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@@ -35,3 +35,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 checkpoints/wandb/wandb/run-20260316_073559-h1hybozy/run-h1hybozy.wandb filter=lfs diff=lfs merge=lfs -text
 checkpoints/wandb/wandb/run-20260316_085932-77uivys0/run-77uivys0.wandb filter=lfs diff=lfs merge=lfs -text
+checkpoints/pretrained_goal_2000step/wandb/wandb/run-20260316_073559-h1hybozy/run-h1hybozy.wandb filter=lfs diff=lfs merge=lfs -text

checkpoints/pretrained_goal_2000step/checkpoints/steps_1000_pytorch_model.pt

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checkpoints/pretrained_goal_2000step/checkpoints/steps_1500_pytorch_model.pt

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checkpoints/pretrained_goal_2000step/checkpoints/steps_2000_pytorch_model.pt

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checkpoints/pretrained_goal_2000step/checkpoints/steps_500_pytorch_model.pt

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checkpoints/pretrained_goal_2000step/config.yaml

@@ -0,0 +1,48 @@
+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: libero_90_t2_33_48
+    data_root_dir: playground/Datasets/LEROBOT_LIBERO_DATA
+    dataset_py: lerobot_datasets
+    per_device_batch_size: 1
+    sequential_step_sampling: false
+    video_backend: torchvision_av
+framework:
+  action_model:
+    action_dim: 7
+    future_action_window_size: 7
+    past_action_window_size: 0
+  name: QwenFast
+  qwenvl:
+    base_vlm: playground/Pretrained_models/Qwen2.5-VL-3B-Instruct-Action
+output_dir: ./results/Checkpoints/pretrained_goal_2000step
+run_id: pretrained_goal_2000step
+run_root_dir: ./results/Checkpoints
+seed: 42
+trainer:
+  eval_interval: 100
+  freeze_modules: qwen_vl_interface.model.model.visual,dino_encoder
+  gradient_accumulation_steps: 1
+  gradient_clipping: 1.0
+  is_resume: true
+  learning_rate:
+    action_model: 0.0001
+    base: 2.5e-05
+    qwen_vl_interface: 1.0e-05
+  logging_frequency: 100
+  lr_scheduler_type: cosine_with_min_lr
+  max_train_steps: 2000
+  num_warmup_steps: 5000
+  optimizer:
+    betas:
+    - 0.9
+    - 0.95
+    eps: 1.0e-08
+    weight_decay: 1.0e-08
+  pretrained_checkpoint: /content/starVLA_r/results/Checkpoints/Qwen2.5-VL-FAST-LIBERO-4in1/checkpoints/steps_30000_pytorch_model.pt
+  save_interval: 500
+  scheduler_specific_kwargs:
+    min_lr: 1.0e-06
+wandb_entity: michellelin9102-usc
+wandb_project: starVLA_Libero

checkpoints/pretrained_goal_2000step/dataset_statistics.json

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+    "num_transitions": 20150,
+    "num_trajectories": 142
+  }
+}

checkpoints/pretrained_goal_2000step/final_model/pytorch_model.pt

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checkpoints/pretrained_goal_2000step/summary.jsonl

@@ -0,0 +1,4 @@
+{"steps": 500}
+{"steps": 1000}
+{"steps": 1500}
+{"steps": 2000}

checkpoints/pretrained_goal_2000step/wandb/wandb/debug-internal.log

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+{"time":"2026-03-16T07:58:41.747155068Z","level":"INFO","msg":"handler: operation stats","stats":{}}
+{"time":"2026-03-16T07:58:41.751293056Z","level":"INFO","msg":"stream: closing","id":"h1hybozy"}
+{"time":"2026-03-16T07:58:41.751310876Z","level":"INFO","msg":"handler: closed","stream_id":"h1hybozy"}
+{"time":"2026-03-16T07:58:41.751385991Z","level":"INFO","msg":"sender: closed","stream_id":"h1hybozy"}
+{"time":"2026-03-16T07:58:41.751392739Z","level":"INFO","msg":"stream: closed","id":"h1hybozy"}

checkpoints/pretrained_goal_2000step/wandb/wandb/run-20260316_073559-h1hybozy/files/config.yaml

