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@@ -57,3 +57,6 @@ fastumi_pickandplace_qwenDiscreteDiffusion_329v2/wandb/wandb/run-20260330_085553
 wandb/wandb/run-20260330_213657-3rc55aw0/run-3rc55aw0.wandb filter=lfs diff=lfs merge=lfs -text
 fastumi_pickandplace_qwenPI_329v2/wandb/wandb/run-20260330_213657-3rc55aw0/run-3rc55aw0.wandb filter=lfs diff=lfs merge=lfs -text
 fastumi_pickandplace_qwenDiscreteDiffusion_329v3/wandb/wandb/run-20260401_080931-8iyo5o8r/run-8iyo5o8r.wandb filter=lfs diff=lfs merge=lfs -text
+wandb/wandb/run-20260402_015347-rztzqreo/run-rztzqreo.wandb filter=lfs diff=lfs merge=lfs -text
+wandb/wandb/run-20260402_174446-b7f4uglx/run-b7f4uglx.wandb filter=lfs diff=lfs merge=lfs -text
+wandb/wandb/run-20260402_182806-6dhdda09/run-6dhdda09.wandb filter=lfs diff=lfs merge=lfs -text

checkpoints/steps_10000_pytorch_model.pt

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checkpoints/steps_20000_pytorch_model.pt

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checkpoints/steps_5000_pytorch_model.pt

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config.yaml

@@ -1,16 +1,19 @@
 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: dynamic-329-v2
+    action_mode: abs
+    data_mix: dynamic-329-v4
     data_root_dir: playground/Datasets/FastUMI
     dataset_py: lerobot_datasets
+    image_size:
+    - 224
+    - 224
     per_device_batch_size: 8
     video_backend: torchvision_av
 framework:
   action_model:
     action_dim: 10
     add_pos_embed: true
+    decode_schedule: cosine
     diffusion_model_cfg:
       attention_head_dim: 64
       cross_attention_dim: 2048
@@ -21,26 +24,28 @@ framework:
       norm_type: ada_norm
       num_attention_heads: 32
       num_layers: 36
-      output_dim: 1024
-      positional_embeddings: null
+      output_dim: 256
+      positional_embeddings: sinusoidal
     future_action_window_size: 15
+    l1_loss_weight: 0.1
     max_seq_len: 1024
-    noise_beta_alpha: 1.5
-    noise_beta_beta: 1.0
-    noise_s: 0.999
-    num_inference_timesteps: 4
+    no_mask_token_prob: 0.0
+    num_bins: 256
+    num_inference_steps: 8
     num_target_vision_tokens: 32
-    num_timestep_buckets: 1000
     past_action_window_size: 0
+    representation: bin
     state_dim: 10
-  name: QwenPI
+    train_mask_schedule: cosine
+    use_simple_max: false
+  name: QwenDiscreteDiffusion
   qwenvl:
     attn_implementation: flash_attention_2
     base_vlm: playground/Pretrained_models/Qwen2.5-VL-3B-Instruct-Action
     num_vl_layers: 36
     vl_hidden_dim: 2048
-output_dir: ./results/Checkpoints/fastumi_pickandplace_qwenPI_329v2
-run_id: fastumi_pickandplace_qwenPI_329v2
+output_dir: ./results/Checkpoints/fastumi_pickandplace_qwenDiscreteDiffusion_329v4
+run_id: fastumi_pickandplace_qwenDiscreteDiffusion_329v4
 run_root_dir: ./results/Checkpoints
 seed: 42
 trainer:
@@ -51,11 +56,11 @@ trainer:
   is_resume: true
   learning_rate:
     action_model: 0.0001
-    base: 2.5e-05
+    base: 1.0e-05
     qwen_vl_interface: 1.0e-05
   logging_frequency: 50
   lr_scheduler_type: cosine_with_min_lr
-  max_train_steps: 50000
+  max_train_steps: 20000
   num_warmup_steps: 5000
   optimizer:
     betas:
@@ -63,8 +68,10 @@ trainer:
     - 0.95
     eps: 1.0e-08
     weight_decay: 1.0e-08
+  repeated_diffusion_steps: 4
+  save_format: pt
   save_interval: 10000
   scheduler_specific_kwargs:
-    min_lr: 1.0e-06
+    min_lr: 5.0e-07
 wandb_entity: 2200011093-peking-university
 wandb_project: starVLA_FastUMI_dynamic_1

dataset_statistics.json

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final_model/pytorch_model.pt

