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 # Video files - compressed
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 *.webm filter=lfs diff=lfs merge=lfs -text
+results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/wandb/wandb/run-20260526_144054-tqzhomyu/run-tqzhomyu.wandb filter=lfs diff=lfs merge=lfs -text

results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/checkpoints/steps_2000_lora_adapter/README.md

@@ -0,0 +1,206 @@
+---
+base_model: /workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action
+library_name: peft
+tags:
+- base_model:adapter:/workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.19.1

results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/checkpoints/steps_2000_lora_adapter/action_model.pt

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+size 131292897

results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/checkpoints/steps_2000_lora_adapter/adapter_config.json

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+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Qwen3VLForConditionalGeneration",
+    "parent_library": "transformers.models.qwen3_vl.modeling_qwen3_vl"
+  },
+  "base_model_name_or_path": "/workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 64,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.19.1",
+  "qalora_group_size": 16,
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "attn.proj",
+    "up_proj",
+    "down_proj",
+    "o_proj",
+    "linear_fc1",
+    "linear_fc2",
+    "gate_proj",
+    "k_proj",
+    "q_proj",
+    "v_proj",
+    "qkv"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/checkpoints/steps_2000_lora_adapter/adapter_model.safetensors

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results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/config.full.yaml

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+rl_games:
+  task: deadly_corridor
+  model_alias: openvla
+  env_eval:
+    enabled: false
+    interval_steps: 100
+    num_episodes: 5
+    max_episode_steps: 2000
+    frameskip: 4
+    image_size: 84
+    deadly:
+      action_layout: factorized_11
+    latency:
+      mode: single
+      values:
+      - 0
+      prompt_map_path: /workspace/playground/Datasets/rl_games/deadly_corridor_fixed_l2_fs4/latency_prompt_map.json
+    mid_train:
+      enabled: false
+      interval_steps: 100
+      latencies:
+      - 0
+      num_episodes: 5
+      max_steps_per_episode: 2000
+    post_train:
+      enabled: false
+      latencies:
+      - 0
+      num_episodes: 5
+      max_steps_per_episode: 2000
+framework:
+  name: QwenOFT
+  qwenvl:
+    base_vlm: /workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action
+    attn_implementation: flash_attention_2
+    enable_gradient_checkpointing: true
+    lora:
+      enabled: true
+      r: 32
+      alpha: 64
+      dropout: 0.05
+      target_modules: all-linear
+      bias: none
+  action_model:
+    action_model_type: MLP
+    action_dim: 11
+    action_hidden_dim: 2560
+    future_action_window_size: 0
+    past_action_window_size: 0
+    loss_type: factorized_ce
+    action_env_dim: 11
+    state_dim: 1
+    action_horizon: 1
+trainer:
+  learning_rate:
+    base: 2.0e-05
+    action_model: 0.0001
+    qwen_vl_interface: 1.0e-05
+  max_train_steps: 2000
+  num_warmup_steps: 100
+  save_interval: 100
+  eval_interval: 100
+  eval_num_batches: 20
+  lr_scheduler_type: cosine_with_min_lr
+  scheduler_specific_kwargs:
+    min_lr: 1.0e-06
+  freeze_modules: ''
+  loss_scale:
+    vla: 1.0
+    vlm: 0.1
+  max_grad_norm: 1.0
+  weight_decay: 0.0
+  logging_frequency: 10
+  gradient_clipping: 1.0
+  gradient_accumulation_steps: 4
+  distributed_backend: deepspeed
+  is_resume: false
+  pretrained_checkpoint: null
+  resume_step: 0
+  reload_modules: null
+  optimizer:
+    betas:
+    - 0.9
+    - 0.95
+    eps: 1.0e-08
+    weight_decay: 1.0e-08
+    fused: false
+  save_format: pt
+datasets:
+  vla_data:
+    data_mix: deadly_corridor_fixed_l2_fs4
+    dataset_py: lerobot_datasets
+    include_state: false
+    data_root_dir: /workspace/playground/Datasets/rl_games
+    eval_data_mix: deadly_corridor_fixed_l2_fs4__val
+    action_type: discrete
+    sequential_step_sampling: false
+    per_device_batch_size: 16
+    load_all_data_for_training: true
+    obs_image_size:
+    - 224
+    - 224
+    video_backend: torchvision_av
+checkpoint:
+  local:
+    keep_last_n: 3
+  sync:
+    enabled: false
+    repo_id: null
+    keep_last_n: 0
+    sync_every_n_checkpoints: 1
+    resume_policy: local_latest
+run_id: openvla_deadly_corridor
+run_root_dir: /workspace/results/Checkpoints
+output_dir: /workspace/results/Checkpoints/openvla_deadly_corridor
+config_yaml: null
+seed: 42
+wandb_entity: saberrr-zju
+wandb_project: starVLA_rl_games
+is_debug: false
+version_id: '0.21'

