
# Dataset Card for "math_dataset"

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [https://github.com/deepmind/mathematics_dataset](https://github.com/deepmind/mathematics_dataset)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 130.65 GB
- **Size of the generated dataset:** 9.08 GB
- **Total amount of disk used:** 139.73 GB

### 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

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## 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

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### 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](https://github.com/patrickvonplaten), [@lewtun](https://github.com/lewtun), [@thomwolf](https://github.com/thomwolf) for adding this dataset.
language:en region:us
{"language": ["en"], "paperswithcode_id": "mathematics", "pretty_name": "Mathematics Dataset", "dataset_info": [{"config_name": "algebra__linear_1d", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 516405, "num_examples": 10000}, {"name": "train", "num_bytes": 92086245, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 92602650}, {"config_name": "algebra__linear_1d_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1018090, "num_examples": 10000}, {"name": "train", "num_bytes": 199566926, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 200585016}, {"config_name": "algebra__linear_2d", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 666095, "num_examples": 10000}, {"name": "train", "num_bytes": 126743526, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 127409621}, {"config_name": "algebra__linear_2d_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1184664, "num_examples": 10000}, {"name": "train", "num_bytes": 234405885, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 235590549}, {"config_name": "algebra__polynomial_roots", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 868630, "num_examples": 10000}, {"name": "train", "num_bytes": 163134199, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 164002829}, {"config_name": "algebra__polynomial_roots_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1281321, "num_examples": 10000}, {"name": "train", "num_bytes": 251435312, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 252716633}, {"config_name": "algebra__sequence_next_term", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 752459, "num_examples": 10000}, {"name": "train", "num_bytes": 138735194, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 139487653}, {"config_name": "algebra__sequence_nth_term", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 947764, "num_examples": 10000}, {"name": "train", "num_bytes": 175945643, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 176893407}, {"config_name": "arithmetic__add_or_sub", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 483725, "num_examples": 10000}, {"name": "train", "num_bytes": 89690356, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 90174081}, {"config_name": "arithmetic__add_or_sub_in_base", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 502221, "num_examples": 10000}, {"name": "train", "num_bytes": 93779137, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 94281358}, {"config_name": "arithmetic__add_sub_multiple", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 498421, "num_examples": 10000}, {"name": "train", "num_bytes": 90962782, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 91461203}, {"config_name": "arithmetic__div", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 421520, "num_examples": 10000}, {"name": "train", "num_bytes": 78417908, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 78839428}, {"config_name": "arithmetic__mixed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 513364, "num_examples": 10000}, {"name": "train", "num_bytes": 93989009, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 94502373}, {"config_name": "arithmetic__mul", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 394004, "num_examples": 10000}, {"name": "train", "num_bytes": 73499093, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 73893097}, {"config_name": "arithmetic__mul_div_multiple", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 497308, "num_examples": 10000}, {"name": "train", "num_bytes": 91406689, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 91903997}, {"config_name": "arithmetic__nearest_integer_root", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 705630, "num_examples": 10000}, {"name": "train", "num_bytes": 137771237, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 138476867}, {"config_name": "arithmetic__simplify_surd", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1261753, "num_examples": 10000}, {"name": "train", "num_bytes": 207753790, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 209015543}, {"config_name": "calculus__differentiate", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1025947, "num_examples": 10000}, {"name": "train", "num_bytes": 199013993, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 200039940}, {"config_name": "calculus__differentiate_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1343416, "num_examples": 10000}, {"name": "train", "num_bytes": 263757570, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 265100986}, {"config_name": "comparison__closest", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 681229, "num_examples": 10000}, {"name": "train", "num_bytes": 132274822, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 132956051}, {"config_name": "comparison__closest_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1071089, "num_examples": 10000}, {"name": "train", "num_bytes": 210658152, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 211729241}, {"config_name": "comparison__kth_biggest", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 797185, "num_examples": 10000}, {"name": "train", "num_bytes": 149077463, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 149874648}, {"config_name": "comparison__kth_biggest_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1144556, "num_examples": 10000}, {"name": "train", "num_bytes": 221547532, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 222692088}, {"config_name": "comparison__pair", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 452528, "num_examples": 10000}, {"name": "train", "num_bytes": 85707543, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 86160071}, {"config_name": "comparison__pair_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 946187, "num_examples": 10000}, {"name": "train", "num_bytes": 184702998, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 185649185}, {"config_name": "comparison__sort", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 712498, "num_examples": 10000}, {"name": "train", "num_bytes": 131752705, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 132465203}, {"config_name": "comparison__sort_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1114257, "num_examples": 10000}, {"name": "train", "num_bytes": 213871896, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 214986153}, {"config_name": "measurement__conversion", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 592904, "num_examples": 10000}, {"name": "train", "num_bytes": 118650852, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 119243756}, {"config_name": "measurement__time", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 