update
Browse files- .DS_Store +0 -0
- Real-world/checkpoints/VLA-JEPA-Real-World.pt +3 -0
- Real-world/config.json +114 -0
- Real-world/config.yaml +99 -0
- Real-world/dataset_statistics.json +133 -0
- Real-world/summary.jsonl +6 -0
- SimplerEnv/checkpoints/VLA-JEPA-SimplerEnv.pt +3 -0
- SimplerEnv/config.json +115 -0
- SimplerEnv/config.yaml +100 -0
- SimplerEnv/dataset_statistics.json +264 -0
- SimplerEnv/summary.jsonl +3 -0
.DS_Store
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Binary file (6.15 kB). View file
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Real-world/checkpoints/VLA-JEPA-Real-World.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:f1ab32b71d2c5f2f755bdb42d9815dece05446d288cbf38bd946c01981949779
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size 6163571823
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Real-world/config.json
ADDED
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@@ -0,0 +1,114 @@
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| 1 |
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{
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| 2 |
+
"run_id": "fr3_realworld",
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| 3 |
+
"run_root_dir": "checkpoints",
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| 4 |
+
"seed": 42,
|
| 5 |
+
"trackers": [
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| 6 |
+
"json"
|
| 7 |
+
],
|
| 8 |
+
"is_debug": false,
|
| 9 |
+
"framework": {
|
| 10 |
+
"name": "VLA_JEPA",
|
| 11 |
+
"qwenvl": {
|
| 12 |
+
"base_vlm": "/home/dataset-local/models/Qwen3-VL-2B-Instruct",
|
| 13 |
+
"attn_implementation": "flash_attention_2",
|
| 14 |
+
"vl_hidden_dim": 2048
|
| 15 |
+
},
|
| 16 |
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"action_model": {
|
| 17 |
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"action_model_type": "DiT-B",
|
| 18 |
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"action_hidden_dim": 1024,
|
| 19 |
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"hidden_size": 1024,
|
| 20 |
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"add_pos_embed": true,
|
| 21 |
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"max_seq_len": 1024,
|
| 22 |
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"action_dim": 7,
|
| 23 |
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"state_dim": 8,
|
| 24 |
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"future_action_window_size": 6,
|
| 25 |
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"action_horizon": 7,
|
| 26 |
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"past_action_window_size": 0,
|
| 27 |
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"repeated_diffusion_steps": 8,
|
| 28 |
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"noise_beta_alpha": 1.5,
|
| 29 |
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"noise_beta_beta": 1.0,
|
| 30 |
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"noise_s": 0.999,
|
| 31 |
+
"num_timestep_buckets": 1000,
|
| 32 |
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"num_inference_timesteps": 4,
|
| 33 |
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"num_target_vision_tokens": 32,
|
| 34 |
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"diffusion_model_cfg": {
|
| 35 |
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"cross_attention_dim": 2048,
|
| 36 |
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"dropout": 0.2,
|
| 37 |
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"final_dropout": true,
|
| 38 |
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"interleave_self_attention": true,
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| 39 |
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"norm_type": "ada_norm",
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| 40 |
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"num_layers": 16,
|
| 41 |
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"output_dim": 1024,
|
| 42 |
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"positional_embeddings": null
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| 43 |
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}
|
| 44 |
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},
