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.gitattributes

@@ -40,3 +40,5 @@ franka_sweep_floor_baseline_QwenOFT/wandb/wandb/run-20260222_125235-th5wsk93/run
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 franka_move_egg_baseline_QwenOFT/wandb/wandb/run-20260225_193458-yw4zdlvv/run-yw4zdlvv.wandb filter=lfs diff=lfs merge=lfs -text
+franka_pick_color_egg_baseline_QwenOFT/wandb/wandb/run-20260224_085210-l9c0lagn/run-l9c0lagn.wandb filter=lfs diff=lfs merge=lfs -text
+franka_pick_color_egg_baseline_QwenOFT/wandb/wandb/run-20260226_150531-tc42wzfv/run-tc42wzfv.wandb filter=lfs diff=lfs merge=lfs -text

franka_move_egg_baseline_QwenOFT/wandb/wandb/run-20260225_193458-yw4zdlvv/logs/debug-core.log

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franka_pick_color_egg_baseline_QwenOFT/checkpoints/steps_10000_pytorch_model.pt

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franka_pick_color_egg_baseline_QwenOFT/checkpoints/steps_20000_pytorch_model.pt

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franka_pick_color_egg_baseline_QwenOFT/config.yaml

@@ -0,0 +1,51 @@
+datasets:
+  vla_data:
+    CoT_prompt: Your task is {instruction}. To identify the key objects for your task.
+      Locate their bounding boxes in [x1,y1,x2,y2] format.
+    data_mix: smartmore_franka_pick_color_egg
+    data_root_dir: /gpfs/wangzixuan/visual_prompting/real_data/lerobot
+    dataset_py: lerobot_datasets
+    image_size:
+    - 224
+    - 224
+    per_device_batch_size: 32
+    video_backend: pyav
+framework:
+  action_model:
+    action_dim: 7
+    action_hidden_dim: 2560
+    action_model_type: DiT-B
+    future_action_window_size: 15
+    past_action_window_size: 0
+  name: QwenOFT
+  qwenvl:
+    base_vlm: /gpfs/wangzixuan/visual_prompting/starVLA_robocasa/playground/Pretrained_models/Qwen3-VL-4B-Instruct
+output_dir: /gpfs/wangzixuan/visual_prompting/starVLA_robocasa/playground/Checkpoints/franka_pick_color_egg_baseline_QwenOFT
+run_id: franka_pick_color_egg_baseline_QwenOFT
+run_root_dir: /gpfs/wangzixuan/visual_prompting/starVLA_robocasa/playground/Checkpoints
+seed: 42
+trainer:
+  eval_interval: 100
+  freeze_modules: null
+  gradient_accumulation_steps: 1
+  gradient_clipping: 1.0
+  is_resume: false
+  learning_rate:
+    action_model: 0.0001
+    base: 3.0e-05
+    qwen_vl_interface: 1.0e-05
+  logging_frequency: 10
+  lr_scheduler_type: cosine_with_min_lr
+  max_train_steps: 100000
+  num_warmup_steps: 5000
+  optimizer:
+    betas:
+    - 0.9
+    - 0.95
+    eps: 1.0e-08
+    weight_decay: 1.0e-08
+  save_interval: 10000
+  scheduler_specific_kwargs:
+    min_lr: 5.0e-07
+wandb_entity: zwanggk
+wandb_project: franka_baseline

franka_pick_color_egg_baseline_QwenOFT/dataset_statistics.json

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+{
+  "franka": {
+    "action": {
+      "mean": [
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+        0.014874552376568317,
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+        true,
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+      ]
+    },
+    "state": {
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+    "num_trajectories": 200
+  }
+}