@@ -0,0 +1,69 @@
+_wandb:
+    value:
+        cli_version: 0.24.2
+        e:
+            tc8jq6me6tl6kehb0voihzue811ccsc4:
+                args:
+                    - --config_yaml
+                    - ./examples/LIBERO/train_files/my_libero_finetune.yaml
+                codePath: starVLA/training/train_starvla.py
+                codePathLocal: starVLA/training/train_starvla.py
+                cpu_count: 6
+                cpu_count_logical: 12
+                cudaVersion: "13.0"
+                disk:
+                    /:
+                        total: "253055008768"
+                        used: "113942818816"
+                email: chihhans@usc.edu
+                executable: /usr/local/envs/starvla/bin/python3.10
+                git:
+                    commit: 35e90d04f0c1fe5b6bdf8a3d6b0da703e1fed425
+                    remote: https://github.com/tliao730/starVLA_r
+                gpu: NVIDIA A100-SXM4-80GB
+                gpu_count: 1
+                gpu_nvidia:
+                    - architecture: Ampere
+                      cudaCores: 6912
+                      memoryTotal: "85899345920"
+                      name: NVIDIA A100-SXM4-80GB
+                      uuid: GPU-1000e8c7-f9d7-74b0-8fdb-aad3f6d24e69
+                host: c89e62d63bf0
+                memory:
+                    total: "179370471424"
+                os: Linux-6.6.113+-x86_64-with-glibc2.35
+                program: /content/starVLA_r/starVLA/training/train_starvla.py
+                python: CPython 3.10.20
+                root: ./results/Checkpoints/pretrained_goal_2000step/wandb
+                startedAt: "2026-03-16T07:35:59.330177Z"
+                writerId: tc8jq6me6tl6kehb0voihzue811ccsc4
+        m: []
+        python_version: 3.10.20
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+                - 2
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+            "4": 3.10.20
+            "5": 0.24.2
+            "6": 4.57.0
+            "12": 0.24.2
+            "13": linux-x86_64

checkpoints/pretrained_goal_2000step/wandb/wandb/run-20260316_073559-h1hybozy/files/output.log