results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/config.yaml

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+checkpoint:
+  local:
+    keep_last_n: 3
+  sync:
+    enabled: false
+    keep_last_n: 0
+    repo_id: null
+datasets:
+  vla_data:
+    data_mix: deadly_corridor_fixed_l2_fs4
+    dataset_py: lerobot_datasets
+    eval_data_mix: deadly_corridor_fixed_l2_fs4__val
+    include_state: false
+    obs_image_size:
+    - 224
+    - 224
+    per_device_batch_size: 16
+framework:
+  action_model:
+    action_dim: 11
+    action_hidden_dim: 2560
+    action_horizon: 1
+    action_model_type: MLP
+    loss_type: factorized_ce
+  name: QwenOFT
+  qwenvl:
+    attn_implementation: flash_attention_2
+    base_vlm: /workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action
+    enable_gradient_checkpointing: true
+    lora:
+      alpha: 64
+      bias: none
+      dropout: 0.05
+      enabled: true
+      r: 32
+      target_modules: all-linear
+output_dir: /workspace/results/Checkpoints/openvla_deadly_corridor
+rl_games:
+  env_eval:
+    enabled: false
+run_id: openvla_deadly_corridor
+run_root_dir: /workspace/results/Checkpoints
+seed: 42
+trainer:
+  eval_interval: 100
+  eval_num_batches: 20
+  freeze_modules: ''
+  is_resume: false
+  learning_rate:
+    action_model: 0.0001
+    base: 2.0e-05
+    qwen_vl_interface: 1.0e-05
+  logging_frequency: 10
+  lr_scheduler_type: cosine_with_min_lr
+  max_train_steps: 2000
+  num_warmup_steps: 100
+  optimizer:
+    betas:
+    - 0.9
+    - 0.95
+    eps: 1.0e-08
+    fused: false
+    weight_decay: 1.0e-08
+  pretrained_checkpoint: null
+  save_format: pt
+  save_interval: 100
+  scheduler_specific_kwargs:
+    min_lr: 1.0e-06
+wandb_entity: saberrr-zju
+wandb_project: starVLA_rl_games

results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/dataset_statistics.json

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results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/dataset_statistics_eval.json

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results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/final_model/README.md

@@ -0,0 +1,206 @@
+---
+base_model: /workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action
+library_name: peft
+tags:
+- base_model:adapter:/workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.19.1

results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/final_model/action_model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:11fdc8037a118eb54ffe882b3ab00d256ed9e8160d4edd4af8819b35c689a0ee
+size 131292897

results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/final_model/adapter_config.json

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+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Qwen3VLForConditionalGeneration",
+    "parent_library": "transformers.models.qwen3_vl.modeling_qwen3_vl"
+  },
+  "base_model_name_or_path": "/workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 64,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.19.1",
+  "qalora_group_size": 16,
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "attn.proj",
+    "up_proj",
+    "down_proj",
+    "o_proj",
+    "linear_fc1",
+    "linear_fc2",
+    "gate_proj",
+    "k_proj",
+    "q_proj",
+    "v_proj",
+    "qkv"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/final_model/adapter_model.safetensors

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+oid sha256:5b3921e9fb66d8a8b5cb0196365cabae9989bca7b6769b75c276e5134c1f7ed6
+size 161192096

results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/hydra/.hydra/config.yaml

