INFO 2026-06-21 16:51:24 ot_train.py:197 {'batch_size': 8,
 'checkpoint_path': None,
 'cudnn_deterministic': False,
 'dataset': {'episodes': None,
             'image_transforms': {'enable': False,
                                  'max_num_transforms': 3,
                                  'random_order': False,
                                  'tfs': {'affine': {'kwargs': {'degrees': [-5.0,
                                                                            5.0],
                                                                'translate': [0.05,
                                                                              0.05]},
                                                     'type': 'RandomAffine',
                                                     'weight': 1.0},
                                          'brightness': {'kwargs': {'brightness': [0.8,
                                                                                   1.2]},
                                                         'type': 'ColorJitter',
                                                         'weight': 1.0},
                                          'contrast': {'kwargs': {'contrast': [0.8,
                                                                               1.2]},
                                                       'type': 'ColorJitter',
                                                       'weight': 1.0},
                                          'hue': {'kwargs': {'hue': [-0.05,
                                                                     0.05]},
                                                  'type': 'ColorJitter',
                                                  'weight': 1.0},
                                          'saturation': {'kwargs': {'saturation': [0.5,
                                                                                   1.5]},
                                                         'type': 'ColorJitter',
                                                         'weight': 1.0},
                                          'sharpness': {'kwargs': {'sharpness': [0.5,
                                                                                 1.5]},
                                                        'type': 'SharpnessJitter',
                                                        'weight': 1.0}}},
             'repo_id': '3a279/piper_place_block_cam0fix_random500',
             'revision': None,
             'root': '/workspace/datasets/piper_place_block_cam0fix_random500_lerobot',
             'streaming': False,
             'use_imagenet_stats': True,
             'video_backend': 'torchcodec'},
 'env': None,
 'eval': {'batch_size': 50, 'n_episodes': 50, 'use_async_envs': False},
 'eval_freq': 20000,
 'job_name': 'piper_place_block_cam0fix_bs8_50k',
 'log_freq': 200,
 'num_workers': 4,
 'optimizer': {'betas': [0.95, 0.999],
               'eps': 1e-08,
               'grad_clip_norm': 10.0,
               'lr': 0.0001,
               'type': 'adam',
               'weight_decay': 1e-06},
 'output_dir': '/workspace/outputs/piper_place_block_cam0fix_bs8_50k',
 'peft': None,
 'policy': {'beta_end': 0.02,
            'beta_schedule': 'squaredcos_cap_v2',
            'beta_start': 0.0001,
            'clip_sample': True,
            'clip_sample_range': 1.0,
            'compile_mode': 'reduce-overhead',
            'compile_model': False,
            'crop_is_random': True,
            'crop_ratio': 1.0,
            'crop_shape': None,
            'device': 'cuda',
            'diffusion_step_embed_dim': 128,
            'do_mask_loss_for_padding': False,
            'down_dims': [512, 1024, 2048],
            'drop_n_last_frames': 7,
            'horizon': 16,
            'input_features': {},
            'kernel_size': 5,
            'license': None,
            'n_action_steps': 8,
            'n_groups': 8,
            'n_obs_steps': 2,
            'noise_scheduler_type': 'DDPM',
            'normalization_mapping': {'ACTION': <NormalizationMode.MIN_MAX: 'MIN_MAX'>,
                                      'STATE': <NormalizationMode.MIN_MAX: 'MIN_MAX'>,
                                      'VISUAL': <NormalizationMode.MEAN_STD: 'MEAN_STD'>},
            'num_inference_steps': None,
            'num_train_timesteps': 100,
            'optimizer_betas': [0.95, 0.999],
            'optimizer_eps': 1e-08,
            'optimizer_lr': 0.0001,
            'optimizer_weight_decay': 1e-06,
            'output_features': {},
            'prediction_type': 'epsilon',
            'pretrained_backbone_weights': None,
            'pretrained_path': None,
            'private': None,
            'push_to_hub': False,
            'repo_id': '3a279/piper_place_block_cam0fix_bs8_50k',
            'resize_shape': None,
            'scheduler_name': 'cosine',
            'scheduler_warmup_steps': 500,
            'spatial_softmax_num_keypoints': 32,
            'tags': None,
            'type': 'diffusion',
            'use_amp': False,
            'use_film_scale_modulation': True,
            'use_group_norm': True,
            'use_peft': False,
            'use_separate_rgb_encoder_per_camera': False,
            'vision_backbone': 'resnet18'},
 'rabc_epsilon': 1e-06,
 'rabc_head_mode': 'sparse',
 'rabc_kappa': 0.01,
 'rabc_progress_path': None,
 'rename_map': {},
 'resume': False,
 'save_checkpoint': True,
 'save_freq': 10000,
 'scheduler': {'name': 'cosine', 'num_warmup_steps': 500, 'type': 'diffuser'},
 'seed': 1000,
 'steps': 50000,
 'tolerance_s': 0.0001,
 'use_policy_training_preset': True,
 'use_rabc': False,
 'wandb': {'add_tags': True,
           'disable_artifact': False,
           'enable': False,
           'entity': None,
           'mode': None,
           'notes': None,
           'project': 'lerobot',
           'run_id': None}}
INFO 2026-06-21 16:51:24 ot_train.py:205 Logs will be saved locally.
INFO 2026-06-21 16:51:24 ot_train.py:221 Creating dataset
INFO 2026-06-21 16:51:25 eo_utils.py:106 Using video codec: libsvtav1
INFO 2026-06-21 16:51:28 ot_train.py:239 Creating policy
INFO 2026-06-21 16:51:32 ot_train.py:294 Creating optimizer and scheduler
INFO 2026-06-21 16:51:32 ot_train.py:329 Output dir: /workspace/outputs/piper_place_block_cam0fix_bs8_50k
INFO 2026-06-21 16:51:32 ot_train.py:336 cfg.steps=50000 (50K)
INFO 2026-06-21 16:51:32 ot_train.py:337 dataset.num_frames=49573 (50K)
INFO 2026-06-21 16:51:32 ot_train.py:338 dataset.num_episodes=500
INFO 2026-06-21 16:51:32 ot_train.py:341 Effective batch size: 8 x 1 = 8
INFO 2026-06-21 16:51:32 ot_train.py:342 num_learnable_params=270353703 (270M)
INFO 2026-06-21 16:51:32 ot_train.py:343 num_total_params=270353703 (270M)

