Parameter	Value
Base model	pi0.5 (PaliGemma 2B + Gemma 2B action expert)
Total parameters	~3.35B
Action dimension	32
Action horizon	10
Batch size	16
Training steps	5,000
Learning rate	Cosine decay: warmup=500, peak=5e-5, end=5e-6
Optimizer	AdamW (gradient clip norm=1.0)
GPUs	8x NVIDIA A100
Normalization	Quantile normalization

Checkpoints

Step 3000: loss = 0.0071
Step 4000: loss = 0.0047
Step 4999

Loss Curve

Step	Loss
0	0.0818
500	0.0155
1000	0.0120
1500	0.0110
2000	0.0084
2500	0.0075
3000	0.0071
3500	0.0060
4000	0.0047
4500	0.0042

Part of Mode Editing Research

This checkpoint is part of the "Don't Filter Your Data, Edit Your Policy" project (CoRL 2026), investigating post-hoc behavior mode editing for robot policies using Classifier-Guided Distillation (CG-Distill).

haohw/pi05_real_pb_mixed

pi05_real_pb_mixed

Task

Training Configuration

Checkpoints

Loss Curve

Part of Mode Editing Research

haohw/
pi05_real_pb_mixed