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QwenAdapter-0130-pre-fintune-v/checkpoints/steps_51000_pytorch_model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2401ef0016ae0a91893523307d0a495b8eda57ca65d71a4cd2019b74650b09e4
+size 6870058775

QwenAdapter-0130-pre-fintune-v/config.json

@@ -35,7 +35,7 @@
       "data_root_dir": "/lumos-vePFS/shenzhen/data/data_warehouse/data_warehouse_output",
       "data_mix": "train_internAdapter",
       "per_device_batch_size": 40,
-      "num_workers": 2,
+      "num_workers": 8,
       "action_type": "abs_ee",
       "image_size": 256,
       "video_backend": "pyav"
@@ -77,7 +77,7 @@
       "weight_decay": 0
     },
     "is_resume": true,
-    "resume_step": 36000
+    "resume_step": 40000
   },
   "is_resume": false,
   "resume_epoch": null,

QwenAdapter-0130-pre-fintune-v/config.yaml

@@ -1,76 +1,48 @@
-run_id: QwenAdapter-0130-pre-fintune+vit-eep
-run_root_dir: /root/jinchengp/LumosVLA/results
-seed: 42
-trackers:
-- jsonl
-- wandb
-wandb_entity: xspadex-nanyang-technological-university-singapore
-wandb_project: qwenvl-0130-pre-fintune+vit-eep
-is_debug: false
+datasets:
+  vla_data:
+    data_mix: train_internAdapter
+    data_root_dir: /lumos-vePFS/shenzhen/data/data_warehouse/data_warehouse_output
+    dataset_py: lerobot_datasets
+    num_workers: 8
+    per_device_batch_size: 40
 framework:
-  name: QwenAdapter
-  qwenvl:
-    base_vlm: /root/jinchengp/LumosVLA/base_vl/Qwen3-VL-2B-Instruct
-    attn_implementation: flash_attention_2
-    vl_hidden_dim: 2048
   action_model:
-    action_model_type: VLA-Adapter
-    hidden_dim: 2048
     action_dim: 20
-    state_dim: 20
     action_query_num: 64
+    hidden_dim: 2048
+    num_actions_chunk: 30
+    phase: Training
+    state_dim: 20
     use_pro_version: true
     use_proprio: true
-    phase: Training
-    num_actions_chunk: 30
-  framework_py: QwenAdapter
-datasets:
-  vla_data:
-    dataset_py: lerobot_datasets
-    data_root_dir: /lumos-vePFS/shenzhen/data/data_warehouse/data_warehouse_output
-    data_mix: train_internAdapter
-    per_device_batch_size: 40
-    num_workers: 2
-    action_type: abs_ee
-    image_size: 256
-    video_backend: pyav
+  name: QwenAdapter
+  qwenvl:
+    base_vlm: /root/jinchengp/LumosVLA/base_vl/Qwen3-VL-2B-Instruct
+    vl_hidden_dim: 2048
+output_dir: /root/jinchengp/LumosVLA/results/QwenAdapter-0130-pre-fintune+vit-eep
+run_id: QwenAdapter-0130-pre-fintune+vit-eep
+run_root_dir: /root/jinchengp/LumosVLA/results
+seed: 42
 trainer:
-  epochs: 100
-  max_train_steps: 85000
-  num_warmup_steps: 1000
-  save_interval: 1000
   eval_interval: 100000
+  freeze_modules: qwen_vl_interface.model.model.language_model
+  gradient_accumulation_steps: 1
+  gradient_clipping: 1.0
+  is_resume: true
   learning_rate:
+    action_model: 1.0e-05
     base: 4.0e-06
     qwen_vl_interface: 4.0e-06
-    action_model: 1.0e-05
-  lr_scheduler_type: cosine_with_min_lr
-  scheduler_specific_kwargs:
-    min_lr: 5.0e-07
-  freeze_modules: qwen_vl_interface.model.model.language_model
-  loss_scale:
-    vla: 1.0
-    vlm: 0.05
-  max_grad_norm: 1.0
-  warmup_ratio: 0.1
-  weight_decay: 0.0
   logging_frequency: 10
-  gradient_clipping: 1.0
-  gradient_accumulation_steps: 1
+  lr_scheduler_type: cosine_with_min_lr
+  max_train_steps: 85000
+  num_warmup_steps: 1000
   optimizer:
-    name: AdamW
     betas:
     - 0.9
     - 0.95
     eps: 1.0e-08
     weight_decay: 0
-  is_resume: true
-  resume_step: 36000
-is_resume: false
-resume_epoch: null
-resume_step: null
-enable_gradient_checkpointing: true
-enable_mixed_precision_training: true
-report_to: wandb
-wandb_run_name: v1
-output_dir: /root/jinchengp/LumosVLA/results/QwenAdapter-0130-pre-fintune+vit-eep
+  save_interval: 1000
+  scheduler_specific_kwargs:
+    min_lr: 5.0e-07

QwenAdapter-0130-pre-fintune-v/dataset_statistics.json

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 }