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@@ -38,3 +38,4 @@ checkpoints/wandb/wandb/run-20260316_085932-77uivys0/run-77uivys0.wandb filter=l
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checkpoints/finetune_task48_2000step/config.yaml

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+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_task_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/finetune_task48_2000step
+run_id: finetune_task48_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/finetune_task48_2000step/dataset_statistics.json

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+}

checkpoints/finetune_task48_2000step/final_model/pytorch_model.pt

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checkpoints/finetune_task48_2000step/summary.jsonl

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+{"steps": 1500}
+{"steps": 2000}

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checkpoints/finetune_task48_2000step/wandb/wandb/run-20260316_102706-w0ljmpp2/files/config.yaml

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+_wandb:
+    value:
+        cli_version: 0.24.2
+        e:
+            xjkqn2u8dse3qnn37usztgd1uc0n91bo:
+                args:
+                    - --config_yaml
+                    - ./examples/LIBERO/train_files/my_libero_finetune.yaml
+                    - --datasets.vla_data.data_mix
+                    - libero_90_task_48
+                    - --run_id
+                    - finetune_task48_2000step
+                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: "155059826688"
+                email: chihhans@usc.edu
+                executable: /usr/local/envs/starvla/bin/python3.10
+                git:
+                    commit: e952c81219e9fac2c3183a27cd378e592c4c9ef0
+                    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/finetune_task48_2000step/wandb
+                startedAt: "2026-03-16T10:27:06.946692Z"
+                writerId: xjkqn2u8dse3qnn37usztgd1uc0n91bo
+        m: []
+        python_version: 3.10.20
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checkpoints/finetune_task48_2000step/wandb/wandb/run-20260316_102706-w0ljmpp2/files/output.log

