': 3.5172314643859863, 'timing/data': 0.00017793988808989525, 'timing/model': 0.4787057489156723, 'learning_rate/action_model': 6.614275886148575e-05, 'learning_rate/action_query_proj': 6.614275886148575e-05, 'learning_rate/base': 1.653568971537144e-05, 'epoch': 0.49}) +[2026-07-27 06:15:25,474][starVLA.training.train_starvla][INFO] - Step 4025, Loss: {'train/loss': 0.1298195868730545, 'train/grad_norm_pre_clip': 4.149613380432129, 'timing/data': 0.00017327768728137016, 'timing/model': 0.48722741985693574, 'learning_rate/action_model': 6.611393561115059e-05, 'learning_rate/action_query_proj': 6.611393561115059e-05, 'learning_rate/base': 1.6528483902787647e-05, 'epoch': 0.49}) +[2026-07-27 06:15:31,128][starVLA.training.train_starvla][INFO] - Step 4026, Loss: {'train/loss': 0.1685936450958252, 'train/grad_norm_pre_clip': 3.043426752090454, 'timing/data': 0.00018978118896484375, 'timing/model': 0.48321520211175084, 'learning_rate/action_model': 6.608510678885716e-05, 'learning_rate/action_query_proj': 6.608510678885716e-05, 'learning_rate/base': 1.652127669721429e-05, 'epoch': 0.49}) +[2026-07-27 06:15:36,775][starVLA.training.train_starvla][INFO] - Step 4027, Loss: {'train/loss': 0.19123747944831848, 'train/grad_norm_pre_clip': 3.642681121826172, 'timing/data': 0.00018182490020990372, 'timing/model': 0.48304813588038087, 'learning_rate/action_model': 6.605627240598665e-05, 'learning_rate/action_query_proj': 6.605627240598665e-05, 'learning_rate/base': 1.6514068101496662e-05, 'epoch': 0.49}) +[2026-07-27 06:15:42,438][starVLA.training.train_starvla][INFO] - Step 4028, Loss: {'train/loss': 0.3615468740463257, 'train/grad_norm_pre_clip': 4.833038806915283, 'timing/data': 0.000174596905708313, 'timing/model': 0.48393380269408226, 'learning_rate/action_model': 6.60274324739224e-05, 'learning_rate/action_query_proj': 6.60274324739224e-05, 'learning_rate/base': 1.65068581184806e-05, 'epoch': 0.49}) +[2026-07-27 06:15:48,091][starVLA.training.train_starvla][INFO] - Step 4029, Loss: {'train/loss': 0.2713180184364319, 'train/grad_norm_pre_clip': 4.362368106842041, 'timing/data': 0.00017690099775791168, 'timing/model': 0.48515633028000593, 'learning_rate/action_model': 6.599858700404996e-05, 'learning_rate/action_query_proj': 6.599858700404996e-05, 'learning_rate/base': 1.649964675101249e-05, 'epoch': 0.49}) +[2026-07-27 06:15:53,753][starVLA.training.train_starvla][INFO] - Step 4030, Loss: {'train/loss': 0.13606500625610352, 'train/grad_norm_pre_clip': 2.898505687713623, 'timing/data': 0.00017822766676545143, 'timing/model': 0.4854900580830872, 'learning_rate/action_model': 6.596973600775704e-05, 'learning_rate/action_query_proj': 6.596973600775704e-05, 'learning_rate/base': 1.649243400193926e-05, 'epoch': 0.49}) +[2026-07-27 06:15:59,437][starVLA.training.train_starvla][INFO] - Step 4031, Loss: {'train/loss': 0.11206705123186111, 'train/grad_norm_pre_clip': 2.9225003719329834, 'timing/data': 0.00017363205552101135, 'timing/model': 0.4871883452869952, 'learning_rate/action_model': 6.594087949643362e-05, 'learning_rate/action_query_proj': 6.594087949643362e-05, 'learning_rate/base': 1.6485219874108404e-05, 'epoch': 0.49}) +[2026-07-27 06:16:05,113][starVLA.training.train_starvla][INFO] - Step 4032, Loss: {'train/loss': 0.2074447125196457, 'train/grad_norm_pre_clip': 3.1378097534179688, 'timing/data': 0.0001744288019835949, 'timing/model': 0.4831330650486052, 'learning_rate/action_model': 6.591201748147173e-05, 'learning_rate/action_query_proj': 6.591201748147173e-05, 'learning_rate/base': 1.6478004370367932e-05, 'epoch': 0.49}) +[2026-07-27 06:16:11,243][starVLA.training.train_starvla][INFO] - Step 4033, Loss: {'train/loss': 0.12127033621072769, 'train/grad_norm_pre_clip': 2.734177827835083, 'timing/data': 0.00018769828602671623, 'timing/model': 0.7036179369315505, 'learning_rate/action_model': 6.588314997426566e-05, 'learning_rate/action_query_proj': 6.588314997426566e-05, 'learning_rate/base': 1.6470787493566416e-05, 'epoch': 0.49}) +[2026-07-27 06:16:16,925][starVLA.training.train_starvla][INFO] - Step 4034, Loss: {'train/loss': 0.1760183721780777, 'train/grad_norm_pre_clip': 3.294203758239746, 'timing/data': 0.00017868028953671455, 'timing/model': 0.49139939108863473, 'learning_rate/action_model': 6.585427698621188e-05, 'learning_rate/action_query_proj': 6.585427698621188e-05, 'learning_rate/base': 1.646356924655297e-05, 'epoch': 0.49}) +[2026-07-27 06:16:22,584][starVLA.training.train_starvla][INFO] - Step 4035, Loss: {'train/loss': 0.2008940577507019, 'train/grad_norm_pre_clip': 3.598299980163574, 'timing/data': 0.00017974618822336197, 'timing/model': 0.4844985823146999, 'learning_rate/action_model': 6.582539852870894e-05, 'learning_rate/action_query_proj': 6.582539852870894e-05, 'learning_rate/base': 1.6456349632177234e-05, 'epoch': 0.49}) +[2026-07-27 06:16:28,247][starVLA.training.train_starvla][INFO] - Step 4036, Loss: {'train/loss': 0.18720492720603943, 'train/grad_norm_pre_clip': 3.356241464614868, 'timing/data': 0.00017847120761871338, 'timing/model': 0.4903714060783386, 'learning_rate/action_model': 6.579651461315761e-05, 'learning_rate/action_query_proj': 6.579651461315761e-05, 'learning_rate/base': 1.6449128653289402e-05, 'epoch': 0.49}) +[2026-07-27 06:16:33,922][starVLA.training.train_starvla][INFO] - Step 4037, Loss: {'train/loss': 0.05843695253133774, 'train/grad_norm_pre_clip': 1.8680133819580078, 'timing/data': 0.0001734779216349125, 'timing/model': 0.48461113683879375, 'learning_rate/action_model': 6.576762525096078e-05, 'learning_rate/action_query_proj': 6.576762525096078e-05, 'learning_rate/base': 1.6441906312740196e-05, 'epoch': 0.49}) +[2026-07-27 06:16:39,585][starVLA.training.train_starvla][INFO] - Step 4038, Loss: {'train/loss': 0.16249528527259827, 'train/grad_norm_pre_clip': 2.246373414993286, 'timing/data': 0.00017117895185947418, 'timing/model': 0.49213297478854656, 'learning_rate/action_model': 6.573873045352357e-05, 'learning_rate/action_query_proj': 6.573873045352357e-05, 'learning_rate/base': 1.6434682613380892e-05, 'epoch': 0.49}) +[2026-07-27 06:16:45,263][starVLA.training.train_starvla][INFO] - Step 4039, Loss: {'train/loss': 0.1805250197649002, 'train/grad_norm_pre_clip': 2.890058755874634, 'timing/data': 0.00017478596419095993, 'timing/model': 0.48950442811474204, 'learning_rate/action_model': 6.570983023225314e-05, 'learning_rate/action_query_proj': 6.570983023225314e-05, 'learning_rate/base': 1.6427457558063284e-05, 'epoch': 0.49}) +[2026-07-27 06:16:50,937][starVLA.training.train_starvla][INFO] - Step 4040, Loss: {'train/loss': 0.09069807827472687, 'train/grad_norm_pre_clip': 2.5959925651550293, 'timing/data': 0.00017139781266450882, 'timing/model': 0.482487210072577, 'learning_rate/action_model': 6.568092459855886e-05, 'learning_rate/action_query_proj': 6.568092459855886e-05, 'learning_rate/base': 1.6420231149639714e-05, 'epoch': 0.49}) +[2026-07-27 06:16:56,600][starVLA.training.train_starvla][INFO] - Step 4041, Loss: {'train/loss': 0.23114818334579468, 'train/grad_norm_pre_clip': 4.930514812469482, 'timing/data': 0.0001763547770678997, 'timing/model': 0.4844245952554047, 'learning_rate/action_model': 6.56520135638522e-05, 'learning_rate/action_query_proj': 6.56520135638522e-05, 'learning_rate/base': 1.641300339096305e-05, 'epoch': 0.49}) +[2026-07-27 06:17:02,458][starVLA.training.train_starvla][INFO] - Step 4042, Loss: {'train/loss': 0.1341732293367386, 'train/grad_norm_pre_clip': 2.318697690963745, 'timing/data': 0.00017984723672270775, 'timing/model': 0.4791924641467631, 'learning_rate/action_model': 6.562309713954682e-05, 'learning_rate/action_query_proj': 6.562309713954682e-05, 'learning_rate/base': 1.6405774284886705e-05, 'epoch': 0.49}) +[2026-07-27 06:17:08,122][starVLA.training.train_starvla][INFO] - Step 4043, Loss: {'train/loss': 0.14607207477092743, 'train/grad_norm_pre_clip': 3.0369882583618164, 'timing/data': 0.00017602089792490005, 'timing/model': 0.47943495493382215, 'learning_rate/action_model': 6.559417533705841e-05, 'learning_rate/action_query_proj': 6.559417533705841e-05, 'learning_rate/base': 1.6398543834264603e-05, 'epoch': 0.49}) +[2026-07-27 06:17:13,781][starVLA.training.train_starvla][INFO] - Step 4044, Loss: {'train/loss': 0.1327144354581833, 'train/grad_norm_pre_clip': 3.1224594116210938, 'timing/data': 0.00017351610586047173, 'timing/model': 0.4838463068008423, 'learning_rate/action_model': 6.55652481678049e-05, 'learning_rate/action_query_proj': 6.55652481678049e-05, 'learning_rate/base': 1.6391312041951224e-05, 'epoch': 0.49}) +[2026-07-27 06:17:19,455][starVLA.training.train_starvla][INFO] - Step 4045, Loss: {'train/loss': 0.12948060035705566, 'train/grad_norm_pre_clip': 2.8721423149108887, 'timing/data': 0.0001747780479490757, 'timing/model': 0.4817914399318397, 'learning_rate/action_model': 6.553631564320621e-05, 'learning_rate/action_query_proj': 6.553631564320621e-05, 'learning_rate/base': 1.6384078910801553e-05, 'epoch': 0.49}) +[2026-07-27 06:17:25,127][starVLA.training.train_starvla][INFO] - Step 4046, Loss: {'train/loss': 0.1726733148097992, 'train/grad_norm_pre_clip': 3.556267738342285, 'timing/data': 0.00017323018983006477, 'timing/model': 0.4796090070158243, 'learning_rate/action_model': 6.550737777468451e-05, 'learning_rate/action_query_proj': 6.550737777468451e-05, 'learning_rate/base': 1.6376844443671127e-05, 'epoch': 0.49}) +[2026-07-27 06:17:30,793][starVLA.training.train_starvla][INFO] - Step 4047, Loss: {'train/loss': 0.16473963856697083, 'train/grad_norm_pre_clip': 2.9171643257141113, 'timing/data': 0.00017447490245103836, 'timing/model': 0.4768692208454013, 'learning_rate/action_model': 6.547843457366396e-05, 'learning_rate/action_query_proj': 6.547843457366396e-05, 'learning_rate/base': 1.636960864341599e-05, 'epoch': 0.49}) +[2026-07-27 06:17:36,459][starVLA.training.train_starvla][INFO] - Step 4048, Loss: {'train/loss': 0.1491302251815796, 'train/grad_norm_pre_clip': 3.4345264434814453, 'timing/data': 0.00019431021064519882, 'timing/model': 0.48462543776258826, 'learning_rate/action_model': 6.54494860515709e-05, 'learning_rate/action_query_proj': 6.54494860515709e-05, 'learning_rate/base': 1.6362371512892726e-05, 'epoch': 0.49}) +[2026-07-27 06:17:42,140][starVLA.training.train_starvla][INFO] - Step 4049, Loss: {'train/loss': 0.10758529603481293, 'train/grad_norm_pre_clip': 3.405510187149048, 'timing/data': 0.0001792418770492077, 'timing/model': 0.4933548578992486, 'learning_rate/action_model': 6.542053221983374e-05, 'learning_rate/action_query_proj': 6.542053221983374e-05, 'learning_rate/base': 1.6355133054958434e-05, 'epoch': 0.49}) +[2026-07-27 06:17:47,805][starVLA.training.train_starvla][INFO] - Step 4050, Loss: {'train/loss': 0.3222961723804474, 'train/grad_norm_pre_clip': 3.9401333332061768, 'timing/data': 0.00019505806267261505, 'timing/model': 0.4829388768412173, 'learning_rate/action_model': 6.539157308988302e-05, 'learning_rate/action_query_proj': 6.539157308988302e-05, 'learning_rate/base': 1.6347893272470754e-05, 'epoch': 0.49}) +[2026-07-27 06:17:53,481][starVLA.training.train_starvla][INFO] - Step 4051, Loss: {'train/loss': 0.2840287685394287, 'train/grad_norm_pre_clip': 4.586310386657715, 'timing/data': 0.00017758691683411598, 'timing/model': 0.48155173426494, 'learning_rate/action_model': 6.536260867315131e-05, 'learning_rate/action_query_proj': 6.536260867315131e-05, 'learning_rate/base': 1.6340652168287828e-05, 'epoch': 0.49}) +[2026-07-27 06:17:59,159][starVLA.training.train_starvla][INFO] - Step 4052, Loss: {'train/loss': 0.1656242460012436, 'train/grad_norm_pre_clip': 3.7990875244140625, 'timing/data': 0.00019070319831371307, 'timing/model': 0.47978001506999135, 'learning_rate/action_model': 6.533363898107333e-05, 'learning_rate/action_query_proj': 6.533363898107333e-05, 'learning_rate/base': 1.6333409745268332e-05, 'epoch': 0.49}) +[2026-07-27 06:18:04,838][starVLA.training.train_starvla][INFO] - Step 4053, Loss: {'train/loss': 0.13390597701072693, 'train/grad_norm_pre_clip': 2.194173812866211, 'timing/data': 0.00017634034156799316, 'timing/model': 0.48227311996743083, 'learning_rate/action_model': 6.530466402508581e-05, 'learning_rate/action_query_proj': 6.530466402508581e-05, 'learning_rate/base': 1.6326166006271452e-05, 'epoch': 0.49}) +[2026-07-27 06:18:10,545][starVLA.training.train_starvla][INFO] - Step 4054, Loss: {'train/loss': 0.18451614677906036, 'train/grad_norm_pre_clip': 3.916147232055664, 'timing/data': 0.00017655221745371819, 'timing/model': 0.4814504259265959, 'learning_rate/action_model': 6.527568381662769e-05, 'learning_rate/action_query_proj': 6.527568381662769e-05, 'learning_rate/base': 1.631892095415692e-05, 'epoch': 0.49}) +[2026-07-27 06:18:16,228][starVLA.training.train_starvla][INFO] - Step 4055, Loss: {'train/loss': 0.1793452948331833, 'train/grad_norm_pre_clip': 3.0166842937469482, 'timing/data': 0.00017787283286452293, 'timing/model': 0.4917202088981867, 'learning_rate/action_model': 6.524669836713981e-05, 'learning_rate/action_query_proj': 6.524669836713981e-05, 'learning_rate/base': 1.6311674591784953e-05, 'epoch': 0.49}) +[2026-07-27 06:18:22,035][starVLA.training.train_starvla][INFO] - Step 4056, Loss: {'train/loss': 0.18348219990730286, 'train/grad_norm_pre_clip': 3.2546591758728027, 'timing/data': 0.00017656898126006126, 'timing/model': 0.5694993892684579, 'learning_rate/action_model': 6.52177076880652e-05, 'learning_rate/action_query_proj': 6.52177076880652e-05, 'learning_rate/base': 1.63044269220163e-05, 'epoch': 0.49}) +[2026-07-27 06:18:27,809][starVLA.training.train_starvla][INFO] - Step 4057, Loss: {'train/loss': 0.22911857068538666, 'train/grad_norm_pre_clip': 3.1517984867095947, 'timing/data': 0.0001742192544043064, 'timing/model': 0.48199185682460666, 'learning_rate/action_model': 6.518871179084895e-05, 'learning_rate/action_query_proj': 6.518871179084895e-05, 'learning_rate/base': 1.6297177947712236e-05, 'epoch': 0.49}) +[2026-07-27 06:18:33,527][starVLA.training.train_starvla][INFO] - Step 4058, Loss: {'train/loss': 0.11408635973930359, 'train/grad_norm_pre_clip': 2.6672818660736084, 'timing/data': 0.00017801811918616295, 'timing/model': 0.482746581081301, 'learning_rate/action_model': 6.515971068693812e-05, 'learning_rate/action_query_proj': 6.515971068693812e-05, 'learning_rate/base': 1.628992767173453e-05, 'epoch': 0.49}) +[2026-07-27 06:18:39,239][starVLA.training.train_starvla][INFO] - Step 4059, Loss: {'train/loss': 0.13456058502197266, 'train/grad_norm_pre_clip': 3.2574594020843506, 'timing/data': 0.00017975596711039543, 'timing/model': 0.48061117995530367, 'learning_rate/action_model': 6.513070438778194e-05, 'learning_rate/action_query_proj': 6.513070438778194e-05, 'learning_rate/base': 1.6282676096945486e-05, 'epoch': 0.49}) +[2026-07-27 06:18:44,972][starVLA.training.train_starvla][INFO] - Step 4060, Loss: {'train/loss': 0.3396301865577698, 'train/grad_norm_pre_clip': 4.76434326171875, 'timing/data': 0.00017736107110977173, 'timing/model': 0.48981473920866847, 'learning_rate/action_model': 6.510169290483163e-05, 'learning_rate/action_query_proj': 6.510169290483163e-05, 'learning_rate/base': 1.6275423226207907e-05, 'epoch': 0.49}) +[2026-07-27 06:18:50,689][starVLA.training.train_starvla][INFO] - Step 4061, Loss: {'train/loss': 0.2987614870071411, 'train/grad_norm_pre_clip': 4.120508193969727, 'timing/data': 0.00017572706565260887, 'timing/model': 0.48332351027056575, 'learning_rate/action_model': 6.507267624954042e-05, 'learning_rate/action_query_proj': 6.507267624954042e-05, 'learning_rate/base': 1.6268169062385105e-05, 'epoch': 0.49}) +[2026-07-27 06:18:56,412][starVLA.training.train_starvla][INFO] - Step 4062, Loss: {'train/loss': 0.2582453489303589, 'train/grad_norm_pre_clip': 4.124264240264893, 'timing/data': 0.00017781788483262062, 'timing/model': 0.4895765879191458, 'learning_rate/action_model': 6.504365443336368e-05, 'learning_rate/action_query_proj': 6.504365443336368e-05, 'learning_rate/base': 1.626091360834092e-05, 'epoch': 0.49}) +[2026-07-27 06:19:02,100][starVLA.training.train_starvla][INFO] - Step 4063, Loss: {'train/loss': 0.21799799799919128, 'train/grad_norm_pre_clip': 4.508054256439209, 'timing/data': 0.0001732013188302517, 'timing/model': 0.4828933300450444, 'learning_rate/action_model': 6.501462746775874e-05, 'learning_rate/action_query_proj': 6.501462746775874e-05, 'learning_rate/base': 1.6253656866939685e-05, 'epoch': 0.49}) +[2026-07-27 06:19:07,810][starVLA.training.train_starvla][INFO] - Step 4064, Loss: {'train/loss': 0.14093594253063202, 'train/grad_norm_pre_clip': 3.054060459136963, 'timing/data': 0.00017345231026411057, 'timing/model': 0.4823004030622542, 'learning_rate/action_model': 6.498559536418498e-05, 'learning_rate/action_query_proj': 6.498559536418498e-05, 'learning_rate/base': 1.6246398841046246e-05, 'epoch': 0.49}) +[2026-07-27 06:19:13,527][starVLA.training.train_starvla][INFO] - Step 4065, Loss: {'train/loss': 0.10995577275753021, 'train/grad_norm_pre_clip': 2.922163486480713, 'timing/data': 0.0001838509924709797, 'timing/model': 0.49149242090061307, 'learning_rate/action_model': 6.495655813410384e-05, 'learning_rate/action_query_proj': 6.495655813410384e-05, 'learning_rate/base': 1.623913953352596e-05, 'epoch': 0.49}) +[2026-07-27 06:19:19,255][starVLA.training.train_starvla][INFO] - Step 4066, Loss: {'train/loss': 0.1941065788269043, 'train/grad_norm_pre_clip': 2.745961904525757, 'timing/data': 0.0001749158836901188, 'timing/model': 0.4844562681391835, 'learning_rate/action_model': 6.49275157889787e-05, 'learning_rate/action_query_proj': 6.49275157889787e-05, 'learning_rate/base': 1.6231878947244676e-05, 'epoch': 0.49}) +[2026-07-27 06:19:24,955][starVLA.training.train_starvla][INFO] - Step 4067, Loss: {'train/loss': 0.09158462285995483, 'train/grad_norm_pre_clip': 2.192847967147827, 'timing/data': 0.00018590176478028297, 'timing/model': 0.48185379384085536, 'learning_rate/action_model': 6.48984683402751e-05, 'learning_rate/action_query_proj': 6.48984683402751e-05, 'learning_rate/base': 1.6224617085068776e-05, 'epoch': 0.49}) +[2026-07-27 06:19:30,655][starVLA.training.train_starvla][INFO] - Step 4068, Loss: {'train/loss': 0.11336018890142441, 'train/grad_norm_pre_clip': 3.3806426525115967, 'timing/data': 0.00017468677833676338, 'timing/model': 0.48226175270974636, 'learning_rate/action_model': 6.486941579946046e-05, 'learning_rate/action_query_proj': 6.486941579946046e-05, 'learning_rate/base': 1.6217353949865115e-05, 'epoch': 0.49}) +[2026-07-27 06:19:36,374][starVLA.training.train_starvla][INFO] - Step 4069, Loss: {'train/loss': 0.3558765947818756, 'train/grad_norm_pre_clip': 5.592012405395508, 'timing/data': 0.00019829720258712769, 'timing/model': 0.48918793769553304, 'learning_rate/action_model': 6.484035817800427e-05, 'learning_rate/action_query_proj': 6.484035817800427e-05, 'learning_rate/base': 1.621008954450107e-05, 'epoch': 0.49}) +[2026-07-27 06:19:42,070][starVLA.training.train_starvla][INFO] - Step 4070, Loss: {'train/loss': 0.17181074619293213, 'train/grad_norm_pre_clip': 3.5127062797546387, 'timing/data': 0.00017440970987081528, 'timing/model': 0.4783661919645965, 'learning_rate/action_model': 6.481129548737803e-05, 'learning_rate/action_query_proj': 6.481129548737803e-05, 'learning_rate/base': 1.6202823871844507e-05, 'epoch': 0.49}) +[2026-07-27 06:19:47,770][starVLA.training.train_starvla][INFO] - Step 4071, Loss: {'train/loss': 0.19869761168956757, 'train/grad_norm_pre_clip': 3.1882052421569824, 'timing/data': 0.00017862394452095032, 'timing/model': 0.4775670268572867, 'learning_rate/action_model': 6.478222773905523e-05, 'learning_rate/action_query_proj': 6.478222773905523e-05, 'learning_rate/base': 1.6195556934763806e-05, 'epoch': 0.49}) +[2026-07-27 06:19:53,439][starVLA.training.train_starvla][INFO] - Step 4072, Loss: {'train/loss': 0.11140023916959763, 'train/grad_norm_pre_clip': 2.428440809249878, 'timing/data': 0.00018348870798945427, 'timing/model': 0.4742823061533272, 'learning_rate/action_model': 6.475315494451133e-05, 'learning_rate/action_query_proj': 6.475315494451133e-05, 'learning_rate/base': 1.6188288736127833e-05, 'epoch': 0.49}) +[2026-07-27 06:19:59,102][starVLA.training.train_starvla][INFO] - Step 4073, Loss: {'train/loss': 0.19372442364692688, 'train/grad_norm_pre_clip': 3.102933168411255, 'timing/data': 0.00017072539776563644, 'timing/model': 0.4903210490010679, 'learning_rate/action_model': 6.472407711522383e-05, 'learning_rate/action_query_proj': 6.472407711522383e-05, 'learning_rate/base': 1.6181019278805958e-05, 'epoch': 0.49}) +[2026-07-27 06:20:04,767][starVLA.training.train_starvla][INFO] - Step 4074, Loss: {'train/loss': 0.1747017800807953, 'train/grad_norm_pre_clip': 3.7771055698394775, 'timing/data': 0.0001728883944451809, 'timing/model': 0.4796735681593418, 'learning_rate/action_model': 6.469499426267221e-05, 'learning_rate/action_query_proj': 6.469499426267221e-05, 'learning_rate/base': 1.6173748565668052e-05, 'epoch': 0.49}) +[2026-07-27 06:20:10,424][starVLA.training.train_starvla][INFO] - Step 4075, Loss: {'train/loss': 0.18850639462471008, 'train/grad_norm_pre_clip': 4.3041229248046875, 'timing/data': 0.00018588872626423836, 'timing/model': 0.48061156226322055, 'learning_rate/action_model': 6.46659063983379e-05, 'learning_rate/action_query_proj': 6.46659063983379e-05, 'learning_rate/base': 1.6166476599584475e-05, 'epoch': 0.49}) +[2026-07-27 06:20:16,062][starVLA.training.train_starvla][INFO] - Step 4076, Loss: {'train/loss': 0.20899167656898499, 'train/grad_norm_pre_clip': 3.3922860622406006, 'timing/data': 0.00017575128003954887, 'timing/model': 0.47966735903173685, 'learning_rate/action_model': 6.463681353370433e-05, 'learning_rate/action_query_proj': 6.463681353370433e-05, 'learning_rate/base': 1.6159203383426083e-05, 'epoch': 0.49}) +[2026-07-27 06:20:21,696][starVLA.training.train_starvla][INFO] - Step 4077, Loss: {'train/loss': 0.17476752400398254, 'train/grad_norm_pre_clip': 3.9547643661499023, 'timing/data': 0.0001759822480380535, 'timing/model': 0.47211705381050706, 'learning_rate/action_model': 6.46077156802569e-05, 'learning_rate/action_query_proj': 6.46077156802569e-05, 'learning_rate/base': 1.6151928920064226e-05, 'epoch': 0.49}) +[2026-07-27 06:20:27,305][starVLA.training.train_starvla][INFO] - Step 4078, Loss: {'train/loss': 0.17453092336654663, 'train/grad_norm_pre_clip': 4.864283084869385, 'timing/data': 0.00018369918689131737, 'timing/model': 0.47082705795764923, 'learning_rate/action_model': 6.4578612849483e-05, 'learning_rate/action_query_proj': 6.4578612849483e-05, 'learning_rate/base': 1.614465321237075e-05, 'epoch': 0.49}) +[2026-07-27 06:20:32,922][starVLA.training.train_starvla][INFO] - Step 4079, Loss: {'train/loss': 0.19692182540893555, 'train/grad_norm_pre_clip': 3.929387331008911, 'timing/data': 0.00017549842596054077, 'timing/model': 0.4684546757489443, 'learning_rate/action_model': 6.454950505287196e-05, 'learning_rate/action_query_proj': 6.454950505287196e-05, 'learning_rate/base': 1.613737626321799e-05, 'epoch': 0.49}) +[2026-07-27 06:20:38,543][starVLA.training.train_starvla][INFO] - Step 4080, Loss: {'train/loss': 0.24299855530261993, 'train/grad_norm_pre_clip': 4.987820148468018, 'timing/data': 0.00017402227967977524, 'timing/model': 0.471372626721859, 'learning_rate/action_model': 6.452039230191506e-05, 'learning_rate/action_query_proj': 6.452039230191506e-05, 'learning_rate/base': 1.6130098075478765e-05, 'epoch': 0.49}) +[2026-07-27 06:20:44,163][starVLA.training.train_starvla][INFO] - Step 4081, Loss: {'train/loss': 0.11239317059516907, 'train/grad_norm_pre_clip': 2.8060033321380615, 'timing/data': 0.00018930388614535332, 'timing/model': 0.47848956706002355, 'learning_rate/action_model': 6.449127460810556e-05, 'learning_rate/action_query_proj': 6.449127460810556e-05, 'learning_rate/base': 1.612281865202639e-05, 'epoch': 0.5}) +[2026-07-27 06:20:49,778][starVLA.training.train_starvla][INFO] - Step 4082, Loss: {'train/loss': 0.18899306654930115, 'train/grad_norm_pre_clip': 3.2623448371887207, 'timing/data': 0.0001745428889989853, 'timing/model': 0.4710761629976332, 'learning_rate/action_model': 6.446215198293868e-05, 'learning_rate/action_query_proj': 6.446215198293868e-05, 'learning_rate/base': 1.611553799573467e-05, 'epoch': 0.5}) +[2026-07-27 06:20:55,707][starVLA.training.train_starvla][INFO] - Step 4083, Loss: {'train/loss': 0.20730581879615784, 'train/grad_norm_pre_clip': 4.482478618621826, 'timing/data': 0.00017704814672470093, 'timing/model': 0.4721257179044187, 'learning_rate/action_model': 6.443302443791153e-05, 'learning_rate/action_query_proj': 6.443302443791153e-05, 'learning_rate/base': 1.6108256109477883e-05, 'epoch': 0.5}) +[2026-07-27 06:21:01,343][starVLA.training.train_starvla][INFO] - Step 4084, Loss: {'train/loss': 0.17971904575824738, 'train/grad_norm_pre_clip': 3.327860116958618, 'timing/data': 0.00017468677833676338, 'timing/model': 0.473404360935092, 'learning_rate/action_model': 6.440389198452327e-05, 'learning_rate/action_query_proj': 6.440389198452327e-05, 'learning_rate/base': 1.6100972996130818e-05, 'epoch': 0.5}) +[2026-07-27 06:21:06,990][starVLA.training.train_starvla][INFO] - Step 4085, Loss: {'train/loss': 0.10355734825134277, 'train/grad_norm_pre_clip': 2.5876452922821045, 'timing/data': 0.0001723170280456543, 'timing/model': 0.4725914178416133, 'learning_rate/action_model': 6.437475463427489e-05, 'learning_rate/action_query_proj': 6.437475463427489e-05, 'learning_rate/base': 1.609368865856872e-05, 'epoch': 0.5}) +[2026-07-27 06:21:12,627][starVLA.training.train_starvla][INFO] - Step 4086, Loss: {'train/loss': 0.17343047261238098, 'train/grad_norm_pre_clip': 3.703221082687378, 'timing/data': 0.00017258897423744202, 'timing/model': 0.47068553511053324, 'learning_rate/action_model': 6.434561239866933e-05, 'learning_rate/action_query_proj': 6.434561239866933e-05, 'learning_rate/base': 1.608640309966733e-05, 'epoch': 0.5}) +[2026-07-27 06:21:18,264][starVLA.training.train_starvla][INFO] - Step 4087, Loss: {'train/loss': 0.136211097240448, 'train/grad_norm_pre_clip': 2.975879430770874, 'timing/data': 0.00017642928287386894, 'timing/model': 0.47235992969945073, 'learning_rate/action_model': 6.431646528921154e-05, 'learning_rate/action_query_proj': 6.431646528921154e-05, 'learning_rate/base': 1.6079116322302884e-05, 'epoch': 0.5}) +[2026-07-27 06:21:23,892][starVLA.training.train_starvla][INFO] - Step 4088, Loss: {'train/loss': 0.22982841730117798, 'train/grad_norm_pre_clip': 4.42694616317749, 'timing/data': 0.00024631107226014137, 'timing/model': 0.4701740159653127, 'learning_rate/action_model': 6.42873133174083e-05, 'learning_rate/action_query_proj': 6.42873133174083e-05, 'learning_rate/base': 1.6071828329352076e-05, 'epoch': 0.5}) +[2026-07-27 06:21:29,513][starVLA.training.train_starvla][INFO] - Step 4089, Loss: {'train/loss': 0.1643475443124771, 'train/grad_norm_pre_clip': 3.168745517730713, 'timing/data': 0.0001779738813638687, 'timing/model': 0.47179051814600825, 'learning_rate/action_model': 6.425815649476834e-05, 'learning_rate/action_query_proj': 6.425815649476834e-05, 'learning_rate/base': 1.6064539123692084e-05, 'epoch': 0.5}) +[2026-07-27 06:21:35,149][starVLA.training.train_starvla][INFO] - Step 4090, Loss: {'train/loss': 0.11846456676721573, 'train/grad_norm_pre_clip': 2.907611131668091, 'timing/data': 0.00017392123118042946, 'timing/model': 0.4720016489736736, 'learning_rate/action_model': 6.422899483280234e-05, 'learning_rate/action_query_proj': 6.422899483280234e-05, 'learning_rate/base': 1.6057248708200585e-05, 'epoch': 0.5}) +[2026-07-27 06:21:40,770][starVLA.training.train_starvla][INFO] - Step 4091, Loss: {'train/loss': 0.16166043281555176, 'train/grad_norm_pre_clip': 2.978325843811035, 'timing/data': 0.0001787613146007061, 'timing/model': 0.47859961399808526, 'learning_rate/action_model': 6.419982834302288e-05, 'learning_rate/action_query_proj': 6.419982834302288e-05, 'learning_rate/base': 1.604995708575572e-05, 'epoch': 0.5}) +[2026-07-27 06:21:46,431][starVLA.training.train_starvla][INFO] - Step 4092, Loss: {'train/loss': 0.14154072105884552, 'train/grad_norm_pre_clip': 3.266834020614624, 'timing/data': 0.00017490796744823456, 'timing/model': 0.47005436196923256, 'learning_rate/action_model': 6.417065703694435e-05, 'learning_rate/action_query_proj': 6.417065703694435e-05, 'learning_rate/base': 1.6042664259236086e-05, 'epoch': 0.5}) +[2026-07-27 06:21:52,049][starVLA.training.train_starvla][INFO] - Step 4093, Loss: {'train/loss': 0.2051762342453003, 'train/grad_norm_pre_clip': 3.7573964595794678, 'timing/data': 0.00017415685579180717, 'timing/model': 0.47760531306266785, 'learning_rate/action_model': 6.414148092608319e-05, 'learning_rate/action_query_proj': 6.414148092608319e-05, 'learning_rate/base': 1.6035370231520796e-05, 'epoch': 0.5}) +[2026-07-27 06:21:57,676][starVLA.training.train_starvla][INFO] - Step 4094, Loss: {'train/loss': 0.19835416972637177, 'train/grad_norm_pre_clip': 4.222321510314941, 'timing/data': 0.00017416290938854218, 'timing/model': 0.4784729862585664, 'learning_rate/action_model': 6.411230002195765e-05, 'learning_rate/action_query_proj': 6.411230002195765e-05, 'learning_rate/base': 1.6028075005489412e-05, 'epoch': 0.5}) +[2026-07-27 06:22:03,292][starVLA.training.train_starvla][INFO] - Step 4095, Loss: {'train/loss': 0.06082175299525261, 'train/grad_norm_pre_clip': 2.1469149589538574, 'timing/data': 0.00019257189705967903, 'timing/model': 0.4749866062775254, 'learning_rate/action_model': 6.408311433608787e-05, 'learning_rate/action_query_proj': 6.408311433608787e-05, 'learning_rate/base': 1.6020778584021967e-05, 'epoch': 0.5}) +[2026-07-27 06:22:08,893][starVLA.training.train_starvla][INFO] - Step 4096, Loss: {'train/loss': 0.14877256751060486, 'train/grad_norm_pre_clip': 2.985703706741333, 'timing/data': 0.00017535220831632614, 'timing/model': 0.47033429285511374, 'learning_rate/action_model': 6.405392387999591e-05, 'learning_rate/action_query_proj': 6.405392387999591e-05, 'learning_rate/base': 1.6013480969998977e-05, 'epoch': 0.5}) +[2026-07-27 06:22:14,498][starVLA.training.train_starvla][INFO] - Step 4097, Loss: {'train/loss': 0.0807403177022934, 'train/grad_norm_pre_clip': 1.9550668001174927, 'timing/data': 0.00017728609964251518, 'timing/model': 0.466035348828882, 'learning_rate/action_model': 6.402472866520571e-05, 'learning_rate/action_query_proj': 6.402472866520571e-05, 'learning_rate/base': 1.6006182166301428e-05, 'epoch': 0.5}) +[2026-07-27 06:22:20,097][starVLA.training.train_starvla][INFO] - Step 4098, Loss: {'train/loss': 0.22562134265899658, 'train/grad_norm_pre_clip': 4.28418493270874, 'timing/data': 0.0001725461333990097, 'timing/model': 0.46541097573935986, 'learning_rate/action_model': 6.399552870324306e-05, 'learning_rate/action_query_proj': 6.399552870324306e-05, 'learning_rate/base': 1.5998882175810766e-05, 'epoch': 0.5}) +[2026-07-27 06:22:25,949][starVLA.training.train_starvla][INFO] - Step 4099, Loss: {'train/loss': 0.11119144409894943, 'train/grad_norm_pre_clip': 2.7717669010162354, 'timing/data': 0.00017331494018435478, 'timing/model': 0.46485438710078597, 'learning_rate/action_model': 6.396632400563565e-05, 'learning_rate/action_query_proj': 6.396632400563565e-05, 'learning_rate/base': 1.5991581001408913e-05, 'epoch': 0.5}) +[2026-07-27 06:22:31,532][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 4100 +[2026-07-27 06:22:31,533][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 4100 +[2026-07-27 06:22:31,534][starVLA.training.train_starvla][INFO] - Step 4100, Loss: {'train/loss': 0.11995630711317062, 'train/grad_norm_pre_clip': 3.0040431022644043, 'timing/data': 0.00018931692466139793, 'timing/model': 0.45990511076524854, 'learning_rate/action_model': 6.393711458391304e-05, 'learning_rate/action_query_proj': 6.393711458391304e-05, 'learning_rate/base': 1.598427864597826e-05, 'epoch': 0.5}) +[2026-07-27 06:22:37,094][starVLA.training.train_starvla][INFO] - Step 4101, Loss: {'train/loss': 0.27352118492126465, 'train/grad_norm_pre_clip': 3.5623345375061035, 'timing/data': 0.0001723109744489193, 'timing/model': 0.4659222820773721, 'learning_rate/action_model': 6.390790044960663e-05, 'learning_rate/action_query_proj': 6.390790044960663e-05, 'learning_rate/base': 1.5976975112401656e-05, 'epoch': 0.5}) +[2026-07-27 06:22:42,675][starVLA.training.train_starvla][INFO] - Step 4102, Loss: {'train/loss': 0.14142775535583496, 'train/grad_norm_pre_clip': 3.6107826232910156, 'timing/data': 0.00017337454482913017, 'timing/model': 0.4611223000101745, 'learning_rate/action_model': 6.387868161424972e-05, 'learning_rate/action_query_proj': 6.387868161424972e-05, 'learning_rate/base': 1.596967040356243e-05, 'epoch': 0.5}) +[2026-07-27 06:22:48,461][starVLA.training.train_starvla][INFO] - Step 4103, Loss: {'train/loss': 0.13142120838165283, 'train/grad_norm_pre_clip': 2.8219335079193115, 'timing/data': 0.00018541468307375908, 'timing/model': 0.46263126423582435, 'learning_rate/action_model': 6.384945808937742e-05, 'learning_rate/action_query_proj': 6.384945808937742e-05, 'learning_rate/base': 1.5962364522344354e-05, 'epoch': 0.5}) +[2026-07-27 06:22:54,035][starVLA.training.train_starvla][INFO] - Step 4104, Loss: {'train/loss': 0.1251891702413559, 'train/grad_norm_pre_clip': 4.291433334350586, 'timing/data': 0.0001887921243906021, 'timing/model': 0.45900947507470846, 'learning_rate/action_model': 6.382022988652673e-05, 'learning_rate/action_query_proj': 6.382022988652673e-05, 'learning_rate/base': 1.5955057471631684e-05, 'epoch': 0.5}) +[2026-07-27 06:22:59,639][starVLA.training.train_starvla][INFO] - Step 4105, Loss: {'train/loss': 0.1758461594581604, 'train/grad_norm_pre_clip': 3.4697532653808594, 'timing/data': 0.00017935503274202347, 'timing/model': 0.4640598511323333, 'learning_rate/action_model': 6.379099701723648e-05, 'learning_rate/action_query_proj': 6.379099701723648e-05, 'learning_rate/base': 1.594774925430912e-05, 'epoch': 0.5}) +[2026-07-27 06:23:05,206][starVLA.training.train_starvla][INFO] - Step 4106, Loss: {'train/loss': 0.1623409539461136, 'train/grad_norm_pre_clip': 3.3353679180145264, 'timing/data': 0.00017416616901755333, 'timing/model': 0.46362732630223036, 'learning_rate/action_model': 6.376175949304733e-05, 'learning_rate/action_query_proj': 6.376175949304733e-05, 'learning_rate/base': 1.594043987326183e-05, 'epoch': 0.5}) +[2026-07-27 06:23:10,796][starVLA.training.train_starvla][INFO] - Step 4107, Loss: {'train/loss': 0.27591925859451294, 'train/grad_norm_pre_clip': 3.962083578109741, 'timing/data': 0.00017800601199269295, 'timing/model': 0.46152200689539313, 'learning_rate/action_model': 6.373251732550182e-05, 'learning_rate/action_query_proj': 6.373251732550182e-05, 'learning_rate/base': 1.5933129331375455e-05, 'epoch': 0.5}) +[2026-07-27 06:23:16,373][starVLA.training.train_starvla][INFO] - Step 4108, Loss: {'train/loss': 0.11922861635684967, 'train/grad_norm_pre_clip': 2.8821229934692383, 'timing/data': 0.00018062954768538475, 'timing/model': 0.46378835989162326, 'learning_rate/action_model': 6.370327052614426e-05, 'learning_rate/action_query_proj': 6.370327052614426e-05, 'learning_rate/base': 1.5925817631536065e-05, 'epoch': 0.5}) +[2026-07-27 06:23:21,957][starVLA.training.train_starvla][INFO] - Step 4109, Loss: {'train/loss': 0.28938916325569153, 'train/grad_norm_pre_clip': 4.17671537399292, 'timing/data': 0.00017203809693455696, 'timing/model': 0.46269122092053294, 'learning_rate/action_model': 6.367401910652084e-05, 'learning_rate/action_query_proj': 6.367401910652084e-05, 'learning_rate/base': 1.591850477663021e-05, 'epoch': 0.5}) +[2026-07-27 06:23:27,544][starVLA.training.train_starvla][INFO] - Step 4110, Loss: {'train/loss': 0.17551270127296448, 'train/grad_norm_pre_clip': 3.016713857650757, 'timing/data': 0.00017495686188340187, 'timing/model': 0.4635433820076287, 'learning_rate/action_model': 6.364476307817956e-05, 'learning_rate/action_query_proj': 6.364476307817956e-05, 'learning_rate/base': 1.591119076954489e-05, 'epoch': 0.5}) +[2026-07-27 06:23:33,115][starVLA.training.train_starvla][INFO] - Step 4111, Loss: {'train/loss': 0.1681775450706482, 'train/grad_norm_pre_clip': 3.104959726333618, 'timing/data': 0.0001737489365041256, 'timing/model': 0.4599276687949896, 'learning_rate/action_model': 6.361550245267024e-05, 'learning_rate/action_query_proj': 6.361550245267024e-05, 'learning_rate/base': 1.590387561316756e-05, 'epoch': 0.5}) +[2026-07-27 06:23:38,705][starVLA.training.train_starvla][INFO] - Step 4112, Loss: {'train/loss': 0.24075499176979065, 'train/grad_norm_pre_clip': 4.359217166900635, 'timing/data': 0.00017351889982819557, 'timing/model': 0.4562210291624069, 'learning_rate/action_model': 6.358623724154451e-05, 'learning_rate/action_query_proj': 6.358623724154451e-05, 'learning_rate/base': 1.5896559310386127e-05, 'epoch': 0.5}) +[2026-07-27 06:23:44,311][starVLA.training.train_starvla][INFO] - Step 4113, Loss: {'train/loss': 0.23795868456363678, 'train/grad_norm_pre_clip': 3.5682365894317627, 'timing/data': 0.00018522422760725021, 'timing/model': 0.4634632901288569, 'learning_rate/action_model': 6.35569674563558e-05, 'learning_rate/action_query_proj': 6.35569674563558e-05, 'learning_rate/base': 1.588924186408895e-05, 'epoch': 0.5}) +[2026-07-27 06:23:49,934][starVLA.training.train_starvla][INFO] - Step 4114, Loss: {'train/loss': 0.19957679510116577, 'train/grad_norm_pre_clip': 4.134800910949707, 'timing/data': 0.00016813213005661964, 'timing/model': 0.4640724519267678, 'learning_rate/action_model': 6.352769310865936e-05, 'learning_rate/action_query_proj': 6.352769310865936e-05, 'learning_rate/base': 1.588192327716484e-05, 'epoch': 0.5}) +[2026-07-27 06:23:55,526][starVLA.training.train_starvla][INFO] - Step 4115, Loss: {'train/loss': 0.14958159625530243, 'train/grad_norm_pre_clip': 3.0308053493499756, 'timing/data': 0.0001751212403178215, 'timing/model': 0.4594567948952317, 'learning_rate/action_model': 6.349841421001226e-05, 'learning_rate/action_query_proj': 6.349841421001226e-05, 'learning_rate/base': 1.5874603552503065e-05, 'epoch': 0.5}) +[2026-07-27 06:24:01,964][starVLA.training.train_starvla][INFO] - Step 4116, Loss: {'train/loss': 0.23803648352622986, 'train/grad_norm_pre_clip': 4.85998010635376, 'timing/data': 0.00017224205657839775, 'timing/model': 0.4652364728972316, 'learning_rate/action_model': 6.346913077197331e-05, 'learning_rate/action_query_proj': 6.346913077197331e-05, 'learning_rate/base': 1.5867282692993328e-05, 'epoch': 0.5}) +[2026-07-27 06:24:07,577][starVLA.training.train_starvla][INFO] - Step 4117, Loss: {'train/loss': 0.15440666675567627, 'train/grad_norm_pre_clip': 2.8700168132781982, 'timing/data': 0.00017703091725707054, 'timing/model': 0.46069418732076883, 'learning_rate/action_model': 6.343984280610317e-05, 'learning_rate/action_query_proj': 6.343984280610317e-05, 'learning_rate/base': 1.5859960701525793e-05, 'epoch': 0.5}) +[2026-07-27 06:24:13,175][starVLA.training.train_starvla][INFO] - Step 4118, Loss: {'train/loss': 0.12448239326477051, 'train/grad_norm_pre_clip': 2.8516292572021484, 'timing/data': 0.00017338618636131287, 'timing/model': 0.4615932423621416, 'learning_rate/action_model': 6.341055032396427e-05, 'learning_rate/action_query_proj': 6.341055032396427e-05, 'learning_rate/base': 1.585263758099107e-05, 'epoch': 0.5}) +[2026-07-27 06:24:18,783][starVLA.training.train_starvla][INFO] - Step 4119, Loss: {'train/loss': 0.19779875874519348, 'train/grad_norm_pre_clip': 3.0579628944396973, 'timing/data': 0.00018629012629389763, 'timing/model': 0.46363178826868534, 'learning_rate/action_model': 6.338125333712082e-05, 'learning_rate/action_query_proj': 6.338125333712082e-05, 'learning_rate/base': 1.5845313334280205e-05, 'epoch': 0.5}) +[2026-07-27 06:24:24,411][starVLA.training.train_starvla][INFO] - Step 4120, Loss: {'train/loss': 0.21198934316635132, 'train/grad_norm_pre_clip': 3.0654823780059814, 'timing/data': 0.00017313892021775246, 'timing/model': 0.4633587310090661, 'learning_rate/action_model': 6.335195185713879e-05, 'learning_rate/action_query_proj': 6.335195185713879e-05, 'learning_rate/base': 1.5837987964284697e-05, 'epoch': 0.5}) +[2026-07-27 06:24:30,060][starVLA.training.train_starvla][INFO] - Step 4121, Loss: {'train/loss': 0.1889723241329193, 'train/grad_norm_pre_clip': 2.803039312362671, 'timing/data': 0.0001698867417871952, 'timing/model': 0.4630141840316355, 'learning_rate/action_model': 6.332264589558595e-05, 'learning_rate/action_query_proj': 6.332264589558595e-05, 'learning_rate/base': 1.5830661473896486e-05, 'epoch': 0.5}) +[2026-07-27 06:24:35,682][starVLA.training.train_starvla][INFO] - Step 4122, Loss: {'train/loss': 0.08832188695669174, 'train/grad_norm_pre_clip': 2.446751117706299, 'timing/data': 0.00017195940017700195, 'timing/model': 0.46796969696879387, 'learning_rate/action_model': 6.329333546403182e-05, 'learning_rate/action_query_proj': 6.329333546403182e-05, 'learning_rate/base': 1.5823333866007954e-05, 'epoch': 0.5}) +[2026-07-27 06:24:41,309][starVLA.training.train_starvla][INFO] - Step 4123, Loss: {'train/loss': 0.14958086609840393, 'train/grad_norm_pre_clip': 3.442002773284912, 'timing/data': 0.00016929907724261284, 'timing/model': 0.4687185729853809, 'learning_rate/action_model': 6.32640205740477e-05, 'learning_rate/action_query_proj': 6.32640205740477e-05, 'learning_rate/base': 1.5816005143511924e-05, 'epoch': 0.5}) +[2026-07-27 06:24:46,980][starVLA.training.train_starvla][INFO] - Step 4124, Loss: {'train/loss': 0.19677747786045074, 'train/grad_norm_pre_clip': 3.01672101020813, 'timing/data': 0.00017622020095586777, 'timing/model': 0.47797968704253435, 'learning_rate/action_model': 6.323470123720665e-05, 'learning_rate/action_query_proj': 6.323470123720665e-05, 'learning_rate/base': 1.580867530930166e-05, 'epoch': 0.5}) +[2026-07-27 06:24:52,879][starVLA.training.train_starvla][INFO] - Step 4125, Loss: {'train/loss': 0.16769787669181824, 'train/grad_norm_pre_clip': 3.0136687755584717, 'timing/data': 0.0001793629489839077, 'timing/model': 0.7064030598849058, 'learning_rate/action_model': 6.320537746508347e-05, 'learning_rate/action_query_proj': 6.320537746508347e-05, 'learning_rate/base': 1.5801344366270868e-05, 'epoch': 0.5}) +[2026-07-27 06:24:58,519][starVLA.training.train_starvla][INFO] - Step 4126, Loss: {'train/loss': 0.1841043382883072, 'train/grad_norm_pre_clip': 3.207305669784546, 'timing/data': 0.00017115194350481033, 'timing/model': 0.4760216739960015, 'learning_rate/action_model': 6.317604926925473e-05, 'learning_rate/action_query_proj': 6.317604926925473e-05, 'learning_rate/base': 1.579401231731368e-05, 'epoch': 0.5}) +[2026-07-27 06:25:04,241][starVLA.training.train_starvla][INFO] - Step 4127, Loss: {'train/loss': 0.11062655597925186, 'train/grad_norm_pre_clip': 2.619455337524414, 'timing/data': 0.00018458301201462746, 'timing/model': 0.4711304600350559, 'learning_rate/action_model': 6.314671666129871e-05, 'learning_rate/action_query_proj': 6.314671666129871e-05, 'learning_rate/base': 1.578667916532468e-05, 'epoch': 0.5}) +[2026-07-27 06:25:09,914][starVLA.training.train_starvla][INFO] - Step 4128, Loss: {'train/loss': 0.15111202001571655, 'train/grad_norm_pre_clip': 2.1878788471221924, 'timing/data': 0.00016903039067983627, 'timing/model': 0.4702744041569531, 'learning_rate/action_model': 6.311737965279551e-05, 'learning_rate/action_query_proj': 6.311737965279551e-05, 'learning_rate/base': 1.577934491319888e-05, 'epoch': 0.5}) +[2026-07-27 06:25:15,579][starVLA.training.train_starvla][INFO] - Step 4129, Loss: {'train/loss': 0.20372891426086426, 'train/grad_norm_pre_clip': 3.5945675373077393, 'timing/data': 0.0001693922095000744, 'timing/model': 0.4701705239713192, 'learning_rate/action_model': 6.308803825532689e-05, 'learning_rate/action_query_proj': 6.308803825532689e-05, 'learning_rate/base': 1.5772009563831722e-05, 'epoch': 0.5}) +[2026-07-27 06:25:21,224][starVLA.training.train_starvla][INFO] - Step 4130, Loss: {'train/loss': 0.1667623370885849, 'train/grad_norm_pre_clip': 3.6022298336029053, 'timing/data': 0.00017169630154967308, 'timing/model': 0.47043064003810287, 'learning_rate/action_model': 6.305869248047635e-05, 'learning_rate/action_query_proj': 6.305869248047635e-05, 'learning_rate/base': 1.576467312011909e-05, 'epoch': 0.5}) +[2026-07-27 06:25:26,870][starVLA.training.train_starvla][INFO] - Step 4131, Loss: {'train/loss': 0.28976961970329285, 'train/grad_norm_pre_clip': 4.541385650634766, 'timing/data': 0.00017162738367915154, 'timing/model': 0.4719993877224624, 'learning_rate/action_model': 6.302934233982916e-05, 'learning_rate/action_query_proj': 6.302934233982916e-05, 'learning_rate/base': 1.575733558495729e-05, 'epoch': 0.5}) +[2026-07-27 06:25:32,497][starVLA.training.train_starvla][INFO] - Step 4132, Loss: {'train/loss': 0.1487843096256256, 'train/grad_norm_pre_clip': 2.952667474746704, 'timing/data': 0.00016867928206920624, 'timing/model': 0.4624261627905071, 'learning_rate/action_model': 6.29999878449723e-05, 'learning_rate/action_query_proj': 6.29999878449723e-05, 'learning_rate/base': 1.5749996961243074e-05, 'epoch': 0.5}) +[2026-07-27 06:25:38,114][starVLA.training.train_starvla][INFO] - Step 4133, Loss: {'train/loss': 0.12564966082572937, 'train/grad_norm_pre_clip': 2.450927257537842, 'timing/data': 0.00017218617722392082, 'timing/model': 0.45731972670182586, 'learning_rate/action_model': 6.297062900749442e-05, 'learning_rate/action_query_proj': 6.297062900749442e-05, 'learning_rate/base': 1.5742657251873605e-05, 'epoch': 0.5}) +[2026-07-27 06:25:43,773][starVLA.training.train_starvla][INFO] - Step 4134, Loss: {'train/loss': 0.3235388398170471, 'train/grad_norm_pre_clip': 3.359064817428589, 'timing/data': 0.00016964692622423172, 'timing/model': 0.4701701910234988, 'learning_rate/action_model': 6.294126583898596e-05, 'learning_rate/action_query_proj': 6.294126583898596e-05, 'learning_rate/base': 1.573531645974649e-05, 'epoch': 0.5}) +[2026-07-27 06:25:49,664][starVLA.training.train_starvla][INFO] - Step 4135, Loss: {'train/loss': 0.14041779935359955, 'train/grad_norm_pre_clip': 3.8636436462402344, 'timing/data': 0.00016988301649689674, 'timing/model': 0.4764003190211952, 'learning_rate/action_model': 6.291189835103903e-05, 'learning_rate/action_query_proj': 6.291189835103903e-05, 'learning_rate/base': 1.572797458775976e-05, 'epoch': 0.5}) +[2026-07-27 06:25:55,322][starVLA.training.train_starvla][INFO] - Step 4136, Loss: {'train/loss': 0.14954236149787903, 'train/grad_norm_pre_clip': 2.4004974365234375, 'timing/data': 0.00022310297936201096, 'timing/model': 0.47686052275821567, 'learning_rate/action_model': 6.288252655524744e-05, 'learning_rate/action_query_proj': 6.288252655524744e-05, 'learning_rate/base': 1.572063163881186e-05, 'epoch': 0.5}) +[2026-07-27 06:26:00,993][starVLA.training.train_starvla][INFO] - Step 4137, Loss: {'train/loss': 0.10244235396385193, 'train/grad_norm_pre_clip': 2.3240973949432373, 'timing/data': 0.0001756511628627777, 'timing/model': 0.4760873429477215, 'learning_rate/action_model': 6.28531504632067e-05, 'learning_rate/action_query_proj': 6.28531504632067e-05, 'learning_rate/base': 1.5713287615801676e-05, 'epoch': 0.5}) +[2026-07-27 06:26:06,693][starVLA.training.train_starvla][INFO] - Step 4138, Loss: {'train/loss': 0.3139258623123169, 'train/grad_norm_pre_clip': 4.557191371917725, 'timing/data': 0.00017532100901007652, 'timing/model': 0.4705868298187852, 'learning_rate/action_model': 6.282377008651405e-05, 'learning_rate/action_query_proj': 6.282377008651405e-05, 'learning_rate/base': 1.5705942521628513e-05, 'epoch': 0.5}) +[2026-07-27 06:26:12,460][starVLA.training.train_starvla][INFO] - Step 4139, Loss: {'train/loss': 0.2059338241815567, 'train/grad_norm_pre_clip': 3.5647735595703125, 'timing/data': 0.00017004599794745445, 'timing/model': 0.4734963309019804, 'learning_rate/action_model': 6.27943854367684e-05, 'learning_rate/action_query_proj': 6.27943854367684e-05, 'learning_rate/base': 1.56985963591921e-05, 'epoch': 0.5}) +[2026-07-27 06:26:18,158][starVLA.training.train_starvla][INFO] - Step 4140, Loss: {'train/loss': 0.25301143527030945, 'train/grad_norm_pre_clip': 4.479679107666016, 'timing/data': 0.00019291089847683907, 'timing/model': 0.46968278801068664, 'learning_rate/action_model': 6.276499652557031e-05, 'learning_rate/action_query_proj': 6.276499652557031e-05, 'learning_rate/base': 1.5691249131392578e-05, 'epoch': 0.5}) +[2026-07-27 06:26:23,879][starVLA.training.train_starvla][INFO] - Step 4141, Loss: {'train/loss': 0.15135833621025085, 'train/grad_norm_pre_clip': 3.2436516284942627, 'timing/data': 0.00016983412206172943, 'timing/model': 0.4766558133997023, 'learning_rate/action_model': 6.273560336452207e-05, 'learning_rate/action_query_proj': 6.273560336452207e-05, 'learning_rate/base': 1.5683900841130517e-05, 'epoch': 0.5}) +[2026-07-27 06:26:29,569][starVLA.training.train_starvla][INFO] - Step 4142, Loss: {'train/loss': 0.13071507215499878, 'train/grad_norm_pre_clip': 2.447944164276123, 'timing/data': 0.00017026998102664948, 'timing/model': 0.4752747220918536, 'learning_rate/action_model': 6.270620596522765e-05, 'learning_rate/action_query_proj': 6.270620596522765e-05, 'learning_rate/base': 1.5676551491306913e-05, 'epoch': 0.5}) +[2026-07-27 06:26:35,238][starVLA.training.train_starvla][INFO] - Step 4143, Loss: {'train/loss': 0.3127550780773163, 'train/grad_norm_pre_clip': 4.635722637176514, 'timing/data': 0.00017337966710329056, 'timing/model': 0.47138324612751603, 'learning_rate/action_model': 6.267680433929269e-05, 'learning_rate/action_query_proj': 6.267680433929269e-05, 'learning_rate/base': 1.5669201084823172e-05, 'epoch': 0.5}) +[2026-07-27 06:26:40,899][starVLA.training.train_starvla][INFO] - Step 4144, Loss: {'train/loss': 0.1543809473514557, 'train/grad_norm_pre_clip': 3.706955671310425, 'timing/data': 0.00016960222274065018, 'timing/model': 0.47138576582074165, 'learning_rate/action_model': 6.264739849832441e-05, 'learning_rate/action_query_proj': 6.264739849832441e-05, 'learning_rate/base': 1.5661849624581103e-05, 'epoch': 0.5}) +[2026-07-27 06:26:46,556][starVLA.training.train_starvla][INFO] - Step 4145, Loss: {'train/loss': 0.2888721227645874, 'train/grad_norm_pre_clip': 4.371078968048096, 'timing/data': 0.00017122505232691765, 'timing/model': 0.47944692987948656, 'learning_rate/action_model': 6.261798845393188e-05, 'learning_rate/action_query_proj': 6.261798845393188e-05, 'learning_rate/base': 1.565449711348297e-05, 'epoch': 0.5}) +[2026-07-27 06:26:52,212][starVLA.training.train_starvla][INFO] - Step 4146, Loss: {'train/loss': 0.14938318729400635, 'train/grad_norm_pre_clip': 2.810523748397827, 'timing/data': 0.00017641298472881317, 'timing/model': 0.4697424708865583, 'learning_rate/action_model': 6.258857421772563e-05, 'learning_rate/action_query_proj': 6.258857421772563e-05, 'learning_rate/base': 1.5647143554431408e-05, 'epoch': 0.5}) +[2026-07-27 06:26:57,778][starVLA.training.train_starvla][INFO] - Step 4147, Loss: {'train/loss': 0.13481709361076355, 'train/grad_norm_pre_clip': 3.301347494125366, 'timing/data': 0.00017287163063883781, 'timing/model': 0.472113149240613, 'learning_rate/action_model': 6.255915580131798e-05, 'learning_rate/action_query_proj': 6.255915580131798e-05, 'learning_rate/base': 1.5639788950329495e-05, 'epoch': 0.5}) +[2026-07-27 06:27:03,378][starVLA.training.train_starvla][INFO] - Step 4148, Loss: {'train/loss': 0.1790134608745575, 'train/grad_norm_pre_clip': 3.072974681854248, 'timing/data': 0.0001735272817313671, 'timing/model': 0.47713213693350554, 'learning_rate/action_model': 6.252973321632285e-05, 'learning_rate/action_query_proj': 6.252973321632285e-05, 'learning_rate/base': 1.563243330408071e-05, 'epoch': 0.5}) +[2026-07-27 06:27:08,976][starVLA.training.train_starvla][INFO] - Step 4149, Loss: {'train/loss': 0.30449363589286804, 'train/grad_norm_pre_clip': 4.403627395629883, 'timing/data': 0.00017262110486626625, 'timing/model': 0.47098046028986573, 'learning_rate/action_model': 6.250030647435581e-05, 'learning_rate/action_query_proj': 6.250030647435581e-05, 'learning_rate/base': 1.5625076618588952e-05, 'epoch': 0.5}) +[2026-07-27 06:27:14,573][starVLA.training.train_starvla][INFO] - Step 4150, Loss: {'train/loss': 0.228496253490448, 'train/grad_norm_pre_clip': 3.974390983581543, 'timing/data': 0.00017532100901007652, 'timing/model': 0.46471075899899006, 'learning_rate/action_model': 6.247087558703405e-05, 'learning_rate/action_query_proj': 6.247087558703405e-05, 'learning_rate/base': 1.561771889675851e-05, 'epoch': 0.5}) +[2026-07-27 06:27:20,178][starVLA.training.train_starvla][INFO] - Step 4151, Loss: {'train/loss': 0.27814781665802, 'train/grad_norm_pre_clip': 4.905864238739014, 'timing/data': 0.00017236219719052315, 'timing/model': 0.46280824672430754, 'learning_rate/action_model': 6.244144056597644e-05, 'learning_rate/action_query_proj': 6.244144056597644e-05, 'learning_rate/base': 1.561036014149411e-05, 'epoch': 0.5}) +[2026-07-27 06:27:25,765][starVLA.training.train_starvla][INFO] - Step 4152, Loss: {'train/loss': 0.1322065144777298, 'train/grad_norm_pre_clip': 2.7010786533355713, 'timing/data': 0.0001752828247845173, 'timing/model': 0.4626965937204659, 'learning_rate/action_model': 6.241200142280347e-05, 'learning_rate/action_query_proj': 6.241200142280347e-05, 'learning_rate/base': 1.5603000355700867e-05, 'epoch': 0.5}) +[2026-07-27 06:27:31,351][starVLA.training.train_starvla][INFO] - Step 4153, Loss: {'train/loss': 0.1595492660999298, 'train/grad_norm_pre_clip': 3.3796470165252686, 'timing/data': 0.00017313985154032707, 'timing/model': 0.461900528986007, 'learning_rate/action_model': 6.238255816913721e-05, 'learning_rate/action_query_proj': 6.238255816913721e-05, 'learning_rate/base': 1.5595639542284303e-05, 'epoch': 0.5}) +[2026-07-27 06:27:36,934][starVLA.training.train_starvla][INFO] - Step 4154, Loss: {'train/loss': 0.12001901865005493, 'train/grad_norm_pre_clip': 2.995922565460205, 'timing/data': 0.00016814004629850388, 'timing/model': 0.4626933680847287, 'learning_rate/action_model': 6.235311081660142e-05, 'learning_rate/action_query_proj': 6.235311081660142e-05, 'learning_rate/base': 1.5588277704150356e-05, 'epoch': 0.5}) +[2026-07-27 06:27:42,520][starVLA.training.train_starvla][INFO] - Step 4155, Loss: {'train/loss': 0.1760869175195694, 'train/grad_norm_pre_clip': 2.718571662902832, 'timing/data': 0.0001841587945818901, 'timing/model': 0.46360314171761274, 'learning_rate/action_model': 6.232365937682145e-05, 'learning_rate/action_query_proj': 6.232365937682145e-05, 'learning_rate/base': 1.558091484420536e-05, 'epoch': 0.5}) +[2026-07-27 06:27:48,131][starVLA.training.train_starvla][INFO] - Step 4156, Loss: {'train/loss': 0.1698719561100006, 'train/grad_norm_pre_clip': 3.2037487030029297, 'timing/data': 0.00017401622608304024, 'timing/model': 0.46352841099724174, 'learning_rate/action_model': 6.229420386142424e-05, 'learning_rate/action_query_proj': 6.229420386142424e-05, 'learning_rate/base': 1.557355096535606e-05, 'epoch': 0.5}) +[2026-07-27 06:27:53,712][starVLA.training.train_starvla][INFO] - Step 4157, Loss: {'train/loss': 0.16014313697814941, 'train/grad_norm_pre_clip': 2.907897472381592, 'timing/data': 0.00017193565145134926, 'timing/model': 0.46092369221150875, 'learning_rate/action_model': 6.226474428203838e-05, 'learning_rate/action_query_proj': 6.226474428203838e-05, 'learning_rate/base': 1.5566186070509596e-05, 'epoch': 0.5}) +[2026-07-27 06:27:59,316][starVLA.training.train_starvla][INFO] - Step 4158, Loss: {'train/loss': 0.20035602152347565, 'train/grad_norm_pre_clip': 3.1983931064605713, 'timing/data': 0.00019116699695587158, 'timing/model': 0.4635592130944133, 'learning_rate/action_model': 6.223528065029406e-05, 'learning_rate/action_query_proj': 6.223528065029406e-05, 'learning_rate/base': 1.5558820162573516e-05, 'epoch': 0.5}) +[2026-07-27 06:28:04,884][starVLA.training.train_starvla][INFO] - Step 4159, Loss: {'train/loss': 0.23380234837532043, 'train/grad_norm_pre_clip': 4.135828495025635, 'timing/data': 0.00017127906903624535, 'timing/model': 0.45904318196699023, 'learning_rate/action_model': 6.2205812977823e-05, 'learning_rate/action_query_proj': 6.2205812977823e-05, 'learning_rate/base': 1.555145324445575e-05, 'epoch': 0.5}) +[2026-07-27 06:28:10,734][starVLA.training.train_starvla][INFO] - Step 4160, Loss: {'train/loss': 0.1834869682788849, 'train/grad_norm_pre_clip': 3.424027919769287, 'timing/data': 0.0001724250614643097, 'timing/model': 0.4622430047020316, 'learning_rate/action_model': 6.217634127625863e-05, 'learning_rate/action_query_proj': 6.217634127625863e-05, 'learning_rate/base': 1.5544085319064658e-05, 'epoch': 0.5}) +[2026-07-27 06:28:16,344][starVLA.training.train_starvla][INFO] - Step 4161, Loss: {'train/loss': 0.1951642781496048, 'train/grad_norm_pre_clip': 4.154363632202148, 'timing/data': 0.00017602788284420967, 'timing/model': 0.46173487789928913, 'learning_rate/action_model': 6.21468655572359e-05, 'learning_rate/action_query_proj': 6.21468655572359e-05, 'learning_rate/base': 1.5536716389308974e-05, 'epoch': 0.5}) +[2026-07-27 06:28:21,961][starVLA.training.train_starvla][INFO] - Step 4162, Loss: {'train/loss': 0.16677923500537872, 'train/grad_norm_pre_clip': 3.3464620113372803, 'timing/data': 0.0001738523133099079, 'timing/model': 0.46418303716927767, 'learning_rate/action_model': 6.211738583239129e-05, 'learning_rate/action_query_proj': 6.211738583239129e-05, 'learning_rate/base': 1.5529346458097823e-05, 'epoch': 0.5}) +[2026-07-27 06:28:27,561][starVLA.training.train_starvla][INFO] - Step 4163, Loss: {'train/loss': 0.15145066380500793, 'train/grad_norm_pre_clip': 3.306365966796875, 'timing/data': 0.0001760357990860939, 'timing/model': 0.46342326095327735, 'learning_rate/action_model': 6.208790211336303e-05, 'learning_rate/action_query_proj': 6.208790211336303e-05, 'learning_rate/base': 1.5521975528340758e-05, 'epoch': 0.51}) +[2026-07-27 06:28:33,175][starVLA.training.train_starvla][INFO] - Step 4164, Loss: {'train/loss': 0.23242689669132233, 'train/grad_norm_pre_clip': 3.3921048641204834, 'timing/data': 0.00017655221745371819, 'timing/model': 0.46440767170861363, 'learning_rate/action_model': 6.205841441179074e-05, 'learning_rate/action_query_proj': 6.205841441179074e-05, 'learning_rate/base': 1.5514603602947685e-05, 'epoch': 0.51}) +[2026-07-27 06:28:38,782][starVLA.training.train_starvla][INFO] - Step 4165, Loss: {'train/loss': 0.15926823019981384, 'train/grad_norm_pre_clip': 2.9035935401916504, 'timing/data': 0.0001711617223918438, 'timing/model': 0.4651373461820185, 'learning_rate/action_model': 6.202892273931577e-05, 'learning_rate/action_query_proj': 6.202892273931577e-05, 'learning_rate/base': 1.550723068482894e-05, 'epoch': 0.51}) +[2026-07-27 06:28:44,393][starVLA.training.train_starvla][INFO] - Step 4166, Loss: {'train/loss': 0.1377558559179306, 'train/grad_norm_pre_clip': 2.5851495265960693, 'timing/data': 0.00017808517441153526, 'timing/model': 0.45928866416215897, 'learning_rate/action_model': 6.199942710758092e-05, 'learning_rate/action_query_proj': 6.199942710758092e-05, 'learning_rate/base': 1.549985677689523e-05, 'epoch': 0.51}) +[2026-07-27 06:28:49,995][starVLA.training.train_starvla][INFO] - Step 4167, Loss: {'train/loss': 0.12216967344284058, 'train/grad_norm_pre_clip': 2.44382905960083, 'timing/data': 0.0001692180521786213, 'timing/model': 0.4608436659909785, 'learning_rate/action_model': 6.19699275282306e-05, 'learning_rate/action_query_proj': 6.19699275282306e-05, 'learning_rate/base': 1.549248188205765e-05, 'epoch': 0.51}) +[2026-07-27 06:28:55,579][starVLA.training.train_starvla][INFO] - Step 4168, Loss: {'train/loss': 0.1874759942293167, 'train/grad_norm_pre_clip': 2.9672112464904785, 'timing/data': 0.0001767929643392563, 'timing/model': 0.46198603976517916, 'learning_rate/action_model': 6.19404240129108e-05, 'learning_rate/action_query_proj': 6.19404240129108e-05, 'learning_rate/base': 1.54851060032277e-05, 'epoch': 0.51}) +[2026-07-27 06:29:01,365][starVLA.training.train_starvla][INFO] - Step 4169, Loss: {'train/loss': 0.3290160000324249, 'train/grad_norm_pre_clip': 4.578751564025879, 'timing/data': 0.00018629804253578186, 'timing/model': 0.461569526232779, 'learning_rate/action_model': 6.191091657326899e-05, 'learning_rate/action_query_proj': 6.191091657326899e-05, 'learning_rate/base': 1.5477729143317248e-05, 'epoch': 0.51}) +[2026-07-27 06:29:06,961][starVLA.training.train_starvla][INFO] - Step 4170, Loss: {'train/loss': 0.19976705312728882, 'train/grad_norm_pre_clip': 3.7672905921936035, 'timing/data': 0.00018306914716959, 'timing/model': 0.46342381462454796, 'learning_rate/action_model': 6.188140522095431e-05, 'learning_rate/action_query_proj': 6.188140522095431e-05, 'learning_rate/base': 1.5470351305238578e-05, 'epoch': 0.51}) +[2026-07-27 06:29:12,535][starVLA.training.train_starvla][INFO] - Step 4171, Loss: {'train/loss': 0.21886032819747925, 'train/grad_norm_pre_clip': 4.3031535148620605, 'timing/data': 0.0001730690710246563, 'timing/model': 0.45918351504951715, 'learning_rate/action_model': 6.185188996761733e-05, 'learning_rate/action_query_proj': 6.185188996761733e-05, 'learning_rate/base': 1.5462972491904332e-05, 'epoch': 0.51}) +[2026-07-27 06:29:18,137][starVLA.training.train_starvla][INFO] - Step 4172, Loss: {'train/loss': 0.19864770770072937, 'train/grad_norm_pre_clip': 3.7730584144592285, 'timing/data': 0.0001784972846508026, 'timing/model': 0.46407533111050725, 'learning_rate/action_model': 6.182237082491021e-05, 'learning_rate/action_query_proj': 6.182237082491021e-05, 'learning_rate/base': 1.5455592706227553e-05, 'epoch': 0.51}) +[2026-07-27 06:29:23,723][starVLA.training.train_starvla][INFO] - Step 4173, Loss: {'train/loss': 0.1788025051355362, 'train/grad_norm_pre_clip': 3.3087618350982666, 'timing/data': 0.00017694337293505669, 'timing/model': 0.4618369028903544, 'learning_rate/action_model': 6.179284780448667e-05, 'learning_rate/action_query_proj': 6.179284780448667e-05, 'learning_rate/base': 1.5448211951121667e-05, 'epoch': 0.51}) +[2026-07-27 06:29:29,420][starVLA.training.train_starvla][INFO] - Step 4174, Loss: {'train/loss': 0.15734818577766418, 'train/grad_norm_pre_clip': 2.5836753845214844, 'timing/data': 0.00018728291615843773, 'timing/model': 0.4622585829347372, 'learning_rate/action_model': 6.176332091800186e-05, 'learning_rate/action_query_proj': 6.176332091800186e-05, 'learning_rate/base': 1.5440830229500465e-05, 'epoch': 0.51}) +[2026-07-27 06:29:35,260][starVLA.training.train_starvla][INFO] - Step 4175, Loss: {'train/loss': 0.13983111083507538, 'train/grad_norm_pre_clip': 2.996708393096924, 'timing/data': 0.00019011599943041801, 'timing/model': 0.46300061559304595, 'learning_rate/action_model': 6.17337901771126e-05, 'learning_rate/action_query_proj': 6.17337901771126e-05, 'learning_rate/base': 1.543344754427815e-05, 'epoch': 0.51}) +[2026-07-27 06:29:40,836][starVLA.training.train_starvla][INFO] - Step 4176, Loss: {'train/loss': 0.1328127533197403, 'train/grad_norm_pre_clip': 3.153080701828003, 'timing/data': 0.00017628399655222893, 'timing/model': 0.4652309990487993, 'learning_rate/action_model': 6.170425559347713e-05, 'learning_rate/action_query_proj': 6.170425559347713e-05, 'learning_rate/base': 1.5426063898369283e-05, 'epoch': 0.51}) +[2026-07-27 06:29:46,410][starVLA.training.train_starvla][INFO] - Step 4177, Loss: {'train/loss': 0.23005232214927673, 'train/grad_norm_pre_clip': 3.766380786895752, 'timing/data': 0.00018166285008192062, 'timing/model': 0.4663772820495069, 'learning_rate/action_model': 6.167471717875523e-05, 'learning_rate/action_query_proj': 6.167471717875523e-05, 'learning_rate/base': 1.5418679294688808e-05, 'epoch': 0.51}) +[2026-07-27 06:29:51,986][starVLA.training.train_starvla][INFO] - Step 4178, Loss: {'train/loss': 0.11127056926488876, 'train/grad_norm_pre_clip': 1.874885082244873, 'timing/data': 0.00017184903845191002, 'timing/model': 0.46492693526670337, 'learning_rate/action_model': 6.164517494460822e-05, 'learning_rate/action_query_proj': 6.164517494460822e-05, 'learning_rate/base': 1.5411293736152055e-05, 'epoch': 0.51}) +[2026-07-27 06:29:57,579][starVLA.training.train_starvla][INFO] - Step 4179, Loss: {'train/loss': 0.17273248732089996, 'train/grad_norm_pre_clip': 2.776249408721924, 'timing/data': 0.0001744767650961876, 'timing/model': 0.4634489151649177, 'learning_rate/action_model': 6.161562890269888e-05, 'learning_rate/action_query_proj': 6.161562890269888e-05, 'learning_rate/base': 1.540390722567472e-05, 'epoch': 0.51}) +[2026-07-27 06:30:03,177][starVLA.training.train_starvla][INFO] - Step 4180, Loss: {'train/loss': 0.32073163986206055, 'train/grad_norm_pre_clip': 4.006705284118652, 'timing/data': 0.0001670639030635357, 'timing/model': 0.46919537568464875, 'learning_rate/action_model': 6.158607906469154e-05, 'learning_rate/action_query_proj': 6.158607906469154e-05, 'learning_rate/base': 1.5396519766172884e-05, 'epoch': 0.51}) +[2026-07-27 06:30:08,747][starVLA.training.train_starvla][INFO] - Step 4181, Loss: {'train/loss': 0.16505488753318787, 'train/grad_norm_pre_clip': 2.796290874481201, 'timing/data': 0.00017211167141795158, 'timing/model': 0.461263416800648, 'learning_rate/action_model': 6.1556525442252e-05, 'learning_rate/action_query_proj': 6.1556525442252e-05, 'learning_rate/base': 1.5389131360563e-05, 'epoch': 0.51}) +[2026-07-27 06:30:14,349][starVLA.training.train_starvla][INFO] - Step 4182, Loss: {'train/loss': 0.13766875863075256, 'train/grad_norm_pre_clip': 2.6326136589050293, 'timing/data': 0.0001862458884716034, 'timing/model': 0.45995826506987214, 'learning_rate/action_model': 6.152696804704755e-05, 'learning_rate/action_query_proj': 6.152696804704755e-05, 'learning_rate/base': 1.5381742011761886e-05, 'epoch': 0.51}) +[2026-07-27 06:30:19,954][starVLA.training.train_starvla][INFO] - Step 4183, Loss: {'train/loss': 0.11301293224096298, 'train/grad_norm_pre_clip': 2.206653356552124, 'timing/data': 0.00017277896404266357, 'timing/model': 0.46396118169650435, 'learning_rate/action_model': 6.1497406890747e-05, 'learning_rate/action_query_proj': 6.1497406890747e-05, 'learning_rate/base': 1.537435172268675e-05, 'epoch': 0.51}) +[2026-07-27 06:30:25,545][starVLA.training.train_starvla][INFO] - Step 4184, Loss: {'train/loss': 0.18682259321212769, 'train/grad_norm_pre_clip': 3.8217930793762207, 'timing/data': 0.00017482880502939224, 'timing/model': 0.45873656030744314, 'learning_rate/action_model': 6.146784198502062e-05, 'learning_rate/action_query_proj': 6.146784198502062e-05, 'learning_rate/base': 1.5366960496255155e-05, 'epoch': 0.51}) +[2026-07-27 06:30:31,134][starVLA.training.train_starvla][INFO] - Step 4185, Loss: {'train/loss': 0.15922477841377258, 'train/grad_norm_pre_clip': 3.116931438446045, 'timing/data': 0.00017646607011556625, 'timing/model': 0.4611738966777921, 'learning_rate/action_model': 6.143827334154016e-05, 'learning_rate/action_query_proj': 6.143827334154016e-05, 'learning_rate/base': 1.535956833538504e-05, 'epoch': 0.51}) +[2026-07-27 06:30:36,717][starVLA.training.train_starvla][INFO] - Step 4186, Loss: {'train/loss': 0.18684348464012146, 'train/grad_norm_pre_clip': 3.9091691970825195, 'timing/data': 0.0001797187142074108, 'timing/model': 0.46514217276126146, 'learning_rate/action_model': 6.140870097197887e-05, 'learning_rate/action_query_proj': 6.140870097197887e-05, 'learning_rate/base': 1.5352175242994718e-05, 'epoch': 0.51}) +[2026-07-27 06:30:42,295][starVLA.training.train_starvla][INFO] - Step 4187, Loss: {'train/loss': 0.16674965620040894, 'train/grad_norm_pre_clip': 3.133798599243164, 'timing/data': 0.00018080603331327438, 'timing/model': 0.4563393057323992, 'learning_rate/action_model': 6.137912488801144e-05, 'learning_rate/action_query_proj': 6.137912488801144e-05, 'learning_rate/base': 1.534478122200286e-05, 'epoch': 0.51}) +[2026-07-27 06:30:47,898][starVLA.training.train_starvla][INFO] - Step 4188, Loss: {'train/loss': 0.25679510831832886, 'train/grad_norm_pre_clip': 4.841620922088623, 'timing/data': 0.00017931917682290077, 'timing/model': 0.4625488109886646, 'learning_rate/action_model': 6.134954510131403e-05, 'learning_rate/action_query_proj': 6.134954510131403e-05, 'learning_rate/base': 1.533738627532851e-05, 'epoch': 0.51}) +[2026-07-27 06:30:53,493][starVLA.training.train_starvla][INFO] - Step 4189, Loss: {'train/loss': 0.1545354276895523, 'train/grad_norm_pre_clip': 3.0834457874298096, 'timing/data': 0.00017817597836256027, 'timing/model': 0.4647365100681782, 'learning_rate/action_model': 6.131996162356428e-05, 'learning_rate/action_query_proj': 6.131996162356428e-05, 'learning_rate/base': 1.532999040589107e-05, 'epoch': 0.51}) +[2026-07-27 06:30:59,098][starVLA.training.train_starvla][INFO] - Step 4190, Loss: {'train/loss': 0.14012028276920319, 'train/grad_norm_pre_clip': 2.6489157676696777, 'timing/data': 0.00017983606085181236, 'timing/model': 0.4653118969872594, 'learning_rate/action_model': 6.12903744664413e-05, 'learning_rate/action_query_proj': 6.12903744664413e-05, 'learning_rate/base': 1.5322593616610325e-05, 'epoch': 0.51}) +[2026-07-27 06:31:04,688][starVLA.training.train_starvla][INFO] - Step 4191, Loss: {'train/loss': 0.15092666447162628, 'train/grad_norm_pre_clip': 2.6177005767822266, 'timing/data': 0.00018058810383081436, 'timing/model': 0.4641673672012985, 'learning_rate/action_model': 6.12607836416256e-05, 'learning_rate/action_query_proj': 6.12607836416256e-05, 'learning_rate/base': 1.53151959104064e-05, 'epoch': 0.51}) +[2026-07-27 06:31:10,301][starVLA.training.train_starvla][INFO] - Step 4192, Loss: {'train/loss': 0.0860125795006752, 'train/grad_norm_pre_clip': 2.2981319427490234, 'timing/data': 0.0001788041554391384, 'timing/model': 0.4700050391256809, 'learning_rate/action_model': 6.123118916079919e-05, 'learning_rate/action_query_proj': 6.123118916079919e-05, 'learning_rate/base': 1.5307797290199798e-05, 'epoch': 0.51}) +[2026-07-27 06:31:15,879][starVLA.training.train_starvla][INFO] - Step 4193, Loss: {'train/loss': 0.17876504361629486, 'train/grad_norm_pre_clip': 2.59354305267334, 'timing/data': 0.0001786649227142334, 'timing/model': 0.46909000910818577, 'learning_rate/action_model': 6.120159103564547e-05, 'learning_rate/action_query_proj': 6.120159103564547e-05, 'learning_rate/base': 1.5300397758911368e-05, 'epoch': 0.51}) +[2026-07-27 06:31:21,494][starVLA.training.train_starvla][INFO] - Step 4194, Loss: {'train/loss': 0.18728864192962646, 'train/grad_norm_pre_clip': 3.4600625038146973, 'timing/data': 0.0001774071715772152, 'timing/model': 0.4804273182526231, 'learning_rate/action_model': 6.117198927784936e-05, 'learning_rate/action_query_proj': 6.117198927784936e-05, 'learning_rate/base': 1.529299731946234e-05, 'epoch': 0.51}) +[2026-07-27 06:31:27,106][starVLA.training.train_starvla][INFO] - Step 4195, Loss: {'train/loss': 0.11447947472333908, 'train/grad_norm_pre_clip': 3.0663251876831055, 'timing/data': 0.00017014890909194946, 'timing/model': 0.47942179907113314, 'learning_rate/action_model': 6.114238389909713e-05, 'learning_rate/action_query_proj': 6.114238389909713e-05, 'learning_rate/base': 1.5285595974774282e-05, 'epoch': 0.51}) +[2026-07-27 06:31:32,709][starVLA.training.train_starvla][INFO] - Step 4196, Loss: {'train/loss': 0.1445450782775879, 'train/grad_norm_pre_clip': 2.404356002807617, 'timing/data': 0.00017506815493106842, 'timing/model': 0.48371928418055177, 'learning_rate/action_model': 6.111277491107652e-05, 'learning_rate/action_query_proj': 6.111277491107652e-05, 'learning_rate/base': 1.527819372776913e-05, 'epoch': 0.51}) +[2026-07-27 06:31:38,299][starVLA.training.train_starvla][INFO] - Step 4197, Loss: {'train/loss': 0.15406641364097595, 'train/grad_norm_pre_clip': 3.1665892601013184, 'timing/data': 0.00017698295414447784, 'timing/model': 0.48014692729339004, 'learning_rate/action_model': 6.108316232547668e-05, 'learning_rate/action_query_proj': 6.108316232547668e-05, 'learning_rate/base': 1.527079058136917e-05, 'epoch': 0.51}) +[2026-07-27 06:31:43,921][starVLA.training.train_starvla][INFO] - Step 4198, Loss: {'train/loss': 0.12584929168224335, 'train/grad_norm_pre_clip': 2.2446422576904297, 'timing/data': 0.00019036512821912766, 'timing/model': 0.4757128809578717, 'learning_rate/action_model': 6.105354615398825e-05, 'learning_rate/action_query_proj': 6.105354615398825e-05, 'learning_rate/base': 1.526338653849706e-05, 'epoch': 0.51}) +[2026-07-27 06:31:49,543][starVLA.training.train_starvla][INFO] - Step 4199, Loss: {'train/loss': 0.25110968947410583, 'train/grad_norm_pre_clip': 2.92387056350708, 'timing/data': 0.00018151383846998215, 'timing/model': 0.47874270798638463, 'learning_rate/action_model': 6.102392640830312e-05, 'learning_rate/action_query_proj': 6.102392640830312e-05, 'learning_rate/base': 1.525598160207578e-05, 'epoch': 0.51}) +[2026-07-27 06:31:55,140][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 4200 +[2026-07-27 06:31:55,142][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 4200 +[2026-07-27 06:31:55,143][starVLA.training.train_starvla][INFO] - Step 4200, Loss: {'train/loss': 0.15283378958702087, 'train/grad_norm_pre_clip': 3.113588571548462, 'timing/data': 0.00018944218754768372, 'timing/model': 0.4890340003184974, 'learning_rate/action_model': 6.099430310011479e-05, 'learning_rate/action_query_proj': 6.099430310011479e-05, 'learning_rate/base': 1.5248575775028697e-05, 'epoch': 0.51}) +[2026-07-27 06:32:00,757][starVLA.training.train_starvla][INFO] - Step 4201, Loss: {'train/loss': 0.184822678565979, 'train/grad_norm_pre_clip': 2.9892146587371826, 'timing/data': 0.000199807807803154, 'timing/model': 0.48109006229788065, 'learning_rate/action_model': 6.0964676241118036e-05, 'learning_rate/action_query_proj': 6.0964676241118036e-05, 'learning_rate/base': 1.5241169060279509e-05, 'epoch': 0.51}) +[2026-07-27 06:32:06,399][starVLA.training.train_starvla][INFO] - Step 4202, Loss: {'train/loss': 0.1534487009048462, 'train/grad_norm_pre_clip': 2.790250539779663, 'timing/data': 0.00022126827389001846, 'timing/model': 0.4818741297349334, 'learning_rate/action_model': 6.093504584300906e-05, 'learning_rate/action_query_proj': 6.093504584300906e-05, 'learning_rate/base': 1.5233761460752265e-05, 'epoch': 0.51}) +[2026-07-27 06:32:12,020][starVLA.training.train_starvla][INFO] - Step 4203, Loss: {'train/loss': 0.14899037778377533, 'train/grad_norm_pre_clip': 3.1481246948242188, 'timing/data': 0.00018061604350805283, 'timing/model': 0.48875818215310574, 'learning_rate/action_model': 6.0905411917485514e-05, 'learning_rate/action_query_proj': 6.0905411917485514e-05, 'learning_rate/base': 1.5226352979371378e-05, 'epoch': 0.51}) +[2026-07-27 06:32:17,629][starVLA.training.train_starvla][INFO] - Step 4204, Loss: {'train/loss': 0.08751433342695236, 'train/grad_norm_pre_clip': 1.7805202007293701, 'timing/data': 0.0001774318516254425, 'timing/model': 0.4814171469770372, 'learning_rate/action_model': 6.087577447624635e-05, 'learning_rate/action_query_proj': 6.087577447624635e-05, 'learning_rate/base': 1.5218943619061587e-05, 'epoch': 0.51}) +[2026-07-27 06:32:23,487][starVLA.training.train_starvla][INFO] - Step 4205, Loss: {'train/loss': 0.07202263176441193, 'train/grad_norm_pre_clip': 2.0020272731781006, 'timing/data': 0.0001815110445022583, 'timing/model': 0.4755041291937232, 'learning_rate/action_model': 6.084613353099201e-05, 'learning_rate/action_query_proj': 6.084613353099201e-05, 'learning_rate/base': 1.5211533382748002e-05, 'epoch': 0.51}) +[2026-07-27 06:32:29,130][starVLA.training.train_starvla][INFO] - Step 4206, Loss: {'train/loss': 0.1827494502067566, 'train/grad_norm_pre_clip': 4.022704124450684, 'timing/data': 0.0001870701089501381, 'timing/model': 0.48070000298321247, 'learning_rate/action_model': 6.081648909342424e-05, 'learning_rate/action_query_proj': 6.081648909342424e-05, 'learning_rate/base': 1.520412227335606e-05, 'epoch': 0.51}) +[2026-07-27 06:32:34,749][starVLA.training.train_starvla][INFO] - Step 4207, Loss: {'train/loss': 0.20763851702213287, 'train/grad_norm_pre_clip': 3.178736686706543, 'timing/data': 0.00017685163766145706, 'timing/model': 0.4802295039407909, 'learning_rate/action_model': 6.078684117524619e-05, 'learning_rate/action_query_proj': 6.078684117524619e-05, 'learning_rate/base': 1.5196710293811547e-05, 'epoch': 0.51}) +[2026-07-27 06:32:40,385][starVLA.training.train_starvla][INFO] - Step 4208, Loss: {'train/loss': 0.1967202126979828, 'train/grad_norm_pre_clip': 3.062788724899292, 'timing/data': 0.0001755119301378727, 'timing/model': 0.48129084007814527, 'learning_rate/action_model': 6.0757189788162414e-05, 'learning_rate/action_query_proj': 6.0757189788162414e-05, 'learning_rate/base': 1.5189297447040604e-05, 'epoch': 0.51}) +[2026-07-27 06:32:46,000][starVLA.training.train_starvla][INFO] - Step 4209, Loss: {'train/loss': 0.252467542886734, 'train/grad_norm_pre_clip': 3.8532662391662598, 'timing/data': 0.00022175023332238197, 'timing/model': 0.4814532850869, 'learning_rate/action_model': 6.0727534943878795e-05, 'learning_rate/action_query_proj': 6.0727534943878795e-05, 'learning_rate/base': 1.5181883735969699e-05, 'epoch': 0.51}) +[2026-07-27 06:32:51,628][starVLA.training.train_starvla][INFO] - Step 4210, Loss: {'train/loss': 0.20276737213134766, 'train/grad_norm_pre_clip': 3.1561782360076904, 'timing/data': 0.00018329592421650887, 'timing/model': 0.4873163620941341, 'learning_rate/action_model': 6.0697876654102594e-05, 'learning_rate/action_query_proj': 6.0697876654102594e-05, 'learning_rate/base': 1.5174469163525649e-05, 'epoch': 0.51}) +[2026-07-27 06:32:57,248][starVLA.training.train_starvla][INFO] - Step 4211, Loss: {'train/loss': 0.23743003606796265, 'train/grad_norm_pre_clip': 3.395601987838745, 'timing/data': 0.0001738760620355606, 'timing/model': 0.47873029997572303, 'learning_rate/action_model': 6.066821493054244e-05, 'learning_rate/action_query_proj': 6.066821493054244e-05, 'learning_rate/base': 1.516705373263561e-05, 'epoch': 0.51}) +[2026-07-27 06:33:02,877][starVLA.training.train_starvla][INFO] - Step 4212, Loss: {'train/loss': 0.17818672955036163, 'train/grad_norm_pre_clip': 3.078270196914673, 'timing/data': 0.0001874133013188839, 'timing/model': 0.4665682199411094, 'learning_rate/action_model': 6.063854978490832e-05, 'learning_rate/action_query_proj': 6.063854978490832e-05, 'learning_rate/base': 1.515963744622708e-05, 'epoch': 0.51}) +[2026-07-27 06:33:08,478][starVLA.training.train_starvla][INFO] - Step 4213, Loss: {'train/loss': 0.18261097371578217, 'train/grad_norm_pre_clip': 3.22868275642395, 'timing/data': 0.000174080953001976, 'timing/model': 0.48306250805035233, 'learning_rate/action_model': 6.060888122891154e-05, 'learning_rate/action_query_proj': 6.060888122891154e-05, 'learning_rate/base': 1.5152220307227885e-05, 'epoch': 0.51}) +[2026-07-27 06:33:14,107][starVLA.training.train_starvla][INFO] - Step 4214, Loss: {'train/loss': 0.11661846935749054, 'train/grad_norm_pre_clip': 2.9484527111053467, 'timing/data': 0.0001730453222990036, 'timing/model': 0.4796173833310604, 'learning_rate/action_model': 6.057920927426479e-05, 'learning_rate/action_query_proj': 6.057920927426479e-05, 'learning_rate/base': 1.5144802318566198e-05, 'epoch': 0.51}) +[2026-07-27 06:33:19,724][starVLA.training.train_starvla][INFO] - Step 4215, Loss: {'train/loss': 0.21074825525283813, 'train/grad_norm_pre_clip': 2.9141907691955566, 'timing/data': 0.00018354691565036774, 'timing/model': 0.4760675420984626, 'learning_rate/action_model': 6.054953393268209e-05, 'learning_rate/action_query_proj': 6.054953393268209e-05, 'learning_rate/base': 1.5137383483170523e-05, 'epoch': 0.51}) +[2026-07-27 06:33:25,344][starVLA.training.train_starvla][INFO] - Step 4216, Loss: {'train/loss': 0.2202884703874588, 'train/grad_norm_pre_clip': 4.21260929107666, 'timing/data': 0.00017841719090938568, 'timing/model': 0.4822090631350875, 'learning_rate/action_model': 6.0519855215878795e-05, 'learning_rate/action_query_proj': 6.0519855215878795e-05, 'learning_rate/base': 1.5129963803969699e-05, 'epoch': 0.51}) +[2026-07-27 06:33:30,975][starVLA.training.train_starvla][INFO] - Step 4217, Loss: {'train/loss': 0.21551942825317383, 'train/grad_norm_pre_clip': 4.096011161804199, 'timing/data': 0.0001775030978024006, 'timing/model': 0.4767544218339026, 'learning_rate/action_model': 6.049017313557158e-05, 'learning_rate/action_query_proj': 6.049017313557158e-05, 'learning_rate/base': 1.5122543283892895e-05, 'epoch': 0.51}) +[2026-07-27 06:33:36,613][starVLA.training.train_starvla][INFO] - Step 4218, Loss: {'train/loss': 0.34967541694641113, 'train/grad_norm_pre_clip': 4.607261657714844, 'timing/data': 0.00017796969041228294, 'timing/model': 0.47887149499729276, 'learning_rate/action_model': 6.046048770347849e-05, 'learning_rate/action_query_proj': 6.046048770347849e-05, 'learning_rate/base': 1.5115121925869622e-05, 'epoch': 0.51}) +[2026-07-27 06:33:42,251][starVLA.training.train_starvla][INFO] - Step 4219, Loss: {'train/loss': 0.18060439825057983, 'train/grad_norm_pre_clip': 3.267925500869751, 'timing/data': 0.00017813127487897873, 'timing/model': 0.4779963339678943, 'learning_rate/action_model': 6.043079893131882e-05, 'learning_rate/action_query_proj': 6.043079893131882e-05, 'learning_rate/base': 1.5107699732829706e-05, 'epoch': 0.51}) +[2026-07-27 06:33:47,890][starVLA.training.train_starvla][INFO] - Step 4220, Loss: {'train/loss': 0.13483653962612152, 'train/grad_norm_pre_clip': 2.569725751876831, 'timing/data': 0.00018447916954755783, 'timing/model': 0.4828328900039196, 'learning_rate/action_model': 6.040110683081326e-05, 'learning_rate/action_query_proj': 6.040110683081326e-05, 'learning_rate/base': 1.5100276707703315e-05, 'epoch': 0.51}) +[2026-07-27 06:33:53,500][starVLA.training.train_starvla][INFO] - Step 4221, Loss: {'train/loss': 0.2100849747657776, 'train/grad_norm_pre_clip': 3.5627710819244385, 'timing/data': 0.00017402973026037216, 'timing/model': 0.46651888312771916, 'learning_rate/action_model': 6.037141141368376e-05, 'learning_rate/action_query_proj': 6.037141141368376e-05, 'learning_rate/base': 1.509285285342094e-05, 'epoch': 0.51}) +[2026-07-27 06:33:59,146][starVLA.training.train_starvla][INFO] - Step 4222, Loss: {'train/loss': 0.31464168429374695, 'train/grad_norm_pre_clip': 4.1985931396484375, 'timing/data': 0.00017727119848132133, 'timing/model': 0.4832785790786147, 'learning_rate/action_model': 6.034171269165362e-05, 'learning_rate/action_query_proj': 6.034171269165362e-05, 'learning_rate/base': 1.5085428172913405e-05, 'epoch': 0.51}) +[2026-07-27 06:34:04,765][starVLA.training.train_starvla][INFO] - Step 4223, Loss: {'train/loss': 0.12762315571308136, 'train/grad_norm_pre_clip': 2.8437697887420654, 'timing/data': 0.00017509935423731804, 'timing/model': 0.4894622787833214, 'learning_rate/action_model': 6.031201067644742e-05, 'learning_rate/action_query_proj': 6.031201067644742e-05, 'learning_rate/base': 1.5078002669111855e-05, 'epoch': 0.51}) +[2026-07-27 06:34:10,377][starVLA.training.train_starvla][INFO] - Step 4224, Loss: {'train/loss': 0.2443448007106781, 'train/grad_norm_pre_clip': 2.9304404258728027, 'timing/data': 0.00018506497144699097, 'timing/model': 0.4781006812117994, 'learning_rate/action_model': 6.028230537979105e-05, 'learning_rate/action_query_proj': 6.028230537979105e-05, 'learning_rate/base': 1.5070576344947763e-05, 'epoch': 0.51}) +[2026-07-27 06:34:16,004][starVLA.training.train_starvla][INFO] - Step 4225, Loss: {'train/loss': 0.1755024641752243, 'train/grad_norm_pre_clip': 3.5564239025115967, 'timing/data': 0.00022988161072134972, 'timing/model': 0.47890738025307655, 'learning_rate/action_model': 6.025259681341166e-05, 'learning_rate/action_query_proj': 6.025259681341166e-05, 'learning_rate/base': 1.5063149203352914e-05, 'epoch': 0.51}) +[2026-07-27 06:34:21,615][starVLA.training.train_starvla][INFO] - Step 4226, Loss: {'train/loss': 0.16060160100460052, 'train/grad_norm_pre_clip': 2.4327337741851807, 'timing/data': 0.00017485488206148148, 'timing/model': 0.47700682282447815, 'learning_rate/action_model': 6.0222884989037755e-05, 'learning_rate/action_query_proj': 6.0222884989037755e-05, 'learning_rate/base': 1.5055721247259439e-05, 'epoch': 0.51}) +[2026-07-27 06:34:27,234][starVLA.training.train_starvla][INFO] - Step 4227, Loss: {'train/loss': 0.15606068074703217, 'train/grad_norm_pre_clip': 2.2549896240234375, 'timing/data': 0.00017147324979305267, 'timing/model': 0.4570548562332988, 'learning_rate/action_model': 6.0193169918399085e-05, 'learning_rate/action_query_proj': 6.0193169918399085e-05, 'learning_rate/base': 1.5048292479599771e-05, 'epoch': 0.51}) +[2026-07-27 06:34:32,867][starVLA.training.train_starvla][INFO] - Step 4228, Loss: {'train/loss': 0.17286942899227142, 'train/grad_norm_pre_clip': 2.965259075164795, 'timing/data': 0.00017925584688782692, 'timing/model': 0.47692534420639277, 'learning_rate/action_model': 6.016345161322669e-05, 'learning_rate/action_query_proj': 6.016345161322669e-05, 'learning_rate/base': 1.5040862903306672e-05, 'epoch': 0.51}) +[2026-07-27 06:34:38,527][starVLA.training.train_starvla][INFO] - Step 4229, Loss: {'train/loss': 0.12825588881969452, 'train/grad_norm_pre_clip': 2.653381824493408, 'timing/data': 0.00017514079809188843, 'timing/model': 0.48010662104934454, 'learning_rate/action_model': 6.013373008525287e-05, 'learning_rate/action_query_proj': 6.013373008525287e-05, 'learning_rate/base': 1.5033432521313217e-05, 'epoch': 0.51}) +[2026-07-27 06:34:44,144][starVLA.training.train_starvla][INFO] - Step 4230, Loss: {'train/loss': 0.16495861113071442, 'train/grad_norm_pre_clip': 2.392235517501831, 'timing/data': 0.00017499225214123726, 'timing/model': 0.4789907969534397, 'learning_rate/action_model': 6.0104005346211225e-05, 'learning_rate/action_query_proj': 6.0104005346211225e-05, 'learning_rate/base': 1.5026001336552806e-05, 'epoch': 0.51}) +[2026-07-27 06:34:49,746][starVLA.training.train_starvla][INFO] - Step 4231, Loss: {'train/loss': 0.11904323846101761, 'train/grad_norm_pre_clip': 3.2904512882232666, 'timing/data': 0.00017906399443745613, 'timing/model': 0.4741483461111784, 'learning_rate/action_model': 6.007427740783663e-05, 'learning_rate/action_query_proj': 6.007427740783663e-05, 'learning_rate/base': 1.5018569351959158e-05, 'epoch': 0.51}) +[2026-07-27 06:34:55,352][starVLA.training.train_starvla][INFO] - Step 4232, Loss: {'train/loss': 0.18691182136535645, 'train/grad_norm_pre_clip': 2.714329719543457, 'timing/data': 0.0001783040352165699, 'timing/model': 0.4768357099965215, 'learning_rate/action_model': 6.004454628186516e-05, 'learning_rate/action_query_proj': 6.004454628186516e-05, 'learning_rate/base': 1.501113657046629e-05, 'epoch': 0.51}) +[2026-07-27 06:35:00,965][starVLA.training.train_starvla][INFO] - Step 4233, Loss: {'train/loss': 0.1440325528383255, 'train/grad_norm_pre_clip': 3.383826732635498, 'timing/data': 0.00017922837287187576, 'timing/model': 0.4773790896870196, 'learning_rate/action_model': 6.001481198003425e-05, 'learning_rate/action_query_proj': 6.001481198003425e-05, 'learning_rate/base': 1.5003702995008562e-05, 'epoch': 0.51}) +[2026-07-27 06:35:06,575][starVLA.training.train_starvla][INFO] - Step 4234, Loss: {'train/loss': 0.24632294476032257, 'train/grad_norm_pre_clip': 4.321732044219971, 'timing/data': 0.00017645396292209625, 'timing/model': 0.48462204029783607, 'learning_rate/action_model': 5.9985074514082475e-05, 'learning_rate/action_query_proj': 5.9985074514082475e-05, 'learning_rate/base': 1.4996268628520619e-05, 'epoch': 0.51}) +[2026-07-27 06:35:12,322][starVLA.training.train_starvla][INFO] - Step 4235, Loss: {'train/loss': 0.2705363929271698, 'train/grad_norm_pre_clip': 3.748568058013916, 'timing/data': 0.00017425883561372757, 'timing/model': 0.4848422473296523, 'learning_rate/action_model': 5.995533389574976e-05, 'learning_rate/action_query_proj': 5.995533389574976e-05, 'learning_rate/base': 1.498883347393744e-05, 'epoch': 0.51}) +[2026-07-27 06:35:17,960][starVLA.training.train_starvla][INFO] - Step 4236, Loss: {'train/loss': 0.1398800015449524, 'train/grad_norm_pre_clip': 2.795482873916626, 'timing/data': 0.0002508601173758507, 'timing/model': 0.47378879273310304, 'learning_rate/action_model': 5.9925590136777187e-05, 'learning_rate/action_query_proj': 5.9925590136777187e-05, 'learning_rate/base': 1.4981397534194297e-05, 'epoch': 0.51}) +[2026-07-27 06:35:23,579][starVLA.training.train_starvla][INFO] - Step 4237, Loss: {'train/loss': 0.16716432571411133, 'train/grad_norm_pre_clip': 2.853682518005371, 'timing/data': 0.00018493877723813057, 'timing/model': 0.4755345140583813, 'learning_rate/action_model': 5.989584324890717e-05, 'learning_rate/action_query_proj': 5.989584324890717e-05, 'learning_rate/base': 1.4973960812226793e-05, 'epoch': 0.51}) +[2026-07-27 06:35:29,181][starVLA.training.train_starvla][INFO] - Step 4238, Loss: {'train/loss': 0.12214964628219604, 'train/grad_norm_pre_clip': 2.8021953105926514, 'timing/data': 0.0001903981901705265, 'timing/model': 0.4807139579206705, 'learning_rate/action_model': 5.986609324388327e-05, 'learning_rate/action_query_proj': 5.986609324388327e-05, 'learning_rate/base': 1.4966523310970817e-05, 'epoch': 0.51}) +[2026-07-27 06:35:34,787][starVLA.training.train_starvla][INFO] - Step 4239, Loss: {'train/loss': 0.13965804874897003, 'train/grad_norm_pre_clip': 2.566565752029419, 'timing/data': 0.000182274729013443, 'timing/model': 0.47684038477018476, 'learning_rate/action_model': 5.983634013345033e-05, 'learning_rate/action_query_proj': 5.983634013345033e-05, 'learning_rate/base': 1.4959085033362582e-05, 'epoch': 0.51}) +[2026-07-27 06:35:40,380][starVLA.training.train_starvla][INFO] - Step 4240, Loss: {'train/loss': 0.17660190165042877, 'train/grad_norm_pre_clip': 3.140700578689575, 'timing/data': 0.00017777876928448677, 'timing/model': 0.47732413886114955, 'learning_rate/action_model': 5.9806583929354424e-05, 'learning_rate/action_query_proj': 5.9806583929354424e-05, 'learning_rate/base': 1.4951645982338606e-05, 'epoch': 0.51}) +[2026-07-27 06:35:46,027][starVLA.training.train_starvla][INFO] - Step 4241, Loss: {'train/loss': 0.06819101423025131, 'train/grad_norm_pre_clip': 2.105654001235962, 'timing/data': 0.00017762882634997368, 'timing/model': 0.4780585030093789, 'learning_rate/action_model': 5.9776824643342813e-05, 'learning_rate/action_query_proj': 5.9776824643342813e-05, 'learning_rate/base': 1.4944206160835703e-05, 'epoch': 0.51}) +[2026-07-27 06:35:51,665][starVLA.training.train_starvla][INFO] - Step 4242, Loss: {'train/loss': 0.19918124377727509, 'train/grad_norm_pre_clip': 3.680743932723999, 'timing/data': 0.00018465332686901093, 'timing/model': 0.48195435106754303, 'learning_rate/action_model': 5.974706228716398e-05, 'learning_rate/action_query_proj': 5.974706228716398e-05, 'learning_rate/base': 1.4936765571790995e-05, 'epoch': 0.51}) +[2026-07-27 06:35:57,475][starVLA.training.train_starvla][INFO] - Step 4243, Loss: {'train/loss': 0.18544581532478333, 'train/grad_norm_pre_clip': 2.2760698795318604, 'timing/data': 0.00018089404329657555, 'timing/model': 0.47724719904363155, 'learning_rate/action_model': 5.971729687256765e-05, 'learning_rate/action_query_proj': 5.971729687256765e-05, 'learning_rate/base': 1.4929324218141913e-05, 'epoch': 0.51}) +[2026-07-27 06:36:03,085][starVLA.training.train_starvla][INFO] - Step 4244, Loss: {'train/loss': 0.15197281539440155, 'train/grad_norm_pre_clip': 2.4517250061035156, 'timing/data': 0.00017494289204478264, 'timing/model': 0.47747453209012747, 'learning_rate/action_model': 5.9687528411304736e-05, 'learning_rate/action_query_proj': 5.9687528411304736e-05, 'learning_rate/base': 1.4921882102826184e-05, 'epoch': 0.51}) +[2026-07-27 06:36:08,694][starVLA.training.train_starvla][INFO] - Step 4245, Loss: {'train/loss': 0.1505199521780014, 'train/grad_norm_pre_clip': 4.02630090713501, 'timing/data': 0.00018333503976464272, 'timing/model': 0.483118643052876, 'learning_rate/action_model': 5.965775691512735e-05, 'learning_rate/action_query_proj': 5.965775691512735e-05, 'learning_rate/base': 1.4914439228781838e-05, 'epoch': 0.51}) +[2026-07-27 06:36:14,290][starVLA.training.train_starvla][INFO] - Step 4246, Loss: {'train/loss': 0.2822515070438385, 'train/grad_norm_pre_clip': 3.1787891387939453, 'timing/data': 0.00016966741532087326, 'timing/model': 0.48250270122662187, 'learning_rate/action_model': 5.962798239578882e-05, 'learning_rate/action_query_proj': 5.962798239578882e-05, 'learning_rate/base': 1.4906995598947205e-05, 'epoch': 0.52}) +[2026-07-27 06:36:19,891][starVLA.training.train_starvla][INFO] - Step 4247, Loss: {'train/loss': 0.06076037511229515, 'train/grad_norm_pre_clip': 2.1305346488952637, 'timing/data': 0.00017320597544312477, 'timing/model': 0.4843555521219969, 'learning_rate/action_model': 5.9598204865043625e-05, 'learning_rate/action_query_proj': 5.9598204865043625e-05, 'learning_rate/base': 1.4899551216260906e-05, 'epoch': 0.52}) +[2026-07-27 06:36:25,488][starVLA.training.train_starvla][INFO] - Step 4248, Loss: {'train/loss': 0.1467105597257614, 'train/grad_norm_pre_clip': 2.4657657146453857, 'timing/data': 0.00017467793077230453, 'timing/model': 0.4801650047302246, 'learning_rate/action_model': 5.95684243346475e-05, 'learning_rate/action_query_proj': 5.95684243346475e-05, 'learning_rate/base': 1.4892106083661875e-05, 'epoch': 0.52}) +[2026-07-27 06:36:31,107][starVLA.training.train_starvla][INFO] - Step 4249, Loss: {'train/loss': 0.14477086067199707, 'train/grad_norm_pre_clip': 3.222978115081787, 'timing/data': 0.00018008984625339508, 'timing/model': 0.4758491818793118, 'learning_rate/action_model': 5.953864081635729e-05, 'learning_rate/action_query_proj': 5.953864081635729e-05, 'learning_rate/base': 1.4884660204089323e-05, 'epoch': 0.52}) +[2026-07-27 06:36:36,702][starVLA.training.train_starvla][INFO] - Step 4250, Loss: {'train/loss': 0.10400900989770889, 'train/grad_norm_pre_clip': 2.918363332748413, 'timing/data': 0.00017535779625177383, 'timing/model': 0.48205214738845825, 'learning_rate/action_model': 5.950885432193108e-05, 'learning_rate/action_query_proj': 5.950885432193108e-05, 'learning_rate/base': 1.487721358048277e-05, 'epoch': 0.52}) +[2026-07-27 06:36:42,292][starVLA.training.train_starvla][INFO] - Step 4251, Loss: {'train/loss': 0.1399305909872055, 'train/grad_norm_pre_clip': 3.204570770263672, 'timing/data': 0.00017766794189810753, 'timing/model': 0.4650308471173048, 'learning_rate/action_model': 5.947906486312812e-05, 'learning_rate/action_query_proj': 5.947906486312812e-05, 'learning_rate/base': 1.486976621578203e-05, 'epoch': 0.52}) +[2026-07-27 06:36:47,903][starVLA.training.train_starvla][INFO] - Step 4252, Loss: {'train/loss': 0.10207802057266235, 'train/grad_norm_pre_clip': 2.6951820850372314, 'timing/data': 0.00017461972311139107, 'timing/model': 0.4761522929184139, 'learning_rate/action_model': 5.944927245170877e-05, 'learning_rate/action_query_proj': 5.944927245170877e-05, 'learning_rate/base': 1.4862318112927192e-05, 'epoch': 0.52}) +[2026-07-27 06:36:53,501][starVLA.training.train_starvla][INFO] - Step 4253, Loss: {'train/loss': 0.20484763383865356, 'train/grad_norm_pre_clip': 4.9850335121154785, 'timing/data': 0.00017641810700297356, 'timing/model': 0.4704816942103207, 'learning_rate/action_model': 5.941947709943465e-05, 'learning_rate/action_query_proj': 5.941947709943465e-05, 'learning_rate/base': 1.4854869274858662e-05, 'epoch': 0.52}) +[2026-07-27 06:36:59,099][starVLA.training.train_starvla][INFO] - Step 4254, Loss: {'train/loss': 0.11441288143396378, 'train/grad_norm_pre_clip': 2.6762115955352783, 'timing/data': 0.0001759449951350689, 'timing/model': 0.4734333870001137, 'learning_rate/action_model': 5.938967881806847e-05, 'learning_rate/action_query_proj': 5.938967881806847e-05, 'learning_rate/base': 1.4847419704517118e-05, 'epoch': 0.52}) +[2026-07-27 06:37:04,695][starVLA.training.train_starvla][INFO] - Step 4255, Loss: {'train/loss': 0.18313851952552795, 'train/grad_norm_pre_clip': 3.0158658027648926, 'timing/data': 0.0001733880490064621, 'timing/model': 0.4685782538726926, 'learning_rate/action_model': 5.935987761937412e-05, 'learning_rate/action_query_proj': 5.935987761937412e-05, 'learning_rate/base': 1.483996940484353e-05, 'epoch': 0.52}) +[2026-07-27 06:37:10,321][starVLA.training.train_starvla][INFO] - Step 4256, Loss: {'train/loss': 0.09216508269309998, 'train/grad_norm_pre_clip': 2.4483678340911865, 'timing/data': 0.00017272960394620895, 'timing/model': 0.4886127533391118, 'learning_rate/action_model': 5.933007351511664e-05, 'learning_rate/action_query_proj': 5.933007351511664e-05, 'learning_rate/base': 1.483251837877916e-05, 'epoch': 0.52}) +[2026-07-27 06:37:15,909][starVLA.training.train_starvla][INFO] - Step 4257, Loss: {'train/loss': 0.2169366031885147, 'train/grad_norm_pre_clip': 3.9872374534606934, 'timing/data': 0.00018454808741807938, 'timing/model': 0.48313994985073805, 'learning_rate/action_model': 5.930026651706222e-05, 'learning_rate/action_query_proj': 5.930026651706222e-05, 'learning_rate/base': 1.4825066629265556e-05, 'epoch': 0.52}) +[2026-07-27 06:37:21,503][starVLA.training.train_starvla][INFO] - Step 4258, Loss: {'train/loss': 0.10211286693811417, 'train/grad_norm_pre_clip': 2.6805028915405273, 'timing/data': 0.00017639994621276855, 'timing/model': 0.48215180402621627, 'learning_rate/action_model': 5.92704566369782e-05, 'learning_rate/action_query_proj': 5.92704566369782e-05, 'learning_rate/base': 1.481761415924455e-05, 'epoch': 0.52}) +[2026-07-27 06:37:27,129][starVLA.training.train_starvla][INFO] - Step 4259, Loss: {'train/loss': 0.2322034388780594, 'train/grad_norm_pre_clip': 3.225160598754883, 'timing/data': 0.00017528515309095383, 'timing/model': 0.47905009612441063, 'learning_rate/action_model': 5.924064388663304e-05, 'learning_rate/action_query_proj': 5.924064388663304e-05, 'learning_rate/base': 1.481016097165826e-05, 'epoch': 0.52}) +[2026-07-27 06:37:32,722][starVLA.training.train_starvla][INFO] - Step 4260, Loss: {'train/loss': 0.2763027250766754, 'train/grad_norm_pre_clip': 3.4290523529052734, 'timing/data': 0.0001718541607260704, 'timing/model': 0.47851939406245947, 'learning_rate/action_model': 5.921082827779635e-05, 'learning_rate/action_query_proj': 5.921082827779635e-05, 'learning_rate/base': 1.4802707069449087e-05, 'epoch': 0.52}) +[2026-07-27 06:37:38,323][starVLA.training.train_starvla][INFO] - Step 4261, Loss: {'train/loss': 0.20976659655570984, 'train/grad_norm_pre_clip': 3.1605210304260254, 'timing/data': 0.00017477013170719147, 'timing/model': 0.4784312439151108, 'learning_rate/action_model': 5.918100982223884e-05, 'learning_rate/action_query_proj': 5.918100982223884e-05, 'learning_rate/base': 1.479525245555971e-05, 'epoch': 0.52}) +[2026-07-27 06:37:43,929][starVLA.training.train_starvla][INFO] - Step 4262, Loss: {'train/loss': 0.1389632225036621, 'train/grad_norm_pre_clip': 3.6182897090911865, 'timing/data': 0.00017202738672494888, 'timing/model': 0.47591188503429294, 'learning_rate/action_model': 5.9151188531732384e-05, 'learning_rate/action_query_proj': 5.9151188531732384e-05, 'learning_rate/base': 1.4787797132933096e-05, 'epoch': 0.52}) +[2026-07-27 06:37:49,539][starVLA.training.train_starvla][INFO] - Step 4263, Loss: {'train/loss': 0.2447059452533722, 'train/grad_norm_pre_clip': 3.5123167037963867, 'timing/data': 0.0001738928258419037, 'timing/model': 0.47903873585164547, 'learning_rate/action_model': 5.9121364418049954e-05, 'learning_rate/action_query_proj': 5.9121364418049954e-05, 'learning_rate/base': 1.4780341104512489e-05, 'epoch': 0.52}) +[2026-07-27 06:37:55,150][starVLA.training.train_starvla][INFO] - Step 4264, Loss: {'train/loss': 0.16616412997245789, 'train/grad_norm_pre_clip': 3.8815672397613525, 'timing/data': 0.00017651868984103203, 'timing/model': 0.4743150221183896, 'learning_rate/action_model': 5.909153749296563e-05, 'learning_rate/action_query_proj': 5.909153749296563e-05, 'learning_rate/base': 1.4772884373241407e-05, 'epoch': 0.52}) +[2026-07-27 06:38:00,765][starVLA.training.train_starvla][INFO] - Step 4265, Loss: {'train/loss': 0.15095660090446472, 'train/grad_norm_pre_clip': 3.320087432861328, 'timing/data': 0.00018852483481168747, 'timing/model': 0.4703563740476966, 'learning_rate/action_model': 5.906170776825459e-05, 'learning_rate/action_query_proj': 5.906170776825459e-05, 'learning_rate/base': 1.4765426942063648e-05, 'epoch': 0.52}) +[2026-07-27 06:38:06,377][starVLA.training.train_starvla][INFO] - Step 4266, Loss: {'train/loss': 0.13953599333763123, 'train/grad_norm_pre_clip': 3.896883726119995, 'timing/data': 0.00017297593876719475, 'timing/model': 0.48300547059625387, 'learning_rate/action_model': 5.903187525569319e-05, 'learning_rate/action_query_proj': 5.903187525569319e-05, 'learning_rate/base': 1.4757968813923298e-05, 'epoch': 0.52}) +[2026-07-27 06:38:12,232][starVLA.training.train_starvla][INFO] - Step 4267, Loss: {'train/loss': 0.1836111694574356, 'train/grad_norm_pre_clip': 2.4730443954467773, 'timing/data': 0.0001822458580136299, 'timing/model': 0.4800760122016072, 'learning_rate/action_model': 5.9002039967058785e-05, 'learning_rate/action_query_proj': 5.9002039967058785e-05, 'learning_rate/base': 1.4750509991764696e-05, 'epoch': 0.52}) +[2026-07-27 06:38:17,849][starVLA.training.train_starvla][INFO] - Step 4268, Loss: {'train/loss': 0.1623842418193817, 'train/grad_norm_pre_clip': 3.4338600635528564, 'timing/data': 0.00017537688836455345, 'timing/model': 0.46980328019708395, 'learning_rate/action_model': 5.89722019141299e-05, 'learning_rate/action_query_proj': 5.89722019141299e-05, 'learning_rate/base': 1.4743050478532474e-05, 'epoch': 0.52}) +[2026-07-27 06:38:23,426][starVLA.training.train_starvla][INFO] - Step 4269, Loss: {'train/loss': 0.17475253343582153, 'train/grad_norm_pre_clip': 3.0001161098480225, 'timing/data': 0.00017840275540947914, 'timing/model': 0.46936415089294314, 'learning_rate/action_model': 5.894236110868612e-05, 'learning_rate/action_query_proj': 5.894236110868612e-05, 'learning_rate/base': 1.473559027717153e-05, 'epoch': 0.52}) +[2026-07-27 06:38:29,309][starVLA.training.train_starvla][INFO] - Step 4270, Loss: {'train/loss': 0.1936461329460144, 'train/grad_norm_pre_clip': 2.5016610622406006, 'timing/data': 0.0001737913116812706, 'timing/model': 0.47611712105572224, 'learning_rate/action_model': 5.8912517562508104e-05, 'learning_rate/action_query_proj': 5.8912517562508104e-05, 'learning_rate/base': 1.4728129390627026e-05, 'epoch': 0.52}) +[2026-07-27 06:38:34,918][starVLA.training.train_starvla][INFO] - Step 4271, Loss: {'train/loss': 0.2231062799692154, 'train/grad_norm_pre_clip': 4.224583625793457, 'timing/data': 0.00017693964764475822, 'timing/model': 0.4880088148638606, 'learning_rate/action_model': 5.8882671287377644e-05, 'learning_rate/action_query_proj': 5.8882671287377644e-05, 'learning_rate/base': 1.4720667821844411e-05, 'epoch': 0.52}) +[2026-07-27 06:38:40,540][starVLA.training.train_starvla][INFO] - Step 4272, Loss: {'train/loss': 0.15403962135314941, 'train/grad_norm_pre_clip': 3.269582986831665, 'timing/data': 0.00017736060544848442, 'timing/model': 0.48173194471746683, 'learning_rate/action_model': 5.885282229507755e-05, 'learning_rate/action_query_proj': 5.885282229507755e-05, 'learning_rate/base': 1.4713205573769387e-05, 'epoch': 0.52}) +[2026-07-27 06:38:46,148][starVLA.training.train_starvla][INFO] - Step 4273, Loss: {'train/loss': 0.18810240924358368, 'train/grad_norm_pre_clip': 4.031045913696289, 'timing/data': 0.00018265191465616226, 'timing/model': 0.4827662259340286, 'learning_rate/action_model': 5.8822970597391745e-05, 'learning_rate/action_query_proj': 5.8822970597391745e-05, 'learning_rate/base': 1.4705742649347936e-05, 'epoch': 0.52}) +[2026-07-27 06:38:51,744][starVLA.training.train_starvla][INFO] - Step 4274, Loss: {'train/loss': 0.1779554784297943, 'train/grad_norm_pre_clip': 2.858090877532959, 'timing/data': 0.00020844163373112679, 'timing/model': 0.4801883529871702, 'learning_rate/action_model': 5.8793116206105215e-05, 'learning_rate/action_query_proj': 5.8793116206105215e-05, 'learning_rate/base': 1.4698279051526304e-05, 'epoch': 0.52}) +[2026-07-27 06:38:57,331][starVLA.training.train_starvla][INFO] - Step 4275, Loss: {'train/loss': 0.13185164332389832, 'train/grad_norm_pre_clip': 2.828620433807373, 'timing/data': 0.00017623277381062508, 'timing/model': 0.4833696549758315, 'learning_rate/action_model': 5.876325913300397e-05, 'learning_rate/action_query_proj': 5.876325913300397e-05, 'learning_rate/base': 1.4690814783250992e-05, 'epoch': 0.52}) +[2026-07-27 06:39:02,920][starVLA.training.train_starvla][INFO] - Step 4276, Loss: {'train/loss': 0.17653663456439972, 'train/grad_norm_pre_clip': 3.270141363143921, 'timing/data': 0.00017449725419282913, 'timing/model': 0.4776067780330777, 'learning_rate/action_model': 5.8733399389875144e-05, 'learning_rate/action_query_proj': 5.8733399389875144e-05, 'learning_rate/base': 1.4683349847468786e-05, 'epoch': 0.52}) +[2026-07-27 06:39:08,745][starVLA.training.train_starvla][INFO] - Step 4277, Loss: {'train/loss': 0.10481981188058853, 'train/grad_norm_pre_clip': 2.2485275268554688, 'timing/data': 0.00017606886103749275, 'timing/model': 0.47787790512666106, 'learning_rate/action_model': 5.870353698850686e-05, 'learning_rate/action_query_proj': 5.870353698850686e-05, 'learning_rate/base': 1.4675884247126715e-05, 'epoch': 0.52}) +[2026-07-27 06:39:14,337][starVLA.training.train_starvla][INFO] - Step 4278, Loss: {'train/loss': 0.1270962655544281, 'train/grad_norm_pre_clip': 3.203852891921997, 'timing/data': 0.00017621181905269623, 'timing/model': 0.48154740082100034, 'learning_rate/action_model': 5.8673671940688344e-05, 'learning_rate/action_query_proj': 5.8673671940688344e-05, 'learning_rate/base': 1.4668417985172086e-05, 'epoch': 0.52}) +[2026-07-27 06:39:19,934][starVLA.training.train_starvla][INFO] - Step 4279, Loss: {'train/loss': 0.11330489069223404, 'train/grad_norm_pre_clip': 2.4524857997894287, 'timing/data': 0.00017017778009176254, 'timing/model': 0.47986629512161016, 'learning_rate/action_model': 5.864380425820984e-05, 'learning_rate/action_query_proj': 5.864380425820984e-05, 'learning_rate/base': 1.466095106455246e-05, 'epoch': 0.52}) +[2026-07-27 06:39:25,536][starVLA.training.train_starvla][INFO] - Step 4280, Loss: {'train/loss': 0.12160783261060715, 'train/grad_norm_pre_clip': 2.690406322479248, 'timing/data': 0.0001775939017534256, 'timing/model': 0.4746469152159989, 'learning_rate/action_model': 5.8613933952862634e-05, 'learning_rate/action_query_proj': 5.8613933952862634e-05, 'learning_rate/base': 1.4653483488215659e-05, 'epoch': 0.52}) +[2026-07-27 06:39:31,134][starVLA.training.train_starvla][INFO] - Step 4281, Loss: {'train/loss': 0.19595597684383392, 'train/grad_norm_pre_clip': 2.720991611480713, 'timing/data': 0.00018537696450948715, 'timing/model': 0.48187171993777156, 'learning_rate/action_model': 5.858406103643904e-05, 'learning_rate/action_query_proj': 5.858406103643904e-05, 'learning_rate/base': 1.464601525910976e-05, 'epoch': 0.52}) +[2026-07-27 06:39:36,860][starVLA.training.train_starvla][INFO] - Step 4282, Loss: {'train/loss': 0.062404900789260864, 'train/grad_norm_pre_clip': 1.7974196672439575, 'timing/data': 0.0002108439803123474, 'timing/model': 0.6029874780215323, 'learning_rate/action_model': 5.855418552073243e-05, 'learning_rate/action_query_proj': 5.855418552073243e-05, 'learning_rate/base': 1.4638546380183108e-05, 'epoch': 0.52}) +[2026-07-27 06:39:42,471][starVLA.training.train_starvla][INFO] - Step 4283, Loss: {'train/loss': 0.16296716034412384, 'train/grad_norm_pre_clip': 2.6324946880340576, 'timing/data': 0.0001734066754579544, 'timing/model': 0.4777125110849738, 'learning_rate/action_model': 5.852430741753717e-05, 'learning_rate/action_query_proj': 5.852430741753717e-05, 'learning_rate/base': 1.4631076854384293e-05, 'epoch': 0.52}) +[2026-07-27 06:39:48,101][starVLA.training.train_starvla][INFO] - Step 4284, Loss: {'train/loss': 0.25257381796836853, 'train/grad_norm_pre_clip': 4.185458183288574, 'timing/data': 0.0002682381309568882, 'timing/model': 0.48136581759899855, 'learning_rate/action_model': 5.8494426738648656e-05, 'learning_rate/action_query_proj': 5.8494426738648656e-05, 'learning_rate/base': 1.4623606684662164e-05, 'epoch': 0.52}) +[2026-07-27 06:39:53,743][starVLA.training.train_starvla][INFO] - Step 4285, Loss: {'train/loss': 0.1004348024725914, 'train/grad_norm_pre_clip': 2.348872661590576, 'timing/data': 0.0001863008365035057, 'timing/model': 0.48157945182174444, 'learning_rate/action_model': 5.846454349586333e-05, 'learning_rate/action_query_proj': 5.846454349586333e-05, 'learning_rate/base': 1.4616135873965833e-05, 'epoch': 0.52}) +[2026-07-27 06:39:59,573][starVLA.training.train_starvla][INFO] - Step 4286, Loss: {'train/loss': 0.1794448345899582, 'train/grad_norm_pre_clip': 3.0318527221679688, 'timing/data': 0.0001827985979616642, 'timing/model': 0.4750619572587311, 'learning_rate/action_model': 5.843465770097861e-05, 'learning_rate/action_query_proj': 5.843465770097861e-05, 'learning_rate/base': 1.4608664425244652e-05, 'epoch': 0.52}) +[2026-07-27 06:40:05,209][starVLA.training.train_starvla][INFO] - Step 4287, Loss: {'train/loss': 0.16771888732910156, 'train/grad_norm_pre_clip': 2.4668807983398438, 'timing/data': 0.0001928950659930706, 'timing/model': 0.4840472601354122, 'learning_rate/action_model': 5.840476936579292e-05, 'learning_rate/action_query_proj': 5.840476936579292e-05, 'learning_rate/base': 1.460119234144823e-05, 'epoch': 0.52}) +[2026-07-27 06:40:10,840][starVLA.training.train_starvla][INFO] - Step 4288, Loss: {'train/loss': 0.1220477819442749, 'train/grad_norm_pre_clip': 3.719896078109741, 'timing/data': 0.00023528560996055603, 'timing/model': 0.4717516843229532, 'learning_rate/action_model': 5.8374878502105745e-05, 'learning_rate/action_query_proj': 5.8374878502105745e-05, 'learning_rate/base': 1.4593719625526436e-05, 'epoch': 0.52}) +[2026-07-27 06:40:16,488][starVLA.training.train_starvla][INFO] - Step 4289, Loss: {'train/loss': 0.15635690093040466, 'train/grad_norm_pre_clip': 3.3148088455200195, 'timing/data': 0.00018429802730679512, 'timing/model': 0.4827854251489043, 'learning_rate/action_model': 5.834498512171748e-05, 'learning_rate/action_query_proj': 5.834498512171748e-05, 'learning_rate/base': 1.458624628042937e-05, 'epoch': 0.52}) +[2026-07-27 06:40:22,071][starVLA.training.train_starvla][INFO] - Step 4290, Loss: {'train/loss': 0.22259250283241272, 'train/grad_norm_pre_clip': 3.0732171535491943, 'timing/data': 0.0001834551803767681, 'timing/model': 0.46899755392223597, 'learning_rate/action_model': 5.8315089236429566e-05, 'learning_rate/action_query_proj': 5.8315089236429566e-05, 'learning_rate/base': 1.4578772309107391e-05, 'epoch': 0.52}) +[2026-07-27 06:40:27,655][starVLA.training.train_starvla][INFO] - Step 4291, Loss: {'train/loss': 0.1488756239414215, 'train/grad_norm_pre_clip': 2.57134747505188, 'timing/data': 0.00018515530973672867, 'timing/model': 0.4830743819475174, 'learning_rate/action_model': 5.828519085804444e-05, 'learning_rate/action_query_proj': 5.828519085804444e-05, 'learning_rate/base': 1.457129771451111e-05, 'epoch': 0.52}) +[2026-07-27 06:40:33,216][starVLA.training.train_starvla][INFO] - Step 4292, Loss: {'train/loss': 0.060682978481054306, 'train/grad_norm_pre_clip': 2.1413323879241943, 'timing/data': 0.00017312029376626015, 'timing/model': 0.4780065482482314, 'learning_rate/action_model': 5.8255289998365515e-05, 'learning_rate/action_query_proj': 5.8255289998365515e-05, 'learning_rate/base': 1.4563822499591379e-05, 'epoch': 0.52}) +[2026-07-27 06:40:38,802][starVLA.training.train_starvla][INFO] - Step 4293, Loss: {'train/loss': 0.20417770743370056, 'train/grad_norm_pre_clip': 3.63681697845459, 'timing/data': 0.0001732129603624344, 'timing/model': 0.4731105021201074, 'learning_rate/action_model': 5.822538666919715e-05, 'learning_rate/action_query_proj': 5.822538666919715e-05, 'learning_rate/base': 1.4556346667299287e-05, 'epoch': 0.52}) +[2026-07-27 06:40:44,393][starVLA.training.train_starvla][INFO] - Step 4294, Loss: {'train/loss': 0.19733713567256927, 'train/grad_norm_pre_clip': 3.576920986175537, 'timing/data': 0.00017274776473641396, 'timing/model': 0.48216176498681307, 'learning_rate/action_model': 5.819548088234471e-05, 'learning_rate/action_query_proj': 5.819548088234471e-05, 'learning_rate/base': 1.4548870220586177e-05, 'epoch': 0.52}) +[2026-07-27 06:40:50,026][starVLA.training.train_starvla][INFO] - Step 4295, Loss: {'train/loss': 0.18818776309490204, 'train/grad_norm_pre_clip': 3.4520115852355957, 'timing/data': 0.00017169024795293808, 'timing/model': 0.48119158716872334, 'learning_rate/action_model': 5.816557264961454e-05, 'learning_rate/action_query_proj': 5.816557264961454e-05, 'learning_rate/base': 1.4541393162403635e-05, 'epoch': 0.52}) +[2026-07-27 06:40:55,835][starVLA.training.train_starvla][INFO] - Step 4296, Loss: {'train/loss': 0.0795169249176979, 'train/grad_norm_pre_clip': 2.785339593887329, 'timing/data': 0.00018122000619769096, 'timing/model': 0.46870484901592135, 'learning_rate/action_model': 5.813566198281394e-05, 'learning_rate/action_query_proj': 5.813566198281394e-05, 'learning_rate/base': 1.4533915495703485e-05, 'epoch': 0.52}) +[2026-07-27 06:41:01,460][starVLA.training.train_starvla][INFO] - Step 4297, Loss: {'train/loss': 0.13957437872886658, 'train/grad_norm_pre_clip': 2.5256214141845703, 'timing/data': 0.00017157290130853653, 'timing/model': 0.48078769259154797, 'learning_rate/action_model': 5.8105748893751164e-05, 'learning_rate/action_query_proj': 5.8105748893751164e-05, 'learning_rate/base': 1.4526437223437791e-05, 'epoch': 0.52}) +[2026-07-27 06:41:07,068][starVLA.training.train_starvla][INFO] - Step 4298, Loss: {'train/loss': 0.07515682280063629, 'train/grad_norm_pre_clip': 2.754420757293701, 'timing/data': 0.0001782621257007122, 'timing/model': 0.47830204106867313, 'learning_rate/action_model': 5.80758333942354e-05, 'learning_rate/action_query_proj': 5.80758333942354e-05, 'learning_rate/base': 1.451895834855885e-05, 'epoch': 0.52}) +[2026-07-27 06:41:12,723][starVLA.training.train_starvla][INFO] - Step 4299, Loss: {'train/loss': 0.09036747366189957, 'train/grad_norm_pre_clip': 3.072800397872925, 'timing/data': 0.00017953384667634964, 'timing/model': 0.47622038470581174, 'learning_rate/action_model': 5.8045915496076853e-05, 'learning_rate/action_query_proj': 5.8045915496076853e-05, 'learning_rate/base': 1.4511478874019213e-05, 'epoch': 0.52}) +[2026-07-27 06:41:18,339][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 4300 +[2026-07-27 06:41:18,340][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 4300 +[2026-07-27 06:41:18,341][starVLA.training.train_starvla][INFO] - Step 4300, Loss: {'train/loss': 0.05803941190242767, 'train/grad_norm_pre_clip': 1.6018002033233643, 'timing/data': 0.0001733102835714817, 'timing/model': 0.4772881562821567, 'learning_rate/action_model': 5.80159952110866e-05, 'learning_rate/action_query_proj': 5.80159952110866e-05, 'learning_rate/base': 1.450399880277165e-05, 'epoch': 0.52}) +[2026-07-27 06:41:23,973][starVLA.training.train_starvla][INFO] - Step 4301, Loss: {'train/loss': 0.19759248197078705, 'train/grad_norm_pre_clip': 2.6685454845428467, 'timing/data': 0.0002400306984782219, 'timing/model': 0.4812848879955709, 'learning_rate/action_model': 5.798607255107674e-05, 'learning_rate/action_query_proj': 5.798607255107674e-05, 'learning_rate/base': 1.4496518137769186e-05, 'epoch': 0.52}) +[2026-07-27 06:41:29,605][starVLA.training.train_starvla][INFO] - Step 4302, Loss: {'train/loss': 0.1447656899690628, 'train/grad_norm_pre_clip': 3.0094189643859863, 'timing/data': 0.00017499085515737534, 'timing/model': 0.48161139991134405, 'learning_rate/action_model': 5.795614752786023e-05, 'learning_rate/action_query_proj': 5.795614752786023e-05, 'learning_rate/base': 1.4489036881965057e-05, 'epoch': 0.52}) +[2026-07-27 06:41:35,259][starVLA.training.train_starvla][INFO] - Step 4303, Loss: {'train/loss': 0.1845027506351471, 'train/grad_norm_pre_clip': 3.982977867126465, 'timing/data': 0.00017312634736299515, 'timing/model': 0.4839555788785219, 'learning_rate/action_model': 5.792622015325098e-05, 'learning_rate/action_query_proj': 5.792622015325098e-05, 'learning_rate/base': 1.4481555038312744e-05, 'epoch': 0.52}) +[2026-07-27 06:41:40,874][starVLA.training.train_starvla][INFO] - Step 4304, Loss: {'train/loss': 0.1965419203042984, 'train/grad_norm_pre_clip': 3.5357470512390137, 'timing/data': 0.00018777372315526009, 'timing/model': 0.4777840259484947, 'learning_rate/action_model': 5.789629043906388e-05, 'learning_rate/action_query_proj': 5.789629043906388e-05, 'learning_rate/base': 1.447407260976597e-05, 'epoch': 0.52}) +[2026-07-27 06:41:46,524][starVLA.training.train_starvla][INFO] - Step 4305, Loss: {'train/loss': 0.060530297458171844, 'train/grad_norm_pre_clip': 1.777428388595581, 'timing/data': 0.00017587188631296158, 'timing/model': 0.48795223562046885, 'learning_rate/action_model': 5.78663583971147e-05, 'learning_rate/action_query_proj': 5.78663583971147e-05, 'learning_rate/base': 1.4466589599278674e-05, 'epoch': 0.52}) +[2026-07-27 06:41:52,162][starVLA.training.train_starvla][INFO] - Step 4306, Loss: {'train/loss': 0.1822180598974228, 'train/grad_norm_pre_clip': 3.52150559425354, 'timing/data': 0.00017027603462338448, 'timing/model': 0.4812226938083768, 'learning_rate/action_model': 5.7836424039220126e-05, 'learning_rate/action_query_proj': 5.7836424039220126e-05, 'learning_rate/base': 1.4459106009805031e-05, 'epoch': 0.52}) +[2026-07-27 06:41:57,792][starVLA.training.train_starvla][INFO] - Step 4307, Loss: {'train/loss': 0.14333271980285645, 'train/grad_norm_pre_clip': 2.219586133956909, 'timing/data': 0.00017281435430049896, 'timing/model': 0.47571490705013275, 'learning_rate/action_model': 5.7806487377197785e-05, 'learning_rate/action_query_proj': 5.7806487377197785e-05, 'learning_rate/base': 1.4451621844299446e-05, 'epoch': 0.52}) +[2026-07-27 06:42:03,434][starVLA.training.train_starvla][INFO] - Step 4308, Loss: {'train/loss': 0.1917443424463272, 'train/grad_norm_pre_clip': 3.2730298042297363, 'timing/data': 0.00017641205340623856, 'timing/model': 0.4886139570735395, 'learning_rate/action_model': 5.777654842286616e-05, 'learning_rate/action_query_proj': 5.777654842286616e-05, 'learning_rate/base': 1.444413710571654e-05, 'epoch': 0.52}) +[2026-07-27 06:42:09,031][starVLA.training.train_starvla][INFO] - Step 4309, Loss: {'train/loss': 0.23474717140197754, 'train/grad_norm_pre_clip': 3.833718776702881, 'timing/data': 0.00018339604139328003, 'timing/model': 0.45916944881901145, 'learning_rate/action_model': 5.774660718804471e-05, 'learning_rate/action_query_proj': 5.774660718804471e-05, 'learning_rate/base': 1.4436651797011177e-05, 'epoch': 0.52}) +[2026-07-27 06:42:14,606][starVLA.training.train_starvla][INFO] - Step 4310, Loss: {'train/loss': 0.11599653214216232, 'train/grad_norm_pre_clip': 2.5353848934173584, 'timing/data': 0.0001714807003736496, 'timing/model': 0.4593105958774686, 'learning_rate/action_model': 5.7716663684553754e-05, 'learning_rate/action_query_proj': 5.7716663684553754e-05, 'learning_rate/base': 1.4429165921138438e-05, 'epoch': 0.52}) +[2026-07-27 06:42:20,173][starVLA.training.train_starvla][INFO] - Step 4311, Loss: {'train/loss': 0.24345169961452484, 'train/grad_norm_pre_clip': 3.727952003479004, 'timing/data': 0.00016765762120485306, 'timing/model': 0.46437102276831865, 'learning_rate/action_model': 5.768671792421452e-05, 'learning_rate/action_query_proj': 5.768671792421452e-05, 'learning_rate/base': 1.442167948105363e-05, 'epoch': 0.52}) +[2026-07-27 06:42:25,729][starVLA.training.train_starvla][INFO] - Step 4312, Loss: {'train/loss': 0.18104268610477448, 'train/grad_norm_pre_clip': 2.9786903858184814, 'timing/data': 0.00017431238666176796, 'timing/model': 0.46443803794682026, 'learning_rate/action_model': 5.76567699188491e-05, 'learning_rate/action_query_proj': 5.76567699188491e-05, 'learning_rate/base': 1.4414192479712275e-05, 'epoch': 0.52}) +[2026-07-27 06:42:31,267][starVLA.training.train_starvla][INFO] - Step 4313, Loss: {'train/loss': 0.21100370585918427, 'train/grad_norm_pre_clip': 3.383547782897949, 'timing/data': 0.00016992073506116867, 'timing/model': 0.4611017107963562, 'learning_rate/action_model': 5.7626819680280485e-05, 'learning_rate/action_query_proj': 5.7626819680280485e-05, 'learning_rate/base': 1.4406704920070121e-05, 'epoch': 0.52}) +[2026-07-27 06:42:36,828][starVLA.training.train_starvla][INFO] - Step 4314, Loss: {'train/loss': 0.15751045942306519, 'train/grad_norm_pre_clip': 2.9975969791412354, 'timing/data': 0.00018068170174956322, 'timing/model': 0.46313836704939604, 'learning_rate/action_model': 5.7596867220332596e-05, 'learning_rate/action_query_proj': 5.7596867220332596e-05, 'learning_rate/base': 1.4399216805083149e-05, 'epoch': 0.52}) +[2026-07-27 06:42:42,374][starVLA.training.train_starvla][INFO] - Step 4315, Loss: {'train/loss': 0.27252697944641113, 'train/grad_norm_pre_clip': 4.303757667541504, 'timing/data': 0.0001825992949306965, 'timing/model': 0.4592462480068207, 'learning_rate/action_model': 5.756691255083015e-05, 'learning_rate/action_query_proj': 5.756691255083015e-05, 'learning_rate/base': 1.4391728137707538e-05, 'epoch': 0.52}) +[2026-07-27 06:42:47,929][starVLA.training.train_starvla][INFO] - Step 4316, Loss: {'train/loss': 0.13735057413578033, 'train/grad_norm_pre_clip': 2.894378423690796, 'timing/data': 0.00017492007464170456, 'timing/model': 0.4611549279652536, 'learning_rate/action_model': 5.7536955683598806e-05, 'learning_rate/action_query_proj': 5.7536955683598806e-05, 'learning_rate/base': 1.4384238920899701e-05, 'epoch': 0.52}) +[2026-07-27 06:42:53,499][starVLA.training.train_starvla][INFO] - Step 4317, Loss: {'train/loss': 0.09496267884969711, 'train/grad_norm_pre_clip': 3.102181911468506, 'timing/data': 0.00017184996977448463, 'timing/model': 0.46340032387524843, 'learning_rate/action_model': 5.750699663046504e-05, 'learning_rate/action_query_proj': 5.750699663046504e-05, 'learning_rate/base': 1.437674915761626e-05, 'epoch': 0.52}) +[2026-07-27 06:42:59,034][starVLA.training.train_starvla][INFO] - Step 4318, Loss: {'train/loss': 0.15361793339252472, 'train/grad_norm_pre_clip': 2.5064620971679688, 'timing/data': 0.0001644231379032135, 'timing/model': 0.4617041847668588, 'learning_rate/action_model': 5.747703540325622e-05, 'learning_rate/action_query_proj': 5.747703540325622e-05, 'learning_rate/base': 1.4369258850814055e-05, 'epoch': 0.52}) +[2026-07-27 06:43:04,588][starVLA.training.train_starvla][INFO] - Step 4319, Loss: {'train/loss': 0.17872515320777893, 'train/grad_norm_pre_clip': 3.6495261192321777, 'timing/data': 0.00017045298591256142, 'timing/model': 0.464098306838423, 'learning_rate/action_model': 5.744707201380055e-05, 'learning_rate/action_query_proj': 5.744707201380055e-05, 'learning_rate/base': 1.4361768003450137e-05, 'epoch': 0.52}) +[2026-07-27 06:43:10,130][starVLA.training.train_starvla][INFO] - Step 4320, Loss: {'train/loss': 0.17833025753498077, 'train/grad_norm_pre_clip': 3.204038143157959, 'timing/data': 0.00017106486484408379, 'timing/model': 0.4638617462478578, 'learning_rate/action_model': 5.741710647392712e-05, 'learning_rate/action_query_proj': 5.741710647392712e-05, 'learning_rate/base': 1.435427661848178e-05, 'epoch': 0.52}) +[2026-07-27 06:43:15,668][starVLA.training.train_starvla][INFO] - Step 4321, Loss: {'train/loss': 0.1124761626124382, 'train/grad_norm_pre_clip': 2.8853511810302734, 'timing/data': 0.0001717451959848404, 'timing/model': 0.4653963102027774, 'learning_rate/action_model': 5.7387138795465855e-05, 'learning_rate/action_query_proj': 5.7387138795465855e-05, 'learning_rate/base': 1.4346784698866464e-05, 'epoch': 0.52}) +[2026-07-27 06:43:21,228][starVLA.training.train_starvla][INFO] - Step 4322, Loss: {'train/loss': 0.11639813333749771, 'train/grad_norm_pre_clip': 2.7024424076080322, 'timing/data': 0.0002116910181939602, 'timing/model': 0.46135286474600434, 'learning_rate/action_model': 5.735716899024751e-05, 'learning_rate/action_query_proj': 5.735716899024751e-05, 'learning_rate/base': 1.4339292247561877e-05, 'epoch': 0.52}) +[2026-07-27 06:43:26,778][starVLA.training.train_starvla][INFO] - Step 4323, Loss: {'train/loss': 0.11168058216571808, 'train/grad_norm_pre_clip': 2.370319366455078, 'timing/data': 0.0001712399534881115, 'timing/model': 0.456058825366199, 'learning_rate/action_model': 5.732719707010368e-05, 'learning_rate/action_query_proj': 5.732719707010368e-05, 'learning_rate/base': 1.433179926752592e-05, 'epoch': 0.52}) +[2026-07-27 06:43:32,331][starVLA.training.train_starvla][INFO] - Step 4324, Loss: {'train/loss': 0.24309533834457397, 'train/grad_norm_pre_clip': 3.9234514236450195, 'timing/data': 0.00017519202083349228, 'timing/model': 0.46162342512980103, 'learning_rate/action_model': 5.729722304686681e-05, 'learning_rate/action_query_proj': 5.729722304686681e-05, 'learning_rate/base': 1.4324305761716702e-05, 'epoch': 0.52}) +[2026-07-27 06:43:37,854][starVLA.training.train_starvla][INFO] - Step 4325, Loss: {'train/loss': 0.10481087118387222, 'train/grad_norm_pre_clip': 2.5506787300109863, 'timing/data': 0.0001753680408000946, 'timing/model': 0.4570868029259145, 'learning_rate/action_model': 5.726724693237017e-05, 'learning_rate/action_query_proj': 5.726724693237017e-05, 'learning_rate/base': 1.4316811733092542e-05, 'epoch': 0.52}) +[2026-07-27 06:43:43,395][starVLA.training.train_starvla][INFO] - Step 4326, Loss: {'train/loss': 0.19769391417503357, 'train/grad_norm_pre_clip': 3.7392590045928955, 'timing/data': 0.0001742062158882618, 'timing/model': 0.463458193000406, 'learning_rate/action_model': 5.723726873844787e-05, 'learning_rate/action_query_proj': 5.723726873844787e-05, 'learning_rate/base': 1.4309317184611968e-05, 'epoch': 0.52}) +[2026-07-27 06:43:49,173][starVLA.training.train_starvla][INFO] - Step 4327, Loss: {'train/loss': 0.09454619884490967, 'train/grad_norm_pre_clip': 2.6030385494232178, 'timing/data': 0.00017310958355665207, 'timing/model': 0.4593591522425413, 'learning_rate/action_model': 5.7207288476934814e-05, 'learning_rate/action_query_proj': 5.7207288476934814e-05, 'learning_rate/base': 1.4301822119233703e-05, 'epoch': 0.52}) +[2026-07-27 06:43:54,758][starVLA.training.train_starvla][INFO] - Step 4328, Loss: {'train/loss': 0.09362911432981491, 'train/grad_norm_pre_clip': 2.5713894367218018, 'timing/data': 0.00016918731853365898, 'timing/model': 0.4634982459247112, 'learning_rate/action_model': 5.7177306159666736e-05, 'learning_rate/action_query_proj': 5.7177306159666736e-05, 'learning_rate/base': 1.4294326539916684e-05, 'epoch': 0.53}) +[2026-07-27 06:44:00,324][starVLA.training.train_starvla][INFO] - Step 4329, Loss: {'train/loss': 0.13288241624832153, 'train/grad_norm_pre_clip': 2.9135358333587646, 'timing/data': 0.00017290422692894936, 'timing/model': 0.46452392591163516, 'learning_rate/action_model': 5.714732179848017e-05, 'learning_rate/action_query_proj': 5.714732179848017e-05, 'learning_rate/base': 1.4286830449620042e-05, 'epoch': 0.53}) +[2026-07-27 06:44:05,910][starVLA.training.train_starvla][INFO] - Step 4330, Loss: {'train/loss': 0.1433621495962143, 'train/grad_norm_pre_clip': 3.6205954551696777, 'timing/data': 0.00018496671691536903, 'timing/model': 0.4591540638357401, 'learning_rate/action_model': 5.711733540521248e-05, 'learning_rate/action_query_proj': 5.711733540521248e-05, 'learning_rate/base': 1.427933385130312e-05, 'epoch': 0.53}) +[2026-07-27 06:44:11,492][starVLA.training.train_starvla][INFO] - Step 4331, Loss: {'train/loss': 0.16952598094940186, 'train/grad_norm_pre_clip': 2.8460376262664795, 'timing/data': 0.00017155427485704422, 'timing/model': 0.46523299301043153, 'learning_rate/action_model': 5.708734699170181e-05, 'learning_rate/action_query_proj': 5.708734699170181e-05, 'learning_rate/base': 1.4271836747925452e-05, 'epoch': 0.53}) +[2026-07-27 06:44:17,066][starVLA.training.train_starvla][INFO] - Step 4332, Loss: {'train/loss': 0.14365123212337494, 'train/grad_norm_pre_clip': 2.8408212661743164, 'timing/data': 0.00017222296446561813, 'timing/model': 0.4594002850353718, 'learning_rate/action_model': 5.7057356569787124e-05, 'learning_rate/action_query_proj': 5.7057356569787124e-05, 'learning_rate/base': 1.4264339142446781e-05, 'epoch': 0.53}) +[2026-07-27 06:44:22,630][starVLA.training.train_starvla][INFO] - Step 4333, Loss: {'train/loss': 0.1794234812259674, 'train/grad_norm_pre_clip': 3.8192365169525146, 'timing/data': 0.0001728171482682228, 'timing/model': 0.4606277560815215, 'learning_rate/action_model': 5.702736415130816e-05, 'learning_rate/action_query_proj': 5.702736415130816e-05, 'learning_rate/base': 1.425684103782704e-05, 'epoch': 0.53}) +[2026-07-27 06:44:28,189][starVLA.training.train_starvla][INFO] - Step 4334, Loss: {'train/loss': 0.11444761604070663, 'train/grad_norm_pre_clip': 2.142396926879883, 'timing/data': 0.00016925903037190437, 'timing/model': 0.45793368201702833, 'learning_rate/action_model': 5.699736974810545e-05, 'learning_rate/action_query_proj': 5.699736974810545e-05, 'learning_rate/base': 1.4249342437026362e-05, 'epoch': 0.53}) +[2026-07-27 06:44:33,749][starVLA.training.train_starvla][INFO] - Step 4335, Loss: {'train/loss': 0.15658769011497498, 'train/grad_norm_pre_clip': 3.7147977352142334, 'timing/data': 0.00017118779942393303, 'timing/model': 0.4606942920945585, 'learning_rate/action_model': 5.6967373372020285e-05, 'learning_rate/action_query_proj': 5.6967373372020285e-05, 'learning_rate/base': 1.4241843343005071e-05, 'epoch': 0.53}) +[2026-07-27 06:44:39,316][starVLA.training.train_starvla][INFO] - Step 4336, Loss: {'train/loss': 0.19037660956382751, 'train/grad_norm_pre_clip': 3.1891441345214844, 'timing/data': 0.00017013493925333023, 'timing/model': 0.4609067947603762, 'learning_rate/action_model': 5.69373750348948e-05, 'learning_rate/action_query_proj': 5.69373750348948e-05, 'learning_rate/base': 1.42343437587237e-05, 'epoch': 0.53}) +[2026-07-27 06:44:44,871][starVLA.training.train_starvla][INFO] - Step 4337, Loss: {'train/loss': 0.23670926690101624, 'train/grad_norm_pre_clip': 3.729795455932617, 'timing/data': 0.00018161768093705177, 'timing/model': 0.45979912113398314, 'learning_rate/action_model': 5.690737474857184e-05, 'learning_rate/action_query_proj': 5.690737474857184e-05, 'learning_rate/base': 1.422684368714296e-05, 'epoch': 0.53}) +[2026-07-27 06:44:50,445][starVLA.training.train_starvla][INFO] - Step 4338, Loss: {'train/loss': 0.1284692883491516, 'train/grad_norm_pre_clip': 2.6531434059143066, 'timing/data': 0.00017421599477529526, 'timing/model': 0.4644194911234081, 'learning_rate/action_model': 5.6877372524895044e-05, 'learning_rate/action_query_proj': 5.6877372524895044e-05, 'learning_rate/base': 1.4219343131223761e-05, 'epoch': 0.53}) +[2026-07-27 06:44:55,988][starVLA.training.train_starvla][INFO] - Step 4339, Loss: {'train/loss': 0.17608700692653656, 'train/grad_norm_pre_clip': 3.126840353012085, 'timing/data': 0.00018580909818410873, 'timing/model': 0.46295988699421287, 'learning_rate/action_model': 5.684736837570882e-05, 'learning_rate/action_query_proj': 5.684736837570882e-05, 'learning_rate/base': 1.4211842093927206e-05, 'epoch': 0.53}) +[2026-07-27 06:45:01,545][starVLA.training.train_starvla][INFO] - Step 4340, Loss: {'train/loss': 0.11999456584453583, 'train/grad_norm_pre_clip': 2.1484925746917725, 'timing/data': 0.00017312169075012207, 'timing/model': 0.4562199297361076, 'learning_rate/action_model': 5.681736231285831e-05, 'learning_rate/action_query_proj': 5.681736231285831e-05, 'learning_rate/base': 1.4204340578214578e-05, 'epoch': 0.53}) +[2026-07-27 06:45:07,104][starVLA.training.train_starvla][INFO] - Step 4341, Loss: {'train/loss': 0.04841262474656105, 'train/grad_norm_pre_clip': 1.654281735420227, 'timing/data': 0.0001697121188044548, 'timing/model': 0.4626503889448941, 'learning_rate/action_model': 5.678735434818948e-05, 'learning_rate/action_query_proj': 5.678735434818948e-05, 'learning_rate/base': 1.419683858704737e-05, 'epoch': 0.53}) +[2026-07-27 06:45:12,711][starVLA.training.train_starvla][INFO] - Step 4342, Loss: {'train/loss': 0.10995498299598694, 'train/grad_norm_pre_clip': 2.3973584175109863, 'timing/data': 0.00017149979248642921, 'timing/model': 0.46472170297056437, 'learning_rate/action_model': 5.675734449354896e-05, 'learning_rate/action_query_proj': 5.675734449354896e-05, 'learning_rate/base': 1.418933612338724e-05, 'epoch': 0.53}) +[2026-07-27 06:45:18,307][starVLA.training.train_starvla][INFO] - Step 4343, Loss: {'train/loss': 0.16760368645191193, 'train/grad_norm_pre_clip': 3.805077314376831, 'timing/data': 0.00017371587455272675, 'timing/model': 0.4599462430924177, 'learning_rate/action_model': 5.6727332760784165e-05, 'learning_rate/action_query_proj': 5.6727332760784165e-05, 'learning_rate/base': 1.4181833190196041e-05, 'epoch': 0.53}) +[2026-07-27 06:45:23,880][starVLA.training.train_starvla][INFO] - Step 4344, Loss: {'train/loss': 0.13567008078098297, 'train/grad_norm_pre_clip': 3.1348819732666016, 'timing/data': 0.0001713600941002369, 'timing/model': 0.464544587302953, 'learning_rate/action_model': 5.669731916174329e-05, 'learning_rate/action_query_proj': 5.669731916174329e-05, 'learning_rate/base': 1.4174329790435822e-05, 'epoch': 0.53}) +[2026-07-27 06:45:29,458][starVLA.training.train_starvla][INFO] - Step 4345, Loss: {'train/loss': 0.13570262491703033, 'train/grad_norm_pre_clip': 3.3113105297088623, 'timing/data': 0.00017229421064257622, 'timing/model': 0.4609167338348925, 'learning_rate/action_model': 5.666730370827519e-05, 'learning_rate/action_query_proj': 5.666730370827519e-05, 'learning_rate/base': 1.4166825927068797e-05, 'epoch': 0.53}) +[2026-07-27 06:45:35,071][starVLA.training.train_starvla][INFO] - Step 4346, Loss: {'train/loss': 0.06590113788843155, 'train/grad_norm_pre_clip': 1.9292807579040527, 'timing/data': 0.00017537176609039307, 'timing/model': 0.4604989751242101, 'learning_rate/action_model': 5.663728641222947e-05, 'learning_rate/action_query_proj': 5.663728641222947e-05, 'learning_rate/base': 1.4159321603057368e-05, 'epoch': 0.53}) +[2026-07-27 06:45:40,674][starVLA.training.train_starvla][INFO] - Step 4347, Loss: {'train/loss': 0.13653826713562012, 'train/grad_norm_pre_clip': 3.0388541221618652, 'timing/data': 0.0001737368293106556, 'timing/model': 0.46579987509176135, 'learning_rate/action_model': 5.660726728545655e-05, 'learning_rate/action_query_proj': 5.660726728545655e-05, 'learning_rate/base': 1.4151816821364138e-05, 'epoch': 0.53}) +[2026-07-27 06:45:46,274][starVLA.training.train_starvla][INFO] - Step 4348, Loss: {'train/loss': 0.1423596292734146, 'train/grad_norm_pre_clip': 4.163973808288574, 'timing/data': 0.00017424626275897026, 'timing/model': 0.4646644052118063, 'learning_rate/action_model': 5.657724633980746e-05, 'learning_rate/action_query_proj': 5.657724633980746e-05, 'learning_rate/base': 1.4144311584951864e-05, 'epoch': 0.53}) +[2026-07-27 06:45:51,864][starVLA.training.train_starvla][INFO] - Step 4349, Loss: {'train/loss': 0.23955106735229492, 'train/grad_norm_pre_clip': 4.776766777038574, 'timing/data': 0.00017842603847384453, 'timing/model': 0.46016727900132537, 'learning_rate/action_model': 5.6547223587134016e-05, 'learning_rate/action_query_proj': 5.6547223587134016e-05, 'learning_rate/base': 1.4136805896783504e-05, 'epoch': 0.53}) +[2026-07-27 06:45:57,462][starVLA.training.train_starvla][INFO] - Step 4350, Loss: {'train/loss': 0.14803647994995117, 'train/grad_norm_pre_clip': 3.788931131362915, 'timing/data': 0.00018194504082202911, 'timing/model': 0.4629378980025649, 'learning_rate/action_model': 5.651719903928871e-05, 'learning_rate/action_query_proj': 5.651719903928871e-05, 'learning_rate/base': 1.4129299759822177e-05, 'epoch': 0.53}) +[2026-07-27 06:46:03,079][starVLA.training.train_starvla][INFO] - Step 4351, Loss: {'train/loss': 0.1315082311630249, 'train/grad_norm_pre_clip': 2.8867604732513428, 'timing/data': 0.00016951700672507286, 'timing/model': 0.4704051949083805, 'learning_rate/action_model': 5.6487172708124735e-05, 'learning_rate/action_query_proj': 5.6487172708124735e-05, 'learning_rate/base': 1.4121793177031184e-05, 'epoch': 0.53}) +[2026-07-27 06:46:08,708][starVLA.training.train_starvla][INFO] - Step 4352, Loss: {'train/loss': 0.08707012981176376, 'train/grad_norm_pre_clip': 2.9335126876831055, 'timing/data': 0.00017278827726840973, 'timing/model': 0.4688942013308406, 'learning_rate/action_model': 5.645714460549606e-05, 'learning_rate/action_query_proj': 5.645714460549606e-05, 'learning_rate/base': 1.4114286151374015e-05, 'epoch': 0.53}) +[2026-07-27 06:46:14,338][starVLA.training.train_starvla][INFO] - Step 4353, Loss: {'train/loss': 0.1568445861339569, 'train/grad_norm_pre_clip': 2.636852979660034, 'timing/data': 0.00018241815268993378, 'timing/model': 0.46907950285822153, 'learning_rate/action_model': 5.642711474325728e-05, 'learning_rate/action_query_proj': 5.642711474325728e-05, 'learning_rate/base': 1.410677868581432e-05, 'epoch': 0.53}) +[2026-07-27 06:46:19,937][starVLA.training.train_starvla][INFO] - Step 4354, Loss: {'train/loss': 0.08850973844528198, 'train/grad_norm_pre_clip': 2.798415184020996, 'timing/data': 0.00017016194760799408, 'timing/model': 0.4760321187786758, 'learning_rate/action_model': 5.6397083133263717e-05, 'learning_rate/action_query_proj': 5.6397083133263717e-05, 'learning_rate/base': 1.4099270783315929e-05, 'epoch': 0.53}) +[2026-07-27 06:46:25,533][starVLA.training.train_starvla][INFO] - Step 4355, Loss: {'train/loss': 0.1075514405965805, 'train/grad_norm_pre_clip': 3.182990312576294, 'timing/data': 0.0001810048706829548, 'timing/model': 0.4622487397864461, 'learning_rate/action_model': 5.6367049787371373e-05, 'learning_rate/action_query_proj': 5.6367049787371373e-05, 'learning_rate/base': 1.4091762446842843e-05, 'epoch': 0.53}) +[2026-07-27 06:46:31,154][starVLA.training.train_starvla][INFO] - Step 4356, Loss: {'train/loss': 0.17022143304347992, 'train/grad_norm_pre_clip': 3.244647264480591, 'timing/data': 0.00017216289415955544, 'timing/model': 0.46451202034950256, 'learning_rate/action_model': 5.633701471743691e-05, 'learning_rate/action_query_proj': 5.633701471743691e-05, 'learning_rate/base': 1.4084253679359228e-05, 'epoch': 0.53}) +[2026-07-27 06:46:36,779][starVLA.training.train_starvla][INFO] - Step 4357, Loss: {'train/loss': 0.12906207144260406, 'train/grad_norm_pre_clip': 3.612107276916504, 'timing/data': 0.00017669424414634705, 'timing/model': 0.46274570608511567, 'learning_rate/action_model': 5.630697793531774e-05, 'learning_rate/action_query_proj': 5.630697793531774e-05, 'learning_rate/base': 1.4076744483829435e-05, 'epoch': 0.53}) +[2026-07-27 06:46:42,399][starVLA.training.train_starvla][INFO] - Step 4358, Loss: {'train/loss': 0.19936603307724, 'train/grad_norm_pre_clip': 3.2692742347717285, 'timing/data': 0.00017039012163877487, 'timing/model': 0.4642656589858234, 'learning_rate/action_model': 5.627693945287189e-05, 'learning_rate/action_query_proj': 5.627693945287189e-05, 'learning_rate/base': 1.4069234863217972e-05, 'epoch': 0.53}) +[2026-07-27 06:46:48,035][starVLA.training.train_starvla][INFO] - Step 4359, Loss: {'train/loss': 0.24513453245162964, 'train/grad_norm_pre_clip': 3.108518362045288, 'timing/data': 0.0001752837561070919, 'timing/model': 0.4565719380043447, 'learning_rate/action_model': 5.6246899281958073e-05, 'learning_rate/action_query_proj': 5.6246899281958073e-05, 'learning_rate/base': 1.4061724820489518e-05, 'epoch': 0.53}) +[2026-07-27 06:46:53,663][starVLA.training.train_starvla][INFO] - Step 4360, Loss: {'train/loss': 0.12250640988349915, 'train/grad_norm_pre_clip': 2.9002087116241455, 'timing/data': 0.00017993291839957237, 'timing/model': 0.46024718321859837, 'learning_rate/action_model': 5.6216857434435687e-05, 'learning_rate/action_query_proj': 5.6216857434435687e-05, 'learning_rate/base': 1.4054214358608922e-05, 'epoch': 0.53}) +[2026-07-27 06:46:59,293][starVLA.training.train_starvla][INFO] - Step 4361, Loss: {'train/loss': 0.14742064476013184, 'train/grad_norm_pre_clip': 2.472759246826172, 'timing/data': 0.0001752898097038269, 'timing/model': 0.47652830090373755, 'learning_rate/action_model': 5.618681392216475e-05, 'learning_rate/action_query_proj': 5.618681392216475e-05, 'learning_rate/base': 1.4046703480541187e-05, 'epoch': 0.53}) +[2026-07-27 06:47:04,934][starVLA.training.train_starvla][INFO] - Step 4362, Loss: {'train/loss': 0.25606250762939453, 'train/grad_norm_pre_clip': 4.286263942718506, 'timing/data': 0.0001792432740330696, 'timing/model': 0.46953071281313896, 'learning_rate/action_model': 5.615676875700599e-05, 'learning_rate/action_query_proj': 5.615676875700599e-05, 'learning_rate/base': 1.4039192189251498e-05, 'epoch': 0.53}) +[2026-07-27 06:47:10,555][starVLA.training.train_starvla][INFO] - Step 4363, Loss: {'train/loss': 0.22118107974529266, 'train/grad_norm_pre_clip': 4.6185622215271, 'timing/data': 0.0001706620678305626, 'timing/model': 0.4656529859639704, 'learning_rate/action_model': 5.612672195082076e-05, 'learning_rate/action_query_proj': 5.612672195082076e-05, 'learning_rate/base': 1.403168048770519e-05, 'epoch': 0.53}) +[2026-07-27 06:47:16,162][starVLA.training.train_starvla][INFO] - Step 4364, Loss: {'train/loss': 0.14885106682777405, 'train/grad_norm_pre_clip': 3.100879192352295, 'timing/data': 0.0002017640508711338, 'timing/model': 0.46282018395140767, 'learning_rate/action_model': 5.609667351547106e-05, 'learning_rate/action_query_proj': 5.609667351547106e-05, 'learning_rate/base': 1.4024168378867766e-05, 'epoch': 0.53}) +[2026-07-27 06:47:21,994][starVLA.training.train_starvla][INFO] - Step 4365, Loss: {'train/loss': 0.10966888070106506, 'train/grad_norm_pre_clip': 2.2696728706359863, 'timing/data': 0.0001795017160475254, 'timing/model': 0.6498795640654862, 'learning_rate/action_model': 5.606662346281953e-05, 'learning_rate/action_query_proj': 5.606662346281953e-05, 'learning_rate/base': 1.4016655865704883e-05, 'epoch': 0.53}) +[2026-07-27 06:47:27,613][starVLA.training.train_starvla][INFO] - Step 4366, Loss: {'train/loss': 0.1431693434715271, 'train/grad_norm_pre_clip': 3.7948710918426514, 'timing/data': 0.00017898622900247574, 'timing/model': 0.4687647740356624, 'learning_rate/action_model': 5.603657180472945e-05, 'learning_rate/action_query_proj': 5.603657180472945e-05, 'learning_rate/base': 1.4009142951182363e-05, 'epoch': 0.53}) +[2026-07-27 06:47:33,229][starVLA.training.train_starvla][INFO] - Step 4367, Loss: {'train/loss': 0.11214102059602737, 'train/grad_norm_pre_clip': 2.940938949584961, 'timing/data': 0.00016919896006584167, 'timing/model': 0.4684064108878374, 'learning_rate/action_model': 5.600651855306477e-05, 'learning_rate/action_query_proj': 5.600651855306477e-05, 'learning_rate/base': 1.4001629638266193e-05, 'epoch': 0.53}) +[2026-07-27 06:47:38,853][starVLA.training.train_starvla][INFO] - Step 4368, Loss: {'train/loss': 0.1554253101348877, 'train/grad_norm_pre_clip': 2.40826416015625, 'timing/data': 0.00017442507669329643, 'timing/model': 0.4687630361877382, 'learning_rate/action_model': 5.597646371969e-05, 'learning_rate/action_query_proj': 5.597646371969e-05, 'learning_rate/base': 1.39941159299225e-05, 'epoch': 0.53}) +[2026-07-27 06:47:44,479][starVLA.training.train_starvla][INFO] - Step 4369, Loss: {'train/loss': 0.16201643645763397, 'train/grad_norm_pre_clip': 2.5219168663024902, 'timing/data': 0.00017364928498864174, 'timing/model': 0.47090293606743217, 'learning_rate/action_model': 5.5946407316470336e-05, 'learning_rate/action_query_proj': 5.5946407316470336e-05, 'learning_rate/base': 1.3986601829117584e-05, 'epoch': 0.53}) +[2026-07-27 06:47:50,097][starVLA.training.train_starvla][INFO] - Step 4370, Loss: {'train/loss': 0.07816654443740845, 'train/grad_norm_pre_clip': 2.577096462249756, 'timing/data': 0.0001768968068063259, 'timing/model': 0.4691323572769761, 'learning_rate/action_model': 5.591634935527158e-05, 'learning_rate/action_query_proj': 5.591634935527158e-05, 'learning_rate/base': 1.3979087338817894e-05, 'epoch': 0.53}) +[2026-07-27 06:47:55,722][starVLA.training.train_starvla][INFO] - Step 4371, Loss: {'train/loss': 0.18064145743846893, 'train/grad_norm_pre_clip': 3.5788071155548096, 'timing/data': 0.00017170188948512077, 'timing/model': 0.4703671671450138, 'learning_rate/action_model': 5.588628984796008e-05, 'learning_rate/action_query_proj': 5.588628984796008e-05, 'learning_rate/base': 1.397157246199002e-05, 'epoch': 0.53}) +[2026-07-27 06:48:01,344][starVLA.training.train_starvla][INFO] - Step 4372, Loss: {'train/loss': 0.12689925730228424, 'train/grad_norm_pre_clip': 2.6283490657806396, 'timing/data': 0.0001794826239347458, 'timing/model': 0.46870609978213906, 'learning_rate/action_model': 5.585622880640293e-05, 'learning_rate/action_query_proj': 5.585622880640293e-05, 'learning_rate/base': 1.3964057201600733e-05, 'epoch': 0.53}) +[2026-07-27 06:48:06,959][starVLA.training.train_starvla][INFO] - Step 4373, Loss: {'train/loss': 0.16807790100574493, 'train/grad_norm_pre_clip': 3.254854202270508, 'timing/data': 0.00017577409744262695, 'timing/model': 0.4687807038426399, 'learning_rate/action_model': 5.582616624246769e-05, 'learning_rate/action_query_proj': 5.582616624246769e-05, 'learning_rate/base': 1.3956541560616923e-05, 'epoch': 0.53}) +[2026-07-27 06:48:12,581][starVLA.training.train_starvla][INFO] - Step 4374, Loss: {'train/loss': 0.2568008005619049, 'train/grad_norm_pre_clip': 4.393995761871338, 'timing/data': 0.00017486698925495148, 'timing/model': 0.46784757822752, 'learning_rate/action_model': 5.579610216802264e-05, 'learning_rate/action_query_proj': 5.579610216802264e-05, 'learning_rate/base': 1.394902554200566e-05, 'epoch': 0.53}) +[2026-07-27 06:48:18,220][starVLA.training.train_starvla][INFO] - Step 4375, Loss: {'train/loss': 0.26619619131088257, 'train/grad_norm_pre_clip': 4.7484002113342285, 'timing/data': 0.00017165206372737885, 'timing/model': 0.47087633330374956, 'learning_rate/action_model': 5.576603659493657e-05, 'learning_rate/action_query_proj': 5.576603659493657e-05, 'learning_rate/base': 1.3941509148734142e-05, 'epoch': 0.53}) +[2026-07-27 06:48:23,849][starVLA.training.train_starvla][INFO] - Step 4376, Loss: {'train/loss': 0.1964322328567505, 'train/grad_norm_pre_clip': 4.011418342590332, 'timing/data': 0.00016871700063347816, 'timing/model': 0.4696896239183843, 'learning_rate/action_model': 5.573596953507887e-05, 'learning_rate/action_query_proj': 5.573596953507887e-05, 'learning_rate/base': 1.3933992383769717e-05, 'epoch': 0.53}) +[2026-07-27 06:48:29,499][starVLA.training.train_starvla][INFO] - Step 4377, Loss: {'train/loss': 0.13588225841522217, 'train/grad_norm_pre_clip': 2.8552277088165283, 'timing/data': 0.0001951446756720543, 'timing/model': 0.4692443530075252, 'learning_rate/action_model': 5.570590100031958e-05, 'learning_rate/action_query_proj': 5.570590100031958e-05, 'learning_rate/base': 1.3926475250079896e-05, 'epoch': 0.53}) +[2026-07-27 06:48:35,128][starVLA.training.train_starvla][INFO] - Step 4378, Loss: {'train/loss': 0.10132601112127304, 'train/grad_norm_pre_clip': 2.344930410385132, 'timing/data': 0.0001855911687016487, 'timing/model': 0.4691095110028982, 'learning_rate/action_model': 5.567583100252928e-05, 'learning_rate/action_query_proj': 5.567583100252928e-05, 'learning_rate/base': 1.391895775063232e-05, 'epoch': 0.53}) +[2026-07-27 06:48:40,752][starVLA.training.train_starvla][INFO] - Step 4379, Loss: {'train/loss': 0.16926740109920502, 'train/grad_norm_pre_clip': 3.4755003452301025, 'timing/data': 0.00017149001359939575, 'timing/model': 0.4576317388564348, 'learning_rate/action_model': 5.564575955357909e-05, 'learning_rate/action_query_proj': 5.564575955357909e-05, 'learning_rate/base': 1.3911439888394773e-05, 'epoch': 0.53}) +[2026-07-27 06:48:46,379][starVLA.training.train_starvla][INFO] - Step 4380, Loss: {'train/loss': 0.18870018422603607, 'train/grad_norm_pre_clip': 3.336544990539551, 'timing/data': 0.000182232353836298, 'timing/model': 0.46092116367071867, 'learning_rate/action_model': 5.561568666534078e-05, 'learning_rate/action_query_proj': 5.561568666534078e-05, 'learning_rate/base': 1.3903921666335195e-05, 'epoch': 0.53}) +[2026-07-27 06:48:51,991][starVLA.training.train_starvla][INFO] - Step 4381, Loss: {'train/loss': 0.11178308725357056, 'train/grad_norm_pre_clip': 2.5536179542541504, 'timing/data': 0.00017606234177947044, 'timing/model': 0.46235733944922686, 'learning_rate/action_model': 5.5585612349686634e-05, 'learning_rate/action_query_proj': 5.5585612349686634e-05, 'learning_rate/base': 1.3896403087421658e-05, 'epoch': 0.53}) +[2026-07-27 06:48:57,636][starVLA.training.train_starvla][INFO] - Step 4382, Loss: {'train/loss': 0.1451069414615631, 'train/grad_norm_pre_clip': 3.005573272705078, 'timing/data': 0.00017558317631483078, 'timing/model': 0.4706971659325063, 'learning_rate/action_model': 5.555553661848951e-05, 'learning_rate/action_query_proj': 5.555553661848951e-05, 'learning_rate/base': 1.3888884154622378e-05, 'epoch': 0.53}) +[2026-07-27 06:49:03,260][starVLA.training.train_starvla][INFO] - Step 4383, Loss: {'train/loss': 0.05151590704917908, 'train/grad_norm_pre_clip': 1.7954285144805908, 'timing/data': 0.00017639202997088432, 'timing/model': 0.46839318284764886, 'learning_rate/action_model': 5.552545948362283e-05, 'learning_rate/action_query_proj': 5.552545948362283e-05, 'learning_rate/base': 1.3881364870905707e-05, 'epoch': 0.53}) +[2026-07-27 06:49:08,919][starVLA.training.train_starvla][INFO] - Step 4384, Loss: {'train/loss': 0.14544442296028137, 'train/grad_norm_pre_clip': 3.6663308143615723, 'timing/data': 0.0001743622124195099, 'timing/model': 0.4778068168088794, 'learning_rate/action_model': 5.549538095696061e-05, 'learning_rate/action_query_proj': 5.549538095696061e-05, 'learning_rate/base': 1.3873845239240152e-05, 'epoch': 0.53}) +[2026-07-27 06:49:14,561][starVLA.training.train_starvla][INFO] - Step 4385, Loss: {'train/loss': 0.1009228453040123, 'train/grad_norm_pre_clip': 3.3720970153808594, 'timing/data': 0.00017317896708846092, 'timing/model': 0.469495867844671, 'learning_rate/action_model': 5.546530105037733e-05, 'learning_rate/action_query_proj': 5.546530105037733e-05, 'learning_rate/base': 1.3866325262594332e-05, 'epoch': 0.53}) +[2026-07-27 06:49:20,205][starVLA.training.train_starvla][INFO] - Step 4386, Loss: {'train/loss': 0.08262874186038971, 'train/grad_norm_pre_clip': 2.2906367778778076, 'timing/data': 0.00017508119344711304, 'timing/model': 0.4710049219429493, 'learning_rate/action_model': 5.5435219775748056e-05, 'learning_rate/action_query_proj': 5.5435219775748056e-05, 'learning_rate/base': 1.3858804943937014e-05, 'epoch': 0.53}) +[2026-07-27 06:49:26,041][starVLA.training.train_starvla][INFO] - Step 4387, Loss: {'train/loss': 0.19279147684574127, 'train/grad_norm_pre_clip': 4.262796401977539, 'timing/data': 0.0001751999370753765, 'timing/model': 0.4623827338218689, 'learning_rate/action_model': 5.5405137144948436e-05, 'learning_rate/action_query_proj': 5.5405137144948436e-05, 'learning_rate/base': 1.3851284286237109e-05, 'epoch': 0.53}) +[2026-07-27 06:49:31,658][starVLA.training.train_starvla][INFO] - Step 4388, Loss: {'train/loss': 0.11416880041360855, 'train/grad_norm_pre_clip': 1.958404779434204, 'timing/data': 0.00017176475375890732, 'timing/model': 0.4641211600974202, 'learning_rate/action_model': 5.53750531698546e-05, 'learning_rate/action_query_proj': 5.53750531698546e-05, 'learning_rate/base': 1.384376329246365e-05, 'epoch': 0.53}) +[2026-07-27 06:49:37,267][starVLA.training.train_starvla][INFO] - Step 4389, Loss: {'train/loss': 0.2067277878522873, 'train/grad_norm_pre_clip': 3.4962191581726074, 'timing/data': 0.00017819181084632874, 'timing/model': 0.4561651200056076, 'learning_rate/action_model': 5.534496786234321e-05, 'learning_rate/action_query_proj': 5.534496786234321e-05, 'learning_rate/base': 1.3836241965585803e-05, 'epoch': 0.53}) +[2026-07-27 06:49:42,884][starVLA.training.train_starvla][INFO] - Step 4390, Loss: {'train/loss': 0.29628172516822815, 'train/grad_norm_pre_clip': 3.5763614177703857, 'timing/data': 0.00017473101615905762, 'timing/model': 0.4598915888927877, 'learning_rate/action_model': 5.531488123429149e-05, 'learning_rate/action_query_proj': 5.531488123429149e-05, 'learning_rate/base': 1.3828720308572873e-05, 'epoch': 0.53}) +[2026-07-27 06:49:48,500][starVLA.training.train_starvla][INFO] - Step 4391, Loss: {'train/loss': 0.07740160822868347, 'train/grad_norm_pre_clip': 2.316500663757324, 'timing/data': 0.0001741349697113037, 'timing/model': 0.46245607268065214, 'learning_rate/action_model': 5.528479329757715e-05, 'learning_rate/action_query_proj': 5.528479329757715e-05, 'learning_rate/base': 1.3821198324394288e-05, 'epoch': 0.53}) +[2026-07-27 06:49:54,124][starVLA.training.train_starvla][INFO] - Step 4392, Loss: {'train/loss': 0.10884951055049896, 'train/grad_norm_pre_clip': 3.5883519649505615, 'timing/data': 0.00017230398952960968, 'timing/model': 0.4654660518281162, 'learning_rate/action_model': 5.5254704064078445e-05, 'learning_rate/action_query_proj': 5.5254704064078445e-05, 'learning_rate/base': 1.3813676016019611e-05, 'epoch': 0.53}) +[2026-07-27 08:32:27,191][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 08:32:27,196][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 08:32:28,086][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 08:32:28,114][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 08:32:28,158][starVLA.model.framework.share_tools][INFO] - [*] [apply_config_compat] normalised config from version_id=0.21 to '0.21' +[2026-07-27 08:32:28,159][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 08:32:28,160][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 08:32:28,161][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 08:32:28,163][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 08:32:28,166][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 08:32:28,170][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 08:32:28,530][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 08:32:28,533][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 08:32:28,673][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 08:32:28,677][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 08:32:28,683][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 08:32:28,689][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 08:32:28,727][starVLA.training.train_starvla][INFO] - VLA Training :: Warming Up +[2026-07-27 08:32:28,731][starVLA.training.rl_games.auth][WARNING] - Hugging Face login skipped/failed: Cannot reach https://huggingface.co/api/whoami-v2: offline mode is enabled. To disable it, please unset the `HF_HUB_OFFLINE` environment variable. +[2026-07-27 08:32:28,988][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 08:32:29,004][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 08:32:29,040][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 08:32:29,057][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 08:32:29,240][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 08:32:29,250][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 08:32:29,256][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 08:32:29,266][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 08:32:29,434][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 08:32:29,453][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 08:32:29,793][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 08:32:29,815][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 08:32:30,229][starVLA.training.rl_games.auth][INFO] - Logged into Weights & Biases +[2026-07-27 08:32:30,245][starVLA.training.train_starvla][INFO] - ✅ Configuration wrapped for access tracking +[2026-07-27 08:32:31,058][starVLA.model.modules.world_model.Wan2][INFO] - [*] Loading Wan2.2-TI2V from /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/playground/Pretrained_models/Wan-AI/Wan2.2-TI2V-5B-Diffusers +[2026-07-27 08:34:39,652][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 08:34:39,789][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 08:34:39,789][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 08:34:39,791][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 08:34:39,791][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 08:34:39,791][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 08:34:39,791][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 08:34:39,822][starVLA.training.train_starvla][INFO] - Creating VLA Dataset with Mixture `demon_attack_train__bridge` +[2026-07-27 08:34:42,443][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 08:34:42,443][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 08:34:42,443][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 08:34:42,443][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 08:34:42,443][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 08:34:42,445][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 08:34:42,447][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 08:34:42,449][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 08:34:42,451][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 08:34:42,453][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 08:34:42,455][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 08:34:42,457][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 08:34:42,460][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 08:34:42,463][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 08:34:42,464][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 08:34:42,464][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 08:34:42,464][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 08:34:42,465][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 08:34:42,466][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,466][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,466][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 08:34:42,466][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 08:34:42,466][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 08:34:42,466][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 08:34:42,467][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 08:34:42,468][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 08:34:42,468][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 08:34:42,468][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 08:34:42,469][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 08:34:42,469][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 08:34:42,469][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 08:34:42,470][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 08:34:42,470][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 08:34:42,470][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 08:34:42,471][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,471][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,471][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 08:34:42,604][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 08:34:42,605][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 08:34:42,605][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 08:34:42,605][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 08:34:42,606][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 08:34:42,606][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 08:34:42,606][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 08:34:42,606][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 08:34:42,607][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 08:34:42,607][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 08:34:42,607][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,607][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,607][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 08:34:42,608][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 08:34:42,608][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 08:34:42,608][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 08:34:42,609][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 08:34:42,609][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 08:34:42,609][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 08:34:42,610][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 08:34:42,610][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 08:34:42,610][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 08:34:42,610][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 08:34:42,610][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 08:34:42,610][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 08:34:42,611][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 08:34:42,611][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 08:34:42,611][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 08:34:42,612][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,612][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,612][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 08:34:42,613][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Behavior (data_config): ['BEHAVIOR_challenge'] +[2026-07-27 08:34:42,614][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from DOMINO: ['robotwin'] +[2026-07-27 08:34:42,614][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from DOMINO (data_config): [] +[2026-07-27 08:34:42,614][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from DOMINO (data_config): ['domino', 'domino_clean', 'domino_random', 'domino_cotrain'] +[2026-07-27 08:34:42,614][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Franka: ['custom_robot_config', 'demo_sim_franka_delta_joints', 'SO101'] +[2026-07-27 08:34:42,614][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Franka (data_config): [] +[2026-07-27 08:34:42,614][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Franka (data_config): ['custom_dataset', 'custom_dataset_2', 'demo_sim_pick_place', 'SO101_pick'] +[2026-07-27 08:34:42,615][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from LIBERO: ['libero_franka'] +[2026-07-27 08:34:42,615][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from LIBERO (data_config): [] +[2026-07-27 08:34:42,615][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from LIBERO (data_config): ['libero_all', 'libero_goal', 'multi_robot'] +[2026-07-27 08:34:42,616][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from RoboChallenge_table30v2: ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,616][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from RoboChallenge_table30v2 (data_config): ['ur5_robochallenge', 'arx5_robochallenge', 'dosw1_robochallenge'] +[2026-07-27 08:34:42,616][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from RoboChallenge_table30v2 (data_config): ['robochallenge_table30v2_shred_paper', 'robochallenge_table30v2_ur5_all', 'robochallenge_table30v2_arx5_all', 'robochallenge_table30v2_dosw1_all'] +[2026-07-27 08:34:42,617][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_365: ['panda_omron_robocasa365'] +[2026-07-27 08:34:42,617][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_365 (data_config): [] +[2026-07-27 08:34:42,617][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_365 (data_config): ['robocasa365_open_drawer_target_human', 'robocasa365_atomic_target_human_all', 'robocasa365_composite_target_human_all', 'robocasa365_target_human_all'] +[2026-07-27 08:34:42,617][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robocasa_tabletop: ['fourier_gr1_arms_waist'] +[2026-07-27 08:34:42,617][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robocasa_tabletop (data_config): [] +[2026-07-27 08:34:42,617][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robocasa_tabletop (data_config): ['fourier_gr1_unified_1000'] +[2026-07-27 08:34:42,618][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from Robotwin: ['robotwin', 'robotwin50', 'arx_x5'] +[2026-07-27 08:34:42,618][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from Robotwin (data_config): [] +[2026-07-27 08:34:42,618][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from Robotwin (data_config): ['robotwin_all', 'robotwin_all_50', 'robotwin', 'robotwin_task1', 'robotwin_task2', 'arx_x5'] +[2026-07-27 08:34:42,619][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from SimplerEnv: ['oxe_droid', 'oxe_bridge', 'oxe_rt1'] +[2026-07-27 08:34:42,619][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from SimplerEnv (data_config): [] +[2026-07-27 08:34:42,619][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from SimplerEnv (data_config): ['bridge', 'bridge_rt_1'] +[2026-07-27 08:34:42,619][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from VLA-Arena: ['vla_arena_franka'] +[2026-07-27 08:34:42,619][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from VLA-Arena (data_config): [] +[2026-07-27 08:34:42,619][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from VLA-Arena (data_config): ['vla_arena_L0_S', 'vla_arena_L0_M', 'vla_arena_L0_L'] +[2026-07-27 08:34:42,620][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded data_config from rl_games: ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,620][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded embodiment_tags from rl_games (data_config): ['rl_games_flappy', 'rl_games_demon_attack', 'rl_games_deadly_corridor'] +[2026-07-27 08:34:42,620][starVLA.dataloader.gr00t_lerobot.registry][INFO] - [registry] Loaded mixtures from rl_games (data_config): ['flappy_train', 'flappy_train__bridge', 'flappy_mixed_latency_train', 'flappy_mixed_latency_train__bridge', 'demon_attack_train', 'demon_attack_train__bridge', 'demon_attack_mixed_latency_train', 'demon_attack_mixed_latency_train__bridge', 'deadly_corridor_train', 'deadly_corridor_train__bridge', 'deadly_corridor_mixed_latency_train', 'deadly_corridor_mixed_latency_train__bridge'] +[2026-07-27 08:34:50,499][starVLA.dataloader][INFO] - Created train VLA dataloader with num_workers=8, persistent_workers=True, cpu_only_workers=True +[2026-07-27 08:34:50,528][starVLA.training.train_starvla][INFO] - LR Group action_model: lr=0.0001, num_params=16 +[2026-07-27 08:34:50,528][starVLA.training.train_starvla][INFO] - LR Group action_query_proj: lr=0.0001, num_params=2 +[2026-07-27 08:34:50,529][starVLA.training.train_starvla][INFO] - LR Group base: lr=2.5e-05, num_params=1263 +[2026-07-27 08:34:50,548][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state, steps: 4000 +[2026-07-27 08:34:50,548][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state, steps: 4000 +[2026-07-27 08:34:50,548][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state, steps: 4000 +[2026-07-27 08:34:50,548][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state, steps: 4000 +[2026-07-27 08:34:50,548][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state, steps: 4000 +[2026-07-27 08:34:50,548][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state, steps: 4000 +[2026-07-27 08:34:50,548][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state, steps: 4000 +[2026-07-27 08:34:50,561][starVLA.training.train_starvla][INFO] - 📝 Full config saved at /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/config.full.yaml +[2026-07-27 08:34:50,572][starVLA.training.train_starvla][INFO] - 📊 Accessed config snapshot saved at /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/config.yaml +[2026-07-27 08:34:50,572][starVLA.training.train_starvla][INFO] - Will resume full training state from checkpoint: /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state, steps: 4000 +[2026-07-27 08:35:44,367][accelerate.accelerator][INFO] - Loading states from /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state +[2026-07-27 08:35:44,367][accelerate.accelerator][INFO] - Loading DeepSpeed Model and Optimizer +[2026-07-27 08:36:27,988][accelerate.accelerator][INFO] - DeepSpeed Model and Optimizer loaded from input dir /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4000_state/pytorch_model +[2026-07-27 08:36:27,989][accelerate.checkpointing][INFO] - All model weights loaded successfully +[2026-07-27 08:36:27,989][accelerate.checkpointing][INFO] - All optimizer states loaded successfully +[2026-07-27 08:36:27,989][accelerate.checkpointing][INFO] - All scheduler states loaded successfully +[2026-07-27 08:36:27,989][accelerate.checkpointing][INFO] - All dataloader sampler states loaded successfully +[2026-07-27 08:36:27,998][accelerate.checkpointing][INFO] - All random states loaded successfully +[2026-07-27 08:36:28,000][accelerate.accelerator][INFO] - Loading in 0 custom states +[2026-07-27 08:36:29,910][starVLA.training.train_starvla][INFO] - ***** Training Configuration ***** +[2026-07-27 08:36:29,910][starVLA.training.train_starvla][INFO] - Total optimization steps = 5000 +[2026-07-27 08:36:29,911][starVLA.training.train_starvla][INFO] - Per device batch size = 1 +[2026-07-27 08:36:29,911][starVLA.training.train_starvla][INFO] - Gradient accumulation steps = 16 +[2026-07-27 08:36:29,911][starVLA.training.train_starvla][INFO] - Total batch size = 128 +[2026-07-27 08:37:48,652][starVLA.training.train_starvla][INFO] - Step 4001, Loss: {'train/loss': 0.06074453145265579, 'train/grad_norm_pre_clip': 2.6932990550994873, 'timing/data': 0.00017309002578258514, 'timing/model': 1.134265350177884, 'learning_rate/action_model': 9.999999052518008e-05, 'learning_rate/action_query_proj': 9.999999052518008e-05, 'learning_rate/base': 2.499999763129502e-05, 'epoch': 0.49}) +[2026-07-27 08:37:54,375][starVLA.training.train_starvla][INFO] - Step 4002, Loss: {'train/loss': 0.0893528014421463, 'train/grad_norm_pre_clip': 2.8755388259887695, 'timing/data': 0.000186210498213768, 'timing/model': 0.4720119498670101, 'learning_rate/action_model': 9.99999621007241e-05, 'learning_rate/action_query_proj': 9.99999621007241e-05, 'learning_rate/base': 2.4999990525181024e-05, 'epoch': 0.49}) +[2026-07-27 08:38:00,085][starVLA.training.train_starvla][INFO] - Step 4003, Loss: {'train/loss': 0.046270519495010376, 'train/grad_norm_pre_clip': 2.3964462280273438, 'timing/data': 0.00027920491993427277, 'timing/model': 0.4669689517468214, 'learning_rate/action_model': 9.999991472664323e-05, 'learning_rate/action_query_proj': 9.999991472664323e-05, 'learning_rate/base': 2.4999978681660807e-05, 'epoch': 0.49}) +[2026-07-27 08:38:05,703][starVLA.training.train_starvla][INFO] - Step 4004, Loss: {'train/loss': 0.10294929891824722, 'train/grad_norm_pre_clip': 3.153256416320801, 'timing/data': 0.00026546791195869446, 'timing/model': 0.4641732554882765, 'learning_rate/action_model': 9.99998484029562e-05, 'learning_rate/action_query_proj': 9.99998484029562e-05, 'learning_rate/base': 2.499996210073905e-05, 'epoch': 0.49}) +[2026-07-27 08:38:11,271][starVLA.training.train_starvla][INFO] - Step 4005, Loss: {'train/loss': 0.03049125149846077, 'train/grad_norm_pre_clip': 1.9021453857421875, 'timing/data': 0.0002019628882408142, 'timing/model': 0.4657870661467314, 'learning_rate/action_model': 9.99997631296892e-05, 'learning_rate/action_query_proj': 9.99997631296892e-05, 'learning_rate/base': 2.49999407824223e-05, 'epoch': 0.49}) +[2026-07-27 08:38:16,866][starVLA.training.train_starvla][INFO] - Step 4006, Loss: {'train/loss': 0.0358814038336277, 'train/grad_norm_pre_clip': 2.033878803253174, 'timing/data': 0.00021573901176452637, 'timing/model': 0.4660957120358944, 'learning_rate/action_model': 9.999965890687587e-05, 'learning_rate/action_query_proj': 9.999965890687587e-05, 'learning_rate/base': 2.4999914726718967e-05, 'epoch': 0.49}) +[2026-07-27 08:38:22,428][starVLA.training.train_starvla][INFO] - Step 4007, Loss: {'train/loss': 0.05618169531226158, 'train/grad_norm_pre_clip': 