pi0.5 Build Block Tower — RLT Stage 1 (Encoder-Decoder)

Experiment

• Objective: Train RLT encoder-decoder to produce a compact RL token representation from frozen VLA prefix embeddings.
• VLA backbone: Baseline 55k checkpoint (pravsels/pi05-build-block-tower-baseline), frozen (rl_vla_loss_weight=0.0).
• Encoder-decoder: 2-layer transformer, 8 heads, dim=2048, SwiGLU FFN.
• Loss: Autoregressive reconstruction of VLA prefix embeddings (L2).
• Steps: 10,000

Config

• Config name: pi05_rl_token_build_block_tower
• Model: Pi0RLConfig (pi05=True, action_horizon=50, rl_vla_loss_weight=0.0)
• Batch size: 36
• Learning rate: 5e-5 cosine decay (1k warmup)
• Optimizer: AdamW (gradient clip norm 1.0)
• EMA decay: 0.999
• Delta actions: enabled
• State/action space: 7D joint-space

Dataset

• villekuosmanen/build_block_tower (200 episodes, LeRobot v2.1)

Checkpoint Hashes

W&B

• pravsels/openpi-rlt-block-tower/runs/i183ouv4

Repo Structure

assets/                      # Norm stats for inference (from baseline)
checkpoints/9999/params/     # Model weights (params only)
README.md                    # This file
TRAINING_LOG.md              # Training log