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+03/16 [10:27:08] 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
+ 20%|██        | 400/2000 [04:19<16:53,  1.58it/s, data_times=0.002, model_times=0.628]
+03/16 [10:28:15] INFO     | >> [RANK 0] Step 100, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          9.314701080322266, 'mse_score':
+                          np.float64(0.034079255802760465),
+                          'data_time':
+                          0.0013499019987648353,
+                          'model_time': 0.635298358,
+                          'learning_rate':
+                          2.0000000000000002e-07, 'epoch':
+                          0.02})
+03/16 [10:29:19] INFO     | >> [RANK 0] Step 200, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          7.929775714874268, 'mse_score':
+                          np.float64(0.03428953959591426),
+                          'data_time':
+                          0.0005867119998583803,
+                          'model_time': 0.6362442019999435,
+                          'learning_rate':
+                          4.0000000000000003e-07, 'epoch':
+                          0.04})
+03/16 [10:30:24] INFO     | >> [RANK 0] Step 300, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          4.264825344085693, 'mse_score':
+                          np.float64(0.036809627059651094),
+                          'data_time':
+                          0.0006798820013500517,
+                          'model_time': 0.6313770140004635,
+                          'learning_rate':
+                          6.000000000000001e-07, 'epoch':
+                          0.06})
+03/16 [10:31:28] INFO     | >> [RANK 0] Step 400, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          5.90472936630249, 'mse_score':
+                          np.float64(0.028770231955113468),
+                          'data_time':
+                          0.0018893399992521154,
+                          'model_time': 0.6276594850005495,
+                          'learning_rate':
+                          8.000000000000001e-07, 'epoch':
+                          0.08})
+03/16 [10:32:32] INFO     | >> [RANK 0] Step 500, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          4.008138656616211, 'mse_score':
+                          np.float64(0.021432459692567525),
+                          'data_time':
+                          0.0005417720003606519,
+                          'model_time': 0.6293254800002615,
+                          'learning_rate':
+                          1.0000000000000002e-06, 'epoch':
+                          0.1})
+✅ Checkpoint saved at ./results/Checkpoints/finetune_task48_2000step/checkpoints/steps_500
+03/16 [10:32:53] INFO     | >> [RANK 0] 📊 Saving accessed  train_starvla.py:229
+                          configuration...
+                 INFO     | >> [RANK 0] ✅ Configuration    train_starvla.py:232
+                          files saved
+03/16 [10:33:58] INFO     | >> [RANK 0] Step 600, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          2.6089346408843994, 'mse_score':
+                          np.float64(0.018183997162692193),
+                          'data_time':
+                          0.0017828830004873453,
+                          'model_time': 0.6282775969993963,
+                          'learning_rate':
+                          1.2000000000000002e-06, 'epoch':
+                          0.11})
+03/16 [10:35:03] INFO     | >> [RANK 0] Step 700, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          2.386871814727783, 'mse_score':
+                          np.float64(0.02084296110337058),
+                          'data_time':
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+                          'model_time': 0.6310159410004417,
+                          'learning_rate':
+                          1.4000000000000001e-06, 'epoch':
+                          0.13})
+03/16 [10:36:07] INFO     | >> [RANK 0] Step 800, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          2.1533708572387695, 'mse_score':
+                          np.float64(0.02266200388939163),
+                          'data_time':
+                          0.0002977069998451043,
+                          'model_time': 0.6323083229999611,
+                          'learning_rate':
+                          1.6000000000000001e-06, 'epoch':
+                          0.15})
+03/16 [10:37:12] INFO     | >> [RANK 0] Step 900, Loss:     train_starvla.py:242
+                          {'action_dit_loss':
+                          3.9568512439727783, 'mse_score':
+                          np.float64(0.010319906140672347),
+                          'data_time':
+                          0.00023809100093785673,
+                          'model_time': 0.6301700330004678,
+                          'learning_rate':
+                          1.8000000000000001e-06, 'epoch':
+                          0.17})
+03/16 [10:38:16] INFO     | >> [RANK 0] Step 1000, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          2.959420680999756, 'mse_score':
+                          np.float64(0.018102484443056295),
+                          'data_time':
+                          0.002947425999082043,
+                          'model_time': 0.6312376300011238,
+                          'learning_rate':
+                          2.0000000000000003e-06, 'epoch':
+                          0.19})
+✅ Checkpoint saved at ./results/Checkpoints/finetune_task48_2000step/checkpoints/steps_1000
+03/16 [10:38:37] INFO     | >> [RANK 0] 📊 Saving accessed  train_starvla.py:229
+                          configuration...
+                 INFO     | >> [RANK 0] ✅ Configuration    train_starvla.py:232
+                          files saved
+03/16 [10:39:43] INFO     | >> [RANK 0] Step 1100, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          2.4097423553466797, 'mse_score':
+                          np.float64(0.010958415389495369),
+                          'data_time':
+                          0.0004303599998820573,