2.29909086227417, 'timing/data': 0.0004556030035018921, 'timing/model': 0.4666059371083975, 'learning_rate/action_model': 9.999953573455739e-05, 'learning_rate/action_query_proj': 9.999953573455739e-05, 'learning_rate/base': 2.4999883933639347e-05, 'epoch': 0.49}) +[2026-07-27 08:38:28,243][starVLA.training.train_starvla][INFO] - Step 4008, Loss: {'train/loss': 0.15415959060192108, 'train/grad_norm_pre_clip': 4.568449974060059, 'timing/data': 0.00020415522158145905, 'timing/model': 0.46694913506507874, 'learning_rate/action_model': 9.999939361278237e-05, 'learning_rate/action_query_proj': 9.999939361278237e-05, 'learning_rate/base': 2.4999848403195593e-05, 'epoch': 0.49}) +[2026-07-27 08:38:34,207][starVLA.training.train_starvla][INFO] - Step 4009, Loss: {'train/loss': 0.01756538823246956, 'train/grad_norm_pre_clip': 1.1935008764266968, 'timing/data': 0.00021312758326530457, 'timing/model': 0.8467775713652372, 'learning_rate/action_model': 9.999923254160689e-05, 'learning_rate/action_query_proj': 9.999923254160689e-05, 'learning_rate/base': 2.4999808135401723e-05, 'epoch': 0.49}) +[2026-07-27 08:38:40,401][starVLA.training.train_starvla][INFO] - Step 4010, Loss: {'train/loss': 0.10644157230854034, 'train/grad_norm_pre_clip': 4.07735538482666, 'timing/data': 0.00019949674606323242, 'timing/model': 1.1061188150197268, 'learning_rate/action_model': 9.999905252109459e-05, 'learning_rate/action_query_proj': 9.999905252109459e-05, 'learning_rate/base': 2.4999763130273646e-05, 'epoch': 0.49}) +[2026-07-27 08:38:45,971][starVLA.training.train_starvla][INFO] - Step 4011, Loss: {'train/loss': 0.12552444636821747, 'train/grad_norm_pre_clip': 3.6177213191986084, 'timing/data': 0.00046196579933166504, 'timing/model': 0.46509091183543205, 'learning_rate/action_model': 9.99988535513165e-05, 'learning_rate/action_query_proj': 9.99988535513165e-05, 'learning_rate/base': 2.4999713387829125e-05, 'epoch': 0.49}) +[2026-07-27 08:38:51,528][starVLA.training.train_starvla][INFO] - Step 4012, Loss: {'train/loss': 0.03528694808483124, 'train/grad_norm_pre_clip': 2.0399515628814697, 'timing/data': 0.0002203136682510376, 'timing/model': 0.467223908752203, 'learning_rate/action_model': 9.999863563235118e-05, 'learning_rate/action_query_proj': 9.999863563235118e-05, 'learning_rate/base': 2.4999658908087796e-05, 'epoch': 0.49}) +[2026-07-27 08:38:57,084][starVLA.training.train_starvla][INFO] - Step 4013, Loss: {'train/loss': 0.11042699217796326, 'train/grad_norm_pre_clip': 3.0737929344177246, 'timing/data': 0.00019517168402671814, 'timing/model': 0.46707725524902344, 'learning_rate/action_model': 9.999839876428467e-05, 'learning_rate/action_query_proj': 9.999839876428467e-05, 'learning_rate/base': 2.4999599691071167e-05, 'epoch': 0.49}) +[2026-07-27 08:39:02,997][starVLA.training.train_starvla][INFO] - Step 4014, Loss: {'train/loss': 0.0660686120390892, 'train/grad_norm_pre_clip': 3.594877243041992, 'timing/data': 0.00020685233175754547, 'timing/model': 0.4652577470988035, 'learning_rate/action_model': 9.999814294721048e-05, 'learning_rate/action_query_proj': 9.999814294721048e-05, 'learning_rate/base': 2.499953573680262e-05, 'epoch': 0.49}) +[2026-07-27 08:39:08,579][starVLA.training.train_starvla][INFO] - Step 4015, Loss: {'train/loss': 0.07783473283052444, 'train/grad_norm_pre_clip': 3.4387617111206055, 'timing/data': 0.00020605884492397308, 'timing/model': 0.4648215379565954, 'learning_rate/action_model': 9.99978681812296e-05, 'learning_rate/action_query_proj': 9.99978681812296e-05, 'learning_rate/base': 2.49994670453074e-05, 'epoch': 0.49}) +[2026-07-27 08:39:14,156][starVLA.training.train_starvla][INFO] - Step 4016, Loss: {'train/loss': 0.07250325381755829, 'train/grad_norm_pre_clip': 2.0702412128448486, 'timing/data': 0.0001972336322069168, 'timing/model': 0.46321011148393154, 'learning_rate/action_model': 9.999757446645048e-05, 'learning_rate/action_query_proj': 9.999757446645048e-05, 'learning_rate/base': 2.499939361661262e-05, 'epoch': 0.49}) +[2026-07-27 08:39:19,712][starVLA.training.train_starvla][INFO] - Step 4017, Loss: {'train/loss': 0.05431216582655907, 'train/grad_norm_pre_clip': 2.9549834728240967, 'timing/data': 0.00021691806614398956, 'timing/model': 0.45783321373164654, 'learning_rate/action_model': 9.999726180298913e-05, 'learning_rate/action_query_proj': 9.999726180298913e-05, 'learning_rate/base': 2.4999315450747283e-05, 'epoch': 0.49}) +[2026-07-27 08:39:25,270][starVLA.training.train_starvla][INFO] - Step 4018, Loss: {'train/loss': 0.03776028752326965, 'train/grad_norm_pre_clip': 2.1040022373199463, 'timing/data': 0.0002018660306930542, 'timing/model': 0.45864694379270077, 'learning_rate/action_model': 9.999693019096892e-05, 'learning_rate/action_query_proj': 9.999693019096892e-05, 'learning_rate/base': 2.499923254774223e-05, 'epoch': 0.49}) +[2026-07-27 08:39:30,877][starVLA.training.train_starvla][INFO] - Step 4019, Loss: {'train/loss': 0.06227172911167145, 'train/grad_norm_pre_clip': 2.7023701667785645, 'timing/data': 0.00019346177577972412, 'timing/model': 0.458566902205348, 'learning_rate/action_model': 9.999657963052081e-05, 'learning_rate/action_query_proj': 9.999657963052081e-05, 'learning_rate/base': 2.4999144907630202e-05, 'epoch': 0.49}) +[2026-07-27 08:39:36,514][starVLA.training.train_starvla][INFO] - Step 4020, Loss: {'train/loss': 0.04877437651157379, 'train/grad_norm_pre_clip': 3.1698837280273438, 'timing/data': 0.0001917332410812378, 'timing/model': 0.5115584544837475, 'learning_rate/action_model': 9.999621012178318e-05, 'learning_rate/action_query_proj': 9.999621012178318e-05, 'learning_rate/base': 2.4999052530445796e-05, 'epoch': 0.49}) +[2026-07-27 08:39:42,136][starVLA.training.train_starvla][INFO] - Step 4021, Loss: {'train/loss': 0.12139047682285309, 'train/grad_norm_pre_clip': 2.9097559452056885, 'timing/data': 0.00021520256996154785, 'timing/model': 0.45732420310378075, 'learning_rate/action_model': 9.999582166490191e-05, 'learning_rate/action_query_proj': 9.999582166490191e-05, 'learning_rate/base': 2.4998955416225478e-05, 'epoch': 0.49}) +[2026-07-27 08:39:47,733][starVLA.training.train_starvla][INFO] - Step 4022, Loss: {'train/loss': 0.12639595568180084, 'train/grad_norm_pre_clip': 3.381805419921875, 'timing/data': 0.00020491890609264374, 'timing/model': 0.45691812597215176, 'learning_rate/action_model': 9.999541426003034e-05, 'learning_rate/action_query_proj': 9.999541426003034e-05, 'learning_rate/base': 2.4998853565007585e-05, 'epoch': 0.49}) +[2026-07-27 08:39:53,272][starVLA.training.train_starvla][INFO] - Step 4023, Loss: {'train/loss': 0.06882911175489426, 'train/grad_norm_pre_clip': 3.6190645694732666, 'timing/data': 0.0002592317759990692, 'timing/model': 0.457519706338644, 'learning_rate/action_model': 9.999498790732934e-05, 'learning_rate/action_query_proj': 9.999498790732934e-05, 'learning_rate/base': 2.4998746976832335e-05, 'epoch': 0.49}) +[2026-07-27 08:39:58,789][starVLA.training.train_starvla][INFO] - Step 4024, Loss: {'train/loss': 0.06383075565099716, 'train/grad_norm_pre_clip': 3.790208578109741, 'timing/data': 0.0002543944865465164, 'timing/model': 0.4575814977288246, 'learning_rate/action_model': 9.999454260696719e-05, 'learning_rate/action_query_proj': 9.999454260696719e-05, 'learning_rate/base': 2.4998635651741797e-05, 'epoch': 0.49}) +[2026-07-27 08:40:04,342][starVLA.training.train_starvla][INFO] - Step 4025, Loss: {'train/loss': 0.10293355584144592, 'train/grad_norm_pre_clip': 3.136768341064453, 'timing/data': 0.0002669263631105423, 'timing/model': 0.45834413915872574, 'learning_rate/action_model': 9.999407835911971e-05, 'learning_rate/action_query_proj': 9.999407835911971e-05, 'learning_rate/base': 2.4998519589779927e-05, 'epoch': 0.49}) +[2026-07-27 08:40:09,880][starVLA.training.train_starvla][INFO] - Step 4026, Loss: {'train/loss': 0.12067549675703049, 'train/grad_norm_pre_clip': 2.986886739730835, 'timing/data': 0.00027460977435112, 'timing/model': 0.4587506949901581, 'learning_rate/action_model': 9.999359516397018e-05, 'learning_rate/action_query_proj': 9.999359516397018e-05, 'learning_rate/base': 2.4998398790992545e-05, 'epoch': 0.49}) +[2026-07-27 08:40:15,441][starVLA.training.train_starvla][INFO] - Step 4027, Loss: {'train/loss': 0.033908650279045105, 'train/grad_norm_pre_clip': 2.2192270755767822, 'timing/data': 0.00021174363791942596, 'timing/model': 0.4582606051117182, 'learning_rate/action_model': 9.999309302170934e-05, 'learning_rate/action_query_proj': 9.999309302170934e-05, 'learning_rate/base': 2.4998273255427336e-05, 'epoch': 0.49}) +[2026-07-27 08:40:20,972][starVLA.training.train_starvla][INFO] - Step 4028, Loss: {'train/loss': 0.07199883460998535, 'train/grad_norm_pre_clip': 3.0495786666870117, 'timing/data': 0.0002051517367362976, 'timing/model': 0.45747492276132107, 'learning_rate/action_model': 9.999257193253546e-05, 'learning_rate/action_query_proj': 9.999257193253546e-05, 'learning_rate/base': 2.4998142983133864e-05, 'epoch': 0.49}) +[2026-07-27 08:40:26,495][starVLA.training.train_starvla][INFO] - Step 4029, Loss: {'train/loss': 0.067745141685009, 'train/grad_norm_pre_clip': 3.3280303478240967, 'timing/data': 0.00020735524594783783, 'timing/model': 0.45721069164574146, 'learning_rate/action_model': 9.999203189665421e-05, 'learning_rate/action_query_proj': 9.999203189665421e-05, 'learning_rate/base': 2.4998007974163552e-05, 'epoch': 0.49}) +[2026-07-27 08:40:32,053][starVLA.training.train_starvla][INFO] - Step 4030, Loss: {'train/loss': 0.039095837622880936, 'train/grad_norm_pre_clip': 2.4066710472106934, 'timing/data': 0.00019555538892745972, 'timing/model': 0.45720880664885044, 'learning_rate/action_model': 9.999147291427884e-05, 'learning_rate/action_query_proj': 9.999147291427884e-05, 'learning_rate/base': 2.499786822856971e-05, 'epoch': 0.49}) +[2026-07-27 08:40:37,578][starVLA.training.train_starvla][INFO] - Step 4031, Loss: {'train/loss': 0.08924960345029831, 'train/grad_norm_pre_clip': 3.2747719287872314, 'timing/data': 0.0003770533949136734, 'timing/model': 0.4584750197827816, 'learning_rate/action_model': 9.999089498562998e-05, 'learning_rate/action_query_proj': 9.999089498562998e-05, 'learning_rate/base': 2.4997723746407496e-05, 'epoch': 0.49}) +[2026-07-27 08:40:43,119][starVLA.training.train_starvla][INFO] - Step 4032, Loss: {'train/loss': 0.04970682039856911, 'train/grad_norm_pre_clip': 3.236295700073242, 'timing/data': 0.00020652823150157928, 'timing/model': 0.45867282152175903, 'learning_rate/action_model': 9.999029811093582e-05, 'learning_rate/action_query_proj': 9.999029811093582e-05, 'learning_rate/base': 2.4997574527733956e-05, 'epoch': 0.49}) +[2026-07-27 08:40:48,663][starVLA.training.train_starvla][INFO] - Step 4033, Loss: {'train/loss': 0.13336879014968872, 'train/grad_norm_pre_clip': 4.670230865478516, 'timing/data': 0.00019746273756027222, 'timing/model': 0.45816962234675884, 'learning_rate/action_model': 9.998968229043199e-05, 'learning_rate/action_query_proj': 9.998968229043199e-05, 'learning_rate/base': 2.4997420572607998e-05, 'epoch': 0.49}) +[2026-07-27 08:40:54,200][starVLA.training.train_starvla][INFO] - Step 4034, Loss: {'train/loss': 0.11648987233638763, 'train/grad_norm_pre_clip': 4.020959854125977, 'timing/data': 0.00019284524023532867, 'timing/model': 0.4578775428235531, 'learning_rate/action_model': 9.99890475243616e-05, 'learning_rate/action_query_proj': 9.99890475243616e-05, 'learning_rate/base': 2.49972618810904e-05, 'epoch': 0.49}) +[2026-07-27 08:40:59,735][starVLA.training.train_starvla][INFO] - Step 4035, Loss: {'train/loss': 0.0401950366795063, 'train/grad_norm_pre_clip': 2.81941294670105, 'timing/data': 0.0001966916024684906, 'timing/model': 0.45861655101180077, 'learning_rate/action_model': 9.998839381297525e-05, 'learning_rate/action_query_proj': 9.998839381297525e-05, 'learning_rate/base': 2.4997098453243813e-05, 'epoch': 0.49}) +[2026-07-27 08:41:05,260][starVLA.training.train_starvla][INFO] - Step 4036, Loss: {'train/loss': 0.0679720789194107, 'train/grad_norm_pre_clip': 3.3585026264190674, 'timing/data': 0.00021264702081680298, 'timing/model': 0.4587192162871361, 'learning_rate/action_model': 9.998772115653099e-05, 'learning_rate/action_query_proj': 9.998772115653099e-05, 'learning_rate/base': 2.4996930289132748e-05, 'epoch': 0.49}) +[2026-07-27 08:41:10,804][starVLA.training.train_starvla][INFO] - Step 4037, Loss: {'train/loss': 0.07620368152856827, 'train/grad_norm_pre_clip': 2.6623167991638184, 'timing/data': 0.00020761974155902863, 'timing/model': 0.45777267776429653, 'learning_rate/action_model': 9.998702955529441e-05, 'learning_rate/action_query_proj': 9.998702955529441e-05, 'learning_rate/base': 2.4996757388823603e-05, 'epoch': 0.49}) +[2026-07-27 08:41:16,352][starVLA.training.train_starvla][INFO] - Step 4038, Loss: {'train/loss': 0.06641941517591476, 'train/grad_norm_pre_clip': 2.664357900619507, 'timing/data': 0.00019644014537334442, 'timing/model': 0.4574741665273905, 'learning_rate/action_model': 9.998631900953854e-05, 'learning_rate/action_query_proj': 9.998631900953854e-05, 'learning_rate/base': 2.4996579752384635e-05, 'epoch': 0.49}) +[2026-07-27 08:41:21,879][starVLA.training.train_starvla][INFO] - Step 4039, Loss: {'train/loss': 0.035834960639476776, 'train/grad_norm_pre_clip': 2.2347116470336914, 'timing/data': 0.00019891373813152313, 'timing/model': 0.4568685106933117, 'learning_rate/action_model': 9.998558951954387e-05, 'learning_rate/action_query_proj': 9.998558951954387e-05, 'learning_rate/base': 2.4996397379885968e-05, 'epoch': 0.49}) +[2026-07-27 08:41:27,422][starVLA.training.train_starvla][INFO] - Step 4040, Loss: {'train/loss': 0.0682099387049675, 'train/grad_norm_pre_clip': 3.1880581378936768, 'timing/data': 0.00020727142691612244, 'timing/model': 0.45858109183609486, 'learning_rate/action_model': 9.99848410855984e-05, 'learning_rate/action_query_proj': 9.99848410855984e-05, 'learning_rate/base': 2.49962102713996e-05, 'epoch': 0.49}) +[2026-07-27 08:41:32,949][starVLA.training.train_starvla][INFO] - Step 4041, Loss: {'train/loss': 0.05376102402806282, 'train/grad_norm_pre_clip': 2.6437675952911377, 'timing/data': 0.00019791722297668457, 'timing/model': 0.45800524204969406, 'learning_rate/action_model': 9.99840737079976e-05, 'learning_rate/action_query_proj': 9.99840737079976e-05, 'learning_rate/base': 2.49960184269994e-05, 'epoch': 0.49}) +[2026-07-27 08:41:38,478][starVLA.training.train_starvla][INFO] - Step 4042, Loss: {'train/loss': 0.0733640268445015, 'train/grad_norm_pre_clip': 3.285761833190918, 'timing/data': 0.0001937858760356903, 'timing/model': 0.4580045063048601, 'learning_rate/action_model': 9.998328738704444e-05, 'learning_rate/action_query_proj': 9.998328738704444e-05, 'learning_rate/base': 2.499582184676111e-05, 'epoch': 0.49}) +[2026-07-27 08:41:43,964][starVLA.training.train_starvla][INFO] - Step 4043, Loss: {'train/loss': 0.1467083841562271, 'train/grad_norm_pre_clip': 4.370985507965088, 'timing/data': 0.0001955851912498474, 'timing/model': 0.457238694652915, 'learning_rate/action_model': 9.998248212304932e-05, 'learning_rate/action_query_proj': 9.998248212304932e-05, 'learning_rate/base': 2.499562053076233e-05, 'epoch': 0.49}) +[2026-07-27 08:41:49,457][starVLA.training.train_starvla][INFO] - Step 4044, Loss: {'train/loss': 0.07242832332849503, 'train/grad_norm_pre_clip': 2.3228931427001953, 'timing/data': 0.00021297670900821686, 'timing/model': 0.459314851090312, 'learning_rate/action_model': 9.998165791633016e-05, 'learning_rate/action_query_proj': 9.998165791633016e-05, 'learning_rate/base': 2.499541447908254e-05, 'epoch': 0.49}) +[2026-07-27 08:41:54,938][starVLA.training.train_starvla][INFO] - Step 4045, Loss: {'train/loss': 0.05599785968661308, 'train/grad_norm_pre_clip': 2.717061996459961, 'timing/data': 0.00020534545183181763, 'timing/model': 0.4574710391461849, 'learning_rate/action_model': 9.998081476721232e-05, 'learning_rate/action_query_proj': 9.998081476721232e-05, 'learning_rate/base': 2.499520369180308e-05, 'epoch': 0.49}) +[2026-07-27 08:42:00,406][starVLA.training.train_starvla][INFO] - Step 4046, Loss: {'train/loss': 0.11524701118469238, 'train/grad_norm_pre_clip': 3.860808849334717, 'timing/data': 0.00019416958093643188, 'timing/model': 0.4580049645155668, 'learning_rate/action_model': 9.997995267602868e-05, 'learning_rate/action_query_proj': 9.997995267602868e-05, 'learning_rate/base': 2.499498816900717e-05, 'epoch': 0.49}) +[2026-07-27 08:42:05,879][starVLA.training.train_starvla][INFO] - Step 4047, Loss: {'train/loss': 0.13612550497055054, 'train/grad_norm_pre_clip': 3.45310115814209, 'timing/data': 0.00019195489585399628, 'timing/model': 0.45640211924910545, 'learning_rate/action_model': 9.997907164311958e-05, 'learning_rate/action_query_proj': 9.997907164311958e-05, 'learning_rate/base': 2.4994767910779894e-05, 'epoch': 0.49}) +[2026-07-27 08:42:11,346][starVLA.training.train_starvla][INFO] - Step 4048, Loss: {'train/loss': 0.02802499756217003, 'train/grad_norm_pre_clip': 2.4132275581359863, 'timing/data': 0.0001964569091796875, 'timing/model': 0.45725223794579506, 'learning_rate/action_model': 9.997817166883286e-05, 'learning_rate/action_query_proj': 9.997817166883286e-05, 'learning_rate/base': 2.4994542917208215e-05, 'epoch': 0.49}) +[2026-07-27 08:42:16,834][starVLA.training.train_starvla][INFO] - Step 4049, Loss: {'train/loss': 0.05369028449058533, 'train/grad_norm_pre_clip': 3.1661291122436523, 'timing/data': 0.00018967688083648682, 'timing/model': 0.4566887132823467, 'learning_rate/action_model': 9.997725275352378e-05, 'learning_rate/action_query_proj': 9.997725275352378e-05, 'learning_rate/base': 2.4994313188380945e-05, 'epoch': 0.49}) +[2026-07-27 08:42:22,301][starVLA.training.train_starvla][INFO] - Step 4050, Loss: {'train/loss': 0.02762502431869507, 'train/grad_norm_pre_clip': 1.818816900253296, 'timing/data': 0.00019302964210510254, 'timing/model': 0.45732870139181614, 'learning_rate/action_model': 9.997631489755513e-05, 'learning_rate/action_query_proj': 9.997631489755513e-05, 'learning_rate/base': 2.4994078724388782e-05, 'epoch': 0.49}) +[2026-07-27 08:42:27,793][starVLA.training.train_starvla][INFO] - Step 4051, Loss: {'train/loss': 0.038454797118902206, 'train/grad_norm_pre_clip': 1.9711599349975586, 'timing/data': 0.000197485089302063, 'timing/model': 0.45630226470530033, 'learning_rate/action_model': 9.997535810129714e-05, 'learning_rate/action_query_proj': 9.997535810129714e-05, 'learning_rate/base': 2.4993839525324285e-05, 'epoch': 0.49}) +[2026-07-27 08:42:33,291][starVLA.training.train_starvla][INFO] - Step 4052, Loss: {'train/loss': 0.14685706794261932, 'train/grad_norm_pre_clip': 3.835594654083252, 'timing/data': 0.0003591291606426239, 'timing/model': 0.45749286375939846, 'learning_rate/action_model': 9.997438236512756e-05, 'learning_rate/action_query_proj': 9.997438236512756e-05, 'learning_rate/base': 2.499359559128189e-05, 'epoch': 0.49}) +[2026-07-27 08:42:38,808][starVLA.training.train_starvla][INFO] - Step 4053, Loss: {'train/loss': 0.031493205577135086, 'train/grad_norm_pre_clip': 1.4731565713882446, 'timing/data': 0.00020586885511875153, 'timing/model': 0.4579954817891121, 'learning_rate/action_model': 9.99733876894316e-05, 'learning_rate/action_query_proj': 9.99733876894316e-05, 'learning_rate/base': 2.49933469223579e-05, 'epoch': 0.49}) +[2026-07-27 08:42:44,302][starVLA.training.train_starvla][INFO] - Step 4054, Loss: {'train/loss': 0.05687103793025017, 'train/grad_norm_pre_clip': 2.5958287715911865, 'timing/data': 0.00019923970103263855, 'timing/model': 0.4567535761743784, 'learning_rate/action_model': 9.997237407460191e-05, 'learning_rate/action_query_proj': 9.997237407460191e-05, 'learning_rate/base': 2.4993093518650478e-05, 'epoch': 0.49}) +[2026-07-27 08:42:49,854][starVLA.training.train_starvla][INFO] - Step 4055, Loss: {'train/loss': 0.0333453007042408, 'train/grad_norm_pre_clip': 1.9078878164291382, 'timing/data': 0.0001940559595823288, 'timing/model': 0.4570981878787279, 'learning_rate/action_model': 9.997134152103871e-05, 'learning_rate/action_query_proj': 9.997134152103871e-05, 'learning_rate/base': 2.4992835380259678e-05, 'epoch': 0.49}) +[2026-07-27 08:42:55,459][starVLA.training.train_starvla][INFO] - Step 4056, Loss: {'train/loss': 0.09062746167182922, 'train/grad_norm_pre_clip': 3.5676796436309814, 'timing/data': 0.0001902356743812561, 'timing/model': 0.4765599351376295, 'learning_rate/action_model': 9.997029002914957e-05, 'learning_rate/action_query_proj': 9.997029002914957e-05, 'learning_rate/base': 2.4992572507287394e-05, 'epoch': 0.49}) +[2026-07-27 08:43:01,044][starVLA.training.train_starvla][INFO] - Step 4057, Loss: {'train/loss': 0.15636813640594482, 'train/grad_norm_pre_clip': 5.127134323120117, 'timing/data': 0.00019516609609127045, 'timing/model': 0.46510692313313484, 'learning_rate/action_model': 9.996921959934963e-05, 'learning_rate/action_query_proj': 9.996921959934963e-05, 'learning_rate/base': 2.4992304899837407e-05, 'epoch': 0.49}) +[2026-07-27 08:43:06,679][starVLA.training.train_starvla][INFO] - Step 4058, Loss: {'train/loss': 0.11871829628944397, 'train/grad_norm_pre_clip': 3.1555964946746826, 'timing/data': 0.000196969136595726, 'timing/model': 0.47990190982818604, 'learning_rate/action_model': 9.996813023206148e-05, 'learning_rate/action_query_proj': 9.996813023206148e-05, 'learning_rate/base': 2.499203255801537e-05, 'epoch': 0.49}) +[2026-07-27 08:43:12,275][starVLA.training.train_starvla][INFO] - Step 4059, Loss: {'train/loss': 0.07623931765556335, 'train/grad_norm_pre_clip': 3.8036999702453613, 'timing/data': 0.00021408312022686005, 'timing/model': 0.466240918263793, 'learning_rate/action_model': 9.996702192771519e-05, 'learning_rate/action_query_proj': 9.996702192771519e-05, 'learning_rate/base': 2.4991755481928798e-05, 'epoch': 0.49}) +[2026-07-27 08:43:17,939][starVLA.training.train_starvla][INFO] - Step 4060, Loss: {'train/loss': 0.06592172384262085, 'train/grad_norm_pre_clip': 4.223669052124023, 'timing/data': 0.00021128356456756592, 'timing/model': 0.4777781367301941, 'learning_rate/action_model': 9.996589468674828e-05, 'learning_rate/action_query_proj': 9.996589468674828e-05, 'learning_rate/base': 2.499147367168707e-05, 'epoch': 0.49}) +[2026-07-27 08:43:23,588][starVLA.training.train_starvla][INFO] - Step 4061, Loss: {'train/loss': 0.09189088642597198, 'train/grad_norm_pre_clip': 4.084499359130859, 'timing/data': 0.000203816220164299, 'timing/model': 0.4768346529453993, 'learning_rate/action_model': 9.99647485096058e-05, 'learning_rate/action_query_proj': 9.99647485096058e-05, 'learning_rate/base': 2.499118712740145e-05, 'epoch': 0.49}) +[2026-07-27 08:43:29,216][starVLA.training.train_starvla][INFO] - Step 4062, Loss: {'train/loss': 0.17691069841384888, 'train/grad_norm_pre_clip': 4.96069860458374, 'timing/data': 0.00018569640815258026, 'timing/model': 0.47713800705969334, 'learning_rate/action_model': 9.996358339674021e-05, 'learning_rate/action_query_proj': 9.996358339674021e-05, 'learning_rate/base': 2.4990895849185053e-05, 'epoch': 0.49}) +[2026-07-27 08:43:34,833][starVLA.training.train_starvla][INFO] - Step 4063, Loss: {'train/loss': 0.07163392752408981, 'train/grad_norm_pre_clip': 3.3740150928497314, 'timing/data': 0.0001965295523405075, 'timing/model': 0.4714066516608, 'learning_rate/action_model': 9.99623993486115e-05, 'learning_rate/action_query_proj': 9.99623993486115e-05, 'learning_rate/base': 2.4990599837152875e-05, 'epoch': 0.49}) +[2026-07-27 08:43:40,429][starVLA.training.train_starvla][INFO] - Step 4064, Loss: {'train/loss': 0.18335123360157013, 'train/grad_norm_pre_clip': 4.537128448486328, 'timing/data': 0.00018963776528835297, 'timing/model': 0.4708246383816004, 'learning_rate/action_model': 9.99611963656871e-05, 'learning_rate/action_query_proj': 9.99611963656871e-05, 'learning_rate/base': 2.4990299091421775e-05, 'epoch': 0.49}) +[2026-07-27 08:43:46,064][starVLA.training.train_starvla][INFO] - Step 4065, Loss: {'train/loss': 0.19074741005897522, 'train/grad_norm_pre_clip': 5.6810173988342285, 'timing/data': 0.00018586032092571259, 'timing/model': 0.47600739635527134, 'learning_rate/action_model': 9.995997444844192e-05, 'learning_rate/action_query_proj': 9.995997444844192e-05, 'learning_rate/base': 2.498999361211048e-05, 'epoch': 0.49}) +[2026-07-27 08:43:51,668][starVLA.training.train_starvla][INFO] - Step 4066, Loss: {'train/loss': 0.26653942465782166, 'train/grad_norm_pre_clip': 6.177319049835205, 'timing/data': 0.00019378028810024261, 'timing/model': 0.47202450037002563, 'learning_rate/action_model': 9.995873359735839e-05, 'learning_rate/action_query_proj': 9.995873359735839e-05, 'learning_rate/base': 2.4989683399339598e-05, 'epoch': 0.49}) +[2026-07-27 08:43:57,286][starVLA.training.train_starvla][INFO] - Step 4067, Loss: {'train/loss': 0.0818316638469696, 'train/grad_norm_pre_clip': 4.444629192352295, 'timing/data': 0.00018214434385299683, 'timing/model': 0.4723206590861082, 'learning_rate/action_model': 9.995747381292634e-05, 'learning_rate/action_query_proj': 9.995747381292634e-05, 'learning_rate/base': 2.4989368453231586e-05, 'epoch': 0.49}) +[2026-07-27 08:44:02,899][starVLA.training.train_starvla][INFO] - Step 4068, Loss: {'train/loss': 0.09585543721914291, 'train/grad_norm_pre_clip': 4.1820244789123535, 'timing/data': 0.00019904598593711853, 'timing/model': 0.47175486385822296, 'learning_rate/action_model': 9.995619509564315e-05, 'learning_rate/action_query_proj': 9.995619509564315e-05, 'learning_rate/base': 2.4989048773910787e-05, 'epoch': 0.49}) +[2026-07-27 08:44:08,517][starVLA.training.train_starvla][INFO] - Step 4069, Loss: {'train/loss': 0.052190110087394714, 'train/grad_norm_pre_clip': 2.7999086380004883, 'timing/data': 0.0001882072538137436, 'timing/model': 0.47216161899268627, 'learning_rate/action_model': 9.995489744601361e-05, 'learning_rate/action_query_proj': 9.995489744601361e-05, 'learning_rate/base': 2.4988724361503402e-05, 'epoch': 0.49}) +[2026-07-27 08:44:14,130][starVLA.training.train_starvla][INFO] - Step 4070, Loss: {'train/loss': 0.2124822437763214, 'train/grad_norm_pre_clip': 5.5039567947387695, 'timing/data': 0.00018275529146194458, 'timing/model': 0.4791738297790289, 'learning_rate/action_model': 9.995358086455e-05, 'learning_rate/action_query_proj': 9.995358086455e-05, 'learning_rate/base': 2.49883952161375e-05, 'epoch': 0.49}) +[2026-07-27 08:44:19,714][starVLA.training.train_starvla][INFO] - Step 4071, Loss: {'train/loss': 0.07942710816860199, 'train/grad_norm_pre_clip': 3.621941328048706, 'timing/data': 0.00018978305160999298, 'timing/model': 0.4696072954684496, 'learning_rate/action_model': 9.99522453517721e-05, 'learning_rate/action_query_proj': 9.99522453517721e-05, 'learning_rate/base': 2.4988061337943024e-05, 'epoch': 0.49}) +[2026-07-27 08:44:25,294][starVLA.training.train_starvla][INFO] - Step 4072, Loss: {'train/loss': 0.039105769246816635, 'train/grad_norm_pre_clip': 1.9043214321136475, 'timing/data': 0.00019234046339988708, 'timing/model': 0.47558706998825073, 'learning_rate/action_model': 9.995089090820716e-05, 'learning_rate/action_query_proj': 9.995089090820716e-05, 'learning_rate/base': 2.498772272705179e-05, 'epoch': 0.49}) +[2026-07-27 08:44:30,876][starVLA.training.train_starvla][INFO] - Step 4073, Loss: {'train/loss': 0.14973974227905273, 'train/grad_norm_pre_clip': 5.886595726013184, 'timing/data': 0.0002025216817855835, 'timing/model': 0.46859708800911903, 'learning_rate/action_model': 9.99495175343899e-05, 'learning_rate/action_query_proj': 9.99495175343899e-05, 'learning_rate/base': 2.4987379383597474e-05, 'epoch': 0.49}) +[2026-07-27 08:44:36,455][starVLA.training.train_starvla][INFO] - Step 4074, Loss: {'train/loss': 0.19800439476966858, 'train/grad_norm_pre_clip': 7.30977725982666, 'timing/data': 0.00018758326768875122, 'timing/model': 0.47111356630921364, 'learning_rate/action_model': 9.994812523086248e-05, 'learning_rate/action_query_proj': 9.994812523086248e-05, 'learning_rate/base': 2.498703130771562e-05, 'epoch': 0.49}) +[2026-07-27 08:44:42,087][starVLA.training.train_starvla][INFO] - Step 4075, Loss: {'train/loss': 0.13734103739261627, 'train/grad_norm_pre_clip': 4.43571662902832, 'timing/data': 0.00018378347158432007, 'timing/model': 0.47677750512957573, 'learning_rate/action_model': 9.994671399817457e-05, 'learning_rate/action_query_proj': 9.994671399817457e-05, 'learning_rate/base': 2.4986678499543643e-05, 'epoch': 0.49}) +[2026-07-27 08:44:47,687][starVLA.training.train_starvla][INFO] - Step 4076, Loss: {'train/loss': 0.0982777550816536, 'train/grad_norm_pre_clip': 4.402736663818359, 'timing/data': 0.00019467249512672424, 'timing/model': 0.4703678507357836, 'learning_rate/action_model': 9.994528383688328e-05, 'learning_rate/action_query_proj': 9.994528383688328e-05, 'learning_rate/base': 2.498632095922082e-05, 'epoch': 0.49}) +[2026-07-27 08:44:53,289][starVLA.training.train_starvla][INFO] - Step 4077, Loss: {'train/loss': 0.03834174573421478, 'train/grad_norm_pre_clip': 2.375319242477417, 'timing/data': 0.00018385984003543854, 'timing/model': 0.4749138932675123, 'learning_rate/action_model': 9.994383474755328e-05, 'learning_rate/action_query_proj': 9.994383474755328e-05, 'learning_rate/base': 2.498595868688832e-05, 'epoch': 0.49}) +[2026-07-27 08:44:58,850][starVLA.training.train_starvla][INFO] - Step 4078, Loss: {'train/loss': 0.03128371387720108, 'train/grad_norm_pre_clip': 2.0579047203063965, 'timing/data': 0.00018409080803394318, 'timing/model': 0.46811470575630665, 'learning_rate/action_model': 9.994236673075659e-05, 'learning_rate/action_query_proj': 9.994236673075659e-05, 'learning_rate/base': 2.4985591682689147e-05, 'epoch': 0.49}) +[2026-07-27 08:45:04,396][starVLA.training.train_starvla][INFO] - Step 4079, Loss: {'train/loss': 0.06835369765758514, 'train/grad_norm_pre_clip': 2.5673837661743164, 'timing/data': 0.00018102489411830902, 'timing/model': 0.4768256042152643, 'learning_rate/action_model': 9.994087978707277e-05, 'learning_rate/action_query_proj': 9.994087978707277e-05, 'learning_rate/base': 2.498521994676819e-05, 'epoch': 0.49}) +[2026-07-27 08:45:09,974][starVLA.training.train_starvla][INFO] - Step 4080, Loss: {'train/loss': 0.16601820290088654, 'train/grad_norm_pre_clip': 3.5858466625213623, 'timing/data': 0.00018534623086452484, 'timing/model': 0.4664599150419235, 'learning_rate/action_model': 9.993937391708885e-05, 'learning_rate/action_query_proj': 9.993937391708885e-05, 'learning_rate/base': 2.4984843479272213e-05, 'epoch': 0.49}) +[2026-07-27 08:45:15,542][starVLA.training.train_starvla][INFO] - Step 4081, Loss: {'train/loss': 0.0840924084186554, 'train/grad_norm_pre_clip': 3.8213613033294678, 'timing/data': 0.00018641166388988495, 'timing/model': 0.4706284813582897, 'learning_rate/action_model': 9.993784912139931e-05, 'learning_rate/action_query_proj': 9.993784912139931e-05, 'learning_rate/base': 2.4984462280349827e-05, 'epoch': 0.5}) +[2026-07-27 08:45:21,082][starVLA.training.train_starvla][INFO] - Step 4082, Loss: {'train/loss': 0.07078880816698074, 'train/grad_norm_pre_clip': 3.0153653621673584, 'timing/data': 0.00019889138638973236, 'timing/model': 0.4708369057625532, 'learning_rate/action_model': 9.993630540060613e-05, 'learning_rate/action_query_proj': 9.993630540060613e-05, 'learning_rate/base': 2.4984076350151533e-05, 'epoch': 0.5}) +[2026-07-27 08:45:26,644][starVLA.training.train_starvla][INFO] - Step 4083, Loss: {'train/loss': 0.31000566482543945, 'train/grad_norm_pre_clip': 6.592958927154541, 'timing/data': 0.00018695183098316193, 'timing/model': 0.47436664812266827, 'learning_rate/action_model': 9.993474275531877e-05, 'learning_rate/action_query_proj': 9.993474275531877e-05, 'learning_rate/base': 2.498368568882969e-05, 'epoch': 0.5}) +[2026-07-27 08:45:32,214][starVLA.training.train_starvla][INFO] - Step 4084, Loss: {'train/loss': 0.08414198458194733, 'train/grad_norm_pre_clip': 3.753675699234009, 'timing/data': 0.00033661723136901855, 'timing/model': 0.46806338615715504, 'learning_rate/action_model': 9.993316118615408e-05, 'learning_rate/action_query_proj': 9.993316118615408e-05, 'learning_rate/base': 2.498329029653852e-05, 'epoch': 0.5}) +[2026-07-27 08:45:37,770][starVLA.training.train_starvla][INFO] - Step 4085, Loss: {'train/loss': 0.14624477922916412, 'train/grad_norm_pre_clip': 4.223960876464844, 'timing/data': 0.0001928713172674179, 'timing/model': 0.47534759901463985, 'learning_rate/action_model': 9.993156069373646e-05, 'learning_rate/action_query_proj': 9.993156069373646e-05, 'learning_rate/base': 2.4982890173434116e-05, 'epoch': 0.5}) +[2026-07-27 08:45:43,307][starVLA.training.train_starvla][INFO] - Step 4086, Loss: {'train/loss': 0.03429211303591728, 'train/grad_norm_pre_clip': 1.9766417741775513, 'timing/data': 0.00018860399723052979, 'timing/model': 0.4697842840105295, 'learning_rate/action_model': 9.992994127869779e-05, 'learning_rate/action_query_proj': 9.992994127869779e-05, 'learning_rate/base': 2.4982485319674448e-05, 'epoch': 0.5}) +[2026-07-27 08:45:48,861][starVLA.training.train_starvla][INFO] - Step 4087, Loss: {'train/loss': 0.020967882126569748, 'train/grad_norm_pre_clip': 1.1432020664215088, 'timing/data': 0.00018681026995182037, 'timing/model': 0.4772588014602661, 'learning_rate/action_model': 9.992830294167737e-05, 'learning_rate/action_query_proj': 9.992830294167737e-05, 'learning_rate/base': 2.4982075735419342e-05, 'epoch': 0.5}) +[2026-07-27 08:45:54,406][starVLA.training.train_starvla][INFO] - Step 4088, Loss: {'train/loss': 0.03221023827791214, 'train/grad_norm_pre_clip': 1.765365481376648, 'timing/data': 0.00019008666276931763, 'timing/model': 0.46961497515439987, 'learning_rate/action_model': 9.992664568332197e-05, 'learning_rate/action_query_proj': 9.992664568332197e-05, 'learning_rate/base': 2.4981661420830493e-05, 'epoch': 0.5}) +[2026-07-27 08:45:59,977][starVLA.training.train_starvla][INFO] - Step 4089, Loss: {'train/loss': 0.07583844661712646, 'train/grad_norm_pre_clip': 3.047473669052124, 'timing/data': 0.00019134394824504852, 'timing/model': 0.4754995685070753, 'learning_rate/action_model': 9.992496950428587e-05, 'learning_rate/action_query_proj': 9.992496950428587e-05, 'learning_rate/base': 2.4981242376071467e-05, 'epoch': 0.5}) +[2026-07-27 08:46:05,570][starVLA.training.train_starvla][INFO] - Step 4090, Loss: {'train/loss': 0.09603738784790039, 'train/grad_norm_pre_clip': 3.554288148880005, 'timing/data': 0.00019470974802970886, 'timing/model': 0.47554352693259716, 'learning_rate/action_model': 9.992327440523081e-05, 'learning_rate/action_query_proj': 9.992327440523081e-05, 'learning_rate/base': 2.4980818601307702e-05, 'epoch': 0.5}) +[2026-07-27 08:46:11,178][starVLA.training.train_starvla][INFO] - Step 4091, Loss: {'train/loss': 0.12739980220794678, 'train/grad_norm_pre_clip': 4.847411155700684, 'timing/data': 0.00018463283777236938, 'timing/model': 0.4762670751661062, 'learning_rate/action_model': 9.992156038682597e-05, 'learning_rate/action_query_proj': 9.992156038682597e-05, 'learning_rate/base': 2.4980390096706492e-05, 'epoch': 0.5}) +[2026-07-27 08:46:16,776][starVLA.training.train_starvla][INFO] - Step 4092, Loss: {'train/loss': 0.09790058434009552, 'train/grad_norm_pre_clip': 3.2282187938690186, 'timing/data': 0.0001905355602502823, 'timing/model': 0.47007180005311966, 'learning_rate/action_model': 9.991982744974799e-05, 'learning_rate/action_query_proj': 9.991982744974799e-05, 'learning_rate/base': 2.4979956862436998e-05, 'epoch': 0.5}) +[2026-07-27 08:46:22,393][starVLA.training.train_starvla][INFO] - Step 4093, Loss: {'train/loss': 0.08500082045793533, 'train/grad_norm_pre_clip': 3.336120843887329, 'timing/data': 0.00019020773470401764, 'timing/model': 0.47149891406297684, 'learning_rate/action_model': 9.991807559468107e-05, 'learning_rate/action_query_proj': 9.991807559468107e-05, 'learning_rate/base': 2.4979518898670267e-05, 'epoch': 0.5}) +[2026-07-27 08:46:27,994][starVLA.training.train_starvla][INFO] - Step 4094, Loss: {'train/loss': 0.08452753722667694, 'train/grad_norm_pre_clip': 3.6322548389434814, 'timing/data': 0.00018514320254325867, 'timing/model': 0.4694319497793913, 'learning_rate/action_model': 9.991630482231677e-05, 'learning_rate/action_query_proj': 9.991630482231677e-05, 'learning_rate/base': 2.4979076205579193e-05, 'epoch': 0.5}) +[2026-07-27 08:46:33,588][starVLA.training.train_starvla][INFO] - Step 4095, Loss: {'train/loss': 0.06653032451868057, 'train/grad_norm_pre_clip': 2.965813159942627, 'timing/data': 0.00019039027392864227, 'timing/model': 0.46657227352261543, 'learning_rate/action_model': 9.991451513335418e-05, 'learning_rate/action_query_proj': 9.991451513335418e-05, 'learning_rate/base': 2.4978628783338545e-05, 'epoch': 0.5}) +[2026-07-27 08:46:39,179][starVLA.training.train_starvla][INFO] - Step 4096, Loss: {'train/loss': 0.042256806045770645, 'train/grad_norm_pre_clip': 2.8197999000549316, 'timing/data': 0.00018568336963653564, 'timing/model': 0.467262776568532, 'learning_rate/action_model': 9.991270652849981e-05, 'learning_rate/action_query_proj': 9.991270652849981e-05, 'learning_rate/base': 2.4978176632124953e-05, 'epoch': 0.5}) +[2026-07-27 08:46:44,732][starVLA.training.train_starvla][INFO] - Step 4097, Loss: {'train/loss': 0.045944441109895706, 'train/grad_norm_pre_clip': 2.364628791809082, 'timing/data': 0.00018597394227981567, 'timing/model': 0.46779330261051655, 'learning_rate/action_model': 9.991087900846772e-05, 'learning_rate/action_query_proj': 9.991087900846772e-05, 'learning_rate/base': 2.497771975211693e-05, 'epoch': 0.5}) +[2026-07-27 08:46:50,334][starVLA.training.train_starvla][INFO] - Step 4098, Loss: {'train/loss': 0.09076537191867828, 'train/grad_norm_pre_clip': 3.416990041732788, 'timing/data': 0.00020075775682926178, 'timing/model': 0.47021788358688354, 'learning_rate/action_model': 9.990903257397934e-05, 'learning_rate/action_query_proj': 9.990903257397934e-05, 'learning_rate/base': 2.4977258143494836e-05, 'epoch': 0.5}) +[2026-07-27 08:46:55,943][starVLA.training.train_starvla][INFO] - Step 4099, Loss: {'train/loss': 0.10378939658403397, 'train/grad_norm_pre_clip': 3.2654576301574707, 'timing/data': 0.00020088627934455872, 'timing/model': 0.47640722803771496, 'learning_rate/action_model': 9.990716722576365e-05, 'learning_rate/action_query_proj': 9.990716722576365e-05, 'learning_rate/base': 2.4976791806440912e-05, 'epoch': 0.5}) +[2026-07-27 08:47:01,538][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 4100 +[2026-07-27 08:47:01,538][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 4100 +[2026-07-27 08:47:01,539][starVLA.training.train_starvla][INFO] - Step 4100, Loss: {'train/loss': 0.09826642274856567, 'train/grad_norm_pre_clip': 3.1601414680480957, 'timing/data': 0.0001907292753458023, 'timing/model': 0.4705669619143009, 'learning_rate/action_model': 9.990528296455703e-05, 'learning_rate/action_query_proj': 9.990528296455703e-05, 'learning_rate/base': 2.4976320741139258e-05, 'epoch': 0.5}) +[2026-07-27 08:47:07,151][starVLA.training.train_starvla][INFO] - Step 4101, Loss: {'train/loss': 0.12028864026069641, 'train/grad_norm_pre_clip': 3.310309648513794, 'timing/data': 0.00018848851323127747, 'timing/model': 0.47181179746985435, 'learning_rate/action_model': 9.990337979110337e-05, 'learning_rate/action_query_proj': 9.990337979110337e-05, 'learning_rate/base': 2.4975844947775844e-05, 'epoch': 0.5}) +[2026-07-27 08:47:12,805][starVLA.training.train_starvla][INFO] - Step 4102, Loss: {'train/loss': 0.06836726516485214, 'train/grad_norm_pre_clip': 2.3770875930786133, 'timing/data': 0.0001971721649169922, 'timing/model': 0.47120945528149605, 'learning_rate/action_model': 9.990145770615403e-05, 'learning_rate/action_query_proj': 9.990145770615403e-05, 'learning_rate/base': 2.4975364426538507e-05, 'epoch': 0.5}) +[2026-07-27 08:47:18,436][starVLA.training.train_starvla][INFO] - Step 4103, Loss: {'train/loss': 0.07326627522706985, 'train/grad_norm_pre_clip': 2.7071549892425537, 'timing/data': 0.0001878645271062851, 'timing/model': 0.47189504094421864, 'learning_rate/action_model': 9.989951671046779e-05, 'learning_rate/action_query_proj': 9.989951671046779e-05, 'learning_rate/base': 2.4974879177616947e-05, 'epoch': 0.5}) +[2026-07-27 08:47:24,057][starVLA.training.train_starvla][INFO] - Step 4104, Loss: {'train/loss': 0.059317298233509064, 'train/grad_norm_pre_clip': 3.035529851913452, 'timing/data': 0.0002394597977399826, 'timing/model': 0.47195817716419697, 'learning_rate/action_model': 9.989755680481093e-05, 'learning_rate/action_query_proj': 9.989755680481093e-05, 'learning_rate/base': 2.497438920120273e-05, 'epoch': 0.5}) +[2026-07-27 08:47:29,683][starVLA.training.train_starvla][INFO] - Step 4105, Loss: {'train/loss': 0.04043052718043327, 'train/grad_norm_pre_clip': 2.3769569396972656, 'timing/data': 0.00018565542995929718, 'timing/model': 0.46929169818758965, 'learning_rate/action_model': 9.98955779899572e-05, 'learning_rate/action_query_proj': 9.98955779899572e-05, 'learning_rate/base': 2.49738944974893e-05, 'epoch': 0.5}) +[2026-07-27 08:47:35,326][starVLA.training.train_starvla][INFO] - Step 4106, Loss: {'train/loss': 0.1269725263118744, 'train/grad_norm_pre_clip': 3.791166067123413, 'timing/data': 0.0001900363713502884, 'timing/model': 0.4744724500924349, 'learning_rate/action_model': 9.98935802666878e-05, 'learning_rate/action_query_proj': 9.98935802666878e-05, 'learning_rate/base': 2.497339506667195e-05, 'epoch': 0.5}) +[2026-07-27 08:47:40,982][starVLA.training.train_starvla][INFO] - Step 4107, Loss: {'train/loss': 0.08509231358766556, 'train/grad_norm_pre_clip': 3.755110263824463, 'timing/data': 0.00018078088760375977, 'timing/model': 0.46240632981061935, 'learning_rate/action_model': 9.989156363579138e-05, 'learning_rate/action_query_proj': 9.989156363579138e-05, 'learning_rate/base': 2.4972890908947846e-05, 'epoch': 0.5}) +[2026-07-27 08:47:46,609][starVLA.training.train_starvla][INFO] - Step 4108, Loss: {'train/loss': 0.07614994049072266, 'train/grad_norm_pre_clip': 3.1402690410614014, 'timing/data': 0.00018192827701568604, 'timing/model': 0.46052377484738827, 'learning_rate/action_model': 9.98895280980641e-05, 'learning_rate/action_query_proj': 9.98895280980641e-05, 'learning_rate/base': 2.4972382024516026e-05, 'epoch': 0.5}) +[2026-07-27 08:47:52,245][starVLA.training.train_starvla][INFO] - Step 4109, Loss: {'train/loss': 0.10109974443912506, 'train/grad_norm_pre_clip': 3.0537631511688232, 'timing/data': 0.00018845312297344208, 'timing/model': 0.4652673080563545, 'learning_rate/action_model': 9.988747365430957e-05, 'learning_rate/action_query_proj': 9.988747365430957e-05, 'learning_rate/base': 2.4971868413577392e-05, 'epoch': 0.5}) +[2026-07-27 08:47:57,871][starVLA.training.train_starvla][INFO] - Step 4110, Loss: {'train/loss': 0.06921595335006714, 'train/grad_norm_pre_clip': 2.8907885551452637, 'timing/data': 0.00018621794879436493, 'timing/model': 0.46211796067655087, 'learning_rate/action_model': 9.98854003053388e-05, 'learning_rate/action_query_proj': 9.98854003053388e-05, 'learning_rate/base': 2.49713500763347e-05, 'epoch': 0.5}) +[2026-07-27 08:48:03,502][starVLA.training.train_starvla][INFO] - Step 4111, Loss: {'train/loss': 0.05472448840737343, 'train/grad_norm_pre_clip': 2.660539150238037, 'timing/data': 0.00019475072622299194, 'timing/model': 0.45916710048913956, 'learning_rate/action_model': 9.988330805197039e-05, 'learning_rate/action_query_proj': 9.988330805197039e-05, 'learning_rate/base': 2.4970827012992596e-05, 'epoch': 0.5}) +[2026-07-27 08:48:09,069][starVLA.training.train_starvla][INFO] - Step 4112, Loss: {'train/loss': 0.15180444717407227, 'train/grad_norm_pre_clip': 5.916079044342041, 'timing/data': 0.00019518472254276276, 'timing/model': 0.45893331803381443, 'learning_rate/action_model': 9.988119689503026e-05, 'learning_rate/action_query_proj': 9.988119689503026e-05, 'learning_rate/base': 2.4970299223757564e-05, 'epoch': 0.5}) +[2026-07-27 08:48:14,665][starVLA.training.train_starvla][INFO] - Step 4113, Loss: {'train/loss': 0.0728631466627121, 'train/grad_norm_pre_clip': 3.1143639087677, 'timing/data': 0.00019417144358158112, 'timing/model': 0.4589610807597637, 'learning_rate/action_model': 9.987906683535189e-05, 'learning_rate/action_query_proj': 9.987906683535189e-05, 'learning_rate/base': 2.4969766708837973e-05, 'epoch': 0.5}) +[2026-07-27 08:48:20,235][starVLA.training.train_starvla][INFO] - Step 4114, Loss: {'train/loss': 0.10256151109933853, 'train/grad_norm_pre_clip': 3.5783498287200928, 'timing/data': 0.00021114014089107513, 'timing/model': 0.45743032544851303, 'learning_rate/action_model': 9.987691787377619e-05, 'learning_rate/action_query_proj': 9.987691787377619e-05, 'learning_rate/base': 2.4969229468444047e-05, 'epoch': 0.5}) +[2026-07-27 08:48:25,804][starVLA.training.train_starvla][INFO] - Step 4115, Loss: {'train/loss': 0.009818550199270248, 'train/grad_norm_pre_clip': 0.5451692342758179, 'timing/data': 0.00019087083637714386, 'timing/model': 0.45813154987990856, 'learning_rate/action_model': 9.987475001115155e-05, 'learning_rate/action_query_proj': 9.987475001115155e-05, 'learning_rate/base': 2.4968687502787886e-05, 'epoch': 0.5}) +[2026-07-27 08:48:31,370][starVLA.training.train_starvla][INFO] - Step 4116, Loss: {'train/loss': 0.08558687567710876, 'train/grad_norm_pre_clip': 2.619457244873047, 'timing/data': 0.00019216351211071014, 'timing/model': 0.45797528326511383, 'learning_rate/action_model': 9.987256324833378e-05, 'learning_rate/action_query_proj': 9.987256324833378e-05, 'learning_rate/base': 2.4968140812083445e-05, 'epoch': 0.5}) +[2026-07-27 08:48:36,923][starVLA.training.train_starvla][INFO] - Step 4117, Loss: {'train/loss': 0.09259946644306183, 'train/grad_norm_pre_clip': 3.970947504043579, 'timing/data': 0.00018701888620853424, 'timing/model': 0.4587415512651205, 'learning_rate/action_model': 9.98703575861862e-05, 'learning_rate/action_query_proj': 9.98703575861862e-05, 'learning_rate/base': 2.496758939654655e-05, 'epoch': 0.5}) +[2026-07-27 08:48:42,502][starVLA.training.train_starvla][INFO] - Step 4118, Loss: {'train/loss': 0.09303325414657593, 'train/grad_norm_pre_clip': 3.519289970397949, 'timing/data': 0.0001827143132686615, 'timing/model': 0.4587626773864031, 'learning_rate/action_model': 9.986813302557955e-05, 'learning_rate/action_query_proj': 9.986813302557955e-05, 'learning_rate/base': 2.4967033256394888e-05, 'epoch': 0.5}) +[2026-07-27 08:48:48,060][starVLA.training.train_starvla][INFO] - Step 4119, Loss: {'train/loss': 0.05287531390786171, 'train/grad_norm_pre_clip': 2.588137626647949, 'timing/data': 0.0001879967749118805, 'timing/model': 0.4580931030213833, 'learning_rate/action_model': 9.98658895673921e-05, 'learning_rate/action_query_proj': 9.98658895673921e-05, 'learning_rate/base': 2.4966472391848025e-05, 'epoch': 0.5}) +[2026-07-27 08:48:53,620][starVLA.training.train_starvla][INFO] - Step 4120, Loss: {'train/loss': 0.10598446428775787, 'train/grad_norm_pre_clip': 2.64154314994812, 'timing/data': 0.00018243305385112762, 'timing/model': 0.4588814117014408, 'learning_rate/action_model': 9.986362721250947e-05, 'learning_rate/action_query_proj': 9.986362721250947e-05, 'learning_rate/base': 2.4965906803127368e-05, 'epoch': 0.5}) +[2026-07-27 08:48:59,460][starVLA.training.train_starvla][INFO] - Step 4121, Loss: {'train/loss': 0.11813592165708542, 'train/grad_norm_pre_clip': 4.208117961883545, 'timing/data': 0.00018168240785598755, 'timing/model': 0.46454718708992004, 'learning_rate/action_model': 9.986134596182483e-05, 'learning_rate/action_query_proj': 9.986134596182483e-05, 'learning_rate/base': 2.4965336490456208e-05, 'epoch': 0.5}) +[2026-07-27 08:49:05,068][starVLA.training.train_starvla][INFO] - Step 4122, Loss: {'train/loss': 0.13523142039775848, 'train/grad_norm_pre_clip': 5.546117782592773, 'timing/data': 0.00018910691142082214, 'timing/model': 0.4663637988269329, 'learning_rate/action_model': 9.98590458162388e-05, 'learning_rate/action_query_proj': 9.98590458162388e-05, 'learning_rate/base': 2.49647614540597e-05, 'epoch': 0.5}) +[2026-07-27 08:49:10,669][starVLA.training.train_starvla][INFO] - Step 4123, Loss: {'train/loss': 0.11521662771701813, 'train/grad_norm_pre_clip': 4.611292362213135, 'timing/data': 0.00018683820962905884, 'timing/model': 0.4669838882982731, 'learning_rate/action_model': 9.985672677665942e-05, 'learning_rate/action_query_proj': 9.985672677665942e-05, 'learning_rate/base': 2.4964181694164854e-05, 'epoch': 0.5}) +[2026-07-27 08:49:16,248][starVLA.training.train_starvla][INFO] - Step 4124, Loss: {'train/loss': 0.14406238496303558, 'train/grad_norm_pre_clip': 3.616826057434082, 'timing/data': 0.00018732808530330658, 'timing/model': 0.46567359007894993, 'learning_rate/action_model': 9.985438884400221e-05, 'learning_rate/action_query_proj': 9.985438884400221e-05, 'learning_rate/base': 2.4963597211000553e-05, 'epoch': 0.5}) +[2026-07-27 08:49:21,793][starVLA.training.train_starvla][INFO] - Step 4125, Loss: {'train/loss': 0.0817055031657219, 'train/grad_norm_pre_clip': 3.4327495098114014, 'timing/data': 0.0001827925443649292, 'timing/model': 0.4572286047041416, 'learning_rate/action_model': 9.985203201919016e-05, 'learning_rate/action_query_proj': 9.985203201919016e-05, 'learning_rate/base': 2.496300800479754e-05, 'epoch': 0.5}) +[2026-07-27 08:49:27,322][starVLA.training.train_starvla][INFO] - Step 4126, Loss: {'train/loss': 0.11748100817203522, 'train/grad_norm_pre_clip': 3.6637423038482666, 'timing/data': 0.00019004754722118378, 'timing/model': 0.4577066544443369, 'learning_rate/action_model': 9.984965630315367e-05, 'learning_rate/action_query_proj': 9.984965630315367e-05, 'learning_rate/base': 2.4962414075788417e-05, 'epoch': 0.5}) +[2026-07-27 08:49:32,858][starVLA.training.train_starvla][INFO] - Step 4127, Loss: {'train/loss': 0.24264082312583923, 'train/grad_norm_pre_clip': 5.708208084106445, 'timing/data': 0.00018830038607120514, 'timing/model': 0.4571208134293556, 'learning_rate/action_model': 9.984726169683069e-05, 'learning_rate/action_query_proj': 9.984726169683069e-05, 'learning_rate/base': 2.4961815424207673e-05, 'epoch': 0.5}) +[2026-07-27 08:49:38,396][starVLA.training.train_starvla][INFO] - Step 4128, Loss: {'train/loss': 0.07729537039995193, 'train/grad_norm_pre_clip': 4.428966522216797, 'timing/data': 0.0001890081912279129, 'timing/model': 0.4580848813056946, 'learning_rate/action_model': 9.984484820116655e-05, 'learning_rate/action_query_proj': 9.984484820116655e-05, 'learning_rate/base': 2.4961212050291636e-05, 'epoch': 0.5}) +[2026-07-27 08:49:43,932][starVLA.training.train_starvla][INFO] - Step 4129, Loss: {'train/loss': 0.11990624666213989, 'train/grad_norm_pre_clip': 4.673038482666016, 'timing/data': 0.000190073624253273, 'timing/model': 0.45678094029426575, 'learning_rate/action_model': 9.984241581711403e-05, 'learning_rate/action_query_proj': 9.984241581711403e-05, 'learning_rate/base': 2.4960603954278507e-05, 'epoch': 0.5}) +[2026-07-27 08:49:49,471][starVLA.training.train_starvla][INFO] - Step 4130, Loss: {'train/loss': 0.2281215935945511, 'train/grad_norm_pre_clip': 4.589778900146484, 'timing/data': 0.00018948689103126526, 'timing/model': 0.4574547838419676, 'learning_rate/action_model': 9.983996454563343e-05, 'learning_rate/action_query_proj': 9.983996454563343e-05, 'learning_rate/base': 2.4959991136408358e-05, 'epoch': 0.5}) +[2026-07-27 08:49:55,283][starVLA.training.train_starvla][INFO] - Step 4131, Loss: {'train/loss': 0.02200780063867569, 'train/grad_norm_pre_clip': 1.5540339946746826, 'timing/data': 0.00024067983031272888, 'timing/model': 0.4587539453059435, 'learning_rate/action_model': 9.983749438769247e-05, 'learning_rate/action_query_proj': 9.983749438769247e-05, 'learning_rate/base': 2.4959373596923118e-05, 'epoch': 0.5}) +[2026-07-27 08:50:00,817][starVLA.training.train_starvla][INFO] - Step 4132, Loss: {'train/loss': 0.0864027589559555, 'train/grad_norm_pre_clip': 3.2335264682769775, 'timing/data': 0.00019990094006061554, 'timing/model': 0.4565220009535551, 'learning_rate/action_model': 9.983500534426635e-05, 'learning_rate/action_query_proj': 9.983500534426635e-05, 'learning_rate/base': 2.4958751336066588e-05, 'epoch': 0.5}) +[2026-07-27 08:50:06,372][starVLA.training.train_starvla][INFO] - Step 4133, Loss: {'train/loss': 0.08262026309967041, 'train/grad_norm_pre_clip': 3.539311647415161, 'timing/data': 0.00019829347729682922, 'timing/model': 0.457206841558218, 'learning_rate/action_model': 9.983249741633765e-05, 'learning_rate/action_query_proj': 9.983249741633765e-05, 'learning_rate/base': 2.4958124354084414e-05, 'epoch': 0.5}) +[2026-07-27 08:50:11,998][starVLA.training.train_starvla][INFO] - Step 4134, Loss: {'train/loss': 0.09809757024049759, 'train/grad_norm_pre_clip': 3.1561152935028076, 'timing/data': 0.00020080804824829102, 'timing/model': 0.4656758438795805, 'learning_rate/action_model': 9.98299706048965e-05, 'learning_rate/action_query_proj': 9.98299706048965e-05, 'learning_rate/base': 2.4957492651224125e-05, 'epoch': 0.5}) +[2026-07-27 08:50:17,618][starVLA.training.train_starvla][INFO] - Step 4135, Loss: {'train/loss': 0.09650814533233643, 'train/grad_norm_pre_clip': 3.5684521198272705, 'timing/data': 0.00019675679504871368, 'timing/model': 0.46266660653054714, 'learning_rate/action_model': 9.982742491094044e-05, 'learning_rate/action_query_proj': 9.982742491094044e-05, 'learning_rate/base': 2.495685622773511e-05, 'epoch': 0.5}) +[2026-07-27 08:50:23,500][starVLA.training.train_starvla][INFO] - Step 4136, Loss: {'train/loss': 0.17955131828784943, 'train/grad_norm_pre_clip': 4.084467887878418, 'timing/data': 0.00019186735153198242, 'timing/model': 0.461616113781929, 'learning_rate/action_model': 9.982486033547446e-05, 'learning_rate/action_query_proj': 9.982486033547446e-05, 'learning_rate/base': 2.4956215083868616e-05, 'epoch': 0.5}) +[2026-07-27 08:50:29,418][starVLA.training.train_starvla][INFO] - Step 4137, Loss: {'train/loss': 0.18890708684921265, 'train/grad_norm_pre_clip': 4.285245895385742, 'timing/data': 0.00018669478595256805, 'timing/model': 0.46767106279730797, 'learning_rate/action_model': 9.982227687951103e-05, 'learning_rate/action_query_proj': 9.982227687951103e-05, 'learning_rate/base': 2.4955569219877756e-05, 'epoch': 0.5}) +[2026-07-27 08:50:35,025][starVLA.training.train_starvla][INFO] - Step 4138, Loss: {'train/loss': 0.15841928124427795, 'train/grad_norm_pre_clip': 3.4061686992645264, 'timing/data': 0.00019341707229614258, 'timing/model': 0.4587764013558626, 'learning_rate/action_model': 9.981967454407004e-05, 'learning_rate/action_query_proj': 9.981967454407004e-05, 'learning_rate/base': 2.495491863601751e-05, 'epoch': 0.5}) +[2026-07-27 08:50:40,594][starVLA.training.train_starvla][INFO] - Step 4139, Loss: {'train/loss': 0.05951612442731857, 'train/grad_norm_pre_clip': 3.1523215770721436, 'timing/data': 0.0001956634223461151, 'timing/model': 0.45916247367858887, 'learning_rate/action_model': 9.981705333017884e-05, 'learning_rate/action_query_proj': 9.981705333017884e-05, 'learning_rate/base': 2.495426333254471e-05, 'epoch': 0.5}) +[2026-07-27 08:50:46,197][starVLA.training.train_starvla][INFO] - Step 4140, Loss: {'train/loss': 0.05796219781041145, 'train/grad_norm_pre_clip': 2.149183750152588, 'timing/data': 0.0001929663121700287, 'timing/model': 0.4574268013238907, 'learning_rate/action_model': 9.981441323887228e-05, 'learning_rate/action_query_proj': 9.981441323887228e-05, 'learning_rate/base': 2.495360330971807e-05, 'epoch': 0.5}) +[2026-07-27 08:50:51,773][starVLA.training.train_starvla][INFO] - Step 4141, Loss: {'train/loss': 0.0573432482779026, 'train/grad_norm_pre_clip': 2.6169159412384033, 'timing/data': 0.00019667670130729675, 'timing/model': 0.4573689792305231, 'learning_rate/action_model': 9.981175427119261e-05, 'learning_rate/action_query_proj': 9.981175427119261e-05, 'learning_rate/base': 2.4952938567798152e-05, 'epoch': 0.5}) +[2026-07-27 08:50:57,358][starVLA.training.train_starvla][INFO] - Step 4142, Loss: {'train/loss': 0.09661586582660675, 'train/grad_norm_pre_clip': 3.3128819465637207, 'timing/data': 0.00019524618983268738, 'timing/model': 0.4572542253881693, 'learning_rate/action_model': 9.980907642818953e-05, 'learning_rate/action_query_proj': 9.980907642818953e-05, 'learning_rate/base': 2.4952269107047384e-05, 'epoch': 0.5}) +[2026-07-27 08:51:02,933][starVLA.training.train_starvla][INFO] - Step 4143, Loss: {'train/loss': 0.09461904317140579, 'train/grad_norm_pre_clip': 2.6866958141326904, 'timing/data': 0.00019448436796665192, 'timing/model': 0.46479702182114124, 'learning_rate/action_model': 9.980637971092024e-05, 'learning_rate/action_query_proj': 9.980637971092024e-05, 'learning_rate/base': 2.495159492773006e-05, 'epoch': 0.5}) +[2026-07-27 08:51:08,530][starVLA.training.train_starvla][INFO] - Step 4144, Loss: {'train/loss': 0.12581920623779297, 'train/grad_norm_pre_clip': 4.101545810699463, 'timing/data': 0.0001917872577905655, 'timing/model': 0.46334181167185307, 'learning_rate/action_model': 9.980366412044934e-05, 'learning_rate/action_query_proj': 9.980366412044934e-05, 'learning_rate/base': 2.4950916030112335e-05, 'epoch': 0.5}) +[2026-07-27 08:51:14,120][starVLA.training.train_starvla][INFO] - Step 4145, Loss: {'train/loss': 0.1332865059375763, 'train/grad_norm_pre_clip': 3.6044795513153076, 'timing/data': 0.00019378773868083954, 'timing/model': 0.4648532960563898, 'learning_rate/action_model': 9.980092965784891e-05, 'learning_rate/action_query_proj': 9.980092965784891e-05, 'learning_rate/base': 2.4950232414462228e-05, 'epoch': 0.5}) +[2026-07-27 08:51:19,690][starVLA.training.train_starvla][INFO] - Step 4146, Loss: {'train/loss': 0.07824462652206421, 'train/grad_norm_pre_clip': 3.0873401165008545, 'timing/data': 0.00019162148237228394, 'timing/model': 0.45711788535118103, 'learning_rate/action_model': 9.979817632419848e-05, 'learning_rate/action_query_proj': 9.979817632419848e-05, 'learning_rate/base': 2.494954408104962e-05, 'epoch': 0.5}) +[2026-07-27 08:51:25,290][starVLA.training.train_starvla][INFO] - Step 4147, Loss: {'train/loss': 0.08731895685195923, 'train/grad_norm_pre_clip': 3.4792990684509277, 'timing/data': 0.00019563734531402588, 'timing/model': 0.458328552544117, 'learning_rate/action_model': 9.979540412058501e-05, 'learning_rate/action_query_proj': 9.979540412058501e-05, 'learning_rate/base': 2.4948851030146252e-05, 'epoch': 0.5}) +[2026-07-27 08:51:30,880][starVLA.training.train_starvla][INFO] - Step 4148, Loss: {'train/loss': 0.1227283626794815, 'train/grad_norm_pre_clip': 3.867335081100464, 'timing/data': 0.00019471347332000732, 'timing/model': 0.4639619179069996, 'learning_rate/action_model': 9.979261304810292e-05, 'learning_rate/action_query_proj': 9.979261304810292e-05, 'learning_rate/base': 2.494815326202573e-05, 'epoch': 0.5}) +[2026-07-27 08:51:36,443][starVLA.training.train_starvla][INFO] - Step 4149, Loss: {'train/loss': 0.08152550458908081, 'train/grad_norm_pre_clip': 3.054751396179199, 'timing/data': 0.00020637735724449158, 'timing/model': 0.4573862161487341, 'learning_rate/action_model': 9.978980310785408e-05, 'learning_rate/action_query_proj': 9.978980310785408e-05, 'learning_rate/base': 2.494745077696352e-05, 'epoch': 0.5}) +[2026-07-27 08:51:42,013][starVLA.training.train_starvla][INFO] - Step 4150, Loss: {'train/loss': 0.04756399244070053, 'train/grad_norm_pre_clip': 1.8843655586242676, 'timing/data': 0.00025763921439647675, 'timing/model': 0.45971333235502243, 'learning_rate/action_model': 9.978697430094785e-05, 'learning_rate/action_query_proj': 9.978697430094785e-05, 'learning_rate/base': 2.494674357523696e-05, 'epoch': 0.5}) +[2026-07-27 08:51:47,582][starVLA.training.train_starvla][INFO] - Step 4151, Loss: {'train/loss': 0.061204880475997925, 'train/grad_norm_pre_clip': 2.852058172225952, 'timing/data': 0.00020060129463672638, 'timing/model': 0.4581849332898855, 'learning_rate/action_model': 9.978412662850094e-05, 'learning_rate/action_query_proj': 9.978412662850094e-05, 'learning_rate/base': 2.4946031657125236e-05, 'epoch': 0.5}) +[2026-07-27 08:51:53,744][starVLA.training.train_starvla][INFO] - Step 4152, Loss: {'train/loss': 0.06572273373603821, 'train/grad_norm_pre_clip': 3.146394729614258, 'timing/data': 0.0002908147871494293, 'timing/model': 0.46232463978230953, 'learning_rate/action_model': 9.97812600916376e-05, 'learning_rate/action_query_proj': 9.97812600916376e-05, 'learning_rate/base': 2.49453150229094e-05, 'epoch': 0.5}) +[2026-07-27 08:51:59,322][starVLA.training.train_starvla][INFO] - Step 4153, Loss: {'train/loss': 0.14265292882919312, 'train/grad_norm_pre_clip': 4.570193290710449, 'timing/data': 0.00020263716578483582, 'timing/model': 0.4620929379016161, 'learning_rate/action_model': 9.977837469148947e-05, 'learning_rate/action_query_proj': 9.977837469148947e-05, 'learning_rate/base': 2.4944593672872368e-05, 'epoch': 0.5}) +[2026-07-27 08:52:04,879][starVLA.training.train_starvla][INFO] - Step 4154, Loss: {'train/loss': 0.07600972801446915, 'train/grad_norm_pre_clip': 3.317814350128174, 'timing/data': 0.00018956325948238373, 'timing/model': 0.46367933228611946, 'learning_rate/action_model': 9.977547042919569e-05, 'learning_rate/action_query_proj': 9.977547042919569e-05, 'learning_rate/base': 2.4943867607298923e-05, 'epoch': 0.5}) +[2026-07-27 08:52:10,430][starVLA.training.train_starvla][INFO] - Step 4155, Loss: {'train/loss': 0.07244067639112473, 'train/grad_norm_pre_clip': 3.3529043197631836, 'timing/data': 0.00020996294915676117, 'timing/model': 0.45953669399023056, 'learning_rate/action_model': 9.977254730590281e-05, 'learning_rate/action_query_proj': 9.977254730590281e-05, 'learning_rate/base': 2.4943136826475702e-05, 'epoch': 0.5}) +[2026-07-27 08:52:15,974][starVLA.training.train_starvla][INFO] - Step 4156, Loss: {'train/loss': 0.13792331516742706, 'train/grad_norm_pre_clip': 4.524689197540283, 'timing/data': 0.00018633529543876648, 'timing/model': 0.4624232277274132, 'learning_rate/action_model': 9.97696053227648e-05, 'learning_rate/action_query_proj': 9.97696053227648e-05, 'learning_rate/base': 2.49424013306912e-05, 'epoch': 0.5}) +[2026-07-27 08:52:21,531][starVLA.training.train_starvla][INFO] - Step 4157, Loss: {'train/loss': 0.057766854763031006, 'train/grad_norm_pre_clip': 3.2032058238983154, 'timing/data': 0.0001929793506860733, 'timing/model': 0.4640852455049753, 'learning_rate/action_model': 9.976664448094316e-05, 'learning_rate/action_query_proj': 9.976664448094316e-05, 'learning_rate/base': 2.494166112023579e-05, 'epoch': 0.5}) +[2026-07-27 08:52:27,086][starVLA.training.train_starvla][INFO] - Step 4158, Loss: {'train/loss': 0.15314048528671265, 'train/grad_norm_pre_clip': 3.3466885089874268, 'timing/data': 0.00019062310457229614, 'timing/model': 0.4578507263213396, 'learning_rate/action_model': 9.976366478160673e-05, 'learning_rate/action_query_proj': 9.976366478160673e-05, 'learning_rate/base': 2.4940916195401682e-05, 'epoch': 0.5}) +[2026-07-27 08:52:32,640][starVLA.training.train_starvla][INFO] - Step 4159, Loss: {'train/loss': 0.1355920433998108, 'train/grad_norm_pre_clip': 3.9885547161102295, 'timing/data': 0.00020211376249790192, 'timing/model': 0.45800232887268066, 'learning_rate/action_model': 9.97606662259319e-05, 'learning_rate/action_query_proj': 9.97606662259319e-05, 'learning_rate/base': 2.4940166556482976e-05, 'epoch': 0.5}) +[2026-07-27 08:52:38,198][starVLA.training.train_starvla][INFO] - Step 4160, Loss: {'train/loss': 0.24310950934886932, 'train/grad_norm_pre_clip': 6.804640769958496, 'timing/data': 0.000195307657122612, 'timing/model': 0.4562827404588461, 'learning_rate/action_model': 9.975764881510242e-05, 'learning_rate/action_query_proj': 9.975764881510242e-05, 'learning_rate/base': 2.4939412203775605e-05, 'epoch': 0.5}) +[2026-07-27 08:52:43,764][starVLA.training.train_starvla][INFO] - Step 4161, Loss: {'train/loss': 0.0620732381939888, 'train/grad_norm_pre_clip': 3.7799487113952637, 'timing/data': 0.00020096078515052795, 'timing/model': 0.4581857994198799, 'learning_rate/action_model': 9.975461255030951e-05, 'learning_rate/action_query_proj': 9.975461255030951e-05, 'learning_rate/base': 2.493865313757738e-05, 'epoch': 0.5}) +[2026-07-27 08:52:49,321][starVLA.training.train_starvla][INFO] - Step 4162, Loss: {'train/loss': 0.15960896015167236, 'train/grad_norm_pre_clip': 6.043692588806152, 'timing/data': 0.00019151903688907623, 'timing/model': 0.4588767606765032, 'learning_rate/action_model': 9.975155743275187e-05, 'learning_rate/action_query_proj': 9.975155743275187e-05, 'learning_rate/base': 2.4937889358187967e-05, 'epoch': 0.5}) +[2026-07-27 08:52:54,879][starVLA.training.train_starvla][INFO] - Step 4163, Loss: {'train/loss': 0.11568310856819153, 'train/grad_norm_pre_clip': 3.2983806133270264, 'timing/data': 0.00019409507513046265, 'timing/model': 0.4571950417011976, 'learning_rate/action_model': 9.974848346363557e-05, 'learning_rate/action_query_proj': 9.974848346363557e-05, 'learning_rate/base': 2.4937120865908894e-05, 'epoch': 0.51}) +[2026-07-27 08:53:00,437][starVLA.training.train_starvla][INFO] - Step 4164, Loss: {'train/loss': 0.10877462476491928, 'train/grad_norm_pre_clip': 3.985091209411621, 'timing/data': 0.00018363632261753082, 'timing/model': 0.4581930674612522, 'learning_rate/action_model': 9.974539064417421e-05, 'learning_rate/action_query_proj': 9.974539064417421e-05, 'learning_rate/base': 2.4936347661043552e-05, 'epoch': 0.51}) +[2026-07-27 08:53:06,001][starVLA.training.train_starvla][INFO] - Step 4165, Loss: {'train/loss': 0.06353744119405746, 'train/grad_norm_pre_clip': 2.6184568405151367, 'timing/data': 0.00026206113398075104, 'timing/model': 0.4568621553480625, 'learning_rate/action_model': 9.974227897558876e-05, 'learning_rate/action_query_proj': 9.974227897558876e-05, 'learning_rate/base': 2.493556974389719e-05, 'epoch': 0.51}) +[2026-07-27 08:53:11,567][starVLA.training.train_starvla][INFO] - Step 4166, Loss: {'train/loss': 0.10470166057348251, 'train/grad_norm_pre_clip': 2.472367763519287, 'timing/data': 0.0002555232495069504, 'timing/model': 0.45942242443561554, 'learning_rate/action_model': 9.973914845910765e-05, 'learning_rate/action_query_proj': 9.973914845910765e-05, 'learning_rate/base': 2.4934787114776913e-05, 'epoch': 0.51}) +[2026-07-27 08:53:17,111][starVLA.training.train_starvla][INFO] - Step 4167, Loss: {'train/loss': 0.12489397078752518, 'train/grad_norm_pre_clip': 4.418792724609375, 'timing/data': 0.00019773095846176147, 'timing/model': 0.45763904973864555, 'learning_rate/action_model': 9.973599909596679e-05, 'learning_rate/action_query_proj': 9.973599909596679e-05, 'learning_rate/base': 2.4933999773991696e-05, 'epoch': 0.51}) +[2026-07-27 08:53:22,664][starVLA.training.train_starvla][INFO] - Step 4168, Loss: {'train/loss': 0.16725045442581177, 'train/grad_norm_pre_clip': 4.887538909912109, 'timing/data': 0.0001950729638338089, 'timing/model': 0.45792009867727757, 'learning_rate/action_model': 9.973283088740948e-05, 'learning_rate/action_query_proj': 9.973283088740948e-05, 'learning_rate/base': 2.493320772185237e-05, 'epoch': 0.51}) +[2026-07-27 08:53:28,225][starVLA.training.train_starvla][INFO] - Step 4169, Loss: {'train/loss': 0.14695850014686584, 'train/grad_norm_pre_clip': 5.2016119956970215, 'timing/data': 0.00019630976021289825, 'timing/model': 0.4571305550634861, 'learning_rate/action_model': 9.972964383468646e-05, 'learning_rate/action_query_proj': 9.972964383468646e-05, 'learning_rate/base': 2.4932410958671615e-05, 'epoch': 0.51}) +[2026-07-27 08:53:33,791][starVLA.training.train_starvla][INFO] - Step 4170, Loss: {'train/loss': 0.09925168007612228, 'train/grad_norm_pre_clip': 4.6055216789245605, 'timing/data': 0.00019006244838237762, 'timing/model': 0.4591939225792885, 'learning_rate/action_model': 9.972643793905595e-05, 'learning_rate/action_query_proj': 9.972643793905595e-05, 'learning_rate/base': 2.4931609484763988e-05, 'epoch': 0.51}) +[2026-07-27 08:53:39,345][starVLA.training.train_starvla][INFO] - Step 4171, Loss: {'train/loss': 0.07147196680307388, 'train/grad_norm_pre_clip': 2.5983827114105225, 'timing/data': 0.00019593164324760437, 'timing/model': 0.45682269893586636, 'learning_rate/action_model': 9.972321320178359e-05, 'learning_rate/action_query_proj': 9.972321320178359e-05, 'learning_rate/base': 2.4930803300445897e-05, 'epoch': 0.51}) +[2026-07-27 08:53:44,897][starVLA.training.train_starvla][INFO] - Step 4172, Loss: {'train/loss': 0.11493757367134094, 'train/grad_norm_pre_clip': 3.6238772869110107, 'timing/data': 0.00019908882677555084, 'timing/model': 0.45719859190285206, 'learning_rate/action_model': 9.971996962414244e-05, 'learning_rate/action_query_proj': 9.971996962414244e-05, 'learning_rate/base': 2.492999240603561e-05, 'epoch': 0.51}) +[2026-07-27 08:53:50,443][starVLA.training.train_starvla][INFO] - Step 4173, Loss: {'train/loss': 0.03752649948000908, 'train/grad_norm_pre_clip': 2.076857089996338, 'timing/data': 0.00019111298024654388, 'timing/model': 0.45749785378575325, 'learning_rate/action_model': 9.971670720741304e-05, 'learning_rate/action_query_proj': 9.971670720741304e-05, 'learning_rate/base': 2.492917680185326e-05, 'epoch': 0.51}) +[2026-07-27 08:53:55,972][starVLA.training.train_starvla][INFO] - Step 4174, Loss: {'train/loss': 0.0905725285410881, 'train/grad_norm_pre_clip': 3.1744771003723145, 'timing/data': 0.00019697844982147217, 'timing/model': 0.4567801021039486, 'learning_rate/action_model': 9.97134259528833e-05, 'learning_rate/action_query_proj': 9.97134259528833e-05, 'learning_rate/base': 2.4928356488220825e-05, 'epoch': 0.51}) +[2026-07-27 08:54:01,539][starVLA.training.train_starvla][INFO] - Step 4175, Loss: {'train/loss': 0.035200562328100204, 'train/grad_norm_pre_clip': 2.1497466564178467, 'timing/data': 0.00018779002130031586, 'timing/model': 0.4574200510978699, 'learning_rate/action_model': 9.971012586184863e-05, 'learning_rate/action_query_proj': 9.971012586184863e-05, 'learning_rate/base': 2.4927531465462158e-05, 'epoch': 0.51}) +[2026-07-27 08:54:07,088][starVLA.training.train_starvla][INFO] - Step 4176, Loss: {'train/loss': 0.07991816103458405, 'train/grad_norm_pre_clip': 3.2093966007232666, 'timing/data': 0.0001950003206729889, 'timing/model': 0.45733992755413055, 'learning_rate/action_model': 9.970680693561186e-05, 'learning_rate/action_query_proj': 9.970680693561186e-05, 'learning_rate/base': 2.4926701733902965e-05, 'epoch': 0.51}) +[2026-07-27 08:54:12,612][starVLA.training.train_starvla][INFO] - Step 4177, Loss: {'train/loss': 0.08538991212844849, 'train/grad_norm_pre_clip': 3.284248113632202, 'timing/data': 0.0001931414008140564, 'timing/model': 0.4570004567503929, 'learning_rate/action_model': 9.970346917548323e-05, 'learning_rate/action_query_proj': 9.970346917548323e-05, 'learning_rate/base': 2.4925867293870808e-05, 'epoch': 0.51}) +[2026-07-27 08:54:18,144][starVLA.training.train_starvla][INFO] - Step 4178, Loss: {'train/loss': 0.06258143484592438, 'train/grad_norm_pre_clip': 2.902259349822998, 'timing/data': 0.00019689276814460754, 'timing/model': 0.45707852952182293, 'learning_rate/action_model': 9.970011258278047e-05, 'learning_rate/action_query_proj': 9.970011258278047e-05, 'learning_rate/base': 2.4925028145695118e-05, 'epoch': 0.51}) +[2026-07-27 08:54:23,725][starVLA.training.train_starvla][INFO] - Step 4179, Loss: {'train/loss': 0.16099844872951508, 'train/grad_norm_pre_clip': 5.535416603088379, 'timing/data': 0.0001889113336801529, 'timing/model': 0.4574114326387644, 'learning_rate/action_model': 9.969673715882866e-05, 'learning_rate/action_query_proj': 9.969673715882866e-05, 'learning_rate/base': 2.4924184289707166e-05, 'epoch': 0.51}) +[2026-07-27 08:54:29,290][starVLA.training.train_starvla][INFO] - Step 4180, Loss: {'train/loss': 0.04490780830383301, 'train/grad_norm_pre_clip': 2.212256669998169, 'timing/data': 0.00024419836699962616, 'timing/model': 0.4595764335244894, 'learning_rate/action_model': 9.96933429049604e-05, 'learning_rate/action_query_proj': 9.96933429049604e-05, 'learning_rate/base': 2.49233357262401e-05, 'epoch': 0.51}) +[2026-07-27 08:54:34,895][starVLA.training.train_starvla][INFO] - Step 4181, Loss: {'train/loss': 0.05507733300328255, 'train/grad_norm_pre_clip': 3.047004461288452, 'timing/data': 0.0002480745315551758, 'timing/model': 0.4618482943624258, 'learning_rate/action_model': 9.968992982251568e-05, 'learning_rate/action_query_proj': 9.968992982251568e-05, 'learning_rate/base': 2.492248245562892e-05, 'epoch': 0.51}) +[2026-07-27 08:54:40,499][starVLA.training.train_starvla][INFO] - Step 4182, Loss: {'train/loss': 0.03129512816667557, 'train/grad_norm_pre_clip': 1.99216890335083, 'timing/data': 0.00025021471083164215, 'timing/model': 0.4596339836716652, 'learning_rate/action_model': 9.968649791284193e-05, 'learning_rate/action_query_proj': 9.968649791284193e-05, 'learning_rate/base': 2.4921624478210483e-05, 'epoch': 0.51}) +[2026-07-27 08:54:46,104][starVLA.training.train_starvla][INFO] - Step 4183, Loss: {'train/loss': 0.14041036367416382, 'train/grad_norm_pre_clip': 4.527996063232422, 'timing/data': 0.00025151483714580536, 'timing/model': 0.46122258342802525, 'learning_rate/action_model': 9.968304717729401e-05, 'learning_rate/action_query_proj': 9.968304717729401e-05, 'learning_rate/base': 2.4920761794323503e-05, 'epoch': 0.51}) +[2026-07-27 08:54:51,702][starVLA.training.train_starvla][INFO] - Step 4184, Loss: {'train/loss': 0.07541581243276596, 'train/grad_norm_pre_clip': 3.015887498855591, 'timing/data': 0.00025232695043087006, 'timing/model': 0.45997887291014194, 'learning_rate/action_model': 9.967957761723423e-05, 'learning_rate/action_query_proj': 9.967957761723423e-05, 'learning_rate/base': 2.4919894404308557e-05, 'epoch': 0.51}) +[2026-07-27 08:54:57,316][starVLA.training.train_starvla][INFO] - Step 4185, Loss: {'train/loss': 0.05252101272344589, 'train/grad_norm_pre_clip': 2.637789726257324, 'timing/data': 0.00024330243468284607, 'timing/model': 0.4628708716481924, 'learning_rate/action_model': 9.96760892340323e-05, 'learning_rate/action_query_proj': 9.96760892340323e-05, 'learning_rate/base': 2.4919022308508075e-05, 'epoch': 0.51}) +[2026-07-27 08:55:02,897][starVLA.training.train_starvla][INFO] - Step 4186, Loss: {'train/loss': 0.06917312741279602, 'train/grad_norm_pre_clip': 3.5487804412841797, 'timing/data': 0.00019249692559242249, 'timing/model': 0.4626646898686886, 'learning_rate/action_model': 9.967258202906537e-05, 'learning_rate/action_query_proj': 9.967258202906537e-05, 'learning_rate/base': 2.4918145507266342e-05, 'epoch': 0.51}) +[2026-07-27 08:55:08,462][starVLA.training.train_starvla][INFO] - Step 4187, Loss: {'train/loss': 0.055541373789310455, 'train/grad_norm_pre_clip': 3.2522921562194824, 'timing/data': 0.0001867692917585373, 'timing/model': 0.4623826704919338, 'learning_rate/action_model': 9.966905600371806e-05, 'learning_rate/action_query_proj': 9.966905600371806e-05, 'learning_rate/base': 2.4917264000929515e-05, 'epoch': 0.51}) +[2026-07-27 08:55:14,031][starVLA.training.train_starvla][INFO] - Step 4188, Loss: {'train/loss': 0.1223955750465393, 'train/grad_norm_pre_clip': 4.182240009307861, 'timing/data': 0.0002494044601917267, 'timing/model': 0.46079932525753975, 'learning_rate/action_model': 9.966551115938236e-05, 'learning_rate/action_query_proj': 9.966551115938236e-05, 'learning_rate/base': 2.491637778984559e-05, 'epoch': 0.51}) +[2026-07-27 08:55:19,566][starVLA.training.train_starvla][INFO] - Step 4189, Loss: {'train/loss': 0.05280427262187004, 'train/grad_norm_pre_clip': 1.4648351669311523, 'timing/data': 0.00025561824440956116, 'timing/model': 0.45728697814047337, 'learning_rate/action_model': 9.966194749745774e-05, 'learning_rate/action_query_proj': 9.966194749745774e-05, 'learning_rate/base': 2.4915486874364434e-05, 'epoch': 0.51}) +[2026-07-27 08:55:25,083][starVLA.training.train_starvla][INFO] - Step 4190, Loss: {'train/loss': 0.11517421901226044, 'train/grad_norm_pre_clip': 4.780909538269043, 'timing/data': 0.00025750696659088135, 'timing/model': 0.4567626751959324, 'learning_rate/action_model': 9.965836501935105e-05, 'learning_rate/action_query_proj': 9.965836501935105e-05, 'learning_rate/base': 2.4914591254837762e-05, 'epoch': 0.51}) +[2026-07-27 08:55:30,634][starVLA.training.train_starvla][INFO] - Step 4191, Loss: {'train/loss': 0.028312738984823227, 'train/grad_norm_pre_clip': 2.191941738128662, 'timing/data': 0.00019855797290802002, 'timing/model': 0.47312424890697, 'learning_rate/action_model': 9.965476372647662e-05, 'learning_rate/action_query_proj': 9.965476372647662e-05, 'learning_rate/base': 2.4913690931619156e-05, 'epoch': 0.51}) +[2026-07-27 08:55:36,168][starVLA.training.train_starvla][INFO] - Step 4192, Loss: {'train/loss': 0.1765313595533371, 'train/grad_norm_pre_clip': 3.884286880493164, 'timing/data': 0.00018789991736412048, 'timing/model': 0.478362612426281, 'learning_rate/action_model': 9.96511436202562e-05, 'learning_rate/action_query_proj': 9.96511436202562e-05, 'learning_rate/base': 2.491278590506405e-05, 'epoch': 0.51}) +[2026-07-27 08:55:41,703][starVLA.training.train_starvla][INFO] - Step 4193, Loss: {'train/loss': 0.08087629079818726, 'train/grad_norm_pre_clip': 3.1414794921875, 'timing/data': 0.00019386596977710724, 'timing/model': 0.47943312488496304, 'learning_rate/action_model': 9.964750470211891e-05, 'learning_rate/action_query_proj': 9.964750470211891e-05, 'learning_rate/base': 2.491187617552973e-05, 'epoch': 0.51}) +[2026-07-27 08:55:47,265][starVLA.training.train_starvla][INFO] - Step 4194, Loss: {'train/loss': 0.09696308523416519, 'train/grad_norm_pre_clip': 3.3736343383789062, 'timing/data': 0.00019308365881443024, 'timing/model': 0.4722594637423754, 'learning_rate/action_model': 9.964384697350134e-05, 'learning_rate/action_query_proj': 9.964384697350134e-05, 'learning_rate/base': 2.4910961743375335e-05, 'epoch': 0.51}) +[2026-07-27 08:55:52,836][starVLA.training.train_starvla][INFO] - Step 4195, Loss: {'train/loss': 0.1834937334060669, 'train/grad_norm_pre_clip': 5.375425815582275, 'timing/data': 0.00018849223852157593, 'timing/model': 0.48085871525108814, 'learning_rate/action_model': 9.964017043584755e-05, 'learning_rate/action_query_proj': 9.964017043584755e-05, 'learning_rate/base': 2.4910042608961888e-05, 'epoch': 0.51}) +[2026-07-27 08:55:58,423][starVLA.training.train_starvla][INFO] - Step 4196, Loss: {'train/loss': 0.21223047375679016, 'train/grad_norm_pre_clip': 5.415898323059082, 'timing/data': 0.00019434653222560883, 'timing/model': 0.47213274613022804, 'learning_rate/action_model': 9.963647509060892e-05, 'learning_rate/action_query_proj': 9.963647509060892e-05, 'learning_rate/base': 2.490911877265223e-05, 'epoch': 0.51}) +[2026-07-27 08:56:04,011][starVLA.training.train_starvla][INFO] - Step 4197, Loss: {'train/loss': 0.06150035187602043, 'train/grad_norm_pre_clip': 3.325024127960205, 'timing/data': 0.0001860838383436203, 'timing/model': 0.4714461360126734, 'learning_rate/action_model': 9.963276093924435e-05, 'learning_rate/action_query_proj': 9.963276093924435e-05, 'learning_rate/base': 2.4908190234811088e-05, 'epoch': 0.51}) +[2026-07-27 08:56:09,610][starVLA.training.train_starvla][INFO] - Step 4198, Loss: {'train/loss': 0.042513903230428696, 'train/grad_norm_pre_clip': 2.9529471397399902, 'timing/data': 0.0001879669725894928, 'timing/model': 0.4785085879266262, 'learning_rate/action_model': 9.962902798322013e-05, 'learning_rate/action_query_proj': 9.962902798322013e-05, 'learning_rate/base': 2.4907256995805032e-05, 'epoch': 0.51}) +[2026-07-27 08:56:15,192][starVLA.training.train_starvla][INFO] - Step 4199, Loss: {'train/loss': 0.14313596487045288, 'train/grad_norm_pre_clip': 3.8601715564727783, 'timing/data': 0.00017990916967391968, 'timing/model': 0.47243776731193066, 'learning_rate/action_model': 9.962527622400994e-05, 'learning_rate/action_query_proj': 9.962527622400994e-05, 'learning_rate/base': 2.4906319056002486e-05, 'epoch': 0.51}) +[2026-07-27 08:56:20,767][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 4200 +[2026-07-27 08:56:20,768][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 4200 +[2026-07-27 08:56:20,769][starVLA.training.train_starvla][INFO] - Step 4200, Loss: {'train/loss': 0.07946328818798065, 'train/grad_norm_pre_clip': 3.7135097980499268, 'timing/data': 0.00018708780407905579, 'timing/model': 0.47071368247270584, 'learning_rate/action_model': 9.962150566309495e-05, 'learning_rate/action_query_proj': 9.962150566309495e-05, 'learning_rate/base': 2.4905376415773737e-05, 'epoch': 0.51}) +[2026-07-27 08:56:26,364][starVLA.training.train_starvla][INFO] - Step 4201, Loss: {'train/loss': 0.06787411868572235, 'train/grad_norm_pre_clip': 3.325612783432007, 'timing/data': 0.0001842901110649109, 'timing/model': 0.4720273781567812, 'learning_rate/action_model': 9.961771630196369e-05, 'learning_rate/action_query_proj': 9.961771630196369e-05, 'learning_rate/base': 2.490442907549092e-05, 'epoch': 0.51}) +[2026-07-27 08:56:31,934][starVLA.training.train_starvla][INFO] - Step 4202, Loss: {'train/loss': 0.1236647367477417, 'train/grad_norm_pre_clip': 4.433033466339111, 'timing/data': 0.00018472783267498016, 'timing/model': 0.47270107455551624, 'learning_rate/action_model': 9.961390814211215e-05, 'learning_rate/action_query_proj': 9.961390814211215e-05, 'learning_rate/base': 2.4903477035528038e-05, 'epoch': 0.51}) +[2026-07-27 08:56:37,505][starVLA.training.train_starvla][INFO] - Step 4203, Loss: {'train/loss': 0.10633626580238342, 'train/grad_norm_pre_clip': 4.5799241065979, 'timing/data': 0.00018579140305519104, 'timing/model': 0.4771115146577358, 'learning_rate/action_model': 9.961008118504374e-05, 'learning_rate/action_query_proj': 9.961008118504374e-05, 'learning_rate/base': 2.4902520296260936e-05, 'epoch': 0.51}) +[2026-07-27 08:56:43,101][starVLA.training.train_starvla][INFO] - Step 4204, Loss: {'train/loss': 0.11643166840076447, 'train/grad_norm_pre_clip': 3.5709388256073, 'timing/data': 0.00023986771702766418, 'timing/model': 0.47852425649762154, 'learning_rate/action_model': 9.96062354322693e-05, 'learning_rate/action_query_proj': 9.96062354322693e-05, 'learning_rate/base': 2.4901558858067324e-05, 'epoch': 0.51}) +[2026-07-27 08:56:48,718][starVLA.training.train_starvla][INFO] - Step 4205, Loss: {'train/loss': 0.06561996042728424, 'train/grad_norm_pre_clip': 2.6363914012908936, 'timing/data': 0.00023996643722057343, 'timing/model': 0.4699580017477274, 'learning_rate/action_model': 9.960237088530703e-05, 'learning_rate/action_query_proj': 9.960237088530703e-05, 'learning_rate/base': 2.4900592721326758e-05, 'epoch': 0.51}) +[2026-07-27 08:56:54,728][starVLA.training.train_starvla][INFO] - Step 4206, Loss: {'train/loss': 0.152114138007164, 'train/grad_norm_pre_clip': 5.6067304611206055, 'timing/data': 0.0002401750534772873, 'timing/model': 0.6393182892352343, 'learning_rate/action_model': 9.959848754568261e-05, 'learning_rate/action_query_proj': 9.959848754568261e-05, 'learning_rate/base': 2.4899621886420652e-05, 'epoch': 0.51}) +[2026-07-27 08:57:00,264][starVLA.training.train_starvla][INFO] - Step 4207, Loss: {'train/loss': 0.11661510169506073, 'train/grad_norm_pre_clip': 3.4048736095428467, 'timing/data': 0.00023576430976390839, 'timing/model': 0.4617568776011467, 'learning_rate/action_model': 9.959458541492912e-05, 'learning_rate/action_query_proj': 9.959458541492912e-05, 'learning_rate/base': 2.489864635373228e-05, 'epoch': 0.51}) +[2026-07-27 08:57:05,815][starVLA.training.train_starvla][INFO] - Step 4208, Loss: {'train/loss': 0.0670166164636612, 'train/grad_norm_pre_clip': 3.263700008392334, 'timing/data': 0.0002620406448841095, 'timing/model': 0.46053671464324, 'learning_rate/action_model': 9.959066449458705e-05, 'learning_rate/action_query_proj': 9.959066449458705e-05, 'learning_rate/base': 2.4897666123646764e-05, 'epoch': 0.51}) +[2026-07-27 08:57:11,365][starVLA.training.train_starvla][INFO] - Step 4209, Loss: {'train/loss': 0.09508584439754486, 'train/grad_norm_pre_clip': 4.095871448516846, 'timing/data': 0.0002070292830467224, 'timing/model': 0.4631215576082468, 'learning_rate/action_model': 9.958672478620435e-05, 'learning_rate/action_query_proj': 9.958672478620435e-05, 'learning_rate/base': 2.4896681196551088e-05, 'epoch': 0.51}) +[2026-07-27 08:57:16,903][starVLA.training.train_starvla][INFO] - Step 4210, Loss: {'train/loss': 0.045470986515283585, 'train/grad_norm_pre_clip': 2.252296209335327, 'timing/data': 0.00018960796296596527, 'timing/model': 0.461865046992898, 'learning_rate/action_model': 9.958276629133632e-05, 'learning_rate/action_query_proj': 9.958276629133632e-05, 'learning_rate/base': 2.489569157283408e-05, 'epoch': 0.51}) +[2026-07-27 08:57:22,467][starVLA.training.train_starvla][INFO] - Step 4211, Loss: {'train/loss': 0.03261386230587959, 'train/grad_norm_pre_clip': 2.4432213306427, 'timing/data': 0.00018346495926380157, 'timing/model': 0.46085509844124317, 'learning_rate/action_model': 9.957878901154573e-05, 'learning_rate/action_query_proj': 9.957878901154573e-05, 'learning_rate/base': 2.4894697252886432e-05, 'epoch': 0.51}) +[2026-07-27 08:57:28,019][starVLA.training.train_starvla][INFO] - Step 4212, Loss: {'train/loss': 0.032661374658346176, 'train/grad_norm_pre_clip': 1.5336248874664307, 'timing/data': 0.0002386178821325302, 'timing/model': 0.46072364784777164, 'learning_rate/action_model': 9.957479294840275e-05, 'learning_rate/action_query_proj': 9.957479294840275e-05, 'learning_rate/base': 2.4893698237100686e-05, 'epoch': 0.51}) +[2026-07-27 08:57:33,563][starVLA.training.train_starvla][INFO] - Step 4213, Loss: {'train/loss': 0.03442783281207085, 'train/grad_norm_pre_clip': 1.7207809686660767, 'timing/data': 0.00024852901697158813, 'timing/model': 0.46042004972696304, 'learning_rate/action_model': 9.957077810348493e-05, 'learning_rate/action_query_proj': 9.957077810348493e-05, 'learning_rate/base': 2.4892694525871234e-05, 'epoch': 0.51}) +[2026-07-27 08:57:39,122][starVLA.training.train_starvla][INFO] - Step 4214, Loss: {'train/loss': 0.11053691059350967, 'train/grad_norm_pre_clip': 4.71144437789917, 'timing/data': 0.00024297460913658142, 'timing/model': 0.46148666739463806, 'learning_rate/action_model': 9.95667444783773e-05, 'learning_rate/action_query_proj': 9.95667444783773e-05, 'learning_rate/base': 2.4891686119594326e-05, 'epoch': 0.51}) +[2026-07-27 08:57:44,663][starVLA.training.train_starvla][INFO] - Step 4215, Loss: {'train/loss': 0.046140074729919434, 'train/grad_norm_pre_clip': 2.81607985496521, 'timing/data': 0.00023057684302330017, 'timing/model': 0.4607192073017359, 'learning_rate/action_model': 9.956269207467226e-05, 'learning_rate/action_query_proj': 9.956269207467226e-05, 'learning_rate/base': 2.4890673018668066e-05, 'epoch': 0.51}) +[2026-07-27 08:57:50,211][starVLA.training.train_starvla][INFO] - Step 4216, Loss: {'train/loss': 0.16526290774345398, 'train/grad_norm_pre_clip': 4.554304122924805, 'timing/data': 0.00023937411606311798, 'timing/model': 0.45949498750269413, 'learning_rate/action_model': 9.955862089396965e-05, 'learning_rate/action_query_proj': 9.955862089396965e-05, 'learning_rate/base': 2.488965522349241e-05, 'epoch': 0.51}) +[2026-07-27 08:57:55,763][starVLA.training.train_starvla][INFO] - Step 4217, Loss: {'train/loss': 0.07772719115018845, 'train/grad_norm_pre_clip': 3.419079303741455, 'timing/data': 0.00018804892897605896, 'timing/model': 0.4602209124714136, 'learning_rate/action_model': 9.955453093787667e-05, 'learning_rate/action_query_proj': 9.955453093787667e-05, 'learning_rate/base': 2.488863273446917e-05, 'epoch': 0.51}) +[2026-07-27 08:58:01,345][starVLA.training.train_starvla][INFO] - Step 4218, Loss: {'train/loss': 0.03879997879266739, 'train/grad_norm_pre_clip': 2.1570682525634766, 'timing/data': 0.00018627196550369263, 'timing/model': 0.4619536120444536, 'learning_rate/action_model': 9.955042220800802e-05, 'learning_rate/action_query_proj': 9.955042220800802e-05, 'learning_rate/base': 2.4887605552002006e-05, 'epoch': 0.51}) +[2026-07-27 08:58:06,922][starVLA.training.train_starvla][INFO] - Step 4219, Loss: {'train/loss': 0.020742017775774002, 'train/grad_norm_pre_clip': 1.591240406036377, 'timing/data': 0.0001862216740846634, 'timing/model': 0.4639465529471636, 'learning_rate/action_model': 9.954629470598571e-05, 'learning_rate/action_query_proj': 9.954629470598571e-05, 'learning_rate/base': 2.488657367649643e-05, 'epoch': 0.51}) +[2026-07-27 08:58:12,486][starVLA.training.train_starvla][INFO] - Step 4220, Loss: {'train/loss': 0.05030171945691109, 'train/grad_norm_pre_clip': 4.011147975921631, 'timing/data': 0.000195259228348732, 'timing/model': 0.4569085445255041, 'learning_rate/action_model': 9.954214843343925e-05, 'learning_rate/action_query_proj': 9.954214843343925e-05, 'learning_rate/base': 2.4885537108359812e-05, 'epoch': 0.51}) +[2026-07-27 08:58:18,041][starVLA.training.train_starvla][INFO] - Step 4221, Loss: {'train/loss': 0.09611984342336655, 'train/grad_norm_pre_clip': 5.013054370880127, 'timing/data': 0.00018789805471897125, 'timing/model': 0.45752521604299545, 'learning_rate/action_model': 9.953798339200553e-05, 'learning_rate/action_query_proj': 9.953798339200553e-05, 'learning_rate/base': 2.4884495848001382e-05, 'epoch': 0.51}) +[2026-07-27 08:58:23,583][starVLA.training.train_starvla][INFO] - Step 4222, Loss: {'train/loss': 0.018156060948967934, 'train/grad_norm_pre_clip': 1.3510966300964355, 'timing/data': 0.00018614530563354492, 'timing/model': 0.4573692735284567, 'learning_rate/action_model': 9.95337995833288e-05, 'learning_rate/action_query_proj': 9.95337995833288e-05, 'learning_rate/base': 2.48834498958322e-05, 'epoch': 0.51}) +[2026-07-27 08:58:29,138][starVLA.training.train_starvla][INFO] - Step 4223, Loss: {'train/loss': 0.11208651959896088, 'train/grad_norm_pre_clip': 5.032710552215576, 'timing/data': 0.00023542903363704681, 'timing/model': 0.45760349929332733, 'learning_rate/action_model': 9.952959700906079e-05, 'learning_rate/action_query_proj': 9.952959700906079e-05, 'learning_rate/base': 2.4882399252265197e-05, 'epoch': 0.51}) +[2026-07-27 08:58:34,685][starVLA.training.train_starvla][INFO] - Step 4224, Loss: {'train/loss': 0.012728775851428509, 'train/grad_norm_pre_clip': 1.182631492614746, 'timing/data': 0.00023955106735229492, 'timing/model': 0.45665203407406807, 'learning_rate/action_model': 9.952537567086062e-05, 'learning_rate/action_query_proj': 9.952537567086062e-05, 'learning_rate/base': 2.4881343917715156e-05, 'epoch': 0.51}) +[2026-07-27 08:58:40,237][starVLA.training.train_starvla][INFO] - Step 4225, Loss: {'train/loss': 0.05774056538939476, 'train/grad_norm_pre_clip': 3.3298990726470947, 'timing/data': 0.0002370402216911316, 'timing/model': 0.45766222290694714, 'learning_rate/action_model': 9.952113557039477e-05, 'learning_rate/action_query_proj': 9.952113557039477e-05, 'learning_rate/base': 2.488028389259869e-05, 'epoch': 0.51}) +[2026-07-27 08:58:45,788][starVLA.training.train_starvla][INFO] - Step 4226, Loss: {'train/loss': 0.023527102544903755, 'train/grad_norm_pre_clip': 1.7609894275665283, 'timing/data': 0.0001844298094511032, 'timing/model': 0.4569783564656973, 'learning_rate/action_model': 9.95168767093372e-05, 'learning_rate/action_query_proj': 9.95168767093372e-05, 'learning_rate/base': 2.48792191773343e-05, 'epoch': 0.51}) +[2026-07-27 08:58:51,333][starVLA.training.train_starvla][INFO] - Step 4227, Loss: {'train/loss': 0.11576522886753082, 'train/grad_norm_pre_clip': 3.417217493057251, 'timing/data': 0.00018059462308883667, 'timing/model': 0.4572984501719475, 'learning_rate/action_model': 9.951259908936921e-05, 'learning_rate/action_query_proj': 9.951259908936921e-05, 'learning_rate/base': 2.4878149772342303e-05, 'epoch': 0.51}) +[2026-07-27 08:58:56,877][starVLA.training.train_starvla][INFO] - Step 4228, Loss: {'train/loss': 0.019007792696356773, 'train/grad_norm_pre_clip': 1.4088635444641113, 'timing/data': 0.00020634569227695465, 'timing/model': 0.4569078888744116, 'learning_rate/action_model': 9.950830271217957e-05, 'learning_rate/action_query_proj': 9.950830271217957e-05, 'learning_rate/base': 2.487707567804489e-05, 'epoch': 0.51}) +[2026-07-27 08:59:02,422][starVLA.training.train_starvla][INFO] - Step 4229, Loss: {'train/loss': 0.029910357668995857, 'train/grad_norm_pre_clip': 2.4817721843719482, 'timing/data': 0.00019244663417339325, 'timing/model': 0.4628915935754776, 'learning_rate/action_model': 9.95039875794644e-05, 'learning_rate/action_query_proj': 9.95039875794644e-05, 'learning_rate/base': 2.48759968948661e-05, 'epoch': 0.51}) +[2026-07-27 08:59:07,942][starVLA.training.train_starvla][INFO] - Step 4230, Loss: {'train/loss': 0.035508327186107635, 'train/grad_norm_pre_clip': 2.7570371627807617, 'timing/data': 0.0002391040325164795, 'timing/model': 0.45804835855960846, 'learning_rate/action_model': 9.949965369292724e-05, 'learning_rate/action_query_proj': 9.949965369292724e-05, 'learning_rate/base': 2.487491342323181e-05, 'epoch': 0.51}) +[2026-07-27 08:59:13,434][starVLA.training.train_starvla][INFO] - Step 4231, Loss: {'train/loss': 0.05207613855600357, 'train/grad_norm_pre_clip': 5.038823127746582, 'timing/data': 0.0002469569444656372, 'timing/model': 0.4593654293566942, 'learning_rate/action_model': 9.949530105427908e-05, 'learning_rate/action_query_proj': 9.949530105427908e-05, 'learning_rate/base': 2.487382526356977e-05, 'epoch': 0.51}) +[2026-07-27 08:59:18,935][starVLA.training.train_starvla][INFO] - Step 4232, Loss: {'train/loss': 0.08658310025930405, 'train/grad_norm_pre_clip': 3.8778419494628906, 'timing/data': 0.000256149098277092, 'timing/model': 0.4617120996117592, 'learning_rate/action_model': 9.949092966523822e-05, 'learning_rate/action_query_proj': 9.949092966523822e-05, 'learning_rate/base': 2.4872732416309556e-05, 'epoch': 0.51}) +[2026-07-27 08:59:24,431][starVLA.training.train_starvla][INFO] - Step 4233, Loss: {'train/loss': 0.06425206363201141, 'train/grad_norm_pre_clip': 4.1121506690979, 'timing/data': 0.00024143420159816742, 'timing/model': 0.4625098668038845, 'learning_rate/action_model': 9.948653952753044e-05, 'learning_rate/action_query_proj': 9.948653952753044e-05, 'learning_rate/base': 2.487163488188261e-05, 'epoch': 0.51}) +[2026-07-27 08:59:29,935][starVLA.training.train_starvla][INFO] - Step 4234, Loss: {'train/loss': 0.0400376096367836, 'train/grad_norm_pre_clip': 2.7051262855529785, 'timing/data': 0.00017940253019332886, 'timing/model': 0.46168642677366734, 'learning_rate/action_model': 9.948213064288892e-05, 'learning_rate/action_query_proj': 9.948213064288892e-05, 'learning_rate/base': 2.487053266072223e-05, 'epoch': 0.51}) +[2026-07-27 08:59:35,446][starVLA.training.train_starvla][INFO] - Step 4235, Loss: {'train/loss': 0.061733607202768326, 'train/grad_norm_pre_clip': 2.948275089263916, 'timing/data': 0.00018450431525707245, 'timing/model': 0.461037227883935, 'learning_rate/action_model': 9.947770301305417e-05, 'learning_rate/action_query_proj': 9.947770301305417e-05, 'learning_rate/base': 2.486942575326354e-05, 'epoch': 0.51}) +[2026-07-27 08:59:40,975][starVLA.training.train_starvla][INFO] - Step 4236, Loss: {'train/loss': 0.0709187388420105, 'train/grad_norm_pre_clip': 4.6001787185668945, 'timing/data': 0.00018061138689517975, 'timing/model': 0.46277040243148804, 'learning_rate/action_model': 9.947325663977418e-05, 'learning_rate/action_query_proj': 9.947325663977418e-05, 'learning_rate/base': 2.4868314159943546e-05, 'epoch': 0.51}) +[2026-07-27 08:59:46,480][starVLA.training.train_starvla][INFO] - Step 4237, Loss: {'train/loss': 0.264538049697876, 'train/grad_norm_pre_clip': 6.626667499542236, 'timing/data': 0.00018196552991867065, 'timing/model': 0.46268494240939617, 'learning_rate/action_model': 9.946879152480431e-05, 'learning_rate/action_query_proj': 9.946879152480431e-05, 'learning_rate/base': 2.4867197881201077e-05, 'epoch': 0.51}) +[2026-07-27 08:59:51,993][starVLA.training.train_starvla][INFO] - Step 4238, Loss: {'train/loss': 0.19588546454906464, 'train/grad_norm_pre_clip': 5.8370866775512695, 'timing/data': 0.00018772296607494354, 'timing/model': 0.462993323802948, 'learning_rate/action_model': 9.946430766990729e-05, 'learning_rate/action_query_proj': 9.946430766990729e-05, 'learning_rate/base': 2.4866076917476822e-05, 'epoch': 0.51}) +[2026-07-27 08:59:57,489][starVLA.training.train_starvla][INFO] - Step 4239, Loss: {'train/loss': 0.17486943304538727, 'train/grad_norm_pre_clip': 4.039267063140869, 'timing/data': 0.00018023699522018433, 'timing/model': 0.4595595467835665, 'learning_rate/action_model': 9.94598050768533e-05, 'learning_rate/action_query_proj': 9.94598050768533e-05, 'learning_rate/base': 2.4864951269213325e-05, 'epoch': 0.51}) +[2026-07-27 09:00:02,971][starVLA.training.train_starvla][INFO] - Step 4240, Loss: {'train/loss': 0.09494997560977936, 'train/grad_norm_pre_clip': 4.702291965484619, 'timing/data': 0.0001805126667022705, 'timing/model': 0.4577625636011362, 'learning_rate/action_model': 9.945528374741986e-05, 'learning_rate/action_query_proj': 9.945528374741986e-05, 'learning_rate/base': 2.4863820936854966e-05, 'epoch': 0.51}) +[2026-07-27 09:00:08,460][starVLA.training.train_starvla][INFO] - Step 4241, Loss: {'train/loss': 0.15369923412799835, 'train/grad_norm_pre_clip': 4.657548904418945, 'timing/data': 0.00018832646310329437, 'timing/model': 0.45761438831686974, 'learning_rate/action_model': 9.945074368339197e-05, 'learning_rate/action_query_proj': 9.945074368339197e-05, 'learning_rate/base': 2.4862685920847993e-05, 'epoch': 0.51}) +[2026-07-27 09:00:14,000][starVLA.training.train_starvla][INFO] - Step 4242, Loss: {'train/loss': 0.15085166692733765, 'train/grad_norm_pre_clip': 5.84919548034668, 'timing/data': 0.00017762184143066406, 'timing/model': 0.45748857967555523, 'learning_rate/action_model': 9.944618488656196e-05, 'learning_rate/action_query_proj': 9.944618488656196e-05, 'learning_rate/base': 2.486154622164049e-05, 'epoch': 0.51}) +[2026-07-27 09:00:19,533][starVLA.training.train_starvla][INFO] - Step 4243, Loss: {'train/loss': 0.2060772329568863, 'train/grad_norm_pre_clip': 6.206162929534912, 'timing/data': 0.00017617829144001007, 'timing/model': 0.4572483655065298, 'learning_rate/action_model': 9.944160735872952e-05, 'learning_rate/action_query_proj': 9.944160735872952e-05, 'learning_rate/base': 2.486040183968238e-05, 'epoch': 0.51}) +[2026-07-27 09:00:25,068][starVLA.training.train_starvla][INFO] - Step 4244, Loss: {'train/loss': 0.10658708214759827, 'train/grad_norm_pre_clip': 4.648409366607666, 'timing/data': 0.00017667748034000397, 'timing/model': 0.46224556863307953, 'learning_rate/action_model': 9.943701110170186e-05, 'learning_rate/action_query_proj': 9.943701110170186e-05, 'learning_rate/base': 2.4859252775425466e-05, 'epoch': 0.51}) +[2026-07-27 09:00:30,592][starVLA.training.train_starvla][INFO] - Step 4245, Loss: {'train/loss': 0.0647343322634697, 'train/grad_norm_pre_clip': 3.3968465328216553, 'timing/data': 0.00018742121756076813, 'timing/model': 0.46148413605988026, 'learning_rate/action_model': 9.943239611729349e-05, 'learning_rate/action_query_proj': 9.943239611729349e-05, 'learning_rate/base': 2.485809902932337e-05, 'epoch': 0.51}) +[2026-07-27 09:00:36,110][starVLA.training.train_starvla][INFO] - Step 4246, Loss: {'train/loss': 0.03678124397993088, 'train/grad_norm_pre_clip': 2.1816015243530273, 'timing/data': 0.00018701888620853424, 'timing/model': 0.46004254557192326, 'learning_rate/action_model': 9.942776240732626e-05, 'learning_rate/action_query_proj': 9.942776240732626e-05, 'learning_rate/base': 2.4856940601831565e-05, 'epoch': 0.52}) +[2026-07-27 09:00:41,665][starVLA.training.train_starvla][INFO] - Step 4247, Loss: {'train/loss': 0.022304002195596695, 'train/grad_norm_pre_clip': 1.729143500328064, 'timing/data': 0.00021540187299251556, 'timing/model': 0.45818328484892845, 'learning_rate/action_model': 9.942310997362958e-05, 'learning_rate/action_query_proj': 9.942310997362958e-05, 'learning_rate/base': 2.4855777493407395e-05, 'epoch': 0.52}) +[2026-07-27 09:00:47,181][starVLA.training.train_starvla][INFO] - Step 4248, Loss: {'train/loss': 0.1874777376651764, 'train/grad_norm_pre_clip': 4.76299524307251, 'timing/data': 0.00017578713595867157, 'timing/model': 0.45821899361908436, 'learning_rate/action_model': 9.941843881804011e-05, 'learning_rate/action_query_proj': 9.941843881804011e-05, 'learning_rate/base': 2.4854609704510027e-05, 'epoch': 0.52}) +[2026-07-27 09:00:52,655][starVLA.training.train_starvla][INFO] - Step 4249, Loss: {'train/loss': 0.21611665189266205, 'train/grad_norm_pre_clip': 6.2360711097717285, 'timing/data': 0.00017712637782096863, 'timing/model': 0.45797825045883656, 'learning_rate/action_model': 9.941374894240196e-05, 'learning_rate/action_query_proj': 9.941374894240196e-05, 'learning_rate/base': 2.485343723560049e-05, 'epoch': 0.52}) +[2026-07-27 09:00:58,124][starVLA.training.train_starvla][INFO] - Step 4250, Loss: {'train/loss': 0.16317220032215118, 'train/grad_norm_pre_clip': 4.150545120239258, 'timing/data': 0.0001774188131093979, 'timing/model': 0.457074549049139, 'learning_rate/action_model': 9.940904034856662e-05, 'learning_rate/action_query_proj': 9.940904034856662e-05, 'learning_rate/base': 2.4852260087141655e-05, 'epoch': 0.52}) +[2026-07-27 09:01:03,597][starVLA.training.train_starvla][INFO] - Step 4251, Loss: {'train/loss': 0.09989677369594574, 'train/grad_norm_pre_clip': 4.116148471832275, 'timing/data': 0.00018068403005599976, 'timing/model': 0.4578580502420664, 'learning_rate/action_model': 9.940431303839296e-05, 'learning_rate/action_query_proj': 9.940431303839296e-05, 'learning_rate/base': 2.485107825959824e-05, 'epoch': 0.52}) +[2026-07-27 09:01:09,112][starVLA.training.train_starvla][INFO] - Step 4252, Loss: {'train/loss': 0.140384703874588, 'train/grad_norm_pre_clip': 4.021913528442383, 'timing/data': 0.0001779738813638687, 'timing/model': 0.4565875716507435, 'learning_rate/action_model': 9.939956701374724e-05, 'learning_rate/action_query_proj': 9.939956701374724e-05, 'learning_rate/base': 2.484989175343681e-05, 'epoch': 0.52}) +[2026-07-27 09:01:14,854][starVLA.training.train_starvla][INFO] - Step 4253, Loss: {'train/loss': 0.10425318777561188, 'train/grad_norm_pre_clip': 2.901054859161377, 'timing/data': 0.0001791827380657196, 'timing/model': 0.4580346383154392, 'learning_rate/action_model': 9.939480227650314e-05, 'learning_rate/action_query_proj': 9.939480227650314e-05, 'learning_rate/base': 2.4848700569125786e-05, 'epoch': 0.52}) +[2026-07-27 09:01:20,332][starVLA.training.train_starvla][INFO] - Step 4254, Loss: {'train/loss': 0.1468300074338913, 'train/grad_norm_pre_clip': 4.280435085296631, 'timing/data': 0.00017796829342842102, 'timing/model': 0.45812288485467434, 'learning_rate/action_model': 9.93900188285417e-05, 'learning_rate/action_query_proj': 9.93900188285417e-05, 'learning_rate/base': 2.4847504707135424e-05, 'epoch': 0.52}) +[2026-07-27 09:01:25,808][starVLA.training.train_starvla][INFO] - Step 4255, Loss: {'train/loss': 0.07980578392744064, 'train/grad_norm_pre_clip': 3.852609157562256, 'timing/data': 0.00017801113426685333, 'timing/model': 0.45764355920255184, 'learning_rate/action_model': 9.938521667175133e-05, 'learning_rate/action_query_proj': 9.938521667175133e-05, 'learning_rate/base': 2.484630416793783e-05, 'epoch': 0.52}) +[2026-07-27 09:01:31,286][starVLA.training.train_starvla][INFO] - Step 4256, Loss: {'train/loss': 0.08359086513519287, 'train/grad_norm_pre_clip': 3.523369789123535, 'timing/data': 0.0001872032880783081, 'timing/model': 0.45945740304887295, 'learning_rate/action_model': 9.938039580802785e-05, 'learning_rate/action_query_proj': 9.938039580802785e-05, 'learning_rate/base': 2.4845098952006962e-05, 'epoch': 0.52}) +[2026-07-27 09:01:36,765][starVLA.training.train_starvla][INFO] - Step 4257, Loss: {'train/loss': 0.10168687999248505, 'train/grad_norm_pre_clip': 4.280367374420166, 'timing/data': 0.0001773592084646225, 'timing/model': 0.45752674899995327, 'learning_rate/action_model': 9.937555623927447e-05, 'learning_rate/action_query_proj': 9.937555623927447e-05, 'learning_rate/base': 2.4843889059818616e-05, 'epoch': 0.52}) +[2026-07-27 09:01:42,282][starVLA.training.train_starvla][INFO] - Step 4258, Loss: {'train/loss': 0.14339090883731842, 'train/grad_norm_pre_clip': 3.617964267730713, 'timing/data': 0.00017597712576389313, 'timing/model': 0.45777352154254913, 'learning_rate/action_model': 9.937069796740176e-05, 'learning_rate/action_query_proj': 9.937069796740176e-05, 'learning_rate/base': 2.484267449185044e-05, 'epoch': 0.52}) +[2026-07-27 09:01:47,782][starVLA.training.train_starvla][INFO] - Step 4259, Loss: {'train/loss': 0.047042883932590485, 'train/grad_norm_pre_clip': 2.46069073677063, 'timing/data': 0.00017561018466949463, 'timing/model': 0.4577864594757557, 'learning_rate/action_model': 9.936582099432772e-05, 'learning_rate/action_query_proj': 9.936582099432772e-05, 'learning_rate/base': 2.484145524858193e-05, 'epoch': 0.52}) +[2026-07-27 09:01:53,273][starVLA.training.train_starvla][INFO] - Step 4260, Loss: {'train/loss': 0.13922934234142303, 'train/grad_norm_pre_clip': 3.7134885787963867, 'timing/data': 0.00017628446221351624, 'timing/model': 0.4577302448451519, 'learning_rate/action_model': 9.936092532197766e-05, 'learning_rate/action_query_proj': 9.936092532197766e-05, 'learning_rate/base': 2.4840231330494415e-05, 'epoch': 0.52}) +[2026-07-27 09:01:58,762][starVLA.training.train_starvla][INFO] - Step 4261, Loss: {'train/loss': 0.12443412840366364, 'train/grad_norm_pre_clip': 4.002711772918701, 'timing/data': 0.00017628073692321777, 'timing/model': 0.4564218129962683, 'learning_rate/action_model': 9.935601095228436e-05, 'learning_rate/action_query_proj': 9.935601095228436e-05, 'learning_rate/base': 2.483900273807109e-05, 'epoch': 0.52}) +[2026-07-27 09:02:04,515][starVLA.training.train_starvla][INFO] - Step 4262, Loss: {'train/loss': 0.09035792946815491, 'train/grad_norm_pre_clip': 3.6944730281829834, 'timing/data': 0.0001778285950422287, 'timing/model': 0.457393866032362, 'learning_rate/action_model': 9.935107788718789e-05, 'learning_rate/action_query_proj': 9.935107788718789e-05, 'learning_rate/base': 2.4837769471796972e-05, 'epoch': 0.52}) +[2026-07-27 09:02:10,016][starVLA.training.train_starvla][INFO] - Step 4263, Loss: {'train/loss': 0.03851374238729477, 'train/grad_norm_pre_clip': 1.7545666694641113, 'timing/data': 0.00018051452934741974, 'timing/model': 0.45765890181064606, 'learning_rate/action_model': 9.934612612863578e-05, 'learning_rate/action_query_proj': 9.934612612863578e-05, 'learning_rate/base': 2.4836531532158945e-05, 'epoch': 0.52}) +[2026-07-27 09:02:15,830][starVLA.training.train_starvla][INFO] - Step 4264, Loss: {'train/loss': 0.05816240608692169, 'train/grad_norm_pre_clip': 2.513042688369751, 'timing/data': 0.0001748744398355484, 'timing/model': 0.45747267454862595, 'learning_rate/action_model': 9.934115567858288e-05, 'learning_rate/action_query_proj': 9.934115567858288e-05, 'learning_rate/base': 2.483528891964572e-05, 'epoch': 0.52}) +[2026-07-27 09:02:21,564][starVLA.training.train_starvla][INFO] - Step 4265, Loss: {'train/loss': 0.03691250458359718, 'train/grad_norm_pre_clip': 2.26705002784729, 'timing/data': 0.00017480552196502686, 'timing/model': 0.4571067187935114, 'learning_rate/action_model': 9.933616653899147e-05, 'learning_rate/action_query_proj': 9.933616653899147e-05, 'learning_rate/base': 2.4834041634747868e-05, 'epoch': 0.52}) +[2026-07-27 09:02:27,098][starVLA.training.train_starvla][INFO] - Step 4266, Loss: {'train/loss': 0.14466848969459534, 'train/grad_norm_pre_clip': 5.143157482147217, 'timing/data': 0.00017596036195755005, 'timing/model': 0.45899407751858234, 'learning_rate/action_model': 9.933115871183117e-05, 'learning_rate/action_query_proj': 9.933115871183117e-05, 'learning_rate/base': 2.4832789677957792e-05, 'epoch': 0.52}) +[2026-07-27 09:02:32,627][starVLA.training.train_starvla][INFO] - Step 4267, Loss: {'train/loss': 0.06819000095129013, 'train/grad_norm_pre_clip': 2.644591808319092, 'timing/data': 0.00018186680972576141, 'timing/model': 0.45751663483679295, 'learning_rate/action_model': 9.932613219907899e-05, 'learning_rate/action_query_proj': 9.932613219907899e-05, 'learning_rate/base': 2.4831533049769746e-05, 'epoch': 0.52}) +[2026-07-27 09:02:38,157][starVLA.training.train_starvla][INFO] - Step 4268, Loss: {'train/loss': 0.06038789451122284, 'train/grad_norm_pre_clip': 3.0210025310516357, 'timing/data': 0.0001867283135652542, 'timing/model': 0.4581585172563791, 'learning_rate/action_model': 9.93210870027193e-05, 'learning_rate/action_query_proj': 9.93210870027193e-05, 'learning_rate/base': 2.4830271750679825e-05, 'epoch': 0.52}) +[2026-07-27 09:02:43,700][starVLA.training.train_starvla][INFO] - Step 4269, Loss: {'train/loss': 0.0615936815738678, 'train/grad_norm_pre_clip': 1.8282955884933472, 'timing/data': 0.00017138198018074036, 'timing/model': 0.45765591226518154, 'learning_rate/action_model': 9.931602312474391e-05, 'learning_rate/action_query_proj': 9.931602312474391e-05, 'learning_rate/base': 2.4829005781185977e-05, 'epoch': 0.52}) +[2026-07-27 09:02:49,326][starVLA.training.train_starvla][INFO] - Step 4270, Loss: {'train/loss': 0.047744911164045334, 'train/grad_norm_pre_clip': 2.840095281600952, 'timing/data': 0.00018902495503425598, 'timing/model': 0.45803250931203365, 'learning_rate/action_model': 9.931094056715191e-05, 'learning_rate/action_query_proj': 9.931094056715191e-05, 'learning_rate/base': 2.4827735141787978e-05, 'epoch': 0.52}) +[2026-07-27 09:02:54,851][starVLA.training.train_starvla][INFO] - Step 4271, Loss: {'train/loss': 0.0777611956000328, 'train/grad_norm_pre_clip': 3.310014009475708, 'timing/data': 0.0001826658844947815, 'timing/model': 0.4576002098619938, 'learning_rate/action_model': 9.930583933194983e-05, 'learning_rate/action_query_proj': 9.930583933194983e-05, 'learning_rate/base': 2.482645983298746e-05, 'epoch': 0.52}) +[2026-07-27 09:03:00,365][starVLA.training.train_starvla][INFO] - Step 4272, Loss: {'train/loss': 0.06442240625619888, 'train/grad_norm_pre_clip': 3.3870933055877686, 'timing/data': 0.00017715245485305786, 'timing/model': 0.4583901520818472, 'learning_rate/action_model': 9.930071942115159e-05, 'learning_rate/action_query_proj': 9.930071942115159e-05, 'learning_rate/base': 2.4825179855287897e-05, 'epoch': 0.52}) +[2026-07-27 09:03:05,896][starVLA.training.train_starvla][INFO] - Step 4273, Loss: {'train/loss': 0.039024971425533295, 'train/grad_norm_pre_clip': 1.9689446687698364, 'timing/data': 0.00017635896801948547, 'timing/model': 0.45734107308089733, 'learning_rate/action_model': 9.92955808367784e-05, 'learning_rate/action_query_proj': 9.92955808367784e-05, 'learning_rate/base': 2.48238952091946e-05, 'epoch': 0.52}) +[2026-07-27 09:03:11,457][starVLA.training.train_starvla][INFO] - Step 4274, Loss: {'train/loss': 0.1291862428188324, 'train/grad_norm_pre_clip': 3.7122914791107178, 'timing/data': 0.00017688050866127014, 'timing/model': 0.458092387765646, 'learning_rate/action_model': 9.929042358085894e-05, 'learning_rate/action_query_proj': 9.929042358085894e-05, 'learning_rate/base': 2.4822605895214735e-05, 'epoch': 0.52}) +[2026-07-27 09:03:17,019][starVLA.training.train_starvla][INFO] - Step 4275, Loss: {'train/loss': 0.09130901843309402, 'train/grad_norm_pre_clip': 3.653430700302124, 'timing/data': 0.00017792917788028717, 'timing/model': 0.45717816427350044, 'learning_rate/action_model': 9.928524765542915e-05, 'learning_rate/action_query_proj': 9.928524765542915e-05, 'learning_rate/base': 2.4821311913857286e-05, 'epoch': 0.52}) +[2026-07-27 09:03:22,580][starVLA.training.train_starvla][INFO] - Step 4276, Loss: {'train/loss': 0.07403437793254852, 'train/grad_norm_pre_clip': 3.3144490718841553, 'timing/data': 0.00017530471086502075, 'timing/model': 0.45762099884450436, 'learning_rate/action_model': 9.928005306253245e-05, 'learning_rate/action_query_proj': 9.928005306253245e-05, 'learning_rate/base': 2.4820013265633112e-05, 'epoch': 0.52}) +[2026-07-27 09:03:28,125][starVLA.training.train_starvla][INFO] - Step 4277, Loss: {'train/loss': 0.10790343582630157, 'train/grad_norm_pre_clip': 4.45227575302124, 'timing/data': 0.00017466582357883453, 'timing/model': 0.4568594191223383, 'learning_rate/action_model': 9.927483980421959e-05, 'learning_rate/action_query_proj': 9.927483980421959e-05, 'learning_rate/base': 2.4818709951054896e-05, 'epoch': 0.52}) +[2026-07-27 09:03:33,691][starVLA.training.train_starvla][INFO] - Step 4278, Loss: {'train/loss': 0.13824759423732758, 'train/grad_norm_pre_clip': 2.910163402557373, 'timing/data': 0.000273263081908226, 'timing/model': 0.45850660279393196, 'learning_rate/action_model': 9.926960788254865e-05, 'learning_rate/action_query_proj': 9.926960788254865e-05, 'learning_rate/base': 2.4817401970637162e-05, 'epoch': 0.52}) +[2026-07-27 09:03:39,258][starVLA.training.train_starvla][INFO] - Step 4279, Loss: {'train/loss': 0.06272319704294205, 'train/grad_norm_pre_clip': 2.651977062225342, 'timing/data': 0.00023842230439186096, 'timing/model': 0.4617431852966547, 'learning_rate/action_model': 9.926435729958512e-05, 'learning_rate/action_query_proj': 9.926435729958512e-05, 'learning_rate/base': 2.481608932489628e-05, 'epoch': 0.52}) +[2026-07-27 09:03:44,835][starVLA.training.train_starvla][INFO] - Step 4280, Loss: {'train/loss': 0.027145439758896828, 'train/grad_norm_pre_clip': 1.3516994714736938, 'timing/data': 0.00027884356677532196, 'timing/model': 0.45660545863211155, 'learning_rate/action_model': 9.925908805740186e-05, 'learning_rate/action_query_proj': 9.925908805740186e-05, 'learning_rate/base': 2.4814772014350464e-05, 'epoch': 0.52}) +[2026-07-27 09:03:50,401][starVLA.training.train_starvla][INFO] - Step 4281, Loss: {'train/loss': 0.04937571659684181, 'train/grad_norm_pre_clip': 2.2591543197631836, 'timing/data': 0.00017105787992477417, 'timing/model': 0.45600026100873947, 'learning_rate/action_model': 9.925380015807908e-05, 'learning_rate/action_query_proj': 9.925380015807908e-05, 'learning_rate/base': 2.481345003951977e-05, 'epoch': 0.52}) +[2026-07-27 09:03:55,956][starVLA.training.train_starvla][INFO] - Step 4282, Loss: {'train/loss': 0.11171901226043701, 'train/grad_norm_pre_clip': 3.6722147464752197, 'timing/data': 0.00022826902568340302, 'timing/model': 0.45872246101498604, 'learning_rate/action_model': 9.924849360370433e-05, 'learning_rate/action_query_proj': 9.924849360370433e-05, 'learning_rate/base': 2.4812123400926083e-05, 'epoch': 0.52}) +[2026-07-27 09:04:01,510][starVLA.training.train_starvla][INFO] - Step 4283, Loss: {'train/loss': 0.08438021689653397, 'train/grad_norm_pre_clip': 3.746342658996582, 'timing/data': 0.00018459558486938477, 'timing/model': 0.45671279169619083, 'learning_rate/action_model': 9.924316839637261e-05, 'learning_rate/action_query_proj': 9.924316839637261e-05, 'learning_rate/base': 2.4810792099093152e-05, 'epoch': 0.52}) +[2026-07-27 09:04:07,096][starVLA.training.train_starvla][INFO] - Step 4284, Loss: {'train/loss': 0.1175651028752327, 'train/grad_norm_pre_clip': 2.5360186100006104, 'timing/data': 0.00022537074983119965, 'timing/model': 0.45720396749675274, 'learning_rate/action_model': 9.923782453818617e-05, 'learning_rate/action_query_proj': 9.923782453818617e-05, 'learning_rate/base': 2.4809456134546542e-05, 'epoch': 0.52}) +[2026-07-27 09:04:12,675][starVLA.training.train_starvla][INFO] - Step 4285, Loss: {'train/loss': 0.10794341564178467, 'train/grad_norm_pre_clip': 3.911360263824463, 'timing/data': 0.0001747123897075653, 'timing/model': 0.462565541267395, 'learning_rate/action_model': 9.923246203125471e-05, 'learning_rate/action_query_proj': 9.923246203125471e-05, 'learning_rate/base': 2.480811550781368e-05, 'epoch': 0.52}) +[2026-07-27 09:04:18,243][starVLA.training.train_starvla][INFO] - Step 4286, Loss: {'train/loss': 0.15416380763053894, 'train/grad_norm_pre_clip': 4.1375322341918945, 'timing/data': 0.0002498086541891098, 'timing/model': 0.46079232543706894, 'learning_rate/action_model': 9.922708087769526e-05, 'learning_rate/action_query_proj': 9.922708087769526e-05, 'learning_rate/base': 2.4806770219423816e-05, 'epoch': 0.52}) +[2026-07-27 09:04:23,838][starVLA.training.train_starvla][INFO] - Step 4287, Loss: {'train/loss': 0.08220521360635757, 'train/grad_norm_pre_clip': 2.683917284011841, 'timing/data': 0.00018251873552799225, 'timing/model': 0.4603955540806055, 'learning_rate/action_model': 9.922168107963222e-05, 'learning_rate/action_query_proj': 9.922168107963222e-05, 'learning_rate/base': 2.4805420269908054e-05, 'epoch': 0.52}) +[2026-07-27 09:04:29,418][starVLA.training.train_starvla][INFO] - Step 4288, Loss: {'train/loss': 0.1262412816286087, 'train/grad_norm_pre_clip': 4.182397365570068, 'timing/data': 0.00022966600954532623, 'timing/model': 0.4606324564665556, 'learning_rate/action_model': 9.921626263919733e-05, 'learning_rate/action_query_proj': 9.921626263919733e-05, 'learning_rate/base': 2.4804065659799333e-05, 'epoch': 0.52}) +[2026-07-27 09:04:34,982][starVLA.training.train_starvla][INFO] - Step 4289, Loss: {'train/loss': 0.13609883189201355, 'train/grad_norm_pre_clip': 4.3750901222229, 'timing/data': 0.00017065554857254028, 'timing/model': 0.46138557232916355, 'learning_rate/action_model': 9.921082555852971e-05, 'learning_rate/action_query_proj': 9.921082555852971e-05, 'learning_rate/base': 2.4802706389632427e-05, 'epoch': 0.52}) +[2026-07-27 09:04:40,545][starVLA.training.train_starvla][INFO] - Step 4290, Loss: {'train/loss': 0.16061024367809296, 'train/grad_norm_pre_clip': 4.595357418060303, 'timing/data': 0.00023128092288970947, 'timing/model': 0.4638571999967098, 'learning_rate/action_model': 9.920536983977583e-05, 'learning_rate/action_query_proj': 9.920536983977583e-05, 'learning_rate/base': 2.4801342459943956e-05, 'epoch': 0.52}) +[2026-07-27 09:04:46,116][starVLA.training.train_starvla][INFO] - Step 4291, Loss: {'train/loss': 0.06866040825843811, 'train/grad_norm_pre_clip': 3.196106433868408, 'timing/data': 0.000173935666680336, 'timing/model': 0.4608250856399536, 'learning_rate/action_model': 9.919989548508953e-05, 'learning_rate/action_query_proj': 9.919989548508953e-05, 'learning_rate/base': 2.4799973871272383e-05, 'epoch': 0.52}) +[2026-07-27 09:04:51,699][starVLA.training.train_starvla][INFO] - Step 4292, Loss: {'train/loss': 0.09316199272871017, 'train/grad_norm_pre_clip': 2.8108127117156982, 'timing/data': 0.00024991482496261597, 'timing/model': 0.4621767196804285, 'learning_rate/action_model': 9.919440249663198e-05, 'learning_rate/action_query_proj': 9.919440249663198e-05, 'learning_rate/base': 2.4798600624157996e-05, 'epoch': 0.52}) +[2026-07-27 09:04:57,526][starVLA.training.train_starvla][INFO] - Step 4293, Loss: {'train/loss': 0.15182170271873474, 'train/grad_norm_pre_clip': 2.6193761825561523, 'timing/data': 0.000229712575674057, 'timing/model': 0.46353232115507126, 'learning_rate/action_model': 9.918889087657177e-05, 'learning_rate/action_query_proj': 9.918889087657177e-05, 'learning_rate/base': 2.4797222719142943e-05, 'epoch': 0.52}) +[2026-07-27 09:05:03,364][starVLA.training.train_starvla][INFO] - Step 4294, Loss: {'train/loss': 0.1542285829782486, 'train/grad_norm_pre_clip': 5.098636627197266, 'timing/data': 0.00023319758474826813, 'timing/model': 0.4592188745737076, 'learning_rate/action_model': 9.918336062708476e-05, 'learning_rate/action_query_proj': 9.918336062708476e-05, 'learning_rate/base': 2.479584015677119e-05, 'epoch': 0.52}) +[2026-07-27 09:05:08,911][starVLA.training.train_starvla][INFO] - Step 4295, Loss: {'train/loss': 0.13970860838890076, 'train/grad_norm_pre_clip': 3.9934606552124023, 'timing/data': 0.00023184530436992645, 'timing/model': 0.4608941860496998, 'learning_rate/action_model': 9.91778117503542e-05, 'learning_rate/action_query_proj': 9.91778117503542e-05, 'learning_rate/base': 2.479445293758855e-05, 'epoch': 0.52}) +[2026-07-27 09:05:14,485][starVLA.training.train_starvla][INFO] - Step 4296, Loss: {'train/loss': 0.15048269927501678, 'train/grad_norm_pre_clip': 4.967196464538574, 'timing/data': 0.00017839856445789337, 'timing/model': 0.4692873004823923, 'learning_rate/action_model': 9.917224424857073e-05, 'learning_rate/action_query_proj': 9.917224424857073e-05, 'learning_rate/base': 2.4793061062142682e-05, 'epoch': 0.52}) +[2026-07-27 09:05:20,019][starVLA.training.train_starvla][INFO] - Step 4297, Loss: {'train/loss': 0.154779314994812, 'train/grad_norm_pre_clip': 5.22277307510376, 'timing/data': 0.00023172982037067413, 'timing/model': 0.46133146435022354, 'learning_rate/action_model': 9.916665812393228e-05, 'learning_rate/action_query_proj': 9.916665812393228e-05, 'learning_rate/base': 2.479166453098307e-05, 'epoch': 0.52}) +[2026-07-27 09:05:25,545][starVLA.training.train_starvla][INFO] - Step 4298, Loss: {'train/loss': 0.08119039237499237, 'train/grad_norm_pre_clip': 3.260561943054199, 'timing/data': 0.00022784806787967682, 'timing/model': 0.460079587996006, 'learning_rate/action_model': 9.916105337864419e-05, 'learning_rate/action_query_proj': 9.916105337864419e-05, 'learning_rate/base': 2.4790263344661048e-05, 'epoch': 0.52}) +[2026-07-27 09:05:31,073][starVLA.training.train_starvla][INFO] - Step 4299, Loss: {'train/loss': 0.12286928296089172, 'train/grad_norm_pre_clip': 3.9461750984191895, 'timing/data': 0.00022798776626586914, 'timing/model': 0.4624277036637068, 'learning_rate/action_model': 9.915543001491912e-05, 'learning_rate/action_query_proj': 9.915543001491912e-05, 'learning_rate/base': 2.478885750372978e-05, 'epoch': 0.52}) +[2026-07-27 09:05:36,609][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 4300 +[2026-07-27 09:05:36,610][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 4300 +[2026-07-27 09:05:36,611][starVLA.training.train_starvla][INFO] - Step 4300, Loss: {'train/loss': 0.1492561399936676, 'train/grad_norm_pre_clip': 3.1981911659240723, 'timing/data': 0.00023306533694267273, 'timing/model': 0.46138904243707657, 'learning_rate/action_model': 9.914978803497707e-05, 'learning_rate/action_query_proj': 9.914978803497707e-05, 'learning_rate/base': 2.4787447008744268e-05, 'epoch': 0.52}) +[2026-07-27 09:05:42,140][starVLA.training.train_starvla][INFO] - Step 4301, Loss: {'train/loss': 0.10124626755714417, 'train/grad_norm_pre_clip': 3.6031007766723633, 'timing/data': 0.00017658434808254242, 'timing/model': 0.46185023337602615, 'learning_rate/action_model': 9.91441274410454e-05, 'learning_rate/action_query_proj': 9.91441274410454e-05, 'learning_rate/base': 2.478603186026135e-05, 'epoch': 0.52}) +[2026-07-27 09:05:47,683][starVLA.training.train_starvla][INFO] - Step 4302, Loss: {'train/loss': 0.3531597852706909, 'train/grad_norm_pre_clip': 6.3963398933410645, 'timing/data': 0.00017465092241764069, 'timing/model': 0.4617377035319805, 'learning_rate/action_model': 9.913844823535884e-05, 'learning_rate/action_query_proj': 9.913844823535884e-05, 'learning_rate/base': 2.478461205883971e-05, 'epoch': 0.52}) +[2026-07-27 09:05:53,212][starVLA.training.train_starvla][INFO] - Step 4303, Loss: {'train/loss': 0.18482622504234314, 'train/grad_norm_pre_clip': 6.094919681549072, 'timing/data': 0.00017041899263858795, 'timing/model': 0.46079537086188793, 'learning_rate/action_model': 9.913275042015944e-05, 'learning_rate/action_query_proj': 9.913275042015944e-05, 'learning_rate/base': 2.478318760503986e-05, 'epoch': 0.52}) +[2026-07-27 09:05:58,751][starVLA.training.train_starvla][INFO] - Step 4304, Loss: {'train/loss': 0.1110929623246193, 'train/grad_norm_pre_clip': 4.468635559082031, 'timing/data': 0.00017381645739078522, 'timing/model': 0.4632781483232975, 'learning_rate/action_model': 9.912703399769664e-05, 'learning_rate/action_query_proj': 9.912703399769664e-05, 'learning_rate/base': 2.478175849942416e-05, 'epoch': 0.52}) +[2026-07-27 09:06:04,308][starVLA.training.train_starvla][INFO] - Step 4305, Loss: {'train/loss': 0.08673234283924103, 'train/grad_norm_pre_clip': 2.4269158840179443, 'timing/data': 0.00016885250806808472, 'timing/model': 0.45986082404851913, 'learning_rate/action_model': 9.912129897022714e-05, 'learning_rate/action_query_proj': 9.912129897022714e-05, 'learning_rate/base': 2.4780324742556786e-05, 'epoch': 0.52}) +[2026-07-27 09:06:09,853][starVLA.training.train_starvla][INFO] - Step 4306, Loss: {'train/loss': 0.1563037484884262, 'train/grad_norm_pre_clip': 3.8399741649627686, 'timing/data': 0.00017295964062213898, 'timing/model': 0.4621268976479769, 'learning_rate/action_model': 9.911554534001508e-05, 'learning_rate/action_query_proj': 9.911554534001508e-05, 'learning_rate/base': 2.477888633500377e-05, 'epoch': 0.52}) +[2026-07-27 09:06:15,393][starVLA.training.train_starvla][INFO] - Step 4307, Loss: {'train/loss': 0.07649887353181839, 'train/grad_norm_pre_clip': 2.944230556488037, 'timing/data': 0.00017365068197250366, 'timing/model': 0.4588649533689022, 'learning_rate/action_model': 9.910977310933189e-05, 'learning_rate/action_query_proj': 9.910977310933189e-05, 'learning_rate/base': 2.477744327733297e-05, 'epoch': 0.52}) +[2026-07-27 09:06:21,337][starVLA.training.train_starvla][INFO] - Step 4308, Loss: {'train/loss': 0.12424604594707489, 'train/grad_norm_pre_clip': 2.9259252548217773, 'timing/data': 0.00017641671001911163, 'timing/model': 0.47537082619965076, 'learning_rate/action_model': 9.910398228045635e-05, 'learning_rate/action_query_proj': 9.910398228045635e-05, 'learning_rate/base': 2.4775995570114086e-05, 'epoch': 0.52}) +[2026-07-27 09:06:26,901][starVLA.training.train_starvla][INFO] - Step 4309, Loss: {'train/loss': 0.08988222479820251, 'train/grad_norm_pre_clip': 4.45291805267334, 'timing/data': 0.00017340108752250671, 'timing/model': 0.4769524745643139, 'learning_rate/action_model': 9.909817285567456e-05, 'learning_rate/action_query_proj': 9.909817285567456e-05, 'learning_rate/base': 2.477454321391864e-05, 'epoch': 0.52}) +[2026-07-27 09:06:32,456][starVLA.training.train_starvla][INFO] - Step 4310, Loss: {'train/loss': 0.09324908256530762, 'train/grad_norm_pre_clip': 3.4191184043884277, 'timing/data': 0.00017692893743515015, 'timing/model': 0.4742929022759199, 'learning_rate/action_model': 9.909234483728003e-05, 'learning_rate/action_query_proj': 9.909234483728003e-05, 'learning_rate/base': 2.477308620932001e-05, 'epoch': 0.52}) +[2026-07-27 09:06:37,996][starVLA.training.train_starvla][INFO] - Step 4311, Loss: {'train/loss': 0.18372906744480133, 'train/grad_norm_pre_clip': 5.68826961517334, 'timing/data': 0.00017666444182395935, 'timing/model': 0.46915923058986664, 'learning_rate/action_model': 9.908649822757358e-05, 'learning_rate/action_query_proj': 9.908649822757358e-05, 'learning_rate/base': 2.4771624556893396e-05, 'epoch': 0.52}) +[2026-07-27 09:06:43,545][starVLA.training.train_starvla][INFO] - Step 4312, Loss: {'train/loss': 0.1930769979953766, 'train/grad_norm_pre_clip': 5.4138336181640625, 'timing/data': 0.00017164088785648346, 'timing/model': 0.47578700073063374, 'learning_rate/action_model': 9.908063302886332e-05, 'learning_rate/action_query_proj': 9.908063302886332e-05, 'learning_rate/base': 2.477015825721583e-05, 'epoch': 0.52}) +[2026-07-27 09:06:49,087][starVLA.training.train_starvla][INFO] - Step 4313, Loss: {'train/loss': 0.07155344635248184, 'train/grad_norm_pre_clip': 3.017942428588867, 'timing/data': 0.00017111003398895264, 'timing/model': 0.46866800636053085, 'learning_rate/action_model': 9.907474924346476e-05, 'learning_rate/action_query_proj': 9.907474924346476e-05, 'learning_rate/base': 2.476868731086619e-05, 'epoch': 0.52}) +[2026-07-27 09:06:54,639][starVLA.training.train_starvla][INFO] - Step 4314, Loss: {'train/loss': 0.13805830478668213, 'train/grad_norm_pre_clip': 3.086298942565918, 'timing/data': 0.00017190910875797272, 'timing/model': 0.47176610492169857, 'learning_rate/action_model': 9.906884687370069e-05, 'learning_rate/action_query_proj': 9.906884687370069e-05, 'learning_rate/base': 2.4767211718425173e-05, 'epoch': 0.52}) +[2026-07-27 09:07:00,190][starVLA.training.train_starvla][INFO] - Step 4315, Loss: {'train/loss': 0.05750870704650879, 'train/grad_norm_pre_clip': 2.6989684104919434, 'timing/data': 0.00017393939197063446, 'timing/model': 0.47596061788499355, 'learning_rate/action_model': 9.906292592190133e-05, 'learning_rate/action_query_proj': 9.906292592190133e-05, 'learning_rate/base': 2.4765731480475333e-05, 'epoch': 0.52}) +[2026-07-27 09:07:05,723][starVLA.training.train_starvla][INFO] - Step 4316, Loss: {'train/loss': 0.09653344750404358, 'train/grad_norm_pre_clip': 3.124542236328125, 'timing/data': 0.00017292797565460205, 'timing/model': 0.4614791329950094, 'learning_rate/action_model': 9.905698639040415e-05, 'learning_rate/action_query_proj': 9.905698639040415e-05, 'learning_rate/base': 2.4764246597601038e-05, 'epoch': 0.52}) +[2026-07-27 09:07:11,257][starVLA.training.train_starvla][INFO] - Step 4317, Loss: {'train/loss': 0.06703152507543564, 'train/grad_norm_pre_clip': 2.5194756984710693, 'timing/data': 0.0001743864268064499, 'timing/model': 0.46137714572250843, 'learning_rate/action_model': 9.905102828155398e-05, 'learning_rate/action_query_proj': 9.905102828155398e-05, 'learning_rate/base': 2.4762757070388494e-05, 'epoch': 0.52}) +[2026-07-27 09:07:16,789][starVLA.training.train_starvla][INFO] - Step 4318, Loss: {'train/loss': 0.18261151015758514, 'train/grad_norm_pre_clip': 4.5691680908203125, 'timing/data': 0.0001718364655971527, 'timing/model': 0.4619154315441847, 'learning_rate/action_model': 9.904505159770298e-05, 'learning_rate/action_query_proj': 9.904505159770298e-05, 'learning_rate/base': 2.4761262899425746e-05, 'epoch': 0.52}) +[2026-07-27 09:07:22,310][starVLA.training.train_starvla][INFO] - Step 4319, Loss: {'train/loss': 0.082806795835495, 'train/grad_norm_pre_clip': 3.7203938961029053, 'timing/data': 0.0001733042299747467, 'timing/model': 0.46282440051436424, 'learning_rate/action_model': 9.903905634121067e-05, 'learning_rate/action_query_proj': 9.903905634121067e-05, 'learning_rate/base': 2.4759764085302667e-05, 'epoch': 0.52}) +[2026-07-27 09:07:27,843][starVLA.training.train_starvla][INFO] - Step 4320, Loss: {'train/loss': 0.06605491787195206, 'train/grad_norm_pre_clip': 2.449510097503662, 'timing/data': 0.0001692734658718109, 'timing/model': 0.4629863742738962, 'learning_rate/action_model': 9.903304251444385e-05, 'learning_rate/action_query_proj': 9.903304251444385e-05, 'learning_rate/base': 2.4758260628610964e-05, 'epoch': 0.52}) +[2026-07-27 09:07:33,359][starVLA.training.train_starvla][INFO] - Step 4321, Loss: {'train/loss': 0.06544366478919983, 'train/grad_norm_pre_clip': 2.5383641719818115, 'timing/data': 0.00017121247947216034, 'timing/model': 0.457328949123621, 'learning_rate/action_model': 9.902701011977672e-05, 'learning_rate/action_query_proj': 9.902701011977672e-05, 'learning_rate/base': 2.475675252994418e-05, 'epoch': 0.52}) +[2026-07-27 09:07:38,873][starVLA.training.train_starvla][INFO] - Step 4322, Loss: {'train/loss': 0.05609962344169617, 'train/grad_norm_pre_clip': 2.9487316608428955, 'timing/data': 0.00017445161938667297, 'timing/model': 0.45657090470194817, 'learning_rate/action_model': 9.902095915959077e-05, 'learning_rate/action_query_proj': 9.902095915959077e-05, 'learning_rate/base': 2.475523978989769e-05, 'epoch': 0.52}) +[2026-07-27 09:07:44,387][starVLA.training.train_starvla][INFO] - Step 4323, Loss: {'train/loss': 0.022938396781682968, 'train/grad_norm_pre_clip': 1.6493172645568848, 'timing/data': 0.00016985274851322174, 'timing/model': 0.45663505233824253, 'learning_rate/action_model': 9.901488963627479e-05, 'learning_rate/action_query_proj': 9.901488963627479e-05, 'learning_rate/base': 2.4753722409068697e-05, 'epoch': 0.52}) +[2026-07-27 09:07:49,899][starVLA.training.train_starvla][INFO] - Step 4324, Loss: {'train/loss': 0.10667908936738968, 'train/grad_norm_pre_clip': 2.3646836280822754, 'timing/data': 0.00016966648399829865, 'timing/model': 0.45736500062048435, 'learning_rate/action_model': 9.900880155222496e-05, 'learning_rate/action_query_proj': 9.900880155222496e-05, 'learning_rate/base': 2.475220038805624e-05, 'epoch': 0.52}) +[2026-07-27 09:07:55,410][starVLA.training.train_starvla][INFO] - Step 4325, Loss: {'train/loss': 0.05289870873093605, 'train/grad_norm_pre_clip': 2.1374762058258057, 'timing/data': 0.00017150118947029114, 'timing/model': 0.45764697901904583, 'learning_rate/action_model': 9.900269490984477e-05, 'learning_rate/action_query_proj': 9.900269490984477e-05, 'learning_rate/base': 2.4750673727461192e-05, 'epoch': 0.52}) +[2026-07-27 09:08:00,923][starVLA.training.train_starvla][INFO] - Step 4326, Loss: {'train/loss': 0.04511381313204765, 'train/grad_norm_pre_clip': 1.9074729681015015, 'timing/data': 0.00018272176384925842, 'timing/model': 0.45744853280484676, 'learning_rate/action_model': 9.899656971154499e-05, 'learning_rate/action_query_proj': 9.899656971154499e-05, 'learning_rate/base': 2.4749142427886247e-05, 'epoch': 0.52}) +[2026-07-27 09:08:06,429][starVLA.training.train_starvla][INFO] - Step 4327, Loss: {'train/loss': 0.05775873363018036, 'train/grad_norm_pre_clip': 2.0253028869628906, 'timing/data': 0.00022532232105731964, 'timing/model': 0.45722975581884384, 'learning_rate/action_model': 9.899042595974377e-05, 'learning_rate/action_query_proj': 9.899042595974377e-05, 'learning_rate/base': 2.4747606489935942e-05, 'epoch': 0.52}) +[2026-07-27 09:08:11,917][starVLA.training.train_starvla][INFO] - Step 4328, Loss: {'train/loss': 0.12755893170833588, 'train/grad_norm_pre_clip': 5.250005722045898, 'timing/data': 0.00016914866864681244, 'timing/model': 0.45699825696647167, 'learning_rate/action_model': 9.898426365686659e-05, 'learning_rate/action_query_proj': 9.898426365686659e-05, 'learning_rate/base': 2.4746065914216647e-05, 'epoch': 0.53}) +[2026-07-27 09:08:17,394][starVLA.training.train_starvla][INFO] - Step 4329, Loss: {'train/loss': 0.1088847815990448, 'train/grad_norm_pre_clip': 4.741330623626709, 'timing/data': 0.00017229095101356506, 'timing/model': 0.4569573886692524, 'learning_rate/action_model': 9.897808280534616e-05, 'learning_rate/action_query_proj': 9.897808280534616e-05, 'learning_rate/base': 2.474452070133654e-05, 'epoch': 0.53}) +[2026-07-27 09:08:22,873][starVLA.training.train_starvla][INFO] - Step 4330, Loss: {'train/loss': 0.04234156012535095, 'train/grad_norm_pre_clip': 2.025261163711548, 'timing/data': 0.00017134658992290497, 'timing/model': 0.45701412856578827, 'learning_rate/action_model': 9.897188340762267e-05, 'learning_rate/action_query_proj': 9.897188340762267e-05, 'learning_rate/base': 2.4742970851905668e-05, 'epoch': 0.53}) +[2026-07-27 09:08:28,355][starVLA.training.train_starvla][INFO] - Step 4331, Loss: {'train/loss': 0.042165786027908325, 'train/grad_norm_pre_clip': 2.213557720184326, 'timing/data': 0.00017576664686203003, 'timing/model': 0.45747797563672066, 'learning_rate/action_model': 9.896566546614349e-05, 'learning_rate/action_query_proj': 9.896566546614349e-05, 'learning_rate/base': 2.4741416366535873e-05, 'epoch': 0.53}) +[2026-07-27 09:08:33,834][starVLA.training.train_starvla][INFO] - Step 4332, Loss: {'train/loss': 0.08635459840297699, 'train/grad_norm_pre_clip': 3.0001890659332275, 'timing/data': 0.00017265789210796356, 'timing/model': 0.45818547904491425, 'learning_rate/action_model': 9.895942898336337e-05, 'learning_rate/action_query_proj': 9.895942898336337e-05, 'learning_rate/base': 2.4739857245840843e-05, 'epoch': 0.53}) +[2026-07-27 09:08:39,305][starVLA.training.train_starvla][INFO] - Step 4333, Loss: {'train/loss': 0.008513347245752811, 'train/grad_norm_pre_clip': 0.6145017147064209, 'timing/data': 0.0001694764941930771, 'timing/model': 0.4572261646389961, 'learning_rate/action_model': 9.895317396174437e-05, 'learning_rate/action_query_proj': 9.895317396174437e-05, 'learning_rate/base': 2.4738293490436092e-05, 'epoch': 0.53}) +[2026-07-27 09:08:44,774][starVLA.training.train_starvla][INFO] - Step 4334, Loss: {'train/loss': 0.10106074810028076, 'train/grad_norm_pre_clip': 4.404952049255371, 'timing/data': 0.00018031708896160126, 'timing/model': 0.4576433598995209, 'learning_rate/action_model': 9.89469004037559e-05, 'learning_rate/action_query_proj': 9.89469004037559e-05, 'learning_rate/base': 2.4736725100938977e-05, 'epoch': 0.53}) +[2026-07-27 09:08:50,238][starVLA.training.train_starvla][INFO] - Step 4335, Loss: {'train/loss': 0.053006917238235474, 'train/grad_norm_pre_clip': 3.0651187896728516, 'timing/data': 0.00016860850155353546, 'timing/model': 0.4574566874653101, 'learning_rate/action_model': 9.894060831187465e-05, 'learning_rate/action_query_proj': 9.894060831187465e-05, 'learning_rate/base': 2.4735152077968663e-05, 'epoch': 0.53}) +[2026-07-27 09:08:55,705][starVLA.training.train_starvla][INFO] - Step 4336, Loss: {'train/loss': 0.11188267171382904, 'train/grad_norm_pre_clip': 4.989573001861572, 'timing/data': 0.00017463788390159607, 'timing/model': 0.45683441311120987, 'learning_rate/action_model': 9.893429768858464e-05, 'learning_rate/action_query_proj': 9.893429768858464e-05, 'learning_rate/base': 2.473357442214616e-05, 'epoch': 0.53}) +[2026-07-27 09:09:01,170][starVLA.training.train_starvla][INFO] - Step 4337, Loss: {'train/loss': 0.11319075524806976, 'train/grad_norm_pre_clip': 3.673288106918335, 'timing/data': 0.0001680459827184677, 'timing/model': 0.45635623671114445, 'learning_rate/action_model': 9.892796853637718e-05, 'learning_rate/action_query_proj': 9.892796853637718e-05, 'learning_rate/base': 2.4731992134094295e-05, 'epoch': 0.53}) +[2026-07-27 09:09:06,640][starVLA.training.train_starvla][INFO] - Step 4338, Loss: {'train/loss': 0.1340954303741455, 'train/grad_norm_pre_clip': 5.673919677734375, 'timing/data': 0.0001700669527053833, 'timing/model': 0.456989960744977, 'learning_rate/action_model': 9.892162085775094e-05, 'learning_rate/action_query_proj': 9.892162085775094e-05, 'learning_rate/base': 2.4730405214437734e-05, 'epoch': 0.53}) +[2026-07-27 09:09:12,104][starVLA.training.train_starvla][INFO] - Step 4339, Loss: {'train/loss': 0.23759254813194275, 'train/grad_norm_pre_clip': 5.453729152679443, 'timing/data': 0.00017071515321731567, 'timing/model': 0.4572056494653225, 'learning_rate/action_model': 9.89152546552119e-05, 'learning_rate/action_query_proj': 9.89152546552119e-05, 'learning_rate/base': 2.4728813663802975e-05, 'epoch': 0.53}) +[2026-07-27 09:09:17,594][starVLA.training.train_starvla][INFO] - Step 4340, Loss: {'train/loss': 0.0714641734957695, 'train/grad_norm_pre_clip': 3.784560203552246, 'timing/data': 0.00016718357801437378, 'timing/model': 0.45648638531565666, 'learning_rate/action_model': 9.89088699312733e-05, 'learning_rate/action_query_proj': 9.89088699312733e-05, 'learning_rate/base': 2.4727217482818323e-05, 'epoch': 0.53}) +[2026-07-27 09:09:23,104][starVLA.training.train_starvla][INFO] - Step 4341, Loss: {'train/loss': 0.08497902750968933, 'train/grad_norm_pre_clip': 2.8954734802246094, 'timing/data': 0.0001780577003955841, 'timing/model': 0.45735989138484, 'learning_rate/action_model': 9.890246668845574e-05, 'learning_rate/action_query_proj': 9.890246668845574e-05, 'learning_rate/base': 2.4725616672113935e-05, 'epoch': 0.53}) +[2026-07-27 09:09:28,627][starVLA.training.train_starvla][INFO] - Step 4342, Loss: {'train/loss': 0.2956560254096985, 'train/grad_norm_pre_clip': 6.821507453918457, 'timing/data': 0.00016989558935165405, 'timing/model': 0.458386467769742, 'learning_rate/action_model': 9.889604492928712e-05, 'learning_rate/action_query_proj': 9.889604492928712e-05, 'learning_rate/base': 2.472401123232178e-05, 'epoch': 0.53}) +[2026-07-27 09:09:34,140][starVLA.training.train_starvla][INFO] - Step 4343, Loss: {'train/loss': 0.1674765944480896, 'train/grad_norm_pre_clip': 4.88639497756958, 'timing/data': 0.00017121993005275726, 'timing/model': 0.4578191116452217, 'learning_rate/action_model': 9.888960465630267e-05, 'learning_rate/action_query_proj': 9.888960465630267e-05, 'learning_rate/base': 2.4722401164075667e-05, 'epoch': 0.53}) +[2026-07-27 09:09:39,699][starVLA.training.train_starvla][INFO] - Step 4344, Loss: {'train/loss': 0.06989579647779465, 'train/grad_norm_pre_clip': 2.823089361190796, 'timing/data': 0.00021771714091300964, 'timing/model': 0.4570552036166191, 'learning_rate/action_model': 9.888314587204488e-05, 'learning_rate/action_query_proj': 9.888314587204488e-05, 'learning_rate/base': 2.472078646801122e-05, 'epoch': 0.53}) +[2026-07-27 09:09:45,239][starVLA.training.train_starvla][INFO] - Step 4345, Loss: {'train/loss': 0.13147443532943726, 'train/grad_norm_pre_clip': 3.89250111579895, 'timing/data': 0.00016968697309494019, 'timing/model': 0.45701972022652626, 'learning_rate/action_model': 9.887666857906358e-05, 'learning_rate/action_query_proj': 9.887666857906358e-05, 'learning_rate/base': 2.4719167144765895e-05, 'epoch': 0.53}) +[2026-07-27 09:09:50,775][starVLA.training.train_starvla][INFO] - Step 4346, Loss: {'train/loss': 0.03253583982586861, 'train/grad_norm_pre_clip': 2.3819501399993896, 'timing/data': 0.00017462298274040222, 'timing/model': 0.4564961902797222, 'learning_rate/action_model': 9.887017277991591e-05, 'learning_rate/action_query_proj': 9.887017277991591e-05, 'learning_rate/base': 2.4717543194978978e-05, 'epoch': 0.53}) +[2026-07-27 09:09:56,319][starVLA.training.train_starvla][INFO] - Step 4347, Loss: {'train/loss': 0.055405180901288986, 'train/grad_norm_pre_clip': 2.8500287532806396, 'timing/data': 0.00016994215548038483, 'timing/model': 0.4568486977368593, 'learning_rate/action_model': 9.886365847716633e-05, 'learning_rate/action_query_proj': 9.886365847716633e-05, 'learning_rate/base': 2.471591461929158e-05, 'epoch': 0.53}) +[2026-07-27 09:10:01,880][starVLA.training.train_starvla][INFO] - Step 4348, Loss: {'train/loss': 0.07321343570947647, 'train/grad_norm_pre_clip': 3.9352409839630127, 'timing/data': 0.000173863023519516, 'timing/model': 0.4573513772338629, 'learning_rate/action_model': 9.885712567338654e-05, 'learning_rate/action_query_proj': 9.885712567338654e-05, 'learning_rate/base': 2.4714281418346635e-05, 'epoch': 0.53}) +[2026-07-27 09:10:07,416][starVLA.training.train_starvla][INFO] - Step 4349, Loss: {'train/loss': 0.16917918622493744, 'train/grad_norm_pre_clip': 5.854311466217041, 'timing/data': 0.0001759510487318039, 'timing/model': 0.4571491554379463, 'learning_rate/action_model': 9.885057437115561e-05, 'learning_rate/action_query_proj': 9.885057437115561e-05, 'learning_rate/base': 2.4712643592788902e-05, 'epoch': 0.53}) +[2026-07-27 09:10:12,938][starVLA.training.train_starvla][INFO] - Step 4350, Loss: {'train/loss': 0.11891203373670578, 'train/grad_norm_pre_clip': 4.756252765655518, 'timing/data': 0.00016804039478302002, 'timing/model': 0.4561348557472229, 'learning_rate/action_model': 9.884400457305988e-05, 'learning_rate/action_query_proj': 9.884400457305988e-05, 'learning_rate/base': 2.471100114326497e-05, 'epoch': 0.53}) +[2026-07-27 09:10:18,474][starVLA.training.train_starvla][INFO] - Step 4351, Loss: {'train/loss': 0.12243218719959259, 'train/grad_norm_pre_clip': 5.489739418029785, 'timing/data': 0.00028952769935131073, 'timing/model': 0.45724345184862614, 'learning_rate/action_model': 9.883741628169302e-05, 'learning_rate/action_query_proj': 9.883741628169302e-05, 'learning_rate/base': 2.4709354070423256e-05, 'epoch': 0.53}) +[2026-07-27 09:10:24,006][starVLA.training.train_starvla][INFO] - Step 4352, Loss: {'train/loss': 0.07941919565200806, 'train/grad_norm_pre_clip': 3.7957866191864014, 'timing/data': 0.0002849698066711426, 'timing/model': 0.45706911757588387, 'learning_rate/action_model': 9.883080949965597e-05, 'learning_rate/action_query_proj': 9.883080949965597e-05, 'learning_rate/base': 2.4707702374913994e-05, 'epoch': 0.53}) +[2026-07-27 09:10:29,531][starVLA.training.train_starvla][INFO] - Step 4353, Loss: {'train/loss': 0.10095463693141937, 'train/grad_norm_pre_clip': 3.6655499935150146, 'timing/data': 0.00017064251005649567, 'timing/model': 0.4567107670009136, 'learning_rate/action_model': 9.882418422955699e-05, 'learning_rate/action_query_proj': 9.882418422955699e-05, 'learning_rate/base': 2.4706046057389246e-05, 'epoch': 0.53}) +[2026-07-27 09:10:35,047][starVLA.training.train_starvla][INFO] - Step 4354, Loss: {'train/loss': 0.06631917506456375, 'train/grad_norm_pre_clip': 3.08540940284729, 'timing/data': 0.00017357617616653442, 'timing/model': 0.4566327780485153, 'learning_rate/action_model': 9.881754047401163e-05, 'learning_rate/action_query_proj': 9.881754047401163e-05, 'learning_rate/base': 2.4704385118502907e-05, 'epoch': 0.53}) +[2026-07-27 09:10:40,601][starVLA.training.train_starvla][INFO] - Step 4355, Loss: {'train/loss': 0.08020569384098053, 'train/grad_norm_pre_clip': 3.7605395317077637, 'timing/data': 0.00021245703101158142, 'timing/model': 0.4573850929737091, 'learning_rate/action_model': 9.881087823564272e-05, 'learning_rate/action_query_proj': 9.881087823564272e-05, 'learning_rate/base': 2.470271955891068e-05, 'epoch': 0.53}) +[2026-07-27 09:10:46,311][starVLA.training.train_starvla][INFO] - Step 4356, Loss: {'train/loss': 0.06839245557785034, 'train/grad_norm_pre_clip': 2.881334066390991, 'timing/data': 0.00021338462829589844, 'timing/model': 0.45621746219694614, 'learning_rate/action_model': 9.880419751708045e-05, 'learning_rate/action_query_proj': 9.880419751708045e-05, 'learning_rate/base': 2.4701049379270112e-05, 'epoch': 0.53}) +[2026-07-27 09:10:51,831][starVLA.training.train_starvla][INFO] - Step 4357, Loss: {'train/loss': 0.08960512280464172, 'train/grad_norm_pre_clip': 4.064594268798828, 'timing/data': 0.00028495676815509796, 'timing/model': 0.45703124813735485, 'learning_rate/action_model': 9.879749832096221e-05, 'learning_rate/action_query_proj': 9.879749832096221e-05, 'learning_rate/base': 2.4699374580240552e-05, 'epoch': 0.53}) +[2026-07-27 09:10:57,353][starVLA.training.train_starvla][INFO] - Step 4358, Loss: {'train/loss': 0.13912950456142426, 'train/grad_norm_pre_clip': 5.395590782165527, 'timing/data': 0.00017220526933670044, 'timing/model': 0.4560064375400543, 'learning_rate/action_model': 9.87907806499328e-05, 'learning_rate/action_query_proj': 9.87907806499328e-05, 'learning_rate/base': 2.46976951624832e-05, 'epoch': 0.53}) +[2026-07-27 09:11:02,882][starVLA.training.train_starvla][INFO] - Step 4359, Loss: {'train/loss': 0.06257840245962143, 'train/grad_norm_pre_clip': 2.6663665771484375, 'timing/data': 0.00017554499208927155, 'timing/model': 0.45765961334109306, 'learning_rate/action_model': 9.878404450664417e-05, 'learning_rate/action_query_proj': 9.878404450664417e-05, 'learning_rate/base': 2.4696011126661043e-05, 'epoch': 0.53}) +[2026-07-27 09:11:08,387][starVLA.training.train_starvla][INFO] - Step 4360, Loss: {'train/loss': 0.09784246236085892, 'train/grad_norm_pre_clip': 4.486693859100342, 'timing/data': 0.00017667189240455627, 'timing/model': 0.45754970982670784, 'learning_rate/action_model': 9.877728989375571e-05, 'learning_rate/action_query_proj': 9.877728989375571e-05, 'learning_rate/base': 2.4694322473438927e-05, 'epoch': 0.53}) +[2026-07-27 09:11:13,885][starVLA.training.train_starvla][INFO] - Step 4361, Loss: {'train/loss': 0.14240097999572754, 'train/grad_norm_pre_clip': 4.321312427520752, 'timing/data': 0.0001731589436531067, 'timing/model': 0.45896934159100056, 'learning_rate/action_model': 9.8770516813934e-05, 'learning_rate/action_query_proj': 9.8770516813934e-05, 'learning_rate/base': 2.46926292034835e-05, 'epoch': 0.53}) +[2026-07-27 09:11:19,384][starVLA.training.train_starvla][INFO] - Step 4362, Loss: {'train/loss': 0.09248056262731552, 'train/grad_norm_pre_clip': 3.0024335384368896, 'timing/data': 0.00016453862190246582, 'timing/model': 0.45739306323230267, 'learning_rate/action_model': 9.876372526985295e-05, 'learning_rate/action_query_proj': 9.876372526985295e-05, 'learning_rate/base': 2.4690931317463238e-05, 'epoch': 0.53}) +[2026-07-27 09:11:24,908][starVLA.training.train_starvla][INFO] - Step 4363, Loss: {'train/loss': 0.055235203355550766, 'train/grad_norm_pre_clip': 2.2257401943206787, 'timing/data': 0.00021381303668022156, 'timing/model': 0.4829133339226246, 'learning_rate/action_model': 9.875691526419377e-05, 'learning_rate/action_query_proj': 9.875691526419377e-05, 'learning_rate/base': 2.4689228816048442e-05, 'epoch': 0.53}) +[2026-07-27 09:11:30,422][starVLA.training.train_starvla][INFO] - Step 4364, Loss: {'train/loss': 0.12638485431671143, 'train/grad_norm_pre_clip': 4.07581901550293, 'timing/data': 0.0001716967672109604, 'timing/model': 0.4639841001480818, 'learning_rate/action_model': 9.875008679964492e-05, 'learning_rate/action_query_proj': 9.875008679964492e-05, 'learning_rate/base': 2.468752169991123e-05, 'epoch': 0.53}) +[2026-07-27 09:11:35,937][starVLA.training.train_starvla][INFO] - Step 4365, Loss: {'train/loss': 0.04581470414996147, 'train/grad_norm_pre_clip': 3.143193006515503, 'timing/data': 0.0001872275024652481, 'timing/model': 0.4586233664304018, 'learning_rate/action_model': 9.874323987890218e-05, 'learning_rate/action_query_proj': 9.874323987890218e-05, 'learning_rate/base': 2.4685809969725546e-05, 'epoch': 0.53}) +[2026-07-27 09:11:41,439][starVLA.training.train_starvla][INFO] - Step 4366, Loss: {'train/loss': 0.09268423169851303, 'train/grad_norm_pre_clip': 3.4977712631225586, 'timing/data': 0.00021566636860370636, 'timing/model': 0.46490687876939774, 'learning_rate/action_model': 9.873637450466862e-05, 'learning_rate/action_query_proj': 9.873637450466862e-05, 'learning_rate/base': 2.4684093626167155e-05, 'epoch': 0.53}) +[2026-07-27 09:11:46,956][starVLA.training.train_starvla][INFO] - Step 4367, Loss: {'train/loss': 0.0954197496175766, 'train/grad_norm_pre_clip': 3.7156083583831787, 'timing/data': 0.000189097598195076, 'timing/model': 0.46631441824138165, 'learning_rate/action_model': 9.872949067965455e-05, 'learning_rate/action_query_proj': 9.872949067965455e-05, 'learning_rate/base': 2.4682372669913638e-05, 'epoch': 0.53}) +[2026-07-27 09:11:52,463][starVLA.training.train_starvla][INFO] - Step 4368, Loss: {'train/loss': 0.14207784831523895, 'train/grad_norm_pre_clip': 4.625577926635742, 'timing/data': 0.0001790020614862442, 'timing/model': 0.4623249303549528, 'learning_rate/action_model': 9.872258840657762e-05, 'learning_rate/action_query_proj': 9.872258840657762e-05, 'learning_rate/base': 2.4680647101644405e-05, 'epoch': 0.53}) +[2026-07-27 09:11:57,987][starVLA.training.train_starvla][INFO] - Step 4369, Loss: {'train/loss': 0.08828169107437134, 'train/grad_norm_pre_clip': 4.091104507446289, 'timing/data': 0.00021724030375480652, 'timing/model': 0.46320035867393017, 'learning_rate/action_model': 9.871566768816274e-05, 'learning_rate/action_query_proj': 9.871566768816274e-05, 'learning_rate/base': 2.4678916922040685e-05, 'epoch': 0.53}) +[2026-07-27 09:12:03,520][starVLA.training.train_starvla][INFO] - Step 4370, Loss: {'train/loss': 0.13878630101680756, 'train/grad_norm_pre_clip': 3.3122482299804688, 'timing/data': 0.00022386573255062103, 'timing/model': 0.4624682553112507, 'learning_rate/action_model': 9.870872852714209e-05, 'learning_rate/action_query_proj': 9.870872852714209e-05, 'learning_rate/base': 2.4677182131785522e-05, 'epoch': 0.53}) +[2026-07-27 09:12:09,055][starVLA.training.train_starvla][INFO] - Step 4371, Loss: {'train/loss': 0.03697333484888077, 'train/grad_norm_pre_clip': 2.2166407108306885, 'timing/data': 0.00017091445624828339, 'timing/model': 0.4628807604312897, 'learning_rate/action_model': 9.870177092625513e-05, 'learning_rate/action_query_proj': 9.870177092625513e-05, 'learning_rate/base': 2.4675442731563782e-05, 'epoch': 0.53}) +[2026-07-27 09:12:14,580][starVLA.training.train_starvla][INFO] - Step 4372, Loss: {'train/loss': 0.09546351432800293, 'train/grad_norm_pre_clip': 3.172180414199829, 'timing/data': 0.0002631526440382004, 'timing/model': 0.463063707575202, 'learning_rate/action_model': 9.869479488824861e-05, 'learning_rate/action_query_proj': 9.869479488824861e-05, 'learning_rate/base': 2.4673698722062152e-05, 'epoch': 0.53}) +[2026-07-27 09:12:20,110][starVLA.training.train_starvla][INFO] - Step 4373, Loss: {'train/loss': 0.03477292135357857, 'train/grad_norm_pre_clip': 1.6098688840866089, 'timing/data': 0.00017860159277915955, 'timing/model': 0.46311855129897594, 'learning_rate/action_model': 9.868780041587659e-05, 'learning_rate/action_query_proj': 9.868780041587659e-05, 'learning_rate/base': 2.4671950103969147e-05, 'epoch': 0.53}) +[2026-07-27 09:12:25,636][starVLA.training.train_starvla][INFO] - Step 4374, Loss: {'train/loss': 0.17260296642780304, 'train/grad_norm_pre_clip': 4.560722351074219, 'timing/data': 0.00021818466484546661, 'timing/model': 0.4642470180988312, 'learning_rate/action_model': 9.868078751190035e-05, 'learning_rate/action_query_proj': 9.868078751190035e-05, 'learning_rate/base': 2.4670196877975087e-05, 'epoch': 0.53}) +[2026-07-27 09:12:31,477][starVLA.training.train_starvla][INFO] - Step 4375, Loss: {'train/loss': 0.1130138486623764, 'train/grad_norm_pre_clip': 4.4625396728515625, 'timing/data': 0.00017433799803256989, 'timing/model': 0.4572515320032835, 'learning_rate/action_model': 9.867375617908848e-05, 'learning_rate/action_query_proj': 9.867375617908848e-05, 'learning_rate/base': 2.466843904477212e-05, 'epoch': 0.53}) +[2026-07-27 09:12:37,015][starVLA.training.train_starvla][INFO] - Step 4376, Loss: {'train/loss': 0.05729373171925545, 'train/grad_norm_pre_clip': 3.260432004928589, 'timing/data': 0.00017529912292957306, 'timing/model': 0.4667273759841919, 'learning_rate/action_model': 9.866670642021684e-05, 'learning_rate/action_query_proj': 9.866670642021684e-05, 'learning_rate/base': 2.466667660505421e-05, 'epoch': 0.53}) +[2026-07-27 09:12:42,566][starVLA.training.train_starvla][INFO] - Step 4377, Loss: {'train/loss': 0.05463666468858719, 'train/grad_norm_pre_clip': 2.851907968521118, 'timing/data': 0.00018029473721981049, 'timing/model': 0.46250998228788376, 'learning_rate/action_model': 9.865963823806857e-05, 'learning_rate/action_query_proj': 9.865963823806857e-05, 'learning_rate/base': 2.4664909559517144e-05, 'epoch': 0.53}) +[2026-07-27 09:12:48,093][starVLA.training.train_starvla][INFO] - Step 4378, Loss: {'train/loss': 0.15694478154182434, 'train/grad_norm_pre_clip': 5.947459697723389, 'timing/data': 0.00018227286636829376, 'timing/model': 0.46407143771648407, 'learning_rate/action_model': 9.865255163543406e-05, 'learning_rate/action_query_proj': 9.865255163543406e-05, 'learning_rate/base': 2.4663137908858515e-05, 'epoch': 0.53}) +[2026-07-27 09:12:53,648][starVLA.training.train_starvla][INFO] - Step 4379, Loss: {'train/loss': 0.08301804214715958, 'train/grad_norm_pre_clip': 3.5134952068328857, 'timing/data': 0.000177847221493721, 'timing/model': 0.4658008571714163, 'learning_rate/action_model': 9.864544661511101e-05, 'learning_rate/action_query_proj': 9.864544661511101e-05, 'learning_rate/base': 2.4661361653777753e-05, 'epoch': 0.53}) +[2026-07-27 09:12:59,167][starVLA.training.train_starvla][INFO] - Step 4380, Loss: {'train/loss': 0.04825381189584732, 'train/grad_norm_pre_clip': 1.587965965270996, 'timing/data': 0.0001851152628660202, 'timing/model': 0.46428481489419937, 'learning_rate/action_model': 9.863832317990436e-05, 'learning_rate/action_query_proj': 9.863832317990436e-05, 'learning_rate/base': 2.465958079497609e-05, 'epoch': 0.53}) +[2026-07-27 09:13:04,788][starVLA.training.train_starvla][INFO] - Step 4381, Loss: {'train/loss': 0.07008537650108337, 'train/grad_norm_pre_clip': 2.7925100326538086, 'timing/data': 0.00017593055963516235, 'timing/model': 0.4643152467906475, 'learning_rate/action_model': 9.863118133262632e-05, 'learning_rate/action_query_proj': 9.863118133262632e-05, 'learning_rate/base': 2.465779533315658e-05, 'epoch': 0.53}) +[2026-07-27 09:13:10,299][starVLA.training.train_starvla][INFO] - Step 4382, Loss: {'train/loss': 0.07175686955451965, 'train/grad_norm_pre_clip': 3.25049090385437, 'timing/data': 0.00018233060836791992, 'timing/model': 0.4630397502332926, 'learning_rate/action_model': 9.862402107609638e-05, 'learning_rate/action_query_proj': 9.862402107609638e-05, 'learning_rate/base': 2.4656005269024094e-05, 'epoch': 0.53}) +[2026-07-27 09:13:15,813][starVLA.training.train_starvla][INFO] - Step 4383, Loss: {'train/loss': 0.10523603856563568, 'train/grad_norm_pre_clip': 5.227493762969971, 'timing/data': 0.00017924606800079346, 'timing/model': 0.46391854621469975, 'learning_rate/action_model': 9.86168424131413e-05, 'learning_rate/action_query_proj': 9.86168424131413e-05, 'learning_rate/base': 2.4654210603285325e-05, 'epoch': 0.53}) +[2026-07-27 09:13:21,314][starVLA.training.train_starvla][INFO] - Step 4384, Loss: {'train/loss': 0.08176188170909882, 'train/grad_norm_pre_clip': 3.2895100116729736, 'timing/data': 0.0001691095530986786, 'timing/model': 0.46238469891250134, 'learning_rate/action_model': 9.860964534659511e-05, 'learning_rate/action_query_proj': 9.860964534659511e-05, 'learning_rate/base': 2.4652411336648777e-05, 'epoch': 0.53}) +[2026-07-27 09:13:26,819][starVLA.training.train_starvla][INFO] - Step 4385, Loss: {'train/loss': 0.07809917628765106, 'train/grad_norm_pre_clip': 4.579872131347656, 'timing/data': 0.00018299557268619537, 'timing/model': 0.4635278917849064, 'learning_rate/action_model': 9.86024298792991e-05, 'learning_rate/action_query_proj': 9.86024298792991e-05, 'learning_rate/base': 2.4650607469824774e-05, 'epoch': 0.53}) +[2026-07-27 09:13:32,323][starVLA.training.train_starvla][INFO] - Step 4386, Loss: {'train/loss': 0.058841265738010406, 'train/grad_norm_pre_clip': 2.9331822395324707, 'timing/data': 0.00022182613611221313, 'timing/model': 0.46339267306029797, 'learning_rate/action_model': 9.85951960141018e-05, 'learning_rate/action_query_proj': 9.85951960141018e-05, 'learning_rate/base': 2.464879900352545e-05, 'epoch': 0.53}) +[2026-07-27 09:13:37,825][starVLA.training.train_starvla][INFO] - Step 4387, Loss: {'train/loss': 0.05829524248838425, 'train/grad_norm_pre_clip': 3.387969493865967, 'timing/data': 0.00017727352678775787, 'timing/model': 0.464245880022645, 'learning_rate/action_model': 9.858794375385903e-05, 'learning_rate/action_query_proj': 9.858794375385903e-05, 'learning_rate/base': 2.464698593846476e-05, 'epoch': 0.53}) +[2026-07-27 09:13:43,328][starVLA.training.train_starvla][INFO] - Step 4388, Loss: {'train/loss': 0.10336431860923767, 'train/grad_norm_pre_clip': 3.695775270462036, 'timing/data': 0.00017913803458213806, 'timing/model': 0.4630743470042944, 'learning_rate/action_model': 9.85806731014339e-05, 'learning_rate/action_query_proj': 9.85806731014339e-05, 'learning_rate/base': 2.4645168275358476e-05, 'epoch': 0.53}) +[2026-07-27 09:13:49,087][starVLA.training.train_starvla][INFO] - Step 4389, Loss: {'train/loss': 0.04347386211156845, 'train/grad_norm_pre_clip': 2.738708257675171, 'timing/data': 0.00018179044127464294, 'timing/model': 0.46318544074893, 'learning_rate/action_model': 9.857338405969672e-05, 'learning_rate/action_query_proj': 9.857338405969672e-05, 'learning_rate/base': 2.464334601492418e-05, 'epoch': 0.53}) +[2026-07-27 09:13:54,612][starVLA.training.train_starvla][INFO] - Step 4390, Loss: {'train/loss': 0.0382467582821846, 'train/grad_norm_pre_clip': 2.4889590740203857, 'timing/data': 0.00016955286264419556, 'timing/model': 0.4642068073153496, 'learning_rate/action_model': 9.856607663152508e-05, 'learning_rate/action_query_proj': 9.856607663152508e-05, 'learning_rate/base': 2.464151915788127e-05, 'epoch': 0.53}) +[2026-07-27 09:14:00,373][starVLA.training.train_starvla][INFO] - Step 4391, Loss: {'train/loss': 0.1858009397983551, 'train/grad_norm_pre_clip': 5.846778869628906, 'timing/data': 0.00017673149704933167, 'timing/model': 0.4633017089217901, 'learning_rate/action_model': 9.855875081980387e-05, 'learning_rate/action_query_proj': 9.855875081980387e-05, 'learning_rate/base': 2.4639687704950968e-05, 'epoch': 0.53}) +[2026-07-27 09:14:05,870][starVLA.training.train_starvla][INFO] - Step 4392, Loss: {'train/loss': 0.11490514874458313, 'train/grad_norm_pre_clip': 3.709303617477417, 'timing/data': 0.00016758963465690613, 'timing/model': 0.46649020723998547, 'learning_rate/action_model': 9.855140662742517e-05, 'learning_rate/action_query_proj': 9.855140662742517e-05, 'learning_rate/base': 2.4637851656856293e-05, 'epoch': 0.53}) +[2026-07-27 09:14:11,387][starVLA.training.train_starvla][INFO] - Step 4393, Loss: {'train/loss': 0.08775800466537476, 'train/grad_norm_pre_clip': 4.32657527923584, 'timing/data': 0.0001874919980764389, 'timing/model': 0.464207598939538, 'learning_rate/action_model': 9.854404405728837e-05, 'learning_rate/action_query_proj': 9.854404405728837e-05, 'learning_rate/base': 2.4636011014322093e-05, 'epoch': 0.53}) +[2026-07-27 09:14:16,902][starVLA.training.train_starvla][INFO] - Step 4394, Loss: {'train/loss': 0.07941026985645294, 'train/grad_norm_pre_clip': 4.055601596832275, 'timing/data': 0.0001690555363893509, 'timing/model': 0.4644126035273075, 'learning_rate/action_model': 9.85366631123001e-05, 'learning_rate/action_query_proj': 9.85366631123001e-05, 'learning_rate/base': 2.4634165778075026e-05, 'epoch': 0.53}) +[2026-07-27 09:14:22,414][starVLA.training.train_starvla][INFO] - Step 4395, Loss: {'train/loss': 0.1077038049697876, 'train/grad_norm_pre_clip': 4.637613296508789, 'timing/data': 0.00017330050468444824, 'timing/model': 0.4636901281774044, 'learning_rate/action_model': 9.852926379537421e-05, 'learning_rate/action_query_proj': 9.852926379537421e-05, 'learning_rate/base': 2.4632315948843552e-05, 'epoch': 0.53}) +[2026-07-27 09:14:27,926][starVLA.training.train_starvla][INFO] - Step 4396, Loss: {'train/loss': 0.08037119358778, 'train/grad_norm_pre_clip': 2.5824129581451416, 'timing/data': 0.00017610378563404083, 'timing/model': 0.465153930708766, 'learning_rate/action_model': 9.852184610943185e-05, 'learning_rate/action_query_proj': 9.852184610943185e-05, 'learning_rate/base': 2.4630461527357964e-05, 'epoch': 0.53}) +[2026-07-27 09:14:33,438][starVLA.training.train_starvla][INFO] - Step 4397, Loss: {'train/loss': 0.05576709657907486, 'train/grad_norm_pre_clip': 3.1397972106933594, 'timing/data': 0.0002170167863368988, 'timing/model': 0.4634483978152275, 'learning_rate/action_model': 9.851441005740144e-05, 'learning_rate/action_query_proj': 9.851441005740144e-05, 'learning_rate/base': 2.462860251435036e-05, 'epoch': 0.53}) +[2026-07-27 09:14:38,950][starVLA.training.train_starvla][INFO] - Step 4398, Loss: {'train/loss': 0.013286709785461426, 'train/grad_norm_pre_clip': 0.9041352272033691, 'timing/data': 0.00018275529146194458, 'timing/model': 0.46445775032043457, 'learning_rate/action_model': 9.850695564221858e-05, 'learning_rate/action_query_proj': 9.850695564221858e-05, 'learning_rate/base': 2.4626738910554645e-05, 'epoch': 0.53}) +[2026-07-27 09:14:44,464][starVLA.training.train_starvla][INFO] - Step 4399, Loss: {'train/loss': 0.07091492414474487, 'train/grad_norm_pre_clip': 2.2187936305999756, 'timing/data': 0.0001781471073627472, 'timing/model': 0.4643989633768797, 'learning_rate/action_model': 9.849948286682615e-05, 'learning_rate/action_query_proj': 9.849948286682615e-05, 'learning_rate/base': 2.4624870716706537e-05, 'epoch': 0.53}) +[2026-07-27 09:14:49,975][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 4400 +[2026-07-27 09:14:49,976][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 4400 +[2026-07-27 09:14:49,976][starVLA.training.train_starvla][INFO] - Step 4400, Loss: {'train/loss': 0.1508062481880188, 'train/grad_norm_pre_clip': 5.598658084869385, 'timing/data': 0.000217316672205925, 'timing/model': 0.46337244287133217, 'learning_rate/action_model': 9.849199173417429e-05, 'learning_rate/action_query_proj': 9.849199173417429e-05, 'learning_rate/base': 2.4622997933543573e-05, 'epoch': 0.53}) +[2026-07-27 09:14:55,507][starVLA.training.train_starvla][INFO] - Step 4401, Loss: {'train/loss': 0.1509154886007309, 'train/grad_norm_pre_clip': 3.695474624633789, 'timing/data': 0.00017506815493106842, 'timing/model': 0.46518155187368393, 'learning_rate/action_model': 9.84844822472204e-05, 'learning_rate/action_query_proj': 9.84844822472204e-05, 'learning_rate/base': 2.46211205618051e-05, 'epoch': 0.53}) +[2026-07-27 09:15:01,012][starVLA.training.train_starvla][INFO] - Step 4402, Loss: {'train/loss': 0.050224918872117996, 'train/grad_norm_pre_clip': 2.539328098297119, 'timing/data': 0.00018168799579143524, 'timing/model': 0.4642919022589922, 'learning_rate/action_model': 9.847695440892908e-05, 'learning_rate/action_query_proj': 9.847695440892908e-05, 'learning_rate/base': 2.461923860223227e-05, 'epoch': 0.53}) +[2026-07-27 09:15:06,531][starVLA.training.train_starvla][INFO] - Step 4403, Loss: {'train/loss': 0.07848303020000458, 'train/grad_norm_pre_clip': 4.060723781585693, 'timing/data': 0.00017492100596427917, 'timing/model': 0.4615285899490118, 'learning_rate/action_model': 9.846940822227222e-05, 'learning_rate/action_query_proj': 9.846940822227222e-05, 'learning_rate/base': 2.4617352055568056e-05, 'epoch': 0.53}) +[2026-07-27 09:15:12,063][starVLA.training.train_starvla][INFO] - Step 4404, Loss: {'train/loss': 0.018637197092175484, 'train/grad_norm_pre_clip': 1.4075285196304321, 'timing/data': 0.00018147192895412445, 'timing/model': 0.4618038795888424, 'learning_rate/action_model': 9.846184369022893e-05, 'learning_rate/action_query_proj': 9.846184369022893e-05, 'learning_rate/base': 2.4615460922557233e-05, 'epoch': 0.53}) +[2026-07-27 09:15:17,622][starVLA.training.train_starvla][INFO] - Step 4405, Loss: {'train/loss': 0.14397874474525452, 'train/grad_norm_pre_clip': 4.599259853363037, 'timing/data': 0.00017959997057914734, 'timing/model': 0.46258990094065666, 'learning_rate/action_model': 9.845426081578554e-05, 'learning_rate/action_query_proj': 9.845426081578554e-05, 'learning_rate/base': 2.4613565203946386e-05, 'epoch': 0.53}) +[2026-07-27 09:15:23,211][starVLA.training.train_starvla][INFO] - Step 4406, Loss: {'train/loss': 0.05650730058550835, 'train/grad_norm_pre_clip': 2.231534957885742, 'timing/data': 0.00018344447016716003, 'timing/model': 0.4633157141506672, 'learning_rate/action_model': 9.844665960193569e-05, 'learning_rate/action_query_proj': 9.844665960193569e-05, 'learning_rate/base': 2.4611664900483923e-05, 'epoch': 0.53}) +[2026-07-27 09:15:28,717][starVLA.training.train_starvla][INFO] - Step 4407, Loss: {'train/loss': 0.11553959548473358, 'train/grad_norm_pre_clip': 3.333272933959961, 'timing/data': 0.00017284415662288666, 'timing/model': 0.46220253594219685, 'learning_rate/action_model': 9.84390400516802e-05, 'learning_rate/action_query_proj': 9.84390400516802e-05, 'learning_rate/base': 2.460976001292005e-05, 'epoch': 0.53}) +[2026-07-27 09:15:34,425][starVLA.training.train_starvla][INFO] - Step 4408, Loss: {'train/loss': 0.06405530124902725, 'train/grad_norm_pre_clip': 2.8613295555114746, 'timing/data': 0.0001829061657190323, 'timing/model': 0.4630694705992937, 'learning_rate/action_model': 9.843140216802716e-05, 'learning_rate/action_query_proj': 9.843140216802716e-05, 'learning_rate/base': 2.460785054200679e-05, 'epoch': 0.53}) +[2026-07-27 09:15:39,940][starVLA.training.train_starvla][INFO] - Step 4409, Loss: {'train/loss': 0.07059808820486069, 'train/grad_norm_pre_clip': 3.5513923168182373, 'timing/data': 0.0001725759357213974, 'timing/model': 0.4616469256579876, 'learning_rate/action_model': 9.842374595399187e-05, 'learning_rate/action_query_proj': 9.842374595399187e-05, 'learning_rate/base': 2.4605936488497968e-05, 'epoch': 0.53}) +[2026-07-27 09:15:45,472][starVLA.training.train_starvla][INFO] - Step 4410, Loss: {'train/loss': 0.09508340060710907, 'train/grad_norm_pre_clip': 4.808271408081055, 'timing/data': 0.00016350112855434418, 'timing/model': 0.46022411249578, 'learning_rate/action_model': 9.841607141259689e-05, 'learning_rate/action_query_proj': 9.841607141259689e-05, 'learning_rate/base': 2.4604017853149223e-05, 'epoch': 0.53}) +[2026-07-27 09:15:50,986][starVLA.training.train_starvla][INFO] - Step 4411, Loss: {'train/loss': 0.1139015406370163, 'train/grad_norm_pre_clip': 5.278570652008057, 'timing/data': 0.00017201155424118042, 'timing/model': 0.4630022030323744, 'learning_rate/action_model': 9.840837854687199e-05, 'learning_rate/action_query_proj': 9.840837854687199e-05, 'learning_rate/base': 2.4602094636717997e-05, 'epoch': 0.54}) +[2026-07-27 09:15:56,495][starVLA.training.train_starvla][INFO] - Step 4412, Loss: {'train/loss': 0.10869035124778748, 'train/grad_norm_pre_clip': 4.096101760864258, 'timing/data': 0.00016800500452518463, 'timing/model': 0.46277054585516453, 'learning_rate/action_model': 9.840066735985422e-05, 'learning_rate/action_query_proj': 9.840066735985422e-05, 'learning_rate/base': 2.4600166839963555e-05, 'epoch': 0.54}) +[2026-07-27 09:16:01,996][starVLA.training.train_starvla][INFO] - Step 4413, Loss: {'train/loss': 0.04219251871109009, 'train/grad_norm_pre_clip': 2.491952419281006, 'timing/data': 0.00017318874597549438, 'timing/model': 0.4612937215715647, 'learning_rate/action_model': 9.839293785458783e-05, 'learning_rate/action_query_proj': 9.839293785458783e-05, 'learning_rate/base': 2.4598234463646957e-05, 'epoch': 0.54}) +[2026-07-27 09:16:07,512][starVLA.training.train_starvla][INFO] - Step 4414, Loss: {'train/loss': 0.20154786109924316, 'train/grad_norm_pre_clip': 5.503162860870361, 'timing/data': 0.00016872771084308624, 'timing/model': 0.463264811784029, 'learning_rate/action_model': 9.838519003412427e-05, 'learning_rate/action_query_proj': 9.838519003412427e-05, 'learning_rate/base': 2.459629750853107e-05, 'epoch': 0.54}) +[2026-07-27 09:16:13,034][starVLA.training.train_starvla][INFO] - Step 4415, Loss: {'train/loss': 0.08989463001489639, 'train/grad_norm_pre_clip': 3.0454769134521484, 'timing/data': 0.00016562454402446747, 'timing/model': 0.4594631567597389, 'learning_rate/action_model': 9.837742390152232e-05, 'learning_rate/action_query_proj': 9.837742390152232e-05, 'learning_rate/base': 2.459435597538058e-05, 'epoch': 0.54}) +[2026-07-27 09:16:18,535][starVLA.training.train_starvla][INFO] - Step 4416, Loss: {'train/loss': 0.023321185261011124, 'train/grad_norm_pre_clip': 1.5470014810562134, 'timing/data': 0.00025235675275325775, 'timing/model': 0.45724285766482353, 'learning_rate/action_model': 9.836963945984786e-05, 'learning_rate/action_query_proj': 9.836963945984786e-05, 'learning_rate/base': 2.4592409864961965e-05, 'epoch': 0.54}) +[2026-07-27 09:16:24,044][starVLA.training.train_starvla][INFO] - Step 4417, Loss: {'train/loss': 0.06576745957136154, 'train/grad_norm_pre_clip': 2.7171664237976074, 'timing/data': 0.0001655053347349167, 'timing/model': 0.4571973215788603, 'learning_rate/action_model': 9.83618367121741e-05, 'learning_rate/action_query_proj': 9.83618367121741e-05, 'learning_rate/base': 2.4590459178043526e-05, 'epoch': 0.54}) +[2026-07-27 09:16:29,547][starVLA.training.train_starvla][INFO] - Step 4418, Loss: {'train/loss': 0.1189715638756752, 'train/grad_norm_pre_clip': 3.3698158264160156, 'timing/data': 0.00017216429114341736, 'timing/model': 0.4583758972585201, 'learning_rate/action_model': 9.835401566158145e-05, 'learning_rate/action_query_proj': 9.835401566158145e-05, 'learning_rate/base': 2.4588503915395362e-05, 'epoch': 0.54}) +[2026-07-27 09:16:35,053][starVLA.training.train_starvla][INFO] - Step 4419, Loss: {'train/loss': 0.06413473188877106, 'train/grad_norm_pre_clip': 2.788412570953369, 'timing/data': 0.00017509981989860535, 'timing/model': 0.45693982392549515, 'learning_rate/action_model': 9.834617631115751e-05, 'learning_rate/action_query_proj': 9.834617631115751e-05, 'learning_rate/base': 2.4586544077789378e-05, 'epoch': 0.54}) +[2026-07-27 09:16:40,554][starVLA.training.train_starvla][INFO] - Step 4420, Loss: {'train/loss': 0.0870899111032486, 'train/grad_norm_pre_clip': 4.234711647033691, 'timing/data': 0.00017430074512958527, 'timing/model': 0.4562279786914587, 'learning_rate/action_model': 9.833831866399716e-05, 'learning_rate/action_query_proj': 9.833831866399716e-05, 