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| 45 |
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"vj2_model": {
|
| 46 |
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"base_encoder": "/home/dataset-local/models/vjepa2-vitl-fpc64-256",
|
| 47 |
+
"depth": 12,
|
| 48 |
+
"num_heads": 8,
|
| 49 |
+
"special_action_token": "<|action_{}|>",
|
| 50 |
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"num_action_tokens_per_timestep": 8,
|
| 51 |
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"embodied_action_token": "<|embodied_action|>",
|
| 52 |
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"num_embodied_action_tokens_per_instruction": 32,
|
| 53 |
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"num_frames": 8
|
| 54 |
+
},
|
| 55 |
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"reduce_in_full_precision": true
|
| 56 |
+
},
|
| 57 |
+
"datasets": {
|
| 58 |
+
"vla_data": {
|
| 59 |
+
"dataset_py": "lerobot_datasets",
|
| 60 |
+
"data_root_dir": "/home/dataset-local/datasets/LeRobot/lerobot_simple_pp_starvla",
|
| 61 |
+
"data_mix": "fr3_realworld",
|
| 62 |
+
"action_type": "delta_qpos",
|
| 63 |
+
"CoT_prompt": "Your task is {instruction}. Infer the temporal dynamics from frames {actions} and produce the corresponding policy actions {e_actions}.",
|
| 64 |
+
"resolution_size": 224,
|
| 65 |
+
"per_device_batch_size": 8,
|
| 66 |
+
"video_resolution_size": 256,
|
| 67 |
+
"load_all_data_for_training": true,
|
| 68 |
+
"with_state": true
|
| 69 |
+
}
|
| 70 |
+
},
|
| 71 |
+
"trainer": {
|
| 72 |
+
"epochs": 100,
|
| 73 |
+
"max_train_steps": 20000,
|
| 74 |
+
"num_warmup_steps": 5000,
|
| 75 |
+
"save_interval": 5000,
|
| 76 |
+
"eval_interval": 100,
|
| 77 |
+
"learning_rate": {
|
| 78 |
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"base": 3e-05,
|
| 79 |
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"qwen_vl_interface": 1e-05,
|
| 80 |
+
"action_model": 0.0001
|
| 81 |
+
},
|
| 82 |
+
"lr_scheduler_type": "cosine_with_min_lr",
|
| 83 |
+
"scheduler_specific_kwargs": {
|
| 84 |
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"min_lr": 1e-06
|
| 85 |
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},
|
| 86 |
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"freeze_modules": "",
|
| 87 |
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"loss_scale": {
|
| 88 |
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"vla": 1.0,
|
| 89 |
+
"vlm": 0.1
|
| 90 |
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},
|
| 91 |
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"max_grad_norm": 1.0,
|
| 92 |
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"warmup_ratio": 0.1,
|
| 93 |
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"weight_decay": 0.0,
|
| 94 |
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"logging_frequency": 10,
|
| 95 |
+
"gradient_clipping": 1.0,
|
| 96 |
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"gradient_accumulation_steps": 1,
|
| 97 |
+
"pretrained_checkpoint": "/home/dataset-local/VLA_JEPA/checkpoints/pretrain/VLA-JEPA-pretrain.pt",
|
| 98 |
+
"optimizer": {
|
| 99 |
+
"name": "AdamW",
|
| 100 |
+
"betas": [
|
| 101 |
+
0.9,
|
| 102 |
+
0.95
|
| 103 |
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],
|
| 104 |
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"eps": 1e-08,
|
| 105 |
+
"weight_decay": 1e-08
|
| 106 |
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},
|
| 107 |
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"is_resume": false,
|
| 108 |
+
"resume_epoch": null,
|
| 109 |
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"resume_step": null,
|
| 110 |
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"enable_gradient_checkpointing": true,
|
| 111 |
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"enable_mixed_precision_training": true
|
| 112 |
+
},
|
| 113 |
+
"output_dir": "checkpoints/fr3_realworld"
|
| 114 |
+
}
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Real-world/config.yaml
ADDED
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@@ -0,0 +1,99 @@
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| 1 |
+
run_id: fr3_realworld
|
| 2 |
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run_root_dir: checkpoints
