---
pretty_name: mC4-es-sampled
annotations_creators:
- no-annotation
language_creators:
- found
languages:
- es
source_datasets:
- extended|mc4
- extended|mc4-sampling
licenses:
- odc-by-1.0
size_categories:
- n<1K
- 1K<n<10K
- 10K<n<100K
- 100K<n<1M
- 1M<n<10M
- 10M<n<100M
- 100M<n<1B
task_categories:
- sequence-modeling
task_ids:
- language-modeling
---

# Dataset Card for mC4-es-sampled

## Table of Contents

- [Dataset Card for mC4-es-sampled](#dataset-card-for-mc4-es-sampled)
  - [Table of Contents](#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)
  - [Additional Information](#additional-information)
    - [Dataset Curators](#dataset-curators)
    - [Licensing Information](#licensing-information)
    - [Citation Information](#citation-information)
    - [Contributions](#contributions)

## Dataset Description

- **Homepage:** https://huggingface.co./datasets/allenai/c4
- **Paper:** https://arxiv.org/abs/1910.10683

### Dataset Summary

This dataset is the result of applying perplexity sampling to the Spanish portion of mC4 using [`mc4-sampling`](https://huggingface.co./datasets/bertin-project/mc4-sampling/). Please, refer to [BERTIN Project](https://huggingface.co./bertin-project/bertin-roberta-base-spanish).

You can load the mC4 Spanish sampled like this:

```python
from datasets import load_dataset

for config in ("random", "stepwise", "gaussian"):
    mc4es = load_dataset(
        "bertin-project/mc4-es-sampled",
        config,
        split="train",
        streaming=True
    ).shuffle(buffer_size=1000)
    for sample in mc4es:
        print(config, sample)
        break       
```
Alternatively, you can bypass the `datasets` library and quickly download (\~1.5hrs, depending on connection) a specific config in the same order used to pre-train BERTIN models in a massive (\~200GB) JSON-lines files:

```python
import io
import gzip
import json
import sys

import requests
from tqdm import tqdm

_DATA_URL_TRAIN = "https://huggingface.co./datasets/bertin-project/mc4-es-sampled/resolve/main/mc4-es-train-50M-{config}-shard-{index:04d}-of-{n_shards:04d}.json.gz"


def main(config="stepwise"):
    data_urls = [
        _DATA_URL_TRAIN.format(
            config=config,
            index=index + 1,
            n_shards=1024,
        )
        for index in range(1024)
    ]
    with open(f"mc4-es-train-50M-{config}.jsonl", "w") as f:
        for dara_url in tqdm(data_urls):
            response = requests.get(dara_url)
            bio = io.BytesIO(response.content)
            with gzip.open(bio, "rt", encoding="utf8") as g:
                for line in g:
                    json_line = json.loads(line.strip())
                    f.write(json.dumps(json_line) + "\
")


if __name__ == "__main__":
    main(sys.argv[1])
```

### Supported Tasks and Leaderboards

mC4-es-sampled is mainly intended for reproducibility purposes of the BERTIN Project and to pretrain language models and word representations on medium budgets.

### Languages

The dataset only supports the Spanish language.

## Dataset Structure

### Data Instances

An example form the `Gaussian` config:

```python
{'timestamp': '2018-10-20T06:20:53Z', 'text': 'Ortho HyaluroTop 200 aporta el colágeno y ácido hialurónico que, con la edad, se producen en menor cantidad. La vitamina C promueve la producción de colágeno para mantener la piel sana y protege a las células contra los radicales libres causados ??por la contaminación ambiental y los rayos UV.', 'url': 'https://www.farmaciagaleno.com/orthonat-hyalurotop-200-30-capsulas'}
```

### Data Fields

The data have several fields:

- `url`: url of the source as a string
- `text`: text content as a string
- `timestamp`: timestamp as a string

### Data Splits

The resulting mC4 subsets for Spanish are reported in this table:

| config   | train   |
|:---------|:--------|
| stepwise | 50M     |
| random   | 50M     |
| gaussian | 50M     |

The split `validation` is exactly the same as the original `mc4` dataset.

## Dataset Creation

### Curation Rationale

This dataset was built from the original [`mc4`](https://huggingface.co./datasets/mc4) by applying perplexity-sampling via [`mc4-sampling`](https://huggingface.co./datasets/bertin-project/mc4-sampling) for Spanish.

## Additional Information

### Dataset Curators

Original data by [Common Crawl](https://commoncrawl.org/).

### Licensing Information

AllenAI are releasing this dataset under the terms of ODC-BY. By using this, you are also bound by the Common Crawl terms of use in respect of the content contained in the dataset.

### Citation Information

```
@article{2019t5,
    author = {Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu},
    title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer},
    journal = {arXiv e-prints},
    year = {2019},
    archivePrefix = {arXiv},
    eprint = {1910.10683},
}
```

### Contributions

Dataset contributed by [@versae](https://github.com/versae) for BERTIN Project.

Thanks to [@dirkgr](https://github.com/dirkgr) and [@lhoestq](https://github.com/lhoestq) for adding the original mC4 dataset.