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intervla-m1/simple/G1WholebodyBendPickMP-v0/20260404_062517/checkpoints/steps_10000_pytorch_model.pt

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intervla-m1/simple/G1WholebodyBendPickMP-v0/20260404_062517/checkpoints/steps_40000_pytorch_model.pt

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intervla-m1/simple/G1WholebodyBendPickMP-v0/20260404_062517/config.json

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+{
+  "run_id": "G1WholebodyBendPick",
+  "run_root_dir": "runs/InternVLA/Checkpoints",
+  "seed": 42,
+  "trackers": [
+    "jsonl",
+    "wandb"
+  ],
+  "wandb_entity": "jliu530-soochow-university",
+  "wandb_project": "psi",
+  "is_debug": false,
+  "framework": {
+    "framework_py": "InternVLA-M1",
+    "qwenvl": {
+      "base_vlm": "Qwen/Qwen2.5-VL-3B-Instruct",
+      "attn_implementation": "flash_attention_2",
+      "vl_hidden_dim": 2048
+    },
+    "dino": {
+      "dino_backbone": "dinov2_vits14"
+    },
+    "layer_qformer": {
+      "qformer_end_layer": 37,
+      "qformer_start_layer": 36,
+      "num_query_tokens": 64,
+      "input_dim": 2048,
+      "ouptput_dim": 768,
+      "grad_scale": 0.5
+    },
+    "action_model": {
+      "action_model_type": "DiT-B",
+      "action_hidden_dim": 768,
+      "action_dim": 36,
+      "use_ema": false,
+      "future_action_window_size": 15,
+      "past_action_window_size": 0,
+      "repeated_diffusion_steps": 8
+    },
+    "fm_head_config": {
+      "input_embedding_dim": 1536,
+      "hidden_size": 1024,
+      "add_pos_embed": true,
+      "max_seq_len": 1024,
+      "action_dim": 36,
+      "future_action_window_size": 15,
+      "action_horizon": 16,
+      "past_action_window_size": 0,
+      "noise_beta_alpha": 1.5,
+      "noise_beta_beta": 1.0,
+      "noise_s": 0.999,
+      "num_timestep_buckets": 1000,
+      "num_inference_timesteps": 4,
+      "num_target_vision_tokens": 32,
+      "diffusion_model_cfg": {
+        "attention_head_dim": 48,
+        "cross_attention_dim": 2048,
+        "dropout": 0.2,
+        "final_dropout": true,
+        "interleave_self_attention": true,
+        "norm_type": "ada_norm",
+        "num_attention_heads": 32,
+        "num_layers": 16,
+        "output_dim": 1024,
+        "positional_embeddings": null
+      }
+    }
+  },
+  "datasets": {
+    "vlm_data": {
+      "dataset_py": "vlm_datasets",
+      "dataformat": "llava_json",
+      "dataset_use": "asv2_conversation_en,asv2_detailed_description_en,asv2_region_captioning_en,coco_internvl_longcap_en,coco_karpathy_train_567_en,coco_negative_gpt4o_en,coco_poetry_zh,coco_rem_en_zh,cocorem_exist_yorn_en,cocotextv2_en,cocotextv2_gpt4o_en,okvqa_en,refcoco_grounding_aug_en,refcoco_grounding_en,tallyqa_coco_en,toloka_grounding_aug_en,vqav2_en,vsr_en",
+      "eval_dataset": "aokvqa_cauldron_llava_format",
+      "data_flatten": false,
+      "base_interval": 2,
+      "max_pixels": 50176,
+      "min_pixels": 784,
+      "model_max_length": 2048,
+      "model_type": "qwen2.5vl",
+      "per_device_batch_size": 4
+    },
+    "vla_data": {
+      "dataset_py": "lerobot_datasets",
+      "data_root_dir": "/hfm/jliu/simple/G1WholebodyBendPick-v0-psi0",
+      "data_mix": "humanoid_",
+      "action_type": "abs_joints",
+      "CoT_prompt": "Your task is {instruction}. To identify the key objects for your task. Locate their bounding boxes in [x1,y1,x2,y2] format.",
+      "CoT_answer": "bbox",
+      "default_image_resolution": [
+        3,
+        224,
+        224
+      ],
+      "per_device_batch_size": 64,
+      "preload_all": true,
+      "load_all_data_for_training": true,
+      "obs": [
+        "image_0"
+      ],
+      "image_size": [
+        224,
+        224
+      ]
+    }
+  },
+  "trainer": {
+    "epochs": 100,
+    "max_train_steps": 40000,
+    "num_warmup_steps": 0,
+    "save_interval": 10000,
+    "eval_interval": 100,
+    "learning_rate": {
+      "base": 5e-05,
+      "qwen_vl_interface": 1e-05,
+      "action_model": 0.0001
+    },
+    "lr_scheduler_type": "cosine_with_min_lr",
+    "scheduler_specific_kwargs": {
+      "min_lr": 5e-07
+    },
+    "freeze_modules": "qwen_vl_interface,layer_qformer,dino_encoder,dino_pro",
+    "loss_scale": {
+      "vla": 1.0,
+      "vlm": 0.1
+    },
+    "pretrained_checkpoint": "/hfm/cache/checkpoints/InternVLA-M1-Pretrain-RT-1-Bridge/checkpoints/steps_50000_pytorch_model.pt",
+    "skip_reload_modules": "action_model",
+    "repeated_diffusion_steps": 4,
+    "max_grad_norm": 1.0,
+    "warmup_ratio": 0.1,
+    "weight_decay": 0.0,
+    "logging_frequency": 10,
+    "gradient_clipping": 1.0,
+    "gradient_accumulation_steps": 1,
+    "optimizer": {
+      "name": "AdamW",
+      "betas": [
+        0.9,
+        0.95
+      ],
+      "eps": 1e-08,
+      "weight_decay": 1e-08
+    },
+    "is_resume": false,
+    "resume_epoch": null,
+    "resume_step": null,
+    "enable_gradient_checkpointing": true,
+    "enable_mixed_precision_training": true
+  },
+  "output_dir": "runs/InternVLA/Checkpoints/G1WholebodyBendPick/20260404_062517"
+}

