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@@ -33,3 +33,10 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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 *.zst filter=lfs diff=lfs merge=lfs -text
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+sys12_meta_query_action_only_sync_pretraining_v2_query_64_mlp_lora_reimplement_history=1_state--image_augstage1.jsonl filter=lfs diff=lfs merge=lfs -text

checkpoints/action_model_55500/README.md

@@ -0,0 +1,202 @@
+---
+base_model: ./pretrained/Qwen2_5-1_5B-Instruct
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.13.0

checkpoints/action_model_55500/adapter_config.json

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+{
+  "alpha_pattern": {},
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+  "base_model_name_or_path": "./pretrained/Qwen2_5-1_5B-Instruct",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 256,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 128,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "mlp.up_proj",
+    "self_attn.o_proj",
+    "mlp.down_proj",
+    "self_attn.v_proj",
+    "self_attn.q_proj",
+    "self_attn.k_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

checkpoints/action_model_55500/adapter_model.safetensors

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checkpoints/action_model_55500_unload.pt

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config.json

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+{
+  "action_dim": 7,
+  "action_model_type": "DiT-B",
+  "data_root_dir": "s3://real_data_raw/open_x_embodiment_origin",
+  "debug": false,
+  "disable_instruction": false,
+  "fix_system1": false,
+  "future_action_window_size": 15,
+  "hf_token": "hf_token",
+  "image_aug": true,
+  "is_resume": false,
+  "load_all_data_for_training": true,
+  "num_of_meta_query": 64,
+  "past_action_window_size": 0,
+  "pretrained_checkpoint": null,
+  "repeated_diffusion_steps": 4,
+  "resume_epoch": null,
+  "resume_step": null,
+  "run_id": "sys12_meta_query_action_only_sync_pretraining_v2_query_64_mlp_lora_reimplement_history=1_state--image_augstage1",
+  "run_id_note": null,
+  "run_root_dir": "outputs/code_reimp",
+  "save_interval": 1500,
+  "seed": 42,
+  "stage": "stage1",
+  "trackers": [
+    "jsonl",
+    "wandb"
+  ],
+  "use_ema": false,
+  "use_mm": false,
+  "vla": {
+    "action_tokenizer": "extra_action_tokenizer",
+    "base_vlm": "/mnt/petrelfs/yangshuai1/yangshuai1/share_mllm/Eagle2-2B",
+    "data_mix": "bridge_rt_1",
+    "enable_gradient_checkpointing": true,
+    "enable_mixed_precision_training": true,
+    "epochs": 100,
+    "expected_world_size": 64,
+    "freeze_llm_backbone": false,
+    "freeze_vision_backbone": false,
+    "global_batch_size": 896,
+    "learning_rate": 5e-05,
+    "lr_scheduler_type": "constant",
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+    "shuffle_buffer_size": 250000,
+    "train_strategy": "fsdp-shard-grad-op",
+    "type": "prism-qwen25-dinosiglip-224px+0_5b",
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+    "vla_id": "prism-qwen25-dinosiglip-224px+0_5b",
+    "warmup_ratio": 0.0,
+    "weight_decay": 0.0
+  },
+  "wandb_entity": "shuaiyang2003",
+  "wandb_project": "dual_sys"
+}

config.yaml

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+action_dim: 7
+action_model_type: DiT-B
+data_root_dir: s3://real_data_raw/open_x_embodiment_origin
+debug: false
+disable_instruction: false
+fix_system1: false
+future_action_window_size: 15
+hf_token: hf_token
+image_aug: true
+is_resume: false
+load_all_data_for_training: true
+num_of_meta_query: 64
+past_action_window_size: 0
+pretrained_checkpoint: null
+repeated_diffusion_steps: 4
+resume_epoch: null
+resume_step: null
+run_id: sys12_meta_query_action_only_sync_pretraining_v2_query_64_mlp_lora_reimplement_history=1_state--image_augstage1
+run_id_note: null
+run_root_dir: outputs/code_reimp
+save_interval: 1500
+seed: 42
+stage: stage1
+trackers:
+- jsonl
+- wandb
+use_ema: false
+use_mm: false
+vla:
+  action_tokenizer: extra_action_tokenizer
+  base_vlm: /mnt/petrelfs/yangshuai1/yangshuai1/share_mllm/Eagle2-2B
+  data_mix: bridge_rt_1
+  enable_gradient_checkpointing: true
+  enable_mixed_precision_training: true
+  epochs: 100
+  expected_world_size: 64
+  freeze_llm_backbone: false
+  freeze_vision_backbone: false
+  global_batch_size: 896
+  learning_rate: 5.0e-05
+  lr_scheduler_type: constant
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+  reduce_in_full_precision: true
+  shuffle_buffer_size: 250000
+  train_strategy: fsdp-shard-grad-op
+  type: prism-qwen25-dinosiglip-224px+0_5b
+  unfreeze_last_llm_layer: false
+  vla_id: prism-qwen25-dinosiglip-224px+0_5b
+  warmup_ratio: 0.0
+  weight_decay: 0.0
+wandb_entity: shuaiyang2003
+wandb_project: dual_sys