@@ -0,0 +1,234 @@
+03/16 [07:36:01] INFO     | >> [RANK 0] ***** Training      train_starvla.py:326
+                          Configuration *****
+                 INFO     | >> [RANK 0]   Total             train_starvla.py:327
+                          optimization steps = 2000
+                 INFO     | >> [RANK 0]   Per device batch  train_starvla.py:328
+                          size = 1
+                 INFO     | >> [RANK 0]   Gradient          train_starvla.py:329
+                          accumulation steps = 1
+                 INFO     | >> [RANK 0]   Total batch size  train_starvla.py:330
+                          = 1
+ 15%|█▌        | 300/2000 [03:08<17:18,  1.64it/s, data_times=0.000, model_times=0.608]
+03/16 [07:37:05] INFO     | >> [RANK 0] Step 100, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          4.210097789764404, 'mse_score':
+                          np.float64(0.021170438258148485),
+                          'data_time':
+                          0.0002306789992871927,
+                          'model_time': 0.6122736000006626,
+                          'learning_rate':
+                          2.0000000000000002e-07, 'epoch':
+                          0.0})
+03/16 [07:38:08] INFO     | >> [RANK 0] Step 200, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          3.746821880340576, 'mse_score':
+                          np.float64(0.06265889627114841),
+                          'data_time':
+                          0.00021090000063850312,
+                          'model_time': 0.6121146070008763,
+                          'learning_rate':
+                          4.0000000000000003e-07, 'epoch':
+                          0.01})
+Error decoding tokens: cannot reshape array of size 55 into shape (7)
+Tokens: [295, 442, 283, 476, 334, 764, 712, 297, 322, 444, 301, 729, 679, 1230, 1262]
+03/16 [07:39:10] INFO     | >> [RANK 0] Step 300, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          4.185059070587158, 'mse_score':
+                          np.float64(0.058571179724887144),
+                          'data_time':
+                          0.00021666100019501755,
+                          'model_time': 0.6081078020006316,
+                          'learning_rate':
+                          6.000000000000001e-07, 'epoch':
+                          0.01})
+03/16 [07:40:12] INFO     | >> [RANK 0] Step 400, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          4.228229999542236, 'mse_score':
+                          np.float64(0.016849551473750893),
+                          'data_time':
+                          0.0018637430002854671,
+                          'model_time': 0.6165952399996968,
+                          'learning_rate':
+                          8.000000000000001e-07, 'epoch':
+                          0.02})
+03/16 [07:41:15] INFO     | >> [RANK 0] Step 500, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          4.664724349975586, 'mse_score':
+                          np.float64(0.03275721034686037),
+                          'data_time':
+                          0.0020331710002210457,
+                          'model_time': 0.6105900989996371,
+                          'learning_rate':
+                          1.0000000000000002e-06, 'epoch':
+                          0.02})
+✅ Checkpoint saved at ./results/Checkpoints/pretrained_goal_2000step/checkpoints/steps_500
+03/16 [07:41:35] INFO     | >> [RANK 0] 📊 Saving accessed  train_starvla.py:229
+                          configuration...
+                 INFO     | >> [RANK 0] ✅ Configuration    train_starvla.py:232
+                          files saved
+03/16 [07:42:38] INFO     | >> [RANK 0] Step 600, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          2.8301002979278564, 'mse_score':
+                          np.float64(0.032034150375178476),
+                          'data_time':
+                          0.00026528400030656485,
+                          'model_time': 0.6179462399995828,
+                          'learning_rate':
+                          1.2000000000000002e-06, 'epoch':
+                          0.03})
+03/16 [07:43:41] INFO     | >> [RANK 0] Step 700, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          2.0515148639678955, 'mse_score':
+                          np.float64(0.006033696640736901),
+                          'data_time':
+                          0.0006040680000296561,
+                          'model_time': 0.6157337129998268,
+                          'learning_rate':
+                          1.4000000000000001e-06, 'epoch':
+                          0.03})
+03/16 [07:44:43] INFO     | >> [RANK 0] Step 800, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          2.978555679321289, 'mse_score':
+                          np.float64(0.014314579221588514),
+                          'data_time':
+                          0.0030624710007032263,
+                          'model_time': 0.6223620569999184,
+                          'learning_rate':
+                          1.6000000000000001e-06, 'epoch':
+                          0.04})
+03/16 [07:45:45] INFO     | >> [RANK 0] Step 900, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          3.1994776725769043, 'mse_score':
+                          np.float64(0.012207442076542497),
+                          'data_time':
+                          0.0005427599999165977,
+                          'model_time': 0.6192654679998668,
+                          'learning_rate':
+                          1.8000000000000001e-06, 'epoch':
+                          0.04})
+03/16 [07:46:48] INFO     | >> [RANK 0] Step 1000, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          1.9634697437286377, 'mse_score':
+                          np.float64(0.012461269572495567),
+                          'data_time':
+                          0.0004611079993992462,
+                          'model_time': 0.6227996640000129,
+                          'learning_rate':
+                          2.0000000000000003e-06, 'epoch':
+                          0.05})
+✅ Checkpoint saved at ./results/Checkpoints/pretrained_goal_2000step/checkpoints/steps_1000
+03/16 [07:47:08] INFO     | >> [RANK 0] 📊 Saving accessed  train_starvla.py:229
+                          configuration...
+                 INFO     | >> [RANK 0] ✅ Configuration    train_starvla.py:232
+                          files saved
+03/16 [07:48:11] INFO     | >> [RANK 0] Step 1100, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          2.469298839569092, 'mse_score':
+                          np.float64(0.01308576087710885),
+                          'data_time':
+                          0.00020786299955943832,
+                          'model_time': 0.6135692699999709,
+                          'learning_rate': 2.2e-06,
+                          'epoch': 0.05})
+03/16 [07:49:14] INFO     | >> [RANK 0] Step 1200, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          2.4971842765808105, 'mse_score':
+                          np.float64(0.01857905762512233),
+                          'data_time':
+                          0.0027338179997968837,
+                          'model_time': 0.6215266220006015,
+                          'learning_rate':
+                          2.4000000000000003e-06, 'epoch':
+                          0.06})
+03/16 [07:50:17] INFO     | >> [RANK 0] Step 1300, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          2.9175233840942383, 'mse_score':
+                          np.float64(0.0304242990983989),
+                          'data_time':
+                          0.00021219399968686048,
+                          'model_time': 0.6181910210007118,
+                          'learning_rate': 2.6e-06,
+                          'epoch': 0.06})
+03/16 [07:51:19] INFO     | >> [RANK 0] Step 1400, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          1.7560175657272339, 'mse_score':
+                          np.float64(0.022060719529597362),
+                          'data_time':
+                          0.0005602889996225713,
+                          'model_time': 0.6143437189994074,
+                          'learning_rate':
+                          2.8000000000000003e-06, 'epoch':
+                          0.07})
+03/16 [07:52:22] INFO     | >> [RANK 0] Step 1500, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          3.392509937286377, 'mse_score':
+                          np.float64(0.02987415900432008),
+                          'data_time':
+                          0.0006196529993758304,
+                          'model_time': 0.6209130370007188,
+                          'learning_rate': 3e-06, 'epoch':
+                          0.07})
+✅ Checkpoint saved at ./results/Checkpoints/pretrained_goal_2000step/checkpoints/steps_1500
+03/16 [07:52:43] INFO     | >> [RANK 0] 📊 Saving accessed  train_starvla.py:229
+                          configuration...
+                 INFO     | >> [RANK 0] ✅ Configuration    train_starvla.py:232
+                          files saved
+03/16 [07:53:46] INFO     | >> [RANK 0] Step 1600, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          2.57142972946167, 'mse_score':
+                          np.float64(0.02036424163621981),
+                          'data_time':
+                          0.003223310999601381,
+                          'model_time': 0.6141595979997874,
+                          'learning_rate':
+                          3.2000000000000003e-06, 'epoch':
+                          0.08})
+03/16 [07:54:49] INFO     | >> [RANK 0] Step 1700, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          2.51837420463562, 'mse_score':
+                          np.float64(0.019623728610405986),
+                          'data_time':
+                          0.0002243489998363657,
+                          'model_time': 0.6128846030005661,
+                          'learning_rate':
+                          3.4000000000000005e-06, 'epoch':
+                          0.08})
+03/16 [07:55:51] INFO     | >> [RANK 0] Step 1800, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          1.7092719078063965, 'mse_score':
+                          np.float64(0.016586748426842924),
+                          'data_time':
+                          0.0002426230003038654,
+                          'model_time': 0.6149865870002031,
+                          'learning_rate':
+                          3.6000000000000003e-06, 'epoch':
+                          0.09})
+03/16 [07:56:54] INFO     | >> [RANK 0] Step 1900, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          1.7662057876586914, 'mse_score':
+                          np.float64(0.01898054127710033),
+                          'data_time':
+                          0.00022221400013222592,
+                          'model_time': 0.6105404540003292,
+                          'learning_rate':
+                          3.8000000000000005e-06, 'epoch':
+                          0.09})
+03/16 [07:57:57] INFO     | >> [RANK 0] Step 2000, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          2.123331308364868, 'mse_score':
+                          np.float64(0.03371996539489637),
+                          'data_time':
+                          0.0016236379997280892,
+                          'model_time': 0.6144314619996294,
+                          'learning_rate':
+                          4.000000000000001e-06, 'epoch':
+                          0.1})
+✅ Checkpoint saved at ./results/Checkpoints/pretrained_goal_2000step/checkpoints/steps_2000
+03/16 [07:58:17] INFO     | >> [RANK 0] 📊 Saving accessed  train_starvla.py:229
+                          configuration...
+                 INFO     | >> [RANK 0] ✅ Configuration    train_starvla.py:232
+                          files saved
+03/16 [07:58:39] INFO     | >> [RANK 0] Training complete.  train_starvla.py:369
+                          Final model saved at
+                          ./results/Checkpoints/pretrained_
+                          goal_2000step/final_model

