datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
yahoo-finance-data
The Financial data from Yahoo!
*** Key Points to Note ***
All financial data is sourced from Yahoo!Ⓡ Finance, Nasdaq!Ⓡ, and the U.S. Department of the Treasury via publicly available APIs, and is intended for research and educational purposes.
I will update the data regularly, and you are welcome to follow this project and use the data.
Each time the data is updated, I will record the update time in spec.json.
Data Usage Instructions
Use DuckDB… See the full description on the dataset page: https://huggingface.co/datasets/defeatbeta/yahoo-finance-data.financebenchFinanceBench is a first-of-its-kind test suite for evaluating the performance of LLMs on open book financial question answering (QA). This is an open source sample of 150 annotated examples used in the evaluation and analysis of models assessed in the FinanceBench paper.
The PDFs linked in the dataset can be found here as well: https://github.com/patronus-ai/financebench/tree/main/pdfs
The dataset comprises of questions about publicly traded companies, with corresponding answers and evidence… See the full description on the dataset page: https://huggingface.co/datasets/PatronusAI/financebench.DragonData-Finance-Corpus
DragonData World Finance Database
Priced like infrastructure. Free like air.
The institutional-grade bilingual (EN/中文) finance database for training and
evaluating expert AI systems — collected, cleaned, deduplicated, tokenized,
license-proven, timestamped. 3,700+ files and counting.
Start here: Browse the data ⬇ · Use it in 4 lines ⬇ · Live build feed ⬇
Browse the data
The table below is live — scroll, search, and read actual records right on this page.… See the full description on the dataset page: https://huggingface.co/datasets/dragonlimited/DragonData-Finance-Corpus.vidore_v3_finance_enViDoRe V3 : Finance - EN
This dataset, Financial_Bank_Reports, is a corpus of annual reports from the banking sector, intended for long-document understanding tasks. It is one of the 10 corpora comprising the ViDoRe v3 Benchmark.
About ViDoRe v3
ViDoRe V3 is our latest benchmark for RAG evaluation on visually-rich documents from real-world applications. It features 10 datasets with, in total, 26,000 pages and 3099 queries, translated into 6 languages. Each query comes with… See the full description on the dataset page: https://huggingface.co/datasets/vidore/vidore_v3_finance_en.Nemotron-SpecializedDomains-Finance-v1
Dataset Description
Nemotron-SpecializedDomains-Finance is a large-scale synthetic financial question-answering dataset designed to improve LLM performance on specialized financial reasoning and document comprehension tasks. The dataset comprises 326K+ high-quality Q&A pairs generated from SEC filings of S&P 500 companies spanning 2019-2024.
This dataset is ready for commercial use.
Overview
The dataset leverages template-based Synthetic Data Generation (SDG) to… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-SpecializedDomains-Finance-v1.IndustryCorpus_finance[中文主页]
Industry models play a crucial role in driving enterprise intelligence transformation and innovative development. High-quality industry data is key to improving the performance of large models and realizing industry applications. However, datasets currently used for industry model training generally suffer from issues such as insufficient data volume, low quality, and lack of domain expertise.
To address these problems, we constructed and applied 22 industry data processing operators to… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryCorpus_finance.finance-alpacaThis dataset is a combination of Stanford's Alpaca (https://github.com/tatsu-lab/stanford_alpaca) and FiQA (https://sites.google.com/view/fiqa/) with another 1.3k pairs custom generated using GPT3.5
Script for tuning through Kaggle's (https://www.kaggle.com) free resources using PEFT/LoRa: https://www.kaggle.com/code/gbhacker23/wealth-alpaca-lora
GitHub repo with performance analyses, training and data generation scripts, and inference notebooks: https://github.com/gaurangbharti1/wealth-alpaca… See the full description on the dataset page: https://huggingface.co/datasets/gbharti/finance-alpaca.synthetic_pii_finance_multilingual
Image generated by DALL-E. See prompt for more details
💼 📊 Synthetic Financial Domain Documents with PII Labels
gretelai/synthetic_pii_finance_multilingual is a dataset of full length synthetic financial documents containing Personally Identifiable Information (PII), generated using Gretel Navigator and released under Apache 2.0.
This dataset is designed to assist with the following use cases:
🏷️ Training NER (Named Entity Recognition) models to detect and label PII in… See the full description on the dataset page: https://huggingface.co/datasets/gretelai/synthetic_pii_finance_multilingual.finance-tasks
Adapting LLMs to Domains via Continual Pre-Training (ICLR 2024)
This repo contains the evaluation datasets for our paper Adapting Large Language Models via Reading Comprehension.