|
| 3 |
+
seed: 42
|
| 4 |
+
trackers:
|
| 5 |
+
- json
|
| 6 |
+
is_debug: false
|
| 7 |
+
framework:
|
| 8 |
+
name: VLA_JEPA
|
| 9 |
+
qwenvl:
|
| 10 |
+
base_vlm: /home/dataset-local/models/Qwen3-VL-2B-Instruct
|
| 11 |
+
attn_implementation: flash_attention_2
|
| 12 |
+
vl_hidden_dim: 2048
|
| 13 |
+
action_model:
|
| 14 |
+
action_model_type: DiT-B
|
| 15 |
+
action_hidden_dim: 1024
|
| 16 |
+
hidden_size: 1024
|
| 17 |
+
add_pos_embed: true
|
| 18 |
+
max_seq_len: 1024
|
| 19 |
+
action_dim: 7
|
| 20 |
+
state_dim: 8
|
| 21 |
+
future_action_window_size: 6
|
| 22 |
+
action_horizon: 7
|
| 23 |
+
past_action_window_size: 0
|
| 24 |
+
repeated_diffusion_steps: 8
|
| 25 |
+
noise_beta_alpha: 1.5
|
| 26 |
+
noise_beta_beta: 1.0
|
| 27 |
+
noise_s: 0.999
|
| 28 |
+
num_timestep_buckets: 1000
|
| 29 |
+
num_inference_timesteps: 4
|
| 30 |
+
num_target_vision_tokens: 32
|
| 31 |
+
diffusion_model_cfg:
|
| 32 |
+
cross_attention_dim: 2048
|
| 33 |
+
dropout: 0.2
|
| 34 |
+
final_dropout: true
|
| 35 |
+
interleave_self_attention: true
|
| 36 |
+
norm_type: ada_norm
|
| 37 |
+
num_layers: 16
|
| 38 |
+
output_dim: 1024
|
| 39 |
+
positional_embeddings: null
|
| 40 |
+
vj2_model:
|
| 41 |
+
base_encoder: /home/dataset-local/models/vjepa2-vitl-fpc64-256
|
| 42 |
+
depth: 12
|
| 43 |
+
num_heads: 8
|
| 44 |
+
special_action_token: <|action_{}|>
|
| 45 |
+
num_action_tokens_per_timestep: 8
|
| 46 |
+
embodied_action_token: <|embodied_action|>
|
| 47 |
+
num_embodied_action_tokens_per_instruction: 32
|
| 48 |
+
num_frames: 8
|
| 49 |
+
reduce_in_full_precision: true
|
| 50 |
+
datasets:
|
| 51 |
+
vla_data:
|
| 52 |
+
dataset_py: lerobot_datasets
|
| 53 |
+
data_root_dir: /home/dataset-local/datasets/LeRobot/lerobot_simple_pp_starvla
|
| 54 |
+
data_mix: fr3_realworld
|
| 55 |
+
action_type: delta_qpos
|
| 56 |
+
CoT_prompt: Your task is {instruction}. Infer the temporal dynamics from frames
|
| 57 |
+
{actions} and produce the corresponding policy actions {e_actions}.
|
| 58 |
+
resolution_size: 224
|
| 59 |
+
per_device_batch_size: 8
|
| 60 |
+
video_resolution_size: 256
|
| 61 |
+
load_all_data_for_training: true
|
| 62 |
+
with_state: true
|
| 63 |
+
trainer:
|
| 64 |
+
epochs: 100
|
| 65 |
+
max_train_steps: 20000
|
| 66 |
+
num_warmup_steps: 5000
|
| 67 |
+
save_interval: 5000
|
| 68 |
+
eval_interval: 100
|
| 69 |
+
learning_rate:
|
| 70 |
+
base: 3.0e-05
|
| 71 |
+
qwen_vl_interface: 1.0e-05
|
| 72 |
+
action_model: 0.0001
|
| 73 |
+
lr_scheduler_type: cosine_with_min_lr
|
| 74 |
+
scheduler_specific_kwargs:
|
| 75 |
+
min_lr: 1.0e-06
|
| 76 |
+
freeze_modules: ''
|
| 77 |
+
loss_scale:
|
| 78 |
+
vla: 1.0
|
| 79 |
+
vlm: 0.1
|
| 80 |
+
max_grad_norm: 1.0
|
| 81 |
+
warmup_ratio: 0.1
|
| 82 |
+
weight_decay: 0.0
|
| 83 |
+
logging_frequency: 10
|
| 84 |
+
gradient_clipping: 1.0
|
| 85 |
+
gradient_accumulation_steps: 1
|
| 86 |
+
pretrained_checkpoint: /home/dataset-local/VLA_JEPA/checkpoints/pretrain/VLA-JEPA-pretrain.pt
|
| 87 |
+
optimizer:
|
| 88 |
+
name: AdamW
|
| 89 |
+
betas:
|
| 90 |
+
- 0.9
|
| 91 |
+
- 0.95
|
| 92 |
+
eps: 1.0e-08
|
| 93 |
+
weight_decay: 1.0e-08
|
| 94 |
+
is_resume: false
|
| 95 |
+
resume_epoch: null
|
| 96 |
+
resume_step: null
|
| 97 |
+
enable_gradient_checkpointing: true
|
| 98 |
+
enable_mixed_precision_training: true
|
| 99 |
+
output_dir: checkpoints/fr3_realworld
|
Real-world/dataset_statistics.json
ADDED
|
@@ -0,0 +1,133 @@
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SimplerEnv/checkpoints/VLA-JEPA-SimplerEnv.pt
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SimplerEnv/config.json
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| 14 |
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| 47 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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| 64 |
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"resolution_size": 224,
|
| 65 |
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|
| 66 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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}
|
| 71 |
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},
|
| 72 |
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"trainer": {
|