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summary.jsonl

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 {"steps": 10000}
+{"steps": 20000}

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wandb/wandb/run-20260402_015347-rztzqreo/files/config.yaml

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+_wandb:
+    value:
+        cli_version: 0.25.0
+        e:
+            q55kndd3prshum8crfqu3k17omtf8jg4:
+                args:
+                    - --config_yaml
+                    - starVLA/config/training/starvla_train_discrete_diffusion_real.yaml
+                    - --framework.name
+                    - QwenDiscreteDiffusion
+                    - --framework.qwenvl.base_vlm
+                    - playground/Pretrained_models/Qwen2.5-VL-3B-Instruct-Action
+                    - --framework.qwenvl.vl_hidden_dim
+                    - "4096"
+                    - --framework.qwenvl.attn_implementation
+                    - flash_attention_2
+                    - --framework.action_model.representation
+                    - bin
+                    - --framework.action_model.num_bins
+                    - "256"
+                    - --framework.action_model.action_low
+                    - "-1.0"
+                    - --framework.action_model.action_high
+                    - "1.0"
+                    - --framework.action_model.num_inference_steps
+                    - "8"
+                    - --datasets.vla_data.data_root_dir
+                    - playground/Datasets/FastUMI
+                    - --datasets.vla_data.data_mix
+                    - dynamic-329-v4
+                    - --datasets.vla_data.include_state
+                    - "false"
+                    - --datasets.vla_data.per_device_batch_size
+                    - "8"
+                    - --datasets.vla_data.video_backend
+                    - torchvision_av
+                    - --trainer.freeze_modules
+                    - ""
+                    - --trainer.is_resume
+                    - "true"
+                    - --trainer.max_train_steps
+                    - "10000"
+                    - --trainer.save_interval
+                    - "5000"
+                    - --trainer.logging_frequency
+                    - "50"
+                    - --trainer.eval_interval
+                    - "100"
+                    - --trainer.gradient_accumulation_steps
+                    - "1"
+                    - --run_root_dir
+                    - ./results/Checkpoints
+                    - --run_id
+                    - fastumi_pickandplace_qwenDiscreteDiffusion_329v4
+                    - --wandb_project
+                    - starVLA_FastUMI_dynamic_1
+                    - --wandb_entity
+                    - 2200011093-peking-university
+                codePath: starVLA/training/train_starvla.py
+                codePathLocal: starVLA/training/train_starvla.py
+                cpu_count: 192
+                cpu_count_logical: 384
+                cudaVersion: "13.1"
+                disk:
+                    /:
+                        total: "3776651378688"
+                        used: "158964899840"
+                email: wangpc@berkeley.edu
+                executable: /home/wangpc/miniconda3/envs/starVLA/bin/python3.10
+                git:
+                    commit: 0c6edf952038b7f2f2180e3ff76a9ba39d9b9363
+                    remote: https://github.com/Kaiwen-Hong/starVLA.git
+                gpu: NVIDIA RTX PRO 6000 Blackwell Server Edition
+                gpu_count: 8
+                gpu_nvidia:
+                    - architecture: Blackwell
+                      cudaCores: 24064
+                      memoryTotal: "102641958912"
+                      name: NVIDIA RTX PRO 6000 Blackwell Server Edition
+                      uuid: GPU-41f2ee49-ba06-f304-cfa5-4d526d8f5673
+                    - architecture: Blackwell
+                      cudaCores: 24064
+                      memoryTotal: "102641958912"
+                      name: NVIDIA RTX PRO 6000 Blackwell Server Edition
+                      uuid: GPU-91f82c0c-10ef-1f95-9f6d-1102b8e832b5
+                    - architecture: Blackwell
+                      cudaCores: 24064
+                      memoryTotal: "102641958912"
+                      name: NVIDIA RTX PRO 6000 Blackwell Server Edition
+                      uuid: GPU-1f3c0889-b740-5143-e064-afeb49245756
+                    - architecture: Blackwell
+                      cudaCores: 24064
+                      memoryTotal: "102641958912"
+                      name: NVIDIA RTX PRO 6000 Blackwell Server Edition
+                      uuid: GPU-49955a45-509a-e8af-a468-b9ef0449b005
+                    - architecture: Blackwell
+                      cudaCores: 24064
+                      memoryTotal: "102641958912"
+                      name: NVIDIA RTX PRO 6000 Blackwell Server Edition
+                      uuid: GPU-065fc6ce-c1cd-c143-b421-32b915c9d8fd
+                    - architecture: Blackwell
+                      cudaCores: 24064
+                      memoryTotal: "102641958912"
+                      name: NVIDIA RTX PRO 6000 Blackwell Server Edition
+                      uuid: GPU-d16b5acf-a100-2d1b-8138-1661892f3d26
+                    - architecture: Blackwell
+                      cudaCores: 24064
+                      memoryTotal: "102641958912"
+                      name: NVIDIA RTX PRO 6000 Blackwell Server Edition
+                      uuid: GPU-b7a88059-1d3f-da1c-9903-fd4acd4936ab
+                    - architecture: Blackwell
+                      cudaCores: 24064
+                      memoryTotal: "102641958912"
+                      name: NVIDIA RTX PRO 6000 Blackwell Server Edition
+                      uuid: GPU-747dc32b-b025-76e9-697d-fd33ef441b47
+                host: tams02
+                memory:
+                    total: "1081552064512"
+                os: Linux-6.8.0-106-generic-x86_64-with-glibc2.39
+                program: /scratch/wangpc/starVLA/starVLA/training/train_starvla.py
+                python: CPython 3.10.19
+                root: ./results/Checkpoints/fastumi_pickandplace_qwenDiscreteDiffusion_329v4/wandb
+                startedAt: "2026-04-02T01:53:47.866453Z"
+                writerId: q55kndd3prshum8crfqu3k17omtf8jg4
+        m: []
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wandb/wandb/run-20260402_015347-rztzqreo/files/requirements.txt

