README.md

metadata

dataset_info:
  features:
    - name: ground_truth
      dtype: string
    - name: expanded_completion
      sequence: string
    - name: simplifications
      sequence: string
    - name: simplified_values
      sequence: float64
    - name: prompt
      dtype: string
    - name: breadth
      dtype: int64
    - name: max_depth
      dtype: int64
  splits:
    - name: train
      num_bytes: 41016069
      num_examples: 6000
  download_size: 5894042
  dataset_size: 41016069
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

Dataset Description:

The Nemotron-RL-math-advanced_calculations is a dataset designed to test a model's ability to solve complex, multi-step math problems in a multi-step agentic environment. It involves counterintuitive calculations with varying levels of function composition.

This dataset is released as part of NVIDIA NeMo Gym, a framework for building reinforcement learning environments to train large language models. NeMo Gym contains a growing collection of training environments and datasets to enable Reinforcement Learning from Verifiable Reward (RLVR).

NeMo Gym is an open-source library within the NVIDIA NeMo framework, NVIDIA's GPU accelerated, end-to-end training framework for large language models (LLMs), multi-modal models and speech models.

This dataset is part of the Nemo Gym Collection.

This dataset is ready for commercial use.

Dataset Owner(s):

NVIDIA Corporation

Dataset Creation Date:

September 3rd 2025

License/Terms of Use:

CC BY 4.0

Intended Usage:

To be used with NeMo Gym for post-training LLMs.

Dataset Characterization

Data Collection Method

• [Synthetic]
  

Labeling Method

• [Synthetic]
  

Dataset Format

Text Only, Compatible with NeMo Gym

Dataset Quantification

Record Count - 6K query-answer tuples.

Reference(s):

NeMo Gym

Ethical Considerations:

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.
Please report model quality, risk, security vulnerabilities or NVIDIA AI Concerns here.