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results_step-055500-epoch-08-loss=0.0819_1/log/final_result.log

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+***Pick coke can results***
+--------------------
+horizontal sim variant avg success {'CogACT-Base': 1.0}
+vertical sim variant avg success {'CogACT-Base': 0.9200000000000002}
+standing sim variant avg success {'CogACT-Base': 0.9733333333333333}
+avg_orientation_sim_variant_results [0.9644444444444445]
+--------------------
+Orientation horizontal, ckpt CogACT-Base all robot arm visual matching success: [1.0, 1.0, 1.0, 1.0]
+Orientation vertical, ckpt CogACT-Base all robot arm visual matching success: [0.8, 0.92, 0.96, 0.92]
+Orientation standing, ckpt CogACT-Base all robot arm visual matching success: [1.0, 1.0, 0.96, 0.92]
+horizontal visual matching sim success {'CogACT-Base': 1.0}
+vertical visual matching sim success {'CogACT-Base': 0.9}
+standing visual matching sim success {'CogACT-Base': 0.97}
+avg_orientation_sim_visual_matching_results [0.9566666666666667]
+********************
+
+
+
+***Move Near results***
+--------------------
+sim variant avg success {'CogACT-Base': 0.8166666666666667}
+--------------------
+Ckpt CogACT-Base all robot arm visual matching success: [0.6666666666666666, 0.6666666666666666, 0.7166666666666667, 0.8333333333333334]
+sim visual matching success {'CogACT-Base': 0.7208333333333333}
+********************
+
+
+
+***Drawer results***
+--------------------
+open sim variant avg success {'CogACT-Base': 0.3121693121693121}
+close sim variant avg success {'CogACT-Base': 0.7195767195767194}
+avg_sim_variant_results [0.5158730158730158]
+--------------------
+Drawer task open, ckpt CogACT-Base all robot arm visual matching success: [0.2777777777777778, 0.33333333333333326, 0.4444444444444444, 0.22222222222222224]
+Drawer task close, ckpt CogACT-Base all robot arm visual matching success: [0.4722222222222222, 0.6666666666666666, 0.5277777777777778, 0.48148148148148145]
+open visual matching sim success {'CogACT-Base': 0.3518518518518518}
+close visual matching sim success {'CogACT-Base': 0.5555555555555556}
+avg_sim_visual_matching_results [0.4537037037037037]
+********************
+
+
+
+***Drawer results***
+--------------------
+put_apple_into_top_drawer sim variant avg success {'CogACT-Base': 0.7248677248677249}
+avg_sim_variant_results [0.7248677248677249]
+--------------------
+Drawer task put_apple_into_top_drawer, ckpt CogACT-Base all robot arm visual matching success: [0.37037037037037035, 0.3950617283950617, 0.42592592592592593, 0.4074074074074074]
+put_apple_into_top_drawer visual matching sim success {'CogACT-Base': 0.37037037037037035}
+avg_sim_visual_matching_results [0.37037037037037035]
+********************
+
+
+
+***Bridge Put On Env results***
+********** Results for put_spoon_on_tablecloth **********
+sim visual matching partial success {'CogACT-Base': 0.625}
+sim visual matching success {'CogACT-Base': 0.4583333333333333}
+********************
+
+
+
+********** Results for put_carrot_on_plate **********
+sim visual matching partial success {'CogACT-Base': 0.625}
+sim visual matching success {'CogACT-Base': 0.625}
+********************
+
+
+
+********** Results for stack_green_block_on_yellow_block **********
+sim visual matching partial success {'CogACT-Base': 0.6666666666666666}
+sim visual matching success {'CogACT-Base': 0.20833333333333334}
+********************
+
+
+
+********** Results for put_eggplant_in_basket **********
+sim visual matching partial success {'CogACT-Base': 0.08333333333333333}
+sim visual matching success {'CogACT-Base': 0.0}
+********************
+
+
+
+
+google_var:
+96.4
+96.4
+81.7
+81.7
+51.6
+51.6
+72.5
+72.5
+
+google_matching
+95.7
+95.7
+72.1
+72.1
+45.4
+45.4
+37.0
+37.0
+
+widowx_matching
+45.8
+45.8
+62.5
+62.5
+20.8
+20.8
+0.0
+0.0

results_step-055500-epoch-08-loss=0.0819_1/log/log3.log

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+oid sha256:8284224cc0ecb6fee08f9e9e698ec31f6c21663295b3c0e980a853563b99cc5a
+size 13997151

