Datasets:
metadata
license: cc-by-nc-4.0
task_categories:
- question-answering
language:
- id
tags:
- MMLU
- exams
size_categories:
- 1K<n<10K
dataset_info: null
configs:
- config_name: all
data_files:
- split: test
path: all/test.csv
- split: dev
path: all/dev.csv
- config_name: Tourism
data_files:
- split: test
path: Tourism/test.csv
- split: dev
path: Tourism/dev.csv
- config_name: Teacher Competency Test
data_files:
- split: test
path: Teacher Competency Test/test.csv
- split: dev
path: Teacher Competency Test/dev.csv
- config_name: Advocate
data_files:
- split: test
path: Advocate/test.csv
- split: dev
path: Advocate/dev.csv
- config_name: Medical Doctor
data_files:
- split: test
path: Medical Doctor/test.csv
- split: dev
path: Medical Doctor/dev.csv
- config_name: Sharia Life Insurance
data_files:
- split: test
path: Sharia Life Insurance/test.csv
- split: dev
path: Sharia Life Insurance/dev.csv
- config_name: Nurse
data_files:
- split: test
path: Nurse/test.csv
- split: dev
path: Nurse/dev.csv
- config_name: Clinical Psychology
data_files:
- split: test
path: Clinical Psychology/test.csv
- split: dev
path: Clinical Psychology/dev.csv
- config_name: Life Insurance
data_files:
- split: test
path: Life Insurance/test.csv
- split: dev
path: Life Insurance/dev.csv
- config_name: Certified Financial Planner
data_files:
- split: test
path: Certified Financial Planner/test.csv
- split: dev
path: Certified Financial Planner/dev.csv
- config_name: Midwife
data_files:
- split: test
path: Midwife/test.csv
- split: dev
path: Midwife/dev.csv
- config_name: Certified Public Accountant
data_files:
- split: test
path: Certified Public Accountant/test.csv
- split: dev
path: Certified Public Accountant/dev.csv
- config_name: Certified Professional Management Accountant
data_files:
- split: test
path: Certified Professional Management Accountant/test.csv
- split: dev
path: Certified Professional Management Accountant/dev.csv
- config_name: Pharmacist
data_files:
- split: test
path: Pharmacist/test.csv
- split: dev
path: Pharmacist/dev.csv
- config_name: Office Administration
data_files:
- split: test
path: Office Administration/test.csv
- split: dev
path: Office Administration/dev.csv
- config_name: Hospitality
data_files:
- split: test
path: Hospitality/test.csv
- split: dev
path: Hospitality/dev.csv
- config_name: Broadcasting
data_files:
- split: test
path: Broadcasting/test.csv
- split: dev
path: Broadcasting/dev.csv
- config_name: Graphic Design
data_files:
- split: test
path: Graphic Design/test.csv
- split: dev
path: Graphic Design/dev.csv
- config_name: Police
data_files:
- split: test
path: Police/test.csv
- split: dev
path: Police/dev.csv
- config_name: Certified Indonesian Tax Accountant
data_files:
- split: test
path: Certified Indonesian Tax Accountant/test.csv
- split: dev
path: Certified Indonesian Tax Accountant/dev.csv
- config_name: Risk Management
data_files:
- split: test
path: Risk Management/test.csv
- split: dev
path: Risk Management/dev.csv
- config_name: Culinary Art
data_files:
- split: test
path: Cullinary Art/test.csv
- split: dev
path: Cullinary Art/dev.csv
- config_name: Fashion Design
data_files:
- split: test
path: Fashion Design/test.csv
- split: dev
path: Fashion Design/dev.csv
Introduction
IndoCareer is a dataset comprising 8,834 multiple-choice questions designed to evaluate performance in vocational and professional certification exams across various fields. With a focus on Indonesia, IndoCareer provides rich local contexts, spanning six key sectors: (1) healthcare, (2) insurance and finance, (3) creative and design, (4) tourism and hospitality, (5) education and training, and (6) law.
Data
Each question in the dataset is a multiple-choice question with up to 5 choices and only one choice as the correct answer.
import datasets
data = datasets.load_dataset('indolem/IndoCareer', 'all')
Examples
These questions are written in Indonesian.
Evaluation
We evaluated one closed-source model (GPT-4o) and 26 open-weight LLMs:
Citation
Please find out paper 📄here.
@inproceedings{koto2025cracking,
title={Cracking the Code: Multi-domain LLM Evaluation on Real-World Professional Exams in Indonesia},
author={"Fajri Koto"},
booktitle={Proceedings of the 2025 Conference of the North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL HLT 2025), Industry Track},
year={2025}
}