datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
IndustryInstruction_Finance-Economics
IndustryInstruction: Finance & Economics
This repository contains the IndustryInstruction: Finance & Economics domain subset of BAAI/IndustryInstruction.
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 IndustryInstruction:
@misc{shi2024industryinstruction,
title = {IndustryInstruction},
author = {Xiaofeng Shi and Lulu Zhao and Hua Zhou… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryInstruction_Finance-Economics.llama2_QA_Economics_230915
Dataset Card for "llama2_QA_Economics_230915"
More Information needed
EconWebArena
EconWebArena
EconWebArena is a curated benchmark for evaluating large language model (LLM) agents on complex, multimodal economic tasks grounded in real-world web content. It features question-answering tasks that require navigating authoritative websites, interpreting structured and visual data, and extracting precise economic information.
Loading the Dataset
Load EconWebArena data with the following code:
from datasets import load_dataset, Features, Value
# Define… See the full description on the dataset page: https://huggingface.co/datasets/EconWebArena/EconWebArena.econ-eval
econ-eval: how much do you give up by using a cheap model for an economist's work?
A reproducible benchmark of frontier and cheap LLMs on the work a trade and
policy economist actually does: Balassa RCA from raw BACI values, CAGR and
share arithmetic, bank capital and systemic-risk formulas, small trade-data
pipeline functions, checking a colleague's numbers, and policy writing in
English and Bangla. Every task carries a source field, every reference value
is derived from… See the full description on the dataset page: https://huggingface.co/datasets/deluair/econ-eval.NCERT_Economics_11thNCERT_Economics_12theconcausal-benchmark📊 EconCausal: A Context-Aware Causal Reasoning Benchmark for LLMs
Donggyu Lee, Hyeok Yun, Meeyoung Cha, Sungwon Park, Sangyoon Park, Jihee Kim
🌍 Overview
Socio-economic causal effects depend heavily on their specific institutional and environmental context. A single intervention can produce opposite results depending on regulatory or market factors.
EconCausal is a large-scale benchmark comprising 10,490 context-annotated causal triplets extracted from 2,595… See the full description on the dataset page: https://huggingface.co/datasets/qwqw3535/econcausal-benchmark.