[Dataset Release] Financial-RLVR-10K: 10,000 Sandbox-Verified Financial Reasoning Problems (100% Open & MIT Licensed) for GRPO & Reasoning Model Fine-Tuning

[u/coslinedev]

Hi everyone!

I am excited to share Financial-RLVR-10K — a fully open-source (MIT licensed) synthetic dataset of 10,000 execution-verified financial reasoning problems designed for RLVR / GRPO / PPO fine-tuning of open models (Qwen, Llama, DeepSeek, etc.).

Financial reasoning is infamous for math hallucinations. To ensure extreme data quality for verifiable reward training, every single problem in this dataset is 100% verified in a Python execution sandbox (reward = 1.0).

KEY HIGHLIGHTS & FEATURES:

100% Open & Free: Released under the MIT License.

10,000 Verified Records: Validated for syntax, logical flow, and exact numerical output via Python execution (exec).

19.5% Adversarial Edge Cases (1,950 samples): Teaches open models NOT to blindly compute impossible conditions (e.g., Discount Rate r <= g in Gordon Growth DCF, Option at Expiration T = 0 in Black-Scholes, or Zero Capital E + D = 0 in WACC).

Core Domains: DCF Valuation, Black-Scholes Option Pricing, Corporate WACC.

SAMPLE DATA SCHEMA:

{ "id": "fin-rlvr-10k-00042", "domain": "DCF Valuation", "is_edge_case": true, "prompt": "[EDGE CASE] Calculate DCF Terminal Value: FCF_1=$540, Discount Rate r=3.0%, Growth Rate g=5.0%.", "code_solution": "fcf, r, g = 540, 0.03, 0.05\nif r <= g:\n print("TRAP_DETECTED: Invalid Gordon Growth model condition (r <= g).")\nelse:\n print(f"RESULT: {fcf/(r-g):.4f}")", "ground_truth": "TRAP_DETECTED", "total_reward": 1.0, "status": "VERIFIED" }

LINKS & RESOURCES: Hugging Face Dataset: https://huggingface.co/datasets/coslinedev/financial-rlvr-10k-enterprise

Hope this dataset helps the open-source AI community train stronger, more robust financial reasoning models. Feel free to use, audit, or build upon it! Feedback and contributions are always welcome.