@@ -0,0 +1,161 @@
+starVLA==1.0.1
+kiwisolver==1.4.9
+scipy==1.15.3
+pyarrow==14.0.1
+protobuf==6.33.5
+platformdirs==4.9.4
+mdurl==0.1.2
+Jinja2==3.1.6
+torchvision==0.22.0+cu128
+exceptiongroup==1.3.1
+nvidia-cusparselt-cu12==0.6.3
+markdown-it-py==4.0.0
+ray==2.54.0
+timm==1.0.25
+nvidia-nvjitlink-cu12==12.8.61
+urllib3==2.6.3
+numpydantic==1.6.9
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+04/02 [17:44:47] INFO     | >> ***** Training Configuration *****                                                  ]8;id=208496;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=750800;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#341\341]8;;\
+                 INFO     | >>   Total optimization steps = 20000                                                  ]8;id=471029;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=617889;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#342\342]8;;\
+                 INFO     | >>   Per device batch size = 8                                                         ]8;id=844962;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=167414;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#343\343]8;;\
+                 INFO     | >>   Gradient accumulation steps = 1                                                   ]8;id=225772;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=800581;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#344\344]8;;\
+                 INFO     | >>   Total batch size = 64                                                             ]8;id=376417;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=888662;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#345\345]8;;\
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+04/02 [17:49:38] INFO     | >> Step 10150, Loss: {'action_dit_loss': 1.5966742038726807, 'data_time':              ]8;id=928463;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=903565;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#253\253]8;;\
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+04/02 [17:54:30] INFO     | >> Step 10300, Loss: {'action_dit_loss': 1.5979719161987305, 'mse_score':              ]8;id=291476;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=475435;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#253\253]8;;\
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+04/02 [17:56:05] INFO     | >> Step 10350, Loss: {'action_dit_loss': 1.5509355068206787, 'data_time':              ]8;id=388162;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=372528;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#253\253]8;;\
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+04/02 [17:57:43] INFO     | >> Step 10400, Loss: {'action_dit_loss': 1.6178094148635864, 'mse_score':              ]8;id=982153;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=716751;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#253\253]8;;\
+                          0.002370418794453144, 'data_time': 0.002294915961101651, 'model_time':                                       
+                          1.911499842070043, 'learning_rate': 7.272451634934096e-06, 'epoch': 10.09})                                  
+04/02 [17:59:19] INFO     | >> Step 10450, Loss: {'action_dit_loss': 1.3621097803115845, 'data_time':              ]8;id=179451;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=560086;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#253\253]8;;\
+                          0.001984058995731175, 'model_time': 1.9121084010694176, 'learning_rate':                                     
+                          7.227333763236907e-06, 'epoch': 10.14})                                                                      
+04/02 [18:00:57] INFO     | >> Step 10500, Loss: {'action_dit_loss': 1.7321473360061646, 'mse_score':              ]8;id=397887;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=283060;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#253\253]8;;\
+                          0.0032398466020822523, 'data_time': 0.0014325060183182359, 'model_time':                                     
+                          1.9180362839251757, 'learning_rate': 7.181999054610053e-06, 'epoch': 10.18})                                 
+04/02 [18:02:33] INFO     | >> Step 10550, Loss: {'action_dit_loss': 1.500677227973938, 'data_time':               ]8;id=230283;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=717870;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#253\253]8;;\
+                          0.0020846440456807613, 'model_time': 1.9105811530025676, 'learning_rate':                                    
+                          7.136452480515208e-06, 'epoch': 10.23})                                                                      
+04/02 [18:04:11] INFO     | >> Step 10600, Loss: {'action_dit_loss': 1.6814020872116089, 'mse_score':              ]8;id=58655;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=240174;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#253\253]8;;\
+                          0.0026212738826870917, 'data_time': 0.000153045984916389, 'model_time':                                      
+                          1.9118029630044475, 'learning_rate': 7.0906990356474895e-06, 'epoch': 10.28})                                
+04/02 [18:05:47] INFO     | >> Step 10650, Loss: {'action_dit_loss': 1.3794829845428467, 'data_time':              ]8;id=420651;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=280746;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#253\253]8;;\
+                          0.00018000707495957613, 'model_time': 1.9139324839925393, 'learning_rate':                                   
+                          7.04474373738772e-06, 'epoch': 10.33})                                                                       
+04/02 [18:07:25] INFO     | >> Step 10700, Loss: {'action_dit_loss': 1.4610731601715088, 'mse_score':              ]8;id=594731;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=918938;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#253\253]8;;\
+                          0.0020972054451704027, 'data_time': 0.0022356780245900154, 'model_time':                                     
+                          1.9126690989360213, 'learning_rate': 6.9985916252522225e-06, 'epoch': 10.38})                                
+04/02 [18:09:01] INFO     | >> Step 10750, Loss: {'action_dit_loss': 1.7340061664581299, 'data_time':              ]8;id=523481;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=414850;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#253\253]8;;\
+                          0.00014866807032376528, 'model_time': 1.911417853902094, 'learning_rate':                                    
+                          6.952247760340176e-06, 'epoch': 10.43})                                                                      
+04/02 [18:10:39] INFO     | >> Step 10800, Loss: {'action_dit_loss': 1.4578142166137695, 'mse_score':              ]8;id=149811;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=277746;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#253\253]8;;\
+                          0.0017744580283761025, 'data_time': 0.0023739089956507087, 'model_time':                                     
+                          1.9098711890401319, 'learning_rate': 6.905717224778623e-06, 'epoch': 10.48})                                 
+04/02 [18:12:14] INFO     | >> Step 10850, Loss: {'action_dit_loss': 1.4391863346099854, 'data_time':              ]8;id=565158;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py\train_starvla.py]8;;\:]8;id=275504;file:///scratch/wangpc/starVLA/starVLA/training/train_starvla.py#253\253]8;;\
+                          0.002512277918867767, 'model_time': 1.9136753680650145, 'learning_rate':                                     
+                          6.859005121165135e-06, 'epoch': 10.52})                                                                      