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+rl_games:
+  task: deadly_corridor
+  model_alias: openvla
+  env_eval:
+    enabled: false
+    interval_steps: 100
+    num_episodes: 5
+    max_episode_steps: 2000
+    frameskip: 4
+    image_size: 84
+    deadly:
+      action_layout: factorized_11
+    latency:
+      mode: single
+      values:
+      - 0
+      prompt_map_path: /workspace/playground/Datasets/rl_games/deadly_corridor_fixed_l2_fs4/latency_prompt_map.json
+    mid_train:
+      enabled: false
+      interval_steps: 100
+      latencies:
+      - 0
+      num_episodes: 5
+      max_steps_per_episode: 2000
+    post_train:
+      enabled: false
+      latencies:
+      - 0
+      num_episodes: 5
+      max_steps_per_episode: 2000
+framework:
+  name: QwenOFT
+  qwenvl:
+    enable_gradient_checkpointing: true
+    base_vlm: /workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action
+    attn_implementation: flash_attention_2
+    lora:
+      enabled: true
+      r: 32
+      alpha: 64
+      dropout: 0.05
+      target_modules: all-linear
+      bias: none
+  action_model:
+    action_dim: 2
+    action_env_dim: 2
+    action_model_type: MLP
+    state_dim: 1
+    action_horizon: 1
+    future_action_window_size: 0
+    past_action_window_size: 0
+    loss_type: factorized_ce
+trainer:
+  learning_rate:
+    base: 2.0e-05
+    action_model: 0.0001
+    qwen_vl_interface: 1.0e-05
+  max_train_steps: 2000
+  num_warmup_steps: 100
+  save_interval: 100
+  eval_interval: 100
+  eval_num_batches: 20
+  lr_scheduler_type: cosine_with_min_lr
+  scheduler_specific_kwargs:
+    min_lr: 1.0e-06
+  freeze_modules: ''
+  loss_scale:
+    vla: 1.0
+    vlm: 0.1
+  max_grad_norm: 1.0
+  weight_decay: 0.0
+  logging_frequency: 10
+  gradient_clipping: 1.0
+  gradient_accumulation_steps: 4
+  distributed_backend: deepspeed
+  is_resume: false
+  pretrained_checkpoint: null
+  resume_step: 0
+  reload_modules: null
+  optimizer:
+    betas:
+    - 0.9
+    - 0.95
+    eps: 1.0e-08
+    weight_decay: 1.0e-08
+    fused: false
+  save_format: pt
+datasets:
+  vla_data:
+    data_mix: deadly_corridor_fixed_l2_fs4
+    dataset_py: lerobot_datasets
+    include_state: false
+    data_root_dir: /workspace/playground/Datasets/rl_games
+    eval_data_mix: deadly_corridor_fixed_l2_fs4__val
+    action_type: discrete
+    sequential_step_sampling: false
+    per_device_batch_size: 16
+    load_all_data_for_training: true
+    obs_image_size:
+    - 224
+    - 224
+    video_backend: torchvision_av
+checkpoint:
+  local:
+    keep_last_n: 3
+  sync:
+    enabled: false
+    repo_id: null
+    keep_last_n: 0
+    sync_every_n_checkpoints: 1
+    resume_policy: local_latest
+run_id: openvla_deadly_corridor
+run_root_dir: /workspace/results/Checkpoints
+output_dir: null
+config_yaml: null
+seed: 42
+wandb_entity: saberrr-zju
+wandb_project: starVLA_rl_games
+is_debug: false
+version_id: '0.21'

results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/hydra/.hydra/hydra.yaml

