frenchtext/banque-fr-2311

Dataset Card for "banque fr websites - 2311"

Dataset extracted from public websites by wordslab-webscraper in 2311:

• domain: banque
• language: fr
• license: Apache 2.0

Dataset Sources

wordslab-webscraper follows the industry best practices for polite web scraping:

• clearly identifies itself as a known text indexing bot: "bingbot"
• doesn't try to hide the user IP address behind proxies
• doesn't try to circumvent bots protection solutions
• waits for a minimum delay between two pages to avoid generating too much load
• respects the website "robots.txt" indexing directives
• respects the web page Meta Robots HTML tag
• respects the web page X-Robots-Tag HTTP header
• respects the web page links rel=nofollow HTML attributes

The text data was extracted from the following websites:

Website	HTML pages	PDF docs	Words
banque.meilleurtaux.com	5055	1	3209252
banquefrancaisemutualiste.fr	196	0	205197
groupebpce.com	1137	3	456194
mabanque.bnpparibas	388	184	1411792
particuliers.sg.fr	385	168	1317226
selectra.info_finance_banques	231	0	490518
www.20minutes.fr_economie_banque_	412	0	220504
www.afb.fr	121	44	159912
www.allianz.fr	854	1	785651
www.axa.fr	1568	0	731906
www.banque-france.fr	212	306	1169549
www.banquebcp.fr	232	0	94114
www.banquedesterritoires.fr	1899	169	2243316
www.banquemondiale.org	216	0	299993
www.banquepopulaire.fr	1530	0	778258
www.bforbank.com	71	0	38220
www.boursobank.com	97	0	89211
www.boursorama.com	24581	0	17269453
www.bpifrance.fr	523	1	489908
www.bred.fr	1531	209	1511004
www.caisse-epargne.fr	1393	0	574874
www.cic.fr	3353	567	6086714
www.credit-agricole.fr	1672	133	2070741
www.creditmutuel.fr	2111	526	3876220
www.ecb.europa.eu	79	1	71446
www.esbanque.fr	269	0	135072
www.fbf.fr	683	571	1939478
www.fortuneo.fr	898	8	573493
www.hellobank.fr	648	31	474719
www.hsbc.fr	295	144	1527838
www.impots.gouv.fr	122	10	63166
www.labanquepostale.fr	1677	0	1224971
www.lafinancepourtous.com	7849	357	6011655
www.lcl.fr	1268	0	834973
www.lesclesdelabanque.com	1478	135	769241
www.lesechos.fr_finance-marches_	1493	0	1412840
www.mafrenchbank.fr	361	10	238469
www.moneyvox.fr	1860	0	1764097
www.orangebank.fr	682	92	1062804
www.palatine.fr	228	0	79346
www.revue-banque.fr	11171	6	3055775
www.service-public.fr	721	2	242446

Uses

WARNING

• the text included in this dataset belongs to its original authors and is protected by copyright laws
• you are not allowed to use this dataset for anything else than training a large language model
• when using a large language model trained on this dataset, you will need to ensure that you comply with the law
• if you benefit from this large language model, you should try to share the value with the original text authors

wordslab-webscraper uses an advanced Html to text conversion algorithm optimized for long context language modeling:

• tries to recover the logical structure of the document from the Html or PDF layout
• preserves document / section / list / table grouping and nesting information
• deduplicates text at the website level while preserving the document structure

Each example in this dataset is a markdown text conversion of a full HTML page or PDF document:

• the document structure is preserved by markdown syntax: headers, lists, tables, paragraphs
• all duplicate paragraphs are removed

Dataset Structure

The dataset is divided in 3 splits:

• train: 80% of the data
• valid: 10% of the data
• test: 10% of the data

wordslab-webscraper generates one parquet file per website and per split.

The parquet files are named with the following pattern:

• banque_fr_2311_[split]_[website].parquet

Note than you can load individual splits or websites with HuggingFace datasets using the following commands:

from datasets import load_dataset

# Load a single plit
dataset = load_dataset("namespace/banque-fr-2311", split="train")

# Load a single website
data_files = { "train": "banque_fr_2311_train_[website].parquet", "valid": "banque_fr_2311_valid_[website].parquet", "test": "banque_fr_2311_test_[website].parquet" }
dataset = load_dataset("namespace/banque-fr-2311", data_files=data_files)

Each example in the dataset contains the text of a full web page or PDF document, with the following features:

• Uri: string
• Timestamp: string
• Lang: string
• Title: string
• Text: string
• Words: int32
• AvgWordsLength: int32
• Chars: int32
• LetterChars: int32
• NumberChars: int32
• OtherChars: int32
• Website: string
• PDF: bool

Note that beause each example is a full page or document, the "Text" feature can be a pretty long string containing thousands of words (as measured by the "Words" feature): you will typically need to chunk it down to the context size of your large language model before using it.

Bias, Risks, and Limitations

This dataset is a direct extraction from the source websites.

It was not manually curated to remove misleading, offensive, or harmful content.

Please add a filtering step before using it to train a large language model if the source websites can't be trusted.

Dataset Card Contact

Please add a comment in the community section of this repository if you want the maintainer to add or remove websites from this dataset.