intervla-m1/simple/G1WholebodyBendPickMP-v0/20260404_062517/config.yaml

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+run_id: G1WholebodyBendPick
+run_root_dir: runs/InternVLA/Checkpoints
+seed: 42
+trackers:
+- jsonl
+- wandb
+wandb_entity: jliu530-soochow-university
+wandb_project: psi
+is_debug: false
+framework:
+  framework_py: InternVLA-M1
+  qwenvl:
+    base_vlm: Qwen/Qwen2.5-VL-3B-Instruct
+    attn_implementation: flash_attention_2
+    vl_hidden_dim: 2048
+  dino:
+    dino_backbone: dinov2_vits14
+  layer_qformer:
+    qformer_end_layer: 37
+    qformer_start_layer: 36
+    num_query_tokens: 64
+    input_dim: 2048
+    ouptput_dim: 768
+    grad_scale: 0.5
+  action_model:
+    action_model_type: DiT-B
+    action_hidden_dim: 768
+    action_dim: 36
+    use_ema: false
+    future_action_window_size: 15
+    past_action_window_size: 0
+    repeated_diffusion_steps: 8
+  fm_head_config:
+    input_embedding_dim: 1536
+    hidden_size: 1024
+    add_pos_embed: true
+    max_seq_len: 1024
+    action_dim: 36
+    future_action_window_size: 15
+    action_horizon: 16
+    past_action_window_size: 0
+    noise_beta_alpha: 1.5
+    noise_beta_beta: 1.0
+    noise_s: 0.999
+    num_timestep_buckets: 1000
+    num_inference_timesteps: 4
+    num_target_vision_tokens: 32
+    diffusion_model_cfg:
+      attention_head_dim: 48
+      cross_attention_dim: 2048
+      dropout: 0.2
+      final_dropout: true
+      interleave_self_attention: true
+      norm_type: ada_norm
+      num_attention_heads: 32
+      num_layers: 16
+      output_dim: 1024
+      positional_embeddings: null
+datasets:
+  vlm_data:
+    dataset_py: vlm_datasets
+    dataformat: llava_json
+    dataset_use: asv2_conversation_en,asv2_detailed_description_en,asv2_region_captioning_en,coco_internvl_longcap_en,coco_karpathy_train_567_en,coco_negative_gpt4o_en,coco_poetry_zh,coco_rem_en_zh,cocorem_exist_yorn_en,cocotextv2_en,cocotextv2_gpt4o_en,okvqa_en,refcoco_grounding_aug_en,refcoco_grounding_en,tallyqa_coco_en,toloka_grounding_aug_en,vqav2_en,vsr_en
+    eval_dataset: aokvqa_cauldron_llava_format
+    data_flatten: false
+    base_interval: 2
+    max_pixels: 50176
+    min_pixels: 784
+    model_max_length: 2048
+    model_type: qwen2.5vl
+    per_device_batch_size: 4
+  vla_data:
+    dataset_py: lerobot_datasets
+    data_root_dir: /hfm/jliu/simple/G1WholebodyBendPick-v0-psi0
+    data_mix: humanoid_
+    action_type: abs_joints
+    CoT_prompt: Your task is {instruction}. To identify the key objects for your task.
+      Locate their bounding boxes in [x1,y1,x2,y2] format.
+    CoT_answer: bbox
+    default_image_resolution:
+    - 3
+    - 224
+    - 224
+    per_device_batch_size: 64
+    preload_all: true
+    load_all_data_for_training: true
+    obs:
+    - image_0
+    image_size:
+    - 224
+    - 224
+trainer:
+  epochs: 100
+  max_train_steps: 40000
+  num_warmup_steps: 0
+  save_interval: 10000
+  eval_interval: 100
+  learning_rate:
+    base: 5.0e-05
+    qwen_vl_interface: 1.0e-05
+    action_model: 0.0001
+  lr_scheduler_type: cosine_with_min_lr
+  scheduler_specific_kwargs:
+    min_lr: 5.0e-07
+  freeze_modules: qwen_vl_interface,layer_qformer,dino_encoder,dino_pro
+  loss_scale:
+    vla: 1.0
+    vlm: 0.1
+  pretrained_checkpoint: /hfm/cache/checkpoints/InternVLA-M1-Pretrain-RT-1-Bridge/checkpoints/steps_50000_pytorch_model.pt
+  skip_reload_modules: action_model
+  repeated_diffusion_steps: 4
+  max_grad_norm: 1.0
+  warmup_ratio: 0.1
+  weight_decay: 0.0
+  logging_frequency: 10
+  gradient_clipping: 1.0
+  gradient_accumulation_steps: 1
+  optimizer:
+    name: AdamW
+    betas:
+    - 0.9
+    - 0.95
+    eps: 1.0e-08
+    weight_decay: 1.0e-08
+  is_resume: false
+  resume_epoch: null
+  resume_step: null
+  enable_gradient_checkpointing: true
+  enable_mixed_precision_training: true
+output_dir: runs/InternVLA/Checkpoints/G1WholebodyBendPick/20260404_062517