@@ -0,0 +1,218 @@
+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=openvla
+    - env=deadly_corridor
+    - mode=single
+    - run_root_dir=/workspace/results/Checkpoints
+    - checkpoint.local.keep_last_n=3
+    - checkpoint.sync.enabled=false
+    - checkpoint.sync.keep_last_n=0
+    - datasets.vla_data.action_type=discrete
+    - datasets.vla_data.load_all_data_for_training=true
+    - datasets.vla_data.obs_image_size=[224,224]
+    - datasets.vla_data.per_device_batch_size=16
+    - datasets.vla_data.sequential_step_sampling=false
+    - datasets.vla_data.video_backend=torchvision_av
+    - framework.action_model.loss_type=factorized_ce
+    - rl_games.env_eval.deadly.action_layout=factorized_11
+    - rl_games.env_eval.enabled=false
+    - rl_games.env_eval.frameskip=4
+    - rl_games.env_eval.image_size=84
+    - 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.max_steps_per_episode=2000
+    - rl_games.env_eval.mid_train.num_episodes=5
+    - rl_games.env_eval.post_train.enabled=false
+    - rl_games.env_eval.post_train.latencies=[0]
+    - rl_games.env_eval.post_train.max_steps_per_episode=2000
+    - rl_games.env_eval.post_train.num_episodes=5
+    - rl_games.model_alias=openvla
+    - rl_games.task=deadly_corridor
+    - run_id=openvla_deadly_corridor
+    - seed=42
+    - trainer.eval_interval=100
+    - trainer.eval_num_batches=20
+    - trainer.gradient_accumulation_steps=4
+    - trainer.gradient_clipping=1.0
+    - trainer.learning_rate.action_model=0.0001
+    - trainer.learning_rate.base=2e-05
+    - trainer.learning_rate.qwen_vl_interface=1e-05
+    - trainer.logging_frequency=10
+    - 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=2000
+    - trainer.num_warmup_steps=100
+    - trainer.save_format=pt
+    - trainer.save_interval=100
+    - trainer.scheduler_specific_kwargs.min_lr=1e-06
+    - trainer.weight_decay=0.0
+    - wandb_entity=saberrr-zju
+    - wandb_project=starVLA_rl_games
+    - datasets.vla_data.data_root_dir=/workspace/playground/Datasets/rl_games
+    - datasets.vla_data.data_mix=deadly_corridor_fixed_l2_fs4
+    - datasets.vla_data.eval_data_mix=deadly_corridor_fixed_l2_fs4__val
+    - framework.qwenvl.base_vlm=/workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action
+    - rl_games.env_eval.latency.prompt_map_path=/workspace/playground/Datasets/rl_games/deadly_corridor_fixed_l2_fs4/latency_prompt_map.json
+    - trainer.is_resume=false
+  job:
+    name: train_starvla_hydra
+    chdir: false
+    override_dirname: checkpoint.local.keep_last_n=3,checkpoint.sync.enabled=false,checkpoint.sync.keep_last_n=0,datasets.vla_data.action_type=discrete,datasets.vla_data.data_mix=deadly_corridor_fixed_l2_fs4,datasets.vla_data.data_root_dir=/workspace/playground/Datasets/rl_games,datasets.vla_data.eval_data_mix=deadly_corridor_fixed_l2_fs4__val,datasets.vla_data.load_all_data_for_training=true,datasets.vla_data.obs_image_size=[224,224],datasets.vla_data.per_device_batch_size=16,datasets.vla_data.sequential_step_sampling=false,datasets.vla_data.video_backend=torchvision_av,env=deadly_corridor,framework.action_model.loss_type=factorized_ce,framework.qwenvl.base_vlm=/workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action,mode=single,model=openvla,rl_games.env_eval.deadly.action_layout=factorized_11,rl_games.env_eval.enabled=false,rl_games.env_eval.frameskip=4,rl_games.env_eval.image_size=84,rl_games.env_eval.latency.mode=single,rl_games.env_eval.latency.prompt_map_path=/workspace/playground/Datasets/rl_games/deadly_corridor_fixed_l2_fs4/latency_prompt_map.json,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.max_steps_per_episode=2000,rl_games.env_eval.mid_train.num_episodes=5,rl_games.env_eval.post_train.enabled=false,rl_games.env_eval.post_train.latencies=[0],rl_games.env_eval.post_train.max_steps_per_episode=2000,rl_games.env_eval.post_train.num_episodes=5,rl_games.model_alias=openvla,rl_games.task=deadly_corridor,run_id=openvla_deadly_corridor,run_root_dir=/workspace/results/Checkpoints,seed=42,trainer.eval_interval=100,trainer.eval_num_batches=20,trainer.gradient_accumulation_steps=4,trainer.gradient_clipping=1.0,trainer.is_resume=false,trainer.learning_rate.action_model=0.0001,trainer.learning_rate.base=2e-05,trainer.learning_rate.qwen_vl_interface=1e-05,trainer.logging_frequency=10,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=2000,trainer.num_warmup_steps=100,trainer.save_format=pt,trainer.save_interval=100,trainer.scheduler_specific_kwargs.min_lr=1e-06,trainer.weight_decay=0.0,wandb_entity=saberrr-zju,wandb_project=starVLA_rl_games
+    id: ???
+    num: ???
+    config_name: train
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.1'
+    cwd: /workspace/latency-sensitive-bench/starVLA
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /workspace/latency-sensitive-bench/starVLA/examples/rl_games/config
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /workspace/results/Checkpoints/openvla_deadly_corridor/hydra
+    choices:
+      checkpoint: default
+      mode: single
+      env: deadly_corridor
+      model: openvla
+      base: common
+      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

results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/hydra/.hydra/overrides.yaml

