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shanyangmie/physics-r1-seed42-v4-step60

sourceHugging Faceapache-2.0updated 4mo agoView on Hugging Face
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Physics-R1 — Seed 42, v4 step-60 (HF safetensors)

**Project Page** | **Paper** | **Code** | **Training corpus**

The Physics-R1 paper checkpoint for the Physics-R1 (binary, seed 42) row of Table 2 — single-seed paper headline. Fine-tune of Qwen3-VL-8B-Thinking on the audited `PhysR1Corp` (2,268 closed-form physics problems) via full-parameter FSDP1 GRPO with binary correctness reward.

This is the easy-to-use HF safetensors release. For the original verl FSDP-sharded archive (for training-state inspection or further RL), see `physics-r1-seed42-v4-step60-fsdp`.

Quickstart

python
from transformers import AutoModelForImageTextToText, AutoProcessor
import torch

model = AutoModelForImageTextToText.from_pretrained(
    "shanyangmie/physics-r1-seed42-v4-step60",
    dtype=torch.bfloat16,
    device_map="auto",
    trust_remote_code=True,
)
processor = AutoProcessor.from_pretrained(
    "shanyangmie/physics-r1-seed42-v4-step60",
    trust_remote_code=True,
)

For evaluation against the paper's benchmark, see PhysOlym-A and the code release.

Performance (paper Table 2, seed-42 row)

EvalPhysics-R1 (this checkpoint)Base Qwen3-VL-8B-ThinkingΔ
PhyX-mini78.073.7+4.3
PhyX-3k76.974.4+2.5
PhysReason32.223.9+8.3
PUB-OE37.035.3+1.7
OlympiadBench-Physics45.439.3+6.1
PhysOlym-A25.68.0+17.6

Scoring: problem-level liberal Sonnet-as-judge (every subpart of a multi-part problem must be correct). The 3-seed mean across {42, 17, 23} is the paper's headline (+18.9 pp on PhysOlym-A).

Other seeds (HF safetensors mirrors)

Training recipe

  • —Base model: `Qwen/Qwen3-VL-8B-Thinking`
  • —Algorithm: GRPO (verl 0.6.1, full-parameter FSDP1 — actor.strategy=fsdp, not fsdp2)
  • —Reward: binary correctness, per-subpart Sonnet judge with problem-level AND aggregation (see paper §3.2)
  • —Data: `shanyangmie/physr1corp` — 2,268 audited closed-form problems
  • —Seed / step: 42 / 60
  • —Hardware: 4×H200 (FSDP1 4-way sharded)

Full hyperparameters in paper Appendix.

License

Apache 2.0, inheriting from the base model `Qwen3-VL-8B-Thinking`. Training data (physr1corp) is CC BY-NC 4.0, so this derivative checkpoint is intended for non-commercial research use.

Citation

bibtex
@misc{yang2026physicsr1,
  title  = {Physics-R1: An Audited Olympiad Corpus and Recipe for Visual Physics Reasoning},
  author = {Yang, Shan},
  year   = {2026},
  url    = {https://huggingface.co/papers/2605.14040}
}