README.md

metadata

license: cc-by-3.0

Dataset Summary

• Homepage: https://sites.google.com/view/salt-nlp-flang
• Models: https://huggingface.co/SALT-NLP/FLANG-BERT
• Repository: https://github.com/SALT-NLP/FLANG

FLUE

FLUE (Financial Language Understanding Evaluation) is a comprehensive and heterogeneous benchmark that has been built from 5 diverse financial domain specific datasets.

Sentiment Classification: Financial PhraseBank
Sentiment Analysis, Question Answering: FiQA 2018
New Headlines Classification: Headlines
Named Entity Recognition: NER
Structure Boundary Detection: FinSBD3

Dataset Structure

The FiQA dataset has a corpus, queries and qrels (relevance judgments file). They are in the following format:

• corpus file: a .jsonl file (jsonlines) that contains a list of dictionaries, each with three fields _id with unique document identifier, title with document title (optional) and text with document paragraph or passage. For example: {"_id": "doc1", "title": "Albert Einstein", "text": "Albert Einstein was a German-born...."}
• queries file: a .jsonl file (jsonlines) that contains a list of dictionaries, each with two fields _id with unique query identifier and text with query text. For example: {"_id": "q1", "text": "Who developed the mass-energy equivalence formula?"}
• qrels file: a .tsv file (tab-seperated) that contains three columns, i.e. the query-id, corpus-id and score in this order. Keep 1st row as header. For example: q1 doc1 1