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# Dataset Card for "math_dataset"

### Dataset Summary

Mathematics database.

This dataset code generates mathematical question and answer pairs, from a range of question types at roughly school-level difficulty. This is designed to test the mathematical learning and algebraic reasoning skills of learning models.

Original paper: Analysing Mathematical Reasoning Abilities of Neural Models (Saxton, Grefenstette, Hill, Kohli).

Example usage: train_examples, val_examples = datasets.load_dataset( 'math_dataset/arithmetic__mul', split=['train', 'test'], as_supervised=True)

### Supported Tasks and Leaderboards

### Languages

## Dataset Structure

### Data Instances

#### algebra__linear_1d

**Size of downloaded dataset files:**2.33 GB**Size of the generated dataset:**92.60 MB**Total amount of disk used:**2.43 GB

An example of 'train' looks as follows.

```
```

#### algebra__linear_1d_composed

**Size of downloaded dataset files:**2.33 GB**Size of the generated dataset:**200.58 MB**Total amount of disk used:**2.53 GB

An example of 'train' looks as follows.

```
```

#### algebra__linear_2d

**Size of downloaded dataset files:**2.33 GB**Size of the generated dataset:**127.41 MB**Total amount of disk used:**2.46 GB

An example of 'train' looks as follows.

```
```

#### algebra__linear_2d_composed

**Size of downloaded dataset files:**2.33 GB**Size of the generated dataset:**235.59 MB**Total amount of disk used:**2.57 GB

An example of 'train' looks as follows.

```
```

#### algebra__polynomial_roots

**Size of downloaded dataset files:**2.33 GB**Size of the generated dataset:**164.01 MB**Total amount of disk used:**2.50 GB

An example of 'train' looks as follows.

```
```

### Data Fields

The data fields are the same among all splits.

#### algebra__linear_1d

`question`

: a`string`

feature.`answer`

: a`string`

feature.

#### algebra__linear_1d_composed

`question`

: a`string`

feature.`answer`

: a`string`

feature.

#### algebra__linear_2d

`question`

: a`string`

feature.`answer`

: a`string`

feature.

#### algebra__linear_2d_composed

`question`

: a`string`

feature.`answer`

: a`string`

feature.

#### algebra__polynomial_roots

`question`

: a`string`

feature.`answer`

: a`string`

feature.

### Data Splits

name | train | test |
---|---|---|

algebra__linear_1d | 1999998 | 10000 |

algebra__linear_1d_composed | 1999998 | 10000 |

algebra__linear_2d | 1999998 | 10000 |

algebra__linear_2d_composed | 1999998 | 10000 |

algebra__polynomial_roots | 1999998 | 10000 |

## Dataset Creation

### Curation Rationale

### Source Data

#### Initial Data Collection and Normalization

#### Who are the source language producers?

### Annotations

#### Annotation process

#### Who are the annotators?

### Personal and Sensitive Information

## Considerations for Using the Data

### Social Impact of Dataset

### Discussion of Biases

### Other Known Limitations

## Additional Information

### Dataset Curators

### Licensing Information

### Citation Information

```
@article{2019arXiv,
author = {Saxton, Grefenstette, Hill, Kohli},
title = {Analysing Mathematical Reasoning Abilities of Neural Models},
year = {2019},
journal = {arXiv:1904.01557}
}
```

### Contributions

Thanks to @patrickvonplaten, @lewtun, @thomwolf for adding this dataset.

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