metadata

language:
  - en
license: mit
size_categories:
  - 1K<n<10K
task_categories:
  - text-generation
  - question-answering
dataset_info:
  - config_name: default
    features:
      - name: question
        dtype: string
      - name: chain
        dtype: string
      - name: result
        dtype: string
      - name: result_float
        dtype: float64
    splits:
      - name: train
        num_bytes: 5176237.798340693
        num_examples: 7273
      - name: validation
        num_bytes: 142341.20165930683
        num_examples: 200
      - name: test
        num_bytes: 957406
        num_examples: 1319
    download_size: 2958009
    dataset_size: 6275985
  - config_name: original-splits
    features:
      - name: question
        dtype: string
      - name: chain
        dtype: string
      - name: result
        dtype: string
      - name: result_float
        dtype: float64
    splits:
      - name: train
        num_bytes: 5318579
        num_examples: 7473
      - name: test
        num_bytes: 957406
        num_examples: 1319
    download_size: 2949137
    dataset_size: 6275985
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
  - config_name: original-splits
    data_files:
      - split: train
        path: original-splits/train-*
      - split: test
        path: original-splits/test-*

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 corresponds to the original gsm8k dataset.

In this version, we created validation set by sampling 200 random examples from the original train split. The original data splits can be downloaded using:

datasets.load_dataset("MU-NLPC/Calc-gsm8k", "original-splits")

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}
}