'learning_rate/base': 2.458457966599929e-05, 'epoch': 0.54}) +[2026-07-27 09:16:46,109][starVLA.training.train_starvla][INFO] - Step 4421, Loss: {'train/loss': 0.022032640874385834, 'train/grad_norm_pre_clip': 1.0620205402374268, 'timing/data': 0.00018288567662239075, 'timing/model': 0.4680449292063713, 'learning_rate/action_model': 9.833044272320245e-05, 'learning_rate/action_query_proj': 9.833044272320245e-05, 'learning_rate/base': 2.4582610680800612e-05, 'epoch': 0.54}) +[2026-07-27 09:16:51,681][starVLA.training.train_starvla][INFO] - Step 4422, Loss: {'train/loss': 0.05456814914941788, 'train/grad_norm_pre_clip': 2.906360149383545, 'timing/data': 0.0001734476536512375, 'timing/model': 0.4640545882284641, 'learning_rate/action_model': 9.832254849188268e-05, 'learning_rate/action_query_proj': 9.832254849188268e-05, 'learning_rate/base': 2.458063712297067e-05, 'epoch': 0.54}) +[2026-07-27 09:16:57,252][starVLA.training.train_starvla][INFO] - Step 4423, Loss: {'train/loss': 0.12057480216026306, 'train/grad_norm_pre_clip': 3.1166834831237793, 'timing/data': 0.00018268823623657227, 'timing/model': 0.46180165372788906, 'learning_rate/action_model': 9.831463597315437e-05, 'learning_rate/action_query_proj': 9.831463597315437e-05, 'learning_rate/base': 2.4578658993288592e-05, 'epoch': 0.54}) +[2026-07-27 09:17:02,805][starVLA.training.train_starvla][INFO] - Step 4424, Loss: {'train/loss': 0.18468178808689117, 'train/grad_norm_pre_clip': 5.457401752471924, 'timing/data': 0.00017539411783218384, 'timing/model': 0.45839244313538074, 'learning_rate/action_model': 9.830670517014126e-05, 'learning_rate/action_query_proj': 9.830670517014126e-05, 'learning_rate/base': 2.4576676292535316e-05, 'epoch': 0.54}) +[2026-07-27 09:17:08,332][starVLA.training.train_starvla][INFO] - Step 4425, Loss: {'train/loss': 0.06082054227590561, 'train/grad_norm_pre_clip': 3.1681156158447266, 'timing/data': 0.00017377547919750214, 'timing/model': 0.4567516855895519, 'learning_rate/action_model': 9.82987560859743e-05, 'learning_rate/action_query_proj': 9.82987560859743e-05, 'learning_rate/base': 2.4574689021493577e-05, 'epoch': 0.54}) +[2026-07-27 09:17:13,850][starVLA.training.train_starvla][INFO] - Step 4426, Loss: {'train/loss': 0.13974012434482574, 'train/grad_norm_pre_clip': 4.365804195404053, 'timing/data': 0.00018023326992988586, 'timing/model': 0.4630459677428007, 'learning_rate/action_model': 9.829078872379169e-05, 'learning_rate/action_query_proj': 9.829078872379169e-05, 'learning_rate/base': 2.4572697180947923e-05, 'epoch': 0.54}) +[2026-07-27 09:17:19,350][starVLA.training.train_starvla][INFO] - Step 4427, Loss: {'train/loss': 0.1635187864303589, 'train/grad_norm_pre_clip': 5.046010971069336, 'timing/data': 0.00018289126455783844, 'timing/model': 0.45795993879437447, 'learning_rate/action_model': 9.828280308673878e-05, 'learning_rate/action_query_proj': 9.828280308673878e-05, 'learning_rate/base': 2.4570700771684696e-05, 'epoch': 0.54}) +[2026-07-27 09:17:24,847][starVLA.training.train_starvla][INFO] - Step 4428, Loss: {'train/loss': 0.0737445279955864, 'train/grad_norm_pre_clip': 3.1206767559051514, 'timing/data': 0.00029435940086841583, 'timing/model': 0.45756377652287483, 'learning_rate/action_model': 9.82747991779682e-05, 'learning_rate/action_query_proj': 9.82747991779682e-05, 'learning_rate/base': 2.456869979449205e-05, 'epoch': 0.54}) +[2026-07-27 09:17:30,348][starVLA.training.train_starvla][INFO] - Step 4429, Loss: {'train/loss': 0.12561389803886414, 'train/grad_norm_pre_clip': 3.431210994720459, 'timing/data': 0.00016389787197113037, 'timing/model': 0.4567862208932638, 'learning_rate/action_model': 9.826677700063977e-05, 'learning_rate/action_query_proj': 9.826677700063977e-05, 'learning_rate/base': 2.4566694250159943e-05, 'epoch': 0.54}) +[2026-07-27 09:17:35,849][starVLA.training.train_starvla][INFO] - Step 4430, Loss: {'train/loss': 0.0518166646361351, 'train/grad_norm_pre_clip': 2.279481887817383, 'timing/data': 0.00017892196774482727, 'timing/model': 0.4628014750778675, 'learning_rate/action_model': 9.825873655792047e-05, 'learning_rate/action_query_proj': 9.825873655792047e-05, 'learning_rate/base': 2.4564684139480118e-05, 'epoch': 0.54}) +[2026-07-27 09:17:41,352][starVLA.training.train_starvla][INFO] - Step 4431, Loss: {'train/loss': 0.07525713741779327, 'train/grad_norm_pre_clip': 3.250121831893921, 'timing/data': 0.00021145492792129517, 'timing/model': 0.46200774423778057, 'learning_rate/action_model': 9.825067785298459e-05, 'learning_rate/action_query_proj': 9.825067785298459e-05, 'learning_rate/base': 2.4562669463246147e-05, 'epoch': 0.54}) +[2026-07-27 09:17:46,862][starVLA.training.train_starvla][INFO] - Step 4432, Loss: {'train/loss': 0.04274649918079376, 'train/grad_norm_pre_clip': 2.360435724258423, 'timing/data': 0.00017482787370681763, 'timing/model': 0.46024541929364204, 'learning_rate/action_model': 9.824260088901355e-05, 'learning_rate/action_query_proj': 9.824260088901355e-05, 'learning_rate/base': 2.456065022225339e-05, 'epoch': 0.54}) +[2026-07-27 09:17:52,370][starVLA.training.train_starvla][INFO] - Step 4433, Loss: {'train/loss': 0.06351228058338165, 'train/grad_norm_pre_clip': 3.335322856903076, 'timing/data': 0.00017127953469753265, 'timing/model': 0.46011404506862164, 'learning_rate/action_model': 9.823450566919606e-05, 'learning_rate/action_query_proj': 9.823450566919606e-05, 'learning_rate/base': 2.4558626417299015e-05, 'epoch': 0.54}) +[2026-07-27 09:17:58,143][starVLA.training.train_starvla][INFO] - Step 4434, Loss: {'train/loss': 0.0657297819852829, 'train/grad_norm_pre_clip': 2.610755443572998, 'timing/data': 0.00017128698527812958, 'timing/model': 0.4623984545469284, 'learning_rate/action_model': 9.82263921967279e-05, 'learning_rate/action_query_proj': 9.82263921967279e-05, 'learning_rate/base': 2.4556598049181975e-05, 'epoch': 0.54}) +[2026-07-27 09:18:03,643][starVLA.training.train_starvla][INFO] - Step 4435, Loss: {'train/loss': 0.07814739644527435, 'train/grad_norm_pre_clip': 3.380272388458252, 'timing/data': 0.00017209909856319427, 'timing/model': 0.4620658662170172, 'learning_rate/action_model': 9.821826047481222e-05, 'learning_rate/action_query_proj': 9.821826047481222e-05, 'learning_rate/base': 2.4554565118703056e-05, 'epoch': 0.54}) +[2026-07-27 09:18:09,403][starVLA.training.train_starvla][INFO] - Step 4436, Loss: {'train/loss': 0.10497458279132843, 'train/grad_norm_pre_clip': 2.815945863723755, 'timing/data': 0.00017171911895275116, 'timing/model': 0.46255808509886265, 'learning_rate/action_model': 9.821011050665924e-05, 'learning_rate/action_query_proj': 9.821011050665924e-05, 'learning_rate/base': 2.455252762666481e-05, 'epoch': 0.54}) +[2026-07-27 09:18:14,910][starVLA.training.train_starvla][INFO] - Step 4437, Loss: {'train/loss': 0.09615527838468552, 'train/grad_norm_pre_clip': 3.762356758117676, 'timing/data': 0.00017008930444717407, 'timing/model': 0.4599500857293606, 'learning_rate/action_model': 9.820194229548645e-05, 'learning_rate/action_query_proj': 9.820194229548645e-05, 'learning_rate/base': 2.4550485573871612e-05, 'epoch': 0.54}) +[2026-07-27 09:18:20,430][starVLA.training.train_starvla][INFO] - Step 4438, Loss: {'train/loss': 0.1514347493648529, 'train/grad_norm_pre_clip': 4.040834903717041, 'timing/data': 0.00017931684851646423, 'timing/model': 0.4629803355783224, 'learning_rate/action_model': 9.819375584451857e-05, 'learning_rate/action_query_proj': 9.819375584451857e-05, 'learning_rate/base': 2.454843896112964e-05, 'epoch': 0.54}) +[2026-07-27 09:18:25,945][starVLA.training.train_starvla][INFO] - Step 4439, Loss: {'train/loss': 0.0656035989522934, 'train/grad_norm_pre_clip': 3.2526726722717285, 'timing/data': 0.0001697242259979248, 'timing/model': 0.4604206793010235, 'learning_rate/action_model': 9.818555115698742e-05, 'learning_rate/action_query_proj': 9.818555115698742e-05, 'learning_rate/base': 2.4546387789246856e-05, 'epoch': 0.54}) +[2026-07-27 09:18:31,451][starVLA.training.train_starvla][INFO] - Step 4440, Loss: {'train/loss': 0.15581542253494263, 'train/grad_norm_pre_clip': 3.710493326187134, 'timing/data': 0.0001738220453262329, 'timing/model': 0.4640745911747217, 'learning_rate/action_model': 9.817732823613213e-05, 'learning_rate/action_query_proj': 9.817732823613213e-05, 'learning_rate/base': 2.4544332059033032e-05, 'epoch': 0.54}) +[2026-07-27 09:18:37,039][starVLA.training.train_starvla][INFO] - Step 4441, Loss: {'train/loss': 0.06298653781414032, 'train/grad_norm_pre_clip': 2.438112258911133, 'timing/data': 0.00016994401812553406, 'timing/model': 0.4637583028525114, 'learning_rate/action_model': 9.816908708519896e-05, 'learning_rate/action_query_proj': 9.816908708519896e-05, 'learning_rate/base': 2.454227177129974e-05, 'epoch': 0.54}) +[2026-07-27 09:18:42,558][starVLA.training.train_starvla][INFO] - Step 4442, Loss: {'train/loss': 0.1433895081281662, 'train/grad_norm_pre_clip': 4.289332866668701, 'timing/data': 0.00017502903938293457, 'timing/model': 0.4646473154425621, 'learning_rate/action_model': 9.816082770744137e-05, 'learning_rate/action_query_proj': 9.816082770744137e-05, 'learning_rate/base': 2.4540206926860343e-05, 'epoch': 0.54}) +[2026-07-27 09:18:48,068][starVLA.training.train_starvla][INFO] - Step 4443, Loss: {'train/loss': 0.05041927099227905, 'train/grad_norm_pre_clip': 3.0014216899871826, 'timing/data': 0.00016935542225837708, 'timing/model': 0.46398877911269665, 'learning_rate/action_model': 9.815255010612007e-05, 'learning_rate/action_query_proj': 9.815255010612007e-05, 'learning_rate/base': 2.4538137526530018e-05, 'epoch': 0.54}) +[2026-07-27 09:18:53,577][starVLA.training.train_starvla][INFO] - Step 4444, Loss: {'train/loss': 0.21362750232219696, 'train/grad_norm_pre_clip': 6.99464750289917, 'timing/data': 0.00018510781228542328, 'timing/model': 0.4640618320554495, 'learning_rate/action_model': 9.814425428450289e-05, 'learning_rate/action_query_proj': 9.814425428450289e-05, 'learning_rate/base': 2.4536063571125723e-05, 'epoch': 0.54}) +[2026-07-27 09:18:59,080][starVLA.training.train_starvla][INFO] - Step 4445, Loss: {'train/loss': 0.13013729453086853, 'train/grad_norm_pre_clip': 5.098202228546143, 'timing/data': 0.0001663845032453537, 'timing/model': 0.4641002044081688, 'learning_rate/action_model': 9.81359402458649e-05, 'learning_rate/action_query_proj': 9.81359402458649e-05, 'learning_rate/base': 2.4533985061466225e-05, 'epoch': 0.54}) +[2026-07-27 09:19:04,641][starVLA.training.train_starvla][INFO] - Step 4446, Loss: {'train/loss': 0.09168136864900589, 'train/grad_norm_pre_clip': 2.6747689247131348, 'timing/data': 0.0001781955361366272, 'timing/model': 0.4723542705178261, 'learning_rate/action_model': 9.812760799348835e-05, 'learning_rate/action_query_proj': 9.812760799348835e-05, 'learning_rate/base': 2.4531901998372088e-05, 'epoch': 0.54}) +[2026-07-27 09:19:10,143][starVLA.training.train_starvla][INFO] - Step 4447, Loss: {'train/loss': 0.1082877442240715, 'train/grad_norm_pre_clip': 4.75791597366333, 'timing/data': 0.00021302513778209686, 'timing/model': 0.46857631020247936, 'learning_rate/action_model': 9.811925753066269e-05, 'learning_rate/action_query_proj': 9.811925753066269e-05, 'learning_rate/base': 2.4529814382665672e-05, 'epoch': 0.54}) +[2026-07-27 09:19:15,642][starVLA.training.train_starvla][INFO] - Step 4448, Loss: {'train/loss': 0.09646878391504288, 'train/grad_norm_pre_clip': 4.351386070251465, 'timing/data': 0.00017909333109855652, 'timing/model': 0.4713650420308113, 'learning_rate/action_model': 9.811088886068454e-05, 'learning_rate/action_query_proj': 9.811088886068454e-05, 'learning_rate/base': 2.4527722215171135e-05, 'epoch': 0.54}) +[2026-07-27 09:19:21,124][starVLA.training.train_starvla][INFO] - Step 4449, Loss: {'train/loss': 0.06223766878247261, 'train/grad_norm_pre_clip': 2.6466403007507324, 'timing/data': 0.00021789409220218658, 'timing/model': 0.4604962784796953, 'learning_rate/action_model': 9.810250198685774e-05, 'learning_rate/action_query_proj': 9.810250198685774e-05, 'learning_rate/base': 2.4525625496714435e-05, 'epoch': 0.54}) +[2026-07-27 09:19:26,598][starVLA.training.train_starvla][INFO] - Step 4450, Loss: {'train/loss': 0.06386341154575348, 'train/grad_norm_pre_clip': 2.741044521331787, 'timing/data': 0.0001808125525712967, 'timing/model': 0.46247840113937855, 'learning_rate/action_model': 9.809409691249328e-05, 'learning_rate/action_query_proj': 9.809409691249328e-05, 'learning_rate/base': 2.452352422812332e-05, 'epoch': 0.54}) +[2026-07-27 09:19:32,086][starVLA.training.train_starvla][INFO] - Step 4451, Loss: {'train/loss': 0.04719625413417816, 'train/grad_norm_pre_clip': 3.2727248668670654, 'timing/data': 0.00017881952226161957, 'timing/model': 0.462052620947361, 'learning_rate/action_model': 9.808567364090932e-05, 'learning_rate/action_query_proj': 9.808567364090932e-05, 'learning_rate/base': 2.452141841022733e-05, 'epoch': 0.54}) +[2026-07-27 09:19:37,597][starVLA.training.train_starvla][INFO] - Step 4452, Loss: {'train/loss': 0.21228712797164917, 'train/grad_norm_pre_clip': 3.8024322986602783, 'timing/data': 0.00017834268510341644, 'timing/model': 0.4647374860942364, 'learning_rate/action_model': 9.80772321754313e-05, 'learning_rate/action_query_proj': 9.80772321754313e-05, 'learning_rate/base': 2.4519308043857824e-05, 'epoch': 0.54}) +[2026-07-27 09:19:43,128][starVLA.training.train_starvla][INFO] - Step 4453, Loss: {'train/loss': 0.07292625308036804, 'train/grad_norm_pre_clip': 3.371483087539673, 'timing/data': 0.0001786705106496811, 'timing/model': 0.463923342525959, 'learning_rate/action_model': 9.80687725193917e-05, 'learning_rate/action_query_proj': 9.80687725193917e-05, 'learning_rate/base': 2.4517193129847925e-05, 'epoch': 0.54}) +[2026-07-27 09:19:48,704][starVLA.training.train_starvla][INFO] - Step 4454, Loss: {'train/loss': 0.0873265191912651, 'train/grad_norm_pre_clip': 3.501150131225586, 'timing/data': 0.00018545426428318024, 'timing/model': 0.4639256726950407, 'learning_rate/action_model': 9.806029467613033e-05, 'learning_rate/action_query_proj': 9.806029467613033e-05, 'learning_rate/base': 2.4515073669032583e-05, 'epoch': 0.54}) +[2026-07-27 09:19:54,267][starVLA.training.train_starvla][INFO] - Step 4455, Loss: {'train/loss': 0.13996338844299316, 'train/grad_norm_pre_clip': 5.587769985198975, 'timing/data': 0.00017977505922317505, 'timing/model': 0.46525838039815426, 'learning_rate/action_model': 9.805179864899407e-05, 'learning_rate/action_query_proj': 9.805179864899407e-05, 'learning_rate/base': 2.4512949662248516e-05, 'epoch': 0.54}) +[2026-07-27 09:19:59,846][starVLA.training.train_starvla][INFO] - Step 4456, Loss: {'train/loss': 0.06531534343957901, 'train/grad_norm_pre_clip': 2.963257312774658, 'timing/data': 0.00018029846251010895, 'timing/model': 0.4653106611222029, 'learning_rate/action_model': 9.804328444133702e-05, 'learning_rate/action_query_proj': 9.804328444133702e-05, 'learning_rate/base': 2.4510821110334254e-05, 'epoch': 0.54}) +[2026-07-27 09:20:05,417][starVLA.training.train_starvla][INFO] - Step 4457, Loss: {'train/loss': 0.041687481105327606, 'train/grad_norm_pre_clip': 2.7765636444091797, 'timing/data': 0.00017921626567840576, 'timing/model': 0.46439826488494873, 'learning_rate/action_model': 9.803475205652044e-05, 'learning_rate/action_query_proj': 9.803475205652044e-05, 'learning_rate/base': 2.450868801413011e-05, 'epoch': 0.54}) +[2026-07-27 09:20:11,010][starVLA.training.train_starvla][INFO] - Step 4458, Loss: {'train/loss': 0.06173405796289444, 'train/grad_norm_pre_clip': 3.269368886947632, 'timing/data': 0.00027083978056907654, 'timing/model': 0.46345506981015205, 'learning_rate/action_model': 9.802620149791282e-05, 'learning_rate/action_query_proj': 9.802620149791282e-05, 'learning_rate/base': 2.4506550374478206e-05, 'epoch': 0.54}) +[2026-07-27 09:20:16,567][starVLA.training.train_starvla][INFO] - Step 4459, Loss: {'train/loss': 0.0728355422616005, 'train/grad_norm_pre_clip': 3.6531333923339844, 'timing/data': 0.00018141232430934906, 'timing/model': 0.4627614188939333, 'learning_rate/action_model': 9.801763276888974e-05, 'learning_rate/action_query_proj': 9.801763276888974e-05, 'learning_rate/base': 2.4504408192222436e-05, 'epoch': 0.54}) +[2026-07-27 09:20:22,132][starVLA.training.train_starvla][INFO] - Step 4460, Loss: {'train/loss': 0.16664022207260132, 'train/grad_norm_pre_clip': 4.505544185638428, 'timing/data': 0.00017981603741645813, 'timing/model': 0.4604550339281559, 'learning_rate/action_model': 9.800904587283404e-05, 'learning_rate/action_query_proj': 9.800904587283404e-05, 'learning_rate/base': 2.450226146820851e-05, 'epoch': 0.54}) +[2026-07-27 09:20:27,710][starVLA.training.train_starvla][INFO] - Step 4461, Loss: {'train/loss': 0.04037437215447426, 'train/grad_norm_pre_clip': 2.6833255290985107, 'timing/data': 0.00017977692186832428, 'timing/model': 0.46228902600705624, 'learning_rate/action_model': 9.800044081313569e-05, 'learning_rate/action_query_proj': 9.800044081313569e-05, 'learning_rate/base': 2.4500110203283923e-05, 'epoch': 0.54}) +[2026-07-27 09:20:33,287][starVLA.training.train_starvla][INFO] - Step 4462, Loss: {'train/loss': 0.07409984618425369, 'train/grad_norm_pre_clip': 3.418856143951416, 'timing/data': 0.00018021650612354279, 'timing/model': 0.46294453367590904, 'learning_rate/action_model': 9.799181759319177e-05, 'learning_rate/action_query_proj': 9.799181759319177e-05, 'learning_rate/base': 2.4497954398297944e-05, 'epoch': 0.54}) +[2026-07-27 09:20:38,855][starVLA.training.train_starvla][INFO] - Step 4463, Loss: {'train/loss': 0.1223626509308815, 'train/grad_norm_pre_clip': 4.163242816925049, 'timing/data': 0.00017950870096683502, 'timing/model': 0.4634041506797075, 'learning_rate/action_model': 9.798317621640667e-05, 'learning_rate/action_query_proj': 9.798317621640667e-05, 'learning_rate/base': 2.449579405410167e-05, 'epoch': 0.54}) +[2026-07-27 09:20:44,406][starVLA.training.train_starvla][INFO] - Step 4464, Loss: {'train/loss': 0.065183624625206, 'train/grad_norm_pre_clip': 4.231688976287842, 'timing/data': 0.00018236786127090454, 'timing/model': 0.4622168652713299, 'learning_rate/action_model': 9.797451668619182e-05, 'learning_rate/action_query_proj': 9.797451668619182e-05, 'learning_rate/base': 2.4493629171547955e-05, 'epoch': 0.54}) +[2026-07-27 09:20:49,975][starVLA.training.train_starvla][INFO] - Step 4465, Loss: {'train/loss': 0.09326566010713577, 'train/grad_norm_pre_clip': 3.990391731262207, 'timing/data': 0.0003260914236307144, 'timing/model': 0.4611752349883318, 'learning_rate/action_model': 9.796583900596586e-05, 'learning_rate/action_query_proj': 9.796583900596586e-05, 'learning_rate/base': 2.4491459751491465e-05, 'epoch': 0.54}) +[2026-07-27 09:20:55,567][starVLA.training.train_starvla][INFO] - Step 4466, Loss: {'train/loss': 0.18696831166744232, 'train/grad_norm_pre_clip': 5.051627159118652, 'timing/data': 0.0001726485788822174, 'timing/model': 0.4625547658652067, 'learning_rate/action_model': 9.795714317915465e-05, 'learning_rate/action_query_proj': 9.795714317915465e-05, 'learning_rate/base': 2.448928579478866e-05, 'epoch': 0.54}) +[2026-07-27 09:21:01,189][starVLA.training.train_starvla][INFO] - Step 4467, Loss: {'train/loss': 0.09579448401927948, 'train/grad_norm_pre_clip': 2.9397380352020264, 'timing/data': 0.00018608570098876953, 'timing/model': 0.4701180215924978, 'learning_rate/action_model': 9.794842920919113e-05, 'learning_rate/action_query_proj': 9.794842920919113e-05, 'learning_rate/base': 2.4487107302297782e-05, 'epoch': 0.54}) +[2026-07-27 09:21:06,811][starVLA.training.train_starvla][INFO] - Step 4468, Loss: {'train/loss': 0.1790882796049118, 'train/grad_norm_pre_clip': 5.787141799926758, 'timing/data': 0.00017444230616092682, 'timing/model': 0.4604796748608351, 'learning_rate/action_model': 9.793969709951543e-05, 'learning_rate/action_query_proj': 9.793969709951543e-05, 'learning_rate/base': 2.4484924274878857e-05, 'epoch': 0.54}) +[2026-07-27 09:21:12,393][starVLA.training.train_starvla][INFO] - Step 4469, Loss: {'train/loss': 0.026479998603463173, 'train/grad_norm_pre_clip': 2.6005942821502686, 'timing/data': 0.0001696217805147171, 'timing/model': 0.46040764451026917, 'learning_rate/action_model': 9.793094685357484e-05, 'learning_rate/action_query_proj': 9.793094685357484e-05, 'learning_rate/base': 2.448273671339371e-05, 'epoch': 0.54}) +[2026-07-27 09:21:17,994][starVLA.training.train_starvla][INFO] - Step 4470, Loss: {'train/loss': 0.12655878067016602, 'train/grad_norm_pre_clip': 3.818148612976074, 'timing/data': 0.00017075613141059875, 'timing/model': 0.45929677225649357, 'learning_rate/action_model': 9.792217847482387e-05, 'learning_rate/action_query_proj': 9.792217847482387e-05, 'learning_rate/base': 2.4480544618705968e-05, 'epoch': 0.54}) +[2026-07-27 09:21:23,602][starVLA.training.train_starvla][INFO] - Step 4471, Loss: {'train/loss': 0.0546334870159626, 'train/grad_norm_pre_clip': 2.8221030235290527, 'timing/data': 0.00017143413424491882, 'timing/model': 0.45840881764888763, 'learning_rate/action_model': 9.791339196672409e-05, 'learning_rate/action_query_proj': 9.791339196672409e-05, 'learning_rate/base': 2.4478347991681022e-05, 'epoch': 0.54}) +[2026-07-27 09:21:29,199][starVLA.training.train_starvla][INFO] - Step 4472, Loss: {'train/loss': 0.11309034377336502, 'train/grad_norm_pre_clip': 3.020770311355591, 'timing/data': 0.00021080486476421356, 'timing/model': 0.4608169421553612, 'learning_rate/action_model': 9.79045873327443e-05, 'learning_rate/action_query_proj': 9.79045873327443e-05, 'learning_rate/base': 2.4476146833186076e-05, 'epoch': 0.54}) +[2026-07-27 09:21:34,790][starVLA.training.train_starvla][INFO] - Step 4473, Loss: {'train/loss': 0.1020876094698906, 'train/grad_norm_pre_clip': 3.4707627296447754, 'timing/data': 0.00020745396614074707, 'timing/model': 0.46175674721598625, 'learning_rate/action_model': 9.789576457636042e-05, 'learning_rate/action_query_proj': 9.789576457636042e-05, 'learning_rate/base': 2.4473941144090105e-05, 'epoch': 0.54}) +[2026-07-27 09:21:40,411][starVLA.training.train_starvla][INFO] - Step 4474, Loss: {'train/loss': 0.13108021020889282, 'train/grad_norm_pre_clip': 4.058834552764893, 'timing/data': 0.00017673149704933167, 'timing/model': 0.46102320961654186, 'learning_rate/action_model': 9.788692370105551e-05, 'learning_rate/action_query_proj': 9.788692370105551e-05, 'learning_rate/base': 2.4471730925263877e-05, 'epoch': 0.54}) +[2026-07-27 09:21:46,029][starVLA.training.train_starvla][INFO] - Step 4475, Loss: {'train/loss': 0.1747312694787979, 'train/grad_norm_pre_clip': 3.0066092014312744, 'timing/data': 0.0001695547252893448, 'timing/model': 0.46134318970143795, 'learning_rate/action_model': 9.787806471031985e-05, 'learning_rate/action_query_proj': 9.787806471031985e-05, 'learning_rate/base': 2.4469516177579963e-05, 'epoch': 0.54}) +[2026-07-27 09:21:51,646][starVLA.training.train_starvla][INFO] - Step 4476, Loss: {'train/loss': 0.0451514832675457, 'train/grad_norm_pre_clip': 2.7803711891174316, 'timing/data': 0.00016791187226772308, 'timing/model': 0.45988085493445396, 'learning_rate/action_model': 9.786918760765082e-05, 'learning_rate/action_query_proj': 9.786918760765082e-05, 'learning_rate/base': 2.4467296901912704e-05, 'epoch': 0.54}) +[2026-07-27 09:21:57,391][starVLA.training.train_starvla][INFO] - Step 4477, Loss: {'train/loss': 0.10327425599098206, 'train/grad_norm_pre_clip': 2.408597469329834, 'timing/data': 0.00019100680947303772, 'timing/model': 0.4613377805799246, 'learning_rate/action_model': 9.786029239655294e-05, 'learning_rate/action_query_proj': 9.786029239655294e-05, 'learning_rate/base': 2.4465073099138234e-05, 'epoch': 0.54}) +[2026-07-27 09:22:03,014][starVLA.training.train_starvla][INFO] - Step 4478, Loss: {'train/loss': 0.09477050602436066, 'train/grad_norm_pre_clip': 4.512569904327393, 'timing/data': 0.00017719902098178864, 'timing/model': 0.4612215533852577, 'learning_rate/action_model': 9.78513790805379e-05, 'learning_rate/action_query_proj': 9.78513790805379e-05, 'learning_rate/base': 2.4462844770134474e-05, 'epoch': 0.54}) +[2026-07-27 09:22:08,644][starVLA.training.train_starvla][INFO] - Step 4479, Loss: {'train/loss': 0.17734268307685852, 'train/grad_norm_pre_clip': 4.086519241333008, 'timing/data': 0.00016578659415245056, 'timing/model': 0.46046813763678074, 'learning_rate/action_model': 9.784244766312455e-05, 'learning_rate/action_query_proj': 9.784244766312455e-05, 'learning_rate/base': 2.4460611915781137e-05, 'epoch': 0.54}) +[2026-07-27 09:22:14,275][starVLA.training.train_starvla][INFO] - Step 4480, Loss: {'train/loss': 0.133692666888237, 'train/grad_norm_pre_clip': 4.008705139160156, 'timing/data': 0.0001759938895702362, 'timing/model': 0.45948174968361855, 'learning_rate/action_model': 9.783349814783888e-05, 'learning_rate/action_query_proj': 9.783349814783888e-05, 'learning_rate/base': 2.445837453695972e-05, 'epoch': 0.54}) +[2026-07-27 09:22:19,899][starVLA.training.train_starvla][INFO] - Step 4481, Loss: {'train/loss': 0.09280560165643692, 'train/grad_norm_pre_clip': 3.2088441848754883, 'timing/data': 0.00016466155648231506, 'timing/model': 0.46241204999387264, 'learning_rate/action_model': 9.782453053821398e-05, 'learning_rate/action_query_proj': 9.782453053821398e-05, 'learning_rate/base': 2.4456132634553494e-05, 'epoch': 0.54}) +[2026-07-27 09:22:25,516][starVLA.training.train_starvla][INFO] - Step 4482, Loss: {'train/loss': 0.3056775629520416, 'train/grad_norm_pre_clip': 6.70086145401001, 'timing/data': 0.00016867928206920624, 'timing/model': 0.46052769012749195, 'learning_rate/action_model': 9.781554483779016e-05, 'learning_rate/action_query_proj': 9.781554483779016e-05, 'learning_rate/base': 2.445388620944754e-05, 'epoch': 0.54}) +[2026-07-27 09:22:31,074][starVLA.training.train_starvla][INFO] - Step 4483, Loss: {'train/loss': 0.08080220222473145, 'train/grad_norm_pre_clip': 3.7711315155029297, 'timing/data': 0.00017256475985050201, 'timing/model': 0.4606199972331524, 'learning_rate/action_model': 9.78065410501148e-05, 'learning_rate/action_query_proj': 9.78065410501148e-05, 'learning_rate/base': 2.44516352625287e-05, 'epoch': 0.54}) +[2026-07-27 09:22:36,705][starVLA.training.train_starvla][INFO] - Step 4484, Loss: {'train/loss': 0.05760680139064789, 'train/grad_norm_pre_clip': 2.8888518810272217, 'timing/data': 0.00021801702678203583, 'timing/model': 0.46123142912983894, 'learning_rate/action_model': 9.779751917874249e-05, 'learning_rate/action_query_proj': 9.779751917874249e-05, 'learning_rate/base': 2.4449379794685623e-05, 'epoch': 0.54}) +[2026-07-27 09:22:42,268][starVLA.training.train_starvla][INFO] - Step 4485, Loss: {'train/loss': 0.02875041589140892, 'train/grad_norm_pre_clip': 1.2556287050247192, 'timing/data': 0.00016871467232704163, 'timing/model': 0.4602659326046705, 'learning_rate/action_model': 9.77884792272349e-05, 'learning_rate/action_query_proj': 9.77884792272349e-05, 'learning_rate/base': 2.4447119806808725e-05, 'epoch': 0.54}) +[2026-07-27 09:22:47,837][starVLA.training.train_starvla][INFO] - Step 4486, Loss: {'train/loss': 0.0952090173959732, 'train/grad_norm_pre_clip': 4.052786827087402, 'timing/data': 0.0002381410449743271, 'timing/model': 0.4614976067095995, 'learning_rate/action_model': 9.777942119916085e-05, 'learning_rate/action_query_proj': 9.777942119916085e-05, 'learning_rate/base': 2.4444855299790212e-05, 'epoch': 0.54}) +[2026-07-27 09:22:53,370][starVLA.training.train_starvla][INFO] - Step 4487, Loss: {'train/loss': 0.10430976003408432, 'train/grad_norm_pre_clip': 3.544731855392456, 'timing/data': 0.0001867096871137619, 'timing/model': 0.4611547812819481, 'learning_rate/action_model': 9.777034509809633e-05, 'learning_rate/action_query_proj': 9.777034509809633e-05, 'learning_rate/base': 2.4442586274524083e-05, 'epoch': 0.54}) +[2026-07-27 09:22:58,928][starVLA.training.train_starvla][INFO] - Step 4488, Loss: {'train/loss': 0.0856488049030304, 'train/grad_norm_pre_clip': 3.6144583225250244, 'timing/data': 0.0001680031418800354, 'timing/model': 0.4578367881476879, 'learning_rate/action_model': 9.776125092762441e-05, 'learning_rate/action_query_proj': 9.776125092762441e-05, 'learning_rate/base': 2.4440312731906103e-05, 'epoch': 0.54}) +[2026-07-27 09:23:04,478][starVLA.training.train_starvla][INFO] - Step 4489, Loss: {'train/loss': 0.09161630272865295, 'train/grad_norm_pre_clip': 4.322615623474121, 'timing/data': 0.00020854733884334564, 'timing/model': 0.46023315750062466, 'learning_rate/action_model': 9.775213869133535e-05, 'learning_rate/action_query_proj': 9.775213869133535e-05, 'learning_rate/base': 2.4438034672833837e-05, 'epoch': 0.54}) +[2026-07-27 09:23:10,048][starVLA.training.train_starvla][INFO] - Step 4490, Loss: {'train/loss': 0.07344678789377213, 'train/grad_norm_pre_clip': 3.664293050765991, 'timing/data': 0.0001764632761478424, 'timing/model': 0.4605650492012501, 'learning_rate/action_model': 9.774300839282652e-05, 'learning_rate/action_query_proj': 9.774300839282652e-05, 'learning_rate/base': 2.443575209820663e-05, 'epoch': 0.54}) +[2026-07-27 09:23:15,604][starVLA.training.train_starvla][INFO] - Step 4491, Loss: {'train/loss': 0.09484328329563141, 'train/grad_norm_pre_clip': 2.550203800201416, 'timing/data': 0.00016573630273342133, 'timing/model': 0.4613566882908344, 'learning_rate/action_model': 9.773386003570238e-05, 'learning_rate/action_query_proj': 9.773386003570238e-05, 'learning_rate/base': 2.4433465008925596e-05, 'epoch': 0.54}) +[2026-07-27 09:23:21,164][starVLA.training.train_starvla][INFO] - Step 4492, Loss: {'train/loss': 0.1718684285879135, 'train/grad_norm_pre_clip': 4.314672946929932, 'timing/data': 0.00016320310533046722, 'timing/model': 0.46118622086942196, 'learning_rate/action_model': 9.772469362357461e-05, 'learning_rate/action_query_proj': 9.772469362357461e-05, 'learning_rate/base': 2.4431173405893652e-05, 'epoch': 0.54}) +[2026-07-27 09:23:26,723][starVLA.training.train_starvla][INFO] - Step 4493, Loss: {'train/loss': 0.10989736020565033, 'train/grad_norm_pre_clip': 3.3063809871673584, 'timing/data': 0.00017405301332473755, 'timing/model': 0.4610358811914921, 'learning_rate/action_model': 9.771550916006191e-05, 'learning_rate/action_query_proj': 9.771550916006191e-05, 'learning_rate/base': 2.4428877290015478e-05, 'epoch': 0.55}) +[2026-07-27 09:23:32,284][starVLA.training.train_starvla][INFO] - Step 4494, Loss: {'train/loss': 0.0682823657989502, 'train/grad_norm_pre_clip': 2.7441823482513428, 'timing/data': 0.00017740018665790558, 'timing/model': 0.4602853301912546, 'learning_rate/action_model': 9.770630664879021e-05, 'learning_rate/action_query_proj': 9.770630664879021e-05, 'learning_rate/base': 2.4426576662197553e-05, 'epoch': 0.55}) +[2026-07-27 09:23:37,852][starVLA.training.train_starvla][INFO] - Step 4495, Loss: {'train/loss': 0.01429598219692707, 'train/grad_norm_pre_clip': 0.9574922323226929, 'timing/data': 0.00017813220620155334, 'timing/model': 0.4611809514462948, 'learning_rate/action_model': 9.769708609339249e-05, 'learning_rate/action_query_proj': 9.769708609339249e-05, 'learning_rate/base': 2.4424271523348122e-05, 'epoch': 0.55}) +[2026-07-27 09:23:43,399][starVLA.training.train_starvla][INFO] - Step 4496, Loss: {'train/loss': 0.09312322735786438, 'train/grad_norm_pre_clip': 3.451723337173462, 'timing/data': 0.00017094239592552185, 'timing/model': 0.4600194860249758, 'learning_rate/action_model': 9.768784749750887e-05, 'learning_rate/action_query_proj': 9.768784749750887e-05, 'learning_rate/base': 2.4421961874377218e-05, 'epoch': 0.55}) +[2026-07-27 09:23:49,170][starVLA.training.train_starvla][INFO] - Step 4497, Loss: {'train/loss': 0.08409546315670013, 'train/grad_norm_pre_clip': 3.564030885696411, 'timing/data': 0.00017723627388477325, 'timing/model': 0.46044769138097763, 'learning_rate/action_model': 9.767859086478662e-05, 'learning_rate/action_query_proj': 9.767859086478662e-05, 'learning_rate/base': 2.4419647716196655e-05, 'epoch': 0.55}) +[2026-07-27 09:23:54,833][starVLA.training.train_starvla][INFO] - Step 4498, Loss: {'train/loss': 0.10648315399885178, 'train/grad_norm_pre_clip': 4.0434088706970215, 'timing/data': 0.00017111562192440033, 'timing/model': 0.456793587654829, 'learning_rate/action_model': 9.766931619888011e-05, 'learning_rate/action_query_proj': 9.766931619888011e-05, 'learning_rate/base': 2.4417329049720028e-05, 'epoch': 0.55}) +[2026-07-27 09:24:00,357][starVLA.training.train_starvla][INFO] - Step 4499, Loss: {'train/loss': 0.14713025093078613, 'train/grad_norm_pre_clip': 4.148869514465332, 'timing/data': 0.00020079687237739563, 'timing/model': 0.45872045680880547, 'learning_rate/action_model': 9.766002350345082e-05, 'learning_rate/action_query_proj': 9.766002350345082e-05, 'learning_rate/base': 2.4415005875862706e-05, 'epoch': 0.55}) +[2026-07-27 09:24:05,938][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 4500 +[2026-07-27 09:24:05,939][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 4500 +[2026-07-27 09:24:05,939][starVLA.training.train_starvla][INFO] - Step 4500, Loss: {'train/loss': 0.10182047635316849, 'train/grad_norm_pre_clip': 3.5366649627685547, 'timing/data': 0.0001741759479045868, 'timing/model': 0.4604476559907198, 'learning_rate/action_model': 9.765071278216737e-05, 'learning_rate/action_query_proj': 9.765071278216737e-05, 'learning_rate/base': 2.4412678195541843e-05, 'epoch': 0.55}) +[2026-07-27 09:24:05,943][accelerate.accelerator][INFO] - Saving current state to /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4500_state +[2026-07-27 09:24:05,943][accelerate.accelerator][INFO] - Saving DeepSpeed Model and Optimizer +[2026-07-27 09:24:51,932][accelerate.accelerator][INFO] - DeepSpeed Model and Optimizer saved to output dir /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4500_state/pytorch_model +[2026-07-27 09:24:51,932][accelerate.checkpointing][INFO] - Sampler state for dataloader 0 saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4500_state/sampler.bin +[2026-07-27 09:24:51,936][accelerate.checkpointing][INFO] - Random states saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_4500_state/random_states_0.pkl +[2026-07-27 09:25:38,279][starVLA.training.rl_games.checkpoint_sync][INFO] - HF checkpoint sync disabled; skipping upload for step 4500 +[2026-07-27 09:25:38,279][starVLA.training.train_starvla][INFO] - 📊 Saving accessed configuration... +[2026-07-27 09:25:38,294][starVLA.training.train_starvla][INFO] - ✅ Configuration files saved +[2026-07-27 09:25:43,981][starVLA.training.train_starvla][INFO] - Step 4501, Loss: {'train/loss': 0.07757960259914398, 'train/grad_norm_pre_clip': 3.328381061553955, 'timing/data': 0.00017487257719039917, 'timing/model': 0.4704920817166567, 'learning_rate/action_model': 9.764138403870548e-05, 'learning_rate/action_query_proj': 9.764138403870548e-05, 'learning_rate/base': 2.441034600967637e-05, 'epoch': 0.55}) +[2026-07-27 09:25:49,644][starVLA.training.train_starvla][INFO] - Step 4502, Loss: {'train/loss': 0.10047737509012222, 'train/grad_norm_pre_clip': 2.1009888648986816, 'timing/data': 0.00018849223852157593, 'timing/model': 0.46907084807753563, 'learning_rate/action_model': 9.7632037276748e-05, 'learning_rate/action_query_proj': 9.7632037276748e-05, 'learning_rate/base': 2.4408009319187e-05, 'epoch': 0.55}) +[2026-07-27 09:25:55,284][starVLA.training.train_starvla][INFO] - Step 4503, Loss: {'train/loss': 0.07074334472417831, 'train/grad_norm_pre_clip': 3.5419867038726807, 'timing/data': 0.0001786462962627411, 'timing/model': 0.4605473503470421, 'learning_rate/action_model': 9.762267249998487e-05, 'learning_rate/action_query_proj': 9.762267249998487e-05, 'learning_rate/base': 2.4405668124996217e-05, 'epoch': 0.55}) +[2026-07-27 09:26:00,932][starVLA.training.train_starvla][INFO] - Step 4504, Loss: {'train/loss': 0.04354771226644516, 'train/grad_norm_pre_clip': 2.3667728900909424, 'timing/data': 0.00018187053501605988, 'timing/model': 0.46524458564817905, 'learning_rate/action_model': 9.761328971211315e-05, 'learning_rate/action_query_proj': 9.761328971211315e-05, 'learning_rate/base': 2.4403322428028287e-05, 'epoch': 0.55}) +[2026-07-27 09:26:06,593][starVLA.training.train_starvla][INFO] - Step 4505, Loss: {'train/loss': 0.12559162080287933, 'train/grad_norm_pre_clip': 3.607760429382324, 'timing/data': 0.0001768004149198532, 'timing/model': 0.4686669185757637, 'learning_rate/action_model': 9.760388891683704e-05, 'learning_rate/action_query_proj': 9.760388891683704e-05, 'learning_rate/base': 2.440097222920926e-05, 'epoch': 0.55}) +[2026-07-27 09:26:12,254][starVLA.training.train_starvla][INFO] - Step 4506, Loss: {'train/loss': 0.07492551952600479, 'train/grad_norm_pre_clip': 3.334284782409668, 'timing/data': 0.00018967501819133759, 'timing/model': 0.46738009341061115, 'learning_rate/action_model': 9.759447011786783e-05, 'learning_rate/action_query_proj': 9.759447011786783e-05, 'learning_rate/base': 2.4398617529466957e-05, 'epoch': 0.55}) +[2026-07-27 09:26:17,883][starVLA.training.train_starvla][INFO] - Step 4507, Loss: {'train/loss': 0.23148992657661438, 'train/grad_norm_pre_clip': 6.9171881675720215, 'timing/data': 0.0001740865409374237, 'timing/model': 0.45898348838090897, 'learning_rate/action_model': 9.758503331892385e-05, 'learning_rate/action_query_proj': 9.758503331892385e-05, 'learning_rate/base': 2.4396258329730964e-05, 'epoch': 0.55}) +[2026-07-27 09:26:23,533][starVLA.training.train_starvla][INFO] - Step 4508, Loss: {'train/loss': 0.1277230829000473, 'train/grad_norm_pre_clip': 5.405431270599365, 'timing/data': 0.00016696564853191376, 'timing/model': 0.45789054967463017, 'learning_rate/action_model': 9.757557852373067e-05, 'learning_rate/action_query_proj': 9.757557852373067e-05, 'learning_rate/base': 2.4393894630932668e-05, 'epoch': 0.55}) +[2026-07-27 09:26:29,187][starVLA.training.train_starvla][INFO] - Step 4509, Loss: {'train/loss': 0.11196979880332947, 'train/grad_norm_pre_clip': 4.3284502029418945, 'timing/data': 0.00017432309687137604, 'timing/model': 0.4702490624040365, 'learning_rate/action_model': 9.756610573602087e-05, 'learning_rate/action_query_proj': 9.756610573602087e-05, 'learning_rate/base': 2.4391526434005218e-05, 'epoch': 0.55}) +[2026-07-27 09:26:34,828][starVLA.training.train_starvla][INFO] - Step 4510, Loss: {'train/loss': 0.10487700998783112, 'train/grad_norm_pre_clip': 3.7302098274230957, 'timing/data': 0.00017512403428554535, 'timing/model': 0.4576331526041031, 'learning_rate/action_model': 9.755661495953414e-05, 'learning_rate/action_query_proj': 9.755661495953414e-05, 'learning_rate/base': 2.4389153739883535e-05, 'epoch': 0.55}) +[2026-07-27 09:26:40,506][starVLA.training.train_starvla][INFO] - Step 4511, Loss: {'train/loss': 0.06097126752138138, 'train/grad_norm_pre_clip': 2.346963405609131, 'timing/data': 0.00023623928427696228, 'timing/model': 0.4718503374606371, 'learning_rate/action_model': 9.754710619801732e-05, 'learning_rate/action_query_proj': 9.754710619801732e-05, 'learning_rate/base': 2.438677654950433e-05, 'epoch': 0.55}) +[2026-07-27 09:26:46,161][starVLA.training.train_starvla][INFO] - Step 4512, Loss: {'train/loss': 0.13891370594501495, 'train/grad_norm_pre_clip': 5.187516689300537, 'timing/data': 0.00016863085329532623, 'timing/model': 0.45826697535812855, 'learning_rate/action_model': 9.753757945522428e-05, 'learning_rate/action_query_proj': 9.753757945522428e-05, 'learning_rate/base': 2.438439486380607e-05, 'epoch': 0.55}) +[2026-07-27 09:26:51,829][starVLA.training.train_starvla][INFO] - Step 4513, Loss: {'train/loss': 0.03721320629119873, 'train/grad_norm_pre_clip': 1.5819698572158813, 'timing/data': 0.0001753196120262146, 'timing/model': 0.46841167844831944, 'learning_rate/action_model': 9.752803473491605e-05, 'learning_rate/action_query_proj': 9.752803473491605e-05, 'learning_rate/base': 2.4382008683729013e-05, 'epoch': 0.55}) +[2026-07-27 09:26:57,457][starVLA.training.train_starvla][INFO] - Step 4514, Loss: {'train/loss': 0.0996854230761528, 'train/grad_norm_pre_clip': 2.7330284118652344, 'timing/data': 0.0002177748829126358, 'timing/model': 0.45982701517641544, 'learning_rate/action_model': 9.751847204086074e-05, 'learning_rate/action_query_proj': 9.751847204086074e-05, 'learning_rate/base': 2.4379618010215186e-05, 'epoch': 0.55}) +[2026-07-27 09:27:03,273][starVLA.training.train_starvla][INFO] - Step 4515, Loss: {'train/loss': 0.12531152367591858, 'train/grad_norm_pre_clip': 3.2851645946502686, 'timing/data': 0.00017335452139377594, 'timing/model': 0.6190372165292501, 'learning_rate/action_model': 9.750889137683354e-05, 'learning_rate/action_query_proj': 9.750889137683354e-05, 'learning_rate/base': 2.4377222844208385e-05, 'epoch': 0.55}) +[2026-07-27 09:27:08,900][starVLA.training.train_starvla][INFO] - Step 4516, Loss: {'train/loss': 0.04863671958446503, 'train/grad_norm_pre_clip': 2.6488535404205322, 'timing/data': 0.00016732513904571533, 'timing/model': 0.46626315265893936, 'learning_rate/action_model': 9.749929274661674e-05, 'learning_rate/action_query_proj': 9.749929274661674e-05, 'learning_rate/base': 2.4374823186654185e-05, 'epoch': 0.55}) +[2026-07-27 09:27:14,531][starVLA.training.train_starvla][INFO] - Step 4517, Loss: {'train/loss': 0.04295138269662857, 'train/grad_norm_pre_clip': 2.6889684200286865, 'timing/data': 0.00017416104674339294, 'timing/model': 0.4694455433636904, 'learning_rate/action_model': 9.748967615399975e-05, 'learning_rate/action_query_proj': 9.748967615399975e-05, 'learning_rate/base': 2.4372419038499937e-05, 'epoch': 0.55}) +[2026-07-27 09:27:20,388][starVLA.training.train_starvla][INFO] - Step 4518, Loss: {'train/loss': 0.09448471665382385, 'train/grad_norm_pre_clip': 3.0292327404022217, 'timing/data': 0.0001794900745153427, 'timing/model': 0.46993264742195606, 'learning_rate/action_model': 9.748004160277901e-05, 'learning_rate/action_query_proj': 9.748004160277901e-05, 'learning_rate/base': 2.4370010400694753e-05, 'epoch': 0.55}) +[2026-07-27 09:27:25,987][starVLA.training.train_starvla][INFO] - Step 4519, Loss: {'train/loss': 0.08391544222831726, 'train/grad_norm_pre_clip': 3.8866870403289795, 'timing/data': 0.00017165392637252808, 'timing/model': 0.4624664392322302, 'learning_rate/action_model': 9.747038909675812e-05, 'learning_rate/action_query_proj': 9.747038909675812e-05, 'learning_rate/base': 2.436759727418953e-05, 'epoch': 0.55}) +[2026-07-27 09:27:31,589][starVLA.training.train_starvla][INFO] - Step 4520, Loss: {'train/loss': 0.04288482666015625, 'train/grad_norm_pre_clip': 1.8730887174606323, 'timing/data': 0.0001722276210784912, 'timing/model': 0.46193088218569756, 'learning_rate/action_model': 9.746071863974773e-05, 'learning_rate/action_query_proj': 9.746071863974773e-05, 'learning_rate/base': 2.4365179659936933e-05, 'epoch': 0.55}) +[2026-07-27 09:27:37,252][starVLA.training.train_starvla][INFO] - Step 4521, Loss: {'train/loss': 0.07584568113088608, 'train/grad_norm_pre_clip': 3.0855724811553955, 'timing/data': 0.00019227340817451477, 'timing/model': 0.4692752920091152, 'learning_rate/action_model': 9.745103023556558e-05, 'learning_rate/action_query_proj': 9.745103023556558e-05, 'learning_rate/base': 2.4362757558891396e-05, 'epoch': 0.55}) +[2026-07-27 09:27:42,905][starVLA.training.train_starvla][INFO] - Step 4522, Loss: {'train/loss': 0.07596158981323242, 'train/grad_norm_pre_clip': 3.409093141555786, 'timing/data': 0.00018334202468395233, 'timing/model': 0.4690979216247797, 'learning_rate/action_model': 9.74413238880365e-05, 'learning_rate/action_query_proj': 9.74413238880365e-05, 'learning_rate/base': 2.4360330972009125e-05, 'epoch': 0.55}) +[2026-07-27 09:27:48,530][starVLA.training.train_starvla][INFO] - Step 4523, Loss: {'train/loss': 0.05505187064409256, 'train/grad_norm_pre_clip': 3.0443532466888428, 'timing/data': 0.00017982907593250275, 'timing/model': 0.4576049167662859, 'learning_rate/action_model': 9.743159960099239e-05, 'learning_rate/action_query_proj': 9.743159960099239e-05, 'learning_rate/base': 2.4357899900248097e-05, 'epoch': 0.55}) +[2026-07-27 09:27:54,139][starVLA.training.train_starvla][INFO] - Step 4524, Loss: {'train/loss': 0.059346407651901245, 'train/grad_norm_pre_clip': 2.2716259956359863, 'timing/data': 0.00017233192920684814, 'timing/model': 0.45808515325188637, 'learning_rate/action_model': 9.742185737827226e-05, 'learning_rate/action_query_proj': 9.742185737827226e-05, 'learning_rate/base': 2.4355464344568065e-05, 'epoch': 0.55}) +[2026-07-27 09:27:59,759][starVLA.training.train_starvla][INFO] - Step 4525, Loss: {'train/loss': 0.023602189496159554, 'train/grad_norm_pre_clip': 1.6493644714355469, 'timing/data': 0.00018114224076271057, 'timing/model': 0.45664106123149395, 'learning_rate/action_model': 9.741209722372218e-05, 'learning_rate/action_query_proj': 9.741209722372218e-05, 'learning_rate/base': 2.4353024305930544e-05, 'epoch': 0.55}) +[2026-07-27 09:28:05,368][starVLA.training.train_starvla][INFO] - Step 4526, Loss: {'train/loss': 0.024140138179063797, 'train/grad_norm_pre_clip': 1.6329442262649536, 'timing/data': 0.00017169490456581116, 'timing/model': 0.4577302485704422, 'learning_rate/action_model': 9.740231914119531e-05, 'learning_rate/action_query_proj': 9.740231914119531e-05, 'learning_rate/base': 2.4350579785298827e-05, 'epoch': 0.55}) +[2026-07-27 09:28:10,985][starVLA.training.train_starvla][INFO] - Step 4527, Loss: {'train/loss': 0.03638802841305733, 'train/grad_norm_pre_clip': 1.903870940208435, 'timing/data': 0.00017791613936424255, 'timing/model': 0.4688215535134077, 'learning_rate/action_model': 9.739252313455186e-05, 'learning_rate/action_query_proj': 9.739252313455186e-05, 'learning_rate/base': 2.4348130783637966e-05, 'epoch': 0.55}) +[2026-07-27 09:28:16,585][starVLA.training.train_starvla][INFO] - Step 4528, Loss: {'train/loss': 0.025691291317343712, 'train/grad_norm_pre_clip': 1.6343979835510254, 'timing/data': 0.00017547421157360077, 'timing/model': 0.46157093718647957, 'learning_rate/action_model': 9.738270920765918e-05, 'learning_rate/action_query_proj': 9.738270920765918e-05, 'learning_rate/base': 2.4345677301914794e-05, 'epoch': 0.55}) +[2026-07-27 09:28:22,187][starVLA.training.train_starvla][INFO] - Step 4529, Loss: {'train/loss': 0.04489757493138313, 'train/grad_norm_pre_clip': 2.911339044570923, 'timing/data': 0.00020611658692359924, 'timing/model': 0.46444653533399105, 'learning_rate/action_model': 9.737287736439162e-05, 'learning_rate/action_query_proj': 9.737287736439162e-05, 'learning_rate/base': 2.4343219341097904e-05, 'epoch': 0.55}) +[2026-07-27 09:28:27,744][starVLA.training.train_starvla][INFO] - Step 4530, Loss: {'train/loss': 0.03384608402848244, 'train/grad_norm_pre_clip': 2.2085957527160645, 'timing/data': 0.00017999671399593353, 'timing/model': 0.46734312176704407, 'learning_rate/action_model': 9.736302760863063e-05, 'learning_rate/action_query_proj': 9.736302760863063e-05, 'learning_rate/base': 2.4340756902157657e-05, 'epoch': 0.55}) +[2026-07-27 09:28:33,321][starVLA.training.train_starvla][INFO] - Step 4531, Loss: {'train/loss': 0.22219061851501465, 'train/grad_norm_pre_clip': 7.055575370788574, 'timing/data': 0.00017406605184078217, 'timing/model': 0.4632189143449068, 'learning_rate/action_model': 9.735315994426476e-05, 'learning_rate/action_query_proj': 9.735315994426476e-05, 'learning_rate/base': 2.433828998606619e-05, 'epoch': 0.55}) +[2026-07-27 09:28:38,901][starVLA.training.train_starvla][INFO] - Step 4532, Loss: {'train/loss': 0.12784621119499207, 'train/grad_norm_pre_clip': 5.3664679527282715, 'timing/data': 0.0001751333475112915, 'timing/model': 0.4751406628638506, 'learning_rate/action_model': 9.734327437518961e-05, 'learning_rate/action_query_proj': 9.734327437518961e-05, 'learning_rate/base': 2.4335818593797402e-05, 'epoch': 0.55}) +[2026-07-27 09:28:44,523][starVLA.training.train_starvla][INFO] - Step 4533, Loss: {'train/loss': 0.055077750235795975, 'train/grad_norm_pre_clip': 3.1086502075195312, 'timing/data': 0.0001759510487318039, 'timing/model': 0.46712464466691017, 'learning_rate/action_model': 9.733337090530783e-05, 'learning_rate/action_query_proj': 9.733337090530783e-05, 'learning_rate/base': 2.433334272632696e-05, 'epoch': 0.55}) +[2026-07-27 09:28:50,087][starVLA.training.train_starvla][INFO] - Step 4534, Loss: {'train/loss': 0.16753575205802917, 'train/grad_norm_pre_clip': 6.0227742195129395, 'timing/data': 0.00017277337610721588, 'timing/model': 0.4611798785626888, 'learning_rate/action_model': 9.732344953852915e-05, 'learning_rate/action_query_proj': 9.732344953852915e-05, 'learning_rate/base': 2.4330862384632288e-05, 'epoch': 0.55}) +[2026-07-27 09:28:55,601][starVLA.training.train_starvla][INFO] - Step 4535, Loss: {'train/loss': 0.17055028676986694, 'train/grad_norm_pre_clip': 5.654818058013916, 'timing/data': 0.00017817877233028412, 'timing/model': 0.4610077943652868, 'learning_rate/action_model': 9.73135102787704e-05, 'learning_rate/action_query_proj': 9.73135102787704e-05, 'learning_rate/base': 2.43283775696926e-05, 'epoch': 0.55}) +[2026-07-27 09:29:01,215][starVLA.training.train_starvla][INFO] - Step 4536, Loss: {'train/loss': 0.03729487955570221, 'train/grad_norm_pre_clip': 2.867772102355957, 'timing/data': 0.00017184577882289886, 'timing/model': 0.46766792610287666, 'learning_rate/action_model': 9.73035531299554e-05, 'learning_rate/action_query_proj': 9.73035531299554e-05, 'learning_rate/base': 2.432588828248885e-05, 'epoch': 0.55}) +[2026-07-27 09:29:06,844][starVLA.training.train_starvla][INFO] - Step 4537, Loss: {'train/loss': 0.09294869750738144, 'train/grad_norm_pre_clip': 4.398406028747559, 'timing/data': 0.00017446093261241913, 'timing/model': 0.4716146867722273, 'learning_rate/action_model': 9.72935780960151e-05, 'learning_rate/action_query_proj': 9.72935780960151e-05, 'learning_rate/base': 2.4323394524003775e-05, 'epoch': 0.55}) +[2026-07-27 09:29:12,434][starVLA.training.train_starvla][INFO] - Step 4538, Loss: {'train/loss': 0.038813039660453796, 'train/grad_norm_pre_clip': 2.4348666667938232, 'timing/data': 0.00017799623310565948, 'timing/model': 0.46937285736203194, 'learning_rate/action_model': 9.728358518088747e-05, 'learning_rate/action_query_proj': 9.728358518088747e-05, 'learning_rate/base': 2.4320896295221867e-05, 'epoch': 0.55}) +[2026-07-27 09:29:18,069][starVLA.training.train_starvla][INFO] - Step 4539, Loss: {'train/loss': 0.10382039099931717, 'train/grad_norm_pre_clip': 4.000089645385742, 'timing/data': 0.00018675997853279114, 'timing/model': 0.46999987587332726, 'learning_rate/action_model': 9.727357438851757e-05, 'learning_rate/action_query_proj': 9.727357438851757e-05, 'learning_rate/base': 2.4318393597129393e-05, 'epoch': 0.55}) +[2026-07-27 09:29:23,677][starVLA.training.train_starvla][INFO] - Step 4540, Loss: {'train/loss': 0.10118505358695984, 'train/grad_norm_pre_clip': 4.389496803283691, 'timing/data': 0.00017178989946842194, 'timing/model': 0.47236062958836555, 'learning_rate/action_model': 9.72635457228575e-05, 'learning_rate/action_query_proj': 9.72635457228575e-05, 'learning_rate/base': 2.4315886430714374e-05, 'epoch': 0.55}) +[2026-07-27 09:29:29,312][starVLA.training.train_starvla][INFO] - Step 4541, Loss: {'train/loss': 0.1767023503780365, 'train/grad_norm_pre_clip': 5.031693935394287, 'timing/data': 0.000171024352312088, 'timing/model': 0.4771276265382767, 'learning_rate/action_model': 9.72534991878664e-05, 'learning_rate/action_query_proj': 9.72534991878664e-05, 'learning_rate/base': 2.43133747969666e-05, 'epoch': 0.55}) +[2026-07-27 09:29:35,163][starVLA.training.train_starvla][INFO] - Step 4542, Loss: {'train/loss': 0.06998509913682938, 'train/grad_norm_pre_clip': 3.166102170944214, 'timing/data': 0.00017425045371055603, 'timing/model': 0.4692528657615185, 'learning_rate/action_model': 9.724343478751052e-05, 'learning_rate/action_query_proj': 9.724343478751052e-05, 'learning_rate/base': 2.431085869687763e-05, 'epoch': 0.55}) +[2026-07-27 09:29:40,700][starVLA.training.train_starvla][INFO] - Step 4543, Loss: {'train/loss': 0.08620022237300873, 'train/grad_norm_pre_clip': 3.7271580696105957, 'timing/data': 0.00017816759645938873, 'timing/model': 0.4676294941455126, 'learning_rate/action_model': 9.723335252576309e-05, 'learning_rate/action_query_proj': 9.723335252576309e-05, 'learning_rate/base': 2.4308338131440773e-05, 'epoch': 0.55}) +[2026-07-27 09:29:46,209][starVLA.training.train_starvla][INFO] - Step 4544, Loss: {'train/loss': 0.12117992341518402, 'train/grad_norm_pre_clip': 3.648817300796509, 'timing/data': 0.0001756679266691208, 'timing/model': 0.4577515460550785, 'learning_rate/action_model': 9.722325240660445e-05, 'learning_rate/action_query_proj': 9.722325240660445e-05, 'learning_rate/base': 2.4305813101651112e-05, 'epoch': 0.55}) +[2026-07-27 09:29:51,726][starVLA.training.train_starvla][INFO] - Step 4545, Loss: {'train/loss': 0.07225427031517029, 'train/grad_norm_pre_clip': 2.484898805618286, 'timing/data': 0.00017583370208740234, 'timing/model': 0.4577660132199526, 'learning_rate/action_model': 9.721313443402194e-05, 'learning_rate/action_query_proj': 9.721313443402194e-05, 'learning_rate/base': 2.4303283608505486e-05, 'epoch': 0.55}) +[2026-07-27 09:29:57,275][starVLA.training.train_starvla][INFO] - Step 4546, Loss: {'train/loss': 0.06137540191411972, 'train/grad_norm_pre_clip': 3.51274037361145, 'timing/data': 0.000176992267370224, 'timing/model': 0.45749147795140743, 'learning_rate/action_model': 9.720299861201003e-05, 'learning_rate/action_query_proj': 9.720299861201003e-05, 'learning_rate/base': 2.4300749653002507e-05, 'epoch': 0.55}) +[2026-07-27 09:30:02,822][starVLA.training.train_starvla][INFO] - Step 4547, Loss: {'train/loss': 0.1922781616449356, 'train/grad_norm_pre_clip': 4.66307258605957, 'timing/data': 0.00019795261323451996, 'timing/model': 0.4575015790760517, 'learning_rate/action_model': 9.719284494457012e-05, 'learning_rate/action_query_proj': 9.719284494457012e-05, 'learning_rate/base': 2.429821123614253e-05, 'epoch': 0.55}) +[2026-07-27 09:30:08,323][starVLA.training.train_starvla][INFO] - Step 4548, Loss: {'train/loss': 0.058723896741867065, 'train/grad_norm_pre_clip': 2.939375877380371, 'timing/data': 0.00017561577260494232, 'timing/model': 0.45776309445500374, 'learning_rate/action_model': 9.718267343571073e-05, 'learning_rate/action_query_proj': 9.718267343571073e-05, 'learning_rate/base': 2.429566835892768e-05, 'epoch': 0.55}) +[2026-07-27 09:30:13,832][starVLA.training.train_starvla][INFO] - Step 4549, Loss: {'train/loss': 0.05075710639357567, 'train/grad_norm_pre_clip': 3.129897356033325, 'timing/data': 0.00018384866416454315, 'timing/model': 0.4563432205468416, 'learning_rate/action_model': 9.717248408944745e-05, 'learning_rate/action_query_proj': 9.717248408944745e-05, 'learning_rate/base': 2.4293121022361863e-05, 'epoch': 0.55}) +[2026-07-27 09:30:19,345][starVLA.training.train_starvla][INFO] - Step 4550, Loss: {'train/loss': 0.057307206094264984, 'train/grad_norm_pre_clip': 3.1234426498413086, 'timing/data': 0.00018100999295711517, 'timing/model': 0.4571602288633585, 'learning_rate/action_model': 9.716227690980283e-05, 'learning_rate/action_query_proj': 9.716227690980283e-05, 'learning_rate/base': 2.4290569227450707e-05, 'epoch': 0.55}) +[2026-07-27 09:30:24,856][starVLA.training.train_starvla][INFO] - Step 4551, Loss: {'train/loss': 0.11831280589103699, 'train/grad_norm_pre_clip': 5.539114952087402, 'timing/data': 0.00018668174743652344, 'timing/model': 0.45728629641234875, 'learning_rate/action_model': 9.715205190080652e-05, 'learning_rate/action_query_proj': 9.715205190080652e-05, 'learning_rate/base': 2.428801297520163e-05, 'epoch': 0.55}) +[2026-07-27 09:30:30,351][starVLA.training.train_starvla][INFO] - Step 4552, Loss: {'train/loss': 0.16089414060115814, 'train/grad_norm_pre_clip': 4.569461345672607, 'timing/data': 0.00017676502466201782, 'timing/model': 0.45611616782844067, 'learning_rate/action_model': 9.71418090664952e-05, 'learning_rate/action_query_proj': 9.71418090664952e-05, 'learning_rate/base': 2.42854522666238e-05, 'epoch': 0.55}) +[2026-07-27 09:30:35,876][starVLA.training.train_starvla][INFO] - Step 4553, Loss: {'train/loss': 0.04726451262831688, 'train/grad_norm_pre_clip': 2.6791231632232666, 'timing/data': 0.00018076971173286438, 'timing/model': 0.4573030546307564, 'learning_rate/action_model': 9.713154841091254e-05, 'learning_rate/action_query_proj': 9.713154841091254e-05, 'learning_rate/base': 2.4282887102728134e-05, 'epoch': 0.55}) +[2026-07-27 09:30:41,393][starVLA.training.train_starvla][INFO] - Step 4554, Loss: {'train/loss': 0.07714928686618805, 'train/grad_norm_pre_clip': 3.6867268085479736, 'timing/data': 0.00017587654292583466, 'timing/model': 0.45681910403072834, 'learning_rate/action_model': 9.712126993810933e-05, 'learning_rate/action_query_proj': 9.712126993810933e-05, 'learning_rate/base': 2.4280317484527334e-05, 'epoch': 0.55}) +[2026-07-27 09:30:46,901][starVLA.training.train_starvla][INFO] - Step 4555, Loss: {'train/loss': 0.0258109662681818, 'train/grad_norm_pre_clip': 1.7488712072372437, 'timing/data': 0.00017620064318180084, 'timing/model': 0.45608759857714176, 'learning_rate/action_model': 9.711097365214335e-05, 'learning_rate/action_query_proj': 9.711097365214335e-05, 'learning_rate/base': 2.4277743413035837e-05, 'epoch': 0.55}) +[2026-07-27 09:30:52,398][starVLA.training.train_starvla][INFO] - Step 4556, Loss: {'train/loss': 0.062581866979599, 'train/grad_norm_pre_clip': 2.9941916465759277, 'timing/data': 0.00018405728042125702, 'timing/model': 0.46145838499069214, 'learning_rate/action_model': 9.710065955707938e-05, 'learning_rate/action_query_proj': 9.710065955707938e-05, 'learning_rate/base': 2.4275164889269844e-05, 'epoch': 0.55}) +[2026-07-27 09:30:57,945][starVLA.training.train_starvla][INFO] - Step 4557, Loss: {'train/loss': 0.08310014754533768, 'train/grad_norm_pre_clip': 3.183457136154175, 'timing/data': 0.00017775967717170715, 'timing/model': 0.45956181548535824, 'learning_rate/action_model': 9.709032765698926e-05, 'learning_rate/action_query_proj': 9.709032765698926e-05, 'learning_rate/base': 2.4272581914247316e-05, 'epoch': 0.55}) +[2026-07-27 09:31:03,475][starVLA.training.train_starvla][INFO] - Step 4558, Loss: {'train/loss': 0.02342231199145317, 'train/grad_norm_pre_clip': 1.6247730255126953, 'timing/data': 0.00021984055638313293, 'timing/model': 0.45796728506684303, 'learning_rate/action_model': 9.70799779559519e-05, 'learning_rate/action_query_proj': 9.70799779559519e-05, 'learning_rate/base': 2.4269994488987973e-05, 'epoch': 0.55}) +[2026-07-27 09:31:09,030][starVLA.training.train_starvla][INFO] - Step 4559, Loss: {'train/loss': 0.09828504174947739, 'train/grad_norm_pre_clip': 2.903282880783081, 'timing/data': 0.00018402934074401855, 'timing/model': 0.4612281620502472, 'learning_rate/action_model': 9.706961045805315e-05, 'learning_rate/action_query_proj': 9.706961045805315e-05, 'learning_rate/base': 2.426740261451329e-05, 'epoch': 0.55}) +[2026-07-27 09:31:14,545][starVLA.training.train_starvla][INFO] - Step 4560, Loss: {'train/loss': 0.09737122058868408, 'train/grad_norm_pre_clip': 2.872215509414673, 'timing/data': 0.0001743864268064499, 'timing/model': 0.4609901886433363, 'learning_rate/action_model': 9.705922516738596e-05, 'learning_rate/action_query_proj': 9.705922516738596e-05, 'learning_rate/base': 2.426480629184649e-05, 'epoch': 0.55}) +[2026-07-27 09:31:20,127][starVLA.training.train_starvla][INFO] - Step 4561, Loss: {'train/loss': 0.07511018216609955, 'train/grad_norm_pre_clip': 3.338348388671875, 'timing/data': 0.00018839910626411438, 'timing/model': 0.47316781990230083, 'learning_rate/action_model': 9.704882208805029e-05, 'learning_rate/action_query_proj': 9.704882208805029e-05, 'learning_rate/base': 2.426220552201257e-05, 'epoch': 0.55}) +[2026-07-27 09:31:25,715][starVLA.training.train_starvla][INFO] - Step 4562, Loss: {'train/loss': 0.07177260518074036, 'train/grad_norm_pre_clip': 2.489285469055176, 'timing/data': 0.00017792731523513794, 'timing/model': 0.4774584472179413, 'learning_rate/action_model': 9.703840122415306e-05, 'learning_rate/action_query_proj': 9.703840122415306e-05, 'learning_rate/base': 2.4259600306038266e-05, 'epoch': 0.55}) +[2026-07-27 09:31:31,294][starVLA.training.train_starvla][INFO] - Step 4563, Loss: {'train/loss': 0.04195959120988846, 'train/grad_norm_pre_clip': 2.623293876647949, 'timing/data': 0.00017507001757621765, 'timing/model': 0.4745714571326971, 'learning_rate/action_model': 9.702796257980835e-05, 'learning_rate/action_query_proj': 9.702796257980835e-05, 'learning_rate/base': 2.4256990644952087e-05, 'epoch': 0.55}) +[2026-07-27 09:31:36,846][starVLA.training.train_starvla][INFO] - Step 4564, Loss: {'train/loss': 0.07342423498630524, 'train/grad_norm_pre_clip': 3.4942142963409424, 'timing/data': 0.0001774802803993225, 'timing/model': 0.46215978264808655, 'learning_rate/action_model': 9.701750615913707e-05, 'learning_rate/action_query_proj': 9.701750615913707e-05, 'learning_rate/base': 2.425437653978427e-05, 'epoch': 0.55}) +[2026-07-27 09:31:42,412][starVLA.training.train_starvla][INFO] - Step 4565, Loss: {'train/loss': 0.01316073164343834, 'train/grad_norm_pre_clip': 0.8899408578872681, 'timing/data': 0.00019298307597637177, 'timing/model': 0.46099985018372536, 'learning_rate/action_model': 9.700703196626731e-05, 'learning_rate/action_query_proj': 9.700703196626731e-05, 'learning_rate/base': 2.4251757991566827e-05, 'epoch': 0.55}) +[2026-07-27 09:31:47,933][starVLA.training.train_starvla][INFO] - Step 4566, Loss: {'train/loss': 0.09607680886983871, 'train/grad_norm_pre_clip': 4.267332553863525, 'timing/data': 0.0001756623387336731, 'timing/model': 0.46094285137951374, 'learning_rate/action_model': 9.699654000533413e-05, 'learning_rate/action_query_proj': 9.699654000533413e-05, 'learning_rate/base': 2.4249135001333532e-05, 'epoch': 0.55}) +[2026-07-27 09:31:53,453][starVLA.training.train_starvla][INFO] - Step 4567, Loss: {'train/loss': 0.0863097757101059, 'train/grad_norm_pre_clip': 1.8200644254684448, 'timing/data': 0.0001785755157470703, 'timing/model': 0.46100679971277714, 'learning_rate/action_model': 9.698603028047954e-05, 'learning_rate/action_query_proj': 9.698603028047954e-05, 'learning_rate/base': 2.4246507570119884e-05, 'epoch': 0.55}) +[2026-07-27 09:31:58,976][starVLA.training.train_starvla][INFO] - Step 4568, Loss: {'train/loss': 0.1313301920890808, 'train/grad_norm_pre_clip': 4.440939426422119, 'timing/data': 0.00017797574400901794, 'timing/model': 0.4588967617601156, 'learning_rate/action_model': 9.697550279585263e-05, 'learning_rate/action_query_proj': 9.697550279585263e-05, 'learning_rate/base': 2.4243875698963157e-05, 'epoch': 0.55}) +[2026-07-27 09:32:04,506][starVLA.training.train_starvla][INFO] - Step 4569, Loss: {'train/loss': 0.14902405440807343, 'train/grad_norm_pre_clip': 4.386959552764893, 'timing/data': 0.0001740194857120514, 'timing/model': 0.46097069419920444, 'learning_rate/action_model': 9.69649575556095e-05, 'learning_rate/action_query_proj': 9.69649575556095e-05, 'learning_rate/base': 2.4241239388902375e-05, 'epoch': 0.55}) +[2026-07-27 09:32:10,031][starVLA.training.train_starvla][INFO] - Step 4570, Loss: {'train/loss': 0.11569447070360184, 'train/grad_norm_pre_clip': 5.04451322555542, 'timing/data': 0.00022062845528125763, 'timing/model': 0.46063026785850525, 'learning_rate/action_model': 9.695439456391323e-05, 'learning_rate/action_query_proj': 9.695439456391323e-05, 'learning_rate/base': 2.4238598640978308e-05, 'epoch': 0.55}) +[2026-07-27 09:32:15,564][starVLA.training.train_starvla][INFO] - Step 4571, Loss: {'train/loss': 0.0774901732802391, 'train/grad_norm_pre_clip': 2.9218809604644775, 'timing/data': 0.0001763962209224701, 'timing/model': 0.4604054968804121, 'learning_rate/action_model': 9.694381382493394e-05, 'learning_rate/action_query_proj': 9.694381382493394e-05, 'learning_rate/base': 2.4235953456233485e-05, 'epoch': 0.55}) +[2026-07-27 09:32:21,138][starVLA.training.train_starvla][INFO] - Step 4572, Loss: {'train/loss': 0.093407042324543, 'train/grad_norm_pre_clip': 2.1151392459869385, 'timing/data': 0.00017488934099674225, 'timing/model': 0.461969967931509, 'learning_rate/action_model': 9.693321534284872e-05, 'learning_rate/action_query_proj': 9.693321534284872e-05, 'learning_rate/base': 2.423330383571218e-05, 'epoch': 0.55}) +[2026-07-27 09:32:26,703][starVLA.training.train_starvla][INFO] - Step 4573, Loss: {'train/loss': 0.19951242208480835, 'train/grad_norm_pre_clip': 3.6848597526550293, 'timing/data': 0.00017785094678401947, 'timing/model': 0.4618050903081894, 'learning_rate/action_model': 9.692259912184169e-05, 'learning_rate/action_query_proj': 9.692259912184169e-05, 'learning_rate/base': 2.4230649780460422e-05, 'epoch': 0.55}) +[2026-07-27 09:32:32,270][starVLA.training.train_starvla][INFO] - Step 4574, Loss: {'train/loss': 0.10352339595556259, 'train/grad_norm_pre_clip': 3.990182638168335, 'timing/data': 0.00018047913908958435, 'timing/model': 0.45991732738912106, 'learning_rate/action_model': 9.691196516610395e-05, 'learning_rate/action_query_proj': 9.691196516610395e-05, 'learning_rate/base': 2.4227991291525987e-05, 'epoch': 0.55}) +[2026-07-27 09:32:38,099][starVLA.training.train_starvla][INFO] - Step 4575, Loss: {'train/loss': 0.1388258934020996, 'train/grad_norm_pre_clip': 3.552680253982544, 'timing/data': 0.00018792785704135895, 'timing/model': 0.46128689125180244, 'learning_rate/action_model': 9.690131347983364e-05, 'learning_rate/action_query_proj': 9.690131347983364e-05, 'learning_rate/base': 2.422532836995841e-05, 'epoch': 0.55}) +[2026-07-27 09:32:43,650][starVLA.training.train_starvla][INFO] - Step 4576, Loss: {'train/loss': 0.1757870316505432, 'train/grad_norm_pre_clip': 4.541076183319092, 'timing/data': 0.0001882612705230713, 'timing/model': 0.45836658775806427, 'learning_rate/action_model': 9.689064406723585e-05, 'learning_rate/action_query_proj': 9.689064406723585e-05, 'learning_rate/base': 2.4222661016808963e-05, 'epoch': 0.56}) +[2026-07-27 09:32:49,448][starVLA.training.train_starvla][INFO] - Step 4577, Loss: {'train/loss': 0.1517883837223053, 'train/grad_norm_pre_clip': 4.45289945602417, 'timing/data': 0.00018528476357460022, 'timing/model': 0.45776329562067986, 'learning_rate/action_model': 9.687995693252274e-05, 'learning_rate/action_query_proj': 9.687995693252274e-05, 'learning_rate/base': 2.4219989233130686e-05, 'epoch': 0.56}) +[2026-07-27 09:32:54,974][starVLA.training.train_starvla][INFO] - Step 4578, Loss: {'train/loss': 0.22735026478767395, 'train/grad_norm_pre_clip': 4.638712406158447, 'timing/data': 0.00018498115241527557, 'timing/model': 0.45749407075345516, 'learning_rate/action_model': 9.686925207991339e-05, 'learning_rate/action_query_proj': 9.686925207991339e-05, 'learning_rate/base': 2.4217313019978348e-05, 'epoch': 0.56}) +[2026-07-27 09:33:00,510][starVLA.training.train_starvla][INFO] - Step 4579, Loss: {'train/loss': 0.14956343173980713, 'train/grad_norm_pre_clip': 4.286101818084717, 'timing/data': 0.00019431114196777344, 'timing/model': 0.456262931227684, 'learning_rate/action_model': 9.68585295136339e-05, 'learning_rate/action_query_proj': 9.68585295136339e-05, 'learning_rate/base': 2.4214632378408474e-05, 'epoch': 0.56}) +[2026-07-27 09:33:06,051][starVLA.training.train_starvla][INFO] - Step 4580, Loss: {'train/loss': 0.06489253044128418, 'train/grad_norm_pre_clip': 1.8444736003875732, 'timing/data': 0.00020167790353298187, 'timing/model': 0.45726324431598186, 'learning_rate/action_model': 9.684778923791739e-05, 'learning_rate/action_query_proj': 9.684778923791739e-05, 'learning_rate/base': 2.4211947309479347e-05, 'epoch': 0.56}) +[2026-07-27 09:33:11,610][starVLA.training.train_starvla][INFO] - Step 4581, Loss: {'train/loss': 0.121794193983078, 'train/grad_norm_pre_clip': 4.199888706207275, 'timing/data': 0.00018597766757011414, 'timing/model': 0.4622784350067377, 'learning_rate/action_model': 9.683703125700392e-05, 'learning_rate/action_query_proj': 9.683703125700392e-05, 'learning_rate/base': 2.420925781425098e-05, 'epoch': 0.56}) +[2026-07-27 09:33:17,158][starVLA.training.train_starvla][INFO] - Step 4582, Loss: {'train/loss': 0.09790368378162384, 'train/grad_norm_pre_clip': 3.577484369277954, 'timing/data': 0.0001828353852033615, 'timing/model': 0.46236037090420723, 'learning_rate/action_model': 9.682625557514062e-05, 'learning_rate/action_query_proj': 9.682625557514062e-05, 'learning_rate/base': 2.4206563893785156e-05, 'epoch': 0.56}) +[2026-07-27 09:33:22,702][starVLA.training.train_starvla][INFO] - Step 4583, Loss: {'train/loss': 0.1568676233291626, 'train/grad_norm_pre_clip': 3.7556729316711426, 'timing/data': 0.00018411315977573395, 'timing/model': 0.45814239606261253, 'learning_rate/action_model': 9.68154621965815e-05, 'learning_rate/action_query_proj': 9.68154621965815e-05, 'learning_rate/base': 2.4203865549145376e-05, 'epoch': 0.56}) +[2026-07-27 09:33:28,232][starVLA.training.train_starvla][INFO] - Step 4584, Loss: {'train/loss': 0.10149580240249634, 'train/grad_norm_pre_clip': 2.0660784244537354, 'timing/data': 0.00024010613560676575, 'timing/model': 0.45686101354658604, 'learning_rate/action_model': 9.680465112558767e-05, 'learning_rate/action_query_proj': 9.680465112558767e-05, 'learning_rate/base': 2.4201162781396917e-05, 'epoch': 0.56}) +[2026-07-27 09:33:33,840][starVLA.training.train_starvla][INFO] - Step 4585, Loss: {'train/loss': 0.17232653498649597, 'train/grad_norm_pre_clip': 5.227311134338379, 'timing/data': 0.00018663518130779266, 'timing/model': 0.45657062344253063, 'learning_rate/action_model': 9.679382236642713e-05, 'learning_rate/action_query_proj': 9.679382236642713e-05, 'learning_rate/base': 2.4198455591606783e-05, 'epoch': 0.56}) +[2026-07-27 09:33:39,367][starVLA.training.train_starvla][INFO] - Step 4586, Loss: {'train/loss': 0.13375315070152283, 'train/grad_norm_pre_clip': 3.6463139057159424, 'timing/data': 0.00019375234842300415, 'timing/model': 0.4572816453874111, 'learning_rate/action_model': 9.678297592337493e-05, 'learning_rate/action_query_proj': 9.678297592337493e-05, 'learning_rate/base': 2.4195743980843733e-05, 'epoch': 0.56}) +[2026-07-27 09:33:44,899][starVLA.training.train_starvla][INFO] - Step 4587, Loss: {'train/loss': 0.2132398933172226, 'train/grad_norm_pre_clip': 5.06911039352417, 'timing/data': 0.00017409585416316986, 'timing/model': 0.45814695581793785, 'learning_rate/action_model': 9.677211180071304e-05, 'learning_rate/action_query_proj': 9.677211180071304e-05, 'learning_rate/base': 2.419302795017826e-05, 'epoch': 0.56}) +[2026-07-27 09:33:50,426][starVLA.training.train_starvla][INFO] - Step 4588, Loss: {'train/loss': 0.03999410197138786, 'train/grad_norm_pre_clip': 2.1861979961395264, 'timing/data': 0.0002598930150270462, 'timing/model': 0.4586291890591383, 'learning_rate/action_model': 9.676123000273049e-05, 'learning_rate/action_query_proj': 9.676123000273049e-05, 'learning_rate/base': 2.4190307500682622e-05, 'epoch': 0.56}) +[2026-07-27 09:33:55,973][starVLA.training.train_starvla][INFO] - Step 4589, Loss: {'train/loss': 0.11916112154722214, 'train/grad_norm_pre_clip': 3.551313877105713, 'timing/data': 0.00017411261796951294, 'timing/model': 0.4572686739265919, 'learning_rate/action_model': 9.675033053372322e-05, 'learning_rate/action_query_proj': 9.675033053372322e-05, 'learning_rate/base': 2.4187582633430804e-05, 'epoch': 0.56}) +[2026-07-27 09:34:01,492][starVLA.training.train_starvla][INFO] - Step 4590, Loss: {'train/loss': 0.05885918810963631, 'train/grad_norm_pre_clip': 2.2814080715179443, 'timing/data': 0.00018043816089630127, 'timing/model': 0.45685033313930035, 'learning_rate/action_model': 9.673941339799412e-05, 'learning_rate/action_query_proj': 9.673941339799412e-05, 'learning_rate/base': 2.418485334949853e-05, 'epoch': 0.56}) +[2026-07-27 09:34:07,015][starVLA.training.train_starvla][INFO] - Step 4591, Loss: {'train/loss': 0.12797358632087708, 'train/grad_norm_pre_clip': 3.2400035858154297, 'timing/data': 0.00017605721950531006, 'timing/model': 0.45763211511075497, 'learning_rate/action_model': 9.672847859985318e-05, 'learning_rate/action_query_proj': 9.672847859985318e-05, 'learning_rate/base': 2.4182119649963294e-05, 'epoch': 0.56}) +[2026-07-27 09:34:12,539][starVLA.training.train_starvla][INFO] - Step 4592, Loss: {'train/loss': 0.20261318981647491, 'train/grad_norm_pre_clip': 5.921366214752197, 'timing/data': 0.00017952919006347656, 'timing/model': 0.45773380249738693, 'learning_rate/action_model': 9.671752614361726e-05, 'learning_rate/action_query_proj': 9.671752614361726e-05, 'learning_rate/base': 2.4179381535904314e-05, 'epoch': 0.56}) +[2026-07-27 09:34:18,110][starVLA.training.train_starvla][INFO] - Step 4593, Loss: {'train/loss': 0.08100377023220062, 'train/grad_norm_pre_clip': 2.5312530994415283, 'timing/data': 0.0002436283975839615, 'timing/model': 0.45734427124261856, 'learning_rate/action_model': 9.670655603361018e-05, 'learning_rate/action_query_proj': 9.670655603361018e-05, 'learning_rate/base': 2.4176639008402545e-05, 'epoch': 0.56}) +[2026-07-27 09:34:23,618][starVLA.training.train_starvla][INFO] - Step 4594, Loss: {'train/loss': 0.06157347187399864, 'train/grad_norm_pre_clip': 3.0619428157806396, 'timing/data': 0.00018871575593948364, 'timing/model': 0.45643327571451664, 'learning_rate/action_model': 9.669556827416282e-05, 'learning_rate/action_query_proj': 9.669556827416282e-05, 'learning_rate/base': 2.4173892068540704e-05, 'epoch': 0.56}) +[2026-07-27 09:34:29,139][starVLA.training.train_starvla][INFO] - Step 4595, Loss: {'train/loss': 0.06102738156914711, 'train/grad_norm_pre_clip': 2.4337496757507324, 'timing/data': 0.0001852177083492279, 'timing/model': 0.4561335016041994, 'learning_rate/action_model': 9.668456286961291e-05, 'learning_rate/action_query_proj': 9.668456286961291e-05, 'learning_rate/base': 2.4171140717403227e-05, 'epoch': 0.56}) +[2026-07-27 09:34:34,784][starVLA.training.train_starvla][INFO] - Step 4596, Loss: {'train/loss': 0.07859323173761368, 'train/grad_norm_pre_clip': 2.1354217529296875, 'timing/data': 0.00019124522805213928, 'timing/model': 0.4720818158239126, 'learning_rate/action_model': 9.667353982430528e-05, 'learning_rate/action_query_proj': 9.667353982430528e-05, 'learning_rate/base': 2.416838495607632e-05, 'epoch': 0.56}) +[2026-07-27 09:34:40,364][starVLA.training.train_starvla][INFO] - Step 4597, Loss: {'train/loss': 0.09809117019176483, 'train/grad_norm_pre_clip': 2.9382684230804443, 'timing/data': 0.00021645985543727875, 'timing/model': 0.47171349078416824, 'learning_rate/action_model': 9.666249914259162e-05, 'learning_rate/action_query_proj': 9.666249914259162e-05, 'learning_rate/base': 2.4165624785647904e-05, 'epoch': 0.56}) +[2026-07-27 09:34:45,929][starVLA.training.train_starvla][INFO] - Step 4598, Loss: {'train/loss': 0.046868011355400085, 'train/grad_norm_pre_clip': 2.2520194053649902, 'timing/data': 0.0001961439847946167, 'timing/model': 0.46863185800611973, 'learning_rate/action_model': 9.665144082883059e-05, 'learning_rate/action_query_proj': 9.665144082883059e-05, 'learning_rate/base': 2.4162860207207646e-05, 'epoch': 0.56}) +[2026-07-27 09:34:51,478][starVLA.training.train_starvla][INFO] - Step 4599, Loss: {'train/loss': 0.10039199888706207, 'train/grad_norm_pre_clip': 2.7582221031188965, 'timing/data': 0.00018256716430187225, 'timing/model': 0.4621140267699957, 'learning_rate/action_model': 9.664036488738788e-05, 'learning_rate/action_query_proj': 9.664036488738788e-05, 'learning_rate/base': 2.416009122184697e-05, 'epoch': 0.56}) +[2026-07-27 09:34:57,018][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 4600 +[2026-07-27 09:34:57,019][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 4600 +[2026-07-27 09:34:57,020][starVLA.training.train_starvla][INFO] - Step 4600, Loss: {'train/loss': 0.040006738156080246, 'train/grad_norm_pre_clip': 1.8448735475540161, 'timing/data': 0.00019050203263759613, 'timing/model': 0.46295960061252117, 'learning_rate/action_model': 9.662927132263607e-05, 'learning_rate/action_query_proj': 9.662927132263607e-05, 'learning_rate/base': 2.4157317830659017e-05, 'epoch': 0.56}) +[2026-07-27 09:35:02,552][starVLA.training.train_starvla][INFO] - Step 4601, Loss: {'train/loss': 0.040775515139102936, 'train/grad_norm_pre_clip': 2.2655751705169678, 'timing/data': 0.00019305013120174408, 'timing/model': 0.46296625956892967, 'learning_rate/action_model': 9.661816013895474e-05, 'learning_rate/action_query_proj': 9.661816013895474e-05, 'learning_rate/base': 2.4154540034738685e-05, 'epoch': 0.56}) +[2026-07-27 09:35:08,082][starVLA.training.train_starvla][INFO] - Step 4602, Loss: {'train/loss': 0.06339319795370102, 'train/grad_norm_pre_clip': 2.65440034866333, 'timing/data': 0.0002491343766450882, 'timing/model': 0.4630236644297838, 'learning_rate/action_model': 9.66070313407304e-05, 'learning_rate/action_query_proj': 9.66070313407304e-05, 'learning_rate/base': 2.41517578351826e-05, 'epoch': 0.56}) +[2026-07-27 09:35:13,619][starVLA.training.train_starvla][INFO] - Step 4603, Loss: {'train/loss': 0.06860771030187607, 'train/grad_norm_pre_clip': 2.1274354457855225, 'timing/data': 0.0001871064305305481, 'timing/model': 0.46131489239633083, 'learning_rate/action_model': 9.659588493235653e-05, 'learning_rate/action_query_proj': 9.659588493235653e-05, 'learning_rate/base': 2.414897123308913e-05, 'epoch': 0.56}) +[2026-07-27 09:35:19,147][starVLA.training.train_starvla][INFO] - Step 4604, Loss: {'train/loss': 0.10441333800554276, 'train/grad_norm_pre_clip': 3.672701120376587, 'timing/data': 0.0001803133636713028, 'timing/model': 0.46265860833227634, 'learning_rate/action_model': 9.658472091823355e-05, 'learning_rate/action_query_proj': 9.658472091823355e-05, 'learning_rate/base': 2.4146180229558388e-05, 'epoch': 0.56}) +[2026-07-27 09:35:24,667][starVLA.training.train_starvla][INFO] - Step 4605, Loss: {'train/loss': 0.0587819442152977, 'train/grad_norm_pre_clip': 2.4183738231658936, 'timing/data': 0.00017152167856693268, 'timing/model': 0.46258969232439995, 'learning_rate/action_model': 9.657353930276884e-05, 'learning_rate/action_query_proj': 9.657353930276884e-05, 'learning_rate/base': 2.414338482569221e-05, 'epoch': 0.56}) +[2026-07-27 09:35:30,185][starVLA.training.train_starvla][INFO] - Step 4606, Loss: {'train/loss': 0.05743858963251114, 'train/grad_norm_pre_clip': 2.6669743061065674, 'timing/data': 0.00019721128046512604, 'timing/model': 0.4618094749748707, 'learning_rate/action_model': 9.656234009037672e-05, 'learning_rate/action_query_proj': 9.656234009037672e-05, 'learning_rate/base': 2.414058502259418e-05, 'epoch': 0.56}) +[2026-07-27 09:35:35,702][starVLA.training.train_starvla][INFO] - Step 4607, Loss: {'train/loss': 0.14115753769874573, 'train/grad_norm_pre_clip': 3.947362184524536, 'timing/data': 0.00018145889043807983, 'timing/model': 0.46258887089788914, 'learning_rate/action_model': 9.655112328547846e-05, 'learning_rate/action_query_proj': 9.655112328547846e-05, 'learning_rate/base': 2.4137780821369614e-05, 'epoch': 0.56}) +[2026-07-27 09:35:41,209][starVLA.training.train_starvla][INFO] - Step 4608, Loss: {'train/loss': 0.05181780830025673, 'train/grad_norm_pre_clip': 2.310497760772705, 'timing/data': 0.00022115930914878845, 'timing/model': 0.4572352524846792, 'learning_rate/action_model': 9.653988889250227e-05, 'learning_rate/action_query_proj': 9.653988889250227e-05, 'learning_rate/base': 2.4134972223125567e-05, 'epoch': 0.56}) +[2026-07-27 09:35:46,730][starVLA.training.train_starvla][INFO] - Step 4609, Loss: {'train/loss': 0.11925742775201797, 'train/grad_norm_pre_clip': 3.140167236328125, 'timing/data': 0.00019793398678302765, 'timing/model': 0.4593667071312666, 'learning_rate/action_model': 9.652863691588334e-05, 'learning_rate/action_query_proj': 9.652863691588334e-05, 'learning_rate/base': 2.4132159228970834e-05, 'epoch': 0.56}) +[2026-07-27 09:35:52,246][starVLA.training.train_starvla][INFO] - Step 4610, Loss: {'train/loss': 0.16894462704658508, 'train/grad_norm_pre_clip': 4.008186340332031, 'timing/data': 0.0001843683421611786, 'timing/model': 0.4568517152220011, 'learning_rate/action_model': 9.651736736006375e-05, 'learning_rate/action_query_proj': 9.651736736006375e-05, 'learning_rate/base': 2.4129341840015938e-05, 'epoch': 0.56}) +[2026-07-27 09:35:57,752][starVLA.training.train_starvla][INFO] - Step 4611, Loss: {'train/loss': 0.08882123231887817, 'train/grad_norm_pre_clip': 3.344682455062866, 'timing/data': 0.00019222497940063477, 'timing/model': 0.4568346384912729, 'learning_rate/action_model': 9.650608022949255e-05, 'learning_rate/action_query_proj': 9.650608022949255e-05, 'learning_rate/base': 2.4126520057373138e-05, 'epoch': 0.56}) +[2026-07-27 09:36:03,302][starVLA.training.train_starvla][INFO] - Step 4612, Loss: {'train/loss': 0.18366990983486176, 'train/grad_norm_pre_clip': 4.189249515533447, 'timing/data': 0.00022004172205924988, 'timing/model': 0.4583082366734743, 'learning_rate/action_model': 9.64947755286257e-05, 'learning_rate/action_query_proj': 9.64947755286257e-05, 'learning_rate/base': 2.4123693882156424e-05, 'epoch': 0.56}) +[2026-07-27 09:36:08,832][starVLA.training.train_starvla][INFO] - Step 4613, Loss: {'train/loss': 0.15465883910655975, 'train/grad_norm_pre_clip': 3.6683545112609863, 'timing/data': 0.00021493621170520782, 'timing/model': 0.4579362403601408, 'learning_rate/action_model': 9.648345326192614e-05, 'learning_rate/action_query_proj': 9.648345326192614e-05, 'learning_rate/base': 2.4120863315481535e-05, 'epoch': 0.56}) +[2026-07-27 09:36:14,353][starVLA.training.train_starvla][INFO] - Step 4614, Loss: {'train/loss': 0.13822142779827118, 'train/grad_norm_pre_clip': 3.3775463104248047, 'timing/data': 0.0002232808619737625, 'timing/model': 0.45666302740573883, 'learning_rate/action_model': 9.647211343386371e-05, 'learning_rate/action_query_proj': 9.647211343386371e-05, 'learning_rate/base': 2.4118028358465927e-05, 'epoch': 0.56}) +[2026-07-27 09:36:19,879][starVLA.training.train_starvla][INFO] - Step 4615, Loss: {'train/loss': 0.058837514370679855, 'train/grad_norm_pre_clip': 2.9662232398986816, 'timing/data': 0.0002013128250837326, 'timing/model': 0.4568284172564745, 'learning_rate/action_model': 9.64607560489152e-05, 'learning_rate/action_query_proj': 9.64607560489152e-05, 'learning_rate/base': 2.41151890122288e-05, 'epoch': 0.56}) +[2026-07-27 09:36:25,408][starVLA.training.train_starvla][INFO] - Step 4616, Loss: {'train/loss': 0.06038276106119156, 'train/grad_norm_pre_clip': 2.7589635848999023, 'timing/data': 0.00017858296632766724, 'timing/model': 0.45696957781910896, 'learning_rate/action_model': 9.644938111156433e-05, 'learning_rate/action_query_proj': 9.644938111156433e-05, 'learning_rate/base': 2.4112345277891082e-05, 'epoch': 0.56}) +[2026-07-27 09:36:30,925][starVLA.training.train_starvla][INFO] - Step 4617, Loss: {'train/loss': 0.0871632918715477, 'train/grad_norm_pre_clip': 2.585270881652832, 'timing/data': 0.00018566474318504333, 'timing/model': 0.4566233567893505, 'learning_rate/action_model': 9.643798862630174e-05, 'learning_rate/action_query_proj': 9.643798862630174e-05, 'learning_rate/base': 2.4109497156575435e-05, 'epoch': 0.56}) +[2026-07-27 09:36:36,713][starVLA.training.train_starvla][INFO] - Step 4618, Loss: {'train/loss': 0.02727334573864937, 'train/grad_norm_pre_clip': 1.3357819318771362, 'timing/data': 0.0001769736409187317, 'timing/model': 0.7200597114861012, 'learning_rate/action_model': 9.6426578597625e-05, 'learning_rate/action_query_proj': 9.6426578597625e-05, 'learning_rate/base': 2.410664464940625e-05, 'epoch': 0.56}) +[2026-07-27 09:36:42,378][starVLA.training.train_starvla][INFO] - Step 4619, Loss: {'train/loss': 0.14316658675670624, 'train/grad_norm_pre_clip': 3.454874277114868, 'timing/data': 0.00020096078515052795, 'timing/model': 0.4782395511865616, 'learning_rate/action_model': 9.64151510300386e-05, 'learning_rate/action_query_proj': 9.64151510300386e-05, 'learning_rate/base': 2.410378775750965e-05, 'epoch': 0.56}) +[2026-07-27 09:36:48,189][starVLA.training.train_starvla][INFO] - Step 4620, Loss: {'train/loss': 0.07966101169586182, 'train/grad_norm_pre_clip': 2.930201768875122, 'timing/data': 0.00023185834288597107, 'timing/model': 0.46896697022020817, 'learning_rate/action_model': 9.640370592805399e-05, 'learning_rate/action_query_proj': 9.640370592805399e-05, 'learning_rate/base': 2.4100926482013497e-05, 'epoch': 0.56}) +[2026-07-27 09:36:53,780][starVLA.training.train_starvla][INFO] - Step 4621, Loss: {'train/loss': 0.06503354012966156, 'train/grad_norm_pre_clip': 3.006922483444214, 'timing/data': 0.00018754228949546814, 'timing/model': 0.45923942141234875, 'learning_rate/action_model': 9.63922432961895e-05, 'learning_rate/action_query_proj': 9.63922432961895e-05, 'learning_rate/base': 2.4098060824047376e-05, 'epoch': 0.56}) +[2026-07-27 09:36:59,563][starVLA.training.train_starvla][INFO] - Step 4622, Loss: {'train/loss': 0.08876100182533264, 'train/grad_norm_pre_clip': 3.2722373008728027, 'timing/data': 0.00020626932382583618, 'timing/model': 0.4663023054599762, 'learning_rate/action_model': 9.638076313897037e-05, 'learning_rate/action_query_proj': 9.638076313897037e-05, 'learning_rate/base': 2.4095190784742594e-05, 'epoch': 0.56}) +[2026-07-27 09:37:05,146][starVLA.training.train_starvla][INFO] - Step 4623, Loss: {'train/loss': 0.08571232855319977, 'train/grad_norm_pre_clip': 4.082472324371338, 'timing/data': 0.00021907873451709747, 'timing/model': 0.45986320450901985, 'learning_rate/action_model': 9.636926546092883e-05, 'learning_rate/action_query_proj': 9.636926546092883e-05, 'learning_rate/base': 2.4092316365232208e-05, 'epoch': 0.56}) +[2026-07-27 09:37:10,682][starVLA.training.train_starvla][INFO] - Step 4624, Loss: {'train/loss': 0.14332598447799683, 'train/grad_norm_pre_clip': 4.179749965667725, 'timing/data': 0.00018943101167678833, 'timing/model': 0.45873283967375755, 'learning_rate/action_model': 9.635775026660396e-05, 'learning_rate/action_query_proj': 9.635775026660396e-05, 'learning_rate/base': 2.408943756665099e-05, 'epoch': 0.56}) +[2026-07-27 09:37:16,178][starVLA.training.train_starvla][INFO] - Step 4625, Loss: {'train/loss': 0.12274947762489319, 'train/grad_norm_pre_clip': 4.798685073852539, 'timing/data': 0.00018265843391418457, 'timing/model': 0.4582718089222908, 'learning_rate/action_model': 9.634621756054177e-05, 'learning_rate/action_query_proj': 9.634621756054177e-05, 'learning_rate/base': 2.4086554390135442e-05, 'epoch': 0.56}) +[2026-07-27 09:37:21,748][starVLA.training.train_starvla][INFO] - Step 4626, Loss: {'train/loss': 0.12441644072532654, 'train/grad_norm_pre_clip': 4.258604526519775, 'timing/data': 0.00019439682364463806, 'timing/model': 0.46756283938884735, 'learning_rate/action_model': 9.63346673472952e-05, 'learning_rate/action_query_proj': 9.63346673472952e-05, 'learning_rate/base': 2.40836668368238e-05, 'epoch': 0.56}) +[2026-07-27 09:37:27,314][starVLA.training.train_starvla][INFO] - Step 4627, Loss: {'train/loss': 0.1286994218826294, 'train/grad_norm_pre_clip': 3.906263589859009, 'timing/data': 0.00018855184316635132, 'timing/model': 0.46948875673115253, 'learning_rate/action_model': 9.632309963142407e-05, 'learning_rate/action_query_proj': 9.632309963142407e-05, 'learning_rate/base': 2.408077490785602e-05, 'epoch': 0.56}) +[2026-07-27 09:37:32,886][starVLA.training.train_starvla][INFO] - Step 4628, Loss: {'train/loss': 0.09689248353242874, 'train/grad_norm_pre_clip': 3.876577138900757, 'timing/data': 0.00019579008221626282, 'timing/model': 0.4686453863978386, 'learning_rate/action_model': 9.631151441749517e-05, 'learning_rate/action_query_proj': 9.631151441749517e-05, 'learning_rate/base': 2.407787860437379e-05, 'epoch': 0.56}) +[2026-07-27 09:37:38,541][starVLA.training.train_starvla][INFO] - Step 4629, Loss: {'train/loss': 0.14701074361801147, 'train/grad_norm_pre_clip': 4.762336730957031, 'timing/data': 0.00018112920224666595, 'timing/model': 0.46955359540879726, 'learning_rate/action_model': 9.629991171008213e-05, 'learning_rate/action_query_proj': 9.629991171008213e-05, 'learning_rate/base': 2.407497792752053e-05, 'epoch': 0.56}) +[2026-07-27 09:37:44,105][starVLA.training.train_starvla][INFO] - Step 4630, Loss: {'train/loss': 0.03847124055027962, 'train/grad_norm_pre_clip': 1.9911798238754272, 'timing/data': 0.00018970482051372528, 'timing/model': 0.46569492667913437, 'learning_rate/action_model': 9.628829151376552e-05, 'learning_rate/action_query_proj': 9.628829151376552e-05, 'learning_rate/base': 2.407207287844138e-05, 'epoch': 0.56}) +[2026-07-27 09:37:49,686][starVLA.training.train_starvla][INFO] - Step 4631, Loss: {'train/loss': 0.09955213963985443, 'train/grad_norm_pre_clip': 3.7864930629730225, 'timing/data': 0.00018782541155815125, 'timing/model': 0.4775024466216564, 'learning_rate/action_model': 9.62766538331328e-05, 'learning_rate/action_query_proj': 9.62766538331328e-05, 'learning_rate/base': 2.40691634582832e-05, 'epoch': 0.56}) +[2026-07-27 09:37:55,332][starVLA.training.train_starvla][INFO] - Step 4632, Loss: {'train/loss': 0.16456139087677002, 'train/grad_norm_pre_clip': 4.879166126251221, 'timing/data': 0.0001954156905412674, 'timing/model': 0.4702583570033312, 'learning_rate/action_model': 9.626499867277837e-05, 'learning_rate/action_query_proj': 9.626499867277837e-05, 'learning_rate/base': 2.4066249668194593e-05, 'epoch': 0.56}) +[2026-07-27 09:38:00,943][starVLA.training.train_starvla][INFO] - Step 4633, Loss: {'train/loss': 0.05217570438981056, 'train/grad_norm_pre_clip': 2.735147476196289, 'timing/data': 0.0001904703676700592, 'timing/model': 0.46730840764939785, 'learning_rate/action_model': 9.62533260373035e-05, 'learning_rate/action_query_proj': 9.62533260373035e-05, 'learning_rate/base': 2.4063331509325873e-05, 'epoch': 0.56}) +[2026-07-27 09:38:06,578][starVLA.training.train_starvla][INFO] - Step 4634, Loss: {'train/loss': 0.050453584641218185, 'train/grad_norm_pre_clip': 2.0896918773651123, 'timing/data': 0.00019464828073978424, 'timing/model': 0.4697552938014269, 'learning_rate/action_model': 9.624163593131632e-05, 'learning_rate/action_query_proj': 9.624163593131632e-05, 'learning_rate/base': 2.406040898282908e-05, 'epoch': 0.56}) +[2026-07-27 09:38:12,245][starVLA.training.train_starvla][INFO] - Step 4635, Loss: {'train/loss': 0.052584659308195114, 'train/grad_norm_pre_clip': 2.8251068592071533, 'timing/data': 0.0007413048297166824, 'timing/model': 0.4745513666421175, 'learning_rate/action_model': 9.622992835943193e-05, 'learning_rate/action_query_proj': 9.622992835943193e-05, 'learning_rate/base': 2.4057482089857984e-05, 'epoch': 0.56}) +[2026-07-27 09:38:17,980][starVLA.training.train_starvla][INFO] - Step 4636, Loss: {'train/loss': 0.09296232461929321, 'train/grad_norm_pre_clip': 3.0154008865356445, 'timing/data': 0.00022748857736587524, 'timing/model': 0.46957180090248585, 'learning_rate/action_model': 9.621820332627229e-05, 'learning_rate/action_query_proj': 9.621820332627229e-05, 'learning_rate/base': 2.4054550831568072e-05, 'epoch': 0.56}) +[2026-07-27 09:38:23,636][starVLA.training.train_starvla][INFO] - Step 4637, Loss: {'train/loss': 0.04298096150159836, 'train/grad_norm_pre_clip': 2.266547441482544, 'timing/data': 0.0008647125214338303, 'timing/model': 0.4695567302405834, 'learning_rate/action_model': 9.620646083646627e-05, 'learning_rate/action_query_proj': 9.620646083646627e-05, 'learning_rate/base': 2.4051615209116568e-05, 'epoch': 0.56}) +[2026-07-27 09:38:29,293][starVLA.training.train_starvla][INFO] - Step 4638, Loss: {'train/loss': 0.13595129549503326, 'train/grad_norm_pre_clip': 4.653914928436279, 'timing/data': 0.00019017420709133148, 'timing/model': 0.4696577303111553, 'learning_rate/action_model': 9.61947008946496e-05, 'learning_rate/action_query_proj': 9.61947008946496e-05, 'learning_rate/base': 2.40486752236624e-05, 'epoch': 0.56}) +[2026-07-27 09:38:34,912][starVLA.training.train_starvla][INFO] - Step 4639, Loss: {'train/loss': 0.1329321414232254, 'train/grad_norm_pre_clip': 3.4950318336486816, 'timing/data': 0.0003114528954029083, 'timing/model': 0.4677994195371866, 'learning_rate/action_model': 9.618292350546494e-05, 'learning_rate/action_query_proj': 9.618292350546494e-05, 'learning_rate/base': 2.4045730876366235e-05, 'epoch': 0.56}) +[2026-07-27 09:38:40,555][starVLA.training.train_starvla][INFO] - Step 4640, Loss: {'train/loss': 0.01715976744890213, 'train/grad_norm_pre_clip': 1.3175936937332153, 'timing/data': 0.00025674887001514435, 'timing/model': 0.47772188670933247, 'learning_rate/action_model': 9.617112867356178e-05, 'learning_rate/action_query_proj': 9.617112867356178e-05, 'learning_rate/base': 2.4042782168390445e-05, 'epoch': 0.56}) +[2026-07-27 09:38:46,231][starVLA.training.train_starvla][INFO] - Step 4641, Loss: {'train/loss': 0.14844584465026855, 'train/grad_norm_pre_clip': 4.496364593505859, 'timing/data': 0.0002246219664812088, 'timing/model': 0.469550471752882, 'learning_rate/action_model': 9.615931640359656e-05, 'learning_rate/action_query_proj': 9.615931640359656e-05, 'learning_rate/base': 2.403982910089914e-05, 'epoch': 0.56}) +[2026-07-27 09:38:52,089][starVLA.training.train_starvla][INFO] - Step 4642, Loss: {'train/loss': 0.055659081786870956, 'train/grad_norm_pre_clip': 1.9001641273498535, 'timing/data': 0.00019744783639907837, 'timing/model': 0.47597991675138474, 'learning_rate/action_model': 9.614748670023258e-05, 'learning_rate/action_query_proj': 9.614748670023258e-05, 'learning_rate/base': 2.4036871675058145e-05, 'epoch': 0.56}) +[2026-07-27 09:38:57,658][starVLA.training.train_starvla][INFO] - Step 4643, Loss: {'train/loss': 0.0634286031126976, 'train/grad_norm_pre_clip': 3.2553551197052, 'timing/data': 0.00018157623708248138, 'timing/model': 0.4695716127753258, 'learning_rate/action_model': 9.613563956814003e-05, 'learning_rate/action_query_proj': 9.613563956814003e-05, 'learning_rate/base': 2.4033909892035006e-05, 'epoch': 0.56}) +[2026-07-27 09:39:03,238][starVLA.training.train_starvla][INFO] - Step 4644, Loss: {'train/loss': 0.0163614172488451, 'train/grad_norm_pre_clip': 0.9403018951416016, 'timing/data': 0.00018794462084770203, 'timing/model': 0.46995699033141136, 'learning_rate/action_model': 9.612377501199592e-05, 'learning_rate/action_query_proj': 9.612377501199592e-05, 'learning_rate/base': 2.403094375299898e-05, 'epoch': 0.56}) +[2026-07-27 09:39:09,092][starVLA.training.train_starvla][INFO] - Step 4645, Loss: {'train/loss': 0.07650166749954224, 'train/grad_norm_pre_clip': 2.954991579055786, 'timing/data': 0.00021229498088359833, 'timing/model': 0.4770440272986889, 'learning_rate/action_model': 9.611189303648423e-05, 'learning_rate/action_query_proj': 9.611189303648423e-05, 'learning_rate/base': 2.4027973259121057e-05, 'epoch': 0.56}) +[2026-07-27 09:39:14,690][starVLA.training.train_starvla][INFO] - Step 4646, Loss: {'train/loss': 0.08677579462528229, 'train/grad_norm_pre_clip': 2.8097381591796875, 'timing/data': 0.0002737510949373245, 'timing/model': 0.4678753577172756, 'learning_rate/action_model': 9.609999364629577e-05, 'learning_rate/action_query_proj': 9.609999364629577e-05, 'learning_rate/base': 2.4024998411573942e-05, 'epoch': 0.56}) +[2026-07-27 09:39:20,373][starVLA.training.train_starvla][INFO] - Step 4647, Loss: {'train/loss': 0.10460813343524933, 'train/grad_norm_pre_clip': 4.3493475914001465, 'timing/data': 0.00022367015480995178, 'timing/model': 0.48301371559500694, 'learning_rate/action_model': 9.608807684612822e-05, 'learning_rate/action_query_proj': 9.608807684612822e-05, 'learning_rate/base': 2.4022019211532055e-05, 'epoch': 0.56}) +[2026-07-27 09:39:26,046][starVLA.training.train_starvla][INFO] - Step 4648, Loss: {'train/loss': 0.1281355768442154, 'train/grad_norm_pre_clip': 6.122564792633057, 'timing/data': 0.0002524815499782562, 'timing/model': 0.47645569406449795, 'learning_rate/action_model': 9.607614264068618e-05, 'learning_rate/action_query_proj': 9.607614264068618e-05, 'learning_rate/base': 2.4019035660171544e-05, 'epoch': 0.56}) +[2026-07-27 09:39:31,765][starVLA.training.train_starvla][INFO] - Step 4649, Loss: {'train/loss': 0.16896305978298187, 'train/grad_norm_pre_clip': 6.110483169555664, 'timing/data': 0.00021705403923988342, 'timing/model': 0.4784069526940584, 'learning_rate/action_model': 9.606419103468103e-05, 'learning_rate/action_query_proj': 9.606419103468103e-05, 'learning_rate/base': 2.4016047758670257e-05, 'epoch': 0.56}) +[2026-07-27 09:39:37,398][starVLA.training.train_starvla][INFO] - Step 4650, Loss: {'train/loss': 0.04075189307332039, 'train/grad_norm_pre_clip': 3.2315807342529297, 'timing/data': 0.00018670037388801575, 'timing/model': 0.4691265933215618, 'learning_rate/action_model': 9.60522220328311e-05, 'learning_rate/action_query_proj': 9.60522220328311e-05, 'learning_rate/base': 2.4013055508207773e-05, 'epoch': 0.56}) +[2026-07-27 09:39:42,984][starVLA.training.train_starvla][INFO] - Step 4651, Loss: {'train/loss': 0.02741239406168461, 'train/grad_norm_pre_clip': 2.2034428119659424, 'timing/data': 0.00022774375975131989, 'timing/model': 0.4730405956506729, 'learning_rate/action_model': 9.604023563986157e-05, 'learning_rate/action_query_proj': 9.604023563986157e-05, 'learning_rate/base': 2.4010058909965392e-05, 'epoch': 0.56}) +[2026-07-27 09:39:48,579][starVLA.training.train_starvla][INFO] - Step 4652, Loss: {'train/loss': 0.057611431926488876, 'train/grad_norm_pre_clip': 3.5712170600891113, 'timing/data': 0.00020296871662139893, 'timing/model': 0.4764574896544218, 'learning_rate/action_model': 9.602823186050448e-05, 'learning_rate/action_query_proj': 9.602823186050448e-05, 'learning_rate/base': 2.400705796512612e-05, 'epoch': 0.56}) +[2026-07-27 09:39:54,233][starVLA.training.train_starvla][INFO] - Step 4653, Loss: {'train/loss': 0.031190678477287292, 'train/grad_norm_pre_clip': 1.9673867225646973, 'timing/data': 0.00019508041441440582, 'timing/model': 0.46684486232697964, 'learning_rate/action_model': 9.601621069949873e-05, 'learning_rate/action_query_proj': 9.601621069949873e-05, 'learning_rate/base': 2.400405267487468e-05, 'epoch': 0.56}) +[2026-07-27 09:39:59,815][starVLA.training.train_starvla][INFO] - Step 4654, Loss: {'train/loss': 0.05484364926815033, 'train/grad_norm_pre_clip': 3.3109853267669678, 'timing/data': 0.00019099190831184387, 'timing/model': 0.4718922786414623, 'learning_rate/action_model': 9.600417216159006e-05, 'learning_rate/action_query_proj': 9.600417216159006e-05, 'learning_rate/base': 2.4001043040397516e-05, 'epoch': 0.56}) +[2026-07-27 09:40:05,436][starVLA.training.train_starvla][INFO] - Step 4655, Loss: {'train/loss': 0.12237264215946198, 'train/grad_norm_pre_clip': 5.374520778656006, 'timing/data': 0.00021147169172763824, 'timing/model': 0.4757887814193964, 'learning_rate/action_model': 9.59921162515311e-05, 'learning_rate/action_query_proj': 9.59921162515311e-05, 'learning_rate/base': 2.3998029062882776e-05, 'epoch': 0.56}) +[2026-07-27 09:40:11,002][starVLA.training.train_starvla][INFO] - Step 4656, Loss: {'train/loss': 0.1479533463716507, 'train/grad_norm_pre_clip': 5.111462593078613, 'timing/data': 0.00017912127077579498, 'timing/model': 0.4683818519115448, 'learning_rate/action_model': 9.598004297408138e-05, 'learning_rate/action_query_proj': 9.598004297408138e-05, 'learning_rate/base': 2.3995010743520345e-05, 'epoch': 0.56}) +[2026-07-27 09:40:16,562][starVLA.training.train_starvla][INFO] - Step 4657, Loss: {'train/loss': 0.015583723783493042, 'train/grad_norm_pre_clip': 1.3519047498703003, 'timing/data': 0.00019613653421401978, 'timing/model': 0.466473825275898, 'learning_rate/action_model': 9.596795233400718e-05, 'learning_rate/action_query_proj': 9.596795233400718e-05, 'learning_rate/base': 2.3991988083501796e-05, 'epoch': 0.56}) +[2026-07-27 09:40:22,129][starVLA.training.train_starvla][INFO] - Step 4658, Loss: {'train/loss': 0.1630011647939682, 'train/grad_norm_pre_clip': 5.450725555419922, 'timing/data': 0.0001862160861492157, 'timing/model': 0.4670070242136717, 'learning_rate/action_model': 9.595584433608172e-05, 'learning_rate/action_query_proj': 9.595584433608172e-05, 'learning_rate/base': 2.398896108402043e-05, 'epoch': 0.57}) +[2026-07-27 09:40:27,697][starVLA.training.train_starvla][INFO] - Step 4659, Loss: {'train/loss': 0.06766707450151443, 'train/grad_norm_pre_clip': 2.543732166290283, 'timing/data': 0.0001856330782175064, 'timing/model': 0.4772939831018448, 'learning_rate/action_model': 9.594371898508504e-05, 'learning_rate/action_query_proj': 9.594371898508504e-05, 'learning_rate/base': 2.398592974627126e-05, 'epoch': 0.57}) +[2026-07-27 09:40:33,245][starVLA.training.train_starvla][INFO] - Step 4660, Loss: {'train/loss': 0.09906129539012909, 'train/grad_norm_pre_clip': 4.980264663696289, 'timing/data': 0.00019337236881256104, 'timing/model': 0.468891141936183, 'learning_rate/action_model': 9.593157628580404e-05, 'learning_rate/action_query_proj': 9.593157628580404e-05, 'learning_rate/base': 2.398289407145101e-05, 'epoch': 0.57}) +[2026-07-27 09:40:38,810][starVLA.training.train_starvla][INFO] - Step 4661, Loss: {'train/loss': 0.10957807302474976, 'train/grad_norm_pre_clip': 4.446028709411621, 'timing/data': 0.00018086470663547516, 'timing/model': 0.4665078725665808, 'learning_rate/action_model': 9.591941624303247e-05, 'learning_rate/action_query_proj': 9.591941624303247e-05, 'learning_rate/base': 2.397985406075812e-05, 'epoch': 0.57}) +[2026-07-27 09:40:44,388][starVLA.training.train_starvla][INFO] - Step 4662, Loss: {'train/loss': 0.11740183085203171, 'train/grad_norm_pre_clip': 5.178304195404053, 'timing/data': 0.00019383244216442108, 'timing/model': 0.4690061956644058, 'learning_rate/action_model': 9.590723886157092e-05, 'learning_rate/action_query_proj': 9.590723886157092e-05, 'learning_rate/base': 2.397680971539273e-05, 'epoch': 0.57}) +[2026-07-27 09:40:49,965][starVLA.training.train_starvla][INFO] - Step 4663, Loss: {'train/loss': 0.04459844529628754, 'train/grad_norm_pre_clip': 2.8184614181518555, 'timing/data': 0.00019079074263572693, 'timing/model': 0.47537668608129025, 'learning_rate/action_model': 9.589504414622682e-05, 'learning_rate/action_query_proj': 9.589504414622682e-05, 'learning_rate/base': 2.3973761036556706e-05, 'epoch': 0.57}) +[2026-07-27 09:40:55,551][starVLA.training.train_starvla][INFO] - Step 4664, Loss: {'train/loss': 0.11112307757139206, 'train/grad_norm_pre_clip': 4.451444625854492, 'timing/data': 0.0002546161413192749, 'timing/model': 0.47020055912435055, 'learning_rate/action_model': 9.588283210181446e-05, 'learning_rate/action_query_proj': 9.588283210181446e-05, 'learning_rate/base': 2.3970708025453614e-05, 'epoch': 0.57}) +[2026-07-27 09:41:01,148][starVLA.training.train_starvla][INFO] - Step 4665, Loss: {'train/loss': 0.055158499628305435, 'train/grad_norm_pre_clip': 2.692108154296875, 'timing/data': 0.00019116699695587158, 'timing/model': 0.475426621735096, 'learning_rate/action_model': 9.587060273315493e-05, 'learning_rate/action_query_proj': 9.587060273315493e-05, 'learning_rate/base': 2.3967650683288733e-05, 'epoch': 0.57}) +[2026-07-27 09:41:06,742][starVLA.training.train_starvla][INFO] - Step 4666, Loss: {'train/loss': 0.0678318664431572, 'train/grad_norm_pre_clip': 3.017113447189331, 'timing/data': 0.00019263476133346558, 'timing/model': 0.47508985362946987, 'learning_rate/action_model': 9.585835604507626e-05, 'learning_rate/action_query_proj': 9.585835604507626e-05, 'learning_rate/base': 2.3964589011269066e-05, 'epoch': 0.57}) +[2026-07-27 09:41:12,338][starVLA.training.train_starvla][INFO] - Step 4667, Loss: {'train/loss': 0.2584996223449707, 'train/grad_norm_pre_clip': 4.072329521179199, 'timing/data': 0.00019613467156887054, 'timing/model': 0.4701656624674797, 'learning_rate/action_model': 9.584609204241318e-05, 'learning_rate/action_query_proj': 9.584609204241318e-05, 'learning_rate/base': 2.3961523010603294e-05, 'epoch': 0.57}) +[2026-07-27 09:41:17,952][starVLA.training.train_starvla][INFO] - Step 4668, Loss: {'train/loss': 0.05740787833929062, 'train/grad_norm_pre_clip': 3.007051706314087, 'timing/data': 0.00019950978457927704, 'timing/model': 0.4689497258514166, 'learning_rate/action_model': 9.583381073000734e-05, 'learning_rate/action_query_proj': 9.583381073000734e-05, 'learning_rate/base': 2.3958452682501835e-05, 'epoch': 0.57}) +[2026-07-27 09:41:23,540][starVLA.training.train_starvla][INFO] - Step 4669, Loss: {'train/loss': 0.15057864785194397, 'train/grad_norm_pre_clip': 5.5306196212768555, 'timing/data': 0.0001932922750711441, 'timing/model': 0.46959410794079304, 'learning_rate/action_model': 9.582151211270724e-05, 'learning_rate/action_query_proj': 9.582151211270724e-05, 'learning_rate/base': 2.395537802817681e-05, 'epoch': 0.57}) +[2026-07-27 09:41:29,110][starVLA.training.train_starvla][INFO] - Step 4670, Loss: {'train/loss': 0.1281988024711609, 'train/grad_norm_pre_clip': 3.672471046447754, 'timing/data': 0.0001772698014974594, 'timing/model': 0.4690269287675619, 'learning_rate/action_model': 9.580919619536814e-05, 'learning_rate/action_query_proj': 9.580919619536814e-05, 'learning_rate/base': 2.3952299048842036e-05, 'epoch': 0.57}) +[2026-07-27 09:41:34,661][starVLA.training.train_starvla][INFO] - Step 4671, Loss: {'train/loss': 0.12596610188484192, 'train/grad_norm_pre_clip': 4.034027099609375, 'timing/data': 0.0001881662756204605, 'timing/model': 0.4758074227720499, 'learning_rate/action_model': 9.579686298285219e-05, 'learning_rate/action_query_proj': 9.579686298285219e-05, 'learning_rate/base': 2.3949215745713047e-05, 'epoch': 0.57}) +[2026-07-27 09:41:40,226][starVLA.training.train_starvla][INFO] - Step 4672, Loss: {'train/loss': 0.12280566990375519, 'train/grad_norm_pre_clip': 4.5298686027526855, 'timing/data': 0.0001789964735507965, 'timing/model': 0.46799675188958645, 'learning_rate/action_model': 9.578451248002835e-05, 'learning_rate/action_query_proj': 9.578451248002835e-05, 'learning_rate/base': 2.3946128120007087e-05, 'epoch': 0.57}) +[2026-07-27 09:41:45,820][starVLA.training.train_starvla][INFO] - Step 4673, Loss: {'train/loss': 0.04629499465227127, 'train/grad_norm_pre_clip': 2.3276991844177246, 'timing/data': 0.00017681531608104706, 'timing/model': 0.46751577220857143, 'learning_rate/action_model': 9.577214469177239e-05, 'learning_rate/action_query_proj': 9.577214469177239e-05, 'learning_rate/base': 2.3943036172943097e-05, 'epoch': 0.57}) +[2026-07-27 09:41:51,436][starVLA.training.train_starvla][INFO] - Step 4674, Loss: {'train/loss': 0.0492568276822567, 'train/grad_norm_pre_clip': 2.3282570838928223, 'timing/data': 0.00017943046987056732, 'timing/model': 0.4671179410070181, 'learning_rate/action_model': 9.575975962296692e-05, 'learning_rate/action_query_proj': 9.575975962296692e-05, 'learning_rate/base': 2.393993990574173e-05, 'epoch': 0.57}) +[2026-07-27 09:41:57,044][starVLA.training.train_starvla][INFO] - Step 4675, Loss: {'train/loss': 0.15335407853126526, 'train/grad_norm_pre_clip': 4.804920673370361, 'timing/data': 0.0001913420855998993, 'timing/model': 0.46734186075627804, 'learning_rate/action_model': 9.574735727850137e-05, 'learning_rate/action_query_proj': 9.574735727850137e-05, 'learning_rate/base': 2.3936839319625343e-05, 'epoch': 0.57}) +[2026-07-27 09:42:02,697][starVLA.training.train_starvla][INFO] - Step 4676, Loss: {'train/loss': 0.053736310452222824, 'train/grad_norm_pre_clip': 2.9732439517974854, 'timing/data': 0.00017351284623146057, 'timing/model': 0.4696684964001179, 'learning_rate/action_model': 9.573493766327201e-05, 'learning_rate/action_query_proj': 9.573493766327201e-05, 'learning_rate/base': 2.3933734415818002e-05, 'epoch': 0.57}) +[2026-07-27 09:42:08,430][starVLA.training.train_starvla][INFO] - Step 4677, Loss: {'train/loss': 0.1327751725912094, 'train/grad_norm_pre_clip': 4.08071231842041, 'timing/data': 0.00017424672842025757, 'timing/model': 0.46989310160279274, 'learning_rate/action_model': 9.572250078218187e-05, 'learning_rate/action_query_proj': 9.572250078218187e-05, 'learning_rate/base': 2.3930625195545466e-05, 'epoch': 0.57}) +[2026-07-27 09:42:14,005][starVLA.training.train_starvla][INFO] - Step 4678, Loss: {'train/loss': 0.08218813687562943, 'train/grad_norm_pre_clip': 3.4442124366760254, 'timing/data': 0.00017441995441913605, 'timing/model': 0.4703249130398035, 'learning_rate/action_model': 9.571004664014085e-05, 'learning_rate/action_query_proj': 9.571004664014085e-05, 'learning_rate/base': 2.3927511660035212e-05, 'epoch': 0.57}) +[2026-07-27 09:42:19,561][starVLA.training.train_starvla][INFO] - Step 4679, Loss: {'train/loss': 0.17097994685173035, 'train/grad_norm_pre_clip': 4.232309818267822, 'timing/data': 0.00019092299044132233, 'timing/model': 0.4690987579524517, 'learning_rate/action_model': 9.569757524206567e-05, 'learning_rate/action_query_proj': 9.569757524206567e-05, 'learning_rate/base': 2.3924393810516417e-05, 'epoch': 0.57}) +[2026-07-27 09:42:25,110][starVLA.training.train_starvla][INFO] - Step 4680, Loss: {'train/loss': 0.07122662663459778, 'train/grad_norm_pre_clip': 3.029297351837158, 'timing/data': 0.00017687305808067322, 'timing/model': 0.46840064972639084, 'learning_rate/action_model': 9.568508659287979e-05, 'learning_rate/action_query_proj': 9.568508659287979e-05, 'learning_rate/base': 2.3921271648219947e-05, 'epoch': 0.57}) +[2026-07-27 09:42:30,678][starVLA.training.train_starvla][INFO] - Step 4681, Loss: {'train/loss': 0.08084743469953537, 'train/grad_norm_pre_clip': 3.373551845550537, 'timing/data': 0.0001887138932943344, 'timing/model': 0.4673966094851494, 'learning_rate/action_model': 9.567258069751358e-05, 'learning_rate/action_query_proj': 9.567258069751358e-05, 'learning_rate/base': 2.3918145174378395e-05, 'epoch': 0.57}) +[2026-07-27 09:42:36,212][starVLA.training.train_starvla][INFO] - Step 4682, Loss: {'train/loss': 0.08447810262441635, 'train/grad_norm_pre_clip': 3.039881944656372, 'timing/data': 0.00018365681171417236, 'timing/model': 0.46879762783646584, 'learning_rate/action_model': 9.566005756090417e-05, 'learning_rate/action_query_proj': 9.566005756090417e-05, 'learning_rate/base': 2.391501439022604e-05, 'epoch': 0.57}) +[2026-07-27 09:42:41,798][starVLA.training.train_starvla][INFO] - Step 4683, Loss: {'train/loss': 0.117952361702919, 'train/grad_norm_pre_clip': 2.969433307647705, 'timing/data': 0.00020199455320835114, 'timing/model': 0.4577241186052561, 'learning_rate/action_model': 9.564751718799543e-05, 'learning_rate/action_query_proj': 9.564751718799543e-05, 'learning_rate/base': 2.391187929699886e-05, 'epoch': 0.57}) +[2026-07-27 09:42:47,749][starVLA.training.train_starvla][INFO] - Step 4684, Loss: {'train/loss': 0.08107755333185196, 'train/grad_norm_pre_clip': 3.041485548019409, 'timing/data': 0.00017799250781536102, 'timing/model': 0.4795803353190422, 'learning_rate/action_model': 9.563495958373818e-05, 'learning_rate/action_query_proj': 9.563495958373818e-05, 'learning_rate/base': 2.3908739895934545e-05, 'epoch': 0.57}) +[2026-07-27 09:42:53,271][starVLA.training.train_starvla][INFO] - Step 4685, Loss: {'train/loss': 0.0643349438905716, 'train/grad_norm_pre_clip': 2.8361127376556396, 'timing/data': 0.00020808912813663483, 'timing/model': 0.45705402828752995, 'learning_rate/action_model': 9.562238475308993e-05, 'learning_rate/action_query_proj': 9.562238475308993e-05, 'learning_rate/base': 2.3905596188272482e-05, 'epoch': 0.57}) +[2026-07-27 09:42:59,131][starVLA.training.train_starvla][INFO] - Step 4686, Loss: {'train/loss': 0.17465172708034515, 'train/grad_norm_pre_clip': 4.167445659637451, 'timing/data': 0.00017330050468444824, 'timing/model': 0.4562784843146801, 'learning_rate/action_model': 9.560979270101502e-05, 'learning_rate/action_query_proj': 9.560979270101502e-05, 'learning_rate/base': 2.3902448175253754e-05, 'epoch': 0.57}) +[2026-07-27 09:43:04,639][starVLA.training.train_starvla][INFO] - Step 4687, Loss: {'train/loss': 0.14148873090744019, 'train/grad_norm_pre_clip': 3.1449244022369385, 'timing/data': 0.00017546676099300385, 'timing/model': 0.457290593534708, 'learning_rate/action_model': 9.559718343248459e-05, 'learning_rate/action_query_proj': 9.559718343248459e-05, 'learning_rate/base': 2.3899295858121147e-05, 'epoch': 0.57}) +[2026-07-27 09:43:10,146][starVLA.training.train_starvla][INFO] - Step 4688, Loss: {'train/loss': 0.11726289987564087, 'train/grad_norm_pre_clip': 4.39301872253418, 'timing/data': 0.00017320923507213593, 'timing/model': 0.4570425432175398, 'learning_rate/action_model': 9.55845569524766e-05, 'learning_rate/action_query_proj': 9.55845569524766e-05, 'learning_rate/base': 2.389613923811915e-05, 'epoch': 0.57}) +[2026-07-27 09:43:15,849][starVLA.training.train_starvla][INFO] - Step 4689, Loss: {'train/loss': 0.06274431943893433, 'train/grad_norm_pre_clip': 2.37410569190979, 'timing/data': 0.00018264725804328918, 'timing/model': 0.45565637573599815, 'learning_rate/action_model': 9.557191326597575e-05, 'learning_rate/action_query_proj': 9.557191326597575e-05, 'learning_rate/base': 2.3892978316493938e-05, 'epoch': 0.57}) +[2026-07-27 09:43:21,448][starVLA.training.train_starvla][INFO] - Step 4690, Loss: {'train/loss': 0.07646577805280685, 'train/grad_norm_pre_clip': 2.7844033241271973, 'timing/data': 0.0002283882349729538, 'timing/model': 0.4711873233318329, 'learning_rate/action_model': 9.555925237797362e-05, 'learning_rate/action_query_proj': 9.555925237797362e-05, 'learning_rate/base': 2.3889813094493405e-05, 'epoch': 0.57}) +[2026-07-27 09:43:27,021][starVLA.training.train_starvla][INFO] - Step 4691, Loss: {'train/loss': 0.03718670457601547, 'train/grad_norm_pre_clip': 1.5722674131393433, 'timing/data': 0.00019093044102191925, 'timing/model': 0.456808777526021, 'learning_rate/action_model': 9.554657429346848e-05, 'learning_rate/action_query_proj': 9.554657429346848e-05, 'learning_rate/base': 2.388664357336712e-05, 'epoch': 0.57}) +[2026-07-27 09:43:32,602][starVLA.training.train_starvla][INFO] - Step 4692, Loss: {'train/loss': 0.10127643495798111, 'train/grad_norm_pre_clip': 3.2781260013580322, 'timing/data': 0.00018928013741970062, 'timing/model': 0.456878162920475, 'learning_rate/action_model': 9.553387901746546e-05, 'learning_rate/action_query_proj': 9.553387901746546e-05, 'learning_rate/base': 2.3883469754366365e-05, 'epoch': 0.57}) +[2026-07-27 09:43:38,195][starVLA.training.train_starvla][INFO] - Step 4693, Loss: {'train/loss': 0.05144081637263298, 'train/grad_norm_pre_clip': 2.332852363586426, 'timing/data': 0.00019317306578159332, 'timing/model': 0.4564821794629097, 'learning_rate/action_model': 9.552116655497644e-05, 'learning_rate/action_query_proj': 9.552116655497644e-05, 'learning_rate/base': 2.388029163874411e-05, 'epoch': 0.57}) +[2026-07-27 09:43:43,775][starVLA.training.train_starvla][INFO] - Step 4694, Loss: {'train/loss': 0.06243661046028137, 'train/grad_norm_pre_clip': 2.158777952194214, 'timing/data': 0.0001804884523153305, 'timing/model': 0.45867698453366756, 'learning_rate/action_model': 9.550843691102011e-05, 'learning_rate/action_query_proj': 9.550843691102011e-05, 'learning_rate/base': 2.3877109227755027e-05, 'epoch': 0.57}) +[2026-07-27 09:43:49,392][starVLA.training.train_starvla][INFO] - Step 4695, Loss: {'train/loss': 0.03802955895662308, 'train/grad_norm_pre_clip': 1.8157814741134644, 'timing/data': 0.0001838039606809616, 'timing/model': 0.45724964141845703, 'learning_rate/action_model': 9.549569009062191e-05, 'learning_rate/action_query_proj': 9.549569009062191e-05, 'learning_rate/base': 2.387392252265548e-05, 'epoch': 0.57}) +[2026-07-27 09:43:54,952][starVLA.training.train_starvla][INFO] - Step 4696, Loss: {'train/loss': 0.04055928811430931, 'train/grad_norm_pre_clip': 2.2647955417633057, 'timing/data': 0.00018629804253578186, 'timing/model': 0.45705725997686386, 'learning_rate/action_model': 9.548292609881412e-05, 'learning_rate/action_query_proj': 9.548292609881412e-05, 'learning_rate/base': 2.387073152470353e-05, 'epoch': 0.57}) +[2026-07-27 09:44:00,542][starVLA.training.train_starvla][INFO] - Step 4697, Loss: {'train/loss': 0.04020262509584427, 'train/grad_norm_pre_clip': 1.8713181018829346, 'timing/data': 0.00023848749697208405, 'timing/model': 0.4851596336811781, 'learning_rate/action_model': 9.547014494063574e-05, 'learning_rate/action_query_proj': 9.547014494063574e-05, 'learning_rate/base': 2.3867536235158935e-05, 'epoch': 0.57}) +[2026-07-27 09:44:06,074][starVLA.training.train_starvla][INFO] - Step 4698, Loss: {'train/loss': 0.07130753993988037, 'train/grad_norm_pre_clip': 2.625269651412964, 'timing/data': 0.00018750131130218506, 'timing/model': 0.45741292275488377, 'learning_rate/action_model': 9.545734662113257e-05, 'learning_rate/action_query_proj': 9.545734662113257e-05, 'learning_rate/base': 2.3864336655283143e-05, 'epoch': 0.57}) +[2026-07-27 09:44:11,612][starVLA.training.train_starvla][INFO] - Step 4699, Loss: {'train/loss': 0.022681349888443947, 'train/grad_norm_pre_clip': 1.270606517791748, 'timing/data': 0.00017688609659671783, 'timing/model': 0.45729120820760727, 'learning_rate/action_model': 9.544453114535719e-05, 'learning_rate/action_query_proj': 9.544453114535719e-05, 'learning_rate/base': 2.3861132786339298e-05, 'epoch': 0.57}) +[2026-07-27 09:44:17,157][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 4700 +[2026-07-27 09:44:17,158][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 4700 +[2026-07-27 09:44:17,159][starVLA.training.train_starvla][INFO] - Step 4700, Loss: {'train/loss': 0.09745775163173676, 'train/grad_norm_pre_clip': 4.6792473793029785, 'timing/data': 0.00018169544637203217, 'timing/model': 0.4577118828892708, 'learning_rate/action_model': 9.543169851836894e-05, 'learning_rate/action_query_proj': 9.543169851836894e-05, 'learning_rate/base': 2.3857924629592234e-05, 'epoch': 0.57}) +[2026-07-27 09:44:22,658][starVLA.training.train_starvla][INFO] - Step 4701, Loss: {'train/loss': 0.04880227521061897, 'train/grad_norm_pre_clip': 3.0147173404693604, 'timing/data': 0.00019547343254089355, 'timing/model': 0.45812686532735825, 'learning_rate/action_model': 9.541884874523394e-05, 'learning_rate/action_query_proj': 9.541884874523394e-05, 'learning_rate/base': 2.3854712186308485e-05, 'epoch': 0.57}) +[2026-07-27 09:44:28,244][starVLA.training.train_starvla][INFO] - Step 4702, Loss: {'train/loss': 0.08765435963869095, 'train/grad_norm_pre_clip': 4.343811988830566, 'timing/data': 0.00017989985644817352, 'timing/model': 0.45984385535120964, 'learning_rate/action_model': 9.540598183102508e-05, 'learning_rate/action_query_proj': 9.540598183102508e-05, 'learning_rate/base': 2.385149545775627e-05, 'epoch': 0.57}) +[2026-07-27 09:44:33,787][starVLA.training.train_starvla][INFO] - Step 4703, Loss: {'train/loss': 0.13208606839179993, 'train/grad_norm_pre_clip': 4.326475620269775, 'timing/data': 0.0001802779734134674, 'timing/model': 0.4575072694569826, 'learning_rate/action_model': 9.5393097780822e-05, 'learning_rate/action_query_proj': 9.5393097780822e-05, 'learning_rate/base': 2.38482744452055e-05, 'epoch': 0.57}) +[2026-07-27 09:44:39,340][starVLA.training.train_starvla][INFO] - Step 4704, Loss: {'train/loss': 0.0750671923160553, 'train/grad_norm_pre_clip': 3.462291955947876, 'timing/data': 0.00017561763525009155, 'timing/model': 0.45678357779979706, 'learning_rate/action_model': 9.538019659971116e-05, 'learning_rate/action_query_proj': 9.538019659971116e-05, 'learning_rate/base': 2.384504914992779e-05, 'epoch': 0.57}) +[2026-07-27 09:44:44,844][starVLA.training.train_starvla][INFO] - Step 4705, Loss: {'train/loss': 0.06374062597751617, 'train/grad_norm_pre_clip': 3.0934031009674072, 'timing/data': 0.00018479488790035248, 'timing/model': 0.45771893858909607, 'learning_rate/action_model': 9.536727829278568e-05, 'learning_rate/action_query_proj': 9.536727829278568e-05, 'learning_rate/base': 2.384181957319642e-05, 'epoch': 0.57}) +[2026-07-27 09:44:50,382][starVLA.training.train_starvla][INFO] - Step 4706, Loss: {'train/loss': 0.12792660295963287, 'train/grad_norm_pre_clip': 4.157882213592529, 'timing/data': 0.00018086470663547516, 'timing/model': 0.4580925442278385, 'learning_rate/action_model': 9.535434286514555e-05, 'learning_rate/action_query_proj': 9.535434286514555e-05, 'learning_rate/base': 2.3838585716286386e-05, 'epoch': 0.57}) +[2026-07-27 09:44:55,913][starVLA.training.train_starvla][INFO] - Step 4707, Loss: {'train/loss': 0.03282711282372475, 'train/grad_norm_pre_clip': 2.072904348373413, 'timing/data': 0.00017748214304447174, 'timing/model': 0.4590146355330944, 'learning_rate/action_model': 9.534139032189744e-05, 'learning_rate/action_query_proj': 9.534139032189744e-05, 'learning_rate/base': 2.383534758047436e-05, 'epoch': 0.57}) +[2026-07-27 09:45:01,453][starVLA.training.train_starvla][INFO] - Step 4708, Loss: {'train/loss': 0.11968016624450684, 'train/grad_norm_pre_clip': 3.905971050262451, 'timing/data': 0.0001771841198205948, 'timing/model': 0.4571585673838854, 'learning_rate/action_model': 9.532842066815484e-05, 'learning_rate/action_query_proj': 9.532842066815484e-05, 'learning_rate/base': 2.383210516703871e-05, 'epoch': 0.57}) +[2026-07-27 09:45:06,995][starVLA.training.train_starvla][INFO] - Step 4709, Loss: {'train/loss': 0.07121483236551285, 'train/grad_norm_pre_clip': 2.6097991466522217, 'timing/data': 0.00018245354294776917, 'timing/model': 0.4580958466976881, 'learning_rate/action_model': 9.531543390903796e-05, 'learning_rate/action_query_proj': 9.531543390903796e-05, 'learning_rate/base': 2.382885847725949e-05, 'epoch': 0.57}) +[2026-07-27 09:45:12,522][starVLA.training.train_starvla][INFO] - Step 4710, Loss: {'train/loss': 0.06591099500656128, 'train/grad_norm_pre_clip': 3.4568488597869873, 'timing/data': 0.00017417781054973602, 'timing/model': 0.45629510283470154, 'learning_rate/action_model': 9.530243004967375e-05, 'learning_rate/action_query_proj': 9.530243004967375e-05, 'learning_rate/base': 2.3825607512418436e-05, 'epoch': 0.57}) +[2026-07-27 09:45:18,062][starVLA.training.train_starvla][INFO] - Step 4711, Loss: {'train/loss': 0.04610348865389824, 'train/grad_norm_pre_clip': 1.8330179452896118, 'timing/data': 0.00017416849732398987, 'timing/model': 0.4577513374388218, 'learning_rate/action_model': 9.528940909519591e-05, 'learning_rate/action_query_proj': 9.528940909519591e-05, 'learning_rate/base': 2.3822352273798978e-05, 'epoch': 0.57}) +[2026-07-27 09:45:23,626][starVLA.training.train_starvla][INFO] - Step 4712, Loss: {'train/loss': 0.09709370136260986, 'train/grad_norm_pre_clip': 4.5494303703308105, 'timing/data': 0.0001916252076625824, 'timing/model': 0.4732002932578325, 'learning_rate/action_model': 9.527637105074497e-05, 'learning_rate/action_query_proj': 9.527637105074497e-05, 'learning_rate/base': 2.381909276268624e-05, 'epoch': 0.57}) +[2026-07-27 09:45:29,301][starVLA.training.train_starvla][INFO] - Step 4713, Loss: {'train/loss': 0.05235917121171951, 'train/grad_norm_pre_clip': 2.6874732971191406, 'timing/data': 0.00017987005412578583, 'timing/model': 0.4572163540869951, 'learning_rate/action_model': 9.526331592146808e-05, 'learning_rate/action_query_proj': 9.526331592146808e-05, 'learning_rate/base': 2.381582898036702e-05, 'epoch': 0.57}) +[2026-07-27 09:45:34,831][starVLA.training.train_starvla][INFO] - Step 4714, Loss: {'train/loss': 0.1511419713497162, 'train/grad_norm_pre_clip': 4.081057548522949, 'timing/data': 0.00017588399350643158, 'timing/model': 0.4561791531741619, 'learning_rate/action_model': 9.525024371251923e-05, 'learning_rate/action_query_proj': 9.525024371251923e-05, 'learning_rate/base': 2.3812560928129806e-05, 'epoch': 0.57}) +[2026-07-27 09:45:40,367][starVLA.training.train_starvla][INFO] - Step 4715, Loss: {'train/loss': 0.05512040853500366, 'train/grad_norm_pre_clip': 2.310835361480713, 'timing/data': 0.00017752684652805328, 'timing/model': 0.4569613952189684, 'learning_rate/action_model': 9.523715442905912e-05, 'learning_rate/action_query_proj': 9.523715442905912e-05, 'learning_rate/base': 2.380928860726478e-05, 'epoch': 0.57}) +[2026-07-27 09:45:46,226][starVLA.training.train_starvla][INFO] - Step 4716, Loss: {'train/loss': 0.0714518278837204, 'train/grad_norm_pre_clip': 2.707794189453125, 'timing/data': 0.00017623230814933777, 'timing/model': 0.4573230389505625, 'learning_rate/action_model': 9.522404807625518e-05, 'learning_rate/action_query_proj': 9.522404807625518e-05, 'learning_rate/base': 2.3806012019063796e-05, 'epoch': 0.57}) +[2026-07-27 09:45:51,820][starVLA.training.train_starvla][INFO] - Step 4717, Loss: {'train/loss': 0.08529593050479889, 'train/grad_norm_pre_clip': 2.9759483337402344, 'timing/data': 0.00017401203513145447, 'timing/model': 0.456640237942338, 'learning_rate/action_model': 9.52109246592816e-05, 'learning_rate/action_query_proj': 9.52109246592816e-05, 'learning_rate/base': 2.38027311648204e-05, 'epoch': 0.57}) +[2026-07-27 09:45:57,380][starVLA.training.train_starvla][INFO] - Step 4718, Loss: {'train/loss': 0.1198296993970871, 'train/grad_norm_pre_clip': 4.865212440490723, 'timing/data': 0.00017951242625713348, 'timing/model': 0.4575849920511246, 'learning_rate/action_model': 9.519778418331928e-05, 'learning_rate/action_query_proj': 9.519778418331928e-05, 'learning_rate/base': 2.379944604582982e-05, 'epoch': 0.57}) +[2026-07-27 09:46:03,201][starVLA.training.train_starvla][INFO] - Step 4719, Loss: {'train/loss': 0.09772360324859619, 'train/grad_norm_pre_clip': 3.6480824947357178, 'timing/data': 0.00017545185983181, 'timing/model': 0.45724466256797314, 'learning_rate/action_model': 9.518462665355588e-05, 'learning_rate/action_query_proj': 9.518462665355588e-05, 'learning_rate/base': 2.379615666338897e-05, 'epoch': 0.57}) +[2026-07-27 09:46:08,730][starVLA.training.train_starvla][INFO] - Step 4720, Loss: {'train/loss': 0.0770113617181778, 'train/grad_norm_pre_clip': 3.323380470275879, 'timing/data': 0.0001762043684720993, 'timing/model': 0.45755922980606556, 'learning_rate/action_model': 9.517145207518581e-05, 'learning_rate/action_query_proj': 9.517145207518581e-05, 'learning_rate/base': 2.3792863018796453e-05, 'epoch': 0.57}) +[2026-07-27 09:46:14,232][starVLA.training.train_starvla][INFO] - Step 4721, Loss: {'train/loss': 0.022295014932751656, 'train/grad_norm_pre_clip': 1.544188141822815, 'timing/data': 0.00017889775335788727, 'timing/model': 0.45784423500299454, 'learning_rate/action_model': 9.515826045341017e-05, 'learning_rate/action_query_proj': 9.515826045341017e-05, 'learning_rate/base': 2.3789565113352542e-05, 'epoch': 0.57}) +[2026-07-27 09:46:19,721][starVLA.training.train_starvla][INFO] - Step 4722, Loss: {'train/loss': 0.16754581034183502, 'train/grad_norm_pre_clip': 4.917500972747803, 'timing/data': 0.00024929456412792206, 'timing/model': 0.45563047751784325, 'learning_rate/action_model': 9.514505179343678e-05, 'learning_rate/action_query_proj': 9.514505179343678e-05, 'learning_rate/base': 2.3786262948359195e-05, 'epoch': 0.57}) +[2026-07-27 09:46:25,228][starVLA.training.train_starvla][INFO] - Step 4723, Loss: {'train/loss': 0.08592836558818817, 'train/grad_norm_pre_clip': 3.675870656967163, 'timing/data': 0.00018154270946979523, 'timing/model': 0.4563397541642189, 'learning_rate/action_model': 9.513182610048024e-05, 'learning_rate/action_query_proj': 9.513182610048024e-05, 'learning_rate/base': 2.378295652512006e-05, 'epoch': 0.57}) +[2026-07-27 09:46:30,932][starVLA.training.train_starvla][INFO] - Step 4724, Loss: {'train/loss': 0.08477365970611572, 'train/grad_norm_pre_clip': 3.6976442337036133, 'timing/data': 0.00018145516514778137, 'timing/model': 0.4629603400826454, 'learning_rate/action_model': 9.511858337976182e-05, 'learning_rate/action_query_proj': 9.511858337976182e-05, 'learning_rate/base': 2.3779645844940456e-05, 'epoch': 0.57}) +[2026-07-27 09:46:36,543][starVLA.training.train_starvla][INFO] - Step 4725, Loss: {'train/loss': 0.15197326242923737, 'train/grad_norm_pre_clip': 4.060897350311279, 'timing/data': 0.0001780446618795395, 'timing/model': 0.46366563625633717, 'learning_rate/action_model': 9.510532363650955e-05, 'learning_rate/action_query_proj': 9.510532363650955e-05, 'learning_rate/base': 2.3776330909127388e-05, 'epoch': 0.57}) +[2026-07-27 09:46:42,086][starVLA.training.train_starvla][INFO] - Step 4726, Loss: {'train/loss': 0.13837270438671112, 'train/grad_norm_pre_clip': 4.414311408996582, 'timing/data': 0.00018082931637763977, 'timing/model': 0.46246043406426907, 'learning_rate/action_model': 9.509204687595817e-05, 'learning_rate/action_query_proj': 9.509204687595817e-05, 'learning_rate/base': 2.3773011718989542e-05, 'epoch': 0.57}) +[2026-07-27 09:46:47,637][starVLA.training.train_starvla][INFO] - Step 4727, Loss: {'train/loss': 0.23064035177230835, 'train/grad_norm_pre_clip': 6.218496799468994, 'timing/data': 0.00018736161291599274, 'timing/model': 0.4614695720374584, 'learning_rate/action_model': 9.507875310334913e-05, 'learning_rate/action_query_proj': 9.507875310334913e-05, 'learning_rate/base': 2.3769688275837283e-05, 'epoch': 0.57}) +[2026-07-27 09:46:53,193][starVLA.training.train_starvla][INFO] - Step 4728, Loss: {'train/loss': 0.21885576844215393, 'train/grad_norm_pre_clip': 4.927677631378174, 'timing/data': 0.00017343275249004364, 'timing/model': 0.4634899068623781, 'learning_rate/action_model': 9.506544232393061e-05, 'learning_rate/action_query_proj': 9.506544232393061e-05, 'learning_rate/base': 2.3766360580982654e-05, 'epoch': 0.57}) +[2026-07-27 09:46:58,734][starVLA.training.train_starvla][INFO] - Step 4729, Loss: {'train/loss': 0.20184196531772614, 'train/grad_norm_pre_clip': 4.167224407196045, 'timing/data': 0.0001814085990190506, 'timing/model': 0.4615915548056364, 'learning_rate/action_model': 9.505211454295747e-05, 'learning_rate/action_query_proj': 9.505211454295747e-05, 'learning_rate/base': 2.3763028635739368e-05, 'epoch': 0.57}) +[2026-07-27 09:47:04,275][starVLA.training.train_starvla][INFO] - Step 4730, Loss: {'train/loss': 0.10485943406820297, 'train/grad_norm_pre_clip': 3.496299982070923, 'timing/data': 0.00017751753330230713, 'timing/model': 0.46232306584715843, 'learning_rate/action_model': 9.503876976569133e-05, 'learning_rate/action_query_proj': 9.503876976569133e-05, 'learning_rate/base': 2.3759692441422832e-05, 'epoch': 0.57}) +[2026-07-27 09:47:09,810][starVLA.training.train_starvla][INFO] - Step 4731, Loss: {'train/loss': 0.2190081626176834, 'train/grad_norm_pre_clip': 4.397802829742432, 'timing/data': 0.00017706304788589478, 'timing/model': 0.46200028993189335, 'learning_rate/action_model': 9.502540799740048e-05, 'learning_rate/action_query_proj': 9.502540799740048e-05, 'learning_rate/base': 2.375635199935012e-05, 'epoch': 0.57}) +[2026-07-27 09:47:15,345][starVLA.training.train_starvla][INFO] - Step 4732, Loss: {'train/loss': 0.1437341421842575, 'train/grad_norm_pre_clip': 3.932839870452881, 'timing/data': 0.00018748454749584198, 'timing/model': 0.4598232991993427, 'learning_rate/action_model': 9.501202924335996e-05, 'learning_rate/action_query_proj': 9.501202924335996e-05, 'learning_rate/base': 2.375300731083999e-05, 'epoch': 0.57}) +[2026-07-27 09:47:20,879][starVLA.training.train_starvla][INFO] - Step 4733, Loss: {'train/loss': 0.12639781832695007, 'train/grad_norm_pre_clip': 4.2895355224609375, 'timing/data': 0.00018588267266750336, 'timing/model': 0.46230567805469036, 'learning_rate/action_model': 9.499863350885146e-05, 'learning_rate/action_query_proj': 9.499863350885146e-05, 'learning_rate/base': 2.3749658377212864e-05, 'epoch': 0.57}) +[2026-07-27 09:47:26,402][starVLA.training.train_starvla][INFO] - Step 4734, Loss: {'train/loss': 0.21799436211585999, 'train/grad_norm_pre_clip': 5.43350076675415, 'timing/data': 0.0001933462917804718, 'timing/model': 0.4633184503763914, 'learning_rate/action_model': 9.498522079916342e-05, 'learning_rate/action_query_proj': 9.498522079916342e-05, 'learning_rate/base': 2.3746305199790854e-05, 'epoch': 0.57}) +[2026-07-27 09:47:31,958][starVLA.training.train_starvla][INFO] - Step 4735, Loss: {'train/loss': 0.1481173187494278, 'train/grad_norm_pre_clip': 4.729770183563232, 'timing/data': 0.00018300488591194153, 'timing/model': 0.4565442092716694, 'learning_rate/action_model': 9.497179111959098e-05, 'learning_rate/action_query_proj': 9.497179111959098e-05, 'learning_rate/base': 2.3742947779897744e-05, 'epoch': 0.57}) +[2026-07-27 09:47:37,505][starVLA.training.train_starvla][INFO] - Step 4736, Loss: {'train/loss': 0.26039162278175354, 'train/grad_norm_pre_clip': 8.21269702911377, 'timing/data': 0.00019067339599132538, 'timing/model': 0.4563149940222502, 'learning_rate/action_model': 9.495834447543591e-05, 'learning_rate/action_query_proj': 9.495834447543591e-05, 'learning_rate/base': 2.3739586118858977e-05, 'epoch': 0.57}) +[2026-07-27 09:47:43,267][starVLA.training.train_starvla][INFO] - Step 4737, Loss: {'train/loss': 0.13429318368434906, 'train/grad_norm_pre_clip': 4.4337687492370605, 'timing/data': 0.0001935865730047226, 'timing/model': 0.45776165649294853, 'learning_rate/action_model': 9.49448808720068e-05, 'learning_rate/action_query_proj': 9.49448808720068e-05, 'learning_rate/base': 2.37362202180017e-05, 'epoch': 0.57}) +[2026-07-27 09:47:48,774][starVLA.training.train_starvla][INFO] - Step 4738, Loss: {'train/loss': 0.15490809082984924, 'train/grad_norm_pre_clip': 5.01699161529541, 'timing/data': 0.00018225610256195068, 'timing/model': 0.4561244212090969, 'learning_rate/action_model': 9.493140031461883e-05, 'learning_rate/action_query_proj': 9.493140031461883e-05, 'learning_rate/base': 2.3732850078654708e-05, 'epoch': 0.57}) +[2026-07-27 09:47:54,342][starVLA.training.train_starvla][INFO] - Step 4739, Loss: {'train/loss': 0.0874176099896431, 'train/grad_norm_pre_clip': 3.8299436569213867, 'timing/data': 0.00018185004591941833, 'timing/model': 0.4571830164641142, 'learning_rate/action_model': 9.491790280859393e-05, 'learning_rate/action_query_proj': 9.491790280859393e-05, 'learning_rate/base': 2.3729475702148482e-05, 'epoch': 0.57}) +[2026-07-27 09:47:59,894][starVLA.training.train_starvla][INFO] - Step 4740, Loss: {'train/loss': 0.08891300857067108, 'train/grad_norm_pre_clip': 3.921384811401367, 'timing/data': 0.00017818249762058258, 'timing/model': 0.4648305904120207, 'learning_rate/action_model': 9.490438835926067e-05, 'learning_rate/action_query_proj': 9.490438835926067e-05, 'learning_rate/base': 2.3726097089815167e-05, 'epoch': 0.58}) +[2026-07-27 09:48:05,706][starVLA.training.train_starvla][INFO] - Step 4741, Loss: {'train/loss': 0.065559983253479, 'train/grad_norm_pre_clip': 2.950521230697632, 'timing/data': 0.00019438192248344421, 'timing/model': 0.4622435737401247, 'learning_rate/action_model': 9.489085697195437e-05, 'learning_rate/action_query_proj': 9.489085697195437e-05, 'learning_rate/base': 2.3722714242988593e-05, 'epoch': 0.58}) +[2026-07-27 09:48:11,214][starVLA.training.train_starvla][INFO] - Step 4742, Loss: {'train/loss': 0.11673805117607117, 'train/grad_norm_pre_clip': 2.4783244132995605, 'timing/data': 0.00017830543220043182, 'timing/model': 0.46208283491432667, 'learning_rate/action_model': 9.4877308652017e-05, 'learning_rate/action_query_proj': 9.4877308652017e-05, 'learning_rate/base': 2.371932716300425e-05, 'epoch': 0.58}) +[2026-07-27 09:48:16,723][starVLA.training.train_starvla][INFO] - Step 4743, Loss: {'train/loss': 0.06735581904649734, 'train/grad_norm_pre_clip': 2.246497631072998, 'timing/data': 0.00017860718071460724, 'timing/model': 0.4602951519191265, 'learning_rate/action_model': 9.48637434047972e-05, 'learning_rate/action_query_proj': 9.48637434047972e-05, 'learning_rate/base': 2.37159358511993e-05, 'epoch': 0.58}) +[2026-07-27 09:48:22,228][starVLA.training.train_starvla][INFO] - Step 4744, Loss: {'train/loss': 0.06658771634101868, 'train/grad_norm_pre_clip': 2.4635729789733887, 'timing/data': 0.0001752655953168869, 'timing/model': 0.46121980994939804, 'learning_rate/action_model': 9.485016123565036e-05, 'learning_rate/action_query_proj': 9.485016123565036e-05, 'learning_rate/base': 2.371254030891259e-05, 'epoch': 0.58}) +[2026-07-27 09:48:27,733][starVLA.training.train_starvla][INFO] - Step 4745, Loss: {'train/loss': 0.14802445471286774, 'train/grad_norm_pre_clip': 6.04392671585083, 'timing/data': 0.0001820102334022522, 'timing/model': 0.46243295446038246, 'learning_rate/action_model': 9.483656214993847e-05, 'learning_rate/action_query_proj': 9.483656214993847e-05, 'learning_rate/base': 2.3709140537484617e-05, 'epoch': 0.58}) +[2026-07-27 09:48:33,244][starVLA.training.train_starvla][INFO] - Step 4746, Loss: {'train/loss': 0.12556861340999603, 'train/grad_norm_pre_clip': 5.146827220916748, 'timing/data': 0.00017503835260868073, 'timing/model': 0.4620202276855707, 'learning_rate/action_model': 9.482294615303024e-05, 'learning_rate/action_query_proj': 9.482294615303024e-05, 'learning_rate/base': 2.370573653825756e-05, 'epoch': 0.58}) +[2026-07-27 09:48:38,757][starVLA.training.train_starvla][INFO] - Step 4747, Loss: {'train/loss': 0.1357179433107376, 'train/grad_norm_pre_clip': 4.290358066558838, 'timing/data': 0.0001798383891582489, 'timing/model': 0.46186724305152893, 'learning_rate/action_model': 9.480931325030104e-05, 'learning_rate/action_query_proj': 9.480931325030104e-05, 'learning_rate/base': 2.370232831257526e-05, 'epoch': 0.58}) +[2026-07-27 09:48:44,357][starVLA.training.train_starvla][INFO] - Step 4748, Loss: {'train/loss': 0.08534492552280426, 'train/grad_norm_pre_clip': 2.9916906356811523, 'timing/data': 0.000177871435880661, 'timing/model': 0.4625521209090948, 'learning_rate/action_model': 9.479566344713298e-05, 'learning_rate/action_query_proj': 9.479566344713298e-05, 'learning_rate/base': 2.3698915861783245e-05, 'epoch': 0.58}) +[2026-07-27 09:48:49,884][starVLA.training.train_starvla][INFO] - Step 4749, Loss: {'train/loss': 0.03642052039504051, 'train/grad_norm_pre_clip': 2.0709283351898193, 'timing/data': 0.00017650611698627472, 'timing/model': 0.46224187687039375, 'learning_rate/action_model': 9.478199674891471e-05, 'learning_rate/action_query_proj': 9.478199674891471e-05, 'learning_rate/base': 2.369549918722868e-05, 'epoch': 0.58}) +[2026-07-27 09:48:55,404][starVLA.training.train_starvla][INFO] - Step 4750, Loss: {'train/loss': 0.10572880506515503, 'train/grad_norm_pre_clip': 3.8973395824432373, 'timing/data': 0.00017319805920124054, 'timing/model': 0.4633290860801935, 'learning_rate/action_model': 9.476831316104165e-05, 'learning_rate/action_query_proj': 9.476831316104165e-05, 'learning_rate/base': 2.3692078290260413e-05, 'epoch': 0.58}) +[2026-07-27 09:49:00,928][starVLA.training.train_starvla][INFO] - Step 4751, Loss: {'train/loss': 0.05653523653745651, 'train/grad_norm_pre_clip': 2.521987199783325, 'timing/data': 0.0001768358051776886, 'timing/model': 0.46324190124869347, 'learning_rate/action_model': 9.475461268891591e-05, 'learning_rate/action_query_proj': 9.475461268891591e-05, 'learning_rate/base': 2.3688653172228978e-05, 'epoch': 0.58}) +[2026-07-27 09:49:06,428][starVLA.training.train_starvla][INFO] - Step 4752, Loss: {'train/loss': 0.12069649994373322, 'train/grad_norm_pre_clip': 3.0912795066833496, 'timing/data': 0.00017157196998596191, 'timing/model': 0.46218164451420307, 'learning_rate/action_model': 9.474089533794616e-05, 'learning_rate/action_query_proj': 9.474089533794616e-05, 'learning_rate/base': 2.368522383448654e-05, 'epoch': 0.58}) +[2026-07-27 09:49:11,933][starVLA.training.train_starvla][INFO] - Step 4753, Loss: {'train/loss': 0.04717890918254852, 'train/grad_norm_pre_clip': 3.2072672843933105, 'timing/data': 0.00018049217760562897, 'timing/model': 0.4613084439188242, 'learning_rate/action_model': 9.472716111354781e-05, 'learning_rate/action_query_proj': 9.472716111354781e-05, 'learning_rate/base': 2.3681790278386953e-05, 'epoch': 0.58}) +[2026-07-27 09:49:17,448][starVLA.training.train_starvla][INFO] - Step 4754, Loss: {'train/loss': 0.02184508927166462, 'train/grad_norm_pre_clip': 1.1919935941696167, 'timing/data': 0.00019920244812965393, 'timing/model': 0.46204686909914017, 'learning_rate/action_model': 9.471341002114293e-05, 'learning_rate/action_query_proj': 9.471341002114293e-05, 'learning_rate/base': 2.3678352505285733e-05, 'epoch': 0.58}) +[2026-07-27 09:49:22,953][starVLA.training.train_starvla][INFO] - Step 4755, Loss: {'train/loss': 0.0585639514029026, 'train/grad_norm_pre_clip': 2.9661073684692383, 'timing/data': 0.00017429329454898834, 'timing/model': 0.46250191517174244, 'learning_rate/action_model': 9.469964206616023e-05, 'learning_rate/action_query_proj': 9.469964206616023e-05, 'learning_rate/base': 2.3674910516540058e-05, 'epoch': 0.58}) +[2026-07-27 09:49:28,460][starVLA.training.train_starvla][INFO] - Step 4756, Loss: {'train/loss': 0.07723572850227356, 'train/grad_norm_pre_clip': 3.319674491882324, 'timing/data': 0.00017770007252693176, 'timing/model': 0.46172688715159893, 'learning_rate/action_model': 9.468585725403506e-05, 'learning_rate/action_query_proj': 9.468585725403506e-05, 'learning_rate/base': 2.3671464313508764e-05, 'epoch': 0.58}) +[2026-07-27 09:49:33,984][starVLA.training.train_starvla][INFO] - Step 4757, Loss: {'train/loss': 0.14461497962474823, 'train/grad_norm_pre_clip': 5.005251407623291, 'timing/data': 0.0001727920025587082, 'timing/model': 0.46104125306010246, 'learning_rate/action_model': 9.467205559020947e-05, 'learning_rate/action_query_proj': 9.467205559020947e-05, 'learning_rate/base': 2.3668013897552367e-05, 'epoch': 0.58}) +[2026-07-27 09:49:39,490][starVLA.training.train_starvla][INFO] - Step 4758, Loss: {'train/loss': 0.05885748937726021, 'train/grad_norm_pre_clip': 2.8586511611938477, 'timing/data': 0.00017929263412952423, 'timing/model': 0.46168050915002823, 'learning_rate/action_model': 9.465823708013211e-05, 'learning_rate/action_query_proj': 9.465823708013211e-05, 'learning_rate/base': 2.3664559270033028e-05, 'epoch': 0.58}) +[2026-07-27 09:49:44,997][starVLA.training.train_starvla][INFO] - Step 4759, Loss: {'train/loss': 0.11740775406360626, 'train/grad_norm_pre_clip': 3.300603151321411, 'timing/data': 0.00018762238323688507, 'timing/model': 0.46023838967084885, 'learning_rate/action_model': 9.464440172925835e-05, 'learning_rate/action_query_proj': 9.464440172925835e-05, 'learning_rate/base': 2.3661100432314587e-05, 'epoch': 0.58}) +[2026-07-27 09:49:50,537][starVLA.training.train_starvla][INFO] - Step 4760, Loss: {'train/loss': 0.11375226080417633, 'train/grad_norm_pre_clip': 4.471850395202637, 'timing/data': 0.0001759026199579239, 'timing/model': 0.4627765789628029, 'learning_rate/action_model': 9.463054954305014e-05, 'learning_rate/action_query_proj': 9.463054954305014e-05, 'learning_rate/base': 2.3657637385762534e-05, 'epoch': 0.58}) +[2026-07-27 09:49:56,061][starVLA.training.train_starvla][INFO] - Step 4761, Loss: {'train/loss': 0.06546736508607864, 'train/grad_norm_pre_clip': 3.107642889022827, 'timing/data': 0.0002351030707359314, 'timing/model': 0.46178641729056835, 'learning_rate/action_model': 9.461668052697611e-05, 'learning_rate/action_query_proj': 9.461668052697611e-05, 'learning_rate/base': 2.3654170131744028e-05, 'epoch': 0.58}) +[2026-07-27 09:50:01,634][starVLA.training.train_starvla][INFO] - Step 4762, Loss: {'train/loss': 0.08847068250179291, 'train/grad_norm_pre_clip': 3.8907485008239746, 'timing/data': 0.00017987936735153198, 'timing/model': 0.45788825675845146, 'learning_rate/action_model': 9.460279468651152e-05, 'learning_rate/action_query_proj': 9.460279468651152e-05, 'learning_rate/base': 2.365069867162788e-05, 'epoch': 0.58}) +[2026-07-27 09:50:07,190][starVLA.training.train_starvla][INFO] - Step 4763, Loss: {'train/loss': 0.15712891519069672, 'train/grad_norm_pre_clip': 4.2692365646362305, 'timing/data': 0.00017964839935302734, 'timing/model': 0.45801187865436077, 'learning_rate/action_model': 9.458889202713828e-05, 'learning_rate/action_query_proj': 9.458889202713828e-05, 'learning_rate/base': 2.364722300678457e-05, 'epoch': 0.58}) +[2026-07-27 09:50:12,741][starVLA.training.train_starvla][INFO] - Step 4764, Loss: {'train/loss': 0.054177384823560715, 'train/grad_norm_pre_clip': 3.4933242797851562, 'timing/data': 0.00026647187769412994, 'timing/model': 0.45615944638848305, 'learning_rate/action_model': 9.457497255434495e-05, 'learning_rate/action_query_proj': 9.457497255434495e-05, 'learning_rate/base': 2.3643743138586238e-05, 'epoch': 0.58}) +[2026-07-27 09:50:18,279][starVLA.training.train_starvla][INFO] - Step 4765, Loss: {'train/loss': 0.06602106988430023, 'train/grad_norm_pre_clip': 3.4481852054595947, 'timing/data': 0.00018004700541496277, 'timing/model': 0.457288047298789, 'learning_rate/action_model': 9.456103627362673e-05, 'learning_rate/action_query_proj': 9.456103627362673e-05, 'learning_rate/base': 2.364025906840668e-05, 'epoch': 0.58}) +[2026-07-27 09:50:23,816][starVLA.training.train_starvla][INFO] - Step 4766, Loss: {'train/loss': 0.030343038961291313, 'train/grad_norm_pre_clip': 1.8533668518066406, 'timing/data': 0.00017611123621463776, 'timing/model': 0.4578430652618408, 'learning_rate/action_model': 9.45470831904854e-05, 'learning_rate/action_query_proj': 9.45470831904854e-05, 'learning_rate/base': 2.363677079762135e-05, 'epoch': 0.58}) +[2026-07-27 09:50:29,354][starVLA.training.train_starvla][INFO] - Step 4767, Loss: {'train/loss': 0.05196871981024742, 'train/grad_norm_pre_clip': 2.98748517036438, 'timing/data': 0.00017892196774482727, 'timing/model': 0.45713347010314465, 'learning_rate/action_model': 9.453311331042945e-05, 'learning_rate/action_query_proj': 9.453311331042945e-05, 'learning_rate/base': 2.3633278327607363e-05, 'epoch': 0.58}) +[2026-07-27 09:50:35,102][starVLA.training.train_starvla][INFO] - Step 4768, Loss: {'train/loss': 0.09633505344390869, 'train/grad_norm_pre_clip': 3.025355815887451, 'timing/data': 0.00017777085304260254, 'timing/model': 0.45735372602939606, 'learning_rate/action_model': 9.451912663897396e-05, 'learning_rate/action_query_proj': 9.451912663897396e-05, 'learning_rate/base': 2.362978165974349e-05, 'epoch': 0.58}) +[2026-07-27 09:50:40,650][starVLA.training.train_starvla][INFO] - Step 4769, Loss: {'train/loss': 0.09081657230854034, 'train/grad_norm_pre_clip': 4.161737442016602, 'timing/data': 0.00017680786550045013, 'timing/model': 0.4561040624976158, 'learning_rate/action_model': 9.450512318164065e-05, 'learning_rate/action_query_proj': 9.450512318164065e-05, 'learning_rate/base': 2.362628079541016e-05, 'epoch': 0.58}) +[2026-07-27 09:50:46,186][starVLA.training.train_starvla][INFO] - Step 4770, Loss: {'train/loss': 0.0687839463353157, 'train/grad_norm_pre_clip': 2.8651366233825684, 'timing/data': 0.0001740679144859314, 'timing/model': 0.4562949016690254, 'learning_rate/action_model': 9.449110294395786e-05, 'learning_rate/action_query_proj': 9.449110294395786e-05, 'learning_rate/base': 2.3622775735989464e-05, 'epoch': 0.58}) +[2026-07-27 09:50:51,720][starVLA.training.train_starvla][INFO] - Step 4771, Loss: {'train/loss': 0.05699247494339943, 'train/grad_norm_pre_clip': 2.9906370639801025, 'timing/data': 0.00019038282334804535, 'timing/model': 0.4570746645331383, 'learning_rate/action_model': 9.447706593146055e-05, 'learning_rate/action_query_proj': 9.447706593146055e-05, 'learning_rate/base': 2.3619266482865138e-05, 'epoch': 0.58}) +[2026-07-27 09:50:57,512][starVLA.training.train_starvla][INFO] - Step 4772, Loss: {'train/loss': 0.0366525873541832, 'train/grad_norm_pre_clip': 2.143601894378662, 'timing/data': 0.00017928332090377808, 'timing/model': 0.4562016259878874, 'learning_rate/action_model': 9.446301214969032e-05, 'learning_rate/action_query_proj': 9.446301214969032e-05, 'learning_rate/base': 2.361575303742258e-05, 'epoch': 0.58}) +[2026-07-27 09:51:03,402][starVLA.training.train_starvla][INFO] - Step 4773, Loss: {'train/loss': 0.10006330907344818, 'train/grad_norm_pre_clip': 2.920478105545044, 'timing/data': 0.0001792553812265396, 'timing/model': 0.4568621274083853, 'learning_rate/action_model': 9.444894160419539e-05, 'learning_rate/action_query_proj': 9.444894160419539e-05, 'learning_rate/base': 2.3612235401048847e-05, 'epoch': 0.58}) +[2026-07-27 09:51:08,897][starVLA.training.train_starvla][INFO] - Step 4774, Loss: {'train/loss': 0.08307424187660217, 'train/grad_norm_pre_clip': 2.2264602184295654, 'timing/data': 0.00018871761858463287, 'timing/model': 0.4574586804956198, 'learning_rate/action_model': 9.443485430053056e-05, 'learning_rate/action_query_proj': 9.443485430053056e-05, 'learning_rate/base': 2.360871357513264e-05, 'epoch': 0.58}) +[2026-07-27 09:51:14,393][starVLA.training.train_starvla][INFO] - Step 4775, Loss: {'train/loss': 0.09856364130973816, 'train/grad_norm_pre_clip': 3.676832437515259, 'timing/data': 0.00017845816910266876, 'timing/model': 0.45604980923235416, 'learning_rate/action_model': 9.44207502442573e-05, 'learning_rate/action_query_proj': 9.44207502442573e-05, 'learning_rate/base': 2.3605187561064324e-05, 'epoch': 0.58}) +[2026-07-27 09:51:19,886][starVLA.training.train_starvla][INFO] - Step 4776, Loss: {'train/loss': 0.09711097180843353, 'train/grad_norm_pre_clip': 2.694085121154785, 'timing/data': 0.0001751575618982315, 'timing/model': 0.45796637050807476, 'learning_rate/action_model': 9.440662944094364e-05, 'learning_rate/action_query_proj': 9.440662944094364e-05, 'learning_rate/base': 2.360165736023591e-05, 'epoch': 0.58}) +[2026-07-27 09:51:25,398][starVLA.training.train_starvla][INFO] - Step 4777, Loss: {'train/loss': 0.22027665376663208, 'train/grad_norm_pre_clip': 4.277848720550537, 'timing/data': 0.00018000230193138123, 'timing/model': 0.4561092983931303, 'learning_rate/action_model': 9.439249189616428e-05, 'learning_rate/action_query_proj': 9.439249189616428e-05, 'learning_rate/base': 2.359812297404107e-05, 'epoch': 0.58}) +[2026-07-27 09:51:30,918][starVLA.training.train_starvla][INFO] - Step 4778, Loss: {'train/loss': 0.07563239336013794, 'train/grad_norm_pre_clip': 4.201905727386475, 'timing/data': 0.00018800236284732819, 'timing/model': 0.4577071312814951, 'learning_rate/action_model': 9.43783376155005e-05, 'learning_rate/action_query_proj': 9.43783376155005e-05, 'learning_rate/base': 2.3594584403875124e-05, 'epoch': 0.58}) +[2026-07-27 09:51:36,464][starVLA.training.train_starvla][INFO] - Step 4779, Loss: {'train/loss': 0.23322202265262604, 'train/grad_norm_pre_clip': 4.860631465911865, 'timing/data': 0.00017719343304634094, 'timing/model': 0.4585208687931299, 'learning_rate/action_model': 9.436416660454016e-05, 'learning_rate/action_query_proj': 9.436416660454016e-05, 'learning_rate/base': 2.359104165113504e-05, 'epoch': 0.58}) +[2026-07-27 09:51:42,007][starVLA.training.train_starvla][INFO] - Step 4780, Loss: {'train/loss': 0.0863858312368393, 'train/grad_norm_pre_clip': 3.0655202865600586, 'timing/data': 0.00018642470240592957, 'timing/model': 0.4581867791712284, 'learning_rate/action_model': 9.434997886887776e-05, 'learning_rate/action_query_proj': 9.434997886887776e-05, 'learning_rate/base': 2.358749471721944e-05, 'epoch': 0.58}) +[2026-07-27 09:51:47,517][starVLA.training.train_starvla][INFO] - Step 4781, Loss: {'train/loss': 0.18366318941116333, 'train/grad_norm_pre_clip': 5.986408233642578, 'timing/data': 0.00018290244042873383, 'timing/model': 0.4574854262173176, 'learning_rate/action_model': 9.43357744141144e-05, 'learning_rate/action_query_proj': 9.43357744141144e-05, 'learning_rate/base': 2.35839436035286e-05, 'epoch': 0.58}) +[2026-07-27 09:51:53,037][starVLA.training.train_starvla][INFO] - Step 4782, Loss: {'train/loss': 0.036400314420461655, 'train/grad_norm_pre_clip': 1.9461907148361206, 'timing/data': 0.00019137561321258545, 'timing/model': 0.4554996732622385, 'learning_rate/action_model': 9.432155324585776e-05, 'learning_rate/action_query_proj': 9.432155324585776e-05, 'learning_rate/base': 2.358038831146444e-05, 'epoch': 0.58}) +[2026-07-27 09:51:58,561][starVLA.training.train_starvla][INFO] - Step 4783, Loss: {'train/loss': 0.08844359964132309, 'train/grad_norm_pre_clip': 2.684762477874756, 'timing/data': 0.0001988764852285385, 'timing/model': 0.4575993027538061, 'learning_rate/action_model': 9.430731536972218e-05, 'learning_rate/action_query_proj': 9.430731536972218e-05, 'learning_rate/base': 2.3576828842430544e-05, 'epoch': 0.58}) +[2026-07-27 09:52:04,192][starVLA.training.train_starvla][INFO] - Step 4784, Loss: {'train/loss': 0.059060998260974884, 'train/grad_norm_pre_clip': 2.1867525577545166, 'timing/data': 0.00017887912690639496, 'timing/model': 0.471347413957119, 'learning_rate/action_model': 9.429306079132849e-05, 'learning_rate/action_query_proj': 9.429306079132849e-05, 'learning_rate/base': 2.3573265197832122e-05, 'epoch': 0.58}) +[2026-07-27 09:52:09,751][starVLA.training.train_starvla][INFO] - Step 4785, Loss: {'train/loss': 0.05235353112220764, 'train/grad_norm_pre_clip': 2.745173931121826, 'timing/data': 0.00017258524894714355, 'timing/model': 0.4566168896853924, 'learning_rate/action_model': 9.427878951630418e-05, 'learning_rate/action_query_proj': 9.427878951630418e-05, 'learning_rate/base': 2.3569697379076044e-05, 'epoch': 0.58}) +[2026-07-27 09:52:15,303][starVLA.training.train_starvla][INFO] - Step 4786, Loss: {'train/loss': 0.14759351313114166, 'train/grad_norm_pre_clip': 4.240505695343018, 'timing/data': 0.00018940307199954987, 'timing/model': 0.45676999539136887, 'learning_rate/action_model': 9.426450155028334e-05, 'learning_rate/action_query_proj': 9.426450155028334e-05, 'learning_rate/base': 2.3566125387570834e-05, 'epoch': 0.58}) +[2026-07-27 09:52:20,865][starVLA.training.train_starvla][INFO] - Step 4787, Loss: {'train/loss': 0.02829485572874546, 'train/grad_norm_pre_clip': 1.6405091285705566, 'timing/data': 0.0001919381320476532, 'timing/model': 0.45597350038588047, 'learning_rate/action_model': 9.425019689890664e-05, 'learning_rate/action_query_proj': 9.425019689890664e-05, 'learning_rate/base': 2.356254922472666e-05, 'epoch': 0.58}) +[2026-07-27 09:52:26,406][starVLA.training.train_starvla][INFO] - Step 4788, Loss: {'train/loss': 0.06781744211912155, 'train/grad_norm_pre_clip': 2.6176915168762207, 'timing/data': 0.00017364323139190674, 'timing/model': 0.45782157219946384, 'learning_rate/action_model': 9.42358755678213e-05, 'learning_rate/action_query_proj': 9.42358755678213e-05, 'learning_rate/base': 2.3558968891955324e-05, 'epoch': 0.58}) +[2026-07-27 09:52:31,989][starVLA.training.train_starvla][INFO] - Step 4789, Loss: {'train/loss': 0.10347811132669449, 'train/grad_norm_pre_clip': 4.066562175750732, 'timing/data': 0.00018084794282913208, 'timing/model': 0.47078640200197697, 'learning_rate/action_model': 9.42215375626812e-05, 'learning_rate/action_query_proj': 9.42215375626812e-05, 'learning_rate/base': 2.35553843906703e-05, 'epoch': 0.58}) +[2026-07-27 09:52:37,564][starVLA.training.train_starvla][INFO] - Step 4790, Loss: {'train/loss': 0.10775246471166611, 'train/grad_norm_pre_clip': 3.6351120471954346, 'timing/data': 0.00018662028014659882, 'timing/model': 0.47063824348151684, 'learning_rate/action_model': 9.42071828891467e-05, 'learning_rate/action_query_proj': 9.42071828891467e-05, 'learning_rate/base': 2.3551795722286675e-05, 'epoch': 0.58}) +[2026-07-27 09:52:43,148][starVLA.training.train_starvla][INFO] - Step 4791, Loss: {'train/loss': 0.07354450225830078, 'train/grad_norm_pre_clip': 3.7266623973846436, 'timing/data': 0.0001787971705198288, 'timing/model': 0.4747445248067379, 'learning_rate/action_model': 9.419281155288484e-05, 'learning_rate/action_query_proj': 9.419281155288484e-05, 'learning_rate/base': 2.354820288822121e-05, 'epoch': 0.58}) +[2026-07-27 09:52:48,754][starVLA.training.train_starvla][INFO] - Step 4792, Loss: {'train/loss': 0.140461266040802, 'train/grad_norm_pre_clip': 4.29401159286499, 'timing/data': 0.00019057095050811768, 'timing/model': 0.4579196386039257, 'learning_rate/action_model': 9.417842355956918e-05, 'learning_rate/action_query_proj': 9.417842355956918e-05, 'learning_rate/base': 2.3544605889892295e-05, 'epoch': 0.58}) +[2026-07-27 09:52:54,287][starVLA.training.train_starvla][INFO] - Step 4793, Loss: {'train/loss': 0.07673326879739761, 'train/grad_norm_pre_clip': 2.796863079071045, 'timing/data': 0.0001769028604030609, 'timing/model': 0.4592727180570364, 'learning_rate/action_model': 9.416401891487989e-05, 'learning_rate/action_query_proj': 9.416401891487989e-05, 'learning_rate/base': 2.3541004728719973e-05, 'epoch': 0.58}) +[2026-07-27 09:52:59,826][starVLA.training.train_starvla][INFO] - Step 4794, Loss: {'train/loss': 0.0847044438123703, 'train/grad_norm_pre_clip': 3.3047282695770264, 'timing/data': 0.00017629750072956085, 'timing/model': 0.4563419222831726, 'learning_rate/action_model': 9.414959762450369e-05, 'learning_rate/action_query_proj': 9.414959762450369e-05, 'learning_rate/base': 2.353739940612592e-05, 'epoch': 0.58}) +[2026-07-27 09:53:05,359][starVLA.training.train_starvla][INFO] - Step 4795, Loss: {'train/loss': 0.14440308511257172, 'train/grad_norm_pre_clip': 4.682662010192871, 'timing/data': 0.00017597898840904236, 'timing/model': 0.4555433467030525, 'learning_rate/action_model': 9.413515969413386e-05, 'learning_rate/action_query_proj': 9.413515969413386e-05, 'learning_rate/base': 2.3533789923533465e-05, 'epoch': 0.58}) +[2026-07-27 09:53:10,920][starVLA.training.train_starvla][INFO] - Step 4796, Loss: {'train/loss': 0.043779224157333374, 'train/grad_norm_pre_clip': 2.5804314613342285, 'timing/data': 0.00018194317817687988, 'timing/model': 0.45606518164277077, 'learning_rate/action_model': 9.412070512947025e-05, 'learning_rate/action_query_proj': 9.412070512947025e-05, 'learning_rate/base': 2.3530176282367562e-05, 'epoch': 0.58}) +[2026-07-27 09:53:16,474][starVLA.training.train_starvla][INFO] - Step 4797, Loss: {'train/loss': 0.06971985846757889, 'train/grad_norm_pre_clip': 3.1094813346862793, 'timing/data': 0.00022378936409950256, 'timing/model': 0.455133568495512, 'learning_rate/action_model': 9.410623393621935e-05, 'learning_rate/action_query_proj': 9.410623393621935e-05, 'learning_rate/base': 2.3526558484054838e-05, 'epoch': 0.58}) +[2026-07-27 09:53:22,059][starVLA.training.train_starvla][INFO] - Step 4798, Loss: {'train/loss': 0.06832576543092728, 'train/grad_norm_pre_clip': 3.315805673599243, 'timing/data': 0.00018733367323875427, 'timing/model': 0.4580806363373995, 'learning_rate/action_model': 9.40917461200941e-05, 'learning_rate/action_query_proj': 9.40917461200941e-05, 'learning_rate/base': 2.3522936530023525e-05, 'epoch': 0.58}) +[2026-07-27 09:53:27,654][starVLA.training.train_starvla][INFO] - Step 4799, Loss: {'train/loss': 0.034753717482089996, 'train/grad_norm_pre_clip': 2.1116933822631836, 'timing/data': 0.00018257088959217072, 'timing/model': 0.45668613724410534, 'learning_rate/action_model': 9.40772416868141e-05, 'learning_rate/action_query_proj': 9.40772416868141e-05, 'learning_rate/base': 2.3519310421703526e-05, 'epoch': 0.58}) +[2026-07-27 09:53:33,229][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 4800 +[2026-07-27 09:53:33,229][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 4800 +[2026-07-27 09:53:33,230][starVLA.training.train_starvla][INFO] - Step 4800, Loss: {'train/loss': 0.20006024837493896, 'train/grad_norm_pre_clip': 5.690243721008301, 'timing/data': 0.00017839297652244568, 'timing/model': 0.4572585392743349, 'learning_rate/action_model': 9.406272064210545e-05, 'learning_rate/action_query_proj': 9.406272064210545e-05, 'learning_rate/base': 2.351568016052636e-05, 'epoch': 0.58}) +[2026-07-27 09:53:38,775][starVLA.training.train_starvla][INFO] - Step 4801, Loss: {'train/loss': 0.09965186566114426, 'train/grad_norm_pre_clip': 2.763051986694336, 'timing/data': 0.00017704255878925323, 'timing/model': 0.4576718844473362, 'learning_rate/action_model': 9.404818299170084e-05, 'learning_rate/action_query_proj': 9.404818299170084e-05, 'learning_rate/base': 2.351204574792521e-05, 'epoch': 0.58}) +[2026-07-27 09:53:44,318][starVLA.training.train_starvla][INFO] - Step 4802, Loss: {'train/loss': 0.14184728264808655, 'train/grad_norm_pre_clip': 3.935868978500366, 'timing/data': 0.00019454769790172577, 'timing/model': 0.4582321047782898, 'learning_rate/action_model': 9.403362874133952e-05, 'learning_rate/action_query_proj': 9.403362874133952e-05, 'learning_rate/base': 2.350840718533488e-05, 'epoch': 0.58}) +[2026-07-27 09:53:49,850][starVLA.training.train_starvla][INFO] - Step 4803, Loss: {'train/loss': 0.06663363426923752, 'train/grad_norm_pre_clip': 2.873386859893799, 'timing/data': 0.00017502717673778534, 'timing/model': 0.4576668869704008, 'learning_rate/action_model': 9.401905789676722e-05, 'learning_rate/action_query_proj': 9.401905789676722e-05, 'learning_rate/base': 2.3504764474191806e-05, 'epoch': 0.58}) +[2026-07-27 09:53:55,388][starVLA.training.train_starvla][INFO] - Step 4804, Loss: {'train/loss': 0.16437123715877533, 'train/grad_norm_pre_clip': 3.7119531631469727, 'timing/data': 0.0001865960657596588, 'timing/model': 0.4583456199616194, 'learning_rate/action_model': 9.400447046373634e-05, 'learning_rate/action_query_proj': 9.400447046373634e-05, 'learning_rate/base': 2.3501117615934086e-05, 'epoch': 0.58}) +[2026-07-27 09:54:00,951][starVLA.training.train_starvla][INFO] - Step 4805, Loss: {'train/loss': 0.06532090902328491, 'train/grad_norm_pre_clip': 3.1371231079101562, 'timing/data': 0.0001950375735759735, 'timing/model': 0.4573340527713299, 'learning_rate/action_model': 9.398986644800573e-05, 'learning_rate/action_query_proj': 9.398986644800573e-05, 'learning_rate/base': 2.3497466612001434e-05, 'epoch': 0.58}) +[2026-07-27 09:54:06,507][starVLA.training.train_starvla][INFO] - Step 4806, Loss: {'train/loss': 0.17127946019172668, 'train/grad_norm_pre_clip': 4.12639045715332, 'timing/data': 0.0001787673681974411, 'timing/model': 0.45988577231764793, 'learning_rate/action_model': 9.397524585534085e-05, 'learning_rate/action_query_proj': 9.397524585534085e-05, 'learning_rate/base': 2.3493811463835213e-05, 'epoch': 0.58}) +[2026-07-27 09:54:12,072][starVLA.training.train_starvla][INFO] - Step 4807, Loss: {'train/loss': 0.09580336511135101, 'train/grad_norm_pre_clip': 4.187339782714844, 'timing/data': 0.00018994510173797607, 'timing/model': 0.4585006795823574, 'learning_rate/action_model': 9.396060869151366e-05, 'learning_rate/action_query_proj': 9.396060869151366e-05, 'learning_rate/base': 2.3490152172878414e-05, 'epoch': 0.58}) +[2026-07-27 09:54:17,654][starVLA.training.train_starvla][INFO] - Step 4808, Loss: {'train/loss': 0.08066678792238235, 'train/grad_norm_pre_clip': 3.6818735599517822, 'timing/data': 0.00017622485756874084, 'timing/model': 0.458997031673789, 'learning_rate/action_model': 9.39459549623027e-05, 'learning_rate/action_query_proj': 9.39459549623027e-05, 'learning_rate/base': 2.3486488740575675e-05, 'epoch': 0.58}) +[2026-07-27 09:54:23,226][starVLA.training.train_starvla][INFO] - Step 4809, Loss: {'train/loss': 0.10973740369081497, 'train/grad_norm_pre_clip': 4.561856269836426, 'timing/data': 0.0001742914319038391, 'timing/model': 0.47404558025300503, 'learning_rate/action_model': 9.393128467349301e-05, 'learning_rate/action_query_proj': 9.393128467349301e-05, 'learning_rate/base': 2.3482821168373252e-05, 'epoch': 0.58}) +[2026-07-27 09:54:28,793][starVLA.training.train_starvla][INFO] - Step 4810, Loss: {'train/loss': 0.13325932621955872, 'train/grad_norm_pre_clip': 4.684430122375488, 'timing/data': 0.00018370337784290314, 'timing/model': 0.4673735909163952, 'learning_rate/action_model': 9.391659783087618e-05, 'learning_rate/action_query_proj': 9.391659783087618e-05, 'learning_rate/base': 2.3479149457719045e-05, 'epoch': 0.58}) +[2026-07-27 09:54:34,421][starVLA.training.train_starvla][INFO] - Step 4811, Loss: {'train/loss': 0.10879633575677872, 'train/grad_norm_pre_clip': 3.0103037357330322, 'timing/data': 0.00017894059419631958, 'timing/model': 0.4704563822597265, 'learning_rate/action_model': 9.390189444025036e-05, 'learning_rate/action_query_proj': 9.390189444025036e-05, 'learning_rate/base': 2.347547361006259e-05, 'epoch': 0.58}) +[2026-07-27 09:54:40,025][starVLA.training.train_starvla][INFO] - Step 4812, Loss: {'train/loss': 0.11282988637685776, 'train/grad_norm_pre_clip': 3.00844144821167, 'timing/data': 0.00017631985247135162, 'timing/model': 0.47123684361577034, 'learning_rate/action_model': 9.388717450742021e-05, 'learning_rate/action_query_proj': 9.388717450742021e-05, 'learning_rate/base': 2.3471793626855053e-05, 'epoch': 0.58}) +[2026-07-27 09:54:45,573][starVLA.training.train_starvla][INFO] - Step 4813, Loss: {'train/loss': 0.11510229855775833, 'train/grad_norm_pre_clip': 3.1637580394744873, 'timing/data': 0.00017504766583442688, 'timing/model': 0.46996600925922394, 'learning_rate/action_model': 9.387243803819694e-05, 'learning_rate/action_query_proj': 9.387243803819694e-05, 'learning_rate/base': 2.3468109509549235e-05, 'epoch': 0.58}) +[2026-07-27 09:54:51,121][starVLA.training.train_starvla][INFO] - Step 4814, Loss: {'train/loss': 0.07204817235469818, 'train/grad_norm_pre_clip': 2.795438289642334, 'timing/data': 0.0001872032880783081, 'timing/model': 0.46928225457668304, 'learning_rate/action_model': 9.385768503839827e-05, 'learning_rate/action_query_proj': 9.385768503839827e-05, 'learning_rate/base': 2.346442125959957e-05, 'epoch': 0.58}) +[2026-07-27 09:54:56,686][starVLA.training.train_starvla][INFO] - Step 4815, Loss: {'train/loss': 0.07110917568206787, 'train/grad_norm_pre_clip': 3.9344682693481445, 'timing/data': 0.00018621794879436493, 'timing/model': 0.47861882485449314, 'learning_rate/action_model': 9.384291551384843e-05, 'learning_rate/action_query_proj': 9.384291551384843e-05, 'learning_rate/base': 2.346072887846211e-05, 'epoch': 0.58}) +[2026-07-27 09:55:02,264][starVLA.training.train_starvla][INFO] - Step 4816, Loss: {'train/loss': 0.05965420603752136, 'train/grad_norm_pre_clip': 2.70910382270813, 'timing/data': 0.00017580948770046234, 'timing/model': 0.47587491758167744, 'learning_rate/action_model': 9.382812947037821e-05, 'learning_rate/action_query_proj': 9.382812947037821e-05, 'learning_rate/base': 2.3457032367594552e-05, 'epoch': 0.58}) +[2026-07-27 09:55:07,832][starVLA.training.train_starvla][INFO] - Step 4817, Loss: {'train/loss': 0.12724284827709198, 'train/grad_norm_pre_clip': 3.906808376312256, 'timing/data': 0.00017987191677093506, 'timing/model': 0.47597626224160194, 'learning_rate/action_model': 9.381332691382491e-05, 'learning_rate/action_query_proj': 9.381332691382491e-05, 'learning_rate/base': 2.345333172845623e-05, 'epoch': 0.58}) +[2026-07-27 09:55:13,380][starVLA.training.train_starvla][INFO] - Step 4818, Loss: {'train/loss': 0.12381857633590698, 'train/grad_norm_pre_clip': 3.8833580017089844, 'timing/data': 0.00017654895782470703, 'timing/model': 0.45847887359559536, 'learning_rate/action_model': 9.379850785003234e-05, 'learning_rate/action_query_proj': 9.379850785003234e-05, 'learning_rate/base': 2.3449626962508086e-05, 'epoch': 0.58}) +[2026-07-27 09:55:18,921][starVLA.training.train_starvla][INFO] - Step 4819, Loss: {'train/loss': 0.06354926526546478, 'train/grad_norm_pre_clip': 2.549311876296997, 'timing/data': 0.00017509795725345612, 'timing/model': 0.469735911116004, 'learning_rate/action_model': 9.378367228485083e-05, 'learning_rate/action_query_proj': 9.378367228485083e-05, 'learning_rate/base': 2.3445918071212707e-05, 'epoch': 0.58}) +[2026-07-27 09:55:24,497][starVLA.training.train_starvla][INFO] - Step 4820, Loss: {'train/loss': 0.12727725505828857, 'train/grad_norm_pre_clip': 4.225377559661865, 'timing/data': 0.0001849345862865448, 'timing/model': 0.476924829185009, 'learning_rate/action_model': 9.376882022413723e-05, 'learning_rate/action_query_proj': 9.376882022413723e-05, 'learning_rate/base': 2.3442205056034307e-05, 'epoch': 0.58}) +[2026-07-27 09:55:30,047][starVLA.training.train_starvla][INFO] - Step 4821, Loss: {'train/loss': 0.1259375661611557, 'train/grad_norm_pre_clip': 3.483039379119873, 'timing/data': 0.00018901750445365906, 'timing/model': 0.47172732651233673, 'learning_rate/action_model': 9.375395167375489e-05, 'learning_rate/action_query_proj': 9.375395167375489e-05, 'learning_rate/base': 2.3438487918438723e-05, 'epoch': 0.58}) +[2026-07-27 09:55:35,605][starVLA.training.train_starvla][INFO] - Step 4822, Loss: {'train/loss': 0.09419228881597519, 'train/grad_norm_pre_clip': 3.0813491344451904, 'timing/data': 0.00017626211047172546, 'timing/model': 0.4705084655433893, 'learning_rate/action_model': 9.37390666395737e-05, 'learning_rate/action_query_proj': 9.37390666395737e-05, 'learning_rate/base': 2.3434766659893427e-05, 'epoch': 0.58}) +[2026-07-27 09:55:41,172][starVLA.training.train_starvla][INFO] - Step 4823, Loss: {'train/loss': 0.041283659636974335, 'train/grad_norm_pre_clip': 1.9964669942855835, 'timing/data': 0.00019469857215881348, 'timing/model': 0.46790734492242336, 'learning_rate/action_model': 9.372416512747e-05, 'learning_rate/action_query_proj': 9.372416512747e-05, 'learning_rate/base': 2.34310412818675e-05, 'epoch': 0.59}) +[2026-07-27 09:55:46,752][starVLA.training.train_starvla][INFO] - Step 4824, Loss: {'train/loss': 0.060322120785713196, 'train/grad_norm_pre_clip': 2.638275623321533, 'timing/data': 0.00018881633877754211, 'timing/model': 0.4695691056549549, 'learning_rate/action_model': 9.370924714332671e-05, 'learning_rate/action_query_proj': 9.370924714332671e-05, 'learning_rate/base': 2.3427311785831678e-05, 'epoch': 0.59}) +[2026-07-27 09:55:52,320][starVLA.training.train_starvla][INFO] - Step 4825, Loss: {'train/loss': 0.15201213955879211, 'train/grad_norm_pre_clip': 3.315952777862549, 'timing/data': 0.00019218958914279938, 'timing/model': 0.45772668346762657, 'learning_rate/action_model': 9.36943126930332e-05, 'learning_rate/action_query_proj': 9.36943126930332e-05, 'learning_rate/base': 2.34235781732583e-05, 'epoch': 0.59}) +[2026-07-27 09:55:57,843][starVLA.training.train_starvla][INFO] - Step 4826, Loss: {'train/loss': 0.0969255119562149, 'train/grad_norm_pre_clip': 4.6318864822387695, 'timing/data': 0.00018639490008354187, 'timing/model': 0.4576368164271116, 'learning_rate/action_model': 9.367936178248533e-05, 'learning_rate/action_query_proj': 9.367936178248533e-05, 'learning_rate/base': 2.341984044562133e-05, 'epoch': 0.59}) +[2026-07-27 09:56:03,415][starVLA.training.train_starvla][INFO] - Step 4827, Loss: {'train/loss': 0.07851546257734299, 'train/grad_norm_pre_clip': 3.8847053050994873, 'timing/data': 0.00018478557467460632, 'timing/model': 0.4581067096441984, 'learning_rate/action_model': 9.36643944175855e-05, 'learning_rate/action_query_proj': 9.36643944175855e-05, 'learning_rate/base': 2.3416098604396374e-05, 'epoch': 0.59}) +[2026-07-27 09:56:08,988][starVLA.training.train_starvla][INFO] - Step 4828, Loss: {'train/loss': 0.13568636775016785, 'train/grad_norm_pre_clip': 5.052450656890869, 'timing/data': 0.0001799166202545166, 'timing/model': 0.45990338549017906, 'learning_rate/action_model': 9.364941060424258e-05, 'learning_rate/action_query_proj': 9.364941060424258e-05, 'learning_rate/base': 2.3412352651060645e-05, 'epoch': 0.59}) +[2026-07-27 09:56:14,580][starVLA.training.train_starvla][INFO] - Step 4829, Loss: {'train/loss': 0.12288526445627213, 'train/grad_norm_pre_clip': 3.6171417236328125, 'timing/data': 0.00017562881112098694, 'timing/model': 0.459042277187109, 'learning_rate/action_model': 9.363441034837199e-05, 'learning_rate/action_query_proj': 9.363441034837199e-05, 'learning_rate/base': 2.3408602587092997e-05, 'epoch': 0.59}) +[2026-07-27 09:56:20,358][starVLA.training.train_starvla][INFO] - Step 4830, Loss: {'train/loss': 0.09037734568119049, 'train/grad_norm_pre_clip': 4.471619129180908, 'timing/data': 0.00017674453556537628, 'timing/model': 0.45752979442477226, 'learning_rate/action_model': 9.361939365589553e-05, 'learning_rate/action_query_proj': 9.361939365589553e-05, 'learning_rate/base': 2.3404848413973883e-05, 'epoch': 0.59}) +[2026-07-27 09:56:25,946][starVLA.training.train_starvla][INFO] - Step 4831, Loss: {'train/loss': 0.09876882284879684, 'train/grad_norm_pre_clip': 3.66510272026062, 'timing/data': 0.0001798924058675766, 'timing/model': 