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intervla-m1/simple/G1WholebodyTabletopGraspMP-v0/20260404_061207/config.json

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+{
+  "run_id": "G1WholebodyTabletopGrasp",
+  "run_root_dir": "runs/InternVLA/Checkpoints",
+  "seed": 42,
+  "trackers": [
+    "jsonl",
+    "wandb"
+  ],
+  "wandb_entity": "jliu530-soochow-university",
+  "wandb_project": "psi",
+  "is_debug": false,
+  "framework": {
+    "framework_py": "InternVLA-M1",
+    "qwenvl": {
+      "base_vlm": "Qwen/Qwen2.5-VL-3B-Instruct",
+      "attn_implementation": "flash_attention_2",
+      "vl_hidden_dim": 2048
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+    "dino": {
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+      "diffusion_model_cfg": {
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+        "cross_attention_dim": 2048,
+        "dropout": 0.2,
+        "final_dropout": true,
+        "interleave_self_attention": true,
+        "norm_type": "ada_norm",
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+        "num_layers": 16,
+        "output_dim": 1024,
+        "positional_embeddings": null
+      }
+    }
+  },
+  "datasets": {
+    "vlm_data": {
+      "dataset_py": "vlm_datasets",
+      "dataformat": "llava_json",
+      "dataset_use": "asv2_conversation_en,asv2_detailed_description_en,asv2_region_captioning_en,coco_internvl_longcap_en,coco_karpathy_train_567_en,coco_negative_gpt4o_en,coco_poetry_zh,coco_rem_en_zh,cocorem_exist_yorn_en,cocotextv2_en,cocotextv2_gpt4o_en,okvqa_en,refcoco_grounding_aug_en,refcoco_grounding_en,tallyqa_coco_en,toloka_grounding_aug_en,vqav2_en,vsr_en",
+      "eval_dataset": "aokvqa_cauldron_llava_format",
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+      "base_interval": 2,
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+    "vla_data": {
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+      "data_root_dir": "/hfm/jliu/simple/G1WholebodyTabletopGrasp-v0",
+      "data_mix": "humanoid_",
+      "action_type": "abs_joints",
+      "CoT_prompt": "Your task is {instruction}. To identify the key objects for your task. Locate their bounding boxes in [x1,y1,x2,y2] format.",
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+    "loss_scale": {
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+      "vlm": 0.1
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+    "pretrained_checkpoint": "/hfm/cache/checkpoints/InternVLA-M1-Pretrain-RT-1-Bridge/checkpoints/steps_50000_pytorch_model.pt",
+    "skip_reload_modules": "action_model",
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+    "enable_mixed_precision_training": true
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+  "output_dir": "runs/InternVLA/Checkpoints/G1WholebodyTabletopGrasp/20260404_061207"
+}