results_step-055500-epoch-08-loss=0.0819_1/log/log7.log

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+oid sha256:a014a667601b152d7611621d5491ae932430921ddab04cd11986f3cf5cbd641f
+size 26752902

results_step-055500-epoch-08-loss=0.0819_2/log/final_result.log

@@ -0,0 +1,114 @@
+***Pick coke can results***
+--------------------
+horizontal sim variant avg success {'CogACT-Base': 1.0}
+vertical sim variant avg success {'CogACT-Base': 0.9377777777777777}
+standing sim variant avg success {'CogACT-Base': 0.9600000000000001}
+avg_orientation_sim_variant_results [0.965925925925926]
+--------------------
+Orientation horizontal, ckpt CogACT-Base all robot arm visual matching success: [1.0, 0.96, 0.96, 1.0]
+Orientation vertical, ckpt CogACT-Base all robot arm visual matching success: [0.88, 0.92, 0.92, 0.96]
+Orientation standing, ckpt CogACT-Base all robot arm visual matching success: [0.96, 0.92, 0.96, 1.0]
+horizontal visual matching sim success {'CogACT-Base': 0.98}
+vertical visual matching sim success {'CogACT-Base': 0.92}
+standing visual matching sim success {'CogACT-Base': 0.96}
+avg_orientation_sim_visual_matching_results [0.9533333333333333]
+********************
+
+
+
+***Move Near results***
+--------------------
+sim variant avg success {'CogACT-Base': 0.8}
+--------------------
+Ckpt CogACT-Base all robot arm visual matching success: [0.7666666666666667, 0.7666666666666667, 0.7666666666666667, 0.7]
+sim visual matching success {'CogACT-Base': 0.75}
+********************
+
+
+
+***Drawer results***
+--------------------
+open sim variant avg success {'CogACT-Base': 0.37037037037037035}
+close sim variant avg success {'CogACT-Base': 0.708994708994709}
+avg_sim_variant_results [0.5396825396825397]
+--------------------
+Drawer task open, ckpt CogACT-Base all robot arm visual matching success: [0.4444444444444444, 0.3333333333333333, 0.24999999999999997, 0.4444444444444444]
+Drawer task close, ckpt CogACT-Base all robot arm visual matching success: [0.5555555555555556, 0.5833333333333333, 0.5555555555555556, 0.5185185185185185]
+open visual matching sim success {'CogACT-Base': 0.3425925925925926}
+close visual matching sim success {'CogACT-Base': 0.5648148148148148}
+avg_sim_visual_matching_results [0.4537037037037037]
+********************
+
+
+
+***Drawer results***
+--------------------
+put_apple_into_top_drawer sim variant avg success {'CogACT-Base': 0.6666666666666667}
+avg_sim_variant_results [0.6666666666666667]
+--------------------
+Drawer task put_apple_into_top_drawer, ckpt CogACT-Base all robot arm visual matching success: [0.46296296296296297, 0.46913580246913583, 0.537037037037037, 0.5555555555555556]
+put_apple_into_top_drawer visual matching sim success {'CogACT-Base': 0.46296296296296297}
+avg_sim_visual_matching_results [0.46296296296296297]
+********************
+
+
+
+***Bridge Put On Env results***
+********** Results for put_spoon_on_tablecloth **********
+sim visual matching partial success {'CogACT-Base': 0.75}
+sim visual matching success {'CogACT-Base': 0.5416666666666666}
+********************
+
+
+
+********** Results for put_carrot_on_plate **********
+sim visual matching partial success {'CogACT-Base': 0.625}
+sim visual matching success {'CogACT-Base': 0.5}
+********************
+
+
+
+********** Results for stack_green_block_on_yellow_block **********
+sim visual matching partial success {'CogACT-Base': 0.6666666666666666}
+sim visual matching success {'CogACT-Base': 0.375}
+********************
+
+
+
+********** Results for put_eggplant_in_basket **********
+sim visual matching partial success {'CogACT-Base': 0.08333333333333333}
+sim visual matching success {'CogACT-Base': 0.0}
+********************
+
+
+
+
+google_var:
+96.6
+96.6
+80.0
+80.0
+54.0
+54.0
+66.7
+66.7
+
+google_matching
+95.3
+95.3
+75.0
+75.0
+45.4
+45.4
+46.3
+46.3
+
+widowx_matching
+54.2
+54.2
+50.0
+50.0
+37.5
+37.5
+0.0
+0.0

results_step-055500-epoch-08-loss=0.0819_2/log/log3.log

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+oid sha256:f4031b66da59bdadfdeccf265769f73971969481a9c6efddb85ae7d9ec1fd080
+size 13996803