wandb/wandb/run-20260402_174446-b7f4uglx/files/requirements.txt

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+kiwisolver==1.4.9
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+protobuf==6.33.5
+platformdirs==4.9.4
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+exceptiongroup==1.3.1
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+MarkupSafe==3.0.3
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+portalocker==3.2.0
+qwen-vl-utils==0.0.14
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+tiktoken==0.12.0
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+gevent==25.9.1
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+nvidia-cufft-cu12==11.3.3.41
+greenlet==3.3.2
+docstring_parser==0.17.0
+iopath==0.1.10
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+tzdata==2025.3
+psutil==7.2.2
+referencing==0.37.0
+grpcio==1.78.0
+nvidia-cusparse-cu12==12.5.7.53
+sentry-sdk==2.54.0
+httpcore==1.0.9
+opencv-python-headless==4.11.0.86
+omegaconf==2.3.0
+pandas==2.3.3
+eva-decord==0.6.1
+pip==26.0.1
+inflect==7.3.1
+jaraco.text==3.12.1
+autocommand==2.2.2
+backports.tarfile==1.2.0
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+more-itertools==10.3.0
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+typing_extensions==4.12.2
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+platformdirs==4.2.2
+importlib_metadata==8.0.0
+jaraco.collections==5.1.0
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wandb/wandb/run-20260402_174446-b7f4uglx/files/wandb-metadata.json