intervla-m1/simple/G1WholebodyTabletopGraspMP-v0/20260404_061207/config.yaml

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+run_id: G1WholebodyTabletopGrasp
+run_root_dir: runs/InternVLA/Checkpoints
+seed: 42
+trackers:
+- jsonl
+- wandb
+wandb_entity: jliu530-soochow-university
+wandb_project: psi
+is_debug: false
+framework:
+  framework_py: InternVLA-M1
+  qwenvl:
+    base_vlm: Qwen/Qwen2.5-VL-3B-Instruct
+    attn_implementation: flash_attention_2
+    vl_hidden_dim: 2048
+  dino:
+    dino_backbone: dinov2_vits14
+  layer_qformer:
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+    qformer_start_layer: 36
+    num_query_tokens: 64
+    input_dim: 2048
+    ouptput_dim: 768
+    grad_scale: 0.5
+  action_model:
+    action_model_type: DiT-B
+    action_hidden_dim: 768
+    action_dim: 36
+    use_ema: false
+    future_action_window_size: 15
+    past_action_window_size: 0
+    repeated_diffusion_steps: 8
+  fm_head_config:
+    input_embedding_dim: 1536
+    hidden_size: 1024
+    add_pos_embed: true
+    max_seq_len: 1024
+    action_dim: 36
+    future_action_window_size: 15
+    action_horizon: 16
+    past_action_window_size: 0
+    noise_beta_alpha: 1.5
+    noise_beta_beta: 1.0
+    noise_s: 0.999
+    num_timestep_buckets: 1000
+    num_inference_timesteps: 4
+    num_target_vision_tokens: 32
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+      attention_head_dim: 48
+      cross_attention_dim: 2048
+      dropout: 0.2
+      final_dropout: true
+      interleave_self_attention: true
+      norm_type: ada_norm
+      num_attention_heads: 32
+      num_layers: 16
+      output_dim: 1024
+      positional_embeddings: null
+datasets:
+  vlm_data:
+    dataset_py: vlm_datasets
+    dataformat: llava_json
+    dataset_use: asv2_conversation_en,asv2_detailed_description_en,asv2_region_captioning_en,coco_internvl_longcap_en,coco_karpathy_train_567_en,coco_negative_gpt4o_en,coco_poetry_zh,coco_rem_en_zh,cocorem_exist_yorn_en,cocotextv2_en,cocotextv2_gpt4o_en,okvqa_en,refcoco_grounding_aug_en,refcoco_grounding_en,tallyqa_coco_en,toloka_grounding_aug_en,vqav2_en,vsr_en
+    eval_dataset: aokvqa_cauldron_llava_format
+    data_flatten: false
+    base_interval: 2
+    max_pixels: 50176
+    min_pixels: 784
+    model_max_length: 2048
+    model_type: qwen2.5vl
+    per_device_batch_size: 4
+  vla_data:
+    dataset_py: lerobot_datasets
+    data_root_dir: /hfm/jliu/simple/G1WholebodyTabletopGrasp-v0
+    data_mix: humanoid_
+    action_type: abs_joints
+    CoT_prompt: Your task is {instruction}. To identify the key objects for your task.
+      Locate their bounding boxes in [x1,y1,x2,y2] format.
+    CoT_answer: bbox
+    default_image_resolution:
+    - 3
+    - 224
+    - 224
+    per_device_batch_size: 64
+    preload_all: true
+    load_all_data_for_training: true
+    obs:
+    - image_0
+    image_size:
+    - 224
+    - 224
+trainer:
+  epochs: 100
+  max_train_steps: 40000
+  num_warmup_steps: 0
+  save_interval: 10000
+  eval_interval: 100
+  learning_rate:
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+    qwen_vl_interface: 1.0e-05
+    action_model: 0.0001
+  lr_scheduler_type: cosine_with_min_lr
+  scheduler_specific_kwargs:
+    min_lr: 5.0e-07
+  freeze_modules: qwen_vl_interface,layer_qformer,dino_encoder,dino_pro
+  loss_scale:
+    vla: 1.0
+    vlm: 0.1
+  pretrained_checkpoint: /hfm/cache/checkpoints/InternVLA-M1-Pretrain-RT-1-Bridge/checkpoints/steps_50000_pytorch_model.pt
+  skip_reload_modules: action_model
+  repeated_diffusion_steps: 4
+  max_grad_norm: 1.0
+  warmup_ratio: 0.1
+  weight_decay: 0.0
+  logging_frequency: 10
+  gradient_clipping: 1.0
+  gradient_accumulation_steps: 1
+  optimizer:
+    name: AdamW
+    betas:
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+    - 0.95
+    eps: 1.0e-08
+    weight_decay: 1.0e-08
+  is_resume: false
+  resume_epoch: null
+  resume_step: null
+  enable_gradient_checkpointing: true
+  enable_mixed_precision_training: true
+output_dir: runs/InternVLA/Checkpoints/G1WholebodyTabletopGrasp/20260404_061207