@@ -0,0 +1,59 @@
+- model=openvla
+- env=deadly_corridor
+- mode=single
+- run_root_dir=/workspace/results/Checkpoints
+- checkpoint.local.keep_last_n=3
+- checkpoint.sync.enabled=false
+- checkpoint.sync.keep_last_n=0
+- datasets.vla_data.action_type=discrete
+- datasets.vla_data.load_all_data_for_training=true
+- datasets.vla_data.obs_image_size=[224,224]
+- datasets.vla_data.per_device_batch_size=16
+- datasets.vla_data.sequential_step_sampling=false
+- datasets.vla_data.video_backend=torchvision_av
+- framework.action_model.loss_type=factorized_ce
+- rl_games.env_eval.deadly.action_layout=factorized_11
+- rl_games.env_eval.enabled=false
+- rl_games.env_eval.frameskip=4
+- rl_games.env_eval.image_size=84
+- 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.max_steps_per_episode=2000
+- rl_games.env_eval.mid_train.num_episodes=5
+- rl_games.env_eval.post_train.enabled=false
+- rl_games.env_eval.post_train.latencies=[0]
+- rl_games.env_eval.post_train.max_steps_per_episode=2000
+- rl_games.env_eval.post_train.num_episodes=5
+- rl_games.model_alias=openvla
+- rl_games.task=deadly_corridor
+- run_id=openvla_deadly_corridor
+- seed=42
+- trainer.eval_interval=100
+- trainer.eval_num_batches=20
+- trainer.gradient_accumulation_steps=4
+- trainer.gradient_clipping=1.0
+- trainer.learning_rate.action_model=0.0001
+- trainer.learning_rate.base=2e-05
+- trainer.learning_rate.qwen_vl_interface=1e-05
+- trainer.logging_frequency=10
+- 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=2000
+- trainer.num_warmup_steps=100
+- trainer.save_format=pt
+- trainer.save_interval=100
+- trainer.scheduler_specific_kwargs.min_lr=1e-06
+- trainer.weight_decay=0.0
+- wandb_entity=saberrr-zju
+- wandb_project=starVLA_rl_games
+- datasets.vla_data.data_root_dir=/workspace/playground/Datasets/rl_games
+- datasets.vla_data.data_mix=deadly_corridor_fixed_l2_fs4
+- datasets.vla_data.eval_data_mix=deadly_corridor_fixed_l2_fs4__val
+- framework.qwenvl.base_vlm=/workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action
+- rl_games.env_eval.latency.prompt_map_path=/workspace/playground/Datasets/rl_games/deadly_corridor_fixed_l2_fs4/latency_prompt_map.json
+- trainer.is_resume=false

results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/summary.jsonl

@@ -0,0 +1,77 @@
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results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/wandb/wandb/run-20260526_144054-tqzhomyu/files/config.yaml