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Training:   4%|▎         | 1800/50000 [08:48<3:56:42,  3.39step/s]INFO 2026-06-21 17:00:21 ot_train.py:439 step:2K smpl:14K ep:145 epch:0.29 loss:0.053 grdn:0.871 lr:1.0e-04 updt_s:0.269 data_s:0.016

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Training:  11%|█         | 5400/50000 [25:46<3:31:09,  3.52step/s]INFO 2026-06-21 17:17:19 ot_train.py:439 step:5K smpl:43K ep:436 epch:0.87 loss:0.034 grdn:0.578 lr:9.8e-05 updt_s:0.267 data_s:0.014

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Training:  18%|█▊        | 8800/50000 [41:56<3:14:07,  3.54step/s]INFO 2026-06-21 17:33:29 ot_train.py:439 step:9K smpl:70K ep:710 epch:1.42 loss:0.029 grdn:0.482 lr:9.3e-05 updt_s:0.267 data_s:0.015

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Training:  20%|██        | 10000/50000 [47:35<3:08:30,  3.54step/s]INFO 2026-06-21 17:39:08 ot_train.py:439 step:10K smpl:80K ep:807 epch:1.61 loss:0.025 grdn:0.454 lr:9.1e-05 updt_s:0.267 data_s:0.014
INFO 2026-06-21 17:39:08 ot_train.py:459 Checkpoint policy after step 10000

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Training:  31%|███       | 15400/50000 [1:13:19<2:43:30,  3.53step/s]INFO 2026-06-21 18:04:52 ot_train.py:439 step:15K smpl:123K ep:1K epch:2.49 loss:0.020 grdn:0.420 lr:8.0e-05 updt_s:0.267 data_s:0.015

