Instructions to use Occupying-Mars/qwen3-4b-symbolic-vanilla-ppo-ent001-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Occupying-Mars/qwen3-4b-symbolic-vanilla-ppo-ent001-v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Occupying-Mars/qwen3-4b-symbolic-vanilla-ppo-ent001-v1") model = AutoModelForCausalLM.from_pretrained("Occupying-Mars/qwen3-4b-symbolic-vanilla-ppo-ent001-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Qwen3-4B โ Vanilla PPO + entropy bonus 0.01 (cmp-vanilla-ppo-ent001-v1)
Second arm of the vanilla-PPO baseline for the GRPO-vs-PPO rollout-compaction
study (prime-rl fork ChinmayK0607/blog-rl, branch feat/vanilla-ppo). Identical
to qwen3-4b-symbolic-vanilla-ppo-v1
(clipped surrogate + value head + trainer-side GAE, full uncompacted rollouts)
plus entropy_coef=0.01 (the PPO paper's Atari setting). Requires the
vanilla LM head (fused_lm_head_token_chunk_size=disabled) โ the fused
kernel has no backward through entropy.
The result: collapse delayed, then terminal
| step | 10 | 30 | 50 | 70 | 90 | 100-150 |
|---|---|---|---|---|---|---|
| val reward | 0.528 | 0.694 | 0.778 | 0.708 | 0.833 | 0.000 |
The no-entropy arm collapsed at step ~80 and self-recovered to 0.972 by 150. This arm survived that window (0.833 at step 90 โ its peak, and better than arm 1 ever was pre-collapse), then collapsed at ~100 with entropy pinned at 1e-4 and never recovered (1-turn degenerate episodes through 150). Vanilla PPO on this task lives on a knife's edge around steps 80-120; a 0.01 entropy bonus shifts the edge, it does not remove it.
Files
- root: step_90 policy โ the pre-collapse peak (val 0.833), value head
stripped, vLLM-loadable;
value_head.safetensorsalongside checkpoints/step_120/,checkpoints/step_150/โ mid/post-collapse policies for collapse forensics (val 0.000, 1-turn degenerate greedy mode)
Training setup
Same as arm 1: prime-rl ppo, GAE gamma=1.0 lambda=0.95, clip 0.2, value
coef 0.5, LR 1e-6, batch 64 x group 8, 150 steps, temp 0.7,
symbolic-curriculum-v2 (588 train / 72 val pass@4-mixed tasks), 4x RTX PRO
6000 Blackwell. W&B: https://wandb.ai/krishnapg2315/blog-rl/runs/fc57f9265a2d4ff8aaa80fabcc9058ab
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Model tree for Occupying-Mars/qwen3-4b-symbolic-vanilla-ppo-ent001-v1
Base model
Qwen/Qwen3-4B-Instruct-2507