Datasets:
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---
language:
- en
license: mit
size_categories:
- 1K<n<10K
task_categories:
- text-generation
- question-answering
dataset_info:
- config_name: default
features:
- name: id
dtype: string
- name: question
dtype: string
- name: chain
dtype: string
- name: result
dtype: string
- name: result_float
dtype: float64
splits:
- name: train
num_bytes: 5373420.477987422
num_examples: 7273
- name: validation
num_bytes: 147763.5220125786
num_examples: 200
- name: test
num_bytes: 993169
num_examples: 1319
download_size: 3140154
dataset_size: 6514353.0
- config_name: original-splits
features:
- name: id
dtype: string
- name: question
dtype: string
- name: chain
dtype: string
- name: result
dtype: string
- name: result_float
dtype: float64
splits:
- name: train
num_bytes: 5521184
num_examples: 7473
- name: test
num_bytes: 993169
num_examples: 1319
download_size: 0
dataset_size: 6514353
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 to 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 outsource the computations in the reasoning chain to a calculator.
## Construction Process
The answers in the original dataset were 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 exported
into a simple html-like language that BeautifulSoup can parse.
We also perform in-dataset and cross-dataset data-leak detection within the [Calc-X collection](https://huggingface.co/collections/MU-NLPC/calc-x-652fee9a6b838fd820055483)
However, in case of gsm8k, we found no data leaks and removed no examples from the data.
## Content and Data splits
For convenience, we created a validation set by sampling 200 random examples from the original train split. This is the default variant:
```python
datasets.load_dataset("MU-NLPC/Calc-gsm8k")
```
The original data splits can be loaded using:
```python
datasets.load_dataset("MU-NLPC/Calc-gsm8k", "original-splits")
```
For more info about the content of the dataset, see [gsm8k HF dataset](https://huggingface.co/datasets/gsm8k) and the [official repository](https://github.com/openai/grade-school-math).
## Related work
This dataset was created as a part of a larger effort in training models capable of using a calculator during inference, which we call Calcformers.
- [**Calc-X collection**](https://huggingface.co/collections/MU-NLPC/calc-x-652fee9a6b838fd820055483) - datasets for training Calcformers
- [**Calcformers collection**](https://huggingface.co/collections/MU-NLPC/calcformers-65367392badc497807b3caf5) - calculator-using models we trained and published on HF
- [**Calc-X and Calcformers paper**](https://arxiv.org/abs/2305.15017)
- [**Calc-X and Calcformers repo**](https://github.com/prompteus/calc-x)
Here are links to the original dataset:
- [**original gsm8k dataset**](https://huggingface.co/datasets/gsm8k)
- [**original gsm8k paper**](https://arxiv.org/abs/2110.14168)
- [**original gsm8k repo**](https://github.com/openai/grade-school-math)
## Licence
MIT, consistently with the original dataset.
## Cite
If you use this version of the dataset in research, please cite the [original GSM8K paper](https://arxiv.org/abs/2110.14168), and [Calc-X collection](https://arxiv.org/abs/2305.15017) as follows:
```bibtex
@inproceedings{kadlcik-etal-2023-soft,
title = "Calc-X and Calcformers: Empowering Arithmetical Chain-of-Thought through Interaction with Symbolic Systems",
author = "Marek Kadlčík and Michal Štefánik and Ondřej Sotolář and Vlastimil Martinek",
booktitle = "Proceedings of the The 2023 Conference on Empirical Methods in Natural Language Processing: Main track",
month = dec,
year = "2023",
address = "Singapore, Singapore",
publisher = "Association for Computational Linguistics",
url = "https://arxiv.org/abs/2305.15017",
}
``` |