--- license: mit task_categories: - text-generation language: - en tags: - math world problems - math - arithmetics size_categories: - 1K. 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 - `body`: problem setup in english - `question`: the question intended to answer - `equation`: an nested expression that evaluates to the correct result - `answer`: result as a floating point - `type`: a category of the problem - `chain`: series of simple operations (derived from `equation`) that leads to the solution ## 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 . ## 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