task_categories:text-generation task_categories:question-answering size_categories:1K<n<10K language:en license:mit region:us
---
dataset_info:
  features:
  - name: question
    dtype: string
  - name: answer
    dtype: string
  - name: chain
    dtype: string
  splits:
  - name: train
    num_bytes: 7507375
    num_examples: 7473
  - name: test
    num_bytes: 1350934
    num_examples: 1319
  download_size: 4400374
  dataset_size: 8858309
license: mit
task_categories:
- text-generation
- question-answering
language:
- en
size_categories:
- 1K<n<10K
---
# Dataset Card for "Calc-gsm8k"


## Summary

This dataset is an instance of gsm8k dataset, converted 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

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.


## Construction Process

The answers in the original dataset was in in a structured but non-standard format. So, the answers were parsed, all arithmetical expressions
were evaluated using a sympy-based calculator, the outputs were checked to be consistent with the intermediate results and finally exported
into a simple html-like language that BeautifulSoup can parse.


## Content and Data splits

Content and splits correspond to the original gsm8k dataset.
See [gsm8k HF dataset](https://huggingface.co/datasets/gsm8k) and [official repository](https://github.com/openai/grade-school-math) for more info.


## Licence

MIT, consistently with the original dataset.