| 73 |
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|
| 74 |
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|
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| 76 |
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|
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| 81 |
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|
| 83 |
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| 85 |
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|
| 114 |
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|
| 115 |
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|
SimplerEnv/config.yaml
ADDED
|
@@ -0,0 +1,100 @@
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|
| 1 |
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run_id: SimplerEnv
|
| 2 |
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run_root_dir: checkpoints
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seed: 42
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| 4 |
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trackers:
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- json
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| 6 |
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is_debug: false
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| 7 |
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framework:
|
| 8 |
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name: VLA_JEPA
|
| 9 |
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qwenvl:
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base_vlm: /home/dataset-local/models/Qwen3-VL-2B-Instruct
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| 11 |
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attn_implementation: flash_attention_2
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vl_hidden_dim: 2048
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| 13 |
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action_model:
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action_model_type: DiT-B
|
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action_hidden_dim: 1024
|
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hidden_size: 1024
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add_pos_embed: true
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max_seq_len: 1024
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action_dim: 7
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state_dim: 8
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future_action_window_size: 6
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action_horizon: 7
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| 23 |
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past_action_window_size: 0
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repeated_diffusion_steps: 8
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| 25 |
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noise_beta_alpha: 1.5
|
| 26 |
+
noise_beta_beta: 1.0
|
| 27 |
+
noise_s: 0.999
|
| 28 |
+
num_timestep_buckets: 1000
|
| 29 |
+
num_inference_timesteps: 4
|
| 30 |
+
num_target_vision_tokens: 32
|
| 31 |
+
diffusion_model_cfg:
|
| 32 |
+
cross_attention_dim: 2048
|
| 33 |
+
dropout: 0.2
|
| 34 |
+
final_dropout: true
|
| 35 |
+
interleave_self_attention: true
|
| 36 |
+
norm_type: ada_norm
|
| 37 |
+
num_layers: 16
|
| 38 |
+
output_dim: 1024
|
| 39 |
+
positional_embeddings: null
|
| 40 |
+
vj2_model:
|
| 41 |
+
base_encoder: /home/dataset-local/models/vjepa2-vitl-fpc64-256
|
| 42 |
+
depth: 12
|
| 43 |
+
num_heads: 8
|
| 44 |
+
special_action_token: <|action_{}|>
|
| 45 |
+
num_action_tokens_per_timestep: 8
|
| 46 |
+
embodied_action_token: <|embodied_action|>
|
| 47 |
+
num_embodied_action_tokens_per_instruction: 32
|
| 48 |
+
num_frames: 8
|
| 49 |
+
reduce_in_full_precision: true
|
| 50 |
+
datasets:
|
| 51 |
+
vla_data:
|
| 52 |
+
dataset_py: lerobot_datasets
|
| 53 |
+
data_root_dir: /home/dataset-local/datasets/LeRobot/OXE_LEROBOT_DATASET
|
| 54 |
+
data_mix: bridge_rt_1
|
| 55 |
+
action_type: delta_ee
|
| 56 |
+
CoT_prompt: Your task is {instruction}. Infer the temporal dynamics from frames
|
| 57 |
+
{actions} and produce the corresponding policy actions {e_actions}.