We explore continued pre-training on domain-specific corpora for large language models. While this approach enriches LLMs with domain knowledge, it significantly hurts their prompting ability for question answering. Inspired by human learning via reading comprehension, we propose a simple method to… See the full description on the dataset page: https://huggingface.co/datasets/AdaptLLM/finance-tasks.consumer-finance-complaints
BEE-spoke-data/consumer-finance-complaints
consumer-finance-complaints but in a format that actually works.
Pulled Feb 2024
finance_agent_benchmark
Finance Agent Benchmark Dataset
We present the Finance Agent Benchmark, featuring challenging and diverse real-world finance research problems which require LLMs to perform complex analysis with the use of of recent SEC filings.
We construct the benchmark using a taxonomy of nine financial task categories, developed in consultation with experts from banks, hedge funds, and private equity firms. The dataset includes 537 expert-authored questions, covering tasks from information… See the full description on the dataset page: https://huggingface.co/datasets/vals-ai/finance_agent_benchmark.finance-data-gdpval
finance-data — DHR / ILMN M&A Analysis Tasks
Investment-banking analysis tasks set in a (fictional) strategic M&A project
where Danaher (DHR) explores acquiring Illumina (ILMN). Each task gives an
agent a prompt plus a full deal-room of reference materials (financial models,
spreadsheets, PDFs, research) and grades the answer against a per-criterion
rubric. Tasks that require modifying a workbook also ship the expert's gold
workbook as a deliverable file.
Layout… See the full description on the dataset page: https://huggingface.co/datasets/noetic-labs/finance-data-gdpval.Argimi-Ardian-Finance-10k-text
The ArGiMI Ardian datasets : Text-only version
The ArGiMi project is committed to open-source principles and data sharing.
Thanks to our generous partners, we are releasing several valuable datasets to the public.
Dataset description
This text-only dataset comprises 34,000 financial annual reports, written in English, meticulously
extracted from their original PDF format to provide a valuable resource for researchers and developers in financial
analysis and natural… See the full description on the dataset page: https://huggingface.co/datasets/artefactory/Argimi-Ardian-Finance-10k-text.yahoo-finance-data
The Financial data from Yahoo!
*** Key Points to Note ***
All financial data is sourced from Yahoo!Ⓡ Finance, Nasdaq!Ⓡ, and the U.S. Department of the Treasury via publicly available APIs, and is intended for research and educational purposes.
I will update the data regularly, and you are welcome to follow this project and use the data.
Each time the data is updated, I will record the update time in spec.json.
Data Usage Instructions
Use DuckDB or… See the full description on the dataset page: https://huggingface.co/datasets/Joshua-Xia/yahoo-finance-data.vidore_v3_finance_frViDoRe V3 : Finance - FR
This dataset, Finance - FR, is a corpus of reports from french companies in the luxury domain, intended for long-document understanding tasks. It is one of the 10 corpora comprising the ViDoRe v3 Benchmark.
About ViDoRe v3
ViDoRe V3 is our latest benchmark for RAG evaluation on visually-rich documents from real-world applications. It features 10 datasets with, in total, 26,000 pages and 3099 queries, translated into 6 languages. Each query comes with… See the full description on the dataset page: https://huggingface.co/datasets/vidore/vidore_v3_finance_fr.vidore_v3_finance_en_mteb_format
Vidore3FinanceEnRetrieval
An MTEB dataset
Massive Text Embedding Benchmark
Retrieve associated pages according to questions.
Task category
t2i
Domains
Academic
Reference
https://huggingface.co/blog/QuentinJG/introducing-vidore-v3
Source datasets:
vidore/vidore_v3_finance_en
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_task("Vidore3FinanceEnRetrieval")
evaluator… See the full description on the dataset page: https://huggingface.co/datasets/vidore/vidore_v3_finance_en_mteb_format.FinanceBenchThe FinanceBench dataset is derived from the PatronusAI/financebench-test dataset, containing only the PASS examples processed into a clean format for question-answering tasks in the financial domain. FinanceBench-rtl has been repurposed for retrieval.
Usage
import datasets
# Download the dataset
queries = datasets.load_dataset("embedding-benchmark/FinanceBench", "queries")
documents = datasets.load_dataset("embedding-benchmark/FinanceBench", "corpus")
pair_labels =… See the full description on the dataset page: https://huggingface.co/datasets/embedding-benchmark/FinanceBench.MTBench_finance_stock
MTBench: A Multimodal Time Series Benchmark
MTBench (Huggingface, Github, Arxiv) is a suite of multimodal datasets for evaluating large language models (LLMs) in temporal and cross-modal reasoning tasks across finance and weather domains.
Each benchmark instance aligns high-resolution time series (e.g., stock prices, weather data) with textual context (e.g., news articles, QA prompts), enabling research into temporally grounded and multimodal understanding.