franka_pick_color_egg_baseline_QwenOFT/run_franka_baseline_pick_color_egg.sh

@@ -0,0 +1,54 @@
+#!/bin/bash
+# Baseline Training Script for Franka - pick_color_egg (no visual prompts)
+
+export NCCL_SOCKET_IFNAME=bond0
+export NCCL_IB_HCA=mlx5_2,mlx5_3
+
+export NCCL_BLOCKING_WAIT=1
+export NCCL_ASYNC_ERROR_HANDLING=1
+export TORCH_NCCL_BLOCKING_WAIT=1
+export TORCH_NCCL_ASYNC_ERROR_HANDLING=1
+
+export NCCL_TIMEOUT=3600
+export TORCH_DISTRIBUTED_DEBUG=DETAIL
+
+Framework_name=QwenOFT
+base_vlm=/gpfs/wangzixuan/visual_prompting/starVLA_robocasa/playground/Pretrained_models/Qwen3-VL-4B-Instruct
+freeze_module_list=''
+DIT_TYPE="DiT-B"
+
+# Data paths
+data_root_dir=/gpfs/wangzixuan/visual_prompting/real_data/lerobot
+data_mix=smartmore_franka_pick_color_egg
+
+# Output
+run_root_dir=/gpfs/wangzixuan/visual_prompting/starVLA_robocasa/playground/Checkpoints
+run_id=franka_pick_color_egg_baseline_QwenOFT
+
+output_dir=${run_root_dir}/${run_id}
+mkdir -p ${output_dir}
+cp $0 ${output_dir}/
+
+accelerate launch \
+  --config_file starVLA/config/deepseeds/deepspeed_zero2.yaml \
+  --num_processes 8 \
+  starVLA/training/train_starvla.py \
+  --config_yaml ./examples/Franka/train_files/starvla_cotrain_franka.yaml \
+  --framework.name ${Framework_name} \
+  --framework.qwenvl.base_vlm ${base_vlm} \
+  --framework.action_model.action_model_type ${DIT_TYPE} \
+  --datasets.vla_data.data_root_dir ${data_root_dir} \
+  --datasets.vla_data.data_mix ${data_mix} \
+  --datasets.vla_data.per_device_batch_size 32 \
+  --datasets.vla_data.video_backend pyav \
+  --trainer.freeze_modules "${freeze_module_list}" \
+  --trainer.max_train_steps 100000 \
+  --trainer.save_interval 10000 \
+  --trainer.logging_frequency 10 \
+  --trainer.eval_interval 100 \
+  --trainer.learning_rate.base 3e-5 \
+  --trainer.learning_rate.qwen_vl_interface 1e-5 \
+  --run_root_dir ${run_root_dir} \
+  --run_id ${run_id} \
+  --wandb_project franka_baseline \
+  --wandb_entity zwanggk

franka_pick_color_egg_baseline_QwenOFT/summary.jsonl

@@ -0,0 +1,5 @@
+{"steps": 10000}
+{"steps": 20000}
+{"steps": 30000}
+{"steps": 40000}
+{"steps": 50000}

franka_pick_color_egg_baseline_QwenOFT/wandb/wandb/debug-internal.log

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+{"time":"2026-02-26T22:49:34.520495266Z","level":"INFO","msg":"api: retrying HTTP error","status":502,"url":"https://api.wandb.ai/files/zwanggk/franka_baseline/tc42wzfv/file_stream","body":"\n<html><head>\n<meta http-equiv=\"content-type\" content=\"text/html;charset=utf-8\">\n<title>502 Server Error</title>\n</head>\n<body text=#000000 bgcolor=#ffffff>\n<h1>Error: Server Error</h1>\n<h2>The server encountered a temporary error and could not complete your request.<p>Please try again in 30 seconds.</h2>\n<h2></h2>\n</body></html>\n"}
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franka_pick_color_egg_baseline_QwenOFT/wandb/wandb/debug.log

@@ -0,0 +1 @@
+2026-02-27 06:00:18,840 INFO    wandb-AsyncioManager-main:2996879 [service_client.py:_forward_responses():80] Reached EOF.

franka_pick_color_egg_baseline_QwenOFT/wandb/wandb/run-20260224_085210-l9c0lagn/files/config.yaml

