task_categories:text-generation size_categories:1K<n<10K language:en license:mit math world problems math arithmetics region:us
---
license: mit
task_categories:
- text-generation
language:
- en
tags:
- math world problems
- math
- arithmetics
size_categories:
- 1K<n<10K
dataset_info:
  features:
  - name: id
    dtype: string
  - name: question
    dtype: string
  - name: chain
    dtype: string
  - name: result
    dtype: string
  - name: result_float
    dtype: float64
  - name: equation
    dtype: string
  - name: problem_type
    dtype: string
  splits:
  - name: test
    num_examples: 1000
---



# Dataset Card for Calc-MAWPS


## Summary

The dataset is a collection of simple math world problems focused on arithmetics. It is derived from <https://github.com/arkilpatel/SVAMP/>.

The main addition in this dataset variant is the `chain` column. It was created by converting the solution to a simple html-like language that can be easily
parsed (e.g. by BeautifulSoup). The data contains 3 types of tags:

- gadget: A tag whose content is intended to be evaluated by calling an external tool (sympy-based calculator in this case)
- output: An output of the external tool
- result: The final answer of the mathematical problem (a number)


##  Supported Tasks

This variant of the dataset is intended for training Chain-of-Thought reasoning models able to use external tools to enhance the factuality of their responses.
This dataset presents in-context scenarios where models can out-source the computations in the reasoning chain to a calculator.


## Attributes:

- `id`: problem id from the original dataset
- `question`: the question intended to answer
- `chain`: series of simple operations (derived from `equation`) that leads to the solution
- `result`: the result (number) as a string
- `result_float`: result converted to a floating point
- `equation`: an nested expression that evaluates to the correct result
- `problem_type`: a category of the problem


## Content and data splits

The dataset contains the same data instances ad the original dataset except for a correction of inconsistency between `equation` and `answer` in one data instance.
To the best of our knowledge, the original dataset does not contain an official train-test split, and we do not create one. However, original authors have used cross-validation in the official repository - for more info, see <https://github.com/arkilpatel/SVAMP/>.


## Licence

MIT, consistent with the original source dataset linked above.


## Related work

If you are interested in related datasets (or models), check out the MU-NLPC organization here on HuggingFace. We have released a few other datasets in a compatible format, and several models that use external calculator during inference.


## Cite

If you use this version of dataset in research, please cite the original [SVAMP paper](https://www.semanticscholar.org/paper/Are-NLP-Models-really-able-to-Solve-Simple-Math-Patel-Bhattamishra/13c4e5a6122f3fa2663f63e49537091da6532f35).
TODO 