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+_wandb:
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+        e:
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+                    - train
+                    - model=openvla
+                    - env=deadly_corridor
+                    - mode=single
+                    - run_root_dir=/workspace/results/Checkpoints
+                    - checkpoint.local.keep_last_n=3
+                    - checkpoint.sync.enabled=false
+                    - checkpoint.sync.keep_last_n=0
+                    - datasets.vla_data.action_type=discrete
+                    - datasets.vla_data.load_all_data_for_training=true
+                    - datasets.vla_data.obs_image_size=[224,224]
+                    - datasets.vla_data.per_device_batch_size=16
+                    - datasets.vla_data.sequential_step_sampling=false
+                    - datasets.vla_data.video_backend=torchvision_av
+                    - framework.action_model.loss_type=factorized_ce
+                    - rl_games.env_eval.deadly.action_layout=factorized_11
+                    - rl_games.env_eval.enabled=false
+                    - rl_games.env_eval.frameskip=4
+                    - rl_games.env_eval.image_size=84
+                    - 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.max_steps_per_episode=2000
+                    - rl_games.env_eval.mid_train.num_episodes=5
+                    - rl_games.env_eval.post_train.enabled=false
+                    - rl_games.env_eval.post_train.latencies=[0]
+                    - rl_games.env_eval.post_train.max_steps_per_episode=2000
+                    - rl_games.env_eval.post_train.num_episodes=5
+                    - rl_games.model_alias=openvla
+                    - rl_games.task=deadly_corridor
+                    - run_id=openvla_deadly_corridor
+                    - seed=42
+                    - trainer.eval_interval=100
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+                    - trainer.learning_rate.base=2e-05
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+                    - trainer.logging_frequency=10
+                    - trainer.loss_scale.vla=1.0
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+                    - trainer.save_format=pt
+                    - trainer.save_interval=100
+                    - trainer.scheduler_specific_kwargs.min_lr=1e-06
+                    - trainer.weight_decay=0.0
+                    - wandb_entity=saberrr-zju
+                    - wandb_project=starVLA_rl_games
+                    - datasets.vla_data.data_root_dir=/workspace/playground/Datasets/rl_games
+                    - datasets.vla_data.data_mix=deadly_corridor_fixed_l2_fs4
+                    - datasets.vla_data.eval_data_mix=deadly_corridor_fixed_l2_fs4__val
+                    - framework.qwenvl.base_vlm=/workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action
+                    - rl_games.env_eval.latency.prompt_map_path=/workspace/playground/Datasets/rl_games/deadly_corridor_fixed_l2_fs4/latency_prompt_map.json
+                    - trainer.is_resume=false
+                codePath: starVLA/training/train_starvla_hydra.py
+                codePathLocal: starVLA/training/train_starvla_hydra.py
+                cpu_count: 20
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+                email: lxy1501454486@gmail.com
+                executable: /venv/starvla_rl_games_openvla/bin/python
+                git:
+                    commit: a35419bba1b5652fbe62ab31839e7ebc81bbf384
+                    remote: git@github.com:talha1503/starVLA.git
+                gpu: NVIDIA RTX PRO 6000 Blackwell Workstation Edition
+                gpu_count: 2
+                gpu_nvidia:
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+                      memoryTotal: "102641958912"
+                      name: NVIDIA RTX PRO 6000 Blackwell Workstation Edition
+                      uuid: GPU-2fbc2113-cbb0-c835-8c29-5bf04b8a69be
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+                      memoryTotal: "102641958912"
+                      name: NVIDIA RTX PRO 6000 Blackwell Workstation Edition
+                      uuid: GPU-8175e2dd-089c-eeea-9974-3685c7a9d61a
+                host: a8e0be9242c0
+                memory:
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+                os: Linux-6.17.0-29-generic-x86_64-with-glibc2.39
+                program: /workspace/latency-sensitive-bench/starVLA/starVLA/training/train_starvla_hydra.py
+                python: CPython 3.10.20
+                root: /workspace/results/Checkpoints/openvla_deadly_corridor/wandb
+                startedAt: "2026-05-26T14:40:54.374047Z"
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results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/wandb/wandb/run-20260526_144054-tqzhomyu/files/requirements.txt

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results/Checkpoints/jitter_deconstruction_openvla_deadly_corridor_ce/wandb/wandb/run-20260526_144054-tqzhomyu/files/wandb-metadata.json

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+    "datasets.vla_data.action_type=discrete",
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+    "datasets.vla_data.obs_image_size=[224,224]",
+    "datasets.vla_data.per_device_batch_size=16",
+    "datasets.vla_data.sequential_step_sampling=false",
+    "datasets.vla_data.video_backend=torchvision_av",
+    "framework.action_model.loss_type=factorized_ce",
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+    "rl_games.env_eval.enabled=false",
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+    "rl_games.env_eval.image_size=84",
+    "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]",
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+    "rl_games.env_eval.mid_train.num_episodes=5",
+    "rl_games.env_eval.post_train.enabled=false",
+    "rl_games.env_eval.post_train.latencies=[0]",
+    "rl_games.env_eval.post_train.max_steps_per_episode=2000",
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+    "rl_games.model_alias=openvla",
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+    "framework.qwenvl.base_vlm=/workspace/playground/Pretrained_models/Qwen3-VL-4B-Instruct-Action",
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