+                          'model_time': 0.629223395999361,
+                          'learning_rate': 2.2e-06,
+                          'epoch': 0.21})
+03/16 [10:40:47] INFO     | >> [RANK 0] Step 1200, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          1.8001140356063843, 'mse_score':
+                          np.float64(0.016425216646615573),
+                          'data_time':
+                          0.0017891709994728444,
+                          'model_time': 0.6432768380000198,
+                          'learning_rate':
+                          2.4000000000000003e-06, 'epoch':
+                          0.23})
+03/16 [10:41:52] INFO     | >> [RANK 0] Step 1300, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          2.450651168823242, 'mse_score':
+                          np.float64(0.03609608879081504),
+                          'data_time':
+                          0.0006008899999869755,
+                          'model_time': 0.6404236750004202,
+                          'learning_rate': 2.6e-06,
+                          'epoch': 0.25})
+03/16 [10:42:57] INFO     | >> [RANK 0] Step 1400, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          1.3520110845565796, 'mse_score':
+                          np.float64(0.015366809051465815),
+                          'data_time':
+                          0.0019384579991310602,
+                          'model_time': 0.6324510970007395,
+                          'learning_rate':
+                          2.8000000000000003e-06, 'epoch':
+                          0.27})
+03/16 [10:44:02] INFO     | >> [RANK 0] Step 1500, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          1.9549362659454346, 'mse_score':
+                          np.float64(0.027217211106191984),
+                          'data_time':
+                          0.000567299997783266,
+                          'model_time': 0.633298984997964,
+                          'learning_rate': 3e-06, 'epoch':
+                          0.29})
+✅ Checkpoint saved at ./results/Checkpoints/finetune_task48_2000step/checkpoints/steps_1500
+03/16 [10:44:27] INFO     | >> [RANK 0] 📊 Saving accessed  train_starvla.py:229
+                          configuration...
+                 INFO     | >> [RANK 0] ✅ Configuration    train_starvla.py:232
+                          files saved
+03/16 [10:45:32] INFO     | >> [RANK 0] Step 1600, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          4.203729152679443, 'mse_score':
+                          np.float64(0.029437476644757394),
+                          'data_time':
+                          0.002075060001516249,
+                          'model_time': 0.633118129997456,
+                          'learning_rate':
+                          3.2000000000000003e-06, 'epoch':
+                          0.3})
+03/16 [10:46:36] INFO     | >> [RANK 0] Step 1700, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          3.06008243560791, 'mse_score':
+                          np.float64(0.018865567485130245),
+                          'data_time':
+                          0.0007922959994175471,
+                          'model_time': 0.6446109249991423,
+                          'learning_rate':
+                          3.4000000000000005e-06, 'epoch':
+                          0.32})
+03/16 [10:47:41] INFO     | >> [RANK 0] Step 1800, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          1.5572900772094727, 'mse_score':
+                          np.float64(0.03312688171523522),
+                          'data_time':
+                          0.0018809510002029128,
+                          'model_time': 0.6576305890012009,
+                          'learning_rate':
+                          3.6000000000000003e-06, 'epoch':
+                          0.34})
+Error decoding tokens: cannot reshape array of size 55 into shape (7)
+Tokens: [266, 393, 272, 610, 1589, 277, 290, 310, 425, 1084, 261, 256]
+03/16 [10:48:46] INFO     | >> [RANK 0] Step 1900, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          3.1513538360595703, 'mse_score':
+                          np.float64(0.06123608522253369),
+                          'data_time':
+                          0.0007130379999580327,
+                          'model_time': 0.6419669289971353,
+                          'learning_rate':
+                          3.8000000000000005e-06, 'epoch':
+                          0.36})
+03/16 [10:49:50] INFO     | >> [RANK 0] Step 2000, Loss:    train_starvla.py:242
+                          {'action_dit_loss':
+                          1.4614311456680298, 'mse_score':
+                          np.float64(0.018765023958714284),
+                          'data_time':
+                          0.002591219999885652,
+                          'model_time': 0.631486190999567,
+                          'learning_rate':
+                          4.000000000000001e-06, 'epoch':
+                          0.38})
+✅ Checkpoint saved at ./results/Checkpoints/finetune_task48_2000step/checkpoints/steps_2000
+03/16 [10:50:11] INFO     | >> [RANK 0] 📊 Saving accessed  train_starvla.py:229
+                          configuration...
+                 INFO     | >> [RANK 0] ✅ Configuration    train_starvla.py:232
+                          files saved
+03/16 [10:50:33] INFO     | >> [RANK 0] Training complete.  train_starvla.py:369
+                          Final model saved at
+                          ./results/Checkpoints/finetune_ta
+                          sk48_2000step/final_model

checkpoints/finetune_task48_2000step/wandb/wandb/run-20260316_102706-w0ljmpp2/files/requirements.txt

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+    "libero_90_task_48",
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+  "git": {
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+    "commit": "e952c81219e9fac2c3183a27cd378e592c4c9ef0"
+  },
+  "email": "chihhans@usc.edu",
+  "root": "./results/Checkpoints/finetune_task48_2000step/wandb",
+  "host": "c89e62d63bf0",
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