🏦 Stock… See the full description on the dataset page: https://huggingface.co/datasets/GGLabYale/MTBench_finance_stock.FinanceRAG-Linguamodeling_valuation_knowledge
Finance Training Data Repository
A curated collection of financial modeling courses, materials, and resources designed to serve as training data for building a finance industry knowledge base.
Repository Structure
Finance_Training_Data/
├── 01_Financial_Statement_Modeling/ # 3-statement modeling fundamentals
├── 02_DCF_Modeling/ # Discounted cash flow valuation
├── 03_Trading_Comps/ # Comparable company analysis
├──… See the full description on the dataset page: https://huggingface.co/datasets/financeindustryknowledgeskills/modeling_valuation_knowledge.FineWeb2024
FineWeb-Edu 2024 — Cleaned and Shuffled
This dataset is a year-specific, cleaned, shuffled, and sharded release derived from HuggingFaceFW/fineweb-edu. It contains English educational web text collected in Common Crawl snapshots whose dump identifier belongs to 2024.
This is not a news-only dataset. The year refers to the Common Crawl capture year, not necessarily the page's publication year.
Dataset summary
Item
Value
Year
2024
Rows
162,500,784… See the full description on the dataset page: https://huggingface.co/datasets/Yahoo-Finance-News/FineWeb2024.big-finance-benchmark
BigFinanceBench Public Release
arXiv | Website | GitHub | Blog post
Finance answers are only useful when another analyst can audit how they were produced. BigFinanceBench evaluates that full workflow: agents must produce a numerical answer, and their traces are graded against point-weighted rubrics for source choice, period, accounting definition, assumptions, adjustments, and calculation.
This release contains a 50-question stratified subset of the 928-item BigFinanceBench… See the full description on the dataset page: https://huggingface.co/datasets/RogoAI/big-finance-benchmark.consumer-finance-complaints-large
CFPB Complaints
A dataset of 7M complaints from the Consumer Financial Protection Bureau (CFPB), from 12/01/2011 to 01/02/2025. For descriptions of each column, please see consumerfinance.gov/complaint/data-use.
More Details
A description from the CFPB website:
The Consumer Complaint Database is a collection of complaints about consumer financial products and services that we sent to companies for response. Complaints are published after the company responds, confirming… See the full description on the dataset page: https://huggingface.co/datasets/davidheineman/consumer-finance-complaints-large.FinanceQAFinanceQA is a comprehensive testing suite designed to evaluate LLMs' performance on complex financial analysis tasks that mirror real-world investment work. The dataset aims to be substantially more challenging and practical than existing financial benchmarks, focusing on tasks that require precise calculations and professional judgment.
Paper: https://arxiv.org/abs/2501.18062
Description
The dataset contains two main categories of questions:
Tactical Questions: Questions based on… See the full description on the dataset page: https://huggingface.co/datasets/AfterQuery/FinanceQA.FineWeb2025
FineWeb-Edu 2025 — Cleaned and Shuffled
This dataset is a year-specific, cleaned, shuffled, and sharded release derived from HuggingFaceFW/fineweb-edu. It contains English educational web text collected in Common Crawl snapshots whose dump identifier belongs to 2025.
This is not a news-only dataset. The year refers to the Common Crawl capture year, not necessarily the page's publication year.
Dataset summary
Item
Value
Year
2025
Rows
99,022,205… See the full description on the dataset page: https://huggingface.co/datasets/Yahoo-Finance-News/FineWeb2025.FinQAFinance-Conversational-Dataset-IndicIndustryCorpus2_finance_economics
IndustryCorpus2: Finance & Economics
This repository contains the IndustryCorpus2: Finance & Economics domain subset of BAAI/IndustryCorpus2.
Refer to the parent dataset card for data construction, intended use, limitations,
and licensing details.
Citation
If you use this dataset in your work, please cite IndustryCorpus2:
@misc{shi2024industrycorpus2,
title = {IndustryCorpus2},
author = {Xiaofeng Shi and Lulu Zhao and Hua Zhou and Donglin Hao},
year… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryCorpus2_finance_economics.TATQAATLAS-Finance
ATLAS Finance
A benchmark of 100 expert-level tasks inside 13 realistic financial firm environments, packaged in the Harbor RLE format.
Each task drops an AI agent into a Linux workstation with a
persistent multi-app world — inbox, chat, calendar, virtual data room, drive,
wiki — and asks the agent to produce the same deliverable a financial professional would be responsible for:
an Excel workbook containing the model and supporting analysis.
Here we provide the data for this… See the full description on the dataset page: https://huggingface.co/datasets/handshake-ai-research/ATLAS-Finance.