checkpoints/pretrained_goal_2000step/wandb/wandb/run-20260316_073559-h1hybozy/files/requirements.txt

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+starVLA==1.0.1
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checkpoints/pretrained_goal_2000step/wandb/wandb/run-20260316_073559-h1hybozy/files/wandb-metadata.json

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+  "startedAt": "2026-03-16T07:35:59.330177Z",
+  "args": [
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+    "./examples/LIBERO/train_files/my_libero_finetune.yaml"
+  ],
+  "program": "/content/starVLA_r/starVLA/training/train_starvla.py",
+  "codePath": "starVLA/training/train_starvla.py",
+  "codePathLocal": "starVLA/training/train_starvla.py",
+  "git": {
+    "remote": "https://github.com/tliao730/starVLA_r",
+    "commit": "35e90d04f0c1fe5b6bdf8a3d6b0da703e1fed425"
+  },
+  "email": "chihhans@usc.edu",
+  "root": "./results/Checkpoints/pretrained_goal_2000step/wandb",
+  "host": "c89e62d63bf0",
+  "executable": "/usr/local/envs/starvla/bin/python3.10",
+  "cpu_count": 6,
+  "cpu_count_logical": 12,
+  "gpu": "NVIDIA A100-SXM4-80GB",
+  "gpu_count": 1,
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