0.45825047604739666, 'learning_rate/action_model': 9.360436053274158e-05, 'learning_rate/action_query_proj': 9.360436053274158e-05, 'learning_rate/base': 2.3401090133185395e-05, 'epoch': 0.59}) +[2026-07-27 09:56:31,545][starVLA.training.train_starvla][INFO] - Step 4832, Loss: {'train/loss': 0.0586913526058197, 'train/grad_norm_pre_clip': 2.5806336402893066, 'timing/data': 0.0002258066087961197, 'timing/model': 0.45731339789927006, 'learning_rate/action_model': 9.358931098484499e-05, 'learning_rate/action_query_proj': 9.358931098484499e-05, 'learning_rate/base': 2.3397327746211247e-05, 'epoch': 0.59}) +[2026-07-27 09:56:37,123][starVLA.training.train_starvla][INFO] - Step 4833, Loss: {'train/loss': 0.13206779956817627, 'train/grad_norm_pre_clip': 3.1044669151306152, 'timing/data': 0.00018064118921756744, 'timing/model': 0.4582712519913912, 'learning_rate/action_model': 9.357424501814706e-05, 'learning_rate/action_query_proj': 9.357424501814706e-05, 'learning_rate/base': 2.3393561254536764e-05, 'epoch': 0.59}) +[2026-07-27 09:56:42,686][starVLA.training.train_starvla][INFO] - Step 4834, Loss: {'train/loss': 0.04768594726920128, 'train/grad_norm_pre_clip': 3.043482780456543, 'timing/data': 0.00018614530563354492, 'timing/model': 0.45804624259471893, 'learning_rate/action_model': 9.355916263859561e-05, 'learning_rate/action_query_proj': 9.355916263859561e-05, 'learning_rate/base': 2.3389790659648904e-05, 'epoch': 0.59}) +[2026-07-27 09:56:48,340][starVLA.training.train_starvla][INFO] - Step 4835, Loss: {'train/loss': 0.04055693745613098, 'train/grad_norm_pre_clip': 2.3701717853546143, 'timing/data': 0.00017708539962768555, 'timing/model': 0.458001172170043, 'learning_rate/action_model': 9.354406385214491e-05, 'learning_rate/action_query_proj': 9.354406385214491e-05, 'learning_rate/base': 2.3386015963036227e-05, 'epoch': 0.59}) +[2026-07-27 09:56:53,910][starVLA.training.train_starvla][INFO] - Step 4836, Loss: {'train/loss': 0.14763620495796204, 'train/grad_norm_pre_clip': 4.431382656097412, 'timing/data': 0.00020125135779380798, 'timing/model': 0.4578188434243202, 'learning_rate/action_model': 9.352894866475575e-05, 'learning_rate/action_query_proj': 9.352894866475575e-05, 'learning_rate/base': 2.3382237166188937e-05, 'epoch': 0.59}) +[2026-07-27 09:56:59,490][starVLA.training.train_starvla][INFO] - Step 4837, Loss: {'train/loss': 0.12483005970716476, 'train/grad_norm_pre_clip': 5.202313423156738, 'timing/data': 0.00017652101814746857, 'timing/model': 0.4581495076417923, 'learning_rate/action_model': 9.351381708239534e-05, 'learning_rate/action_query_proj': 9.351381708239534e-05, 'learning_rate/base': 2.3378454270598835e-05, 'epoch': 0.59}) +[2026-07-27 09:57:05,001][starVLA.training.train_starvla][INFO] - Step 4838, Loss: {'train/loss': 0.20643407106399536, 'train/grad_norm_pre_clip': 5.755760669708252, 'timing/data': 0.00017883442342281342, 'timing/model': 0.4581914898008108, 'learning_rate/action_model': 9.34986691110374e-05, 'learning_rate/action_query_proj': 9.34986691110374e-05, 'learning_rate/base': 2.337466727775935e-05, 'epoch': 0.59}) +[2026-07-27 09:57:10,547][starVLA.training.train_starvla][INFO] - Step 4839, Loss: {'train/loss': 0.11734592914581299, 'train/grad_norm_pre_clip': 3.8047585487365723, 'timing/data': 0.0001890864223241806, 'timing/model': 0.46125526167452335, 'learning_rate/action_model': 9.34835047566621e-05, 'learning_rate/action_query_proj': 9.34835047566621e-05, 'learning_rate/base': 2.3370876189165525e-05, 'epoch': 0.59}) +[2026-07-27 09:57:16,087][starVLA.training.train_starvla][INFO] - Step 4840, Loss: {'train/loss': 0.08497141301631927, 'train/grad_norm_pre_clip': 4.600988864898682, 'timing/data': 0.00017501600086688995, 'timing/model': 0.45740069448947906, 'learning_rate/action_model': 9.34683240252561e-05, 'learning_rate/action_query_proj': 9.34683240252561e-05, 'learning_rate/base': 2.3367081006314024e-05, 'epoch': 0.59}) +[2026-07-27 09:57:21,624][starVLA.training.train_starvla][INFO] - Step 4841, Loss: {'train/loss': 0.03845711424946785, 'train/grad_norm_pre_clip': 2.185767889022827, 'timing/data': 0.00018138810992240906, 'timing/model': 0.4572832677513361, 'learning_rate/action_model': 9.345312692281251e-05, 'learning_rate/action_query_proj': 9.345312692281251e-05, 'learning_rate/base': 2.3363281730703128e-05, 'epoch': 0.59}) +[2026-07-27 09:57:27,145][starVLA.training.train_starvla][INFO] - Step 4842, Loss: {'train/loss': 0.095588818192482, 'train/grad_norm_pre_clip': 3.900015354156494, 'timing/data': 0.00018515437841415405, 'timing/model': 0.4588326159864664, 'learning_rate/action_model': 9.34379134553309e-05, 'learning_rate/action_query_proj': 9.34379134553309e-05, 'learning_rate/base': 2.3359478363832725e-05, 'epoch': 0.59}) +[2026-07-27 09:57:32,687][starVLA.training.train_starvla][INFO] - Step 4843, Loss: {'train/loss': 0.020772205665707588, 'train/grad_norm_pre_clip': 1.8559175729751587, 'timing/data': 0.000181613489985466, 'timing/model': 0.4583566375076771, 'learning_rate/action_model': 9.342268362881729e-05, 'learning_rate/action_query_proj': 9.342268362881729e-05, 'learning_rate/base': 2.3355670907204323e-05, 'epoch': 0.59}) +[2026-07-27 09:57:38,235][starVLA.training.train_starvla][INFO] - Step 4844, Loss: {'train/loss': 0.10455670207738876, 'train/grad_norm_pre_clip': 3.852954149246216, 'timing/data': 0.00018173456192016602, 'timing/model': 0.4759212676435709, 'learning_rate/action_model': 9.340743744928422e-05, 'learning_rate/action_query_proj': 9.340743744928422e-05, 'learning_rate/base': 2.3351859362321054e-05, 'epoch': 0.59}) +[2026-07-27 09:57:43,773][starVLA.training.train_starvla][INFO] - Step 4845, Loss: {'train/loss': 0.1166437491774559, 'train/grad_norm_pre_clip': 3.644127130508423, 'timing/data': 0.00017720460891723633, 'timing/model': 0.46689629182219505, 'learning_rate/action_model': 9.33921749227506e-05, 'learning_rate/action_query_proj': 9.33921749227506e-05, 'learning_rate/base': 2.334804373068765e-05, 'epoch': 0.59}) +[2026-07-27 09:57:49,308][starVLA.training.train_starvla][INFO] - Step 4846, Loss: {'train/loss': 0.08906333893537521, 'train/grad_norm_pre_clip': 4.097177028656006, 'timing/data': 0.00017485767602920532, 'timing/model': 0.4574561398476362, 'learning_rate/action_model': 9.337689605524184e-05, 'learning_rate/action_query_proj': 9.337689605524184e-05, 'learning_rate/base': 2.334422401381046e-05, 'epoch': 0.59}) +[2026-07-27 09:57:54,827][starVLA.training.train_starvla][INFO] - Step 4847, Loss: {'train/loss': 0.04358102008700371, 'train/grad_norm_pre_clip': 2.860088586807251, 'timing/data': 0.00022208504378795624, 'timing/model': 0.4581461250782013, 'learning_rate/action_model': 9.336160085278981e-05, 'learning_rate/action_query_proj': 9.336160085278981e-05, 'learning_rate/base': 2.3340400213197452e-05, 'epoch': 0.59}) +[2026-07-27 09:58:00,427][starVLA.training.train_starvla][INFO] - Step 4848, Loss: {'train/loss': 0.13138966262340546, 'train/grad_norm_pre_clip': 5.286785125732422, 'timing/data': 0.00018150918185710907, 'timing/model': 0.46728465147316456, 'learning_rate/action_model': 9.33462893214328e-05, 'learning_rate/action_query_proj': 9.33462893214328e-05, 'learning_rate/base': 2.33365723303582e-05, 'epoch': 0.59}) +[2026-07-27 09:58:05,933][starVLA.training.train_starvla][INFO] - Step 4849, Loss: {'train/loss': 0.13513383269309998, 'train/grad_norm_pre_clip': 4.121044158935547, 'timing/data': 0.00017447210848331451, 'timing/model': 0.459385359659791, 'learning_rate/action_model': 9.333096146721557e-05, 'learning_rate/action_query_proj': 9.333096146721557e-05, 'learning_rate/base': 2.333274036680389e-05, 'epoch': 0.59}) +[2026-07-27 09:58:11,433][starVLA.training.train_starvla][INFO] - Step 4850, Loss: {'train/loss': 0.1160987988114357, 'train/grad_norm_pre_clip': 3.6586508750915527, 'timing/data': 0.00017854198813438416, 'timing/model': 0.4578844476491213, 'learning_rate/action_model': 9.33156172961893e-05, 'learning_rate/action_query_proj': 9.33156172961893e-05, 'learning_rate/base': 2.3328904324047325e-05, 'epoch': 0.59}) +[2026-07-27 09:58:16,942][starVLA.training.train_starvla][INFO] - Step 4851, Loss: {'train/loss': 0.1011936366558075, 'train/grad_norm_pre_clip': 3.8227007389068604, 'timing/data': 0.00018196739256381989, 'timing/model': 0.4588621910661459, 'learning_rate/action_model': 9.330025681441163e-05, 'learning_rate/action_query_proj': 9.330025681441163e-05, 'learning_rate/base': 2.3325064203602908e-05, 'epoch': 0.59}) +[2026-07-27 09:58:22,463][starVLA.training.train_starvla][INFO] - Step 4852, Loss: {'train/loss': 0.06655574589967728, 'train/grad_norm_pre_clip': 2.6568400859832764, 'timing/data': 0.00017713569104671478, 'timing/model': 0.46409897692501545, 'learning_rate/action_model': 9.328488002794666e-05, 'learning_rate/action_query_proj': 9.328488002794666e-05, 'learning_rate/base': 2.3321220006986664e-05, 'epoch': 0.59}) +[2026-07-27 09:58:27,993][starVLA.training.train_starvla][INFO] - Step 4853, Loss: {'train/loss': 0.065948985517025, 'train/grad_norm_pre_clip': 2.9140143394470215, 'timing/data': 0.00018008239567279816, 'timing/model': 0.4617494475096464, 'learning_rate/action_model': 9.326948694286486e-05, 'learning_rate/action_query_proj': 9.326948694286486e-05, 'learning_rate/base': 2.3317371735716215e-05, 'epoch': 0.59}) +[2026-07-27 09:58:33,536][starVLA.training.train_starvla][INFO] - Step 4854, Loss: {'train/loss': 0.10633980482816696, 'train/grad_norm_pre_clip': 2.603749990463257, 'timing/data': 0.0001802407205104828, 'timing/model': 0.4613079186528921, 'learning_rate/action_model': 9.325407756524321e-05, 'learning_rate/action_query_proj': 9.325407756524321e-05, 'learning_rate/base': 2.3313519391310802e-05, 'epoch': 0.59}) +[2026-07-27 09:58:39,070][starVLA.training.train_starvla][INFO] - Step 4855, Loss: {'train/loss': 0.09445886313915253, 'train/grad_norm_pre_clip': 2.41125226020813, 'timing/data': 0.00017618760466575623, 'timing/model': 0.4622096512466669, 'learning_rate/action_model': 9.323865190116508e-05, 'learning_rate/action_query_proj': 9.323865190116508e-05, 'learning_rate/base': 2.330966297529127e-05, 'epoch': 0.59}) +[2026-07-27 09:58:44,610][starVLA.training.train_starvla][INFO] - Step 4856, Loss: {'train/loss': 0.09507584571838379, 'train/grad_norm_pre_clip': 3.3526856899261475, 'timing/data': 0.00017771311104297638, 'timing/model': 0.47602376341819763, 'learning_rate/action_model': 9.322320995672028e-05, 'learning_rate/action_query_proj': 9.322320995672028e-05, 'learning_rate/base': 2.330580248918007e-05, 'epoch': 0.59}) +[2026-07-27 09:58:50,321][starVLA.training.train_starvla][INFO] - Step 4857, Loss: {'train/loss': 0.04974432289600372, 'train/grad_norm_pre_clip': 2.340216875076294, 'timing/data': 0.00017192959785461426, 'timing/model': 0.6439372152090073, 'learning_rate/action_model': 9.3207751738005e-05, 'learning_rate/action_query_proj': 9.3207751738005e-05, 'learning_rate/base': 2.330193793450125e-05, 'epoch': 0.59}) +[2026-07-27 09:58:55,857][starVLA.training.train_starvla][INFO] - Step 4858, Loss: {'train/loss': 0.0513683445751667, 'train/grad_norm_pre_clip': 2.60872745513916, 'timing/data': 0.0001962035894393921, 'timing/model': 0.4737959485501051, 'learning_rate/action_model': 9.319227725112199e-05, 'learning_rate/action_query_proj': 9.319227725112199e-05, 'learning_rate/base': 2.3298069312780497e-05, 'epoch': 0.59}) +[2026-07-27 09:59:01,387][starVLA.training.train_starvla][INFO] - Step 4859, Loss: {'train/loss': 0.07713475823402405, 'train/grad_norm_pre_clip': 2.7016851902008057, 'timing/data': 0.0001696404069662094, 'timing/model': 0.4719357006251812, 'learning_rate/action_model': 9.317678650218024e-05, 'learning_rate/action_query_proj': 9.317678650218024e-05, 'learning_rate/base': 2.329419662554506e-05, 'epoch': 0.59}) +[2026-07-27 09:59:06,917][starVLA.training.train_starvla][INFO] - Step 4860, Loss: {'train/loss': 0.10027826577425003, 'train/grad_norm_pre_clip': 4.037066459655762, 'timing/data': 0.00016615167260169983, 'timing/model': 0.47820076160132885, 'learning_rate/action_model': 9.316127949729531e-05, 'learning_rate/action_query_proj': 9.316127949729531e-05, 'learning_rate/base': 2.329031987432383e-05, 'epoch': 0.59}) +[2026-07-27 09:59:12,717][starVLA.training.train_starvla][INFO] - Step 4861, Loss: {'train/loss': 0.03309472277760506, 'train/grad_norm_pre_clip': 1.7989542484283447, 'timing/data': 0.0001788567751646042, 'timing/model': 0.47741141729056835, 'learning_rate/action_model': 9.314575624258912e-05, 'learning_rate/action_query_proj': 9.314575624258912e-05, 'learning_rate/base': 2.328643906064728e-05, 'epoch': 0.59}) +[2026-07-27 09:59:18,275][starVLA.training.train_starvla][INFO] - Step 4862, Loss: {'train/loss': 0.06627414375543594, 'train/grad_norm_pre_clip': 1.8990176916122437, 'timing/data': 0.00017512217164039612, 'timing/model': 0.47047943621873856, 'learning_rate/action_model': 9.313021674418996e-05, 'learning_rate/action_query_proj': 9.313021674418996e-05, 'learning_rate/base': 2.328255418604749e-05, 'epoch': 0.59}) +[2026-07-27 09:59:24,167][starVLA.training.train_starvla][INFO] - Step 4863, Loss: {'train/loss': 0.02743656374514103, 'train/grad_norm_pre_clip': 1.8678059577941895, 'timing/data': 0.00016992166638374329, 'timing/model': 0.4703102521598339, 'learning_rate/action_model': 9.311466100823261e-05, 'learning_rate/action_query_proj': 9.311466100823261e-05, 'learning_rate/base': 2.3278665252058152e-05, 'epoch': 0.59}) +[2026-07-27 09:59:29,785][starVLA.training.train_starvla][INFO] - Step 4864, Loss: {'train/loss': 0.08188212662935257, 'train/grad_norm_pre_clip': 2.9276280403137207, 'timing/data': 0.0001676958054304123, 'timing/model': 0.47027916461229324, 'learning_rate/action_model': 9.309908904085823e-05, 'learning_rate/action_query_proj': 9.309908904085823e-05, 'learning_rate/base': 2.327477226021456e-05, 'epoch': 0.59}) +[2026-07-27 09:59:35,346][starVLA.training.train_starvla][INFO] - Step 4865, Loss: {'train/loss': 0.08032558113336563, 'train/grad_norm_pre_clip': 3.373465061187744, 'timing/data': 0.00017115846276283264, 'timing/model': 0.4804928656667471, 'learning_rate/action_model': 9.308350084821439e-05, 'learning_rate/action_query_proj': 9.308350084821439e-05, 'learning_rate/base': 2.3270875212053597e-05, 'epoch': 0.59}) +[2026-07-27 09:59:40,872][starVLA.training.train_starvla][INFO] - Step 4866, Loss: {'train/loss': 0.0795649066567421, 'train/grad_norm_pre_clip': 4.344071865081787, 'timing/data': 0.00017347559332847595, 'timing/model': 0.471810819581151, 'learning_rate/action_model': 9.306789643645505e-05, 'learning_rate/action_query_proj': 9.306789643645505e-05, 'learning_rate/base': 2.3266974109113763e-05, 'epoch': 0.59}) +[2026-07-27 09:59:46,406][starVLA.training.train_starvla][INFO] - Step 4867, Loss: {'train/loss': 0.040997885167598724, 'train/grad_norm_pre_clip': 2.9717211723327637, 'timing/data': 0.00018761493265628815, 'timing/model': 0.4714688453823328, 'learning_rate/action_model': 9.305227581174057e-05, 'learning_rate/action_query_proj': 9.305227581174057e-05, 'learning_rate/base': 2.3263068952935142e-05, 'epoch': 0.59}) +[2026-07-27 09:59:51,924][starVLA.training.train_starvla][INFO] - Step 4868, Loss: {'train/loss': 0.07776332646608353, 'train/grad_norm_pre_clip': 2.7714040279388428, 'timing/data': 0.0001725759357213974, 'timing/model': 0.4577674772590399, 'learning_rate/action_model': 9.303663898023776e-05, 'learning_rate/action_query_proj': 9.303663898023776e-05, 'learning_rate/base': 2.325915974505944e-05, 'epoch': 0.59}) +[2026-07-27 09:59:57,414][starVLA.training.train_starvla][INFO] - Step 4869, Loss: {'train/loss': 0.11812874674797058, 'train/grad_norm_pre_clip': 4.101599216461182, 'timing/data': 0.00017596222460269928, 'timing/model': 0.4581382032483816, 'learning_rate/action_model': 9.302098594811976e-05, 'learning_rate/action_query_proj': 9.302098594811976e-05, 'learning_rate/base': 2.325524648702994e-05, 'epoch': 0.59}) +[2026-07-27 10:00:02,941][starVLA.training.train_starvla][INFO] - Step 4870, Loss: {'train/loss': 0.11543000489473343, 'train/grad_norm_pre_clip': 3.124014377593994, 'timing/data': 0.0001759100705385208, 'timing/model': 0.458022715523839, 'learning_rate/action_model': 9.300531672156618e-05, 'learning_rate/action_query_proj': 9.300531672156618e-05, 'learning_rate/base': 2.3251329180391544e-05, 'epoch': 0.59}) +[2026-07-27 10:00:08,447][starVLA.training.train_starvla][INFO] - Step 4871, Loss: {'train/loss': 0.02957873046398163, 'train/grad_norm_pre_clip': 1.5526790618896484, 'timing/data': 0.0001801326870918274, 'timing/model': 0.4686821326613426, 'learning_rate/action_model': 9.298963130676294e-05, 'learning_rate/action_query_proj': 9.298963130676294e-05, 'learning_rate/base': 2.3247407826690736e-05, 'epoch': 0.59}) +[2026-07-27 10:00:13,975][starVLA.training.train_starvla][INFO] - Step 4872, Loss: {'train/loss': 0.030310561880469322, 'train/grad_norm_pre_clip': 2.250081777572632, 'timing/data': 0.00018061138689517975, 'timing/model': 0.47460926696658134, 'learning_rate/action_model': 9.297392970990241e-05, 'learning_rate/action_query_proj': 9.297392970990241e-05, 'learning_rate/base': 2.3243482427475603e-05, 'epoch': 0.59}) +[2026-07-27 10:00:19,512][starVLA.training.train_starvla][INFO] - Step 4873, Loss: {'train/loss': 0.1462591141462326, 'train/grad_norm_pre_clip': 5.136019706726074, 'timing/data': 0.00022145919501781464, 'timing/model': 0.4769252110272646, 'learning_rate/action_model': 9.295821193718334e-05, 'learning_rate/action_query_proj': 9.295821193718334e-05, 'learning_rate/base': 2.3239552984295835e-05, 'epoch': 0.59}) +[2026-07-27 10:00:25,043][starVLA.training.train_starvla][INFO] - Step 4874, Loss: {'train/loss': 0.0631779357790947, 'train/grad_norm_pre_clip': 3.0146806240081787, 'timing/data': 0.00018730014562606812, 'timing/model': 0.4696388728916645, 'learning_rate/action_model': 9.294247799481083e-05, 'learning_rate/action_query_proj': 9.294247799481083e-05, 'learning_rate/base': 2.3235619498702706e-05, 'epoch': 0.59}) +[2026-07-27 10:00:30,618][starVLA.training.train_starvla][INFO] - Step 4875, Loss: {'train/loss': 0.0935530886054039, 'train/grad_norm_pre_clip': 3.038592576980591, 'timing/data': 0.00017868727445602417, 'timing/model': 0.46817695163190365, 'learning_rate/action_model': 9.292672788899643e-05, 'learning_rate/action_query_proj': 9.292672788899643e-05, 'learning_rate/base': 2.3231681972249107e-05, 'epoch': 0.59}) +[2026-07-27 10:00:36,134][starVLA.training.train_starvla][INFO] - Step 4876, Loss: {'train/loss': 0.022302333265542984, 'train/grad_norm_pre_clip': 1.6433846950531006, 'timing/data': 0.0001778099685907364, 'timing/model': 0.46982194297015667, 'learning_rate/action_model': 9.291096162595801e-05, 'learning_rate/action_query_proj': 9.291096162595801e-05, 'learning_rate/base': 2.3227740406489503e-05, 'epoch': 0.59}) +[2026-07-27 10:00:41,653][starVLA.training.train_starvla][INFO] - Step 4877, Loss: {'train/loss': 0.10624248534440994, 'train/grad_norm_pre_clip': 3.6042678356170654, 'timing/data': 0.0001786462962627411, 'timing/model': 0.47042466700077057, 'learning_rate/action_model': 9.289517921191985e-05, 'learning_rate/action_query_proj': 9.289517921191985e-05, 'learning_rate/base': 2.3223794802979963e-05, 'epoch': 0.59}) +[2026-07-27 10:00:47,173][starVLA.training.train_starvla][INFO] - Step 4878, Loss: {'train/loss': 0.0412742979824543, 'train/grad_norm_pre_clip': 2.269089460372925, 'timing/data': 0.00017622113227844238, 'timing/model': 0.4722718261182308, 'learning_rate/action_model': 9.287938065311258e-05, 'learning_rate/action_query_proj': 9.287938065311258e-05, 'learning_rate/base': 2.3219845163278144e-05, 'epoch': 0.59}) +[2026-07-27 10:00:52,704][starVLA.training.train_starvla][INFO] - Step 4879, Loss: {'train/loss': 0.13653673231601715, 'train/grad_norm_pre_clip': 3.6121931076049805, 'timing/data': 0.00018818117678165436, 'timing/model': 0.4693934712558985, 'learning_rate/action_model': 9.286356595577325e-05, 'learning_rate/action_query_proj': 9.286356595577325e-05, 'learning_rate/base': 2.3215891488943312e-05, 'epoch': 0.59}) +[2026-07-27 10:00:58,340][starVLA.training.train_starvla][INFO] - Step 4880, Loss: {'train/loss': 0.04832975193858147, 'train/grad_norm_pre_clip': 2.267690896987915, 'timing/data': 0.00018902122974395752, 'timing/model': 0.47053309716284275, 'learning_rate/action_model': 9.284773512614522e-05, 'learning_rate/action_query_proj': 9.284773512614522e-05, 'learning_rate/base': 2.3211933781536305e-05, 'epoch': 0.59}) +[2026-07-27 10:01:03,867][starVLA.training.train_starvla][INFO] - Step 4881, Loss: {'train/loss': 0.07276137173175812, 'train/grad_norm_pre_clip': 3.553987503051758, 'timing/data': 0.00017471052706241608, 'timing/model': 0.4720308128744364, 'learning_rate/action_model': 9.283188817047826e-05, 'learning_rate/action_query_proj': 9.283188817047826e-05, 'learning_rate/base': 2.3207972042619566e-05, 'epoch': 0.59}) +[2026-07-27 10:01:09,381][starVLA.training.train_starvla][INFO] - Step 4882, Loss: {'train/loss': 0.05420766398310661, 'train/grad_norm_pre_clip': 2.829428195953369, 'timing/data': 0.00017513707280158997, 'timing/model': 0.4682665280997753, 'learning_rate/action_model': 9.281602509502851e-05, 'learning_rate/action_query_proj': 9.281602509502851e-05, 'learning_rate/base': 2.320400627375713e-05, 'epoch': 0.59}) +[2026-07-27 10:01:14,920][starVLA.training.train_starvla][INFO] - Step 4883, Loss: {'train/loss': 0.13679878413677216, 'train/grad_norm_pre_clip': 5.22874641418457, 'timing/data': 0.00017854943871498108, 'timing/model': 0.47313067689538, 'learning_rate/action_model': 9.280014590605847e-05, 'learning_rate/action_query_proj': 9.280014590605847e-05, 'learning_rate/base': 2.3200036476514617e-05, 'epoch': 0.59}) +[2026-07-27 10:01:20,458][starVLA.training.train_starvla][INFO] - Step 4884, Loss: {'train/loss': 0.1143542006611824, 'train/grad_norm_pre_clip': 4.7998175621032715, 'timing/data': 0.00017575547099113464, 'timing/model': 0.47569548338651657, 'learning_rate/action_model': 9.278425060983696e-05, 'learning_rate/action_query_proj': 9.278425060983696e-05, 'learning_rate/base': 2.319606265245924e-05, 'epoch': 0.59}) +[2026-07-27 10:01:25,977][starVLA.training.train_starvla][INFO] - Step 4885, Loss: {'train/loss': 0.11500271409749985, 'train/grad_norm_pre_clip': 4.323829650878906, 'timing/data': 0.00018014758825302124, 'timing/model': 0.47454516775906086, 'learning_rate/action_model': 9.27683392126392e-05, 'learning_rate/action_query_proj': 9.27683392126392e-05, 'learning_rate/base': 2.31920848031598e-05, 'epoch': 0.59}) +[2026-07-27 10:01:31,492][starVLA.training.train_starvla][INFO] - Step 4886, Loss: {'train/loss': 0.10552988201379776, 'train/grad_norm_pre_clip': 4.412445068359375, 'timing/data': 0.00018511340022087097, 'timing/model': 0.45763477869331837, 'learning_rate/action_model': 9.275241172074677e-05, 'learning_rate/action_query_proj': 9.275241172074677e-05, 'learning_rate/base': 2.318810293018669e-05, 'epoch': 0.59}) +[2026-07-27 10:01:37,028][starVLA.training.train_starvla][INFO] - Step 4887, Loss: {'train/loss': 0.06214458867907524, 'train/grad_norm_pre_clip': 3.110811710357666, 'timing/data': 0.0001798681914806366, 'timing/model': 0.4706386849284172, 'learning_rate/action_model': 9.273646814044759e-05, 'learning_rate/action_query_proj': 9.273646814044759e-05, 'learning_rate/base': 2.3184117035111898e-05, 'epoch': 0.59}) +[2026-07-27 10:01:42,536][starVLA.training.train_starvla][INFO] - Step 4888, Loss: {'train/loss': 0.09378864616155624, 'train/grad_norm_pre_clip': 4.018591403961182, 'timing/data': 0.00017579644918441772, 'timing/model': 0.47120783291757107, 'learning_rate/action_model': 9.272050847803593e-05, 'learning_rate/action_query_proj': 9.272050847803593e-05, 'learning_rate/base': 2.3180127119508982e-05, 'epoch': 0.59}) +[2026-07-27 10:01:48,059][starVLA.training.train_starvla][INFO] - Step 4889, Loss: {'train/loss': 0.03137791156768799, 'train/grad_norm_pre_clip': 1.8491442203521729, 'timing/data': 0.0001759883016347885, 'timing/model': 0.47192662209272385, 'learning_rate/action_model': 9.270453273981241e-05, 'learning_rate/action_query_proj': 9.270453273981241e-05, 'learning_rate/base': 2.3176133184953103e-05, 'epoch': 0.59}) +[2026-07-27 10:01:53,568][starVLA.training.train_starvla][INFO] - Step 4890, Loss: {'train/loss': 0.10153163969516754, 'train/grad_norm_pre_clip': 3.8317043781280518, 'timing/data': 0.00018006563186645508, 'timing/model': 0.4669166188687086, 'learning_rate/action_model': 9.2688540932084e-05, 'learning_rate/action_query_proj': 9.2688540932084e-05, 'learning_rate/base': 2.3172135233021e-05, 'epoch': 0.59}) +[2026-07-27 10:01:59,098][starVLA.training.train_starvla][INFO] - Step 4891, Loss: {'train/loss': 0.15960901975631714, 'train/grad_norm_pre_clip': 4.356873035430908, 'timing/data': 0.00017966702580451965, 'timing/model': 0.4763343445956707, 'learning_rate/action_model': 9.267253306116401e-05, 'learning_rate/action_query_proj': 9.267253306116401e-05, 'learning_rate/base': 2.3168133265291003e-05, 'epoch': 0.59}) +[2026-07-27 10:02:04,644][starVLA.training.train_starvla][INFO] - Step 4892, Loss: {'train/loss': 0.032279305160045624, 'train/grad_norm_pre_clip': 2.0846636295318604, 'timing/data': 0.00018035247921943665, 'timing/model': 0.4751597046852112, 'learning_rate/action_model': 9.265650913337209e-05, 'learning_rate/action_query_proj': 9.265650913337209e-05, 'learning_rate/base': 2.3164127283343022e-05, 'epoch': 0.59}) +[2026-07-27 10:02:10,158][starVLA.training.train_starvla][INFO] - Step 4893, Loss: {'train/loss': 0.11410028487443924, 'train/grad_norm_pre_clip': 4.717339038848877, 'timing/data': 0.00018013082444667816, 'timing/model': 0.4689620155841112, 'learning_rate/action_model': 9.264046915503425e-05, 'learning_rate/action_query_proj': 9.264046915503425e-05, 'learning_rate/base': 2.316011728875856e-05, 'epoch': 0.59}) +[2026-07-27 10:02:15,671][starVLA.training.train_starvla][INFO] - Step 4894, Loss: {'train/loss': 0.1831388920545578, 'train/grad_norm_pre_clip': 5.501943111419678, 'timing/data': 0.00021786615252494812, 'timing/model': 0.46588454209268093, 'learning_rate/action_model': 9.262441313248281e-05, 'learning_rate/action_query_proj': 9.262441313248281e-05, 'learning_rate/base': 2.3156103283120703e-05, 'epoch': 0.59}) +[2026-07-27 10:02:21,385][starVLA.training.train_starvla][INFO] - Step 4895, Loss: {'train/loss': 0.17282719910144806, 'train/grad_norm_pre_clip': 4.991598606109619, 'timing/data': 0.00018314458429813385, 'timing/model': 0.4591409247368574, 'learning_rate/action_model': 9.260834107205643e-05, 'learning_rate/action_query_proj': 9.260834107205643e-05, 'learning_rate/base': 2.3152085268014107e-05, 'epoch': 0.59}) +[2026-07-27 10:02:26,907][starVLA.training.train_starvla][INFO] - Step 4896, Loss: {'train/loss': 0.16989275813102722, 'train/grad_norm_pre_clip': 5.2975664138793945, 'timing/data': 0.0001722034066915512, 'timing/model': 0.47609599493443966, 'learning_rate/action_model': 9.259225298010011e-05, 'learning_rate/action_query_proj': 9.259225298010011e-05, 'learning_rate/base': 2.3148063245025027e-05, 'epoch': 0.59}) +[2026-07-27 10:02:32,430][starVLA.training.train_starvla][INFO] - Step 4897, Loss: {'train/loss': 0.04958360269665718, 'train/grad_norm_pre_clip': 2.4449105262756348, 'timing/data': 0.00018126890063285828, 'timing/model': 0.4709242004901171, 'learning_rate/action_model': 9.257614886296516e-05, 'learning_rate/action_query_proj': 9.257614886296516e-05, 'learning_rate/base': 2.314403721574129e-05, 'epoch': 0.59}) +[2026-07-27 10:02:38,015][starVLA.training.train_starvla][INFO] - Step 4898, Loss: {'train/loss': 0.08381260931491852, 'train/grad_norm_pre_clip': 3.293752431869507, 'timing/data': 0.00017810054123401642, 'timing/model': 0.47037247009575367, 'learning_rate/action_model': 9.256002872700924e-05, 'learning_rate/action_query_proj': 9.256002872700924e-05, 'learning_rate/base': 2.314000718175231e-05, 'epoch': 0.59}) +[2026-07-27 10:02:43,968][starVLA.training.train_starvla][INFO] - Step 4899, Loss: {'train/loss': 0.07764048874378204, 'train/grad_norm_pre_clip': 3.008981466293335, 'timing/data': 0.00017763115465641022, 'timing/model': 0.47107415087521076, 'learning_rate/action_model': 9.254389257859633e-05, 'learning_rate/action_query_proj': 9.254389257859633e-05, 'learning_rate/base': 2.3135973144649083e-05, 'epoch': 0.59}) +[2026-07-27 10:02:49,503][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 4900 +[2026-07-27 10:02:49,503][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 4900 +[2026-07-27 10:02:49,504][starVLA.training.train_starvla][INFO] - Step 4900, Loss: {'train/loss': 0.2663310468196869, 'train/grad_norm_pre_clip': 5.622500896453857, 'timing/data': 0.000177089124917984, 'timing/model': 0.4692696053534746, 'learning_rate/action_model': 9.252774042409673e-05, 'learning_rate/action_query_proj': 9.252774042409673e-05, 'learning_rate/base': 2.313193510602418e-05, 'epoch': 0.59}) +[2026-07-27 10:02:55,038][starVLA.training.train_starvla][INFO] - Step 4901, Loss: {'train/loss': 0.15705856680870056, 'train/grad_norm_pre_clip': 4.8022780418396, 'timing/data': 0.0001791883260011673, 'timing/model': 0.47023910097777843, 'learning_rate/action_model': 9.251157226988703e-05, 'learning_rate/action_query_proj': 9.251157226988703e-05, 'learning_rate/base': 2.3127893067471758e-05, 'epoch': 0.59}) +[2026-07-27 10:03:00,578][starVLA.training.train_starvla][INFO] - Step 4902, Loss: {'train/loss': 0.1472999006509781, 'train/grad_norm_pre_clip': 4.773837566375732, 'timing/data': 0.00018579140305519104, 'timing/model': 0.4704195987433195, 'learning_rate/action_model': 9.249538812235019e-05, 'learning_rate/action_query_proj': 9.249538812235019e-05, 'learning_rate/base': 2.3123847030587548e-05, 'epoch': 0.59}) +[2026-07-27 10:03:06,131][starVLA.training.train_starvla][INFO] - Step 4903, Loss: {'train/loss': 0.141558438539505, 'train/grad_norm_pre_clip': 5.033206939697266, 'timing/data': 0.0001882445067167282, 'timing/model': 0.46998471952974796, 'learning_rate/action_model': 9.247918798787544e-05, 'learning_rate/action_query_proj': 9.247918798787544e-05, 'learning_rate/base': 2.311979699696886e-05, 'epoch': 0.59}) +[2026-07-27 10:03:11,687][starVLA.training.train_starvla][INFO] - Step 4904, Loss: {'train/loss': 0.10906725376844406, 'train/grad_norm_pre_clip': 4.5506134033203125, 'timing/data': 0.00017945468425750732, 'timing/model': 0.47480418533086777, 'learning_rate/action_model': 9.246297187285834e-05, 'learning_rate/action_query_proj': 9.246297187285834e-05, 'learning_rate/base': 2.3115742968214584e-05, 'epoch': 0.59}) +[2026-07-27 10:03:17,271][starVLA.training.train_starvla][INFO] - Step 4905, Loss: {'train/loss': 0.18567460775375366, 'train/grad_norm_pre_clip': 6.13300895690918, 'timing/data': 0.00017848238348960876, 'timing/model': 0.4713528975844383, 'learning_rate/action_model': 9.244673978370076e-05, 'learning_rate/action_query_proj': 9.244673978370076e-05, 'learning_rate/base': 2.311168494592519e-05, 'epoch': 0.6}) +[2026-07-27 10:03:22,851][starVLA.training.train_starvla][INFO] - Step 4906, Loss: {'train/loss': 0.1073693111538887, 'train/grad_norm_pre_clip': 4.120395660400391, 'timing/data': 0.00017827562987804413, 'timing/model': 0.4588705897331238, 'learning_rate/action_model': 9.243049172681085e-05, 'learning_rate/action_query_proj': 9.243049172681085e-05, 'learning_rate/base': 2.3107622931702712e-05, 'epoch': 0.6}) +[2026-07-27 10:03:28,409][starVLA.training.train_starvla][INFO] - Step 4907, Loss: {'train/loss': 0.1589847058057785, 'train/grad_norm_pre_clip': 5.073145389556885, 'timing/data': 0.0001843925565481186, 'timing/model': 0.4583323337137699, 'learning_rate/action_model': 9.241422770860311e-05, 'learning_rate/action_query_proj': 9.241422770860311e-05, 'learning_rate/base': 2.3103556927150778e-05, 'epoch': 0.6}) +[2026-07-27 10:03:33,944][starVLA.training.train_starvla][INFO] - Step 4908, Loss: {'train/loss': 0.09291373938322067, 'train/grad_norm_pre_clip': 3.0372121334075928, 'timing/data': 0.0001774802803993225, 'timing/model': 0.47957563772797585, 'learning_rate/action_model': 9.239794773549832e-05, 'learning_rate/action_query_proj': 9.239794773549832e-05, 'learning_rate/base': 2.309948693387458e-05, 'epoch': 0.6}) +[2026-07-27 10:03:39,457][starVLA.training.train_starvla][INFO] - Step 4909, Loss: {'train/loss': 0.08900313824415207, 'train/grad_norm_pre_clip': 2.684056282043457, 'timing/data': 0.00017776526510715485, 'timing/model': 0.4682498387992382, 'learning_rate/action_model': 9.238165181392354e-05, 'learning_rate/action_query_proj': 9.238165181392354e-05, 'learning_rate/base': 2.3095412953480884e-05, 'epoch': 0.6}) +[2026-07-27 10:03:44,972][starVLA.training.train_starvla][INFO] - Step 4910, Loss: {'train/loss': 0.0428534671664238, 'train/grad_norm_pre_clip': 2.305812358856201, 'timing/data': 0.0001809932291507721, 'timing/model': 0.474880950525403, 'learning_rate/action_model': 9.236533995031212e-05, 'learning_rate/action_query_proj': 9.236533995031212e-05, 'learning_rate/base': 2.309133498757803e-05, 'epoch': 0.6}) +[2026-07-27 10:03:50,470][starVLA.training.train_starvla][INFO] - Step 4911, Loss: {'train/loss': 0.11742325127124786, 'train/grad_norm_pre_clip': 4.079736232757568, 'timing/data': 0.00017972849309444427, 'timing/model': 0.4574400894343853, 'learning_rate/action_model': 9.234901215110378e-05, 'learning_rate/action_query_proj': 9.234901215110378e-05, 'learning_rate/base': 2.3087253037775945e-05, 'epoch': 0.6}) +[2026-07-27 10:03:55,974][starVLA.training.train_starvla][INFO] - Step 4912, Loss: {'train/loss': 0.11168927699327469, 'train/grad_norm_pre_clip': 2.706122636795044, 'timing/data': 0.00017732568085193634, 'timing/model': 0.46696047857403755, 'learning_rate/action_model': 9.233266842274442e-05, 'learning_rate/action_query_proj': 9.233266842274442e-05, 'learning_rate/base': 2.3083167105686106e-05, 'epoch': 0.6}) +[2026-07-27 10:04:01,498][starVLA.training.train_starvla][INFO] - Step 4913, Loss: {'train/loss': 0.07837136834859848, 'train/grad_norm_pre_clip': 3.2158048152923584, 'timing/data': 0.0001795608550310135, 'timing/model': 0.46955362521111965, 'learning_rate/action_model': 9.231630877168634e-05, 'learning_rate/action_query_proj': 9.231630877168634e-05, 'learning_rate/base': 2.3079077192921584e-05, 'epoch': 0.6}) +[2026-07-27 10:04:07,003][starVLA.training.train_starvla][INFO] - Step 4914, Loss: {'train/loss': 0.12066872417926788, 'train/grad_norm_pre_clip': 4.340816020965576, 'timing/data': 0.00017896294593811035, 'timing/model': 0.4683518912643194, 'learning_rate/action_model': 9.229993320438804e-05, 'learning_rate/action_query_proj': 9.229993320438804e-05, 'learning_rate/base': 2.307498330109701e-05, 'epoch': 0.6}) +[2026-07-27 10:04:12,514][starVLA.training.train_starvla][INFO] - Step 4915, Loss: {'train/loss': 0.1714034527540207, 'train/grad_norm_pre_clip': 5.311382293701172, 'timing/data': 0.00018121488392353058, 'timing/model': 0.4690662585198879, 'learning_rate/action_model': 9.228354172731432e-05, 'learning_rate/action_query_proj': 9.228354172731432e-05, 'learning_rate/base': 2.307088543182858e-05, 'epoch': 0.6}) +[2026-07-27 10:04:18,023][starVLA.training.train_starvla][INFO] - Step 4916, Loss: {'train/loss': 0.10224637389183044, 'train/grad_norm_pre_clip': 3.3006575107574463, 'timing/data': 0.00018787942826747894, 'timing/model': 0.4694727323949337, 'learning_rate/action_model': 9.226713434693632e-05, 'learning_rate/action_query_proj': 9.226713434693632e-05, 'learning_rate/base': 2.306678358673408e-05, 'epoch': 0.6}) +[2026-07-27 10:04:23,535][starVLA.training.train_starvla][INFO] - Step 4917, Loss: {'train/loss': 0.1167600229382515, 'train/grad_norm_pre_clip': 3.670853614807129, 'timing/data': 0.00018482469022274017, 'timing/model': 0.4674049112945795, 'learning_rate/action_model': 9.225071106973137e-05, 'learning_rate/action_query_proj': 9.225071106973137e-05, 'learning_rate/base': 2.3062677767432842e-05, 'epoch': 0.6}) +[2026-07-27 10:04:29,056][starVLA.training.train_starvla][INFO] - Step 4918, Loss: {'train/loss': 0.09607589989900589, 'train/grad_norm_pre_clip': 4.250678062438965, 'timing/data': 0.0001798924058675766, 'timing/model': 0.4742466788738966, 'learning_rate/action_model': 9.223427190218314e-05, 'learning_rate/action_query_proj': 9.223427190218314e-05, 'learning_rate/base': 2.3058567975545785e-05, 'epoch': 0.6}) +[2026-07-27 10:04:34,577][starVLA.training.train_starvla][INFO] - Step 4919, Loss: {'train/loss': 0.13666026294231415, 'train/grad_norm_pre_clip': 3.473052978515625, 'timing/data': 0.00018011592328548431, 'timing/model': 0.46905349008738995, 'learning_rate/action_model': 9.221781685078157e-05, 'learning_rate/action_query_proj': 9.221781685078157e-05, 'learning_rate/base': 2.3054454212695392e-05, 'epoch': 0.6}) +[2026-07-27 10:04:40,095][starVLA.training.train_starvla][INFO] - Step 4920, Loss: {'train/loss': 0.04386762157082558, 'train/grad_norm_pre_clip': 1.9778109788894653, 'timing/data': 0.00017794780433177948, 'timing/model': 0.4757923185825348, 'learning_rate/action_model': 9.220134592202282e-05, 'learning_rate/action_query_proj': 9.220134592202282e-05, 'learning_rate/base': 2.3050336480505704e-05, 'epoch': 0.6}) +[2026-07-27 10:04:45,601][starVLA.training.train_starvla][INFO] - Step 4921, Loss: {'train/loss': 0.05164092779159546, 'train/grad_norm_pre_clip': 1.8391999006271362, 'timing/data': 0.0001807529479265213, 'timing/model': 0.47056765481829643, 'learning_rate/action_model': 9.218485912240935e-05, 'learning_rate/action_query_proj': 9.218485912240935e-05, 'learning_rate/base': 2.3046214780602336e-05, 'epoch': 0.6}) +[2026-07-27 10:04:51,113][starVLA.training.train_starvla][INFO] - Step 4922, Loss: {'train/loss': 0.02881065011024475, 'train/grad_norm_pre_clip': 1.539121150970459, 'timing/data': 0.00018127262592315674, 'timing/model': 0.4683355074375868, 'learning_rate/action_model': 9.216835645844992e-05, 'learning_rate/action_query_proj': 9.216835645844992e-05, 'learning_rate/base': 2.304208911461248e-05, 'epoch': 0.6}) +[2026-07-27 10:04:56,632][starVLA.training.train_starvla][INFO] - Step 4923, Loss: {'train/loss': 0.1511143296957016, 'train/grad_norm_pre_clip': 4.374466419219971, 'timing/data': 0.00018038414418697357, 'timing/model': 0.4701976142823696, 'learning_rate/action_model': 9.215183793665952e-05, 'learning_rate/action_query_proj': 9.215183793665952e-05, 'learning_rate/base': 2.303795948416488e-05, 'epoch': 0.6}) +[2026-07-27 10:05:02,143][starVLA.training.train_starvla][INFO] - Step 4924, Loss: {'train/loss': 0.12838691473007202, 'train/grad_norm_pre_clip': 3.3861939907073975, 'timing/data': 0.00017820671200752258, 'timing/model': 0.46971018239855766, 'learning_rate/action_model': 9.213530356355935e-05, 'learning_rate/action_query_proj': 9.213530356355935e-05, 'learning_rate/base': 2.3033825890889838e-05, 'epoch': 0.6}) +[2026-07-27 10:05:07,652][starVLA.training.train_starvla][INFO] - Step 4925, Loss: {'train/loss': 0.03726198896765709, 'train/grad_norm_pre_clip': 1.7392226457595825, 'timing/data': 0.00018011592328548431, 'timing/model': 0.46974410861730576, 'learning_rate/action_model': 9.211875334567698e-05, 'learning_rate/action_query_proj': 9.211875334567698e-05, 'learning_rate/base': 2.3029688336419245e-05, 'epoch': 0.6}) +[2026-07-27 10:05:13,166][starVLA.training.train_starvla][INFO] - Step 4926, Loss: {'train/loss': 0.08396203815937042, 'train/grad_norm_pre_clip': 3.7722437381744385, 'timing/data': 0.00017988868057727814, 'timing/model': 0.4757151138037443, 'learning_rate/action_model': 9.210218728954614e-05, 'learning_rate/action_query_proj': 9.210218728954614e-05, 'learning_rate/base': 2.3025546822386536e-05, 'epoch': 0.6}) +[2026-07-27 10:05:18,667][starVLA.training.train_starvla][INFO] - Step 4927, Loss: {'train/loss': 0.05247209966182709, 'train/grad_norm_pre_clip': 2.069931745529175, 'timing/data': 0.00017708726227283478, 'timing/model': 0.46816660091280937, 'learning_rate/action_model': 9.208560540170686e-05, 'learning_rate/action_query_proj': 9.208560540170686e-05, 'learning_rate/base': 2.3021401350426714e-05, 'epoch': 0.6}) +[2026-07-27 10:05:24,178][starVLA.training.train_starvla][INFO] - Step 4928, Loss: {'train/loss': 0.047559704631567, 'train/grad_norm_pre_clip': 2.3017055988311768, 'timing/data': 0.00017528049647808075, 'timing/model': 0.47519174590706825, 'learning_rate/action_model': 9.20690076887054e-05, 'learning_rate/action_query_proj': 9.20690076887054e-05, 'learning_rate/base': 2.301725192217635e-05, 'epoch': 0.6}) +[2026-07-27 10:05:29,686][starVLA.training.train_starvla][INFO] - Step 4929, Loss: {'train/loss': 0.08735983818769455, 'train/grad_norm_pre_clip': 3.5897765159606934, 'timing/data': 0.00017830915749073029, 'timing/model': 0.4698176793754101, 'learning_rate/action_model': 9.205239415709426e-05, 'learning_rate/action_query_proj': 9.205239415709426e-05, 'learning_rate/base': 2.3013098539273564e-05, 'epoch': 0.6}) +[2026-07-27 10:05:35,190][starVLA.training.train_starvla][INFO] - Step 4930, Loss: {'train/loss': 0.10967212915420532, 'train/grad_norm_pre_clip': 2.9397194385528564, 'timing/data': 0.0001800432801246643, 'timing/model': 0.4697474241256714, 'learning_rate/action_model': 9.203576481343223e-05, 'learning_rate/action_query_proj': 9.203576481343223e-05, 'learning_rate/base': 2.3008941203358057e-05, 'epoch': 0.6}) +[2026-07-27 10:05:40,710][starVLA.training.train_starvla][INFO] - Step 4931, Loss: {'train/loss': 0.05083952471613884, 'train/grad_norm_pre_clip': 2.8121440410614014, 'timing/data': 0.00018013082444667816, 'timing/model': 0.4702776260674, 'learning_rate/action_model': 9.201911966428429e-05, 'learning_rate/action_query_proj': 9.201911966428429e-05, 'learning_rate/base': 2.3004779916071072e-05, 'epoch': 0.6}) +[2026-07-27 10:05:46,224][starVLA.training.train_starvla][INFO] - Step 4932, Loss: {'train/loss': 0.021110370755195618, 'train/grad_norm_pre_clip': 1.1010175943374634, 'timing/data': 0.00017641298472881317, 'timing/model': 0.4679793454706669, 'learning_rate/action_model': 9.200245871622167e-05, 'learning_rate/action_query_proj': 9.200245871622167e-05, 'learning_rate/base': 2.3000614679055417e-05, 'epoch': 0.6}) +[2026-07-27 10:05:51,728][starVLA.training.train_starvla][INFO] - Step 4933, Loss: {'train/loss': 0.10238749533891678, 'train/grad_norm_pre_clip': 2.9448866844177246, 'timing/data': 0.00018034689128398895, 'timing/model': 0.46884340792894363, 'learning_rate/action_model': 9.19857819758219e-05, 'learning_rate/action_query_proj': 9.19857819758219e-05, 'learning_rate/base': 2.2996445493955475e-05, 'epoch': 0.6}) +[2026-07-27 10:05:57,293][starVLA.training.train_starvla][INFO] - Step 4934, Loss: {'train/loss': 0.08596007525920868, 'train/grad_norm_pre_clip': 3.1662404537200928, 'timing/data': 0.00018085725605487823, 'timing/model': 0.4703593049198389, 'learning_rate/action_model': 9.196908944966863e-05, 'learning_rate/action_query_proj': 9.196908944966863e-05, 'learning_rate/base': 2.2992272362417158e-05, 'epoch': 0.6}) +[2026-07-27 10:06:02,852][starVLA.training.train_starvla][INFO] - Step 4935, Loss: {'train/loss': 0.08032263815402985, 'train/grad_norm_pre_clip': 3.523162841796875, 'timing/data': 0.00018035247921943665, 'timing/model': 0.4762910157442093, 'learning_rate/action_model': 9.195238114435186e-05, 'learning_rate/action_query_proj': 9.195238114435186e-05, 'learning_rate/base': 2.2988095286087964e-05, 'epoch': 0.6}) +[2026-07-27 10:06:08,414][starVLA.training.train_starvla][INFO] - Step 4936, Loss: {'train/loss': 0.17385233938694, 'train/grad_norm_pre_clip': 5.2810564041137695, 'timing/data': 0.0001779906451702118, 'timing/model': 0.46878342516720295, 'learning_rate/action_model': 9.193565706646772e-05, 'learning_rate/action_query_proj': 9.193565706646772e-05, 'learning_rate/base': 2.298391426661693e-05, 'epoch': 0.6}) +[2026-07-27 10:06:13,966][starVLA.training.train_starvla][INFO] - Step 4937, Loss: {'train/loss': 0.09564511477947235, 'train/grad_norm_pre_clip': 4.017993927001953, 'timing/data': 0.0001766681671142578, 'timing/model': 0.47222054935991764, 'learning_rate/action_model': 9.191891722261861e-05, 'learning_rate/action_query_proj': 9.191891722261861e-05, 'learning_rate/base': 2.2979729305654653e-05, 'epoch': 0.6}) +[2026-07-27 10:06:19,515][starVLA.training.train_starvla][INFO] - Step 4938, Loss: {'train/loss': 0.04491683095693588, 'train/grad_norm_pre_clip': 2.3236241340637207, 'timing/data': 0.00017540156841278076, 'timing/model': 0.47643337957561016, 'learning_rate/action_model': 9.190216161941321e-05, 'learning_rate/action_query_proj': 9.190216161941321e-05, 'learning_rate/base': 2.2975540404853302e-05, 'epoch': 0.6}) +[2026-07-27 10:06:25,061][starVLA.training.train_starvla][INFO] - Step 4939, Loss: {'train/loss': 0.1266639530658722, 'train/grad_norm_pre_clip': 5.556666851043701, 'timing/data': 0.00018041767179965973, 'timing/model': 0.47058683075010777, 'learning_rate/action_model': 9.188539026346632e-05, 'learning_rate/action_query_proj': 9.188539026346632e-05, 'learning_rate/base': 2.297134756586658e-05, 'epoch': 0.6}) +[2026-07-27 10:06:30,625][starVLA.training.train_starvla][INFO] - Step 4940, Loss: {'train/loss': 0.04559874162077904, 'train/grad_norm_pre_clip': 3.5550100803375244, 'timing/data': 0.00017543509602546692, 'timing/model': 0.4757327903062105, 'learning_rate/action_model': 9.186860316139901e-05, 'learning_rate/action_query_proj': 9.186860316139901e-05, 'learning_rate/base': 2.2967150790349752e-05, 'epoch': 0.6}) +[2026-07-27 10:06:36,171][starVLA.training.train_starvla][INFO] - Step 4941, Loss: {'train/loss': 0.09136679768562317, 'train/grad_norm_pre_clip': 3.772845983505249, 'timing/data': 0.00017722882330417633, 'timing/model': 0.4725090768188238, 'learning_rate/action_model': 9.185180031983857e-05, 'learning_rate/action_query_proj': 9.185180031983857e-05, 'learning_rate/base': 2.2962950079959643e-05, 'epoch': 0.6}) +[2026-07-27 10:06:41,734][starVLA.training.train_starvla][INFO] - Step 4942, Loss: {'train/loss': 0.06493626534938812, 'train/grad_norm_pre_clip': 3.544650077819824, 'timing/data': 0.00017934665083885193, 'timing/model': 0.47057631239295006, 'learning_rate/action_model': 9.18349817454185e-05, 'learning_rate/action_query_proj': 9.18349817454185e-05, 'learning_rate/base': 2.2958745436354624e-05, 'epoch': 0.6}) +[2026-07-27 10:06:47,300][starVLA.training.train_starvla][INFO] - Step 4943, Loss: {'train/loss': 0.06833666563034058, 'train/grad_norm_pre_clip': 4.126514911651611, 'timing/data': 0.00018010102212429047, 'timing/model': 0.47613682597875595, 'learning_rate/action_model': 9.181814744477851e-05, 'learning_rate/action_query_proj': 9.181814744477851e-05, 'learning_rate/base': 2.2954536861194627e-05, 'epoch': 0.6}) +[2026-07-27 10:06:52,853][starVLA.training.train_starvla][INFO] - Step 4944, Loss: {'train/loss': 0.11801452934741974, 'train/grad_norm_pre_clip': 4.544785976409912, 'timing/data': 0.0001763366162776947, 'timing/model': 0.4712204784154892, 'learning_rate/action_model': 9.180129742456448e-05, 'learning_rate/action_query_proj': 9.180129742456448e-05, 'learning_rate/base': 2.295032435614112e-05, 'epoch': 0.6}) +[2026-07-27 10:06:58,397][starVLA.training.train_starvla][INFO] - Step 4945, Loss: {'train/loss': 0.13575829565525055, 'train/grad_norm_pre_clip': 3.5517940521240234, 'timing/data': 0.00017675571143627167, 'timing/model': 0.4707446601241827, 'learning_rate/action_model': 9.178443169142858e-05, 'learning_rate/action_query_proj': 9.178443169142858e-05, 'learning_rate/base': 2.2946107922857144e-05, 'epoch': 0.6}) +[2026-07-27 10:07:03,957][starVLA.training.train_starvla][INFO] - Step 4946, Loss: {'train/loss': 0.05530882999300957, 'train/grad_norm_pre_clip': 2.8769147396087646, 'timing/data': 0.0001769494265317917, 'timing/model': 0.4750665668398142, 'learning_rate/action_model': 9.176755025202911e-05, 'learning_rate/action_query_proj': 9.176755025202911e-05, 'learning_rate/base': 2.2941887563007278e-05, 'epoch': 0.6}) +[2026-07-27 10:07:09,513][starVLA.training.train_starvla][INFO] - Step 4947, Loss: {'train/loss': 0.1247950941324234, 'train/grad_norm_pre_clip': 4.385258197784424, 'timing/data': 0.000183766707777977, 'timing/model': 0.4615529663860798, 'learning_rate/action_model': 9.175065311303058e-05, 'learning_rate/action_query_proj': 9.175065311303058e-05, 'learning_rate/base': 2.2937663278257646e-05, 'epoch': 0.6}) +[2026-07-27 10:07:15,042][starVLA.training.train_starvla][INFO] - Step 4948, Loss: {'train/loss': 0.1407616287469864, 'train/grad_norm_pre_clip': 4.215917110443115, 'timing/data': 0.0001819618046283722, 'timing/model': 0.457168385386467, 'learning_rate/action_model': 9.173374028110373e-05, 'learning_rate/action_query_proj': 9.173374028110373e-05, 'learning_rate/base': 2.2933435070275934e-05, 'epoch': 0.6}) +[2026-07-27 10:07:20,564][starVLA.training.train_starvla][INFO] - Step 4949, Loss: {'train/loss': 0.02763775922358036, 'train/grad_norm_pre_clip': 1.3397589921951294, 'timing/data': 0.00017930753529071808, 'timing/model': 0.4580506179481745, 'learning_rate/action_model': 9.17168117629255e-05, 'learning_rate/action_query_proj': 9.17168117629255e-05, 'learning_rate/base': 2.2929202940731376e-05, 'epoch': 0.6}) +[2026-07-27 10:07:26,109][starVLA.training.train_starvla][INFO] - Step 4950, Loss: {'train/loss': 0.08801480382680893, 'train/grad_norm_pre_clip': 2.9104323387145996, 'timing/data': 0.00017615407705307007, 'timing/model': 0.4583884086459875, 'learning_rate/action_model': 9.169986756517896e-05, 'learning_rate/action_query_proj': 9.169986756517896e-05, 'learning_rate/base': 2.292496689129474e-05, 'epoch': 0.6}) +[2026-07-27 10:07:31,638][starVLA.training.train_starvla][INFO] - Step 4951, Loss: {'train/loss': 0.040400467813014984, 'train/grad_norm_pre_clip': 1.9848754405975342, 'timing/data': 0.0001763850450515747, 'timing/model': 0.45776958763599396, 'learning_rate/action_model': 9.168290769455344e-05, 'learning_rate/action_query_proj': 9.168290769455344e-05, 'learning_rate/base': 2.292072692363836e-05, 'epoch': 0.6}) +[2026-07-27 10:07:37,184][starVLA.training.train_starvla][INFO] - Step 4952, Loss: {'train/loss': 0.10977009683847427, 'train/grad_norm_pre_clip': 3.0275423526763916, 'timing/data': 0.00017579086124897003, 'timing/model': 0.4577381517738104, 'learning_rate/action_model': 9.166593215774442e-05, 'learning_rate/action_query_proj': 9.166593215774442e-05, 'learning_rate/base': 2.2916483039436106e-05, 'epoch': 0.6}) +[2026-07-27 10:07:42,731][starVLA.training.train_starvla][INFO] - Step 4953, Loss: {'train/loss': 0.08616053313016891, 'train/grad_norm_pre_clip': 2.5417258739471436, 'timing/data': 0.0001826006919145584, 'timing/model': 0.45742269419133663, 'learning_rate/action_model': 9.164894096145357e-05, 'learning_rate/action_query_proj': 9.164894096145357e-05, 'learning_rate/base': 2.2912235240363393e-05, 'epoch': 0.6}) +[2026-07-27 10:07:48,301][starVLA.training.train_starvla][INFO] - Step 4954, Loss: {'train/loss': 0.1134302094578743, 'train/grad_norm_pre_clip': 4.726673603057861, 'timing/data': 0.00017530471086502075, 'timing/model': 0.4583231955766678, 'learning_rate/action_model': 9.163193411238875e-05, 'learning_rate/action_query_proj': 9.163193411238875e-05, 'learning_rate/base': 2.2907983528097187e-05, 'epoch': 0.6}) +[2026-07-27 10:07:53,853][starVLA.training.train_starvla][INFO] - Step 4955, Loss: {'train/loss': 0.09185627847909927, 'train/grad_norm_pre_clip': 3.744488000869751, 'timing/data': 0.00017806515097618103, 'timing/model': 0.4577964339405298, 'learning_rate/action_model': 9.161491161726398e-05, 'learning_rate/action_query_proj': 9.161491161726398e-05, 'learning_rate/base': 2.2903727904315996e-05, 'epoch': 0.6}) +[2026-07-27 10:07:59,401][starVLA.training.train_starvla][INFO] - Step 4956, Loss: {'train/loss': 0.13117259740829468, 'train/grad_norm_pre_clip': 5.49643087387085, 'timing/data': 0.00017635710537433624, 'timing/model': 0.4575053844600916, 'learning_rate/action_model': 9.15978734827995e-05, 'learning_rate/action_query_proj': 9.15978734827995e-05, 'learning_rate/base': 2.2899468370699875e-05, 'epoch': 0.6}) +[2026-07-27 10:08:04,968][starVLA.training.train_starvla][INFO] - Step 4957, Loss: {'train/loss': 0.08871806412935257, 'train/grad_norm_pre_clip': 3.2388813495635986, 'timing/data': 0.00018545612692832947, 'timing/model': 0.45837025344371796, 'learning_rate/action_model': 9.158081971572165e-05, 'learning_rate/action_query_proj': 9.158081971572165e-05, 'learning_rate/base': 2.2895204928930413e-05, 'epoch': 0.6}) +[2026-07-27 10:08:10,754][starVLA.training.train_starvla][INFO] - Step 4958, Loss: {'train/loss': 0.06356749683618546, 'train/grad_norm_pre_clip': 2.5045721530914307, 'timing/data': 0.00017852522432804108, 'timing/model': 0.45819449983537197, 'learning_rate/action_model': 9.156375032276305e-05, 'learning_rate/action_query_proj': 9.156375032276305e-05, 'learning_rate/base': 2.289093758069076e-05, 'epoch': 0.6}) +[2026-07-27 10:08:16,303][starVLA.training.train_starvla][INFO] - Step 4959, Loss: {'train/loss': 0.09119436889886856, 'train/grad_norm_pre_clip': 2.898634910583496, 'timing/data': 0.00017922557890415192, 'timing/model': 0.45812133327126503, 'learning_rate/action_model': 9.154666531066236e-05, 'learning_rate/action_query_proj': 9.154666531066236e-05, 'learning_rate/base': 2.288666632766559e-05, 'epoch': 0.6}) +[2026-07-27 10:08:21,845][starVLA.training.train_starvla][INFO] - Step 4960, Loss: {'train/loss': 0.10725990682840347, 'train/grad_norm_pre_clip': 3.673816442489624, 'timing/data': 0.0001874491572380066, 'timing/model': 0.4589162413030863, 'learning_rate/action_model': 9.152956468616451e-05, 'learning_rate/action_query_proj': 9.152956468616451e-05, 'learning_rate/base': 2.2882391171541128e-05, 'epoch': 0.6}) +[2026-07-27 10:08:27,410][starVLA.training.train_starvla][INFO] - Step 4961, Loss: {'train/loss': 0.02946971170604229, 'train/grad_norm_pre_clip': 1.9641977548599243, 'timing/data': 0.00017692521214485168, 'timing/model': 0.4572987947613001, 'learning_rate/action_model': 9.151244845602056e-05, 'learning_rate/action_query_proj': 9.151244845602056e-05, 'learning_rate/base': 2.287811211400514e-05, 'epoch': 0.6}) +[2026-07-27 10:08:32,976][starVLA.training.train_starvla][INFO] - Step 4962, Loss: {'train/loss': 0.06948889046907425, 'train/grad_norm_pre_clip': 2.6884870529174805, 'timing/data': 0.0001733154058456421, 'timing/model': 0.45671943947672844, 'learning_rate/action_model': 9.149531662698772e-05, 'learning_rate/action_query_proj': 9.149531662698772e-05, 'learning_rate/base': 2.287382915674693e-05, 'epoch': 0.6}) +[2026-07-27 10:08:38,529][starVLA.training.train_starvla][INFO] - Step 4963, Loss: {'train/loss': 0.055894091725349426, 'train/grad_norm_pre_clip': 2.3988211154937744, 'timing/data': 0.00018092617392539978, 'timing/model': 0.45854400657117367, 'learning_rate/action_model': 9.147816920582935e-05, 'learning_rate/action_query_proj': 9.147816920582935e-05, 'learning_rate/base': 2.286954230145734e-05, 'epoch': 0.6}) +[2026-07-27 10:08:44,106][starVLA.training.train_starvla][INFO] - Step 4964, Loss: {'train/loss': 0.038876038044691086, 'train/grad_norm_pre_clip': 2.733518123626709, 'timing/data': 0.0001775342971086502, 'timing/model': 0.45725965313613415, 'learning_rate/action_model': 9.1461006199315e-05, 'learning_rate/action_query_proj': 9.1461006199315e-05, 'learning_rate/base': 2.286525154982875e-05, 'epoch': 0.6}) +[2026-07-27 10:08:49,645][starVLA.training.train_starvla][INFO] - Step 4965, Loss: {'train/loss': 0.04191743582487106, 'train/grad_norm_pre_clip': 2.4033069610595703, 'timing/data': 0.00017827004194259644, 'timing/model': 0.4573669880628586, 'learning_rate/action_model': 9.144382761422033e-05, 'learning_rate/action_query_proj': 9.144382761422033e-05, 'learning_rate/base': 2.2860956903555083e-05, 'epoch': 0.6}) +[2026-07-27 10:08:55,183][starVLA.training.train_starvla][INFO] - Step 4966, Loss: {'train/loss': 0.045075424015522, 'train/grad_norm_pre_clip': 2.0158956050872803, 'timing/data': 0.00017946027219295502, 'timing/model': 0.45847384072840214, 'learning_rate/action_model': 9.14266334573272e-05, 'learning_rate/action_query_proj': 9.14266334573272e-05, 'learning_rate/base': 2.28566583643318e-05, 'epoch': 0.6}) +[2026-07-27 10:09:00,728][starVLA.training.train_starvla][INFO] - Step 4967, Loss: {'train/loss': 0.03400849550962448, 'train/grad_norm_pre_clip': 1.6927367448806763, 'timing/data': 0.0001781415194272995, 'timing/model': 0.45842443220317364, 'learning_rate/action_model': 9.140942373542359e-05, 'learning_rate/action_query_proj': 9.140942373542359e-05, 'learning_rate/base': 2.2852355933855896e-05, 'epoch': 0.6}) +[2026-07-27 10:09:06,273][starVLA.training.train_starvla][INFO] - Step 4968, Loss: {'train/loss': 0.05622968450188637, 'train/grad_norm_pre_clip': 2.0380783081054688, 'timing/data': 0.0001795683056116104, 'timing/model': 0.45793681405484676, 'learning_rate/action_model': 9.139219845530359e-05, 'learning_rate/action_query_proj': 9.139219845530359e-05, 'learning_rate/base': 2.2848049613825898e-05, 'epoch': 0.6}) +[2026-07-27 10:09:11,894][starVLA.training.train_starvla][INFO] - Step 4969, Loss: {'train/loss': 0.057491742074489594, 'train/grad_norm_pre_clip': 3.4254965782165527, 'timing/data': 0.00017977505922317505, 'timing/model': 0.45970893651247025, 'learning_rate/action_model': 9.13749576237675e-05, 'learning_rate/action_query_proj': 9.13749576237675e-05, 'learning_rate/base': 2.2843739405941874e-05, 'epoch': 0.6}) +[2026-07-27 10:09:17,485][starVLA.training.train_starvla][INFO] - Step 4970, Loss: {'train/loss': 0.09126967936754227, 'train/grad_norm_pre_clip': 2.1683080196380615, 'timing/data': 0.00017416663467884064, 'timing/model': 0.4695178736001253, 'learning_rate/action_model': 9.135770124762172e-05, 'learning_rate/action_query_proj': 9.135770124762172e-05, 'learning_rate/base': 2.283942531190543e-05, 'epoch': 0.6}) +[2026-07-27 10:09:23,297][starVLA.training.train_starvla][INFO] - Step 4971, Loss: {'train/loss': 0.10395865887403488, 'train/grad_norm_pre_clip': 3.700082778930664, 'timing/data': 0.0001802109181880951, 'timing/model': 0.4570758603513241, 'learning_rate/action_model': 9.134042933367879e-05, 'learning_rate/action_query_proj': 9.134042933367879e-05, 'learning_rate/base': 2.2835107333419697e-05, 'epoch': 0.6}) +[2026-07-27 10:09:28,900][starVLA.training.train_starvla][INFO] - Step 4972, Loss: {'train/loss': 0.11211882531642914, 'train/grad_norm_pre_clip': 4.084780216217041, 'timing/data': 0.0001819133758544922, 'timing/model': 0.4689635783433914, 'learning_rate/action_model': 9.13231418887574e-05, 'learning_rate/action_query_proj': 9.13231418887574e-05, 'learning_rate/base': 2.283078547218935e-05, 'epoch': 0.6}) +[2026-07-27 10:09:34,483][starVLA.training.train_starvla][INFO] - Step 4973, Loss: {'train/loss': 0.06870344281196594, 'train/grad_norm_pre_clip': 3.9166722297668457, 'timing/data': 0.00017820298671722412, 'timing/model': 0.46859107725322247, 'learning_rate/action_model': 9.130583891968233e-05, 'learning_rate/action_query_proj': 9.130583891968233e-05, 'learning_rate/base': 2.2826459729920583e-05, 'epoch': 0.6}) +[2026-07-27 10:09:40,279][starVLA.training.train_starvla][INFO] - Step 4974, Loss: {'train/loss': 0.12263080477714539, 'train/grad_norm_pre_clip': 3.6230878829956055, 'timing/data': 0.00018995441496372223, 'timing/model': 0.4697401151061058, 'learning_rate/action_model': 9.128852043328456e-05, 'learning_rate/action_query_proj': 9.128852043328456e-05, 'learning_rate/base': 2.282213010832114e-05, 'epoch': 0.6}) +[2026-07-27 10:09:45,884][starVLA.training.train_starvla][INFO] - Step 4975, Loss: {'train/loss': 0.08292947709560394, 'train/grad_norm_pre_clip': 4.102099418640137, 'timing/data': 0.00018468499183654785, 'timing/model': 0.47973094694316387, 'learning_rate/action_model': 9.127118643640112e-05, 'learning_rate/action_query_proj': 9.127118643640112e-05, 'learning_rate/base': 2.281779660910028e-05, 'epoch': 0.6}) +[2026-07-27 10:09:51,467][starVLA.training.train_starvla][INFO] - Step 4976, Loss: {'train/loss': 0.13242924213409424, 'train/grad_norm_pre_clip': 4.065885543823242, 'timing/data': 0.0001857113093137741, 'timing/model': 0.46936677768826485, 'learning_rate/action_model': 9.125383693587523e-05, 'learning_rate/action_query_proj': 9.125383693587523e-05, 'learning_rate/base': 2.281345923396881e-05, 'epoch': 0.6}) +[2026-07-27 10:09:57,115][starVLA.training.train_starvla][INFO] - Step 4977, Loss: {'train/loss': 0.06545085459947586, 'train/grad_norm_pre_clip': 2.7356841564178467, 'timing/data': 0.0001826714724302292, 'timing/model': 0.46723697707057, 'learning_rate/action_model': 9.123647193855617e-05, 'learning_rate/action_query_proj': 9.123647193855617e-05, 'learning_rate/base': 2.280911798463904e-05, 'epoch': 0.6}) +[2026-07-27 10:10:02,682][starVLA.training.train_starvla][INFO] - Step 4978, Loss: {'train/loss': 0.17881813645362854, 'train/grad_norm_pre_clip': 5.783434867858887, 'timing/data': 0.00017515011131763458, 'timing/model': 0.4705181047320366, 'learning_rate/action_model': 9.121909145129937e-05, 'learning_rate/action_query_proj': 9.121909145129937e-05, 'learning_rate/base': 2.2804772862824842e-05, 'epoch': 0.6}) +[2026-07-27 10:10:08,254][starVLA.training.train_starvla][INFO] - Step 4979, Loss: {'train/loss': 0.027453402057290077, 'train/grad_norm_pre_clip': 2.1836657524108887, 'timing/data': 0.00017586909234523773, 'timing/model': 0.4710026141256094, 'learning_rate/action_model': 9.120169548096637e-05, 'learning_rate/action_query_proj': 9.120169548096637e-05, 'learning_rate/base': 2.280042387024159e-05, 'epoch': 0.6}) +[2026-07-27 10:10:13,828][starVLA.training.train_starvla][INFO] - Step 4980, Loss: {'train/loss': 0.08650832623243332, 'train/grad_norm_pre_clip': 3.40022349357605, 'timing/data': 0.0001884177327156067, 'timing/model': 0.4674525447189808, 'learning_rate/action_model': 9.118428403442483e-05, 'learning_rate/action_query_proj': 9.118428403442483e-05, 'learning_rate/base': 2.2796071008606208e-05, 'epoch': 0.6}) +[2026-07-27 10:10:19,375][starVLA.training.train_starvla][INFO] - Step 4981, Loss: {'train/loss': 0.05714922398328781, 'train/grad_norm_pre_clip': 2.8448104858398438, 'timing/data': 0.00017556920647621155, 'timing/model': 0.4569094367325306, 'learning_rate/action_model': 9.116685711854853e-05, 'learning_rate/action_query_proj': 9.116685711854853e-05, 'learning_rate/base': 2.2791714279637132e-05, 'epoch': 0.6}) +[2026-07-27 10:10:24,888][starVLA.training.train_starvla][INFO] - Step 4982, Loss: {'train/loss': 0.03444617986679077, 'train/grad_norm_pre_clip': 2.445824384689331, 'timing/data': 0.00017796829342842102, 'timing/model': 0.4566210377961397, 'learning_rate/action_model': 9.11494147402173e-05, 'learning_rate/action_query_proj': 9.11494147402173e-05, 'learning_rate/base': 2.2787353685054325e-05, 'epoch': 0.6}) +[2026-07-27 10:10:30,421][starVLA.training.train_starvla][INFO] - Step 4983, Loss: {'train/loss': 0.01825050450861454, 'train/grad_norm_pre_clip': 1.1708327531814575, 'timing/data': 0.0001736525446176529, 'timing/model': 0.4714923668652773, 'learning_rate/action_model': 9.113195690631716e-05, 'learning_rate/action_query_proj': 9.113195690631716e-05, 'learning_rate/base': 2.278298922657929e-05, 'epoch': 0.6}) +[2026-07-27 10:10:35,949][starVLA.training.train_starvla][INFO] - Step 4984, Loss: {'train/loss': 0.1401546448469162, 'train/grad_norm_pre_clip': 4.3729352951049805, 'timing/data': 0.00017204321920871735, 'timing/model': 0.4757682029157877, 'learning_rate/action_model': 9.111448362374014e-05, 'learning_rate/action_query_proj': 9.111448362374014e-05, 'learning_rate/base': 2.2778620905935036e-05, 'epoch': 0.6}) +[2026-07-27 10:10:41,746][starVLA.training.train_starvla][INFO] - Step 4985, Loss: {'train/loss': 0.15472277998924255, 'train/grad_norm_pre_clip': 3.2866883277893066, 'timing/data': 0.00017354078590869904, 'timing/model': 0.4712711162865162, 'learning_rate/action_model': 9.109699489938446e-05, 'learning_rate/action_query_proj': 9.109699489938446e-05, 'learning_rate/base': 2.2774248724846114e-05, 'epoch': 0.6}) +[2026-07-27 10:10:47,291][starVLA.training.train_starvla][INFO] - Step 4986, Loss: {'train/loss': 0.054569974541664124, 'train/grad_norm_pre_clip': 2.807924270629883, 'timing/data': 0.00017926469445228577, 'timing/model': 0.47432306967675686, 'learning_rate/action_model': 9.107949074015435e-05, 'learning_rate/action_query_proj': 9.107949074015435e-05, 'learning_rate/base': 2.2769872685038588e-05, 'epoch': 0.6}) +[2026-07-27 10:10:52,820][starVLA.training.train_starvla][INFO] - Step 4987, Loss: {'train/loss': 0.052276235073804855, 'train/grad_norm_pre_clip': 2.781705141067505, 'timing/data': 0.00018129870295524597, 'timing/model': 0.4684272650629282, 'learning_rate/action_model': 9.106197115296022e-05, 'learning_rate/action_query_proj': 9.106197115296022e-05, 'learning_rate/base': 2.2765492788240054e-05, 'epoch': 0.6}) +[2026-07-27 10:10:58,345][starVLA.training.train_starvla][INFO] - Step 4988, Loss: {'train/loss': 0.14626163244247437, 'train/grad_norm_pre_clip': 3.859212636947632, 'timing/data': 0.00017398595809936523, 'timing/model': 0.46941435895860195, 'learning_rate/action_model': 9.104443614471848e-05, 'learning_rate/action_query_proj': 9.104443614471848e-05, 'learning_rate/base': 2.276110903617962e-05, 'epoch': 0.61}) +[2026-07-27 10:11:03,877][starVLA.training.train_starvla][INFO] - Step 4989, Loss: {'train/loss': 0.10628121346235275, 'train/grad_norm_pre_clip': 4.274402618408203, 'timing/data': 0.00017903931438922882, 'timing/model': 0.47176665626466274, 'learning_rate/action_model': 9.102688572235171e-05, 'learning_rate/action_query_proj': 9.102688572235171e-05, 'learning_rate/base': 2.2756721430587927e-05, 'epoch': 0.61}) +[2026-07-27 10:11:09,420][starVLA.training.train_starvla][INFO] - Step 4990, Loss: {'train/loss': 0.061497244983911514, 'train/grad_norm_pre_clip': 3.017704963684082, 'timing/data': 0.00017503462731838226, 'timing/model': 0.47620863281190395, 'learning_rate/action_model': 9.100931989278851e-05, 'learning_rate/action_query_proj': 9.100931989278851e-05, 'learning_rate/base': 2.2752329973197127e-05, 'epoch': 0.61}) +[2026-07-27 10:11:14,948][starVLA.training.train_starvla][INFO] - Step 4991, Loss: {'train/loss': 0.06138121336698532, 'train/grad_norm_pre_clip': 4.5049028396606445, 'timing/data': 0.0001751929521560669, 'timing/model': 0.471696212887764, 'learning_rate/action_model': 9.099173866296361e-05, 'learning_rate/action_query_proj': 9.099173866296361e-05, 'learning_rate/base': 2.2747934665740902e-05, 'epoch': 0.61}) +[2026-07-27 10:11:20,465][starVLA.training.train_starvla][INFO] - Step 4992, Loss: {'train/loss': 0.03869301825761795, 'train/grad_norm_pre_clip': 1.4905426502227783, 'timing/data': 0.00017893314361572266, 'timing/model': 0.4675806201994419, 'learning_rate/action_model': 9.097414203981781e-05, 'learning_rate/action_query_proj': 9.097414203981781e-05, 'learning_rate/base': 2.2743535509954454e-05, 'epoch': 0.61}) +[2026-07-27 10:11:26,028][starVLA.training.train_starvla][INFO] - Step 4993, Loss: {'train/loss': 0.04273327812552452, 'train/grad_norm_pre_clip': 1.9579004049301147, 'timing/data': 0.00018391385674476624, 'timing/model': 0.46835762076079845, 'learning_rate/action_model': 9.095653003029793e-05, 'learning_rate/action_query_proj': 9.095653003029793e-05, 'learning_rate/base': 2.2739132507574483e-05, 'epoch': 0.61}) +[2026-07-27 10:11:31,621][starVLA.training.train_starvla][INFO] - Step 4994, Loss: {'train/loss': 0.14461004734039307, 'train/grad_norm_pre_clip': 3.680476188659668, 'timing/data': 0.00023640692234039307, 'timing/model': 0.46902826242148876, 'learning_rate/action_model': 9.093890264135698e-05, 'learning_rate/action_query_proj': 9.093890264135698e-05, 'learning_rate/base': 2.2734725660339245e-05, 'epoch': 0.61}) +[2026-07-27 10:11:37,188][starVLA.training.train_starvla][INFO] - Step 4995, Loss: {'train/loss': 0.05859972536563873, 'train/grad_norm_pre_clip': 3.7644243240356445, 'timing/data': 0.00017680972814559937, 'timing/model': 0.4771916326135397, 'learning_rate/action_model': 9.092125987995393e-05, 'learning_rate/action_query_proj': 9.092125987995393e-05, 'learning_rate/base': 2.2730314969988483e-05, 'epoch': 0.61}) +[2026-07-27 10:11:42,762][starVLA.training.train_starvla][INFO] - Step 4996, Loss: {'train/loss': 0.09488468617200851, 'train/grad_norm_pre_clip': 3.4370460510253906, 'timing/data': 0.00017783232033252716, 'timing/model': 0.47098415717482567, 'learning_rate/action_model': 9.090360175305387e-05, 'learning_rate/action_query_proj': 9.090360175305387e-05, 'learning_rate/base': 2.272590043826347e-05, 'epoch': 0.61}) +[2026-07-27 10:11:48,288][starVLA.training.train_starvla][INFO] - Step 4997, Loss: {'train/loss': 0.12366018444299698, 'train/grad_norm_pre_clip': 4.178625106811523, 'timing/data': 0.00017347000539302826, 'timing/model': 0.456208199262619, 'learning_rate/action_model': 9.088592826762795e-05, 'learning_rate/action_query_proj': 9.088592826762795e-05, 'learning_rate/base': 2.2721482066906987e-05, 'epoch': 0.61}) +[2026-07-27 10:11:53,979][starVLA.training.train_starvla][INFO] - Step 4998, Loss: {'train/loss': 0.14032872021198273, 'train/grad_norm_pre_clip': 3.7679195404052734, 'timing/data': 0.00018256530165672302, 'timing/model': 0.45654746145009995, 'learning_rate/action_model': 9.08682394306534e-05, 'learning_rate/action_query_proj': 9.08682394306534e-05, 'learning_rate/base': 2.271705985766335e-05, 'epoch': 0.61}) +[2026-07-27 10:11:59,804][starVLA.training.train_starvla][INFO] - Step 4999, Loss: {'train/loss': 0.04632486775517464, 'train/grad_norm_pre_clip': 3.0195844173431396, 'timing/data': 0.00017775967717170715, 'timing/model': 0.45574768260121346, 'learning_rate/action_model': 9.085053524911345e-05, 'learning_rate/action_query_proj': 9.085053524911345e-05, 'learning_rate/base': 2.2712633812278362e-05, 'epoch': 0.61}) +[2026-07-27 10:12:05,360][starVLA.training.train_starvla][INFO] - Starting held-out action loss eval at step 5000 +[2026-07-27 10:12:05,362][starVLA.training.train_starvla][INFO] - Finished held-out action loss eval at step 5000 +[2026-07-27 10:12:05,363][starVLA.training.train_starvla][INFO] - Step 5000, Loss: {'train/loss': 0.1067465990781784, 'train/grad_norm_pre_clip': 2.8250558376312256, 'timing/data': 0.00017407536506652832, 'timing/model': 0.4566498026251793, 'learning_rate/action_model': 9.083281572999748e-05, 'learning_rate/action_query_proj': 9.083281572999748e-05, 'learning_rate/base': 2.270820393249937e-05, 'epoch': 0.61}) +[2026-07-27 10:12:05,366][accelerate.accelerator][INFO] - Saving current state to /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_5000_state +[2026-07-27 10:12:05,366][accelerate.accelerator][INFO] - Saving DeepSpeed Model and Optimizer +[2026-07-27 10:12:51,610][accelerate.accelerator][INFO] - DeepSpeed Model and Optimizer saved to output dir /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_5000_state/pytorch_model +[2026-07-27 10:12:51,611][accelerate.checkpointing][INFO] - Sampler state for dataloader 0 saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_5000_state/sampler.bin +[2026-07-27 10:12:51,618][accelerate.checkpointing][INFO] - Random states saved in /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints/steps_5000_state/random_states_0.pkl +[2026-07-27 10:13:21,140][starVLA.training.rl_games.checkpoint_sync][INFO] - HF checkpoint sync disabled; skipping upload for step 5000 +[2026-07-27 10:13:21,141][starVLA.training.train_starvla][INFO] - 📊 Saving accessed configuration... +[2026-07-27 10:13:21,155][starVLA.training.train_starvla][INFO] - ✅ Configuration files saved +[2026-07-27 10:13:21,157][starVLA.training.train_starvla][INFO] - Training complete. Final training state is saved under /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/wanoft_bench/third_party/starVLA/results/Checkpoints/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/checkpoints +[2026-07-27 10:13:23,103][starVLA.training.train_starvla][INFO] - ... and that's all, folks! +[2026-07-27 10:13:23,104][starVLA.training.train_starvla][INFO] - ... and that's all, folks! +[2026-07-27 10:13:23,104][starVLA.training.train_starvla][INFO] - ... and that's all, folks! +[2026-07-27 10:13:23,104][starVLA.training.train_starvla][INFO] - ... and that's all, folks! +[2026-07-27 10:13:23,104][starVLA.training.train_starvla][INFO] - ... and that's all, folks! +[2026-07-27 10:13:23,104][starVLA.training.train_starvla][INFO] - ... and that's all, folks! +[2026-07-27 10:13:23,104][starVLA.training.train_starvla][INFO] - ... and that's all, folks! +[2026-07-27 10:13:23,104][starVLA.training.train_starvla][INFO] - ... and that's all, folks! +[2026-07-27 10:13:27,771][starVLA.training.train_starvla][INFO] - Destroyed distributed process group +[2026-07-27 10:13:28,052][starVLA.training.train_starvla][INFO] - Destroyed distributed process group +[2026-07-27 10:13:28,174][starVLA.training.train_starvla][INFO] - Destroyed distributed process group +[2026-07-27 10:13:28,279][starVLA.training.train_starvla][INFO] - Destroyed distributed process group +[2026-07-27 10:13:28,297][starVLA.training.train_starvla][INFO] - Destroyed distributed process group +[2026-07-27 10:13:28,337][starVLA.training.train_starvla][INFO] - Destroyed distributed process group +[2026-07-27 10:13:28,341][starVLA.training.train_starvla][INFO] - Destroyed distributed process group +[2026-07-27 10:13:28,344][starVLA.training.train_starvla][INFO] - Destroyed distributed process group diff --git a/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/summary.jsonl b/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/summary.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a0e21985e6b7ed5b88fddcc5f74f6ec45063b603 --- /dev/null +++ b/evaluations/demon-attack/wan_oft_demon_attack_fix_latency_6_context5_standard_sft_5000_effbs128_224_currentce/summary.jsonl @@ -0,0 +1,10 @@ +{"steps": 500} +{"steps": 1000} +{"steps": 1500} +{"steps": 2000} +{"steps": 2500} +{"steps": 3000} +{"steps": 3500} +{"steps": 4000} +{"steps": 4500} +{"steps": 5000} diff --git a/evaluations/flappy/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/train/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/episode_metrics.jsonl b/evaluations/flappy/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/train/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/episode_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3a6d324cd5303f22a0945c7c33933273025d7e7a --- /dev/null +++ b/evaluations/flappy/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/train/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/episode_metrics.jsonl @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:db8769831ceffad9d0fa3a2970035339e038fdc549b9de3253d1dd05f5f9fb06 +size 23536650 diff --git a/evaluations/flappy/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/train/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/git.diff b/evaluations/flappy/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/train/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/git.diff new file mode 100644 index 0000000000000000000000000000000000000000..6b6c9ac9337fbfd2d8a0ec3ddbe582bc9c8ca961 --- /dev/null +++ b/evaluations/flappy/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/train/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/git.diff @@ -0,0 +1,1947 @@ +diff --git a/configs/experiments/fixed_latency_curve.yaml b/configs/experiments/fixed_latency_curve.yaml +deleted file mode 100644 +index 3ab184f..0000000 +--- a/configs/experiments/fixed_latency_curve.yaml ++++ /dev/null +@@ -1,17 +0,0 @@ +-__base__: ../base/dummy.yaml +- +-experiment: +- name: fixed_latency_curve +- +-executor: +- mode: simulated +- +-latency: +- method: fixed +- fixed_latency_ms: 100 +- +-evaluation: +- eval_episodes: 20 +- +-logging: +- output_dir: outputs/fixed_latency_curve +diff --git a/configs/experiments/flappy/frame_stack/base.yaml b/configs/experiments/flappy/frame_stack/base.yaml +deleted file mode 100644 +index f1557d5..0000000 +--- a/configs/experiments/flappy/frame_stack/base.yaml ++++ /dev/null +@@ -1,123 +0,0 @@ +-experiment: +- name: flappy_base +- seed: 0 +- +-backend: +- type: sample_factory +- algo: APPO +- device: cuda +- train_dir: results/checkpoints +- restart_behavior: resume +- run_mode: train +- +-executor: +- mode: simulated +- +-env: +- name: flappy +- # note that env_fps must be an integer multiple of obs_fps! +- env_fps: 30 +- obs_fps: 30 +- gym_id: FlappyBird-v0 +- render_mode: rgb_array +- observation_mode: image +- use_lidar: false +- normalize_obs: true +- audio_on: false +- frame_stack: 4 +- obs_resize: +- - 84 +- - 84 +- # for training it could be true, but for realtime mode, THIS MUST BE FALSE! +- use_gpu_render: true +- simulator: gpu +- gpu_render_device: auto +- gpu_render_profile: false +- gpu_render_profile_interval: 200 +- noop_action: noop +- action_map: +- noop: 0 +- flap: 1 +- oneshot_actions: +- - flap +- +-latency: +- method: normal +- mean_latency_ms: 66.7 +- std_latency_ms: 33.3 +- min_latency_ms: 0 +- max_latency_ms: 500.0 +- +- +-scheduler: +- # [one_frame_then_noop, hold] +- # if hold, default hold duration is: env_fps / obs_fps +- hold_policy: one_frame_then_noop +- # can be either `issue_order_fifo` or `latest ready` +- ordering_policy: latest_ready +- +-policy: +- type: random +- actions: +- - noop +- - flap +- +-training: +- train_for_env_steps: 25000000 +- num_workers: 2 +- num_envs_per_worker: 128 +- worker_num_splits: 1 +- num_policies: 1 +- batch_size: 4096 +- rollout: 128 +- recurrence: 1 +- num_epochs: 8 +- num_batches_per_epoch: 8 +- max_policy_lag: 400 +- learning_rate: 0.00025 +- gamma: 0.99 +- gae_lambda: 0.95 +- ppo_clip_ratio: 0.1 +- ppo_clip_value: 0.2 +- value_loss_coeff: 0.5 +- max_grad_norm: 0.5 +- async_rl: true +- use_rnn: false +- normalize_input: true +- normalize_returns: true +- stats_avg: 100 +- experiment_summaries_interval: 1 +- save_every_sec: 600 +- keep_checkpoints: 5 +- +-evaluation: +- eval_interval_steps: 1000000 +- eval_episodes: 100 +- eval_parallel_envs: 100 +- eval_max_steps: 3600 +- eval_deterministic: true +- eval_raw_reward: false +- eval_suites: +- fixed: +- - [0, 8] # [start, end] +- normal: +- - [2.0, 0.5, 0, 15] # low latency, low jitter +- - [2.0, 1.0, 0, 15] # low latency, medium jitter +- - [4.0, 0.5, 0, 15] # high latency, low jitter +- - [4.0, 1.0, 0, 15] # high latency, medium jitter +- - [4.0, 2.0, 0, 15] # high latency, high jitter +- uniform: +- - [1, 3] # low latency, low jitter +- - [0, 4] # low latency, high jitter +- - [3, 5] # high latency, low jitter +- - [2, 6] # high latency, high jitter +- +-logging: +- output_dir: outputs/flappy_base +- save_step_records: true +- save_action_records: true +- save_latency_records: true +- wandb_project: latency-sensitive-bench +- wandb_group: flappy-frame_stack +- wandb_job_type: sample_factory +- wandb_tags: "" +diff --git a/latency_bench/data/exporters/starvla_lerobot.py b/latency_bench/data/exporters/starvla_lerobot.py +index c693460..4ad276a 100644 +--- a/latency_bench/data/exporters/starvla_lerobot.py ++++ b/latency_bench/data/exporters/starvla_lerobot.py +@@ -18,12 +18,17 @@ from latency_bench.utils.io import write_jsonl + from latency_bench.data.action_layouts import action_spec_for_env + from latency_bench.data.filters import density_weights_clean_v1 + +-FPS_BY_ENV = { +- "flappy": 30, +- "demon_attack": 60, +- "deadly_corridor": 35, +-} + STATE_DIM = 1 ++BRIDGE_DIM = 7 ++DEADLY_CORRIDOR_BRIDGE_ACTION_LABELS = ( ++ "MOVE_FORWARD", ++ "MOVE_BACKWARD", ++ "MOVE_LEFT", ++ "MOVE_RIGHT", ++ "TURN_LEFT", ++ "TURN_RIGHT", ++ "ATTACK", ++) + + + def _png_bytes(image: Any) -> bytes: +@@ -64,30 +69,38 @@ def _load_rows(raw_export_dir: Path, split: str) -> list[dict[str, Any]]: + + + def _episode_groups(rows: list[dict[str, Any]]) -> list[list[dict[str, Any]]]: +- """Group canonical rows by episode and order by decision step. ++ """Group canonical rows by trajectory and order by decision step. + + Args: + rows: Canonical rollout rows from one split. + + Returns: +- Episode row groups sorted by episode index. ++ Trajectory row groups sorted by episode and trajectory index. + """ +- grouped: dict[int, list[dict[str, Any]]] = {} ++ grouped: dict[tuple[int, int], list[dict[str, Any]]] = {} + for row in rows: +- grouped.setdefault(int(row["episode_idx"]), []).append(row) ++ key = (int(row["episode_idx"]), int(row["trajectory_idx"])) ++ grouped.setdefault(key, []).append(row) + return [ + sorted(episode_rows, key=lambda row: int(row["decision_step"])) + for _, episode_rows in sorted(grouped.items()) + ] + + +-def _write_episode(path: Path, rows: list[dict[str, Any]], *, action_dim: int) -> None: ++def _write_episode( ++ path: Path, ++ rows: list[dict[str, Any]], ++ *, ++ action_dim: int, ++ state_dim: int, ++) -> None: + """Write one LeRobot episode parquet file. + + Args: + path: Destination episode parquet path. + rows: Converted LeRobot frame rows. + action_dim: Expected action vector dimension. ++ state_dim: Expected state carrier dimension. + """ + path.parent.mkdir(parents=True, exist_ok=True) + table = pa.table( +@@ -97,8 +110,8 @@ def _write_episode(path: Path, rows: list[dict[str, Any]], *, action_dim: int) - + type=pa.struct([("bytes", pa.binary()), ("path", pa.string())]), + ), + "observation.state": pa.array( +- [[0.0] * STATE_DIM for _ in rows], +- type=pa.list_(pa.float32(), STATE_DIM), ++ [[0.0] * state_dim for _ in rows], ++ type=pa.list_(pa.float32(), state_dim), + ), + "action": pa.array( + [row["action"] for row in rows], +@@ -131,11 +144,47 @@ def _row_action_vector(row: dict[str, Any], *, action_dim: int) -> list[float]: + return [1.0 if idx == action_id else 0.0 for idx in range(action_dim)] + + ++def _bridge_action_vector( ++ row: dict[str, Any], ++ *, ++ env_name: str, ++ active_action_dim: int, ++) -> list[float]: ++ if env_name == "deadly_corridor": ++ action_text = str(row["action_text"]).upper() ++ return [ ++ 1.0 if label in action_text else 0.0 ++ for label in DEADLY_CORRIDOR_BRIDGE_ACTION_LABELS ++ ] ++ action = _row_action_vector(row, action_dim=active_action_dim) ++ return [*action, *([0.0] * (BRIDGE_DIM - active_action_dim))] ++ ++ ++def _target_action_labels( ++ *, ++ env_name: str, ++ source_action_labels: list[str], ++ action_carrier: str, ++) -> list[str]: ++ if action_carrier == "native": ++ return source_action_labels ++ if env_name == "deadly_corridor": ++ return list(DEADLY_CORRIDOR_BRIDGE_ACTION_LABELS) ++ return [ ++ *source_action_labels, ++ *[ ++ f"BRIDGE_PAD_{idx}" ++ for idx in range(len(source_action_labels), BRIDGE_DIM) ++ ], ++ ] ++ ++ + def _write_metadata( + dataset_dir: Path, + *, +- fps: int, ++ fps: float, + action_labels: list[str], ++ state_dim: int, + episode_lengths: list[int], + task_prompts: list[str], + ) -> None: +@@ -144,7 +193,8 @@ def _write_metadata( + Args: + dataset_dir: LeRobot dataset split directory. + fps: Frame rate stored in metadata. +- action_labels: Canonical action labels in vector order. ++ action_labels: Target action labels in vector order. ++ state_dim: State carrier dimension. + episode_lengths: Number of frames per converted episode. + task_prompts: Unique prompts used as LeRobot tasks. + """ +@@ -155,10 +205,10 @@ def _write_metadata( + json.dumps( + { + "codebase_version": "v2.0", +- "fps": int(fps), ++ "fps": fps, + "features": { + "observation.image": {"dtype": "image"}, +- "observation.state": {"dtype": "float32", "shape": [STATE_DIM]}, ++ "observation.state": {"dtype": "float32", "shape": [state_dim]}, + "action": {"dtype": "float32", "shape": [action_dim], "names": action_labels}, + "timestamp": {"dtype": "float64", "shape": [1]}, + "episode_index": {"dtype": "int64", "shape": [1]}, +@@ -183,9 +233,11 @@ def _convert_split( + *, + env_name: str, + action_labels: list[str], +- fps: int, ++ fps: float, + reward_field: str, +- obs_stride: int = 1, ++ action_carrier: str, ++ active_action_dim: int, ++ state_dim: int, + density_weighting: bool = False, + ) -> dict[str, Any]: + """Convert one canonical rollout split into a LeRobot dataset directory. +@@ -195,13 +247,11 @@ def _convert_split( + output_dir: Destination LeRobot split directory. + env_name: Canonical benchmark environment name. + action_labels: Canonical action labels in vector order. +- fps: Frame rate used for timestamps. ++ fps: Observation frame rate used for timestamps. + reward_field: Source canonical reward column. +- obs_stride: Raw frames per observation decision (``round(env_fps/obs_fps)``). +- Canonical rows are recorded once per raw frame; keeping only the obs +- decisions (``decision_step % obs_stride == 0``) makes adjacent LeRobot +- rows adjacent observations, so KV-memory rollouts unroll at the eval +- observation cadence. ++ action_carrier: Target action/state carrier. ++ active_action_dim: Number of active environment action dimensions. ++ state_dim: Target state carrier dimension. + density_weighting: When True, write per-row ``density_weight`` from clean_v1's + event balancing (train split). When False, weights are uniform 1.0 (val + split keeps an unweighted held-out loss). +@@ -214,7 +264,6 @@ def _convert_split( + task_prompts: list[str] = [] + episode_lengths: list[int] = [] + for new_episode_idx, episode_rows in enumerate(_episode_groups(rows)): +- episode_rows = [row for row in episode_rows if int(row["decision_step"]) % obs_stride == 0] + density_weights = ( + density_weights_clean_v1(env_name, episode_rows) + if density_weighting +@@ -231,8 +280,14 @@ def _convert_split( + out_rows.append( + { + "image_bytes": _png_bytes(row["image"]), +- "action": _row_action_vector(row, action_dim=len(action_labels)), +- "timestamp": float(frame_idx) / int(fps), ++ "action": _bridge_action_vector( ++ row, ++ env_name=env_name, ++ active_action_dim=active_action_dim, ++ ) ++ if action_carrier == "bridge" ++ else _row_action_vector(row, action_dim=len(action_labels)), ++ "timestamp": float(frame_idx) / fps, + "episode_index": new_episode_idx, + "frame_index": frame_idx, + "task_index": prompt_to_task_index[prompt], +@@ -248,11 +303,13 @@ def _convert_split( + output_dir / f"data/chunk-{episode_chunk:03d}/episode_{new_episode_idx:06d}.parquet", + out_rows, + action_dim=len(action_labels), ++ state_dim=state_dim, + ) + _write_metadata( + output_dir, + fps=fps, + action_labels=action_labels, ++ state_dim=state_dim, + episode_lengths=episode_lengths, + task_prompts=task_prompts, + ) +@@ -269,6 +326,7 @@ def convert_canonical_rollout_to_lerobot( + raw_export_dir: Path | str, + output_dir: Path | str, + *, ++ action_carrier: str = "native", + force: bool = False, + ) -> dict[str, Any]: + """Convert a canonical rollout export into train/val LeRobot datasets. +@@ -276,6 +334,7 @@ def convert_canonical_rollout_to_lerobot( + Args: + raw_export_dir: Directory with canonical rollout parquet files and metadata. + output_dir: Destination LeRobot train dataset directory. ++ action_carrier: Target action/state carrier, ``native`` or ``bridge``. + force: Remove existing train/val output directories before writing. + + Returns: +@@ -286,11 +345,20 @@ def convert_canonical_rollout_to_lerobot( + metadata = json.loads((raw_export_dir / "metadata.json").read_text(encoding="utf-8")) + env_name = str(metadata["env_name"]) + action_spec = action_spec_for_env(env_name) +- action_labels = list(metadata["action_labels"]) ++ source_action_labels = list(metadata["action_labels"]) ++ action_labels = _target_action_labels( ++ env_name=env_name, ++ source_action_labels=source_action_labels, ++ action_carrier=action_carrier, ++ ) ++ active_action_dim = { ++ "flappy": 2, ++ "demon_attack": 6, ++ "deadly_corridor": 7, ++ }[env_name] ++ state_dim = {"native": STATE_DIM, "bridge": BRIDGE_DIM}[action_carrier] + reward_field = str(metadata["reward_field"]) +- obs_stride = int(metadata.get("obs_stride_raw_frames", 1)) +- # Rows survive at the observation cadence, so timestamps advance at obs_fps. +- fps = max(1, int(FPS_BY_ENV[env_name]) // obs_stride) ++ fps = metadata["obs_fps"] + val_output_dir = output_dir.with_name(f"{output_dir.name}__val") + if output_dir.exists() and force: + shutil.rmtree(output_dir) +@@ -303,7 +371,9 @@ def convert_canonical_rollout_to_lerobot( + action_labels=action_labels, + fps=fps, + reward_field=reward_field, +- obs_stride=obs_stride, ++ action_carrier=action_carrier, ++ active_action_dim=active_action_dim, ++ state_dim=state_dim, + density_weighting=True, + ) + val_manifest = _convert_split( +@@ -313,7 +383,9 @@ def convert_canonical_rollout_to_lerobot( + action_labels=action_labels, + fps=fps, + reward_field=reward_field, +- obs_stride=obs_stride, ++ action_carrier=action_carrier, ++ active_action_dim=active_action_dim, ++ state_dim=state_dim, + density_weighting=False, + ) + manifest = { +@@ -321,9 +393,13 @@ def convert_canonical_rollout_to_lerobot( + "format": "starvla_lerobot_v2_image_parquet", + "source": str(raw_export_dir), + "action_layout": str(metadata["action_layout"]), ++ "action_carrier": action_carrier, + "action_labels": action_labels, + "action_dim": len(action_labels), +- "active_action_dim": len(action_spec.labels), ++ "active_action_dim": active_action_dim ++ if action_carrier == "bridge" ++ else len(action_spec.labels), ++ "state_dim": state_dim, + "validation_dataset_name": val_output_dir.name, + "validation_episodes": val_manifest["episodes"], + "validation_frames": val_manifest["frames"], +diff --git a/latency_bench/data/hf_parquet.py b/latency_bench/data/hf_parquet.py +index 7a26426..6163c0d 100644 +--- a/latency_bench/data/hf_parquet.py ++++ b/latency_bench/data/hf_parquet.py +@@ -205,7 +205,9 @@ def completed_episode_indices_from_shards(output_dir: Path) -> set[int]: + with shard_path.open("r", encoding="utf-8") as handle: + for line in handle: + if line.strip(): +- completed_episode_indices.add(int(json.loads(line)["episode_idx"])) ++ row = json.loads(line) ++ row["trajectory_idx"] ++ completed_episode_indices.add(int(row["episode_idx"])) + break + return completed_episode_indices + +diff --git a/latency_bench/data/rollout_schema.py b/latency_bench/data/rollout_schema.py +index 11426b9..21d2bf5 100644 +--- a/latency_bench/data/rollout_schema.py ++++ b/latency_bench/data/rollout_schema.py +@@ -7,11 +7,12 @@ from datasets import Features, Image as HFImage, Sequence as HFSequence, Value + from latency_bench.data.action_layouts import ActionSpec + + +-SCHEMA_VERSION = 2 ++SCHEMA_VERSION = 3 + CANONICAL_ROW_FIELDS = ( + "image", + "env_name", + "episode_idx", ++ "trajectory_idx", + "decision_step", + "split", + "seed", +@@ -26,6 +27,7 @@ def _rollout_feature_map(action_spec: ActionSpec) -> dict[str, Any]: + "image": HFImage(), + "env_name": Value("string"), + "episode_idx": Value("int64"), ++ "trajectory_idx": Value("int64"), + "decision_step": Value("int64"), + "split": Value("string"), + "seed": Value("int64"), +diff --git a/latency_bench/data/sf_teacher_rollout.py b/latency_bench/data/sf_teacher_rollout.py +index af2b64f..bbbd157 100644 +--- a/latency_bench/data/sf_teacher_rollout.py ++++ b/latency_bench/data/sf_teacher_rollout.py +@@ -355,6 +355,7 @@ def _write_filtered_episode_images( + image_writer: RolloutImageWriter, + rows: list[dict[str, Any]], + frames_by_decision_step: Mapping[int, np.ndarray], ++ trajectory_by_decision_step: Mapping[int, int], + *, + context_window: int, + ) -> list[dict[str, Any]]: +@@ -364,6 +365,7 @@ def _write_filtered_episode_images( + image_writer: Image writer shared by the rollout run. + rows: Final rows selected for materialization. + frames_by_decision_step: Captured frames keyed by decision step. ++ trajectory_by_decision_step: Trajectory index keyed by decision step. + context_window: Total image window length including the current ``image`` field. + + Returns: +@@ -371,10 +373,15 @@ def _write_filtered_episode_images( + """ + if not rows: + return [] +- available_decision_steps = sorted(frames_by_decision_step) + required_steps: set[int] = set() + for row in rows: + decision_step = int(row["decision_step"]) ++ trajectory_idx = int(row["trajectory_idx"]) ++ available_decision_steps = sorted( ++ step ++ for step, step_trajectory_idx in trajectory_by_decision_step.items() ++ if step_trajectory_idx == trajectory_idx ++ ) + required_steps.add(decision_step) + if int(context_window) > 1: + required_steps.update( +@@ -396,6 +403,12 @@ def _write_filtered_episode_images( + for row in rows: + written = dict(row) + decision_step = int(written["decision_step"]) ++ trajectory_idx = int(written["trajectory_idx"]) ++ available_decision_steps = sorted( ++ step ++ for step, step_trajectory_idx in trajectory_by_decision_step.items() ++ if step_trajectory_idx == trajectory_idx ++ ) + written["image"] = written_paths_by_step[decision_step] + if int(context_window) > 1: + written["context_images"] = [ +@@ -804,6 +817,7 @@ def _replay_accepted_specs( + active_episode_rows: list[list[dict[str, Any]]] = [[] for _ in range(driver.slot_count)] + active_episode_frames: list[list[np.ndarray]] = [[] for _ in range(driver.slot_count)] + active_decision_steps = [0 for _ in range(driver.slot_count)] ++ active_trajectory_indices = [0 for _ in range(driver.slot_count)] + active_ghost_streams: list[Any | None] = [None for _ in range(driver.slot_count)] + rnn_states = torch.zeros([driver.slot_count, rnn_size], dtype=torch.float32, device=device) + image_writer = RolloutImageWriter( +@@ -844,6 +858,7 @@ def _replay_accepted_specs( + active_episode_rows[slot] = [] + active_episode_frames[slot] = [] + active_decision_steps[slot] = 0 ++ active_trajectory_indices[slot] = 0 + rnn_states[slot].zero_() + + with tqdm(total=len(specs_to_replay), initial=0, unit="episode") as progress: +@@ -881,21 +896,21 @@ def _replay_accepted_specs( + next_decision_step=next_decision_step, + max_steps_per_episode=int(max_steps_per_episode), + ) +- if not life_loss_boundary: +- active_episode_frames[slot].append(np.array(image_frame, copy=True)) +- row = teacher_dataset_row( +- env_name=env_name, +- spec=spec, +- decision_step=decision_step, +- image=str(image_path), +- raw_action=raw_actions[batch_idx], +- info=step_result.info, +- reward=step_result.reward, +- env_fps=env_fps, +- obs_fps=obs_fps, +- image_transform=image_transform_config.normalized_transform(), +- ) +- active_episode_rows[slot].append(row) ++ active_episode_frames[slot].append(np.array(image_frame, copy=True)) ++ row = teacher_dataset_row( ++ env_name=env_name, ++ spec=spec, ++ trajectory_idx=active_trajectory_indices[slot], ++ decision_step=decision_step, ++ image=str(image_path), ++ raw_action=raw_actions[batch_idx], ++ info=step_result.info, ++ reward=step_result.reward, ++ env_fps=env_fps, ++ obs_fps=obs_fps, ++ image_transform=image_transform_config.normalized_transform(), ++ ) ++ active_episode_rows[slot].append(row) + rnn_states[slot] = new_rnn_states[batch_idx] + if episode_done: + final_rows = _finalize_attempt_rows( +@@ -931,6 +946,10 @@ def _replay_accepted_specs( + image_writer, + shard_rows, + frames_by_decision_step, ++ { ++ int(row["decision_step"]): int(row["trajectory_idx"]) ++ for row in final_rows ++ }, + context_window=int(context_window), + ) + write_episode_row_shard(output_dir, shard_rows) +@@ -943,12 +962,14 @@ def _replay_accepted_specs( + active_episode_rows[slot] = [] + active_episode_frames[slot] = [] + active_decision_steps[slot] = 0 ++ active_trajectory_indices[slot] = 0 + if _is_demon_ghost_trail: + active_ghost_streams[slot] = None + rnn_states[slot].zero_() + else: + if life_loss_boundary: + active_obs[slot], reset_info = driver.continue_after_life_loss(slot) ++ active_trajectory_indices[slot] += 1 + if _is_demon_ghost_trail: + active_ghost_streams[slot].clear() + active_image_frames[slot] = frame_from_env_raw_rgb_info(reset_info).copy() +@@ -981,6 +1002,7 @@ def _replay_accepted_specs( + active_episode_rows[slot] = [] + active_episode_frames[slot] = [] + active_decision_steps[slot] = 0 ++ active_trajectory_indices[slot] = 0 + rnn_states[slot].zero_() + else: + if isinstance(driver, BatchedTeacherRolloutDriver): +diff --git a/latency_bench/data/sf_teacher_rows.py b/latency_bench/data/sf_teacher_rows.py +index efa6f3e..4e7ce9a 100644 +--- a/latency_bench/data/sf_teacher_rows.py ++++ b/latency_bench/data/sf_teacher_rows.py +@@ -14,6 +14,7 @@ def teacher_dataset_row( + *, + env_name: str, + spec: Mapping[str, Any], ++ trajectory_idx: int, + decision_step: int, + image: str, + raw_action: Any, +@@ -28,6 +29,7 @@ def teacher_dataset_row( + Args: + env_name: Canonical benchmark environment name. + spec: Episode spec containing index, split, and seed. ++ trajectory_idx: Zero-based trajectory index within the full-game episode. + decision_step: Zero-based policy decision step within the episode. + image: Path to the saved pre-step image. + raw_action: Raw teacher action for this decision. +@@ -48,6 +50,7 @@ def teacher_dataset_row( + "image": image, + "env_name": str(env_name), + "episode_idx": int(spec["episode_idx"]), ++ "trajectory_idx": int(trajectory_idx), + "decision_step": int(decision_step), + "split": str(spec["split"]), + "seed": int(spec["seed"]), +diff --git a/latency_bench/integrations/sample_factory/runtime.py b/latency_bench/integrations/sample_factory/runtime.py +index e1efadb..aa4f941 100644 +--- a/latency_bench/integrations/sample_factory/runtime.py ++++ b/latency_bench/integrations/sample_factory/runtime.py +@@ -58,7 +58,10 @@ class SampleFactoryIntegrationModule: + getattr(self.module, self._register_attr)() + + def build_sf_cfg_from_config(self, config: dict[str, Any]): +- return self.module.parse_cfg(self.module.build_cli_args_from_config(config)) ++ return self.module.parse_cfg( ++ self.module.build_cli_args_from_config(config), ++ evaluation=True, ++ ) + + def make_reference_env(self, cfg: Any): + return self.module.make_reference_env(cfg) +diff --git a/scripts/experiment_runner/run_manifest_jobs.py b/scripts/experiment_runner/run_manifest_jobs.py +index e2d1b5e..133ccdc 100644 +--- a/scripts/experiment_runner/run_manifest_jobs.py ++++ b/scripts/experiment_runner/run_manifest_jobs.py +@@ -73,11 +73,6 @@ def _event_writer(event_log: Path) -> Callable[[dict[str, Any]], None]: + return write + + +-def _register_process(process: subprocess.Popen) -> None: +- with _ACTIVE_PROCESSES_LOCK: +- _ACTIVE_PROCESSES.add(process) +- +- + def _forget_process(process: subprocess.Popen) -> None: + with _ACTIVE_PROCESSES_LOCK: + _ACTIVE_PROCESSES.discard(process) +@@ -89,11 +84,10 @@ def _active_processes() -> list[subprocess.Popen]: + + + def _signal_process_group(process: subprocess.Popen, sig: int) -> None: +- if process.poll() is None: +- try: +- os.killpg(process.pid, sig) +- except ProcessLookupError: +- pass ++ try: ++ os.killpg(process.pid, sig) ++ except ProcessLookupError: ++ pass + + + def _terminate_active_processes(sig: int = signal.SIGTERM) -> None: +@@ -118,15 +112,24 @@ def _terminate_active_processes(sig: int = signal.SIGTERM) -> None: + pass + + +-def _run_command(command: str, *, gpu: str) -> None: ++def _run_command( ++ command: str, ++ *, ++ gpu: str, ++ cancel_event: threading.Event | None = None, ++) -> bool: + env = os.environ.copy() + env["CUDA_VISIBLE_DEVICES"] = str(gpu) +- process = subprocess.Popen(command, shell=True, env=env, start_new_session=True) +- _register_process(process) ++ with _ACTIVE_PROCESSES_LOCK: ++ if cancel_event is not None and cancel_event.is_set(): ++ return False ++ process = subprocess.Popen(command, shell=True, env=env, start_new_session=True) ++ _ACTIVE_PROCESSES.add(process) + try: + returncode = process.wait() + if returncode != 0: + raise subprocess.CalledProcessError(returncode, command) ++ return True + finally: + _forget_process(process) + +@@ -201,14 +204,11 @@ def _resume_stage(job: dict[str, str], states: dict[str, str]) -> str: + stage = states.get(str(job["job_id"]), "") + if stage in {"job_complete", "upload_skipped", "upload_succeeded"}: + return "complete" +- if stage in {"eval_succeeded", "upload_failed"}: ++ if stage in {"eval_succeeded", "upload_started", "upload_failed"}: + return "upload" +- if stage == "train_succeeded": +- return "eval" +- if stage == "eval_failed": +- # Training already succeeded before eval ran; re-eval from the checkpoint +- # instead of retraining from scratch. +- return "eval" ++ if stage in {"train_succeeded", "eval_started", "eval_failed"}: ++ train_config = Path(job["train_artifact_dir"]) / "config.json" ++ return "eval" if train_config.is_file() else "train" + return "train" + + +@@ -223,16 +223,6 @@ def run_jobs( + dry_run: bool = False, + uploader: Callable[[dict[str, str]], None] | None = None, + ) -> int: +- previous_sigint = signal.getsignal(signal.SIGINT) +- previous_sigterm = signal.getsignal(signal.SIGTERM) +- +- def stop_active_processes(signum, frame): +- del frame +- _terminate_active_processes(signal.SIGTERM) +- raise KeyboardInterrupt(signum) +- +- signal.signal(signal.SIGINT, stop_active_processes) +- signal.signal(signal.SIGTERM, stop_active_processes) + manifest_file = Path(manifest_path).expanduser().resolve() + event_log = event_log_path_for_manifest(manifest_file) + write_event = _event_writer(event_log) +@@ -253,12 +243,16 @@ def run_jobs( + jobs = [ + row + for row in rows +- if states.get(row["job_id"], "") in {"eval_succeeded", "upload_failed"} ++ if states.get(row["job_id"], "") ++ in {"eval_succeeded", "upload_started", "upload_failed"} + ] + job_queue: queue.Queue[dict[str, str] | None] = queue.Queue() + upload_queue: queue.Queue[UploadTask | None] = queue.Queue() + failures: list[tuple[str, str]] = [] + failure_lock = threading.Lock() ++ cancel_event = threading.Event() ++ signal_event = threading.Event() ++ cleanup_started = False + uploader_fn = _default_uploader if uploader is None else uploader + + if stage != "upload": +@@ -280,28 +274,49 @@ def run_jobs( + if job is None: + job_queue.task_done() + break ++ if cancel_event.is_set(): ++ job_queue.task_done() ++ continue + next_stage = _resume_stage(job, states) if stage == "all" else stage + job_id = str(job["job_id"]) + try: + if next_stage == "train": ++ if cancel_event.is_set(): ++ continue + if dry_run: + print(f"[dry-run] CUDA_VISIBLE_DEVICES={gpu} {job['train_command']}", flush=True) + else: + write_event({"job_id": job_id, "stage": "train_started", "gpu": gpu, "ts": _now()}) +- _run_command(str(job["train_command"]), gpu=gpu) ++ started = _run_command( ++ str(job["train_command"]), ++ gpu=gpu, ++ cancel_event=cancel_event, ++ ) ++ if not started or cancel_event.is_set(): ++ continue + write_event({"job_id": job_id, "stage": "train_succeeded", "gpu": gpu, "ts": _now()}) + next_stage = "eval" if stage == "all" else "complete" + if next_stage == "eval": ++ if cancel_event.is_set(): ++ continue + if dry_run: + print(f"[dry-run] CUDA_VISIBLE_DEVICES={gpu} {job['eval_command']}", flush=True) + else: + write_event({"job_id": job_id, "stage": "eval_started", "gpu": gpu, "ts": _now()}) +- _run_command(str(job["eval_command"]), gpu=gpu) ++ started = _run_command( ++ str(job["eval_command"]), ++ gpu=gpu, ++ cancel_event=cancel_event, ++ ) ++ if not started or cancel_event.is_set(): ++ continue + write_event({"job_id": job_id, "stage": "eval_succeeded", "gpu": gpu, "ts": _now()}) + next_stage = "upload" if stage == "all" else "complete" +- if next_stage == "upload": ++ if next_stage == "upload" and not cancel_event.is_set(): + upload_queue.put(UploadTask(job)) + except subprocess.CalledProcessError: ++ if cancel_event.is_set(): ++ continue + failed_stage = "train_failed" if next_stage == "train" else "eval_failed" + write_event({"job_id": job_id, "stage": failed_stage, "gpu": gpu, "ts": _now()}) + record_failure(job_id, failed_stage) +@@ -311,48 +326,52 @@ def run_jobs( + def upload_worker() -> None: + while True: + task = upload_queue.get() +- if task is None: +- upload_queue.task_done() +- break +- job = task.job +- job_id = str(job["job_id"]) +- train_repo_id = str(job["train_upload_repo_id"]) +- eval_repo_id = str(job["eval_upload_repo_id"]) +- if dry_run: +- targets = [repo_id for repo_id in (eval_repo_id, train_repo_id) if repo_id] +- print(f"[dry-run] upload {job_id}: {', '.join(targets) or 'no upload target'}", flush=True) +- upload_queue.task_done() +- continue +- if not train_repo_id and not eval_repo_id: +- write_event({"job_id": job_id, "stage": "upload_skipped", "ts": _now()}) +- write_event({"job_id": job_id, "stage": "job_complete", "ts": _now()}) +- upload_queue.task_done() +- continue +- attempt = 0 +- success = False +- while attempt < max_upload_attempts and not success: +- attempt += 1 +- write_event({"job_id": job_id, "stage": "upload_started", "attempt": attempt, "ts": _now()}) +- try: +- if not dry_run: +- uploader_fn(job) +- write_event({"job_id": job_id, "stage": "upload_succeeded", "attempt": attempt, "ts": _now()}) ++ try: ++ if task is None: ++ break ++ if cancel_event.is_set(): ++ continue ++ job = task.job ++ job_id = str(job["job_id"]) ++ train_repo_id = str(job["train_upload_repo_id"]) ++ eval_repo_id = str(job["eval_upload_repo_id"]) ++ if dry_run: ++ targets = [repo_id for repo_id in (eval_repo_id, train_repo_id) if repo_id] ++ print(f"[dry-run] upload {job_id}: {', '.join(targets) or 'no upload target'}", flush=True) ++ continue ++ if not train_repo_id and not eval_repo_id: ++ write_event({"job_id": job_id, "stage": "upload_skipped", "ts": _now()}) + write_event({"job_id": job_id, "stage": "job_complete", "ts": _now()}) +- success = True +- except Exception as error: +- write_event( +- { +- "job_id": job_id, +- "stage": "upload_failed", +- "attempt": attempt, +- "error": repr(error), +- "ts": _now(), +- } +- ) +- print(f"upload failed for {job_id} (attempt {attempt}): {error!r}", file=sys.stderr) +- if not success: +- record_failure(job_id, "upload_failed") +- upload_queue.task_done() ++ continue ++ attempt = 0 ++ success = False ++ while attempt < max_upload_attempts and not success and not cancel_event.is_set(): ++ attempt += 1 ++ write_event({"job_id": job_id, "stage": "upload_started", "attempt": attempt, "ts": _now()}) ++ try: ++ uploader_fn(job) ++ if cancel_event.is_set(): ++ continue ++ write_event({"job_id": job_id, "stage": "upload_succeeded", "attempt": attempt, "ts": _now()}) ++ write_event({"job_id": job_id, "stage": "job_complete", "ts": _now()}) ++ success = True ++ except Exception as error: ++ if cancel_event.is_set(): ++ continue ++ write_event( ++ { ++ "job_id": job_id, ++ "stage": "upload_failed", ++ "attempt": attempt, ++ "error": repr(error), ++ "ts": _now(), ++ } ++ ) ++ print(f"upload failed for {job_id} (attempt {attempt}): {error!r}", file=sys.stderr) ++ if not success and not cancel_event.is_set(): ++ record_failure(job_id, "upload_failed") ++ finally: ++ upload_queue.task_done() + + upload_threads = [ + threading.Thread(target=upload_worker, name=f"upload-{idx}", daemon=True) +@@ -362,17 +381,44 @@ def run_jobs( + threading.Thread(target=train_worker, args=(gpu,), name=f"train-{gpu}", daemon=True) + for gpu in gpus if stage != "upload" + ] ++ previous_sigint = signal.getsignal(signal.SIGINT) ++ previous_sigterm = signal.getsignal(signal.SIGTERM) ++ ++ def stop_active_processes(signum, frame): ++ nonlocal cleanup_started ++ del frame ++ if signal_event.is_set(): ++ return ++ signal_event.set() ++ cancel_event.set() ++ if cleanup_started: ++ return ++ raise KeyboardInterrupt(signum) ++ ++ signal.signal(signal.SIGINT, stop_active_processes) ++ signal.signal(signal.SIGTERM, stop_active_processes) + try: + for thread in upload_threads + train_threads: + thread.start() + job_queue.join() +- for _ in upload_threads: +- upload_queue.put(None) + upload_queue.join() +- for thread in train_threads + upload_threads: +- thread.join() + return 1 if failures else 0 + finally: ++ cleanup_started = True ++ cancel_event.set() ++ _terminate_active_processes(signal.SIGTERM) ++ for thread in train_threads: ++ thread.join() ++ _terminate_active_processes(signal.SIGTERM) ++ if signal_event.is_set(): ++ for _ in upload_threads: ++ upload_queue.put(None) ++ else: ++ upload_queue.join() ++ for _ in upload_threads: ++ upload_queue.put(None) ++ for thread in upload_threads: ++ thread.join() + _terminate_active_processes(signal.SIGTERM) + signal.signal(signal.SIGINT, previous_sigint) + signal.signal(signal.SIGTERM, previous_sigterm) +diff --git a/scripts/rollout_data/prepare_starvla_lerobot_dataset.py b/scripts/rollout_data/prepare_starvla_lerobot_dataset.py +index e202657..2521899 100644 +--- a/scripts/rollout_data/prepare_starvla_lerobot_dataset.py ++++ b/scripts/rollout_data/prepare_starvla_lerobot_dataset.py +@@ -26,6 +26,7 @@ def convert_raw_export_to_lerobot( + raw_export_dir: Path, + lerobot_root: Path, + data_mix: str, ++ action_carrier: str = "native", + ) -> dict: + """Convert a raw rollout export into a named LeRobot data mix. + +@@ -33,6 +34,7 @@ def convert_raw_export_to_lerobot( + raw_export_dir: Canonical rollout export directory. + lerobot_root: Directory that will contain the LeRobot datasets. + data_mix: Train dataset directory name under ``lerobot_root``. ++ action_carrier: Target action/state carrier. + + Returns: + Conversion manifest returned by the LeRobot adapter. +@@ -41,6 +43,7 @@ def convert_raw_export_to_lerobot( + return convert_canonical_rollout_to_lerobot( + raw_export_dir, + output_dir, ++ action_carrier=action_carrier, + force=True, + ) + +@@ -92,6 +95,7 @@ def build_parser() -> argparse.ArgumentParser: + parser.add_argument("raw_export_dir") + parser.add_argument("lerobot_root") + parser.add_argument("data_mix") ++ parser.add_argument("--action-carrier", choices=("native", "bridge"), default="native") + parser.add_argument("--push-to-hub", default="") + parser.add_argument("--private", action="store_true") + return parser +@@ -115,6 +119,7 @@ def main(argv: Sequence[str] | None = None) -> int: + raw_export_dir=raw_export_dir, + lerobot_root=lerobot_root, + data_mix=data_mix, ++ action_carrier=args.action_carrier, + ) + if args.push_to_hub: + push_lerobot_dataset( +diff --git a/scripts/sweeps/generate_sweep_configs.py b/scripts/sweeps/generate_sweep_configs.py +index 8074c79..bd5fafe 100644 +--- a/scripts/sweeps/generate_sweep_configs.py ++++ b/scripts/sweeps/generate_sweep_configs.py +@@ -116,6 +116,7 @@ ENV_KEYS_BY_NAME = { + "obs_fps", + "screen_size", + "noop_max", ++ "reset_mode", + "frame_stack", + "terminal_on_life_loss", + "clip_reward", +diff --git a/tests/data/test_rollout_dataset_schema.py b/tests/data/test_rollout_dataset_schema.py +index 06a6091..55ccebf 100644 +--- a/tests/data/test_rollout_dataset_schema.py ++++ b/tests/data/test_rollout_dataset_schema.py +@@ -8,6 +8,7 @@ def test_canonical_rollout_fields_exclude_legacy_aliases(): + "image", + "env_name", + "episode_idx", ++ "trajectory_idx", + "decision_step", + "split", + "seed", +@@ -36,6 +37,7 @@ def test_rollout_features_include_env_specific_action_fields(): + assert "action_tuple" not in deadly_features + assert "action" not in deadly_features + for features in (flappy_features, deadly_features): ++ assert "trajectory_idx" in features + assert "decision_step" in features + assert "latency_raw_frames" in features + assert "raw_reward" in features +diff --git a/tests/data/test_rollout_hf_parquet.py b/tests/data/test_rollout_hf_parquet.py +index 9fa4c48..4e56de6 100644 +--- a/tests/data/test_rollout_hf_parquet.py ++++ b/tests/data/test_rollout_hf_parquet.py +@@ -15,6 +15,7 @@ def test_hf_parquet_writes_canonical_columns_only(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -56,6 +57,7 @@ def test_hf_parquet_shards_sort_by_decision_step(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": decision_step, + "split": "train", + "seed": 11, +@@ -92,6 +94,7 @@ def test_hf_parquet_embeds_context_images_when_rows_provide_them(tmp_path): + "context_images": [str(path) for path in context_paths], + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -116,3 +119,18 @@ def test_hf_parquet_embeds_context_images_when_rows_provide_them(tmp_path): + assert "context_images" in table.column_names + assert len(exported["context_images"]) == 3 + assert exported["context_images"][0]["bytes"].startswith(b"\x89PNG\r\n\x1a\n") ++ ++ ++def test_completed_episode_shards_require_trajectory_identity(tmp_path): ++ import json ++ ++ import pytest ++ ++ from latency_bench.data.hf_parquet import completed_episode_indices_from_shards ++ ++ shard_path = tmp_path / "episode_rows" / "train" / "episode_000000.jsonl" ++ shard_path.parent.mkdir(parents=True) ++ shard_path.write_text(json.dumps({"episode_idx": 0}) + "\n", encoding="utf-8") ++ ++ with pytest.raises(KeyError, match="trajectory_idx"): ++ completed_episode_indices_from_shards(tmp_path) +diff --git a/tests/data/test_sf_teacher_dataset_export.py b/tests/data/test_sf_teacher_dataset_export.py +index 62b30a6..ba4644b 100644 +--- a/tests/data/test_sf_teacher_dataset_export.py ++++ b/tests/data/test_sf_teacher_dataset_export.py +@@ -1299,7 +1299,7 @@ def test_write_filtered_episode_images_preserves_empty_filtered_episode(tmp_path + + image_writer = RolloutImageWriter(max_workers=0, row_buffer_size=1, export_image_size=None) + +- rows = _write_filtered_episode_images(image_writer, [], {}, context_window=5) ++ rows = _write_filtered_episode_images(image_writer, [], {}, {}, context_window=5) + + assert rows == [] + +@@ -1314,6 +1314,7 @@ def test_write_filtered_episode_images_resets_context_after_decision_step_gap(tm + { + "image": str(tmp_path / "images" / "train" / "episode_000000" / f"decision_step_{step:06d}.png"), + "decision_step": step, ++ "trajectory_idx": 0, + } + for step in [0, 1, 4, 5] + ] +@@ -1326,6 +1327,7 @@ def test_write_filtered_episode_images_resets_context_after_decision_step_gap(tm + image_writer, + rows, + frames_by_decision_step, ++ {step: 0 for step in frames_by_decision_step}, + context_window=4, + ) + +@@ -1733,13 +1735,24 @@ def test_collect_teacher_dataset_demon_attack_exports_full_game_across_life_loss + image_writer_workers=0, + row_buffer_size=1, + filter_preset="none", ++ context_window=3, + ) + train_rows = _read_shard_rows(output_dir, "train") + state = json.loads((output_dir / "probe_state.json").read_text(encoding="utf-8")) + + assert ScriptedDemonEnv.reset_seeds == [100, None, None, 100, None, None] +- assert [row["decision_step"] for row in train_rows] == [2] +- assert train_rows[0]["raw_reward"] == 30.0 ++ assert [row["decision_step"] for row in train_rows] == [0, 1, 2] ++ assert [row["trajectory_idx"] for row in train_rows] == [0, 1, 2] ++ assert [row["action_id"] for row in train_rows] == [1, 1, 1] ++ assert [row["raw_reward"] for row in train_rows] == [10.0, 20.0, 30.0] ++ from PIL import Image ++ ++ context_values = [ ++ [np.asarray(Image.open(path))[0, 0, 0].item() for path in row["context_images"]] ++ for row in train_rows ++ ] ++ current_values = [np.asarray(Image.open(row["image"]))[0, 0, 0].item() for row in train_rows] ++ assert context_values == [[value, value] for value in current_values] + assert state["accepted_specs"] == [ + { + "attempt_idx": 0, +@@ -1900,6 +1913,7 @@ def test_collect_teacher_dataset_skips_runtime_when_probe_and_shards_complete(mo + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 100, +@@ -2264,6 +2278,7 @@ def test_write_parquet_splits_handles_empty_validation_rows(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -2300,6 +2315,7 @@ def test_write_parquet_splits_embeds_image_bytes(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -2336,6 +2352,7 @@ def test_write_parquet_splits_preserves_rows_across_large_exports(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": episode_idx, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11 + episode_idx, +@@ -2390,6 +2407,7 @@ def test_write_parquet_splits_from_shards_writes_train_and_val_rows(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": episode_idx, ++ "trajectory_idx": 0, + "decision_step": decision_step, + "split": split, + "seed": 11 + episode_idx, +@@ -2432,6 +2450,7 @@ def test_write_parquet_splits_from_shards_replaces_stale_partial_file(tmp_path): + "image": str(stale_image_path), + "env_name": "flappy", + "episode_idx": 99, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 99, +@@ -2452,6 +2471,7 @@ def test_write_parquet_splits_from_shards_replaces_stale_partial_file(tmp_path): + "image": str(image_path), + "env_name": "flappy", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 11, +@@ -2536,6 +2556,8 @@ def test_prepare_starvla_lerobot_dataset_converts_from_raw_export(monkeypatch, t + str(raw_export), + str(tmp_path / "lerobot"), + "demon_attack_train", ++ "--action-carrier", ++ "bridge", + ]) + + assert result == 0 +@@ -2543,7 +2565,7 @@ def test_prepare_starvla_lerobot_dataset_converts_from_raw_export(monkeypatch, t + ( + raw_export, + tmp_path / "lerobot" / "demon_attack_train", +- {"force": True}, ++ {"action_carrier": "bridge", "force": True}, + ) + ] + +diff --git a/tests/data/test_starvla_lerobot_exporter.py b/tests/data/test_starvla_lerobot_exporter.py +index 64b5f47..58391c7 100644 +--- a/tests/data/test_starvla_lerobot_exporter.py ++++ b/tests/data/test_starvla_lerobot_exporter.py +@@ -3,6 +3,7 @@ from __future__ import annotations + import json + + import pyarrow.parquet as pq ++import pytest + + from helpers import save_test_image + +@@ -20,6 +21,7 @@ def test_starvla_lerobot_exporter_reads_canonical_rollout_schema(tmp_path): + "image": str(image_path), + "env_name": "deadly_corridor", + "episode_idx": 3, ++ "trajectory_idx": 0, + "decision_step": 0, + "split": "train", + "seed": 14, +@@ -38,6 +40,7 @@ def test_starvla_lerobot_exporter_reads_canonical_rollout_schema(tmp_path): + "action_layout": "deadly_corridor_joint_54", + "reward_field": "raw_reward", + "action_labels": list(action_spec.labels), ++ "obs_fps": 8.75, + } + ), + encoding="utf-8", +@@ -54,10 +57,102 @@ def test_starvla_lerobot_exporter_reads_canonical_rollout_schema(tmp_path): + assert table.to_pylist()[0]["done"] is True + + +-def test_starvla_lerobot_exporter_subsamples_to_obs_cadence(tmp_path): +- """Adjacent LeRobot rows must be adjacent obs decisions (every obs_stride raw +- frames), with contiguous frame_index, so KV-memory rollouts unroll at the eval +- observation cadence rather than at every raw frame.""" ++@pytest.mark.parametrize( ++ ("env_name", "obs_fps", "latency", "action_values", "expected_action", "active_action_dim"), ++ [ ++ ("flappy", 30, 3, (1, [0.0, 1.0], "FLAP"), [0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0], 2), ++ ( ++ "demon_attack", ++ 15, ++ 6, ++ (5, [0.0, 0.0, 0.0, 0.0, 0.0, 1.0], "LEFTFIRE"), ++ [0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0], ++ 6, ++ ), ++ ( ++ "deadly_corridor", ++ 8.75, ++ 6, ++ (11, None, "MOVE_FORWARD + MOVE_RIGHT + ATTACK"), ++ [1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 1.0], ++ 7, ++ ), ++ ], ++) ++def test_starvla_lerobot_exporter_writes_bridge_carrier_with_raw_latency_prompt( ++ tmp_path, ++ env_name, ++ obs_fps, ++ latency, ++ action_values, ++ expected_action, ++ active_action_dim, ++): ++ from latency_bench.data.action_layouts import action_spec_for_env ++ from latency_bench.data.exporters.starvla_lerobot import convert_canonical_rollout_to_lerobot ++ from latency_bench.data.hf_parquet import write_parquet_splits ++ ++ image_path = tmp_path / "image.png" ++ save_test_image(image_path, 9) ++ raw_export = tmp_path / "raw" ++ action_spec = action_spec_for_env(env_name) ++ action_id, action, action_text = action_values ++ row = { ++ "image": str(image_path), ++ "env_name": env_name, ++ "episode_idx": 0, ++ "trajectory_idx": 0, ++ "decision_step": 0, ++ "split": "train", ++ "seed": 0, ++ "prompt": f"The action latency is fixed at {latency} raw environment frames.", ++ "latency_raw_frames": latency, ++ "latency_ms": latency * 1000 / {"flappy": 30, "demon_attack": 60, "deadly_corridor": 35}[env_name], ++ "raw_reward": 1.0, ++ "action_id": action_id, ++ "action_text": action_text, ++ } ++ if action is not None: ++ row["action"] = action ++ write_parquet_splits(raw_export, [row], [], action_spec=action_spec) ++ (raw_export / "metadata.json").write_text( ++ json.dumps( ++ { ++ "env_name": env_name, ++ "action_layout": action_spec.layout, ++ "reward_field": action_spec.reward_field, ++ "action_labels": list(action_spec.labels), ++ "obs_fps": obs_fps, ++ } ++ ), ++ encoding="utf-8", ++ ) ++ ++ manifest = convert_canonical_rollout_to_lerobot( ++ raw_export, ++ tmp_path / "lerobot", ++ action_carrier="bridge", ++ force=True, ++ ) ++ ++ table = pq.read_table(tmp_path / "lerobot" / "data" / "chunk-000" / "episode_000000.parquet") ++ info = json.loads((tmp_path / "lerobot" / "meta" / "info.json").read_text(encoding="utf-8")) ++ task_lines = (tmp_path / "lerobot" / "meta" / "tasks.jsonl").read_text( ++ encoding="utf-8" ++ ).splitlines() ++ tasks = [json.loads(line) for line in task_lines] ++ converted_row = table.to_pylist()[0] ++ assert converted_row["action"] == expected_action ++ assert converted_row["observation.state"] == [0.0] * 7 ++ assert info["features"]["action"]["shape"] == [7] ++ assert info["features"]["observation.state"]["shape"] == [7] ++ assert tasks == [{"task_index": 0, "task": row["prompt"]}] ++ assert manifest["action_carrier"] == "bridge" ++ assert manifest["active_action_dim"] == active_action_dim ++ ++ ++def test_starvla_lerobot_exporter_keeps_every_observation_decision(tmp_path): ++ """Canonical rows already occur at the policy observation cadence.""" + from latency_bench.data.action_layouts import action_spec_for_env + from latency_bench.data.exporters.starvla_lerobot import convert_canonical_rollout_to_lerobot + from latency_bench.data.hf_parquet import write_parquet_splits +@@ -66,12 +161,13 @@ def test_starvla_lerobot_exporter_subsamples_to_obs_cadence(tmp_path): + save_test_image(image_path, 9) + raw_export = tmp_path / "raw" + action_spec = action_spec_for_env("deadly_corridor") +- # One episode, 8 contiguous per-raw-frame decision steps; obs_stride = 4. ++ # One trajectory with eight contiguous policy-decision observations. + train_rows = [ + { + "image": str(image_path), + "env_name": "deadly_corridor", + "episode_idx": 0, ++ "trajectory_idx": 0, + "decision_step": step, + "split": "train", + "seed": 7, +@@ -92,6 +188,7 @@ def test_starvla_lerobot_exporter_subsamples_to_obs_cadence(tmp_path): + "action_layout": "deadly_corridor_joint_54", + "reward_field": "raw_reward", + "action_labels": list(action_spec.labels), ++ "obs_fps": 8.75, + "obs_stride_raw_frames": 4, + } + ), +@@ -102,12 +199,73 @@ def test_starvla_lerobot_exporter_subsamples_to_obs_cadence(tmp_path): + + table = pq.read_table(tmp_path / "lerobot" / "data" / "chunk-000" / "episode_000000.parquet") + rows = table.to_pylist() +- # Only decision_steps 0 and 4 survive; frame_index is contiguous obs index. +- assert [r["frame_index"] for r in rows] == [0, 1] +- assert [r["episode_index"] for r in rows] == [0, 0] ++ assert [r["frame_index"] for r in rows] == list(range(8)) ++ assert [r["episode_index"] for r in rows] == [0] * 8 + assert rows[-1]["done"] is True + + ++def test_starvla_lerobot_exporter_splits_life_trajectories(tmp_path): ++ from latency_bench.data.action_layouts import action_spec_for_env ++ from latency_bench.data.exporters.starvla_lerobot import convert_canonical_rollout_to_lerobot ++ from latency_bench.data.hf_parquet import write_parquet_splits ++ ++ image_path = tmp_path / "image.png" ++ save_test_image(image_path, 9) ++ raw_export = tmp_path / "raw" ++ action_spec = action_spec_for_env("demon_attack") ++ train_rows = [ ++ { ++ "image": str(image_path), ++ "env_name": "demon_attack", ++ "episode_idx": 0, ++ "trajectory_idx": trajectory_idx, ++ "decision_step": decision_step, ++ "split": "train", ++ "seed": 7, ++ "prompt": "pick action", ++ "latency_raw_frames": 6, ++ "latency_ms": 100.0, ++ "raw_reward": 1.0, ++ "action_id": 0, ++ "action": [1.0, 0.0, 0.0, 0.0, 0.0, 0.0], ++ "action_text": "NOOP", ++ } ++ for trajectory_idx, decision_step in ((0, 0), (0, 1), (1, 2), (1, 3)) ++ ] ++ write_parquet_splits(raw_export, train_rows, [], action_spec=action_spec) ++ (raw_export / "metadata.json").write_text( ++ json.dumps( ++ { ++ "env_name": "demon_attack", ++ "action_layout": action_spec.layout, ++ "reward_field": action_spec.reward_field, ++ "action_labels": list(action_spec.labels), ++ "obs_fps": 15, ++ } ++ ), ++ encoding="utf-8", ++ ) ++ ++ manifest = convert_canonical_rollout_to_lerobot( ++ raw_export, ++ tmp_path / "lerobot", ++ action_carrier="bridge", ++ force=True, ++ ) ++ ++ first = pq.read_table( ++ tmp_path / "lerobot" / "data" / "chunk-000" / "episode_000000.parquet" ++ ).to_pylist() ++ second = pq.read_table( ++ tmp_path / "lerobot" / "data" / "chunk-000" / "episode_000001.parquet" ++ ).to_pylist() ++ assert manifest["episodes"] == 2 ++ assert [row["frame_index"] for row in first] == [0, 1] ++ assert [row["frame_index"] for row in second] == [0, 1] ++ assert [row["done"] for row in first] == [False, True] ++ assert [row["done"] for row in second] == [False, True] ++ ++ + def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + from datasets import Dataset, Features, Image as HFImage, Sequence as HFSequence, Value + from latency_bench.data.exporters.starvla_lerobot import convert_canonical_rollout_to_lerobot +@@ -121,6 +279,7 @@ def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + "image": HFImage(), + "env_name": Value("string"), + "episode_idx": Value("int64"), ++ "trajectory_idx": Value("int64"), + "decision_step": Value("int64"), + "split": Value("string"), + "seed": Value("int64"), +@@ -138,6 +297,7 @@ def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + "image": [str(image_path)], + "env_name": ["flappy"], + "episode_idx": [0], ++ "trajectory_idx": [0], + "decision_step": [0], + "split": ["train"], + "seed": [11], +@@ -156,6 +316,7 @@ def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + "image": [str(image_path)], + "env_name": ["flappy"], + "episode_idx": [1], ++ "trajectory_idx": [0], + "decision_step": [0], + "split": ["val"], + "seed": [12], +@@ -176,6 +337,7 @@ def test_starvla_lerobot_exporter_does_not_accept_latency_alias(tmp_path): + "action_layout": "flappy_discrete", + "reward_field": "raw_reward", + "action_labels": ["NOOP", "FLAP"], ++ "obs_fps": 30, + } + ), + encoding="utf-8", +diff --git a/tests/policies/test_sample_factory_policy.py b/tests/policies/test_sample_factory_policy.py +index 0cfe0e1..e61b69c 100644 +--- a/tests/policies/test_sample_factory_policy.py ++++ b/tests/policies/test_sample_factory_policy.py +@@ -18,6 +18,21 @@ from latency_bench.policy import sample_factory as sample_factory_policy + from latency_bench.policy import sample_factory_common + + ++def test_sample_factory_integration_parses_policy_config_for_evaluation(): ++ calls = [] ++ parsed_cfg = object() ++ module = SimpleNamespace( ++ build_cli_args_from_config=lambda config: ["--experiment", config["experiment"]], ++ parse_cfg=lambda argv, *, evaluation: calls.append((argv, evaluation)) or parsed_cfg, ++ ) ++ integration = sf_runtime.SampleFactoryIntegrationModule(module, "register_components") ++ ++ result = integration.build_sf_cfg_from_config({"experiment": "teacher"}) ++ ++ assert result is parsed_cfg ++ assert calls == [(["--experiment", "teacher"], True)] ++ ++ + @pytest.mark.parametrize( + ("policy_type", "integration_module_name", "register_attr"), + [ +diff --git a/tests/scripts/test_generate_sweep_configs.py b/tests/scripts/test_generate_sweep_configs.py +index 23d79cb..438b296 100644 +--- a/tests/scripts/test_generate_sweep_configs.py ++++ b/tests/scripts/test_generate_sweep_configs.py +@@ -23,6 +23,75 @@ def _read_manifest(path: Path) -> list[dict[str, str]]: + return [dict(zip(header, line.split("\t"))) for line in lines[1:]] + + ++@pytest.mark.parametrize( ++ ("env_name", "latency_label", "latency_frames", "obs_fps", "obs_fps_label"), ++ [ ++ ("flappy", "fixed_l3", 3, 30, "30"), ++ ("demon_attack", "fixed_l6", 6, 15, "15"), ++ ("deadly_corridor", "fixed_l6", 6, 8.75, "8p75"), ++ ], ++) ++def test_memory_rollout_teacher_spec_emits_single_uploadable_job( ++ tmp_path, ++ env_name, ++ latency_label, ++ latency_frames, ++ obs_fps, ++ obs_fps_label, ++): ++ generated_root = tmp_path / "configs" ++ output_root = tmp_path / "outputs" ++ train_dir = tmp_path / "checkpoints" ++ ++ generate_sweep_configs( ++ [ ++ "--spec", ++ f"configs/experiments/memory/rollout_teacher/{env_name}.yaml", ++ "--generated-root", ++ str(generated_root), ++ "--output-root", ++ str(output_root), ++ "--train-dir", ++ str(train_dir), ++ ] ++ ) ++ ++ rows = _read_manifest(generated_root / "manifest.tsv") ++ assert len(rows) == 1 ++ row = rows[0] ++ assert row["env"] == env_name ++ assert row["experiment_family"] == "memory_rollout_teacher" ++ assert row["sweep_name"] == "teacher" ++ assert row["seed"] == "0" ++ assert row["frame_stack"] == "4" ++ assert row["obs_fps"] == obs_fps_label ++ assert row["latency_label"] == latency_label ++ assert row["latency_kind"] == "fixed" ++ assert row["latency_fixed_frames"] == str(latency_frames) ++ assert row["train_upload_repo_id"] == "latency-sensitive-bench/paper-experiment-models" ++ assert row["train_upload_repo_type"] == "model" ++ assert row["eval_upload_repo_id"] == "" ++ assert row["train_artifact_repo_path"].startswith( ++ f"memory/rollout_teachers/{env_name}/train/" ++ ) ++ ++ train_cfg = yaml.safe_load(Path(row["train_config"]).read_text(encoding="utf-8")) ++ assert train_cfg["experiment"]["seed"] == 0 ++ assert train_cfg["env"]["frame_stack"] == 4 ++ assert train_cfg["env"]["obs_fps"] == pytest.approx(obs_fps) ++ if env_name == "demon_attack": ++ assert train_cfg["env"]["reset_mode"] == "fire" ++ assert train_cfg["latency"]["method"] == "fixed" ++ assert train_cfg["latency"]["fixed_latency_ms"] == pytest.approx( ++ latency_frames * 1000 / train_cfg["env"]["env_fps"] ++ ) ++ assert train_cfg["evaluation"]["eval_suites"] == { ++ "fixed": [[latency_frames]], ++ "normal": [], ++ "uniform": [], ++ } ++ ++ + def test_latency_bench_eval_config_disables_full_trace_records(tmp_path): + base_config = { + "backend": { +diff --git a/tests/scripts/test_manifest_jobs.py b/tests/scripts/test_manifest_jobs.py +index bd7bf03..c9dd3c6 100644 +--- a/tests/scripts/test_manifest_jobs.py ++++ b/tests/scripts/test_manifest_jobs.py +@@ -1,8 +1,10 @@ + from __future__ import annotations + ++import json + import os +-import subprocess ++import shlex + import signal ++import subprocess + import sys + import threading + import time +@@ -10,6 +12,7 @@ import types + from pathlib import Path + + import pytest ++from helpers import REPO_ROOT + + import scripts.experiment_runner.run_manifest_jobs as run_manifest_jobs + from scripts.experiment_runner.job_manifest import ( +@@ -68,6 +71,39 @@ def test_train_stage_only_trains_and_resumes_from_success(tmp_path): + assert [event["stage"] for event in events] == ["train_started", "train_succeeded"] + + ++@pytest.mark.parametrize( ++ ("recorded_stage", "expected_stage"), ++ [ ++ ("train_started", "train"), ++ ("train_succeeded", "eval"), ++ ("eval_started", "eval"), ++ ("eval_failed", "eval"), ++ ("eval_succeeded", "upload"), ++ ("upload_started", "upload"), ++ ], ++) ++def test_resume_stage_keeps_interrupted_job_at_its_current_pipeline_stage( ++ tmp_path, ++ recorded_stage, ++ expected_stage, ++): ++ train_artifact_dir = tmp_path / "train_artifact" ++ train_artifact_dir.mkdir() ++ (train_artifact_dir / "config.json").write_text("{}") ++ assert run_manifest_jobs._resume_stage( ++ {"job_id": "job1", "train_artifact_dir": str(train_artifact_dir)}, ++ {"job1": recorded_stage}, ++ ) == expected_stage ++ ++ ++@pytest.mark.parametrize("recorded_stage", ["train_succeeded", "eval_started", "eval_failed"]) ++def test_resume_stage_retrains_when_train_artifact_was_deleted(tmp_path, recorded_stage): ++ assert run_manifest_jobs._resume_stage( ++ {"job_id": "job1", "train_artifact_dir": str(tmp_path / "deleted_train_artifact")}, ++ {"job1": recorded_stage}, ++ ) == "train" ++ ++ + def test_eval_stage_does_not_train_or_upload(tmp_path): + manifest_path, train_mark, eval_mark = _write_single_job(tmp_path) + uploads: list[str] = [] +@@ -134,6 +170,26 @@ def test_upload_stage_needs_no_gpu_and_retries_failed_upload(tmp_path): + ] + + ++def test_upload_stage_resumes_interrupted_upload(tmp_path): ++ manifest_path, _, _ = _write_single_job(tmp_path) ++ append_event( ++ event_log_path_for_manifest(manifest_path), ++ {"job_id": "job1", "stage": "upload_started", "ts": 1.0}, ++ ) ++ uploads: list[str] = [] ++ ++ assert run_jobs( ++ manifest_path=manifest_path, ++ gpus=[], ++ upload_workers=1, ++ max_upload_attempts=1, ++ stage="upload", ++ uploader=lambda job: uploads.append(job["job_id"]), ++ ) == 0 ++ ++ assert uploads == ["job1"] ++ ++ + def test_dry_run_does_not_execute_or_record_success(tmp_path, capsys): + manifest_path, train_mark, eval_mark = _write_single_job(tmp_path) + +@@ -310,6 +366,186 @@ def test_run_command_cleanup_terminates_child_process_group(tmp_path): + os.kill(child_pid, 0) + + ++def test_sigint_cancels_queue_and_kills_all_active_process_groups(tmp_path): ++ helper_path = tmp_path / "ignore_term_job.py" ++ helper_path.write_text( ++ """from __future__ import annotations ++ ++import json ++import os ++from pathlib import Path ++import signal ++import subprocess ++import sys ++import time ++ ++signal.signal(signal.SIGTERM, signal.SIG_IGN) ++child = subprocess.Popen( ++ [ ++ sys.executable, ++ "-c", ++ "import signal, time; signal.signal(signal.SIGTERM, signal.SIG_IGN); time.sleep(60)", ++ ] ++) ++Path(sys.argv[1]).write_text( ++ json.dumps( ++ { ++ "leader_pid": os.getpid(), ++ "leader_pgid": os.getpgid(0), ++ "child_pid": child.pid, ++ "child_pgid": os.getpgid(child.pid), ++ } ++ ), ++ encoding="utf-8", ++) ++time.sleep(60) ++""", ++ encoding="utf-8", ++ ) ++ manifest_path = tmp_path / "manifest.tsv" ++ markers = [tmp_path / f"job_{idx}.json" for idx in range(4)] ++ rows = [] ++ for idx, marker in enumerate(markers): ++ row = {column: "" for column in MANIFEST_V2_COLUMNS} ++ row.update( ++ { ++ "schema_version": "v2", ++ "job_id": f"job{idx}", ++ "train_command": f"exec {shlex.join([sys.executable, str(helper_path), str(marker)])}", ++ } ++ ) ++ rows.append(row) ++ write_manifest(manifest_path, rows) ++ ++ runner = subprocess.Popen( ++ [ ++ sys.executable, ++ "-m", ++ "scripts.experiment_runner.run_manifest_jobs", ++ "--manifest", ++ str(manifest_path), ++ "--stage", ++ "train", ++ "--gpus", ++ "0,1", ++ ], ++ cwd=REPO_ROOT, ++ stdout=subprocess.PIPE, ++ stderr=subprocess.PIPE, ++ text=True, ++ ) ++ process_groups: set[int] = set() ++ try: ++ deadline = time.time() + 10.0 ++ while sum(marker.is_file() for marker in markers) < 2 and time.time() < deadline: ++ time.sleep(0.05) ++ assert [marker.is_file() for marker in markers] == [True, True, False, False] ++ for marker in markers[:2]: ++ process_info = json.loads(marker.read_text(encoding="utf-8")) ++ assert process_info["leader_pgid"] == process_info["child_pgid"] ++ process_groups.add(int(process_info["leader_pgid"])) ++ ++ runner.send_signal(signal.SIGINT) ++ time.sleep(0.1) ++ runner.send_signal(signal.SIGINT) ++ stdout, stderr = runner.communicate(timeout=10.0) ++ assert runner.returncode != 0, (stdout, stderr) ++ assert [marker.is_file() for marker in markers] == [True, True, False, False] ++ ++ deadline = time.time() + 5.0 ++ while process_groups and time.time() < deadline: ++ for process_group in list(process_groups): ++ try: ++ os.killpg(process_group, 0) ++ except ProcessLookupError: ++ process_groups.remove(process_group) ++ time.sleep(0.05) ++ assert not process_groups ++ ++ events = load_events(event_log_path_for_manifest(manifest_path)) ++ assert [event["stage"] for event in events] == ["train_started", "train_started"] ++ finally: ++ if runner.poll() is None: ++ runner.kill() ++ runner.wait() ++ for process_group in process_groups: ++ try: ++ os.killpg(process_group, signal.SIGKILL) ++ except ProcessLookupError: ++ pass ++ ++ ++def test_sigint_does_not_wait_for_in_flight_upload(tmp_path): ++ manifest_path = tmp_path / "manifest.tsv" ++ row = {column: "" for column in MANIFEST_V2_COLUMNS} ++ row.update( ++ { ++ "schema_version": "v2", ++ "job_id": "job0", ++ "train_upload_repo_id": "repo-model", ++ "train_upload_repo_type": "model", ++ } ++ ) ++ write_manifest(manifest_path, [row]) ++ append_event( ++ event_log_path_for_manifest(manifest_path), ++ {"job_id": "job0", "stage": "eval_succeeded"}, ++ ) ++ upload_started = tmp_path / "upload_started" ++ helper_path = tmp_path / "blocking_upload_runner.py" ++ helper_path.write_text( ++ """from pathlib import Path ++import sys ++import time ++ ++from scripts.experiment_runner.run_manifest_jobs import run_jobs ++ ++manifest_path = Path(sys.argv[1]) ++upload_started = Path(sys.argv[2]) ++ ++def blocking_uploader(job): ++ del job ++ upload_started.write_text("started", encoding="utf-8") ++ time.sleep(60) ++ ++raise SystemExit( ++ run_jobs( ++ manifest_path=manifest_path, ++ gpus=[], ++ upload_workers=1, ++ max_upload_attempts=1, ++ stage="upload", ++ uploader=blocking_uploader, ++ ) ++) ++""", ++ encoding="utf-8", ++ ) ++ runner = subprocess.Popen( ++ [sys.executable, str(helper_path), str(manifest_path), str(upload_started)], ++ cwd=REPO_ROOT, ++ env={**os.environ, "PYTHONPATH": str(REPO_ROOT)}, ++ stdout=subprocess.PIPE, ++ stderr=subprocess.PIPE, ++ text=True, ++ ) ++ try: ++ deadline = time.time() + 10.0 ++ while not upload_started.is_file() and time.time() < deadline: ++ time.sleep(0.05) ++ assert upload_started.is_file() ++ ++ started_at = time.monotonic() ++ runner.send_signal(signal.SIGINT) ++ stdout, stderr = runner.communicate(timeout=5.0) ++ assert runner.returncode != 0, (stdout, stderr) ++ assert time.monotonic() - started_at < 3.0 ++ finally: ++ if runner.poll() is None: ++ runner.kill() ++ runner.wait() ++ ++ + def test_default_uploader_prefers_env_token_over_dotenv(monkeypatch, tmp_path): + monkeypatch.chdir(tmp_path) + (tmp_path / ".env").write_text("HF_TOKEN=dotenv-token\n", encoding="utf-8") +diff --git a/training/deadly_corridor_sf/integration.py b/training/deadly_corridor_sf/integration.py +index 08fc63e..6405b7c 100644 +--- a/training/deadly_corridor_sf/integration.py ++++ b/training/deadly_corridor_sf/integration.py +@@ -287,7 +287,7 @@ def add_latency_args(parser: argparse.ArgumentParser) -> None: + parser.add_argument("--vizdoom_init_retry_jitter_sec", type=float, default=0.25) + + +-def parse_cfg(argv=None): ++def parse_cfg(argv=None, *, evaluation: bool = True): + from sample_factory.cfg.arguments import parse_full_cfg, parse_sf_args + from sf_examples.vizdoom.doom.doom_params import ( + add_doom_env_args, +@@ -295,7 +295,7 @@ def parse_cfg(argv=None): + doom_override_defaults, + ) + +- parser, _ = parse_sf_args(argv=argv, evaluation=True) ++ parser, _ = parse_sf_args(argv=argv, evaluation=evaluation) + add_doom_env_args(parser) + add_doom_env_eval_args(parser) + add_latency_args(parser) +diff --git a/training/demon_attack_sf/integration.py b/training/demon_attack_sf/integration.py +index 1ee9060..9097048 100644 +--- a/training/demon_attack_sf/integration.py ++++ b/training/demon_attack_sf/integration.py +@@ -318,10 +318,10 @@ def demon_attack_override_defaults(parser: argparse.ArgumentParser) -> None: + ) + + +-def parse_cfg(argv=None): ++def parse_cfg(argv=None, *, evaluation: bool = False): + from sample_factory.cfg.arguments import parse_full_cfg, parse_sf_args + +- parser, _ = parse_sf_args(argv=argv, evaluation=False) ++ parser, _ = parse_sf_args(argv=argv, evaluation=evaluation) + add_demon_attack_env_args(parser) + demon_attack_override_defaults(parser) + cfg = parse_full_cfg(parser, argv) +diff --git a/training/flappy_sf/integration.py b/training/flappy_sf/integration.py +index 6f666be..c342ba7 100644 +--- a/training/flappy_sf/integration.py ++++ b/training/flappy_sf/integration.py +@@ -541,10 +541,10 @@ def flappy_override_defaults(parser: argparse.ArgumentParser) -> None: + ) + + +-def parse_cfg(argv=None): ++def parse_cfg(argv=None, *, evaluation: bool = False): + from sample_factory.cfg.arguments import parse_full_cfg, parse_sf_args + +- parser, _ = parse_sf_args(argv=argv, evaluation=False) ++ parser, _ = parse_sf_args(argv=argv, evaluation=evaluation) + add_flappy_env_args(parser) + flappy_override_defaults(parser) + cfg = parse_full_cfg(parser, argv) diff --git a/evaluations/flappy/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/train/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/sf_log.txt b/evaluations/flappy/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/train/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/sf_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..0a98d898d339198663249b7bbe20f6b99d12fc14 --- /dev/null +++ b/evaluations/flappy/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/train/memory_rollout_teacher:flappy:teacher:fixed_l3:fs4:obs30:stride1:seed0/sf_log.txt @@ -0,0 +1,5793 @@ +[2026-07-22 22:49:20,924][543203] Saving configuration to results/checkpoints/memory/rollout_teacher/flappy_teacher_fixed_l3_obs30_seed0/config.json... +[2026-07-22 22:49:21,089][543203] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 22:49:21,090][543203] Rollout worker 0 uses device cuda:0 +[2026-07-22 22:49:21,090][543203] Using GPUs [0] for process 1 (actually maps to GPUs [1]) +[2026-07-22 22:49:21,090][543203] Rollout worker 1 uses device cuda:0 +[2026-07-22 22:49:22,635][543203] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 22:49:22,636][543203] InferenceWorker_p0-w0: min num requests: 1 +[2026-07-22 22:49:22,640][543203] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 22:49:22,644][543203] Using GPUs [0] for process 1 (actually maps to GPUs [1]) +[2026-07-22 22:49:22,645][543203] Starting all processes... +[2026-07-22 22:49:22,645][543203] Starting process learner_proc0 +[2026-07-22 22:49:24,934][543203] Starting all processes... +[2026-07-22 22:49:24,938][543203] Starting process inference_proc0-0 +[2026-07-22 22:49:24,938][543203] Starting process rollout_proc0 +[2026-07-22 22:49:24,938][543203] Starting process rollout_proc1 +[2026-07-22 22:49:25,178][543696] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 22:49:25,178][543696] Set environment var CUDA_VISIBLE_DEVICES to '1' (GPU indices [0]) for learning process 0 +[2026-07-22 22:49:25,178][543696] Num visible devices: 1 +[2026-07-22 22:49:25,184][543696] Setting fixed seed 0 +[2026-07-22 22:49:25,189][543696] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 22:49:25,189][543696] Initializing actor-critic model on device cuda:0 +[2026-07-22 22:49:25,189][543696] RunningMeanStd input shape: (12, 84, 84) +[2026-07-22 22:49:25,191][543696] RunningMeanStd input shape: (1,) +[2026-07-22 22:49:25,206][543696] ConvEncoder: input_channels=12 +[2026-07-22 22:49:25,312][543696] Conv encoder output size: 512 +[2026-07-22 22:49:25,318][543696] Created Actor Critic model with architecture: +[2026-07-22 22:49:25,319][543696] ActorCriticSharedWeights( + (obs_normalizer): ObservationNormalizer( + (running_mean_std): RunningMeanStdDictInPlace( + (running_mean_std): ModuleDict( + (obs): RunningMeanStdInPlace() + ) + ) + ) + (returns_normalizer): RecursiveScriptModule(original_name=RunningMeanStdInPlace) + (encoder): MultiInputEncoder( + (encoders): ModuleDict( + (obs): ConvEncoder( + (enc): RecursiveScriptModule( + original_name=ConvEncoderImpl + (conv_head): RecursiveScriptModule( + original_name=Sequential + (0): RecursiveScriptModule(original_name=Conv2d) + (1): RecursiveScriptModule(original_name=ELU) + (2): RecursiveScriptModule(original_name=Conv2d) + (3): RecursiveScriptModule(original_name=ELU) + (4): RecursiveScriptModule(original_name=Conv2d) + (5): RecursiveScriptModule(original_name=ELU) + ) + (mlp_layers): RecursiveScriptModule( + original_name=Sequential + (0): RecursiveScriptModule(original_name=Linear) + (1): RecursiveScriptModule(original_name=ELU) + ) + ) + ) + ) + ) + (core): ModelCoreIdentity() + (decoder): MlpDecoder( + (mlp): Identity() + ) + (critic_linear): Linear(in_features=512, out_features=1, bias=True) + (action_parameterization): ActionParameterizationDefault( + (distribution_linear): Linear(in_features=512, out_features=2, bias=True) + ) +) +[2026-07-22 22:49:25,322][543696] Using optimizer +[2026-07-22 22:49:27,617][543985] Worker 1 uses CPU cores [14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27] +[2026-07-22 22:49:27,617][543985] Using GPUs [0] for process 1 (actually maps to GPUs [1]) +[2026-07-22 22:49:27,618][543985] Set environment var CUDA_VISIBLE_DEVICES to '1' (GPU indices [0]) for actor process 1 +[2026-07-22 22:49:27,618][543985] Num visible devices: 1 +[2026-07-22 22:49:27,748][543984] Worker 0 uses CPU cores [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13] +[2026-07-22 22:49:27,749][543984] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 22:49:27,749][543984] Set environment var CUDA_VISIBLE_DEVICES to '1' (GPU indices [0]) for actor process 0 +[2026-07-22 22:49:27,749][543984] Num visible devices: 1 +[2026-07-22 22:49:27,823][543983] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 22:49:27,823][543983] Set environment var CUDA_VISIBLE_DEVICES to '1' (GPU indices [0]) for inference process 0 +[2026-07-22 22:49:27,824][543983] Num visible devices: 1 +[2026-07-22 22:49:28,584][543696] No checkpoints found +[2026-07-22 22:49:28,584][543696] Did not load from checkpoint, starting from scratch! +[2026-07-22 22:49:28,585][543696] Initialized policy 0 weights for model version 0 +[2026-07-22 22:49:28,586][543696] LearnerWorker_p0 finished initialization! +[2026-07-22 22:49:28,586][543696] Using GPUs [0] for process 0 (actually maps to GPUs [1]) +[2026-07-22 22:49:28,587][543983] RunningMeanStd input shape: (12, 84, 84) +[2026-07-22 22:49:28,589][543983] RunningMeanStd input shape: (1,) +[2026-07-22 22:49:28,600][543983] ConvEncoder: input_channels=12 +[2026-07-22 22:49:28,682][543983] Conv encoder output size: 512 +[2026-07-22 22:49:28,687][543203] Inference worker 0-0 is ready! +[2026-07-22 22:49:28,687][543203] All inference workers are ready! Signal rollout workers to start! +[2026-07-22 22:49:28,688][543984] EnvRunner 0-0 uses policy 0 +[2026-07-22 22:49:28,688][543985] EnvRunner 1-0 uses policy 0 +[2026-07-22 22:49:31,818][543696] Signal inference workers to stop experience collection... +[2026-07-22 22:49:31,824][543983] InferenceWorker_p0-w0: stopping experience collection +[2026-07-22 22:49:32,287][543203] Fps is (10 sec: nan, 60 sec: nan, 300 sec: nan). Total num frames: 0. Throughput: 0: nan. Samples: 64000. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) +[2026-07-22 22:49:32,288][543203] Avg episode reward: [(0, '-7.317')] +[2026-07-22 22:49:34,780][543696] Signal inference workers to resume experience collection... +[2026-07-22 22:49:34,781][543983] InferenceWorker_p0-w0: resuming experience collection +[2026-07-22 22:49:35,298][543983] Updated weights for policy 0, policy_version 73 (0.0068) +[2026-07-22 22:49:35,850][543983] Updated weights for policy 0, policy_version 92 (0.0007) +[2026-07-22 22:49:36,193][543983] Updated weights for policy 0, policy_version 102 (0.0007) +[2026-07-22 22:49:36,657][543983] Updated weights for policy 0, policy_version 118 (0.0007) +[2026-07-22 22:49:36,978][543983] Updated weights for policy 0, policy_version 128 (0.0007) +[2026-07-22 22:49:37,286][543203] Fps is (10 sec: 13108.9, 60 sec: 13108.9, 300 sec: 13108.9). Total num frames: 65536. Throughput: 0: 384.0. Samples: 65920. Policy #0 lag: (min: 63.0, avg: 63.0, max: 63.0) +[2026-07-22 22:49:37,287][543203] Avg episode reward: [(0, '-7.266')] +[2026-07-22 22:49:37,666][543983] Updated weights for policy 0, policy_version 143 (0.0007) +[2026-07-22 22:49:38,016][543983] Updated weights for policy 0, policy_version 153 (0.0006) +[2026-07-22 22:49:38,327][543983] Updated weights for policy 0, policy_version 163 (0.0007) +[2026-07-22 22:49:38,733][543983] Updated weights for policy 0, policy_version 177 (0.0006) +[2026-07-22 22:49:39,088][543983] Updated weights for policy 0, policy_version 187 (0.0007) +[2026-07-22 22:49:39,765][543983] Updated weights for policy 0, policy_version 197 (0.0006) +[2026-07-22 22:49:40,192][543983] Updated weights for policy 0, policy_version 212 (0.0008) +[2026-07-22 22:49:40,511][543983] Updated weights for policy 0, policy_version 222 (0.0008) +[2026-07-22 22:49:40,849][543983] Updated weights for policy 0, policy_version 232 (0.0007) +[2026-07-22 22:49:41,178][543983] Updated weights for policy 0, policy_version 244 (0.0007) +[2026-07-22 22:49:41,522][543983] Updated weights for policy 0, policy_version 254 (0.0006) +[2026-07-22 22:49:42,094][543983] Updated weights for policy 0, policy_version 265 (0.0006) +[2026-07-22 22:49:42,286][543203] Fps is (10 sec: 13108.1, 60 sec: 13108.1, 300 sec: 13108.1). Total num frames: 131072. Throughput: 0: 8640.6. Samples: 150400. Policy #0 lag: (min: 63.0, avg: 97.8, max: 191.0) +[2026-07-22 22:49:42,287][543203] Avg episode reward: [(0, '-6.891')] +[2026-07-22 22:49:42,422][543983] Updated weights for policy 0, policy_version 275 (0.0007) +[2026-07-22 22:49:42,625][543203] Heartbeat connected on Batcher_0 +[2026-07-22 22:49:42,640][543203] Heartbeat connected on RolloutWorker_w0 +[2026-07-22 22:49:42,654][543203] Heartbeat connected on InferenceWorker_p0-w0 +[2026-07-22 22:49:42,741][543983] Updated weights for policy 0, policy_version 285 (0.0008) +[2026-07-22 22:49:42,849][543203] Heartbeat connected on RolloutWorker_w1 +[2026-07-22 22:49:43,027][543983] Updated weights for policy 0, policy_version 295 (0.0007) +[2026-07-22 22:49:43,379][543983] Updated weights for policy 0, policy_version 305 (0.0006) +[2026-07-22 22:49:43,698][543983] Updated weights for policy 0, policy_version 315 (0.0007) +[2026-07-22 22:49:43,836][543696] Saving new best policy, reward=-6.891! +[2026-07-22 22:49:43,870][543203] Heartbeat connected on LearnerWorker_p0 +[2026-07-22 22:49:44,343][543983] Updated weights for policy 0, policy_version 325 (0.0006) +[2026-07-22 22:49:44,685][543983] Updated weights for policy 0, policy_version 337 (0.0006) +[2026-07-22 22:49:45,018][543983] Updated weights for policy 0, policy_version 347 (0.0006) +[2026-07-22 22:49:45,351][543983] Updated weights for policy 0, policy_version 357 (0.0007) +[2026-07-22 22:49:45,645][543983] Updated weights for policy 0, policy_version 367 (0.0007) +[2026-07-22 22:49:45,966][543983] Updated weights for policy 0, policy_version 377 (0.0007) +[2026-07-22 22:49:46,553][543983] Updated weights for policy 0, policy_version 387 (0.0007) +[2026-07-22 22:49:46,856][543983] Updated weights for policy 0, policy_version 397 (0.0006) +[2026-07-22 22:49:47,140][543983] Updated weights for policy 0, policy_version 407 (0.0006) +[2026-07-22 22:49:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.8, 300 sec: 13107.8). Total num frames: 196608. Throughput: 0: 11460.8. Samples: 235904. Policy #0 lag: (min: 43.0, avg: 78.5, max: 106.0) +[2026-07-22 22:49:47,287][543203] Avg episode reward: [(0, '-5.934')] +[2026-07-22 22:49:47,473][543983] Updated weights for policy 0, policy_version 417 (0.0007) +[2026-07-22 22:49:47,769][543983] Updated weights for policy 0, policy_version 427 (0.0006) +[2026-07-22 22:49:48,080][543983] Updated weights for policy 0, policy_version 437 (0.0007) +[2026-07-22 22:49:48,393][543983] Updated weights for policy 0, policy_version 447 (0.0007) +[2026-07-22 22:49:48,435][543696] Saving new best policy, reward=-5.934! +[2026-07-22 22:49:49,114][543983] Updated weights for policy 0, policy_version 457 (0.0007) +[2026-07-22 22:49:49,407][543983] Updated weights for policy 0, policy_version 467 (0.0006) +[2026-07-22 22:49:49,716][543983] Updated weights for policy 0, policy_version 477 (0.0007) +[2026-07-22 22:49:50,070][543983] Updated weights for policy 0, policy_version 487 (0.0006) +[2026-07-22 22:49:50,370][543983] Updated weights for policy 0, policy_version 498 (0.0007) +[2026-07-22 22:49:50,671][543983] Updated weights for policy 0, policy_version 508 (0.0007) +[2026-07-22 22:49:51,346][543983] Updated weights for policy 0, policy_version 518 (0.0007) +[2026-07-22 22:49:51,698][543983] Updated weights for policy 0, policy_version 528 (0.0006) +[2026-07-22 22:49:51,990][543983] Updated weights for policy 0, policy_version 538 (0.0007) +[2026-07-22 22:49:52,286][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.6, 300 sec: 13107.6). Total num frames: 262144. Throughput: 0: 10752.3. Samples: 279040. Policy #0 lag: (min: 63.0, avg: 93.0, max: 127.0) +[2026-07-22 22:49:52,287][543203] Avg episode reward: [(0, '-4.453')] +[2026-07-22 22:49:52,292][543983] Updated weights for policy 0, policy_version 548 (0.0006) +[2026-07-22 22:49:52,627][543983] Updated weights for policy 0, policy_version 558 (0.0011) +[2026-07-22 22:49:52,932][543983] Updated weights for policy 0, policy_version 568 (0.0006) +[2026-07-22 22:49:53,177][543696] Saving new best policy, reward=-4.453! +[2026-07-22 22:49:53,526][543983] Updated weights for policy 0, policy_version 578 (0.0007) +[2026-07-22 22:49:53,880][543983] Updated weights for policy 0, policy_version 590 (0.0006) +[2026-07-22 22:49:54,174][543983] Updated weights for policy 0, policy_version 600 (0.0007) +[2026-07-22 22:49:54,520][543983] Updated weights for policy 0, policy_version 610 (0.0008) +[2026-07-22 22:49:54,849][543983] Updated weights for policy 0, policy_version 621 (0.0006) +[2026-07-22 22:49:55,133][543983] Updated weights for policy 0, policy_version 631 (0.0007) +[2026-07-22 22:49:55,814][543983] Updated weights for policy 0, policy_version 641 (0.0007) +[2026-07-22 22:49:56,119][543983] Updated weights for policy 0, policy_version 651 (0.0007) +[2026-07-22 22:49:56,439][543983] Updated weights for policy 0, policy_version 661 (0.0007) +[2026-07-22 22:49:56,732][543983] Updated weights for policy 0, policy_version 671 (0.0007) +[2026-07-22 22:49:57,030][543983] Updated weights for policy 0, policy_version 681 (0.0007) +[2026-07-22 22:49:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.5, 300 sec: 13107.5). Total num frames: 327680. Throughput: 0: 12109.1. Samples: 366720. Policy #0 lag: (min: 63.0, avg: 91.9, max: 127.0) +[2026-07-22 22:49:57,287][543203] Avg episode reward: [(0, '-0.150')] +[2026-07-22 22:49:57,359][543983] Updated weights for policy 0, policy_version 691 (0.0007) +[2026-07-22 22:49:57,650][543983] Updated weights for policy 0, policy_version 701 (0.0007) +[2026-07-22 22:49:57,753][543696] Saving new best policy, reward=-0.150! +[2026-07-22 22:49:58,321][543983] Updated weights for policy 0, policy_version 711 (0.0007) +[2026-07-22 22:49:58,589][543983] Updated weights for policy 0, policy_version 721 (0.0008) +[2026-07-22 22:49:58,897][543983] Updated weights for policy 0, policy_version 731 (0.0007) +[2026-07-22 22:49:59,249][543983] Updated weights for policy 0, policy_version 741 (0.0007) +[2026-07-22 22:49:59,586][543983] Updated weights for policy 0, policy_version 753 (0.0007) +[2026-07-22 22:49:59,900][543983] Updated weights for policy 0, policy_version 764 (0.0008) +[2026-07-22 22:50:00,674][543983] Updated weights for policy 0, policy_version 774 (0.0006) +[2026-07-22 22:50:00,996][543983] Updated weights for policy 0, policy_version 784 (0.0007) +[2026-07-22 22:50:01,284][543983] Updated weights for policy 0, policy_version 794 (0.0006) +[2026-07-22 22:50:01,559][543983] Updated weights for policy 0, policy_version 804 (0.0007) +[2026-07-22 22:50:01,855][543983] Updated weights for policy 0, policy_version 814 (0.0006) +[2026-07-22 22:50:02,192][543983] Updated weights for policy 0, policy_version 824 (0.0007) +[2026-07-22 22:50:02,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.5, 300 sec: 13107.5). Total num frames: 393216. Throughput: 0: 12736.2. Samples: 446080. Policy #0 lag: (min: 63.0, avg: 91.6, max: 127.0) +[2026-07-22 22:50:02,287][543203] Avg episode reward: [(0, '2.806')] +[2026-07-22 22:50:02,419][543696] Saving new best policy, reward=2.806! +[2026-07-22 22:50:02,907][543983] Updated weights for policy 0, policy_version 834 (0.0007) +[2026-07-22 22:50:03,269][543983] Updated weights for policy 0, policy_version 847 (0.0008) +[2026-07-22 22:50:03,551][543983] Updated weights for policy 0, policy_version 857 (0.0007) +[2026-07-22 22:50:03,848][543983] Updated weights for policy 0, policy_version 867 (0.0007) +[2026-07-22 22:50:04,199][543983] Updated weights for policy 0, policy_version 878 (0.0006) +[2026-07-22 22:50:04,508][543983] Updated weights for policy 0, policy_version 889 (0.0007) +[2026-07-22 22:50:05,476][543983] Updated weights for policy 0, policy_version 901 (0.0007) +[2026-07-22 22:50:05,801][543983] Updated weights for policy 0, policy_version 911 (0.0007) +[2026-07-22 22:50:06,116][543983] Updated weights for policy 0, policy_version 922 (0.0006) +[2026-07-22 22:50:06,409][543983] Updated weights for policy 0, policy_version 933 (0.0006) +[2026-07-22 22:50:06,714][543983] Updated weights for policy 0, policy_version 943 (0.0007) +[2026-07-22 22:50:07,039][543983] Updated weights for policy 0, policy_version 954 (0.0008) +[2026-07-22 22:50:07,286][543203] Fps is (10 sec: 16384.0, 60 sec: 14043.7, 300 sec: 14043.7). Total num frames: 491520. Throughput: 0: 11951.8. Samples: 482304. Policy #0 lag: (min: 63.0, avg: 81.9, max: 127.0) +[2026-07-22 22:50:07,287][543203] Avg episode reward: [(0, '3.871')] +[2026-07-22 22:50:07,300][543696] Saving new best policy, reward=3.871! +[2026-07-22 22:50:07,868][543983] Updated weights for policy 0, policy_version 964 (0.0007) +[2026-07-22 22:50:08,162][543983] Updated weights for policy 0, policy_version 974 (0.0007) +[2026-07-22 22:50:08,445][543983] Updated weights for policy 0, policy_version 984 (0.0007) +[2026-07-22 22:50:08,715][543983] Updated weights for policy 0, policy_version 994 (0.0007) +[2026-07-22 22:50:09,017][543983] Updated weights for policy 0, policy_version 1004 (0.0006) +[2026-07-22 22:50:09,321][543983] Updated weights for policy 0, policy_version 1015 (0.0007) +[2026-07-22 22:50:10,442][543983] Updated weights for policy 0, policy_version 1027 (0.0007) +[2026-07-22 22:50:10,727][543983] Updated weights for policy 0, policy_version 1037 (0.0007) +[2026-07-22 22:50:11,002][543983] Updated weights for policy 0, policy_version 1047 (0.0007) +[2026-07-22 22:50:11,318][543983] Updated weights for policy 0, policy_version 1058 (0.0007) +[2026-07-22 22:50:11,612][543983] Updated weights for policy 0, policy_version 1069 (0.0007) +[2026-07-22 22:50:11,913][543983] Updated weights for policy 0, policy_version 1079 (0.0007) +[2026-07-22 22:50:12,286][543203] Fps is (10 sec: 16384.2, 60 sec: 13926.6, 300 sec: 13926.6). Total num frames: 557056. Throughput: 0: 12515.4. Samples: 564608. Policy #0 lag: (min: 63.0, avg: 78.9, max: 127.0) +[2026-07-22 22:50:12,287][543203] Avg episode reward: [(0, '3.930')] +[2026-07-22 22:50:12,294][543696] Saving new best policy, reward=3.930! +[2026-07-22 22:50:12,939][543983] Updated weights for policy 0, policy_version 1089 (0.0007) +[2026-07-22 22:50:13,220][543983] Updated weights for policy 0, policy_version 1099 (0.0007) +[2026-07-22 22:50:13,494][543983] Updated weights for policy 0, policy_version 1109 (0.0007) +[2026-07-22 22:50:13,796][543983] Updated weights for policy 0, policy_version 1119 (0.0007) +[2026-07-22 22:50:14,068][543983] Updated weights for policy 0, policy_version 1129 (0.0007) +[2026-07-22 22:50:14,377][543983] Updated weights for policy 0, policy_version 1140 (0.0008) +[2026-07-22 22:50:14,685][543983] Updated weights for policy 0, policy_version 1151 (0.0007) +[2026-07-22 22:50:15,789][543983] Updated weights for policy 0, policy_version 1161 (0.0006) +[2026-07-22 22:50:16,063][543983] Updated weights for policy 0, policy_version 1171 (0.0006) +[2026-07-22 22:50:16,419][543983] Updated weights for policy 0, policy_version 1184 (0.0007) +[2026-07-22 22:50:16,746][543983] Updated weights for policy 0, policy_version 1195 (0.0007) +[2026-07-22 22:50:17,019][543983] Updated weights for policy 0, policy_version 1205 (0.0007) +[2026-07-22 22:50:17,286][543203] Fps is (10 sec: 9830.4, 60 sec: 13107.4, 300 sec: 13107.4). Total num frames: 589824. Throughput: 0: 12677.9. Samples: 634496. Policy #0 lag: (min: 63.0, avg: 78.9, max: 127.0) +[2026-07-22 22:50:17,287][543203] Avg episode reward: [(0, '4.011')] +[2026-07-22 22:50:17,326][543696] Saving new best policy, reward=4.011! +[2026-07-22 22:50:17,329][543983] Updated weights for policy 0, policy_version 1216 (0.0007) +[2026-07-22 22:50:18,377][543983] Updated weights for policy 0, policy_version 1226 (0.0006) +[2026-07-22 22:50:18,661][543983] Updated weights for policy 0, policy_version 1236 (0.0006) +[2026-07-22 22:50:18,940][543983] Updated weights for policy 0, policy_version 1246 (0.0006) +[2026-07-22 22:50:19,237][543983] Updated weights for policy 0, policy_version 1256 (0.0006) +[2026-07-22 22:50:19,520][543983] Updated weights for policy 0, policy_version 1266 (0.0006) +[2026-07-22 22:50:19,776][543983] Updated weights for policy 0, policy_version 1276 (0.0007) +[2026-07-22 22:50:20,922][543983] Updated weights for policy 0, policy_version 1286 (0.0006) +[2026-07-22 22:50:21,187][543983] Updated weights for policy 0, policy_version 1296 (0.0007) +[2026-07-22 22:50:21,489][543983] Updated weights for policy 0, policy_version 1307 (0.0006) +[2026-07-22 22:50:21,781][543983] Updated weights for policy 0, policy_version 1317 (0.0006) +[2026-07-22 22:50:22,076][543983] Updated weights for policy 0, policy_version 1328 (0.0007) +[2026-07-22 22:50:22,286][543203] Fps is (10 sec: 9830.4, 60 sec: 13107.4, 300 sec: 13107.4). Total num frames: 655360. Throughput: 0: 13405.9. Samples: 669184. Policy #0 lag: (min: 1.0, avg: 24.7, max: 65.0) +[2026-07-22 22:50:22,287][543203] Avg episode reward: [(0, '4.118')] +[2026-07-22 22:50:22,388][543983] Updated weights for policy 0, policy_version 1339 (0.0006) +[2026-07-22 22:50:22,543][543696] Saving new best policy, reward=4.118! +[2026-07-22 22:50:23,566][543983] Updated weights for policy 0, policy_version 1350 (0.0006) +[2026-07-22 22:50:23,848][543983] Updated weights for policy 0, policy_version 1360 (0.0009) +[2026-07-22 22:50:24,140][543983] Updated weights for policy 0, policy_version 1370 (0.0007) +[2026-07-22 22:50:24,437][543983] Updated weights for policy 0, policy_version 1381 (0.0006) +[2026-07-22 22:50:24,719][543983] Updated weights for policy 0, policy_version 1391 (0.0006) +[2026-07-22 22:50:24,981][543983] Updated weights for policy 0, policy_version 1401 (0.0006) +[2026-07-22 22:50:26,214][543983] Updated weights for policy 0, policy_version 1412 (0.0006) +[2026-07-22 22:50:26,509][543983] Updated weights for policy 0, policy_version 1422 (0.0006) +[2026-07-22 22:50:26,771][543983] Updated weights for policy 0, policy_version 1432 (0.0006) +[2026-07-22 22:50:27,076][543983] Updated weights for policy 0, policy_version 1443 (0.0008) +[2026-07-22 22:50:27,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.4, 300 sec: 13107.4). Total num frames: 720896. Throughput: 0: 13294.9. Samples: 748672. Policy #0 lag: (min: 63.0, avg: 78.3, max: 127.0) +[2026-07-22 22:50:27,287][543203] Avg episode reward: [(0, '4.093')] +[2026-07-22 22:50:27,368][543983] Updated weights for policy 0, policy_version 1453 (0.0007) +[2026-07-22 22:50:27,631][543983] Updated weights for policy 0, policy_version 1463 (0.0006) +[2026-07-22 22:50:28,781][543983] Updated weights for policy 0, policy_version 1473 (0.0007) +[2026-07-22 22:50:29,047][543983] Updated weights for policy 0, policy_version 1483 (0.0006) +[2026-07-22 22:50:29,333][543983] Updated weights for policy 0, policy_version 1493 (0.0006) +[2026-07-22 22:50:29,616][543983] Updated weights for policy 0, policy_version 1503 (0.0006) +[2026-07-22 22:50:29,938][543983] Updated weights for policy 0, policy_version 1514 (0.0006) +[2026-07-22 22:50:30,202][543983] Updated weights for policy 0, policy_version 1524 (0.0007) +[2026-07-22 22:50:30,475][543983] Updated weights for policy 0, policy_version 1534 (0.0006) +[2026-07-22 22:50:31,668][543983] Updated weights for policy 0, policy_version 1544 (0.0006) +[2026-07-22 22:50:31,965][543983] Updated weights for policy 0, policy_version 1555 (0.0007) +[2026-07-22 22:50:32,242][543983] Updated weights for policy 0, policy_version 1565 (0.0006) +[2026-07-22 22:50:32,286][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.3, 300 sec: 13107.3). Total num frames: 786432. Throughput: 0: 13061.7. Samples: 823680. Policy #0 lag: (min: 63.0, avg: 78.0, max: 127.0) +[2026-07-22 22:50:32,287][543203] Avg episode reward: [(0, '4.253')] +[2026-07-22 22:50:32,524][543983] Updated weights for policy 0, policy_version 1575 (0.0006) +[2026-07-22 22:50:32,824][543983] Updated weights for policy 0, policy_version 1585 (0.0006) +[2026-07-22 22:50:33,137][543983] Updated weights for policy 0, policy_version 1596 (0.0006) +[2026-07-22 22:50:33,228][543696] Saving new best policy, reward=4.253! +[2026-07-22 22:50:34,295][543983] Updated weights for policy 0, policy_version 1606 (0.0006) +[2026-07-22 22:50:34,615][543983] Updated weights for policy 0, policy_version 1617 (0.0006) +[2026-07-22 22:50:34,890][543983] Updated weights for policy 0, policy_version 1627 (0.0006) +[2026-07-22 22:50:35,180][543983] Updated weights for policy 0, policy_version 1637 (0.0005) +[2026-07-22 22:50:35,499][543983] Updated weights for policy 0, policy_version 1649 (0.0006) +[2026-07-22 22:50:35,801][543983] Updated weights for policy 0, policy_version 1660 (0.0006) +[2026-07-22 22:50:36,991][543983] Updated weights for policy 0, policy_version 1670 (0.0007) +[2026-07-22 22:50:37,280][543983] Updated weights for policy 0, policy_version 1680 (0.0008) +[2026-07-22 22:50:37,286][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 13107.3). Total num frames: 851968. Throughput: 0: 12882.5. Samples: 858752. Policy #0 lag: (min: 45.0, avg: 59.4, max: 109.0) +[2026-07-22 22:50:37,287][543203] Avg episode reward: [(0, '4.662')] +[2026-07-22 22:50:37,594][543983] Updated weights for policy 0, policy_version 1692 (0.0007) +[2026-07-22 22:50:37,869][543983] Updated weights for policy 0, policy_version 1702 (0.0007) +[2026-07-22 22:50:38,201][543983] Updated weights for policy 0, policy_version 1713 (0.0006) +[2026-07-22 22:50:38,491][543983] Updated weights for policy 0, policy_version 1724 (0.0006) +[2026-07-22 22:50:38,612][543696] Saving new best policy, reward=4.662! +[2026-07-22 22:50:39,721][543983] Updated weights for policy 0, policy_version 1734 (0.0007) +[2026-07-22 22:50:40,017][543983] Updated weights for policy 0, policy_version 1745 (0.0006) +[2026-07-22 22:50:40,314][543983] Updated weights for policy 0, policy_version 1756 (0.0006) +[2026-07-22 22:50:40,613][543983] Updated weights for policy 0, policy_version 1766 (0.0007) +[2026-07-22 22:50:40,938][543983] Updated weights for policy 0, policy_version 1778 (0.0007) +[2026-07-22 22:50:41,213][543983] Updated weights for policy 0, policy_version 1788 (0.0006) +[2026-07-22 22:50:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 13107.3). Total num frames: 917504. Throughput: 0: 12498.5. Samples: 929152. Policy #0 lag: (min: 63.0, avg: 78.1, max: 127.0) +[2026-07-22 22:50:42,287][543203] Avg episode reward: [(0, '4.820')] +[2026-07-22 22:50:42,466][543983] Updated weights for policy 0, policy_version 1800 (0.0006) +[2026-07-22 22:50:42,746][543983] Updated weights for policy 0, policy_version 1810 (0.0007) +[2026-07-22 22:50:43,034][543983] Updated weights for policy 0, policy_version 1820 (0.0008) +[2026-07-22 22:50:43,309][543983] Updated weights for policy 0, policy_version 1830 (0.0007) +[2026-07-22 22:50:43,659][543983] Updated weights for policy 0, policy_version 1842 (0.0006) +[2026-07-22 22:50:43,915][543983] Updated weights for policy 0, policy_version 1852 (0.0006) +[2026-07-22 22:50:44,044][543696] Saving new best policy, reward=4.820! +[2026-07-22 22:50:45,153][543983] Updated weights for policy 0, policy_version 1863 (0.0006) +[2026-07-22 22:50:45,412][543983] Updated weights for policy 0, policy_version 1873 (0.0006) +[2026-07-22 22:50:45,720][543983] Updated weights for policy 0, policy_version 1884 (0.0008) +[2026-07-22 22:50:46,014][543983] Updated weights for policy 0, policy_version 1894 (0.0007) +[2026-07-22 22:50:46,296][543983] Updated weights for policy 0, policy_version 1905 (0.0007) +[2026-07-22 22:50:46,645][543983] Updated weights for policy 0, policy_version 1917 (0.0007) +[2026-07-22 22:50:47,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 13107.3). Total num frames: 983040. Throughput: 0: 12293.7. Samples: 999296. Policy #0 lag: (min: 63.0, avg: 78.0, max: 127.0) +[2026-07-22 22:50:47,287][543203] Avg episode reward: [(0, '5.151')] +[2026-07-22 22:50:47,294][543696] Saving new best policy, reward=5.151! +[2026-07-22 22:50:47,879][543983] Updated weights for policy 0, policy_version 1928 (0.0008) +[2026-07-22 22:50:48,153][543983] Updated weights for policy 0, policy_version 1938 (0.0006) +[2026-07-22 22:50:48,454][543983] Updated weights for policy 0, policy_version 1949 (0.0006) +[2026-07-22 22:50:48,733][543983] Updated weights for policy 0, policy_version 1959 (0.0007) +[2026-07-22 22:50:49,042][543983] Updated weights for policy 0, policy_version 1970 (0.0007) +[2026-07-22 22:50:49,320][543983] Updated weights for policy 0, policy_version 1980 (0.0007) +[2026-07-22 22:50:50,561][543983] Updated weights for policy 0, policy_version 1991 (0.0006) +[2026-07-22 22:50:50,832][543983] Updated weights for policy 0, policy_version 2001 (0.0006) +[2026-07-22 22:50:51,136][543983] Updated weights for policy 0, policy_version 2011 (0.0006) +[2026-07-22 22:50:51,421][543983] Updated weights for policy 0, policy_version 2022 (0.0006) +[2026-07-22 22:50:51,741][543983] Updated weights for policy 0, policy_version 2033 (0.0006) +[2026-07-22 22:50:52,041][543983] Updated weights for policy 0, policy_version 2044 (0.0007) +[2026-07-22 22:50:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 13107.3). Total num frames: 1048576. Throughput: 0: 12370.5. Samples: 1038976. Policy #0 lag: (min: 63.0, avg: 78.9, max: 127.0) +[2026-07-22 22:50:52,287][543203] Avg episode reward: [(0, '5.781')] +[2026-07-22 22:50:52,302][543696] Saving new best policy, reward=5.781! +[2026-07-22 22:50:53,264][543983] Updated weights for policy 0, policy_version 2054 (0.0007) +[2026-07-22 22:50:53,542][543983] Updated weights for policy 0, policy_version 2064 (0.0006) +[2026-07-22 22:50:53,825][543983] Updated weights for policy 0, policy_version 2074 (0.0006) +[2026-07-22 22:50:54,102][543983] Updated weights for policy 0, policy_version 2084 (0.0006) +[2026-07-22 22:50:54,418][543983] Updated weights for policy 0, policy_version 2095 (0.0006) +[2026-07-22 22:50:54,736][543983] Updated weights for policy 0, policy_version 2107 (0.0006) +[2026-07-22 22:50:55,973][543983] Updated weights for policy 0, policy_version 2118 (0.0007) +[2026-07-22 22:50:56,271][543983] Updated weights for policy 0, policy_version 2129 (0.0008) +[2026-07-22 22:50:56,635][543983] Updated weights for policy 0, policy_version 2142 (0.0006) +[2026-07-22 22:50:56,925][543983] Updated weights for policy 0, policy_version 2152 (0.0006) +[2026-07-22 22:50:57,200][543983] Updated weights for policy 0, policy_version 2162 (0.0007) +[2026-07-22 22:50:57,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12721.8). Total num frames: 1081344. Throughput: 0: 12285.1. Samples: 1117440. Policy #0 lag: (min: 63.0, avg: 78.9, max: 127.0) +[2026-07-22 22:50:57,287][543203] Avg episode reward: [(0, '5.577')] +[2026-07-22 22:50:57,474][543983] Updated weights for policy 0, policy_version 2172 (0.0006) +[2026-07-22 22:50:58,675][543983] Updated weights for policy 0, policy_version 2182 (0.0007) +[2026-07-22 22:50:58,962][543983] Updated weights for policy 0, policy_version 2192 (0.0007) +[2026-07-22 22:50:59,302][543983] Updated weights for policy 0, policy_version 2205 (0.0007) +[2026-07-22 22:50:59,578][543983] Updated weights for policy 0, policy_version 2215 (0.0007) +[2026-07-22 22:50:59,905][543983] Updated weights for policy 0, policy_version 2226 (0.0008) +[2026-07-22 22:51:00,197][543983] Updated weights for policy 0, policy_version 2237 (0.0007) +[2026-07-22 22:51:01,412][543983] Updated weights for policy 0, policy_version 2247 (0.0007) +[2026-07-22 22:51:01,694][543983] Updated weights for policy 0, policy_version 2257 (0.0007) +[2026-07-22 22:51:01,990][543983] Updated weights for policy 0, policy_version 2268 (0.0007) +[2026-07-22 22:51:02,274][543983] Updated weights for policy 0, policy_version 2278 (0.0007) +[2026-07-22 22:51:02,286][543203] Fps is (10 sec: 9830.3, 60 sec: 12561.1, 300 sec: 12743.2). Total num frames: 1146880. Throughput: 0: 12268.1. Samples: 1186560. Policy #0 lag: (min: 44.0, avg: 59.0, max: 108.0) +[2026-07-22 22:51:02,287][543203] Avg episode reward: [(0, '6.049')] +[2026-07-22 22:51:02,595][543983] Updated weights for policy 0, policy_version 2289 (0.0007) +[2026-07-22 22:51:02,856][543983] Updated weights for policy 0, policy_version 2299 (0.0006) +[2026-07-22 22:51:02,991][543696] Saving new best policy, reward=6.049! +[2026-07-22 22:51:04,132][543983] Updated weights for policy 0, policy_version 2310 (0.0007) +[2026-07-22 22:51:04,423][543983] Updated weights for policy 0, policy_version 2321 (0.0008) +[2026-07-22 22:51:04,701][543983] Updated weights for policy 0, policy_version 2331 (0.0007) +[2026-07-22 22:51:05,040][543983] Updated weights for policy 0, policy_version 2343 (0.0007) +[2026-07-22 22:51:05,329][543983] Updated weights for policy 0, policy_version 2353 (0.0007) +[2026-07-22 22:51:05,646][543983] Updated weights for policy 0, policy_version 2364 (0.0006) +[2026-07-22 22:51:06,928][543983] Updated weights for policy 0, policy_version 2376 (0.0007) +[2026-07-22 22:51:07,214][543983] Updated weights for policy 0, policy_version 2386 (0.0007) +[2026-07-22 22:51:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12014.9, 300 sec: 12762.4). Total num frames: 1212416. Throughput: 0: 12268.1. Samples: 1221248. Policy #0 lag: (min: 38.0, avg: 52.4, max: 102.0) +[2026-07-22 22:51:07,287][543203] Avg episode reward: [(0, '6.156')] +[2026-07-22 22:51:07,521][543983] Updated weights for policy 0, policy_version 2397 (0.0006) +[2026-07-22 22:51:07,791][543983] Updated weights for policy 0, policy_version 2407 (0.0007) +[2026-07-22 22:51:08,104][543983] Updated weights for policy 0, policy_version 2418 (0.0006) +[2026-07-22 22:51:08,432][543983] Updated weights for policy 0, policy_version 2430 (0.0006) +[2026-07-22 22:51:08,476][543696] Saving new best policy, reward=6.156! +[2026-07-22 22:51:09,650][543983] Updated weights for policy 0, policy_version 2440 (0.0007) +[2026-07-22 22:51:09,962][543983] Updated weights for policy 0, policy_version 2451 (0.0007) +[2026-07-22 22:51:10,241][543983] Updated weights for policy 0, policy_version 2461 (0.0007) +[2026-07-22 22:51:10,537][543983] Updated weights for policy 0, policy_version 2471 (0.0007) +[2026-07-22 22:51:10,812][543983] Updated weights for policy 0, policy_version 2481 (0.0007) +[2026-07-22 22:51:11,121][543983] Updated weights for policy 0, policy_version 2492 (0.0006) +[2026-07-22 22:51:12,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12014.9, 300 sec: 12779.6). Total num frames: 1277952. Throughput: 0: 12063.3. Samples: 1291520. Policy #0 lag: (min: 36.0, avg: 50.6, max: 100.0) +[2026-07-22 22:51:12,288][543203] Avg episode reward: [(0, '6.934')] +[2026-07-22 22:51:12,405][543983] Updated weights for policy 0, policy_version 2505 (0.0006) +[2026-07-22 22:51:12,762][543983] Updated weights for policy 0, policy_version 2518 (0.0006) +[2026-07-22 22:51:13,038][543983] Updated weights for policy 0, policy_version 2528 (0.0006) +[2026-07-22 22:51:13,341][543983] Updated weights for policy 0, policy_version 2539 (0.0007) +[2026-07-22 22:51:13,634][543983] Updated weights for policy 0, policy_version 2550 (0.0007) +[2026-07-22 22:51:13,905][543696] Saving new best policy, reward=6.934! +[2026-07-22 22:51:14,914][543983] Updated weights for policy 0, policy_version 2563 (0.0006) +[2026-07-22 22:51:15,269][543983] Updated weights for policy 0, policy_version 2576 (0.0007) +[2026-07-22 22:51:15,576][543983] Updated weights for policy 0, policy_version 2587 (0.0006) +[2026-07-22 22:51:15,861][543983] Updated weights for policy 0, policy_version 2597 (0.0006) +[2026-07-22 22:51:16,187][543983] Updated weights for policy 0, policy_version 2609 (0.0007) +[2026-07-22 22:51:16,528][543983] Updated weights for policy 0, policy_version 2621 (0.0006) +[2026-07-22 22:51:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12795.2). Total num frames: 1343488. Throughput: 0: 11958.1. Samples: 1361792. Policy #0 lag: (min: 63.0, avg: 77.4, max: 127.0) +[2026-07-22 22:51:17,287][543203] Avg episode reward: [(0, '7.121')] +[2026-07-22 22:51:17,295][543696] Saving new best policy, reward=7.121! +[2026-07-22 22:51:17,754][543983] Updated weights for policy 0, policy_version 2632 (0.0007) +[2026-07-22 22:51:18,065][543983] Updated weights for policy 0, policy_version 2643 (0.0006) +[2026-07-22 22:51:18,364][543983] Updated weights for policy 0, policy_version 2654 (0.0007) +[2026-07-22 22:51:18,673][543983] Updated weights for policy 0, policy_version 2665 (0.0007) +[2026-07-22 22:51:18,966][543983] Updated weights for policy 0, policy_version 2675 (0.0006) +[2026-07-22 22:51:19,235][543983] Updated weights for policy 0, policy_version 2685 (0.0007) +[2026-07-22 22:51:20,519][543983] Updated weights for policy 0, policy_version 2698 (0.0007) +[2026-07-22 22:51:20,790][543983] Updated weights for policy 0, policy_version 2708 (0.0006) +[2026-07-22 22:51:21,155][543983] Updated weights for policy 0, policy_version 2721 (0.0007) +[2026-07-22 22:51:21,441][543983] Updated weights for policy 0, policy_version 2731 (0.0007) +[2026-07-22 22:51:21,751][543983] Updated weights for policy 0, policy_version 2742 (0.0006) +[2026-07-22 22:51:22,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12809.4). Total num frames: 1409024. Throughput: 0: 12063.3. Samples: 1401600. Policy #0 lag: (min: 11.0, avg: 34.5, max: 75.0) +[2026-07-22 22:51:22,287][543203] Avg episode reward: [(0, '7.791')] +[2026-07-22 22:51:22,294][543696] Saving new best policy, reward=7.791! +[2026-07-22 22:51:22,986][543983] Updated weights for policy 0, policy_version 2754 (0.0006) +[2026-07-22 22:51:23,284][543983] Updated weights for policy 0, policy_version 2765 (0.0007) +[2026-07-22 22:51:23,591][543983] Updated weights for policy 0, policy_version 2776 (0.0007) +[2026-07-22 22:51:23,866][543983] Updated weights for policy 0, policy_version 2786 (0.0007) +[2026-07-22 22:51:24,148][543983] Updated weights for policy 0, policy_version 2796 (0.0007) +[2026-07-22 22:51:24,418][543983] Updated weights for policy 0, policy_version 2806 (0.0006) +[2026-07-22 22:51:24,700][543983] Updated weights for policy 0, policy_version 2816 (0.0006) +[2026-07-22 22:51:25,950][543983] Updated weights for policy 0, policy_version 2826 (0.0007) +[2026-07-22 22:51:26,275][543983] Updated weights for policy 0, policy_version 2837 (0.0007) +[2026-07-22 22:51:26,576][543983] Updated weights for policy 0, policy_version 2848 (0.0006) +[2026-07-22 22:51:26,866][543983] Updated weights for policy 0, policy_version 2858 (0.0007) +[2026-07-22 22:51:27,141][543983] Updated weights for policy 0, policy_version 2868 (0.0007) +[2026-07-22 22:51:27,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12014.9, 300 sec: 12537.4). Total num frames: 1441792. Throughput: 0: 12208.4. Samples: 1478528. Policy #0 lag: (min: 11.0, avg: 34.5, max: 75.0) +[2026-07-22 22:51:27,287][543203] Avg episode reward: [(0, '8.871')] +[2026-07-22 22:51:27,459][543696] Saving new best policy, reward=8.871! +[2026-07-22 22:51:27,464][543983] Updated weights for policy 0, policy_version 2880 (0.0008) +[2026-07-22 22:51:28,715][543983] Updated weights for policy 0, policy_version 2892 (0.0007) +[2026-07-22 22:51:28,998][543983] Updated weights for policy 0, policy_version 2902 (0.0006) +[2026-07-22 22:51:29,304][543983] Updated weights for policy 0, policy_version 2913 (0.0007) +[2026-07-22 22:51:29,665][543983] Updated weights for policy 0, policy_version 2926 (0.0007) +[2026-07-22 22:51:29,947][543983] Updated weights for policy 0, policy_version 2937 (0.0006) +[2026-07-22 22:51:31,254][543983] Updated weights for policy 0, policy_version 2948 (0.0006) +[2026-07-22 22:51:31,578][543983] Updated weights for policy 0, policy_version 2960 (0.0006) +[2026-07-22 22:51:31,868][543983] Updated weights for policy 0, policy_version 2971 (0.0006) +[2026-07-22 22:51:32,225][543983] Updated weights for policy 0, policy_version 2984 (0.0006) +[2026-07-22 22:51:32,286][543203] Fps is (10 sec: 9830.3, 60 sec: 12014.9, 300 sec: 12561.1). Total num frames: 1507328. Throughput: 0: 12205.5. Samples: 1548544. Policy #0 lag: (min: 20.0, avg: 33.8, max: 84.0) +[2026-07-22 22:51:32,287][543203] Avg episode reward: [(0, '8.526')] +[2026-07-22 22:51:32,520][543983] Updated weights for policy 0, policy_version 2994 (0.0006) +[2026-07-22 22:51:32,813][543983] Updated weights for policy 0, policy_version 3004 (0.0006) +[2026-07-22 22:51:34,000][543983] Updated weights for policy 0, policy_version 3014 (0.0006) +[2026-07-22 22:51:34,307][543983] Updated weights for policy 0, policy_version 3025 (0.0006) +[2026-07-22 22:51:34,681][543983] Updated weights for policy 0, policy_version 3038 (0.0007) +[2026-07-22 22:51:34,969][543983] Updated weights for policy 0, policy_version 3048 (0.0007) +[2026-07-22 22:51:35,263][543983] Updated weights for policy 0, policy_version 3059 (0.0007) +[2026-07-22 22:51:35,583][543983] Updated weights for policy 0, policy_version 3071 (0.0006) +[2026-07-22 22:51:36,774][543983] Updated weights for policy 0, policy_version 3081 (0.0007) +[2026-07-22 22:51:37,077][543983] Updated weights for policy 0, policy_version 3092 (0.0007) +[2026-07-22 22:51:37,286][543203] Fps is (10 sec: 13107.1, 60 sec: 12014.9, 300 sec: 12583.0). Total num frames: 1572864. Throughput: 0: 12103.1. Samples: 1583616. Policy #0 lag: (min: 40.0, avg: 65.1, max: 104.0) +[2026-07-22 22:51:37,287][543203] Avg episode reward: [(0, '10.167')] +[2026-07-22 22:51:37,410][543983] Updated weights for policy 0, policy_version 3104 (0.0007) +[2026-07-22 22:51:37,714][543983] Updated weights for policy 0, policy_version 3115 (0.0006) +[2026-07-22 22:51:38,036][543983] Updated weights for policy 0, policy_version 3127 (0.0007) +[2026-07-22 22:51:38,297][543696] Saving new best policy, reward=10.167! +[2026-07-22 22:51:39,381][543983] Updated weights for policy 0, policy_version 3139 (0.0008) +[2026-07-22 22:51:39,659][543983] Updated weights for policy 0, policy_version 3149 (0.0006) +[2026-07-22 22:51:39,964][543983] Updated weights for policy 0, policy_version 3160 (0.0006) +[2026-07-22 22:51:40,240][543983] Updated weights for policy 0, policy_version 3170 (0.0006) +[2026-07-22 22:51:40,537][543983] Updated weights for policy 0, policy_version 3180 (0.0006) +[2026-07-22 22:51:40,842][543983] Updated weights for policy 0, policy_version 3192 (0.0006) +[2026-07-22 22:51:42,117][543983] Updated weights for policy 0, policy_version 3204 (0.0006) +[2026-07-22 22:51:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12014.9, 300 sec: 12603.1). Total num frames: 1638400. Throughput: 0: 11926.8. Samples: 1654144. Policy #0 lag: (min: 63.0, avg: 78.3, max: 127.0) +[2026-07-22 22:51:42,287][543203] Avg episode reward: [(0, '11.249')] +[2026-07-22 22:51:42,379][543983] Updated weights for policy 0, policy_version 3214 (0.0007) +[2026-07-22 22:51:42,679][543983] Updated weights for policy 0, policy_version 3225 (0.0006) +[2026-07-22 22:51:43,013][543983] Updated weights for policy 0, policy_version 3237 (0.0007) +[2026-07-22 22:51:43,327][543983] Updated weights for policy 0, policy_version 3248 (0.0006) +[2026-07-22 22:51:43,600][543983] Updated weights for policy 0, policy_version 3258 (0.0006) +[2026-07-22 22:51:43,759][543696] Saving new best policy, reward=11.249! +[2026-07-22 22:51:44,829][543983] Updated weights for policy 0, policy_version 3268 (0.0006) +[2026-07-22 22:51:45,113][543983] Updated weights for policy 0, policy_version 3278 (0.0006) +[2026-07-22 22:51:45,474][543983] Updated weights for policy 0, policy_version 3290 (0.0007) +[2026-07-22 22:51:45,783][543983] Updated weights for policy 0, policy_version 3302 (0.0007) +[2026-07-22 22:51:46,152][543983] Updated weights for policy 0, policy_version 3315 (0.0006) +[2026-07-22 22:51:46,445][543983] Updated weights for policy 0, policy_version 3326 (0.0006) +[2026-07-22 22:51:47,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12014.9, 300 sec: 12621.8). Total num frames: 1703936. Throughput: 0: 12026.3. Samples: 1727744. Policy #0 lag: (min: 22.0, avg: 35.3, max: 86.0) +[2026-07-22 22:51:47,287][543203] Avg episode reward: [(0, '11.556')] +[2026-07-22 22:51:47,699][543983] Updated weights for policy 0, policy_version 3339 (0.0006) +[2026-07-22 22:51:48,062][543983] Updated weights for policy 0, policy_version 3352 (0.0006) +[2026-07-22 22:51:48,353][543983] Updated weights for policy 0, policy_version 3363 (0.0006) +[2026-07-22 22:51:48,630][543983] Updated weights for policy 0, policy_version 3373 (0.0006) +[2026-07-22 22:51:48,913][543983] Updated weights for policy 0, policy_version 3383 (0.0006) +[2026-07-22 22:51:49,150][543696] Saving new best policy, reward=11.556! +[2026-07-22 22:51:50,133][543983] Updated weights for policy 0, policy_version 3393 (0.0006) +[2026-07-22 22:51:50,422][543983] Updated weights for policy 0, policy_version 3403 (0.0006) +[2026-07-22 22:51:50,718][543983] Updated weights for policy 0, policy_version 3414 (0.0007) +[2026-07-22 22:51:51,004][543983] Updated weights for policy 0, policy_version 3424 (0.0006) +[2026-07-22 22:51:51,265][543983] Updated weights for policy 0, policy_version 3434 (0.0006) +[2026-07-22 22:51:51,589][543983] Updated weights for policy 0, policy_version 3446 (0.0008) +[2026-07-22 22:51:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12014.9, 300 sec: 12639.1). Total num frames: 1769472. Throughput: 0: 12137.2. Samples: 1767424. Policy #0 lag: (min: 63.0, avg: 76.4, max: 127.0) +[2026-07-22 22:51:52,287][543203] Avg episode reward: [(0, '13.137')] +[2026-07-22 22:51:52,301][543696] Saving new best policy, reward=13.137! +[2026-07-22 22:51:52,861][543983] Updated weights for policy 0, policy_version 3457 (0.0006) +[2026-07-22 22:51:53,184][543983] Updated weights for policy 0, policy_version 3468 (0.0007) +[2026-07-22 22:51:53,521][543983] Updated weights for policy 0, policy_version 3480 (0.0006) +[2026-07-22 22:51:53,820][543983] Updated weights for policy 0, policy_version 3491 (0.0006) +[2026-07-22 22:51:54,144][543983] Updated weights for policy 0, policy_version 3503 (0.0006) +[2026-07-22 22:51:54,430][543983] Updated weights for policy 0, policy_version 3513 (0.0007) +[2026-07-22 22:51:55,585][543983] Updated weights for policy 0, policy_version 3523 (0.0007) +[2026-07-22 22:51:55,921][543983] Updated weights for policy 0, policy_version 3535 (0.0011) +[2026-07-22 22:51:56,227][543983] Updated weights for policy 0, policy_version 3546 (0.0006) +[2026-07-22 22:51:56,526][543983] Updated weights for policy 0, policy_version 3557 (0.0006) +[2026-07-22 22:51:56,804][543983] Updated weights for policy 0, policy_version 3567 (0.0007) +[2026-07-22 22:51:57,086][543983] Updated weights for policy 0, policy_version 3577 (0.0007) +[2026-07-22 22:51:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12655.3). Total num frames: 1835008. Throughput: 0: 12239.7. Samples: 1842304. Policy #0 lag: (min: 63.0, avg: 76.4, max: 127.0) +[2026-07-22 22:51:57,287][543203] Avg episode reward: [(0, '14.492')] +[2026-07-22 22:51:57,294][543696] Saving new best policy, reward=14.492! +[2026-07-22 22:51:58,319][543983] Updated weights for policy 0, policy_version 3589 (0.0007) +[2026-07-22 22:51:58,629][543983] Updated weights for policy 0, policy_version 3600 (0.0006) +[2026-07-22 22:51:58,938][543983] Updated weights for policy 0, policy_version 3611 (0.0006) +[2026-07-22 22:51:59,268][543983] Updated weights for policy 0, policy_version 3623 (0.0007) +[2026-07-22 22:51:59,693][543983] Updated weights for policy 0, policy_version 3639 (0.0008) +[2026-07-22 22:52:00,930][543983] Updated weights for policy 0, policy_version 3650 (0.0007) +[2026-07-22 22:52:01,228][543983] Updated weights for policy 0, policy_version 3661 (0.0006) +[2026-07-22 22:52:01,516][543983] Updated weights for policy 0, policy_version 3671 (0.0006) +[2026-07-22 22:52:01,844][543983] Updated weights for policy 0, policy_version 3683 (0.0008) +[2026-07-22 22:52:02,139][543983] Updated weights for policy 0, policy_version 3694 (0.0008) +[2026-07-22 22:52:02,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12014.9, 300 sec: 12451.9). Total num frames: 1867776. Throughput: 0: 12208.3. Samples: 1911168. Policy #0 lag: (min: 12.0, avg: 27.3, max: 76.0) +[2026-07-22 22:52:02,287][543203] Avg episode reward: [(0, '15.198')] +[2026-07-22 22:52:02,479][543983] Updated weights for policy 0, policy_version 3706 (0.0007) +[2026-07-22 22:52:02,640][543696] Saving new best policy, reward=15.198! +[2026-07-22 22:52:03,715][543983] Updated weights for policy 0, policy_version 3717 (0.0007) +[2026-07-22 22:52:04,031][543983] Updated weights for policy 0, policy_version 3728 (0.0007) +[2026-07-22 22:52:04,317][543983] Updated weights for policy 0, policy_version 3738 (0.0007) +[2026-07-22 22:52:04,632][543983] Updated weights for policy 0, policy_version 3749 (0.0007) +[2026-07-22 22:52:04,952][543983] Updated weights for policy 0, policy_version 3761 (0.0006) +[2026-07-22 22:52:05,265][543983] Updated weights for policy 0, policy_version 3772 (0.0008) +[2026-07-22 22:52:06,483][543983] Updated weights for policy 0, policy_version 3784 (0.0006) +[2026-07-22 22:52:06,763][543983] Updated weights for policy 0, policy_version 3794 (0.0006) +[2026-07-22 22:52:07,082][543983] Updated weights for policy 0, policy_version 3806 (0.0007) +[2026-07-22 22:52:07,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12014.9, 300 sec: 12473.0). Total num frames: 1933312. Throughput: 0: 12108.8. Samples: 1946496. Policy #0 lag: (min: 26.0, avg: 55.1, max: 90.0) +[2026-07-22 22:52:07,287][543203] Avg episode reward: [(0, '17.520')] +[2026-07-22 22:52:07,379][543983] Updated weights for policy 0, policy_version 3816 (0.0006) +[2026-07-22 22:52:07,671][543983] Updated weights for policy 0, policy_version 3827 (0.0007) +[2026-07-22 22:52:07,945][543983] Updated weights for policy 0, policy_version 3837 (0.0007) +[2026-07-22 22:52:08,015][543696] Saving new best policy, reward=17.520! +[2026-07-22 22:52:09,170][543983] Updated weights for policy 0, policy_version 3848 (0.0007) +[2026-07-22 22:52:09,512][543983] Updated weights for policy 0, policy_version 3860 (0.0006) +[2026-07-22 22:52:09,823][543983] Updated weights for policy 0, policy_version 3871 (0.0007) +[2026-07-22 22:52:10,125][543983] Updated weights for policy 0, policy_version 3882 (0.0007) +[2026-07-22 22:52:10,437][543983] Updated weights for policy 0, policy_version 3893 (0.0007) +[2026-07-22 22:52:10,731][543983] Updated weights for policy 0, policy_version 3904 (0.0007) +[2026-07-22 22:52:12,022][543983] Updated weights for policy 0, policy_version 3917 (0.0007) +[2026-07-22 22:52:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12014.9, 300 sec: 12492.8). Total num frames: 1998848. Throughput: 0: 11946.7. Samples: 2016128. Policy #0 lag: (min: 30.0, avg: 43.9, max: 94.0) +[2026-07-22 22:52:12,287][543203] Avg episode reward: [(0, '20.059')] +[2026-07-22 22:52:12,359][543983] Updated weights for policy 0, policy_version 3929 (0.0007) +[2026-07-22 22:52:12,646][543983] Updated weights for policy 0, policy_version 3939 (0.0007) +[2026-07-22 22:52:12,948][543983] Updated weights for policy 0, policy_version 3950 (0.0007) +[2026-07-22 22:52:13,321][543983] Updated weights for policy 0, policy_version 3963 (0.0008) +[2026-07-22 22:52:13,445][543696] Saving new best policy, reward=20.059! +[2026-07-22 22:52:14,490][543983] Updated weights for policy 0, policy_version 3973 (0.0007) +[2026-07-22 22:52:14,788][543983] Updated weights for policy 0, policy_version 3983 (0.0006) +[2026-07-22 22:52:15,084][543983] Updated weights for policy 0, policy_version 3994 (0.0007) +[2026-07-22 22:52:15,370][543983] Updated weights for policy 0, policy_version 4004 (0.0007) +[2026-07-22 22:52:15,666][543983] Updated weights for policy 0, policy_version 4015 (0.0007) +[2026-07-22 22:52:15,974][543983] Updated weights for policy 0, policy_version 4026 (0.0007) +[2026-07-22 22:52:17,181][543983] Updated weights for policy 0, policy_version 4036 (0.0006) +[2026-07-22 22:52:17,286][543203] Fps is (10 sec: 13107.1, 60 sec: 12014.9, 300 sec: 12511.5). Total num frames: 2064384. Throughput: 0: 12185.6. Samples: 2096896. Policy #0 lag: (min: 5.0, avg: 18.7, max: 69.0) +[2026-07-22 22:52:17,287][543203] Avg episode reward: [(0, '23.241')] +[2026-07-22 22:52:17,489][543983] Updated weights for policy 0, policy_version 4047 (0.0007) +[2026-07-22 22:52:17,762][543983] Updated weights for policy 0, policy_version 4057 (0.0007) +[2026-07-22 22:52:18,050][543983] Updated weights for policy 0, policy_version 4067 (0.0007) +[2026-07-22 22:52:18,358][543983] Updated weights for policy 0, policy_version 4079 (0.0007) +[2026-07-22 22:52:18,703][543983] Updated weights for policy 0, policy_version 4091 (0.0007) +[2026-07-22 22:52:18,825][543696] Saving new best policy, reward=23.241! +[2026-07-22 22:52:19,994][543983] Updated weights for policy 0, policy_version 4103 (0.0007) +[2026-07-22 22:52:20,287][543983] Updated weights for policy 0, policy_version 4114 (0.0007) +[2026-07-22 22:52:20,595][543983] Updated weights for policy 0, policy_version 4124 (0.0007) +[2026-07-22 22:52:20,921][543983] Updated weights for policy 0, policy_version 4136 (0.0006) +[2026-07-22 22:52:21,236][543983] Updated weights for policy 0, policy_version 4147 (0.0006) +[2026-07-22 22:52:21,511][543983] Updated weights for policy 0, policy_version 4157 (0.0007) +[2026-07-22 22:52:22,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12014.9, 300 sec: 12529.0). Total num frames: 2129920. Throughput: 0: 12288.0. Samples: 2136576. Policy #0 lag: (min: 19.0, avg: 53.2, max: 83.0) +[2026-07-22 22:52:22,287][543203] Avg episode reward: [(0, '23.674')] +[2026-07-22 22:52:22,647][543983] Updated weights for policy 0, policy_version 4167 (0.0006) +[2026-07-22 22:52:22,950][543983] Updated weights for policy 0, policy_version 4178 (0.0006) +[2026-07-22 22:52:23,219][543983] Updated weights for policy 0, policy_version 4188 (0.0006) +[2026-07-22 22:52:23,548][543983] Updated weights for policy 0, policy_version 4199 (0.0006) +[2026-07-22 22:52:23,857][543983] Updated weights for policy 0, policy_version 4210 (0.0005) +[2026-07-22 22:52:24,121][543983] Updated weights for policy 0, policy_version 4220 (0.0006) +[2026-07-22 22:52:24,223][543696] Saving new best policy, reward=23.674! +[2026-07-22 22:52:25,323][543983] Updated weights for policy 0, policy_version 4230 (0.0006) +[2026-07-22 22:52:25,627][543983] Updated weights for policy 0, policy_version 4241 (0.0008) +[2026-07-22 22:52:25,955][543983] Updated weights for policy 0, policy_version 4253 (0.0006) +[2026-07-22 22:52:26,311][543983] Updated weights for policy 0, policy_version 4265 (0.0006) +[2026-07-22 22:52:26,647][543983] Updated weights for policy 0, policy_version 4277 (0.0006) +[2026-07-22 22:52:26,945][543983] Updated weights for policy 0, policy_version 4288 (0.0006) +[2026-07-22 22:52:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12545.5). Total num frames: 2195456. Throughput: 0: 12290.8. Samples: 2207232. Policy #0 lag: (min: 31.0, avg: 45.5, max: 95.0) +[2026-07-22 22:52:27,287][543203] Avg episode reward: [(0, '26.509')] +[2026-07-22 22:52:27,294][543696] Saving new best policy, reward=26.509! +[2026-07-22 22:52:28,118][543983] Updated weights for policy 0, policy_version 4300 (0.0006) +[2026-07-22 22:52:28,446][543983] Updated weights for policy 0, policy_version 4312 (0.0007) +[2026-07-22 22:52:28,752][543983] Updated weights for policy 0, policy_version 4323 (0.0008) +[2026-07-22 22:52:29,105][543983] Updated weights for policy 0, policy_version 4335 (0.0007) +[2026-07-22 22:52:29,387][543983] Updated weights for policy 0, policy_version 4345 (0.0006) +[2026-07-22 22:52:30,514][543983] Updated weights for policy 0, policy_version 4355 (0.0006) +[2026-07-22 22:52:30,795][543983] Updated weights for policy 0, policy_version 4365 (0.0006) +[2026-07-22 22:52:31,066][543983] Updated weights for policy 0, policy_version 4375 (0.0007) +[2026-07-22 22:52:31,376][543983] Updated weights for policy 0, policy_version 4386 (0.0006) +[2026-07-22 22:52:31,746][543983] Updated weights for policy 0, policy_version 4399 (0.0006) +[2026-07-22 22:52:32,057][543983] Updated weights for policy 0, policy_version 4410 (0.0007) +[2026-07-22 22:52:32,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12561.1). Total num frames: 2260992. Throughput: 0: 12208.3. Samples: 2277120. Policy #0 lag: (min: 31.0, avg: 45.5, max: 95.0) +[2026-07-22 22:52:32,287][543203] Avg episode reward: [(0, '29.719')] +[2026-07-22 22:52:32,293][543696] Saving new best policy, reward=29.719! +[2026-07-22 22:52:33,172][543983] Updated weights for policy 0, policy_version 4420 (0.0007) +[2026-07-22 22:52:33,484][543983] Updated weights for policy 0, policy_version 4431 (0.0006) +[2026-07-22 22:52:33,761][543983] Updated weights for policy 0, policy_version 4441 (0.0006) +[2026-07-22 22:52:34,128][543983] Updated weights for policy 0, policy_version 4454 (0.0007) +[2026-07-22 22:52:34,411][543983] Updated weights for policy 0, policy_version 4464 (0.0006) +[2026-07-22 22:52:34,748][543983] Updated weights for policy 0, policy_version 4476 (0.0007) +[2026-07-22 22:52:35,882][543983] Updated weights for policy 0, policy_version 4486 (0.0007) +[2026-07-22 22:52:36,214][543983] Updated weights for policy 0, policy_version 4498 (0.0006) +[2026-07-22 22:52:36,528][543983] Updated weights for policy 0, policy_version 4509 (0.0007) +[2026-07-22 22:52:36,806][543983] Updated weights for policy 0, policy_version 4519 (0.0006) +[2026-07-22 22:52:37,082][543983] Updated weights for policy 0, policy_version 4529 (0.0007) +[2026-07-22 22:52:37,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12014.9, 300 sec: 12398.7). Total num frames: 2293760. Throughput: 0: 12097.4. Samples: 2311808. Policy #0 lag: (min: 37.0, avg: 51.1, max: 101.0) +[2026-07-22 22:52:37,287][543203] Avg episode reward: [(0, '31.648')] +[2026-07-22 22:52:37,383][543983] Updated weights for policy 0, policy_version 4540 (0.0007) +[2026-07-22 22:52:37,496][543696] Saving new best policy, reward=31.648! +[2026-07-22 22:52:38,548][543983] Updated weights for policy 0, policy_version 4551 (0.0008) +[2026-07-22 22:52:38,868][543983] Updated weights for policy 0, policy_version 4562 (0.0007) +[2026-07-22 22:52:39,180][543983] Updated weights for policy 0, policy_version 4573 (0.0008) +[2026-07-22 22:52:39,480][543983] Updated weights for policy 0, policy_version 4584 (0.0008) +[2026-07-22 22:52:39,770][543983] Updated weights for policy 0, policy_version 4594 (0.0006) +[2026-07-22 22:52:40,056][543983] Updated weights for policy 0, policy_version 4604 (0.0006) +[2026-07-22 22:52:41,141][543983] Updated weights for policy 0, policy_version 4614 (0.0006) +[2026-07-22 22:52:41,428][543983] Updated weights for policy 0, policy_version 4624 (0.0006) +[2026-07-22 22:52:41,705][543983] Updated weights for policy 0, policy_version 4634 (0.0006) +[2026-07-22 22:52:42,009][543983] Updated weights for policy 0, policy_version 4645 (0.0005) +[2026-07-22 22:52:42,286][543203] Fps is (10 sec: 9830.5, 60 sec: 12014.9, 300 sec: 12417.4). Total num frames: 2359296. Throughput: 0: 12233.9. Samples: 2392832. Policy #0 lag: (min: 37.0, avg: 51.1, max: 101.0) +[2026-07-22 22:52:42,287][543203] Avg episode reward: [(0, '39.287')] +[2026-07-22 22:52:42,298][543983] Updated weights for policy 0, policy_version 4655 (0.0007) +[2026-07-22 22:52:42,607][543983] Updated weights for policy 0, policy_version 4666 (0.0006) +[2026-07-22 22:52:42,755][543696] Saving new best policy, reward=39.287! +[2026-07-22 22:52:43,742][543983] Updated weights for policy 0, policy_version 4676 (0.0006) +[2026-07-22 22:52:44,045][543983] Updated weights for policy 0, policy_version 4687 (0.0006) +[2026-07-22 22:52:44,323][543983] Updated weights for policy 0, policy_version 4697 (0.0006) +[2026-07-22 22:52:44,609][543983] Updated weights for policy 0, policy_version 4707 (0.0006) +[2026-07-22 22:52:44,885][543983] Updated weights for policy 0, policy_version 4717 (0.0006) +[2026-07-22 22:52:45,168][543983] Updated weights for policy 0, policy_version 4727 (0.0007) +[2026-07-22 22:52:46,262][543983] Updated weights for policy 0, policy_version 4738 (0.0006) +[2026-07-22 22:52:46,557][543983] Updated weights for policy 0, policy_version 4749 (0.0008) +[2026-07-22 22:52:46,893][543983] Updated weights for policy 0, policy_version 4760 (0.0007) +[2026-07-22 22:52:47,191][543983] Updated weights for policy 0, policy_version 4771 (0.0006) +[2026-07-22 22:52:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12014.9, 300 sec: 12435.1). Total num frames: 2424832. Throughput: 0: 12313.6. Samples: 2465280. Policy #0 lag: (min: 41.0, avg: 73.9, max: 105.0) +[2026-07-22 22:52:47,287][543203] Avg episode reward: [(0, '43.920')] +[2026-07-22 22:52:47,478][543983] Updated weights for policy 0, policy_version 4781 (0.0007) +[2026-07-22 22:52:47,788][543983] Updated weights for policy 0, policy_version 4792 (0.0007) +[2026-07-22 22:52:48,007][543696] Saving new best policy, reward=43.920! +[2026-07-22 22:52:48,908][543983] Updated weights for policy 0, policy_version 4802 (0.0007) +[2026-07-22 22:52:49,187][543983] Updated weights for policy 0, policy_version 4812 (0.0006) +[2026-07-22 22:52:49,472][543983] Updated weights for policy 0, policy_version 4822 (0.0007) +[2026-07-22 22:52:49,751][543983] Updated weights for policy 0, policy_version 4832 (0.0006) +[2026-07-22 22:52:50,032][543983] Updated weights for policy 0, policy_version 4842 (0.0007) +[2026-07-22 22:52:50,335][543983] Updated weights for policy 0, policy_version 4853 (0.0006) +[2026-07-22 22:52:50,650][543983] Updated weights for policy 0, policy_version 4864 (0.0006) +[2026-07-22 22:52:51,814][543983] Updated weights for policy 0, policy_version 4874 (0.0007) +[2026-07-22 22:52:52,117][543983] Updated weights for policy 0, policy_version 4885 (0.0007) +[2026-07-22 22:52:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12014.9, 300 sec: 12451.9). Total num frames: 2490368. Throughput: 0: 12322.1. Samples: 2500992. Policy #0 lag: (min: 63.0, avg: 78.2, max: 127.0) +[2026-07-22 22:52:52,287][543203] Avg episode reward: [(0, '43.278')] +[2026-07-22 22:52:52,418][543983] Updated weights for policy 0, policy_version 4896 (0.0006) +[2026-07-22 22:52:52,757][543983] Updated weights for policy 0, policy_version 4908 (0.0006) +[2026-07-22 22:52:53,042][543983] Updated weights for policy 0, policy_version 4918 (0.0006) +[2026-07-22 22:52:54,220][543983] Updated weights for policy 0, policy_version 4929 (0.0006) +[2026-07-22 22:52:54,531][543983] Updated weights for policy 0, policy_version 4940 (0.0006) +[2026-07-22 22:52:54,837][543983] Updated weights for policy 0, policy_version 4950 (0.0006) +[2026-07-22 22:52:55,114][543983] Updated weights for policy 0, policy_version 4960 (0.0007) +[2026-07-22 22:52:55,398][543983] Updated weights for policy 0, policy_version 4970 (0.0008) +[2026-07-22 22:52:55,763][543983] Updated weights for policy 0, policy_version 4983 (0.0008) +[2026-07-22 22:52:56,913][543983] Updated weights for policy 0, policy_version 4995 (0.0008) +[2026-07-22 22:52:57,196][543983] Updated weights for policy 0, policy_version 5005 (0.0006) +[2026-07-22 22:52:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12014.9, 300 sec: 12467.9). Total num frames: 2555904. Throughput: 0: 12390.4. Samples: 2573696. Policy #0 lag: (min: 63.0, avg: 78.2, max: 127.0) +[2026-07-22 22:52:57,287][543203] Avg episode reward: [(0, '53.350')] +[2026-07-22 22:52:57,472][543983] Updated weights for policy 0, policy_version 5015 (0.0006) +[2026-07-22 22:52:57,751][543983] Updated weights for policy 0, policy_version 5025 (0.0006) +[2026-07-22 22:52:58,054][543983] Updated weights for policy 0, policy_version 5036 (0.0007) +[2026-07-22 22:52:58,348][543983] Updated weights for policy 0, policy_version 5046 (0.0007) +[2026-07-22 22:52:58,636][543696] Saving new best policy, reward=53.350! +[2026-07-22 22:52:58,637][543983] Updated weights for policy 0, policy_version 5056 (0.0006) +[2026-07-22 22:52:59,790][543983] Updated weights for policy 0, policy_version 5066 (0.0007) +[2026-07-22 22:53:00,051][543983] Updated weights for policy 0, policy_version 5076 (0.0007) +[2026-07-22 22:53:00,330][543983] Updated weights for policy 0, policy_version 5086 (0.0007) +[2026-07-22 22:53:00,644][543983] Updated weights for policy 0, policy_version 5097 (0.0007) +[2026-07-22 22:53:00,988][543983] Updated weights for policy 0, policy_version 5109 (0.0006) +[2026-07-22 22:53:01,283][543983] Updated weights for policy 0, policy_version 5119 (0.0007) +[2026-07-22 22:53:02,286][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12483.1). Total num frames: 2621440. Throughput: 0: 12356.3. Samples: 2652928. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 22:53:02,287][543203] Avg episode reward: [(0, '52.018')] +[2026-07-22 22:53:02,456][543983] Updated weights for policy 0, policy_version 5129 (0.0006) +[2026-07-22 22:53:02,764][543983] Updated weights for policy 0, policy_version 5140 (0.0007) +[2026-07-22 22:53:03,083][543983] Updated weights for policy 0, policy_version 5151 (0.0007) +[2026-07-22 22:53:03,356][543983] Updated weights for policy 0, policy_version 5161 (0.0008) +[2026-07-22 22:53:03,683][543983] Updated weights for policy 0, policy_version 5173 (0.0007) +[2026-07-22 22:53:03,974][543983] Updated weights for policy 0, policy_version 5183 (0.0007) +[2026-07-22 22:53:05,168][543983] Updated weights for policy 0, policy_version 5194 (0.0008) +[2026-07-22 22:53:05,485][543983] Updated weights for policy 0, policy_version 5205 (0.0007) +[2026-07-22 22:53:05,847][543983] Updated weights for policy 0, policy_version 5217 (0.0007) +[2026-07-22 22:53:06,179][543983] Updated weights for policy 0, policy_version 5229 (0.0006) +[2026-07-22 22:53:06,459][543983] Updated weights for policy 0, policy_version 5239 (0.0006) +[2026-07-22 22:53:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12497.6). Total num frames: 2686976. Throughput: 0: 12413.2. Samples: 2695168. Policy #0 lag: (min: 27.0, avg: 72.2, max: 91.0) +[2026-07-22 22:53:07,287][543203] Avg episode reward: [(0, '47.911')] +[2026-07-22 22:53:07,530][543983] Updated weights for policy 0, policy_version 5249 (0.0006) +[2026-07-22 22:53:07,830][543983] Updated weights for policy 0, policy_version 5259 (0.0007) +[2026-07-22 22:53:08,133][543983] Updated weights for policy 0, policy_version 5270 (0.0008) +[2026-07-22 22:53:08,441][543983] Updated weights for policy 0, policy_version 5281 (0.0007) +[2026-07-22 22:53:08,735][543983] Updated weights for policy 0, policy_version 5291 (0.0007) +[2026-07-22 22:53:09,051][543983] Updated weights for policy 0, policy_version 5302 (0.0007) +[2026-07-22 22:53:10,167][543983] Updated weights for policy 0, policy_version 5313 (0.0007) +[2026-07-22 22:53:10,494][543983] Updated weights for policy 0, policy_version 5324 (0.0007) +[2026-07-22 22:53:10,819][543983] Updated weights for policy 0, policy_version 5336 (0.0007) +[2026-07-22 22:53:11,123][543983] Updated weights for policy 0, policy_version 5347 (0.0007) +[2026-07-22 22:53:11,400][543983] Updated weights for policy 0, policy_version 5357 (0.0007) +[2026-07-22 22:53:11,684][543983] Updated weights for policy 0, policy_version 5367 (0.0007) +[2026-07-22 22:53:12,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12511.5). Total num frames: 2752512. Throughput: 0: 12435.9. Samples: 2766848. Policy #0 lag: (min: 27.0, avg: 72.2, max: 91.0) +[2026-07-22 22:53:12,287][543203] Avg episode reward: [(0, '60.533')] +[2026-07-22 22:53:12,294][543696] Saving new best policy, reward=60.533! +[2026-07-22 22:53:12,825][543983] Updated weights for policy 0, policy_version 5377 (0.0007) +[2026-07-22 22:53:13,099][543983] Updated weights for policy 0, policy_version 5387 (0.0008) +[2026-07-22 22:53:13,422][543983] Updated weights for policy 0, policy_version 5398 (0.0007) +[2026-07-22 22:53:13,722][543983] Updated weights for policy 0, policy_version 5409 (0.0007) +[2026-07-22 22:53:14,011][543983] Updated weights for policy 0, policy_version 5419 (0.0006) +[2026-07-22 22:53:14,315][543983] Updated weights for policy 0, policy_version 5430 (0.0006) +[2026-07-22 22:53:15,502][543983] Updated weights for policy 0, policy_version 5442 (0.0007) +[2026-07-22 22:53:15,806][543983] Updated weights for policy 0, policy_version 5453 (0.0006) +[2026-07-22 22:53:16,147][543983] Updated weights for policy 0, policy_version 5465 (0.0006) +[2026-07-22 22:53:16,459][543983] Updated weights for policy 0, policy_version 5476 (0.0006) +[2026-07-22 22:53:16,746][543983] Updated weights for policy 0, policy_version 5487 (0.0006) +[2026-07-22 22:53:17,054][543983] Updated weights for policy 0, policy_version 5498 (0.0007) +[2026-07-22 22:53:17,286][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12524.7). Total num frames: 2818048. Throughput: 0: 12490.0. Samples: 2839168. Policy #0 lag: (min: 59.0, avg: 107.9, max: 121.0) +[2026-07-22 22:53:17,287][543203] Avg episode reward: [(0, '58.489')] +[2026-07-22 22:53:18,116][543983] Updated weights for policy 0, policy_version 5508 (0.0007) +[2026-07-22 22:53:18,388][543983] Updated weights for policy 0, policy_version 5518 (0.0006) +[2026-07-22 22:53:18,668][543983] Updated weights for policy 0, policy_version 5528 (0.0007) +[2026-07-22 22:53:18,953][543983] Updated weights for policy 0, policy_version 5538 (0.0008) +[2026-07-22 22:53:19,234][543983] Updated weights for policy 0, policy_version 5548 (0.0007) +[2026-07-22 22:53:19,506][543983] Updated weights for policy 0, policy_version 5558 (0.0007) +[2026-07-22 22:53:19,784][543983] Updated weights for policy 0, policy_version 5568 (0.0008) +[2026-07-22 22:53:20,956][543983] Updated weights for policy 0, policy_version 5579 (0.0008) +[2026-07-22 22:53:21,246][543983] Updated weights for policy 0, policy_version 5589 (0.0011) +[2026-07-22 22:53:21,535][543983] Updated weights for policy 0, policy_version 5599 (0.0008) +[2026-07-22 22:53:21,838][543983] Updated weights for policy 0, policy_version 5610 (0.0008) +[2026-07-22 22:53:22,142][543983] Updated weights for policy 0, policy_version 5621 (0.0008) +[2026-07-22 22:53:22,286][543203] Fps is (10 sec: 9830.3, 60 sec: 12014.9, 300 sec: 12394.9). Total num frames: 2850816. Throughput: 0: 12495.6. Samples: 2874112. Policy #0 lag: (min: 59.0, avg: 107.9, max: 121.0) +[2026-07-22 22:53:22,287][543203] Avg episode reward: [(0, '67.822')] +[2026-07-22 22:53:22,464][543696] Saving new best policy, reward=67.822! +[2026-07-22 22:53:23,283][543983] Updated weights for policy 0, policy_version 5633 (0.0006) +[2026-07-22 22:53:23,569][543983] Updated weights for policy 0, policy_version 5643 (0.0007) +[2026-07-22 22:53:23,851][543983] Updated weights for policy 0, policy_version 5653 (0.0008) +[2026-07-22 22:53:24,158][543983] Updated weights for policy 0, policy_version 5664 (0.0007) +[2026-07-22 22:53:24,431][543983] Updated weights for policy 0, policy_version 5674 (0.0008) +[2026-07-22 22:53:24,737][543983] Updated weights for policy 0, policy_version 5684 (0.0007) +[2026-07-22 22:53:25,023][543983] Updated weights for policy 0, policy_version 5694 (0.0007) +[2026-07-22 22:53:26,092][543983] Updated weights for policy 0, policy_version 5704 (0.0006) +[2026-07-22 22:53:26,394][543983] Updated weights for policy 0, policy_version 5715 (0.0006) +[2026-07-22 22:53:26,676][543983] Updated weights for policy 0, policy_version 5725 (0.0007) +[2026-07-22 22:53:26,969][543983] Updated weights for policy 0, policy_version 5735 (0.0008) +[2026-07-22 22:53:27,248][543983] Updated weights for policy 0, policy_version 5745 (0.0007) +[2026-07-22 22:53:27,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12014.9, 300 sec: 12410.0). Total num frames: 2916352. Throughput: 0: 12563.9. Samples: 2958208. Policy #0 lag: (min: 63.0, avg: 78.3, max: 127.0) +[2026-07-22 22:53:27,287][543203] Avg episode reward: [(0, '85.246')] +[2026-07-22 22:53:27,553][543983] Updated weights for policy 0, policy_version 5756 (0.0007) +[2026-07-22 22:53:27,661][543696] Saving new best policy, reward=85.246! +[2026-07-22 22:53:28,629][543983] Updated weights for policy 0, policy_version 5766 (0.0007) +[2026-07-22 22:53:28,944][543983] Updated weights for policy 0, policy_version 5777 (0.0007) +[2026-07-22 22:53:29,223][543983] Updated weights for policy 0, policy_version 5787 (0.0007) +[2026-07-22 22:53:29,541][543983] Updated weights for policy 0, policy_version 5798 (0.0007) +[2026-07-22 22:53:29,823][543983] Updated weights for policy 0, policy_version 5808 (0.0007) +[2026-07-22 22:53:30,103][543983] Updated weights for policy 0, policy_version 5818 (0.0007) +[2026-07-22 22:53:31,232][543983] Updated weights for policy 0, policy_version 5831 (0.0008) +[2026-07-22 22:53:31,522][543983] Updated weights for policy 0, policy_version 5841 (0.0008) +[2026-07-22 22:53:31,809][543983] Updated weights for policy 0, policy_version 5851 (0.0007) +[2026-07-22 22:53:32,104][543983] Updated weights for policy 0, policy_version 5862 (0.0007) +[2026-07-22 22:53:32,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12014.9, 300 sec: 12424.6). Total num frames: 2981888. Throughput: 0: 12529.8. Samples: 3029120. Policy #0 lag: (min: 63.0, avg: 78.4, max: 127.0) +[2026-07-22 22:53:32,287][543203] Avg episode reward: [(0, '88.399')] +[2026-07-22 22:53:32,401][543983] Updated weights for policy 0, policy_version 5872 (0.0006) +[2026-07-22 22:53:32,686][543983] Updated weights for policy 0, policy_version 5882 (0.0007) +[2026-07-22 22:53:32,848][543696] Saving new best policy, reward=88.399! +[2026-07-22 22:53:33,783][543983] Updated weights for policy 0, policy_version 5892 (0.0007) +[2026-07-22 22:53:34,118][543983] Updated weights for policy 0, policy_version 5904 (0.0007) +[2026-07-22 22:53:34,407][543983] Updated weights for policy 0, policy_version 5914 (0.0006) +[2026-07-22 22:53:34,691][543983] Updated weights for policy 0, policy_version 5924 (0.0007) +[2026-07-22 22:53:35,007][543983] Updated weights for policy 0, policy_version 5935 (0.0006) +[2026-07-22 22:53:35,286][543983] Updated weights for policy 0, policy_version 5945 (0.0006) +[2026-07-22 22:53:36,357][543983] Updated weights for policy 0, policy_version 5955 (0.0006) +[2026-07-22 22:53:36,670][543983] Updated weights for policy 0, policy_version 5966 (0.0006) +[2026-07-22 22:53:36,994][543983] Updated weights for policy 0, policy_version 5977 (0.0006) +[2026-07-22 22:53:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12438.5). Total num frames: 3047424. Throughput: 0: 12544.0. Samples: 3065472. Policy #0 lag: (min: 63.0, avg: 78.4, max: 127.0) +[2026-07-22 22:53:37,287][543203] Avg episode reward: [(0, '85.191')] +[2026-07-22 22:53:37,299][543983] Updated weights for policy 0, policy_version 5988 (0.0006) +[2026-07-22 22:53:37,672][543983] Updated weights for policy 0, policy_version 6001 (0.0006) +[2026-07-22 22:53:37,962][543983] Updated weights for policy 0, policy_version 6011 (0.0006) +[2026-07-22 22:53:39,048][543983] Updated weights for policy 0, policy_version 6022 (0.0005) +[2026-07-22 22:53:39,342][543983] Updated weights for policy 0, policy_version 6032 (0.0006) +[2026-07-22 22:53:39,642][543983] Updated weights for policy 0, policy_version 6043 (0.0007) +[2026-07-22 22:53:39,926][543983] Updated weights for policy 0, policy_version 6053 (0.0006) +[2026-07-22 22:53:40,226][543983] Updated weights for policy 0, policy_version 6064 (0.0007) +[2026-07-22 22:53:40,515][543983] Updated weights for policy 0, policy_version 6074 (0.0007) +[2026-07-22 22:53:41,590][543983] Updated weights for policy 0, policy_version 6084 (0.0006) +[2026-07-22 22:53:41,906][543983] Updated weights for policy 0, policy_version 6095 (0.0007) +[2026-07-22 22:53:42,232][543983] Updated weights for policy 0, policy_version 6107 (0.0006) +[2026-07-22 22:53:42,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.0, 300 sec: 12451.9). Total num frames: 3112960. Throughput: 0: 12535.4. Samples: 3137792. Policy #0 lag: (min: 63.0, avg: 78.9, max: 127.0) +[2026-07-22 22:53:42,287][543203] Avg episode reward: [(0, '93.519')] +[2026-07-22 22:53:42,514][543983] Updated weights for policy 0, policy_version 6117 (0.0006) +[2026-07-22 22:53:42,798][543983] Updated weights for policy 0, policy_version 6127 (0.0006) +[2026-07-22 22:53:43,088][543983] Updated weights for policy 0, policy_version 6137 (0.0006) +[2026-07-22 22:53:43,279][543696] Saving new best policy, reward=93.519! +[2026-07-22 22:53:44,165][543983] Updated weights for policy 0, policy_version 6148 (0.0006) +[2026-07-22 22:53:44,478][543983] Updated weights for policy 0, policy_version 6158 (0.0007) +[2026-07-22 22:53:44,749][543983] Updated weights for policy 0, policy_version 6168 (0.0006) +[2026-07-22 22:53:45,038][543983] Updated weights for policy 0, policy_version 6178 (0.0006) +[2026-07-22 22:53:45,338][543983] Updated weights for policy 0, policy_version 6188 (0.0007) +[2026-07-22 22:53:45,607][543983] Updated weights for policy 0, policy_version 6198 (0.0007) +[2026-07-22 22:53:46,676][543983] Updated weights for policy 0, policy_version 6209 (0.0006) +[2026-07-22 22:53:46,956][543983] Updated weights for policy 0, policy_version 6220 (0.0006) +[2026-07-22 22:53:47,250][543983] Updated weights for policy 0, policy_version 6230 (0.0005) +[2026-07-22 22:53:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12464.7). Total num frames: 3178496. Throughput: 0: 12620.8. Samples: 3220864. Policy #0 lag: (min: 4.0, avg: 20.0, max: 68.0) +[2026-07-22 22:53:47,287][543203] Avg episode reward: [(0, '109.251')] +[2026-07-22 22:53:47,527][543983] Updated weights for policy 0, policy_version 6240 (0.0006) +[2026-07-22 22:53:47,855][543983] Updated weights for policy 0, policy_version 6251 (0.0006) +[2026-07-22 22:53:48,123][543983] Updated weights for policy 0, policy_version 6261 (0.0007) +[2026-07-22 22:53:48,420][543696] Saving new best policy, reward=109.251! +[2026-07-22 22:53:48,428][543983] Updated weights for policy 0, policy_version 6272 (0.0006) +[2026-07-22 22:53:49,518][543983] Updated weights for policy 0, policy_version 6283 (0.0006) +[2026-07-22 22:53:49,833][543983] Updated weights for policy 0, policy_version 6294 (0.0006) +[2026-07-22 22:53:50,123][543983] Updated weights for policy 0, policy_version 6304 (0.0007) +[2026-07-22 22:53:50,433][543983] Updated weights for policy 0, policy_version 6315 (0.0007) +[2026-07-22 22:53:50,745][543983] Updated weights for policy 0, policy_version 6326 (0.0006) +[2026-07-22 22:53:51,025][543983] Updated weights for policy 0, policy_version 6336 (0.0006) +[2026-07-22 22:53:52,053][543983] Updated weights for policy 0, policy_version 6346 (0.0007) +[2026-07-22 22:53:52,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12477.1). Total num frames: 3244032. Throughput: 0: 12475.7. Samples: 3256576. Policy #0 lag: (min: 4.0, avg: 20.0, max: 68.0) +[2026-07-22 22:53:52,287][543203] Avg episode reward: [(0, '122.338')] +[2026-07-22 22:53:52,360][543983] Updated weights for policy 0, policy_version 6357 (0.0007) +[2026-07-22 22:53:52,648][543983] Updated weights for policy 0, policy_version 6367 (0.0007) +[2026-07-22 22:53:52,965][543983] Updated weights for policy 0, policy_version 6378 (0.0007) +[2026-07-22 22:53:53,253][543983] Updated weights for policy 0, policy_version 6388 (0.0007) +[2026-07-22 22:53:53,566][543983] Updated weights for policy 0, policy_version 6399 (0.0008) +[2026-07-22 22:53:53,588][543696] Saving new best policy, reward=122.338! +[2026-07-22 22:53:54,712][543983] Updated weights for policy 0, policy_version 6411 (0.0007) +[2026-07-22 22:53:55,001][543983] Updated weights for policy 0, policy_version 6421 (0.0007) +[2026-07-22 22:53:55,298][543983] Updated weights for policy 0, policy_version 6432 (0.0008) +[2026-07-22 22:53:55,636][543983] Updated weights for policy 0, policy_version 6444 (0.0007) +[2026-07-22 22:53:55,966][543983] Updated weights for policy 0, policy_version 6455 (0.0008) +[2026-07-22 22:53:57,026][543983] Updated weights for policy 0, policy_version 6466 (0.0007) +[2026-07-22 22:53:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12489.0). Total num frames: 3309568. Throughput: 0: 12455.8. Samples: 3327360. Policy #0 lag: (min: 56.0, avg: 100.5, max: 120.0) +[2026-07-22 22:53:57,287][543203] Avg episode reward: [(0, '124.641')] +[2026-07-22 22:53:57,339][543983] Updated weights for policy 0, policy_version 6477 (0.0007) +[2026-07-22 22:53:57,614][543983] Updated weights for policy 0, policy_version 6487 (0.0007) +[2026-07-22 22:53:57,896][543983] Updated weights for policy 0, policy_version 6497 (0.0008) +[2026-07-22 22:53:58,210][543983] Updated weights for policy 0, policy_version 6508 (0.0008) +[2026-07-22 22:53:58,499][543983] Updated weights for policy 0, policy_version 6518 (0.0006) +[2026-07-22 22:53:58,771][543696] Saving new best policy, reward=124.641! +[2026-07-22 22:53:58,773][543983] Updated weights for policy 0, policy_version 6528 (0.0007) +[2026-07-22 22:53:59,921][543983] Updated weights for policy 0, policy_version 6540 (0.0007) +[2026-07-22 22:54:00,233][543983] Updated weights for policy 0, policy_version 6551 (0.0007) +[2026-07-22 22:54:00,529][543983] Updated weights for policy 0, policy_version 6561 (0.0006) +[2026-07-22 22:54:00,812][543983] Updated weights for policy 0, policy_version 6571 (0.0008) +[2026-07-22 22:54:01,142][543983] Updated weights for policy 0, policy_version 6583 (0.0007) +[2026-07-22 22:54:02,261][543983] Updated weights for policy 0, policy_version 6596 (0.0006) +[2026-07-22 22:54:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12500.4). Total num frames: 3375104. Throughput: 0: 12583.8. Samples: 3405440. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 22:54:02,287][543203] Avg episode reward: [(0, '136.788')] +[2026-07-22 22:54:02,531][543983] Updated weights for policy 0, policy_version 6606 (0.0008) +[2026-07-22 22:54:02,820][543983] Updated weights for policy 0, policy_version 6616 (0.0007) +[2026-07-22 22:54:03,108][543983] Updated weights for policy 0, policy_version 6626 (0.0008) +[2026-07-22 22:54:03,415][543983] Updated weights for policy 0, policy_version 6637 (0.0007) +[2026-07-22 22:54:03,709][543983] Updated weights for policy 0, policy_version 6647 (0.0008) +[2026-07-22 22:54:03,953][543696] Saving new best policy, reward=136.788! +[2026-07-22 22:54:04,741][543983] Updated weights for policy 0, policy_version 6657 (0.0007) +[2026-07-22 22:54:05,057][543983] Updated weights for policy 0, policy_version 6668 (0.0007) +[2026-07-22 22:54:05,344][543983] Updated weights for policy 0, policy_version 6678 (0.0008) +[2026-07-22 22:54:05,615][543983] Updated weights for policy 0, policy_version 6688 (0.0009) +[2026-07-22 22:54:05,922][543983] Updated weights for policy 0, policy_version 6698 (0.0007) +[2026-07-22 22:54:06,199][543983] Updated weights for policy 0, policy_version 6708 (0.0006) +[2026-07-22 22:54:06,523][543983] Updated weights for policy 0, policy_version 6719 (0.0007) +[2026-07-22 22:54:07,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.0, 300 sec: 12511.4). Total num frames: 3440640. Throughput: 0: 12720.3. Samples: 3446528. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 22:54:07,287][543203] Avg episode reward: [(0, '135.975')] +[2026-07-22 22:54:07,566][543983] Updated weights for policy 0, policy_version 6729 (0.0007) +[2026-07-22 22:54:07,854][543983] Updated weights for policy 0, policy_version 6739 (0.0007) +[2026-07-22 22:54:08,184][543983] Updated weights for policy 0, policy_version 6750 (0.0008) +[2026-07-22 22:54:08,512][543983] Updated weights for policy 0, policy_version 6762 (0.0006) +[2026-07-22 22:54:08,800][543983] Updated weights for policy 0, policy_version 6772 (0.0006) +[2026-07-22 22:54:09,108][543983] Updated weights for policy 0, policy_version 6783 (0.0006) +[2026-07-22 22:54:10,228][543983] Updated weights for policy 0, policy_version 6793 (0.0007) +[2026-07-22 22:54:10,539][543983] Updated weights for policy 0, policy_version 6804 (0.0007) +[2026-07-22 22:54:10,837][543983] Updated weights for policy 0, policy_version 6814 (0.0007) +[2026-07-22 22:54:11,108][543983] Updated weights for policy 0, policy_version 6824 (0.0008) +[2026-07-22 22:54:11,421][543983] Updated weights for policy 0, policy_version 6835 (0.0007) +[2026-07-22 22:54:11,713][543983] Updated weights for policy 0, policy_version 6845 (0.0007) +[2026-07-22 22:54:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12522.1). Total num frames: 3506176. Throughput: 0: 12475.7. Samples: 3519616. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 22:54:12,287][543203] Avg episode reward: [(0, '150.067')] +[2026-07-22 22:54:12,298][543696] Saving new best policy, reward=150.067! +[2026-07-22 22:54:12,769][543983] Updated weights for policy 0, policy_version 6855 (0.0007) +[2026-07-22 22:54:13,080][543983] Updated weights for policy 0, policy_version 6866 (0.0007) +[2026-07-22 22:54:13,357][543983] Updated weights for policy 0, policy_version 6876 (0.0006) +[2026-07-22 22:54:13,647][543983] Updated weights for policy 0, policy_version 6886 (0.0007) +[2026-07-22 22:54:13,981][543983] Updated weights for policy 0, policy_version 6897 (0.0007) +[2026-07-22 22:54:14,288][543983] Updated weights for policy 0, policy_version 6908 (0.0008) +[2026-07-22 22:54:15,326][543983] Updated weights for policy 0, policy_version 6918 (0.0007) +[2026-07-22 22:54:15,610][543983] Updated weights for policy 0, policy_version 6928 (0.0007) +[2026-07-22 22:54:15,914][543983] Updated weights for policy 0, policy_version 6939 (0.0007) +[2026-07-22 22:54:16,227][543983] Updated weights for policy 0, policy_version 6950 (0.0006) +[2026-07-22 22:54:16,533][543983] Updated weights for policy 0, policy_version 6961 (0.0007) +[2026-07-22 22:54:16,823][543983] Updated weights for policy 0, policy_version 6971 (0.0007) +[2026-07-22 22:54:17,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12532.4). Total num frames: 3571712. Throughput: 0: 12481.4. Samples: 3590784. Policy #0 lag: (min: 63.0, avg: 80.2, max: 127.0) +[2026-07-22 22:54:17,287][543203] Avg episode reward: [(0, '153.922')] +[2026-07-22 22:54:17,293][543696] Saving new best policy, reward=153.922! +[2026-07-22 22:54:17,941][543983] Updated weights for policy 0, policy_version 6981 (0.0007) +[2026-07-22 22:54:18,250][543983] Updated weights for policy 0, policy_version 6992 (0.0007) +[2026-07-22 22:54:18,538][543983] Updated weights for policy 0, policy_version 7002 (0.0007) +[2026-07-22 22:54:18,850][543983] Updated weights for policy 0, policy_version 7013 (0.0006) +[2026-07-22 22:54:19,135][543983] Updated weights for policy 0, policy_version 7023 (0.0006) +[2026-07-22 22:54:19,409][543983] Updated weights for policy 0, policy_version 7033 (0.0008) +[2026-07-22 22:54:20,447][543983] Updated weights for policy 0, policy_version 7043 (0.0006) +[2026-07-22 22:54:20,719][543983] Updated weights for policy 0, policy_version 7053 (0.0007) +[2026-07-22 22:54:21,001][543983] Updated weights for policy 0, policy_version 7063 (0.0007) +[2026-07-22 22:54:21,305][543983] Updated weights for policy 0, policy_version 7073 (0.0006) +[2026-07-22 22:54:21,609][543983] Updated weights for policy 0, policy_version 7084 (0.0008) +[2026-07-22 22:54:21,888][543983] Updated weights for policy 0, policy_version 7094 (0.0007) +[2026-07-22 22:54:22,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12542.3). Total num frames: 3637248. Throughput: 0: 12526.9. Samples: 3629184. Policy #0 lag: (min: 63.0, avg: 80.2, max: 127.0) +[2026-07-22 22:54:22,287][543203] Avg episode reward: [(0, '164.031')] +[2026-07-22 22:54:22,293][543696] Saving new best policy, reward=164.031! +[2026-07-22 22:54:23,001][543983] Updated weights for policy 0, policy_version 7105 (0.0006) +[2026-07-22 22:54:23,289][543983] Updated weights for policy 0, policy_version 7115 (0.0007) +[2026-07-22 22:54:23,580][543983] Updated weights for policy 0, policy_version 7125 (0.0007) +[2026-07-22 22:54:23,914][543983] Updated weights for policy 0, policy_version 7137 (0.0008) +[2026-07-22 22:54:24,222][543983] Updated weights for policy 0, policy_version 7148 (0.0007) +[2026-07-22 22:54:24,519][543983] Updated weights for policy 0, policy_version 7158 (0.0007) +[2026-07-22 22:54:24,802][543983] Updated weights for policy 0, policy_version 7168 (0.0007) +[2026-07-22 22:54:25,826][543983] Updated weights for policy 0, policy_version 7178 (0.0007) +[2026-07-22 22:54:26,139][543983] Updated weights for policy 0, policy_version 7188 (0.0007) +[2026-07-22 22:54:26,410][543983] Updated weights for policy 0, policy_version 7198 (0.0007) +[2026-07-22 22:54:26,698][543983] Updated weights for policy 0, policy_version 7208 (0.0007) +[2026-07-22 22:54:26,987][543983] Updated weights for policy 0, policy_version 7218 (0.0007) +[2026-07-22 22:54:27,284][543983] Updated weights for policy 0, policy_version 7228 (0.0007) +[2026-07-22 22:54:27,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12440.8). Total num frames: 3670016. Throughput: 0: 12746.0. Samples: 3711360. Policy #0 lag: (min: 63.0, avg: 80.2, max: 127.0) +[2026-07-22 22:54:27,287][543203] Avg episode reward: [(0, '167.860')] +[2026-07-22 22:54:27,370][543696] Saving new best policy, reward=167.860! +[2026-07-22 22:54:28,323][543983] Updated weights for policy 0, policy_version 7239 (0.0006) +[2026-07-22 22:54:28,598][543983] Updated weights for policy 0, policy_version 7249 (0.0006) +[2026-07-22 22:54:28,917][543983] Updated weights for policy 0, policy_version 7260 (0.0006) +[2026-07-22 22:54:29,199][543983] Updated weights for policy 0, policy_version 7270 (0.0006) +[2026-07-22 22:54:29,516][543983] Updated weights for policy 0, policy_version 7281 (0.0007) +[2026-07-22 22:54:29,810][543983] Updated weights for policy 0, policy_version 7292 (0.0007) +[2026-07-22 22:54:30,939][543983] Updated weights for policy 0, policy_version 7303 (0.0007) +[2026-07-22 22:54:31,263][543983] Updated weights for policy 0, policy_version 7314 (0.0007) +[2026-07-22 22:54:31,569][543983] Updated weights for policy 0, policy_version 7325 (0.0007) +[2026-07-22 22:54:31,852][543983] Updated weights for policy 0, policy_version 7335 (0.0008) +[2026-07-22 22:54:32,137][543983] Updated weights for policy 0, policy_version 7345 (0.0007) +[2026-07-22 22:54:32,286][543203] Fps is (10 sec: 9830.5, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 3735552. Throughput: 0: 12489.9. Samples: 3782912. Policy #0 lag: (min: 16.0, avg: 57.7, max: 80.0) +[2026-07-22 22:54:32,287][543203] Avg episode reward: [(0, '163.573')] +[2026-07-22 22:54:32,440][543983] Updated weights for policy 0, policy_version 7356 (0.0007) +[2026-07-22 22:54:33,541][543983] Updated weights for policy 0, policy_version 7367 (0.0008) +[2026-07-22 22:54:33,832][543983] Updated weights for policy 0, policy_version 7377 (0.0006) +[2026-07-22 22:54:34,126][543983] Updated weights for policy 0, policy_version 7387 (0.0007) +[2026-07-22 22:54:34,410][543983] Updated weights for policy 0, policy_version 7397 (0.0008) +[2026-07-22 22:54:34,699][543983] Updated weights for policy 0, policy_version 7407 (0.0008) +[2026-07-22 22:54:34,989][543983] Updated weights for policy 0, policy_version 7417 (0.0007) +[2026-07-22 22:54:36,070][543983] Updated weights for policy 0, policy_version 7428 (0.0007) +[2026-07-22 22:54:36,384][543983] Updated weights for policy 0, policy_version 7439 (0.0008) +[2026-07-22 22:54:36,688][543983] Updated weights for policy 0, policy_version 7449 (0.0007) +[2026-07-22 22:54:36,965][543983] Updated weights for policy 0, policy_version 7459 (0.0007) +[2026-07-22 22:54:37,254][543983] Updated weights for policy 0, policy_version 7469 (0.0008) +[2026-07-22 22:54:37,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 3801088. Throughput: 0: 12507.0. Samples: 3819392. Policy #0 lag: (min: 46.0, avg: 62.4, max: 110.0) +[2026-07-22 22:54:37,287][543203] Avg episode reward: [(0, '169.498')] +[2026-07-22 22:54:37,593][543983] Updated weights for policy 0, policy_version 7481 (0.0007) +[2026-07-22 22:54:37,787][543696] Saving new best policy, reward=169.498! +[2026-07-22 22:54:38,654][543983] Updated weights for policy 0, policy_version 7491 (0.0007) +[2026-07-22 22:54:38,958][543983] Updated weights for policy 0, policy_version 7501 (0.0007) +[2026-07-22 22:54:39,251][543983] Updated weights for policy 0, policy_version 7512 (0.0007) +[2026-07-22 22:54:39,564][543983] Updated weights for policy 0, policy_version 7523 (0.0007) +[2026-07-22 22:54:39,895][543983] Updated weights for policy 0, policy_version 7534 (0.0007) +[2026-07-22 22:54:40,167][543983] Updated weights for policy 0, policy_version 7544 (0.0008) +[2026-07-22 22:54:41,223][543983] Updated weights for policy 0, policy_version 7555 (0.0007) +[2026-07-22 22:54:41,550][543983] Updated weights for policy 0, policy_version 7565 (0.0007) +[2026-07-22 22:54:41,822][543983] Updated weights for policy 0, policy_version 7575 (0.0007) +[2026-07-22 22:54:42,111][543983] Updated weights for policy 0, policy_version 7585 (0.0008) +[2026-07-22 22:54:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 3866624. Throughput: 0: 12669.2. Samples: 3897472. Policy #0 lag: (min: 46.0, avg: 62.4, max: 110.0) +[2026-07-22 22:54:42,287][543203] Avg episode reward: [(0, '189.301')] +[2026-07-22 22:54:42,446][543983] Updated weights for policy 0, policy_version 7597 (0.0008) +[2026-07-22 22:54:42,776][543983] Updated weights for policy 0, policy_version 7609 (0.0007) +[2026-07-22 22:54:42,953][543696] Saving new best policy, reward=189.301! +[2026-07-22 22:54:43,904][543983] Updated weights for policy 0, policy_version 7620 (0.0007) +[2026-07-22 22:54:44,191][543983] Updated weights for policy 0, policy_version 7630 (0.0007) +[2026-07-22 22:54:44,505][543983] Updated weights for policy 0, policy_version 7641 (0.0007) +[2026-07-22 22:54:44,819][543983] Updated weights for policy 0, policy_version 7652 (0.0007) +[2026-07-22 22:54:45,128][543983] Updated weights for policy 0, policy_version 7663 (0.0006) +[2026-07-22 22:54:45,438][543983] Updated weights for policy 0, policy_version 7674 (0.0007) +[2026-07-22 22:54:46,493][543983] Updated weights for policy 0, policy_version 7684 (0.0007) +[2026-07-22 22:54:46,799][543983] Updated weights for policy 0, policy_version 7695 (0.0006) +[2026-07-22 22:54:47,091][543983] Updated weights for policy 0, policy_version 7705 (0.0006) +[2026-07-22 22:54:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 3932160. Throughput: 0: 12657.8. Samples: 3975040. Policy #0 lag: (min: 3.0, avg: 45.9, max: 67.0) +[2026-07-22 22:54:47,287][543203] Avg episode reward: [(0, '197.953')] +[2026-07-22 22:54:47,355][543983] Updated weights for policy 0, policy_version 7715 (0.0006) +[2026-07-22 22:54:47,643][543983] Updated weights for policy 0, policy_version 7725 (0.0006) +[2026-07-22 22:54:47,936][543983] Updated weights for policy 0, policy_version 7735 (0.0006) +[2026-07-22 22:54:48,177][543696] Saving new best policy, reward=197.953! +[2026-07-22 22:54:49,011][543983] Updated weights for policy 0, policy_version 7746 (0.0007) +[2026-07-22 22:54:49,301][543983] Updated weights for policy 0, policy_version 7756 (0.0007) +[2026-07-22 22:54:49,593][543983] Updated weights for policy 0, policy_version 7766 (0.0007) +[2026-07-22 22:54:49,910][543983] Updated weights for policy 0, policy_version 7777 (0.0007) +[2026-07-22 22:54:50,225][543983] Updated weights for policy 0, policy_version 7788 (0.0007) +[2026-07-22 22:54:50,564][543983] Updated weights for policy 0, policy_version 7800 (0.0007) +[2026-07-22 22:54:51,638][543983] Updated weights for policy 0, policy_version 7810 (0.0007) +[2026-07-22 22:54:51,929][543983] Updated weights for policy 0, policy_version 7820 (0.0006) +[2026-07-22 22:54:52,218][543983] Updated weights for policy 0, policy_version 7830 (0.0006) +[2026-07-22 22:54:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 3997696. Throughput: 0: 12552.5. Samples: 4011392. Policy #0 lag: (min: 11.0, avg: 52.2, max: 75.0) +[2026-07-22 22:54:52,287][543203] Avg episode reward: [(0, '197.454')] +[2026-07-22 22:54:52,538][543983] Updated weights for policy 0, policy_version 7841 (0.0007) +[2026-07-22 22:54:52,838][543983] Updated weights for policy 0, policy_version 7852 (0.0007) +[2026-07-22 22:54:53,166][543983] Updated weights for policy 0, policy_version 7863 (0.0006) +[2026-07-22 22:54:54,178][543983] Updated weights for policy 0, policy_version 7873 (0.0006) +[2026-07-22 22:54:54,459][543983] Updated weights for policy 0, policy_version 7883 (0.0007) +[2026-07-22 22:54:54,757][543983] Updated weights for policy 0, policy_version 7894 (0.0006) +[2026-07-22 22:54:55,057][543983] Updated weights for policy 0, policy_version 7904 (0.0006) +[2026-07-22 22:54:55,335][543983] Updated weights for policy 0, policy_version 7914 (0.0007) +[2026-07-22 22:54:55,644][543983] Updated weights for policy 0, policy_version 7924 (0.0006) +[2026-07-22 22:54:55,933][543983] Updated weights for policy 0, policy_version 7935 (0.0007) +[2026-07-22 22:54:57,015][543983] Updated weights for policy 0, policy_version 7945 (0.0007) +[2026-07-22 22:54:57,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 4063232. Throughput: 0: 12521.3. Samples: 4083072. Policy #0 lag: (min: 11.0, avg: 52.2, max: 75.0) +[2026-07-22 22:54:57,287][543203] Avg episode reward: [(0, '179.889')] +[2026-07-22 22:54:57,313][543983] Updated weights for policy 0, policy_version 7956 (0.0006) +[2026-07-22 22:54:57,603][543983] Updated weights for policy 0, policy_version 7966 (0.0006) +[2026-07-22 22:54:57,911][543983] Updated weights for policy 0, policy_version 7976 (0.0006) +[2026-07-22 22:54:58,218][543983] Updated weights for policy 0, policy_version 7987 (0.0006) +[2026-07-22 22:54:58,485][543983] Updated weights for policy 0, policy_version 7997 (0.0006) +[2026-07-22 22:54:59,543][543983] Updated weights for policy 0, policy_version 8007 (0.0006) +[2026-07-22 22:54:59,823][543983] Updated weights for policy 0, policy_version 8017 (0.0006) +[2026-07-22 22:55:00,114][543983] Updated weights for policy 0, policy_version 8027 (0.0006) +[2026-07-22 22:55:00,400][543983] Updated weights for policy 0, policy_version 8037 (0.0006) +[2026-07-22 22:55:00,667][543983] Updated weights for policy 0, policy_version 8047 (0.0006) +[2026-07-22 22:55:00,989][543983] Updated weights for policy 0, policy_version 8058 (0.0006) +[2026-07-22 22:55:02,058][543983] Updated weights for policy 0, policy_version 8068 (0.0007) +[2026-07-22 22:55:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12329.7). Total num frames: 4128768. Throughput: 0: 12777.2. Samples: 4165760. Policy #0 lag: (min: 63.0, avg: 78.4, max: 127.0) +[2026-07-22 22:55:02,287][543203] Avg episode reward: [(0, '182.505')] +[2026-07-22 22:55:02,386][543983] Updated weights for policy 0, policy_version 8079 (0.0008) +[2026-07-22 22:55:02,656][543983] Updated weights for policy 0, policy_version 8089 (0.0006) +[2026-07-22 22:55:02,938][543983] Updated weights for policy 0, policy_version 8099 (0.0006) +[2026-07-22 22:55:03,238][543983] Updated weights for policy 0, policy_version 8109 (0.0006) +[2026-07-22 22:55:03,507][543983] Updated weights for policy 0, policy_version 8119 (0.0006) +[2026-07-22 22:55:04,597][543983] Updated weights for policy 0, policy_version 8130 (0.0007) +[2026-07-22 22:55:04,893][543983] Updated weights for policy 0, policy_version 8141 (0.0006) +[2026-07-22 22:55:05,175][543983] Updated weights for policy 0, policy_version 8151 (0.0007) +[2026-07-22 22:55:05,465][543983] Updated weights for policy 0, policy_version 8161 (0.0006) +[2026-07-22 22:55:05,752][543983] Updated weights for policy 0, policy_version 8171 (0.0006) +[2026-07-22 22:55:06,073][543983] Updated weights for policy 0, policy_version 8182 (0.0006) +[2026-07-22 22:55:06,332][543983] Updated weights for policy 0, policy_version 8192 (0.0007) +[2026-07-22 22:55:07,286][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12329.7). Total num frames: 4194304. Throughput: 0: 12757.4. Samples: 4203264. Policy #0 lag: (min: 63.0, avg: 78.4, max: 127.0) +[2026-07-22 22:55:07,287][543203] Avg episode reward: [(0, '181.022')] +[2026-07-22 22:55:07,408][543983] Updated weights for policy 0, policy_version 8202 (0.0006) +[2026-07-22 22:55:07,675][543983] Updated weights for policy 0, policy_version 8212 (0.0007) +[2026-07-22 22:55:07,966][543983] Updated weights for policy 0, policy_version 8222 (0.0006) +[2026-07-22 22:55:08,270][543983] Updated weights for policy 0, policy_version 8232 (0.0006) +[2026-07-22 22:55:08,530][543983] Updated weights for policy 0, policy_version 8242 (0.0006) +[2026-07-22 22:55:08,847][543983] Updated weights for policy 0, policy_version 8253 (0.0006) +[2026-07-22 22:55:09,918][543983] Updated weights for policy 0, policy_version 8263 (0.0007) +[2026-07-22 22:55:10,202][543983] Updated weights for policy 0, policy_version 8273 (0.0007) +[2026-07-22 22:55:10,474][543983] Updated weights for policy 0, policy_version 8283 (0.0006) +[2026-07-22 22:55:10,760][543983] Updated weights for policy 0, policy_version 8293 (0.0006) +[2026-07-22 22:55:11,052][543983] Updated weights for policy 0, policy_version 8303 (0.0006) +[2026-07-22 22:55:11,335][543983] Updated weights for policy 0, policy_version 8313 (0.0008) +[2026-07-22 22:55:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 4259840. Throughput: 0: 12538.3. Samples: 4275584. Policy #0 lag: (min: 63.0, avg: 79.0, max: 127.0) +[2026-07-22 22:55:12,287][543203] Avg episode reward: [(0, '180.801')] +[2026-07-22 22:55:12,408][543983] Updated weights for policy 0, policy_version 8323 (0.0006) +[2026-07-22 22:55:12,719][543983] Updated weights for policy 0, policy_version 8334 (0.0006) +[2026-07-22 22:55:13,019][543983] Updated weights for policy 0, policy_version 8344 (0.0006) +[2026-07-22 22:55:13,291][543983] Updated weights for policy 0, policy_version 8354 (0.0007) +[2026-07-22 22:55:13,585][543983] Updated weights for policy 0, policy_version 8364 (0.0007) +[2026-07-22 22:55:13,867][543983] Updated weights for policy 0, policy_version 8374 (0.0006) +[2026-07-22 22:55:14,912][543983] Updated weights for policy 0, policy_version 8385 (0.0006) +[2026-07-22 22:55:15,214][543983] Updated weights for policy 0, policy_version 8396 (0.0006) +[2026-07-22 22:55:15,510][543983] Updated weights for policy 0, policy_version 8406 (0.0006) +[2026-07-22 22:55:15,772][543983] Updated weights for policy 0, policy_version 8416 (0.0006) +[2026-07-22 22:55:16,064][543983] Updated weights for policy 0, policy_version 8426 (0.0006) +[2026-07-22 22:55:16,446][543983] Updated weights for policy 0, policy_version 8440 (0.0007) +[2026-07-22 22:55:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 4325376. Throughput: 0: 12552.5. Samples: 4347776. Policy #0 lag: (min: 63.0, avg: 79.0, max: 127.0) +[2026-07-22 22:55:17,287][543203] Avg episode reward: [(0, '181.555')] +[2026-07-22 22:55:17,529][543983] Updated weights for policy 0, policy_version 8450 (0.0006) +[2026-07-22 22:55:17,791][543983] Updated weights for policy 0, policy_version 8460 (0.0008) +[2026-07-22 22:55:18,076][543983] Updated weights for policy 0, policy_version 8470 (0.0006) +[2026-07-22 22:55:18,400][543983] Updated weights for policy 0, policy_version 8481 (0.0006) +[2026-07-22 22:55:18,730][543983] Updated weights for policy 0, policy_version 8493 (0.0006) +[2026-07-22 22:55:19,008][543983] Updated weights for policy 0, policy_version 8503 (0.0007) +[2026-07-22 22:55:20,093][543983] Updated weights for policy 0, policy_version 8513 (0.0008) +[2026-07-22 22:55:20,397][543983] Updated weights for policy 0, policy_version 8524 (0.0008) +[2026-07-22 22:55:20,684][543983] Updated weights for policy 0, policy_version 8534 (0.0007) +[2026-07-22 22:55:20,993][543983] Updated weights for policy 0, policy_version 8545 (0.0007) +[2026-07-22 22:55:21,328][543983] Updated weights for policy 0, policy_version 8557 (0.0006) +[2026-07-22 22:55:21,627][543983] Updated weights for policy 0, policy_version 8568 (0.0007) +[2026-07-22 22:55:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 4390912. Throughput: 0: 12726.1. Samples: 4392064. Policy #0 lag: (min: 55.0, avg: 70.6, max: 119.0) +[2026-07-22 22:55:22,287][543203] Avg episode reward: [(0, '196.927')] +[2026-07-22 22:55:22,722][543983] Updated weights for policy 0, policy_version 8579 (0.0007) +[2026-07-22 22:55:23,055][543983] Updated weights for policy 0, policy_version 8591 (0.0006) +[2026-07-22 22:55:23,336][543983] Updated weights for policy 0, policy_version 8601 (0.0006) +[2026-07-22 22:55:23,615][543983] Updated weights for policy 0, policy_version 8611 (0.0007) +[2026-07-22 22:55:23,893][543983] Updated weights for policy 0, policy_version 8621 (0.0006) +[2026-07-22 22:55:24,166][543983] Updated weights for policy 0, policy_version 8631 (0.0006) +[2026-07-22 22:55:25,284][543983] Updated weights for policy 0, policy_version 8641 (0.0006) +[2026-07-22 22:55:25,574][543983] Updated weights for policy 0, policy_version 8651 (0.0006) +[2026-07-22 22:55:25,855][543983] Updated weights for policy 0, policy_version 8661 (0.0006) +[2026-07-22 22:55:26,134][543983] Updated weights for policy 0, policy_version 8671 (0.0006) +[2026-07-22 22:55:26,441][543983] Updated weights for policy 0, policy_version 8682 (0.0006) +[2026-07-22 22:55:26,722][543983] Updated weights for policy 0, policy_version 8692 (0.0007) +[2026-07-22 22:55:27,036][543983] Updated weights for policy 0, policy_version 8703 (0.0006) +[2026-07-22 22:55:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12440.7). Total num frames: 4456448. Throughput: 0: 12689.1. Samples: 4468480. Policy #0 lag: (min: 55.0, avg: 70.6, max: 119.0) +[2026-07-22 22:55:27,287][543203] Avg episode reward: [(0, '190.789')] +[2026-07-22 22:55:28,096][543983] Updated weights for policy 0, policy_version 8713 (0.0006) +[2026-07-22 22:55:28,387][543983] Updated weights for policy 0, policy_version 8723 (0.0006) +[2026-07-22 22:55:28,674][543983] Updated weights for policy 0, policy_version 8733 (0.0006) +[2026-07-22 22:55:28,957][543983] Updated weights for policy 0, policy_version 8743 (0.0006) +[2026-07-22 22:55:29,244][543983] Updated weights for policy 0, policy_version 8753 (0.0006) +[2026-07-22 22:55:29,549][543983] Updated weights for policy 0, policy_version 8764 (0.0007) +[2026-07-22 22:55:30,656][543983] Updated weights for policy 0, policy_version 8775 (0.0007) +[2026-07-22 22:55:30,998][543983] Updated weights for policy 0, policy_version 8787 (0.0006) +[2026-07-22 22:55:31,279][543983] Updated weights for policy 0, policy_version 8797 (0.0007) +[2026-07-22 22:55:31,553][543983] Updated weights for policy 0, policy_version 8807 (0.0007) +[2026-07-22 22:55:31,864][543983] Updated weights for policy 0, policy_version 8818 (0.0007) +[2026-07-22 22:55:32,168][543983] Updated weights for policy 0, policy_version 8829 (0.0007) +[2026-07-22 22:55:32,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12440.7). Total num frames: 4521984. Throughput: 0: 12558.2. Samples: 4540160. Policy #0 lag: (min: 63.0, avg: 79.5, max: 127.0) +[2026-07-22 22:55:32,287][543203] Avg episode reward: [(0, '189.167')] +[2026-07-22 22:55:33,295][543983] Updated weights for policy 0, policy_version 8840 (0.0007) +[2026-07-22 22:55:33,553][543983] Updated weights for policy 0, policy_version 8850 (0.0006) +[2026-07-22 22:55:33,852][543983] Updated weights for policy 0, policy_version 8860 (0.0006) +[2026-07-22 22:55:34,179][543983] Updated weights for policy 0, policy_version 8872 (0.0006) +[2026-07-22 22:55:34,483][543983] Updated weights for policy 0, policy_version 8883 (0.0006) +[2026-07-22 22:55:34,759][543983] Updated weights for policy 0, policy_version 8893 (0.0006) +[2026-07-22 22:55:35,838][543983] Updated weights for policy 0, policy_version 8903 (0.0006) +[2026-07-22 22:55:36,172][543983] Updated weights for policy 0, policy_version 8915 (0.0006) +[2026-07-22 22:55:36,457][543983] Updated weights for policy 0, policy_version 8925 (0.0006) +[2026-07-22 22:55:36,741][543983] Updated weights for policy 0, policy_version 8935 (0.0007) +[2026-07-22 22:55:37,021][543983] Updated weights for policy 0, policy_version 8945 (0.0006) +[2026-07-22 22:55:37,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12329.7). Total num frames: 4554752. Throughput: 0: 12552.5. Samples: 4576256. Policy #0 lag: (min: 63.0, avg: 79.5, max: 127.0) +[2026-07-22 22:55:37,287][543203] Avg episode reward: [(0, '172.189')] +[2026-07-22 22:55:37,306][543983] Updated weights for policy 0, policy_version 8955 (0.0006) +[2026-07-22 22:55:38,385][543983] Updated weights for policy 0, policy_version 8966 (0.0006) +[2026-07-22 22:55:38,678][543983] Updated weights for policy 0, policy_version 8976 (0.0007) +[2026-07-22 22:55:38,954][543983] Updated weights for policy 0, policy_version 8986 (0.0006) +[2026-07-22 22:55:39,235][543983] Updated weights for policy 0, policy_version 8996 (0.0007) +[2026-07-22 22:55:39,536][543983] Updated weights for policy 0, policy_version 9007 (0.0006) +[2026-07-22 22:55:39,870][543983] Updated weights for policy 0, policy_version 9018 (0.0007) +[2026-07-22 22:55:40,950][543983] Updated weights for policy 0, policy_version 9030 (0.0006) +[2026-07-22 22:55:41,248][543983] Updated weights for policy 0, policy_version 9040 (0.0006) +[2026-07-22 22:55:41,550][543983] Updated weights for policy 0, policy_version 9051 (0.0006) +[2026-07-22 22:55:41,833][543983] Updated weights for policy 0, policy_version 9061 (0.0006) +[2026-07-22 22:55:42,100][543983] Updated weights for policy 0, policy_version 9071 (0.0007) +[2026-07-22 22:55:42,286][543203] Fps is (10 sec: 9830.5, 60 sec: 12561.1, 300 sec: 12329.7). Total num frames: 4620288. Throughput: 0: 12837.0. Samples: 4660736. Policy #0 lag: (min: 56.0, avg: 102.5, max: 120.0) +[2026-07-22 22:55:42,287][543203] Avg episode reward: [(0, '178.140')] +[2026-07-22 22:55:42,396][543983] Updated weights for policy 0, policy_version 9081 (0.0007) +[2026-07-22 22:55:43,452][543983] Updated weights for policy 0, policy_version 9091 (0.0007) +[2026-07-22 22:55:43,733][543983] Updated weights for policy 0, policy_version 9101 (0.0006) +[2026-07-22 22:55:44,013][543983] Updated weights for policy 0, policy_version 9111 (0.0007) +[2026-07-22 22:55:44,300][543983] Updated weights for policy 0, policy_version 9121 (0.0006) +[2026-07-22 22:55:44,573][543983] Updated weights for policy 0, policy_version 9131 (0.0006) +[2026-07-22 22:55:44,865][543983] Updated weights for policy 0, policy_version 9141 (0.0007) +[2026-07-22 22:55:45,142][543983] Updated weights for policy 0, policy_version 9151 (0.0006) +[2026-07-22 22:55:46,200][543983] Updated weights for policy 0, policy_version 9161 (0.0006) +[2026-07-22 22:55:46,493][543983] Updated weights for policy 0, policy_version 9171 (0.0006) +[2026-07-22 22:55:46,774][543983] Updated weights for policy 0, policy_version 9181 (0.0006) +[2026-07-22 22:55:47,071][543983] Updated weights for policy 0, policy_version 9192 (0.0006) +[2026-07-22 22:55:47,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12329.6). Total num frames: 4685824. Throughput: 0: 12598.0. Samples: 4732672. Policy #0 lag: (min: 56.0, avg: 102.5, max: 120.0) +[2026-07-22 22:55:47,287][543203] Avg episode reward: [(0, '203.645')] +[2026-07-22 22:55:47,357][543983] Updated weights for policy 0, policy_version 9202 (0.0006) +[2026-07-22 22:55:47,657][543983] Updated weights for policy 0, policy_version 9212 (0.0006) +[2026-07-22 22:55:47,763][543696] Saving new best policy, reward=203.645! +[2026-07-22 22:55:48,721][543983] Updated weights for policy 0, policy_version 9223 (0.0007) +[2026-07-22 22:55:49,003][543983] Updated weights for policy 0, policy_version 9233 (0.0006) +[2026-07-22 22:55:49,288][543983] Updated weights for policy 0, policy_version 9243 (0.0007) +[2026-07-22 22:55:49,562][543983] Updated weights for policy 0, policy_version 9253 (0.0006) +[2026-07-22 22:55:49,854][543983] Updated weights for policy 0, policy_version 9263 (0.0007) +[2026-07-22 22:55:50,166][543983] Updated weights for policy 0, policy_version 9274 (0.0006) +[2026-07-22 22:55:51,247][543983] Updated weights for policy 0, policy_version 9284 (0.0007) +[2026-07-22 22:55:51,577][543983] Updated weights for policy 0, policy_version 9296 (0.0006) +[2026-07-22 22:55:51,853][543983] Updated weights for policy 0, policy_version 9306 (0.0006) +[2026-07-22 22:55:52,145][543983] Updated weights for policy 0, policy_version 9316 (0.0006) +[2026-07-22 22:55:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 4751360. Throughput: 0: 12558.2. Samples: 4768384. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 22:55:52,287][543203] Avg episode reward: [(0, '208.907')] +[2026-07-22 22:55:52,420][543983] Updated weights for policy 0, policy_version 9326 (0.0007) +[2026-07-22 22:55:52,727][543983] Updated weights for policy 0, policy_version 9337 (0.0006) +[2026-07-22 22:55:52,927][543696] Saving new best policy, reward=208.907! +[2026-07-22 22:55:53,819][543983] Updated weights for policy 0, policy_version 9347 (0.0006) +[2026-07-22 22:55:54,101][543983] Updated weights for policy 0, policy_version 9357 (0.0006) +[2026-07-22 22:55:54,366][543983] Updated weights for policy 0, policy_version 9367 (0.0006) +[2026-07-22 22:55:54,681][543983] Updated weights for policy 0, policy_version 9378 (0.0006) +[2026-07-22 22:55:54,998][543983] Updated weights for policy 0, policy_version 9389 (0.0007) +[2026-07-22 22:55:55,287][543983] Updated weights for policy 0, policy_version 9399 (0.0006) +[2026-07-22 22:55:56,334][543983] Updated weights for policy 0, policy_version 9410 (0.0006) +[2026-07-22 22:55:56,646][543983] Updated weights for policy 0, policy_version 9421 (0.0007) +[2026-07-22 22:55:56,921][543983] Updated weights for policy 0, policy_version 9431 (0.0006) +[2026-07-22 22:55:57,208][543983] Updated weights for policy 0, policy_version 9441 (0.0006) +[2026-07-22 22:55:57,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 4816896. Throughput: 0: 12637.9. Samples: 4844288. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 22:55:57,287][543203] Avg episode reward: [(0, '213.689')] +[2026-07-22 22:55:57,517][543983] Updated weights for policy 0, policy_version 9452 (0.0006) +[2026-07-22 22:55:57,812][543983] Updated weights for policy 0, policy_version 9463 (0.0006) +[2026-07-22 22:55:58,068][543696] Saving new best policy, reward=213.689! +[2026-07-22 22:55:58,905][543983] Updated weights for policy 0, policy_version 9473 (0.0006) +[2026-07-22 22:55:59,184][543983] Updated weights for policy 0, policy_version 9483 (0.0006) +[2026-07-22 22:55:59,478][543983] Updated weights for policy 0, policy_version 9493 (0.0006) +[2026-07-22 22:55:59,768][543983] Updated weights for policy 0, policy_version 9504 (0.0006) +[2026-07-22 22:56:00,062][543983] Updated weights for policy 0, policy_version 9514 (0.0006) +[2026-07-22 22:56:00,386][543983] Updated weights for policy 0, policy_version 9525 (0.0007) +[2026-07-22 22:56:00,670][543983] Updated weights for policy 0, policy_version 9535 (0.0006) +[2026-07-22 22:56:01,686][543983] Updated weights for policy 0, policy_version 9545 (0.0006) +[2026-07-22 22:56:01,993][543983] Updated weights for policy 0, policy_version 9556 (0.0006) +[2026-07-22 22:56:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 4882432. Throughput: 0: 12814.2. Samples: 4924416. Policy #0 lag: (min: 42.0, avg: 82.9, max: 106.0) +[2026-07-22 22:56:02,287][543203] Avg episode reward: [(0, '221.746')] +[2026-07-22 22:56:02,292][543983] Updated weights for policy 0, policy_version 9566 (0.0006) +[2026-07-22 22:56:02,575][543983] Updated weights for policy 0, policy_version 9576 (0.0007) +[2026-07-22 22:56:02,859][543983] Updated weights for policy 0, policy_version 9586 (0.0006) +[2026-07-22 22:56:03,166][543983] Updated weights for policy 0, policy_version 9597 (0.0007) +[2026-07-22 22:56:03,240][543696] Saving new best policy, reward=221.746! +[2026-07-22 22:56:04,199][543983] Updated weights for policy 0, policy_version 9607 (0.0006) +[2026-07-22 22:56:04,491][543983] Updated weights for policy 0, policy_version 9617 (0.0006) +[2026-07-22 22:56:04,772][543983] Updated weights for policy 0, policy_version 9627 (0.0006) +[2026-07-22 22:56:05,057][543983] Updated weights for policy 0, policy_version 9637 (0.0006) +[2026-07-22 22:56:05,335][543983] Updated weights for policy 0, policy_version 9647 (0.0006) +[2026-07-22 22:56:05,604][543983] Updated weights for policy 0, policy_version 9657 (0.0007) +[2026-07-22 22:56:06,672][543983] Updated weights for policy 0, policy_version 9667 (0.0006) +[2026-07-22 22:56:06,965][543983] Updated weights for policy 0, policy_version 9677 (0.0006) +[2026-07-22 22:56:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 4947968. Throughput: 0: 12623.6. Samples: 4960128. Policy #0 lag: (min: 42.0, avg: 82.9, max: 106.0) +[2026-07-22 22:56:07,287][543203] Avg episode reward: [(0, '226.253')] +[2026-07-22 22:56:07,287][543983] Updated weights for policy 0, policy_version 9689 (0.0006) +[2026-07-22 22:56:07,574][543983] Updated weights for policy 0, policy_version 9699 (0.0006) +[2026-07-22 22:56:07,896][543983] Updated weights for policy 0, policy_version 9710 (0.0007) +[2026-07-22 22:56:08,201][543983] Updated weights for policy 0, policy_version 9721 (0.0007) +[2026-07-22 22:56:08,390][543696] Saving new best policy, reward=226.253! +[2026-07-22 22:56:09,239][543983] Updated weights for policy 0, policy_version 9731 (0.0006) +[2026-07-22 22:56:09,520][543983] Updated weights for policy 0, policy_version 9741 (0.0007) +[2026-07-22 22:56:09,794][543983] Updated weights for policy 0, policy_version 9751 (0.0006) +[2026-07-22 22:56:10,083][543983] Updated weights for policy 0, policy_version 9761 (0.0007) +[2026-07-22 22:56:10,361][543983] Updated weights for policy 0, policy_version 9771 (0.0007) +[2026-07-22 22:56:10,664][543983] Updated weights for policy 0, policy_version 9782 (0.0007) +[2026-07-22 22:56:10,966][543983] Updated weights for policy 0, policy_version 9792 (0.0006) +[2026-07-22 22:56:12,036][543983] Updated weights for policy 0, policy_version 9803 (0.0006) +[2026-07-22 22:56:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 5013504. Throughput: 0: 12515.6. Samples: 5031680. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 22:56:12,287][543203] Avg episode reward: [(0, '216.323')] +[2026-07-22 22:56:12,305][543983] Updated weights for policy 0, policy_version 9813 (0.0006) +[2026-07-22 22:56:12,595][543983] Updated weights for policy 0, policy_version 9823 (0.0007) +[2026-07-22 22:56:12,878][543983] Updated weights for policy 0, policy_version 9833 (0.0006) +[2026-07-22 22:56:13,160][543983] Updated weights for policy 0, policy_version 9843 (0.0006) +[2026-07-22 22:56:13,440][543983] Updated weights for policy 0, policy_version 9853 (0.0006) +[2026-07-22 22:56:14,556][543983] Updated weights for policy 0, policy_version 9866 (0.0007) +[2026-07-22 22:56:14,854][543983] Updated weights for policy 0, policy_version 9876 (0.0007) +[2026-07-22 22:56:15,184][543983] Updated weights for policy 0, policy_version 9887 (0.0006) +[2026-07-22 22:56:15,461][543983] Updated weights for policy 0, policy_version 9897 (0.0006) +[2026-07-22 22:56:15,776][543983] Updated weights for policy 0, policy_version 9908 (0.0006) +[2026-07-22 22:56:16,044][543983] Updated weights for policy 0, policy_version 9918 (0.0006) +[2026-07-22 22:56:17,120][543983] Updated weights for policy 0, policy_version 9929 (0.0007) +[2026-07-22 22:56:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12440.7). Total num frames: 5079040. Throughput: 0: 12788.6. Samples: 5115648. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 22:56:17,287][543203] Avg episode reward: [(0, '218.957')] +[2026-07-22 22:56:17,434][543983] Updated weights for policy 0, policy_version 9940 (0.0007) +[2026-07-22 22:56:17,726][543983] Updated weights for policy 0, policy_version 9950 (0.0006) +[2026-07-22 22:56:18,022][543983] Updated weights for policy 0, policy_version 9960 (0.0006) +[2026-07-22 22:56:18,296][543983] Updated weights for policy 0, policy_version 9970 (0.0008) +[2026-07-22 22:56:18,582][543983] Updated weights for policy 0, policy_version 9980 (0.0006) +[2026-07-22 22:56:19,637][543983] Updated weights for policy 0, policy_version 9990 (0.0006) +[2026-07-22 22:56:19,916][543983] Updated weights for policy 0, policy_version 10000 (0.0007) +[2026-07-22 22:56:20,244][543983] Updated weights for policy 0, policy_version 10011 (0.0007) +[2026-07-22 22:56:20,576][543983] Updated weights for policy 0, policy_version 10023 (0.0007) +[2026-07-22 22:56:20,887][543983] Updated weights for policy 0, policy_version 10033 (0.0006) +[2026-07-22 22:56:21,200][543983] Updated weights for policy 0, policy_version 10044 (0.0006) +[2026-07-22 22:56:22,227][543983] Updated weights for policy 0, policy_version 10054 (0.0007) +[2026-07-22 22:56:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12551.8). Total num frames: 5144576. Throughput: 0: 12802.8. Samples: 5152384. Policy #0 lag: (min: 45.0, avg: 62.2, max: 109.0) +[2026-07-22 22:56:22,287][543203] Avg episode reward: [(0, '230.111')] +[2026-07-22 22:56:22,542][543983] Updated weights for policy 0, policy_version 10065 (0.0007) +[2026-07-22 22:56:22,846][543983] Updated weights for policy 0, policy_version 10076 (0.0007) +[2026-07-22 22:56:23,161][543983] Updated weights for policy 0, policy_version 10087 (0.0006) +[2026-07-22 22:56:23,496][543983] Updated weights for policy 0, policy_version 10099 (0.0007) +[2026-07-22 22:56:23,773][543983] Updated weights for policy 0, policy_version 10109 (0.0006) +[2026-07-22 22:56:23,845][543696] Saving new best policy, reward=230.111! +[2026-07-22 22:56:24,870][543983] Updated weights for policy 0, policy_version 10120 (0.0006) +[2026-07-22 22:56:25,174][543983] Updated weights for policy 0, policy_version 10130 (0.0006) +[2026-07-22 22:56:25,455][543983] Updated weights for policy 0, policy_version 10140 (0.0006) +[2026-07-22 22:56:25,738][543983] Updated weights for policy 0, policy_version 10150 (0.0007) +[2026-07-22 22:56:26,040][543983] Updated weights for policy 0, policy_version 10161 (0.0006) +[2026-07-22 22:56:26,335][543983] Updated weights for policy 0, policy_version 10171 (0.0006) +[2026-07-22 22:56:27,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12551.8). Total num frames: 5210112. Throughput: 0: 12529.8. Samples: 5224576. Policy #0 lag: (min: 45.0, avg: 62.2, max: 109.0) +[2026-07-22 22:56:27,287][543203] Avg episode reward: [(0, '236.270')] +[2026-07-22 22:56:27,400][543983] Updated weights for policy 0, policy_version 10182 (0.0006) +[2026-07-22 22:56:27,705][543983] Updated weights for policy 0, policy_version 10193 (0.0006) +[2026-07-22 22:56:28,044][543983] Updated weights for policy 0, policy_version 10205 (0.0006) +[2026-07-22 22:56:28,324][543983] Updated weights for policy 0, policy_version 10215 (0.0006) +[2026-07-22 22:56:28,610][543983] Updated weights for policy 0, policy_version 10225 (0.0007) +[2026-07-22 22:56:28,891][543983] Updated weights for policy 0, policy_version 10235 (0.0007) +[2026-07-22 22:56:29,016][543696] Saving new best policy, reward=236.270! +[2026-07-22 22:56:29,933][543983] Updated weights for policy 0, policy_version 10245 (0.0006) +[2026-07-22 22:56:30,236][543983] Updated weights for policy 0, policy_version 10256 (0.0007) +[2026-07-22 22:56:30,570][543983] Updated weights for policy 0, policy_version 10267 (0.0006) +[2026-07-22 22:56:30,886][543983] Updated weights for policy 0, policy_version 10278 (0.0007) +[2026-07-22 22:56:31,168][543983] Updated weights for policy 0, policy_version 10288 (0.0007) +[2026-07-22 22:56:31,482][543983] Updated weights for policy 0, policy_version 10299 (0.0006) +[2026-07-22 22:56:32,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12551.8). Total num frames: 5275648. Throughput: 0: 12561.1. Samples: 5297920. Policy #0 lag: (min: 18.0, avg: 51.7, max: 82.0) +[2026-07-22 22:56:32,287][543203] Avg episode reward: [(0, '241.184')] +[2026-07-22 22:56:32,544][543983] Updated weights for policy 0, policy_version 10310 (0.0006) +[2026-07-22 22:56:32,828][543983] Updated weights for policy 0, policy_version 10320 (0.0006) +[2026-07-22 22:56:33,097][543983] Updated weights for policy 0, policy_version 10330 (0.0006) +[2026-07-22 22:56:33,390][543983] Updated weights for policy 0, policy_version 10340 (0.0006) +[2026-07-22 22:56:33,675][543983] Updated weights for policy 0, policy_version 10350 (0.0007) +[2026-07-22 22:56:34,015][543983] Updated weights for policy 0, policy_version 10362 (0.0006) +[2026-07-22 22:56:34,173][543696] Saving new best policy, reward=241.184! +[2026-07-22 22:56:35,052][543983] Updated weights for policy 0, policy_version 10372 (0.0007) +[2026-07-22 22:56:35,343][543983] Updated weights for policy 0, policy_version 10382 (0.0006) +[2026-07-22 22:56:35,646][543983] Updated weights for policy 0, policy_version 10393 (0.0006) +[2026-07-22 22:56:35,922][543983] Updated weights for policy 0, policy_version 10403 (0.0007) +[2026-07-22 22:56:36,251][543983] Updated weights for policy 0, policy_version 10414 (0.0008) +[2026-07-22 22:56:36,535][543983] Updated weights for policy 0, policy_version 10424 (0.0006) +[2026-07-22 22:56:37,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12551.8). Total num frames: 5341184. Throughput: 0: 12757.3. Samples: 5342464. Policy #0 lag: (min: 18.0, avg: 51.7, max: 82.0) +[2026-07-22 22:56:37,287][543203] Avg episode reward: [(0, '247.597')] +[2026-07-22 22:56:37,293][543696] Saving new best policy, reward=247.597! +[2026-07-22 22:56:37,611][543983] Updated weights for policy 0, policy_version 10434 (0.0006) +[2026-07-22 22:56:37,925][543983] Updated weights for policy 0, policy_version 10445 (0.0006) +[2026-07-22 22:56:38,202][543983] Updated weights for policy 0, policy_version 10455 (0.0006) +[2026-07-22 22:56:38,521][543983] Updated weights for policy 0, policy_version 10467 (0.0006) +[2026-07-22 22:56:38,814][543983] Updated weights for policy 0, policy_version 10477 (0.0007) +[2026-07-22 22:56:39,102][543983] Updated weights for policy 0, policy_version 10487 (0.0007) +[2026-07-22 22:56:40,152][543983] Updated weights for policy 0, policy_version 10497 (0.0007) +[2026-07-22 22:56:40,462][543983] Updated weights for policy 0, policy_version 10508 (0.0006) +[2026-07-22 22:56:40,759][543983] Updated weights for policy 0, policy_version 10518 (0.0006) +[2026-07-22 22:56:41,085][543983] Updated weights for policy 0, policy_version 10529 (0.0007) +[2026-07-22 22:56:41,381][543983] Updated weights for policy 0, policy_version 10539 (0.0006) +[2026-07-22 22:56:41,674][543983] Updated weights for policy 0, policy_version 10550 (0.0006) +[2026-07-22 22:56:41,962][543983] Updated weights for policy 0, policy_version 10560 (0.0007) +[2026-07-22 22:56:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12551.8). Total num frames: 5406720. Throughput: 0: 12717.5. Samples: 5416576. Policy #0 lag: (min: 31.0, avg: 47.6, max: 95.0) +[2026-07-22 22:56:42,287][543203] Avg episode reward: [(0, '262.975')] +[2026-07-22 22:56:42,293][543696] Saving new best policy, reward=262.975! +[2026-07-22 22:56:43,054][543983] Updated weights for policy 0, policy_version 10571 (0.0007) +[2026-07-22 22:56:43,334][543983] Updated weights for policy 0, policy_version 10581 (0.0007) +[2026-07-22 22:56:43,669][543983] Updated weights for policy 0, policy_version 10593 (0.0006) +[2026-07-22 22:56:43,980][543983] Updated weights for policy 0, policy_version 10604 (0.0006) +[2026-07-22 22:56:44,250][543983] Updated weights for policy 0, policy_version 10614 (0.0006) +[2026-07-22 22:56:45,324][543983] Updated weights for policy 0, policy_version 10625 (0.0006) +[2026-07-22 22:56:45,607][543983] Updated weights for policy 0, policy_version 10635 (0.0007) +[2026-07-22 22:56:45,916][543983] Updated weights for policy 0, policy_version 10646 (0.0006) +[2026-07-22 22:56:46,197][543983] Updated weights for policy 0, policy_version 10656 (0.0006) +[2026-07-22 22:56:46,502][543983] Updated weights for policy 0, policy_version 10667 (0.0007) +[2026-07-22 22:56:46,789][543983] Updated weights for policy 0, policy_version 10677 (0.0006) +[2026-07-22 22:56:47,071][543983] Updated weights for policy 0, policy_version 10687 (0.0006) +[2026-07-22 22:56:47,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12551.8). Total num frames: 5472256. Throughput: 0: 12541.1. Samples: 5488768. Policy #0 lag: (min: 31.0, avg: 47.6, max: 95.0) +[2026-07-22 22:56:47,287][543203] Avg episode reward: [(0, '287.082')] +[2026-07-22 22:56:47,293][543696] Saving new best policy, reward=287.082! +[2026-07-22 22:56:48,150][543983] Updated weights for policy 0, policy_version 10698 (0.0007) +[2026-07-22 22:56:48,446][543983] Updated weights for policy 0, policy_version 10708 (0.0006) +[2026-07-22 22:56:48,716][543983] Updated weights for policy 0, policy_version 10718 (0.0007) +[2026-07-22 22:56:48,999][543983] Updated weights for policy 0, policy_version 10728 (0.0006) +[2026-07-22 22:56:49,277][543983] Updated weights for policy 0, policy_version 10738 (0.0006) +[2026-07-22 22:56:49,561][543983] Updated weights for policy 0, policy_version 10748 (0.0006) +[2026-07-22 22:56:50,616][543983] Updated weights for policy 0, policy_version 10758 (0.0007) +[2026-07-22 22:56:50,906][543983] Updated weights for policy 0, policy_version 10768 (0.0006) +[2026-07-22 22:56:51,195][543983] Updated weights for policy 0, policy_version 10778 (0.0006) +[2026-07-22 22:56:51,468][543983] Updated weights for policy 0, policy_version 10788 (0.0006) +[2026-07-22 22:56:51,787][543983] Updated weights for policy 0, policy_version 10799 (0.0006) +[2026-07-22 22:56:52,084][543983] Updated weights for policy 0, policy_version 10810 (0.0006) +[2026-07-22 22:56:52,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12551.8). Total num frames: 5537792. Throughput: 0: 12549.7. Samples: 5524864. Policy #0 lag: (min: 63.0, avg: 78.6, max: 127.0) +[2026-07-22 22:56:52,287][543203] Avg episode reward: [(0, '289.802')] +[2026-07-22 22:56:52,293][543696] Saving new best policy, reward=289.802! +[2026-07-22 22:56:53,146][543983] Updated weights for policy 0, policy_version 10820 (0.0006) +[2026-07-22 22:56:53,426][543983] Updated weights for policy 0, policy_version 10830 (0.0006) +[2026-07-22 22:56:53,696][543983] Updated weights for policy 0, policy_version 10840 (0.0006) +[2026-07-22 22:56:54,006][543983] Updated weights for policy 0, policy_version 10850 (0.0006) +[2026-07-22 22:56:54,291][543983] Updated weights for policy 0, policy_version 10860 (0.0006) +[2026-07-22 22:56:54,590][543983] Updated weights for policy 0, policy_version 10871 (0.0006) +[2026-07-22 22:56:55,676][543983] Updated weights for policy 0, policy_version 10882 (0.0006) +[2026-07-22 22:56:55,953][543983] Updated weights for policy 0, policy_version 10892 (0.0006) +[2026-07-22 22:56:56,240][543983] Updated weights for policy 0, policy_version 10902 (0.0007) +[2026-07-22 22:56:56,514][543983] Updated weights for policy 0, policy_version 10912 (0.0006) +[2026-07-22 22:56:56,801][543983] Updated weights for policy 0, policy_version 10922 (0.0006) +[2026-07-22 22:56:57,094][543983] Updated weights for policy 0, policy_version 10932 (0.0007) +[2026-07-22 22:56:57,286][543203] Fps is (10 sec: 9830.5, 60 sec: 12561.1, 300 sec: 12551.8). Total num frames: 5570560. Throughput: 0: 12805.7. Samples: 5607936. Policy #0 lag: (min: 63.0, avg: 78.6, max: 127.0) +[2026-07-22 22:56:57,287][543203] Avg episode reward: [(0, '300.846')] +[2026-07-22 22:56:57,372][543983] Updated weights for policy 0, policy_version 10942 (0.0007) +[2026-07-22 22:56:57,424][543696] Saving new best policy, reward=300.846! +[2026-07-22 22:56:58,410][543983] Updated weights for policy 0, policy_version 10952 (0.0006) +[2026-07-22 22:56:58,723][543983] Updated weights for policy 0, policy_version 10963 (0.0006) +[2026-07-22 22:56:59,026][543983] Updated weights for policy 0, policy_version 10973 (0.0006) +[2026-07-22 22:56:59,326][543983] Updated weights for policy 0, policy_version 10984 (0.0006) +[2026-07-22 22:56:59,614][543983] Updated weights for policy 0, policy_version 10994 (0.0007) +[2026-07-22 22:56:59,906][543983] Updated weights for policy 0, policy_version 11004 (0.0006) +[2026-07-22 22:57:00,939][543983] Updated weights for policy 0, policy_version 11014 (0.0007) +[2026-07-22 22:57:01,287][543983] Updated weights for policy 0, policy_version 11026 (0.0006) +[2026-07-22 22:57:01,600][543983] Updated weights for policy 0, policy_version 11037 (0.0007) +[2026-07-22 22:57:01,897][543983] Updated weights for policy 0, policy_version 11048 (0.0007) +[2026-07-22 22:57:02,178][543983] Updated weights for policy 0, policy_version 11058 (0.0006) +[2026-07-22 22:57:02,286][543203] Fps is (10 sec: 9830.3, 60 sec: 12561.1, 300 sec: 12551.8). Total num frames: 5636096. Throughput: 0: 12544.0. Samples: 5680128. Policy #0 lag: (min: 63.0, avg: 78.6, max: 127.0) +[2026-07-22 22:57:02,287][543203] Avg episode reward: [(0, '310.271')] +[2026-07-22 22:57:02,465][543983] Updated weights for policy 0, policy_version 11068 (0.0007) +[2026-07-22 22:57:02,568][543696] Saving new best policy, reward=310.271! +[2026-07-22 22:57:03,531][543983] Updated weights for policy 0, policy_version 11078 (0.0006) +[2026-07-22 22:57:03,817][543983] Updated weights for policy 0, policy_version 11088 (0.0006) +[2026-07-22 22:57:04,084][543983] Updated weights for policy 0, policy_version 11098 (0.0006) +[2026-07-22 22:57:04,381][543983] Updated weights for policy 0, policy_version 11108 (0.0007) +[2026-07-22 22:57:04,658][543983] Updated weights for policy 0, policy_version 11118 (0.0007) +[2026-07-22 22:57:04,967][543983] Updated weights for policy 0, policy_version 11129 (0.0006) +[2026-07-22 22:57:06,059][543983] Updated weights for policy 0, policy_version 11140 (0.0006) +[2026-07-22 22:57:06,339][543983] Updated weights for policy 0, policy_version 11150 (0.0007) +[2026-07-22 22:57:06,663][543983] Updated weights for policy 0, policy_version 11162 (0.0006) +[2026-07-22 22:57:06,957][543983] Updated weights for policy 0, policy_version 11172 (0.0006) +[2026-07-22 22:57:07,251][543983] Updated weights for policy 0, policy_version 11182 (0.0006) +[2026-07-22 22:57:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12551.8). Total num frames: 5701632. Throughput: 0: 12521.3. Samples: 5715840. Policy #0 lag: (min: 17.0, avg: 44.4, max: 81.0) +[2026-07-22 22:57:07,287][543203] Avg episode reward: [(0, '311.887')] +[2026-07-22 22:57:07,526][543983] Updated weights for policy 0, policy_version 11192 (0.0006) +[2026-07-22 22:57:07,746][543696] Saving new best policy, reward=311.887! +[2026-07-22 22:57:08,560][543983] Updated weights for policy 0, policy_version 11202 (0.0006) +[2026-07-22 22:57:08,870][543983] Updated weights for policy 0, policy_version 11213 (0.0006) +[2026-07-22 22:57:09,152][543983] Updated weights for policy 0, policy_version 11223 (0.0006) +[2026-07-22 22:57:09,436][543983] Updated weights for policy 0, policy_version 11233 (0.0007) +[2026-07-22 22:57:09,749][543983] Updated weights for policy 0, policy_version 11244 (0.0006) +[2026-07-22 22:57:10,029][543983] Updated weights for policy 0, policy_version 11254 (0.0006) +[2026-07-22 22:57:10,313][543983] Updated weights for policy 0, policy_version 11264 (0.0006) +[2026-07-22 22:57:11,376][543983] Updated weights for policy 0, policy_version 11274 (0.0006) +[2026-07-22 22:57:11,657][543983] Updated weights for policy 0, policy_version 11284 (0.0006) +[2026-07-22 22:57:11,946][543983] Updated weights for policy 0, policy_version 11294 (0.0006) +[2026-07-22 22:57:12,207][543983] Updated weights for policy 0, policy_version 11304 (0.0006) +[2026-07-22 22:57:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12551.8). Total num frames: 5767168. Throughput: 0: 12694.8. Samples: 5795840. Policy #0 lag: (min: 17.0, avg: 44.4, max: 81.0) +[2026-07-22 22:57:12,287][543203] Avg episode reward: [(0, '307.530')] +[2026-07-22 22:57:12,510][543983] Updated weights for policy 0, policy_version 11314 (0.0006) +[2026-07-22 22:57:12,819][543983] Updated weights for policy 0, policy_version 11325 (0.0007) +[2026-07-22 22:57:13,876][543983] Updated weights for policy 0, policy_version 11335 (0.0006) +[2026-07-22 22:57:14,147][543983] Updated weights for policy 0, policy_version 11345 (0.0006) +[2026-07-22 22:57:14,419][543983] Updated weights for policy 0, policy_version 11355 (0.0006) +[2026-07-22 22:57:14,707][543983] Updated weights for policy 0, policy_version 11365 (0.0007) +[2026-07-22 22:57:15,021][543983] Updated weights for policy 0, policy_version 11376 (0.0006) +[2026-07-22 22:57:15,329][543983] Updated weights for policy 0, policy_version 11387 (0.0007) +[2026-07-22 22:57:16,386][543983] Updated weights for policy 0, policy_version 11397 (0.0006) +[2026-07-22 22:57:16,717][543983] Updated weights for policy 0, policy_version 11408 (0.0006) +[2026-07-22 22:57:17,009][543983] Updated weights for policy 0, policy_version 11419 (0.0007) +[2026-07-22 22:57:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12551.8). Total num frames: 5832704. Throughput: 0: 12774.4. Samples: 5872768. Policy #0 lag: (min: 63.0, avg: 78.9, max: 127.0) +[2026-07-22 22:57:17,287][543203] Avg episode reward: [(0, '319.707')] +[2026-07-22 22:57:17,296][543983] Updated weights for policy 0, policy_version 11429 (0.0007) +[2026-07-22 22:57:17,618][543983] Updated weights for policy 0, policy_version 11440 (0.0006) +[2026-07-22 22:57:17,899][543983] Updated weights for policy 0, policy_version 11450 (0.0006) +[2026-07-22 22:57:18,054][543696] Saving new best policy, reward=319.707! +[2026-07-22 22:57:18,937][543983] Updated weights for policy 0, policy_version 11460 (0.0006) +[2026-07-22 22:57:19,249][543983] Updated weights for policy 0, policy_version 11471 (0.0006) +[2026-07-22 22:57:19,557][543983] Updated weights for policy 0, policy_version 11482 (0.0006) +[2026-07-22 22:57:19,852][543983] Updated weights for policy 0, policy_version 11493 (0.0006) +[2026-07-22 22:57:20,145][543983] Updated weights for policy 0, policy_version 11503 (0.0006) +[2026-07-22 22:57:20,437][543983] Updated weights for policy 0, policy_version 11513 (0.0006) +[2026-07-22 22:57:21,503][543983] Updated weights for policy 0, policy_version 11523 (0.0006) +[2026-07-22 22:57:21,812][543983] Updated weights for policy 0, policy_version 11534 (0.0007) +[2026-07-22 22:57:22,095][543983] Updated weights for policy 0, policy_version 11544 (0.0006) +[2026-07-22 22:57:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12551.8). Total num frames: 5898240. Throughput: 0: 12572.4. Samples: 5908224. Policy #0 lag: (min: 63.0, avg: 78.9, max: 127.0) +[2026-07-22 22:57:22,287][543203] Avg episode reward: [(0, '325.509')] +[2026-07-22 22:57:22,378][543983] Updated weights for policy 0, policy_version 11554 (0.0006) +[2026-07-22 22:57:22,707][543983] Updated weights for policy 0, policy_version 11566 (0.0006) +[2026-07-22 22:57:22,997][543983] Updated weights for policy 0, policy_version 11576 (0.0008) +[2026-07-22 22:57:23,212][543696] Saving new best policy, reward=325.509! +[2026-07-22 22:57:24,070][543983] Updated weights for policy 0, policy_version 11587 (0.0006) +[2026-07-22 22:57:24,358][543983] Updated weights for policy 0, policy_version 11597 (0.0006) +[2026-07-22 22:57:24,670][543983] Updated weights for policy 0, policy_version 11608 (0.0006) +[2026-07-22 22:57:24,972][543983] Updated weights for policy 0, policy_version 11618 (0.0006) +[2026-07-22 22:57:25,276][543983] Updated weights for policy 0, policy_version 11629 (0.0006) +[2026-07-22 22:57:25,576][543983] Updated weights for policy 0, policy_version 11639 (0.0006) +[2026-07-22 22:57:26,602][543983] Updated weights for policy 0, policy_version 11649 (0.0006) +[2026-07-22 22:57:26,880][543983] Updated weights for policy 0, policy_version 11659 (0.0006) +[2026-07-22 22:57:27,169][543983] Updated weights for policy 0, policy_version 11669 (0.0006) +[2026-07-22 22:57:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12551.8). Total num frames: 5963776. Throughput: 0: 12541.2. Samples: 5980928. Policy #0 lag: (min: 32.0, avg: 56.9, max: 96.0) +[2026-07-22 22:57:27,287][543203] Avg episode reward: [(0, '333.659')] +[2026-07-22 22:57:27,481][543983] Updated weights for policy 0, policy_version 11680 (0.0006) +[2026-07-22 22:57:27,764][543983] Updated weights for policy 0, policy_version 11690 (0.0006) +[2026-07-22 22:57:28,052][543983] Updated weights for policy 0, policy_version 11700 (0.0006) +[2026-07-22 22:57:28,330][543983] Updated weights for policy 0, policy_version 11710 (0.0006) +[2026-07-22 22:57:28,375][543696] Saving new best policy, reward=333.659! +[2026-07-22 22:57:29,458][543983] Updated weights for policy 0, policy_version 11723 (0.0006) +[2026-07-22 22:57:29,758][543983] Updated weights for policy 0, policy_version 11733 (0.0006) +[2026-07-22 22:57:30,046][543983] Updated weights for policy 0, policy_version 11743 (0.0008) +[2026-07-22 22:57:30,328][543983] Updated weights for policy 0, policy_version 11753 (0.0006) +[2026-07-22 22:57:30,633][543983] Updated weights for policy 0, policy_version 11764 (0.0006) +[2026-07-22 22:57:30,921][543983] Updated weights for policy 0, policy_version 11774 (0.0006) +[2026-07-22 22:57:31,969][543983] Updated weights for policy 0, policy_version 11784 (0.0006) +[2026-07-22 22:57:32,262][543983] Updated weights for policy 0, policy_version 11794 (0.0006) +[2026-07-22 22:57:32,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 6029312. Throughput: 0: 12802.9. Samples: 6064896. Policy #0 lag: (min: 32.0, avg: 56.9, max: 96.0) +[2026-07-22 22:57:32,287][543203] Avg episode reward: [(0, '336.012')] +[2026-07-22 22:57:32,569][543983] Updated weights for policy 0, policy_version 11805 (0.0006) +[2026-07-22 22:57:32,849][543983] Updated weights for policy 0, policy_version 11815 (0.0007) +[2026-07-22 22:57:33,171][543983] Updated weights for policy 0, policy_version 11826 (0.0006) +[2026-07-22 22:57:33,493][543983] Updated weights for policy 0, policy_version 11837 (0.0006) +[2026-07-22 22:57:33,560][543696] Saving new best policy, reward=336.012! +[2026-07-22 22:57:34,501][543983] Updated weights for policy 0, policy_version 11847 (0.0006) +[2026-07-22 22:57:34,824][543983] Updated weights for policy 0, policy_version 11858 (0.0006) +[2026-07-22 22:57:35,099][543983] Updated weights for policy 0, policy_version 11868 (0.0007) +[2026-07-22 22:57:35,384][543983] Updated weights for policy 0, policy_version 11878 (0.0006) +[2026-07-22 22:57:35,667][543983] Updated weights for policy 0, policy_version 11888 (0.0006) +[2026-07-22 22:57:35,966][543983] Updated weights for policy 0, policy_version 11899 (0.0006) +[2026-07-22 22:57:37,041][543983] Updated weights for policy 0, policy_version 11909 (0.0007) +[2026-07-22 22:57:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 6094848. Throughput: 0: 12797.1. Samples: 6100736. Policy #0 lag: (min: 63.0, avg: 80.2, max: 127.0) +[2026-07-22 22:57:37,287][543203] Avg episode reward: [(0, '339.367')] +[2026-07-22 22:57:37,321][543983] Updated weights for policy 0, policy_version 11919 (0.0008) +[2026-07-22 22:57:37,606][543983] Updated weights for policy 0, policy_version 11929 (0.0006) +[2026-07-22 22:57:37,889][543983] Updated weights for policy 0, policy_version 11939 (0.0006) +[2026-07-22 22:57:38,213][543983] Updated weights for policy 0, policy_version 11951 (0.0006) +[2026-07-22 22:57:38,496][543983] Updated weights for policy 0, policy_version 11961 (0.0006) +[2026-07-22 22:57:38,697][543696] Saving new best policy, reward=339.367! +[2026-07-22 22:57:39,561][543983] Updated weights for policy 0, policy_version 11971 (0.0006) +[2026-07-22 22:57:39,874][543983] Updated weights for policy 0, policy_version 11982 (0.0006) +[2026-07-22 22:57:40,157][543983] Updated weights for policy 0, policy_version 11992 (0.0007) +[2026-07-22 22:57:40,423][543983] Updated weights for policy 0, policy_version 12002 (0.0006) +[2026-07-22 22:57:40,744][543983] Updated weights for policy 0, policy_version 12013 (0.0007) +[2026-07-22 22:57:41,025][543983] Updated weights for policy 0, policy_version 12023 (0.0007) +[2026-07-22 22:57:42,085][543983] Updated weights for policy 0, policy_version 12033 (0.0006) +[2026-07-22 22:57:42,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 6160384. Throughput: 0: 12549.7. Samples: 6172672. Policy #0 lag: (min: 63.0, avg: 80.2, max: 127.0) +[2026-07-22 22:57:42,287][543203] Avg episode reward: [(0, '347.923')] +[2026-07-22 22:57:42,387][543983] Updated weights for policy 0, policy_version 12044 (0.0007) +[2026-07-22 22:57:42,674][543983] Updated weights for policy 0, policy_version 12054 (0.0007) +[2026-07-22 22:57:42,946][543983] Updated weights for policy 0, policy_version 12064 (0.0006) +[2026-07-22 22:57:43,233][543983] Updated weights for policy 0, policy_version 12074 (0.0007) +[2026-07-22 22:57:43,583][543983] Updated weights for policy 0, policy_version 12086 (0.0008) +[2026-07-22 22:57:43,849][543696] Saving new best policy, reward=347.923! +[2026-07-22 22:57:43,855][543983] Updated weights for policy 0, policy_version 12096 (0.0007) +[2026-07-22 22:57:44,912][543983] Updated weights for policy 0, policy_version 12107 (0.0007) +[2026-07-22 22:57:45,221][543983] Updated weights for policy 0, policy_version 12117 (0.0008) +[2026-07-22 22:57:45,504][543983] Updated weights for policy 0, policy_version 12127 (0.0006) +[2026-07-22 22:57:45,833][543983] Updated weights for policy 0, policy_version 12139 (0.0006) +[2026-07-22 22:57:46,146][543983] Updated weights for policy 0, policy_version 12150 (0.0006) +[2026-07-22 22:57:46,427][543983] Updated weights for policy 0, policy_version 12160 (0.0007) +[2026-07-22 22:57:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 6225920. Throughput: 0: 12657.8. Samples: 6249728. Policy #0 lag: (min: 63.0, avg: 80.2, max: 127.0) +[2026-07-22 22:57:47,287][543203] Avg episode reward: [(0, '359.356')] +[2026-07-22 22:57:47,467][543983] Updated weights for policy 0, policy_version 12170 (0.0007) +[2026-07-22 22:57:47,770][543983] Updated weights for policy 0, policy_version 12180 (0.0007) +[2026-07-22 22:57:48,124][543983] Updated weights for policy 0, policy_version 12192 (0.0007) +[2026-07-22 22:57:48,407][543983] Updated weights for policy 0, policy_version 12202 (0.0006) +[2026-07-22 22:57:48,695][543983] Updated weights for policy 0, policy_version 12212 (0.0006) +[2026-07-22 22:57:48,972][543983] Updated weights for policy 0, policy_version 12222 (0.0006) +[2026-07-22 22:57:49,025][543696] Saving new best policy, reward=359.356! +[2026-07-22 22:57:50,012][543983] Updated weights for policy 0, policy_version 12232 (0.0006) +[2026-07-22 22:57:50,309][543983] Updated weights for policy 0, policy_version 12242 (0.0007) +[2026-07-22 22:57:50,638][543983] Updated weights for policy 0, policy_version 12254 (0.0006) +[2026-07-22 22:57:50,947][543983] Updated weights for policy 0, policy_version 12265 (0.0006) +[2026-07-22 22:57:51,228][543983] Updated weights for policy 0, policy_version 12275 (0.0006) +[2026-07-22 22:57:51,564][543983] Updated weights for policy 0, policy_version 12287 (0.0006) +[2026-07-22 22:57:52,286][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 6291456. Throughput: 0: 12828.5. Samples: 6293120. Policy #0 lag: (min: 30.0, avg: 46.2, max: 94.0) +[2026-07-22 22:57:52,287][543203] Avg episode reward: [(0, '359.550')] +[2026-07-22 22:57:52,653][543983] Updated weights for policy 0, policy_version 12297 (0.0006) +[2026-07-22 22:57:52,924][543983] Updated weights for policy 0, policy_version 12307 (0.0006) +[2026-07-22 22:57:53,243][543983] Updated weights for policy 0, policy_version 12318 (0.0006) +[2026-07-22 22:57:53,559][543983] Updated weights for policy 0, policy_version 12329 (0.0006) +[2026-07-22 22:57:53,845][543983] Updated weights for policy 0, policy_version 12339 (0.0007) +[2026-07-22 22:57:54,132][543983] Updated weights for policy 0, policy_version 12349 (0.0006) +[2026-07-22 22:57:54,206][543696] Saving new best policy, reward=359.550! +[2026-07-22 22:57:55,161][543983] Updated weights for policy 0, policy_version 12359 (0.0006) +[2026-07-22 22:57:55,430][543983] Updated weights for policy 0, policy_version 12369 (0.0006) +[2026-07-22 22:57:55,732][543983] Updated weights for policy 0, policy_version 12379 (0.0007) +[2026-07-22 22:57:56,030][543983] Updated weights for policy 0, policy_version 12390 (0.0006) +[2026-07-22 22:57:56,296][543983] Updated weights for policy 0, policy_version 12400 (0.0006) +[2026-07-22 22:57:56,674][543983] Updated weights for policy 0, policy_version 12413 (0.0006) +[2026-07-22 22:57:57,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 6356992. Throughput: 0: 12643.6. Samples: 6364800. Policy #0 lag: (min: 30.0, avg: 46.2, max: 94.0) +[2026-07-22 22:57:57,287][543203] Avg episode reward: [(0, '362.312')] +[2026-07-22 22:57:57,293][543696] Saving new best policy, reward=362.312! +[2026-07-22 22:57:57,806][543983] Updated weights for policy 0, policy_version 12426 (0.0007) +[2026-07-22 22:57:58,099][543983] Updated weights for policy 0, policy_version 12436 (0.0006) +[2026-07-22 22:57:58,374][543983] Updated weights for policy 0, policy_version 12446 (0.0006) +[2026-07-22 22:57:58,669][543983] Updated weights for policy 0, policy_version 12456 (0.0006) +[2026-07-22 22:57:58,947][543983] Updated weights for policy 0, policy_version 12466 (0.0006) +[2026-07-22 22:57:59,246][543983] Updated weights for policy 0, policy_version 12477 (0.0006) +[2026-07-22 22:57:59,336][543696] Early stopping after 8 epochs (64 sgd steps), loss delta 0.0000001 +[2026-07-22 22:58:00,306][543983] Updated weights for policy 0, policy_version 12487 (0.0006) +[2026-07-22 22:58:00,666][543983] Updated weights for policy 0, policy_version 12500 (0.0006) +[2026-07-22 22:58:01,002][543983] Updated weights for policy 0, policy_version 12512 (0.0007) +[2026-07-22 22:58:01,318][543983] Updated weights for policy 0, policy_version 12523 (0.0006) +[2026-07-22 22:58:01,601][543983] Updated weights for policy 0, policy_version 12533 (0.0006) +[2026-07-22 22:58:01,882][543983] Updated weights for policy 0, policy_version 12543 (0.0006) +[2026-07-22 22:58:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 6422528. Throughput: 0: 12526.9. Samples: 6436480. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 22:58:02,287][543203] Avg episode reward: [(0, '367.889')] +[2026-07-22 22:58:02,293][543696] Saving new best policy, reward=367.889! +[2026-07-22 22:58:03,013][543983] Updated weights for policy 0, policy_version 12555 (0.0006) +[2026-07-22 22:58:03,325][543983] Updated weights for policy 0, policy_version 12566 (0.0006) +[2026-07-22 22:58:03,621][543983] Updated weights for policy 0, policy_version 12576 (0.0006) +[2026-07-22 22:58:03,900][543983] Updated weights for policy 0, policy_version 12586 (0.0006) +[2026-07-22 22:58:04,189][543983] Updated weights for policy 0, policy_version 12596 (0.0006) +[2026-07-22 22:58:04,486][543983] Updated weights for policy 0, policy_version 12607 (0.0006) +[2026-07-22 22:58:05,543][543983] Updated weights for policy 0, policy_version 12617 (0.0007) +[2026-07-22 22:58:05,869][543983] Updated weights for policy 0, policy_version 12628 (0.0006) +[2026-07-22 22:58:06,167][543983] Updated weights for policy 0, policy_version 12639 (0.0006) +[2026-07-22 22:58:06,458][543983] Updated weights for policy 0, policy_version 12649 (0.0006) +[2026-07-22 22:58:06,737][543983] Updated weights for policy 0, policy_version 12659 (0.0006) +[2026-07-22 22:58:07,030][543983] Updated weights for policy 0, policy_version 12669 (0.0008) +[2026-07-22 22:58:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 6488064. Throughput: 0: 12635.0. Samples: 6476800. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 22:58:07,287][543203] Avg episode reward: [(0, '375.688')] +[2026-07-22 22:58:07,293][543696] Saving new best policy, reward=375.688! +[2026-07-22 22:58:08,084][543983] Updated weights for policy 0, policy_version 12679 (0.0007) +[2026-07-22 22:58:08,374][543983] Updated weights for policy 0, policy_version 12689 (0.0007) +[2026-07-22 22:58:08,683][543983] Updated weights for policy 0, policy_version 12700 (0.0006) +[2026-07-22 22:58:08,955][543983] Updated weights for policy 0, policy_version 12710 (0.0007) +[2026-07-22 22:58:09,282][543983] Updated weights for policy 0, policy_version 12721 (0.0006) +[2026-07-22 22:58:09,557][543983] Updated weights for policy 0, policy_version 12731 (0.0006) +[2026-07-22 22:58:10,627][543983] Updated weights for policy 0, policy_version 12741 (0.0006) +[2026-07-22 22:58:10,919][543983] Updated weights for policy 0, policy_version 12751 (0.0006) +[2026-07-22 22:58:11,232][543983] Updated weights for policy 0, policy_version 12762 (0.0007) +[2026-07-22 22:58:11,524][543983] Updated weights for policy 0, policy_version 12772 (0.0006) +[2026-07-22 22:58:11,819][543983] Updated weights for policy 0, policy_version 12783 (0.0006) +[2026-07-22 22:58:12,130][543983] Updated weights for policy 0, policy_version 12794 (0.0007) +[2026-07-22 22:58:12,287][543203] Fps is (10 sec: 9830.3, 60 sec: 12561.1, 300 sec: 12551.8). Total num frames: 6520832. Throughput: 0: 12834.1. Samples: 6558464. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 22:58:12,287][543203] Avg episode reward: [(0, '370.867')] +[2026-07-22 22:58:13,213][543983] Updated weights for policy 0, policy_version 12804 (0.0006) +[2026-07-22 22:58:13,537][543983] Updated weights for policy 0, policy_version 12815 (0.0007) +[2026-07-22 22:58:13,816][543983] Updated weights for policy 0, policy_version 12825 (0.0006) +[2026-07-22 22:58:14,126][543983] Updated weights for policy 0, policy_version 12836 (0.0007) +[2026-07-22 22:58:14,448][543983] Updated weights for policy 0, policy_version 12847 (0.0006) +[2026-07-22 22:58:14,703][543983] Updated weights for policy 0, policy_version 12857 (0.0006) +[2026-07-22 22:58:15,787][543983] Updated weights for policy 0, policy_version 12868 (0.0006) +[2026-07-22 22:58:16,068][543983] Updated weights for policy 0, policy_version 12878 (0.0006) +[2026-07-22 22:58:16,348][543983] Updated weights for policy 0, policy_version 12888 (0.0006) +[2026-07-22 22:58:16,692][543983] Updated weights for policy 0, policy_version 12900 (0.0006) +[2026-07-22 22:58:16,975][543983] Updated weights for policy 0, policy_version 12910 (0.0006) +[2026-07-22 22:58:17,262][543983] Updated weights for policy 0, policy_version 12920 (0.0007) +[2026-07-22 22:58:17,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 6586368. Throughput: 0: 12583.8. Samples: 6631168. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 22:58:17,287][543203] Avg episode reward: [(0, '383.728')] +[2026-07-22 22:58:17,476][543696] Saving new best policy, reward=383.728! +[2026-07-22 22:58:18,328][543983] Updated weights for policy 0, policy_version 12930 (0.0006) +[2026-07-22 22:58:18,636][543983] Updated weights for policy 0, policy_version 12941 (0.0007) +[2026-07-22 22:58:18,928][543983] Updated weights for policy 0, policy_version 12951 (0.0006) +[2026-07-22 22:58:19,242][543983] Updated weights for policy 0, policy_version 12962 (0.0006) +[2026-07-22 22:58:19,548][543983] Updated weights for policy 0, policy_version 12973 (0.0006) +[2026-07-22 22:58:19,830][543983] Updated weights for policy 0, policy_version 12983 (0.0007) +[2026-07-22 22:58:20,906][543983] Updated weights for policy 0, policy_version 12994 (0.0006) +[2026-07-22 22:58:21,179][543983] Updated weights for policy 0, policy_version 13004 (0.0006) +[2026-07-22 22:58:21,480][543983] Updated weights for policy 0, policy_version 13015 (0.0006) +[2026-07-22 22:58:21,767][543983] Updated weights for policy 0, policy_version 13025 (0.0006) +[2026-07-22 22:58:22,085][543983] Updated weights for policy 0, policy_version 13036 (0.0006) +[2026-07-22 22:58:22,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 6651904. Throughput: 0: 12598.0. Samples: 6667648. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 22:58:22,287][543203] Avg episode reward: [(0, '401.746')] +[2026-07-22 22:58:22,387][543983] Updated weights for policy 0, policy_version 13047 (0.0006) +[2026-07-22 22:58:22,629][543696] Saving new best policy, reward=401.746! +[2026-07-22 22:58:23,467][543983] Updated weights for policy 0, policy_version 13058 (0.0006) +[2026-07-22 22:58:23,765][543983] Updated weights for policy 0, policy_version 13068 (0.0006) +[2026-07-22 22:58:24,034][543983] Updated weights for policy 0, policy_version 13078 (0.0006) +[2026-07-22 22:58:24,328][543983] Updated weights for policy 0, policy_version 13088 (0.0006) +[2026-07-22 22:58:24,625][543983] Updated weights for policy 0, policy_version 13098 (0.0006) +[2026-07-22 22:58:24,932][543983] Updated weights for policy 0, policy_version 13109 (0.0006) +[2026-07-22 22:58:25,222][543983] Updated weights for policy 0, policy_version 13119 (0.0006) +[2026-07-22 22:58:26,265][543983] Updated weights for policy 0, policy_version 13129 (0.0006) +[2026-07-22 22:58:26,551][543983] Updated weights for policy 0, policy_version 13139 (0.0006) +[2026-07-22 22:58:26,827][543983] Updated weights for policy 0, policy_version 13149 (0.0006) +[2026-07-22 22:58:27,148][543983] Updated weights for policy 0, policy_version 13160 (0.0007) +[2026-07-22 22:58:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 6717440. Throughput: 0: 12805.7. Samples: 6748928. Policy #0 lag: (min: 34.0, avg: 60.3, max: 98.0) +[2026-07-22 22:58:27,287][543203] Avg episode reward: [(0, '418.233')] +[2026-07-22 22:58:27,418][543983] Updated weights for policy 0, policy_version 13170 (0.0006) +[2026-07-22 22:58:27,711][543983] Updated weights for policy 0, policy_version 13180 (0.0007) +[2026-07-22 22:58:27,806][543696] Saving new best policy, reward=418.233! +[2026-07-22 22:58:28,790][543983] Updated weights for policy 0, policy_version 13190 (0.0007) +[2026-07-22 22:58:29,063][543983] Updated weights for policy 0, policy_version 13200 (0.0007) +[2026-07-22 22:58:29,355][543983] Updated weights for policy 0, policy_version 13210 (0.0008) +[2026-07-22 22:58:29,630][543983] Updated weights for policy 0, policy_version 13220 (0.0007) +[2026-07-22 22:58:29,929][543983] Updated weights for policy 0, policy_version 13231 (0.0006) +[2026-07-22 22:58:30,233][543983] Updated weights for policy 0, policy_version 13241 (0.0006) +[2026-07-22 22:58:31,368][543983] Updated weights for policy 0, policy_version 13252 (0.0007) +[2026-07-22 22:58:31,680][543983] Updated weights for policy 0, policy_version 13263 (0.0006) +[2026-07-22 22:58:31,963][543983] Updated weights for policy 0, policy_version 13273 (0.0006) +[2026-07-22 22:58:32,236][543983] Updated weights for policy 0, policy_version 13283 (0.0007) +[2026-07-22 22:58:32,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 6782976. Throughput: 0: 12788.6. Samples: 6825216. Policy #0 lag: (min: 34.0, avg: 60.3, max: 98.0) +[2026-07-22 22:58:32,287][543203] Avg episode reward: [(0, '402.016')] +[2026-07-22 22:58:32,561][543983] Updated weights for policy 0, policy_version 13294 (0.0006) +[2026-07-22 22:58:32,876][543983] Updated weights for policy 0, policy_version 13305 (0.0006) +[2026-07-22 22:58:33,855][543983] Updated weights for policy 0, policy_version 13315 (0.0006) +[2026-07-22 22:58:34,123][543983] Updated weights for policy 0, policy_version 13325 (0.0007) +[2026-07-22 22:58:34,406][543983] Updated weights for policy 0, policy_version 13335 (0.0007) +[2026-07-22 22:58:34,708][543983] Updated weights for policy 0, policy_version 13346 (0.0006) +[2026-07-22 22:58:34,997][543983] Updated weights for policy 0, policy_version 13356 (0.0007) +[2026-07-22 22:58:35,272][543983] Updated weights for policy 0, policy_version 13366 (0.0008) +[2026-07-22 22:58:35,554][543983] Updated weights for policy 0, policy_version 13376 (0.0007) +[2026-07-22 22:58:36,605][543983] Updated weights for policy 0, policy_version 13386 (0.0007) +[2026-07-22 22:58:36,882][543983] Updated weights for policy 0, policy_version 13396 (0.0006) +[2026-07-22 22:58:37,237][543983] Updated weights for policy 0, policy_version 13407 (0.0006) +[2026-07-22 22:58:37,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 6848512. Throughput: 0: 12595.2. Samples: 6859904. Policy #0 lag: (min: 34.0, avg: 60.3, max: 98.0) +[2026-07-22 22:58:37,287][543203] Avg episode reward: [(0, '392.083')] +[2026-07-22 22:58:37,521][543983] Updated weights for policy 0, policy_version 13418 (0.0007) +[2026-07-22 22:58:37,808][543983] Updated weights for policy 0, policy_version 13428 (0.0006) +[2026-07-22 22:58:38,116][543983] Updated weights for policy 0, policy_version 13439 (0.0006) +[2026-07-22 22:58:39,184][543983] Updated weights for policy 0, policy_version 13450 (0.0006) +[2026-07-22 22:58:39,457][543983] Updated weights for policy 0, policy_version 13460 (0.0007) +[2026-07-22 22:58:39,776][543983] Updated weights for policy 0, policy_version 13471 (0.0007) +[2026-07-22 22:58:40,088][543983] Updated weights for policy 0, policy_version 13482 (0.0006) +[2026-07-22 22:58:40,375][543983] Updated weights for policy 0, policy_version 13492 (0.0007) +[2026-07-22 22:58:40,683][543983] Updated weights for policy 0, policy_version 13503 (0.0007) +[2026-07-22 22:58:41,733][543983] Updated weights for policy 0, policy_version 13513 (0.0008) +[2026-07-22 22:58:42,008][543983] Updated weights for policy 0, policy_version 13523 (0.0006) +[2026-07-22 22:58:42,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 6914048. Throughput: 0: 12600.9. Samples: 6931840. Policy #0 lag: (min: 29.0, avg: 44.9, max: 93.0) +[2026-07-22 22:58:42,287][543203] Avg episode reward: [(0, '389.121')] +[2026-07-22 22:58:42,322][543983] Updated weights for policy 0, policy_version 13534 (0.0006) +[2026-07-22 22:58:42,594][543983] Updated weights for policy 0, policy_version 13544 (0.0006) +[2026-07-22 22:58:42,939][543983] Updated weights for policy 0, policy_version 13556 (0.0006) +[2026-07-22 22:58:43,213][543983] Updated weights for policy 0, policy_version 13566 (0.0007) +[2026-07-22 22:58:44,309][543983] Updated weights for policy 0, policy_version 13576 (0.0007) +[2026-07-22 22:58:44,647][543983] Updated weights for policy 0, policy_version 13588 (0.0007) +[2026-07-22 22:58:44,966][543983] Updated weights for policy 0, policy_version 13599 (0.0007) +[2026-07-22 22:58:45,244][543983] Updated weights for policy 0, policy_version 13609 (0.0006) +[2026-07-22 22:58:45,535][543983] Updated weights for policy 0, policy_version 13619 (0.0006) +[2026-07-22 22:58:45,830][543983] Updated weights for policy 0, policy_version 13629 (0.0007) +[2026-07-22 22:58:46,872][543983] Updated weights for policy 0, policy_version 13639 (0.0006) +[2026-07-22 22:58:47,182][543983] Updated weights for policy 0, policy_version 13650 (0.0007) +[2026-07-22 22:58:47,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 6979584. Throughput: 0: 12893.9. Samples: 7016704. Policy #0 lag: (min: 29.0, avg: 44.9, max: 93.0) +[2026-07-22 22:58:47,287][543203] Avg episode reward: [(0, '384.192')] +[2026-07-22 22:58:47,499][543983] Updated weights for policy 0, policy_version 13661 (0.0009) +[2026-07-22 22:58:47,788][543983] Updated weights for policy 0, policy_version 13671 (0.0006) +[2026-07-22 22:58:48,069][543983] Updated weights for policy 0, policy_version 13681 (0.0006) +[2026-07-22 22:58:48,382][543983] Updated weights for policy 0, policy_version 13692 (0.0006) +[2026-07-22 22:58:49,420][543983] Updated weights for policy 0, policy_version 13702 (0.0006) +[2026-07-22 22:58:49,760][543983] Updated weights for policy 0, policy_version 13713 (0.0006) +[2026-07-22 22:58:50,062][543983] Updated weights for policy 0, policy_version 13724 (0.0007) +[2026-07-22 22:58:50,356][543983] Updated weights for policy 0, policy_version 13735 (0.0006) +[2026-07-22 22:58:50,656][543983] Updated weights for policy 0, policy_version 13745 (0.0006) +[2026-07-22 22:58:50,955][543983] Updated weights for policy 0, policy_version 13755 (0.0006) +[2026-07-22 22:58:52,060][543983] Updated weights for policy 0, policy_version 13766 (0.0006) +[2026-07-22 22:58:52,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 7045120. Throughput: 0: 12802.8. Samples: 7052928. Policy #0 lag: (min: 43.0, avg: 70.4, max: 107.0) +[2026-07-22 22:58:52,287][543203] Avg episode reward: [(0, '370.604')] +[2026-07-22 22:58:52,330][543983] Updated weights for policy 0, policy_version 13776 (0.0006) +[2026-07-22 22:58:52,617][543983] Updated weights for policy 0, policy_version 13786 (0.0006) +[2026-07-22 22:58:52,922][543983] Updated weights for policy 0, policy_version 13796 (0.0006) +[2026-07-22 22:58:53,192][543983] Updated weights for policy 0, policy_version 13806 (0.0006) +[2026-07-22 22:58:53,502][543983] Updated weights for policy 0, policy_version 13817 (0.0006) +[2026-07-22 22:58:54,587][543983] Updated weights for policy 0, policy_version 13829 (0.0006) +[2026-07-22 22:58:54,877][543983] Updated weights for policy 0, policy_version 13839 (0.0006) +[2026-07-22 22:58:55,165][543983] Updated weights for policy 0, policy_version 13849 (0.0007) +[2026-07-22 22:58:55,441][543983] Updated weights for policy 0, policy_version 13859 (0.0006) +[2026-07-22 22:58:55,725][543983] Updated weights for policy 0, policy_version 13869 (0.0007) +[2026-07-22 22:58:56,035][543983] Updated weights for policy 0, policy_version 13880 (0.0006) +[2026-07-22 22:58:57,124][543983] Updated weights for policy 0, policy_version 13890 (0.0006) +[2026-07-22 22:58:57,286][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 7110656. Throughput: 0: 12581.0. Samples: 7124608. Policy #0 lag: (min: 43.0, avg: 70.4, max: 107.0) +[2026-07-22 22:58:57,287][543203] Avg episode reward: [(0, '374.986')] +[2026-07-22 22:58:57,448][543983] Updated weights for policy 0, policy_version 13901 (0.0007) +[2026-07-22 22:58:57,721][543983] Updated weights for policy 0, policy_version 13911 (0.0006) +[2026-07-22 22:58:57,995][543983] Updated weights for policy 0, policy_version 13921 (0.0006) +[2026-07-22 22:58:58,321][543983] Updated weights for policy 0, policy_version 13932 (0.0007) +[2026-07-22 22:58:58,597][543983] Updated weights for policy 0, policy_version 13942 (0.0006) +[2026-07-22 22:58:59,665][543983] Updated weights for policy 0, policy_version 13953 (0.0006) +[2026-07-22 22:58:59,966][543983] Updated weights for policy 0, policy_version 13963 (0.0006) +[2026-07-22 22:59:00,232][543983] Updated weights for policy 0, policy_version 13973 (0.0006) +[2026-07-22 22:59:00,547][543983] Updated weights for policy 0, policy_version 13984 (0.0006) +[2026-07-22 22:59:00,832][543983] Updated weights for policy 0, policy_version 13994 (0.0006) +[2026-07-22 22:59:01,132][543983] Updated weights for policy 0, policy_version 14005 (0.0007) +[2026-07-22 22:59:01,426][543983] Updated weights for policy 0, policy_version 14015 (0.0006) +[2026-07-22 22:59:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 7176192. Throughput: 0: 12683.4. Samples: 7201920. Policy #0 lag: (min: 43.0, avg: 70.4, max: 107.0) +[2026-07-22 22:59:02,287][543203] Avg episode reward: [(0, '378.408')] +[2026-07-22 22:59:02,523][543983] Updated weights for policy 0, policy_version 14025 (0.0006) +[2026-07-22 22:59:02,800][543983] Updated weights for policy 0, policy_version 14035 (0.0007) +[2026-07-22 22:59:03,083][543983] Updated weights for policy 0, policy_version 14045 (0.0006) +[2026-07-22 22:59:03,384][543983] Updated weights for policy 0, policy_version 14055 (0.0006) +[2026-07-22 22:59:03,690][543983] Updated weights for policy 0, policy_version 14066 (0.0007) +[2026-07-22 22:59:03,987][543983] Updated weights for policy 0, policy_version 14076 (0.0006) +[2026-07-22 22:59:05,024][543983] Updated weights for policy 0, policy_version 14086 (0.0006) +[2026-07-22 22:59:05,312][543983] Updated weights for policy 0, policy_version 14096 (0.0007) +[2026-07-22 22:59:05,609][543983] Updated weights for policy 0, policy_version 14107 (0.0006) +[2026-07-22 22:59:05,914][543983] Updated weights for policy 0, policy_version 14118 (0.0008) +[2026-07-22 22:59:06,198][543983] Updated weights for policy 0, policy_version 14128 (0.0006) +[2026-07-22 22:59:06,514][543983] Updated weights for policy 0, policy_version 14139 (0.0006) +[2026-07-22 22:59:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 7241728. Throughput: 0: 12851.2. Samples: 7245952. Policy #0 lag: (min: 35.0, avg: 64.9, max: 99.0) +[2026-07-22 22:59:07,287][543203] Avg episode reward: [(0, '414.241')] +[2026-07-22 22:59:07,585][543983] Updated weights for policy 0, policy_version 14150 (0.0006) +[2026-07-22 22:59:07,888][543983] Updated weights for policy 0, policy_version 14161 (0.0006) +[2026-07-22 22:59:08,158][543983] Updated weights for policy 0, policy_version 14171 (0.0006) +[2026-07-22 22:59:08,447][543983] Updated weights for policy 0, policy_version 14181 (0.0006) +[2026-07-22 22:59:08,757][543983] Updated weights for policy 0, policy_version 14192 (0.0006) +[2026-07-22 22:59:09,045][543983] Updated weights for policy 0, policy_version 14202 (0.0006) +[2026-07-22 22:59:10,107][543983] Updated weights for policy 0, policy_version 14212 (0.0009) +[2026-07-22 22:59:10,423][543983] Updated weights for policy 0, policy_version 14223 (0.0006) +[2026-07-22 22:59:10,704][543983] Updated weights for policy 0, policy_version 14233 (0.0006) +[2026-07-22 22:59:10,994][543983] Updated weights for policy 0, policy_version 14243 (0.0006) +[2026-07-22 22:59:11,278][543983] Updated weights for policy 0, policy_version 14253 (0.0006) +[2026-07-22 22:59:11,568][543983] Updated weights for policy 0, policy_version 14263 (0.0006) +[2026-07-22 22:59:12,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 7307264. Throughput: 0: 12640.7. Samples: 7317760. Policy #0 lag: (min: 35.0, avg: 64.9, max: 99.0) +[2026-07-22 22:59:12,288][543203] Avg episode reward: [(0, '416.271')] +[2026-07-22 22:59:12,661][543983] Updated weights for policy 0, policy_version 14274 (0.0006) +[2026-07-22 22:59:12,925][543983] Updated weights for policy 0, policy_version 14284 (0.0006) +[2026-07-22 22:59:13,234][543983] Updated weights for policy 0, policy_version 14295 (0.0006) +[2026-07-22 22:59:13,550][543983] Updated weights for policy 0, policy_version 14306 (0.0006) +[2026-07-22 22:59:13,830][543983] Updated weights for policy 0, policy_version 14316 (0.0006) +[2026-07-22 22:59:14,124][543983] Updated weights for policy 0, policy_version 14326 (0.0006) +[2026-07-22 22:59:14,395][543983] Updated weights for policy 0, policy_version 14336 (0.0006) +[2026-07-22 22:59:15,474][543983] Updated weights for policy 0, policy_version 14347 (0.0007) +[2026-07-22 22:59:15,775][543983] Updated weights for policy 0, policy_version 14357 (0.0007) +[2026-07-22 22:59:16,045][543983] Updated weights for policy 0, policy_version 14367 (0.0007) +[2026-07-22 22:59:16,334][543983] Updated weights for policy 0, policy_version 14377 (0.0006) +[2026-07-22 22:59:16,625][543983] Updated weights for policy 0, policy_version 14387 (0.0006) +[2026-07-22 22:59:16,912][543983] Updated weights for policy 0, policy_version 14397 (0.0006) +[2026-07-22 22:59:17,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 7372800. Throughput: 0: 12561.0. Samples: 7390464. Policy #0 lag: (min: 63.0, avg: 79.7, max: 127.0) +[2026-07-22 22:59:17,287][543203] Avg episode reward: [(0, '419.152')] +[2026-07-22 22:59:17,293][543696] Saving results/checkpoints/memory/rollout_teacher/flappy_teacher_fixed_l3_obs30_seed0/checkpoint_p0/checkpoint_000014400_7372800.pth... +[2026-07-22 22:59:17,325][543696] Saving new best policy, reward=419.152! +[2026-07-22 22:59:17,990][543983] Updated weights for policy 0, policy_version 14408 (0.0006) +[2026-07-22 22:59:18,262][543983] Updated weights for policy 0, policy_version 14418 (0.0007) +[2026-07-22 22:59:18,586][543983] Updated weights for policy 0, policy_version 14429 (0.0006) +[2026-07-22 22:59:18,889][543983] Updated weights for policy 0, policy_version 14440 (0.0006) +[2026-07-22 22:59:19,169][543983] Updated weights for policy 0, policy_version 14450 (0.0007) +[2026-07-22 22:59:19,449][543983] Updated weights for policy 0, policy_version 14460 (0.0006) +[2026-07-22 22:59:20,541][543983] Updated weights for policy 0, policy_version 14470 (0.0006) +[2026-07-22 22:59:20,815][543983] Updated weights for policy 0, policy_version 14480 (0.0006) +[2026-07-22 22:59:21,101][543983] Updated weights for policy 0, policy_version 14490 (0.0006) +[2026-07-22 22:59:21,381][543983] Updated weights for policy 0, policy_version 14500 (0.0006) +[2026-07-22 22:59:21,673][543983] Updated weights for policy 0, policy_version 14510 (0.0006) +[2026-07-22 22:59:21,950][543983] Updated weights for policy 0, policy_version 14520 (0.0006) +[2026-07-22 22:59:22,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 7438336. Throughput: 0: 12646.4. Samples: 7428992. Policy #0 lag: (min: 63.0, avg: 79.7, max: 127.0) +[2026-07-22 22:59:22,287][543203] Avg episode reward: [(0, '423.945')] +[2026-07-22 22:59:22,295][543696] Saving new best policy, reward=423.945! +[2026-07-22 22:59:22,983][543983] Updated weights for policy 0, policy_version 14530 (0.0006) +[2026-07-22 22:59:23,320][543983] Updated weights for policy 0, policy_version 14542 (0.0006) +[2026-07-22 22:59:23,638][543983] Updated weights for policy 0, policy_version 14553 (0.0007) +[2026-07-22 22:59:23,924][543983] Updated weights for policy 0, policy_version 14563 (0.0007) +[2026-07-22 22:59:24,234][543983] Updated weights for policy 0, policy_version 14574 (0.0007) +[2026-07-22 22:59:24,512][543983] Updated weights for policy 0, policy_version 14584 (0.0007) +[2026-07-22 22:59:25,557][543983] Updated weights for policy 0, policy_version 14594 (0.0006) +[2026-07-22 22:59:25,882][543983] Updated weights for policy 0, policy_version 14605 (0.0006) +[2026-07-22 22:59:26,148][543983] Updated weights for policy 0, policy_version 14615 (0.0006) +[2026-07-22 22:59:26,461][543983] Updated weights for policy 0, policy_version 14626 (0.0006) +[2026-07-22 22:59:26,737][543983] Updated weights for policy 0, policy_version 14636 (0.0006) +[2026-07-22 22:59:27,012][543983] Updated weights for policy 0, policy_version 14646 (0.0006) +[2026-07-22 22:59:27,286][543203] Fps is (10 sec: 9830.5, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 7471104. Throughput: 0: 12871.1. Samples: 7511040. Policy #0 lag: (min: 63.0, avg: 79.7, max: 127.0) +[2026-07-22 22:59:27,287][543203] Avg episode reward: [(0, '418.032')] +[2026-07-22 22:59:27,302][543983] Updated weights for policy 0, policy_version 14656 (0.0007) +[2026-07-22 22:59:28,373][543983] Updated weights for policy 0, policy_version 14667 (0.0007) +[2026-07-22 22:59:28,660][543983] Updated weights for policy 0, policy_version 14677 (0.0006) +[2026-07-22 22:59:28,943][543983] Updated weights for policy 0, policy_version 14687 (0.0007) +[2026-07-22 22:59:29,232][543983] Updated weights for policy 0, policy_version 14697 (0.0006) +[2026-07-22 22:59:29,553][543983] Updated weights for policy 0, policy_version 14708 (0.0007) +[2026-07-22 22:59:29,836][543983] Updated weights for policy 0, policy_version 14718 (0.0006) +[2026-07-22 22:59:30,878][543983] Updated weights for policy 0, policy_version 14728 (0.0007) +[2026-07-22 22:59:31,158][543983] Updated weights for policy 0, policy_version 14738 (0.0008) +[2026-07-22 22:59:31,465][543983] Updated weights for policy 0, policy_version 14749 (0.0008) +[2026-07-22 22:59:31,747][543983] Updated weights for policy 0, policy_version 14759 (0.0007) +[2026-07-22 22:59:32,094][543983] Updated weights for policy 0, policy_version 14771 (0.0007) +[2026-07-22 22:59:32,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 7536640. Throughput: 0: 12586.7. Samples: 7583104. Policy #0 lag: (min: 48.0, avg: 81.4, max: 112.0) +[2026-07-22 22:59:32,287][543203] Avg episode reward: [(0, '431.921')] +[2026-07-22 22:59:32,369][543983] Updated weights for policy 0, policy_version 14781 (0.0007) +[2026-07-22 22:59:32,451][543696] Saving new best policy, reward=431.921! +[2026-07-22 22:59:33,475][543983] Updated weights for policy 0, policy_version 14792 (0.0006) +[2026-07-22 22:59:33,751][543983] Updated weights for policy 0, policy_version 14802 (0.0006) +[2026-07-22 22:59:34,065][543983] Updated weights for policy 0, policy_version 14813 (0.0007) +[2026-07-22 22:59:34,347][543983] Updated weights for policy 0, policy_version 14823 (0.0006) +[2026-07-22 22:59:34,636][543983] Updated weights for policy 0, policy_version 14833 (0.0006) +[2026-07-22 22:59:34,913][543983] Updated weights for policy 0, policy_version 14843 (0.0006) +[2026-07-22 22:59:35,961][543983] Updated weights for policy 0, policy_version 14854 (0.0007) +[2026-07-22 22:59:36,245][543983] Updated weights for policy 0, policy_version 14864 (0.0006) +[2026-07-22 22:59:36,539][543983] Updated weights for policy 0, policy_version 14874 (0.0007) +[2026-07-22 22:59:36,854][543983] Updated weights for policy 0, policy_version 14885 (0.0007) +[2026-07-22 22:59:37,144][543983] Updated weights for policy 0, policy_version 14895 (0.0007) +[2026-07-22 22:59:37,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 7602176. Throughput: 0: 12595.2. Samples: 7619712. Policy #0 lag: (min: 48.0, avg: 81.4, max: 112.0) +[2026-07-22 22:59:37,287][543203] Avg episode reward: [(0, '421.775')] +[2026-07-22 22:59:37,422][543983] Updated weights for policy 0, policy_version 14905 (0.0006) +[2026-07-22 22:59:38,501][543983] Updated weights for policy 0, policy_version 14915 (0.0007) +[2026-07-22 22:59:38,829][543983] Updated weights for policy 0, policy_version 14927 (0.0006) +[2026-07-22 22:59:39,155][543983] Updated weights for policy 0, policy_version 14938 (0.0007) +[2026-07-22 22:59:39,429][543983] Updated weights for policy 0, policy_version 14948 (0.0006) +[2026-07-22 22:59:39,709][543983] Updated weights for policy 0, policy_version 14958 (0.0006) +[2026-07-22 22:59:40,003][543983] Updated weights for policy 0, policy_version 14968 (0.0006) +[2026-07-22 22:59:41,062][543983] Updated weights for policy 0, policy_version 14979 (0.0008) +[2026-07-22 22:59:41,384][543983] Updated weights for policy 0, policy_version 14990 (0.0006) +[2026-07-22 22:59:41,659][543983] Updated weights for policy 0, policy_version 15000 (0.0008) +[2026-07-22 22:59:41,942][543983] Updated weights for policy 0, policy_version 15010 (0.0007) +[2026-07-22 22:59:42,254][543983] Updated weights for policy 0, policy_version 15021 (0.0007) +[2026-07-22 22:59:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 7667712. Throughput: 0: 12822.7. Samples: 7701632. Policy #0 lag: (min: 48.0, avg: 81.4, max: 112.0) +[2026-07-22 22:59:42,287][543203] Avg episode reward: [(0, '415.302')] +[2026-07-22 22:59:42,546][543983] Updated weights for policy 0, policy_version 15031 (0.0006) +[2026-07-22 22:59:43,580][543983] Updated weights for policy 0, policy_version 15041 (0.0007) +[2026-07-22 22:59:43,858][543983] Updated weights for policy 0, policy_version 15051 (0.0007) +[2026-07-22 22:59:44,152][543983] Updated weights for policy 0, policy_version 15061 (0.0006) +[2026-07-22 22:59:44,432][543983] Updated weights for policy 0, policy_version 15071 (0.0006) +[2026-07-22 22:59:44,701][543983] Updated weights for policy 0, policy_version 15081 (0.0007) +[2026-07-22 22:59:45,002][543983] Updated weights for policy 0, policy_version 15091 (0.0006) +[2026-07-22 22:59:45,285][543983] Updated weights for policy 0, policy_version 15101 (0.0007) +[2026-07-22 22:59:46,374][543983] Updated weights for policy 0, policy_version 15112 (0.0007) +[2026-07-22 22:59:46,686][543983] Updated weights for policy 0, policy_version 15123 (0.0008) +[2026-07-22 22:59:46,991][543983] Updated weights for policy 0, policy_version 15133 (0.0007) +[2026-07-22 22:59:47,265][543983] Updated weights for policy 0, policy_version 15143 (0.0006) +[2026-07-22 22:59:47,287][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 7733248. Throughput: 0: 12765.9. Samples: 7776384. Policy #0 lag: (min: 63.0, avg: 79.7, max: 127.0) +[2026-07-22 22:59:47,287][543203] Avg episode reward: [(0, '413.185')] +[2026-07-22 22:59:47,578][543983] Updated weights for policy 0, policy_version 15154 (0.0006) +[2026-07-22 22:59:47,861][543983] Updated weights for policy 0, policy_version 15164 (0.0007) +[2026-07-22 22:59:48,893][543983] Updated weights for policy 0, policy_version 15174 (0.0007) +[2026-07-22 22:59:49,170][543983] Updated weights for policy 0, policy_version 15184 (0.0006) +[2026-07-22 22:59:49,484][543983] Updated weights for policy 0, policy_version 15195 (0.0006) +[2026-07-22 22:59:49,766][543983] Updated weights for policy 0, policy_version 15205 (0.0006) +[2026-07-22 22:59:50,060][543983] Updated weights for policy 0, policy_version 15215 (0.0007) +[2026-07-22 22:59:50,347][543983] Updated weights for policy 0, policy_version 15225 (0.0007) +[2026-07-22 22:59:51,386][543983] Updated weights for policy 0, policy_version 15235 (0.0006) +[2026-07-22 22:59:51,682][543983] Updated weights for policy 0, policy_version 15245 (0.0008) +[2026-07-22 22:59:51,998][543983] Updated weights for policy 0, policy_version 15256 (0.0007) +[2026-07-22 22:59:52,275][543983] Updated weights for policy 0, policy_version 15266 (0.0006) +[2026-07-22 22:59:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 7798784. Throughput: 0: 12592.3. Samples: 7812608. Policy #0 lag: (min: 63.0, avg: 79.7, max: 127.0) +[2026-07-22 22:59:52,287][543203] Avg episode reward: [(0, '430.956')] +[2026-07-22 22:59:52,561][543983] Updated weights for policy 0, policy_version 15276 (0.0006) +[2026-07-22 22:59:52,848][543983] Updated weights for policy 0, policy_version 15286 (0.0007) +[2026-07-22 22:59:53,132][543983] Updated weights for policy 0, policy_version 15296 (0.0007) +[2026-07-22 22:59:54,205][543983] Updated weights for policy 0, policy_version 15307 (0.0007) +[2026-07-22 22:59:54,481][543983] Updated weights for policy 0, policy_version 15317 (0.0007) +[2026-07-22 22:59:54,752][543983] Updated weights for policy 0, policy_version 15327 (0.0007) +[2026-07-22 22:59:55,075][543983] Updated weights for policy 0, policy_version 15338 (0.0006) +[2026-07-22 22:59:55,425][543983] Updated weights for policy 0, policy_version 15350 (0.0007) +[2026-07-22 22:59:55,714][543983] Updated weights for policy 0, policy_version 15360 (0.0006) +[2026-07-22 22:59:56,751][543983] Updated weights for policy 0, policy_version 15370 (0.0007) +[2026-07-22 22:59:57,033][543983] Updated weights for policy 0, policy_version 15380 (0.0006) +[2026-07-22 22:59:57,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 7864320. Throughput: 0: 12603.8. Samples: 7884928. Policy #0 lag: (min: 63.0, avg: 80.2, max: 127.0) +[2026-07-22 22:59:57,287][543203] Avg episode reward: [(0, '430.459')] +[2026-07-22 22:59:57,318][543983] Updated weights for policy 0, policy_version 15390 (0.0007) +[2026-07-22 22:59:57,639][543983] Updated weights for policy 0, policy_version 15401 (0.0007) +[2026-07-22 22:59:57,917][543983] Updated weights for policy 0, policy_version 15411 (0.0006) +[2026-07-22 22:59:58,210][543983] Updated weights for policy 0, policy_version 15421 (0.0006) +[2026-07-22 22:59:59,310][543983] Updated weights for policy 0, policy_version 15432 (0.0007) +[2026-07-22 22:59:59,597][543983] Updated weights for policy 0, policy_version 15442 (0.0006) +[2026-07-22 22:59:59,908][543983] Updated weights for policy 0, policy_version 15453 (0.0006) +[2026-07-22 23:00:00,188][543983] Updated weights for policy 0, policy_version 15463 (0.0007) +[2026-07-22 23:00:00,477][543983] Updated weights for policy 0, policy_version 15473 (0.0006) +[2026-07-22 23:00:00,749][543983] Updated weights for policy 0, policy_version 15483 (0.0006) +[2026-07-22 23:00:01,808][543983] Updated weights for policy 0, policy_version 15494 (0.0006) +[2026-07-22 23:00:02,102][543983] Updated weights for policy 0, policy_version 15504 (0.0007) +[2026-07-22 23:00:02,287][543203] Fps is (10 sec: 13106.1, 60 sec: 12560.9, 300 sec: 12662.9). Total num frames: 7929856. Throughput: 0: 12865.2. Samples: 7969408. Policy #0 lag: (min: 63.0, avg: 80.2, max: 127.0) +[2026-07-22 23:00:02,288][543203] Avg episode reward: [(0, '423.124')] +[2026-07-22 23:00:02,414][543983] Updated weights for policy 0, policy_version 15515 (0.0007) +[2026-07-22 23:00:02,731][543983] Updated weights for policy 0, policy_version 15526 (0.0007) +[2026-07-22 23:00:03,011][543983] Updated weights for policy 0, policy_version 15536 (0.0007) +[2026-07-22 23:00:03,295][543983] Updated weights for policy 0, policy_version 15546 (0.0007) +[2026-07-22 23:00:04,342][543983] Updated weights for policy 0, policy_version 15556 (0.0007) +[2026-07-22 23:00:04,612][543983] Updated weights for policy 0, policy_version 15566 (0.0007) +[2026-07-22 23:00:04,924][543983] Updated weights for policy 0, policy_version 15577 (0.0006) +[2026-07-22 23:00:05,220][543983] Updated weights for policy 0, policy_version 15587 (0.0007) +[2026-07-22 23:00:05,505][543983] Updated weights for policy 0, policy_version 15597 (0.0007) +[2026-07-22 23:00:05,778][543983] Updated weights for policy 0, policy_version 15607 (0.0007) +[2026-07-22 23:00:06,869][543983] Updated weights for policy 0, policy_version 15617 (0.0006) +[2026-07-22 23:00:07,157][543983] Updated weights for policy 0, policy_version 15627 (0.0007) +[2026-07-22 23:00:07,287][543203] Fps is (10 sec: 13106.8, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 7995392. Throughput: 0: 12817.0. Samples: 8005760. Policy #0 lag: (min: 63.0, avg: 80.2, max: 127.0) +[2026-07-22 23:00:07,287][543203] Avg episode reward: [(0, '434.076')] +[2026-07-22 23:00:07,447][543983] Updated weights for policy 0, policy_version 15637 (0.0007) +[2026-07-22 23:00:07,776][543983] Updated weights for policy 0, policy_version 15649 (0.0007) +[2026-07-22 23:00:08,097][543983] Updated weights for policy 0, policy_version 15660 (0.0008) +[2026-07-22 23:00:08,385][543983] Updated weights for policy 0, policy_version 15670 (0.0007) +[2026-07-22 23:00:08,696][543696] Saving new best policy, reward=434.076! +[2026-07-22 23:00:08,698][543983] Updated weights for policy 0, policy_version 15680 (0.0007) +[2026-07-22 23:00:09,686][543983] Updated weights for policy 0, policy_version 15690 (0.0008) +[2026-07-22 23:00:09,978][543983] Updated weights for policy 0, policy_version 15700 (0.0008) +[2026-07-22 23:00:10,244][543983] Updated weights for policy 0, policy_version 15710 (0.0008) +[2026-07-22 23:00:10,531][543983] Updated weights for policy 0, policy_version 15720 (0.0008) +[2026-07-22 23:00:10,865][543983] Updated weights for policy 0, policy_version 15731 (0.0007) +[2026-07-22 23:00:11,148][543983] Updated weights for policy 0, policy_version 15741 (0.0007) +[2026-07-22 23:00:12,222][543983] Updated weights for policy 0, policy_version 15751 (0.0006) +[2026-07-22 23:00:12,286][543203] Fps is (10 sec: 13108.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 8060928. Throughput: 0: 12589.5. Samples: 8077568. Policy #0 lag: (min: 63.0, avg: 79.4, max: 127.0) +[2026-07-22 23:00:12,287][543203] Avg episode reward: [(0, '451.927')] +[2026-07-22 23:00:12,532][543983] Updated weights for policy 0, policy_version 15762 (0.0009) +[2026-07-22 23:00:12,844][543983] Updated weights for policy 0, policy_version 15772 (0.0008) +[2026-07-22 23:00:13,120][543983] Updated weights for policy 0, policy_version 15782 (0.0006) +[2026-07-22 23:00:13,428][543983] Updated weights for policy 0, policy_version 15793 (0.0007) +[2026-07-22 23:00:13,710][543983] Updated weights for policy 0, policy_version 15803 (0.0007) +[2026-07-22 23:00:13,839][543696] Saving new best policy, reward=451.927! +[2026-07-22 23:00:14,723][543983] Updated weights for policy 0, policy_version 15813 (0.0007) +[2026-07-22 23:00:15,014][543983] Updated weights for policy 0, policy_version 15823 (0.0006) +[2026-07-22 23:00:15,305][543983] Updated weights for policy 0, policy_version 15833 (0.0007) +[2026-07-22 23:00:15,582][543983] Updated weights for policy 0, policy_version 15843 (0.0007) +[2026-07-22 23:00:15,866][543983] Updated weights for policy 0, policy_version 15853 (0.0009) +[2026-07-22 23:00:16,173][543983] Updated weights for policy 0, policy_version 15863 (0.0016) +[2026-07-22 23:00:17,201][543983] Updated weights for policy 0, policy_version 15873 (0.0012) +[2026-07-22 23:00:17,286][543203] Fps is (10 sec: 13107.6, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 8126464. Throughput: 0: 12711.8. Samples: 8155136. Policy #0 lag: (min: 63.0, avg: 79.4, max: 127.0) +[2026-07-22 23:00:17,287][543203] Avg episode reward: [(0, '463.707')] +[2026-07-22 23:00:17,490][543983] Updated weights for policy 0, policy_version 15883 (0.0007) +[2026-07-22 23:00:17,818][543983] Updated weights for policy 0, policy_version 15894 (0.0007) +[2026-07-22 23:00:18,092][543983] Updated weights for policy 0, policy_version 15904 (0.0007) +[2026-07-22 23:00:18,406][543983] Updated weights for policy 0, policy_version 15915 (0.0007) +[2026-07-22 23:00:18,702][543983] Updated weights for policy 0, policy_version 15925 (0.0008) +[2026-07-22 23:00:18,996][543983] Updated weights for policy 0, policy_version 15935 (0.0007) +[2026-07-22 23:00:19,010][543696] Saving new best policy, reward=463.707! +[2026-07-22 23:00:20,029][543983] Updated weights for policy 0, policy_version 15945 (0.0008) +[2026-07-22 23:00:20,304][543983] Updated weights for policy 0, policy_version 15955 (0.0009) +[2026-07-22 23:00:20,617][543983] Updated weights for policy 0, policy_version 15965 (0.0010) +[2026-07-22 23:00:20,928][543983] Updated weights for policy 0, policy_version 15976 (0.0009) +[2026-07-22 23:00:21,219][543983] Updated weights for policy 0, policy_version 15986 (0.0009) +[2026-07-22 23:00:21,493][543983] Updated weights for policy 0, policy_version 15996 (0.0008) +[2026-07-22 23:00:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 8192000. Throughput: 0: 12842.7. Samples: 8197632. Policy #0 lag: (min: 63.0, avg: 79.4, max: 127.0) +[2026-07-22 23:00:22,287][543203] Avg episode reward: [(0, '461.983')] +[2026-07-22 23:00:22,563][543983] Updated weights for policy 0, policy_version 16006 (0.0008) +[2026-07-22 23:00:22,872][543983] Updated weights for policy 0, policy_version 16017 (0.0007) +[2026-07-22 23:00:23,161][543983] Updated weights for policy 0, policy_version 16027 (0.0008) +[2026-07-22 23:00:23,435][543983] Updated weights for policy 0, policy_version 16037 (0.0007) +[2026-07-22 23:00:23,780][543983] Updated weights for policy 0, policy_version 16048 (0.0006) +[2026-07-22 23:00:24,070][543983] Updated weights for policy 0, policy_version 16058 (0.0008) +[2026-07-22 23:00:25,104][543983] Updated weights for policy 0, policy_version 16068 (0.0007) +[2026-07-22 23:00:25,422][543983] Updated weights for policy 0, policy_version 16079 (0.0007) +[2026-07-22 23:00:25,706][543983] Updated weights for policy 0, policy_version 16089 (0.0006) +[2026-07-22 23:00:26,024][543983] Updated weights for policy 0, policy_version 16100 (0.0007) +[2026-07-22 23:00:26,302][543983] Updated weights for policy 0, policy_version 16110 (0.0007) +[2026-07-22 23:00:26,594][543983] Updated weights for policy 0, policy_version 16120 (0.0006) +[2026-07-22 23:00:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 8257536. Throughput: 0: 12629.3. Samples: 8269952. Policy #0 lag: (min: 46.0, avg: 63.2, max: 110.0) +[2026-07-22 23:00:27,287][543203] Avg episode reward: [(0, '456.741')] +[2026-07-22 23:00:27,655][543983] Updated weights for policy 0, policy_version 16130 (0.0006) +[2026-07-22 23:00:27,944][543983] Updated weights for policy 0, policy_version 16140 (0.0007) +[2026-07-22 23:00:28,226][543983] Updated weights for policy 0, policy_version 16150 (0.0007) +[2026-07-22 23:00:28,507][543983] Updated weights for policy 0, policy_version 16160 (0.0007) +[2026-07-22 23:00:28,823][543983] Updated weights for policy 0, policy_version 16171 (0.0007) +[2026-07-22 23:00:29,111][543983] Updated weights for policy 0, policy_version 16181 (0.0006) +[2026-07-22 23:00:29,386][543983] Updated weights for policy 0, policy_version 16191 (0.0007) +[2026-07-22 23:00:30,420][543983] Updated weights for policy 0, policy_version 16201 (0.0008) +[2026-07-22 23:00:30,695][543983] Updated weights for policy 0, policy_version 16211 (0.0007) +[2026-07-22 23:00:30,992][543983] Updated weights for policy 0, policy_version 16221 (0.0006) +[2026-07-22 23:00:31,270][543983] Updated weights for policy 0, policy_version 16231 (0.0007) +[2026-07-22 23:00:31,559][543983] Updated weights for policy 0, policy_version 16241 (0.0006) +[2026-07-22 23:00:31,849][543983] Updated weights for policy 0, policy_version 16251 (0.0006) +[2026-07-22 23:00:32,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 8323072. Throughput: 0: 12575.3. Samples: 8342272. Policy #0 lag: (min: 46.0, avg: 63.2, max: 110.0) +[2026-07-22 23:00:32,287][543203] Avg episode reward: [(0, '466.116')] +[2026-07-22 23:00:32,306][543696] Saving new best policy, reward=466.116! +[2026-07-22 23:00:32,858][543983] Updated weights for policy 0, policy_version 16261 (0.0007) +[2026-07-22 23:00:33,162][543983] Updated weights for policy 0, policy_version 16272 (0.0008) +[2026-07-22 23:00:33,454][543983] Updated weights for policy 0, policy_version 16282 (0.0011) +[2026-07-22 23:00:33,740][543983] Updated weights for policy 0, policy_version 16292 (0.0007) +[2026-07-22 23:00:34,085][543983] Updated weights for policy 0, policy_version 16304 (0.0007) +[2026-07-22 23:00:34,375][543983] Updated weights for policy 0, policy_version 16314 (0.0007) +[2026-07-22 23:00:35,398][543983] Updated weights for policy 0, policy_version 16324 (0.0008) +[2026-07-22 23:00:35,687][543983] Updated weights for policy 0, policy_version 16334 (0.0007) +[2026-07-22 23:00:35,988][543983] Updated weights for policy 0, policy_version 16344 (0.0007) +[2026-07-22 23:00:36,270][543983] Updated weights for policy 0, policy_version 16354 (0.0007) +[2026-07-22 23:00:36,582][543983] Updated weights for policy 0, policy_version 16365 (0.0008) +[2026-07-22 23:00:36,874][543983] Updated weights for policy 0, policy_version 16375 (0.0007) +[2026-07-22 23:00:37,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 8388608. Throughput: 0: 12620.8. Samples: 8380544. Policy #0 lag: (min: 63.0, avg: 80.3, max: 127.0) +[2026-07-22 23:00:37,287][543203] Avg episode reward: [(0, '490.032')] +[2026-07-22 23:00:37,313][543696] Saving new best policy, reward=490.032! +[2026-07-22 23:00:37,931][543983] Updated weights for policy 0, policy_version 16386 (0.0009) +[2026-07-22 23:00:38,251][543983] Updated weights for policy 0, policy_version 16397 (0.0007) +[2026-07-22 23:00:38,541][543983] Updated weights for policy 0, policy_version 16407 (0.0007) +[2026-07-22 23:00:38,832][543983] Updated weights for policy 0, policy_version 16417 (0.0008) +[2026-07-22 23:00:39,114][543983] Updated weights for policy 0, policy_version 16427 (0.0007) +[2026-07-22 23:00:39,408][543983] Updated weights for policy 0, policy_version 16437 (0.0007) +[2026-07-22 23:00:39,704][543983] Updated weights for policy 0, policy_version 16447 (0.0008) +[2026-07-22 23:00:40,758][543983] Updated weights for policy 0, policy_version 16457 (0.0007) +[2026-07-22 23:00:41,061][543983] Updated weights for policy 0, policy_version 16467 (0.0011) +[2026-07-22 23:00:41,347][543983] Updated weights for policy 0, policy_version 16477 (0.0010) +[2026-07-22 23:00:41,616][543983] Updated weights for policy 0, policy_version 16487 (0.0008) +[2026-07-22 23:00:41,915][543983] Updated weights for policy 0, policy_version 16497 (0.0006) +[2026-07-22 23:00:42,181][543983] Updated weights for policy 0, policy_version 16507 (0.0006) +[2026-07-22 23:00:42,287][543203] Fps is (10 sec: 9830.