584278, "num_examples": 10000}, {"name": "train", "num_bytes": 116962599, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 117546877}, {"config_name": "numbers__base_conversion", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 490881, "num_examples": 10000}, {"name": "train", "num_bytes": 90363333, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 90854214}, {"config_name": "numbers__div_remainder", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 644523, "num_examples": 10000}, {"name": "train", "num_bytes": 125046212, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 125690735}, {"config_name": "numbers__div_remainder_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1151347, "num_examples": 10000}, {"name": "train", "num_bytes": 226341870, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 227493217}, {"config_name": "numbers__gcd", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 659492, "num_examples": 10000}, {"name": "train", "num_bytes": 127914889, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 128574381}, {"config_name": "numbers__gcd_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1206805, "num_examples": 10000}, {"name": "train", "num_bytes": 237534189, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 238740994}, {"config_name": "numbers__is_factor", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 396129, "num_examples": 10000}, {"name": "train", "num_bytes": 75875988, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 76272117}, {"config_name": "numbers__is_factor_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 949828, "num_examples": 10000}, {"name": "train", "num_bytes": 185369842, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 186319670}, {"config_name": "numbers__is_prime", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 385749, "num_examples": 10000}, {"name": "train", "num_bytes": 73983639, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 74369388}, {"config_name": "numbers__is_prime_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 947888, "num_examples": 10000}, {"name": "train", "num_bytes": 184808483, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 185756371}, {"config_name": "numbers__lcm", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 717978, "num_examples": 10000}, {"name": "train", "num_bytes": 136826050, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 137544028}, {"config_name": "numbers__lcm_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1127744, "num_examples": 10000}, {"name": "train", "num_bytes": 221148668, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 222276412}, {"config_name": "numbers__list_prime_factors", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 585749, "num_examples": 10000}, {"name": "train", "num_bytes": 109982816, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 110568565}, {"config_name": "numbers__list_prime_factors_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1053510, "num_examples": 10000}, {"name": "train", "num_bytes": 205379513, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 206433023}, {"config_name": "numbers__place_value", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 496977, "num_examples": 10000}, {"name": "train", "num_bytes": 95180091, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 95677068}, {"config_name": "numbers__place_value_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1011130, "num_examples": 10000}, {"name": "train", "num_bytes": 197187918, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 198199048}, {"config_name": "numbers__round_number", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 570636, "num_examples": 10000}, {"name": "train", "num_bytes": 111472483, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 112043119}, {"config_name": "numbers__round_number_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1016754, "num_examples": 10000}, {"name": "train", "num_bytes": 201057283, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 202074037}, {"config_name": "polynomials__add", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1308455, "num_examples": 10000}, {"name": "train", "num_bytes": 257576092, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 258884547}, {"config_name": "polynomials__coefficient_named", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1137226, "num_examples": 10000}, {"name": "train", "num_bytes": 219716251, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 220853477}, {"config_name": "polynomials__collect", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 774709, "num_examples": 10000}, {"name": "train", "num_bytes": 143743260, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 144517969}, {"config_name": "polynomials__compose", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1209763, "num_examples": 10000}, {"name": "train", "num_bytes": 233651887, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 234861650}, {"config_name": "polynomials__evaluate", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 599446, "num_examples": 10000}, {"name": "train", "num_bytes": 114538250, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 115137696}, {"config_name": "polynomials__evaluate_composed", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1148362, "num_examples": 10000}, {"name": "train", "num_bytes": 226022455, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 227170817}, {"config_name": "polynomials__expand", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1057353, "num_examples": 10000}, {"name": "train", "num_bytes": 202338235, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 203395588}, {"config_name": "polynomials__simplify_power", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1248040, "num_examples": 10000}, {"name": "train", "num_bytes": 216407582, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 217655622}, {"config_name": "probability__swr_p_level_set", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1159050, "num_examples": 10000}, {"name": "train", "num_bytes": 227540179, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 228699229}, {"config_name": "probability__swr_p_sequence", "features": [{"name": "question", "dtype": "string"}, {"name": "answer", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1097442, "num_examples": 10000}, {"name": "train", "num_bytes": 215865725, "num_examples": 1999998}], "download_size": 2333082954, "dataset_size": 216963167}]}
TAGS
#language-English #region-us 

Dataset Card for "math\_dataset"
================================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ 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
	+ Contributions


Dataset Description
-------------------


* Homepage: URL
* Repository:
* Paper:
* Point of Contact:
* Size of downloaded dataset files: 130.65 GB
* Size of the generated dataset: 9.08 GB
* Total amount of disk used: 139.73 GB


### 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



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


### Contributions


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



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 ### Contributions


Thanks to @patrickvonplaten, @lewtun, @thomwolf for adding this dataset.
TAGS
#language-English #region-us 
 ### 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



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 ### Contributions


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