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intervla-m1/simple/G1WholebodyXMovePickTeleop-v0/20260404_061741/config.yaml

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+run_id: G1WholebodyXMovePick
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+      norm_type: ada_norm
+      num_attention_heads: 32
+      num_layers: 16
+      output_dim: 1024
+      positional_embeddings: null
+datasets:
+  vlm_data:
+    dataset_py: vlm_datasets
+    dataformat: llava_json
+    dataset_use: asv2_conversation_en,asv2_detailed_description_en,asv2_region_captioning_en,coco_internvl_longcap_en,coco_karpathy_train_567_en,coco_negative_gpt4o_en,coco_poetry_zh,coco_rem_en_zh,cocorem_exist_yorn_en,cocotextv2_en,cocotextv2_gpt4o_en,okvqa_en,refcoco_grounding_aug_en,refcoco_grounding_en,tallyqa_coco_en,toloka_grounding_aug_en,vqav2_en,vsr_en
+    eval_dataset: aokvqa_cauldron_llava_format
+    data_flatten: false
+    base_interval: 2
+    max_pixels: 50176
+    min_pixels: 784
+    model_max_length: 2048
+    model_type: qwen2.5vl
+    per_device_batch_size: 4
+  vla_data:
+    dataset_py: lerobot_datasets
+    data_root_dir: /hfm/jliu/simple/G1WholebodyXMovePick-v0
+    data_mix: humanoid_
+    action_type: abs_joints
+    CoT_prompt: Your task is {instruction}. To identify the key objects for your task.
+      Locate their bounding boxes in [x1,y1,x2,y2] format.
+    CoT_answer: bbox
+    default_image_resolution:
+    - 3
+    - 224
+    - 224
+    per_device_batch_size: 64
+    preload_all: true
+    load_all_data_for_training: true
+    obs:
+    - image_0
+    image_size:
+    - 224
+    - 224
+trainer:
+  epochs: 100
+  max_train_steps: 40000
+  num_warmup_steps: 0
+  save_interval: 10000
+  eval_interval: 100
+  learning_rate:
+    base: 5.0e-05
+    qwen_vl_interface: 1.0e-05
+    action_model: 0.0001
+  lr_scheduler_type: cosine_with_min_lr
+  scheduler_specific_kwargs:
+    min_lr: 5.0e-07
+  freeze_modules: qwen_vl_interface,layer_qformer,dino_encoder,dino_pro
+  loss_scale:
+    vla: 1.0
+    vlm: 0.1
+  pretrained_checkpoint: /hfm/cache/checkpoints/InternVLA-M1-Pretrain-RT-1-Bridge/checkpoints/steps_50000_pytorch_model.pt
+  skip_reload_modules: action_model
+  repeated_diffusion_steps: 4
+  max_grad_norm: 1.0
+  warmup_ratio: 0.1
+  weight_decay: 0.0
+  logging_frequency: 10
+  gradient_clipping: 1.0
+  gradient_accumulation_steps: 1
+  optimizer:
+    name: AdamW
+    betas:
+    - 0.9
+    - 0.95
+    eps: 1.0e-08
+    weight_decay: 1.0e-08
+  is_resume: false
+  resume_epoch: null
+  resume_step: null
+  enable_gradient_checkpointing: true
+  enable_mixed_precision_training: true
+output_dir: runs/InternVLA/Checkpoints/G1WholebodyXMovePick/20260404_061741

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intervla-m1/simple/G1WholebodyXMovePickTeleop-v0/20260404_061741/summary.jsonl

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