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 8421376. Throughput: 0: 12811.4. Samples: 8461440. Policy #0 lag: (min: 63.0, avg: 80.3, max: 127.0) +[2026-07-22 23:00:42,287][543203] Avg episode reward: [(0, '512.920')] +[2026-07-22 23:00:42,335][543696] Saving new best policy, reward=512.920! +[2026-07-22 23:00:43,255][543983] Updated weights for policy 0, policy_version 16518 (0.0007) +[2026-07-22 23:00:43,558][543983] Updated weights for policy 0, policy_version 16528 (0.0007) +[2026-07-22 23:00:43,862][543983] Updated weights for policy 0, policy_version 16539 (0.0007) +[2026-07-22 23:00:44,136][543983] Updated weights for policy 0, policy_version 16549 (0.0006) +[2026-07-22 23:00:44,431][543983] Updated weights for policy 0, policy_version 16559 (0.0006) +[2026-07-22 23:00:44,712][543983] Updated weights for policy 0, policy_version 16569 (0.0007) +[2026-07-22 23:00:45,818][543983] Updated weights for policy 0, policy_version 16580 (0.0006) +[2026-07-22 23:00:46,100][543983] Updated weights for policy 0, policy_version 16590 (0.0006) +[2026-07-22 23:00:46,391][543983] Updated weights for policy 0, policy_version 16600 (0.0007) +[2026-07-22 23:00:46,665][543983] Updated weights for policy 0, policy_version 16610 (0.0006) +[2026-07-22 23:00:46,963][543983] Updated weights for policy 0, policy_version 16620 (0.0006) +[2026-07-22 23:00:47,272][543983] Updated weights for policy 0, policy_version 16631 (0.0007) +[2026-07-22 23:00:47,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 8486912. Throughput: 0: 12552.8. Samples: 8534272. Policy #0 lag: (min: 63.0, avg: 80.3, max: 127.0) +[2026-07-22 23:00:47,287][543203] Avg episode reward: [(0, '526.417')] +[2026-07-22 23:00:47,515][543696] Saving new best policy, reward=526.417! +[2026-07-22 23:00:48,290][543983] Updated weights for policy 0, policy_version 16641 (0.0006) +[2026-07-22 23:00:48,562][543983] Updated weights for policy 0, policy_version 16651 (0.0007) +[2026-07-22 23:00:48,846][543983] Updated weights for policy 0, policy_version 16661 (0.0006) +[2026-07-22 23:00:49,169][543983] Updated weights for policy 0, policy_version 16672 (0.0006) +[2026-07-22 23:00:49,471][543983] Updated weights for policy 0, policy_version 16683 (0.0006) +[2026-07-22 23:00:49,741][543983] Updated weights for policy 0, policy_version 16693 (0.0006) +[2026-07-22 23:00:50,056][543983] Updated weights for policy 0, policy_version 16704 (0.0007) +[2026-07-22 23:00:51,122][543983] Updated weights for policy 0, policy_version 16714 (0.0006) +[2026-07-22 23:00:51,409][543983] Updated weights for policy 0, policy_version 16724 (0.0006) +[2026-07-22 23:00:51,701][543983] Updated weights for policy 0, policy_version 16734 (0.0006) +[2026-07-22 23:00:51,990][543983] Updated weights for policy 0, policy_version 16744 (0.0006) +[2026-07-22 23:00:52,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 8552448. Throughput: 0: 12529.9. Samples: 8569600. Policy #0 lag: (min: 63.0, avg: 80.3, max: 127.0) +[2026-07-22 23:00:52,287][543203] Avg episode reward: [(0, '529.513')] +[2026-07-22 23:00:52,309][543983] Updated weights for policy 0, policy_version 16755 (0.0006) +[2026-07-22 23:00:52,585][543983] Updated weights for policy 0, policy_version 16765 (0.0006) +[2026-07-22 23:00:52,655][543696] Saving new best policy, reward=529.513! +[2026-07-22 23:00:53,655][543983] Updated weights for policy 0, policy_version 16775 (0.0006) +[2026-07-22 23:00:53,929][543983] Updated weights for policy 0, policy_version 16785 (0.0006) +[2026-07-22 23:00:54,216][543983] Updated weights for policy 0, policy_version 16795 (0.0006) +[2026-07-22 23:00:54,491][543983] Updated weights for policy 0, policy_version 16805 (0.0006) +[2026-07-22 23:00:54,776][543983] Updated weights for policy 0, policy_version 16815 (0.0006) +[2026-07-22 23:00:55,076][543983] Updated weights for policy 0, policy_version 16825 (0.0006) +[2026-07-22 23:00:56,115][543983] Updated weights for policy 0, policy_version 16835 (0.0007) +[2026-07-22 23:00:56,396][543983] Updated weights for policy 0, policy_version 16845 (0.0006) +[2026-07-22 23:00:56,691][543983] Updated weights for policy 0, policy_version 16856 (0.0006) +[2026-07-22 23:00:57,029][543983] Updated weights for policy 0, policy_version 16868 (0.0006) +[2026-07-22 23:00:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 8617984. Throughput: 0: 12743.1. Samples: 8651008. Policy #0 lag: (min: 16.0, avg: 49.0, max: 80.0) +[2026-07-22 23:00:57,287][543203] Avg episode reward: [(0, '523.121')] +[2026-07-22 23:00:57,327][543983] Updated weights for policy 0, policy_version 16878 (0.0006) +[2026-07-22 23:00:57,647][543983] Updated weights for policy 0, policy_version 16889 (0.0006) +[2026-07-22 23:00:58,666][543983] Updated weights for policy 0, policy_version 16899 (0.0006) +[2026-07-22 23:00:58,948][543983] Updated weights for policy 0, policy_version 16909 (0.0007) +[2026-07-22 23:00:59,235][543983] Updated weights for policy 0, policy_version 16919 (0.0006) +[2026-07-22 23:00:59,540][543983] Updated weights for policy 0, policy_version 16930 (0.0008) +[2026-07-22 23:00:59,840][543983] Updated weights for policy 0, policy_version 16940 (0.0007) +[2026-07-22 23:01:00,112][543983] Updated weights for policy 0, policy_version 16950 (0.0008) +[2026-07-22 23:01:00,385][543983] Updated weights for policy 0, policy_version 16960 (0.0006) +[2026-07-22 23:01:01,464][543983] Updated weights for policy 0, policy_version 16971 (0.0006) +[2026-07-22 23:01:01,766][543983] Updated weights for policy 0, policy_version 16982 (0.0006) +[2026-07-22 23:01:02,066][543983] Updated weights for policy 0, policy_version 16992 (0.0006) +[2026-07-22 23:01:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.2, 300 sec: 12662.9). Total num frames: 8683520. Throughput: 0: 12686.2. Samples: 8726016. Policy #0 lag: (min: 16.0, avg: 49.0, max: 80.0) +[2026-07-22 23:01:02,287][543203] Avg episode reward: [(0, '507.195')] +[2026-07-22 23:01:02,347][543983] Updated weights for policy 0, policy_version 17003 (0.0006) +[2026-07-22 23:01:02,641][543983] Updated weights for policy 0, policy_version 17013 (0.0007) +[2026-07-22 23:01:02,928][543983] Updated weights for policy 0, policy_version 17023 (0.0007) +[2026-07-22 23:01:04,022][543983] Updated weights for policy 0, policy_version 17033 (0.0007) +[2026-07-22 23:01:04,327][543983] Updated weights for policy 0, policy_version 17044 (0.0006) +[2026-07-22 23:01:04,619][543983] Updated weights for policy 0, policy_version 17054 (0.0006) +[2026-07-22 23:01:04,919][543983] Updated weights for policy 0, policy_version 17065 (0.0006) +[2026-07-22 23:01:05,216][543983] Updated weights for policy 0, policy_version 17075 (0.0006) +[2026-07-22 23:01:05,506][543983] Updated weights for policy 0, policy_version 17085 (0.0006) +[2026-07-22 23:01:06,520][543983] Updated weights for policy 0, policy_version 17095 (0.0006) +[2026-07-22 23:01:06,794][543983] Updated weights for policy 0, policy_version 17105 (0.0007) +[2026-07-22 23:01:07,116][543983] Updated weights for policy 0, policy_version 17116 (0.0006) +[2026-07-22 23:01:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 8749056. Throughput: 0: 12566.8. Samples: 8763136. Policy #0 lag: (min: 63.0, avg: 78.4, max: 127.0) +[2026-07-22 23:01:07,287][543203] Avg episode reward: [(0, '509.343')] +[2026-07-22 23:01:07,399][543983] Updated weights for policy 0, policy_version 17126 (0.0006) +[2026-07-22 23:01:07,696][543983] Updated weights for policy 0, policy_version 17136 (0.0007) +[2026-07-22 23:01:07,972][543983] Updated weights for policy 0, policy_version 17146 (0.0006) +[2026-07-22 23:01:09,038][543983] Updated weights for policy 0, policy_version 17156 (0.0006) +[2026-07-22 23:01:09,314][543983] Updated weights for policy 0, policy_version 17166 (0.0006) +[2026-07-22 23:01:09,617][543983] Updated weights for policy 0, policy_version 17177 (0.0006) +[2026-07-22 23:01:09,939][543983] Updated weights for policy 0, policy_version 17188 (0.0007) +[2026-07-22 23:01:10,211][543983] Updated weights for policy 0, policy_version 17198 (0.0006) +[2026-07-22 23:01:10,534][543983] Updated weights for policy 0, policy_version 17209 (0.0006) +[2026-07-22 23:01:11,569][543983] Updated weights for policy 0, policy_version 17219 (0.0007) +[2026-07-22 23:01:11,846][543983] Updated weights for policy 0, policy_version 17229 (0.0007) +[2026-07-22 23:01:12,150][543983] Updated weights for policy 0, policy_version 17240 (0.0007) +[2026-07-22 23:01:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 8814592. Throughput: 0: 12558.2. Samples: 8835072. Policy #0 lag: (min: 63.0, avg: 78.4, max: 127.0) +[2026-07-22 23:01:12,287][543203] Avg episode reward: [(0, '503.524')] +[2026-07-22 23:01:12,436][543983] Updated weights for policy 0, policy_version 17250 (0.0006) +[2026-07-22 23:01:12,735][543983] Updated weights for policy 0, policy_version 17260 (0.0006) +[2026-07-22 23:01:13,037][543983] Updated weights for policy 0, policy_version 17271 (0.0006) +[2026-07-22 23:01:14,082][543983] Updated weights for policy 0, policy_version 17281 (0.0007) +[2026-07-22 23:01:14,393][543983] Updated weights for policy 0, policy_version 17292 (0.0007) +[2026-07-22 23:01:14,683][543983] Updated weights for policy 0, policy_version 17302 (0.0006) +[2026-07-22 23:01:14,965][543983] Updated weights for policy 0, policy_version 17312 (0.0006) +[2026-07-22 23:01:15,263][543983] Updated weights for policy 0, policy_version 17323 (0.0006) +[2026-07-22 23:01:15,572][543983] Updated weights for policy 0, policy_version 17333 (0.0007) +[2026-07-22 23:01:15,842][543983] Updated weights for policy 0, policy_version 17343 (0.0006) +[2026-07-22 23:01:16,894][543983] Updated weights for policy 0, policy_version 17353 (0.0006) +[2026-07-22 23:01:17,188][543983] Updated weights for policy 0, policy_version 17363 (0.0006) +[2026-07-22 23:01:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 8880128. Throughput: 0: 12828.4. Samples: 8919552. Policy #0 lag: (min: 63.0, avg: 78.4, max: 127.0) +[2026-07-22 23:01:17,287][543203] Avg episode reward: [(0, '501.168')] +[2026-07-22 23:01:17,515][543983] Updated weights for policy 0, policy_version 17374 (0.0007) +[2026-07-22 23:01:17,794][543983] Updated weights for policy 0, policy_version 17384 (0.0006) +[2026-07-22 23:01:18,122][543983] Updated weights for policy 0, policy_version 17395 (0.0006) +[2026-07-22 23:01:18,391][543983] Updated weights for policy 0, policy_version 17405 (0.0006) +[2026-07-22 23:01:19,411][543983] Updated weights for policy 0, policy_version 17415 (0.0007) +[2026-07-22 23:01:19,707][543983] Updated weights for policy 0, policy_version 17425 (0.0006) +[2026-07-22 23:01:19,989][543983] Updated weights for policy 0, policy_version 17435 (0.0006) +[2026-07-22 23:01:20,286][543983] Updated weights for policy 0, policy_version 17445 (0.0006) +[2026-07-22 23:01:20,569][543983] Updated weights for policy 0, policy_version 17455 (0.0006) +[2026-07-22 23:01:20,870][543983] Updated weights for policy 0, policy_version 17465 (0.0006) +[2026-07-22 23:01:21,887][543983] Updated weights for policy 0, policy_version 17475 (0.0006) +[2026-07-22 23:01:22,171][543983] Updated weights for policy 0, policy_version 17485 (0.0006) +[2026-07-22 23:01:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 8945664. Throughput: 0: 12785.8. Samples: 8955904. Policy #0 lag: (min: 31.0, avg: 47.9, max: 95.0) +[2026-07-22 23:01:22,287][543203] Avg episode reward: [(0, '513.887')] +[2026-07-22 23:01:22,479][543983] Updated weights for policy 0, policy_version 17496 (0.0006) +[2026-07-22 23:01:22,798][543983] Updated weights for policy 0, policy_version 17507 (0.0006) +[2026-07-22 23:01:23,105][543983] Updated weights for policy 0, policy_version 17518 (0.0006) +[2026-07-22 23:01:23,374][543983] Updated weights for policy 0, policy_version 17528 (0.0006) +[2026-07-22 23:01:24,436][543983] Updated weights for policy 0, policy_version 17538 (0.0006) +[2026-07-22 23:01:24,734][543983] Updated weights for policy 0, policy_version 17549 (0.0007) +[2026-07-22 23:01:25,043][543983] Updated weights for policy 0, policy_version 17560 (0.0007) +[2026-07-22 23:01:25,320][543983] Updated weights for policy 0, policy_version 17570 (0.0006) +[2026-07-22 23:01:25,619][543983] Updated weights for policy 0, policy_version 17580 (0.0007) +[2026-07-22 23:01:25,963][543983] Updated weights for policy 0, policy_version 17592 (0.0006) +[2026-07-22 23:01:27,043][543983] Updated weights for policy 0, policy_version 17603 (0.0006) +[2026-07-22 23:01:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 9011200. Throughput: 0: 12581.0. Samples: 9027584. Policy #0 lag: (min: 31.0, avg: 47.9, max: 95.0) +[2026-07-22 23:01:27,287][543203] Avg episode reward: [(0, '508.578')] +[2026-07-22 23:01:27,322][543983] Updated weights for policy 0, policy_version 17613 (0.0007) +[2026-07-22 23:01:27,611][543983] Updated weights for policy 0, policy_version 17623 (0.0006) +[2026-07-22 23:01:27,902][543983] Updated weights for policy 0, policy_version 17633 (0.0007) +[2026-07-22 23:01:28,190][543983] Updated weights for policy 0, policy_version 17643 (0.0006) +[2026-07-22 23:01:28,476][543983] Updated weights for policy 0, policy_version 17653 (0.0006) +[2026-07-22 23:01:28,749][543983] Updated weights for policy 0, policy_version 17663 (0.0007) +[2026-07-22 23:01:29,814][543983] Updated weights for policy 0, policy_version 17673 (0.0006) +[2026-07-22 23:01:30,091][543983] Updated weights for policy 0, policy_version 17683 (0.0006) +[2026-07-22 23:01:30,405][543983] Updated weights for policy 0, policy_version 17694 (0.0006) +[2026-07-22 23:01:30,712][543983] Updated weights for policy 0, policy_version 17705 (0.0006) +[2026-07-22 23:01:31,018][543983] Updated weights for policy 0, policy_version 17716 (0.0006) +[2026-07-22 23:01:31,303][543983] Updated weights for policy 0, policy_version 17726 (0.0006) +[2026-07-22 23:01:32,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 9076736. Throughput: 0: 12728.9. Samples: 9107072. Policy #0 lag: (min: 31.0, avg: 47.9, max: 95.0) +[2026-07-22 23:01:32,287][543203] Avg episode reward: [(0, '496.130')] +[2026-07-22 23:01:32,355][543983] Updated weights for policy 0, policy_version 17737 (0.0006) +[2026-07-22 23:01:32,651][543983] Updated weights for policy 0, policy_version 17747 (0.0007) +[2026-07-22 23:01:32,937][543983] Updated weights for policy 0, policy_version 17757 (0.0006) +[2026-07-22 23:01:33,235][543983] Updated weights for policy 0, policy_version 17768 (0.0006) +[2026-07-22 23:01:33,515][543983] Updated weights for policy 0, policy_version 17778 (0.0006) +[2026-07-22 23:01:33,801][543983] Updated weights for policy 0, policy_version 17788 (0.0006) +[2026-07-22 23:01:34,882][543983] Updated weights for policy 0, policy_version 17799 (0.0006) +[2026-07-22 23:01:35,162][543983] Updated weights for policy 0, policy_version 17809 (0.0006) +[2026-07-22 23:01:35,438][543983] Updated weights for policy 0, policy_version 17819 (0.0006) +[2026-07-22 23:01:35,767][543983] Updated weights for policy 0, policy_version 17830 (0.0006) +[2026-07-22 23:01:36,052][543983] Updated weights for policy 0, policy_version 17840 (0.0006) +[2026-07-22 23:01:36,324][543983] Updated weights for policy 0, policy_version 17850 (0.0007) +[2026-07-22 23:01:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 9142272. Throughput: 0: 12856.9. Samples: 9148160. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:01:37,287][543203] Avg episode reward: [(0, '520.730')] +[2026-07-22 23:01:37,415][543983] Updated weights for policy 0, policy_version 17862 (0.0006) +[2026-07-22 23:01:37,699][543983] Updated weights for policy 0, policy_version 17872 (0.0006) +[2026-07-22 23:01:38,020][543983] Updated weights for policy 0, policy_version 17883 (0.0006) +[2026-07-22 23:01:38,302][543983] Updated weights for policy 0, policy_version 17893 (0.0006) +[2026-07-22 23:01:38,622][543983] Updated weights for policy 0, policy_version 17904 (0.0006) +[2026-07-22 23:01:38,891][543983] Updated weights for policy 0, policy_version 17914 (0.0006) +[2026-07-22 23:01:39,966][543983] Updated weights for policy 0, policy_version 17925 (0.0006) +[2026-07-22 23:01:40,272][543983] Updated weights for policy 0, policy_version 17936 (0.0006) +[2026-07-22 23:01:40,568][543983] Updated weights for policy 0, policy_version 17946 (0.0008) +[2026-07-22 23:01:40,854][543983] Updated weights for policy 0, policy_version 17956 (0.0007) +[2026-07-22 23:01:41,122][543983] Updated weights for policy 0, policy_version 17966 (0.0006) +[2026-07-22 23:01:41,413][543983] Updated weights for policy 0, policy_version 17976 (0.0006) +[2026-07-22 23:01:42,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 9207808. Throughput: 0: 12646.4. Samples: 9220096. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:01:42,287][543203] Avg episode reward: [(0, '509.931')] +[2026-07-22 23:01:42,492][543983] Updated weights for policy 0, policy_version 17987 (0.0006) +[2026-07-22 23:01:42,818][543983] Updated weights for policy 0, policy_version 17998 (0.0006) +[2026-07-22 23:01:43,096][543983] Updated weights for policy 0, policy_version 18008 (0.0006) +[2026-07-22 23:01:43,379][543983] Updated weights for policy 0, policy_version 18018 (0.0007) +[2026-07-22 23:01:43,656][543983] Updated weights for policy 0, policy_version 18028 (0.0007) +[2026-07-22 23:01:43,941][543983] Updated weights for policy 0, policy_version 18038 (0.0007) +[2026-07-22 23:01:44,214][543983] Updated weights for policy 0, policy_version 18048 (0.0006) +[2026-07-22 23:01:45,321][543983] Updated weights for policy 0, policy_version 18059 (0.0006) +[2026-07-22 23:01:45,606][543983] Updated weights for policy 0, policy_version 18069 (0.0006) +[2026-07-22 23:01:45,908][543983] Updated weights for policy 0, policy_version 18080 (0.0006) +[2026-07-22 23:01:46,229][543983] Updated weights for policy 0, policy_version 18091 (0.0006) +[2026-07-22 23:01:46,516][543983] Updated weights for policy 0, policy_version 18101 (0.0006) +[2026-07-22 23:01:46,816][543983] Updated weights for policy 0, policy_version 18112 (0.0006) +[2026-07-22 23:01:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 9273344. Throughput: 0: 12598.1. Samples: 9292928. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:01:47,287][543203] Avg episode reward: [(0, '505.432')] +[2026-07-22 23:01:47,935][543983] Updated weights for policy 0, policy_version 18124 (0.0007) +[2026-07-22 23:01:48,214][543983] Updated weights for policy 0, policy_version 18134 (0.0007) +[2026-07-22 23:01:48,499][543983] Updated weights for policy 0, policy_version 18144 (0.0006) +[2026-07-22 23:01:48,781][543983] Updated weights for policy 0, policy_version 18154 (0.0006) +[2026-07-22 23:01:49,058][543983] Updated weights for policy 0, policy_version 18164 (0.0007) +[2026-07-22 23:01:49,370][543983] Updated weights for policy 0, policy_version 18175 (0.0007) +[2026-07-22 23:01:50,439][543983] Updated weights for policy 0, policy_version 18185 (0.0006) +[2026-07-22 23:01:50,716][543983] Updated weights for policy 0, policy_version 18195 (0.0007) +[2026-07-22 23:01:51,007][543983] Updated weights for policy 0, policy_version 18205 (0.0007) +[2026-07-22 23:01:51,296][543983] Updated weights for policy 0, policy_version 18215 (0.0006) +[2026-07-22 23:01:51,569][543983] Updated weights for policy 0, policy_version 18225 (0.0006) +[2026-07-22 23:01:51,874][543983] Updated weights for policy 0, policy_version 18236 (0.0006) +[2026-07-22 23:01:52,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 9338880. Throughput: 0: 12709.0. Samples: 9335040. Policy #0 lag: (min: 63.0, avg: 79.1, max: 127.0) +[2026-07-22 23:01:52,287][543203] Avg episode reward: [(0, '517.680')] +[2026-07-22 23:01:52,948][543983] Updated weights for policy 0, policy_version 18246 (0.0006) +[2026-07-22 23:01:53,235][543983] Updated weights for policy 0, policy_version 18256 (0.0006) +[2026-07-22 23:01:53,531][543983] Updated weights for policy 0, policy_version 18266 (0.0006) +[2026-07-22 23:01:53,834][543983] Updated weights for policy 0, policy_version 18277 (0.0006) +[2026-07-22 23:01:54,162][543983] Updated weights for policy 0, policy_version 18289 (0.0006) +[2026-07-22 23:01:54,467][543983] Updated weights for policy 0, policy_version 18299 (0.0006) +[2026-07-22 23:01:55,507][543983] Updated weights for policy 0, policy_version 18309 (0.0006) +[2026-07-22 23:01:55,798][543983] Updated weights for policy 0, policy_version 18319 (0.0006) +[2026-07-22 23:01:56,121][543983] Updated weights for policy 0, policy_version 18330 (0.0006) +[2026-07-22 23:01:56,380][543983] Updated weights for policy 0, policy_version 18340 (0.0006) +[2026-07-22 23:01:56,673][543983] Updated weights for policy 0, policy_version 18350 (0.0006) +[2026-07-22 23:01:56,951][543983] Updated weights for policy 0, policy_version 18360 (0.0006) +[2026-07-22 23:01:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 9404416. Throughput: 0: 12871.1. Samples: 9414272. Policy #0 lag: (min: 63.0, avg: 79.1, max: 127.0) +[2026-07-22 23:01:57,287][543203] Avg episode reward: [(0, '513.348')] +[2026-07-22 23:01:58,012][543983] Updated weights for policy 0, policy_version 18370 (0.0006) +[2026-07-22 23:01:58,289][543983] Updated weights for policy 0, policy_version 18380 (0.0006) +[2026-07-22 23:01:58,576][543983] Updated weights for policy 0, policy_version 18390 (0.0007) +[2026-07-22 23:01:58,859][543983] Updated weights for policy 0, policy_version 18400 (0.0006) +[2026-07-22 23:01:59,173][543983] Updated weights for policy 0, policy_version 18411 (0.0006) +[2026-07-22 23:01:59,474][543983] Updated weights for policy 0, policy_version 18422 (0.0006) +[2026-07-22 23:01:59,758][543983] Updated weights for policy 0, policy_version 18432 (0.0006) +[2026-07-22 23:02:00,855][543983] Updated weights for policy 0, policy_version 18443 (0.0006) +[2026-07-22 23:02:01,153][543983] Updated weights for policy 0, policy_version 18453 (0.0006) +[2026-07-22 23:02:01,426][543983] Updated weights for policy 0, policy_version 18463 (0.0006) +[2026-07-22 23:02:01,708][543983] Updated weights for policy 0, policy_version 18473 (0.0006) +[2026-07-22 23:02:02,015][543983] Updated weights for policy 0, policy_version 18484 (0.0006) +[2026-07-22 23:02:02,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 9437184. Throughput: 0: 12615.1. Samples: 9487232. Policy #0 lag: (min: 63.0, avg: 79.1, max: 127.0) +[2026-07-22 23:02:02,287][543203] Avg episode reward: [(0, '534.571')] +[2026-07-22 23:02:02,315][543983] Updated weights for policy 0, policy_version 18494 (0.0006) +[2026-07-22 23:02:02,358][543696] Saving new best policy, reward=534.571! +[2026-07-22 23:02:03,396][543983] Updated weights for policy 0, policy_version 18505 (0.0006) +[2026-07-22 23:02:03,687][543983] Updated weights for policy 0, policy_version 18515 (0.0006) +[2026-07-22 23:02:03,963][543983] Updated weights for policy 0, policy_version 18525 (0.0006) +[2026-07-22 23:02:04,236][543983] Updated weights for policy 0, policy_version 18535 (0.0006) +[2026-07-22 23:02:04,536][543983] Updated weights for policy 0, policy_version 18545 (0.0006) +[2026-07-22 23:02:04,823][543983] Updated weights for policy 0, policy_version 18555 (0.0007) +[2026-07-22 23:02:05,933][543983] Updated weights for policy 0, policy_version 18567 (0.0006) +[2026-07-22 23:02:06,261][543983] Updated weights for policy 0, policy_version 18579 (0.0006) +[2026-07-22 23:02:06,551][543983] Updated weights for policy 0, policy_version 18589 (0.0006) +[2026-07-22 23:02:06,831][543983] Updated weights for policy 0, policy_version 18599 (0.0006) +[2026-07-22 23:02:07,150][543983] Updated weights for policy 0, policy_version 18609 (0.0006) +[2026-07-22 23:02:07,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 9502720. Throughput: 0: 12620.8. Samples: 9523840. Policy #0 lag: (min: 63.0, avg: 79.1, max: 127.0) +[2026-07-22 23:02:07,287][543203] Avg episode reward: [(0, '562.522')] +[2026-07-22 23:02:07,510][543983] Updated weights for policy 0, policy_version 18622 (0.0006) +[2026-07-22 23:02:07,555][543696] Saving new best policy, reward=562.522! +[2026-07-22 23:02:08,546][543983] Updated weights for policy 0, policy_version 18632 (0.0006) +[2026-07-22 23:02:08,824][543983] Updated weights for policy 0, policy_version 18642 (0.0006) +[2026-07-22 23:02:09,126][543983] Updated weights for policy 0, policy_version 18652 (0.0006) +[2026-07-22 23:02:09,439][543983] Updated weights for policy 0, policy_version 18663 (0.0006) +[2026-07-22 23:02:09,739][543983] Updated weights for policy 0, policy_version 18674 (0.0006) +[2026-07-22 23:02:10,041][543983] Updated weights for policy 0, policy_version 18685 (0.0006) +[2026-07-22 23:02:11,162][543983] Updated weights for policy 0, policy_version 18696 (0.0006) +[2026-07-22 23:02:11,452][543983] Updated weights for policy 0, policy_version 18706 (0.0006) +[2026-07-22 23:02:11,754][543983] Updated weights for policy 0, policy_version 18717 (0.0007) +[2026-07-22 23:02:12,040][543983] Updated weights for policy 0, policy_version 18727 (0.0006) +[2026-07-22 23:02:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 9568256. Throughput: 0: 12885.3. Samples: 9607424. Policy #0 lag: (min: 40.0, avg: 85.3, max: 104.0) +[2026-07-22 23:02:12,287][543203] Avg episode reward: [(0, '583.913')] +[2026-07-22 23:02:12,323][543983] Updated weights for policy 0, policy_version 18737 (0.0006) +[2026-07-22 23:02:12,635][543983] Updated weights for policy 0, policy_version 18748 (0.0006) +[2026-07-22 23:02:12,736][543696] Saving new best policy, reward=583.913! +[2026-07-22 23:02:13,665][543983] Updated weights for policy 0, policy_version 18758 (0.0007) +[2026-07-22 23:02:13,954][543983] Updated weights for policy 0, policy_version 18768 (0.0006) +[2026-07-22 23:02:14,269][543983] Updated weights for policy 0, policy_version 18779 (0.0006) +[2026-07-22 23:02:14,558][543983] Updated weights for policy 0, policy_version 18789 (0.0007) +[2026-07-22 23:02:14,859][543983] Updated weights for policy 0, policy_version 18800 (0.0006) +[2026-07-22 23:02:15,155][543983] Updated weights for policy 0, policy_version 18810 (0.0006) +[2026-07-22 23:02:16,225][543983] Updated weights for policy 0, policy_version 18820 (0.0006) +[2026-07-22 23:02:16,513][543983] Updated weights for policy 0, policy_version 18830 (0.0006) +[2026-07-22 23:02:16,791][543983] Updated weights for policy 0, policy_version 18840 (0.0006) +[2026-07-22 23:02:17,077][543983] Updated weights for policy 0, policy_version 18850 (0.0006) +[2026-07-22 23:02:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 9633792. Throughput: 0: 12763.0. Samples: 9681408. Policy #0 lag: (min: 40.0, avg: 85.3, max: 104.0) +[2026-07-22 23:02:17,287][543203] Avg episode reward: [(0, '602.096')] +[2026-07-22 23:02:17,358][543983] Updated weights for policy 0, policy_version 18860 (0.0006) +[2026-07-22 23:02:17,634][543983] Updated weights for policy 0, policy_version 18870 (0.0006) +[2026-07-22 23:02:17,912][543696] Saving new best policy, reward=602.096! +[2026-07-22 23:02:17,916][543983] Updated weights for policy 0, policy_version 18880 (0.0007) +[2026-07-22 23:02:18,993][543983] Updated weights for policy 0, policy_version 18891 (0.0006) +[2026-07-22 23:02:19,285][543983] Updated weights for policy 0, policy_version 18901 (0.0007) +[2026-07-22 23:02:19,565][543983] Updated weights for policy 0, policy_version 18911 (0.0006) +[2026-07-22 23:02:19,847][543983] Updated weights for policy 0, policy_version 18921 (0.0006) +[2026-07-22 23:02:20,129][543983] Updated weights for policy 0, policy_version 18931 (0.0006) +[2026-07-22 23:02:20,411][543983] Updated weights for policy 0, policy_version 18941 (0.0008) +[2026-07-22 23:02:21,467][543983] Updated weights for policy 0, policy_version 18951 (0.0006) +[2026-07-22 23:02:21,742][543983] Updated weights for policy 0, policy_version 18961 (0.0006) +[2026-07-22 23:02:22,057][543983] Updated weights for policy 0, policy_version 18972 (0.0006) +[2026-07-22 23:02:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 9699328. Throughput: 0: 12652.1. Samples: 9717504. Policy #0 lag: (min: 40.0, avg: 85.3, max: 104.0) +[2026-07-22 23:02:22,287][543203] Avg episode reward: [(0, '633.278')] +[2026-07-22 23:02:22,349][543983] Updated weights for policy 0, policy_version 18982 (0.0006) +[2026-07-22 23:02:22,626][543983] Updated weights for policy 0, policy_version 18992 (0.0007) +[2026-07-22 23:02:22,969][543983] Updated weights for policy 0, policy_version 19003 (0.0007) +[2026-07-22 23:02:23,099][543696] Saving new best policy, reward=633.278! +[2026-07-22 23:02:24,035][543983] Updated weights for policy 0, policy_version 19014 (0.0006) +[2026-07-22 23:02:24,317][543983] Updated weights for policy 0, policy_version 19024 (0.0006) +[2026-07-22 23:02:24,624][543983] Updated weights for policy 0, policy_version 19035 (0.0006) +[2026-07-22 23:02:24,922][543983] Updated weights for policy 0, policy_version 19045 (0.0007) +[2026-07-22 23:02:25,202][543983] Updated weights for policy 0, policy_version 19055 (0.0007) +[2026-07-22 23:02:25,518][543983] Updated weights for policy 0, policy_version 19066 (0.0006) +[2026-07-22 23:02:26,571][543983] Updated weights for policy 0, policy_version 19076 (0.0007) +[2026-07-22 23:02:26,852][543983] Updated weights for policy 0, policy_version 19086 (0.0006) +[2026-07-22 23:02:27,145][543983] Updated weights for policy 0, policy_version 19096 (0.0007) +[2026-07-22 23:02:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 9764864. Throughput: 0: 12674.8. Samples: 9790464. Policy #0 lag: (min: 62.0, avg: 108.1, max: 125.0) +[2026-07-22 23:02:27,287][543203] Avg episode reward: [(0, '656.850')] +[2026-07-22 23:02:27,436][543983] Updated weights for policy 0, policy_version 19106 (0.0006) +[2026-07-22 23:02:27,716][543983] Updated weights for policy 0, policy_version 19116 (0.0006) +[2026-07-22 23:02:28,038][543983] Updated weights for policy 0, policy_version 19127 (0.0006) +[2026-07-22 23:02:28,273][543696] Saving new best policy, reward=656.850! +[2026-07-22 23:02:29,088][543983] Updated weights for policy 0, policy_version 19137 (0.0007) +[2026-07-22 23:02:29,408][543983] Updated weights for policy 0, policy_version 19148 (0.0007) +[2026-07-22 23:02:29,700][543983] Updated weights for policy 0, policy_version 19158 (0.0006) +[2026-07-22 23:02:29,998][543983] Updated weights for policy 0, policy_version 19169 (0.0007) +[2026-07-22 23:02:30,326][543983] Updated weights for policy 0, policy_version 19180 (0.0007) +[2026-07-22 23:02:30,627][543983] Updated weights for policy 0, policy_version 19191 (0.0006) +[2026-07-22 23:02:31,680][543983] Updated weights for policy 0, policy_version 19201 (0.0007) +[2026-07-22 23:02:31,968][543983] Updated weights for policy 0, policy_version 19211 (0.0006) +[2026-07-22 23:02:32,277][543983] Updated weights for policy 0, policy_version 19222 (0.0007) +[2026-07-22 23:02:32,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 9830400. Throughput: 0: 12942.2. Samples: 9875328. Policy #0 lag: (min: 62.0, avg: 108.1, max: 125.0) +[2026-07-22 23:02:32,287][543203] Avg episode reward: [(0, '613.958')] +[2026-07-22 23:02:32,612][543983] Updated weights for policy 0, policy_version 19234 (0.0006) +[2026-07-22 23:02:32,900][543983] Updated weights for policy 0, policy_version 19244 (0.0007) +[2026-07-22 23:02:33,214][543983] Updated weights for policy 0, policy_version 19255 (0.0006) +[2026-07-22 23:02:34,243][543983] Updated weights for policy 0, policy_version 19265 (0.0006) +[2026-07-22 23:02:34,559][543983] Updated weights for policy 0, policy_version 19276 (0.0006) +[2026-07-22 23:02:34,872][543983] Updated weights for policy 0, policy_version 19287 (0.0006) +[2026-07-22 23:02:35,191][543983] Updated weights for policy 0, policy_version 19298 (0.0007) +[2026-07-22 23:02:35,483][543983] Updated weights for policy 0, policy_version 19309 (0.0006) +[2026-07-22 23:02:35,786][543983] Updated weights for policy 0, policy_version 19319 (0.0006) +[2026-07-22 23:02:36,891][543983] Updated weights for policy 0, policy_version 19330 (0.0006) +[2026-07-22 23:02:37,199][543983] Updated weights for policy 0, policy_version 19340 (0.0006) +[2026-07-22 23:02:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 9895936. Throughput: 0: 12800.0. Samples: 9911040. Policy #0 lag: (min: 62.0, avg: 108.1, max: 125.0) +[2026-07-22 23:02:37,287][543203] Avg episode reward: [(0, '648.446')] +[2026-07-22 23:02:37,528][543983] Updated weights for policy 0, policy_version 19352 (0.0007) +[2026-07-22 23:02:37,820][543983] Updated weights for policy 0, policy_version 19362 (0.0006) +[2026-07-22 23:02:38,156][543983] Updated weights for policy 0, policy_version 19374 (0.0006) +[2026-07-22 23:02:38,430][543983] Updated weights for policy 0, policy_version 19384 (0.0007) +[2026-07-22 23:02:39,448][543983] Updated weights for policy 0, policy_version 19394 (0.0006) +[2026-07-22 23:02:39,718][543983] Updated weights for policy 0, policy_version 19404 (0.0006) +[2026-07-22 23:02:39,994][543983] Updated weights for policy 0, policy_version 19414 (0.0006) +[2026-07-22 23:02:40,278][543983] Updated weights for policy 0, policy_version 19424 (0.0007) +[2026-07-22 23:02:40,576][543983] Updated weights for policy 0, policy_version 19434 (0.0006) +[2026-07-22 23:02:40,838][543983] Updated weights for policy 0, policy_version 19444 (0.0007) +[2026-07-22 23:02:41,130][543983] Updated weights for policy 0, policy_version 19454 (0.0006) +[2026-07-22 23:02:42,191][543983] Updated weights for policy 0, policy_version 19464 (0.0006) +[2026-07-22 23:02:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 9961472. Throughput: 0: 12646.4. Samples: 9983360. Policy #0 lag: (min: 4.0, avg: 20.0, max: 68.0) +[2026-07-22 23:02:42,287][543203] Avg episode reward: [(0, '652.310')] +[2026-07-22 23:02:42,473][543983] Updated weights for policy 0, policy_version 19474 (0.0007) +[2026-07-22 23:02:42,755][543983] Updated weights for policy 0, policy_version 19484 (0.0007) +[2026-07-22 23:02:43,049][543983] Updated weights for policy 0, policy_version 19494 (0.0009) +[2026-07-22 23:02:43,369][543983] Updated weights for policy 0, policy_version 19505 (0.0008) +[2026-07-22 23:02:43,659][543983] Updated weights for policy 0, policy_version 19516 (0.0007) +[2026-07-22 23:02:44,740][543983] Updated weights for policy 0, policy_version 19526 (0.0006) +[2026-07-22 23:02:45,018][543983] Updated weights for policy 0, policy_version 19536 (0.0006) +[2026-07-22 23:02:45,310][543983] Updated weights for policy 0, policy_version 19546 (0.0006) +[2026-07-22 23:02:45,618][543983] Updated weights for policy 0, policy_version 19557 (0.0006) +[2026-07-22 23:02:45,891][543983] Updated weights for policy 0, policy_version 19567 (0.0007) +[2026-07-22 23:02:46,184][543983] Updated weights for policy 0, policy_version 19577 (0.0007) +[2026-07-22 23:02:47,214][543983] Updated weights for policy 0, policy_version 19587 (0.0006) +[2026-07-22 23:02:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 10027008. Throughput: 0: 12782.9. Samples: 10062464. Policy #0 lag: (min: 4.0, avg: 20.0, max: 68.0) +[2026-07-22 23:02:47,287][543203] Avg episode reward: [(0, '639.583')] +[2026-07-22 23:02:47,515][543983] Updated weights for policy 0, policy_version 19597 (0.0006) +[2026-07-22 23:02:47,822][543983] Updated weights for policy 0, policy_version 19608 (0.0006) +[2026-07-22 23:02:48,132][543983] Updated weights for policy 0, policy_version 19619 (0.0006) +[2026-07-22 23:02:48,416][543983] Updated weights for policy 0, policy_version 19629 (0.0006) +[2026-07-22 23:02:48,737][543983] Updated weights for policy 0, policy_version 19640 (0.0006) +[2026-07-22 23:02:49,836][543983] Updated weights for policy 0, policy_version 19651 (0.0007) +[2026-07-22 23:02:50,204][543983] Updated weights for policy 0, policy_version 19664 (0.0007) +[2026-07-22 23:02:50,481][543983] Updated weights for policy 0, policy_version 19674 (0.0007) +[2026-07-22 23:02:50,761][543983] Updated weights for policy 0, policy_version 19684 (0.0006) +[2026-07-22 23:02:51,084][543983] Updated weights for policy 0, policy_version 19695 (0.0006) +[2026-07-22 23:02:51,363][543983] Updated weights for policy 0, policy_version 19705 (0.0006) +[2026-07-22 23:02:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 10092544. Throughput: 0: 12910.9. Samples: 10104832. Policy #0 lag: (min: 4.0, avg: 20.0, max: 68.0) +[2026-07-22 23:02:52,287][543203] Avg episode reward: [(0, '649.825')] +[2026-07-22 23:02:52,422][543983] Updated weights for policy 0, policy_version 19715 (0.0006) +[2026-07-22 23:02:52,704][543983] Updated weights for policy 0, policy_version 19725 (0.0006) +[2026-07-22 23:02:52,985][543983] Updated weights for policy 0, policy_version 19735 (0.0006) +[2026-07-22 23:02:53,283][543983] Updated weights for policy 0, policy_version 19746 (0.0006) +[2026-07-22 23:02:53,568][543983] Updated weights for policy 0, policy_version 19756 (0.0006) +[2026-07-22 23:02:53,864][543983] Updated weights for policy 0, policy_version 19766 (0.0006) +[2026-07-22 23:02:54,946][543983] Updated weights for policy 0, policy_version 19777 (0.0006) +[2026-07-22 23:02:55,221][543983] Updated weights for policy 0, policy_version 19787 (0.0006) +[2026-07-22 23:02:55,513][543983] Updated weights for policy 0, policy_version 19797 (0.0007) +[2026-07-22 23:02:55,785][543983] Updated weights for policy 0, policy_version 19807 (0.0006) +[2026-07-22 23:02:56,068][543983] Updated weights for policy 0, policy_version 19817 (0.0006) +[2026-07-22 23:02:56,349][543983] Updated weights for policy 0, policy_version 19827 (0.0006) +[2026-07-22 23:02:56,668][543983] Updated weights for policy 0, policy_version 19838 (0.0006) +[2026-07-22 23:02:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 10158080. Throughput: 0: 12657.8. Samples: 10177024. Policy #0 lag: (min: 63.0, avg: 79.1, max: 127.0) +[2026-07-22 23:02:57,287][543203] Avg episode reward: [(0, '642.051')] +[2026-07-22 23:02:57,738][543983] Updated weights for policy 0, policy_version 19848 (0.0007) +[2026-07-22 23:02:58,021][543983] Updated weights for policy 0, policy_version 19858 (0.0006) +[2026-07-22 23:02:58,300][543983] Updated weights for policy 0, policy_version 19868 (0.0006) +[2026-07-22 23:02:58,581][543983] Updated weights for policy 0, policy_version 19878 (0.0006) +[2026-07-22 23:02:58,867][543983] Updated weights for policy 0, policy_version 19888 (0.0006) +[2026-07-22 23:02:59,177][543983] Updated weights for policy 0, policy_version 19899 (0.0006) +[2026-07-22 23:03:00,245][543983] Updated weights for policy 0, policy_version 19910 (0.0006) +[2026-07-22 23:03:00,555][543983] Updated weights for policy 0, policy_version 19921 (0.0006) +[2026-07-22 23:03:00,850][543983] Updated weights for policy 0, policy_version 19931 (0.0007) +[2026-07-22 23:03:01,127][543983] Updated weights for policy 0, policy_version 19941 (0.0006) +[2026-07-22 23:03:01,418][543983] Updated weights for policy 0, policy_version 19951 (0.0007) +[2026-07-22 23:03:01,757][543983] Updated weights for policy 0, policy_version 19963 (0.0007) +[2026-07-22 23:03:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 10223616. Throughput: 0: 12632.2. Samples: 10249856. Policy #0 lag: (min: 63.0, avg: 79.1, max: 127.0) +[2026-07-22 23:03:02,287][543203] Avg episode reward: [(0, '657.347')] +[2026-07-22 23:03:02,368][543696] Saving new best policy, reward=657.347! +[2026-07-22 23:03:02,826][543983] Updated weights for policy 0, policy_version 19973 (0.0007) +[2026-07-22 23:03:03,097][543983] Updated weights for policy 0, policy_version 19983 (0.0007) +[2026-07-22 23:03:03,424][543983] Updated weights for policy 0, policy_version 19994 (0.0007) +[2026-07-22 23:03:03,707][543983] Updated weights for policy 0, policy_version 20004 (0.0008) +[2026-07-22 23:03:03,985][543983] Updated weights for policy 0, policy_version 20014 (0.0006) +[2026-07-22 23:03:04,266][543983] Updated weights for policy 0, policy_version 20024 (0.0006) +[2026-07-22 23:03:05,315][543983] Updated weights for policy 0, policy_version 20034 (0.0006) +[2026-07-22 23:03:05,617][543983] Updated weights for policy 0, policy_version 20045 (0.0007) +[2026-07-22 23:03:05,907][543983] Updated weights for policy 0, policy_version 20055 (0.0007) +[2026-07-22 23:03:06,224][543983] Updated weights for policy 0, policy_version 20066 (0.0008) +[2026-07-22 23:03:06,494][543983] Updated weights for policy 0, policy_version 20076 (0.0006) +[2026-07-22 23:03:06,810][543983] Updated weights for policy 0, policy_version 20087 (0.0009) +[2026-07-22 23:03:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 10289152. Throughput: 0: 12726.0. Samples: 10290176. Policy #0 lag: (min: 63.0, avg: 79.1, max: 127.0) +[2026-07-22 23:03:07,287][543203] Avg episode reward: [(0, '656.990')] +[2026-07-22 23:03:07,862][543983] Updated weights for policy 0, policy_version 20098 (0.0007) +[2026-07-22 23:03:08,185][543983] Updated weights for policy 0, policy_version 20109 (0.0007) +[2026-07-22 23:03:08,472][543983] Updated weights for policy 0, policy_version 20119 (0.0006) +[2026-07-22 23:03:08,758][543983] Updated weights for policy 0, policy_version 20129 (0.0008) +[2026-07-22 23:03:09,040][543983] Updated weights for policy 0, policy_version 20139 (0.0007) +[2026-07-22 23:03:09,333][543983] Updated weights for policy 0, policy_version 20149 (0.0007) +[2026-07-22 23:03:09,614][543983] Updated weights for policy 0, policy_version 20159 (0.0007) +[2026-07-22 23:03:10,657][543983] Updated weights for policy 0, policy_version 20169 (0.0006) +[2026-07-22 23:03:10,964][543983] Updated weights for policy 0, policy_version 20180 (0.0007) +[2026-07-22 23:03:11,262][543983] Updated weights for policy 0, policy_version 20190 (0.0007) +[2026-07-22 23:03:11,577][543983] Updated weights for policy 0, policy_version 20201 (0.0006) +[2026-07-22 23:03:11,863][543983] Updated weights for policy 0, policy_version 20211 (0.0006) +[2026-07-22 23:03:12,164][543983] Updated weights for policy 0, policy_version 20222 (0.0006) +[2026-07-22 23:03:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 10354688. Throughput: 0: 12876.8. Samples: 10369920. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:03:12,287][543203] Avg episode reward: [(0, '668.978')] +[2026-07-22 23:03:12,294][543696] Saving new best policy, reward=668.978! +[2026-07-22 23:03:13,210][543983] Updated weights for policy 0, policy_version 20232 (0.0006) +[2026-07-22 23:03:13,493][543983] Updated weights for policy 0, policy_version 20242 (0.0007) +[2026-07-22 23:03:13,784][543983] Updated weights for policy 0, policy_version 20252 (0.0007) +[2026-07-22 23:03:14,086][543983] Updated weights for policy 0, policy_version 20263 (0.0006) +[2026-07-22 23:03:14,383][543983] Updated weights for policy 0, policy_version 20273 (0.0006) +[2026-07-22 23:03:14,697][543983] Updated weights for policy 0, policy_version 20284 (0.0006) +[2026-07-22 23:03:15,778][543983] Updated weights for policy 0, policy_version 20295 (0.0006) +[2026-07-22 23:03:16,054][543983] Updated weights for policy 0, policy_version 20305 (0.0006) +[2026-07-22 23:03:16,336][543983] Updated weights for policy 0, policy_version 20315 (0.0006) +[2026-07-22 23:03:16,662][543983] Updated weights for policy 0, policy_version 20326 (0.0007) +[2026-07-22 23:03:16,971][543983] Updated weights for policy 0, policy_version 20337 (0.0007) +[2026-07-22 23:03:17,245][543983] Updated weights for policy 0, policy_version 20347 (0.0008) +[2026-07-22 23:03:17,287][543203] Fps is (10 sec: 9830.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 10387456. Throughput: 0: 12603.7. Samples: 10442496. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:03:17,287][543203] Avg episode reward: [(0, '666.457')] +[2026-07-22 23:03:18,285][543983] Updated weights for policy 0, policy_version 20357 (0.0006) +[2026-07-22 23:03:18,593][543983] Updated weights for policy 0, policy_version 20368 (0.0006) +[2026-07-22 23:03:18,915][543983] Updated weights for policy 0, policy_version 20379 (0.0006) +[2026-07-22 23:03:19,189][543983] Updated weights for policy 0, policy_version 20389 (0.0006) +[2026-07-22 23:03:19,498][543983] Updated weights for policy 0, policy_version 20400 (0.0007) +[2026-07-22 23:03:19,772][543983] Updated weights for policy 0, policy_version 20410 (0.0006) +[2026-07-22 23:03:20,862][543983] Updated weights for policy 0, policy_version 20421 (0.0006) +[2026-07-22 23:03:21,173][543983] Updated weights for policy 0, policy_version 20432 (0.0006) +[2026-07-22 23:03:21,453][543983] Updated weights for policy 0, policy_version 20442 (0.0006) +[2026-07-22 23:03:21,726][543983] Updated weights for policy 0, policy_version 20452 (0.0006) +[2026-07-22 23:03:22,052][543983] Updated weights for policy 0, policy_version 20463 (0.0007) +[2026-07-22 23:03:22,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 10452992. Throughput: 0: 12612.3. Samples: 10478592. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:03:22,287][543203] Avg episode reward: [(0, '681.949')] +[2026-07-22 23:03:22,349][543983] Updated weights for policy 0, policy_version 20474 (0.0006) +[2026-07-22 23:03:22,514][543696] Saving new best policy, reward=681.949! +[2026-07-22 23:03:23,466][543983] Updated weights for policy 0, policy_version 20485 (0.0006) +[2026-07-22 23:03:23,764][543983] Updated weights for policy 0, policy_version 20496 (0.0006) +[2026-07-22 23:03:24,054][543983] Updated weights for policy 0, policy_version 20506 (0.0006) +[2026-07-22 23:03:24,331][543983] Updated weights for policy 0, policy_version 20516 (0.0006) +[2026-07-22 23:03:24,630][543983] Updated weights for policy 0, policy_version 20527 (0.0007) +[2026-07-22 23:03:24,934][543983] Updated weights for policy 0, policy_version 20537 (0.0006) +[2026-07-22 23:03:25,993][543983] Updated weights for policy 0, policy_version 20547 (0.0006) +[2026-07-22 23:03:26,282][543983] Updated weights for policy 0, policy_version 20557 (0.0006) +[2026-07-22 23:03:26,554][543983] Updated weights for policy 0, policy_version 20567 (0.0006) +[2026-07-22 23:03:26,837][543983] Updated weights for policy 0, policy_version 20577 (0.0006) +[2026-07-22 23:03:27,144][543983] Updated weights for policy 0, policy_version 20588 (0.0006) +[2026-07-22 23:03:27,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 10518528. Throughput: 0: 12871.1. Samples: 10562560. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:03:27,287][543203] Avg episode reward: [(0, '668.967')] +[2026-07-22 23:03:27,433][543983] Updated weights for policy 0, policy_version 20598 (0.0006) +[2026-07-22 23:03:27,733][543983] Updated weights for policy 0, policy_version 20608 (0.0007) +[2026-07-22 23:03:28,833][543983] Updated weights for policy 0, policy_version 20620 (0.0007) +[2026-07-22 23:03:29,129][543983] Updated weights for policy 0, policy_version 20631 (0.0006) +[2026-07-22 23:03:29,453][543983] Updated weights for policy 0, policy_version 20642 (0.0007) +[2026-07-22 23:03:29,767][543983] Updated weights for policy 0, policy_version 20653 (0.0007) +[2026-07-22 23:03:30,053][543983] Updated weights for policy 0, policy_version 20663 (0.0006) +[2026-07-22 23:03:31,139][543983] Updated weights for policy 0, policy_version 20673 (0.0006) +[2026-07-22 23:03:31,417][543983] Updated weights for policy 0, policy_version 20683 (0.0007) +[2026-07-22 23:03:31,701][543983] Updated weights for policy 0, policy_version 20693 (0.0007) +[2026-07-22 23:03:31,983][543983] Updated weights for policy 0, policy_version 20703 (0.0006) +[2026-07-22 23:03:32,274][543983] Updated weights for policy 0, policy_version 20713 (0.0006) +[2026-07-22 23:03:32,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 10584064. Throughput: 0: 12760.2. Samples: 10636672. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:03:32,287][543203] Avg episode reward: [(0, '700.474')] +[2026-07-22 23:03:32,554][543983] Updated weights for policy 0, policy_version 20723 (0.0006) +[2026-07-22 23:03:32,870][543983] Updated weights for policy 0, policy_version 20734 (0.0007) +[2026-07-22 23:03:32,913][543696] Saving new best policy, reward=700.474! +[2026-07-22 23:03:33,928][543983] Updated weights for policy 0, policy_version 20745 (0.0007) +[2026-07-22 23:03:34,205][543983] Updated weights for policy 0, policy_version 20755 (0.0006) +[2026-07-22 23:03:34,498][543983] Updated weights for policy 0, policy_version 20765 (0.0007) +[2026-07-22 23:03:34,776][543983] Updated weights for policy 0, policy_version 20775 (0.0006) +[2026-07-22 23:03:35,066][543983] Updated weights for policy 0, policy_version 20785 (0.0006) +[2026-07-22 23:03:35,344][543983] Updated weights for policy 0, policy_version 20795 (0.0006) +[2026-07-22 23:03:36,412][543983] Updated weights for policy 0, policy_version 20805 (0.0006) +[2026-07-22 23:03:36,689][543983] Updated weights for policy 0, policy_version 20815 (0.0006) +[2026-07-22 23:03:36,971][543983] Updated weights for policy 0, policy_version 20825 (0.0007) +[2026-07-22 23:03:37,251][543983] Updated weights for policy 0, policy_version 20835 (0.0007) +[2026-07-22 23:03:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 10649600. Throughput: 0: 12612.3. Samples: 10672384. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:03:37,287][543203] Avg episode reward: [(0, '716.419')] +[2026-07-22 23:03:37,547][543983] Updated weights for policy 0, policy_version 20845 (0.0007) +[2026-07-22 23:03:37,823][543983] Updated weights for policy 0, policy_version 20855 (0.0006) +[2026-07-22 23:03:38,067][543696] Saving new best policy, reward=716.419! +[2026-07-22 23:03:38,856][543983] Updated weights for policy 0, policy_version 20865 (0.0007) +[2026-07-22 23:03:39,148][543983] Updated weights for policy 0, policy_version 20875 (0.0006) +[2026-07-22 23:03:39,423][543983] Updated weights for policy 0, policy_version 20885 (0.0006) +[2026-07-22 23:03:39,725][543983] Updated weights for policy 0, policy_version 20895 (0.0007) +[2026-07-22 23:03:39,986][543983] Updated weights for policy 0, policy_version 20905 (0.0006) +[2026-07-22 23:03:40,265][543983] Updated weights for policy 0, policy_version 20915 (0.0007) +[2026-07-22 23:03:40,578][543983] Updated weights for policy 0, policy_version 20926 (0.0006) +[2026-07-22 23:03:41,636][543983] Updated weights for policy 0, policy_version 20936 (0.0007) +[2026-07-22 23:03:41,953][543983] Updated weights for policy 0, policy_version 20947 (0.0006) +[2026-07-22 23:03:42,240][543983] Updated weights for policy 0, policy_version 20957 (0.0006) +[2026-07-22 23:03:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 10715136. Throughput: 0: 12632.2. Samples: 10745472. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:03:42,287][543203] Avg episode reward: [(0, '731.439')] +[2026-07-22 23:03:42,519][543983] Updated weights for policy 0, policy_version 20967 (0.0006) +[2026-07-22 23:03:42,839][543983] Updated weights for policy 0, policy_version 20978 (0.0006) +[2026-07-22 23:03:43,139][543983] Updated weights for policy 0, policy_version 20989 (0.0008) +[2026-07-22 23:03:43,214][543696] Saving new best policy, reward=731.439! +[2026-07-22 23:03:44,210][543983] Updated weights for policy 0, policy_version 20999 (0.0007) +[2026-07-22 23:03:44,526][543983] Updated weights for policy 0, policy_version 21010 (0.0007) +[2026-07-22 23:03:44,803][543983] Updated weights for policy 0, policy_version 21020 (0.0006) +[2026-07-22 23:03:45,101][543983] Updated weights for policy 0, policy_version 21030 (0.0007) +[2026-07-22 23:03:45,384][543983] Updated weights for policy 0, policy_version 21040 (0.0006) +[2026-07-22 23:03:45,670][543983] Updated weights for policy 0, policy_version 21050 (0.0006) +[2026-07-22 23:03:46,699][543983] Updated weights for policy 0, policy_version 21060 (0.0007) +[2026-07-22 23:03:46,996][543983] Updated weights for policy 0, policy_version 21070 (0.0006) +[2026-07-22 23:03:47,266][543983] Updated weights for policy 0, policy_version 21080 (0.0006) +[2026-07-22 23:03:47,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 10780672. Throughput: 0: 12876.8. Samples: 10829312. Policy #0 lag: (min: 28.0, avg: 44.4, max: 92.0) +[2026-07-22 23:03:47,287][543203] Avg episode reward: [(0, '725.132')] +[2026-07-22 23:03:47,548][543983] Updated weights for policy 0, policy_version 21090 (0.0006) +[2026-07-22 23:03:47,840][543983] Updated weights for policy 0, policy_version 21100 (0.0006) +[2026-07-22 23:03:48,155][543983] Updated weights for policy 0, policy_version 21111 (0.0007) +[2026-07-22 23:03:49,220][543983] Updated weights for policy 0, policy_version 21121 (0.0007) +[2026-07-22 23:03:49,498][543983] Updated weights for policy 0, policy_version 21131 (0.0006) +[2026-07-22 23:03:49,776][543983] Updated weights for policy 0, policy_version 21141 (0.0006) +[2026-07-22 23:03:50,069][543983] Updated weights for policy 0, policy_version 21151 (0.0007) +[2026-07-22 23:03:50,347][543983] Updated weights for policy 0, policy_version 21161 (0.0006) +[2026-07-22 23:03:50,655][543983] Updated weights for policy 0, policy_version 21172 (0.0006) +[2026-07-22 23:03:50,948][543983] Updated weights for policy 0, policy_version 21182 (0.0007) +[2026-07-22 23:03:52,002][543983] Updated weights for policy 0, policy_version 21192 (0.0006) +[2026-07-22 23:03:52,272][543983] Updated weights for policy 0, policy_version 21202 (0.0006) +[2026-07-22 23:03:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 10846208. Throughput: 0: 12785.8. Samples: 10865536. Policy #0 lag: (min: 28.0, avg: 44.4, max: 92.0) +[2026-07-22 23:03:52,287][543203] Avg episode reward: [(0, '751.623')] +[2026-07-22 23:03:52,551][543983] Updated weights for policy 0, policy_version 21212 (0.0008) +[2026-07-22 23:03:52,837][543983] Updated weights for policy 0, policy_version 21222 (0.0007) +[2026-07-22 23:03:53,150][543983] Updated weights for policy 0, policy_version 21233 (0.0006) +[2026-07-22 23:03:53,425][543983] Updated weights for policy 0, policy_version 21243 (0.0006) +[2026-07-22 23:03:53,561][543696] Saving new best policy, reward=751.623! +[2026-07-22 23:03:54,510][543983] Updated weights for policy 0, policy_version 21253 (0.0007) +[2026-07-22 23:03:54,817][543983] Updated weights for policy 0, policy_version 21264 (0.0007) +[2026-07-22 23:03:55,137][543983] Updated weights for policy 0, policy_version 21275 (0.0007) +[2026-07-22 23:03:55,411][543983] Updated weights for policy 0, policy_version 21285 (0.0007) +[2026-07-22 23:03:55,732][543983] Updated weights for policy 0, policy_version 21296 (0.0008) +[2026-07-22 23:03:56,005][543983] Updated weights for policy 0, policy_version 21306 (0.0008) +[2026-07-22 23:03:57,050][543983] Updated weights for policy 0, policy_version 21316 (0.0007) +[2026-07-22 23:03:57,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 10911744. Throughput: 0: 12635.0. Samples: 10938496. Policy #0 lag: (min: 28.0, avg: 44.4, max: 92.0) +[2026-07-22 23:03:57,287][543203] Avg episode reward: [(0, '727.229')] +[2026-07-22 23:03:57,342][543983] Updated weights for policy 0, policy_version 21326 (0.0006) +[2026-07-22 23:03:57,628][543983] Updated weights for policy 0, policy_version 21336 (0.0006) +[2026-07-22 23:03:57,934][543983] Updated weights for policy 0, policy_version 21347 (0.0006) +[2026-07-22 23:03:58,251][543983] Updated weights for policy 0, policy_version 21358 (0.0007) +[2026-07-22 23:03:58,542][543983] Updated weights for policy 0, policy_version 21368 (0.0007) +[2026-07-22 23:03:59,573][543983] Updated weights for policy 0, policy_version 21378 (0.0006) +[2026-07-22 23:03:59,891][543983] Updated weights for policy 0, policy_version 21389 (0.0006) +[2026-07-22 23:04:00,188][543983] Updated weights for policy 0, policy_version 21399 (0.0006) +[2026-07-22 23:04:00,526][543983] Updated weights for policy 0, policy_version 21411 (0.0006) +[2026-07-22 23:04:00,820][543983] Updated weights for policy 0, policy_version 21421 (0.0006) +[2026-07-22 23:04:01,126][543983] Updated weights for policy 0, policy_version 21432 (0.0006) +[2026-07-22 23:04:02,167][543983] Updated weights for policy 0, policy_version 21442 (0.0006) +[2026-07-22 23:04:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 10977280. Throughput: 0: 12785.8. Samples: 11017856. Policy #0 lag: (min: 74.0, avg: 91.9, max: 135.0) +[2026-07-22 23:04:02,287][543203] Avg episode reward: [(0, '767.949')] +[2026-07-22 23:04:02,450][543983] Updated weights for policy 0, policy_version 21452 (0.0006) +[2026-07-22 23:04:02,761][543983] Updated weights for policy 0, policy_version 21463 (0.0007) +[2026-07-22 23:04:03,046][543983] Updated weights for policy 0, policy_version 21473 (0.0007) +[2026-07-22 23:04:03,319][543983] Updated weights for policy 0, policy_version 21483 (0.0007) +[2026-07-22 23:04:03,637][543983] Updated weights for policy 0, policy_version 21494 (0.0006) +[2026-07-22 23:04:03,922][543696] Saving new best policy, reward=767.949! +[2026-07-22 23:04:03,927][543983] Updated weights for policy 0, policy_version 21504 (0.0006) +[2026-07-22 23:04:05,000][543983] Updated weights for policy 0, policy_version 21515 (0.0006) +[2026-07-22 23:04:05,324][543983] Updated weights for policy 0, policy_version 21526 (0.0006) +[2026-07-22 23:04:05,644][543983] Updated weights for policy 0, policy_version 21537 (0.0006) +[2026-07-22 23:04:05,947][543983] Updated weights for policy 0, policy_version 21548 (0.0006) +[2026-07-22 23:04:06,237][543983] Updated weights for policy 0, policy_version 21558 (0.0006) +[2026-07-22 23:04:06,505][543983] Updated weights for policy 0, policy_version 21568 (0.0006) +[2026-07-22 23:04:07,286][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11042816. Throughput: 0: 12893.9. Samples: 11058816. Policy #0 lag: (min: 74.0, avg: 91.9, max: 135.0) +[2026-07-22 23:04:07,287][543203] Avg episode reward: [(0, '753.010')] +[2026-07-22 23:04:07,583][543983] Updated weights for policy 0, policy_version 21578 (0.0007) +[2026-07-22 23:04:07,855][543983] Updated weights for policy 0, policy_version 21588 (0.0007) +[2026-07-22 23:04:08,187][543983] Updated weights for policy 0, policy_version 21599 (0.0007) +[2026-07-22 23:04:08,494][543983] Updated weights for policy 0, policy_version 21610 (0.0008) +[2026-07-22 23:04:08,782][543983] Updated weights for policy 0, policy_version 21620 (0.0007) +[2026-07-22 23:04:09,076][543983] Updated weights for policy 0, policy_version 21630 (0.0007) +[2026-07-22 23:04:10,123][543983] Updated weights for policy 0, policy_version 21640 (0.0006) +[2026-07-22 23:04:10,408][543983] Updated weights for policy 0, policy_version 21650 (0.0006) +[2026-07-22 23:04:10,732][543983] Updated weights for policy 0, policy_version 21662 (0.0006) +[2026-07-22 23:04:11,028][543983] Updated weights for policy 0, policy_version 21672 (0.0007) +[2026-07-22 23:04:11,315][543983] Updated weights for policy 0, policy_version 21682 (0.0007) +[2026-07-22 23:04:11,590][543983] Updated weights for policy 0, policy_version 21692 (0.0007) +[2026-07-22 23:04:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11108352. Throughput: 0: 12652.1. Samples: 11131904. Policy #0 lag: (min: 74.0, avg: 91.9, max: 135.0) +[2026-07-22 23:04:12,287][543203] Avg episode reward: [(0, '770.552')] +[2026-07-22 23:04:12,293][543696] Saving new best policy, reward=770.552! +[2026-07-22 23:04:12,674][543983] Updated weights for policy 0, policy_version 21702 (0.0009) +[2026-07-22 23:04:12,974][543983] Updated weights for policy 0, policy_version 21712 (0.0012) +[2026-07-22 23:04:13,301][543983] Updated weights for policy 0, policy_version 21723 (0.0007) +[2026-07-22 23:04:13,595][543983] Updated weights for policy 0, policy_version 21733 (0.0007) +[2026-07-22 23:04:13,893][543983] Updated weights for policy 0, policy_version 21743 (0.0007) +[2026-07-22 23:04:14,204][543983] Updated weights for policy 0, policy_version 21754 (0.0007) +[2026-07-22 23:04:15,186][543983] Updated weights for policy 0, policy_version 21764 (0.0007) +[2026-07-22 23:04:15,491][543983] Updated weights for policy 0, policy_version 21774 (0.0007) +[2026-07-22 23:04:15,766][543983] Updated weights for policy 0, policy_version 21784 (0.0007) +[2026-07-22 23:04:16,063][543983] Updated weights for policy 0, policy_version 21794 (0.0008) +[2026-07-22 23:04:16,364][543983] Updated weights for policy 0, policy_version 21805 (0.0008) +[2026-07-22 23:04:16,660][543983] Updated weights for policy 0, policy_version 21815 (0.0008) +[2026-07-22 23:04:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 11173888. Throughput: 0: 12615.1. Samples: 11204352. Policy #0 lag: (min: 63.0, avg: 82.5, max: 127.0) +[2026-07-22 23:04:17,287][543203] Avg episode reward: [(0, '764.654')] +[2026-07-22 23:04:17,716][543983] Updated weights for policy 0, policy_version 21825 (0.0008) +[2026-07-22 23:04:18,031][543983] Updated weights for policy 0, policy_version 21836 (0.0008) +[2026-07-22 23:04:18,354][543983] Updated weights for policy 0, policy_version 21847 (0.0009) +[2026-07-22 23:04:18,638][543983] Updated weights for policy 0, policy_version 21857 (0.0008) +[2026-07-22 23:04:18,942][543983] Updated weights for policy 0, policy_version 21867 (0.0008) +[2026-07-22 23:04:19,237][543983] Updated weights for policy 0, policy_version 21878 (0.0007) +[2026-07-22 23:04:19,525][543983] Updated weights for policy 0, policy_version 21888 (0.0007) +[2026-07-22 23:04:20,559][543983] Updated weights for policy 0, policy_version 21898 (0.0008) +[2026-07-22 23:04:20,841][543983] Updated weights for policy 0, policy_version 21908 (0.0007) +[2026-07-22 23:04:21,127][543983] Updated weights for policy 0, policy_version 21918 (0.0007) +[2026-07-22 23:04:21,422][543983] Updated weights for policy 0, policy_version 21928 (0.0007) +[2026-07-22 23:04:21,701][543983] Updated weights for policy 0, policy_version 21938 (0.0007) +[2026-07-22 23:04:22,014][543983] Updated weights for policy 0, policy_version 21949 (0.0006) +[2026-07-22 23:04:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 11239424. Throughput: 0: 12700.4. Samples: 11243904. Policy #0 lag: (min: 63.0, avg: 82.5, max: 127.0) +[2026-07-22 23:04:22,287][543203] Avg episode reward: [(0, '785.910')] +[2026-07-22 23:04:22,293][543696] Saving new best policy, reward=785.910! +[2026-07-22 23:04:23,064][543983] Updated weights for policy 0, policy_version 21959 (0.0007) +[2026-07-22 23:04:23,351][543983] Updated weights for policy 0, policy_version 21969 (0.0008) +[2026-07-22 23:04:23,626][543983] Updated weights for policy 0, policy_version 21979 (0.0007) +[2026-07-22 23:04:23,912][543983] Updated weights for policy 0, policy_version 21989 (0.0007) +[2026-07-22 23:04:24,198][543983] Updated weights for policy 0, policy_version 21999 (0.0008) +[2026-07-22 23:04:24,500][543983] Updated weights for policy 0, policy_version 22009 (0.0007) +[2026-07-22 23:04:25,549][543983] Updated weights for policy 0, policy_version 22019 (0.0008) +[2026-07-22 23:04:25,846][543983] Updated weights for policy 0, policy_version 22029 (0.0008) +[2026-07-22 23:04:26,129][543983] Updated weights for policy 0, policy_version 22039 (0.0006) +[2026-07-22 23:04:26,414][543983] Updated weights for policy 0, policy_version 22049 (0.0007) +[2026-07-22 23:04:26,700][543983] Updated weights for policy 0, policy_version 22059 (0.0007) +[2026-07-22 23:04:26,982][543983] Updated weights for policy 0, policy_version 22069 (0.0007) +[2026-07-22 23:04:27,273][543983] Updated weights for policy 0, policy_version 22079 (0.0006) +[2026-07-22 23:04:27,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11272192. Throughput: 0: 12865.4. Samples: 11324416. Policy #0 lag: (min: 63.0, avg: 82.5, max: 127.0) +[2026-07-22 23:04:27,287][543203] Avg episode reward: [(0, '799.250')] +[2026-07-22 23:04:27,298][543696] Saving new best policy, reward=799.250! +[2026-07-22 23:04:28,354][543983] Updated weights for policy 0, policy_version 22090 (0.0007) +[2026-07-22 23:04:28,659][543983] Updated weights for policy 0, policy_version 22101 (0.0006) +[2026-07-22 23:04:28,965][543983] Updated weights for policy 0, policy_version 22111 (0.0007) +[2026-07-22 23:04:29,251][543983] Updated weights for policy 0, policy_version 22121 (0.0006) +[2026-07-22 23:04:29,566][543983] Updated weights for policy 0, policy_version 22132 (0.0007) +[2026-07-22 23:04:29,871][543983] Updated weights for policy 0, policy_version 22143 (0.0006) +[2026-07-22 23:04:30,897][543983] Updated weights for policy 0, policy_version 22153 (0.0006) +[2026-07-22 23:04:31,205][543983] Updated weights for policy 0, policy_version 22164 (0.0006) +[2026-07-22 23:04:31,487][543983] Updated weights for policy 0, policy_version 22174 (0.0006) +[2026-07-22 23:04:31,777][543983] Updated weights for policy 0, policy_version 22184 (0.0007) +[2026-07-22 23:04:32,075][543983] Updated weights for policy 0, policy_version 22195 (0.0007) +[2026-07-22 23:04:32,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11337728. Throughput: 0: 12603.7. Samples: 11396480. Policy #0 lag: (min: 63.0, avg: 82.5, max: 127.0) +[2026-07-22 23:04:32,287][543203] Avg episode reward: [(0, '796.323')] +[2026-07-22 23:04:32,369][543983] Updated weights for policy 0, policy_version 22205 (0.0006) +[2026-07-22 23:04:33,404][543983] Updated weights for policy 0, policy_version 22216 (0.0006) +[2026-07-22 23:04:33,719][543983] Updated weights for policy 0, policy_version 22227 (0.0006) +[2026-07-22 23:04:34,034][543983] Updated weights for policy 0, policy_version 22238 (0.0006) +[2026-07-22 23:04:34,317][543983] Updated weights for policy 0, policy_version 22248 (0.0006) +[2026-07-22 23:04:34,600][543983] Updated weights for policy 0, policy_version 22258 (0.0006) +[2026-07-22 23:04:34,875][543983] Updated weights for policy 0, policy_version 22268 (0.0008) +[2026-07-22 23:04:35,963][543983] Updated weights for policy 0, policy_version 22278 (0.0006) +[2026-07-22 23:04:36,259][543983] Updated weights for policy 0, policy_version 22288 (0.0006) +[2026-07-22 23:04:36,526][543983] Updated weights for policy 0, policy_version 22298 (0.0006) +[2026-07-22 23:04:36,798][543983] Updated weights for policy 0, policy_version 22308 (0.0006) +[2026-07-22 23:04:37,092][543983] Updated weights for policy 0, policy_version 22318 (0.0006) +[2026-07-22 23:04:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11403264. Throughput: 0: 12586.7. Samples: 11431936. Policy #0 lag: (min: 63.0, avg: 79.4, max: 127.0) +[2026-07-22 23:04:37,287][543203] Avg episode reward: [(0, '764.966')] +[2026-07-22 23:04:37,385][543983] Updated weights for policy 0, policy_version 22328 (0.0006) +[2026-07-22 23:04:38,444][543983] Updated weights for policy 0, policy_version 22339 (0.0007) +[2026-07-22 23:04:38,726][543983] Updated weights for policy 0, policy_version 22349 (0.0006) +[2026-07-22 23:04:39,008][543983] Updated weights for policy 0, policy_version 22359 (0.0006) +[2026-07-22 23:04:39,296][543983] Updated weights for policy 0, policy_version 22369 (0.0008) +[2026-07-22 23:04:39,587][543983] Updated weights for policy 0, policy_version 22379 (0.0007) +[2026-07-22 23:04:39,849][543983] Updated weights for policy 0, policy_version 22389 (0.0006) +[2026-07-22 23:04:40,959][543983] Updated weights for policy 0, policy_version 22401 (0.0006) +[2026-07-22 23:04:41,237][543983] Updated weights for policy 0, policy_version 22411 (0.0007) +[2026-07-22 23:04:41,550][543983] Updated weights for policy 0, policy_version 22422 (0.0006) +[2026-07-22 23:04:41,862][543983] Updated weights for policy 0, policy_version 22433 (0.0006) +[2026-07-22 23:04:42,206][543983] Updated weights for policy 0, policy_version 22445 (0.0006) +[2026-07-22 23:04:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11468800. Throughput: 0: 12811.4. Samples: 11515008. Policy #0 lag: (min: 63.0, avg: 79.4, max: 127.0) +[2026-07-22 23:04:42,287][543203] Avg episode reward: [(0, '754.180')] +[2026-07-22 23:04:42,491][543983] Updated weights for policy 0, policy_version 22455 (0.0006) +[2026-07-22 23:04:43,523][543983] Updated weights for policy 0, policy_version 22465 (0.0006) +[2026-07-22 23:04:43,836][543983] Updated weights for policy 0, policy_version 22476 (0.0006) +[2026-07-22 23:04:44,127][543983] Updated weights for policy 0, policy_version 22486 (0.0006) +[2026-07-22 23:04:44,402][543983] Updated weights for policy 0, policy_version 22496 (0.0006) +[2026-07-22 23:04:44,696][543983] Updated weights for policy 0, policy_version 22506 (0.0006) +[2026-07-22 23:04:44,975][543983] Updated weights for policy 0, policy_version 22516 (0.0006) +[2026-07-22 23:04:45,276][543983] Updated weights for policy 0, policy_version 22526 (0.0006) +[2026-07-22 23:04:46,358][543983] Updated weights for policy 0, policy_version 22538 (0.0006) +[2026-07-22 23:04:46,641][543983] Updated weights for policy 0, policy_version 22548 (0.0006) +[2026-07-22 23:04:46,926][543983] Updated weights for policy 0, policy_version 22558 (0.0006) +[2026-07-22 23:04:47,236][543983] Updated weights for policy 0, policy_version 22569 (0.0006) +[2026-07-22 23:04:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11534336. Throughput: 0: 12674.9. Samples: 11588224. Policy #0 lag: (min: 63.0, avg: 79.4, max: 127.0) +[2026-07-22 23:04:47,287][543203] Avg episode reward: [(0, '718.319')] +[2026-07-22 23:04:47,542][543983] Updated weights for policy 0, policy_version 22580 (0.0006) +[2026-07-22 23:04:47,823][543983] Updated weights for policy 0, policy_version 22590 (0.0006) +[2026-07-22 23:04:48,892][543983] Updated weights for policy 0, policy_version 22600 (0.0006) +[2026-07-22 23:04:49,211][543983] Updated weights for policy 0, policy_version 22611 (0.0006) +[2026-07-22 23:04:49,491][543983] Updated weights for policy 0, policy_version 22621 (0.0006) +[2026-07-22 23:04:49,808][543983] Updated weights for policy 0, policy_version 22632 (0.0006) +[2026-07-22 23:04:50,085][543983] Updated weights for policy 0, policy_version 22642 (0.0006) +[2026-07-22 23:04:50,365][543983] Updated weights for policy 0, policy_version 22652 (0.0006) +[2026-07-22 23:04:51,436][543983] Updated weights for policy 0, policy_version 22663 (0.0007) +[2026-07-22 23:04:51,718][543983] Updated weights for policy 0, policy_version 22673 (0.0007) +[2026-07-22 23:04:52,024][543983] Updated weights for policy 0, policy_version 22684 (0.0007) +[2026-07-22 23:04:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11599872. Throughput: 0: 12575.3. Samples: 11624704. Policy #0 lag: (min: 63.0, avg: 79.4, max: 127.0) +[2026-07-22 23:04:52,287][543203] Avg episode reward: [(0, '719.402')] +[2026-07-22 23:04:52,317][543983] Updated weights for policy 0, policy_version 22694 (0.0006) +[2026-07-22 23:04:52,600][543983] Updated weights for policy 0, policy_version 22704 (0.0006) +[2026-07-22 23:04:52,901][543983] Updated weights for policy 0, policy_version 22715 (0.0007) +[2026-07-22 23:04:53,979][543983] Updated weights for policy 0, policy_version 22726 (0.0006) +[2026-07-22 23:04:54,274][543983] Updated weights for policy 0, policy_version 22736 (0.0007) +[2026-07-22 23:04:54,558][543983] Updated weights for policy 0, policy_version 22746 (0.0006) +[2026-07-22 23:04:54,863][543983] Updated weights for policy 0, policy_version 22757 (0.0007) +[2026-07-22 23:04:55,210][543983] Updated weights for policy 0, policy_version 22769 (0.0006) +[2026-07-22 23:04:55,493][543983] Updated weights for policy 0, policy_version 22779 (0.0006) +[2026-07-22 23:04:56,530][543983] Updated weights for policy 0, policy_version 22789 (0.0006) +[2026-07-22 23:04:56,817][543983] Updated weights for policy 0, policy_version 22799 (0.0006) +[2026-07-22 23:04:57,099][543983] Updated weights for policy 0, policy_version 22809 (0.0006) +[2026-07-22 23:04:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11665408. Throughput: 0: 12583.8. Samples: 11698176. Policy #0 lag: (min: 63.0, avg: 79.8, max: 127.0) +[2026-07-22 23:04:57,287][543203] Avg episode reward: [(0, '719.656')] +[2026-07-22 23:04:57,407][543983] Updated weights for policy 0, policy_version 22820 (0.0007) +[2026-07-22 23:04:57,704][543983] Updated weights for policy 0, policy_version 22830 (0.0006) +[2026-07-22 23:04:58,027][543983] Updated weights for policy 0, policy_version 22842 (0.0006) +[2026-07-22 23:04:59,071][543983] Updated weights for policy 0, policy_version 22852 (0.0006) +[2026-07-22 23:04:59,410][543983] Updated weights for policy 0, policy_version 22864 (0.0007) +[2026-07-22 23:04:59,731][543983] Updated weights for policy 0, policy_version 22875 (0.0007) +[2026-07-22 23:05:00,053][543983] Updated weights for policy 0, policy_version 22887 (0.0006) +[2026-07-22 23:05:00,361][543983] Updated weights for policy 0, policy_version 22898 (0.0006) +[2026-07-22 23:05:00,662][543983] Updated weights for policy 0, policy_version 22909 (0.0006) +[2026-07-22 23:05:01,722][543983] Updated weights for policy 0, policy_version 22919 (0.0007) +[2026-07-22 23:05:02,037][543983] Updated weights for policy 0, policy_version 22930 (0.0007) +[2026-07-22 23:05:02,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11730944. Throughput: 0: 12802.8. Samples: 11780480. Policy #0 lag: (min: 63.0, avg: 79.8, max: 127.0) +[2026-07-22 23:05:02,287][543203] Avg episode reward: [(0, '709.763')] +[2026-07-22 23:05:02,350][543983] Updated weights for policy 0, policy_version 22940 (0.0006) +[2026-07-22 23:05:02,623][543983] Updated weights for policy 0, policy_version 22950 (0.0007) +[2026-07-22 23:05:02,936][543983] Updated weights for policy 0, policy_version 22961 (0.0007) +[2026-07-22 23:05:03,229][543983] Updated weights for policy 0, policy_version 22971 (0.0006) +[2026-07-22 23:05:04,249][543983] Updated weights for policy 0, policy_version 22981 (0.0007) +[2026-07-22 23:05:04,557][543983] Updated weights for policy 0, policy_version 22992 (0.0006) +[2026-07-22 23:05:04,865][543983] Updated weights for policy 0, policy_version 23003 (0.0007) +[2026-07-22 23:05:05,169][543983] Updated weights for policy 0, policy_version 23014 (0.0008) +[2026-07-22 23:05:05,453][543983] Updated weights for policy 0, policy_version 23024 (0.0007) +[2026-07-22 23:05:05,749][543983] Updated weights for policy 0, policy_version 23034 (0.0008) +[2026-07-22 23:05:06,782][543983] Updated weights for policy 0, policy_version 23044 (0.0007) +[2026-07-22 23:05:07,075][543983] Updated weights for policy 0, policy_version 23055 (0.0006) +[2026-07-22 23:05:07,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11796480. Throughput: 0: 12726.0. Samples: 11816576. Policy #0 lag: (min: 63.0, avg: 79.8, max: 127.0) +[2026-07-22 23:05:07,287][543203] Avg episode reward: [(0, '719.146')] +[2026-07-22 23:05:07,358][543983] Updated weights for policy 0, policy_version 23065 (0.0007) +[2026-07-22 23:05:07,654][543983] Updated weights for policy 0, policy_version 23075 (0.0006) +[2026-07-22 23:05:08,014][543983] Updated weights for policy 0, policy_version 23087 (0.0007) +[2026-07-22 23:05:08,284][543983] Updated weights for policy 0, policy_version 23097 (0.0007) +[2026-07-22 23:05:09,376][543983] Updated weights for policy 0, policy_version 23107 (0.0007) +[2026-07-22 23:05:09,660][543983] Updated weights for policy 0, policy_version 23117 (0.0007) +[2026-07-22 23:05:09,938][543983] Updated weights for policy 0, policy_version 23127 (0.0007) +[2026-07-22 23:05:10,251][543983] Updated weights for policy 0, policy_version 23138 (0.0007) +[2026-07-22 23:05:10,544][543983] Updated weights for policy 0, policy_version 23148 (0.0006) +[2026-07-22 23:05:10,831][543983] Updated weights for policy 0, policy_version 23158 (0.0006) +[2026-07-22 23:05:11,135][543983] Updated weights for policy 0, policy_version 23168 (0.0007) +[2026-07-22 23:05:12,157][543983] Updated weights for policy 0, policy_version 23178 (0.0006) +[2026-07-22 23:05:12,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11862016. Throughput: 0: 12552.5. Samples: 11889280. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:05:12,287][543203] Avg episode reward: [(0, '719.100')] +[2026-07-22 23:05:12,473][543983] Updated weights for policy 0, policy_version 23189 (0.0006) +[2026-07-22 23:05:12,792][543983] Updated weights for policy 0, policy_version 23200 (0.0007) +[2026-07-22 23:05:13,105][543983] Updated weights for policy 0, policy_version 23211 (0.0006) +[2026-07-22 23:05:13,390][543983] Updated weights for policy 0, policy_version 23221 (0.0008) +[2026-07-22 23:05:13,668][543983] Updated weights for policy 0, policy_version 23231 (0.0006) +[2026-07-22 23:05:14,688][543983] Updated weights for policy 0, policy_version 23241 (0.0006) +[2026-07-22 23:05:15,001][543983] Updated weights for policy 0, policy_version 23251 (0.0009) +[2026-07-22 23:05:15,273][543983] Updated weights for policy 0, policy_version 23261 (0.0007) +[2026-07-22 23:05:15,558][543983] Updated weights for policy 0, policy_version 23271 (0.0008) +[2026-07-22 23:05:15,900][543983] Updated weights for policy 0, policy_version 23283 (0.0006) +[2026-07-22 23:05:16,029][543696] Early stopping after 7 epochs (56 sgd steps), loss delta 0.0000001 +[2026-07-22 23:05:16,995][543983] Updated weights for policy 0, policy_version 23293 (0.0006) +[2026-07-22 23:05:17,287][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11927552. Throughput: 0: 12837.0. Samples: 11974144. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:05:17,287][543203] Avg episode reward: [(0, '723.647')] +[2026-07-22 23:05:17,313][543983] Updated weights for policy 0, policy_version 23304 (0.0006) +[2026-07-22 23:05:17,588][543983] Updated weights for policy 0, policy_version 23314 (0.0006) +[2026-07-22 23:05:17,875][543983] Updated weights for policy 0, policy_version 23324 (0.0006) +[2026-07-22 23:05:18,158][543983] Updated weights for policy 0, policy_version 23334 (0.0006) +[2026-07-22 23:05:18,443][543983] Updated weights for policy 0, policy_version 23344 (0.0006) +[2026-07-22 23:05:19,470][543983] Updated weights for policy 0, policy_version 23354 (0.0006) +[2026-07-22 23:05:19,801][543983] Updated weights for policy 0, policy_version 23366 (0.0006) +[2026-07-22 23:05:20,089][543983] Updated weights for policy 0, policy_version 23376 (0.0006) +[2026-07-22 23:05:20,375][543983] Updated weights for policy 0, policy_version 23386 (0.0006) +[2026-07-22 23:05:20,665][543983] Updated weights for policy 0, policy_version 23396 (0.0006) +[2026-07-22 23:05:20,949][543983] Updated weights for policy 0, policy_version 23406 (0.0006) +[2026-07-22 23:05:21,221][543983] Updated weights for policy 0, policy_version 23416 (0.0006) +[2026-07-22 23:05:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 11993088. Throughput: 0: 12842.7. Samples: 12009856. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:05:22,287][543983] Updated weights for policy 0, policy_version 23426 (0.0006) +[2026-07-22 23:05:22,287][543203] Avg episode reward: [(0, '766.117')] +[2026-07-22 23:05:22,598][543983] Updated weights for policy 0, policy_version 23437 (0.0006) +[2026-07-22 23:05:22,874][543983] Updated weights for policy 0, policy_version 23447 (0.0006) +[2026-07-22 23:05:23,185][543983] Updated weights for policy 0, policy_version 23458 (0.0006) +[2026-07-22 23:05:23,455][543983] Updated weights for policy 0, policy_version 23468 (0.0006) +[2026-07-22 23:05:23,762][543983] Updated weights for policy 0, policy_version 23478 (0.0007) +[2026-07-22 23:05:24,850][543983] Updated weights for policy 0, policy_version 23489 (0.0007) +[2026-07-22 23:05:25,136][543983] Updated weights for policy 0, policy_version 23499 (0.0007) +[2026-07-22 23:05:25,415][543983] Updated weights for policy 0, policy_version 23509 (0.0006) +[2026-07-22 23:05:25,712][543983] Updated weights for policy 0, policy_version 23520 (0.0006) +[2026-07-22 23:05:26,037][543983] Updated weights for policy 0, policy_version 23531 (0.0008) +[2026-07-22 23:05:26,316][543983] Updated weights for policy 0, policy_version 23541 (0.0006) +[2026-07-22 23:05:27,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 12058624. Throughput: 0: 12603.7. Samples: 12082176. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:05:27,287][543203] Avg episode reward: [(0, '773.624')] +[2026-07-22 23:05:27,370][543983] Updated weights for policy 0, policy_version 23552 (0.0006) +[2026-07-22 23:05:27,650][543983] Updated weights for policy 0, policy_version 23562 (0.0007) +[2026-07-22 23:05:27,948][543983] Updated weights for policy 0, policy_version 23572 (0.0007) +[2026-07-22 23:05:28,239][543983] Updated weights for policy 0, policy_version 23582 (0.0007) +[2026-07-22 23:05:28,530][543983] Updated weights for policy 0, policy_version 23592 (0.0006) +[2026-07-22 23:05:28,823][543983] Updated weights for policy 0, policy_version 23602 (0.0006) +[2026-07-22 23:05:29,825][543983] Updated weights for policy 0, policy_version 23612 (0.0007) +[2026-07-22 23:05:30,145][543983] Updated weights for policy 0, policy_version 23623 (0.0006) +[2026-07-22 23:05:30,433][543983] Updated weights for policy 0, policy_version 23633 (0.0006) +[2026-07-22 23:05:30,711][543983] Updated weights for policy 0, policy_version 23643 (0.0006) +[2026-07-22 23:05:31,018][543983] Updated weights for policy 0, policy_version 23654 (0.0006) +[2026-07-22 23:05:31,307][543983] Updated weights for policy 0, policy_version 23664 (0.0006) +[2026-07-22 23:05:32,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 12124160. Throughput: 0: 12637.9. Samples: 12156928. Policy #0 lag: (min: 36.0, avg: 52.5, max: 100.0) +[2026-07-22 23:05:32,287][543203] Avg episode reward: [(0, '715.737')] +[2026-07-22 23:05:32,375][543983] Updated weights for policy 0, policy_version 23674 (0.0006) +[2026-07-22 23:05:32,648][543983] Updated weights for policy 0, policy_version 23684 (0.0006) +[2026-07-22 23:05:32,967][543983] Updated weights for policy 0, policy_version 23695 (0.0006) +[2026-07-22 23:05:33,269][543983] Updated weights for policy 0, policy_version 23706 (0.0006) +[2026-07-22 23:05:33,560][543983] Updated weights for policy 0, policy_version 23716 (0.0006) +[2026-07-22 23:05:33,875][543983] Updated weights for policy 0, policy_version 23727 (0.0006) +[2026-07-22 23:05:34,930][543983] Updated weights for policy 0, policy_version 23737 (0.0006) +[2026-07-22 23:05:35,198][543983] Updated weights for policy 0, policy_version 23747 (0.0007) +[2026-07-22 23:05:35,511][543983] Updated weights for policy 0, policy_version 23758 (0.0006) +[2026-07-22 23:05:35,803][543983] Updated weights for policy 0, policy_version 23768 (0.0006) +[2026-07-22 23:05:36,132][543983] Updated weights for policy 0, policy_version 23779 (0.0007) +[2026-07-22 23:05:36,428][543983] Updated weights for policy 0, policy_version 23790 (0.0006) +[2026-07-22 23:05:36,703][543983] Updated weights for policy 0, policy_version 23800 (0.0006) +[2026-07-22 23:05:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 12189696. Throughput: 0: 12817.1. Samples: 12201472. Policy #0 lag: (min: 36.0, avg: 52.5, max: 100.0) +[2026-07-22 23:05:37,287][543203] Avg episode reward: [(0, '698.098')] +[2026-07-22 23:05:37,792][543983] Updated weights for policy 0, policy_version 23810 (0.0007) +[2026-07-22 23:05:38,083][543983] Updated weights for policy 0, policy_version 23820 (0.0007) +[2026-07-22 23:05:38,363][543983] Updated weights for policy 0, policy_version 23830 (0.0006) +[2026-07-22 23:05:38,639][543983] Updated weights for policy 0, policy_version 23840 (0.0006) +[2026-07-22 23:05:38,947][543983] Updated weights for policy 0, policy_version 23851 (0.0007) +[2026-07-22 23:05:39,239][543983] Updated weights for policy 0, policy_version 23861 (0.0006) +[2026-07-22 23:05:40,276][543983] Updated weights for policy 0, policy_version 23871 (0.0007) +[2026-07-22 23:05:40,551][543983] Updated weights for policy 0, policy_version 23881 (0.0008) +[2026-07-22 23:05:40,859][543983] Updated weights for policy 0, policy_version 23892 (0.0007) +[2026-07-22 23:05:41,154][543983] Updated weights for policy 0, policy_version 23902 (0.0006) +[2026-07-22 23:05:41,424][543983] Updated weights for policy 0, policy_version 23912 (0.0006) +[2026-07-22 23:05:41,710][543983] Updated weights for policy 0, policy_version 23922 (0.0006) +[2026-07-22 23:05:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 12255232. Throughput: 0: 12817.1. Samples: 12274944. Policy #0 lag: (min: 36.0, avg: 52.5, max: 100.0) +[2026-07-22 23:05:42,287][543203] Avg episode reward: [(0, '696.355')] +[2026-07-22 23:05:42,750][543983] Updated weights for policy 0, policy_version 23932 (0.0006) +[2026-07-22 23:05:43,039][543983] Updated weights for policy 0, policy_version 23942 (0.0006) +[2026-07-22 23:05:43,359][543983] Updated weights for policy 0, policy_version 23953 (0.0007) +[2026-07-22 23:05:43,629][543983] Updated weights for policy 0, policy_version 23963 (0.0007) +[2026-07-22 23:05:43,897][543983] Updated weights for policy 0, policy_version 23973 (0.0006) +[2026-07-22 23:05:44,190][543983] Updated weights for policy 0, policy_version 23983 (0.0007) +[2026-07-22 23:05:45,253][543983] Updated weights for policy 0, policy_version 23993 (0.0007) +[2026-07-22 23:05:45,543][543983] Updated weights for policy 0, policy_version 24003 (0.0006) +[2026-07-22 23:05:45,824][543983] Updated weights for policy 0, policy_version 24013 (0.0007) +[2026-07-22 23:05:46,094][543983] Updated weights for policy 0, policy_version 24023 (0.0007) +[2026-07-22 23:05:46,389][543983] Updated weights for policy 0, policy_version 24033 (0.0007) +[2026-07-22 23:05:46,678][543983] Updated weights for policy 0, policy_version 24043 (0.0007) +[2026-07-22 23:05:46,983][543983] Updated weights for policy 0, policy_version 24054 (0.0006) +[2026-07-22 23:05:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 12320768. Throughput: 0: 12592.4. Samples: 12347136. Policy #0 lag: (min: 63.0, avg: 78.7, max: 127.0) +[2026-07-22 23:05:47,287][543203] Avg episode reward: [(0, '710.486')] +[2026-07-22 23:05:48,081][543983] Updated weights for policy 0, policy_version 24065 (0.0007) +[2026-07-22 23:05:48,382][543983] Updated weights for policy 0, policy_version 24075 (0.0006) +[2026-07-22 23:05:48,649][543983] Updated weights for policy 0, policy_version 24085 (0.0007) +[2026-07-22 23:05:48,932][543983] Updated weights for policy 0, policy_version 24095 (0.0006) +[2026-07-22 23:05:49,227][543983] Updated weights for policy 0, policy_version 24105 (0.0006) +[2026-07-22 23:05:49,512][543983] Updated weights for policy 0, policy_version 24115 (0.0007) +[2026-07-22 23:05:50,551][543983] Updated weights for policy 0, policy_version 24126 (0.0006) +[2026-07-22 23:05:50,850][543983] Updated weights for policy 0, policy_version 24136 (0.0006) +[2026-07-22 23:05:51,117][543983] Updated weights for policy 0, policy_version 24146 (0.0007) +[2026-07-22 23:05:51,409][543983] Updated weights for policy 0, policy_version 24156 (0.0007) +[2026-07-22 23:05:51,694][543983] Updated weights for policy 0, policy_version 24166 (0.0006) +[2026-07-22 23:05:52,005][543983] Updated weights for policy 0, policy_version 24177 (0.0006) +[2026-07-22 23:05:52,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 12386304. Throughput: 0: 12626.5. Samples: 12384768. Policy #0 lag: (min: 63.0, avg: 78.7, max: 127.0) +[2026-07-22 23:05:52,287][543203] Avg episode reward: [(0, '708.865')] +[2026-07-22 23:05:53,057][543983] Updated weights for policy 0, policy_version 24187 (0.0006) +[2026-07-22 23:05:53,335][543983] Updated weights for policy 0, policy_version 24197 (0.0006) +[2026-07-22 23:05:53,627][543983] Updated weights for policy 0, policy_version 24207 (0.0006) +[2026-07-22 23:05:53,906][543983] Updated weights for policy 0, policy_version 24217 (0.0006) +[2026-07-22 23:05:54,207][543983] Updated weights for policy 0, policy_version 24228 (0.0006) +[2026-07-22 23:05:54,501][543983] Updated weights for policy 0, policy_version 24238 (0.0006) +[2026-07-22 23:05:54,777][543983] Updated weights for policy 0, policy_version 24248 (0.0006) +[2026-07-22 23:05:55,820][543983] Updated weights for policy 0, policy_version 24258 (0.0006) +[2026-07-22 23:05:56,110][543983] Updated weights for policy 0, policy_version 24268 (0.0007) +[2026-07-22 23:05:56,402][543983] Updated weights for policy 0, policy_version 24279 (0.0007) +[2026-07-22 23:05:56,711][543983] Updated weights for policy 0, policy_version 24289 (0.0006) +[2026-07-22 23:05:56,978][543983] Updated weights for policy 0, policy_version 24299 (0.0006) +[2026-07-22 23:05:57,271][543983] Updated weights for policy 0, policy_version 24309 (0.0006) +[2026-07-22 23:05:57,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 12419072. Throughput: 0: 12834.1. Samples: 12466816. Policy #0 lag: (min: 63.0, avg: 78.7, max: 127.0) +[2026-07-22 23:05:57,287][543203] Avg episode reward: [(0, '722.801')] +[2026-07-22 23:05:58,319][543983] Updated weights for policy 0, policy_version 24319 (0.0007) +[2026-07-22 23:05:58,623][543983] Updated weights for policy 0, policy_version 24330 (0.0006) +[2026-07-22 23:05:58,921][543983] Updated weights for policy 0, policy_version 24341 (0.0006) +[2026-07-22 23:05:59,222][543983] Updated weights for policy 0, policy_version 24351 (0.0006) +[2026-07-22 23:05:59,523][543983] Updated weights for policy 0, policy_version 24362 (0.0007) +[2026-07-22 23:05:59,824][543983] Updated weights for policy 0, policy_version 24372 (0.0006) +[2026-07-22 23:06:00,875][543983] Updated weights for policy 0, policy_version 24382 (0.0006) +[2026-07-22 23:06:01,142][543983] Updated weights for policy 0, policy_version 24392 (0.0006) +[2026-07-22 23:06:01,443][543983] Updated weights for policy 0, policy_version 24402 (0.0006) +[2026-07-22 23:06:01,714][543983] Updated weights for policy 0, policy_version 24412 (0.0006) +[2026-07-22 23:06:02,039][543983] Updated weights for policy 0, policy_version 24423 (0.0006) +[2026-07-22 23:06:02,286][543203] Fps is (10 sec: 9830.5, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 12484608. Throughput: 0: 12558.3. Samples: 12539264. Policy #0 lag: (min: 63.0, avg: 78.7, max: 127.0) +[2026-07-22 23:06:02,287][543203] Avg episode reward: [(0, '791.876')] +[2026-07-22 23:06:02,343][543983] Updated weights for policy 0, policy_version 24434 (0.0007) +[2026-07-22 23:06:03,389][543983] Updated weights for policy 0, policy_version 24444 (0.0006) +[2026-07-22 23:06:03,664][543983] Updated weights for policy 0, policy_version 24454 (0.0006) +[2026-07-22 23:06:03,977][543983] Updated weights for policy 0, policy_version 24465 (0.0006) +[2026-07-22 23:06:04,271][543983] Updated weights for policy 0, policy_version 24475 (0.0006) +[2026-07-22 23:06:04,548][543983] Updated weights for policy 0, policy_version 24485 (0.0007) +[2026-07-22 23:06:04,852][543983] Updated weights for policy 0, policy_version 24495 (0.0007) +[2026-07-22 23:06:05,902][543983] Updated weights for policy 0, policy_version 24505 (0.0006) +[2026-07-22 23:06:06,219][543983] Updated weights for policy 0, policy_version 24516 (0.0007) +[2026-07-22 23:06:06,502][543983] Updated weights for policy 0, policy_version 24526 (0.0007) +[2026-07-22 23:06:06,781][543983] Updated weights for policy 0, policy_version 24536 (0.0006) +[2026-07-22 23:06:07,082][543983] Updated weights for policy 0, policy_version 24546 (0.0006) +[2026-07-22 23:06:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 12550144. Throughput: 0: 12566.7. Samples: 12575360. Policy #0 lag: (min: 62.0, avg: 78.8, max: 126.0) +[2026-07-22 23:06:07,287][543203] Avg episode reward: [(0, '800.072')] +[2026-07-22 23:06:07,355][543983] Updated weights for policy 0, policy_version 24556 (0.0006) +[2026-07-22 23:06:07,675][543983] Updated weights for policy 0, policy_version 24567 (0.0007) +[2026-07-22 23:06:07,689][543696] Saving new best policy, reward=800.072! +[2026-07-22 23:06:08,682][543983] Updated weights for policy 0, policy_version 24577 (0.0008) +[2026-07-22 23:06:08,986][543983] Updated weights for policy 0, policy_version 24588 (0.0006) +[2026-07-22 23:06:09,318][543983] Updated weights for policy 0, policy_version 24599 (0.0006) +[2026-07-22 23:06:09,610][543983] Updated weights for policy 0, policy_version 24609 (0.0006) +[2026-07-22 23:06:09,874][543983] Updated weights for policy 0, policy_version 24619 (0.0006) +[2026-07-22 23:06:10,156][543983] Updated weights for policy 0, policy_version 24629 (0.0007) +[2026-07-22 23:06:11,193][543983] Updated weights for policy 0, policy_version 24639 (0.0006) +[2026-07-22 23:06:11,490][543983] Updated weights for policy 0, policy_version 24649 (0.0008) +[2026-07-22 23:06:11,792][543983] Updated weights for policy 0, policy_version 24660 (0.0007) +[2026-07-22 23:06:12,078][543983] Updated weights for policy 0, policy_version 24670 (0.0007) +[2026-07-22 23:06:12,286][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 12615680. Throughput: 0: 12760.2. Samples: 12656384. Policy #0 lag: (min: 62.0, avg: 78.8, max: 126.0) +[2026-07-22 23:06:12,287][543203] Avg episode reward: [(0, '847.373')] +[2026-07-22 23:06:12,356][543983] Updated weights for policy 0, policy_version 24680 (0.0006) +[2026-07-22 23:06:12,656][543983] Updated weights for policy 0, policy_version 24690 (0.0006) +[2026-07-22 23:06:12,824][543696] Saving new best policy, reward=847.373! +[2026-07-22 23:06:13,701][543983] Updated weights for policy 0, policy_version 24700 (0.0007) +[2026-07-22 23:06:13,976][543983] Updated weights for policy 0, policy_version 24710 (0.0006) +[2026-07-22 23:06:14,272][543983] Updated weights for policy 0, policy_version 24720 (0.0006) +[2026-07-22 23:06:14,555][543983] Updated weights for policy 0, policy_version 24730 (0.0006) +[2026-07-22 23:06:14,841][543983] Updated weights for policy 0, policy_version 24740 (0.0006) +[2026-07-22 23:06:15,234][543983] Updated weights for policy 0, policy_version 24754 (0.0006) +[2026-07-22 23:06:16,251][543983] Updated weights for policy 0, policy_version 24764 (0.0006) +[2026-07-22 23:06:16,554][543983] Updated weights for policy 0, policy_version 24774 (0.0006) +[2026-07-22 23:06:16,836][543983] Updated weights for policy 0, policy_version 24784 (0.0008) +[2026-07-22 23:06:17,118][543983] Updated weights for policy 0, policy_version 24794 (0.0006) +[2026-07-22 23:06:17,287][543203] Fps is (10 sec: 13107.0, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 12681216. Throughput: 0: 12763.0. Samples: 12731264. Policy #0 lag: (min: 62.0, avg: 78.8, max: 126.0) +[2026-07-22 23:06:17,287][543203] Avg episode reward: [(0, '847.373')] +[2026-07-22 23:06:17,456][543983] Updated weights for policy 0, policy_version 24806 (0.0006) +[2026-07-22 23:06:17,736][543983] Updated weights for policy 0, policy_version 24816 (0.0006) +[2026-07-22 23:06:18,779][543983] Updated weights for policy 0, policy_version 24826 (0.0006) +[2026-07-22 23:06:19,071][543983] Updated weights for policy 0, policy_version 24836 (0.0006) +[2026-07-22 23:06:19,354][543983] Updated weights for policy 0, policy_version 24846 (0.0007) +[2026-07-22 23:06:19,643][543983] Updated weights for policy 0, policy_version 24856 (0.0006) +[2026-07-22 23:06:19,907][543983] Updated weights for policy 0, policy_version 24866 (0.0006) +[2026-07-22 23:06:20,196][543983] Updated weights for policy 0, policy_version 24876 (0.0006) +[2026-07-22 23:06:20,473][543983] Updated weights for policy 0, policy_version 24886 (0.0006) +[2026-07-22 23:06:21,543][543983] Updated weights for policy 0, policy_version 24897 (0.0007) +[2026-07-22 23:06:21,820][543983] Updated weights for policy 0, policy_version 24907 (0.0006) +[2026-07-22 23:06:22,109][543983] Updated weights for policy 0, policy_version 24917 (0.0007) +[2026-07-22 23:06:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 12746752. Throughput: 0: 12572.4. Samples: 12767232. Policy #0 lag: (min: 62.0, avg: 78.8, max: 126.0) +[2026-07-22 23:06:22,287][543203] Avg episode reward: [(0, '860.283')] +[2026-07-22 23:06:22,397][543983] Updated weights for policy 0, policy_version 24927 (0.0006) +[2026-07-22 23:06:22,700][543983] Updated weights for policy 0, policy_version 24938 (0.0007) +[2026-07-22 23:06:22,987][543983] Updated weights for policy 0, policy_version 24948 (0.0006) +[2026-07-22 23:06:23,096][543696] Saving new best policy, reward=860.283! +[2026-07-22 23:06:24,054][543983] Updated weights for policy 0, policy_version 24958 (0.0006) +[2026-07-22 23:06:24,338][543983] Updated weights for policy 0, policy_version 24968 (0.0006) +[2026-07-22 23:06:24,623][543983] Updated weights for policy 0, policy_version 24978 (0.0006) +[2026-07-22 23:06:24,932][543983] Updated weights for policy 0, policy_version 24989 (0.0006) +[2026-07-22 23:06:25,210][543983] Updated weights for policy 0, policy_version 24999 (0.0006) +[2026-07-22 23:06:25,490][543983] Updated weights for policy 0, policy_version 25009 (0.0007) +[2026-07-22 23:06:26,558][543983] Updated weights for policy 0, policy_version 25020 (0.0006) +[2026-07-22 23:06:26,851][543983] Updated weights for policy 0, policy_version 25030 (0.0006) +[2026-07-22 23:06:27,147][543983] Updated weights for policy 0, policy_version 25041 (0.0007) +[2026-07-22 23:06:27,286][543203] Fps is (10 sec: 13107.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 12812288. Throughput: 0: 12558.2. Samples: 12840064. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:06:27,287][543203] Avg episode reward: [(0, '880.010')] +[2026-07-22 23:06:27,443][543983] Updated weights for policy 0, policy_version 25051 (0.0007) +[2026-07-22 23:06:27,723][543983] Updated weights for policy 0, policy_version 25061 (0.0006) +[2026-07-22 23:06:27,997][543983] Updated weights for policy 0, policy_version 25071 (0.0007) +[2026-07-22 23:06:28,250][543696] Saving new best policy, reward=880.010! +[2026-07-22 23:06:29,043][543983] Updated weights for policy 0, policy_version 25081 (0.0006) +[2026-07-22 23:06:29,404][543983] Updated weights for policy 0, policy_version 25094 (0.0007) +[2026-07-22 23:06:29,714][543983] Updated weights for policy 0, policy_version 25105 (0.0006) +[2026-07-22 23:06:30,006][543983] Updated weights for policy 0, policy_version 25115 (0.0007) +[2026-07-22 23:06:30,292][543983] Updated weights for policy 0, policy_version 25125 (0.0008) +[2026-07-22 23:06:30,570][543983] Updated weights for policy 0, policy_version 25135 (0.0007) +[2026-07-22 23:06:31,611][543983] Updated weights for policy 0, policy_version 25145 (0.0007) +[2026-07-22 23:06:31,895][543983] Updated weights for policy 0, policy_version 25155 (0.0006) +[2026-07-22 23:06:32,200][543983] Updated weights for policy 0, policy_version 25166 (0.0006) +[2026-07-22 23:06:32,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 12877824. Throughput: 0: 12811.3. Samples: 12923648. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:06:32,288][543203] Avg episode reward: [(0, '871.983')] +[2026-07-22 23:06:32,508][543983] Updated weights for policy 0, policy_version 25177 (0.0007) +[2026-07-22 23:06:32,805][543983] Updated weights for policy 0, policy_version 25187 (0.0007) +[2026-07-22 23:06:33,080][543983] Updated weights for policy 0, policy_version 25197 (0.0007) +[2026-07-22 23:06:33,375][543983] Updated weights for policy 0, policy_version 25207 (0.0006) +[2026-07-22 23:06:34,439][543983] Updated weights for policy 0, policy_version 25218 (0.0006) +[2026-07-22 23:06:34,785][543983] Updated weights for policy 0, policy_version 25230 (0.0006) +[2026-07-22 23:06:35,082][543983] Updated weights for policy 0, policy_version 25240 (0.0008) +[2026-07-22 23:06:35,367][543983] Updated weights for policy 0, policy_version 25250 (0.0006) +[2026-07-22 23:06:35,673][543983] Updated weights for policy 0, policy_version 25261 (0.0006) +[2026-07-22 23:06:35,976][543983] Updated weights for policy 0, policy_version 25271 (0.0006) +[2026-07-22 23:06:36,995][543983] Updated weights for policy 0, policy_version 25281 (0.0006) +[2026-07-22 23:06:37,283][543983] Updated weights for policy 0, policy_version 25291 (0.0006) +[2026-07-22 23:06:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 12943360. Throughput: 0: 12777.3. Samples: 12959744. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:06:37,287][543203] Avg episode reward: [(0, '875.161')] +[2026-07-22 23:06:37,581][543983] Updated weights for policy 0, policy_version 25301 (0.0007) +[2026-07-22 23:06:37,857][543983] Updated weights for policy 0, policy_version 25311 (0.0007) +[2026-07-22 23:06:38,134][543983] Updated weights for policy 0, policy_version 25321 (0.0008) +[2026-07-22 23:06:38,435][543983] Updated weights for policy 0, policy_version 25331 (0.0007) +[2026-07-22 23:06:39,503][543983] Updated weights for policy 0, policy_version 25341 (0.0009) +[2026-07-22 23:06:39,833][543983] Updated weights for policy 0, policy_version 25353 (0.0006) +[2026-07-22 23:06:40,139][543983] Updated weights for policy 0, policy_version 25364 (0.0006) +[2026-07-22 23:06:40,432][543983] Updated weights for policy 0, policy_version 25374 (0.0007) +[2026-07-22 23:06:40,727][543983] Updated weights for policy 0, policy_version 25384 (0.0008) +[2026-07-22 23:06:41,030][543983] Updated weights for policy 0, policy_version 25395 (0.0006) +[2026-07-22 23:06:42,036][543983] Updated weights for policy 0, policy_version 25405 (0.0007) +[2026-07-22 23:06:42,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 13008896. Throughput: 0: 12546.8. Samples: 13031424. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:06:42,287][543203] Avg episode reward: [(0, '863.363')] +[2026-07-22 23:06:42,326][543983] Updated weights for policy 0, policy_version 25415 (0.0007) +[2026-07-22 23:06:42,630][543983] Updated weights for policy 0, policy_version 25425 (0.0007) +[2026-07-22 23:06:42,918][543983] Updated weights for policy 0, policy_version 25435 (0.0008) +[2026-07-22 23:06:43,215][543983] Updated weights for policy 0, policy_version 25446 (0.0008) +[2026-07-22 23:06:43,507][543983] Updated weights for policy 0, policy_version 25456 (0.0008) +[2026-07-22 23:06:44,570][543983] Updated weights for policy 0, policy_version 25466 (0.0008) +[2026-07-22 23:06:44,850][543983] Updated weights for policy 0, policy_version 25476 (0.0008) +[2026-07-22 23:06:45,180][543983] Updated weights for policy 0, policy_version 25487 (0.0008) +[2026-07-22 23:06:45,493][543983] Updated weights for policy 0, policy_version 25498 (0.0006) +[2026-07-22 23:06:45,805][543983] Updated weights for policy 0, policy_version 25509 (0.0006) +[2026-07-22 23:06:46,086][543983] Updated weights for policy 0, policy_version 25519 (0.0006) +[2026-07-22 23:06:47,091][543983] Updated weights for policy 0, policy_version 25529 (0.0007) +[2026-07-22 23:06:47,287][543203] Fps is (10 sec: 13106.9, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 13074432. Throughput: 0: 12683.3. Samples: 13110016. Policy #0 lag: (min: 13.0, avg: 29.7, max: 77.0) +[2026-07-22 23:06:47,287][543203] Avg episode reward: [(0, '881.620')] +[2026-07-22 23:06:47,429][543983] Updated weights for policy 0, policy_version 25541 (0.0007) +[2026-07-22 23:06:47,729][543983] Updated weights for policy 0, policy_version 25551 (0.0007) +[2026-07-22 23:06:48,030][543983] Updated weights for policy 0, policy_version 25562 (0.0007) +[2026-07-22 23:06:48,330][543983] Updated weights for policy 0, policy_version 25572 (0.0007) +[2026-07-22 23:06:48,607][543983] Updated weights for policy 0, policy_version 25582 (0.0006) +[2026-07-22 23:06:48,881][543696] Saving new best policy, reward=881.620! +[2026-07-22 23:06:48,884][543983] Updated weights for policy 0, policy_version 25592 (0.0006) +[2026-07-22 23:06:49,926][543983] Updated weights for policy 0, policy_version 25602 (0.0008) +[2026-07-22 23:06:50,236][543983] Updated weights for policy 0, policy_version 25613 (0.0008) +[2026-07-22 23:06:50,560][543983] Updated weights for policy 0, policy_version 25624 (0.0009) +[2026-07-22 23:06:50,854][543983] Updated weights for policy 0, policy_version 25634 (0.0009) +[2026-07-22 23:06:51,131][543983] Updated weights for policy 0, policy_version 25644 (0.0006) +[2026-07-22 23:06:51,455][543983] Updated weights for policy 0, policy_version 25655 (0.0008) +[2026-07-22 23:06:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 13139968. Throughput: 0: 12771.6. Samples: 13150080. Policy #0 lag: (min: 13.0, avg: 29.7, max: 77.0) +[2026-07-22 23:06:52,287][543203] Avg episode reward: [(0, '905.575')] +[2026-07-22 23:06:52,503][543983] Updated weights for policy 0, policy_version 25665 (0.0008) +[2026-07-22 23:06:52,798][543983] Updated weights for policy 0, policy_version 25675 (0.0006) +[2026-07-22 23:06:53,104][543983] Updated weights for policy 0, policy_version 25686 (0.0006) +[2026-07-22 23:06:53,383][543983] Updated weights for policy 0, policy_version 25696 (0.0006) +[2026-07-22 23:06:53,673][543983] Updated weights for policy 0, policy_version 25706 (0.0008) +[2026-07-22 23:06:53,990][543983] Updated weights for policy 0, policy_version 25717 (0.0006) +[2026-07-22 23:06:54,059][543696] Saving new best policy, reward=905.575! +[2026-07-22 23:06:55,024][543983] Updated weights for policy 0, policy_version 25727 (0.0006) +[2026-07-22 23:06:55,311][543983] Updated weights for policy 0, policy_version 25737 (0.0006) +[2026-07-22 23:06:55,584][543983] Updated weights for policy 0, policy_version 25747 (0.0006) +[2026-07-22 23:06:55,865][543983] Updated weights for policy 0, policy_version 25757 (0.0007) +[2026-07-22 23:06:56,149][543983] Updated weights for policy 0, policy_version 25767 (0.0007) +[2026-07-22 23:06:56,441][543983] Updated weights for policy 0, policy_version 25777 (0.0007) +[2026-07-22 23:06:57,286][543203] Fps is (10 sec: 13107.5, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 13205504. Throughput: 0: 12581.0. Samples: 13222528. Policy #0 lag: (min: 13.0, avg: 29.7, max: 77.0) +[2026-07-22 23:06:57,287][543203] Avg episode reward: [(0, '963.236')] +[2026-07-22 23:06:57,493][543983] Updated weights for policy 0, policy_version 25787 (0.0007) +[2026-07-22 23:06:57,835][543983] Updated weights for policy 0, policy_version 25799 (0.0006) +[2026-07-22 23:06:58,139][543983] Updated weights for policy 0, policy_version 25810 (0.0006) +[2026-07-22 23:06:58,478][543983] Updated weights for policy 0, policy_version 25822 (0.0007) +[2026-07-22 23:06:58,767][543983] Updated weights for policy 0, policy_version 25832 (0.0007) +[2026-07-22 23:06:59,038][543983] Updated weights for policy 0, policy_version 25842 (0.0006) +[2026-07-22 23:06:59,201][543696] Saving new best policy, reward=963.236! +[2026-07-22 23:07:00,063][543983] Updated weights for policy 0, policy_version 25852 (0.0006) +[2026-07-22 23:07:00,354][543983] Updated weights for policy 0, policy_version 25862 (0.0006) +[2026-07-22 23:07:00,628][543983] Updated weights for policy 0, policy_version 25872 (0.0006) +[2026-07-22 23:07:00,911][543983] Updated weights for policy 0, policy_version 25882 (0.0006) +[2026-07-22 23:07:01,186][543983] Updated weights for policy 0, policy_version 25892 (0.0006) +[2026-07-22 23:07:01,469][543983] Updated weights for policy 0, policy_version 25902 (0.0006) +[2026-07-22 23:07:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 13271040. Throughput: 0: 12504.2. Samples: 13293952. Policy #0 lag: (min: 13.0, avg: 29.7, max: 77.0) +[2026-07-22 23:07:02,287][543203] Avg episode reward: [(0, '973.578')] +[2026-07-22 23:07:02,293][543696] Saving new best policy, reward=973.578! +[2026-07-22 23:07:02,545][543983] Updated weights for policy 0, policy_version 25913 (0.0008) +[2026-07-22 23:07:02,876][543983] Updated weights for policy 0, policy_version 25924 (0.0006) +[2026-07-22 23:07:03,172][543983] Updated weights for policy 0, policy_version 25934 (0.0007) +[2026-07-22 23:07:03,450][543983] Updated weights for policy 0, policy_version 25944 (0.0006) +[2026-07-22 23:07:03,757][543983] Updated weights for policy 0, policy_version 25955 (0.0006) +[2026-07-22 23:07:04,067][543983] Updated weights for policy 0, policy_version 25966 (0.0006) +[2026-07-22 23:07:05,098][543983] Updated weights for policy 0, policy_version 25977 (0.0007) +[2026-07-22 23:07:05,396][543983] Updated weights for policy 0, policy_version 25987 (0.0006) +[2026-07-22 23:07:05,667][543983] Updated weights for policy 0, policy_version 25997 (0.0006) +[2026-07-22 23:07:06,011][543983] Updated weights for policy 0, policy_version 26009 (0.0006) +[2026-07-22 23:07:06,296][543983] Updated weights for policy 0, policy_version 26019 (0.0006) +[2026-07-22 23:07:06,600][543983] Updated weights for policy 0, policy_version 26030 (0.0006) +[2026-07-22 23:07:06,880][543983] Updated weights for policy 0, policy_version 26040 (0.0006) +[2026-07-22 23:07:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 13336576. Throughput: 0: 12669.2. Samples: 13337344. Policy #0 lag: (min: 11.0, avg: 58.6, max: 75.0) +[2026-07-22 23:07:07,287][543203] Avg episode reward: [(0, '1034.106')] +[2026-07-22 23:07:07,306][543696] Saving new best policy, reward=1034.106! +[2026-07-22 23:07:07,938][543983] Updated weights for policy 0, policy_version 26050 (0.0007) +[2026-07-22 23:07:08,224][543983] Updated weights for policy 0, policy_version 26060 (0.0007) +[2026-07-22 23:07:08,518][543983] Updated weights for policy 0, policy_version 26070 (0.0006) +[2026-07-22 23:07:08,787][543983] Updated weights for policy 0, policy_version 26080 (0.0006) +[2026-07-22 23:07:09,108][543983] Updated weights for policy 0, policy_version 26091 (0.0006) +[2026-07-22 23:07:09,405][543983] Updated weights for policy 0, policy_version 26102 (0.0006) +[2026-07-22 23:07:10,452][543983] Updated weights for policy 0, policy_version 26112 (0.0006) +[2026-07-22 23:07:10,735][543983] Updated weights for policy 0, policy_version 26122 (0.0006) +[2026-07-22 23:07:11,002][543983] Updated weights for policy 0, policy_version 26132 (0.0006) +[2026-07-22 23:07:11,324][543983] Updated weights for policy 0, policy_version 26143 (0.0007) +[2026-07-22 23:07:11,643][543983] Updated weights for policy 0, policy_version 26154 (0.0007) +[2026-07-22 23:07:11,927][543983] Updated weights for policy 0, policy_version 26164 (0.0006) +[2026-07-22 23:07:12,286][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 13402112. Throughput: 0: 12754.5. Samples: 13414016. Policy #0 lag: (min: 11.0, avg: 58.6, max: 75.0) +[2026-07-22 23:07:12,287][543203] Avg episode reward: [(0, '1080.038')] +[2026-07-22 23:07:12,293][543696] Saving new best policy, reward=1080.038! +[2026-07-22 23:07:12,977][543983] Updated weights for policy 0, policy_version 26175 (0.0007) +[2026-07-22 23:07:13,261][543983] Updated weights for policy 0, policy_version 26185 (0.0006) +[2026-07-22 23:07:13,552][543983] Updated weights for policy 0, policy_version 26195 (0.0007) +[2026-07-22 23:07:13,844][543983] Updated weights for policy 0, policy_version 26205 (0.0006) +[2026-07-22 23:07:14,152][543983] Updated weights for policy 0, policy_version 26216 (0.0007) +[2026-07-22 23:07:14,436][543983] Updated weights for policy 0, policy_version 26226 (0.0006) +[2026-07-22 23:07:15,470][543983] Updated weights for policy 0, policy_version 26236 (0.0006) +[2026-07-22 23:07:15,756][543983] Updated weights for policy 0, policy_version 26246 (0.0006) +[2026-07-22 23:07:16,041][543983] Updated weights for policy 0, policy_version 26256 (0.0007) +[2026-07-22 23:07:16,317][543983] Updated weights for policy 0, policy_version 26266 (0.0007) +[2026-07-22 23:07:16,602][543983] Updated weights for policy 0, policy_version 26276 (0.0006) +[2026-07-22 23:07:16,896][543983] Updated weights for policy 0, policy_version 26286 (0.0006) +[2026-07-22 23:07:17,177][543983] Updated weights for policy 0, policy_version 26296 (0.0007) +[2026-07-22 23:07:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 13467648. Throughput: 0: 12501.4. Samples: 13486208. Policy #0 lag: (min: 11.0, avg: 58.6, max: 75.0) +[2026-07-22 23:07:17,287][543203] Avg episode reward: [(0, '1072.100')] +[2026-07-22 23:07:18,237][543983] Updated weights for policy 0, policy_version 26307 (0.0006) +[2026-07-22 23:07:18,539][543983] Updated weights for policy 0, policy_version 26318 (0.0006) +[2026-07-22 23:07:18,863][543983] Updated weights for policy 0, policy_version 26329 (0.0007) +[2026-07-22 23:07:19,136][543983] Updated weights for policy 0, policy_version 26339 (0.0007) +[2026-07-22 23:07:19,424][543983] Updated weights for policy 0, policy_version 26349 (0.0006) +[2026-07-22 23:07:19,710][543983] Updated weights for policy 0, policy_version 26359 (0.0006) +[2026-07-22 23:07:20,754][543983] Updated weights for policy 0, policy_version 26369 (0.0008) +[2026-07-22 23:07:21,039][543983] Updated weights for policy 0, policy_version 26379 (0.0007) +[2026-07-22 23:07:21,319][543983] Updated weights for policy 0, policy_version 26389 (0.0006) +[2026-07-22 23:07:21,613][543983] Updated weights for policy 0, policy_version 26399 (0.0008) +[2026-07-22 23:07:21,891][543983] Updated weights for policy 0, policy_version 26409 (0.0007) +[2026-07-22 23:07:22,163][543983] Updated weights for policy 0, policy_version 26419 (0.0007) +[2026-07-22 23:07:22,287][543203] Fps is (10 sec: 9830.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 13500416. Throughput: 0: 12489.9. Samples: 13521792. Policy #0 lag: (min: 11.0, avg: 58.6, max: 75.0) +[2026-07-22 23:07:22,287][543203] Avg episode reward: [(0, '1107.184')] +[2026-07-22 23:07:22,323][543696] Saving new best policy, reward=1107.184! +[2026-07-22 23:07:23,313][543983] Updated weights for policy 0, policy_version 26431 (0.0006) +[2026-07-22 23:07:23,596][543983] Updated weights for policy 0, policy_version 26441 (0.0006) +[2026-07-22 23:07:23,905][543983] Updated weights for policy 0, policy_version 26452 (0.0007) +[2026-07-22 23:07:24,190][543983] Updated weights for policy 0, policy_version 26462 (0.0007) +[2026-07-22 23:07:24,480][543983] Updated weights for policy 0, policy_version 26472 (0.0006) +[2026-07-22 23:07:24,784][543983] Updated weights for policy 0, policy_version 26482 (0.0006) +[2026-07-22 23:07:25,815][543983] Updated weights for policy 0, policy_version 26493 (0.0006) +[2026-07-22 23:07:26,126][543983] Updated weights for policy 0, policy_version 26504 (0.0006) +[2026-07-22 23:07:26,399][543983] Updated weights for policy 0, policy_version 26514 (0.0006) +[2026-07-22 23:07:26,678][543983] Updated weights for policy 0, policy_version 26524 (0.0006) +[2026-07-22 23:07:26,960][543983] Updated weights for policy 0, policy_version 26534 (0.0006) +[2026-07-22 23:07:27,240][543983] Updated weights for policy 0, policy_version 26544 (0.0007) +[2026-07-22 23:07:27,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 13565952. Throughput: 0: 12777.2. Samples: 13606400. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:07:27,287][543203] Avg episode reward: [(0, '1136.849')] +[2026-07-22 23:07:27,457][543696] Saving new best policy, reward=1136.849! +[2026-07-22 23:07:28,345][543983] Updated weights for policy 0, policy_version 26555 (0.0007) +[2026-07-22 23:07:28,636][543983] Updated weights for policy 0, policy_version 26565 (0.0006) +[2026-07-22 23:07:28,919][543983] Updated weights for policy 0, policy_version 26575 (0.0007) +[2026-07-22 23:07:29,202][543983] Updated weights for policy 0, policy_version 26585 (0.0006) +[2026-07-22 23:07:29,496][543983] Updated weights for policy 0, policy_version 26595 (0.0006) +[2026-07-22 23:07:29,778][543983] Updated weights for policy 0, policy_version 26605 (0.0006) +[2026-07-22 23:07:30,052][543983] Updated weights for policy 0, policy_version 26615 (0.0006) +[2026-07-22 23:07:31,089][543983] Updated weights for policy 0, policy_version 26625 (0.0007) +[2026-07-22 23:07:31,366][543983] Updated weights for policy 0, policy_version 26635 (0.0006) +[2026-07-22 23:07:31,634][543983] Updated weights for policy 0, policy_version 26645 (0.0006) +[2026-07-22 23:07:31,930][543983] Updated weights for policy 0, policy_version 26655 (0.0006) +[2026-07-22 23:07:32,225][543983] Updated weights for policy 0, policy_version 26665 (0.0006) +[2026-07-22 23:07:32,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 13631488. Throughput: 0: 12635.1. Samples: 13678592. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:07:32,287][543203] Avg episode reward: [(0, '1155.559')] +[2026-07-22 23:07:32,502][543983] Updated weights for policy 0, policy_version 26675 (0.0006) +[2026-07-22 23:07:32,635][543696] Saving new best policy, reward=1155.559! +[2026-07-22 23:07:33,587][543983] Updated weights for policy 0, policy_version 26686 (0.0006) +[2026-07-22 23:07:33,870][543983] Updated weights for policy 0, policy_version 26696 (0.0006) +[2026-07-22 23:07:34,152][543983] Updated weights for policy 0, policy_version 26706 (0.0006) +[2026-07-22 23:07:34,434][543983] Updated weights for policy 0, policy_version 26716 (0.0006) +[2026-07-22 23:07:34,764][543983] Updated weights for policy 0, policy_version 26728 (0.0006) +[2026-07-22 23:07:35,116][543983] Updated weights for policy 0, policy_version 26740 (0.0006) +[2026-07-22 23:07:36,188][543983] Updated weights for policy 0, policy_version 26751 (0.0007) +[2026-07-22 23:07:36,510][543983] Updated weights for policy 0, policy_version 26762 (0.0006) +[2026-07-22 23:07:36,823][543983] Updated weights for policy 0, policy_version 26773 (0.0006) +[2026-07-22 23:07:37,163][543983] Updated weights for policy 0, policy_version 26785 (0.0006) +[2026-07-22 23:07:37,287][543203] Fps is (10 sec: 13107.0, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 13697024. Throughput: 0: 12555.3. Samples: 13715072. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:07:37,287][543203] Avg episode reward: [(0, '1124.142')] +[2026-07-22 23:07:37,447][543983] Updated weights for policy 0, policy_version 26795 (0.0006) +[2026-07-22 23:07:37,722][543983] Updated weights for policy 0, policy_version 26805 (0.0006) +[2026-07-22 23:07:38,725][543983] Updated weights for policy 0, policy_version 26815 (0.0006) +[2026-07-22 23:07:39,015][543983] Updated weights for policy 0, policy_version 26825 (0.0007) +[2026-07-22 23:07:39,321][543983] Updated weights for policy 0, policy_version 26836 (0.0006) +[2026-07-22 23:07:39,605][543983] Updated weights for policy 0, policy_version 26846 (0.0006) +[2026-07-22 23:07:39,907][543983] Updated weights for policy 0, policy_version 26857 (0.0006) +[2026-07-22 23:07:40,200][543983] Updated weights for policy 0, policy_version 26867 (0.0007) +[2026-07-22 23:07:41,307][543983] Updated weights for policy 0, policy_version 26879 (0.0006) +[2026-07-22 23:07:41,609][543983] Updated weights for policy 0, policy_version 26890 (0.0006) +[2026-07-22 23:07:41,891][543983] Updated weights for policy 0, policy_version 26900 (0.0006) +[2026-07-22 23:07:42,181][543983] Updated weights for policy 0, policy_version 26910 (0.0006) +[2026-07-22 23:07:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 13762560. Throughput: 0: 12697.6. Samples: 13793920. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:07:42,287][543203] Avg episode reward: [(0, '1092.962')] +[2026-07-22 23:07:42,492][543983] Updated weights for policy 0, policy_version 26921 (0.0006) +[2026-07-22 23:07:42,767][543983] Updated weights for policy 0, policy_version 26931 (0.0006) +[2026-07-22 23:07:43,817][543983] Updated weights for policy 0, policy_version 26941 (0.0006) +[2026-07-22 23:07:44,144][543983] Updated weights for policy 0, policy_version 26952 (0.0008) +[2026-07-22 23:07:44,453][543983] Updated weights for policy 0, policy_version 26963 (0.0006) +[2026-07-22 23:07:44,743][543983] Updated weights for policy 0, policy_version 26973 (0.0006) +[2026-07-22 23:07:45,045][543983] Updated weights for policy 0, policy_version 26984 (0.0006) +[2026-07-22 23:07:45,372][543983] Updated weights for policy 0, policy_version 26995 (0.0006) +[2026-07-22 23:07:46,399][543983] Updated weights for policy 0, policy_version 27005 (0.0006) +[2026-07-22 23:07:46,679][543983] Updated weights for policy 0, policy_version 27015 (0.0006) +[2026-07-22 23:07:46,972][543983] Updated weights for policy 0, policy_version 27025 (0.0006) +[2026-07-22 23:07:47,254][543983] Updated weights for policy 0, policy_version 27035 (0.0006) +[2026-07-22 23:07:47,286][543203] Fps is (10 sec: 13107.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 13828096. Throughput: 0: 12825.6. Samples: 13871104. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:07:47,288][543203] Avg episode reward: [(0, '1097.337')] +[2026-07-22 23:07:47,575][543983] Updated weights for policy 0, policy_version 27046 (0.0007) +[2026-07-22 23:07:47,882][543983] Updated weights for policy 0, policy_version 27057 (0.0006) +[2026-07-22 23:07:48,946][543983] Updated weights for policy 0, policy_version 27067 (0.0007) +[2026-07-22 23:07:49,230][543983] Updated weights for policy 0, policy_version 27077 (0.0006) +[2026-07-22 23:07:49,529][543983] Updated weights for policy 0, policy_version 27088 (0.0006) +[2026-07-22 23:07:49,822][543983] Updated weights for policy 0, policy_version 27098 (0.0007) +[2026-07-22 23:07:50,102][543983] Updated weights for policy 0, policy_version 27108 (0.0006) +[2026-07-22 23:07:50,390][543983] Updated weights for policy 0, policy_version 27118 (0.0006) +[2026-07-22 23:07:51,468][543983] Updated weights for policy 0, policy_version 27129 (0.0007) +[2026-07-22 23:07:51,738][543983] Updated weights for policy 0, policy_version 27139 (0.0006) +[2026-07-22 23:07:52,027][543983] Updated weights for policy 0, policy_version 27149 (0.0006) +[2026-07-22 23:07:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 13893632. Throughput: 0: 12669.2. Samples: 13907456. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:07:52,287][543203] Avg episode reward: [(0, '1109.714')] +[2026-07-22 23:07:52,314][543983] Updated weights for policy 0, policy_version 27159 (0.0006) +[2026-07-22 23:07:52,612][543983] Updated weights for policy 0, policy_version 27170 (0.0007) +[2026-07-22 23:07:52,931][543983] Updated weights for policy 0, policy_version 27181 (0.0006) +[2026-07-22 23:07:53,225][543983] Updated weights for policy 0, policy_version 27192 (0.0006) +[2026-07-22 23:07:54,297][543983] Updated weights for policy 0, policy_version 27202 (0.0007) +[2026-07-22 23:07:54,592][543983] Updated weights for policy 0, policy_version 27212 (0.0006) +[2026-07-22 23:07:54,876][543983] Updated weights for policy 0, policy_version 27222 (0.0006) +[2026-07-22 23:07:55,172][543983] Updated weights for policy 0, policy_version 27233 (0.0006) +[2026-07-22 23:07:55,467][543983] Updated weights for policy 0, policy_version 27243 (0.0006) +[2026-07-22 23:07:55,780][543983] Updated weights for policy 0, policy_version 27254 (0.0006) +[2026-07-22 23:07:56,811][543983] Updated weights for policy 0, policy_version 27264 (0.0006) +[2026-07-22 23:07:57,100][543983] Updated weights for policy 0, policy_version 27274 (0.0008) +[2026-07-22 23:07:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 13959168. Throughput: 0: 12569.6. Samples: 13979648. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:07:57,287][543203] Avg episode reward: [(0, '1127.088')] +[2026-07-22 23:07:57,378][543983] Updated weights for policy 0, policy_version 27284 (0.0007) +[2026-07-22 23:07:57,657][543983] Updated weights for policy 0, policy_version 27294 (0.0007) +[2026-07-22 23:07:57,949][543983] Updated weights for policy 0, policy_version 27304 (0.0006) +[2026-07-22 23:07:58,236][543983] Updated weights for policy 0, policy_version 27314 (0.0007) +[2026-07-22 23:07:59,274][543983] Updated weights for policy 0, policy_version 27324 (0.0007) +[2026-07-22 23:07:59,550][543983] Updated weights for policy 0, policy_version 27334 (0.0007) +[2026-07-22 23:07:59,834][543983] Updated weights for policy 0, policy_version 27344 (0.0006) +[2026-07-22 23:08:00,129][543983] Updated weights for policy 0, policy_version 27354 (0.0006) +[2026-07-22 23:08:00,414][543983] Updated weights for policy 0, policy_version 27364 (0.0006) +[2026-07-22 23:08:00,691][543983] Updated weights for policy 0, policy_version 27374 (0.0007) +[2026-07-22 23:08:00,957][543983] Updated weights for policy 0, policy_version 27384 (0.0006) +[2026-07-22 23:08:02,037][543983] Updated weights for policy 0, policy_version 27394 (0.0007) +[2026-07-22 23:08:02,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 14024704. Throughput: 0: 12834.1. Samples: 14063744. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:08:02,287][543203] Avg episode reward: [(0, '1159.631')] +[2026-07-22 23:08:02,320][543983] Updated weights for policy 0, policy_version 27404 (0.0007) +[2026-07-22 23:08:02,613][543983] Updated weights for policy 0, policy_version 27414 (0.0008) +[2026-07-22 23:08:02,907][543983] Updated weights for policy 0, policy_version 27424 (0.0007) +[2026-07-22 23:08:03,186][543983] Updated weights for policy 0, policy_version 27434 (0.0008) +[2026-07-22 23:08:03,566][543983] Updated weights for policy 0, policy_version 27447 (0.0007) +[2026-07-22 23:08:03,583][543696] Saving new best policy, reward=1159.631! +[2026-07-22 23:08:04,593][543983] Updated weights for policy 0, policy_version 27458 (0.0007) +[2026-07-22 23:08:04,919][543983] Updated weights for policy 0, policy_version 27469 (0.0006) +[2026-07-22 23:08:05,187][543983] Updated weights for policy 0, policy_version 27479 (0.0006) +[2026-07-22 23:08:05,478][543983] Updated weights for policy 0, policy_version 27489 (0.0007) +[2026-07-22 23:08:05,782][543983] Updated weights for policy 0, policy_version 27500 (0.0006) +[2026-07-22 23:08:06,057][543983] Updated weights for policy 0, policy_version 27510 (0.0006) +[2026-07-22 23:08:07,113][543983] Updated weights for policy 0, policy_version 27520 (0.0006) +[2026-07-22 23:08:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 14090240. Throughput: 0: 12837.0. Samples: 14099456. Policy #0 lag: (min: 21.0, avg: 36.9, max: 85.0) +[2026-07-22 23:08:07,287][543203] Avg episode reward: [(0, '1157.219')] +[2026-07-22 23:08:07,404][543983] Updated weights for policy 0, policy_version 27530 (0.0007) +[2026-07-22 23:08:07,668][543983] Updated weights for policy 0, policy_version 27540 (0.0007) +[2026-07-22 23:08:07,994][543983] Updated weights for policy 0, policy_version 27551 (0.0007) +[2026-07-22 23:08:08,318][543983] Updated weights for policy 0, policy_version 27563 (0.0006) +[2026-07-22 23:08:08,634][543983] Updated weights for policy 0, policy_version 27574 (0.0007) +[2026-07-22 23:08:09,661][543983] Updated weights for policy 0, policy_version 27584 (0.0006) +[2026-07-22 23:08:09,972][543983] Updated weights for policy 0, policy_version 27595 (0.0007) +[2026-07-22 23:08:10,269][543983] Updated weights for policy 0, policy_version 27605 (0.0006) +[2026-07-22 23:08:10,550][543983] Updated weights for policy 0, policy_version 27615 (0.0008) +[2026-07-22 23:08:10,852][543983] Updated weights for policy 0, policy_version 27626 (0.0007) +[2026-07-22 23:08:11,137][543983] Updated weights for policy 0, policy_version 27636 (0.0007) +[2026-07-22 23:08:12,215][543983] Updated weights for policy 0, policy_version 27648 (0.0006) +[2026-07-22 23:08:12,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 14155776. Throughput: 0: 12555.4. Samples: 14171392. Policy #0 lag: (min: 21.0, avg: 36.9, max: 85.0) +[2026-07-22 23:08:12,287][543203] Avg episode reward: [(0, '1151.500')] +[2026-07-22 23:08:12,502][543983] Updated weights for policy 0, policy_version 27658 (0.0006) +[2026-07-22 23:08:12,817][543983] Updated weights for policy 0, policy_version 27669 (0.0008) +[2026-07-22 23:08:13,109][543983] Updated weights for policy 0, policy_version 27679 (0.0006) +[2026-07-22 23:08:13,373][543983] Updated weights for policy 0, policy_version 27689 (0.0006) +[2026-07-22 23:08:13,669][543983] Updated weights for policy 0, policy_version 27699 (0.0007) +[2026-07-22 23:08:14,759][543983] Updated weights for policy 0, policy_version 27710 (0.0006) +[2026-07-22 23:08:15,030][543983] Updated weights for policy 0, policy_version 27720 (0.0006) +[2026-07-22 23:08:15,316][543983] Updated weights for policy 0, policy_version 27730 (0.0006) +[2026-07-22 23:08:15,596][543983] Updated weights for policy 0, policy_version 27740 (0.0006) +[2026-07-22 23:08:15,871][543983] Updated weights for policy 0, policy_version 27750 (0.0006) +[2026-07-22 23:08:16,160][543983] Updated weights for policy 0, policy_version 27760 (0.0006) +[2026-07-22 23:08:17,203][543983] Updated weights for policy 0, policy_version 27770 (0.0006) +[2026-07-22 23:08:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 14221312. Throughput: 0: 12691.9. Samples: 14249728. Policy #0 lag: (min: 21.0, avg: 36.9, max: 85.0) +[2026-07-22 23:08:17,287][543203] Avg episode reward: [(0, '1154.451')] +[2026-07-22 23:08:17,477][543983] Updated weights for policy 0, policy_version 27780 (0.0006) +[2026-07-22 23:08:17,813][543983] Updated weights for policy 0, policy_version 27792 (0.0006) +[2026-07-22 23:08:18,160][543983] Updated weights for policy 0, policy_version 27804 (0.0006) +[2026-07-22 23:08:18,443][543983] Updated weights for policy 0, policy_version 27814 (0.0006) +[2026-07-22 23:08:18,715][543983] Updated weights for policy 0, policy_version 27824 (0.0007) +[2026-07-22 23:08:19,756][543983] Updated weights for policy 0, policy_version 27834 (0.0006) +[2026-07-22 23:08:20,056][543983] Updated weights for policy 0, policy_version 27844 (0.0006) +[2026-07-22 23:08:20,336][543983] Updated weights for policy 0, policy_version 27854 (0.0006) +[2026-07-22 23:08:20,642][543983] Updated weights for policy 0, policy_version 27865 (0.0006) +[2026-07-22 23:08:20,918][543983] Updated weights for policy 0, policy_version 27875 (0.0006) +[2026-07-22 23:08:21,200][543983] Updated weights for policy 0, policy_version 27885 (0.0006) +[2026-07-22 23:08:21,512][543983] Updated weights for policy 0, policy_version 27896 (0.0006) +[2026-07-22 23:08:22,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 14286848. Throughput: 0: 12805.7. Samples: 14291328. Policy #0 lag: (min: 21.0, avg: 36.9, max: 85.0) +[2026-07-22 23:08:22,287][543203] Avg episode reward: [(0, '1136.375')] +[2026-07-22 23:08:22,590][543983] Updated weights for policy 0, policy_version 27906 (0.0006) +[2026-07-22 23:08:22,867][543983] Updated weights for policy 0, policy_version 27916 (0.0007) +[2026-07-22 23:08:23,156][543983] Updated weights for policy 0, policy_version 27926 (0.0007) +[2026-07-22 23:08:23,469][543983] Updated weights for policy 0, policy_version 27937 (0.0007) +[2026-07-22 23:08:23,758][543983] Updated weights for policy 0, policy_version 27947 (0.0006) +[2026-07-22 23:08:24,076][543983] Updated weights for policy 0, policy_version 27958 (0.0006) +[2026-07-22 23:08:25,128][543983] Updated weights for policy 0, policy_version 27969 (0.0006) +[2026-07-22 23:08:25,401][543983] Updated weights for policy 0, policy_version 27979 (0.0007) +[2026-07-22 23:08:25,695][543983] Updated weights for policy 0, policy_version 27989 (0.0006) +[2026-07-22 23:08:25,992][543983] Updated weights for policy 0, policy_version 28000 (0.0006) +[2026-07-22 23:08:26,282][543983] Updated weights for policy 0, policy_version 28010 (0.0006) +[2026-07-22 23:08:26,587][543983] Updated weights for policy 0, policy_version 28021 (0.0006) +[2026-07-22 23:08:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 14352384. Throughput: 0: 12663.5. Samples: 14363776. Policy #0 lag: (min: 19.0, avg: 49.4, max: 83.0) +[2026-07-22 23:08:27,287][543203] Avg episode reward: [(0, '1167.305')] +[2026-07-22 23:08:27,663][543983] Updated weights for policy 0, policy_version 28031 (0.0006) +[2026-07-22 23:08:27,942][543983] Updated weights for policy 0, policy_version 28041 (0.0008) +[2026-07-22 23:08:28,222][543983] Updated weights for policy 0, policy_version 28051 (0.0007) +[2026-07-22 23:08:28,533][543983] Updated weights for policy 0, policy_version 28062 (0.0006) +[2026-07-22 23:08:28,819][543983] Updated weights for policy 0, policy_version 28072 (0.0007) +[2026-07-22 23:08:29,129][543983] Updated weights for policy 0, policy_version 28083 (0.0007) +[2026-07-22 23:08:29,262][543696] Saving new best policy, reward=1167.305! +[2026-07-22 23:08:30,159][543983] Updated weights for policy 0, policy_version 28093 (0.0006) +[2026-07-22 23:08:30,469][543983] Updated weights for policy 0, policy_version 28104 (0.0006) +[2026-07-22 23:08:30,779][543983] Updated weights for policy 0, policy_version 28115 (0.0006) +[2026-07-22 23:08:31,070][543983] Updated weights for policy 0, policy_version 28125 (0.0007) +[2026-07-22 23:08:31,355][543983] Updated weights for policy 0, policy_version 28135 (0.0006) +[2026-07-22 23:08:31,630][543983] Updated weights for policy 0, policy_version 28145 (0.0007) +[2026-07-22 23:08:32,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 14417920. Throughput: 0: 12552.5. Samples: 14435968. Policy #0 lag: (min: 19.0, avg: 49.4, max: 83.0) +[2026-07-22 23:08:32,288][543203] Avg episode reward: [(0, '1174.383')] +[2026-07-22 23:08:32,294][543696] Saving new best policy, reward=1174.383! +[2026-07-22 23:08:32,666][543983] Updated weights for policy 0, policy_version 28155 (0.0006) +[2026-07-22 23:08:32,962][543983] Updated weights for policy 0, policy_version 28165 (0.0006) +[2026-07-22 23:08:33,239][543983] Updated weights for policy 0, policy_version 28175 (0.0007) +[2026-07-22 23:08:33,577][543983] Updated weights for policy 0, policy_version 28187 (0.0007) +[2026-07-22 23:08:33,860][543983] Updated weights for policy 0, policy_version 28197 (0.0006) +[2026-07-22 23:08:34,154][543983] Updated weights for policy 0, policy_version 28207 (0.0006) +[2026-07-22 23:08:35,203][543983] Updated weights for policy 0, policy_version 28217 (0.0006) +[2026-07-22 23:08:35,487][543983] Updated weights for policy 0, policy_version 28227 (0.0006) +[2026-07-22 23:08:35,787][543983] Updated weights for policy 0, policy_version 28237 (0.0006) +[2026-07-22 23:08:36,059][543983] Updated weights for policy 0, policy_version 28247 (0.0006) +[2026-07-22 23:08:36,359][543983] Updated weights for policy 0, policy_version 28257 (0.0006) +[2026-07-22 23:08:36,626][543983] Updated weights for policy 0, policy_version 28267 (0.0006) +[2026-07-22 23:08:36,915][543983] Updated weights for policy 0, policy_version 28277 (0.0006) +[2026-07-22 23:08:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 14483456. Throughput: 0: 12672.0. Samples: 14477696. Policy #0 lag: (min: 19.0, avg: 49.4, max: 83.0) +[2026-07-22 23:08:37,287][543203] Avg episode reward: [(0, '1202.996')] +[2026-07-22 23:08:37,294][543696] Saving new best policy, reward=1202.996! +[2026-07-22 23:08:37,964][543983] Updated weights for policy 0, policy_version 28287 (0.0007) +[2026-07-22 23:08:38,273][543983] Updated weights for policy 0, policy_version 28298 (0.0008) +[2026-07-22 23:08:38,579][543983] Updated weights for policy 0, policy_version 28309 (0.0006) +[2026-07-22 23:08:38,887][543983] Updated weights for policy 0, policy_version 28320 (0.0006) +[2026-07-22 23:08:39,190][543983] Updated weights for policy 0, policy_version 28331 (0.0006) +[2026-07-22 23:08:39,493][543983] Updated weights for policy 0, policy_version 28341 (0.0006) +[2026-07-22 23:08:40,585][543983] Updated weights for policy 0, policy_version 28353 (0.0007) +[2026-07-22 23:08:40,913][543983] Updated weights for policy 0, policy_version 28364 (0.0006) +[2026-07-22 23:08:41,218][543983] Updated weights for policy 0, policy_version 28375 (0.0006) +[2026-07-22 23:08:41,570][543983] Updated weights for policy 0, policy_version 28387 (0.0006) +[2026-07-22 23:08:41,853][543983] Updated weights for policy 0, policy_version 28397 (0.0007) +[2026-07-22 23:08:42,120][543983] Updated weights for policy 0, policy_version 28407 (0.0006) +[2026-07-22 23:08:42,287][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 14548992. Throughput: 0: 12811.3. Samples: 14556160. Policy #0 lag: (min: 19.0, avg: 49.4, max: 83.0) +[2026-07-22 23:08:42,287][543203] Avg episode reward: [(0, '1182.923')] +[2026-07-22 23:08:43,145][543983] Updated weights for policy 0, policy_version 28417 (0.0006) +[2026-07-22 23:08:43,453][543983] Updated weights for policy 0, policy_version 28428 (0.0006) +[2026-07-22 23:08:43,737][543983] Updated weights for policy 0, policy_version 28438 (0.0006) +[2026-07-22 23:08:44,070][543983] Updated weights for policy 0, policy_version 28449 (0.0006) +[2026-07-22 23:08:44,372][543983] Updated weights for policy 0, policy_version 28460 (0.0006) +[2026-07-22 23:08:44,649][543983] Updated weights for policy 0, policy_version 28470 (0.0007) +[2026-07-22 23:08:45,695][543983] Updated weights for policy 0, policy_version 28480 (0.0006) +[2026-07-22 23:08:45,973][543983] Updated weights for policy 0, policy_version 28490 (0.0007) +[2026-07-22 23:08:46,246][543983] Updated weights for policy 0, policy_version 28500 (0.0007) +[2026-07-22 23:08:46,563][543983] Updated weights for policy 0, policy_version 28511 (0.0006) +[2026-07-22 23:08:46,857][543983] Updated weights for policy 0, policy_version 28521 (0.0006) +[2026-07-22 23:08:47,182][543983] Updated weights for policy 0, policy_version 28532 (0.0008) +[2026-07-22 23:08:47,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 14614528. Throughput: 0: 12541.2. Samples: 14628096. Policy #0 lag: (min: 19.0, avg: 47.3, max: 83.0) +[2026-07-22 23:08:47,287][543203] Avg episode reward: [(0, '1165.458')] +[2026-07-22 23:08:48,205][543983] Updated weights for policy 0, policy_version 28542 (0.0007) +[2026-07-22 23:08:48,551][543983] Updated weights for policy 0, policy_version 28554 (0.0007) +[2026-07-22 23:08:48,829][543983] Updated weights for policy 0, policy_version 28564 (0.0007) +[2026-07-22 23:08:49,121][543983] Updated weights for policy 0, policy_version 28574 (0.0008) +[2026-07-22 23:08:49,400][543983] Updated weights for policy 0, policy_version 28584 (0.0006) +[2026-07-22 23:08:49,684][543983] Updated weights for policy 0, policy_version 28594 (0.0006) +[2026-07-22 23:08:50,725][543983] Updated weights for policy 0, policy_version 28605 (0.0006) +[2026-07-22 23:08:50,997][543983] Updated weights for policy 0, policy_version 28615 (0.0006) +[2026-07-22 23:08:51,298][543983] Updated weights for policy 0, policy_version 28625 (0.0006) +[2026-07-22 23:08:51,569][543983] Updated weights for policy 0, policy_version 28635 (0.0007) +[2026-07-22 23:08:51,861][543983] Updated weights for policy 0, policy_version 28645 (0.0007) +[2026-07-22 23:08:52,157][543983] Updated weights for policy 0, policy_version 28655 (0.0007) +[2026-07-22 23:08:52,286][543203] Fps is (10 sec: 9830.5, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 14647296. Throughput: 0: 12546.9. Samples: 14664064. Policy #0 lag: (min: 19.0, avg: 47.3, max: 83.0) +[2026-07-22 23:08:52,287][543203] Avg episode reward: [(0, '1146.850')] +[2026-07-22 23:08:53,206][543983] Updated weights for policy 0, policy_version 28665 (0.0007) +[2026-07-22 23:08:53,541][543983] Updated weights for policy 0, policy_version 28677 (0.0007) +[2026-07-22 23:08:53,834][543983] Updated weights for policy 0, policy_version 28687 (0.0006) +[2026-07-22 23:08:54,109][543983] Updated weights for policy 0, policy_version 28697 (0.0006) +[2026-07-22 23:08:54,392][543983] Updated weights for policy 0, policy_version 28707 (0.0006) +[2026-07-22 23:08:54,673][543983] Updated weights for policy 0, policy_version 28717 (0.0006) +[2026-07-22 23:08:54,965][543983] Updated weights for policy 0, policy_version 28727 (0.0008) +[2026-07-22 23:08:56,019][543983] Updated weights for policy 0, policy_version 28737 (0.0006) +[2026-07-22 23:08:56,325][543983] Updated weights for policy 0, policy_version 28748 (0.0006) +[2026-07-22 23:08:56,611][543983] Updated weights for policy 0, policy_version 28758 (0.0006) +[2026-07-22 23:08:56,921][543983] Updated weights for policy 0, policy_version 28769 (0.0007) +[2026-07-22 23:08:57,270][543983] Updated weights for policy 0, policy_version 28781 (0.0006) +[2026-07-22 23:08:57,286][543203] Fps is (10 sec: 9830.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 14712832. Throughput: 0: 12805.7. Samples: 14747648. Policy #0 lag: (min: 19.0, avg: 47.3, max: 83.0) +[2026-07-22 23:08:57,287][543203] Avg episode reward: [(0, '1135.258')] +[2026-07-22 23:08:57,567][543983] Updated weights for policy 0, policy_version 28792 (0.0006) +[2026-07-22 23:08:58,592][543983] Updated weights for policy 0, policy_version 28802 (0.0007) +[2026-07-22 23:08:58,884][543983] Updated weights for policy 0, policy_version 28812 (0.0007) +[2026-07-22 23:08:59,158][543983] Updated weights for policy 0, policy_version 28822 (0.0006) +[2026-07-22 23:08:59,471][543983] Updated weights for policy 0, policy_version 28833 (0.0007) +[2026-07-22 23:08:59,749][543983] Updated weights for policy 0, policy_version 28843 (0.0006) +[2026-07-22 23:09:00,055][543983] Updated weights for policy 0, policy_version 28853 (0.0006) +[2026-07-22 23:09:01,089][543983] Updated weights for policy 0, policy_version 28863 (0.0007) +[2026-07-22 23:09:01,381][543983] Updated weights for policy 0, policy_version 28873 (0.0007) +[2026-07-22 23:09:01,690][543983] Updated weights for policy 0, policy_version 28884 (0.0007) +[2026-07-22 23:09:01,967][543983] Updated weights for policy 0, policy_version 28894 (0.0007) +[2026-07-22 23:09:02,245][543983] Updated weights for policy 0, policy_version 28904 (0.0007) +[2026-07-22 23:09:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 14778368. Throughput: 0: 12660.6. Samples: 14819456. Policy #0 lag: (min: 19.0, avg: 47.3, max: 83.0) +[2026-07-22 23:09:02,287][543203] Avg episode reward: [(0, '1143.732')] +[2026-07-22 23:09:02,550][543983] Updated weights for policy 0, policy_version 28914 (0.0007) +[2026-07-22 23:09:03,632][543983] Updated weights for policy 0, policy_version 28925 (0.0007) +[2026-07-22 23:09:03,907][543983] Updated weights for policy 0, policy_version 28935 (0.0006) +[2026-07-22 23:09:04,237][543983] Updated weights for policy 0, policy_version 28946 (0.0007) +[2026-07-22 23:09:04,514][543983] Updated weights for policy 0, policy_version 28956 (0.0007) +[2026-07-22 23:09:04,796][543983] Updated weights for policy 0, policy_version 28966 (0.0006) +[2026-07-22 23:09:05,141][543983] Updated weights for policy 0, policy_version 28977 (0.0006) +[2026-07-22 23:09:06,263][543983] Updated weights for policy 0, policy_version 28987 (0.0008) +[2026-07-22 23:09:06,561][543983] Updated weights for policy 0, policy_version 28998 (0.0006) +[2026-07-22 23:09:06,872][543983] Updated weights for policy 0, policy_version 29009 (0.0006) +[2026-07-22 23:09:07,162][543983] Updated weights for policy 0, policy_version 29019 (0.0007) +[2026-07-22 23:09:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 14843904. Throughput: 0: 12555.4. Samples: 14856320. Policy #0 lag: (min: 50.0, avg: 69.8, max: 114.0) +[2026-07-22 23:09:07,287][543203] Avg episode reward: [(0, '1172.506')] +[2026-07-22 23:09:07,478][543983] Updated weights for policy 0, policy_version 29030 (0.0006) +[2026-07-22 23:09:07,820][543983] Updated weights for policy 0, policy_version 29042 (0.0007) +[2026-07-22 23:09:08,838][543983] Updated weights for policy 0, policy_version 29052 (0.0007) +[2026-07-22 23:09:09,125][543983] Updated weights for policy 0, policy_version 29062 (0.0006) +[2026-07-22 23:09:09,433][543983] Updated weights for policy 0, policy_version 29073 (0.0007) +[2026-07-22 23:09:09,731][543983] Updated weights for policy 0, policy_version 29083 (0.0007) +[2026-07-22 23:09:10,004][543983] Updated weights for policy 0, policy_version 29093 (0.0007) +[2026-07-22 23:09:10,289][543983] Updated weights for policy 0, policy_version 29103 (0.0007) +[2026-07-22 23:09:11,361][543983] Updated weights for policy 0, policy_version 29114 (0.0007) +[2026-07-22 23:09:11,640][543983] Updated weights for policy 0, policy_version 29124 (0.0007) +[2026-07-22 23:09:11,928][543983] Updated weights for policy 0, policy_version 29134 (0.0006) +[2026-07-22 23:09:12,222][543983] Updated weights for policy 0, policy_version 29144 (0.0007) +[2026-07-22 23:09:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 14909440. Throughput: 0: 12609.4. Samples: 14931200. Policy #0 lag: (min: 50.0, avg: 69.8, max: 114.0) +[2026-07-22 23:09:12,287][543203] Avg episode reward: [(0, '1166.643')] +[2026-07-22 23:09:12,508][543983] Updated weights for policy 0, policy_version 29154 (0.0007) +[2026-07-22 23:09:12,798][543983] Updated weights for policy 0, policy_version 29164 (0.0010) +[2026-07-22 23:09:13,094][543983] Updated weights for policy 0, policy_version 29174 (0.0008) +[2026-07-22 23:09:14,125][543983] Updated weights for policy 0, policy_version 29184 (0.0008) +[2026-07-22 23:09:14,425][543983] Updated weights for policy 0, policy_version 29194 (0.0006) +[2026-07-22 23:09:14,713][543983] Updated weights for policy 0, policy_version 29204 (0.0007) +[2026-07-22 23:09:15,051][543983] Updated weights for policy 0, policy_version 29216 (0.0008) +[2026-07-22 23:09:15,356][543983] Updated weights for policy 0, policy_version 29226 (0.0008) +[2026-07-22 23:09:15,664][543983] Updated weights for policy 0, policy_version 29237 (0.0007) +[2026-07-22 23:09:16,723][543983] Updated weights for policy 0, policy_version 29247 (0.0009) +[2026-07-22 23:09:17,065][543983] Updated weights for policy 0, policy_version 29259 (0.0008) +[2026-07-22 23:09:17,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 14974976. Throughput: 0: 12802.9. Samples: 15012096. Policy #0 lag: (min: 50.0, avg: 69.8, max: 114.0) +[2026-07-22 23:09:17,287][543203] Avg episode reward: [(0, '1160.447')] +[2026-07-22 23:09:17,392][543983] Updated weights for policy 0, policy_version 29270 (0.0007) +[2026-07-22 23:09:17,684][543983] Updated weights for policy 0, policy_version 29280 (0.0007) +[2026-07-22 23:09:17,967][543983] Updated weights for policy 0, policy_version 29290 (0.0006) +[2026-07-22 23:09:18,268][543983] Updated weights for policy 0, policy_version 29301 (0.0006) +[2026-07-22 23:09:18,348][543696] Saving results/checkpoints/memory/rollout_teacher/flappy_teacher_fixed_l3_obs30_seed0/checkpoint_p0/checkpoint_000029304_15007744.pth... +[2026-07-22 23:09:19,373][543983] Updated weights for policy 0, policy_version 29313 (0.0006) +[2026-07-22 23:09:19,661][543983] Updated weights for policy 0, policy_version 29323 (0.0006) +[2026-07-22 23:09:19,995][543983] Updated weights for policy 0, policy_version 29335 (0.0006) +[2026-07-22 23:09:20,306][543983] Updated weights for policy 0, policy_version 29346 (0.0006) +[2026-07-22 23:09:20,587][543983] Updated weights for policy 0, policy_version 29356 (0.0006) +[2026-07-22 23:09:20,895][543983] Updated weights for policy 0, policy_version 29367 (0.0006) +[2026-07-22 23:09:21,964][543983] Updated weights for policy 0, policy_version 29377 (0.0006) +[2026-07-22 23:09:22,279][543983] Updated weights for policy 0, policy_version 29388 (0.0007) +[2026-07-22 23:09:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 15040512. Throughput: 0: 12689.1. Samples: 15048704. Policy #0 lag: (min: 50.0, avg: 69.8, max: 114.0) +[2026-07-22 23:09:22,287][543203] Avg episode reward: [(0, '1119.588')] +[2026-07-22 23:09:22,565][543983] Updated weights for policy 0, policy_version 29398 (0.0007) +[2026-07-22 23:09:22,870][543983] Updated weights for policy 0, policy_version 29409 (0.0007) +[2026-07-22 23:09:23,169][543983] Updated weights for policy 0, policy_version 29419 (0.0006) +[2026-07-22 23:09:23,482][543983] Updated weights for policy 0, policy_version 29430 (0.0006) +[2026-07-22 23:09:24,542][543983] Updated weights for policy 0, policy_version 29440 (0.0006) +[2026-07-22 23:09:24,849][543983] Updated weights for policy 0, policy_version 29451 (0.0006) +[2026-07-22 23:09:25,163][543983] Updated weights for policy 0, policy_version 29462 (0.0006) +[2026-07-22 23:09:25,484][543983] Updated weights for policy 0, policy_version 29473 (0.0006) +[2026-07-22 23:09:25,768][543983] Updated weights for policy 0, policy_version 29483 (0.0007) +[2026-07-22 23:09:26,056][543983] Updated weights for policy 0, policy_version 29493 (0.0006) +[2026-07-22 23:09:27,097][543983] Updated weights for policy 0, policy_version 29504 (0.0007) +[2026-07-22 23:09:27,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 15106048. Throughput: 0: 12563.9. Samples: 15121536. Policy #0 lag: (min: 3.0, avg: 29.5, max: 67.0) +[2026-07-22 23:09:27,287][543203] Avg episode reward: [(0, '1120.066')] +[2026-07-22 23:09:27,387][543983] Updated weights for policy 0, policy_version 29514 (0.0006) +[2026-07-22 23:09:27,667][543983] Updated weights for policy 0, policy_version 29524 (0.0006) +[2026-07-22 23:09:27,947][543983] Updated weights for policy 0, policy_version 29534 (0.0006) +[2026-07-22 23:09:28,240][543983] Updated weights for policy 0, policy_version 29544 (0.0006) +[2026-07-22 23:09:28,517][543983] Updated weights for policy 0, policy_version 29554 (0.0006) +[2026-07-22 23:09:29,646][543983] Updated weights for policy 0, policy_version 29566 (0.0006) +[2026-07-22 23:09:29,933][543983] Updated weights for policy 0, policy_version 29576 (0.0006) +[2026-07-22 23:09:30,255][543983] Updated weights for policy 0, policy_version 29587 (0.0006) +[2026-07-22 23:09:30,526][543983] Updated weights for policy 0, policy_version 29597 (0.0006) +[2026-07-22 23:09:30,800][543983] Updated weights for policy 0, policy_version 29607 (0.0006) +[2026-07-22 23:09:31,110][543983] Updated weights for policy 0, policy_version 29617 (0.0006) +[2026-07-22 23:09:32,136][543983] Updated weights for policy 0, policy_version 29627 (0.0007) +[2026-07-22 23:09:32,287][543203] Fps is (10 sec: 13107.0, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 15171584. Throughput: 0: 12748.7. Samples: 15201792. Policy #0 lag: (min: 3.0, avg: 29.5, max: 67.0) +[2026-07-22 23:09:32,288][543203] Avg episode reward: [(0, '1123.288')] +[2026-07-22 23:09:32,474][543983] Updated weights for policy 0, policy_version 29639 (0.0007) +[2026-07-22 23:09:32,770][543983] Updated weights for policy 0, policy_version 29649 (0.0007) +[2026-07-22 23:09:33,049][543983] Updated weights for policy 0, policy_version 29659 (0.0006) +[2026-07-22 23:09:33,334][543983] Updated weights for policy 0, policy_version 29669 (0.0006) +[2026-07-22 23:09:33,643][543983] Updated weights for policy 0, policy_version 29680 (0.0006) +[2026-07-22 23:09:34,710][543983] Updated weights for policy 0, policy_version 29691 (0.0006) +[2026-07-22 23:09:35,046][543983] Updated weights for policy 0, policy_version 29703 (0.0006) +[2026-07-22 23:09:35,332][543983] Updated weights for policy 0, policy_version 29713 (0.0006) +[2026-07-22 23:09:35,628][543983] Updated weights for policy 0, policy_version 29723 (0.0006) +[2026-07-22 23:09:35,905][543983] Updated weights for policy 0, policy_version 29733 (0.0006) +[2026-07-22 23:09:36,182][543983] Updated weights for policy 0, policy_version 29743 (0.0006) +[2026-07-22 23:09:37,219][543983] Updated weights for policy 0, policy_version 29753 (0.0006) +[2026-07-22 23:09:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 15237120. Throughput: 0: 12831.3. Samples: 15241472. Policy #0 lag: (min: 3.0, avg: 29.5, max: 67.0) +[2026-07-22 23:09:37,287][543203] Avg episode reward: [(0, '1105.721')] +[2026-07-22 23:09:37,535][543983] Updated weights for policy 0, policy_version 29764 (0.0007) +[2026-07-22 23:09:37,814][543983] Updated weights for policy 0, policy_version 29774 (0.0006) +[2026-07-22 23:09:38,130][543983] Updated weights for policy 0, policy_version 29785 (0.0008) +[2026-07-22 23:09:38,445][543983] Updated weights for policy 0, policy_version 29796 (0.0007) +[2026-07-22 23:09:38,734][543983] Updated weights for policy 0, policy_version 29806 (0.0006) +[2026-07-22 23:09:39,007][543983] Updated weights for policy 0, policy_version 29816 (0.0006) +[2026-07-22 23:09:40,038][543983] Updated weights for policy 0, policy_version 29826 (0.0006) +[2026-07-22 23:09:40,318][543983] Updated weights for policy 0, policy_version 29836 (0.0007) +[2026-07-22 23:09:40,650][543983] Updated weights for policy 0, policy_version 29848 (0.0007) +[2026-07-22 23:09:40,953][543983] Updated weights for policy 0, policy_version 29859 (0.0006) +[2026-07-22 23:09:41,250][543983] Updated weights for policy 0, policy_version 29869 (0.0007) +[2026-07-22 23:09:41,537][543983] Updated weights for policy 0, policy_version 29879 (0.0006) +[2026-07-22 23:09:42,286][543203] Fps is (10 sec: 13107.4, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 15302656. Throughput: 0: 12572.5. Samples: 15313408. Policy #0 lag: (min: 3.0, avg: 29.5, max: 67.0) +[2026-07-22 23:09:42,287][543203] Avg episode reward: [(0, '1082.250')] +[2026-07-22 23:09:42,616][543983] Updated weights for policy 0, policy_version 29890 (0.0007) +[2026-07-22 23:09:42,910][543983] Updated weights for policy 0, policy_version 29900 (0.0007) +[2026-07-22 23:09:43,212][543983] Updated weights for policy 0, policy_version 29911 (0.0006) +[2026-07-22 23:09:43,489][543983] Updated weights for policy 0, policy_version 29921 (0.0007) +[2026-07-22 23:09:43,780][543983] Updated weights for policy 0, policy_version 29931 (0.0006) +[2026-07-22 23:09:44,062][543983] Updated weights for policy 0, policy_version 29941 (0.0007) +[2026-07-22 23:09:45,140][543983] Updated weights for policy 0, policy_version 29952 (0.0008) +[2026-07-22 23:09:45,456][543983] Updated weights for policy 0, policy_version 29962 (0.0006) +[2026-07-22 23:09:45,720][543983] Updated weights for policy 0, policy_version 29972 (0.0007) +[2026-07-22 23:09:46,015][543983] Updated weights for policy 0, policy_version 29982 (0.0007) +[2026-07-22 23:09:46,321][543983] Updated weights for policy 0, policy_version 29993 (0.0006) +[2026-07-22 23:09:46,615][543983] Updated weights for policy 0, policy_version 30003 (0.0007) +[2026-07-22 23:09:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 15368192. Throughput: 0: 12589.5. Samples: 15385984. Policy #0 lag: (min: 10.0, avg: 33.9, max: 74.0) +[2026-07-22 23:09:47,287][543203] Avg episode reward: [(0, '1094.159')] +[2026-07-22 23:09:47,647][543983] Updated weights for policy 0, policy_version 30013 (0.0007) +[2026-07-22 23:09:47,954][543983] Updated weights for policy 0, policy_version 30024 (0.0006) +[2026-07-22 23:09:48,244][543983] Updated weights for policy 0, policy_version 30034 (0.0007) +[2026-07-22 23:09:48,518][543983] Updated weights for policy 0, policy_version 30044 (0.0006) +[2026-07-22 23:09:48,804][543983] Updated weights for policy 0, policy_version 30054 (0.0006) +[2026-07-22 23:09:49,080][543983] Updated weights for policy 0, policy_version 30064 (0.0006) +[2026-07-22 23:09:50,121][543983] Updated weights for policy 0, policy_version 30074 (0.0006) +[2026-07-22 23:09:50,432][543983] Updated weights for policy 0, policy_version 30085 (0.0007) +[2026-07-22 23:09:50,734][543983] Updated weights for policy 0, policy_version 30096 (0.0006) +[2026-07-22 23:09:51,027][543983] Updated weights for policy 0, policy_version 30106 (0.0006) +[2026-07-22 23:09:51,299][543983] Updated weights for policy 0, policy_version 30116 (0.0006) +[2026-07-22 23:09:51,589][543983] Updated weights for policy 0, policy_version 30126 (0.0006) +[2026-07-22 23:09:52,286][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 15433728. Throughput: 0: 12740.3. Samples: 15429632. Policy #0 lag: (min: 10.0, avg: 33.9, max: 74.0) +[2026-07-22 23:09:52,287][543203] Avg episode reward: [(0, '1113.624')] +[2026-07-22 23:09:52,652][543983] Updated weights for policy 0, policy_version 30137 (0.0006) +[2026-07-22 23:09:52,957][543983] Updated weights for policy 0, policy_version 30148 (0.0006) +[2026-07-22 23:09:53,266][543983] Updated weights for policy 0, policy_version 30159 (0.0007) +[2026-07-22 23:09:53,580][543983] Updated weights for policy 0, policy_version 30170 (0.0006) +[2026-07-22 23:09:53,931][543983] Updated weights for policy 0, policy_version 30182 (0.0007) +[2026-07-22 23:09:54,199][543983] Updated weights for policy 0, policy_version 30192 (0.0006) +[2026-07-22 23:09:55,258][543983] Updated weights for policy 0, policy_version 30203 (0.0006) +[2026-07-22 23:09:55,545][543983] Updated weights for policy 0, policy_version 30213 (0.0007) +[2026-07-22 23:09:55,828][543983] Updated weights for policy 0, policy_version 30223 (0.0007) +[2026-07-22 23:09:56,126][543983] Updated weights for policy 0, policy_version 30233 (0.0006) +[2026-07-22 23:09:56,396][543983] Updated weights for policy 0, policy_version 30243 (0.0006) +[2026-07-22 23:09:56,692][543983] Updated weights for policy 0, policy_version 30253 (0.0006) +[2026-07-22 23:09:57,001][543983] Updated weights for policy 0, policy_version 30264 (0.0006) +[2026-07-22 23:09:57,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 15499264. Throughput: 0: 12760.2. Samples: 15505408. Policy #0 lag: (min: 10.0, avg: 33.9, max: 74.0) +[2026-07-22 23:09:57,287][543203] Avg episode reward: [(0, '1107.479')] +[2026-07-22 23:09:58,083][543983] Updated weights for policy 0, policy_version 30275 (0.0006) +[2026-07-22 23:09:58,376][543983] Updated weights for policy 0, policy_version 30286 (0.0007) +[2026-07-22 23:09:58,675][543983] Updated weights for policy 0, policy_version 30296 (0.0006) +[2026-07-22 23:09:58,989][543983] Updated weights for policy 0, policy_version 30307 (0.0006) +[2026-07-22 23:09:59,259][543983] Updated weights for policy 0, policy_version 30317 (0.0006) +[2026-07-22 23:10:00,384][543983] Updated weights for policy 0, policy_version 30329 (0.0007) +[2026-07-22 23:10:00,667][543983] Updated weights for policy 0, policy_version 30339 (0.0006) +[2026-07-22 23:10:00,955][543983] Updated weights for policy 0, policy_version 30349 (0.0006) +[2026-07-22 23:10:01,240][543983] Updated weights for policy 0, policy_version 30359 (0.0006) +[2026-07-22 23:10:01,520][543983] Updated weights for policy 0, policy_version 30369 (0.0006) +[2026-07-22 23:10:01,802][543983] Updated weights for policy 0, policy_version 30379 (0.0006) +[2026-07-22 23:10:02,076][543983] Updated weights for policy 0, policy_version 30389 (0.0006) +[2026-07-22 23:10:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 15564800. Throughput: 0: 12569.6. Samples: 15577728. Policy #0 lag: (min: 10.0, avg: 33.9, max: 74.0) +[2026-07-22 23:10:02,287][543203] Avg episode reward: [(0, '1130.654')] +[2026-07-22 23:10:03,144][543983] Updated weights for policy 0, policy_version 30399 (0.0006) +[2026-07-22 23:10:03,428][543983] Updated weights for policy 0, policy_version 30409 (0.0007) +[2026-07-22 23:10:03,705][543983] Updated weights for policy 0, policy_version 30419 (0.0006) +[2026-07-22 23:10:03,989][543983] Updated weights for policy 0, policy_version 30429 (0.0006) +[2026-07-22 23:10:04,264][543983] Updated weights for policy 0, policy_version 30439 (0.0007) +[2026-07-22 23:10:04,557][543983] Updated weights for policy 0, policy_version 30449 (0.0006) +[2026-07-22 23:10:05,588][543983] Updated weights for policy 0, policy_version 30459 (0.0006) +[2026-07-22 23:10:05,856][543983] Updated weights for policy 0, policy_version 30469 (0.0006) +[2026-07-22 23:10:06,147][543983] Updated weights for policy 0, policy_version 30479 (0.0007) +[2026-07-22 23:10:06,434][543983] Updated weights for policy 0, policy_version 30489 (0.0007) +[2026-07-22 23:10:06,725][543983] Updated weights for policy 0, policy_version 30499 (0.0007) +[2026-07-22 23:10:07,029][543983] Updated weights for policy 0, policy_version 30510 (0.0006) +[2026-07-22 23:10:07,287][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 15597568. Throughput: 0: 12563.9. Samples: 15614080. Policy #0 lag: (min: 10.0, avg: 33.9, max: 74.0) +[2026-07-22 23:10:07,287][543203] Avg episode reward: [(0, '1165.946')] +[2026-07-22 23:10:07,317][543983] Updated weights for policy 0, policy_version 30520 (0.0006) +[2026-07-22 23:10:08,392][543983] Updated weights for policy 0, policy_version 30530 (0.0007) +[2026-07-22 23:10:08,672][543983] Updated weights for policy 0, policy_version 30540 (0.0006) +[2026-07-22 23:10:09,010][543983] Updated weights for policy 0, policy_version 30552 (0.0006) +[2026-07-22 23:10:09,290][543983] Updated weights for policy 0, policy_version 30562 (0.0006) +[2026-07-22 23:10:09,568][543983] Updated weights for policy 0, policy_version 30572 (0.0006) +[2026-07-22 23:10:09,853][543983] Updated weights for policy 0, policy_version 30582 (0.0006) +[2026-07-22 23:10:10,900][543983] Updated weights for policy 0, policy_version 30592 (0.0006) +[2026-07-22 23:10:11,214][543983] Updated weights for policy 0, policy_version 30603 (0.0007) +[2026-07-22 23:10:11,490][543983] Updated weights for policy 0, policy_version 30613 (0.0007) +[2026-07-22 23:10:11,779][543983] Updated weights for policy 0, policy_version 30623 (0.0006) +[2026-07-22 23:10:12,057][543983] Updated weights for policy 0, policy_version 30633 (0.0007) +[2026-07-22 23:10:12,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 15663104. Throughput: 0: 12817.1. Samples: 15698304. Policy #0 lag: (min: 55.0, avg: 71.7, max: 119.0) +[2026-07-22 23:10:12,287][543203] Avg episode reward: [(0, '1128.372')] +[2026-07-22 23:10:12,343][543983] Updated weights for policy 0, policy_version 30643 (0.0006) +[2026-07-22 23:10:13,376][543983] Updated weights for policy 0, policy_version 30653 (0.0006) +[2026-07-22 23:10:13,674][543983] Updated weights for policy 0, policy_version 30663 (0.0006) +[2026-07-22 23:10:13,985][543983] Updated weights for policy 0, policy_version 30674 (0.0006) +[2026-07-22 23:10:14,278][543983] Updated weights for policy 0, policy_version 30684 (0.0006) +[2026-07-22 23:10:14,573][543983] Updated weights for policy 0, policy_version 30695 (0.0006) +[2026-07-22 23:10:14,861][543983] Updated weights for policy 0, policy_version 30705 (0.0006) +[2026-07-22 23:10:15,899][543983] Updated weights for policy 0, policy_version 30715 (0.0007) +[2026-07-22 23:10:16,181][543983] Updated weights for policy 0, policy_version 30725 (0.0006) +[2026-07-22 23:10:16,473][543983] Updated weights for policy 0, policy_version 30735 (0.0007) +[2026-07-22 23:10:16,766][543983] Updated weights for policy 0, policy_version 30746 (0.0007) +[2026-07-22 23:10:17,073][543983] Updated weights for policy 0, policy_version 30757 (0.0006) +[2026-07-22 23:10:17,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 15728640. Throughput: 0: 12635.0. Samples: 15770368. Policy #0 lag: (min: 55.0, avg: 71.7, max: 119.0) +[2026-07-22 23:10:17,288][543203] Avg episode reward: [(0, '1132.086')] +[2026-07-22 23:10:17,398][543983] Updated weights for policy 0, policy_version 30768 (0.0007) +[2026-07-22 23:10:18,463][543983] Updated weights for policy 0, policy_version 30778 (0.0007) +[2026-07-22 23:10:18,747][543983] Updated weights for policy 0, policy_version 30788 (0.0006) +[2026-07-22 23:10:19,028][543983] Updated weights for policy 0, policy_version 30798 (0.0006) +[2026-07-22 23:10:19,321][543983] Updated weights for policy 0, policy_version 30808 (0.0006) +[2026-07-22 23:10:19,600][543983] Updated weights for policy 0, policy_version 30818 (0.0006) +[2026-07-22 23:10:19,877][543983] Updated weights for policy 0, policy_version 30828 (0.0008) +[2026-07-22 23:10:20,169][543983] Updated weights for policy 0, policy_version 30838 (0.0007) +[2026-07-22 23:10:21,236][543983] Updated weights for policy 0, policy_version 30848 (0.0006) +[2026-07-22 23:10:21,534][543983] Updated weights for policy 0, policy_version 30858 (0.0007) +[2026-07-22 23:10:21,820][543983] Updated weights for policy 0, policy_version 30868 (0.0006) +[2026-07-22 23:10:22,084][543983] Updated weights for policy 0, policy_version 30878 (0.0006) +[2026-07-22 23:10:22,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 15794176. Throughput: 0: 12561.0. Samples: 15806720. Policy #0 lag: (min: 55.0, avg: 71.7, max: 119.0) +[2026-07-22 23:10:22,287][543203] Avg episode reward: [(0, '1144.174')] +[2026-07-22 23:10:22,388][543983] Updated weights for policy 0, policy_version 30888 (0.0006) +[2026-07-22 23:10:22,666][543983] Updated weights for policy 0, policy_version 30898 (0.0006) +[2026-07-22 23:10:23,755][543983] Updated weights for policy 0, policy_version 30909 (0.0007) +[2026-07-22 23:10:24,029][543983] Updated weights for policy 0, policy_version 30919 (0.0006) +[2026-07-22 23:10:24,310][543983] Updated weights for policy 0, policy_version 30929 (0.0006) +[2026-07-22 23:10:24,598][543983] Updated weights for policy 0, policy_version 30939 (0.0006) +[2026-07-22 23:10:24,878][543983] Updated weights for policy 0, policy_version 30949 (0.0006) +[2026-07-22 23:10:25,180][543983] Updated weights for policy 0, policy_version 30960 (0.0006) +[2026-07-22 23:10:26,219][543983] Updated weights for policy 0, policy_version 30970 (0.0006) +[2026-07-22 23:10:26,502][543983] Updated weights for policy 0, policy_version 30980 (0.0007) +[2026-07-22 23:10:26,782][543983] Updated weights for policy 0, policy_version 30990 (0.0007) +[2026-07-22 23:10:27,085][543983] Updated weights for policy 0, policy_version 31001 (0.0006) +[2026-07-22 23:10:27,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 15859712. Throughput: 0: 12703.3. Samples: 15885056. Policy #0 lag: (min: 55.0, avg: 71.7, max: 119.0) +[2026-07-22 23:10:27,287][543203] Avg episode reward: [(0, '1152.972')] +[2026-07-22 23:10:27,377][543983] Updated weights for policy 0, policy_version 31011 (0.0006) +[2026-07-22 23:10:27,656][543983] Updated weights for policy 0, policy_version 31021 (0.0006) +[2026-07-22 23:10:27,937][543983] Updated weights for policy 0, policy_version 31031 (0.0006) +[2026-07-22 23:10:29,001][543983] Updated weights for policy 0, policy_version 31042 (0.0006) +[2026-07-22 23:10:29,301][543983] Updated weights for policy 0, policy_version 31052 (0.0006) +[2026-07-22 23:10:29,604][543983] Updated weights for policy 0, policy_version 31063 (0.0007) +[2026-07-22 23:10:29,906][543983] Updated weights for policy 0, policy_version 31073 (0.0006) +[2026-07-22 23:10:30,182][543983] Updated weights for policy 0, policy_version 31083 (0.0006) +[2026-07-22 23:10:30,462][543983] Updated weights for policy 0, policy_version 31093 (0.0006) +[2026-07-22 23:10:31,546][543983] Updated weights for policy 0, policy_version 31104 (0.0006) +[2026-07-22 23:10:31,813][543983] Updated weights for policy 0, policy_version 31114 (0.0006) +[2026-07-22 23:10:32,092][543983] Updated weights for policy 0, policy_version 31124 (0.0006) +[2026-07-22 23:10:32,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 15925248. Throughput: 0: 12834.1. Samples: 15963520. Policy #0 lag: (min: 39.0, avg: 54.8, max: 103.0) +[2026-07-22 23:10:32,287][543203] Avg episode reward: [(0, '1157.188')] +[2026-07-22 23:10:32,400][543983] Updated weights for policy 0, policy_version 31134 (0.0006) +[2026-07-22 23:10:32,693][543983] Updated weights for policy 0, policy_version 31145 (0.0007) +[2026-07-22 23:10:32,965][543983] Updated weights for policy 0, policy_version 31155 (0.0006) +[2026-07-22 23:10:34,017][543983] Updated weights for policy 0, policy_version 31165 (0.0006) +[2026-07-22 23:10:34,304][543983] Updated weights for policy 0, policy_version 31175 (0.0006) +[2026-07-22 23:10:34,595][543983] Updated weights for policy 0, policy_version 31185 (0.0006) +[2026-07-22 23:10:34,858][543983] Updated weights for policy 0, policy_version 31195 (0.0006) +[2026-07-22 23:10:35,155][543983] Updated weights for policy 0, policy_version 31205 (0.0006) +[2026-07-22 23:10:35,458][543983] Updated weights for policy 0, policy_version 31216 (0.0006) +[2026-07-22 23:10:36,533][543983] Updated weights for policy 0, policy_version 31226 (0.0006) +[2026-07-22 23:10:36,842][543983] Updated weights for policy 0, policy_version 31237 (0.0006) +[2026-07-22 23:10:37,151][543983] Updated weights for policy 0, policy_version 31248 (0.0007) +[2026-07-22 23:10:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 15990784. Throughput: 0: 12669.2. Samples: 15999744. Policy #0 lag: (min: 39.0, avg: 54.8, max: 103.0) +[2026-07-22 23:10:37,287][543203] Avg episode reward: [(0, '1149.323')] +[2026-07-22 23:10:37,455][543983] Updated weights for policy 0, policy_version 31258 (0.0007) +[2026-07-22 23:10:37,738][543983] Updated weights for policy 0, policy_version 31268 (0.0006) +[2026-07-22 23:10:38,004][543983] Updated weights for policy 0, policy_version 31278 (0.0006) +[2026-07-22 23:10:39,098][543983] Updated weights for policy 0, policy_version 31290 (0.0007) +[2026-07-22 23:10:39,384][543983] Updated weights for policy 0, policy_version 31300 (0.0006) +[2026-07-22 23:10:39,672][543983] Updated weights for policy 0, policy_version 31310 (0.0006) +[2026-07-22 23:10:39,947][543983] Updated weights for policy 0, policy_version 31320 (0.0006) +[2026-07-22 23:10:40,290][543983] Updated weights for policy 0, policy_version 31332 (0.0006) +[2026-07-22 23:10:40,605][543983] Updated weights for policy 0, policy_version 31343 (0.0006) +[2026-07-22 23:10:41,672][543983] Updated weights for policy 0, policy_version 31354 (0.0006) +[2026-07-22 23:10:41,979][543983] Updated weights for policy 0, policy_version 31364 (0.0006) +[2026-07-22 23:10:42,251][543983] Updated weights for policy 0, policy_version 31374 (0.0006) +[2026-07-22 23:10:42,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 16056320. Throughput: 0: 12595.2. Samples: 16072192. Policy #0 lag: (min: 39.0, avg: 54.8, max: 103.0) +[2026-07-22 23:10:42,287][543203] Avg episode reward: [(0, '1168.429')] +[2026-07-22 23:10:42,534][543983] Updated weights for policy 0, policy_version 31384 (0.0006) +[2026-07-22 23:10:42,809][543983] Updated weights for policy 0, policy_version 31394 (0.0006) +[2026-07-22 23:10:43,097][543983] Updated weights for policy 0, policy_version 31404 (0.0006) +[2026-07-22 23:10:43,419][543983] Updated weights for policy 0, policy_version 31415 (0.0006) +[2026-07-22 23:10:44,542][543983] Updated weights for policy 0, policy_version 31429 (0.0006) +[2026-07-22 23:10:44,827][543983] Updated weights for policy 0, policy_version 31439 (0.0007) +[2026-07-22 23:10:45,112][543983] Updated weights for policy 0, policy_version 31449 (0.0006) +[2026-07-22 23:10:45,401][543983] Updated weights for policy 0, policy_version 31459 (0.0006) +[2026-07-22 23:10:45,740][543983] Updated weights for policy 0, policy_version 31471 (0.0006) +[2026-07-22 23:10:46,798][543983] Updated weights for policy 0, policy_version 31481 (0.0006) +[2026-07-22 23:10:47,095][543983] Updated weights for policy 0, policy_version 31491 (0.0006) +[2026-07-22 23:10:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 16121856. Throughput: 0: 12859.7. Samples: 16156416. Policy #0 lag: (min: 39.0, avg: 54.8, max: 103.0) +[2026-07-22 23:10:47,287][543203] Avg episode reward: [(0, '1178.009')] +[2026-07-22 23:10:47,368][543983] Updated weights for policy 0, policy_version 31501 (0.0006) +[2026-07-22 23:10:47,710][543983] Updated weights for policy 0, policy_version 31513 (0.0006) +[2026-07-22 23:10:47,979][543983] Updated weights for policy 0, policy_version 31523 (0.0006) +[2026-07-22 23:10:48,264][543983] Updated weights for policy 0, policy_version 31533 (0.0006) +[2026-07-22 23:10:48,565][543983] Updated weights for policy 0, policy_version 31544 (0.0006) +[2026-07-22 23:10:49,610][543983] Updated weights for policy 0, policy_version 31554 (0.0006) +[2026-07-22 23:10:49,904][543983] Updated weights for policy 0, policy_version 31564 (0.0006) +[2026-07-22 23:10:50,199][543983] Updated weights for policy 0, policy_version 31575 (0.0006) +[2026-07-22 23:10:50,544][543983] Updated weights for policy 0, policy_version 31587 (0.0006) +[2026-07-22 23:10:50,844][543983] Updated weights for policy 0, policy_version 31597 (0.0006) +[2026-07-22 23:10:51,141][543983] Updated weights for policy 0, policy_version 31608 (0.0006) +[2026-07-22 23:10:52,195][543983] Updated weights for policy 0, policy_version 31618 (0.0006) +[2026-07-22 23:10:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 16187392. Throughput: 0: 12856.9. Samples: 16192640. Policy #0 lag: (min: 39.0, avg: 54.8, max: 103.0) +[2026-07-22 23:10:52,287][543203] Avg episode reward: [(0, '1171.123')] +[2026-07-22 23:10:52,493][543983] Updated weights for policy 0, policy_version 31628 (0.0006) +[2026-07-22 23:10:52,770][543983] Updated weights for policy 0, policy_version 31638 (0.0006) +[2026-07-22 23:10:53,069][543983] Updated weights for policy 0, policy_version 31648 (0.0006) +[2026-07-22 23:10:53,371][543983] Updated weights for policy 0, policy_version 31659 (0.0006) +[2026-07-22 23:10:53,660][543983] Updated weights for policy 0, policy_version 31669 (0.0006) +[2026-07-22 23:10:54,693][543983] Updated weights for policy 0, policy_version 31679 (0.0007) +[2026-07-22 23:10:54,980][543983] Updated weights for policy 0, policy_version 31689 (0.0007) +[2026-07-22 23:10:55,260][543983] Updated weights for policy 0, policy_version 31699 (0.0006) +[2026-07-22 23:10:55,559][543983] Updated weights for policy 0, policy_version 31710 (0.0006) +[2026-07-22 23:10:55,852][543983] Updated weights for policy 0, policy_version 31720 (0.0006) +[2026-07-22 23:10:56,168][543983] Updated weights for policy 0, policy_version 31731 (0.0006) +[2026-07-22 23:10:57,208][543983] Updated weights for policy 0, policy_version 31741 (0.0006) +[2026-07-22 23:10:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 16252928. Throughput: 0: 12583.8. Samples: 16264576. Policy #0 lag: (min: 18.0, avg: 38.1, max: 82.0) +[2026-07-22 23:10:57,287][543203] Avg episode reward: [(0, '1169.235')] +[2026-07-22 23:10:57,501][543983] Updated weights for policy 0, policy_version 31751 (0.0006) +[2026-07-22 23:10:57,779][543983] Updated weights for policy 0, policy_version 31761 (0.0006) +[2026-07-22 23:10:58,092][543983] Updated weights for policy 0, policy_version 31772 (0.0007) +[2026-07-22 23:10:58,412][543983] Updated weights for policy 0, policy_version 31783 (0.0007) +[2026-07-22 23:10:58,682][543983] Updated weights for policy 0, policy_version 31793 (0.0006) +[2026-07-22 23:10:59,733][543983] Updated weights for policy 0, policy_version 31804 (0.0006) +[2026-07-22 23:11:00,061][543983] Updated weights for policy 0, policy_version 31815 (0.0006) +[2026-07-22 23:11:00,341][543983] Updated weights for policy 0, policy_version 31825 (0.0006) +[2026-07-22 23:11:00,619][543983] Updated weights for policy 0, policy_version 31835 (0.0006) +[2026-07-22 23:11:00,907][543983] Updated weights for policy 0, policy_version 31845 (0.0006) +[2026-07-22 23:11:01,179][543983] Updated weights for policy 0, policy_version 31855 (0.0006) +[2026-07-22 23:11:02,275][543983] Updated weights for policy 0, policy_version 31866 (0.0006) +[2026-07-22 23:11:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 16318464. Throughput: 0: 12691.9. Samples: 16341504. Policy #0 lag: (min: 18.0, avg: 38.1, max: 82.0) +[2026-07-22 23:11:02,287][543203] Avg episode reward: [(0, '1176.949')] +[2026-07-22 23:11:02,594][543983] Updated weights for policy 0, policy_version 31877 (0.0006) +[2026-07-22 23:11:02,854][543983] Updated weights for policy 0, policy_version 31887 (0.0006) +[2026-07-22 23:11:03,141][543983] Updated weights for policy 0, policy_version 31897 (0.0006) +[2026-07-22 23:11:03,417][543983] Updated weights for policy 0, policy_version 31907 (0.0006) +[2026-07-22 23:11:03,714][543983] Updated weights for policy 0, policy_version 31917 (0.0006) +[2026-07-22 23:11:04,000][543983] Updated weights for policy 0, policy_version 31927 (0.0006) +[2026-07-22 23:11:05,098][543983] Updated weights for policy 0, policy_version 31939 (0.0007) +[2026-07-22 23:11:05,396][543983] Updated weights for policy 0, policy_version 31949 (0.0007) +[2026-07-22 23:11:05,677][543983] Updated weights for policy 0, policy_version 31959 (0.0009) +[2026-07-22 23:11:05,997][543983] Updated weights for policy 0, policy_version 31970 (0.0007) +[2026-07-22 23:11:06,309][543983] Updated weights for policy 0, policy_version 31981 (0.0007) +[2026-07-22 23:11:06,594][543983] Updated weights for policy 0, policy_version 31991 (0.0007) +[2026-07-22 23:11:07,287][543203] Fps is (10 sec: 13107.0, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 16384000. Throughput: 0: 12859.7. Samples: 16385408. Policy #0 lag: (min: 18.0, avg: 38.1, max: 82.0) +[2026-07-22 23:11:07,287][543203] Avg episode reward: [(0, '1173.606')] +[2026-07-22 23:11:07,653][543983] Updated weights for policy 0, policy_version 32001 (0.0008) +[2026-07-22 23:11:07,942][543983] Updated weights for policy 0, policy_version 32011 (0.0007) +[2026-07-22 23:11:08,222][543983] Updated weights for policy 0, policy_version 32021 (0.0006) +[2026-07-22 23:11:08,508][543983] Updated weights for policy 0, policy_version 32031 (0.0006) +[2026-07-22 23:11:08,793][543983] Updated weights for policy 0, policy_version 32041 (0.0006) +[2026-07-22 23:11:09,077][543983] Updated weights for policy 0, policy_version 32051 (0.0006) +[2026-07-22 23:11:10,145][543983] Updated weights for policy 0, policy_version 32063 (0.0007) +[2026-07-22 23:11:10,466][543983] Updated weights for policy 0, policy_version 32074 (0.0006) +[2026-07-22 23:11:10,730][543983] Updated weights for policy 0, policy_version 32084 (0.0006) +[2026-07-22 23:11:11,020][543983] Updated weights for policy 0, policy_version 32094 (0.0006) +[2026-07-22 23:11:11,303][543983] Updated weights for policy 0, policy_version 32104 (0.0006) +[2026-07-22 23:11:11,584][543983] Updated weights for policy 0, policy_version 32114 (0.0006) +[2026-07-22 23:11:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 16449536. Throughput: 0: 12709.0. Samples: 16456960. Policy #0 lag: (min: 18.0, avg: 38.1, max: 82.0) +[2026-07-22 23:11:12,287][543203] Avg episode reward: [(0, '1170.257')] +[2026-07-22 23:11:12,667][543983] Updated weights for policy 0, policy_version 32124 (0.0006) +[2026-07-22 23:11:12,958][543983] Updated weights for policy 0, policy_version 32134 (0.0006) +[2026-07-22 23:11:13,264][543983] Updated weights for policy 0, policy_version 32145 (0.0006) +[2026-07-22 23:11:13,567][543983] Updated weights for policy 0, policy_version 32156 (0.0006) +[2026-07-22 23:11:13,890][543983] Updated weights for policy 0, policy_version 32167 (0.0006) +[2026-07-22 23:11:14,176][543983] Updated weights for policy 0, policy_version 32177 (0.0006) +[2026-07-22 23:11:15,223][543983] Updated weights for policy 0, policy_version 32187 (0.0006) +[2026-07-22 23:11:15,520][543983] Updated weights for policy 0, policy_version 32198 (0.0006) +[2026-07-22 23:11:15,816][543983] Updated weights for policy 0, policy_version 32208 (0.0006) +[2026-07-22 23:11:16,091][543983] Updated weights for policy 0, policy_version 32218 (0.0006) +[2026-07-22 23:11:16,378][543983] Updated weights for policy 0, policy_version 32228 (0.0006) +[2026-07-22 23:11:16,657][543983] Updated weights for policy 0, policy_version 32238 (0.0006) +[2026-07-22 23:11:16,951][543983] Updated weights for policy 0, policy_version 32248 (0.0007) +[2026-07-22 23:11:17,286][543203] Fps is (10 sec: 13107.4, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 16515072. Throughput: 0: 12586.7. Samples: 16529920. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:11:17,287][543203] Avg episode reward: [(0, '1191.854')] +[2026-07-22 23:11:17,996][543983] Updated weights for policy 0, policy_version 32258 (0.0007) +[2026-07-22 23:11:18,289][543983] Updated weights for policy 0, policy_version 32268 (0.0007) +[2026-07-22 23:11:18,571][543983] Updated weights for policy 0, policy_version 32278 (0.0006) +[2026-07-22 23:11:18,883][543983] Updated weights for policy 0, policy_version 32289 (0.0007) +[2026-07-22 23:11:19,158][543983] Updated weights for policy 0, policy_version 32299 (0.0007) +[2026-07-22 23:11:19,438][543983] Updated weights for policy 0, policy_version 32309 (0.0006) +[2026-07-22 23:11:20,499][543983] Updated weights for policy 0, policy_version 32319 (0.0006) +[2026-07-22 23:11:20,784][543983] Updated weights for policy 0, policy_version 32329 (0.0006) +[2026-07-22 23:11:21,069][543983] Updated weights for policy 0, policy_version 32339 (0.0006) +[2026-07-22 23:11:21,351][543983] Updated weights for policy 0, policy_version 32349 (0.0006) +[2026-07-22 23:11:21,647][543983] Updated weights for policy 0, policy_version 32359 (0.0006) +[2026-07-22 23:11:21,962][543983] Updated weights for policy 0, policy_version 32370 (0.0006) +[2026-07-22 23:11:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 16580608. Throughput: 0: 12666.3. Samples: 16569728. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:11:22,287][543203] Avg episode reward: [(0, '1182.671')] +[2026-07-22 23:11:23,004][543983] Updated weights for policy 0, policy_version 32380 (0.0006) +[2026-07-22 23:11:23,279][543983] Updated weights for policy 0, policy_version 32390 (0.0006) +[2026-07-22 23:11:23,604][543983] Updated weights for policy 0, policy_version 32401 (0.0007) +[2026-07-22 23:11:23,880][543983] Updated weights for policy 0, policy_version 32411 (0.0006) +[2026-07-22 23:11:24,176][543983] Updated weights for policy 0, policy_version 32421 (0.0006) +[2026-07-22 23:11:24,444][543983] Updated weights for policy 0, policy_version 32431 (0.0006) +[2026-07-22 23:11:25,497][543983] Updated weights for policy 0, policy_version 32441 (0.0006) +[2026-07-22 23:11:25,807][543983] Updated weights for policy 0, policy_version 32452 (0.0006) +[2026-07-22 23:11:26,080][543983] Updated weights for policy 0, policy_version 32462 (0.0006) +[2026-07-22 23:11:26,360][543983] Updated weights for policy 0, policy_version 32472 (0.0006) +[2026-07-22 23:11:26,677][543983] Updated weights for policy 0, policy_version 32483 (0.0006) +[2026-07-22 23:11:27,017][543983] Updated weights for policy 0, policy_version 32495 (0.0006) +[2026-07-22 23:11:27,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 16646144. Throughput: 0: 12859.7. Samples: 16650880. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:11:27,287][543203] Avg episode reward: [(0, '1175.780')] +[2026-07-22 23:11:28,074][543983] Updated weights for policy 0, policy_version 32505 (0.0006) +[2026-07-22 23:11:28,394][543983] Updated weights for policy 0, policy_version 32516 (0.0007) +[2026-07-22 23:11:28,687][543983] Updated weights for policy 0, policy_version 32526 (0.0006) +[2026-07-22 23:11:28,960][543983] Updated weights for policy 0, policy_version 32536 (0.0006) +[2026-07-22 23:11:29,246][543983] Updated weights for policy 0, policy_version 32546 (0.0006) +[2026-07-22 23:11:29,534][543983] Updated weights for policy 0, policy_version 32556 (0.0006) +[2026-07-22 23:11:29,844][543983] Updated weights for policy 0, policy_version 32567 (0.0006) +[2026-07-22 23:11:30,880][543983] Updated weights for policy 0, policy_version 32577 (0.0006) +[2026-07-22 23:11:31,168][543983] Updated weights for policy 0, policy_version 32587 (0.0006) +[2026-07-22 23:11:31,490][543983] Updated weights for policy 0, policy_version 32598 (0.0007) +[2026-07-22 23:11:31,800][543983] Updated weights for policy 0, policy_version 32609 (0.0007) +[2026-07-22 23:11:32,078][543983] Updated weights for policy 0, policy_version 32619 (0.0007) +[2026-07-22 23:11:32,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 16678912. Throughput: 0: 12598.0. Samples: 16723328. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:11:32,287][543203] Avg episode reward: [(0, '1186.593')] +[2026-07-22 23:11:32,364][543983] Updated weights for policy 0, policy_version 32629 (0.0007) +[2026-07-22 23:11:33,376][543983] Updated weights for policy 0, policy_version 32639 (0.0007) +[2026-07-22 23:11:33,677][543983] Updated weights for policy 0, policy_version 32649 (0.0007) +[2026-07-22 23:11:33,967][543983] Updated weights for policy 0, policy_version 32659 (0.0006) +[2026-07-22 23:11:34,239][543983] Updated weights for policy 0, policy_version 32669 (0.0007) +[2026-07-22 23:11:34,520][543983] Updated weights for policy 0, policy_version 32679 (0.0006) +[2026-07-22 23:11:34,826][543983] Updated weights for policy 0, policy_version 32690 (0.0007) +[2026-07-22 23:11:35,938][543983] Updated weights for policy 0, policy_version 32701 (0.0006) +[2026-07-22 23:11:36,210][543983] Updated weights for policy 0, policy_version 32711 (0.0006) +[2026-07-22 23:11:36,510][543983] Updated weights for policy 0, policy_version 32721 (0.0006) +[2026-07-22 23:11:36,794][543983] Updated weights for policy 0, policy_version 32731 (0.0007) +[2026-07-22 23:11:37,105][543983] Updated weights for policy 0, policy_version 32742 (0.0006) +[2026-07-22 23:11:37,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 16744448. Throughput: 0: 12586.7. Samples: 16759040. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:11:37,287][543203] Avg episode reward: [(0, '1235.469')] +[2026-07-22 23:11:37,378][543983] Updated weights for policy 0, policy_version 32752 (0.0006) +[2026-07-22 23:11:37,603][543696] Saving new best policy, reward=1235.469! +[2026-07-22 23:11:38,467][543983] Updated weights for policy 0, policy_version 32763 (0.0006) +[2026-07-22 23:11:38,736][543983] Updated weights for policy 0, policy_version 32773 (0.0006) +[2026-07-22 23:11:39,044][543983] Updated weights for policy 0, policy_version 32784 (0.0006) +[2026-07-22 23:11:39,331][543983] Updated weights for policy 0, policy_version 32794 (0.0006) +[2026-07-22 23:11:39,619][543983] Updated weights for policy 0, policy_version 32804 (0.0006) +[2026-07-22 23:11:39,922][543983] Updated weights for policy 0, policy_version 32814 (0.0006) +[2026-07-22 23:11:40,983][543983] Updated weights for policy 0, policy_version 32825 (0.0006) +[2026-07-22 23:11:41,319][543983] Updated weights for policy 0, policy_version 32837 (0.0007) +[2026-07-22 23:11:41,636][543983] Updated weights for policy 0, policy_version 32848 (0.0007) +[2026-07-22 23:11:41,953][543983] Updated weights for policy 0, policy_version 32859 (0.0006) +[2026-07-22 23:11:42,240][543983] Updated weights for policy 0, policy_version 32869 (0.0007) +[2026-07-22 23:11:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 16809984. Throughput: 0: 12839.8. Samples: 16842368. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:11:42,287][543203] Avg episode reward: [(0, '1207.289')] +[2026-07-22 23:11:42,511][543983] Updated weights for policy 0, policy_version 32879 (0.0006) +[2026-07-22 23:11:43,611][543983] Updated weights for policy 0, policy_version 32890 (0.0006) +[2026-07-22 23:11:43,902][543983] Updated weights for policy 0, policy_version 32900 (0.0006) +[2026-07-22 23:11:44,202][543983] Updated weights for policy 0, policy_version 32911 (0.0006) +[2026-07-22 23:11:44,498][543983] Updated weights for policy 0, policy_version 32921 (0.0006) +[2026-07-22 23:11:44,788][543983] Updated weights for policy 0, policy_version 32931 (0.0006) +[2026-07-22 23:11:45,052][543983] Updated weights for policy 0, policy_version 32941 (0.0006) +[2026-07-22 23:11:45,328][543983] Updated weights for policy 0, policy_version 32951 (0.0007) +[2026-07-22 23:11:46,402][543983] Updated weights for policy 0, policy_version 32961 (0.0007) +[2026-07-22 23:11:46,687][543983] Updated weights for policy 0, policy_version 32971 (0.0006) +[2026-07-22 23:11:46,966][543983] Updated weights for policy 0, policy_version 32981 (0.0007) +[2026-07-22 23:11:47,249][543983] Updated weights for policy 0, policy_version 32991 (0.0006) +[2026-07-22 23:11:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 16875520. Throughput: 0: 12797.2. Samples: 16917376. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:11:47,287][543203] Avg episode reward: [(0, '1232.095')] +[2026-07-22 23:11:47,575][543983] Updated weights for policy 0, policy_version 33003 (0.0006) +[2026-07-22 23:11:47,878][543983] Updated weights for policy 0, policy_version 33013 (0.0006) +[2026-07-22 23:11:48,910][543983] Updated weights for policy 0, policy_version 33023 (0.0006) +[2026-07-22 23:11:49,218][543983] Updated weights for policy 0, policy_version 33033 (0.0007) +[2026-07-22 23:11:49,506][543983] Updated weights for policy 0, policy_version 33044 (0.0006) +[2026-07-22 23:11:49,797][543983] Updated weights for policy 0, policy_version 33054 (0.0006) +[2026-07-22 23:11:50,095][543983] Updated weights for policy 0, policy_version 33064 (0.0006) +[2026-07-22 23:11:50,381][543983] Updated weights for policy 0, policy_version 33074 (0.0006) +[2026-07-22 23:11:51,441][543983] Updated weights for policy 0, policy_version 33085 (0.0007) +[2026-07-22 23:11:51,804][543983] Updated weights for policy 0, policy_version 33098 (0.0006) +[2026-07-22 23:11:52,108][543983] Updated weights for policy 0, policy_version 33108 (0.0007) +[2026-07-22 23:11:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 16941056. Throughput: 0: 12626.5. Samples: 16953600. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:11:52,287][543203] Avg episode reward: [(0, '1231.240')] +[2026-07-22 23:11:52,405][543983] Updated weights for policy 0, policy_version 33119 (0.0006) +[2026-07-22 23:11:52,705][543983] Updated weights for policy 0, policy_version 33130 (0.0007) +[2026-07-22 23:11:53,010][543983] Updated weights for policy 0, policy_version 33140 (0.0006) +[2026-07-22 23:11:54,090][543983] Updated weights for policy 0, policy_version 33151 (0.0006) +[2026-07-22 23:11:54,378][543983] Updated weights for policy 0, policy_version 33161 (0.0007) +[2026-07-22 23:11:54,674][543983] Updated weights for policy 0, policy_version 33172 (0.0006) +[2026-07-22 23:11:54,966][543983] Updated weights for policy 0, policy_version 33182 (0.0007) +[2026-07-22 23:11:55,253][543983] Updated weights for policy 0, policy_version 33192 (0.0006) +[2026-07-22 23:11:55,521][543983] Updated weights for policy 0, policy_version 33202 (0.0006) +[2026-07-22 23:11:56,620][543983] Updated weights for policy 0, policy_version 33213 (0.0006) +[2026-07-22 23:11:56,955][543983] Updated weights for policy 0, policy_version 33225 (0.0006) +[2026-07-22 23:11:57,234][543983] Updated weights for policy 0, policy_version 33235 (0.0006) +[2026-07-22 23:11:57,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 17006592. Throughput: 0: 12637.8. Samples: 17025664. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:11:57,287][543203] Avg episode reward: [(0, '1254.202')] +[2026-07-22 23:11:57,547][543983] Updated weights for policy 0, policy_version 33246 (0.0007) +[2026-07-22 23:11:57,828][543983] Updated weights for policy 0, policy_version 33256 (0.0007) +[2026-07-22 23:11:58,138][543983] Updated weights for policy 0, policy_version 33266 (0.0007) +[2026-07-22 23:11:58,280][543696] Saving new best policy, reward=1254.202! +[2026-07-22 23:11:59,253][543983] Updated weights for policy 0, policy_version 33279 (0.0006) +[2026-07-22 23:11:59,550][543983] Updated weights for policy 0, policy_version 33289 (0.0006) +[2026-07-22 23:11:59,853][543983] Updated weights for policy 0, policy_version 33300 (0.0006) +[2026-07-22 23:12:00,142][543983] Updated weights for policy 0, policy_version 33310 (0.0007) +[2026-07-22 23:12:00,419][543983] Updated weights for policy 0, policy_version 33320 (0.0007) +[2026-07-22 23:12:00,700][543983] Updated weights for policy 0, policy_version 33330 (0.0006) +[2026-07-22 23:12:01,780][543983] Updated weights for policy 0, policy_version 33341 (0.0006) +[2026-07-22 23:12:02,115][543983] Updated weights for policy 0, policy_version 33353 (0.0006) +[2026-07-22 23:12:02,286][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 17072128. Throughput: 0: 12905.2. Samples: 17110656. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:12:02,287][543203] Avg episode reward: [(0, '1227.836')] +[2026-07-22 23:12:02,407][543983] Updated weights for policy 0, policy_version 33363 (0.0006) +[2026-07-22 23:12:02,711][543983] Updated weights for policy 0, policy_version 33373 (0.0006) +[2026-07-22 23:12:03,020][543983] Updated weights for policy 0, policy_version 33384 (0.0006) +[2026-07-22 23:12:03,310][543983] Updated weights for policy 0, policy_version 33394 (0.0007) +[2026-07-22 23:12:04,363][543983] Updated weights for policy 0, policy_version 33404 (0.0007) +[2026-07-22 23:12:04,636][543983] Updated weights for policy 0, policy_version 33414 (0.0006) +[2026-07-22 23:12:04,925][543983] Updated weights for policy 0, policy_version 33424 (0.0006) +[2026-07-22 23:12:05,245][543983] Updated weights for policy 0, policy_version 33435 (0.0006) +[2026-07-22 23:12:05,535][543983] Updated weights for policy 0, policy_version 33445 (0.0007) +[2026-07-22 23:12:05,822][543983] Updated weights for policy 0, policy_version 33456 (0.0006) +[2026-07-22 23:12:06,913][543983] Updated weights for policy 0, policy_version 33466 (0.0006) +[2026-07-22 23:12:07,222][543983] Updated weights for policy 0, policy_version 33477 (0.0006) +[2026-07-22 23:12:07,287][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 17137664. Throughput: 0: 12828.4. Samples: 17147008. Policy #0 lag: (min: 30.0, avg: 46.3, max: 94.0) +[2026-07-22 23:12:07,287][543203] Avg episode reward: [(0, '1265.103')] +[2026-07-22 23:12:07,485][543983] Updated weights for policy 0, policy_version 33487 (0.0006) +[2026-07-22 23:12:07,783][543983] Updated weights for policy 0, policy_version 33497 (0.0006) +[2026-07-22 23:12:08,097][543983] Updated weights for policy 0, policy_version 33508 (0.0006) +[2026-07-22 23:12:08,381][543983] Updated weights for policy 0, policy_version 33518 (0.0007) +[2026-07-22 23:12:08,656][543696] Saving new best policy, reward=1265.103! +[2026-07-22 23:12:08,658][543983] Updated weights for policy 0, policy_version 33528 (0.0007) +[2026-07-22 23:12:09,739][543983] Updated weights for policy 0, policy_version 33538 (0.0008) +[2026-07-22 23:12:10,027][543983] Updated weights for policy 0, policy_version 33548 (0.0006) +[2026-07-22 23:12:10,332][543983] Updated weights for policy 0, policy_version 33559 (0.0008) +[2026-07-22 23:12:10,644][543983] Updated weights for policy 0, policy_version 33570 (0.0007) +[2026-07-22 23:12:10,917][543983] Updated weights for policy 0, policy_version 33580 (0.0006) +[2026-07-22 23:12:11,208][543983] Updated weights for policy 0, policy_version 33590 (0.0006) +[2026-07-22 23:12:12,257][543983] Updated weights for policy 0, policy_version 33600 (0.0006) +[2026-07-22 23:12:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 17203200. Throughput: 0: 12654.9. Samples: 17220352. Policy #0 lag: (min: 30.0, avg: 46.3, max: 94.0) +[2026-07-22 23:12:12,287][543203] Avg episode reward: [(0, '1272.790')] +[2026-07-22 23:12:12,538][543983] Updated weights for policy 0, policy_version 33610 (0.0007) +[2026-07-22 23:12:12,835][543983] Updated weights for policy 0, policy_version 33621 (0.0007) +[2026-07-22 23:12:13,130][543983] Updated weights for policy 0, policy_version 33631 (0.0007) +[2026-07-22 23:12:13,407][543983] Updated weights for policy 0, policy_version 33641 (0.0007) +[2026-07-22 23:12:13,683][543983] Updated weights for policy 0, policy_version 33651 (0.0006) +[2026-07-22 23:12:13,817][543696] Saving new best policy, reward=1272.790! +[2026-07-22 23:12:14,774][543983] Updated weights for policy 0, policy_version 33662 (0.0007) +[2026-07-22 23:12:15,056][543983] Updated weights for policy 0, policy_version 33672 (0.0006) +[2026-07-22 23:12:15,329][543983] Updated weights for policy 0, policy_version 33682 (0.0007) +[2026-07-22 23:12:15,626][543983] Updated weights for policy 0, policy_version 33692 (0.0006) +[2026-07-22 23:12:15,910][543983] Updated weights for policy 0, policy_version 33702 (0.0006) +[2026-07-22 23:12:16,190][543983] Updated weights for policy 0, policy_version 33712 (0.0006) +[2026-07-22 23:12:17,238][543983] Updated weights for policy 0, policy_version 33722 (0.0007) +[2026-07-22 23:12:17,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 17268736. Throughput: 0: 12777.3. Samples: 17298304. Policy #0 lag: (min: 30.0, avg: 46.3, max: 94.0) +[2026-07-22 23:12:17,287][543203] Avg episode reward: [(0, '1292.237')] +[2026-07-22 23:12:17,514][543983] Updated weights for policy 0, policy_version 33732 (0.0006) +[2026-07-22 23:12:17,814][543983] Updated weights for policy 0, policy_version 33742 (0.0006) +[2026-07-22 23:12:18,093][543983] Updated weights for policy 0, policy_version 33752 (0.0006) +[2026-07-22 23:12:18,362][543983] Updated weights for policy 0, policy_version 33762 (0.0006) +[2026-07-22 23:12:18,649][543983] Updated weights for policy 0, policy_version 33772 (0.0006) +[2026-07-22 23:12:18,939][543983] Updated weights for policy 0, policy_version 33782 (0.0006) +[2026-07-22 23:12:18,983][543696] Saving new best policy, reward=1292.237! +[2026-07-22 23:12:20,025][543983] Updated weights for policy 0, policy_version 33793 (0.0006) +[2026-07-22 23:12:20,338][543983] Updated weights for policy 0, policy_version 33804 (0.0006) +[2026-07-22 23:12:20,632][543983] Updated weights for policy 0, policy_version 33814 (0.0006) +[2026-07-22 23:12:20,899][543983] Updated weights for policy 0, policy_version 33824 (0.0006) +[2026-07-22 23:12:21,193][543983] Updated weights for policy 0, policy_version 33834 (0.0007) +[2026-07-22 23:12:21,488][543983] Updated weights for policy 0, policy_version 33845 (0.0007) +[2026-07-22 23:12:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 17334272. Throughput: 0: 12945.1. Samples: 17341568. Policy #0 lag: (min: 30.0, avg: 46.3, max: 94.0) +[2026-07-22 23:12:22,287][543203] Avg episode reward: [(0, '1289.779')] +[2026-07-22 23:12:22,554][543983] Updated weights for policy 0, policy_version 33855 (0.0007) +[2026-07-22 23:12:22,837][543983] Updated weights for policy 0, policy_version 33865 (0.0006) +[2026-07-22 23:12:23,136][543983] Updated weights for policy 0, policy_version 33875 (0.0006) +[2026-07-22 23:12:23,444][543983] Updated weights for policy 0, policy_version 33886 (0.0006) +[2026-07-22 23:12:23,730][543983] Updated weights for policy 0, policy_version 33896 (0.0006) +[2026-07-22 23:12:24,007][543983] Updated weights for policy 0, policy_version 33906 (0.0007) +[2026-07-22 23:12:25,063][543983] Updated weights for policy 0, policy_version 33917 (0.0006) +[2026-07-22 23:12:25,369][543983] Updated weights for policy 0, policy_version 33927 (0.0006) +[2026-07-22 23:12:25,648][543983] Updated weights for policy 0, policy_version 33937 (0.0006) +[2026-07-22 23:12:25,975][543983] Updated weights for policy 0, policy_version 33948 (0.0006) +[2026-07-22 23:12:26,268][543983] Updated weights for policy 0, policy_version 33958 (0.0006) +[2026-07-22 23:12:26,567][543983] Updated weights for policy 0, policy_version 33969 (0.0006) +[2026-07-22 23:12:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 17399808. Throughput: 0: 12700.4. Samples: 17413888. Policy #0 lag: (min: 31.0, avg: 48.1, max: 95.0) +[2026-07-22 23:12:27,287][543203] Avg episode reward: [(0, '1281.710')] +[2026-07-22 23:12:27,633][543983] Updated weights for policy 0, policy_version 33980 (0.0007) +[2026-07-22 23:12:27,950][543983] Updated weights for policy 0, policy_version 33991 (0.0006) +[2026-07-22 23:12:28,270][543983] Updated weights for policy 0, policy_version 34002 (0.0006) +[2026-07-22 23:12:28,549][543983] Updated weights for policy 0, policy_version 34012 (0.0006) +[2026-07-22 23:12:28,829][543983] Updated weights for policy 0, policy_version 34022 (0.0006) +[2026-07-22 23:12:29,121][543983] Updated weights for policy 0, policy_version 34032 (0.0006) +[2026-07-22 23:12:30,175][543983] Updated weights for policy 0, policy_version 34042 (0.0006) +[2026-07-22 23:12:30,455][543983] Updated weights for policy 0, policy_version 34052 (0.0006) +[2026-07-22 23:12:30,745][543983] Updated weights for policy 0, policy_version 34062 (0.0007) +[2026-07-22 23:12:31,028][543983] Updated weights for policy 0, policy_version 34072 (0.0008) +[2026-07-22 23:12:31,309][543983] Updated weights for policy 0, policy_version 34082 (0.0008) +[2026-07-22 23:12:31,578][543983] Updated weights for policy 0, policy_version 34092 (0.0007) +[2026-07-22 23:12:31,868][543983] Updated weights for policy 0, policy_version 34102 (0.0007) +[2026-07-22 23:12:32,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 17465344. Throughput: 0: 12646.4. Samples: 17486464. Policy #0 lag: (min: 31.0, avg: 48.1, max: 95.0) +[2026-07-22 23:12:32,287][543203] Avg episode reward: [(0, '1261.953')] +[2026-07-22 23:12:32,935][543983] Updated weights for policy 0, policy_version 34112 (0.0007) +[2026-07-22 23:12:33,233][543983] Updated weights for policy 0, policy_version 34123 (0.0008) +[2026-07-22 23:12:33,535][543983] Updated weights for policy 0, policy_version 34133 (0.0007) +[2026-07-22 23:12:33,827][543983] Updated weights for policy 0, policy_version 34143 (0.0006) +[2026-07-22 23:12:34,135][543983] Updated weights for policy 0, policy_version 34154 (0.0006) +[2026-07-22 23:12:34,436][543983] Updated weights for policy 0, policy_version 34164 (0.0007) +[2026-07-22 23:12:35,475][543983] Updated weights for policy 0, policy_version 34174 (0.0006) +[2026-07-22 23:12:35,771][543983] Updated weights for policy 0, policy_version 34184 (0.0006) +[2026-07-22 23:12:36,041][543983] Updated weights for policy 0, policy_version 34194 (0.0006) +[2026-07-22 23:12:36,361][543983] Updated weights for policy 0, policy_version 34204 (0.0012) +[2026-07-22 23:12:36,691][543983] Updated weights for policy 0, policy_version 34215 (0.0012) +[2026-07-22 23:12:36,974][543983] Updated weights for policy 0, policy_version 34225 (0.0006) +[2026-07-22 23:12:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 17530880. Throughput: 0: 12723.2. Samples: 17526144. Policy #0 lag: (min: 31.0, avg: 48.1, max: 95.0) +[2026-07-22 23:12:37,287][543203] Avg episode reward: [(0, '1252.304')] +[2026-07-22 23:12:37,976][543983] Updated weights for policy 0, policy_version 34235 (0.0006) +[2026-07-22 23:12:38,279][543983] Updated weights for policy 0, policy_version 34246 (0.0006) +[2026-07-22 23:12:38,556][543983] Updated weights for policy 0, policy_version 34256 (0.0007) +[2026-07-22 23:12:38,883][543983] Updated weights for policy 0, policy_version 34267 (0.0008) +[2026-07-22 23:12:39,161][543983] Updated weights for policy 0, policy_version 34277 (0.0006) +[2026-07-22 23:12:39,451][543983] Updated weights for policy 0, policy_version 34287 (0.0006) +[2026-07-22 23:12:40,514][543983] Updated weights for policy 0, policy_version 34297 (0.0006) +[2026-07-22 23:12:40,804][543983] Updated weights for policy 0, policy_version 34307 (0.0007) +[2026-07-22 23:12:41,079][543983] Updated weights for policy 0, policy_version 34317 (0.0007) +[2026-07-22 23:12:41,369][543983] Updated weights for policy 0, policy_version 34327 (0.0008) +[2026-07-22 23:12:41,655][543983] Updated weights for policy 0, policy_version 34337 (0.0007) +[2026-07-22 23:12:41,940][543983] Updated weights for policy 0, policy_version 34347 (0.0007) +[2026-07-22 23:12:42,248][543983] Updated weights for policy 0, policy_version 34358 (0.0006) +[2026-07-22 23:12:42,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 17563648. Throughput: 0: 12922.3. Samples: 17607168. Policy #0 lag: (min: 31.0, avg: 48.1, max: 95.0) +[2026-07-22 23:12:42,287][543203] Avg episode reward: [(0, '1264.988')] +[2026-07-22 23:12:43,300][543983] Updated weights for policy 0, policy_version 34368 (0.0008) +[2026-07-22 23:12:43,583][543983] Updated weights for policy 0, policy_version 34378 (0.0008) +[2026-07-22 23:12:43,883][543983] Updated weights for policy 0, policy_version 34388 (0.0008) +[2026-07-22 23:12:44,174][543983] Updated weights for policy 0, policy_version 34398 (0.0009) +[2026-07-22 23:12:44,466][543983] Updated weights for policy 0, policy_version 34408 (0.0008) +[2026-07-22 23:12:44,785][543983] Updated weights for policy 0, policy_version 34419 (0.0009) +[2026-07-22 23:12:45,843][543983] Updated weights for policy 0, policy_version 34430 (0.0007) +[2026-07-22 23:12:46,142][543983] Updated weights for policy 0, policy_version 34441 (0.0008) +[2026-07-22 23:12:46,473][543983] Updated weights for policy 0, policy_version 34452 (0.0008) +[2026-07-22 23:12:46,751][543983] Updated weights for policy 0, policy_version 34462 (0.0007) +[2026-07-22 23:12:47,063][543983] Updated weights for policy 0, policy_version 34473 (0.0008) +[2026-07-22 23:12:47,289][543203] Fps is (10 sec: 9828.4, 60 sec: 12560.6, 300 sec: 12662.8). Total num frames: 17629184. Throughput: 0: 12651.5. Samples: 17680000. Policy #0 lag: (min: 31.0, avg: 48.1, max: 95.0) +[2026-07-22 23:12:47,289][543203] Avg episode reward: [(0, '1291.070')] +[2026-07-22 23:12:47,358][543983] Updated weights for policy 0, policy_version 34483 (0.0007) +[2026-07-22 23:12:48,446][543983] Updated weights for policy 0, policy_version 34493 (0.0007) +[2026-07-22 23:12:48,729][543983] Updated weights for policy 0, policy_version 34503 (0.0006) +[2026-07-22 23:12:49,044][543983] Updated weights for policy 0, policy_version 34514 (0.0006) +[2026-07-22 23:12:49,350][543983] Updated weights for policy 0, policy_version 34525 (0.0006) +[2026-07-22 23:12:49,649][543983] Updated weights for policy 0, policy_version 34535 (0.0006) +[2026-07-22 23:12:50,006][543983] Updated weights for policy 0, policy_version 34547 (0.0006) +[2026-07-22 23:12:51,022][543983] Updated weights for policy 0, policy_version 34557 (0.0006) +[2026-07-22 23:12:51,306][543983] Updated weights for policy 0, policy_version 34567 (0.0006) +[2026-07-22 23:12:51,584][543983] Updated weights for policy 0, policy_version 34577 (0.0006) +[2026-07-22 23:12:51,878][543983] Updated weights for policy 0, policy_version 34587 (0.0006) +[2026-07-22 23:12:52,191][543983] Updated weights for policy 0, policy_version 34598 (0.0006) +[2026-07-22 23:12:52,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 17694720. Throughput: 0: 12652.1. Samples: 17716352. Policy #0 lag: (min: 50.0, avg: 98.1, max: 113.0) +[2026-07-22 23:12:52,287][543203] Avg episode reward: [(0, '1279.857')] +[2026-07-22 23:12:52,472][543983] Updated weights for policy 0, policy_version 34608 (0.0006) +[2026-07-22 23:12:53,519][543983] Updated weights for policy 0, policy_version 34618 (0.0006) +[2026-07-22 23:12:53,838][543983] Updated weights for policy 0, policy_version 34629 (0.0006) +[2026-07-22 23:12:54,134][543983] Updated weights for policy 0, policy_version 34639 (0.0006) +[2026-07-22 23:12:54,401][543983] Updated weights for policy 0, policy_version 34649 (0.0006) +[2026-07-22 23:12:54,679][543983] Updated weights for policy 0, policy_version 34659 (0.0006) +[2026-07-22 23:12:54,989][543983] Updated weights for policy 0, policy_version 34670 (0.0007) +[2026-07-22 23:12:55,264][543983] Updated weights for policy 0, policy_version 34680 (0.0006) +[2026-07-22 23:12:56,397][543983] Updated weights for policy 0, policy_version 34692 (0.0006) +[2026-07-22 23:12:56,695][543983] Updated weights for policy 0, policy_version 34702 (0.0006) +[2026-07-22 23:12:56,972][543983] Updated weights for policy 0, policy_version 34712 (0.0006) +[2026-07-22 23:12:57,246][543983] Updated weights for policy 0, policy_version 34722 (0.0006) +[2026-07-22 23:12:57,286][543203] Fps is (10 sec: 13109.9, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 17760256. Throughput: 0: 12811.4. Samples: 17796864. Policy #0 lag: (min: 50.0, avg: 98.1, max: 113.0) +[2026-07-22 23:12:57,287][543203] Avg episode reward: [(0, '1296.079')] +[2026-07-22 23:12:57,540][543983] Updated weights for policy 0, policy_version 34732 (0.0007) +[2026-07-22 23:12:57,815][543983] Updated weights for policy 0, policy_version 34742 (0.0006) +[2026-07-22 23:12:57,866][543696] Saving new best policy, reward=1296.079! +[2026-07-22 23:12:58,866][543983] Updated weights for policy 0, policy_version 34752 (0.0007) +[2026-07-22 23:12:59,141][543983] Updated weights for policy 0, policy_version 34762 (0.0006) +[2026-07-22 23:12:59,436][543983] Updated weights for policy 0, policy_version 34772 (0.0006) +[2026-07-22 23:12:59,720][543983] Updated weights for policy 0, policy_version 34782 (0.0006) +[2026-07-22 23:12:59,987][543983] Updated weights for policy 0, policy_version 34792 (0.0006) +[2026-07-22 23:13:00,299][543983] Updated weights for policy 0, policy_version 34803 (0.0006) +[2026-07-22 23:13:01,382][543983] Updated weights for policy 0, policy_version 34813 (0.0006) +[2026-07-22 23:13:01,668][543983] Updated weights for policy 0, policy_version 34823 (0.0006) +[2026-07-22 23:13:01,945][543983] Updated weights for policy 0, policy_version 34833 (0.0007) +[2026-07-22 23:13:02,252][543983] Updated weights for policy 0, policy_version 34843 (0.0006) +[2026-07-22 23:13:02,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 17825792. Throughput: 0: 12791.5. Samples: 17873920. Policy #0 lag: (min: 50.0, avg: 98.1, max: 113.0) +[2026-07-22 23:13:02,287][543203] Avg episode reward: [(0, '1323.073')] +[2026-07-22 23:13:02,516][543983] Updated weights for policy 0, policy_version 34853 (0.0007) +[2026-07-22 23:13:02,839][543983] Updated weights for policy 0, policy_version 34864 (0.0007) +[2026-07-22 23:13:03,059][543696] Saving new best policy, reward=1323.073! +[2026-07-22 23:13:03,862][543983] Updated weights for policy 0, policy_version 34874 (0.0006) +[2026-07-22 23:13:04,145][543983] Updated weights for policy 0, policy_version 34884 (0.0007) +[2026-07-22 23:13:04,438][543983] Updated weights for policy 0, policy_version 34894 (0.0006) +[2026-07-22 23:13:04,713][543983] Updated weights for policy 0, policy_version 34904 (0.0006) +[2026-07-22 23:13:05,023][543983] Updated weights for policy 0, policy_version 34915 (0.0006) +[2026-07-22 23:13:05,344][543983] Updated weights for policy 0, policy_version 34926 (0.0006) +[2026-07-22 23:13:06,428][543983] Updated weights for policy 0, policy_version 34937 (0.0006) +[2026-07-22 23:13:06,725][543983] Updated weights for policy 0, policy_version 34947 (0.0006) +[2026-07-22 23:13:07,021][543983] Updated weights for policy 0, policy_version 34958 (0.0007) +[2026-07-22 23:13:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 17891328. Throughput: 0: 12626.5. Samples: 17909760. Policy #0 lag: (min: 50.0, avg: 98.1, max: 113.0) +[2026-07-22 23:13:07,287][543203] Avg episode reward: [(0, '1305.365')] +[2026-07-22 23:13:07,319][543983] Updated weights for policy 0, policy_version 34968 (0.0006) +[2026-07-22 23:13:07,597][543983] Updated weights for policy 0, policy_version 34978 (0.0007) +[2026-07-22 23:13:07,878][543983] Updated weights for policy 0, policy_version 34988 (0.0006) +[2026-07-22 23:13:08,187][543983] Updated weights for policy 0, policy_version 34999 (0.0007) +[2026-07-22 23:13:09,235][543983] Updated weights for policy 0, policy_version 35009 (0.0006) +[2026-07-22 23:13:09,528][543983] Updated weights for policy 0, policy_version 35019 (0.0007) +[2026-07-22 23:13:09,821][543983] Updated weights for policy 0, policy_version 35029 (0.0006) +[2026-07-22 23:13:10,107][543983] Updated weights for policy 0, policy_version 35039 (0.0007) +[2026-07-22 23:13:10,398][543983] Updated weights for policy 0, policy_version 35049 (0.0007) +[2026-07-22 23:13:10,685][543983] Updated weights for policy 0, policy_version 35059 (0.0006) +[2026-07-22 23:13:11,721][543983] Updated weights for policy 0, policy_version 35069 (0.0006) +[2026-07-22 23:13:12,023][543983] Updated weights for policy 0, policy_version 35080 (0.0006) +[2026-07-22 23:13:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 17956864. Throughput: 0: 12649.2. Samples: 17983104. Policy #0 lag: (min: 50.0, avg: 98.1, max: 113.0) +[2026-07-22 23:13:12,287][543203] Avg episode reward: [(0, '1326.226')] +[2026-07-22 23:13:12,370][543983] Updated weights for policy 0, policy_version 35092 (0.0006) +[2026-07-22 23:13:12,649][543983] Updated weights for policy 0, policy_version 35102 (0.0006) +[2026-07-22 23:13:12,967][543983] Updated weights for policy 0, policy_version 35113 (0.0006) +[2026-07-22 23:13:13,250][543983] Updated weights for policy 0, policy_version 35123 (0.0006) +[2026-07-22 23:13:13,381][543696] Saving new best policy, reward=1326.226! +[2026-07-22 23:13:14,324][543983] Updated weights for policy 0, policy_version 35134 (0.0006) +[2026-07-22 23:13:14,588][543983] Updated weights for policy 0, policy_version 35144 (0.0006) +[2026-07-22 23:13:14,858][543983] Updated weights for policy 0, policy_version 35154 (0.0006) +[2026-07-22 23:13:15,148][543983] Updated weights for policy 0, policy_version 35164 (0.0006) +[2026-07-22 23:13:15,424][543983] Updated weights for policy 0, policy_version 35174 (0.0006) +[2026-07-22 23:13:15,709][543983] Updated weights for policy 0, policy_version 35184 (0.0006) +[2026-07-22 23:13:16,778][543983] Updated weights for policy 0, policy_version 35194 (0.0006) +[2026-07-22 23:13:17,079][543983] Updated weights for policy 0, policy_version 35204 (0.0006) +[2026-07-22 23:13:17,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 18022400. Throughput: 0: 12905.2. Samples: 18067200. Policy #0 lag: (min: 63.0, avg: 79.8, max: 127.0) +[2026-07-22 23:13:17,287][543203] Avg episode reward: [(0, '1326.715')] +[2026-07-22 23:13:17,348][543983] Updated weights for policy 0, policy_version 35214 (0.0006) +[2026-07-22 23:13:17,670][543983] Updated weights for policy 0, policy_version 35225 (0.0007) +[2026-07-22 23:13:17,953][543983] Updated weights for policy 0, policy_version 35235 (0.0006) +[2026-07-22 23:13:18,243][543983] Updated weights for policy 0, policy_version 35245 (0.0006) +[2026-07-22 23:13:18,536][543696] Saving new best policy, reward=1326.715! +[2026-07-22 23:13:18,541][543983] Updated weights for policy 0, policy_version 35256 (0.0007) +[2026-07-22 23:13:19,592][543983] Updated weights for policy 0, policy_version 35266 (0.0007) +[2026-07-22 23:13:19,910][543983] Updated weights for policy 0, policy_version 35277 (0.0006) +[2026-07-22 23:13:20,197][543983] Updated weights for policy 0, policy_version 35287 (0.0007) +[2026-07-22 23:13:20,507][543983] Updated weights for policy 0, policy_version 35298 (0.0006) +[2026-07-22 23:13:20,794][543983] Updated weights for policy 0, policy_version 35308 (0.0007) +[2026-07-22 23:13:21,088][543983] Updated weights for policy 0, policy_version 35318 (0.0007) +[2026-07-22 23:13:22,137][543983] Updated weights for policy 0, policy_version 35328 (0.0006) +[2026-07-22 23:13:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 18087936. Throughput: 0: 12828.4. Samples: 18103424. Policy #0 lag: (min: 63.0, avg: 79.8, max: 127.0) +[2026-07-22 23:13:22,287][543203] Avg episode reward: [(0, '1312.046')] +[2026-07-22 23:13:22,422][543983] Updated weights for policy 0, policy_version 35338 (0.0006) +[2026-07-22 23:13:22,731][543983] Updated weights for policy 0, policy_version 35349 (0.0006) +[2026-07-22 23:13:23,010][543983] Updated weights for policy 0, policy_version 35359 (0.0006) +[2026-07-22 23:13:23,305][543983] Updated weights for policy 0, policy_version 35369 (0.0006) +[2026-07-22 23:13:23,598][543983] Updated weights for policy 0, policy_version 35379 (0.0006) +[2026-07-22 23:13:24,690][543983] Updated weights for policy 0, policy_version 35390 (0.0006) +[2026-07-22 23:13:24,959][543983] Updated weights for policy 0, policy_version 35400 (0.0006) +[2026-07-22 23:13:25,281][543983] Updated weights for policy 0, policy_version 35411 (0.0007) +[2026-07-22 23:13:25,588][543983] Updated weights for policy 0, policy_version 35422 (0.0006) +[2026-07-22 23:13:25,878][543983] Updated weights for policy 0, policy_version 35432 (0.0008) +[2026-07-22 23:13:26,181][543983] Updated weights for policy 0, policy_version 35443 (0.0006) +[2026-07-22 23:13:27,257][543983] Updated weights for policy 0, policy_version 35454 (0.0006) +[2026-07-22 23:13:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 18153472. Throughput: 0: 12649.2. Samples: 18176384. Policy #0 lag: (min: 63.0, avg: 79.8, max: 127.0) +[2026-07-22 23:13:27,287][543203] Avg episode reward: [(0, '1312.046')] +[2026-07-22 23:13:27,529][543983] Updated weights for policy 0, policy_version 35464 (0.0006) +[2026-07-22 23:13:27,831][543983] Updated weights for policy 0, policy_version 35474 (0.0006) +[2026-07-22 23:13:28,116][543983] Updated weights for policy 0, policy_version 35484 (0.0006) +[2026-07-22 23:13:28,456][543983] Updated weights for policy 0, policy_version 35496 (0.0007) +[2026-07-22 23:13:28,730][543983] Updated weights for policy 0, policy_version 35506 (0.0006) +[2026-07-22 23:13:29,784][543983] Updated weights for policy 0, policy_version 35516 (0.0006) +[2026-07-22 23:13:30,069][543983] Updated weights for policy 0, policy_version 35526 (0.0007) +[2026-07-22 23:13:30,346][543983] Updated weights for policy 0, policy_version 35536 (0.0006) +[2026-07-22 23:13:30,636][543983] Updated weights for policy 0, policy_version 35546 (0.0007) +[2026-07-22 23:13:30,946][543983] Updated weights for policy 0, policy_version 35557 (0.0006) +[2026-07-22 23:13:31,239][543983] Updated weights for policy 0, policy_version 35567 (0.0007) +[2026-07-22 23:13:32,281][543983] Updated weights for policy 0, policy_version 35577 (0.0006) +[2026-07-22 23:13:32,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 18219008. Throughput: 0: 12732.3. Samples: 18252928. Policy #0 lag: (min: 63.0, avg: 79.8, max: 127.0) +[2026-07-22 23:13:32,287][543203] Avg episode reward: [(0, '1339.709')] +[2026-07-22 23:13:32,565][543983] Updated weights for policy 0, policy_version 35587 (0.0006) +[2026-07-22 23:13:32,860][543983] Updated weights for policy 0, policy_version 35597 (0.0007) +[2026-07-22 23:13:33,132][543983] Updated weights for policy 0, policy_version 35607 (0.0006) +[2026-07-22 23:13:33,434][543983] Updated weights for policy 0, policy_version 35617 (0.0006) +[2026-07-22 23:13:33,736][543983] Updated weights for policy 0, policy_version 35628 (0.0006) +[2026-07-22 23:13:34,034][543983] Updated weights for policy 0, policy_version 35638 (0.0007) +[2026-07-22 23:13:34,076][543696] Saving new best policy, reward=1339.709! +[2026-07-22 23:13:35,066][543983] Updated weights for policy 0, policy_version 35648 (0.0007) +[2026-07-22 23:13:35,347][543983] Updated weights for policy 0, policy_version 35658 (0.0006) +[2026-07-22 23:13:35,620][543983] Updated weights for policy 0, policy_version 35668 (0.0006) +[2026-07-22 23:13:35,905][543983] Updated weights for policy 0, policy_version 35678 (0.0006) +[2026-07-22 23:13:36,191][543983] Updated weights for policy 0, policy_version 35688 (0.0006) +[2026-07-22 23:13:36,473][543983] Updated weights for policy 0, policy_version 35698 (0.0006) +[2026-07-22 23:13:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 18284544. Throughput: 0: 12908.1. Samples: 18297216. Policy #0 lag: (min: 63.0, avg: 79.8, max: 127.0) +[2026-07-22 23:13:37,287][543203] Avg episode reward: [(0, '1339.709')] +[2026-07-22 23:13:37,545][543983] Updated weights for policy 0, policy_version 35708 (0.0006) +[2026-07-22 23:13:37,825][543983] Updated weights for policy 0, policy_version 35718 (0.0006) +[2026-07-22 23:13:38,161][543983] Updated weights for policy 0, policy_version 35730 (0.0007) +[2026-07-22 23:13:38,452][543983] Updated weights for policy 0, policy_version 35740 (0.0006) +[2026-07-22 23:13:38,760][543983] Updated weights for policy 0, policy_version 35751 (0.0006) +[2026-07-22 23:13:39,058][543983] Updated weights for policy 0, policy_version 35761 (0.0006) +[2026-07-22 23:13:40,078][543983] Updated weights for policy 0, policy_version 35771 (0.0006) +[2026-07-22 23:13:40,357][543983] Updated weights for policy 0, policy_version 35781 (0.0007) +[2026-07-22 23:13:40,648][543983] Updated weights for policy 0, policy_version 35791 (0.0006) +[2026-07-22 23:13:40,953][543983] Updated weights for policy 0, policy_version 35802 (0.0006) +[2026-07-22 23:13:41,239][543983] Updated weights for policy 0, policy_version 35812 (0.0006) +[2026-07-22 23:13:41,540][543983] Updated weights for policy 0, policy_version 35822 (0.0006) +[2026-07-22 23:13:41,838][543983] Updated weights for policy 0, policy_version 35832 (0.0006) +[2026-07-22 23:13:42,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 18350080. Throughput: 0: 12720.4. Samples: 18369280. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:13:42,287][543203] Avg episode reward: [(0, '1347.462')] +[2026-07-22 23:13:42,292][543696] Saving new best policy, reward=1347.462! +[2026-07-22 23:13:42,852][543983] Updated weights for policy 0, policy_version 35842 (0.0006) +[2026-07-22 23:13:43,162][543983] Updated weights for policy 0, policy_version 35853 (0.0006) +[2026-07-22 23:13:43,453][543983] Updated weights for policy 0, policy_version 35863 (0.0006) +[2026-07-22 23:13:43,732][543983] Updated weights for policy 0, policy_version 35873 (0.0006) +[2026-07-22 23:13:44,017][543983] Updated weights for policy 0, policy_version 35883 (0.0006) +[2026-07-22 23:13:44,315][543983] Updated weights for policy 0, policy_version 35894 (0.0006) +[2026-07-22 23:13:45,395][543983] Updated weights for policy 0, policy_version 35904 (0.0006) +[2026-07-22 23:13:45,664][543983] Updated weights for policy 0, policy_version 35914 (0.0006) +[2026-07-22 23:13:45,959][543983] Updated weights for policy 0, policy_version 35924 (0.0006) +[2026-07-22 23:13:46,232][543983] Updated weights for policy 0, policy_version 35934 (0.0007) +[2026-07-22 23:13:46,579][543983] Updated weights for policy 0, policy_version 35946 (0.0007) +[2026-07-22 23:13:46,883][543983] Updated weights for policy 0, policy_version 35956 (0.0006) +[2026-07-22 23:13:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.6, 300 sec: 12774.0). Total num frames: 18415616. Throughput: 0: 12618.0. Samples: 18441728. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:13:47,287][543203] Avg episode reward: [(0, '1347.462')] +[2026-07-22 23:13:47,911][543983] Updated weights for policy 0, policy_version 35966 (0.0007) +[2026-07-22 23:13:48,199][543983] Updated weights for policy 0, policy_version 35976 (0.0007) +[2026-07-22 23:13:48,479][543983] Updated weights for policy 0, policy_version 35986 (0.0006) +[2026-07-22 23:13:48,759][543983] Updated weights for policy 0, policy_version 35996 (0.0006) +[2026-07-22 23:13:49,046][543983] Updated weights for policy 0, policy_version 36006 (0.0006) +[2026-07-22 23:13:49,325][543983] Updated weights for policy 0, policy_version 36016 (0.0006) +[2026-07-22 23:13:50,384][543983] Updated weights for policy 0, policy_version 36026 (0.0006) +[2026-07-22 23:13:50,688][543983] Updated weights for policy 0, policy_version 36037 (0.0006) +[2026-07-22 23:13:50,967][543983] Updated weights for policy 0, policy_version 36047 (0.0006) +[2026-07-22 23:13:51,249][543983] Updated weights for policy 0, policy_version 36057 (0.0006) +[2026-07-22 23:13:51,546][543983] Updated weights for policy 0, policy_version 36067 (0.0006) +[2026-07-22 23:13:51,827][543983] Updated weights for policy 0, policy_version 36077 (0.0006) +[2026-07-22 23:13:52,128][543983] Updated weights for policy 0, policy_version 36088 (0.0006) +[2026-07-22 23:13:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 18481152. Throughput: 0: 12686.2. Samples: 18480640. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:13:52,287][543203] Avg episode reward: [(0, '1357.836')] +[2026-07-22 23:13:52,293][543696] Saving new best policy, reward=1357.836! +[2026-07-22 23:13:53,222][543983] Updated weights for policy 0, policy_version 36099 (0.0006) +[2026-07-22 23:13:53,501][543983] Updated weights for policy 0, policy_version 36109 (0.0006) +[2026-07-22 23:13:53,784][543983] Updated weights for policy 0, policy_version 36119 (0.0006) +[2026-07-22 23:13:54,056][543983] Updated weights for policy 0, policy_version 36129 (0.0006) +[2026-07-22 23:13:54,339][543983] Updated weights for policy 0, policy_version 36139 (0.0006) +[2026-07-22 23:13:54,681][543983] Updated weights for policy 0, policy_version 36151 (0.0006) +[2026-07-22 23:13:55,732][543983] Updated weights for policy 0, policy_version 36161 (0.0006) +[2026-07-22 23:13:56,027][543983] Updated weights for policy 0, policy_version 36171 (0.0006) +[2026-07-22 23:13:56,302][543983] Updated weights for policy 0, policy_version 36181 (0.0006) +[2026-07-22 23:13:56,615][543983] Updated weights for policy 0, policy_version 36192 (0.0006) +[2026-07-22 23:13:56,885][543983] Updated weights for policy 0, policy_version 36202 (0.0006) +[2026-07-22 23:13:57,192][543983] Updated weights for policy 0, policy_version 36212 (0.0007) +[2026-07-22 23:13:57,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 18546688. Throughput: 0: 12865.4. Samples: 18562048. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:13:57,287][543203] Avg episode reward: [(0, '1415.869')] +[2026-07-22 23:13:57,293][543696] Saving new best policy, reward=1415.869! +[2026-07-22 23:13:58,297][543983] Updated weights for policy 0, policy_version 36224 (0.0007) +[2026-07-22 23:13:58,576][543983] Updated weights for policy 0, policy_version 36234 (0.0006) +[2026-07-22 23:13:58,856][543983] Updated weights for policy 0, policy_version 36244 (0.0006) +[2026-07-22 23:13:59,144][543983] Updated weights for policy 0, policy_version 36254 (0.0006) +[2026-07-22 23:13:59,450][543983] Updated weights for policy 0, policy_version 36265 (0.0006) +[2026-07-22 23:13:59,735][543983] Updated weights for policy 0, policy_version 36275 (0.0007) +[2026-07-22 23:14:00,816][543983] Updated weights for policy 0, policy_version 36285 (0.0006) +[2026-07-22 23:14:01,170][543983] Updated weights for policy 0, policy_version 36297 (0.0007) +[2026-07-22 23:14:01,436][543983] Updated weights for policy 0, policy_version 36307 (0.0006) +[2026-07-22 23:14:01,715][543983] Updated weights for policy 0, policy_version 36317 (0.0006) +[2026-07-22 23:14:02,000][543983] Updated weights for policy 0, policy_version 36327 (0.0006) +[2026-07-22 23:14:02,287][543203] Fps is (10 sec: 9830.3, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 18579456. Throughput: 0: 12617.9. Samples: 18635008. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:14:02,287][543203] Avg episode reward: [(0, '1426.322')] +[2026-07-22 23:14:02,294][543983] Updated weights for policy 0, policy_version 36337 (0.0007) +[2026-07-22 23:14:02,480][543696] Saving new best policy, reward=1426.322! +[2026-07-22 23:14:03,345][543983] Updated weights for policy 0, policy_version 36347 (0.0007) +[2026-07-22 23:14:03,670][543983] Updated weights for policy 0, policy_version 36359 (0.0006) +[2026-07-22 23:14:03,973][543983] Updated weights for policy 0, policy_version 36369 (0.0006) +[2026-07-22 23:14:04,268][543983] Updated weights for policy 0, policy_version 36380 (0.0007) +[2026-07-22 23:14:04,551][543983] Updated weights for policy 0, policy_version 36390 (0.0007) +[2026-07-22 23:14:04,899][543983] Updated weights for policy 0, policy_version 36402 (0.0007) +[2026-07-22 23:14:05,981][543983] Updated weights for policy 0, policy_version 36413 (0.0007) +[2026-07-22 23:14:06,269][543983] Updated weights for policy 0, policy_version 36423 (0.0006) +[2026-07-22 23:14:06,557][543983] Updated weights for policy 0, policy_version 36433 (0.0007) +[2026-07-22 23:14:06,858][543983] Updated weights for policy 0, policy_version 36444 (0.0006) +[2026-07-22 23:14:07,146][543983] Updated weights for policy 0, policy_version 36454 (0.0006) +[2026-07-22 23:14:07,287][543203] Fps is (10 sec: 9830.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 18644992. Throughput: 0: 12615.1. Samples: 18671104. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:14:07,287][543203] Avg episode reward: [(0, '1468.305')] +[2026-07-22 23:14:07,433][543983] Updated weights for policy 0, policy_version 36464 (0.0007) +[2026-07-22 23:14:07,671][543696] Saving new best policy, reward=1468.305! +[2026-07-22 23:14:08,502][543983] Updated weights for policy 0, policy_version 36474 (0.0007) +[2026-07-22 23:14:08,783][543983] Updated weights for policy 0, policy_version 36484 (0.0006) +[2026-07-22 23:14:09,069][543983] Updated weights for policy 0, policy_version 36494 (0.0006) +[2026-07-22 23:14:09,356][543983] Updated weights for policy 0, policy_version 36504 (0.0007) +[2026-07-22 23:14:09,639][543983] Updated weights for policy 0, policy_version 36514 (0.0006) +[2026-07-22 23:14:09,946][543983] Updated weights for policy 0, policy_version 36525 (0.0006) +[2026-07-22 23:14:10,240][543983] Updated weights for policy 0, policy_version 36536 (0.0006) +[2026-07-22 23:14:11,298][543983] Updated weights for policy 0, policy_version 36546 (0.0008) +[2026-07-22 23:14:11,591][543983] Updated weights for policy 0, policy_version 36556 (0.0007) +[2026-07-22 23:14:11,867][543983] Updated weights for policy 0, policy_version 36566 (0.0006) +[2026-07-22 23:14:12,152][543983] Updated weights for policy 0, policy_version 36576 (0.0006) +[2026-07-22 23:14:12,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 18710528. Throughput: 0: 12808.5. Samples: 18752768. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:14:12,287][543203] Avg episode reward: [(0, '1482.709')] +[2026-07-22 23:14:12,438][543983] Updated weights for policy 0, policy_version 36586 (0.0006) +[2026-07-22 23:14:12,739][543983] Updated weights for policy 0, policy_version 36597 (0.0007) +[2026-07-22 23:14:12,822][543696] Saving new best policy, reward=1482.709! +[2026-07-22 23:14:13,852][543983] Updated weights for policy 0, policy_version 36607 (0.0008) +[2026-07-22 23:14:14,122][543983] Updated weights for policy 0, policy_version 36617 (0.0006) +[2026-07-22 23:14:14,420][543983] Updated weights for policy 0, policy_version 36628 (0.0007) +[2026-07-22 23:14:14,715][543983] Updated weights for policy 0, policy_version 36638 (0.0006) +[2026-07-22 23:14:15,007][543983] Updated weights for policy 0, policy_version 36648 (0.0006) +[2026-07-22 23:14:15,307][543983] Updated weights for policy 0, policy_version 36659 (0.0007) +[2026-07-22 23:14:16,376][543983] Updated weights for policy 0, policy_version 36669 (0.0007) +[2026-07-22 23:14:16,660][543983] Updated weights for policy 0, policy_version 36679 (0.0006) +[2026-07-22 23:14:16,952][543983] Updated weights for policy 0, policy_version 36690 (0.0007) +[2026-07-22 23:14:17,276][543983] Updated weights for policy 0, policy_version 36701 (0.0006) +[2026-07-22 23:14:17,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 18776064. Throughput: 0: 12800.0. Samples: 18828928. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:14:17,287][543203] Avg episode reward: [(0, '1562.246')] +[2026-07-22 23:14:17,539][543983] Updated weights for policy 0, policy_version 36711 (0.0007) +[2026-07-22 23:14:17,837][543983] Updated weights for policy 0, policy_version 36721 (0.0007) +[2026-07-22 23:14:18,031][543696] Saving new best policy, reward=1562.246! +[2026-07-22 23:14:18,906][543983] Updated weights for policy 0, policy_version 36731 (0.0007) +[2026-07-22 23:14:19,193][543983] Updated weights for policy 0, policy_version 36741 (0.0007) +[2026-07-22 23:14:19,467][543983] Updated weights for policy 0, policy_version 36751 (0.0007) +[2026-07-22 23:14:19,766][543983] Updated weights for policy 0, policy_version 36761 (0.0008) +[2026-07-22 23:14:20,043][543983] Updated weights for policy 0, policy_version 36771 (0.0007) +[2026-07-22 23:14:20,335][543983] Updated weights for policy 0, policy_version 36781 (0.0007) +[2026-07-22 23:14:20,620][543983] Updated weights for policy 0, policy_version 36791 (0.0007) +[2026-07-22 23:14:21,662][543983] Updated weights for policy 0, policy_version 36801 (0.0007) +[2026-07-22 23:14:21,944][543983] Updated weights for policy 0, policy_version 36811 (0.0008) +[2026-07-22 23:14:22,232][543983] Updated weights for policy 0, policy_version 36821 (0.0007) +[2026-07-22 23:14:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 18841600. Throughput: 0: 12629.3. Samples: 18865536. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:14:22,287][543203] Avg episode reward: [(0, '1547.652')] +[2026-07-22 23:14:22,517][543983] Updated weights for policy 0, policy_version 36831 (0.0007) +[2026-07-22 23:14:22,809][543983] Updated weights for policy 0, policy_version 36841 (0.0006) +[2026-07-22 23:14:23,109][543983] Updated weights for policy 0, policy_version 36852 (0.0007) +[2026-07-22 23:14:24,157][543983] Updated weights for policy 0, policy_version 36862 (0.0006) +[2026-07-22 23:14:24,448][543983] Updated weights for policy 0, policy_version 36872 (0.0006) +[2026-07-22 23:14:24,777][543983] Updated weights for policy 0, policy_version 36884 (0.0006) +[2026-07-22 23:14:25,055][543983] Updated weights for policy 0, policy_version 36894 (0.0006) +[2026-07-22 23:14:25,340][543983] Updated weights for policy 0, policy_version 36904 (0.0006) +[2026-07-22 23:14:25,630][543983] Updated weights for policy 0, policy_version 36914 (0.0007) +[2026-07-22 23:14:26,683][543983] Updated weights for policy 0, policy_version 36924 (0.0008) +[2026-07-22 23:14:26,965][543983] Updated weights for policy 0, policy_version 36934 (0.0006) +[2026-07-22 23:14:27,241][543983] Updated weights for policy 0, policy_version 36944 (0.0006) +[2026-07-22 23:14:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 18907136. Throughput: 0: 12620.8. Samples: 18937216. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:14:27,287][543203] Avg episode reward: [(0, '1510.272')] +[2026-07-22 23:14:27,533][543983] Updated weights for policy 0, policy_version 36954 (0.0007) +[2026-07-22 23:14:27,834][543983] Updated weights for policy 0, policy_version 36965 (0.0007) +[2026-07-22 23:14:28,131][543983] Updated weights for policy 0, policy_version 36975 (0.0006) +[2026-07-22 23:14:29,167][543983] Updated weights for policy 0, policy_version 36985 (0.0007) +[2026-07-22 23:14:29,530][543983] Updated weights for policy 0, policy_version 36997 (0.0007) +[2026-07-22 23:14:29,799][543983] Updated weights for policy 0, policy_version 37007 (0.0006) +[2026-07-22 23:14:30,116][543983] Updated weights for policy 0, policy_version 37018 (0.0006) +[2026-07-22 23:14:30,417][543983] Updated weights for policy 0, policy_version 37028 (0.0007) +[2026-07-22 23:14:30,725][543983] Updated weights for policy 0, policy_version 37039 (0.0007) +[2026-07-22 23:14:31,753][543983] Updated weights for policy 0, policy_version 37049 (0.0006) +[2026-07-22 23:14:32,064][543983] Updated weights for policy 0, policy_version 37060 (0.0006) +[2026-07-22 23:14:32,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 18972672. Throughput: 0: 12891.0. Samples: 19021824. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:14:32,287][543203] Avg episode reward: [(0, '1527.039')] +[2026-07-22 23:14:32,375][543983] Updated weights for policy 0, policy_version 37071 (0.0006) +[2026-07-22 23:14:32,646][543983] Updated weights for policy 0, policy_version 37081 (0.0006) +[2026-07-22 23:14:32,938][543983] Updated weights for policy 0, policy_version 37091 (0.0007) +[2026-07-22 23:14:33,220][543983] Updated weights for policy 0, policy_version 37101 (0.0007) +[2026-07-22 23:14:33,499][543983] Updated weights for policy 0, policy_version 37111 (0.0006) +[2026-07-22 23:14:34,580][543983] Updated weights for policy 0, policy_version 37121 (0.0006) +[2026-07-22 23:14:34,845][543983] Updated weights for policy 0, policy_version 37131 (0.0007) +[2026-07-22 23:14:35,143][543983] Updated weights for policy 0, policy_version 37141 (0.0006) +[2026-07-22 23:14:35,451][543983] Updated weights for policy 0, policy_version 37152 (0.0007) +[2026-07-22 23:14:35,734][543983] Updated weights for policy 0, policy_version 37162 (0.0006) +[2026-07-22 23:14:36,018][543983] Updated weights for policy 0, policy_version 37172 (0.0006) +[2026-07-22 23:14:37,077][543983] Updated weights for policy 0, policy_version 37183 (0.0006) +[2026-07-22 23:14:37,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 19038208. Throughput: 0: 12831.3. Samples: 19058048. Policy #0 lag: (min: 63.0, avg: 80.0, max: 127.0) +[2026-07-22 23:14:37,287][543203] Avg episode reward: [(0, '1539.235')] +[2026-07-22 23:14:37,381][543983] Updated weights for policy 0, policy_version 37193 (0.0006) +[2026-07-22 23:14:37,647][543983] Updated weights for policy 0, policy_version 37203 (0.0006) +[2026-07-22 23:14:37,960][543983] Updated weights for policy 0, policy_version 37214 (0.0006) +[2026-07-22 23:14:38,235][543983] Updated weights for policy 0, policy_version 37224 (0.0007) +[2026-07-22 23:14:38,524][543983] Updated weights for policy 0, policy_version 37234 (0.0006) +[2026-07-22 23:14:39,626][543983] Updated weights for policy 0, policy_version 37246 (0.0006) +[2026-07-22 23:14:39,896][543983] Updated weights for policy 0, policy_version 37256 (0.0006) +[2026-07-22 23:14:40,187][543983] Updated weights for policy 0, policy_version 37266 (0.0006) +[2026-07-22 23:14:40,490][543983] Updated weights for policy 0, policy_version 37277 (0.0007) +[2026-07-22 23:14:40,786][543983] Updated weights for policy 0, policy_version 37287 (0.0009) +[2026-07-22 23:14:41,069][543983] Updated weights for policy 0, policy_version 37297 (0.0007) +[2026-07-22 23:14:42,137][543983] Updated weights for policy 0, policy_version 37307 (0.0006) +[2026-07-22 23:14:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 19103744. Throughput: 0: 12626.5. Samples: 19130240. Policy #0 lag: (min: 63.0, avg: 80.0, max: 127.0) +[2026-07-22 23:14:42,287][543203] Avg episode reward: [(0, '1552.205')] +[2026-07-22 23:14:42,446][543983] Updated weights for policy 0, policy_version 37318 (0.0006) +[2026-07-22 23:14:42,737][543983] Updated weights for policy 0, policy_version 37328 (0.0006) +[2026-07-22 23:14:43,037][543983] Updated weights for policy 0, policy_version 37339 (0.0006) +[2026-07-22 23:14:43,327][543983] Updated weights for policy 0, policy_version 37349 (0.0006) +[2026-07-22 23:14:43,608][543983] Updated weights for policy 0, policy_version 37359 (0.0006) +[2026-07-22 23:14:44,672][543983] Updated weights for policy 0, policy_version 37369 (0.0007) +[2026-07-22 23:14:44,948][543983] Updated weights for policy 0, policy_version 37379 (0.0006) +[2026-07-22 23:14:45,217][543983] Updated weights for policy 0, policy_version 37389 (0.0006) +[2026-07-22 23:14:45,498][543983] Updated weights for policy 0, policy_version 37399 (0.0006) +[2026-07-22 23:14:45,781][543983] Updated weights for policy 0, policy_version 37409 (0.0007) +[2026-07-22 23:14:46,074][543983] Updated weights for policy 0, policy_version 37419 (0.0006) +[2026-07-22 23:14:46,380][543983] Updated weights for policy 0, policy_version 37430 (0.0006) +[2026-07-22 23:14:47,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 19169280. Throughput: 0: 12731.8. Samples: 19207936. Policy #0 lag: (min: 63.0, avg: 80.0, max: 127.0) +[2026-07-22 23:14:47,287][543203] Avg episode reward: [(0, '1559.728')] +[2026-07-22 23:14:47,461][543983] Updated weights for policy 0, policy_version 37440 (0.0006) +[2026-07-22 23:14:47,744][543983] Updated weights for policy 0, policy_version 37450 (0.0007) +[2026-07-22 23:14:48,025][543983] Updated weights for policy 0, policy_version 37460 (0.0006) +[2026-07-22 23:14:48,339][543983] Updated weights for policy 0, policy_version 37471 (0.0007) +[2026-07-22 23:14:48,615][543983] Updated weights for policy 0, policy_version 37481 (0.0007) +[2026-07-22 23:14:48,929][543983] Updated weights for policy 0, policy_version 37492 (0.0006) +[2026-07-22 23:14:49,955][543983] Updated weights for policy 0, policy_version 37502 (0.0006) +[2026-07-22 23:14:50,273][543983] Updated weights for policy 0, policy_version 37513 (0.0006) +[2026-07-22 23:14:50,553][543983] Updated weights for policy 0, policy_version 37523 (0.0007) +[2026-07-22 23:14:50,816][543983] Updated weights for policy 0, policy_version 37533 (0.0007) +[2026-07-22 23:14:51,130][543983] Updated weights for policy 0, policy_version 37544 (0.0008) +[2026-07-22 23:14:51,420][543983] Updated weights for policy 0, policy_version 37554 (0.0007) +[2026-07-22 23:14:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 19234816. Throughput: 0: 12896.7. Samples: 19251456. Policy #0 lag: (min: 63.0, avg: 80.0, max: 127.0) +[2026-07-22 23:14:52,287][543203] Avg episode reward: [(0, '1586.513')] +[2026-07-22 23:14:52,490][543983] Updated weights for policy 0, policy_version 37564 (0.0007) +[2026-07-22 23:14:52,781][543983] Updated weights for policy 0, policy_version 37574 (0.0007) +[2026-07-22 23:14:53,115][543983] Updated weights for policy 0, policy_version 37586 (0.0007) +[2026-07-22 23:14:53,395][543983] Updated weights for policy 0, policy_version 37596 (0.0006) +[2026-07-22 23:14:53,680][543983] Updated weights for policy 0, policy_version 37606 (0.0006) +[2026-07-22 23:14:53,959][543983] Updated weights for policy 0, policy_version 37616 (0.0007) +[2026-07-22 23:14:54,173][543696] Saving new best policy, reward=1586.513! +[2026-07-22 23:14:55,007][543983] Updated weights for policy 0, policy_version 37626 (0.0007) +[2026-07-22 23:14:55,308][543983] Updated weights for policy 0, policy_version 37637 (0.0007) +[2026-07-22 23:14:55,605][543983] Updated weights for policy 0, policy_version 37647 (0.0006) +[2026-07-22 23:14:55,887][543983] Updated weights for policy 0, policy_version 37657 (0.0006) +[2026-07-22 23:14:56,169][543983] Updated weights for policy 0, policy_version 37667 (0.0006) +[2026-07-22 23:14:56,481][543983] Updated weights for policy 0, policy_version 37678 (0.0006) +[2026-07-22 23:14:56,756][543983] Updated weights for policy 0, policy_version 37688 (0.0006) +[2026-07-22 23:14:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 19300352. Throughput: 0: 12689.1. Samples: 19323776. Policy #0 lag: (min: 63.0, avg: 80.0, max: 127.0) +[2026-07-22 23:14:57,287][543203] Avg episode reward: [(0, '1596.301')] +[2026-07-22 23:14:57,293][543696] Saving new best policy, reward=1596.301! +[2026-07-22 23:14:57,833][543983] Updated weights for policy 0, policy_version 37699 (0.0006) +[2026-07-22 23:14:58,118][543983] Updated weights for policy 0, policy_version 37709 (0.0006) +[2026-07-22 23:14:58,412][543983] Updated weights for policy 0, policy_version 37720 (0.0007) +[2026-07-22 23:14:58,718][543983] Updated weights for policy 0, policy_version 37730 (0.0006) +[2026-07-22 23:14:58,990][543983] Updated weights for policy 0, policy_version 37740 (0.0007) +[2026-07-22 23:14:59,253][543983] Updated weights for policy 0, policy_version 37750 (0.0006) +[2026-07-22 23:15:00,322][543983] Updated weights for policy 0, policy_version 37760 (0.0006) +[2026-07-22 23:15:00,608][543983] Updated weights for policy 0, policy_version 37770 (0.0006) +[2026-07-22 23:15:00,911][543983] Updated weights for policy 0, policy_version 37781 (0.0006) +[2026-07-22 23:15:01,205][543983] Updated weights for policy 0, policy_version 37791 (0.0006) +[2026-07-22 23:15:01,480][543983] Updated weights for policy 0, policy_version 37801 (0.0007) +[2026-07-22 23:15:01,759][543983] Updated weights for policy 0, policy_version 37811 (0.0006) +[2026-07-22 23:15:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 19365888. Throughput: 0: 12592.4. Samples: 19395584. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:15:02,287][543203] Avg episode reward: [(0, '1603.429')] +[2026-07-22 23:15:02,293][543696] Saving new best policy, reward=1603.429! +[2026-07-22 23:15:02,836][543983] Updated weights for policy 0, policy_version 37821 (0.0006) +[2026-07-22 23:15:03,112][543983] Updated weights for policy 0, policy_version 37831 (0.0007) +[2026-07-22 23:15:03,396][543983] Updated weights for policy 0, policy_version 37841 (0.0007) +[2026-07-22 23:15:03,688][543983] Updated weights for policy 0, policy_version 37851 (0.0006) +[2026-07-22 23:15:03,974][543983] Updated weights for policy 0, policy_version 37861 (0.0007) +[2026-07-22 23:15:04,252][543983] Updated weights for policy 0, policy_version 37871 (0.0008) +[2026-07-22 23:15:05,294][543983] Updated weights for policy 0, policy_version 37881 (0.0007) +[2026-07-22 23:15:05,635][543983] Updated weights for policy 0, policy_version 37893 (0.0006) +[2026-07-22 23:15:05,916][543983] Updated weights for policy 0, policy_version 37903 (0.0006) +[2026-07-22 23:15:06,229][543983] Updated weights for policy 0, policy_version 37914 (0.0006) +[2026-07-22 23:15:06,514][543983] Updated weights for policy 0, policy_version 37924 (0.0007) +[2026-07-22 23:15:06,801][543983] Updated weights for policy 0, policy_version 37934 (0.0007) +[2026-07-22 23:15:07,072][543983] Updated weights for policy 0, policy_version 37944 (0.0006) +[2026-07-22 23:15:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 19431424. Throughput: 0: 12677.7. Samples: 19436032. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:15:07,287][543203] Avg episode reward: [(0, '1603.429')] +[2026-07-22 23:15:08,183][543983] Updated weights for policy 0, policy_version 37955 (0.0008) +[2026-07-22 23:15:08,468][543983] Updated weights for policy 0, policy_version 37966 (0.0007) +[2026-07-22 23:15:08,760][543983] Updated weights for policy 0, policy_version 37976 (0.0006) +[2026-07-22 23:15:09,040][543983] Updated weights for policy 0, policy_version 37986 (0.0006) +[2026-07-22 23:15:09,380][543983] Updated weights for policy 0, policy_version 37998 (0.0006) +[2026-07-22 23:15:09,665][543983] Updated weights for policy 0, policy_version 38008 (0.0006) +[2026-07-22 23:15:10,708][543983] Updated weights for policy 0, policy_version 38018 (0.0006) +[2026-07-22 23:15:11,013][543983] Updated weights for policy 0, policy_version 38029 (0.0006) +[2026-07-22 23:15:11,326][543983] Updated weights for policy 0, policy_version 38040 (0.0006) +[2026-07-22 23:15:11,624][543983] Updated weights for policy 0, policy_version 38050 (0.0007) +[2026-07-22 23:15:11,901][543983] Updated weights for policy 0, policy_version 38060 (0.0006) +[2026-07-22 23:15:12,217][543983] Updated weights for policy 0, policy_version 38071 (0.0008) +[2026-07-22 23:15:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 19496960. Throughput: 0: 12879.6. Samples: 19516800. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:15:12,287][543203] Avg episode reward: [(0, '1627.617')] +[2026-07-22 23:15:12,292][543696] Saving new best policy, reward=1627.617! +[2026-07-22 23:15:13,220][543983] Updated weights for policy 0, policy_version 38081 (0.0006) +[2026-07-22 23:15:13,521][543983] Updated weights for policy 0, policy_version 38091 (0.0007) +[2026-07-22 23:15:13,828][543983] Updated weights for policy 0, policy_version 38102 (0.0006) +[2026-07-22 23:15:14,104][543983] Updated weights for policy 0, policy_version 38112 (0.0006) +[2026-07-22 23:15:14,397][543983] Updated weights for policy 0, policy_version 38122 (0.0006) +[2026-07-22 23:15:14,703][543983] Updated weights for policy 0, policy_version 38133 (0.0007) +[2026-07-22 23:15:15,753][543983] Updated weights for policy 0, policy_version 38143 (0.0006) +[2026-07-22 23:15:16,052][543983] Updated weights for policy 0, policy_version 38154 (0.0006) +[2026-07-22 23:15:16,351][543983] Updated weights for policy 0, policy_version 38164 (0.0006) +[2026-07-22 23:15:16,668][543983] Updated weights for policy 0, policy_version 38175 (0.0006) +[2026-07-22 23:15:16,942][543983] Updated weights for policy 0, policy_version 38185 (0.0007) +[2026-07-22 23:15:17,224][543983] Updated weights for policy 0, policy_version 38195 (0.0006) +[2026-07-22 23:15:17,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 19529728. Throughput: 0: 12592.3. Samples: 19588480. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:15:17,287][543203] Avg episode reward: [(0, '1627.582')] +[2026-07-22 23:15:18,247][543983] Updated weights for policy 0, policy_version 38205 (0.0006) +[2026-07-22 23:15:18,513][543983] Updated weights for policy 0, policy_version 38215 (0.0007) +[2026-07-22 23:15:18,806][543983] Updated weights for policy 0, policy_version 38225 (0.0006) +[2026-07-22 23:15:19,084][543983] Updated weights for policy 0, policy_version 38235 (0.0006) +[2026-07-22 23:15:19,407][543983] Updated weights for policy 0, policy_version 38246 (0.0007) +[2026-07-22 23:15:19,674][543983] Updated weights for policy 0, policy_version 38256 (0.0006) +[2026-07-22 23:15:20,777][543983] Updated weights for policy 0, policy_version 38267 (0.0006) +[2026-07-22 23:15:21,036][543983] Updated weights for policy 0, policy_version 38277 (0.0006) +[2026-07-22 23:15:21,324][543983] Updated weights for policy 0, policy_version 38287 (0.0006) +[2026-07-22 23:15:21,662][543983] Updated weights for policy 0, policy_version 38299 (0.0006) +[2026-07-22 23:15:21,948][543983] Updated weights for policy 0, policy_version 38309 (0.0006) +[2026-07-22 23:15:22,255][543983] Updated weights for policy 0, policy_version 38320 (0.0006) +[2026-07-22 23:15:22,287][543203] Fps is (10 sec: 9830.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 19595264. Throughput: 0: 12575.3. Samples: 19623936. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:15:22,287][543203] Avg episode reward: [(0, '1671.182')] +[2026-07-22 23:15:22,484][543696] Saving new best policy, reward=1671.182! +[2026-07-22 23:15:23,313][543983] Updated weights for policy 0, policy_version 38330 (0.0006) +[2026-07-22 23:15:23,592][543983] Updated weights for policy 0, policy_version 38340 (0.0006) +[2026-07-22 23:15:23,861][543983] Updated weights for policy 0, policy_version 38350 (0.0006) +[2026-07-22 23:15:24,148][543983] Updated weights for policy 0, policy_version 38360 (0.0006) +[2026-07-22 23:15:24,492][543983] Updated weights for policy 0, policy_version 38372 (0.0007) +[2026-07-22 23:15:24,803][543983] Updated weights for policy 0, policy_version 38383 (0.0006) +[2026-07-22 23:15:25,853][543983] Updated weights for policy 0, policy_version 38393 (0.0006) +[2026-07-22 23:15:26,127][543983] Updated weights for policy 0, policy_version 38403 (0.0007) +[2026-07-22 23:15:26,426][543983] Updated weights for policy 0, policy_version 38413 (0.0006) +[2026-07-22 23:15:26,714][543983] Updated weights for policy 0, policy_version 38423 (0.0008) +[2026-07-22 23:15:27,025][543983] Updated weights for policy 0, policy_version 38434 (0.0007) +[2026-07-22 23:15:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 19660800. Throughput: 0: 12845.5. Samples: 19708288. Policy #0 lag: (min: 63.0, avg: 79.6, max: 127.0) +[2026-07-22 23:15:27,287][543203] Avg episode reward: [(0, '1673.815')] +[2026-07-22 23:15:27,329][543983] Updated weights for policy 0, policy_version 38445 (0.0006) +[2026-07-22 23:15:27,616][543983] Updated weights for policy 0, policy_version 38455 (0.0006) +[2026-07-22 23:15:27,659][543696] Saving new best policy, reward=1673.815! +[2026-07-22 23:15:28,667][543983] Updated weights for policy 0, policy_version 38465 (0.0006) +[2026-07-22 23:15:28,951][543983] Updated weights for policy 0, policy_version 38475 (0.0007) +[2026-07-22 23:15:29,246][543983] Updated weights for policy 0, policy_version 38486 (0.0007) +[2026-07-22 23:15:29,575][543983] Updated weights for policy 0, policy_version 38497 (0.0006) +[2026-07-22 23:15:29,866][543983] Updated weights for policy 0, policy_version 38507 (0.0006) +[2026-07-22 23:15:30,194][543983] Updated weights for policy 0, policy_version 38519 (0.0006) +[2026-07-22 23:15:31,258][543983] Updated weights for policy 0, policy_version 38530 (0.0006) +[2026-07-22 23:15:31,543][543983] Updated weights for policy 0, policy_version 38540 (0.0007) +[2026-07-22 23:15:31,854][543983] Updated weights for policy 0, policy_version 38551 (0.0006) +[2026-07-22 23:15:32,157][543983] Updated weights for policy 0, policy_version 38562 (0.0007) +[2026-07-22 23:15:32,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 19726336. Throughput: 0: 12720.4. Samples: 19780352. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:15:32,287][543203] Avg episode reward: [(0, '1734.592')] +[2026-07-22 23:15:32,429][543983] Updated weights for policy 0, policy_version 38572 (0.0006) +[2026-07-22 23:15:32,745][543983] Updated weights for policy 0, policy_version 38583 (0.0007) +[2026-07-22 23:15:32,764][543696] Saving new best policy, reward=1734.592! +[2026-07-22 23:15:33,831][543983] Updated weights for policy 0, policy_version 38594 (0.0006) +[2026-07-22 23:15:34,117][543983] Updated weights for policy 0, policy_version 38604 (0.0006) +[2026-07-22 23:15:34,405][543983] Updated weights for policy 0, policy_version 38614 (0.0006) +[2026-07-22 23:15:34,669][543983] Updated weights for policy 0, policy_version 38624 (0.0006) +[2026-07-22 23:15:34,957][543983] Updated weights for policy 0, policy_version 38634 (0.0006) +[2026-07-22 23:15:35,241][543983] Updated weights for policy 0, policy_version 38644 (0.0006) +[2026-07-22 23:15:36,290][543983] Updated weights for policy 0, policy_version 38654 (0.0006) +[2026-07-22 23:15:36,583][543983] Updated weights for policy 0, policy_version 38664 (0.0007) +[2026-07-22 23:15:36,865][543983] Updated weights for policy 0, policy_version 38674 (0.0006) +[2026-07-22 23:15:37,153][543983] Updated weights for policy 0, policy_version 38684 (0.0007) +[2026-07-22 23:15:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 19791872. Throughput: 0: 12546.8. Samples: 19816064. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:15:37,287][543203] Avg episode reward: [(0, '1708.523')] +[2026-07-22 23:15:37,434][543983] Updated weights for policy 0, policy_version 38694 (0.0007) +[2026-07-22 23:15:37,709][543983] Updated weights for policy 0, policy_version 38704 (0.0007) +[2026-07-22 23:15:38,787][543983] Updated weights for policy 0, policy_version 38715 (0.0006) +[2026-07-22 23:15:39,087][543983] Updated weights for policy 0, policy_version 38725 (0.0006) +[2026-07-22 23:15:39,381][543983] Updated weights for policy 0, policy_version 38736 (0.0006) +[2026-07-22 23:15:39,655][543983] Updated weights for policy 0, policy_version 38746 (0.0006) +[2026-07-22 23:15:39,939][543983] Updated weights for policy 0, policy_version 38756 (0.0007) +[2026-07-22 23:15:40,265][543983] Updated weights for policy 0, policy_version 38767 (0.0007) +[2026-07-22 23:15:41,305][543983] Updated weights for policy 0, policy_version 38777 (0.0007) +[2026-07-22 23:15:41,586][543983] Updated weights for policy 0, policy_version 38787 (0.0008) +[2026-07-22 23:15:41,874][543983] Updated weights for policy 0, policy_version 38797 (0.0009) +[2026-07-22 23:15:42,166][543983] Updated weights for policy 0, policy_version 38807 (0.0008) +[2026-07-22 23:15:42,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 19857408. Throughput: 0: 12626.5. Samples: 19891968. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:15:42,287][543203] Avg episode reward: [(0, '1732.638')] +[2026-07-22 23:15:42,445][543983] Updated weights for policy 0, policy_version 38817 (0.0006) +[2026-07-22 23:15:42,736][543983] Updated weights for policy 0, policy_version 38827 (0.0007) +[2026-07-22 23:15:43,044][543983] Updated weights for policy 0, policy_version 38837 (0.0007) +[2026-07-22 23:15:44,037][543983] Updated weights for policy 0, policy_version 38847 (0.0008) +[2026-07-22 23:15:44,359][543983] Updated weights for policy 0, policy_version 38858 (0.0007) +[2026-07-22 23:15:44,659][543983] Updated weights for policy 0, policy_version 38868 (0.0007) +[2026-07-22 23:15:44,939][543983] Updated weights for policy 0, policy_version 38878 (0.0007) +[2026-07-22 23:15:45,226][543983] Updated weights for policy 0, policy_version 38888 (0.0008) +[2026-07-22 23:15:45,501][543983] Updated weights for policy 0, policy_version 38898 (0.0007) +[2026-07-22 23:15:46,510][543983] Updated weights for policy 0, policy_version 38908 (0.0008) +[2026-07-22 23:15:46,793][543983] Updated weights for policy 0, policy_version 38918 (0.0007) +[2026-07-22 23:15:47,080][543983] Updated weights for policy 0, policy_version 38928 (0.0007) +[2026-07-22 23:15:47,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 19922944. Throughput: 0: 12802.8. Samples: 19971712. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:15:47,287][543203] Avg episode reward: [(0, '1822.271')] +[2026-07-22 23:15:47,358][543983] Updated weights for policy 0, policy_version 38938 (0.0008) +[2026-07-22 23:15:47,634][543983] Updated weights for policy 0, policy_version 38948 (0.0007) +[2026-07-22 23:15:47,931][543983] Updated weights for policy 0, policy_version 38958 (0.0006) +[2026-07-22 23:15:48,202][543696] Saving new best policy, reward=1822.271! +[2026-07-22 23:15:49,004][543983] Updated weights for policy 0, policy_version 38969 (0.0007) +[2026-07-22 23:15:49,299][543983] Updated weights for policy 0, policy_version 38979 (0.0007) +[2026-07-22 23:15:49,591][543983] Updated weights for policy 0, policy_version 38989 (0.0006) +[2026-07-22 23:15:49,879][543983] Updated weights for policy 0, policy_version 38999 (0.0008) +[2026-07-22 23:15:50,150][543983] Updated weights for policy 0, policy_version 39009 (0.0007) +[2026-07-22 23:15:50,452][543983] Updated weights for policy 0, policy_version 39019 (0.0006) +[2026-07-22 23:15:50,796][543983] Updated weights for policy 0, policy_version 39031 (0.0007) +[2026-07-22 23:15:51,803][543983] Updated weights for policy 0, policy_version 39041 (0.0006) +[2026-07-22 23:15:52,085][543983] Updated weights for policy 0, policy_version 39051 (0.0006) +[2026-07-22 23:15:52,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 19988480. Throughput: 0: 12709.0. Samples: 20007936. Policy #0 lag: (min: 63.0, avg: 79.3, max: 127.0) +[2026-07-22 23:15:52,287][543203] Avg episode reward: [(0, '1834.232')] +[2026-07-22 23:15:52,384][543983] Updated weights for policy 0, policy_version 39061 (0.0006) +[2026-07-22 23:15:52,660][543983] Updated weights for policy 0, policy_version 39071 (0.0006) +[2026-07-22 23:15:52,979][543983] Updated weights for policy 0, policy_version 39082 (0.0007) +[2026-07-22 23:15:53,276][543983] Updated weights for policy 0, policy_version 39093 (0.0006) +[2026-07-22 23:15:53,349][543696] Saving new best policy, reward=1834.232! +[2026-07-22 23:15:54,335][543983] Updated weights for policy 0, policy_version 39104 (0.0006) +[2026-07-22 23:15:54,628][543983] Updated weights for policy 0, policy_version 39114 (0.0006) +[2026-07-22 23:15:54,904][543983] Updated weights for policy 0, policy_version 39124 (0.0006) +[2026-07-22 23:15:55,194][543983] Updated weights for policy 0, policy_version 39134 (0.0006) +[2026-07-22 23:15:55,476][543983] Updated weights for policy 0, policy_version 39144 (0.0007) +[2026-07-22 23:15:55,763][543983] Updated weights for policy 0, policy_version 39154 (0.0007) +[2026-07-22 23:15:56,820][543983] Updated weights for policy 0, policy_version 39164 (0.0006) +[2026-07-22 23:15:57,140][543983] Updated weights for policy 0, policy_version 39176 (0.0006) +[2026-07-22 23:15:57,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 20054016. Throughput: 0: 12495.6. Samples: 20079104. Policy #0 lag: (min: 63.0, avg: 79.5, max: 127.0) +[2026-07-22 23:15:57,287][543203] Avg episode reward: [(0, '1849.052')] +[2026-07-22 23:15:57,460][543983] Updated weights for policy 0, policy_version 39187 (0.0006) +[2026-07-22 23:15:57,741][543983] Updated weights for policy 0, policy_version 39197 (0.0007) +[2026-07-22 23:15:58,056][543983] Updated weights for policy 0, policy_version 39208 (0.0007) +[2026-07-22 23:15:58,374][543983] Updated weights for policy 0, policy_version 39219 (0.0006) +[2026-07-22 23:15:58,497][543696] Saving new best policy, reward=1849.052! +[2026-07-22 23:15:59,411][543983] Updated weights for policy 0, policy_version 39229 (0.0006) +[2026-07-22 23:15:59,688][543983] Updated weights for policy 0, policy_version 39239 (0.0006) +[2026-07-22 23:15:59,978][543983] Updated weights for policy 0, policy_version 39249 (0.0006) +[2026-07-22 23:16:00,282][543983] Updated weights for policy 0, policy_version 39260 (0.0007) +[2026-07-22 23:16:00,624][543983] Updated weights for policy 0, policy_version 39272 (0.0007) +[2026-07-22 23:16:00,969][543983] Updated weights for policy 0, policy_version 39284 (0.0006) +[2026-07-22 23:16:02,012][543983] Updated weights for policy 0, policy_version 39294 (0.0007) +[2026-07-22 23:16:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 20119552. Throughput: 0: 12780.1. Samples: 20163584. Policy #0 lag: (min: 63.0, avg: 79.5, max: 127.0) +[2026-07-22 23:16:02,287][543203] Avg episode reward: [(0, '1868.122')] +[2026-07-22 23:16:02,335][543983] Updated weights for policy 0, policy_version 39305 (0.0007) +[2026-07-22 23:16:02,684][543983] Updated weights for policy 0, policy_version 39318 (0.0006) +[2026-07-22 23:16:02,995][543983] Updated weights for policy 0, policy_version 39328 (0.0007) +[2026-07-22 23:16:03,266][543983] Updated weights for policy 0, policy_version 39338 (0.0007) +[2026-07-22 23:16:03,562][543983] Updated weights for policy 0, policy_version 39349 (0.0006) +[2026-07-22 23:16:03,647][543696] Saving new best policy, reward=1868.122! +[2026-07-22 23:16:04,628][543983] Updated weights for policy 0, policy_version 39359 (0.0006) +[2026-07-22 23:16:04,907][543983] Updated weights for policy 0, policy_version 39369 (0.0006) +[2026-07-22 23:16:05,213][543983] Updated weights for policy 0, policy_version 39380 (0.0007) +[2026-07-22 23:16:05,518][543983] Updated weights for policy 0, policy_version 39391 (0.0007) +[2026-07-22 23:16:05,851][543983] Updated weights for policy 0, policy_version 39402 (0.0007) +[2026-07-22 23:16:06,117][543983] Updated weights for policy 0, policy_version 39412 (0.0008) +[2026-07-22 23:16:07,144][543983] Updated weights for policy 0, policy_version 39422 (0.0006) +[2026-07-22 23:16:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 20185088. Throughput: 0: 12791.5. Samples: 20199552. Policy #0 lag: (min: 63.0, avg: 79.5, max: 127.0) +[2026-07-22 23:16:07,287][543203] Avg episode reward: [(0, '1871.256')] +[2026-07-22 23:16:07,468][543983] Updated weights for policy 0, policy_version 39433 (0.0007) +[2026-07-22 23:16:07,756][543983] Updated weights for policy 0, policy_version 39443 (0.0006) +[2026-07-22 23:16:08,037][543983] Updated weights for policy 0, policy_version 39453 (0.0006) +[2026-07-22 23:16:08,309][543983] Updated weights for policy 0, policy_version 39463 (0.0006) +[2026-07-22 23:16:08,646][543983] Updated weights for policy 0, policy_version 39475 (0.0007) +[2026-07-22 23:16:08,785][543696] Saving new best policy, reward=1871.256! +[2026-07-22 23:16:09,683][543983] Updated weights for policy 0, policy_version 39485 (0.0006) +[2026-07-22 23:16:09,989][543983] Updated weights for policy 0, policy_version 39496 (0.0006) +[2026-07-22 23:16:10,271][543983] Updated weights for policy 0, policy_version 39506 (0.0006) +[2026-07-22 23:16:10,554][543983] Updated weights for policy 0, policy_version 39516 (0.0006) +[2026-07-22 23:16:10,820][543983] Updated weights for policy 0, policy_version 39526 (0.0006) +[2026-07-22 23:16:11,146][543983] Updated weights for policy 0, policy_version 39537 (0.0006) +[2026-07-22 23:16:12,194][543983] Updated weights for policy 0, policy_version 39547 (0.0007) +[2026-07-22 23:16:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 20250624. Throughput: 0: 12504.2. Samples: 20270976. Policy #0 lag: (min: 63.0, avg: 79.5, max: 127.0) +[2026-07-22 23:16:12,287][543203] Avg episode reward: [(0, '1903.140')] +[2026-07-22 23:16:12,504][543983] Updated weights for policy 0, policy_version 39558 (0.0006) +[2026-07-22 23:16:12,788][543983] Updated weights for policy 0, policy_version 39568 (0.0006) +[2026-07-22 23:16:13,077][543983] Updated weights for policy 0, policy_version 39578 (0.0006) +[2026-07-22 23:16:13,360][543983] Updated weights for policy 0, policy_version 39588 (0.0006) +[2026-07-22 23:16:13,649][543983] Updated weights for policy 0, policy_version 39598 (0.0006) +[2026-07-22 23:16:13,911][543696] Saving new best policy, reward=1903.140! +[2026-07-22 23:16:13,914][543983] Updated weights for policy 0, policy_version 39608 (0.0006) +[2026-07-22 23:16:14,965][543983] Updated weights for policy 0, policy_version 39618 (0.0006) +[2026-07-22 23:16:15,250][543983] Updated weights for policy 0, policy_version 39628 (0.0006) +[2026-07-22 23:16:15,532][543983] Updated weights for policy 0, policy_version 39638 (0.0007) +[2026-07-22 23:16:15,811][543983] Updated weights for policy 0, policy_version 39648 (0.0006) +[2026-07-22 23:16:16,098][543983] Updated weights for policy 0, policy_version 39658 (0.0007) +[2026-07-22 23:16:16,372][543983] Updated weights for policy 0, policy_version 39668 (0.0006) +[2026-07-22 23:16:17,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 20316160. Throughput: 0: 12595.2. Samples: 20347136. Policy #0 lag: (min: 63.0, avg: 79.5, max: 127.0) +[2026-07-22 23:16:17,287][543203] Avg episode reward: [(0, '1871.167')] +[2026-07-22 23:16:17,417][543983] Updated weights for policy 0, policy_version 39678 (0.0006) +[2026-07-22 23:16:17,699][543983] Updated weights for policy 0, policy_version 39688 (0.0007) +[2026-07-22 23:16:17,993][543983] Updated weights for policy 0, policy_version 39698 (0.0008) +[2026-07-22 23:16:18,280][543983] Updated weights for policy 0, policy_version 39708 (0.0007) +[2026-07-22 23:16:18,560][543983] Updated weights for policy 0, policy_version 39718 (0.0007) +[2026-07-22 23:16:18,863][543983] Updated weights for policy 0, policy_version 39729 (0.0006) +[2026-07-22 23:16:19,899][543983] Updated weights for policy 0, policy_version 39739 (0.0006) +[2026-07-22 23:16:20,193][543983] Updated weights for policy 0, policy_version 39749 (0.0006) +[2026-07-22 23:16:20,476][543983] Updated weights for policy 0, policy_version 39759 (0.0006) +[2026-07-22 23:16:20,785][543983] Updated weights for policy 0, policy_version 39770 (0.0006) +[2026-07-22 23:16:21,095][543983] Updated weights for policy 0, policy_version 39781 (0.0008) +[2026-07-22 23:16:21,394][543983] Updated weights for policy 0, policy_version 39791 (0.0007) +[2026-07-22 23:16:22,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12662.9). Total num frames: 20381696. Throughput: 0: 12785.8. Samples: 20391424. Policy #0 lag: (min: 63.0, avg: 79.5, max: 127.0) +[2026-07-22 23:16:22,287][543203] Avg episode reward: [(0, '1895.123')] +[2026-07-22 23:16:22,456][543983] Updated weights for policy 0, policy_version 39802 (0.0007) +[2026-07-22 23:16:22,757][543983] Updated weights for policy 0, policy_version 39813 (0.0007) +[2026-07-22 23:16:23,047][543983] Updated weights for policy 0, policy_version 39823 (0.0007) +[2026-07-22 23:16:23,348][543983] Updated weights for policy 0, policy_version 39833 (0.0007) +[2026-07-22 23:16:23,631][543983] Updated weights for policy 0, policy_version 39843 (0.0006) +[2026-07-22 23:16:23,967][543983] Updated weights for policy 0, policy_version 39855 (0.0006) +[2026-07-22 23:16:24,999][543983] Updated weights for policy 0, policy_version 39865 (0.0007) +[2026-07-22 23:16:25,288][543983] Updated weights for policy 0, policy_version 39875 (0.0006) +[2026-07-22 23:16:25,576][543983] Updated weights for policy 0, policy_version 39885 (0.0007) +[2026-07-22 23:16:25,857][543983] Updated weights for policy 0, policy_version 39895 (0.0006) +[2026-07-22 23:16:26,160][543983] Updated weights for policy 0, policy_version 39906 (0.0006) +[2026-07-22 23:16:26,459][543983] Updated weights for policy 0, policy_version 39916 (0.0006) +[2026-07-22 23:16:26,768][543983] Updated weights for policy 0, policy_version 39927 (0.0007) +[2026-07-22 23:16:27,286][543203] Fps is (10 sec: 13107.4, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 20447232. Throughput: 0: 12691.9. Samples: 20463104. Policy #0 lag: (min: 31.0, avg: 78.2, max: 99.0) +[2026-07-22 23:16:27,287][543203] Avg episode reward: [(0, '1941.319')] +[2026-07-22 23:16:27,293][543696] Saving new best policy, reward=1941.319! +[2026-07-22 23:16:27,784][543983] Updated weights for policy 0, policy_version 39937 (0.0007) +[2026-07-22 23:16:28,092][543983] Updated weights for policy 0, policy_version 39948 (0.0006) +[2026-07-22 23:16:28,413][543983] Updated weights for policy 0, policy_version 39959 (0.0006) +[2026-07-22 23:16:28,728][543983] Updated weights for policy 0, policy_version 39970 (0.0006) +[2026-07-22 23:16:29,039][543983] Updated weights for policy 0, policy_version 39981 (0.0006) +[2026-07-22 23:16:29,321][543983] Updated weights for policy 0, policy_version 39991 (0.0007) +[2026-07-22 23:16:30,341][543983] Updated weights for policy 0, policy_version 40001 (0.0007) +[2026-07-22 23:16:30,624][543983] Updated weights for policy 0, policy_version 40011 (0.0007) +[2026-07-22 23:16:30,919][543983] Updated weights for policy 0, policy_version 40021 (0.0006) +[2026-07-22 23:16:31,224][543983] Updated weights for policy 0, policy_version 40032 (0.0007) +[2026-07-22 23:16:31,525][543983] Updated weights for policy 0, policy_version 40043 (0.0007) +[2026-07-22 23:16:31,832][543983] Updated weights for policy 0, policy_version 40054 (0.0006) +[2026-07-22 23:16:32,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 20512768. Throughput: 0: 12504.2. Samples: 20534400. Policy #0 lag: (min: 31.0, avg: 78.2, max: 99.0) +[2026-07-22 23:16:32,287][543203] Avg episode reward: [(0, '1995.555')] +[2026-07-22 23:16:32,293][543696] Saving new best policy, reward=1995.555! +[2026-07-22 23:16:32,898][543983] Updated weights for policy 0, policy_version 40064 (0.0006) +[2026-07-22 23:16:33,185][543983] Updated weights for policy 0, policy_version 40074 (0.0007) +[2026-07-22 23:16:33,464][543983] Updated weights for policy 0, policy_version 40084 (0.0006) +[2026-07-22 23:16:33,778][543983] Updated weights for policy 0, policy_version 40095 (0.0007) +[2026-07-22 23:16:34,061][543983] Updated weights for policy 0, policy_version 40105 (0.0008) +[2026-07-22 23:16:34,356][543983] Updated weights for policy 0, policy_version 40115 (0.0006) +[2026-07-22 23:16:35,363][543983] Updated weights for policy 0, policy_version 40125 (0.0006) +[2026-07-22 23:16:35,655][543983] Updated weights for policy 0, policy_version 40135 (0.0007) +[2026-07-22 23:16:35,931][543983] Updated weights for policy 0, policy_version 40145 (0.0008) +[2026-07-22 23:16:36,216][543983] Updated weights for policy 0, policy_version 40155 (0.0007) +[2026-07-22 23:16:36,510][543983] Updated weights for policy 0, policy_version 40165 (0.0007) +[2026-07-22 23:16:36,822][543983] Updated weights for policy 0, policy_version 40176 (0.0006) +[2026-07-22 23:16:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 20578304. Throughput: 0: 12592.4. Samples: 20574592. Policy #0 lag: (min: 31.0, avg: 78.2, max: 99.0) +[2026-07-22 23:16:37,287][543203] Avg episode reward: [(0, '2005.735')] +[2026-07-22 23:16:37,292][543696] Saving new best policy, reward=2005.735! +[2026-07-22 23:16:37,854][543983] Updated weights for policy 0, policy_version 40186 (0.0007) +[2026-07-22 23:16:38,195][543983] Updated weights for policy 0, policy_version 40198 (0.0007) +[2026-07-22 23:16:38,543][543983] Updated weights for policy 0, policy_version 40210 (0.0007) +[2026-07-22 23:16:38,820][543983] Updated weights for policy 0, policy_version 40220 (0.0007) +[2026-07-22 23:16:39,112][543983] Updated weights for policy 0, policy_version 40230 (0.0007) +[2026-07-22 23:16:39,415][543983] Updated weights for policy 0, policy_version 40241 (0.0007) +[2026-07-22 23:16:40,457][543983] Updated weights for policy 0, policy_version 40251 (0.0007) +[2026-07-22 23:16:40,740][543983] Updated weights for policy 0, policy_version 40261 (0.0008) +[2026-07-22 23:16:41,068][543983] Updated weights for policy 0, policy_version 40272 (0.0006) +[2026-07-22 23:16:41,384][543983] Updated weights for policy 0, policy_version 40283 (0.0007) +[2026-07-22 23:16:41,641][543983] Updated weights for policy 0, policy_version 40293 (0.0007) +[2026-07-22 23:16:41,942][543983] Updated weights for policy 0, policy_version 40303 (0.0006) +[2026-07-22 23:16:42,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 20643840. Throughput: 0: 12774.4. Samples: 20653952. Policy #0 lag: (min: 31.0, avg: 78.2, max: 99.0) +[2026-07-22 23:16:42,288][543203] Avg episode reward: [(0, '2011.942')] +[2026-07-22 23:16:42,369][543696] Saving new best policy, reward=2011.942! +[2026-07-22 23:16:42,995][543983] Updated weights for policy 0, policy_version 40314 (0.0007) +[2026-07-22 23:16:43,266][543983] Updated weights for policy 0, policy_version 40324 (0.0007) +[2026-07-22 23:16:43,581][543983] Updated weights for policy 0, policy_version 40335 (0.0007) +[2026-07-22 23:16:43,877][543983] Updated weights for policy 0, policy_version 40345 (0.0006) +[2026-07-22 23:16:44,165][543983] Updated weights for policy 0, policy_version 40355 (0.0006) +[2026-07-22 23:16:44,451][543983] Updated weights for policy 0, policy_version 40365 (0.0007) +[2026-07-22 23:16:44,726][543983] Updated weights for policy 0, policy_version 40375 (0.0007) +[2026-07-22 23:16:45,727][543983] Updated weights for policy 0, policy_version 40385 (0.0007) +[2026-07-22 23:16:46,020][543983] Updated weights for policy 0, policy_version 40395 (0.0006) +[2026-07-22 23:16:46,310][543983] Updated weights for policy 0, policy_version 40405 (0.0006) +[2026-07-22 23:16:46,607][543983] Updated weights for policy 0, policy_version 40416 (0.0006) +[2026-07-22 23:16:46,974][543983] Updated weights for policy 0, policy_version 40428 (0.0007) +[2026-07-22 23:16:47,257][543983] Updated weights for policy 0, policy_version 40438 (0.0007) +[2026-07-22 23:16:47,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 20676608. Throughput: 0: 12481.4. Samples: 20725248. Policy #0 lag: (min: 31.0, avg: 78.2, max: 99.0) +[2026-07-22 23:16:47,287][543203] Avg episode reward: [(0, '2013.781')] +[2026-07-22 23:16:47,297][543696] Saving new best policy, reward=2013.781! +[2026-07-22 23:16:48,308][543983] Updated weights for policy 0, policy_version 40449 (0.0006) +[2026-07-22 23:16:48,596][543983] Updated weights for policy 0, policy_version 40459 (0.0007) +[2026-07-22 23:16:48,890][543983] Updated weights for policy 0, policy_version 40469 (0.0007) +[2026-07-22 23:16:49,164][543983] Updated weights for policy 0, policy_version 40479 (0.0007) +[2026-07-22 23:16:49,494][543983] Updated weights for policy 0, policy_version 40490 (0.0007) +[2026-07-22 23:16:49,762][543983] Updated weights for policy 0, policy_version 40500 (0.0006) +[2026-07-22 23:16:50,811][543983] Updated weights for policy 0, policy_version 40510 (0.0007) +[2026-07-22 23:16:51,093][543983] Updated weights for policy 0, policy_version 40520 (0.0006) +[2026-07-22 23:16:51,378][543983] Updated weights for policy 0, policy_version 40530 (0.0007) +[2026-07-22 23:16:51,665][543983] Updated weights for policy 0, policy_version 40540 (0.0006) +[2026-07-22 23:16:51,938][543983] Updated weights for policy 0, policy_version 40550 (0.0006) +[2026-07-22 23:16:52,233][543983] Updated weights for policy 0, policy_version 40560 (0.0006) +[2026-07-22 23:16:52,286][543203] Fps is (10 sec: 9830.5, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 20742144. Throughput: 0: 12487.1. Samples: 20761472. Policy #0 lag: (min: 31.0, avg: 78.2, max: 99.0) +[2026-07-22 23:16:52,287][543203] Avg episode reward: [(0, '1992.611')] +[2026-07-22 23:16:53,273][543983] Updated weights for policy 0, policy_version 40570 (0.0007) +[2026-07-22 23:16:53,572][543983] Updated weights for policy 0, policy_version 40580 (0.0008) +[2026-07-22 23:16:53,856][543983] Updated weights for policy 0, policy_version 40590 (0.0007) +[2026-07-22 23:16:54,186][543983] Updated weights for policy 0, policy_version 40601 (0.0006) +[2026-07-22 23:16:54,455][543983] Updated weights for policy 0, policy_version 40611 (0.0006) +[2026-07-22 23:16:54,747][543983] Updated weights for policy 0, policy_version 40621 (0.0006) +[2026-07-22 23:16:55,023][543983] Updated weights for policy 0, policy_version 40631 (0.0007) +[2026-07-22 23:16:56,054][543983] Updated weights for policy 0, policy_version 40641 (0.0007) +[2026-07-22 23:16:56,361][543983] Updated weights for policy 0, policy_version 40652 (0.0007) +[2026-07-22 23:16:56,700][543983] Updated weights for policy 0, policy_version 40664 (0.0006) +[2026-07-22 23:16:57,035][543983] Updated weights for policy 0, policy_version 40675 (0.0006) +[2026-07-22 23:16:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 20807680. Throughput: 0: 12763.0. Samples: 20845312. Policy #0 lag: (min: 63.0, avg: 79.5, max: 127.0) +[2026-07-22 23:16:57,287][543203] Avg episode reward: [(0, '1948.085')] +[2026-07-22 23:16:57,305][543983] Updated weights for policy 0, policy_version 40685 (0.0006) +[2026-07-22 23:16:57,574][543983] Updated weights for policy 0, policy_version 40695 (0.0008) +[2026-07-22 23:16:58,621][543983] Updated weights for policy 0, policy_version 40705 (0.0007) +[2026-07-22 23:16:58,928][543983] Updated weights for policy 0, policy_version 40716 (0.0008) +[2026-07-22 23:16:59,213][543983] Updated weights for policy 0, policy_version 40726 (0.0007) +[2026-07-22 23:16:59,503][543983] Updated weights for policy 0, policy_version 40736 (0.0007) +[2026-07-22 23:16:59,818][543983] Updated weights for policy 0, policy_version 40747 (0.0007) +[2026-07-22 23:17:00,094][543983] Updated weights for policy 0, policy_version 40757 (0.0008) +[2026-07-22 23:17:01,117][543983] Updated weights for policy 0, policy_version 40767 (0.0006) +[2026-07-22 23:17:01,421][543983] Updated weights for policy 0, policy_version 40777 (0.0007) +[2026-07-22 23:17:01,706][543983] Updated weights for policy 0, policy_version 40787 (0.0007) +[2026-07-22 23:17:01,986][543983] Updated weights for policy 0, policy_version 40797 (0.0007) +[2026-07-22 23:17:02,280][543983] Updated weights for policy 0, policy_version 40807 (0.0007) +[2026-07-22 23:17:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 20873216. Throughput: 0: 12660.6. Samples: 20916864. Policy #0 lag: (min: 63.0, avg: 79.5, max: 127.0) +[2026-07-22 23:17:02,287][543203] Avg episode reward: [(0, '1916.645')] +[2026-07-22 23:17:02,552][543983] Updated weights for policy 0, policy_version 40817 (0.0007) +[2026-07-22 23:17:03,584][543983] Updated weights for policy 0, policy_version 40827 (0.0006) +[2026-07-22 23:17:03,866][543983] Updated weights for policy 0, policy_version 40837 (0.0007) +[2026-07-22 23:17:04,155][543983] Updated weights for policy 0, policy_version 40847 (0.0006) +[2026-07-22 23:17:04,455][543983] Updated weights for policy 0, policy_version 40858 (0.0007) +[2026-07-22 23:17:04,743][543983] Updated weights for policy 0, policy_version 40868 (0.0006) +[2026-07-22 23:17:05,035][543983] Updated weights for policy 0, policy_version 40878 (0.0007) +[2026-07-22 23:17:05,322][543983] Updated weights for policy 0, policy_version 40888 (0.0008) +[2026-07-22 23:17:06,372][543983] Updated weights for policy 0, policy_version 40898 (0.0008) +[2026-07-22 23:17:06,652][543983] Updated weights for policy 0, policy_version 40908 (0.0007) +[2026-07-22 23:17:06,945][543983] Updated weights for policy 0, policy_version 40918 (0.0007) +[2026-07-22 23:17:07,224][543983] Updated weights for policy 0, policy_version 40928 (0.0007) +[2026-07-22 23:17:07,286][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 20938752. Throughput: 0: 12472.9. Samples: 20952704. Policy #0 lag: (min: 63.0, avg: 79.5, max: 127.0) +[2026-07-22 23:17:07,287][543203] Avg episode reward: [(0, '1942.981')] +[2026-07-22 23:17:07,522][543983] Updated weights for policy 0, policy_version 40938 (0.0008) +[2026-07-22 23:17:07,804][543983] Updated weights for policy 0, policy_version 40948 (0.0008) +[2026-07-22 23:17:08,810][543983] Updated weights for policy 0, policy_version 40958 (0.0007) +[2026-07-22 23:17:09,096][543983] Updated weights for policy 0, policy_version 40968 (0.0008) +[2026-07-22 23:17:09,372][543983] Updated weights for policy 0, policy_version 40978 (0.0007) +[2026-07-22 23:17:09,676][543983] Updated weights for policy 0, policy_version 40988 (0.0007) +[2026-07-22 23:17:09,947][543983] Updated weights for policy 0, policy_version 40998 (0.0007) +[2026-07-22 23:17:10,244][543983] Updated weights for policy 0, policy_version 41008 (0.0008) +[2026-07-22 23:17:11,284][543983] Updated weights for policy 0, policy_version 41018 (0.0007) +[2026-07-22 23:17:11,560][543983] Updated weights for policy 0, policy_version 41028 (0.0007) +[2026-07-22 23:17:11,852][543983] Updated weights for policy 0, policy_version 41038 (0.0007) +[2026-07-22 23:17:12,184][543983] Updated weights for policy 0, policy_version 41049 (0.0007) +[2026-07-22 23:17:12,287][543203] Fps is (10 sec: 13107.0, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 21004288. Throughput: 0: 12569.6. Samples: 21028736. Policy #0 lag: (min: 63.0, avg: 79.5, max: 127.0) +[2026-07-22 23:17:12,288][543203] Avg episode reward: [(0, '1897.006')] +[2026-07-22 23:17:12,452][543983] Updated weights for policy 0, policy_version 41059 (0.0007) +[2026-07-22 23:17:12,747][543983] Updated weights for policy 0, policy_version 41069 (0.0007) +[2026-07-22 23:17:13,030][543983] Updated weights for policy 0, policy_version 41079 (0.0006) +[2026-07-22 23:17:14,064][543983] Updated weights for policy 0, policy_version 41089 (0.0006) +[2026-07-22 23:17:14,338][543983] Updated weights for policy 0, policy_version 41099 (0.0007) +[2026-07-22 23:17:14,622][543983] Updated weights for policy 0, policy_version 41109 (0.0006) +[2026-07-22 23:17:14,929][543983] Updated weights for policy 0, policy_version 41119 (0.0006) +[2026-07-22 23:17:15,211][543983] Updated weights for policy 0, policy_version 41129 (0.0006) +[2026-07-22 23:17:15,553][543983] Updated weights for policy 0, policy_version 41141 (0.0006) +[2026-07-22 23:17:16,589][543983] Updated weights for policy 0, policy_version 41152 (0.0007) +[2026-07-22 23:17:16,887][543983] Updated weights for policy 0, policy_version 41162 (0.0006) +[2026-07-22 23:17:17,201][543983] Updated weights for policy 0, policy_version 41173 (0.0007) +[2026-07-22 23:17:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 21069824. Throughput: 0: 12743.1. Samples: 21107840. Policy #0 lag: (min: 63.0, avg: 79.5, max: 127.0) +[2026-07-22 23:17:17,287][543203] Avg episode reward: [(0, '1858.354')] +[2026-07-22 23:17:17,490][543983] Updated weights for policy 0, policy_version 41183 (0.0006) +[2026-07-22 23:17:17,777][543983] Updated weights for policy 0, policy_version 41193 (0.0006) +[2026-07-22 23:17:18,054][543983] Updated weights for policy 0, policy_version 41203 (0.0006) +[2026-07-22 23:17:19,161][543983] Updated weights for policy 0, policy_version 41213 (0.0007) +[2026-07-22 23:17:19,463][543983] Updated weights for policy 0, policy_version 41224 (0.0007) +[2026-07-22 23:17:19,793][543983] Updated weights for policy 0, policy_version 41235 (0.0007) +[2026-07-22 23:17:20,068][543983] Updated weights for policy 0, policy_version 41245 (0.0007) +[2026-07-22 23:17:20,365][543983] Updated weights for policy 0, policy_version 41255 (0.0007) +[2026-07-22 23:17:20,650][543983] Updated weights for policy 0, policy_version 41265 (0.0008) +[2026-07-22 23:17:21,672][543983] Updated weights for policy 0, policy_version 41275 (0.0007) +[2026-07-22 23:17:21,956][543983] Updated weights for policy 0, policy_version 41285 (0.0007) +[2026-07-22 23:17:22,243][543983] Updated weights for policy 0, policy_version 41295 (0.0007) +[2026-07-22 23:17:22,287][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 21135360. Throughput: 0: 12680.5. Samples: 21145216. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:17:22,287][543203] Avg episode reward: [(0, '1793.988')] +[2026-07-22 23:17:22,526][543983] Updated weights for policy 0, policy_version 41305 (0.0007) +[2026-07-22 23:17:22,807][543983] Updated weights for policy 0, policy_version 41315 (0.0008) +[2026-07-22 23:17:23,085][543983] Updated weights for policy 0, policy_version 41325 (0.0007) +[2026-07-22 23:17:23,368][543983] Updated weights for policy 0, policy_version 41335 (0.0007) +[2026-07-22 23:17:24,449][543983] Updated weights for policy 0, policy_version 41346 (0.0006) +[2026-07-22 23:17:24,772][543983] Updated weights for policy 0, policy_version 41357 (0.0006) +[2026-07-22 23:17:25,057][543983] Updated weights for policy 0, policy_version 41367 (0.0007) +[2026-07-22 23:17:25,330][543983] Updated weights for policy 0, policy_version 41377 (0.0006) +[2026-07-22 23:17:25,644][543983] Updated weights for policy 0, policy_version 41388 (0.0006) +[2026-07-22 23:17:25,928][543983] Updated weights for policy 0, policy_version 41398 (0.0006) +[2026-07-22 23:17:26,965][543983] Updated weights for policy 0, policy_version 41408 (0.0007) +[2026-07-22 23:17:27,252][543983] Updated weights for policy 0, policy_version 41418 (0.0007) +[2026-07-22 23:17:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 21200896. Throughput: 0: 12501.4. Samples: 21216512. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:17:27,287][543203] Avg episode reward: [(0, '1752.009')] +[2026-07-22 23:17:27,529][543983] Updated weights for policy 0, policy_version 41428 (0.0006) +[2026-07-22 23:17:27,863][543983] Updated weights for policy 0, policy_version 41440 (0.0006) +[2026-07-22 23:17:28,160][543983] Updated weights for policy 0, policy_version 41450 (0.0008) +[2026-07-22 23:17:28,446][543983] Updated weights for policy 0, policy_version 41460 (0.0007) +[2026-07-22 23:17:29,447][543983] Updated weights for policy 0, policy_version 41470 (0.0006) +[2026-07-22 23:17:29,735][543983] Updated weights for policy 0, policy_version 41480 (0.0007) +[2026-07-22 23:17:30,071][543983] Updated weights for policy 0, policy_version 41492 (0.0008) +[2026-07-22 23:17:30,360][543983] Updated weights for policy 0, policy_version 41502 (0.0007) +[2026-07-22 23:17:30,630][543983] Updated weights for policy 0, policy_version 41512 (0.0008) +[2026-07-22 23:17:30,959][543983] Updated weights for policy 0, policy_version 41523 (0.0008) +[2026-07-22 23:17:31,992][543983] Updated weights for policy 0, policy_version 41533 (0.0006) +[2026-07-22 23:17:32,285][543983] Updated weights for policy 0, policy_version 41543 (0.0007) +[2026-07-22 23:17:32,286][543203] Fps is (10 sec: 13107.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 21266432. Throughput: 0: 12768.7. Samples: 21299840. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:17:32,287][543203] Avg episode reward: [(0, '1746.957')] +[2026-07-22 23:17:32,573][543983] Updated weights for policy 0, policy_version 41553 (0.0007) +[2026-07-22 23:17:32,853][543983] Updated weights for policy 0, policy_version 41563 (0.0006) +[2026-07-22 23:17:33,144][543983] Updated weights for policy 0, policy_version 41573 (0.0008) +[2026-07-22 23:17:33,474][543983] Updated weights for policy 0, policy_version 41585 (0.0007) +[2026-07-22 23:17:34,543][543983] Updated weights for policy 0, policy_version 41596 (0.0006) +[2026-07-22 23:17:34,855][543983] Updated weights for policy 0, policy_version 41607 (0.0007) +[2026-07-22 23:17:35,140][543983] Updated weights for policy 0, policy_version 41617 (0.0007) +[2026-07-22 23:17:35,417][543983] Updated weights for policy 0, policy_version 41627 (0.0007) +[2026-07-22 23:17:35,705][543983] Updated weights for policy 0, policy_version 41637 (0.0006) +[2026-07-22 23:17:36,026][543983] Updated weights for policy 0, policy_version 41648 (0.0007) +[2026-07-22 23:17:37,069][543983] Updated weights for policy 0, policy_version 41658 (0.0007) +[2026-07-22 23:17:37,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 21331968. Throughput: 0: 12765.9. Samples: 21335936. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:17:37,287][543203] Avg episode reward: [(0, '1765.703')] +[2026-07-22 23:17:37,376][543983] Updated weights for policy 0, policy_version 41669 (0.0007) +[2026-07-22 23:17:37,659][543983] Updated weights for policy 0, policy_version 41679 (0.0007) +[2026-07-22 23:17:37,967][543983] Updated weights for policy 0, policy_version 41689 (0.0007) +[2026-07-22 23:17:38,264][543983] Updated weights for policy 0, policy_version 41700 (0.0006) +[2026-07-22 23:17:38,578][543983] Updated weights for policy 0, policy_version 41711 (0.0007) +[2026-07-22 23:17:39,627][543983] Updated weights for policy 0, policy_version 41721 (0.0006) +[2026-07-22 23:17:39,909][543983] Updated weights for policy 0, policy_version 41731 (0.0006) +[2026-07-22 23:17:40,213][543983] Updated weights for policy 0, policy_version 41741 (0.0007) +[2026-07-22 23:17:40,485][543983] Updated weights for policy 0, policy_version 41751 (0.0006) +[2026-07-22 23:17:40,791][543983] Updated weights for policy 0, policy_version 41762 (0.0006) +[2026-07-22 23:17:41,087][543983] Updated weights for policy 0, policy_version 41772 (0.0007) +[2026-07-22 23:17:41,419][543983] Updated weights for policy 0, policy_version 41783 (0.0007) +[2026-07-22 23:17:42,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12774.1). Total num frames: 21397504. Throughput: 0: 12509.8. Samples: 21408256. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:17:42,287][543203] Avg episode reward: [(0, '1801.616')] +[2026-07-22 23:17:42,439][543983] Updated weights for policy 0, policy_version 41793 (0.0008) +[2026-07-22 23:17:42,725][543983] Updated weights for policy 0, policy_version 41803 (0.0007) +[2026-07-22 23:17:43,060][543983] Updated weights for policy 0, policy_version 41815 (0.0008) +[2026-07-22 23:17:43,350][543983] Updated weights for policy 0, policy_version 41825 (0.0007) +[2026-07-22 23:17:43,637][543983] Updated weights for policy 0, policy_version 41835 (0.0007) +[2026-07-22 23:17:43,955][543983] Updated weights for policy 0, policy_version 41846 (0.0007) +[2026-07-22 23:17:44,988][543983] Updated weights for policy 0, policy_version 41856 (0.0008) +[2026-07-22 23:17:45,300][543983] Updated weights for policy 0, policy_version 41867 (0.0008) +[2026-07-22 23:17:45,590][543983] Updated weights for policy 0, policy_version 41877 (0.0007) +[2026-07-22 23:17:45,889][543983] Updated weights for policy 0, policy_version 41888 (0.0009) +[2026-07-22 23:17:46,205][543983] Updated weights for policy 0, policy_version 41899 (0.0007) +[2026-07-22 23:17:46,490][543983] Updated weights for policy 0, policy_version 41909 (0.0008) +[2026-07-22 23:17:47,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 21463040. Throughput: 0: 12569.6. Samples: 21482496. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:17:47,287][543203] Avg episode reward: [(0, '1802.145')] +[2026-07-22 23:17:47,543][543983] Updated weights for policy 0, policy_version 41919 (0.0007) +[2026-07-22 23:17:47,854][543983] Updated weights for policy 0, policy_version 41930 (0.0006) +[2026-07-22 23:17:48,156][543983] Updated weights for policy 0, policy_version 41940 (0.0006) +[2026-07-22 23:17:48,444][543983] Updated weights for policy 0, policy_version 41950 (0.0007) +[2026-07-22 23:17:48,737][543983] Updated weights for policy 0, policy_version 41960 (0.0007) +[2026-07-22 23:17:49,017][543983] Updated weights for policy 0, policy_version 41970 (0.0007) +[2026-07-22 23:17:50,031][543983] Updated weights for policy 0, policy_version 41980 (0.0007) +[2026-07-22 23:17:50,300][543983] Updated weights for policy 0, policy_version 41990 (0.0007) +[2026-07-22 23:17:50,607][543983] Updated weights for policy 0, policy_version 42001 (0.0008) +[2026-07-22 23:17:50,903][543983] Updated weights for policy 0, policy_version 42011 (0.0008) +[2026-07-22 23:17:51,189][543983] Updated weights for policy 0, policy_version 42021 (0.0007) +[2026-07-22 23:17:51,485][543983] Updated weights for policy 0, policy_version 42031 (0.0007) +[2026-07-22 23:17:52,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 21528576. Throughput: 0: 12763.0. Samples: 21527040. Policy #0 lag: (min: 18.0, avg: 35.2, max: 82.0) +[2026-07-22 23:17:52,287][543203] Avg episode reward: [(0, '1808.915')] +[2026-07-22 23:17:52,541][543983] Updated weights for policy 0, policy_version 42041 (0.0007) +[2026-07-22 23:17:52,835][543983] Updated weights for policy 0, policy_version 42051 (0.0007) +[2026-07-22 23:17:53,124][543983] Updated weights for policy 0, policy_version 42061 (0.0007) +[2026-07-22 23:17:53,409][543983] Updated weights for policy 0, policy_version 42071 (0.0007) +[2026-07-22 23:17:53,708][543983] Updated weights for policy 0, policy_version 42081 (0.0009) +[2026-07-22 23:17:53,981][543983] Updated weights for policy 0, policy_version 42091 (0.0008) +[2026-07-22 23:17:54,279][543983] Updated weights for policy 0, policy_version 42101 (0.0007) +[2026-07-22 23:17:55,297][543983] Updated weights for policy 0, policy_version 42111 (0.0008) +[2026-07-22 23:17:55,589][543983] Updated weights for policy 0, policy_version 42121 (0.0008) +[2026-07-22 23:17:55,865][543983] Updated weights for policy 0, policy_version 42131 (0.0008) +[2026-07-22 23:17:56,168][543983] Updated weights for policy 0, policy_version 42141 (0.0007) +[2026-07-22 23:17:56,441][543983] Updated weights for policy 0, policy_version 42151 (0.0007) +[2026-07-22 23:17:56,733][543983] Updated weights for policy 0, policy_version 42161 (0.0006) +[2026-07-22 23:17:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 21594112. Throughput: 0: 12694.8. Samples: 21600000. Policy #0 lag: (min: 18.0, avg: 35.2, max: 82.0) +[2026-07-22 23:17:57,287][543203] Avg episode reward: [(0, '1811.862')] +[2026-07-22 23:17:57,757][543983] Updated weights for policy 0, policy_version 42171 (0.0006) +[2026-07-22 23:17:58,045][543983] Updated weights for policy 0, policy_version 42181 (0.0006) +[2026-07-22 23:17:58,377][543983] Updated weights for policy 0, policy_version 42193 (0.0006) +[2026-07-22 23:17:58,698][543983] Updated weights for policy 0, policy_version 42204 (0.0006) +[2026-07-22 23:17:59,019][543983] Updated weights for policy 0, policy_version 42216 (0.0006) +[2026-07-22 23:17:59,325][543983] Updated weights for policy 0, policy_version 42226 (0.0006) +[2026-07-22 23:18:00,363][543983] Updated weights for policy 0, policy_version 42236 (0.0006) +[2026-07-22 23:18:00,643][543983] Updated weights for policy 0, policy_version 42246 (0.0006) +[2026-07-22 23:18:00,927][543983] Updated weights for policy 0, policy_version 42256 (0.0007) +[2026-07-22 23:18:01,240][543983] Updated weights for policy 0, policy_version 42267 (0.0006) +[2026-07-22 23:18:01,580][543983] Updated weights for policy 0, policy_version 42279 (0.0006) +[2026-07-22 23:18:01,869][543983] Updated weights for policy 0, policy_version 42289 (0.0007) +[2026-07-22 23:18:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 21659648. Throughput: 0: 12549.7. Samples: 21672576. Policy #0 lag: (min: 18.0, avg: 35.2, max: 82.0) +[2026-07-22 23:18:02,287][543203] Avg episode reward: [(0, '1815.639')] +[2026-07-22 23:18:02,918][543983] Updated weights for policy 0, policy_version 42299 (0.0007) +[2026-07-22 23:18:03,198][543983] Updated weights for policy 0, policy_version 42309 (0.0006) +[2026-07-22 23:18:03,493][543983] Updated weights for policy 0, policy_version 42319 (0.0007) +[2026-07-22 23:18:03,779][543983] Updated weights for policy 0, policy_version 42329 (0.0007) +[2026-07-22 23:18:04,080][543983] Updated weights for policy 0, policy_version 42339 (0.0007) +[2026-07-22 23:18:04,389][543983] Updated weights for policy 0, policy_version 42350 (0.0007) +[2026-07-22 23:18:04,661][543983] Updated weights for policy 0, policy_version 42360 (0.0006) +[2026-07-22 23:18:05,724][543983] Updated weights for policy 0, policy_version 42370 (0.0006) +[2026-07-22 23:18:06,021][543983] Updated weights for policy 0, policy_version 42380 (0.0006) +[2026-07-22 23:18:06,298][543983] Updated weights for policy 0, policy_version 42390 (0.0006) +[2026-07-22 23:18:06,578][543983] Updated weights for policy 0, policy_version 42400 (0.0007) +[2026-07-22 23:18:06,861][543983] Updated weights for policy 0, policy_version 42410 (0.0006) +[2026-07-22 23:18:07,147][543983] Updated weights for policy 0, policy_version 42420 (0.0006) +[2026-07-22 23:18:07,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 21725184. Throughput: 0: 12541.2. Samples: 21709568. Policy #0 lag: (min: 18.0, avg: 35.2, max: 82.0) +[2026-07-22 23:18:07,287][543203] Avg episode reward: [(0, '1815.639')] +[2026-07-22 23:18:08,242][543983] Updated weights for policy 0, policy_version 42432 (0.0006) +[2026-07-22 23:18:08,518][543983] Updated weights for policy 0, policy_version 42442 (0.0008) +[2026-07-22 23:18:08,822][543983] Updated weights for policy 0, policy_version 42452 (0.0006) +[2026-07-22 23:18:09,098][543983] Updated weights for policy 0, policy_version 42463 (0.0006) +[2026-07-22 23:18:09,395][543983] Updated weights for policy 0, policy_version 42473 (0.0006) +[2026-07-22 23:18:09,705][543983] Updated weights for policy 0, policy_version 42484 (0.0006) +[2026-07-22 23:18:10,738][543983] Updated weights for policy 0, policy_version 42494 (0.0006) +[2026-07-22 23:18:11,058][543983] Updated weights for policy 0, policy_version 42505 (0.0007) +[2026-07-22 23:18:11,371][543983] Updated weights for policy 0, policy_version 42516 (0.0007) +[2026-07-22 23:18:11,683][543983] Updated weights for policy 0, policy_version 42527 (0.0006) +[2026-07-22 23:18:12,001][543983] Updated weights for policy 0, policy_version 42538 (0.0006) +[2026-07-22 23:18:12,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 21757952. Throughput: 0: 12811.4. Samples: 21793024. Policy #0 lag: (min: 18.0, avg: 35.2, max: 82.0) +[2026-07-22 23:18:12,287][543203] Avg episode reward: [(0, '1820.383')] +[2026-07-22 23:18:12,316][543983] Updated weights for policy 0, policy_version 42549 (0.0006) +[2026-07-22 23:18:13,382][543983] Updated weights for policy 0, policy_version 42559 (0.0006) +[2026-07-22 23:18:13,704][543983] Updated weights for policy 0, policy_version 42570 (0.0006) +[2026-07-22 23:18:13,971][543983] Updated weights for policy 0, policy_version 42580 (0.0006) +[2026-07-22 23:18:14,288][543983] Updated weights for policy 0, policy_version 42591 (0.0007) +[2026-07-22 23:18:14,608][543983] Updated weights for policy 0, policy_version 42602 (0.0007) +[2026-07-22 23:18:14,933][543983] Updated weights for policy 0, policy_version 42613 (0.0007) +[2026-07-22 23:18:15,962][543983] Updated weights for policy 0, policy_version 42623 (0.0006) +[2026-07-22 23:18:16,244][543983] Updated weights for policy 0, policy_version 42633 (0.0006) +[2026-07-22 23:18:16,524][543983] Updated weights for policy 0, policy_version 42643 (0.0006) +[2026-07-22 23:18:16,815][543983] Updated weights for policy 0, policy_version 42653 (0.0006) +[2026-07-22 23:18:17,131][543983] Updated weights for policy 0, policy_version 42664 (0.0006) +[2026-07-22 23:18:17,287][543203] Fps is (10 sec: 9830.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 21823488. Throughput: 0: 12581.0. Samples: 21865984. Policy #0 lag: (min: 18.0, avg: 35.2, max: 82.0) +[2026-07-22 23:18:17,287][543203] Avg episode reward: [(0, '1830.116')] +[2026-07-22 23:18:17,416][543983] Updated weights for policy 0, policy_version 42674 (0.0007) +[2026-07-22 23:18:18,473][543983] Updated weights for policy 0, policy_version 42684 (0.0006) +[2026-07-22 23:18:18,757][543983] Updated weights for policy 0, policy_version 42694 (0.0006) +[2026-07-22 23:18:19,035][543983] Updated weights for policy 0, policy_version 42704 (0.0006) +[2026-07-22 23:18:19,314][543983] Updated weights for policy 0, policy_version 42714 (0.0006) +[2026-07-22 23:18:19,611][543983] Updated weights for policy 0, policy_version 42724 (0.0007) +[2026-07-22 23:18:19,891][543983] Updated weights for policy 0, policy_version 42734 (0.0007) +[2026-07-22 23:18:20,987][543983] Updated weights for policy 0, policy_version 42745 (0.0006) +[2026-07-22 23:18:21,250][543983] Updated weights for policy 0, policy_version 42755 (0.0006) +[2026-07-22 23:18:21,544][543983] Updated weights for policy 0, policy_version 42765 (0.0006) +[2026-07-22 23:18:21,819][543983] Updated weights for policy 0, policy_version 42775 (0.0006) +[2026-07-22 23:18:22,128][543983] Updated weights for policy 0, policy_version 42786 (0.0006) +[2026-07-22 23:18:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 21889024. Throughput: 0: 12583.8. Samples: 21902208. Policy #0 lag: (min: 63.0, avg: 79.9, max: 127.0) +[2026-07-22 23:18:22,287][543203] Avg episode reward: [(0, '1845.536')] +[2026-07-22 23:18:22,451][543983] Updated weights for policy 0, policy_version 42797 (0.0006) +[2026-07-22 23:18:22,753][543983] Updated weights for policy 0, policy_version 42808 (0.0006) +[2026-07-22 23:18:23,823][543983] Updated weights for policy 0, policy_version 42818 (0.0006) +[2026-07-22 23:18:24,167][543983] Updated weights for policy 0, policy_version 42830 (0.0007) +[2026-07-22 23:18:24,444][543983] Updated weights for policy 0, policy_version 42840 (0.0006) +[2026-07-22 23:18:24,740][543983] Updated weights for policy 0, policy_version 42850 (0.0006) +[2026-07-22 23:18:25,029][543983] Updated weights for policy 0, policy_version 42860 (0.0006) +[2026-07-22 23:18:25,309][543983] Updated weights for policy 0, policy_version 42870 (0.0006) +[2026-07-22 23:18:26,347][543983] Updated weights for policy 0, policy_version 42880 (0.0006) +[2026-07-22 23:18:26,652][543983] Updated weights for policy 0, policy_version 42890 (0.0007) +[2026-07-22 23:18:26,915][543983] Updated weights for policy 0, policy_version 42900 (0.0006) +[2026-07-22 23:18:27,215][543983] Updated weights for policy 0, policy_version 42910 (0.0007) +[2026-07-22 23:18:27,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 21954560. Throughput: 0: 12734.6. Samples: 21981312. Policy #0 lag: (min: 63.0, avg: 79.9, max: 127.0) +[2026-07-22 23:18:27,287][543203] Avg episode reward: [(0, '1845.536')] +[2026-07-22 23:18:27,525][543983] Updated weights for policy 0, policy_version 42921 (0.0008) +[2026-07-22 23:18:27,814][543983] Updated weights for policy 0, policy_version 42931 (0.0006) +[2026-07-22 23:18:28,849][543983] Updated weights for policy 0, policy_version 42941 (0.0006) +[2026-07-22 23:18:29,139][543983] Updated weights for policy 0, policy_version 42951 (0.0006) +[2026-07-22 23:18:29,471][543983] Updated weights for policy 0, policy_version 42963 (0.0006) +[2026-07-22 23:18:29,802][543983] Updated weights for policy 0, policy_version 42974 (0.0007) +[2026-07-22 23:18:30,058][543983] Updated weights for policy 0, policy_version 42984 (0.0006) +[2026-07-22 23:18:30,336][543983] Updated weights for policy 0, policy_version 42994 (0.0006) +[2026-07-22 23:18:31,419][543983] Updated weights for policy 0, policy_version 43004 (0.0006) +[2026-07-22 23:18:31,686][543983] Updated weights for policy 0, policy_version 43014 (0.0007) +[2026-07-22 23:18:31,999][543983] Updated weights for policy 0, policy_version 43025 (0.0006) +[2026-07-22 23:18:32,279][543983] Updated weights for policy 0, policy_version 43035 (0.0006) +[2026-07-22 23:18:32,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 22020096. Throughput: 0: 12817.1. Samples: 22059264. Policy #0 lag: (min: 63.0, avg: 79.9, max: 127.0) +[2026-07-22 23:18:32,287][543203] Avg episode reward: [(0, '1845.536')] +[2026-07-22 23:18:32,569][543983] Updated weights for policy 0, policy_version 43045 (0.0007) +[2026-07-22 23:18:32,885][543983] Updated weights for policy 0, policy_version 43056 (0.0006) +[2026-07-22 23:18:33,950][543983] Updated weights for policy 0, policy_version 43066 (0.0006) +[2026-07-22 23:18:34,222][543983] Updated weights for policy 0, policy_version 43076 (0.0006) +[2026-07-22 23:18:34,498][543983] Updated weights for policy 0, policy_version 43086 (0.0006) +[2026-07-22 23:18:34,793][543983] Updated weights for policy 0, policy_version 43096 (0.0006) +[2026-07-22 23:18:35,091][543983] Updated weights for policy 0, policy_version 43107 (0.0006) +[2026-07-22 23:18:35,378][543983] Updated weights for policy 0, policy_version 43117 (0.0006) +[2026-07-22 23:18:35,682][543983] Updated weights for policy 0, policy_version 43127 (0.0007) +[2026-07-22 23:18:36,709][543983] Updated weights for policy 0, policy_version 43137 (0.0006) +[2026-07-22 23:18:36,978][543983] Updated weights for policy 0, policy_version 43147 (0.0006) +[2026-07-22 23:18:37,271][543983] Updated weights for policy 0, policy_version 43157 (0.0006) +[2026-07-22 23:18:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 22085632. Throughput: 0: 12637.9. Samples: 22095744. Policy #0 lag: (min: 63.0, avg: 79.9, max: 127.0) +[2026-07-22 23:18:37,287][543203] Avg episode reward: [(0, '1857.306')] +[2026-07-22 23:18:37,566][543983] Updated weights for policy 0, policy_version 43167 (0.0007) +[2026-07-22 23:18:37,851][543983] Updated weights for policy 0, policy_version 43177 (0.0006) +[2026-07-22 23:18:38,161][543983] Updated weights for policy 0, policy_version 43188 (0.0006) +[2026-07-22 23:18:39,209][543983] Updated weights for policy 0, policy_version 43198 (0.0007) +[2026-07-22 23:18:39,493][543983] Updated weights for policy 0, policy_version 43208 (0.0006) +[2026-07-22 23:18:39,792][543983] Updated weights for policy 0, policy_version 43218 (0.0006) +[2026-07-22 23:18:40,061][543983] Updated weights for policy 0, policy_version 43228 (0.0006) +[2026-07-22 23:18:40,368][543983] Updated weights for policy 0, policy_version 43239 (0.0006) +[2026-07-22 23:18:40,650][543983] Updated weights for policy 0, policy_version 43249 (0.0006) +[2026-07-22 23:18:41,699][543983] Updated weights for policy 0, policy_version 43259 (0.0006) +[2026-07-22 23:18:42,000][543983] Updated weights for policy 0, policy_version 43270 (0.0006) +[2026-07-22 23:18:42,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 22151168. Throughput: 0: 12620.8. Samples: 22167936. Policy #0 lag: (min: 63.0, avg: 79.9, max: 127.0) +[2026-07-22 23:18:42,287][543203] Avg episode reward: [(0, '1870.997')] +[2026-07-22 23:18:42,308][543983] Updated weights for policy 0, policy_version 43281 (0.0007) +[2026-07-22 23:18:42,609][543983] Updated weights for policy 0, policy_version 43292 (0.0006) +[2026-07-22 23:18:42,942][543983] Updated weights for policy 0, policy_version 43303 (0.0006) +[2026-07-22 23:18:43,253][543983] Updated weights for policy 0, policy_version 43314 (0.0006) +[2026-07-22 23:18:44,318][543983] Updated weights for policy 0, policy_version 43324 (0.0006) +[2026-07-22 23:18:44,580][543983] Updated weights for policy 0, policy_version 43334 (0.0006) +[2026-07-22 23:18:44,864][543983] Updated weights for policy 0, policy_version 43344 (0.0006) +[2026-07-22 23:18:45,159][543983] Updated weights for policy 0, policy_version 43354 (0.0006) +[2026-07-22 23:18:45,443][543983] Updated weights for policy 0, policy_version 43364 (0.0006) +[2026-07-22 23:18:45,774][543983] Updated weights for policy 0, policy_version 43376 (0.0006) +[2026-07-22 23:18:46,835][543983] Updated weights for policy 0, policy_version 43386 (0.0006) +[2026-07-22 23:18:47,145][543983] Updated weights for policy 0, policy_version 43397 (0.0007) +[2026-07-22 23:18:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 22216704. Throughput: 0: 12888.2. Samples: 22252544. Policy #0 lag: (min: 63.0, avg: 79.9, max: 127.0) +[2026-07-22 23:18:47,287][543203] Avg episode reward: [(0, '1871.724')] +[2026-07-22 23:18:47,454][543983] Updated weights for policy 0, policy_version 43408 (0.0006) +[2026-07-22 23:18:47,765][543983] Updated weights for policy 0, policy_version 43419 (0.0006) +[2026-07-22 23:18:48,060][543983] Updated weights for policy 0, policy_version 43429 (0.0006) +[2026-07-22 23:18:48,336][543983] Updated weights for policy 0, policy_version 43439 (0.0006) +[2026-07-22 23:18:49,410][543983] Updated weights for policy 0, policy_version 43450 (0.0006) +[2026-07-22 23:18:49,723][543983] Updated weights for policy 0, policy_version 43461 (0.0006) +[2026-07-22 23:18:49,989][543983] Updated weights for policy 0, policy_version 43471 (0.0006) +[2026-07-22 23:18:50,328][543983] Updated weights for policy 0, policy_version 43482 (0.0006) +[2026-07-22 23:18:50,632][543983] Updated weights for policy 0, policy_version 43493 (0.0007) +[2026-07-22 23:18:50,907][543983] Updated weights for policy 0, policy_version 43503 (0.0006) +[2026-07-22 23:18:52,002][543983] Updated weights for policy 0, policy_version 43514 (0.0006) +[2026-07-22 23:18:52,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 22282240. Throughput: 0: 12865.4. Samples: 22288512. Policy #0 lag: (min: 63.0, avg: 79.7, max: 127.0) +[2026-07-22 23:18:52,287][543203] Avg episode reward: [(0, '1913.030')] +[2026-07-22 23:18:52,336][543983] Updated weights for policy 0, policy_version 43525 (0.0006) +[2026-07-22 23:18:52,644][543983] Updated weights for policy 0, policy_version 43536 (0.0007) +[2026-07-22 23:18:52,916][543983] Updated weights for policy 0, policy_version 43546 (0.0007) +[2026-07-22 23:18:53,196][543983] Updated weights for policy 0, policy_version 43556 (0.0006) +[2026-07-22 23:18:53,506][543983] Updated weights for policy 0, policy_version 43567 (0.0006) +[2026-07-22 23:18:54,553][543983] Updated weights for policy 0, policy_version 43577 (0.0006) +[2026-07-22 23:18:54,826][543983] Updated weights for policy 0, policy_version 43587 (0.0006) +[2026-07-22 23:18:55,121][543983] Updated weights for policy 0, policy_version 43597 (0.0006) +[2026-07-22 23:18:55,398][543983] Updated weights for policy 0, policy_version 43607 (0.0006) +[2026-07-22 23:18:55,683][543983] Updated weights for policy 0, policy_version 43617 (0.0006) +[2026-07-22 23:18:56,005][543983] Updated weights for policy 0, policy_version 43628 (0.0006) +[2026-07-22 23:18:56,301][543983] Updated weights for policy 0, policy_version 43639 (0.0006) +[2026-07-22 23:18:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 22347776. Throughput: 0: 12626.5. Samples: 22361216. Policy #0 lag: (min: 63.0, avg: 79.7, max: 127.0) +[2026-07-22 23:18:57,287][543203] Avg episode reward: [(0, '1912.927')] +[2026-07-22 23:18:57,401][543983] Updated weights for policy 0, policy_version 43650 (0.0006) +[2026-07-22 23:18:57,690][543983] Updated weights for policy 0, policy_version 43660 (0.0006) +[2026-07-22 23:18:57,997][543983] Updated weights for policy 0, policy_version 43671 (0.0006) +[2026-07-22 23:18:58,333][543983] Updated weights for policy 0, policy_version 43683 (0.0006) +[2026-07-22 23:18:58,615][543983] Updated weights for policy 0, policy_version 43693 (0.0006) +[2026-07-22 23:18:58,905][543983] Updated weights for policy 0, policy_version 43703 (0.0007) +[2026-07-22 23:18:59,992][543983] Updated weights for policy 0, policy_version 43714 (0.0007) +[2026-07-22 23:19:00,271][543983] Updated weights for policy 0, policy_version 43724 (0.0007) +[2026-07-22 23:19:00,581][543983] Updated weights for policy 0, policy_version 43735 (0.0006) +[2026-07-22 23:19:00,866][543983] Updated weights for policy 0, policy_version 43745 (0.0006) +[2026-07-22 23:19:01,200][543983] Updated weights for policy 0, policy_version 43756 (0.0006) +[2026-07-22 23:19:01,476][543983] Updated weights for policy 0, policy_version 43766 (0.0006) +[2026-07-22 23:19:02,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 22413312. Throughput: 0: 12703.3. Samples: 22437632. Policy #0 lag: (min: 63.0, avg: 79.7, max: 127.0) +[2026-07-22 23:19:02,287][543203] Avg episode reward: [(0, '1939.543')] +[2026-07-22 23:19:02,502][543983] Updated weights for policy 0, policy_version 43776 (0.0007) +[2026-07-22 23:19:02,792][543983] Updated weights for policy 0, policy_version 43786 (0.0008) +[2026-07-22 23:19:03,063][543983] Updated weights for policy 0, policy_version 43796 (0.0006) +[2026-07-22 23:19:03,344][543983] Updated weights for policy 0, policy_version 43806 (0.0006) +[2026-07-22 23:19:03,632][543983] Updated weights for policy 0, policy_version 43816 (0.0006) +[2026-07-22 23:19:03,913][543983] Updated weights for policy 0, policy_version 43826 (0.0006) +[2026-07-22 23:19:05,008][543983] Updated weights for policy 0, policy_version 43837 (0.0006) +[2026-07-22 23:19:05,323][543983] Updated weights for policy 0, policy_version 43848 (0.0006) +[2026-07-22 23:19:05,614][543983] Updated weights for policy 0, policy_version 43858 (0.0006) +[2026-07-22 23:19:05,892][543983] Updated weights for policy 0, policy_version 43868 (0.0006) +[2026-07-22 23:19:06,177][543983] Updated weights for policy 0, policy_version 43878 (0.0006) +[2026-07-22 23:19:06,465][543983] Updated weights for policy 0, policy_version 43888 (0.0006) +[2026-07-22 23:19:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 22478848. Throughput: 0: 12888.2. Samples: 22482176. Policy #0 lag: (min: 63.0, avg: 79.7, max: 127.0) +[2026-07-22 23:19:07,287][543203] Avg episode reward: [(0, '1947.977')] +[2026-07-22 23:19:07,501][543983] Updated weights for policy 0, policy_version 43898 (0.0006) +[2026-07-22 23:19:07,830][543983] Updated weights for policy 0, policy_version 43910 (0.0006) +[2026-07-22 23:19:08,108][543983] Updated weights for policy 0, policy_version 43920 (0.0006) +[2026-07-22 23:19:08,393][543983] Updated weights for policy 0, policy_version 43930 (0.0006) +[2026-07-22 23:19:08,685][543983] Updated weights for policy 0, policy_version 43940 (0.0006) +[2026-07-22 23:19:08,978][543983] Updated weights for policy 0, policy_version 43950 (0.0006) +[2026-07-22 23:19:09,246][543983] Updated weights for policy 0, policy_version 43960 (0.0006) +[2026-07-22 23:19:10,383][543983] Updated weights for policy 0, policy_version 43972 (0.0006) +[2026-07-22 23:19:10,674][543983] Updated weights for policy 0, policy_version 43982 (0.0006) +[2026-07-22 23:19:10,951][543983] Updated weights for policy 0, policy_version 43992 (0.0006) +[2026-07-22 23:19:11,223][543983] Updated weights for policy 0, policy_version 44002 (0.0006) +[2026-07-22 23:19:11,516][543983] Updated weights for policy 0, policy_version 44012 (0.0006) +[2026-07-22 23:19:11,811][543983] Updated weights for policy 0, policy_version 44022 (0.0006) +[2026-07-22 23:19:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 22544384. Throughput: 0: 12757.3. Samples: 22555392. Policy #0 lag: (min: 63.0, avg: 79.7, max: 127.0) +[2026-07-22 23:19:12,287][543203] Avg episode reward: [(0, '1948.642')] +[2026-07-22 23:19:12,863][543983] Updated weights for policy 0, policy_version 44032 (0.0006) +[2026-07-22 23:19:13,181][543983] Updated weights for policy 0, policy_version 44043 (0.0006) +[2026-07-22 23:19:13,457][543983] Updated weights for policy 0, policy_version 44053 (0.0007) +[2026-07-22 23:19:13,732][543983] Updated weights for policy 0, policy_version 44063 (0.0007) +[2026-07-22 23:19:14,061][543983] Updated weights for policy 0, policy_version 44074 (0.0006) +[2026-07-22 23:19:14,350][543983] Updated weights for policy 0, policy_version 44085 (0.0006) +[2026-07-22 23:19:15,388][543983] Updated weights for policy 0, policy_version 44095 (0.0006) +[2026-07-22 23:19:15,677][543983] Updated weights for policy 0, policy_version 44105 (0.0006) +[2026-07-22 23:19:15,960][543983] Updated weights for policy 0, policy_version 44115 (0.0006) +[2026-07-22 23:19:16,263][543983] Updated weights for policy 0, policy_version 44126 (0.0006) +[2026-07-22 23:19:16,545][543983] Updated weights for policy 0, policy_version 44136 (0.0006) +[2026-07-22 23:19:16,829][543983] Updated weights for policy 0, policy_version 44146 (0.0006) +[2026-07-22 23:19:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 22609920. Throughput: 0: 12626.5. Samples: 22627456. Policy #0 lag: (min: 63.0, avg: 79.7, max: 127.0) +[2026-07-22 23:19:17,287][543203] Avg episode reward: [(0, '1944.087')] +[2026-07-22 23:19:17,295][543696] Saving results/checkpoints/memory/rollout_teacher/flappy_teacher_fixed_l3_obs30_seed0/checkpoint_p0/checkpoint_000044152_22609920.pth... +[2026-07-22 23:19:17,926][543983] Updated weights for policy 0, policy_version 44156 (0.0006) +[2026-07-22 23:19:18,236][543983] Updated weights for policy 0, policy_version 44167 (0.0006) +[2026-07-22 23:19:18,504][543983] Updated weights for policy 0, policy_version 44177 (0.0006) +[2026-07-22 23:19:18,800][543983] Updated weights for policy 0, policy_version 44187 (0.0006) +[2026-07-22 23:19:19,086][543983] Updated weights for policy 0, policy_version 44197 (0.0007) +[2026-07-22 23:19:19,391][543983] Updated weights for policy 0, policy_version 44208 (0.0006) +[2026-07-22 23:19:20,435][543983] Updated weights for policy 0, policy_version 44218 (0.0006) +[2026-07-22 23:19:20,725][543983] Updated weights for policy 0, policy_version 44228 (0.0007) +[2026-07-22 23:19:21,025][543983] Updated weights for policy 0, policy_version 44239 (0.0006) +[2026-07-22 23:19:21,319][543983] Updated weights for policy 0, policy_version 44249 (0.0006) +[2026-07-22 23:19:21,633][543983] Updated weights for policy 0, policy_version 44260 (0.0006) +[2026-07-22 23:19:21,940][543983] Updated weights for policy 0, policy_version 44271 (0.0006) +[2026-07-22 23:19:22,287][543203] Fps is (10 sec: 13107.1, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 22675456. Throughput: 0: 12663.4. Samples: 22665600. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:19:22,288][543203] Avg episode reward: [(0, '1956.619')] +[2026-07-22 23:19:22,999][543983] Updated weights for policy 0, policy_version 44281 (0.0006) +[2026-07-22 23:19:23,319][543983] Updated weights for policy 0, policy_version 44292 (0.0007) +[2026-07-22 23:19:23,620][543983] Updated weights for policy 0, policy_version 44302 (0.0007) +[2026-07-22 23:19:23,883][543983] Updated weights for policy 0, policy_version 44312 (0.0006) +[2026-07-22 23:19:24,185][543983] Updated weights for policy 0, policy_version 44323 (0.0007) +[2026-07-22 23:19:24,490][543983] Updated weights for policy 0, policy_version 44333 (0.0007) +[2026-07-22 23:19:24,783][543983] Updated weights for policy 0, policy_version 44344 (0.0007) +[2026-07-22 23:19:25,890][543983] Updated weights for policy 0, policy_version 44355 (0.0006) +[2026-07-22 23:19:26,172][543983] Updated weights for policy 0, policy_version 44365 (0.0006) +[2026-07-22 23:19:26,489][543983] Updated weights for policy 0, policy_version 44376 (0.0006) +[2026-07-22 23:19:26,764][543983] Updated weights for policy 0, policy_version 44386 (0.0006) +[2026-07-22 23:19:27,064][543983] Updated weights for policy 0, policy_version 44396 (0.0006) +[2026-07-22 23:19:27,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 22708224. Throughput: 0: 12913.8. Samples: 22749056. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:19:27,287][543203] Avg episode reward: [(0, '1950.921')] +[2026-07-22 23:19:27,337][543983] Updated weights for policy 0, policy_version 44406 (0.0007) +[2026-07-22 23:19:28,379][543983] Updated weights for policy 0, policy_version 44417 (0.0007) +[2026-07-22 23:19:28,674][543983] Updated weights for policy 0, policy_version 44427 (0.0007) +[2026-07-22 23:19:28,957][543983] Updated weights for policy 0, policy_version 44437 (0.0007) +[2026-07-22 23:19:29,239][543983] Updated weights for policy 0, policy_version 44447 (0.0007) +[2026-07-22 23:19:29,521][543983] Updated weights for policy 0, policy_version 44457 (0.0006) +[2026-07-22 23:19:29,813][543983] Updated weights for policy 0, policy_version 44467 (0.0006) +[2026-07-22 23:19:30,862][543983] Updated weights for policy 0, policy_version 44477 (0.0006) +[2026-07-22 23:19:31,147][543983] Updated weights for policy 0, policy_version 44487 (0.0006) +[2026-07-22 23:19:31,421][543983] Updated weights for policy 0, policy_version 44497 (0.0006) +[2026-07-22 23:19:31,714][543983] Updated weights for policy 0, policy_version 44507 (0.0006) +[2026-07-22 23:19:31,997][543983] Updated weights for policy 0, policy_version 44517 (0.0006) +[2026-07-22 23:19:32,286][543203] Fps is (10 sec: 9830.5, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 22773760. Throughput: 0: 12632.2. Samples: 22820992. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:19:32,287][543203] Avg episode reward: [(0, '1917.325')] +[2026-07-22 23:19:32,304][543983] Updated weights for policy 0, policy_version 44528 (0.0006) +[2026-07-22 23:19:33,338][543983] Updated weights for policy 0, policy_version 44538 (0.0006) +[2026-07-22 23:19:33,623][543983] Updated weights for policy 0, policy_version 44548 (0.0006) +[2026-07-22 23:19:33,908][543983] Updated weights for policy 0, policy_version 44558 (0.0006) +[2026-07-22 23:19:34,181][543983] Updated weights for policy 0, policy_version 44568 (0.0006) +[2026-07-22 23:19:34,469][543983] Updated weights for policy 0, policy_version 44578 (0.0006) +[2026-07-22 23:19:34,779][543983] Updated weights for policy 0, policy_version 44589 (0.0006) +[2026-07-22 23:19:35,062][543983] Updated weights for policy 0, policy_version 44599 (0.0006) +[2026-07-22 23:19:36,132][543983] Updated weights for policy 0, policy_version 44609 (0.0006) +[2026-07-22 23:19:36,420][543983] Updated weights for policy 0, policy_version 44619 (0.0006) +[2026-07-22 23:19:36,737][543983] Updated weights for policy 0, policy_version 44630 (0.0006) +[2026-07-22 23:19:37,013][543983] Updated weights for policy 0, policy_version 44640 (0.0006) +[2026-07-22 23:19:37,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 22839296. Throughput: 0: 12635.0. Samples: 22857088. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:19:37,287][543203] Avg episode reward: [(0, '1917.325')] +[2026-07-22 23:19:37,310][543983] Updated weights for policy 0, policy_version 44651 (0.0006) +[2026-07-22 23:19:37,593][543983] Updated weights for policy 0, policy_version 44661 (0.0006) +[2026-07-22 23:19:38,626][543983] Updated weights for policy 0, policy_version 44671 (0.0006) +[2026-07-22 23:19:38,943][543983] Updated weights for policy 0, policy_version 44682 (0.0006) +[2026-07-22 23:19:39,255][543983] Updated weights for policy 0, policy_version 44693 (0.0006) +[2026-07-22 23:19:39,538][543983] Updated weights for policy 0, policy_version 44703 (0.0006) +[2026-07-22 23:19:39,835][543983] Updated weights for policy 0, policy_version 44713 (0.0006) +[2026-07-22 23:19:40,135][543983] Updated weights for policy 0, policy_version 44724 (0.0006) +[2026-07-22 23:19:41,174][543983] Updated weights for policy 0, policy_version 44735 (0.0006) +[2026-07-22 23:19:41,500][543983] Updated weights for policy 0, policy_version 44746 (0.0006) +[2026-07-22 23:19:41,776][543983] Updated weights for policy 0, policy_version 44756 (0.0006) +[2026-07-22 23:19:42,074][543983] Updated weights for policy 0, policy_version 44766 (0.0006) +[2026-07-22 23:19:42,286][543203] Fps is (10 sec: 13107.3, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 22904832. Throughput: 0: 12831.3. Samples: 22938624. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:19:42,287][543203] Avg episode reward: [(0, '1952.536')] +[2026-07-22 23:19:42,356][543983] Updated weights for policy 0, policy_version 44776 (0.0006) +[2026-07-22 23:19:42,670][543983] Updated weights for policy 0, policy_version 44787 (0.0007) +[2026-07-22 23:19:43,742][543983] Updated weights for policy 0, policy_version 44798 (0.0006) +[2026-07-22 23:19:44,049][543983] Updated weights for policy 0, policy_version 44809 (0.0006) +[2026-07-22 23:19:44,334][543983] Updated weights for policy 0, policy_version 44819 (0.0006) +[2026-07-22 23:19:44,625][543983] Updated weights for policy 0, policy_version 44829 (0.0006) +[2026-07-22 23:19:44,906][543983] Updated weights for policy 0, policy_version 44839 (0.0006) +[2026-07-22 23:19:45,191][543983] Updated weights for policy 0, policy_version 44849 (0.0006) +[2026-07-22 23:19:46,216][543983] Updated weights for policy 0, policy_version 44859 (0.0006) +[2026-07-22 23:19:46,525][543983] Updated weights for policy 0, policy_version 44870 (0.0006) +[2026-07-22 23:19:46,809][543983] Updated weights for policy 0, policy_version 44880 (0.0006) +[2026-07-22 23:19:47,094][543983] Updated weights for policy 0, policy_version 44890 (0.0006) +[2026-07-22 23:19:47,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 22970368. Throughput: 0: 12797.1. Samples: 23013504. Policy #0 lag: (min: 63.0, avg: 78.8, max: 127.0) +[2026-07-22 23:19:47,287][543203] Avg episode reward: [(0, '1923.358')] +[2026-07-22 23:19:47,470][543983] Updated weights for policy 0, policy_version 44903 (0.0006) +[2026-07-22 23:19:47,777][543983] Updated weights for policy 0, policy_version 44914 (0.0007) +[2026-07-22 23:19:48,873][543983] Updated weights for policy 0, policy_version 44925 (0.0006) +[2026-07-22 23:19:49,171][543983] Updated weights for policy 0, policy_version 44936 (0.0006) +[2026-07-22 23:19:49,459][543983] Updated weights for policy 0, policy_version 44946 (0.0006) +[2026-07-22 23:19:49,770][543983] Updated weights for policy 0, policy_version 44957 (0.0006) +[2026-07-22 23:19:50,072][543983] Updated weights for policy 0, policy_version 44968 (0.0006) +[2026-07-22 23:19:50,370][543983] Updated weights for policy 0, policy_version 44978 (0.0007) +[2026-07-22 23:19:51,426][543983] Updated weights for policy 0, policy_version 44988 (0.0006) +[2026-07-22 23:19:51,732][543983] Updated weights for policy 0, policy_version 44999 (0.0006) +[2026-07-22 23:19:52,040][543983] Updated weights for policy 0, policy_version 45010 (0.0006) +[2026-07-22 23:19:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 23035904. Throughput: 0: 12617.9. Samples: 23049984. Policy #0 lag: (min: 63.0, avg: 79.0, max: 127.0) +[2026-07-22 23:19:52,287][543203] Avg episode reward: [(0, '1923.358')] +[2026-07-22 23:19:52,326][543983] Updated weights for policy 0, policy_version 45020 (0.0006) +[2026-07-22 23:19:52,604][543983] Updated weights for policy 0, policy_version 45030 (0.0007) +[2026-07-22 23:19:52,894][543983] Updated weights for policy 0, policy_version 45040 (0.0007) +[2026-07-22 23:19:53,951][543983] Updated weights for policy 0, policy_version 45050 (0.0007) +[2026-07-22 23:19:54,264][543983] Updated weights for policy 0, policy_version 45061 (0.0006) +[2026-07-22 23:19:54,533][543983] Updated weights for policy 0, policy_version 45071 (0.0006) +[2026-07-22 23:19:54,832][543983] Updated weights for policy 0, policy_version 45081 (0.0006) +[2026-07-22 23:19:55,114][543983] Updated weights for policy 0, policy_version 45091 (0.0006) +[2026-07-22 23:19:55,395][543983] Updated weights for policy 0, policy_version 45101 (0.0006) +[2026-07-22 23:19:55,683][543983] Updated weights for policy 0, policy_version 45111 (0.0006) +[2026-07-22 23:19:56,740][543983] Updated weights for policy 0, policy_version 45121 (0.0006) +[2026-07-22 23:19:57,027][543983] Updated weights for policy 0, policy_version 45131 (0.0006) +[2026-07-22 23:19:57,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 23101440. Throughput: 0: 12603.7. Samples: 23122560. Policy #0 lag: (min: 63.0, avg: 79.0, max: 127.0) +[2026-07-22 23:19:57,287][543203] Avg episode reward: [(0, '1948.098')] +[2026-07-22 23:19:57,312][543983] Updated weights for policy 0, policy_version 45141 (0.0006) +[2026-07-22 23:19:57,595][543983] Updated weights for policy 0, policy_version 45151 (0.0006) +[2026-07-22 23:19:57,871][543983] Updated weights for policy 0, policy_version 45161 (0.0006) +[2026-07-22 23:19:58,188][543983] Updated weights for policy 0, policy_version 45172 (0.0006) +[2026-07-22 23:19:59,230][543983] Updated weights for policy 0, policy_version 45182 (0.0006) +[2026-07-22 23:19:59,514][543983] Updated weights for policy 0, policy_version 45193 (0.0006) +[2026-07-22 23:19:59,826][543983] Updated weights for policy 0, policy_version 45204 (0.0007) +[2026-07-22 23:20:00,115][543983] Updated weights for policy 0, policy_version 45214 (0.0006) +[2026-07-22 23:20:00,397][543983] Updated weights for policy 0, policy_version 45224 (0.0006) +[2026-07-22 23:20:00,677][543983] Updated weights for policy 0, policy_version 45234 (0.0006) +[2026-07-22 23:20:01,766][543983] Updated weights for policy 0, policy_version 45245 (0.0006) +[2026-07-22 23:20:02,046][543983] Updated weights for policy 0, policy_version 45255 (0.0006) +[2026-07-22 23:20:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 23166976. Throughput: 0: 12882.5. Samples: 23207168. Policy #0 lag: (min: 63.0, avg: 79.0, max: 127.0) +[2026-07-22 23:20:02,287][543203] Avg episode reward: [(0, '1950.238')] +[2026-07-22 23:20:02,364][543983] Updated weights for policy 0, policy_version 45266 (0.0007) +[2026-07-22 23:20:02,644][543983] Updated weights for policy 0, policy_version 45276 (0.0007) +[2026-07-22 23:20:02,960][543983] Updated weights for policy 0, policy_version 45287 (0.0006) +[2026-07-22 23:20:03,246][543983] Updated weights for policy 0, policy_version 45297 (0.0006) +[2026-07-22 23:20:04,294][543983] Updated weights for policy 0, policy_version 45307 (0.0006) +[2026-07-22 23:20:04,608][543983] Updated weights for policy 0, policy_version 45318 (0.0006) +[2026-07-22 23:20:04,903][543983] Updated weights for policy 0, policy_version 45329 (0.0006) +[2026-07-22 23:20:05,210][543983] Updated weights for policy 0, policy_version 45340 (0.0007) +[2026-07-22 23:20:05,504][543983] Updated weights for policy 0, policy_version 45350 (0.0006) +[2026-07-22 23:20:05,819][543983] Updated weights for policy 0, policy_version 45361 (0.0007) +[2026-07-22 23:20:06,899][543983] Updated weights for policy 0, policy_version 45372 (0.0006) +[2026-07-22 23:20:07,164][543983] Updated weights for policy 0, policy_version 45382 (0.0006) +[2026-07-22 23:20:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 23232512. Throughput: 0: 12845.5. Samples: 23243648. Policy #0 lag: (min: 63.0, avg: 79.0, max: 127.0) +[2026-07-22 23:20:07,287][543203] Avg episode reward: [(0, '1963.447')] +[2026-07-22 23:20:07,438][543983] Updated weights for policy 0, policy_version 45392 (0.0006) +[2026-07-22 23:20:07,727][543983] Updated weights for policy 0, policy_version 45402 (0.0006) +[2026-07-22 23:20:08,010][543983] Updated weights for policy 0, policy_version 45412 (0.0006) +[2026-07-22 23:20:08,291][543983] Updated weights for policy 0, policy_version 45422 (0.0006) +[2026-07-22 23:20:08,563][543983] Updated weights for policy 0, policy_version 45432 (0.0006) +[2026-07-22 23:20:09,646][543983] Updated weights for policy 0, policy_version 45442 (0.0006) +[2026-07-22 23:20:09,939][543983] Updated weights for policy 0, policy_version 45452 (0.0006) +[2026-07-22 23:20:10,253][543983] Updated weights for policy 0, policy_version 45463 (0.0006) +[2026-07-22 23:20:10,531][543983] Updated weights for policy 0, policy_version 45473 (0.0007) +[2026-07-22 23:20:10,809][543983] Updated weights for policy 0, policy_version 45483 (0.0006) +[2026-07-22 23:20:11,106][543983] Updated weights for policy 0, policy_version 45493 (0.0009) +[2026-07-22 23:20:12,128][543983] Updated weights for policy 0, policy_version 45503 (0.0007) +[2026-07-22 23:20:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 23298048. Throughput: 0: 12603.7. Samples: 23316224. Policy #0 lag: (min: 63.0, avg: 79.0, max: 127.0) +[2026-07-22 23:20:12,287][543203] Avg episode reward: [(0, '1978.273')] +[2026-07-22 23:20:12,436][543983] Updated weights for policy 0, policy_version 45514 (0.0006) +[2026-07-22 23:20:12,712][543983] Updated weights for policy 0, policy_version 45524 (0.0006) +[2026-07-22 23:20:13,007][543983] Updated weights for policy 0, policy_version 45534 (0.0006) +[2026-07-22 23:20:13,278][543983] Updated weights for policy 0, policy_version 45544 (0.0008) +[2026-07-22 23:20:13,568][543983] Updated weights for policy 0, policy_version 45554 (0.0006) +[2026-07-22 23:20:14,636][543983] Updated weights for policy 0, policy_version 45564 (0.0006) +[2026-07-22 23:20:14,917][543983] Updated weights for policy 0, policy_version 45574 (0.0007) +[2026-07-22 23:20:15,185][543983] Updated weights for policy 0, policy_version 45584 (0.0006) +[2026-07-22 23:20:15,472][543983] Updated weights for policy 0, policy_version 45594 (0.0006) +[2026-07-22 23:20:15,759][543983] Updated weights for policy 0, policy_version 45604 (0.0006) +[2026-07-22 23:20:16,028][543983] Updated weights for policy 0, policy_version 45614 (0.0006) +[2026-07-22 23:20:17,134][543983] Updated weights for policy 0, policy_version 45625 (0.0006) +[2026-07-22 23:20:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 23363584. Throughput: 0: 12785.8. Samples: 23396352. Policy #0 lag: (min: 63.0, avg: 79.0, max: 127.0) +[2026-07-22 23:20:17,287][543203] Avg episode reward: [(0, '1991.612')] +[2026-07-22 23:20:17,417][543983] Updated weights for policy 0, policy_version 45635 (0.0006) +[2026-07-22 23:20:17,711][543983] Updated weights for policy 0, policy_version 45645 (0.0006) +[2026-07-22 23:20:17,993][543983] Updated weights for policy 0, policy_version 45655 (0.0006) +[2026-07-22 23:20:18,282][543983] Updated weights for policy 0, policy_version 45666 (0.0006) +[2026-07-22 23:20:18,580][543983] Updated weights for policy 0, policy_version 45676 (0.0006) +[2026-07-22 23:20:18,878][543983] Updated weights for policy 0, policy_version 45687 (0.0006) +[2026-07-22 23:20:19,934][543983] Updated weights for policy 0, policy_version 45697 (0.0007) +[2026-07-22 23:20:20,215][543983] Updated weights for policy 0, policy_version 45707 (0.0006) +[2026-07-22 23:20:20,520][543983] Updated weights for policy 0, policy_version 45717 (0.0006) +[2026-07-22 23:20:20,838][543983] Updated weights for policy 0, policy_version 45729 (0.0006) +[2026-07-22 23:20:21,142][543983] Updated weights for policy 0, policy_version 45739 (0.0006) +[2026-07-22 23:20:21,402][543983] Updated weights for policy 0, policy_version 45749 (0.0006) +[2026-07-22 23:20:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 23429120. Throughput: 0: 12896.7. Samples: 23437440. Policy #0 lag: (min: 62.0, avg: 78.9, max: 126.0) +[2026-07-22 23:20:22,287][543203] Avg episode reward: [(0, '1985.848')] +[2026-07-22 23:20:22,464][543983] Updated weights for policy 0, policy_version 45759 (0.0007) +[2026-07-22 23:20:22,755][543983] Updated weights for policy 0, policy_version 45769 (0.0006) +[2026-07-22 23:20:23,041][543983] Updated weights for policy 0, policy_version 45779 (0.0006) +[2026-07-22 23:20:23,350][543983] Updated weights for policy 0, policy_version 45790 (0.0006) +[2026-07-22 23:20:23,631][543983] Updated weights for policy 0, policy_version 45800 (0.0006) +[2026-07-22 23:20:23,911][543983] Updated weights for policy 0, policy_version 45810 (0.0007) +[2026-07-22 23:20:24,958][543983] Updated weights for policy 0, policy_version 45820 (0.0006) +[2026-07-22 23:20:25,252][543983] Updated weights for policy 0, policy_version 45830 (0.0006) +[2026-07-22 23:20:25,516][543983] Updated weights for policy 0, policy_version 45840 (0.0007) +[2026-07-22 23:20:25,809][543983] Updated weights for policy 0, policy_version 45850 (0.0006) +[2026-07-22 23:20:26,096][543983] Updated weights for policy 0, policy_version 45860 (0.0006) +[2026-07-22 23:20:26,375][543983] Updated weights for policy 0, policy_version 45870 (0.0007) +[2026-07-22 23:20:27,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 23494656. Throughput: 0: 12691.9. Samples: 23509760. Policy #0 lag: (min: 62.0, avg: 78.9, max: 126.0) +[2026-07-22 23:20:27,287][543203] Avg episode reward: [(0, '1988.837')] +[2026-07-22 23:20:27,457][543983] Updated weights for policy 0, policy_version 45881 (0.0006) +[2026-07-22 23:20:27,760][543983] Updated weights for policy 0, policy_version 45892 (0.0006) +[2026-07-22 23:20:28,051][543983] Updated weights for policy 0, policy_version 45902 (0.0006) +[2026-07-22 23:20:28,320][543983] Updated weights for policy 0, policy_version 45912 (0.0006) +[2026-07-22 23:20:28,607][543983] Updated weights for policy 0, policy_version 45922 (0.0006) +[2026-07-22 23:20:28,900][543983] Updated weights for policy 0, policy_version 45932 (0.0006) +[2026-07-22 23:20:29,182][543983] Updated weights for policy 0, policy_version 45942 (0.0006) +[2026-07-22 23:20:30,242][543983] Updated weights for policy 0, policy_version 45952 (0.0006) +[2026-07-22 23:20:30,532][543983] Updated weights for policy 0, policy_version 45962 (0.0006) +[2026-07-22 23:20:30,826][543983] Updated weights for policy 0, policy_version 45973 (0.0006) +[2026-07-22 23:20:31,140][543983] Updated weights for policy 0, policy_version 45984 (0.0006) +[2026-07-22 23:20:31,423][543983] Updated weights for policy 0, policy_version 45994 (0.0006) +[2026-07-22 23:20:31,722][543983] Updated weights for policy 0, policy_version 46004 (0.0006) +[2026-07-22 23:20:32,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 23560192. Throughput: 0: 12649.3. Samples: 23582720. Policy #0 lag: (min: 62.0, avg: 78.9, max: 126.0) +[2026-07-22 23:20:32,287][543203] Avg episode reward: [(0, '1966.202')] +[2026-07-22 23:20:32,804][543983] Updated weights for policy 0, policy_version 46015 (0.0006) +[2026-07-22 23:20:33,077][543983] Updated weights for policy 0, policy_version 46025 (0.0007) +[2026-07-22 23:20:33,367][543983] Updated weights for policy 0, policy_version 46035 (0.0006) +[2026-07-22 23:20:33,640][543983] Updated weights for policy 0, policy_version 46045 (0.0006) +[2026-07-22 23:20:33,921][543983] Updated weights for policy 0, policy_version 46055 (0.0006) +[2026-07-22 23:20:34,249][543983] Updated weights for policy 0, policy_version 46066 (0.0006) +[2026-07-22 23:20:35,329][543983] Updated weights for policy 0, policy_version 46077 (0.0007) +[2026-07-22 23:20:35,604][543983] Updated weights for policy 0, policy_version 46087 (0.0006) +[2026-07-22 23:20:35,894][543983] Updated weights for policy 0, policy_version 46097 (0.0006) +[2026-07-22 23:20:36,164][543983] Updated weights for policy 0, policy_version 46107 (0.0006) +[2026-07-22 23:20:36,447][543983] Updated weights for policy 0, policy_version 46117 (0.0006) +[2026-07-22 23:20:36,740][543983] Updated weights for policy 0, policy_version 46127 (0.0006) +[2026-07-22 23:20:37,286][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 23625728. Throughput: 0: 12765.9. Samples: 23624448. Policy #0 lag: (min: 62.0, avg: 78.9, max: 126.0) +[2026-07-22 23:20:37,287][543203] Avg episode reward: [(0, '1969.335')] +[2026-07-22 23:20:37,796][543983] Updated weights for policy 0, policy_version 46137 (0.0006) +[2026-07-22 23:20:38,086][543983] Updated weights for policy 0, policy_version 46147 (0.0006) +[2026-07-22 23:20:38,384][543983] Updated weights for policy 0, policy_version 46158 (0.0006) +[2026-07-22 23:20:38,699][543983] Updated weights for policy 0, policy_version 46169 (0.0006) +[2026-07-22 23:20:38,977][543983] Updated weights for policy 0, policy_version 46179 (0.0006) +[2026-07-22 23:20:39,257][543983] Updated weights for policy 0, policy_version 46189 (0.0006) +[2026-07-22 23:20:39,565][543983] Updated weights for policy 0, policy_version 46200 (0.0006) +[2026-07-22 23:20:40,633][543983] Updated weights for policy 0, policy_version 46210 (0.0006) +[2026-07-22 23:20:40,910][543983] Updated weights for policy 0, policy_version 46220 (0.0006) +[2026-07-22 23:20:41,210][543983] Updated weights for policy 0, policy_version 46231 (0.0006) +[2026-07-22 23:20:41,514][543983] Updated weights for policy 0, policy_version 46241 (0.0006) +[2026-07-22 23:20:41,782][543983] Updated weights for policy 0, policy_version 46251 (0.0007) +[2026-07-22 23:20:42,063][543983] Updated weights for policy 0, policy_version 46261 (0.0006) +[2026-07-22 23:20:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 23691264. Throughput: 0: 12905.2. Samples: 23703296. Policy #0 lag: (min: 62.0, avg: 78.9, max: 126.0) +[2026-07-22 23:20:42,287][543203] Avg episode reward: [(0, '1963.793')] +[2026-07-22 23:20:43,176][543983] Updated weights for policy 0, policy_version 46272 (0.0006) +[2026-07-22 23:20:43,463][543983] Updated weights for policy 0, policy_version 46282 (0.0006) +[2026-07-22 23:20:43,767][543983] Updated weights for policy 0, policy_version 46293 (0.0006) +[2026-07-22 23:20:44,049][543983] Updated weights for policy 0, policy_version 46303 (0.0006) +[2026-07-22 23:20:44,328][543983] Updated weights for policy 0, policy_version 46313 (0.0006) +[2026-07-22 23:20:44,620][543983] Updated weights for policy 0, policy_version 46323 (0.0006) +[2026-07-22 23:20:45,696][543983] Updated weights for policy 0, policy_version 46334 (0.0006) +[2026-07-22 23:20:45,976][543983] Updated weights for policy 0, policy_version 46344 (0.0006) +[2026-07-22 23:20:46,254][543983] Updated weights for policy 0, policy_version 46354 (0.0007) +[2026-07-22 23:20:46,575][543983] Updated weights for policy 0, policy_version 46365 (0.0006) +[2026-07-22 23:20:46,878][543983] Updated weights for policy 0, policy_version 46376 (0.0006) +[2026-07-22 23:20:47,153][543983] Updated weights for policy 0, policy_version 46386 (0.0006) +[2026-07-22 23:20:47,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 23724032. Throughput: 0: 12649.3. Samples: 23776384. Policy #0 lag: (min: 62.0, avg: 78.9, max: 126.0) +[2026-07-22 23:20:47,287][543203] Avg episode reward: [(0, '1943.126')] +[2026-07-22 23:20:48,221][543983] Updated weights for policy 0, policy_version 46396 (0.0007) +[2026-07-22 23:20:48,509][543983] Updated weights for policy 0, policy_version 46406 (0.0006) +[2026-07-22 23:20:48,780][543983] Updated weights for policy 0, policy_version 46416 (0.0006) +[2026-07-22 23:20:49,060][543983] Updated weights for policy 0, policy_version 46426 (0.0007) +[2026-07-22 23:20:49,358][543983] Updated weights for policy 0, policy_version 46436 (0.0006) +[2026-07-22 23:20:49,649][543983] Updated weights for policy 0, policy_version 46446 (0.0007) +[2026-07-22 23:20:49,927][543983] Updated weights for policy 0, policy_version 46456 (0.0008) +[2026-07-22 23:20:50,980][543983] Updated weights for policy 0, policy_version 46467 (0.0006) +[2026-07-22 23:20:51,273][543983] Updated weights for policy 0, policy_version 46477 (0.0009) +[2026-07-22 23:20:51,544][543983] Updated weights for policy 0, policy_version 46487 (0.0006) +[2026-07-22 23:20:51,876][543983] Updated weights for policy 0, policy_version 46498 (0.0007) +[2026-07-22 23:20:52,184][543983] Updated weights for policy 0, policy_version 46508 (0.0006) +[2026-07-22 23:20:52,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 23789568. Throughput: 0: 12649.3. Samples: 23812864. Policy #0 lag: (min: 62.0, avg: 78.9, max: 126.0) +[2026-07-22 23:20:52,287][543203] Avg episode reward: [(0, '1951.078')] +[2026-07-22 23:20:52,464][543983] Updated weights for policy 0, policy_version 46518 (0.0007) +[2026-07-22 23:20:53,493][543983] Updated weights for policy 0, policy_version 46528 (0.0006) +[2026-07-22 23:20:53,779][543983] Updated weights for policy 0, policy_version 46538 (0.0006) +[2026-07-22 23:20:54,091][543983] Updated weights for policy 0, policy_version 46549 (0.0006) +[2026-07-22 23:20:54,384][543983] Updated weights for policy 0, policy_version 46559 (0.0006) +[2026-07-22 23:20:54,653][543983] Updated weights for policy 0, policy_version 46569 (0.0006) +[2026-07-22 23:20:54,937][543983] Updated weights for policy 0, policy_version 46579 (0.0006) +[2026-07-22 23:20:56,012][543983] Updated weights for policy 0, policy_version 46589 (0.0006) +[2026-07-22 23:20:56,297][543983] Updated weights for policy 0, policy_version 46599 (0.0007) +[2026-07-22 23:20:56,635][543983] Updated weights for policy 0, policy_version 46611 (0.0006) +[2026-07-22 23:20:56,926][543983] Updated weights for policy 0, policy_version 46621 (0.0006) +[2026-07-22 23:20:57,225][543983] Updated weights for policy 0, policy_version 46632 (0.0006) +[2026-07-22 23:20:57,286][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 23855104. Throughput: 0: 12905.2. Samples: 23896960. Policy #0 lag: (min: 47.0, avg: 93.5, max: 107.0) +[2026-07-22 23:20:57,287][543203] Avg episode reward: [(0, '1949.838')] +[2026-07-22 23:20:57,506][543983] Updated weights for policy 0, policy_version 46642 (0.0007) +[2026-07-22 23:20:58,542][543983] Updated weights for policy 0, policy_version 46652 (0.0006) +[2026-07-22 23:20:58,842][543983] Updated weights for policy 0, policy_version 46663 (0.0006) +[2026-07-22 23:20:59,128][543983] Updated weights for policy 0, policy_version 46673 (0.0007) +[2026-07-22 23:20:59,426][543983] Updated weights for policy 0, policy_version 46683 (0.0006) +[2026-07-22 23:20:59,705][543983] Updated weights for policy 0, policy_version 46693 (0.0006) +[2026-07-22 23:21:00,046][543983] Updated weights for policy 0, policy_version 46705 (0.0006) +[2026-07-22 23:21:01,113][543983] Updated weights for policy 0, policy_version 46715 (0.0006) +[2026-07-22 23:21:01,398][543983] Updated weights for policy 0, policy_version 46725 (0.0007) +[2026-07-22 23:21:01,682][543983] Updated weights for policy 0, policy_version 46735 (0.0006) +[2026-07-22 23:21:01,989][543983] Updated weights for policy 0, policy_version 46746 (0.0007) +[2026-07-22 23:21:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 23920640. Throughput: 0: 12740.3. Samples: 23969664. Policy #0 lag: (min: 47.0, avg: 93.5, max: 107.0) +[2026-07-22 23:21:02,287][543203] Avg episode reward: [(0, '1976.737')] +[2026-07-22 23:21:02,293][543983] Updated weights for policy 0, policy_version 46756 (0.0006) +[2026-07-22 23:21:02,560][543983] Updated weights for policy 0, policy_version 46766 (0.0006) +[2026-07-22 23:21:03,634][543983] Updated weights for policy 0, policy_version 46777 (0.0006) +[2026-07-22 23:21:03,925][543983] Updated weights for policy 0, policy_version 46787 (0.0006) +[2026-07-22 23:21:04,254][543983] Updated weights for policy 0, policy_version 46799 (0.0006) +[2026-07-22 23:21:04,533][543983] Updated weights for policy 0, policy_version 46809 (0.0006) +[2026-07-22 23:21:04,866][543983] Updated weights for policy 0, policy_version 46820 (0.0006) +[2026-07-22 23:21:05,148][543983] Updated weights for policy 0, policy_version 46830 (0.0006) +[2026-07-22 23:21:05,422][543983] Updated weights for policy 0, policy_version 46840 (0.0006) +[2026-07-22 23:21:06,486][543983] Updated weights for policy 0, policy_version 46850 (0.0006) +[2026-07-22 23:21:06,779][543983] Updated weights for policy 0, policy_version 46860 (0.0006) +[2026-07-22 23:21:07,049][543983] Updated weights for policy 0, policy_version 46870 (0.0006) +[2026-07-22 23:21:07,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 23986176. Throughput: 0: 12635.0. Samples: 24006016. Policy #0 lag: (min: 47.0, avg: 93.5, max: 107.0) +[2026-07-22 23:21:07,287][543203] Avg episode reward: [(0, '2001.526')] +[2026-07-22 23:21:07,315][543983] Updated weights for policy 0, policy_version 46880 (0.0006) +[2026-07-22 23:21:07,612][543983] Updated weights for policy 0, policy_version 46890 (0.0007) +[2026-07-22 23:21:07,893][543983] Updated weights for policy 0, policy_version 46900 (0.0007) +[2026-07-22 23:21:08,977][543983] Updated weights for policy 0, policy_version 46911 (0.0007) +[2026-07-22 23:21:09,273][543983] Updated weights for policy 0, policy_version 46921 (0.0007) +[2026-07-22 23:21:09,548][543983] Updated weights for policy 0, policy_version 46931 (0.0006) +[2026-07-22 23:21:09,832][543983] Updated weights for policy 0, policy_version 46941 (0.0006) +[2026-07-22 23:21:10,122][543983] Updated weights for policy 0, policy_version 46951 (0.0006) +[2026-07-22 23:21:10,407][543983] Updated weights for policy 0, policy_version 46961 (0.0006) +[2026-07-22 23:21:11,461][543983] Updated weights for policy 0, policy_version 46971 (0.0006) +[2026-07-22 23:21:11,740][543983] Updated weights for policy 0, policy_version 46981 (0.0007) +[2026-07-22 23:21:12,050][543983] Updated weights for policy 0, policy_version 46992 (0.0006) +[2026-07-22 23:21:12,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 24051712. Throughput: 0: 12689.1. Samples: 24080768. Policy #0 lag: (min: 47.0, avg: 93.5, max: 107.0) +[2026-07-22 23:21:12,287][543203] Avg episode reward: [(0, '2001.526')] +[2026-07-22 23:21:12,353][543983] Updated weights for policy 0, policy_version 47003 (0.0006) +[2026-07-22 23:21:12,641][543983] Updated weights for policy 0, policy_version 47013 (0.0007) +[2026-07-22 23:21:12,959][543983] Updated weights for policy 0, policy_version 47024 (0.0007) +[2026-07-22 23:21:14,064][543983] Updated weights for policy 0, policy_version 47036 (0.0006) +[2026-07-22 23:21:14,372][543983] Updated weights for policy 0, policy_version 47046 (0.0006) +[2026-07-22 23:21:14,670][543983] Updated weights for policy 0, policy_version 47057 (0.0006) +[2026-07-22 23:21:14,979][543983] Updated weights for policy 0, policy_version 47068 (0.0006) +[2026-07-22 23:21:15,280][543983] Updated weights for policy 0, policy_version 47079 (0.0006) +[2026-07-22 23:21:15,571][543983] Updated weights for policy 0, policy_version 47089 (0.0006) +[2026-07-22 23:21:16,609][543983] Updated weights for policy 0, policy_version 47099 (0.0006) +[2026-07-22 23:21:16,888][543983] Updated weights for policy 0, policy_version 47109 (0.0006) +[2026-07-22 23:21:17,186][543983] Updated weights for policy 0, policy_version 47119 (0.0006) +[2026-07-22 23:21:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 24117248. Throughput: 0: 12899.6. Samples: 24163200. Policy #0 lag: (min: 47.0, avg: 93.5, max: 107.0) +[2026-07-22 23:21:17,287][543203] Avg episode reward: [(0, '1977.949')] +[2026-07-22 23:21:17,452][543983] Updated weights for policy 0, policy_version 47129 (0.0006) +[2026-07-22 23:21:17,746][543983] Updated weights for policy 0, policy_version 47139 (0.0006) +[2026-07-22 23:21:18,044][543983] Updated weights for policy 0, policy_version 47150 (0.0006) +[2026-07-22 23:21:18,328][543983] Updated weights for policy 0, policy_version 47160 (0.0006) +[2026-07-22 23:21:19,387][543983] Updated weights for policy 0, policy_version 47170 (0.0006) +[2026-07-22 23:21:19,698][543983] Updated weights for policy 0, policy_version 47181 (0.0006) +[2026-07-22 23:21:20,016][543983] Updated weights for policy 0, policy_version 47192 (0.0006) +[2026-07-22 23:21:20,299][543983] Updated weights for policy 0, policy_version 47202 (0.0006) +[2026-07-22 23:21:20,578][543983] Updated weights for policy 0, policy_version 47212 (0.0006) +[2026-07-22 23:21:20,907][543983] Updated weights for policy 0, policy_version 47224 (0.0006) +[2026-07-22 23:21:21,975][543983] Updated weights for policy 0, policy_version 47234 (0.0006) +[2026-07-22 23:21:22,265][543983] Updated weights for policy 0, policy_version 47244 (0.0006) +[2026-07-22 23:21:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 24182784. Throughput: 0: 12780.1. Samples: 24199552. Policy #0 lag: (min: 47.0, avg: 93.5, max: 107.0) +[2026-07-22 23:21:22,287][543203] Avg episode reward: [(0, '1958.134')] +[2026-07-22 23:21:22,558][543983] Updated weights for policy 0, policy_version 47254 (0.0006) +[2026-07-22 23:21:22,871][543983] Updated weights for policy 0, policy_version 47265 (0.0007) +[2026-07-22 23:21:23,179][543983] Updated weights for policy 0, policy_version 47276 (0.0006) +[2026-07-22 23:21:23,466][543983] Updated weights for policy 0, policy_version 47286 (0.0006) +[2026-07-22 23:21:24,509][543983] Updated weights for policy 0, policy_version 47296 (0.0006) +[2026-07-22 23:21:24,805][543983] Updated weights for policy 0, policy_version 47306 (0.0006) +[2026-07-22 23:21:25,080][543983] Updated weights for policy 0, policy_version 47316 (0.0006) +[2026-07-22 23:21:25,395][543983] Updated weights for policy 0, policy_version 47327 (0.0006) +[2026-07-22 23:21:25,660][543983] Updated weights for policy 0, policy_version 47337 (0.0006) +[2026-07-22 23:21:25,988][543983] Updated weights for policy 0, policy_version 47348 (0.0007) +[2026-07-22 23:21:27,036][543983] Updated weights for policy 0, policy_version 47358 (0.0006) +[2026-07-22 23:21:27,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 24248320. Throughput: 0: 12640.7. Samples: 24272128. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:21:27,287][543203] Avg episode reward: [(0, '1958.134')] +[2026-07-22 23:21:27,349][543983] Updated weights for policy 0, policy_version 47369 (0.0006) +[2026-07-22 23:21:27,632][543983] Updated weights for policy 0, policy_version 47379 (0.0006) +[2026-07-22 23:21:27,950][543983] Updated weights for policy 0, policy_version 47390 (0.0006) +[2026-07-22 23:21:28,252][543983] Updated weights for policy 0, policy_version 47401 (0.0006) +[2026-07-22 23:21:28,556][543983] Updated weights for policy 0, policy_version 47412 (0.0006) +[2026-07-22 23:21:29,590][543983] Updated weights for policy 0, policy_version 47422 (0.0006) +[2026-07-22 23:21:29,864][543983] Updated weights for policy 0, policy_version 47432 (0.0006) +[2026-07-22 23:21:30,155][543983] Updated weights for policy 0, policy_version 47442 (0.0006) +[2026-07-22 23:21:30,441][543983] Updated weights for policy 0, policy_version 47452 (0.0006) +[2026-07-22 23:21:30,752][543983] Updated weights for policy 0, policy_version 47463 (0.0006) +[2026-07-22 23:21:31,068][543983] Updated weights for policy 0, policy_version 47474 (0.0006) +[2026-07-22 23:21:32,137][543983] Updated weights for policy 0, policy_version 47484 (0.0006) +[2026-07-22 23:21:32,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 24313856. Throughput: 0: 12828.4. Samples: 24353664. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:21:32,287][543203] Avg episode reward: [(0, '1958.134')] +[2026-07-22 23:21:32,419][543983] Updated weights for policy 0, policy_version 47494 (0.0007) +[2026-07-22 23:21:32,699][543983] Updated weights for policy 0, policy_version 47504 (0.0006) +[2026-07-22 23:21:32,990][543983] Updated weights for policy 0, policy_version 47514 (0.0006) +[2026-07-22 23:21:33,275][543983] Updated weights for policy 0, policy_version 47524 (0.0006) +[2026-07-22 23:21:33,581][543983] Updated weights for policy 0, policy_version 47535 (0.0006) +[2026-07-22 23:21:34,631][543983] Updated weights for policy 0, policy_version 47545 (0.0006) +[2026-07-22 23:21:34,907][543983] Updated weights for policy 0, policy_version 47555 (0.0007) +[2026-07-22 23:21:35,198][543983] Updated weights for policy 0, policy_version 47565 (0.0007) +[2026-07-22 23:21:35,480][543983] Updated weights for policy 0, policy_version 47575 (0.0006) +[2026-07-22 23:21:35,809][543983] Updated weights for policy 0, policy_version 47586 (0.0006) +[2026-07-22 23:21:36,112][543983] Updated weights for policy 0, policy_version 47597 (0.0006) +[2026-07-22 23:21:36,393][543983] Updated weights for policy 0, policy_version 47607 (0.0006) +[2026-07-22 23:21:37,287][543203] Fps is (10 sec: 13107.1, 60 sec: 12561.0, 300 sec: 12662.9). Total num frames: 24379392. Throughput: 0: 12899.5. Samples: 24393344. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:21:37,288][543203] Avg episode reward: [(0, '1966.140')] +[2026-07-22 23:21:37,450][543983] Updated weights for policy 0, policy_version 47617 (0.0007) +[2026-07-22 23:21:37,736][543983] Updated weights for policy 0, policy_version 47628 (0.0006) +[2026-07-22 23:21:38,060][543983] Updated weights for policy 0, policy_version 47639 (0.0006) +[2026-07-22 23:21:38,340][543983] Updated weights for policy 0, policy_version 47649 (0.0006) +[2026-07-22 23:21:38,661][543983] Updated weights for policy 0, policy_version 47660 (0.0006) +[2026-07-22 23:21:38,947][543983] Updated weights for policy 0, policy_version 47670 (0.0007) +[2026-07-22 23:21:40,012][543983] Updated weights for policy 0, policy_version 47681 (0.0006) +[2026-07-22 23:21:40,312][543983] Updated weights for policy 0, policy_version 47691 (0.0006) +[2026-07-22 23:21:40,600][543983] Updated weights for policy 0, policy_version 47701 (0.0006) +[2026-07-22 23:21:40,927][543983] Updated weights for policy 0, policy_version 47713 (0.0006) +[2026-07-22 23:21:41,207][543983] Updated weights for policy 0, policy_version 47723 (0.0006) +[2026-07-22 23:21:41,499][543983] Updated weights for policy 0, policy_version 47733 (0.0006) +[2026-07-22 23:21:42,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12774.0). Total num frames: 24444928. Throughput: 0: 12646.4. Samples: 24466048. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:21:42,287][543203] Avg episode reward: [(0, '1967.233')] +[2026-07-22 23:21:42,593][543983] Updated weights for policy 0, policy_version 47744 (0.0006) +[2026-07-22 23:21:42,874][543983] Updated weights for policy 0, policy_version 47754 (0.0006) +[2026-07-22 23:21:43,231][543983] Updated weights for policy 0, policy_version 47767 (0.0006) +[2026-07-22 23:21:43,546][543983] Updated weights for policy 0, policy_version 47778 (0.0006) +[2026-07-22 23:21:43,855][543983] Updated weights for policy 0, policy_version 47789 (0.0006) +[2026-07-22 23:21:44,139][543983] Updated weights for policy 0, policy_version 47799 (0.0006) +[2026-07-22 23:21:45,201][543983] Updated weights for policy 0, policy_version 47809 (0.0006) +[2026-07-22 23:21:45,485][543983] Updated weights for policy 0, policy_version 47819 (0.0006) +[2026-07-22 23:21:45,769][543983] Updated weights for policy 0, policy_version 47829 (0.0006) +[2026-07-22 23:21:46,072][543983] Updated weights for policy 0, policy_version 47840 (0.0006) +[2026-07-22 23:21:46,380][543983] Updated weights for policy 0, policy_version 47851 (0.0006) +[2026-07-22 23:21:46,672][543983] Updated weights for policy 0, policy_version 47861 (0.0006) +[2026-07-22 23:21:47,287][543203] Fps is (10 sec: 13107.3, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 24510464. Throughput: 0: 12652.1. Samples: 24539008. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:21:47,287][543203] Avg episode reward: [(0, '1967.233')] +[2026-07-22 23:21:47,777][543983] Updated weights for policy 0, policy_version 47872 (0.0006) +[2026-07-22 23:21:48,084][543983] Updated weights for policy 0, policy_version 47883 (0.0006) +[2026-07-22 23:21:48,405][543983] Updated weights for policy 0, policy_version 47895 (0.0006) +[2026-07-22 23:21:48,695][543983] Updated weights for policy 0, policy_version 47905 (0.0006) +[2026-07-22 23:21:48,992][543983] Updated weights for policy 0, policy_version 47915 (0.0006) +[2026-07-22 23:21:49,301][543983] Updated weights for policy 0, policy_version 47926 (0.0007) +[2026-07-22 23:21:50,344][543983] Updated weights for policy 0, policy_version 47936 (0.0006) +[2026-07-22 23:21:50,638][543983] Updated weights for policy 0, policy_version 47946 (0.0006) +[2026-07-22 23:21:50,917][543983] Updated weights for policy 0, policy_version 47956 (0.0006) +[2026-07-22 23:21:51,234][543983] Updated weights for policy 0, policy_version 47967 (0.0006) +[2026-07-22 23:21:51,511][543983] Updated weights for policy 0, policy_version 47977 (0.0006) +[2026-07-22 23:21:51,826][543983] Updated weights for policy 0, policy_version 47988 (0.0006) +[2026-07-22 23:21:52,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 24576000. Throughput: 0: 12808.5. Samples: 24582400. Policy #0 lag: (min: 63.0, avg: 79.2, max: 127.0) +[2026-07-22 23:21:52,287][543203] Avg episode reward: [(0, '1984.771')] +[2026-07-22 23:21:52,878][543983] Updated weights for policy 0, policy_version 47998 (0.0006) +[2026-07-22 23:21:53,211][543983] Updated weights for policy 0, policy_version 48009 (0.0006) +[2026-07-22 23:21:53,474][543983] Updated weights for policy 0, policy_version 48019 (0.0006) +[2026-07-22 23:21:53,786][543983] Updated weights for policy 0, policy_version 48030 (0.0006) +[2026-07-22 23:21:54,089][543983] Updated weights for policy 0, policy_version 48041 (0.0006) +[2026-07-22 23:21:54,376][543983] Updated weights for policy 0, policy_version 48051 (0.0006) +[2026-07-22 23:21:55,437][543983] Updated weights for policy 0, policy_version 48062 (0.0006) +[2026-07-22 23:21:55,726][543983] Updated weights for policy 0, policy_version 48072 (0.0006) +[2026-07-22 23:21:56,062][543983] Updated weights for policy 0, policy_version 48084 (0.0006) +[2026-07-22 23:21:56,338][543983] Updated weights for policy 0, policy_version 48094 (0.0007) +[2026-07-22 23:21:56,632][543983] Updated weights for policy 0, policy_version 48104 (0.0006) +[2026-07-22 23:21:56,933][543983] Updated weights for policy 0, policy_version 48114 (0.0006) +[2026-07-22 23:21:57,287][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 24641536. Throughput: 0: 12862.6. Samples: 24659584. Policy #0 lag: (min: 53.0, avg: 69.6, max: 117.0) +[2026-07-22 23:21:57,287][543203] Avg episode reward: [(0, '2000.105')] +[2026-07-22 23:21:58,036][543983] Updated weights for policy 0, policy_version 48126 (0.0007) +[2026-07-22 23:21:58,316][543983] Updated weights for policy 0, policy_version 48136 (0.0007) +[2026-07-22 23:21:58,606][543983] Updated weights for policy 0, policy_version 48146 (0.0006) +[2026-07-22 23:21:58,920][543983] Updated weights for policy 0, policy_version 48157 (0.0006) +[2026-07-22 23:21:59,197][543983] Updated weights for policy 0, policy_version 48167 (0.0006) +[2026-07-22 23:21:59,465][543983] Updated weights for policy 0, policy_version 48177 (0.0006) +[2026-07-22 23:22:00,545][543983] Updated weights for policy 0, policy_version 48187 (0.0006) +[2026-07-22 23:22:00,825][543983] Updated weights for policy 0, policy_version 48197 (0.0006) +[2026-07-22 23:22:01,107][543983] Updated weights for policy 0, policy_version 48207 (0.0007) +[2026-07-22 23:22:01,407][543983] Updated weights for policy 0, policy_version 48218 (0.0006) +[2026-07-22 23:22:01,703][543983] Updated weights for policy 0, policy_version 48228 (0.0007) +[2026-07-22 23:22:01,987][543983] Updated weights for policy 0, policy_version 48238 (0.0006) +[2026-07-22 23:22:02,286][543203] Fps is (10 sec: 13107.2, 60 sec: 13107.2, 300 sec: 12774.0). Total num frames: 24707072. Throughput: 0: 12660.6. Samples: 24732928. Policy #0 lag: (min: 53.0, avg: 69.6, max: 117.0) +[2026-07-22 23:22:02,287][543203] Avg episode reward: [(0, '2005.776')] +[2026-07-22 23:22:03,066][543983] Updated weights for policy 0, policy_version 48249 (0.0006) +[2026-07-22 23:22:03,340][543983] Updated weights for policy 0, policy_version 48259 (0.0006) +[2026-07-22 23:22:03,625][543983] Updated weights for policy 0, policy_version 48269 (0.0006) +[2026-07-22 23:22:03,918][543983] Updated weights for policy 0, policy_version 48279 (0.0006) +[2026-07-22 23:22:04,221][543983] Updated weights for policy 0, policy_version 48290 (0.0006) +[2026-07-22 23:22:04,521][543983] Updated weights for policy 0, policy_version 48301 (0.0006) +[2026-07-22 23:22:04,812][543983] Updated weights for policy 0, policy_version 48311 (0.0006) +[2026-07-22 23:22:05,891][543983] Updated weights for policy 0, policy_version 48321 (0.0006) +[2026-07-22 23:22:06,191][543983] Updated weights for policy 0, policy_version 48332 (0.0006) +[2026-07-22 23:22:06,509][543983] Updated weights for policy 0, policy_version 48343 (0.0006) +[2026-07-22 23:22:06,791][543983] Updated weights for policy 0, policy_version 48353 (0.0006) +[2026-07-22 23:22:07,113][543983] Updated weights for policy 0, policy_version 48364 (0.0007) +[2026-07-22 23:22:07,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 24739840. Throughput: 0: 12654.9. Samples: 24769024. Policy #0 lag: (min: 53.0, avg: 69.6, max: 117.0) +[2026-07-22 23:22:07,287][543203] Avg episode reward: [(0, '1977.464')] +[2026-07-22 23:22:07,422][543983] Updated weights for policy 0, policy_version 48375 (0.0006) +[2026-07-22 23:22:08,476][543983] Updated weights for policy 0, policy_version 48386 (0.0006) +[2026-07-22 23:22:08,755][543983] Updated weights for policy 0, policy_version 48396 (0.0007) +[2026-07-22 23:22:09,062][543983] Updated weights for policy 0, policy_version 48407 (0.0006) +[2026-07-22 23:22:09,361][543983] Updated weights for policy 0, policy_version 48417 (0.0006) +[2026-07-22 23:22:09,670][543983] Updated weights for policy 0, policy_version 48428 (0.0006) +[2026-07-22 23:22:09,979][543983] Updated weights for policy 0, policy_version 48439 (0.0006) +[2026-07-22 23:22:11,066][543983] Updated weights for policy 0, policy_version 48450 (0.0006) +[2026-07-22 23:22:11,377][543983] Updated weights for policy 0, policy_version 48461 (0.0006) +[2026-07-22 23:22:11,684][543983] Updated weights for policy 0, policy_version 48472 (0.0006) +[2026-07-22 23:22:11,980][543983] Updated weights for policy 0, policy_version 48482 (0.0008) +[2026-07-22 23:22:12,262][543983] Updated weights for policy 0, policy_version 48492 (0.0007) +[2026-07-22 23:22:12,286][543203] Fps is (10 sec: 9830.4, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 24805376. Throughput: 0: 12933.7. Samples: 24854144. Policy #0 lag: (min: 53.0, avg: 69.6, max: 117.0) +[2026-07-22 23:22:12,287][543203] Avg episode reward: [(0, '1977.464')] +[2026-07-22 23:22:12,538][543983] Updated weights for policy 0, policy_version 48502 (0.0006) +[2026-07-22 23:22:13,588][543983] Updated weights for policy 0, policy_version 48512 (0.0006) +[2026-07-22 23:22:13,883][543983] Updated weights for policy 0, policy_version 48523 (0.0006) +[2026-07-22 23:22:14,172][543983] Updated weights for policy 0, policy_version 48533 (0.0008) +[2026-07-22 23:22:14,457][543983] Updated weights for policy 0, policy_version 48543 (0.0006) +[2026-07-22 23:22:14,738][543983] Updated weights for policy 0, policy_version 48553 (0.0006) +[2026-07-22 23:22:15,109][543983] Updated weights for policy 0, policy_version 48566 (0.0006) +[2026-07-22 23:22:16,159][543983] Updated weights for policy 0, policy_version 48576 (0.0006) +[2026-07-22 23:22:16,454][543983] Updated weights for policy 0, policy_version 48586 (0.0006) +[2026-07-22 23:22:16,754][543983] Updated weights for policy 0, policy_version 48597 (0.0006) +[2026-07-22 23:22:17,042][543983] Updated weights for policy 0, policy_version 48607 (0.0006) +[2026-07-22 23:22:17,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 24870912. Throughput: 0: 12737.4. Samples: 24926848. Policy #0 lag: (min: 53.0, avg: 69.6, max: 117.0) +[2026-07-22 23:22:17,287][543203] Avg episode reward: [(0, '1964.740')] +[2026-07-22 23:22:17,321][543983] Updated weights for policy 0, policy_version 48617 (0.0006) +[2026-07-22 23:22:17,598][543983] Updated weights for policy 0, policy_version 48627 (0.0006) +[2026-07-22 23:22:18,630][543983] Updated weights for policy 0, policy_version 48637 (0.0006) +[2026-07-22 23:22:18,933][543983] Updated weights for policy 0, policy_version 48647 (0.0006) +[2026-07-22 23:22:19,257][543983] Updated weights for policy 0, policy_version 48659 (0.0007) +[2026-07-22 23:22:19,551][543983] Updated weights for policy 0, policy_version 48669 (0.0007) +[2026-07-22 23:22:19,831][543983] Updated weights for policy 0, policy_version 48679 (0.0006) +[2026-07-22 23:22:20,116][543983] Updated weights for policy 0, policy_version 48689 (0.0006) +[2026-07-22 23:22:21,207][543983] Updated weights for policy 0, policy_version 48701 (0.0006) +[2026-07-22 23:22:21,491][543983] Updated weights for policy 0, policy_version 48711 (0.0007) +[2026-07-22 23:22:21,777][543983] Updated weights for policy 0, policy_version 48721 (0.0007) +[2026-07-22 23:22:22,083][543983] Updated weights for policy 0, policy_version 48732 (0.0006) +[2026-07-22 23:22:22,286][543203] Fps is (10 sec: 13107.2, 60 sec: 12561.1, 300 sec: 12662.9). Total num frames: 24936448. Throughput: 0: 12652.1. Samples: 24962688. Policy #0 lag: (min: 53.0, avg: 69.6, max: 117.0) +[2026-07-22 23:22:22,287][543203] Avg episode reward: [(0, '2001.211')] +[2026-07-22 23:22:22,388][543983] Updated weights for policy 0, policy_version 48742 (0.0006) +[2026-07-22 23:22:22,646][543983] Updated weights for policy 0, policy_version 48752 (0.0006) +[2026-07-22 23:22:23,716][543983] Updated weights for policy 0, policy_version 48762 (0.0007) +[2026-07-22 23:22:24,013][543983] Updated weights for policy 0, policy_version 48772 (0.0006) +[2026-07-22 23:22:24,298][543983] Updated weights for policy 0, policy_version 48782 (0.0006) +[2026-07-22 23:22:24,601][543983] Updated weights for policy 0, policy_version 48793 (0.0007) +[2026-07-22 23:22:24,881][543983] Updated weights for policy 0, policy_version 48803 (0.0006) +[2026-07-22 23:22:25,173][543983] Updated weights for policy 0, policy_version 48813 (0.0006) +[2026-07-22 23:22:25,451][543983] Updated weights for policy 0, policy_version 48823 (0.0007) +[2026-07-22 23:22:26,510][543983] Updated weights for policy 0, policy_version 48833 (0.0006) +[2026-07-22 23:22:26,693][543696] Early stopping after 2 epochs (16 sgd steps), loss delta 0.0000000 +[2026-07-22 23:22:26,695][543696] Saving results/checkpoints/memory/rollout_teacher/flappy_teacher_fixed_l3_obs30_seed0/checkpoint_p0/checkpoint_000048840_25034752.pth... +[2026-07-22 23:22:26,695][543203] Component Batcher_0 stopped! +[2026-07-22 23:22:26,695][543984] Stopping RolloutWorker_w0... +[2026-07-22 23:22:26,695][543984] Loop rollout_proc0_evt_loop terminating... +[2026-07-22 23:22:26,696][543203] Component RolloutWorker_w0 stopped! +[2026-07-22 23:22:26,697][543696] Stopping Batcher_0... +[2026-07-22 23:22:26,698][543696] Loop batcher_evt_loop terminating... +[2026-07-22 23:22:26,699][543985] Stopping RolloutWorker_w1... +[2026-07-22 23:22:26,699][543985] Loop rollout_proc1_evt_loop terminating... +[2026-07-22 23:22:26,699][543203] Component RolloutWorker_w1 stopped! +[2026-07-22 23:22:26,715][543983] Weights refcount: 2 0 +[2026-07-22 23:22:26,716][543983] Stopping InferenceWorker_p0-w0... +[2026-07-22 23:22:26,716][543983] Loop inference_proc0-0_evt_loop terminating... +[2026-07-22 23:22:26,716][543203] Component InferenceWorker_p0-w0 stopped! +[2026-07-22 23:22:26,727][543696] Saving results/checkpoints/memory/rollout_teacher/flappy_teacher_fixed_l3_obs30_seed0/checkpoint_p0/checkpoint_000048840_25034752.pth... +[2026-07-22 23:22:26,767][543696] Stopping LearnerWorker_p0... +[2026-07-22 23:22:26,767][543203] Component LearnerWorker_p0 stopped! +[2026-07-22 23:22:26,767][543696] Loop learner_proc0_evt_loop terminating... +[2026-07-22 23:22:26,768][543203] Waiting for process learner_proc0 to stop... +[2026-07-22 23:22:27,629][543203] Waiting for process inference_proc0-0 to join... +[2026-07-22 23:22:27,629][543203] Waiting for process rollout_proc0 to join... +[2026-07-22 23:22:27,630][543203] Waiting for process rollout_proc1 to join... +[2026-07-22 23:22:27,630][543203] Batcher 0 profile tree view: +batching: 0.6425, releasing_batches: 0.0178 +[2026-07-22 23:22:27,631][543203] InferenceWorker_p0-w0 profile tree view: +wait_policy: 0.0016 + wait_policy_total: 1398.9621 +update_model: 37.2869 + weight_update: 0.0006 +one_step: 0.0017 + handle_policy_step: 515.7314 + deserialize: 13.2815, stack: 0.3091, obs_to_device_normalize: 49.6571, forward: 130.0013, prepare_outputs: 297.1298, send_messages: 10.5020 +[2026-07-22 23:22:27,631][543203] Learner 0 profile tree view: +misc: 0.0029, prepare_batch: 114.1214 +train: 1389.0956 + epoch_init: 0.0765, minibatch_init: 4.2894, losses_postprocess: 486.5960, kl_divergence: 58.3220, after_optimizer: 634.2792 + calculate_losses: 61.2422 + losses_init: 0.1339, forward_head: 19.6726, bptt_initial: 0.6357, bptt: 0.6563, tail: 13.8999, advantages_returns: 4.7501, losses: 17.1408 + update: 139.4362 + clip: 21.1257 +[2026-07-22 23:22:27,631][543203] RolloutWorker_w0 profile tree view: +wait_for_trajectories: 0.0533, enqueue_policy_requests: 20.0323, wait_policy_outputs_event: 4.2654, process_policy_outputs: 11.5958, env_step: 1576.4473, finalize_trajectories: 0.1701, complete_rollouts: 0.1539 +post_env_step: 25.9768 + process_env_step: 7.9931 +[2026-07-22 23:22:27,631][543203] RolloutWorker_w1 profile tree view: +wait_for_trajectories: 0.0549, enqueue_policy_requests: 20.3411, wait_policy_outputs_event: 4.3426, process_policy_outputs: 11.6140, env_step: 1550.0711, finalize_trajectories: 0.1745, complete_rollouts: 0.1684 +post_env_step: 26.6173 + process_env_step: 8.2372 +[2026-07-22 23:22:27,635][543203] Loop Runner_EvtLoop terminating... +[2026-07-22 23:22:27,636][543203] Runner profile tree view: +main_loop: 1984.9911 +[2026-07-22 23:22:27,636][543203] Collected {0: 25034752}, FPS: 12612.0 diff --git a/evaluations/flappy/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/eval/fixed_3/eval_latency_3/episode_metrics.jsonl b/evaluations/flappy/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/eval/fixed_3/eval_latency_3/episode_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..49039411d7c04503b212416ab6c73dc39f62bf25 --- /dev/null +++ b/evaluations/flappy/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/eval/fixed_3/eval_latency_3/episode_metrics.jsonl @@ -0,0 +1,20 @@ +{"episode_id": 0, "episode_return": 444.6000052243471, "episode_return_env": 444.6000052243471, "game_score": 94.0, "mean_latency_ms": 100.0, "metadata": {"checkpoint_path": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/checkpoints/steps_2000_pytorch_model.pt", "config_name": "starvla_wan_oft_flappy_raw3", "configured_latency_ms": 100.0, "env_fps": 30.0, "env_id": "flappy", "episode_seed": 42, "eval_latency_steps": 3, "frame_ms": 33.333333333333336, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 30.0, "output_dir": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/eval/fixed_3/eval_latency_3", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_flappy_raw3", "suite_name": "fixed_3", "target_device": null, "train_latency_steps": 3}, "num_actions": 3600, "num_dropped_actions": 2, "num_invalid_actions": 0, "p90_latency_ms": 100.0, "p99_latency_ms": 100.0, "return_raw": null, "survival_steps": 3600} +{"episode_id": 1, "episode_return": 444.6000052243471, "episode_return_env": 444.6000052243471, "game_score": 94.0, "mean_latency_ms": 100.0, "metadata": {"checkpoint_path": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/checkpoints/steps_2000_pytorch_model.pt", "config_name": "starvla_wan_oft_flappy_raw3", "configured_latency_ms": 100.0, "env_fps": 30.0, "env_id": "flappy", "episode_seed": 43, "eval_latency_steps": 3, "frame_ms": 33.333333333333336, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 30.0, "output_dir": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/eval/fixed_3/eval_latency_3", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_flappy_raw3", "suite_name": "fixed_3", "target_device": null, "train_latency_steps": 3}, "num_actions": 3600, "num_dropped_actions": 2, "num_invalid_actions": 0, "p90_latency_ms": 100.0, "p99_latency_ms": 100.0, "return_raw": null, "survival_steps": 3600} +{"episode_id": 2, "episode_return": 444.6000052243471, "episode_return_env": 444.6000052243471, "game_score": 94.0, "mean_latency_ms": 100.0, "metadata": {"checkpoint_path": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/checkpoints/steps_2000_pytorch_model.pt", "config_name": "starvla_wan_oft_flappy_raw3", "configured_latency_ms": 100.0, "env_fps": 30.0, "env_id": "flappy", "episode_seed": 44, "eval_latency_steps": 3, "frame_ms": 33.333333333333336, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 30.0, "output_dir": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/eval/fixed_3/eval_latency_3", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_flappy_raw3", "suite_name": "fixed_3", "target_device": null, "train_latency_steps": 3}, "num_actions": 3600, "num_dropped_actions": 2, "num_invalid_actions": 0, "p90_latency_ms": 100.0, "p99_latency_ms": 100.0, "return_raw": null, "survival_steps": 3600} +{"episode_id": 3, "episode_return": 444.6000052243471, "episode_return_env": 444.6000052243471, "game_score": 94.0, "mean_latency_ms": 100.0, "metadata": {"checkpoint_path": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/checkpoints/steps_2000_pytorch_model.pt", "config_name": "starvla_wan_oft_flappy_raw3", "configured_latency_ms": 100.0, "env_fps": 30.0, "env_id": "flappy", "episode_seed": 45, "eval_latency_steps": 3, "frame_ms": 33.333333333333336, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 30.0, "output_dir": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/eval/fixed_3/eval_latency_3", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_flappy_raw3", "suite_name": "fixed_3", "target_device": null, "train_latency_steps": 3}, "num_actions": 3600, "num_dropped_actions": 2, "num_invalid_actions": 0, "p90_latency_ms": 100.0, "p99_latency_ms": 100.0, "return_raw": null, "survival_steps": 3600} +{"episode_id": 4, "episode_return": 444.6000052243471, "episode_return_env": 444.6000052243471, "game_score": 94.0, "mean_latency_ms": 100.0, "metadata": {"checkpoint_path": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/checkpoints/steps_2000_pytorch_model.pt", "config_name": "starvla_wan_oft_flappy_raw3", "configured_latency_ms": 100.0, "env_fps": 30.0, "env_id": "flappy", "episode_seed": 46, "eval_latency_steps": 3, "frame_ms": 33.333333333333336, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 30.0, "output_dir": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/eval/fixed_3/eval_latency_3", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_flappy_raw3", "suite_name": "fixed_3", "target_device": null, "train_latency_steps": 3}, "num_actions": 3600, "num_dropped_actions": 2, "num_invalid_actions": 0, "p90_latency_ms": 100.0, "p99_latency_ms": 100.0, "return_raw": null, "survival_steps": 3600} +{"episode_id": 5, "episode_return": 444.6000052243471, "episode_return_env": 444.6000052243471, "game_score": 94.0, "mean_latency_ms": 100.0, "metadata": {"checkpoint_path": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/checkpoints/steps_2000_pytorch_model.pt", "config_name": "starvla_wan_oft_flappy_raw3", "configured_latency_ms": 100.0, "env_fps": 30.0, "env_id": "flappy", "episode_seed": 47, "eval_latency_steps": 3, "frame_ms": 33.333333333333336, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 30.0, "output_dir": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/eval/fixed_3/eval_latency_3", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_flappy_raw3", "suite_name": "fixed_3", "target_device": null, "train_latency_steps": 3}, "num_actions": 3600, "num_dropped_actions": 2, "num_invalid_actions": 0, "p90_latency_ms": 100.0, "p99_latency_ms": 100.0, "return_raw": null, "survival_steps": 3600} +{"episode_id": 6, "episode_return": 444.6000052243471, "episode_return_env": 444.6000052243471, "game_score": 94.0, "mean_latency_ms": 100.0, "metadata": {"checkpoint_path": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/checkpoints/steps_2000_pytorch_model.pt", "config_name": "starvla_wan_oft_flappy_raw3", "configured_latency_ms": 100.0, "env_fps": 30.0, "env_id": "flappy", "episode_seed": 48, "eval_latency_steps": 3, "frame_ms": 33.333333333333336, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 30.0, "output_dir": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/eval/fixed_3/eval_latency_3", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_flappy_raw3", "suite_name": "fixed_3", "target_device": null, "train_latency_steps": 3}, "num_actions": 3600, "num_dropped_actions": 2, "num_invalid_actions": 0, "p90_latency_ms": 100.0, "p99_latency_ms": 100.0, "return_raw": null, "survival_steps": 3600} +{"episode_id": 7, "episode_return": 444.6000052243471, "episode_return_env": 444.6000052243471, "game_score": 94.0, "mean_latency_ms": 100.0, "metadata": {"checkpoint_path": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/checkpoints/steps_2000_pytorch_model.pt", "config_name": "starvla_wan_oft_flappy_raw3", "configured_latency_ms": 100.0, "env_fps": 30.0, "env_id": "flappy", "episode_seed": 49, "eval_latency_steps": 3, "frame_ms": 33.333333333333336, "instance_id": null, "instance_origin": null, "latency_type": "fixed_sweep", "mode": "simulated", "obs_fps": 30.0, "output_dir": "/workspace/runtime/wanoft/wan_oft_flappy_fix_latency_3_context5_standard_sft_2000_effbs128_224_currentce/eval/fixed_3/eval_latency_3", "policy_id": "starvla", "profile_id": null, "profile_path": null, "replay_host": null, "run_name": "starvla_wan_oft_flappy_raw3", "suite_name": "fixed_3", "target_device": null, "train_latency_steps": 3}, "num_actions": 3600, "num_dropped_actions": 2, "num_invalid_actions": 0, "p90_latency_ms": 100.0, "p99_latency_ms": 100.0, "return_raw": null, "survival_steps": 3600} +{"episode_id": 8, "episode_return": 444.6000052243471, "episode_return_env": 444.6000052243471, "game_score": 94.0, "mean_latency_ms": 100.0, "metadata": 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null, "latency_type": "zero", "mode": "simulated", "model_id": null, "obs_fps": 25.0, "output_dir": "/home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_0", "policy_id": "starvla", "profile_ref": null, "run_name": "starvla_gymnasium_train_eval", "source_run_id": null, "workload_id": null}, "num_actions": 85, "num_dropped_actions": 0, "num_invalid_actions": 0, "p90_latency_ms": 0.0, "p99_latency_ms": 0.0, "return_raw": null, "survival_steps": 85} diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_0/observation_attempts.jsonl b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_0/observation_attempts.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_0/resolved_config.yaml b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_0/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..800118e56452894cd2d8aa2df8ab6b89dc138eaa --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_0/resolved_config.yaml @@ -0,0 +1,138 @@ +experiment: + name: starvla_gymnasium_train_eval + seed: 42 +backend: + run_mode: eval +executor: + mode: simulated + simulated_inference_pool: false + simulated_worker_capacity: null +env: + name: gymnasium + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose exactly + one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + action_order: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_map: + push_left_hard: 0 + push_left_soft: 1 + zero_force: 2 + push_right_soft: 3 + push_right_hard: 4 + noop_action: zero_force + obs_resize: + - 224 + - 224 +latency: + method: zero + add_latency_info: false +scheduler: + hold_policy: hold + ordering_policy: issue_order_fifo +policy: + type: starvla + checkpoint_path: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_0 + device: cuda + task_manifest_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/manifest.json + gymnasium_training_task_contract: + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose + exactly one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + latency_prompt_map_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_prompt_map.json + latency_prompt_key: 0 + action_prefix: + mode: none +evaluation: + eval_episodes: 20 + eval_parallel_envs: 5 + eval_max_steps: 3600 + eval_max_decision_steps: 3600 + eval_deterministic: true + eval_raw_reward: false + eval_latency_values: null +logging: + output_dir: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_0 + video: + enabled: false + num_bins: 1 + save_step_records: false + save_action_records: false + save_latency_records: false + simulated_pipeline_profile: false diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/episode_metrics.jsonl b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/episode_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0749bb695232cd2d3deb2f480cbc2400d5b55058 --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/episode_metrics.jsonl @@ -0,0 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a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/observation_attempts.jsonl b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/observation_attempts.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/resolved_config.yaml b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..39ff62ae5dd6703ed1a5edcfaef5ab9a17e13c44 --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/resolved_config.yaml @@ -0,0 +1,139 @@ +experiment: + name: starvla_gymnasium_train_eval + seed: 42 +backend: + run_mode: eval +executor: + mode: simulated + simulated_inference_pool: false + simulated_worker_capacity: null +env: + name: gymnasium + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose exactly + one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + action_order: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_map: + push_left_hard: 0 + push_left_soft: 1 + zero_force: 2 + push_right_soft: 3 + push_right_hard: 4 + noop_action: zero_force + obs_resize: + - 224 + - 224 +latency: + method: fixed + add_latency_info: false + fixed_latency_ms: 80.0 +scheduler: + hold_policy: hold + ordering_policy: issue_order_fifo +policy: + type: starvla + checkpoint_path: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2 + device: cuda + task_manifest_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/manifest.json + gymnasium_training_task_contract: + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose + exactly one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + latency_prompt_map_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_prompt_map.json + latency_prompt_key: 2 + action_prefix: + mode: none +evaluation: + eval_episodes: 20 + eval_parallel_envs: 5 + eval_max_steps: 3600 + eval_max_decision_steps: 3600 + eval_deterministic: true + eval_raw_reward: false + eval_latency_values: null +logging: + output_dir: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2 + video: + enabled: false + num_bins: 1 + save_step_records: false + save_action_records: false + save_latency_records: false + simulated_pipeline_profile: false diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/episode_metrics.jsonl b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/episode_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0d2e978792cde3c4e01b28fdd388054f027eee92 --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/episode_metrics.jsonl @@ -0,0 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a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/observation_attempts.jsonl b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/observation_attempts.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/resolved_config.yaml b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9135117339b703da7f937533661ed406fc0b32cb --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/resolved_config.yaml @@ -0,0 +1,139 @@ +experiment: + name: starvla_gymnasium_train_eval + seed: 42 +backend: + run_mode: eval +executor: + mode: simulated + simulated_inference_pool: false + simulated_worker_capacity: null +env: + name: gymnasium + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose exactly + one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + action_order: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_map: + push_left_hard: 0 + push_left_soft: 1 + zero_force: 2 + push_right_soft: 3 + push_right_hard: 4 + noop_action: zero_force + obs_resize: + - 224 + - 224 +latency: + method: fixed + add_latency_info: false + fixed_latency_ms: 160.0 +scheduler: + hold_policy: hold + ordering_policy: issue_order_fifo +policy: + type: starvla + checkpoint_path: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4 + device: cuda + task_manifest_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/manifest.json + gymnasium_training_task_contract: + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose + exactly one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + latency_prompt_map_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_prompt_map.json + latency_prompt_key: 4 + action_prefix: + mode: none +evaluation: + eval_episodes: 20 + eval_parallel_envs: 5 + eval_max_steps: 3600 + eval_max_decision_steps: 3600 + eval_deterministic: true + eval_raw_reward: false + eval_latency_values: null +logging: + output_dir: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4 + video: + enabled: false + num_bins: 1 + save_step_records: false + save_action_records: false + save_latency_records: false + simulated_pipeline_profile: false diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/eval/post_train/step_5000.json b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/eval/post_train/step_5000.json new file mode 100644 index 0000000000000000000000000000000000000000..58a52a44238b26566fd1059004a71b774d347a2f --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/eval/post_train/step_5000.json @@ -0,0 +1,318 @@ +{ + "per_latency": { + "gymnasium/latency_0": { + "latency": 0, + "num_episodes": 20, + "mean_reward": 539.85, + "mean_length": 539.85, + 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"LatencyBench/InvertedPendulumDiscrete-v0", "episode_seed": 61, "frame_ms": 40.0, "gpu_class": null, "instance_id": null, "latency_type": "zero", "mode": "simulated", "model_id": null, "obs_fps": 25.0, "output_dir": "/home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_0", "policy_id": "starvla", "profile_ref": null, "run_name": "starvla_gymnasium_train_eval", "source_run_id": null, "workload_id": null}, "num_actions": 1000, "num_dropped_actions": 0, "num_invalid_actions": 0, "p90_latency_ms": 0.0, "p99_latency_ms": 0.0, "return_raw": null, "survival_steps": 1000} diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_0/observation_attempts.jsonl b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_0/observation_attempts.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_0/resolved_config.yaml b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_0/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..68e05ce76bec2b608317f45fc1789f1ac03cd388 --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_0/resolved_config.yaml @@ -0,0 +1,138 @@ +experiment: + name: starvla_gymnasium_train_eval + seed: 42 +backend: + run_mode: eval +executor: + mode: simulated + simulated_inference_pool: false + simulated_worker_capacity: null +env: + name: gymnasium + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose exactly + one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + action_order: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_map: + push_left_hard: 0 + push_left_soft: 1 + zero_force: 2 + push_right_soft: 3 + push_right_hard: 4 + noop_action: zero_force + obs_resize: + - 224 + - 224 +latency: + method: zero + add_latency_info: false +scheduler: + hold_policy: hold + ordering_policy: issue_order_fifo +policy: + type: starvla + checkpoint_path: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_0 + device: cuda + task_manifest_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/manifest.json + gymnasium_training_task_contract: + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose + exactly one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + latency_prompt_map_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_prompt_map.json + latency_prompt_key: 0 + action_prefix: + mode: none +evaluation: + eval_episodes: 20 + eval_parallel_envs: 5 + eval_max_steps: 3600 + eval_max_decision_steps: 3600 + eval_deterministic: true + eval_raw_reward: false + eval_latency_values: null +logging: + output_dir: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_0 + video: + enabled: false + num_bins: 1 + save_step_records: false + save_action_records: false + save_latency_records: false + simulated_pipeline_profile: false diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/episode_metrics.jsonl b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/episode_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ba06da9d5de6b18b09858e41817ffde304ebd445 --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/episode_metrics.jsonl @@ -0,0 +1,20 @@ +{"episode_id": 0, "episode_return": 91.0, "episode_return_env": 91.0, "game_score": null, "mean_latency_ms": 80.0, "metadata": {"action_prefix": {"mode": "none"}, "checkpoint_path": "/home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2", "config_name": "starvla_gymnasium_train_eval", "env_fps": 25.0, "env_id": "LatencyBench/InvertedPendulumDiscrete-v0", "episode_seed": 42, "frame_ms": 40.0, "gpu_class": null, "instance_id": null, "latency_type": "fixed", "mode": "simulated", "model_id": null, "obs_fps": 25.0, "output_dir": "/home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2", "policy_id": "starvla", "profile_ref": null, "run_name": "starvla_gymnasium_train_eval", "source_run_id": null, "workload_id": null}, "num_actions": 91, "num_dropped_actions": 0, "num_invalid_actions": 0, "p90_latency_ms": 80.0, "p99_latency_ms": 80.0, "return_raw": null, "survival_steps": 91} +{"episode_id": 1, "episode_return": 41.0, "episode_return_env": 41.0, "game_score": null, "mean_latency_ms": 80.0, "metadata": {"action_prefix": {"mode": "none"}, "checkpoint_path": "/home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2", "config_name": "starvla_gymnasium_train_eval", "env_fps": 25.0, "env_id": "LatencyBench/InvertedPendulumDiscrete-v0", "episode_seed": 43, "frame_ms": 40.0, "gpu_class": null, "instance_id": null, "latency_type": "fixed", "mode": "simulated", "model_id": null, "obs_fps": 25.0, "output_dir": "/home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2", "policy_id": "starvla", "profile_ref": null, "run_name": 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"/home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2", "config_name": "starvla_gymnasium_train_eval", "env_fps": 25.0, "env_id": "LatencyBench/InvertedPendulumDiscrete-v0", "episode_seed": 61, "frame_ms": 40.0, "gpu_class": null, "instance_id": null, "latency_type": "fixed", "mode": "simulated", "model_id": null, "obs_fps": 25.0, "output_dir": "/home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2", "policy_id": "starvla", "profile_ref": null, "run_name": "starvla_gymnasium_train_eval", "source_run_id": null, "workload_id": null}, "num_actions": 86, "num_dropped_actions": 0, "num_invalid_actions": 0, "p90_latency_ms": 80.0, "p99_latency_ms": 80.0, "return_raw": null, "survival_steps": 86} diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/observation_attempts.jsonl b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/observation_attempts.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/resolved_config.yaml b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..833a93b73c89ea7203913fa43433a19a139f3985 --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/resolved_config.yaml @@ -0,0 +1,139 @@ +experiment: + name: starvla_gymnasium_train_eval + seed: 42 +backend: + run_mode: eval +executor: + mode: simulated + simulated_inference_pool: false + simulated_worker_capacity: null +env: + name: gymnasium + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose exactly + one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + action_order: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_map: + push_left_hard: 0 + push_left_soft: 1 + zero_force: 2 + push_right_soft: 3 + push_right_hard: 4 + noop_action: zero_force + obs_resize: + - 224 + - 224 +latency: + method: fixed + add_latency_info: false + fixed_latency_ms: 80.0 +scheduler: + hold_policy: hold + ordering_policy: issue_order_fifo +policy: + type: starvla + checkpoint_path: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2 + device: cuda + task_manifest_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/manifest.json + gymnasium_training_task_contract: + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose + exactly one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + latency_prompt_map_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_prompt_map.json + latency_prompt_key: 2 + action_prefix: + mode: none +evaluation: + eval_episodes: 20 + eval_parallel_envs: 5 + eval_max_steps: 3600 + eval_max_decision_steps: 3600 + eval_deterministic: true + eval_raw_reward: false + eval_latency_values: null +logging: + output_dir: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_2 + video: + enabled: false + num_bins: 1 + save_step_records: false + save_action_records: false + save_latency_records: false + simulated_pipeline_profile: false diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/episode_metrics.jsonl b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/episode_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3122772b2c1171384db5160cc16bf04875541b6e --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/episode_metrics.jsonl @@ -0,0 +1,20 @@ +{"episode_id": 0, "episode_return": 37.0, "episode_return_env": 37.0, "game_score": null, "mean_latency_ms": 160.0, "metadata": {"action_prefix": {"mode": "none"}, "checkpoint_path": "/home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_4", "config_name": "starvla_gymnasium_train_eval", "env_fps": 25.0, "env_id": "LatencyBench/InvertedPendulumDiscrete-v0", "episode_seed": 42, "frame_ms": 40.0, "gpu_class": null, "instance_id": null, "latency_type": "fixed", "mode": "simulated", "model_id": null, "obs_fps": 25.0, "output_dir": "/home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_4", "policy_id": "starvla", "profile_ref": null, "run_name": "starvla_gymnasium_train_eval", "source_run_id": null, "workload_id": null}, "num_actions": 37, "num_dropped_actions": 0, 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a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/observation_attempts.jsonl b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/observation_attempts.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/resolved_config.yaml b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..054b503fd5a634dbcbcc1b12dceb05c2defcb5ee --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/resolved_config.yaml @@ -0,0 +1,139 @@ +experiment: + name: starvla_gymnasium_train_eval + seed: 42 +backend: + run_mode: eval +executor: + mode: simulated + simulated_inference_pool: false + simulated_worker_capacity: null +env: + name: gymnasium + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose exactly + one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + action_order: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_map: + push_left_hard: 0 + push_left_soft: 1 + zero_force: 2 + push_right_soft: 3 + push_right_hard: 4 + noop_action: zero_force + obs_resize: + - 224 + - 224 +latency: + method: fixed + add_latency_info: false + fixed_latency_ms: 160.0 +scheduler: + hold_policy: hold + ordering_policy: issue_order_fifo +policy: + type: starvla + checkpoint_path: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_4 + device: cuda + task_manifest_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/manifest.json + gymnasium_training_task_contract: + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose + exactly one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + latency_prompt_map_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_prompt_map.json + latency_prompt_key: 4 + action_prefix: + mode: none +evaluation: + eval_episodes: 20 + eval_parallel_envs: 5 + eval_max_steps: 3600 + eval_max_decision_steps: 3600 + eval_deterministic: true + eval_raw_reward: false + eval_latency_values: null +logging: + output_dir: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3/latency_bench_eval/post_train/step_5000/gymnasium/latency_4 + video: + enabled: false + num_bins: 1 + save_step_records: false + save_action_records: false + save_latency_records: false + simulated_pipeline_profile: false diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/eval/post_train/step_5000.json b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/eval/post_train/step_5000.json new file mode 100644 index 0000000000000000000000000000000000000000..ea0a1ab80d9388d4b7410d0b128a6d5491c17b80 --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/eval/post_train/step_5000.json @@ -0,0 +1,318 @@ +{ + "per_latency": { + "gymnasium/latency_0": { + "latency": 0, + "num_episodes": 20, + 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b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_0/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..02521cad177a8cb60ff0ae570e4009b2c5f74e0c --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_0/resolved_config.yaml @@ -0,0 +1,139 @@ +experiment: + name: starvla_gymnasium_train_eval + seed: 42 +backend: + run_mode: eval +executor: + mode: simulated + simulated_inference_pool: false + simulated_worker_capacity: null +env: + name: gymnasium + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose exactly + one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + action_order: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_map: + push_left_hard: 0 + push_left_soft: 1 + zero_force: 2 + push_right_soft: 3 + push_right_hard: 4 + noop_action: zero_force + obs_resize: + - 224 + - 224 +latency: + method: zero + add_latency_info: false +scheduler: + hold_policy: hold + ordering_policy: issue_order_fifo +policy: + type: starvla + checkpoint_path: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_0 + device: cuda + task_manifest_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/manifest.json + gymnasium_training_task_contract: + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose + exactly one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + latency_prompt_map_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_prompt_map.json + latency_prompt_key: 0 + prompt_mode: latency_neutral + action_prefix: + mode: none +evaluation: + eval_episodes: 20 + eval_parallel_envs: 5 + eval_max_steps: 3600 + eval_max_decision_steps: 3600 + eval_deterministic: true + eval_raw_reward: false + eval_latency_values: null +logging: + output_dir: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_0 + video: + enabled: false + num_bins: 1 + save_step_records: false + save_action_records: false + save_latency_records: false + simulated_pipeline_profile: false diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/episode_metrics.jsonl b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/episode_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8604a6829f2f747868786fd33ace00f86272ae19 --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/episode_metrics.jsonl @@ -0,0 +1,20 @@ +{"episode_id": 0, "episode_return": 114.0, "episode_return_env": 114.0, "game_score": null, "mean_latency_ms": 80.0, "metadata": {"action_prefix": {"mode": "none"}, "checkpoint_path": "/home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2", "config_name": "starvla_gymnasium_train_eval", "env_fps": 25.0, "env_id": "LatencyBench/InvertedPendulumDiscrete-v0", "episode_seed": 42, "frame_ms": 40.0, "gpu_class": null, "instance_id": null, "latency_type": "fixed", "mode": "simulated", "model_id": null, "obs_fps": 25.0, "output_dir": 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b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/observation_attempts.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/resolved_config.yaml b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..2660715a8f34a6a945e3f75bc8763c03e4adbac2 --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2/resolved_config.yaml @@ -0,0 +1,140 @@ +experiment: + name: starvla_gymnasium_train_eval + seed: 42 +backend: + run_mode: eval +executor: + mode: simulated + simulated_inference_pool: false + simulated_worker_capacity: null +env: + name: gymnasium + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose exactly + one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + action_order: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_map: + push_left_hard: 0 + push_left_soft: 1 + zero_force: 2 + push_right_soft: 3 + push_right_hard: 4 + noop_action: zero_force + obs_resize: + - 224 + - 224 +latency: + method: fixed + add_latency_info: false + fixed_latency_ms: 80.0 +scheduler: + hold_policy: hold + ordering_policy: issue_order_fifo +policy: + type: starvla + checkpoint_path: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2 + device: cuda + task_manifest_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/manifest.json + gymnasium_training_task_contract: + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose + exactly one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + latency_prompt_map_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_prompt_map.json + latency_prompt_key: 2 + prompt_mode: latency_neutral + action_prefix: + mode: none +evaluation: + eval_episodes: 20 + eval_parallel_envs: 5 + eval_max_steps: 3600 + eval_max_decision_steps: 3600 + eval_deterministic: true + eval_raw_reward: false + eval_latency_values: null +logging: + output_dir: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_2 + video: + enabled: false + num_bins: 1 + save_step_records: false + save_action_records: false + save_latency_records: false + simulated_pipeline_profile: false diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/episode_metrics.jsonl b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/episode_metrics.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b2042bfb8fc0d8b0694b93e317f54fd3db422ba6 --- /dev/null +++ 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b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/observation_attempts.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/resolved_config.yaml b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/resolved_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..0809a537d706f96f5e5d44e5b85f9ce2ccc22f78 --- /dev/null +++ b/evaluations/inverted-pendulum/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4/resolved_config.yaml @@ -0,0 +1,140 @@ +experiment: + name: starvla_gymnasium_train_eval + seed: 42 +backend: + run_mode: eval +executor: + mode: simulated + simulated_inference_pool: false + simulated_worker_capacity: null +env: + name: gymnasium + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose exactly + one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + action_order: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_map: + push_left_hard: 0 + push_left_soft: 1 + zero_force: 2 + push_right_soft: 3 + push_right_hard: 4 + noop_action: zero_force + obs_resize: + - 224 + - 224 +latency: + method: fixed + add_latency_info: false + fixed_latency_ms: 160.0 +scheduler: + hold_policy: hold + ordering_policy: issue_order_fifo +policy: + type: starvla + checkpoint_path: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4 + device: cuda + task_manifest_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/manifest.json + gymnasium_training_task_contract: + task_name: inverted_pendulum_rgb_state + env_id: LatencyBench/InvertedPendulumDiscrete-v0 + registration_imports: + - latency_bench.envs.gymnasium_mujoco + env_fps: 25.0 + obs_fps: 25.0 + frame_stack: 1 + base_prompt: 'Keep the pole upright by applying horizontal cart forces. Choose + exactly one action from: push_left_hard, push_left_soft, zero_force, push_right_soft, + push_right_hard.' + action_labels: + - push_left_hard + - push_left_soft + - zero_force + - push_right_soft + - push_right_hard + action_values: + - 0 + - 1 + - 2 + - 3 + - 4 + noop_action_id: 2 + make_kwargs: + base_env_id: InvertedPendulum-v4 + render_mode: rgb_array + force_values: + - -3.0 + - -1.5 + - 0.0 + - 1.5 + - 3.0 + base_make_kwargs: {} + state_space: + labels: + - cart_position + - pole_angle + - cart_velocity + - pole_angular_velocity + latency_prompt_map_path: /home/ubuntu/talha/playground/Datasets/rl_games/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_prompt_map.json + latency_prompt_key: 4 + prompt_mode: latency_neutral + action_prefix: + mode: none +evaluation: + eval_episodes: 20 + eval_parallel_envs: 5 + eval_max_steps: 3600 + eval_max_decision_steps: 3600 + eval_deterministic: true + eval_raw_reward: false + eval_latency_values: null +logging: + output_dir: /home/ubuntu/talha/results/Checkpoints/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2/latency_bench_eval/post_train/step_5000/gymnasium/latency_4 + video: + enabled: false + num_bins: 1 + save_step_records: false + save_action_records: false + save_latency_records: false + simulated_pipeline_profile: false diff --git a/experiments/latency-in-prompt/provenance/latency-information-data/README.md b/experiments/latency-in-prompt/provenance/latency-information-data/README.md new file mode 100644 index 0000000000000000000000000000000000000000..800d20489055e6b2333bf9345757514755f6e4a7 --- /dev/null +++ b/experiments/latency-in-prompt/provenance/latency-information-data/README.md @@ -0,0 +1,398 @@ +--- +configs: +- config_name: inverted_pendulum_200ep_2__inverted_pendulum_fixed_latency_0_100ep_1ksteps_og + data_files: + - split: train + path: + - training/inverted_pendulum_200ep_2/inverted_pendulum_fixed_latency_0_100ep_1ksteps_og/train.parquet + - split: val + path: + - training/inverted_pendulum_200ep_2/inverted_pendulum_fixed_latency_0_100ep_1ksteps_og/val.parquet +- config_name: inverted_pendulum_200ep_2__inverted_pendulum_fixed_latency_2_1000ep_7k2steps + data_files: + - split: train + path: + - training/inverted_pendulum_200ep_2/inverted_pendulum_fixed_latency_2_1000ep_7k2steps/train-00000-of-00002.parquet + - training/inverted_pendulum_200ep_2/inverted_pendulum_fixed_latency_2_1000ep_7k2steps/train-00001-of-00002.parquet + - split: val + path: + - training/inverted_pendulum_200ep_2/inverted_pendulum_fixed_latency_2_1000ep_7k2steps/val-00000-of-00001.parquet +- config_name: inverted_pendulum_200ep_2__inverted_pendulum_fixed_latency_4_1000ep_7k2steps + data_files: + - split: train + path: + - training/inverted_pendulum_200ep_2/inverted_pendulum_fixed_latency_4_1000ep_7k2steps/train-00000-of-00001.parquet + - split: val + path: + - training/inverted_pendulum_200ep_2/inverted_pendulum_fixed_latency_4_1000ep_7k2steps/val-00000-of-00001.parquet +- config_name: inverted_pendulum_200ep__inverted_pendulum_fixed_latency_0_200ep_7k2steps + data_files: + - split: train + path: + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00000-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00001-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00002-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00003-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00004-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00005-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00006-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00007-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00008-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00009-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00010-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00011-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00012-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00013-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00014-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00015-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00016-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00017-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00018-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00019-of-00021.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/train-00020-of-00021.parquet + - split: val + path: + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_0_200ep_7k2steps/val-00000-of-00001.parquet +- config_name: inverted_pendulum_200ep__inverted_pendulum_fixed_latency_2_1000ep_7k2steps + data_files: + - split: train + path: + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_2_1000ep_7k2steps/train-00000-of-00002.parquet + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_2_1000ep_7k2steps/train-00001-of-00002.parquet + - split: val + path: + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_2_1000ep_7k2steps/val-00000-of-00001.parquet +- config_name: inverted_pendulum_200ep__inverted_pendulum_fixed_latency_4_1000ep_7k2steps + data_files: + - split: train + path: + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_4_1000ep_7k2steps/train-00000-of-00001.parquet + - split: val + path: + - training/inverted_pendulum_200ep/inverted_pendulum_fixed_latency_4_1000ep_7k2steps/val-00000-of-00001.parquet +tags: +- latency-sensitive-bench +- latency-information +- research-artifacts +- simulation-control +- evaluation +- latency +pretty_name: Latency-in-prompt ablations and archived Inverted Pendulum data +language: +- en +task_categories: +- reinforcement-learning +dataset_info: +- config_name: inverted_pendulum_200ep_2__inverted_pendulum_fixed_latency_0_100ep_1ksteps_og + features: + - name: action + list: float32 + - name: action_id + dtype: int64 + - name: action_text + dtype: string + - name: decision_step + dtype: int64 + - name: env_name + dtype: string + - name: episode_idx + dtype: int64 + - name: image + dtype: image + - name: latency_ms + dtype: float64 + - name: latency_raw_frames + dtype: int64 + - name: prompt + dtype: string + - name: raw_reward + dtype: float64 + - name: seed + dtype: int64 + - name: split + dtype: string + - name: state + list: float32 + download_size: 311624367 +- config_name: inverted_pendulum_200ep_2__inverted_pendulum_fixed_latency_2_1000ep_7k2steps + features: + - name: image + dtype: image + - name: env_name + dtype: string + - name: episode_idx + dtype: int64 + - name: decision_step + dtype: int64 + - name: split + dtype: string + - name: seed + dtype: int64 + - name: prompt + dtype: string + - name: latency_raw_frames + dtype: int64 + - name: latency_ms + dtype: float64 + - name: raw_reward + dtype: float64 + - name: action_id + dtype: int64 + - name: action + list: float32 + - name: action_text + dtype: string + - name: state + list: float32 + download_size: 613208881 +- config_name: inverted_pendulum_200ep_2__inverted_pendulum_fixed_latency_4_1000ep_7k2steps + features: + - name: image + dtype: image + - name: env_name + dtype: string + - name: episode_idx + dtype: int64 + - name: decision_step + dtype: int64 + - name: split + dtype: string + - name: seed + dtype: int64 + - name: prompt + dtype: string + - name: latency_raw_frames + dtype: int64 + - name: latency_ms + dtype: float64 + - name: raw_reward + dtype: float64 + - name: action_id + dtype: int64 + - name: action + list: float32 + - name: action_text + dtype: string + - name: state + list: float32 + download_size: 209654575 +- config_name: inverted_pendulum_200ep__inverted_pendulum_fixed_latency_0_200ep_7k2steps + features: + - name: image + dtype: image + - name: env_name + dtype: string + - name: episode_idx + dtype: int64 + - name: decision_step + dtype: int64 + - name: split + dtype: string + - name: seed + dtype: int64 + - name: prompt + dtype: string + - name: latency_raw_frames + dtype: int64 + - name: latency_ms + dtype: float64 + - name: raw_reward + dtype: float64 + - name: action_id + dtype: int64 + - name: action + list: float32 + - name: action_text + dtype: string + - name: state + list: float32 + download_size: 9666412181 +- config_name: inverted_pendulum_200ep__inverted_pendulum_fixed_latency_2_1000ep_7k2steps + features: + - name: image + dtype: image + - name: env_name + dtype: string + - name: episode_idx + dtype: int64 + - name: decision_step + dtype: int64 + - name: split + dtype: string + - name: seed + dtype: int64 + - name: prompt + dtype: string + - name: latency_raw_frames + dtype: int64 + - name: latency_ms + dtype: float64 + - name: raw_reward + dtype: float64 + - name: action_id + dtype: int64 + - name: action + list: float32 + - name: action_text + dtype: string + - name: state + list: float32 + download_size: 613208881 +- config_name: inverted_pendulum_200ep__inverted_pendulum_fixed_latency_4_1000ep_7k2steps + features: + - name: image + dtype: image + - name: env_name + dtype: string + - name: episode_idx + dtype: int64 + - name: decision_step + dtype: int64 + - name: split + dtype: string + - name: seed + dtype: int64 + - name: prompt + dtype: string + - name: latency_raw_frames + dtype: int64 + - name: latency_ms + dtype: float64 + - name: raw_reward + dtype: float64 + - name: action_id + dtype: int64 + - name: action + list: float32 + - name: action_text + dtype: string + - name: state + list: float32 + download_size: 209654575 +--- + +# Latency-in-prompt ablations — experiment evidence and archived data + +Inverted Pendulum prompt-aware and prompt-neutral models, source data and their exact provenance. These model identities are not substituted for the unidentified historical checkpoints behind the paper table. + +## Active paper experiments and archived version + +The current latency-in-prompt experiment uses **Flappy Bird and Demon Attack**. +The Inverted Pendulum model and data files in this repository are a retained +archive version. Their existing paths and dataset configs remain unchanged. + +| Active task | Source status | Training-data relation | +|---|---|---| +| Flappy Bird | Two fixed step-5000 sources confirmed against all 200 paper returns | Mix L0–L4 Flappy partitions, 40 training episodes per latency | +| Demon Attack | Step-7000 paper summaries retained; model/run links pending the responsible researcher | `demon_attack_01234_40ep` is a candidate source, not a confirmed student pairing | + +Confirmed Flappy model sources: + +- [With latency in prompt](https://huggingface.co/talha15032/openvla_bridge_flappy_latency_mixed_exp2/tree/610906e990beefa44c23d438a3b50a556d152900). +- [Without latency information](https://huggingface.co/talha15032/openvla_bridge_flappy_latency_mixed_exp2_no_latency_information/tree/bf8368f6adc45ce8f4c31e1bbe25fc3f9432b68d). + +The public Flappy sources contain weights and evaluations, but lack complete +original model configs and normalization statistics. The source weights remain +at those fixed repositories; this card does not label them as complete local +inference bundles. Their exact historical training-time dataset revision is not recorded. `active_paper_sources.json` records the source identities. + +The current maintained Flappy recipe pins its raw source in +`latency-transfer-data@5305590625c28a6922e73f46d18d52738762c906`, under +`training/flappy_200ep/flappy_fix_latency__200ep`. +Demon's candidate +[data export](https://huggingface.co/datasets/latency-sensitive-bench/demon_attack_01234_40ep/tree/fa0a14bb3cbba8701cc9da52453c4b143089ffb4) +uses L0–L4 decision-step labels, or 0/4/8/12/16 raw frames with frameskip 4. +The exact training consumer is not yet confirmed. The paper values remain unchanged. + +## Experiment repository consolidation + +Independent experiment sources are retained under `training//`. Each source has its own dataset config and original metadata. Different latency units, episode budgets and action layouts are preserved. Evaluation JSON files are under `evaluations//`. `experiment_repository_index.json` records immutable source identities and model/data/paper relationships. + +## Archived Inverted Pendulum dataset contents and collection + +Six Parquet configs retain two Inverted Pendulum source exports and their original L0/L2/L4 partitions. +The source collection metadata, model evaluations and paper episode returns remain separate evidence. +The source configs record their own episode counts, latency conditions and preprocessing budgets. + +## Fields and units + +The YAML provides each config's exact image, action, prompt, episode and latency schema. The table below gives measured split row counts. +The selected model uses a five-choice discrete action head; its action IDs are not a generic continuous-control tensor contract. +The recorded environment and observation rates are 25 FPS for these model recipes. +Read the source latency fields and original metadata rather than interpreting a filename alone. + +## Source limitations + +The two source exports share identical L2/L4 file objects, while their L0 data differ. +These repeated configs are not independent samples. +The original paper table's checkpoint identity is unrecorded. +The three archived model runs cannot replace that table's 120 original episode returns. + +## Rows in each source configuration + +Counts refer to stored rows, not independent episodes or unique samples across overlapping configs. +New split byte sizes are not estimated for metadata fields that require decoded Arrow sizes. + +| Dataset config | Split | Rows | +|---|---|---:| +| `inverted_pendulum_200ep_2__inverted_pendulum_fixed_latency_0_100ep_1ksteps_og` | train | 90,000 | +| `inverted_pendulum_200ep_2__inverted_pendulum_fixed_latency_0_100ep_1ksteps_og` | val | 10,000 | +| `inverted_pendulum_200ep_2__inverted_pendulum_fixed_latency_2_1000ep_7k2steps` | train | 98,293 | +| `inverted_pendulum_200ep_2__inverted_pendulum_fixed_latency_2_1000ep_7k2steps` | val | 944 | +| `inverted_pendulum_200ep_2__inverted_pendulum_fixed_latency_4_1000ep_7k2steps` | train | 30,304 | +| `inverted_pendulum_200ep_2__inverted_pendulum_fixed_latency_4_1000ep_7k2steps` | val | 292 | +| `inverted_pendulum_200ep__inverted_pendulum_fixed_latency_0_200ep_7k2steps` | train | 1,425,600 | +| `inverted_pendulum_200ep__inverted_pendulum_fixed_latency_0_200ep_7k2steps` | val | 14,400 | +| `inverted_pendulum_200ep__inverted_pendulum_fixed_latency_2_1000ep_7k2steps` | train | 98,293 | +| `inverted_pendulum_200ep__inverted_pendulum_fixed_latency_2_1000ep_7k2steps` | val | 944 | +| `inverted_pendulum_200ep__inverted_pendulum_fixed_latency_4_1000ep_7k2steps` | train | 30,304 | +| `inverted_pendulum_200ep__inverted_pendulum_fixed_latency_4_1000ep_7k2steps` | val | 292 | + +## Read a named dataset configuration + +This archive has 6 separate dataset configs. +Choose a config explicitly rather than concatenating unrelated experiments. +The revision below identifies the existing data files and selectors. + +```python +from datasets import load_dataset + +rows = load_dataset( + "latency-sensitive-bench/latency-information-data", + name="inverted_pendulum_200ep_2__inverted_pendulum_fixed_latency_0_100ep_1ksteps_og", + revision="d49c68089337d3974c41208f02c9fb9c73bf83c2", + split="train", + streaming=True, +) +episode_or_step = next(iter(rows)) +``` + +Download the original files when a consumer needs the source layout: + +```bash +HF_ENDPOINT=https://huggingface.co hf download latency-sensitive-bench/latency-information-data \ + --revision d49c68089337d3974c41208f02c9fb9c73bf83c2 \ + --repo-type dataset --include 'training/inverted_pendulum_200ep_2/inverted_pendulum_fixed_latency_0_100ep_1ksteps_og/**' \ + --local-dir /path/to/latency-information-data +``` + +## Model consumers and provenance + +[Model archive at fixed revision](https://huggingface.co/latency-sensitive-bench/latency-information-models/tree/05f6f35c1b5a86d0674ea956c7ffcd2c0a9d3d3c) records model/data relationships and identity limits. +Original collection metadata and source cards remain unchanged inside the source directories. +The structured indexes distinguish source facts, accepted paper inputs and unresolved bindings. + +## Recorded code snapshots + +Available training and validation source snapshots are in the +[shared code archive](https://huggingface.co/datasets/latency-sensitive-bench/latency-transfer-data/tree/d0008f86ede35ee7db6e8d43aea75281417255b6/code) and the +[fine-tuning code archive](https://huggingface.co/datasets/latency-sensitive-bench/vla-finetuning-scope-data/tree/082d01f51db0d7489d5ee2ac0ca9cf49530688d2/code). +Select the commit recorded for the run when that source is available. +A compatible validation loader is not evidence of an unknown original training commit. + +## License and source rights + +The archive has no documented common license for all retained artifacts. +The YAML therefore does not assign a new archive-wide license. +Original source cards, backbone terms and environment assets retain their own provenance. +The license of experiment code does not establish the license of every checkpoint or rendered dataset. diff --git a/experiments/latency-in-prompt/provenance/latency-information-data/active_paper_sources.json b/experiments/latency-in-prompt/provenance/latency-information-data/active_paper_sources.json new file mode 100644 index 0000000000000000000000000000000000000000..764202d27b7d8b445d92fad54035883ead02b29e --- /dev/null +++ b/experiments/latency-in-prompt/provenance/latency-information-data/active_paper_sources.json @@ -0,0 +1,128 @@ +{ + "active_paper_tasks": [ + "Flappy Bird", + "Demon Attack" + ], + "archive_task": "Inverted Pendulum", + "flappy_models": [ + { + "condition": "with_latency_prompt", + "repo": "talha15032/openvla_bridge_flappy_latency_mixed_exp2", + "revision": "610906e990beefa44c23d438a3b50a556d152900", + "eval_path": "eval/post_train/step_5000.json", + "paper_episode_values_match": true, + "paper_episodes": 100, + "weight_path": "steps_5000_state/model.safetensors", + "weight_identity": "95065673334e0cfd68585fa569393bfee903194b78fa88f27c224c6f7bc222a5", + "weight_bytes": 9138230516, + "training_mode": "mixed_latency", + "training_latencies": [ + 0, + 1, + 2, + 3, + 4 + ], + "training_episodes_per_latency": 40, + "checkpoint_step": 5000, + "training_protocol_evidence": "Recorded paper manifest and matching current source script. Full original model configuration and normalization statistics are absent from the public source bundle.", + "training_data": { + "repo": "latency-sensitive-bench/latency-transfer-data", + "revision": "5305590625c28a6922e73f46d18d52738762c906", + "paths": [ + "training/flappy_200ep/flappy_fix_latency_0_200ep", + "training/flappy_200ep/flappy_fix_latency_1_200ep", + "training/flappy_200ep/flappy_fix_latency_2_200ep", + "training/flappy_200ep/flappy_fix_latency_3_200ep", + "training/flappy_200ep/flappy_fix_latency_4_200ep" + ], + "selection": "40 training episodes from each latency partition", + "binding_scope": "Current maintained training recipe and retained raw source. 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"starVLA_rl_games", + "log_first_timestamp": null, + "log_last_timestamp": null + }, + { + "source_repo": "latency-sensitive-bench/openvla_flappy_l2_lora", + "source_revision": "427f4c0582d6eb9419fa39f5942db1d59585993c", + "source_config": "config.full.yaml", + "source_run_id": "openvla_flappy_l2_lora", + "framework": "QwenOFT", + "steps": 2000, + "data_root": "/mnt/data/latency_data/playground/Datasets/rl_games", + "data_mix": "flappy_fixed_l2_fs4", + "wandb_entity": "saberrr-zju", + "wandb_project": "starVLA_rl_games", + "log_first_timestamp": null, + "log_last_timestamp": null + }, + { + "source_repo": "latency-sensitive-bench/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2", + "source_revision": "177c11a86ee64432264ae8f1e577ecfd6c767918", + "source_config": "config.full.yaml", + "source_run_id": "openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2", + "framework": "QwenOFT", + "steps": 5000, + "data_root": "/home/ubuntu/talha/playground/Datasets/rl_games", + "data_mix": "openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp2", + "wandb_entity": "talha1503", + "wandb_project": "latency-sensitive-bench", + "log_first_timestamp": "2026-10-03 13:00:02", + "log_last_timestamp": "2026-10-03 14:02:29" + }, + { + "source_repo": "latency-sensitive-bench/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3", + "source_revision": "1967aac3fadf905a7f693e388cbf2aebdd40e5de", + "source_config": "config.full.yaml", + "source_run_id": "openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3", + "framework": "QwenOFT", + "steps": 5000, + "data_root": "/home/ubuntu/talha/playground/Datasets/rl_games", + "data_mix": "openvla_inverted_pendulum_mixed_latency_024_og_l0_native_exp3", + "wandb_entity": "talha1503", + "wandb_project": "latency-sensitive-bench", + "log_first_timestamp": "2026-10-03 18:54:30", + "log_last_timestamp": "2026-10-03 19:57:24" + }, + { + "source_repo": "latency-sensitive-bench/openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2", + "source_revision": "bd6274f20b7ff2f36c0b758058ef8ce2e996d7f6", + "source_config": "config.full.yaml", + "source_run_id": "openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2", + "framework": "QwenOFT", + "steps": 5000, + "data_root": "/home/ubuntu/talha/playground/Datasets/rl_games", + "data_mix": "openvla_inverted_pendulum_mixed_latency_024_og_l0_native_no_latency_prompt_exp2", + "wandb_entity": "talha1503", + "wandb_project": "latency-sensitive-bench", + "log_first_timestamp": "2026-10-03 14:37:16", + "log_last_timestamp": "2026-10-03 15:35:35" + } + ], + "wandb_provenance_file": "provenance/wandb_provenance.json" +} \ No newline at end of file diff --git a/experiments/latency-in-prompt/provenance/latency-information-data/paper/legacy/figures/inverted_pendulum_prompt_ablation/README.md b/experiments/latency-in-prompt/provenance/latency-information-data/paper/legacy/figures/inverted_pendulum_prompt_ablation/README.md new file mode 100644 index 0000000000000000000000000000000000000000..3ea067b99f2c7a03aecd0a15c31e1bc4f92faa40 --- /dev/null +++ b/experiments/latency-in-prompt/provenance/latency-information-data/paper/legacy/figures/inverted_pendulum_prompt_ablation/README.md @@ -0,0 +1,19 @@ +# Archived Inverted Pendulum latency-prompt experiment + +This directory preserves the former standalone plot and its 120 episode returns. +The active latency-in-prompt table uses Flappy Bird and Demon Attack. +The Inverted Pendulum inputs do not enter the active table renderer. + +`fig.pdf`, `fig.png` and `data.csv` retain their original bytes from paper revision +`74a79adcbe8fe8e320afe93f8487e2794ca7babe`. +`episodes.csv` retains all rows and values of the former +`inverted_pendulum_episodes.csv`; line endings are normalized to LF. +The original plot source is recorded at paper revision +`b263886b6cfd5cf14b4e31b19d94fc4d9d087e22`, path +`figures/fig22_inverted_pendulum_prompt_ablation/plot.py`. + +The three separately archived model runs and two dataset exports remain in +[latency-information-models](https://huggingface.co/latency-sensitive-bench/latency-information-models) +and [latency-information-data](https://huggingface.co/datasets/latency-sensitive-bench/latency-information-data). +The old paper result did not record exact checkpoint identities. +Those three models are not established as the weights behind these 120 returns. diff --git a/experiments/latency-in-prompt/provenance/latency-information-data/paper/legacy/figures/inverted_pendulum_prompt_ablation/data.csv b/experiments/latency-in-prompt/provenance/latency-information-data/paper/legacy/figures/inverted_pendulum_prompt_ablation/data.csv new file mode 100644 index 0000000000000000000000000000000000000000..a2d92f7f6f1fefcb7372fd47b30cb44314c91e3b --- /dev/null +++ b/experiments/latency-in-prompt/provenance/latency-information-data/paper/legacy/figures/inverted_pendulum_prompt_ablation/data.csv @@ -0,0 +1,7 @@ +latency,condition,mean_return +0,with_latency_prompt,539.9 +0,no_latency_prompt,56.2 +2,with_latency_prompt,80.1 +2,no_latency_prompt,71.5 +4,with_latency_prompt,27.6 +4,no_latency_prompt,27.4 diff --git a/experiments/latency-in-prompt/provenance/latency-information-data/paper/legacy/figures/inverted_pendulum_prompt_ablation/episodes.csv b/experiments/latency-in-prompt/provenance/latency-information-data/paper/legacy/figures/inverted_pendulum_prompt_ablation/episodes.csv new file mode 100644 index 0000000000000000000000000000000000000000..3d228cfaed9bb6185d5f003be63fee0ef5987c6b --- /dev/null +++ b/experiments/latency-in-prompt/provenance/latency-information-data/paper/legacy/figures/inverted_pendulum_prompt_ablation/episodes.csv @@ -0,0 +1,121 @@ +condition_id,eval_latency_steps,episode_index,episode_return +with_latency_prompt,0,0,94 +with_latency_prompt,0,1,1000 +with_latency_prompt,0,2,969 +with_latency_prompt,0,3,1000 +with_latency_prompt,0,4,1000 +with_latency_prompt,0,5,344 +with_latency_prompt,0,6,1000 +with_latency_prompt,0,7,225 +with_latency_prompt,0,8,138 +with_latency_prompt,0,9,954 +with_latency_prompt,0,10,98 +with_latency_prompt,0,11,572 +with_latency_prompt,0,12,1000 +with_latency_prompt,0,13,90 +with_latency_prompt,0,14,487 +with_latency_prompt,0,15,311 +with_latency_prompt,0,16,317 +with_latency_prompt,0,17,92 +with_latency_prompt,0,18,106 +with_latency_prompt,0,19,1000 +with_latency_prompt,2,0,91 +with_latency_prompt,2,1,41 +with_latency_prompt,2,2,48 +with_latency_prompt,2,3,86 +with_latency_prompt,2,4,42 +with_latency_prompt,2,5,98 +with_latency_prompt,2,6,93 +with_latency_prompt,2,7,152 +with_latency_prompt,2,8,98 +with_latency_prompt,2,9,46 +with_latency_prompt,2,10,114 +with_latency_prompt,2,11,83 +with_latency_prompt,2,12,52 +with_latency_prompt,2,13,101 +with_latency_prompt,2,14,26 +with_latency_prompt,2,15,112 +with_latency_prompt,2,16,97 +with_latency_prompt,2,17,94 +with_latency_prompt,2,18,42 +with_latency_prompt,2,19,86 +with_latency_prompt,4,0,37 +with_latency_prompt,4,1,22 +with_latency_prompt,4,2,29 +with_latency_prompt,4,3,31 +with_latency_prompt,4,4,22 +with_latency_prompt,4,5,28 +with_latency_prompt,4,6,25 +with_latency_prompt,4,7,30 +with_latency_prompt,4,8,25 +with_latency_prompt,4,9,26 +with_latency_prompt,4,10,30 +with_latency_prompt,4,11,26 +with_latency_prompt,4,12,33 +with_latency_prompt,4,13,26 +with_latency_prompt,4,14,22 +with_latency_prompt,4,15,40 +with_latency_prompt,4,16,27 +with_latency_prompt,4,17,26 +with_latency_prompt,4,18,22 +with_latency_prompt,4,19,26 +no_latency_information,0,0,63 +no_latency_information,0,1,46 +no_latency_information,0,2,63 +no_latency_information,0,3,58 +no_latency_information,0,4,54 +no_latency_information,0,5,54 +no_latency_information,0,6,46 +no_latency_information,0,7,58 +no_latency_information,0,8,46 +no_latency_information,0,9,60 +no_latency_information,0,10,53 +no_latency_information,0,11,48 +no_latency_information,0,12,79 +no_latency_information,0,13,46 +no_latency_information,0,14,72 +no_latency_information,0,15,58 +no_latency_information,0,16,48 +no_latency_information,0,17,65 +no_latency_information,0,18,50 +no_latency_information,0,19,57 +no_latency_information,2,0,114 +no_latency_information,2,1,45 +no_latency_information,2,2,64 +no_latency_information,2,3,66 +no_latency_information,2,4,42 +no_latency_information,2,5,115 +no_latency_information,2,6,82 +no_latency_information,2,7,94 +no_latency_information,2,8,98 +no_latency_information,2,9,46 +no_latency_information,2,10,114 +no_latency_information,2,11,34 +no_latency_information,2,12,52 +no_latency_information,2,13,100 +no_latency_information,2,14,45 +no_latency_information,2,15,112 +no_latency_information,2,16,54 +no_latency_information,2,17,60 +no_latency_information,2,18,42 +no_latency_information,2,19,52 +no_latency_information,4,0,37 +no_latency_information,4,1,22 +no_latency_information,4,2,29 +no_latency_information,4,3,31 +no_latency_information,4,4,22 +no_latency_information,4,5,28 +no_latency_information,4,6,25 +no_latency_information,4,7,30 +no_latency_information,4,8,25 +no_latency_information,4,9,26 +no_latency_information,4,10,30 +no_latency_information,4,11,26 +no_latency_information,4,12,33 +no_latency_information,4,13,26 +no_latency_information,4,14,22 +no_latency_information,4,15,36 +no_latency_information,4,16,27 +no_latency_information,4,17,26 +no_latency_information,4,18,22 +no_latency_information,4,19,26 diff --git a/experiments/latency-in-prompt/provenance/latency-information-data/paper/legacy/figures/inverted_pendulum_prompt_ablation/fig.pdf b/experiments/latency-in-prompt/provenance/latency-information-data/paper/legacy/figures/inverted_pendulum_prompt_ablation/fig.pdf new file mode 100644 index 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a/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/README.md b/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/README.md new file mode 100644 index 0000000000000000000000000000000000000000..78b68885bfdc9b3ae5a81df5af3a19943f767e70 --- /dev/null +++ b/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/README.md @@ -0,0 +1,136 @@ +# Table 3: latency information ablations + +Table 3 in Section 5.1 compares mixed-latency OpenVLA policies with and without +an explicit delay value in the prompt. The first column is Task, with each +task name spanning its Yes/No rows. The second column is Latency in prompt; +five shared columns under Evaluation latency list 0--4. + +The Flappy Bird policies both +train on delays 0--4 with 40 episodes per delay (200 total) for 5,000 steps; +the only prompt difference is whether the latency value is included. Each +policy is evaluated after training at fixed delays 0--4 for 20 episodes per +delay, with a 3,600-step horizon. The earlier fixed-delay sweeps use 30 Hz, so +one evaluation frame is 33.33 ms. + +Demon Attack is a post-train step-7,000 mixed-latency prompt ablation. The +checked-in summary records the mean and standard deviation of return and +episode length for 20 episodes at each evaluation latency. Unlike Flappy Bird +it stores cell summaries rather than all episode returns. + +Each task has Yes/No prompt-condition rows at delays 0--4. Each cell shows +mean episode return and the half-width of a two-sided Student-t 95% confidence +interval over 20 evaluation episodes, rounded to one decimal. Flappy Bird has +one training seed per prompt condition. The intervals describe uncertainty in +the mean across evaluation episodes, not variation across training seeds. + +The full-width table aligns both tasks to the same delay columns. +Fixed-width numeric boxes align the means on the right and interval +half-widths on the left, keeping the plus/minus signs aligned across rows. Each +Yes row uses `PURPLE_FILL` from `paper_colors.py`, starting at the Latency in +prompt column; the merged Task cells stay white, as in Table 1's shared model +column. + +## Sources + +### Flappy Bird + +`data.csv` contains all 200 episode-level returns. +`local_sources.csv` records +the raw file path, SHA-256, source revision, checkpoint, mean, population +standard deviation, and episode count for each cell. `hf_sources.csv` records +the source scripts and immutable Hugging Face revisions: + +- Prompt-aware: `talha15032/openvla_bridge_flappy_latency_mixed_exp2`, + revision `610906e990beefa44c23d438a3b50a556d152900`, file + `eval/post_train/step_5000.json`. +- Prompt-neutral: `talha15032/openvla_bridge_flappy_latency_mixed_exp2_no_latency_information`, + revision `bf8368f6adc45ce8f4c31e1bbe25fc3f9432b68d`, file + `eval/post_train/step_5000.json`. + +The model uses OpenVLA with Bridge initialization. The prompt-aware source +script is `examples/rl_games/bash_scripts/openvla/bridge/mixed/flappy.sh`; +the prompt-neutral script is +`examples/rl_games/bash_scripts/openvla/bridge/latency_ablation/flappy_bird_mixed_latency.sh`. + +### Demon Attack + +`demon_attack_means.csv` contains the post-train step-7,000 means from the +mixed-latency OpenVLA prompt ablation. Both conditions use fixed episode seeds, +evaluation seed 42, and 20 episodes per latency. + +## Confidence interval calculation + +The interval is `mean ± t(0.975, n-1) * s / sqrt(n)`, where `s` is the sample +standard deviation and `n` is the episode count. At `n=20`, the critical value +is approximately 2.093024. + +For Flappy Bird, `render_table.py` computes the mean, sample standard deviation +(`statistics.stdev`, denominator `n-1`), and count from the episode returns. +For Demon Attack, `std_return` follows the evaluator's `np.std(rewards)` +convention (`ddof=0`), as used in +`third_party/starVLA/starVLA/training/rl_games/eval_core.py` in the benchmark +repository. The renderer converts it to `s = std_return * sqrt(n/(n-1))` +before calculating the interval. It reads `n` from `episode_count`. + +`table.tex` and `summary.json` use the same calculated means and interval +half-widths. The JSON stores their one-decimal display values for the website; +the input CSVs retain their original precision. A source standard deviation +is never displayed as a confidence interval. + +## Reproduction + +With SciPy and Matplotlib installed, `python render_table.py` regenerates +`table.tex` and `summary.json` from local CSVs without network access. The existing `fetch_hf.py` and +`build_data.py` entrypoints refresh only the pinned Flappy Bird inputs; +they do not alter `demon_attack_means.csv`. + +Compile the manuscript and regenerate the standalone vector PDF and 300-DPI +PNG from the paper root: + +```bash +python3 tables/table2_latency_information_ablation/render_table.py +latexmk -pdf arxiv.tex +latexmk -pdf iclr2027.tex +latexmk -pdf -outdir=build/table3 -auxdir=build/table3 tables/table2_latency_information_ablation/preview.tex +pdfcrop --margins 6 build/table3/preview.pdf tables/table2_latency_information_ablation/table.pdf +pdftoppm -singlefile -r 300 -png tables/table2_latency_information_ablation/table.pdf tables/table2_latency_information_ablation/table +``` + +To synchronize the website from the paper repository root: + +```bash +cp tables/table2_latency_information_ablation/summary.json ../lagen/src/data/prompt.json +cp arxiv.pdf ../lagen/public/assets/paper.pdf +``` + +## Archive ownership and confirmed model links + +The active experiment owner is `latency-information-models/data` for both +Flappy Bird and Demon Attack. Inverted Pendulum is a retained archive version +under `legacy/figures/inverted_pendulum_prompt_ablation/`, outside the active table. + +Flappy source checkpoints are both `steps_5000_state/model.safetensors`: + +- [With latency in prompt](https://huggingface.co/talha15032/openvla_bridge_flappy_latency_mixed_exp2/tree/610906e990beefa44c23d438a3b50a556d152900). +- [Without latency information](https://huggingface.co/talha15032/openvla_bridge_flappy_latency_mixed_exp2_no_latency_information/tree/bf8368f6adc45ce8f4c31e1bbe25fc3f9432b68d). + +All 200 stored Flappy episode returns match the two fixed source evaluation files. +Both source scripts mix five Flappy latency partitions, L0–L4, with 40 training +episodes from each. This is mixed-latency training within one game. +The current maintained recipe points to the shared raw owner +`latency-transfer-data@5305590625c28a6922e73f46d18d52738762c906`, prefixes +`training/flappy_200ep/flappy_fix_latency__200ep`. +The two model repositories retain inference weights but do not include complete +original model configs and normalization statistics. The historical training-time +dataset revision is not recorded there. Those gaps remain explicit. + +Demon Attack's step-7000 source model and training-run links remain pending +confirmation from the responsible researcher. The current CSV alone does not +establish a model identity or an exact training-data pairing. +The retained candidate dataset +[demon_attack_01234_40ep](https://huggingface.co/datasets/latency-sensitive-bench/demon_attack_01234_40ep/tree/fa0a14bb3cbba8701cc9da52453c4b143089ffb4) +contains 40 training episodes from each of five fixed-latency sources. +Its L0–L4 labels mean decision steps and correspond to 0/4/8/12/16 raw Atari +frames with frameskip 4. Its use by the current table's student models is +unconfirmed. Older mixed-0/2/4/6/8 and single-L4 scripts are not substituted +for the current table's sources. diff --git a/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/build_data.py b/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/build_data.py new file mode 100644 index 0000000000000000000000000000000000000000..231bcc9962e8f917106f8c8d08d2cf838a670434 --- /dev/null +++ b/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/build_data.py @@ -0,0 +1,189 @@ +from __future__ import annotations + +import csv +import hashlib +import json +import math +import statistics +from pathlib import Path +from typing import Sequence + + +HERE = Path(__file__).resolve().parent +DATA = HERE / "data.csv" +HF_SOURCES = HERE / "hf_sources.csv" +LOCAL_SOURCES = HERE / "local_sources.csv" + +EXPECTED_LATENCIES = tuple(range(5)) +EXPECTED_EPISODES = 20 +EXPECTED_STEP = 5000 + +DATA_FIELDS = ( + "record_type", + "model_family", + "env_id", + "env_title", + "condition_id", + "condition_label", + "prompt_mode", + "training_mode", + "train_latencies", + "episodes_per_latency", + "training_episode_count", + "max_train_steps", + "checkpoint_step", + "eval_latency_steps", + "eval_latency_ms", + "eval_seed", + "episode_id", + "episode_index", + "episode_seed", + "episode_return", + "episode_length", + "source_id", +) + +LOCAL_SOURCE_FIELDS = ( + "source_id", + "condition_id", + "condition_label", + "prompt_mode", + "relative_path", + "sha256", + "hf_repo_id", + "hf_revision", + "hf_path", + "checkpoint_step", + "eval_latency_steps", + "episode_count", + "mean_return", + "std_return_population", + "mean_episode_length", +) + + +def sha256(path: Path) -> str: + return hashlib.sha256(path.read_bytes()).hexdigest() + + +def read_sources() -> list[dict[str, str]]: + with HF_SOURCES.open(newline="", encoding="utf-8") as file: + return list(csv.DictReader(file)) + + +def require_close(actual: float, expected: float, context: str) -> None: + if not math.isclose(actual, expected, rel_tol=1e-9, abs_tol=1e-9): + raise ValueError(f"{context}: expected {expected}, got {actual}") + + +def latency_key(env_id: str, latency: int) -> str: + return f"{env_id}/latency_{latency}" + + +def build_rows(sources: Sequence[dict[str, str]]) -> tuple[list[dict[str, object]], list[dict[str, object]]]: + data_rows: list[dict[str, object]] = [] + local_rows: list[dict[str, object]] = [] + + for source in sources: + raw_path = HERE / source["local_raw_path"] + payload = json.loads(raw_path.read_text(encoding="utf-8")) + aggregate = payload["aggregate"] + per_latency = payload["per_latency"] + checkpoint_step = int(source["checkpoint_step"]) + if checkpoint_step != EXPECTED_STEP: + raise ValueError(f"unexpected checkpoint step {checkpoint_step}") + if int(aggregate["step"]) != checkpoint_step: + raise ValueError(f"{raw_path}: aggregate step does not match source") + + for latency in EXPECTED_LATENCIES: + key = latency_key(source["env_id"], latency) + metrics = per_latency[key] + rewards = [float(value) for value in metrics["episode_rewards"]] + lengths = [int(value) for value in metrics["episode_lengths"]] + episode_indices = [int(value) for value in metrics["episode_indices"]] + episode_seeds = metrics.get("episode_seeds") or [None] * len(rewards) + + if int(metrics["latency"]) != latency: + raise ValueError(f"{key}: latency mismatch") + if len(rewards) != EXPECTED_EPISODES: + raise ValueError(f"{key}: expected {EXPECTED_EPISODES} episodes, got {len(rewards)}") + if len(lengths) != len(rewards) or len(episode_indices) != len(rewards): + raise ValueError(f"{key}: per-episode arrays have inconsistent lengths") + + mean_return = statistics.fmean(rewards) + std_return = statistics.pstdev(rewards) + mean_length = statistics.fmean(lengths) + require_close(mean_return, float(metrics["mean_reward"]), f"{key} mean return") + require_close(std_return, float(metrics["std_reward"]), f"{key} return std") + require_close(mean_length, float(metrics["mean_length"]), f"{key} mean length") + + source_id = f"{source['condition_id']}_latency_{latency}" + local_rows.append( + { + "source_id": source_id, + "condition_id": source["condition_id"], + "condition_label": source["condition_label"], + "prompt_mode": source["prompt_mode"], + "relative_path": source["local_raw_path"], + "sha256": sha256(raw_path), + "hf_repo_id": source["hf_repo_id"], + "hf_revision": source["hf_revision"], + "hf_path": source["hf_path"], + "checkpoint_step": checkpoint_step, + "eval_latency_steps": latency, + "episode_count": len(rewards), + "mean_return": f"{mean_return:.12g}", + "std_return_population": f"{std_return:.12g}", + "mean_episode_length": f"{mean_length:.12g}", + } + ) + + for episode_id, (reward, length, episode_index, episode_seed) in enumerate( + zip(rewards, lengths, episode_indices, episode_seeds, strict=True) + ): + data_rows.append( + { + "record_type": "episode", + "model_family": "OpenVLA", + "env_id": source["env_id"], + "env_title": source["env_title"], + "condition_id": source["condition_id"], + "condition_label": source["condition_label"], + "prompt_mode": source["prompt_mode"], + "training_mode": source["training_mode"], + "train_latencies": source["train_latencies"], + "episodes_per_latency": int(source["episodes_per_latency"]), + "training_episode_count": int(source["training_episode_count"]), + "max_train_steps": int(source["max_train_steps"]), + "checkpoint_step": checkpoint_step, + "eval_latency_steps": latency, + "eval_latency_ms": f"{latency * (1000.0 / 30.0):.6f}", + "eval_seed": metrics["eval_seed"], + "episode_id": episode_id, + "episode_index": episode_index, + "episode_seed": "" if episode_seed is None else episode_seed, + "episode_return": f"{reward:.12g}", + "episode_length": length, + "source_id": source_id, + } + ) + + return data_rows, local_rows + + +def write_csv(path: Path, fields: Sequence[str], rows: Sequence[dict[str, object]]) -> None: + with path.open("w", newline="", encoding="utf-8") as file: + writer = csv.DictWriter(file, fieldnames=fields) + writer.writeheader() + writer.writerows(rows) + print(f"wrote {path} ({len(rows)} rows)") + + +def main() -> None: + rows, local_sources = build_rows(read_sources()) + write_csv(DATA, DATA_FIELDS, rows) + write_csv(LOCAL_SOURCES, LOCAL_SOURCE_FIELDS, local_sources) + + +if __name__ == "__main__": + main() diff --git a/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/data.csv b/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/data.csv new file mode 100644 index 0000000000000000000000000000000000000000..e2ffb09ea0db6df06bf837401df1c8608ed32e6c --- /dev/null +++ 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information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,1,33.333333,42,19,19,,4.100000076,52,no_latency_information_latency_1 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,0,0,,6.80000010133,70,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,1,1,,15.2000001967,136,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,2,2,,4.20000007749,53,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,3,3,,4.70000008494,58,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,4,4,,13.8000001907,131,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,5,5,,20.5000002608,180,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,6,6,,6.70000009984,69,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,7,7,,6.80000010133,70,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,8,8,,4.30000007898,54,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,9,9,,4.00000007451,51,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,10,10,,4.70000008494,58,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,11,11,,4.80000008643,59,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,12,12,,20.5000002608,180,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,13,13,,4.00000007451,51,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,14,14,,3.90000007302,50,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,15,15,,13.1000001803,124,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,16,16,,18.3000002429,167,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,17,17,,4.30000007898,54,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,18,18,,22.9000002965,204,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,2,66.666667,42,19,19,,4.00000007451,51,no_latency_information_latency_2 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,0,0,,3.90000007302,50,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,1,1,,4.90000008792,60,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,2,2,,4.100000076,52,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,3,3,,13.2000001818,125,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,4,4,,5.00000008941,61,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,5,5,,3.90000007302,50,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,6,6,,9.50000014156,97,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,7,7,,4.90000008792,60,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,8,8,,4.20000007749,53,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,9,9,,3.90000007302,50,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,10,10,,9.50000014156,97,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,11,11,,6.1000000909,63,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,12,12,,3.90000007302,50,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,13,13,,12.9000001773,122,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,14,14,,3.90000007302,50,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,15,15,,3.90000007302,50,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,16,16,,8.40000012517,86,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,17,17,,6.20000009239,64,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,18,18,,12.9000001773,122,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,3,100.000000,42,19,19,,3.90000007302,50,no_latency_information_latency_3 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,0,0,,4.80000008643,59,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,1,1,,3.90000007302,50,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,2,2,,4.80000008643,59,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,3,3,,4.40000008047,55,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,4,4,,3.90000007302,50,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,5,5,,4.80000008643,59,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,6,6,,3.90000007302,50,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,7,7,,3.90000007302,50,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,8,8,,6.1000000909,63,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,9,9,,3.90000007302,50,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,10,10,,6.20000009239,64,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,11,11,,4.20000007749,53,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,12,12,,3.90000007302,50,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,13,13,,6.30000009388,65,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,14,14,,3.90000007302,50,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,15,15,,4.80000008643,59,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,16,16,,3.90000007302,50,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,17,17,,4.20000007749,53,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,18,18,,3.90000007302,50,no_latency_information_latency_4 +episode,OpenVLA,flappy,Flappy Bird,no_latency_information,no latency information,latency_neutral,mixed,0;1;2;3;4,40,200,5000,5000,4,133.333333,42,19,19,,3.90000007302,50,no_latency_information_latency_4 diff --git a/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/demon_attack_means.csv b/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/demon_attack_means.csv new file mode 100644 index 0000000000000000000000000000000000000000..49c5d9660f1eaf6769b871c77d4eaf9459296182 --- /dev/null +++ b/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/demon_attack_means.csv @@ -0,0 +1,11 @@ +condition_id,eval_latency_steps,mean_return,std_return,mean_episode_length,std_episode_length,checkpoint_step,episode_count +with_latency_prompt,0,7409.00,630.155933,3560.00,121.393575,7000,20 +with_latency_prompt,1,6558.00,1061.517075,3495.05,206.356603,7000,20 +with_latency_prompt,2,5551.25,987.568827,3430.90,223.104213,7000,20 +with_latency_prompt,3,4038.00,1866.912826,2948.60,833.599988,7000,20 +with_latency_prompt,4,3630.00,1494.149424,2978.55,857.917506,7000,20 +no_latency_information,0,3814.75,1974.074767,3004.25,803.545635,7000,20 +no_latency_information,1,4392.50,1773.865482,3192.65,723.209947,7000,20 +no_latency_information,2,4478.75,1076.415202,3366.70,406.178791,7000,20 +no_latency_information,3,4091.25,1827.481105,3139.35,701.786811,7000,20 +no_latency_information,4,1995.25,1469.165133,2153.85,863.209724,7000,20 diff --git a/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/fetch_hf.py b/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/fetch_hf.py new file mode 100644 index 0000000000000000000000000000000000000000..36db715640c07ff748a3d1a4c7130dedd20414a7 --- /dev/null +++ b/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/fetch_hf.py @@ -0,0 +1,119 @@ +from __future__ import annotations + +import csv +from dataclasses import dataclass +from pathlib import Path + +from huggingface_hub import hf_hub_download + + +HERE = Path(__file__).resolve().parent +RAW = HERE / "raw" +HF_SOURCES = HERE / "hf_sources.csv" + + +@dataclass(frozen=True) +class Source: + condition_id: str + condition_label: str + prompt_mode: str + training_mode: str + env_id: str + env_title: str + hf_repo_id: str + hf_revision: str + hf_path: str + checkpoint_step: int + train_latencies: str + episodes_per_latency: int + training_episode_count: int + max_train_steps: int + source_script: str + + +SOURCES = ( + Source( + condition_id="with_latency_prompt", + condition_label="mixed latency (with latency in prompt)", + prompt_mode="latency_prompt", + training_mode="mixed", + env_id="flappy", + env_title="Flappy Bird", + hf_repo_id="talha15032/openvla_bridge_flappy_latency_mixed_exp2", + hf_revision="610906e990beefa44c23d438a3b50a556d152900", + hf_path="eval/post_train/step_5000.json", + checkpoint_step=5000, + train_latencies="0;1;2;3;4", + episodes_per_latency=40, + training_episode_count=200, + max_train_steps=5000, + source_script=( + "examples/rl_games/bash_scripts/openvla/bridge/mixed/flappy.sh" + ), + ), + Source( + condition_id="no_latency_information", + condition_label="no latency information", + prompt_mode="latency_neutral", + training_mode="mixed", + env_id="flappy", + env_title="Flappy Bird", + hf_repo_id="talha15032/openvla_bridge_flappy_latency_mixed_exp2_no_latency_information", + hf_revision="bf8368f6adc45ce8f4c31e1bbe25fc3f9432b68d", + hf_path="eval/post_train/step_5000.json", + checkpoint_step=5000, + train_latencies="0;1;2;3;4", + episodes_per_latency=40, + training_episode_count=200, + max_train_steps=5000, + source_script=( + "examples/rl_games/bash_scripts/openvla/bridge/latency_ablation/" + "flappy_bird_mixed_latency.sh" + ), + ), +) + + +FIELDS = ( + "condition_id", + "condition_label", + "prompt_mode", + "training_mode", + "env_id", + "env_title", + "hf_repo_id", + "hf_revision", + "hf_path", + "local_raw_path", + "checkpoint_step", + "train_latencies", + "episodes_per_latency", + "training_episode_count", + "max_train_steps", + "source_script", +) + + +def main() -> None: + RAW.mkdir(exist_ok=True) + with HF_SOURCES.open("w", newline="", encoding="utf-8") as file: + writer = csv.DictWriter(file, fieldnames=FIELDS) + writer.writeheader() + for source in SOURCES: + downloaded = hf_hub_download( + repo_id=source.hf_repo_id, + filename=source.hf_path, + revision=source.hf_revision, + ) + raw_name = f"{source.condition_id}_step_{source.checkpoint_step}.json" + raw_path = RAW / raw_name + raw_path.write_bytes(Path(downloaded).read_bytes()) + row = {field: getattr(source, field) for field in FIELDS if hasattr(source, field)} + row["local_raw_path"] = f"raw/{raw_name}" + writer.writerow(row) + print(f"wrote {raw_path}") + print(f"wrote {HF_SOURCES}") + + +if __name__ == "__main__": + main() diff --git a/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/hf_sources.csv b/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/hf_sources.csv new file mode 100644 index 0000000000000000000000000000000000000000..bca31699a67b101b8831a0a9cc0722ac8aade45b --- /dev/null +++ b/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/hf_sources.csv @@ -0,0 +1,3 @@ +condition_id,condition_label,prompt_mode,training_mode,env_id,env_title,hf_repo_id,hf_revision,hf_path,local_raw_path,checkpoint_step,train_latencies,episodes_per_latency,training_episode_count,max_train_steps,source_script +with_latency_prompt,mixed latency (with latency in prompt),latency_prompt,mixed,flappy,Flappy Bird,talha15032/openvla_bridge_flappy_latency_mixed_exp2,610906e990beefa44c23d438a3b50a556d152900,eval/post_train/step_5000.json,raw/with_latency_prompt_step_5000.json,5000,0;1;2;3;4,40,200,5000,examples/rl_games/bash_scripts/openvla/bridge/mixed/flappy.sh +no_latency_information,no latency information,latency_neutral,mixed,flappy,Flappy Bird,talha15032/openvla_bridge_flappy_latency_mixed_exp2_no_latency_information,bf8368f6adc45ce8f4c31e1bbe25fc3f9432b68d,eval/post_train/step_5000.json,raw/no_latency_information_step_5000.json,5000,0;1;2;3;4,40,200,5000,examples/rl_games/bash_scripts/openvla/bridge/latency_ablation/flappy_bird_mixed_latency.sh diff --git a/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/local_sources.csv b/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/local_sources.csv new file mode 100644 index 0000000000000000000000000000000000000000..3f39992f6ee793c6ee4c0fc8085cb6ba5fa63aa2 --- /dev/null +++ b/experiments/latency-in-prompt/provenance/latency-information-data/paper/tables/table2_latency_information_ablation/local_sources.csv @@ -0,0 +1,11 @@ +source_id,condition_id,condition_label,prompt_mode,relative_path,sha256,hf_repo_id,hf_revision,hf_path,checkpoint_step,eval_latency_steps,episode_count,mean_return,std_return_population,mean_episode_length +with_latency_prompt_latency_0,with_latency_prompt,mixed latency (with latency in prompt),latency_prompt,raw/with_latency_prompt_step_5000.json,04df4ae1c43bead8bdd97832176b10a2cfbcbfe4a34357befaaa1c3503e1f4ed,talha15032/openvla_bridge_flappy_latency_mixed_exp2,610906e990beefa44c23d438a3b50a556d152900,eval/post_train/step_5000.json,5000,0,20,433.775005098,32.7401572999,3513.1 +with_latency_prompt_latency_1,with_latency_prompt,mixed latency (with latency in prompt),latency_prompt,raw/with_latency_prompt_step_5000.json,04df4ae1c43bead8bdd97832176b10a2cfbcbfe4a34357befaaa1c3503e1f4ed,talha15032/openvla_bridge_flappy_latency_mixed_exp2,610906e990beefa44c23d438a3b50a556d152900,eval/post_train/step_5000.json,5000,1,20,433.990005101,46.2479183307,3514.7 +with_latency_prompt_latency_2,with_latency_prompt,mixed latency (with latency in prompt),latency_prompt,raw/with_latency_prompt_step_5000.json,04df4ae1c43bead8bdd97832176b10a2cfbcbfe4a34357befaaa1c3503e1f4ed,talha15032/openvla_bridge_flappy_latency_mixed_exp2,610906e990beefa44c23d438a3b50a556d152900,eval/post_train/step_5000.json,5000,2,20,341.295004018,144.18571691,2768.9 +with_latency_prompt_latency_3,with_latency_prompt,mixed latency (with latency in prompt),latency_prompt,raw/with_latency_prompt_step_5000.json,04df4ae1c43bead8bdd97832176b10a2cfbcbfe4a34357befaaa1c3503e1f4ed,talha15032/openvla_bridge_flappy_latency_mixed_exp2,610906e990beefa44c23d438a3b50a556d152900,eval/post_train/step_5000.json,5000,3,20,290.295003423,169.107918631,2358.75 +with_latency_prompt_latency_4,with_latency_prompt,mixed latency (with latency in prompt),latency_prompt,raw/with_latency_prompt_step_5000.json,04df4ae1c43bead8bdd97832176b10a2cfbcbfe4a34357befaaa1c3503e1f4ed,talha15032/openvla_bridge_flappy_latency_mixed_exp2,610906e990beefa44c23d438a3b50a556d152900,eval/post_train/step_5000.json,5000,4,20,267.580003156,143.601863088,2175.1 +no_latency_information_latency_0,no_latency_information,no latency information,latency_neutral,raw/no_latency_information_step_5000.json,630293ee44cfdb2f3dcd15d6c50ca85af14c292276cda10754d7c65f878d1791,talha15032/openvla_bridge_flappy_latency_mixed_exp2_no_latency_information,bf8368f6adc45ce8f4c31e1bbe25fc3f9432b68d,eval/post_train/step_5000.json,5000,0,20,18.7800002426,15.1325677044,167.3 +no_latency_information_latency_1,no_latency_information,no latency information,latency_neutral,raw/no_latency_information_step_5000.json,630293ee44cfdb2f3dcd15d6c50ca85af14c292276cda10754d7c65f878d1791,talha15032/openvla_bridge_flappy_latency_mixed_exp2_no_latency_information,bf8368f6adc45ce8f4c31e1bbe25fc3f9432b68d,eval/post_train/step_5000.json,5000,1,20,14.3200001933,15.2868769035,133.05 +no_latency_information_latency_2,no_latency_information,no latency information,latency_neutral,raw/no_latency_information_step_5000.json,630293ee44cfdb2f3dcd15d6c50ca85af14c292276cda10754d7c65f878d1791,talha15032/openvla_bridge_flappy_latency_mixed_exp2_no_latency_information,bf8368f6adc45ce8f4c31e1bbe25fc3f9432b68d,eval/post_train/step_5000.json,5000,2,20,9.37500013597,6.54789095709,93.5 +no_latency_information_latency_3,no_latency_information,no latency information,latency_neutral,raw/no_latency_information_step_5000.json,630293ee44cfdb2f3dcd15d6c50ca85af14c292276cda10754d7c65f878d1791,talha15032/openvla_bridge_flappy_latency_mixed_exp2_no_latency_information,bf8368f6adc45ce8f4c31e1bbe25fc3f9432b68d,eval/post_train/step_5000.json,5000,3,20,6.45500010289,3.27390825312,70.6 +no_latency_information_latency_4,no_latency_information,no latency information,latency_neutral,raw/no_latency_information_step_5000.json,630293ee44cfdb2f3dcd15d6c50ca85af14c292276cda10754d7c65f878d1791,talha15032/openvla_bridge_flappy_latency_mixed_exp2_no_latency_information,bf8368f6adc45ce8f4c31e1bbe25fc3f9432b68d,eval/post_train/step_5000.json,5000,4,20,4.48000007942,0.800999382916,54.45 diff --git a/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/INVALIDATION.md b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/INVALIDATION.md new file mode 100644 index 0000000000000000000000000000000000000000..e7e69ae9a5e4a4db2feac3221052876106a44929 --- /dev/null +++ b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/INVALIDATION.md @@ -0,0 +1,65 @@ +# Invalidated standalone evaluation batches + +## Legacy eval_core backend + +The first comparison snapshot is not a valid measure of the trained +checkpoints. Its 11 completed cells came from standalone evaluation runs +created with workspace commit `f4627427f75856181572faba7dc45cabcc03395d`, +which pinned starVLA commit +`9662ad113a8910207f7a17b0faab3480c78756f1`. + +At that revision, training honored +`rl_games.env_eval.eval_backend=latency_bench`, but +`examples/rl_games/scripts/eval_checkpoint.py` always instantiated the legacy +`RlGamesEvalRunner`. For non-KV inputs that runner did not consume +`datasets.vla_data.image_mode` or `num_obs_frames`. With +`pack_image_sequence=false`, both the four-frame prompt and 2x2 mosaic +checkpoints received one current frame; the mosaic was not constructed. + +This backend mismatch explains the direct checkpoint contradiction on Flappy +Bird: + +| Method | Training-integrated post-train eval | Invalid standalone eval | +| --- | ---: | ---: | +| Single frame | 345.658 | 362.314 | +| Four-frame prompt | 346.750 | 42.051 | +| 2x2 mosaic | 361.504 | 2.000 | +| KV memory (Flex) | 389.242 | not run under the 100-episode contract | + +The integrated values are checkpoint-4000, latency-3 means over 50 episodes. +They are not substitutes for the required 100-episode comparison, but they +show that the trained multi-frame checkpoints had not collapsed. StarVLA +commit `81f529f0166ef8d907926789463d2172bd4d8d94` subsequently made standalone +evaluation select the configured backend. The rejected aggregates remain in +`invalidated_eval_core_data.csv`. + +## Demon Attack short-horizon LatencyBench rerun + +The corrected-backend batch created with workspace commit +`0c850807c9d6d4964e4641bcf2ae784994af3a15` did instantiate +`LatencyBenchRlGamesEvalRunner`, but its Demon Attack horizon was still wrong. +StarVLA's `max_steps_per_episode=3600` counts policy decision steps. With +`frameskip=4`, eval_core therefore permits 14400 ALE raw frames. The +LatencyBench integration copied 3600 directly to `eval_max_steps`, whose unit +is raw environment frames, shortening the episode budget by four. + +All four runs reached a mean length of exactly 3600 raw frames: + +| Method | Run ID | Rejected mean reward | +| --- | --- | ---: | +| Single frame | `d69mbmeb` | 306.10 | +| Four-frame prompt | `p2qje13m` | 300.70 | +| 2x2 mosaic | `s7nhs3d1` | 333.60 | +| KV memory (Flex) | `3ycxsk83` | 330.95 | + +These values are excluded from `data.csv`, the figure, and the table. The +accepted replacement evaluations pass `--max-steps-per-episode 14400` and +record the raw-frame budget in their W&B run names. At +`env_fps / obs_fps = 4`, 14400 raw frames correspond to 3600 policy decision +steps. The replacement run IDs are pinned in `wandb_sources.csv`; Flappy Bird +and Deadly Corridor are unchanged. + +The high-reward Demon Attack ghost-trail runs are not substitutes. Their saved +W&B configs declare `eval_backend=eval_core`, `frameskip=4`, and a 3600 +decision-step limit. Their latency label 6 is also six decision steps (24 raw +frames), whereas this comparison evaluates latency 6 raw frames. diff --git a/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/README.md b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/README.md new file mode 100644 index 0000000000000000000000000000000000000000..8a373ce9c342b2bc0e291645fdb7b471ca1832bb --- /dev/null +++ b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/README.md @@ -0,0 +1,152 @@ +# VLA memory-method comparison + +This directory compares four temporal input formats for the same OpenVLA +policy across Flappy Bird, Demon Attack, and Deadly Corridor. The shared table +also includes WanOFT, whose committed source data live in +`exps/memory/compare_table/wanoft/`. + +| Key | Display name | Temporal input | +| --- | --- | --- | +| `single_baseline` | Single frame | Current observation only | +| `plain_multi` | Four-frame prompt | Four observations as separate prompt images | +| `stitch` | 2x2 mosaic | The same four observations tiled into one image | +| `kv_memory_flex` | KV memory (Flex) | Four-frame streaming KV window with packed FlexAttention replay | +| `ghost_trail` | Ghost trail | Ghost-trail image overlay | +| `wanoft` | WanOFT | Five-image ordered context window | + +The non-Flex `kv_memory` method is intentionally absent because it was not run +for this comparison. + +## Evaluation contract + +The comparison uses checkpoint 4000 and one fixed training latency per +environment: + +| Environment | Latency (raw frames) | Max steps (raw frames) | Episodes | Parallel environments | +| --- | ---: | ---: | ---: | ---: | +| Flappy Bird | 3 | 3600 | 100 | 20 | +| Demon Attack | 6 | 14400 | 100 | 20 | +| Deadly Corridor | 6 | 3600 | 100 | 1 | + +All active values come from the standalone `latency_bench` checkpoint +evaluator. The first standalone batch used starVLA's legacy `eval_core` +backend and was invalidated. A corrected-backend Demon Attack rerun was also +invalidated because its 3600-step episode budget was copied directly into +LatencyBench, where the unit is raw frames rather than decision steps. + +For the accepted Demon Attack rerun, `14400` is the per-episode limit in **raw +environment frames**; it is not a checkpoint or a number of policy decisions. +Here `env_fps / obs_fps = 4`, so the policy makes one decision per four raw +frames and `14400 / 4 = 3600` decision steps. The evaluated training checkpoint +remains checkpoint 4000. + +## Current result + +The accepted 14400-raw-frame Demon Attack rerun is shown below. Earlier rejected +Demon Attack values remain excluded; see `INVALIDATION.md` for both root causes +and the exact rejected run IDs. + +| Method | Flappy Bird | Demon Attack | Deadly Corridor | +| --- | ---: | ---: | ---: | +| Single frame | 368.9 +/- 25.9 | 5671.8 +/- 126.3 | 232.0 +/- 51.3 | +| Four-frame prompt | 352.1 +/- 28.2 | 6474.6 +/- 117.8 | 227.1 +/- 33.9 | +| 2x2 mosaic | 343.1 +/- 29.5 | 5783.2 +/- 212.5 | 271.1 +/- 56.7 | +| KV memory (Flex) | 382.2 +/- 25.1 | 6483.5 +/- 109.9 | 229.2 +/- 33.2 | +| Ghost trail | 426.9 +/- 13.7 | 5688.7 +/- 312.7 | - | +| WanOFT | 425.3 +/- 33.1 | 4608.8 +/- 714.8 | 238.9 +/- 74.2 | + +All intervals in the shared table are episode-level Student-t 95% confidence +intervals. The four W&B comparison methods and Ghost trail use checkpoint 4000 +and 100 fixed seeds where available; WanOFT uses its committed +environment-specific checkpoints and 20 fixed seeds. These comparisons do not +establish training-seed significance because there is one training run per cell. + +## Artifacts + +- `wandb_sources.csv`: source states, exact run IDs, and W&B history steps. +- `fetch_wandb.py`: W&B boundary reader and `data.csv` exporter. +- `data.csv`: active W&B comparison matrix plus the Flappy Bird Ghost trail + aggregate. +- `../../exps/memory/compare_table/wanoft/data.csv`: immutable WanOFT source data merged into + the shared table. +- `invalidated_eval_core_data.csv`: rejected legacy-backend aggregates retained + for audit only. +- `INVALIDATION.md`: root-cause and code-version evidence. +- `render_table.py`: merged data validator and TeX table-source writer. +- `table.tex`: manuscript-ready table fragment. +- `preview.tex`: standalone TeX wrapper. +- `table.{pdf,png}`: vector and 300-DPI table previews. + +Valid source records are pinned by independent W&B run ID and history step. +The fetcher also requires the run to declare the LatencyBench backend, +checkpoint 4000, and the method's exact temporal input contract. + +## Statistics + +Only checkpoint-level aggregates remain in W&B; individual episode returns +are unavailable. The logged population standard deviation is converted to a +sample standard deviation before computing + +```text +m +/- t(0.975, n - 1) * s / sqrt(n) +``` + +The interval reflects finite evaluation-episode sampling with fixed episode +seeds. It is not a confidence interval across training seeds. + +## Accepted Demon Attack rerun + +The four accepted W&B sources are pinned independently: + +| Method | Run ID | +| --- | --- | +| Single frame | `nsb0fpng` | +| Four-frame prompt | `dariw0bn` | +| 2x2 mosaic | `aflyy974` | +| KV memory (Flex) | `6anuta9n` | + +To reproduce only the four Demon Attack checkpoint evaluations: + +```bash +scripts/experiments/memory/eval_vla.sh demon_attack all +``` + +The script evaluates 100 episodes at latency 6 raw frames and an episode limit +of 14400 raw frames, equivalent to 3600 decision steps because +`env_fps / obs_fps = 4`. Run names end in +`__latency_bench__max_raw_steps_14400`. + +Refresh the committed data and TeX-rendered table from the pinned sources with: + +```bash +paper/tables/table7_memory_comparison/refresh.sh +``` + +A source is accepted only when one unique checkpoint-4000 history record +contains exactly 100 episodes and its W&B provenance matches the expected run +name, input format, instantiated LatencyBench runner, attention implementation, +and KV-memory packing mode. + +## Limitations + +- One training seed is available per method and environment. +- Episode-level raw returns cannot be reconstructed from W&B aggregates. +- Any remaining Ghost-trail eval_core results are not direct references: their + 3600-step limit counts decision steps, and latency 6 also counts decision + steps rather than raw frames. +- The table is not included in `legacy/neurips_2026.tex`. + +## Fixed experiment archive + +Ten independent Ghost-trail sources are retained separately in +`latency-sensitive-bench/memory-models@3883a9a77b2768f921c413d7e120a35229c13d77`. +The two standalone Ghost-15 datasets are in +`latency-sensitive-bench/memory-data@a27ffac271d5b1d4c32fbd7e0d65b12e8c5579d9`, +under `training/flappy_fixed_latency_3_200ep_7k2steps_ghost15/` and +`training/demon_attack_fixed_latency_6_200ep_7k2steps_ghost15/`. +Model configs also reference their original Ghost-7 training paths. +Equal normalization statistics do not make the Ghost-7 no-exp and exp3 +weights identical. Both versions are retained. One repository contains only +metadata and no runnable checkpoint. The archival index distinguishes the +experiment type from an exact table-checkpoint match; the table's accepted +source manifests and numerical values remain unchanged. diff --git a/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/data.csv b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/data.csv new file mode 100644 index 0000000000000000000000000000000000000000..f1f23ee6eeea0118643d6815860c0baf67926092 --- /dev/null +++ b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/data.csv @@ -0,0 +1,15 @@ +task_key,method_key,checkpoint_step,source_history_step,latency_raw_frames,mean_reward,std_reward,mean_length,std_length,episode_count,reward_ci95_lo,reward_ci95_hi,length_ci95_lo,length_ci95_hi,status,source_run_id +flappy,single_baseline,4000,4000,3,368.88000434055925,129.9747321399612,2991.19,1046.6452951692852,100,342.9602733809536,394.7997353001649,2782.466627277741,3199.9133727222593,complete,58z6j7a1 +flappy,plain_multi,4000,4000,3,352.05800414279105,141.33372174823657,2855.02,1138.840058831792,100,323.8730486293666,380.2429596562155,2627.9110270101187,3082.1289729898813,complete,vxfcccte +flappy,stitch,4000,4000,3,343.13200403884053,148.14556452769997,2783.31,1193.5298462543783,100,313.5886219352948,372.6753861423863,2545.2947181230575,3021.3252818769424,complete,mmgsys8m +flappy,kv_memory_flex,4000,4000,3,382.2460044965148,126.10104779734837,3098.57,1015.2618899082147,100,357.09876873139694,407.3932402616326,2896.1051469728404,3301.03485302716,complete,bpr9q0nb +flappy,ghost_trail,4000,4000,3,426.8950050175935,68.51719627053934,3457.58,551.8799539754999,100,413.23121618572674,440.5587938494603,3347.5233782741643,3567.6366217258355,complete,hf:latency-sensitive-bench/openvla_bridge_flappy_fixed_latency_3_200ep_7k2steps_ghost7_exp3/eval/post_train/step_4000.json +demon_attack,single_baseline,4000,4000,6,5671.75,633.3815496997051,14368.08,181.5048032422283,100,5545.44022353271,5798.05977646729,14331.884074911663,14404.275925088337,complete,nsb0fpng +demon_attack,plain_multi,4000,4000,6,6474.55,590.6941234683142,14342.57,163.35894557691051,100,6356.753005864003,6592.346994135997,14309.992745563815,14375.147254436184,complete,dariw0bn +demon_attack,stitch,4000,4000,6,5783.2,1065.7545496032376,14400.0,0.0,100,5570.6658347828325,5995.734165217167,14400.0,14400.0,complete,aflyy974 +demon_attack,kv_memory_flex,4000,4000,6,6483.5,550.8922308401163,14370.24,101.39468625130216,100,6373.640351312772,6593.359648687228,14350.019739145471,14390.460260854528,complete,6anuta9n +demon_attack,ghost_trail,4000,4000,6,5688.7,1568.0109406506065,13459.91,2335.200291602414,100,5376.005208833846,6001.3947911661535,12994.221305754807,13925.598694245193,complete,hf:latency-sensitive-bench/openvla_bridge_demon_attack_fixed_latency_6_200ep_7k2steps_ghost15_2_exp3/eval/post_train/step_4000.json +deadly_corridor,single_baseline,4000,4000,6,232.00475982666015,257.1936181111822,64.61,24.343333789766756,100,180.71487235229466,283.29464730102563,59.755420559042356,69.46457944095764,complete,sxgh13gg +deadly_corridor,plain_multi,4000,4000,6,227.0985302734375,170.04333449353234,66.55,23.632763274742125,100,193.18826626304144,261.00879428383354,61.837123459860294,71.2628765401397,complete,g8yprapd +deadly_corridor,stitch,4000,4000,6,271.0697445678711,284.4073394474786,79.47,32.63907320988143,100,214.35286121643844,327.7866279193038,72.96107336139764,85.97892663860236,complete,6lxzrons +deadly_corridor,kv_memory_flex,4000,4000,6,229.2106620788574,166.31335369199877,66.96,22.641077712865172,100,196.04423571496744,262.3770884427474,62.44488669073733,71.47511330926267,complete,wb7qhv7z diff --git a/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/fetch_wandb.py b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/fetch_wandb.py new file mode 100644 index 0000000000000000000000000000000000000000..9daa9241fcdb785876604377aa9e24be088abbf4 --- /dev/null +++ b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/fetch_wandb.py @@ -0,0 +1,310 @@ +from __future__ import annotations + +import argparse +import csv +import math +from pathlib import Path +from typing import Any, Iterable + +from scipy.stats import t as student_t +import wandb + + +HERE = Path(__file__).resolve().parent +DEFAULT_SOURCES = HERE / "wandb_sources.csv" +ENTITY = "zihanwang-ai-northwestern-university" +PROJECT = "starVLA_rl_games" + +SOURCE_FIELDS = ( + "source_mode", + "task_key", + "method_key", + "run_id", + "expected_run_name", + "expected_group", + "checkpoint_step", + "source_step", + "latency_raw_frames", + "expected_episodes", +) + +DATA_FIELDS = ( + "task_key", + "method_key", + "checkpoint_step", + "source_history_step", + "latency_raw_frames", + "mean_reward", + "std_reward", + "mean_length", + "std_length", + "episode_count", + "reward_ci95_lo", + "reward_ci95_hi", + "length_ci95_lo", + "length_ci95_hi", + "status", + "source_run_id", +) + +TASK_ORDER = {"flappy": 0, "demon_attack": 1, "deadly_corridor": 2} +METHOD_ORDER = { + "single_baseline": 0, + "plain_multi": 1, + "stitch": 2, + "kv_memory_flex": 3, +} +METHOD_INPUT_CONFIG = { + "single_baseline": ("single", 1, False, "flash_attention_2", False), + "plain_multi": ("multiframe", 4, False, "flash_attention_2", False), + "stitch": ("stitch", 4, False, "flash_attention_2", False), + "kv_memory_flex": ("multiframe", 8, True, "flex_attention", True), +} + + +def read_sources(path: Path) -> list[dict[str, str]]: + with path.open(newline="", encoding="utf-8") as file: + reader = csv.DictReader(file) + if tuple(reader.fieldnames or ()) != SOURCE_FIELDS: + raise ValueError(f"Unexpected source manifest columns: {reader.fieldnames}") + return list(reader) + + +def validate_run(run: Any, source: dict[str, str]) -> None: + if run.name != source["expected_run_name"]: + raise ValueError( + f"Run {source['run_id']} has name {run.name!r}, " + f"expected {source['expected_run_name']!r}" + ) + if run.group != source["expected_group"]: + raise ValueError( + f"Run {source['run_id']} has group {run.group!r}, " + f"expected {source['expected_group']!r}" + ) + ( + expected_image_mode, + expected_num_frames, + expected_kv_memory, + expected_attn_implementation, + expected_packed_train, + ) = ( + METHOD_INPUT_CONFIG[source["method_key"]] + ) + if run.config["eval_backend"] != "latency_bench": + raise ValueError( + f"Run {source['run_id']} used eval backend " + f"{run.config['eval_backend']!r}" + ) + expected_runner = ( + "latency_bench.integrations.starvla_rl_games_eval_runner." + "LatencyBenchRlGamesEvalRunner" + ) + if run.config["eval_runner"] != expected_runner: + raise ValueError( + f"Run {source['run_id']} used eval runner " + f"{run.config['eval_runner']!r}, expected {expected_runner!r}" + ) + if run.config["checkpoint_step"] != int(source["checkpoint_step"]): + raise ValueError( + f"Run {source['run_id']} evaluated checkpoint " + f"{run.config['checkpoint_step']!r}" + ) + if run.config["image_mode"] != expected_image_mode: + raise ValueError( + f"Run {source['run_id']} used image mode " + f"{run.config['image_mode']!r}, expected {expected_image_mode!r}" + ) + if run.config["num_obs_frames"] != expected_num_frames: + raise ValueError( + f"Run {source['run_id']} used {run.config['num_obs_frames']!r} " + f"observation frames, expected {expected_num_frames}" + ) + if run.config["kv_memory_enabled"] != expected_kv_memory: + raise ValueError( + f"Run {source['run_id']} has kv_memory_enabled=" + f"{run.config['kv_memory_enabled']!r}, expected {expected_kv_memory}" + ) + if run.config["attn_implementation"] != expected_attn_implementation: + raise ValueError( + f"Run {source['run_id']} used attention implementation " + f"{run.config['attn_implementation']!r}, " + f"expected {expected_attn_implementation!r}" + ) + if run.config["kv_memory_packed_train"] != expected_packed_train: + raise ValueError( + f"Run {source['run_id']} has kv_memory_packed_train=" + f"{run.config['kv_memory_packed_train']!r}, expected {expected_packed_train}" + ) + + +def distinct_rows( + rows: Iterable[dict[str, Any]], + keys: tuple[str, ...], +) -> list[dict[str, Any]]: + distinct: dict[tuple[Any, ...], dict[str, Any]] = {} + for row in rows: + identity = tuple(row[key] for key in keys) + distinct[identity] = row + return list(distinct.values()) + + +def finite_float(value: Any, label: str) -> float: + number = float(value) + if not math.isfinite(number): + raise ValueError(f"{label} is not finite: {value!r}") + return number + + +def ci95(mean: float, std: float, count: int) -> tuple[float, float]: + sample_std = std * math.sqrt(count / (count - 1)) + halfwidth = float(student_t.ppf(0.975, count - 1)) * sample_std / math.sqrt(count) + return mean - halfwidth, mean + halfwidth + + +def metric_keys(source: dict[str, str]) -> tuple[str, ...]: + slug = f"{source['task_key']}__latency_{source['latency_raw_frames']}" + prefix = f"rl_games_eval/post_train/{slug}" + return ( + f"{prefix}/mean_reward", + f"{prefix}/std_reward", + f"{prefix}/mean_length", + f"{prefix}/std_length", + f"{prefix}/num_episodes", + ) + + +def scan_records(run: Any, source: dict[str, str]) -> list[dict[str, Any]]: + metrics = metric_keys(source) + keys = ("_step", *metrics) + return distinct_rows( + run.scan_history(keys=list(keys), page_size=1000), + keys, + ) + + +def invalid_row(source: dict[str, str]) -> dict[str, object]: + return { + "task_key": source["task_key"], + "method_key": source["method_key"], + "checkpoint_step": int(source["checkpoint_step"]), + "source_history_step": "", + "latency_raw_frames": int(source["latency_raw_frames"]), + "mean_reward": "", + "std_reward": "", + "mean_length": "", + "std_length": "", + "episode_count": "", + "reward_ci95_lo": "", + "reward_ci95_hi": "", + "length_ci95_lo": "", + "length_ci95_hi": "", + "status": "invalid", + "source_run_id": source["run_id"], + } + + +def complete_row( + source: dict[str, str], + history_row: dict[str, Any], +) -> dict[str, object]: + mean_reward_key, std_reward_key, mean_length_key, std_length_key, count_key = ( + metric_keys(source) + ) + count = int(history_row[count_key]) + expected_count = int(source["expected_episodes"]) + if count != expected_count: + raise ValueError( + f"Run {source['run_id']} step {history_row['_step']} has {count} episodes, " + f"expected {expected_count}" + ) + + mean_reward = finite_float(history_row[mean_reward_key], mean_reward_key) + std_reward = finite_float(history_row[std_reward_key], std_reward_key) + mean_length = finite_float(history_row[mean_length_key], mean_length_key) + std_length = finite_float(history_row[std_length_key], std_length_key) + reward_lo, reward_hi = ci95(mean_reward, std_reward, count) + length_lo, length_hi = ci95(mean_length, std_length, count) + return { + "task_key": source["task_key"], + "method_key": source["method_key"], + "checkpoint_step": int(source["checkpoint_step"]), + "source_history_step": int(history_row["_step"]), + "latency_raw_frames": int(source["latency_raw_frames"]), + "mean_reward": mean_reward, + "std_reward": std_reward, + "mean_length": mean_length, + "std_length": std_length, + "episode_count": count, + "reward_ci95_lo": reward_lo, + "reward_ci95_hi": reward_hi, + "length_ci95_lo": length_lo, + "length_ci95_hi": length_hi, + "status": "complete", + "source_run_id": source["run_id"], + } + + +def collect_source(run: Any, source: dict[str, str]) -> dict[str, object]: + records = scan_records(run, source) + if source["source_mode"] != "pinned_step": + raise ValueError(f"Unsupported source mode: {source['source_mode']}") + source_step = int(source["source_step"]) + candidates = [ + row for row in records if int(row["_step"]) == source_step + ] + + if len(candidates) != 1: + raise ValueError( + f"Run {source['run_id']} produced {len(candidates)} distinct records " + f"for source mode {source['source_mode']}" + ) + return complete_row(source, candidates[0]) + + +def collect_rows(sources: list[dict[str, str]]) -> list[dict[str, object]]: + api = wandb.Api(timeout=180) + rows: list[dict[str, object]] = [] + for source in sources: + if source["source_mode"] == "invalid": + rows.append(invalid_row(source)) + continue + run = api.run(f"{ENTITY}/{PROJECT}/{source['run_id']}") + validate_run(run, source) + rows.append(collect_source(run, source)) + return sorted( + rows, + key=lambda row: ( + TASK_ORDER[str(row["task_key"])], + METHOD_ORDER[str(row["method_key"])], + ), + ) + + +def write_rows(rows: list[dict[str, object]], output: Path) -> None: + with output.open("w", newline="", encoding="utf-8") as file: + writer = csv.DictWriter(file, fieldnames=DATA_FIELDS, lineterminator="\n") + writer.writeheader() + writer.writerows(rows) + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser() + parser.add_argument("--sources", type=Path, default=DEFAULT_SOURCES) + parser.add_argument("--output", type=Path, required=True) + return parser.parse_args() + + +def main() -> None: + args = parse_args() + rows = collect_rows(read_sources(args.sources)) + write_rows(rows, args.output) + pending = [row for row in rows if row["status"] == "pending"] + invalid = [row for row in rows if row["status"] == "invalid"] + print( + f"Wrote {args.output} ({len(rows)} rows, {len(pending)} pending, " + f"{len(invalid)} invalid)" + ) + + +if __name__ == "__main__": + main() diff --git a/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/invalidated_eval_core_data.csv b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/invalidated_eval_core_data.csv new file mode 100644 index 0000000000000000000000000000000000000000..3f42023aafff8cc5c15e58fc1d0f79245dab1817 --- /dev/null +++ b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/invalidated_eval_core_data.csv @@ -0,0 +1,13 @@ +task_key,method_key,checkpoint_step,source_history_step,latency_raw_frames,mean_reward,std_reward,mean_length,std_length,episode_count,reward_ci95_lo,reward_ci95_hi,length_ci95_lo,length_ci95_hi,status,source_run_id +flappy,single_baseline,4000,4000,3,362.31400000001696,132.32875803846665,2938.22,1065.3713209956422,100,336.05710351281533,388.5708964872186,2726.8272165229246,3149.612783477075,invalid,0gbu5fpb +flappy,plain_multi,4000,4000,3,42.050999999999924,34.24127770688415,358.52,276.32822801878206,100,35.25678763326834,48.84521236673151,303.6904845784776,413.34951542152237,invalid,qun51dr2 +flappy,stitch,4000,4000,3,2.000000000000001,4.440892098500626e-16,31.0,0.0,100,2.000000000000001,2.000000000000001,31.0,31.0,invalid,wi84hllf +flappy,kv_memory_flex,4000,,3,,,,,,,,,,invalid,e1ewjv6r +demon_attack,single_baseline,4000,4000,6,96.1,51.16434305255956,481.97,183.69569701002797,100,85.94788432023057,106.25211567976942,445.52078840735,518.4192115926501,invalid,muuriphx +demon_attack,plain_multi,4000,4000,6,84.6,38.48168395483753,453.26,131.85466392964642,100,76.96439903742116,92.23560096257883,427.0971740695315,479.4228259304685,invalid,flf0ul2i +demon_attack,stitch,4000,4000,6,122.65,65.11702926270516,609.98,304.93687805839426,100,109.72936867050535,135.57063132949466,549.4739077416398,670.4860922583603,invalid,fdtboqvj +demon_attack,kv_memory_flex,4000,4000,6,97.5,30.17863482664516,503.19,156.42568171499207,100,91.51190412035804,103.48809587964196,472.15175106898107,534.2282489310189,invalid,97kp6bb4 +deadly_corridor,single_baseline,4000,4000,6,154.07666595458986,160.47856349958442,18.05,5.479735395071554,100,122.23423734962606,185.91909455955366,16.96270161393169,19.137298386068313,invalid,b3532s5g +deadly_corridor,plain_multi,4000,4000,6,7.0391246032714845,102.5435296791443,21.15,5.433921236087251,100,-13.307736382417698,27.38598558896067,20.071792137019266,22.22820786298073,invalid,kp11868h +deadly_corridor,stitch,4000,4000,6,153.74478500366212,160.16978825531336,18.04,5.44778854215176,100,121.96362410608721,185.52594590123704,16.95904056264277,19.12095943735723,invalid,6kbng7qo +deadly_corridor,kv_memory_flex,4000,4000,6,109.39283874511719,136.5404309565039,19.06,4.896570228231186,100,82.3002549780976,136.48542251213678,18.088414234889093,20.031585765110904,invalid,qc9vrlwo diff --git a/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/preview.tex b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/preview.tex new file mode 100644 index 0000000000000000000000000000000000000000..4ebfa9a76b22f11c335b4f312234d8e10cd93e4d --- /dev/null +++ b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/preview.tex @@ -0,0 +1,17 @@ +\documentclass[varwidth=true,border=3pt]{standalone} +\usepackage{amsmath} +\usepackage{booktabs} +\usepackage{float} +\usepackage{iftex} +\ifPDFTeX +\else + \usepackage{fontspec} + \usepackage{unicode-math} + \IfFontExistsTF{Tinos}{\setmainfont{Tinos}}{} + \IfFontExistsTF{TeX Gyre Termes Math}{\setmathfont{TeX Gyre Termes Math}}{} +\fi + +\begin{document} +\setcounter{table}{6} +\input{table.tex} +\end{document} diff --git a/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/render_table.py b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/render_table.py new file mode 100644 index 0000000000000000000000000000000000000000..3d17cef90810e74b51bfeb522806792639538717 --- /dev/null +++ b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/render_table.py @@ -0,0 +1,265 @@ +from __future__ import annotations + +import argparse +import csv +import math +from pathlib import Path +from typing import Sequence + +try: + from scipy.stats import t as student_t +except ImportError: # pragma: no cover - exercised only in minimal local envs. + student_t = None + + +HERE = Path(__file__).resolve().parent +DEFAULT_COMPARISON_DATA = HERE / "data.csv" +DEFAULT_WANOFT_DATA = HERE.parents[1] / "exps/memory/compare_table/wanoft/data.csv" + +METHODS = ( + ("single_baseline", "Single frame"), + ("plain_multi", "Four-frame prompt"), + ("stitch", r"4-frame grid ($2{\times}2$)"), + ("kv_memory_flex", "KV memory (Flex)"), + ("ghost_trail", "Ghost trail"), + ("wanoft", "WanOFT"), +) +TASKS = ( + ("flappy", "Flappy Bird", 3), + ("demon_attack", "Demon Attack", 6), + ("deadly_corridor", "Deadly Corridor", 6), +) +COMPARISON_DATA_FIELDS = ( + "task_key", + "method_key", + "checkpoint_step", + "source_history_step", + "latency_raw_frames", + "mean_reward", + "std_reward", + "mean_length", + "std_length", + "episode_count", + "reward_ci95_lo", + "reward_ci95_hi", + "length_ci95_lo", + "length_ci95_hi", + "status", + "source_run_id", +) +WANOFT_DATA_FIELDS = ( + "method_key", + "method_label", + "env_key", + "env_label", + "env_id", + "context_window", + "train_latency_raw_frames", + "eval_latency_raw_frames", + "configured_latency_ms", + "env_fps", + "obs_fps", + "num_episodes", + "episode_seed_first", + "episode_seed_last", + "mean_return", + "std_return", + "ci95_halfwidth", + "ci95_lo", + "ci95_hi", + "queue_result_records", + "evaluation_timestamp_utc", + "source_revision", + "source_episode_metrics", + "source_summary", + "source_queue_results", +) +COMPARISON_DENSE_METHODS = ( + "single_baseline", + "plain_multi", + "stitch", + "kv_memory_flex", +) +COMPARISON_SPARSE_CELLS = { + ("flappy", "ghost_trail"), + ("demon_attack", "ghost_trail"), +} +T_CRITICAL_975 = { + 19: 2.093024054408263, + 99: 1.9842169515086827, +} + + +def read_csv(path: Path, fields: Sequence[str]) -> list[dict[str, str]]: + with path.open(newline="", encoding="utf-8") as file: + reader = csv.DictReader(file) + if tuple(reader.fieldnames or ()) != tuple(fields): + raise ValueError(f"Unexpected columns in {path}: {reader.fieldnames}") + return list(reader) + + +def validate_comparison_rows(rows: Sequence[dict[str, str]]) -> None: + expected_cells = { + (task_key, method_key) + for task_key, _, _ in TASKS + for method_key in COMPARISON_DENSE_METHODS + } | COMPARISON_SPARSE_CELLS + cells = {(row["task_key"], row["method_key"]) for row in rows} + if cells != expected_cells or len(rows) != len(expected_cells): + raise ValueError("Comparison data do not contain the expected cells") + + expected_latency = {task_key: latency for task_key, _, latency in TASKS} + for row in rows: + if row["status"] != "complete": + raise ValueError(f"Comparison row is not complete: {row}") + if int(row["checkpoint_step"]) != 4000: + raise ValueError("A comparison evaluation is not checkpoint 4000") + if int(row["episode_count"]) != 100: + raise ValueError("A comparison evaluation does not contain 100 episodes") + if int(row["latency_raw_frames"]) != expected_latency[row["task_key"]]: + raise ValueError("A comparison evaluation has the wrong raw-frame latency") + + +def validate_wanoft_rows(rows: Sequence[dict[str, str]]) -> None: + expected_tasks = tuple(task_key for task_key, _, _ in TASKS) + if tuple(row["env_key"] for row in rows) != expected_tasks: + raise ValueError("WanOFT data do not contain the three ordered environments") + if {row["method_key"] for row in rows} != {"wanoft"}: + raise ValueError("WanOFT data contain an unexpected method") + expected_latency = {task_key: latency for task_key, _, latency in TASKS} + for row in rows: + if int(row["eval_latency_raw_frames"]) != expected_latency[row["env_key"]]: + raise ValueError("A WanOFT row has the wrong raw-frame latency") + if int(row["num_episodes"]) != 20: + raise ValueError("A WanOFT row does not contain 20 episodes") + if not row["source_revision"]: + raise ValueError("A WanOFT row is missing its immutable source revision") + + +def t_critical_975(degrees_of_freedom: int) -> float: + if student_t is not None: + return float(student_t.ppf(0.975, degrees_of_freedom)) + if degrees_of_freedom not in T_CRITICAL_975: + raise RuntimeError("SciPy is required for this episode count") + return T_CRITICAL_975[degrees_of_freedom] + + +def ci95_from_population_std(mean: float, std: float, count: int) -> tuple[float, float]: + sample_std = std * math.sqrt(count / (count - 1)) + halfwidth = t_critical_975(count - 1) * sample_std / math.sqrt(count) + return mean - halfwidth, mean + halfwidth + + +def merged_values( + comparison_rows: Sequence[dict[str, str]], + wanoft_rows: Sequence[dict[str, str]], +) -> dict[tuple[str, str], tuple[float, float, float]]: + values: dict[tuple[str, str], tuple[float, float, float]] = {} + for row in comparison_rows: + values[(row["task_key"], row["method_key"])] = ( + float(row["mean_reward"]), + float(row["reward_ci95_lo"]), + float(row["reward_ci95_hi"]), + ) + for row in wanoft_rows: + mean = float(row["mean_return"]) + lo, hi = ci95_from_population_std( + mean, + float(row["std_return"]), + int(row["num_episodes"]), + ) + values[(row["env_key"], "wanoft")] = (mean, lo, hi) + expected_cells = { + (task_key, method_key) + for task_key, _, _ in TASKS + for method_key, _ in METHODS + if method_key != "ghost_trail" or (task_key, method_key) in COMPARISON_SPARSE_CELLS + } + if set(values) != expected_cells: + raise ValueError("Merged data do not contain the expected numeric cells") + return values + + +def format_cell(mean: float, lo: float, hi: float) -> str: + return f"{mean:.1f} $\\pm$ {(hi - lo) / 2:.1f}" + + +def write_tex_table( + values: dict[tuple[str, str], tuple[float, float, float]], + output_dir: Path, +) -> None: + best_method = { + task_key: max( + (values[(task_key, method_key)][0], method_key) + for method_key, _ in METHODS + if (task_key, method_key) in values + )[1] + for task_key, _, _ in TASKS + } + lines = [ + r"\begin{table}[H]", + r"\centering", + r"\footnotesize", + r"\setlength{\tabcolsep}{3pt}", + r"\renewcommand{\arraystretch}{1.12}", + ( + r"\caption{\textbf{No visual-history interface gives the highest mean return on all three tasks under fixed latency.} " + r"Cells report mean episode return $\pm$ Student-$t$ 95\% " + r"confidence halfwidth; bold marks the largest mean in each column. " + r"Training and evaluation use the same raw-frame delay. " + r"OpenVLA variants use checkpoint 4000 and 100 fixed-seed episodes; " + r"WanOFT is a different-backbone reference with task-specific checkpoints " + r"and 20 episodes. Intervals describe episode sampling, with one training " + r"run per cell. Ghost trail was not evaluated on Deadly Corridor (-).}" + ), + r"\label{tab:vla-memory-comparison}", + r"\begin{tabular}{@{}lccc@{}}", + r"\toprule", + ( + r"Method & Flappy Bird ($\Delta k{=}3$) " + r"& Demon Attack ($\Delta k{=}6$) " + r"& Deadly Corridor ($\Delta k{=}6$) \\" + ), + r"\midrule", + ] + for method_key, method_label in METHODS: + cells = [] + for task_key, _, _ in TASKS: + value = values.get((task_key, method_key)) + if value is None: + cells.append("-") + continue + mean, lo, hi = value + cell = format_cell(mean, lo, hi) + if best_method[task_key] == method_key: + cell = rf"\textbf{{{cell}}}" + cells.append(cell) + lines.append(method_label + " & " + " & ".join(cells) + " \\\\") + lines.extend([r"\bottomrule", r"\end{tabular}", r"\end{table}", ""]) + (output_dir / "table.tex").write_text( + "\n".join(lines), + encoding="utf-8", + ) + + +def parse_args() -> argparse.Namespace: + parser = argparse.ArgumentParser() + parser.add_argument("--comparison-data", type=Path, default=DEFAULT_COMPARISON_DATA) + parser.add_argument("--wanoft-data", type=Path, default=DEFAULT_WANOFT_DATA) + parser.add_argument("--output-dir", type=Path, default=HERE) + return parser.parse_args() + + +def main() -> None: + args = parse_args() + comparison_rows = read_csv(args.comparison_data, COMPARISON_DATA_FIELDS) + wanoft_rows = read_csv(args.wanoft_data, WANOFT_DATA_FIELDS) + validate_comparison_rows(comparison_rows) + validate_wanoft_rows(wanoft_rows) + args.output_dir.mkdir(parents=True, exist_ok=True) + write_tex_table(merged_values(comparison_rows, wanoft_rows), args.output_dir) + print(f"Wrote merged comparison table source to {args.output_dir}") + + +if __name__ == "__main__": + main() diff --git a/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/table.tex b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/table.tex new file mode 100644 index 0000000000000000000000000000000000000000..aa42a116bf694c8d09e2e23125b9902b05cee482 --- /dev/null +++ b/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/table.tex @@ -0,0 +1,29 @@ +\begin{table}[H] +\centering +\footnotesize +\setlength{\tabcolsep}{3pt} +\renewcommand{\arraystretch}{1.12} +\caption{Raw returns for the visual-history comparison in +Figure~\ref{fig:vla_memory_interfaces}. No interface has the highest mean on +all three tasks. Training and evaluation use the same fixed raw-frame delay, +shown in each column header. Cells report mean episode return $\pm$ the +Student-$t$ 95\% confidence-interval half-width from at least 20 evaluation +episodes; these intervals measure episode variation for one training run per +cell. Bold marks the largest mean in each task. The OpenVLA methods use +checkpoint 4000; WanOFT uses a separate backbone and task-specific +checkpoints. A hyphen means that Ghost trail was not evaluated on Deadly +Corridor.} +\label{tab:vla-memory-comparison} +\begin{tabular}{@{}lccc@{}} +\toprule +Method & Flappy Bird ($\Delta k{=}3$) & Demon Attack ($\Delta k{=}6$) & Deadly Corridor ($\Delta k{=}6$) \\ +\midrule +Single frame & 368.9 $\pm$ 25.9 & 5671.8 $\pm$ 126.3 & 232.0 $\pm$ 51.3 \\ +Four separate frames & 352.1 $\pm$ 28.2 & 6474.6 $\pm$ 117.8 & 227.1 $\pm$ 33.9 \\ +4-frame grid ($2{\times}2$) & 343.1 $\pm$ 29.5 & 5783.2 $\pm$ 212.5 & \textbf{271.1 $\pm$ 56.7} \\ +KV memory (packed replay) & 382.2 $\pm$ 25.1 & \textbf{6483.5 $\pm$ 109.9} & 229.2 $\pm$ 33.2 \\ +Ghost trail & \textbf{426.9 $\pm$ 13.7} & 5688.7 $\pm$ 312.7 & - \\ +WanOFT & 425.3 $\pm$ 33.1 & 4608.8 $\pm$ 714.8 & 238.9 $\pm$ 74.2 \\ +\bottomrule +\end{tabular} +\end{table} diff --git a/experiments/visual-history/provenance/memory-data/paper/tables/table7_memory_comparison/wandb_sources.csv 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+pinned_step,flappy,kv_memory_flex,bpr9q0nb,flappy_fix_latency_3_200ep_7k2steps_kv_memory_flex__post_train__step_4000__latency_bench,rl-games-eval,4000,4000,3,100 +pinned_step,demon_attack,single_baseline,nsb0fpng,demon_attack_fix_latency_6_200ep_7k2steps_single_baseline__post_train__step_4000__latency_bench__max_raw_steps_14400,rl-games-eval,4000,4000,6,100 +pinned_step,demon_attack,plain_multi,dariw0bn,demon_attack_fix_latency_6_200ep_7k2steps_plain_multi__post_train__step_4000__latency_bench__max_raw_steps_14400,rl-games-eval,4000,4000,6,100 +pinned_step,demon_attack,stitch,aflyy974,demon_attack_fix_latency_6_200ep_7k2steps_stitch__post_train__step_4000__latency_bench__max_raw_steps_14400,rl-games-eval,4000,4000,6,100 +pinned_step,demon_attack,kv_memory_flex,6anuta9n,demon_attack_fix_latency_6_200ep_7k2steps_kv_memory_flex__post_train__step_4000__latency_bench__max_raw_steps_14400,rl-games-eval,4000,4000,6,100 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"id": "latency-sensitive-bench/demon_attack_fixed_latency_6_200ep_7k2steps_ghost15", + "author": "latency-sensitive-bench", + "sha": "862b6cad9b2c87dc129d5cf45a9b23b18450c4ef", + "lastModified": "2026-07-28T05:28:11.000Z", + "private": false, + "gated": false, + "disabled": false, + "tags": [ + "size_categories:100K/`；训练数据位于 `training/<原仓库>/`。 + 正式 Flappy 为 30 FPS、L0–L4 raw frames。Demon 训练配置的 L0/2/4/6/8 decision intervals + 对应 0/8/16/24/32 raw frames，60 FPS、frameskip 4。历史数据保留自己的 episode 数与协议。 +- `memory-models/data`：10 个 Ghost 模型源和 2 个 Ghost-15 独立数据源。 + Ghost-7 no-exp 与 exp3 的权重不同，分别保留。其余 Ghost 训练数据按原配置引用仍保留的 `memory-rollouts` 固定 revision。 +- `vla-finetuning-scope-models/data`：旧 LoRA/full 的模型、adapter/action head、`flappy_fixed_l2_fs4` 与评测 JSON。 + 与正式 7 个 scope run 分开。正式 scope 的共享 Flappy L2 数据改为 `latency-transfer-data` 固定 revision。 +- `latency-information-models/data`：三个 Inverted Pendulum run 与两套原始数据。 + 两个 `raw` prompt run、一个 `latency_neutral` run分别保留。两个源中的 L2/L4 文件身份相同；L0 文件不同。 + +`experiment_repository_index.json` 记录原仓库和 revision、训练配置、数据引用、权重身份、teacher 元数据、schema/行数和论文位置。 +`training_bindings.json` 与 `wandb_provenance.json` 保存已记录的日期、W&B run、代码 commit。 +训练代码快照存于 `latency-transfer-data/code/`。没有 W&B 或精确数据来源的资产保留原始缺失状态。 +原配置与原引用文档作为 provenance 保留；当前消费者使用新归档的固定 revision。 + +## 不能据此推断的内容 + +- Flappy cumulative curriculum 配置声明 L0–L5、每个 latency 40 episodes，但存储统计是 200 trajectories、341369 transitions。 + exclusive 声明 L0–L4，存储统计同样是 200 trajectories、341369 transitions。 + 原本的本地 curriculum 数据未发布。不能把配置中的 240 episodes 当作已验证的数据组成，也不能拿固定延迟数据补造配对。 +- Inverted Pendulum 的原论文表没有 checkpoint 标识。归档三个候选模型不证明它们就是表中的评测权重。 + 论文 120 条原始 episode returns 保持不变。 +- 旧 LoRA/full 的 HF 评测各有 50 episodes，Full/LoRA 均值为 18.5180/3.8620。 + 论文旧图 CSV 各有 100 episodes，均值为 22.3080/3.4820。两套记录分别保留。 + 论文旧图的逐 episode 原文件与精确权重绑定未恢复，不能声称 HF 50 局就是图中的 100 局。 +- Ghost 模型的实验类型已确认，但归档全部版本不等于确定每个版本的表格用途。 + 表格仍以已有 accepted source manifest 为准。 +- `openvla_demon_attack_fix_latency_6_small` 原仓库没有可用 checkpoint； + `openvla_bridge_demon_attack_fixed_latency_6_200ep_7k2steps_ghost15_2` 仅有元数据。 + 原始状态保留，不补造配置或权重。 +- 一些早期模型只记录本地训练目录。能够匹配原目录名的配对已记录证据，未恢复的原始训练数据明确留空。 + 所有不同权重仍分别保留。 + +## 验证结果 + +- 735 个迁移源文件的对象身份匹配。训练状态中的推理权重规范为 `steps__model.safetensors`；权重字节未修改。 +- 55 个 checkpoint/adapter 文件通过原生加载，归一化统计一致。LoRA 的 action head 同时加载。 + 两份旧 safetensors 使用现有 tied-LM-head 兼容加载逻辑，具体 loader revision 已记录。 + 批次 0 Wan L1 与之前通过原生加载的归档权重身份相同。 +- 135 个不同 Parquet 对象、160 个路径引用通过 schema、总行数和真实样本读取检查。 + 含图像的样本通过解码。检查没有声称逐行解码全部数据。 +- Flappy 700 条和 Demon 500 条论文记录的 60 个汇总单元均值与 source manifest 一致；相关 CSV 数值未改变。 +- 迁移相关测试 8 项、数据转换测试 22 项通过。另有一次较宽测试：98 项通过、4 项现有失败、1 项未运行。 + 四项失败涉及三个 pi0 initializer 断言和一个 runtime-cache 断言，未把它们算作通过。 +- 58 个 shell、3 个 YAML、7 个 Python 消费者文件检查通过。修复四个既有消费者脚本缺失的关闭引号。 +- arXiv 与 ICLR 稿编译通过，`git diff --check` 通过。 + 9 份来源文档已提交并同步 Overleaf：`7d13a2f74fc3933f12916e08f103044af782b624`。既有未提交的五份论文编辑保留。 +- 删除后，从四个模型归档重新下载并原生加载各一份 checkpoint/adapter，从四个数据归档读取各一个 Parquet。 + 全部通过。80 个删除源在最终组织 API 列表中均不存在。 + +## 保留并继续调查的资产 + +已重新固定 **51 个**待调查资产的 revision，详见 `pending_asset_inventory.json`。 + +| 组 | 独立仓库数 | 当前结论 | +|---|---:|---| +| 其余 image-history/fs 数据 | 12 datasets | teacher frame_stack 与导出 image_stack 不是同一参数；不归入论文 APPO context-window 扫描 | +| Deadly jitter | 5 datasets | teacher 与随机延迟参数保留；学生消费者与论文绑定尚未确认 | +| mixed 数据 | 2 datasets | 存在旧跨任务消费者；用途不与固定延迟或 prompt 消融混写 | +| 零延迟候选 | 19 models | 正式基线、重跑、其他任务和未完成产物分别核对 | +| RTX3090 profile 历史组 | 11 models | 保留差结果/失效/未正式发布状态；不并入 formal benchmark | +| 跨任务模型 | 2 models | 保留原跨任务用途，未按 latency transfer 删除 | + +独立 WanOFT `demon_attack_200ep` 模型保留。此次删除同名 **dataset** 不代表删除同名 **model**。 +前一批 factor-sweeps 中 9 个 Deadly Corridor run 的候选权重仍分别保留，本次没有消除其评测权重歧义。 + +## 主要证据 + +- `deletion_receipts.json`：80 个整仓删除回执。 +- `organization_before.json` / `organization_final.json`：数量与存储复核。 +- `deletion_gate.json`：固定源 revision、完整迁移与数值核对。 +- `legacy_lora_evaluation_difference.json`：旧 LoRA/full 的 50 局和 100 局记录差异。 +- `native_loader_verification.json` / `data_readability_verification.json`：全批加载/读取记录。 +- `postcleanup_verification.json`：删除后的真实下载、加载与读取。 +- `credential_boundary_check.json`：HF 客户端使用官方端点；公开文件下载不接收工作区 token；已检查的元数据文本未发现凭据字面量。 diff --git a/experiments/visual-history/provenance/memory-data/reports/experiment-repos-20261007/credential_boundary_check.json b/experiments/visual-history/provenance/memory-data/reports/experiment-repos-20261007/credential_boundary_check.json new file mode 100644 index 0000000000000000000000000000000000000000..2cae00aa78829f6b55c58b83f9c5d6ecd0a6a806 --- /dev/null +++ b/experiments/visual-history/provenance/memory-data/reports/experiment-repos-20261007/credential_boundary_check.json @@ -0,0 +1,6 @@ +{ + "hf_endpoint": "https://huggingface.co", + "credential_literals_detected": [], + "tracked_env_archives": [], + "downloads": "Public artifact downloads did not receive the workspace token." +} diff --git 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Use it to make your decision.", + "flappy_ghost_trail": " You can see the past motion of the bird in the image. Use it to make your decision." + }, + "latency_override": { + "add_latency_info": false, + "fixed_latency_ms": 400.0, + "method": "fixed" + }, + "latency_source": "legacy_checkpoint_name", + "max_episodes": 200, + "max_steps_per_episode": 7200, + "num_envs": 2048, + "obs_fps": 15.0, + "obs_stride_raw_frames": 4, + "prompt_source": "latency_bench.data.prompts", + "prompt_timing_suffix": " Current action latency is {latency_raw_frames} raw frames ({latency_ms:.2f} ms). The environment runs at {env_fps:g} FPS and observations are emitted at {obs_fps:g} FPS. Choose the best next action.", + "replay_num_envs": 16, + "reward_field": "raw_reward", + "reward_semantics": "raw_reward", + "rows_unit": "decision_step", + "schema_version": 2, + "split_seed": 0, + "total_episodes": 200, + "total_rows": 563463, + "train_episodes": 198, + "train_rows": 559520, + "val_episodes": 2, + "val_fraction": 0.1, + "val_rows": 3943 +} diff --git a/latency-aware/demon-attack/demon_attack_fixed_latency_6_200ep_7k2steps_ghost15/sample_factory_init.log b/latency-aware/demon-attack/demon_attack_fixed_latency_6_200ep_7k2steps_ghost15/sample_factory_init.log new file mode 100644 index 0000000000000000000000000000000000000000..992eb30ac01edc1ca28dcb94d577bd2b9dabf43a --- /dev/null +++ b/latency-aware/demon-attack/demon_attack_fixed_latency_6_200ep_7k2steps_ghost15/sample_factory_init.log @@ -0,0 +1,90 @@ +[2026-07-25 19:31:11,100][1487747] Loading existing experiment configuration from /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/ghost_ws/regenerate_final_ghost_trail_15/small_model/checkpoints_old/demon_attack_sf_same_latency_l6_seed0/config.json +[2026-07-25 19:31:11,101][1487747] Overriding arg 'train_dir' with value '/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/ghost_ws/regenerate_final_ghost_trail_15/small_model/checkpoints_old' passed from command line +[2026-07-25 19:31:11,101][1487747] Overriding arg 'mode' with value 'eval' passed from command line +[2026-07-25 19:31:11,101][1487747] Adding new argument 'fps'=0 that is not in the saved config file! +[2026-07-25 19:31:11,101][1487747] Adding new argument 'eval_env_frameskip'=1 that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'no_render'=False that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'save_video'=False that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'video_name'=None that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'max_num_frames'=1000000000.0 that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'max_num_episodes'=1000000000.0 that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'push_to_hub'=False that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'hf_repository'=None that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'policy_index'=0 that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'train_script'=None that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'enjoy_script'=None that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'env_fps'=60 that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'obs_fps'=15 that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'reset_mode'='fire' that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'simulator'='cpu' that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'gpu_env_device'='auto' that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'gpu_env_batch_size'=1 that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'export_env_raw_rgb_frames'=False that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'latency_type'='zero' that is not in the saved config file! +[2026-07-25 19:31:11,102][1487747] Adding new argument 'fixed_latency_ms'=None that is not in the saved config file! +[2026-07-25 19:31:11,103][1487747] Adding new argument 'mean_latency_ms'=None that is not in the saved config file! +[2026-07-25 19:31:11,103][1487747] Adding new argument 'std_latency_ms'=None that is not in the saved config file! +[2026-07-25 19:31:11,103][1487747] Adding new argument 'min_latency_ms'=None that is not in the saved config file! +[2026-07-25 19:31:11,103][1487747] Adding new argument 'max_latency_ms'=None that is not in the saved config file! +[2026-07-25 19:31:11,103][1487747] Adding new argument 'latency_seed'=None that is not in the saved config file! +[2026-07-25 19:31:11,103][1487747] Adding new argument 'max_pending_actions'=None that is not in the saved config file! +[2026-07-25 19:31:11,103][1487747] Adding new argument 'hold_policy'='hold' that is not in the saved config file! +[2026-07-25 19:31:11,103][1487747] Adding new argument 'ordering_policy'='latest_ready' that is not in the saved config file! +[2026-07-25 19:31:11,103][1487747] Adding new argument 'eval_parallel_envs'=1 that is not in the saved config file! +[2026-07-25 19:31:11,103][1487747] Adding new argument 'eval_latency_raw_frame_values'='0,1,2,3,4,5' that is not in the saved config file! +A.L.E: Arcade Learning Environment (version 0.10.2+c9d4b19) +[Powered by Stella] +/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/latency/lib/python3.10/site-packages/gymnasium/core.py:311: UserWarning: WARN: env.num_agents to get variables from other wrappers is deprecated and will be removed in v1.0, to get this variable you can do `env.unwrapped.num_agents` for environment variables or `env.get_wrapper_attr('num_agents')` that will search the reminding wrappers. + logger.warn( +/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/latency/lib/python3.10/site-packages/gymnasium/core.py:311: UserWarning: WARN: env.is_multiagent to get variables from other wrappers is deprecated and will be removed in v1.0, to get this variable you can do `env.unwrapped.is_multiagent` for environment variables or `env.get_wrapper_attr('is_multiagent')` that will search the reminding wrappers. + logger.warn( +[2026-07-25 19:31:13,789][1487747] RunningMeanStd input shape: (4, 84, 84) +[2026-07-25 19:31:13,820][1487747] RunningMeanStd input shape: (1,) +[2026-07-25 19:31:13,828][1487747] ConvEncoder: input_channels=4 +[2026-07-25 19:31:14,209][1487747] Conv encoder output size: 512 +[2026-07-25 23:30:07,345][4034983] Loading existing experiment configuration from /lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/ghost_ws/regenerate_final_ghost_trail_15/small_model/checkpoints_old/demon_attack_sf_same_latency_l6_seed0/config.json +[2026-07-25 23:30:07,347][4034983] Overriding arg 'train_dir' with value '/lustre/fsw/portfolios/nvr/projects/nvr_lacr_llm/users/zihwang/ghost_ws/regenerate_final_ghost_trail_15/small_model/checkpoints_old' passed from command line +[2026-07-25 23:30:07,347][4034983] Overriding arg 'mode' with value 'eval' passed from command line +[2026-07-25 23:30:07,347][4034983] Adding new argument 'fps'=0 that is not in the saved config file! +[2026-07-25 23:30:07,347][4034983] Adding new argument 'eval_env_frameskip'=1 that is not in the saved config file! +[2026-07-25 23:30:07,347][4034983] Adding new argument 'no_render'=False that is not in the saved config file! +[2026-07-25 23:30:07,347][4034983] Adding new argument 'save_video'=False that is not in the saved config file! +[2026-07-25 23:30:07,347][4034983] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! +[2026-07-25 23:30:07,347][4034983] Adding new argument 'video_name'=None that is not in the saved config file! +[2026-07-25 23:30:07,347][4034983] Adding new argument 'max_num_frames'=1000000000.0 that is not in the saved config file! +[2026-07-25 23:30:07,347][4034983] Adding new argument 'max_num_episodes'=1000000000.0 that is not in the saved config file! +[2026-07-25 23:30:07,347][4034983] Adding new argument 'push_to_hub'=False that is not in the saved config file! +[2026-07-25 23:30:07,347][4034983] Adding new argument 'hf_repository'=None that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'policy_index'=0 that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'train_script'=None that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'enjoy_script'=None that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'env_fps'=60 that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'obs_fps'=15 that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'reset_mode'='fire' that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'simulator'='cpu' that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'gpu_env_device'='auto' that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'gpu_env_batch_size'=1 that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'export_env_raw_rgb_frames'=False that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'latency_type'='zero' that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'fixed_latency_ms'=None that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'mean_latency_ms'=None that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'std_latency_ms'=None that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'min_latency_ms'=None that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'max_latency_ms'=None that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'latency_seed'=None that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'max_pending_actions'=None that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'hold_policy'='hold' that is not in the saved config file! +[2026-07-25 23:30:07,348][4034983] Adding new argument 'ordering_policy'='latest_ready' that is not in the saved config file! +[2026-07-25 23:30:07,349][4034983] Adding new argument 'eval_parallel_envs'=1 that is not in the saved config file! +[2026-07-25 23:30:07,349][4034983] Adding new argument 'eval_latency_raw_frame_values'='0,1,2,3,4,5' that is not in the saved config file! +A.L.E: Arcade Learning Environment (version 0.10.2+c9d4b19) +[Powered by Stella] +/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/latency/lib/python3.10/site-packages/gymnasium/core.py:311: UserWarning: WARN: env.num_agents to get variables from other wrappers is deprecated and will be removed in v1.0, to get this variable you can do `env.unwrapped.num_agents` for environment variables or `env.get_wrapper_attr('num_agents')` that will search the reminding wrappers. + logger.warn( +/lustre/fsw/portfolios/nvr/users/zihwang/miniconda3/envs/latency/lib/python3.10/site-packages/gymnasium/core.py:311: UserWarning: WARN: env.is_multiagent to get variables from other wrappers is deprecated and will be removed in v1.0, to get this variable you can do `env.unwrapped.is_multiagent` for environment variables or `env.get_wrapper_attr('is_multiagent')` that will search the reminding wrappers. + logger.warn( +[2026-07-25 23:30:10,133][4034983] RunningMeanStd input shape: (4, 84, 84) +[2026-07-25 23:30:10,159][4034983] RunningMeanStd input shape: (1,) +[2026-07-25 23:30:10,168][4034983] ConvEncoder: input_channels=4 +[2026-07-25 23:30:10,424][4034983] Conv encoder output size: 512 diff --git a/latency-aware/demon-attack/demon_attack_fixed_latency_6_200ep_7k2steps_ghost15/train.parquet b/latency-aware/demon-attack/demon_attack_fixed_latency_6_200ep_7k2steps_ghost15/train.parquet new file mode 100644 index 0000000000000000000000000000000000000000..9dd60ffc1c449bcf7bdb55efd9c998fc239c1243 --- /dev/null +++ b/latency-aware/demon-attack/demon_attack_fixed_latency_6_200ep_7k2steps_ghost15/train.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ef3d65a30d0e9222cf7e688de509821fd7697585bacd56ed7c54084773b3d756 +size 986794901 diff --git a/latency-aware/demon-attack/demon_attack_fixed_latency_6_200ep_7k2steps_ghost15/val.parquet b/latency-aware/demon-attack/demon_attack_fixed_latency_6_200ep_7k2steps_ghost15/val.parquet new file mode 100644 index 0000000000000000000000000000000000000000..101b8489c337c4beec00563df8a1e89f6a05d409 --- /dev/null +++ b/latency-aware/demon-attack/demon_attack_fixed_latency_6_200ep_7k2steps_ghost15/val.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1fde0d1e2a9d3adf2447cd9ac35c8d9e63d4c4b867d1bcc65a31309c04847735 +size 6813323 diff --git a/latency-aware/flappy/flappy_fixed_latency_3_200ep_7k2steps/train-00006-of-00034.parquet b/latency-aware/flappy/flappy_fixed_latency_3_200ep_7k2steps/train-00006-of-00034.parquet new file mode 100644 index 0000000000000000000000000000000000000000..6d11cb788d4b92bbbfd17ebbdb55149d5b8e6dd9 --- /dev/null +++ b/latency-aware/flappy/flappy_fixed_latency_3_200ep_7k2steps/train-00006-of-00034.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5b2ad35022cf94c94985f76026bc2e08b2e5a42c1991ec0b6bd2e518d9566167 +size 484170770 diff --git 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/dev/null +++ b/latency-aware/flappy/flappy_fixed_latency_3_200ep_7k2steps/train-00010-of-00034.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:fd29bf759ca0e8e73cf1acbf174d61091d6b7def5072697849230572c7d27ca9 +size 482778094 diff --git a/latency-aware/flappy/flappy_fixed_latency_3_200ep_7k2steps/train-00011-of-00034.parquet b/latency-aware/flappy/flappy_fixed_latency_3_200ep_7k2steps/train-00011-of-00034.parquet new file mode 100644 index 0000000000000000000000000000000000000000..25039e11e25a5dab1e6ab02e5faba8349bc71bea --- /dev/null +++ b/latency-aware/flappy/flappy_fixed_latency_3_200ep_7k2steps/train-00011-of-00034.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0d754aadc34d4c5b4b236db909debab1d73a25707b8e29127a58688e2f8128f8 +size 484014932 diff --git a/latency-aware/flappy/flappy_fixed_latency_3_200ep_7k2steps/train-00012-of-00034.parquet b/latency-aware/flappy/flappy_fixed_latency_3_200ep_7k2steps/train-00012-of-00034.parquet new file mode 100644 index 0000000000000000000000000000000000000000..92a3cc829c26eab6952e0c54471b1cb187af783c --- /dev/null +++ b/latency-aware/flappy/flappy_fixed_latency_3_200ep_7k2steps/train-00012-of-00034.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8a0f60285c79d7aad2204b1860701066c3b3a3de48a60bab0007da7392825151 +size 482551737 diff --git a/latency-aware/flappy/flappy_fixed_latency_3_200ep_7k2steps/train-00013-of-00034.parquet b/latency-aware/flappy/flappy_fixed_latency_3_200ep_7k2steps/train-00013-of-00034.parquet new file mode 100644 index 0000000000000000000000000000000000000000..726d8cbbc7b9277419095a48ead5b5d180b08bb5 --- /dev/null +++ b/latency-aware/flappy/flappy_fixed_latency_3_200ep_7k2steps/train-00013-of-00034.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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