|
| 58 |
+
resolution_size: 224
|
| 59 |
+
video_resolution_size: 256
|
| 60 |
+
per_device_batch_size: 32
|
| 61 |
+
load_all_data_for_training: true
|
| 62 |
+
action_horizon: 7
|
| 63 |
+
with_state: false
|
| 64 |
+
trainer:
|
| 65 |
+
epochs: 100
|
| 66 |
+
max_train_steps: 30000
|
| 67 |
+
num_warmup_steps: 5000
|
| 68 |
+
save_interval: 10000
|
| 69 |
+
eval_interval: 100
|
| 70 |
+
learning_rate:
|
| 71 |
+
base: 3.0e-05
|
| 72 |
+
qwen_vl_interface: 1.0e-05
|
| 73 |
+
action_model: 0.0001
|
| 74 |
+
vj_predictor: 0.0005
|
| 75 |
+
lr_scheduler_type: cosine_with_min_lr
|
| 76 |
+
scheduler_specific_kwargs:
|
| 77 |
+
min_lr: 1.0e-05
|
| 78 |
+
freeze_modules: ''
|
| 79 |
+
loss_scale:
|
| 80 |
+
vla: 1.0
|
| 81 |
+
vlm: 0.1
|
| 82 |
+
max_grad_norm: 1.0
|
| 83 |
+
warmup_ratio: 0.1
|
| 84 |
+
weight_decay: 0.0
|
| 85 |
+
logging_frequency: 10
|
| 86 |
+
gradient_clipping: 1.0
|
| 87 |
+
gradient_accumulation_steps: 1
|
| 88 |
+
optimizer:
|
| 89 |
+
name: AdamW
|
| 90 |
+
betas:
|
| 91 |
+
- 0.9
|
| 92 |
+
- 0.95
|
| 93 |
+
eps: 1.0e-08
|
| 94 |
+
weight_decay: 1.0e-08
|
| 95 |
+
is_resume: false
|
| 96 |
+
resume_epoch: null
|
| 97 |
+
resume_step: null
|
| 98 |
+
enable_gradient_checkpointing: true
|
| 99 |
+
enable_mixed_precision_training: true
|
| 100 |
+
output_dir: checkpoints/SimplerEnv
|
SimplerEnv/dataset_statistics.json
ADDED
|
@@ -0,0 +1,264 @@
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| 1 |
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{
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|
| 205 |
+
0.24756911396980286,
|
| 206 |
+
0.046330634504556656,
|
| 207 |
+
0.10487449914216995,
|
| 208 |
+
0.21306729316711426
|
| 209 |
+
],
|
| 210 |
+
"std": [
|
| 211 |
+
0.29342642876909925,
|
| 212 |
+
0.09174024655686211,
|
| 213 |
+
0.42569508885539115,
|
| 214 |
+
0.38314586427420927,
|
| 215 |
+
0.44433568806919804,
|
| 216 |
+
0.1263927443679382,
|
| 217 |
+
0.22122596673781084,
|
| 218 |
+
0.38616252611341306
|
| 219 |
+
],
|
| 220 |
+
"max": [
|
| 221 |
+
1.0534898042678833,
|
| 222 |
+
0.48018959164619446,
|
| 223 |
+
1.6896663904190063,
|
| 224 |
+
0.9999993443489075,
|
| 225 |
+
0.9999874830245972,
|
| 226 |
+
0.9554369449615479,
|
| 227 |
+
0.9914546012878418,
|
| 228 |
+
1.0
|
| 229 |
+
],
|
| 230 |
+
"min": [
|
| 231 |
+
-0.4436439275741577,
|
| 232 |
+
-0.9970501065254211,
|
| 233 |
+
-0.006579156965017319,
|
| 234 |
+
-0.8643477559089661,
|
| 235 |
+
-0.7079970240592957,
|
| 236 |
+
-0.7688722014427185,
|
| 237 |
+
-0.4999994933605194,
|
| 238 |
+
0.0
|
| 239 |
+
],
|
| 240 |
+
"q01": [
|
| 241 |
+
0.3248138129711151,
|
| 242 |
+
-0.2833428978919983,
|
| 243 |
+
0.14107070863246918,
|
| 244 |
+
-0.6864742040634155,
|
| 245 |
+
-0.6808923482894897,
|
| 246 |
+
-0.3604559600353241,
|
| 247 |
+
-0.45438095927238464,
|
| 248 |
+
0.0
|
| 249 |
+
],
|
| 250 |
+
"q99": [
|
| 251 |
+
0.8750156164169312,
|
| 252 |
+
0.21247053146362305,
|
| 253 |
+
1.0727112293243408,
|
| 254 |
+
0.9377871155738831,
|
| 255 |
+
0.9563050866127014,
|
| 256 |
+
0.4599004089832306,
|
| 257 |
+
0.7216041088104248,
|
| 258 |
+
1.0
|
| 259 |
+
]
|
| 260 |
+
},
|
| 261 |
+
"num_transitions": 3449894,
|
| 262 |
+
"num_trajectories": 87212
|
| 263 |
+
}
|
| 264 |
+
}
|
SimplerEnv/summary.jsonl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{"steps": 10000}
|
| 2 |
+
{"steps": 20000}
|
| 3 |
+
{"steps": 30000}
|