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Training:  31%|███       | 15600/50000 [1:14:16<2:41:17,  3.55step/s]INFO 2026-06-21 18:05:48 ot_train.py:439 step:16K smpl:125K ep:1K epch:2.52 loss:0.022 grdn:0.447 lr:7.9e-05 updt_s:0.267 data_s:0.014

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Training:  34%|███▎      | 16800/50000 [1:19:56<2:36:36,  3.53step/s]INFO 2026-06-21 18:11:29 ot_train.py:439 step:17K smpl:134K ep:1K epch:2.71 loss:0.020 grdn:0.407 lr:7.6e-05 updt_s:0.268 data_s:0.014

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Training:  40%|███▉      | 19800/50000 [1:34:11<2:21:49,  3.55step/s]INFO 2026-06-21 18:25:44 ot_train.py:439 step:20K smpl:158K ep:2K epch:3.20 loss:0.014 grdn:0.351 lr:6.7e-05 updt_s:0.268 data_s:0.014

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Training:  40%|████      | 20000/50000 [1:35:08<2:20:13,  3.57step/s]INFO 2026-06-21 18:26:41 ot_train.py:439 step:20K smpl:160K ep:2K epch:3.23 loss:0.017 grdn:0.381 lr:6.7e-05 updt_s:0.269 data_s:0.015
INFO 2026-06-21 18:26:41 ot_train.py:459 Checkpoint policy after step 20000

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INFO 2026-06-21 19:14:12 ot_train.py:459 Checkpoint policy after step 30000

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Training:  77%|███████▋  | 38600/50000 [3:03:26<53:04,  3.58step/s]INFO 2026-06-21 19:54:58 ot_train.py:439 step:39K smpl:309K ep:3K epch:6.23 loss:0.006 grdn:0.285 lr:1.3e-05 updt_s:0.268 data_s:0.013

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Training:  80%|████████  | 40000/50000 [3:10:01<47:17,  3.52step/s]INFO 2026-06-21 20:01:34 ot_train.py:439 step:40K smpl:320K ep:3K epch:6.46 loss:0.006 grdn:0.273 lr:9.9e-06 updt_s:0.268 data_s:0.014
INFO 2026-06-21 20:01:34 ot_train.py:459 Checkpoint policy after step 40000

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Training:  83%|████████▎ | 41400/50000 [3:16:49<40:45,  3.52step/s]INFO 2026-06-21 20:08:22 ot_train.py:439 step:41K smpl:331K ep:3K epch:6.68 loss:0.005 grdn:0.242 lr:7.4e-06 updt_s:0.269 data_s:0.015

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Training:  83%|████████▎ | 41600/50000 [3:17:47<41:14,  3.40step/s]INFO 2026-06-21 20:09:19 ot_train.py:439 step:42K smpl:333K ep:3K epch:6.71 loss:0.006 grdn:0.262 lr:7.1e-06 updt_s:0.270 data_s:0.015

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Training:  84%|████████▎ | 41800/50000 [3:18:44<38:23,  3.56step/s]INFO 2026-06-21 20:10:16 ot_train.py:439 step:42K smpl:334K ep:3K epch:6.75 loss:0.005 grdn:0.268 lr:6.8e-06 updt_s:0.270 data_s:0.013

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Training:  88%|████████▊ | 43800/50000 [3:28:03<28:43,  3.60step/s]INFO 2026-06-21 20:19:35 ot_train.py:439 step:44K smpl:350K ep:4K epch:7.07 loss:0.005 grdn:0.254 lr:3.9e-06 updt_s:0.266 data_s:0.011

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Training: 100%|██████████| 50000/50000 [3:57:01<00:00,  3.56step/s]INFO 2026-06-21 20:48:34 ot_train.py:439 step:50K smpl:400K ep:4K epch:8.07 loss:0.004 grdn:0.231 lr:1.3e-09 updt_s:0.269 data_s:0.013
INFO 2026-06-21 20:48:34 ot_train.py:459 Checkpoint policy after step 50000

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INFO 2026-06-21 20:48:45 ot_train.py:533 End of training