dataset_info:
features:
- name: input_ids
sequence: int32
splits:
- name: train
num_bytes: 38252459784
num_examples: 74132674
download_size: 20976468705
dataset_size: 38252459784
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: other
multilinguality:
- monolingual
pretty_name: pretokenized,filtered,sorted subset of the Pile
size_categories:
- 10B<n<100B
source_datasets:
- the-pile
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
paperswithcode_id: the-pile-cramming
Dataset Card for "the_pile_WordPiecex32768_8eb2d0ea9da707676c81314c4ea04507"
Dataset Description
- Repository: https://github.com/JonasGeiping/cramming
- Paper: https://arxiv.org/abs/2212.14034
- Raw Data Source Paper: The Pile: An 800GB Dataset of Diverse Text for Language Modeling
- Raw Data Source Datasheet: Datasheet for the Pile
Dataset Summary
This is a preprocessed, tokenized dataset for the cramming-project.
Use only with the tokenizer uploaded here.
This version is 8eb2d0ea9da707676c81314c4ea04507, which corresponds to a specific dataset construction setup, described below.
The raw data source is the Pile, a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality
datasets combined together.
Languages
This dataset is in English (EN).
Data Splits
This preprocessed subset contains only a train split.
Dataset Creation
The configuration to create this dataset with the cramming project code (https://github.com/JonasGeiping/cramming) is
# This is a slice of the pile
name: the_pile
defaults:
- sources:
- the_pile
#
# Preprocessing
normalizer:
force_lowercase: True
strip_accents: True
force_english_keyboard: True
whitespace_escape: False
tokenizer: WordPiece
vocab_size: 32768
# Dataset Formation
seq_length: 128
include_cls_token_in_corpus: False
include_sep_token_in_corpus: True
use_type_ids: False
max_entries_in_raw_dataset: 16e6
max_seq_in_tokenized_dataset: 85e6
# Data Cleaning:
named_entity_simplification: False
remove_whitespaces: False
remove_trash: True
trash_cutoff: 0.25
deduplicate_entries: True
deduplication_threshold: 75
# Data Order:
ordering: sentence-length-curriculum
Considerations for Using the Data
Limitations and bias: This training data was further filtered and sorted beyond the normal preprocessing. These modifications were not tested for unintended consequences.
Additional Information
Dataset Curators
This dataset is a filtered, sorted and preprocessed subset of the the-Pile made by Jonas Geiping . The original dataset was primarily curated by Leo Gao and Stella Biderman, with assistance from other authors of the Pile paper.
Licensing Information
Please refer to the specific license depending on the subset you use at https://huggingface.co/datasets/EleutherAI/pile
Citation Information
Filtered version for the cramming project:
@article{geiping_cramming_2022,
title = {Cramming: {{Training}} a {{Language Model}} on a {{Single GPU}} in {{One Day}}},
shorttitle = {Cramming},
author = {Geiping, Jonas and Goldstein, Tom},
year = {2022},
month = dec,
eprint = {2212.14034},
primaryclass = {cs},
publisher = {{arXiv}},
doi = {10.48550/arXiv.2212.14034},
url = {http://arxiv.org/abs/2212.14034},
urldate = {2023-01-10},
archiveprefix = {arxiv},
keywords = {Computer Science - Computation and Language,Computer Science - Machine Learning},
journal = {arxiv:2212.14034[cs]}
}
Original Data Curation:
@article{gao2020pile,
title={The {P}ile: An 800{GB} dataset of diverse text for language modeling},
author={Gao, Leo and Biderman, Stella and Black, Sid and Golding, Laurence and Hoppe, Travis and Foster, Charles and Phang, Jason and He, Horace and Thite, Anish and Nabeshima, Noa and others},
journal={arXiv preprint arXiv:2101.00027},
year={2020}
}
@article{biderman2022datasheet,
title={Datasheet for the pile},
author={Biderman, Stella and Bicheno, Kieran and Gao, Leo},
journal={arXiv preprint arXiv:2201.07311},
year={2022}
}