M2W-VLA-LIBERO-query4 / config.yaml
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run_id: subtask_m2w_libero_implicit_jepa_query_4
run_root_dir: results
seed: 42
wandb_entity: livion
wandb_project: m2w-vla
is_debug: false
framework:
name: QwenSubtaskM2W_phs
qwenvl:
base_vlm: ./playground/Pretrained_models/Qwen3-VL-4B-Instruct
attn_implementation: sdpa
vl_hidden_dim: 2048
reasoning:
cot_reasoning_mode: implicit_query
latent_cot_num_queries: 4
qwen_action_context_mode: exclude_cot_prompt
lambda_cot: 0.1
generate_cot_at_inference: false
inference_cot_max_new_tokens: 96
inference_cot_use_cache: true
inference_empty_cache: false
vjepa2:
hub_repo: facebookresearch/vjepa2:main
hub_model: vjepa2_1_vit_large_384
hub_source: github
num_frames: 8
image_size: 224
jepa_predictor:
prediction_view: wrist
dropout: 0.0
use_jepa_loss: true
lambda_jepa: 0.2
jepa_predictor_depth: 4
jepa_predictor_num_heads: 8
jepa_predictor_bf16_autocast: true
jepa_predictor_activation_checkpointing: true
policy_context:
use_state: false
wrist_action_context_tokens: 32
wrist_action_context_heads: 8
wrist_action_context_layers: 1
detach_wrist_action_context: true
action_model:
action_model_type: DiT-B
gradient_checkpointing: true
action_hidden_dim: 1024
hidden_size: 1024
add_pos_embed: true
max_seq_len: 1024
action_dim: 7
state_dim: null
action_horizon: 8
past_action_window_size: 0
noise_beta_alpha: 1.5
noise_beta_beta: 1.0
noise_s: 0.999
num_timestep_buckets: 1000
num_inference_timesteps: 4
num_target_vision_tokens: 32
diffusion_model_cfg:
cross_attention_dim: 2560
dropout: 0.2
final_dropout: true
interleave_self_attention: true
norm_type: ada_norm
num_layers: 16
output_dim: 1024
positional_embeddings: null
datasets:
vla_data:
dataset_py: subtask_m2w_datasets_phs
data_root_dir: playground/Datasets/LEROBOT_LIBERO_DATA
data_mix: libero_all
action_type: delta_qpos
per_device_batch_size: 16
load_all_data_for_training: true
video_backend: torchvision_av
jepa_prediction_view: wrist
vlm_include_wrist_view: true
wrist_history_frames: 8
future_wrist_frames: 8
future_wrist_k: 8
subtask_label_dir: playground/Datasets/subtask_m2w_labels_libero_qwen3vl_full_softqa_v31_compact_final_v16_20260630
CoT_prompt: 'Your task is: {instruction}
Using the current main-view and wrist-view images, identify the robot''s current
manipulation step.
Output exactly:
Subtask: ...
Reasoning: ...
Wrist: ...
Do not add extra text.'
trainer:
max_train_steps: 30000
num_warmup_steps: 2500
is_resume: false
pretrained_checkpoint: null
reload_modules: null
resume_optimizer_state: true
train_qwen_vl: true
save_interval: 10000
logging_frequency: 100
repeated_diffusion_steps: 8
learning_rate:
base: 2.5e-05
jepa_predictor: 5.0e-05
wrist_context_adapter: 5.0e-05
action_model: 0.0001
vlm: 1.0e-05
lr_scheduler_type: cosine_with_min_lr
scheduler_specific_kwargs:
min_lr: 1.0e-06
gradient_clipping: 1.0
gradient_accumulation_steps: 1
optimizer:
name: AdamW
betas:
- 0.9
- 0.95
eps: 1.0e-08
weight_decay: 1.0e-08
output_dir: results/subtask_m2w_libero_implicit_jepa_query_4