metadata

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 and official repository for more info.

Licence

MIT, consistently with the original dataset.

Cite

If you use this version of dataset in research, please cite the original GSM8K paper and our report as follows:

@article{kadlcik2023calcx,
         title={Calc-X: Enriching Arithmetical Chain-of-Thoughts Datasets by Interaction with Symbolic Systems}, 
         author={Marek Kadlčík and Michal Štefánik},
         year={2023},
         eprint={2305.15017},
         archivePrefix={arXiv},
         primaryClass={cs.LG}
}