results_step-055500-epoch-08-loss=0.0819_2/log/log7.log

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+size 26756126

results_step-055500-epoch-08-loss=0.0819_3/log/final_result.log

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+***Pick coke can results***
+--------------------
+horizontal sim variant avg success {'CogACT-Base': 0.991111111111111}
+vertical sim variant avg success {'CogACT-Base': 0.9377777777777777}
+standing sim variant avg success {'CogACT-Base': 0.9688888888888889}
+avg_orientation_sim_variant_results [0.965925925925926]
+--------------------
+Orientation horizontal, ckpt CogACT-Base all robot arm visual matching success: [1.0, 1.0, 1.0, 1.0]
+Orientation vertical, ckpt CogACT-Base all robot arm visual matching success: [0.96, 0.96, 0.92, 0.92]
+Orientation standing, ckpt CogACT-Base all robot arm visual matching success: [1.0, 0.88, 0.96, 0.96]
+horizontal visual matching sim success {'CogACT-Base': 1.0}
+vertical visual matching sim success {'CogACT-Base': 0.94}
+standing visual matching sim success {'CogACT-Base': 0.95}
+avg_orientation_sim_visual_matching_results [0.9633333333333333]
+********************
+
+
+
+***Move Near results***
+--------------------
+sim variant avg success {'CogACT-Base': 0.84375}
+--------------------
+Ckpt CogACT-Base all robot arm visual matching success: [0.9, 0.7666666666666667, 0.8, 0.8166666666666667]
+sim visual matching success {'CogACT-Base': 0.8208333333333333}
+********************
+
+
+
+***Drawer results***
+--------------------
+open sim variant avg success {'CogACT-Base': 0.3650793650793651}
+close sim variant avg success {'CogACT-Base': 0.7248677248677248}
+avg_sim_variant_results [0.5449735449735449]
+--------------------
+Drawer task open, ckpt CogACT-Base all robot arm visual matching success: [0.3055555555555555, 0.2777777777777778, 0.44444444444444436, 0.25925925925925924]
+Drawer task close, ckpt CogACT-Base all robot arm visual matching success: [0.5277777777777777, 0.6111111111111112, 0.6666666666666666, 0.5555555555555556]
+open visual matching sim success {'CogACT-Base': 0.34259259259259256}
+close visual matching sim success {'CogACT-Base': 0.6018518518518519}
+avg_sim_visual_matching_results [0.4722222222222222]
+********************
+
+
+
+***Drawer results***
+--------------------
+put_apple_into_top_drawer sim variant avg success {'CogACT-Base': 0.6984126984126985}
+avg_sim_variant_results [0.6984126984126985]
+--------------------
+Drawer task put_apple_into_top_drawer, ckpt CogACT-Base all robot arm visual matching success: [0.45370370370370366, 0.419753086419753, 0.4629629629629629, 0.48148148148148145]
+put_apple_into_top_drawer visual matching sim success {'CogACT-Base': 0.45370370370370366}
+avg_sim_visual_matching_results [0.45370370370370366]
+********************
+
+
+
+***Bridge Put On Env results***
+********** Results for put_spoon_on_tablecloth **********
+sim visual matching partial success {'CogACT-Base': 0.7916666666666666}
+sim visual matching success {'CogACT-Base': 0.6666666666666666}
+********************
+
+
+
+********** Results for put_carrot_on_plate **********
+sim visual matching partial success {'CogACT-Base': 0.625}
+sim visual matching success {'CogACT-Base': 0.5}
+********************
+
+
+
+********** Results for stack_green_block_on_yellow_block **********
+sim visual matching partial success {'CogACT-Base': 0.7916666666666666}
+sim visual matching success {'CogACT-Base': 0.375}
+********************
+
+
+
+********** Results for put_eggplant_in_basket **********
+sim visual matching partial success {'CogACT-Base': 0.2916666666666667}
+sim visual matching success {'CogACT-Base': 0.08333333333333333}
+********************
+
+
+
+
+google_var:
+96.6
+96.6
+84.4
+84.4
+54.5
+54.5
+69.8
+69.8
+
+google_matching
+96.3
+96.3
+82.1
+82.1
+47.2
+47.2
+45.4
+45.4
+
+widowx_matching
+66.7
+66.7
+50.0
+50.0
+37.5
+37.5
+8.3
+8.3

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results_step-055500-epoch-08-loss=0.0819_instruct_1/log/final_results_instruct.log

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+Alt,AltPutSponeOnPlateInScene-v0,0.2083
+
+Category,Average_Success_Rate
+Free,0.2119
+Alt,0.2134

results_step-055500-epoch-08-loss=0.0819_instruct_2/log/final_results_instruct.log

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+
+Category,Average_Success_Rate
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