tinker-rl-bench-frontier_gsm8k_deepseek-v3.1 – AI Model by arvindcr4 | AlphaNeural AI

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arvindcr4/
tinker-rl-bench-frontier_gsm8k_deepseek-v3.1

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reinforcement-learning

tinker-rl-bench

deepseek-ai/DeepSeek-V3.1

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frontier_gsm8k_deepseek-v3.1

GRPO experiment from TinkerRL-Bench world-class experiment suite.

Training Details

Base model: deepseek-ai/DeepSeek-V3.1
Method: GRPO (Group Relative Policy Optimization)
Platform: Tinker API v0.18.1
Task: gsm8k
Seed: 42
LoRA rank: 16
Learning rate: 1e-05
Group size: 4
Steps: 20

Results

First-5 avg reward: 85.0%
Last-10 avg reward: 85.0%
Peak reward: 100.0%
Zero-loss steps: 30%
Tinker Run ID: 56b99b24-03bd-5d00-ae23-831933ef53b2:train:0

Reward Trace

[
  0.875,
  0.875,
  1.0,
  0.75,
  0.75,
  0.75,
  0.625,
  0.875,
  0.875,
  1.0,
  0.75,
  1.0,
  1.0,
  0.875,
  1.0,
  0.5,
  0.875,
  0.75,
  0.75,
  1.0
]

Citation

bibtex

@misc{tinker-rl-bench-2026,
  title={TinkerRL-Bench: A Unified Benchmark for RL Post-Training},
  author={Arvind C R and Sandhya Jeyaraj and Madhu Kumara L and Mohammad Rafi and Dhruva N Murthy and Arumugam K},
  year={2026},
  url={https://github.com/arvindcr4/tinker-rl-lab}
}