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+    "--framework.name",
+    "QwenDiscreteDiffusion",
+    "--framework.qwenvl.base_vlm",
+    "playground/Pretrained_models/Qwen2.5-VL-3B-Instruct-Action",
+    "--framework.qwenvl.vl_hidden_dim",
+    "4096",
+    "--framework.qwenvl.attn_implementation",
+    "flash_attention_2",
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+    "bin",
+    "--framework.action_model.num_bins",
+    "256",
+    "--framework.action_model.action_low",
+    "-1.0",
+    "--framework.action_model.action_high",
+    "1.0",
+    "--framework.action_model.num_inference_steps",
+    "8",
+    "--datasets.vla_data.data_root_dir",
+    "playground/Datasets/FastUMI",
+    "--datasets.vla_data.data_mix",
+    "dynamic-329-v4",
+    "--datasets.vla_data.include_state",
+    "false",
+    "--datasets.vla_data.per_device_batch_size",
+    "8",
+    "--datasets.vla_data.video_backend",
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+    "",
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+    "true",
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+    "100",
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+    "1",
+    "--run_root_dir",
+    "./results/Checkpoints",
+    "--run_id",
+    "fastumi_pickandplace_qwenDiscreteDiffusion_329v4",
+    "--wandb_project",
+    "starVLA_FastUMI_dynamic_1",
+    "--wandb_entity",
+    "2200011093-peking-university"
+  ],
+  "program":  "/scratch/wangpc/starVLA/starVLA/training/train_starvla.py",
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wandb/wandb/run-20260402_182806-6dhdda09/files/config.yaml

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+    value:
+        cli_version: 0.25.0
+        e:
+            5zu64iez7kgczugbmvfclqvtfokp8iw0:
+                args:
+                    - --config_yaml
+                    - starVLA/config/training/starvla_train_discrete_diffusion_real.yaml
+                    - --framework.name
+                    - QwenDiscreteDiffusion
+                    - --framework.qwenvl.base_vlm
+                    - playground/Pretrained_models/Qwen2.5-VL-3B-Instruct-Action
+                    - --framework.qwenvl.vl_hidden_dim
+                    - "4096"
+                    - --framework.qwenvl.attn_implementation
+                    - flash_attention_2
+                    - --framework.action_model.representation
+                    - bin
+                    - --framework.action_model.num_bins
+                    - "256"
+                    - --framework.action_model.action_low
+                    - "-1.0"
+                    - --framework.action_model.action_high
+                    - "1.0"
+                    - --framework.action_model.num_inference_steps
+                    - "8"
+                    - --datasets.vla_data.data_root_dir
+                    - playground/Datasets/FastUMI
+                    - --datasets.vla_data.data_mix
+                    - dynamic-329-v4
+                    - --datasets.vla_data.include_state
+                    - "false"
+                    - --datasets.vla_data.per_device_batch_size
+                    - "8"
+                    - --datasets.vla_data.video_backend
+                    - torchvision_av
+                    - --trainer.freeze_modules
+                    - ""
+                    - --trainer.is_resume
+                    - "true"
+                    - --trainer.max_train_steps
+                    - "20000"
+                    - --trainer.save_interval
+                    - "10000"
+                    - --trainer.logging_frequency
+                    - "50"
+                    - --trainer.eval_interval
+                    - "100"
+                    - --trainer.gradient_accumulation_steps
+                    - "1"
+                    - --run_root_dir
+                    - ./results/Checkpoints
+                    - --run_id
+                    - fastumi_pickandplace_qwenDiscreteDiffusion_329v4
+                    - --wandb_project
+                    - starVLA_FastUMI_dynamic_1
+                    - --wandb_entity
+                    - 2200011093-peking-university
+                codePath: starVLA/training/train_starvla.py
+                codePathLocal: starVLA/training/train_starvla.py
+                cpu_count: 192
+                cpu_count_logical: 384
+                cudaVersion: "13.1"
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