@@ -0,0 +1,139 @@
+_wandb:
+    value:
+        cli_version: 0.24.0
+        e:
+            ynp9xtzyf8b9lkst91pz3g9ztf7t6p9h:
+                args:
+                    - --config_yaml
+                    - ./examples/Franka/train_files/starvla_cotrain_franka.yaml
+                    - --framework.name
+                    - QwenOFT
+                    - --framework.qwenvl.base_vlm
+                    - /gpfs/wangzixuan/visual_prompting/starVLA_robocasa/playground/Pretrained_models/Qwen3-VL-4B-Instruct
+                    - --framework.action_model.action_model_type
+                    - DiT-B
+                    - --datasets.vla_data.data_root_dir
+                    - /gpfs/wangzixuan/visual_prompting/real_data/lerobot
+                    - --datasets.vla_data.data_mix
+                    - smartmore_franka_pick_color_egg
+                    - --datasets.vla_data.per_device_batch_size
+                    - "32"
+                    - --datasets.vla_data.video_backend
+                    - pyav
+                    - --trainer.freeze_modules
+                    - ""
+                    - --trainer.max_train_steps
+                    - "100000"
+                    - --trainer.save_interval
+                    - "10000"
+                    - --trainer.logging_frequency
+                    - "10"
+                    - --trainer.eval_interval
+                    - "100"
+                    - --trainer.learning_rate.base
+                    - "3e-5"
+                    - --trainer.learning_rate.qwen_vl_interface
+                    - "1e-5"
+                    - --run_root_dir
+                    - /gpfs/wangzixuan/visual_prompting/starVLA_robocasa/playground/Checkpoints
+                    - --run_id
+                    - franka_pick_color_egg_baseline_QwenOFT
+                    - --wandb_project
+                    - franka_baseline
+                    - --wandb_entity
+                    - zwanggk
+                codePath: starVLA_robocasa/starVLA/training/train_starvla.py
+                codePathLocal: starVLA/training/train_starvla.py
+                cpu_count: 96
+                cpu_count_logical: 192
+                cudaVersion: "12.5"
+                disk:
+                    /:
+                        total: "942793330688"
+                        used: "717125599232"
+                email: zwanggk@connect.ust.hk
+                executable: /gpfs/wangzixuan/conda_envs/starVLA-Robocasa/bin/python3.10
+                git:
+                    commit: c53a6c11679f38afa4bb3de09d8c540d11f8a500
+                    remote: https://github.com/Vincent2311/visual_prompting.git
+                gpu: NVIDIA H200
+                gpu_count: 8
+                gpu_nvidia:
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-397bd6b3-e89a-bb71-4bfc-ba5495d359da
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-f2b4af4a-fd61-2b16-7b54-7f0e0926bdcd
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-d05fb150-dd47-8890-ece8-03205a09a8f3
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-3a893c22-7154-b9de-4ba6-86e87055c9a6
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-eea7d972-f9c2-0648-4d8a-845e6a2a74a7
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-ac8c17b6-1752-c9e9-533e-20e5cbd94678
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-7e924378-26a9-7f17-3eb5-8ab9d7910ad5
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-84d7dc9a-1673-019f-bf97-112e89cd64fa
+                host: C04-GPU-03-10U
+                memory:
+                    total: "2163973517312"
+                os: Linux-5.15.0-113-generic-x86_64-with-glibc2.35
+                program: /gpfs/wangzixuan/visual_prompting/starVLA_robocasa/starVLA/training/train_starvla.py
+                python: CPython 3.10.19
+                root: /gpfs/wangzixuan/visual_prompting/starVLA_robocasa/playground/Checkpoints/franka_pick_color_egg_baseline_QwenOFT/wandb
+                startedAt: "2026-02-24T08:52:10.562776Z"
+                writerId: ynp9xtzyf8b9lkst91pz3g9ztf7t6p9h
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franka_pick_color_egg_baseline_QwenOFT/wandb/wandb/run-20260224_085210-l9c0lagn/files/requirements.txt

@@ -0,0 +1,151 @@
+starVLA==1.0.1
+docstring_parser==0.17.0
+pydantic_core==2.27.2
+py-cpuinfo==9.0.0
+Werkzeug==3.1.5
+pandas==2.3.3
+kiwisolver==1.4.9
+httpcore==1.0.9
+nvidia-cuda-runtime-cu12==12.4.127
+Jinja2==3.1.6
+exceptiongroup==1.3.1
+filelock==3.20.3
+torchvision==0.21.0
+gitdb==4.0.12
+fastparquet==2024.11.0
+tensorboard==2.20.0
+portalocker==3.2.0
+timm==1.0.24
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+    "--datasets.vla_data.data_mix",
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+    "32",
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+                    - ./examples/Franka/train_files/starvla_cotrain_franka.yaml
+                    - --framework.name
+                    - QwenOFT
+                    - --framework.qwenvl.base_vlm
+                    - /gpfs/wangzixuan/visual_prompting/starVLA_robocasa/playground/Pretrained_models/Qwen3-VL-4B-Instruct
+                    - --framework.action_model.action_model_type
+                    - DiT-B
+                    - --datasets.vla_data.data_root_dir
+                    - /gpfs/wangzixuan/visual_prompting/real_data/lerobot
+                    - --datasets.vla_data.data_mix
+                    - smartmore_franka_pick_color_egg
+                    - --datasets.vla_data.per_device_batch_size
+                    - "32"
+                    - --datasets.vla_data.video_backend
+                    - pyav
+                    - --trainer.freeze_modules
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+                    - "3e-5"
+                    - --trainer.learning_rate.qwen_vl_interface
+                    - "1e-5"
+                    - --run_root_dir
+                    - /gpfs/wangzixuan/visual_prompting/starVLA_robocasa/playground/Checkpoints
+                    - --run_id
+                    - franka_pick_color_egg_baseline_QwenOFT
+                    - --wandb_project
+                    - franka_baseline
+                    - --wandb_entity
+                    - zwanggk
+                codePath: starVLA_robocasa/starVLA/training/train_starvla.py
+                codePathLocal: starVLA/training/train_starvla.py
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+                cudaVersion: "12.5"
+                disk:
+                    /:
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+                        used: "721955307520"
+                email: zwanggk@connect.ust.hk
+                executable: /gpfs/wangzixuan/conda_envs/starVLA-Robocasa/bin/python3.10
+                git:
+                    commit: c53a6c11679f38afa4bb3de09d8c540d11f8a500
+                    remote: https://github.com/Vincent2311/visual_prompting.git
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+                program: /gpfs/wangzixuan/visual_prompting/starVLA_robocasa/starVLA/training/train_starvla.py
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