Datasets:
metadata
license: apache-2.0
dataset_info:
- config_name: cat_Latn
features:
- name: corpus
dtype: string
- name: category
dtype: string
- name: dataset
dtype: string
- name: task
dtype: string
- name: prompt
dtype: string
- name: model
dtype: string
- name: ckpt_num
dtype: int64
- name: score
dtype: float64
splits:
- name: results
num_bytes: 2921244
num_examples: 13248
download_size: 167200
dataset_size: 2921244
- config_name: ces_Latn
features:
- name: corpus
dtype: string
- name: category
dtype: string
- name: dataset
dtype: string
- name: task
dtype: string
- name: prompt
dtype: string
- name: model
dtype: string
- name: ckpt_num
dtype: int64
- name: score
dtype: float64
splits:
- name: results
num_bytes: 3245157
num_examples: 14256
download_size: 135814
dataset_size: 3245157
- config_name: eus_Latn
features:
- name: corpus
dtype: string
- name: category
dtype: string
- name: dataset
dtype: string
- name: task
dtype: string
- name: prompt
dtype: string
- name: model
dtype: string
- name: ckpt_num
dtype: int64
- name: score
dtype: float64
splits:
- name: results
num_bytes: 2619840
num_examples: 9216
download_size: 95934
dataset_size: 2619840
- config_name: fin_Latn
features:
- name: corpus
dtype: string
- name: category
dtype: string
- name: dataset
dtype: string
- name: task
dtype: string
- name: prompt
dtype: string
- name: model
dtype: string
- name: ckpt_num
dtype: int64
- name: score
dtype: float64
splits:
- name: results
num_bytes: 4683024
num_examples: 19200
download_size: 221268
dataset_size: 4683024
- config_name: fra_Latn
features:
- name: corpus
dtype: string
- name: category
dtype: string
- name: dataset
dtype: string
- name: task
dtype: string
- name: prompt
dtype: string
- name: model
dtype: string
- name: ckpt_num
dtype: int64
- name: score
dtype: float64
splits:
- name: results
num_bytes: 1261596
num_examples: 5184
download_size: 46933
dataset_size: 1261596
- config_name: glg_Latn
features:
- name: corpus
dtype: string
- name: category
dtype: string
- name: dataset
dtype: string
- name: task
dtype: string
- name: prompt
dtype: string
- name: model
dtype: string
- name: ckpt_num
dtype: int64
- name: score
dtype: float64
splits:
- name: results
num_bytes: 1281960
num_examples: 5760
download_size: 54175
dataset_size: 1281960
- config_name: nor_Latn
features:
- name: corpus
dtype: string
- name: category
dtype: string
- name: dataset
dtype: string
- name: task
dtype: string
- name: prompt
dtype: string
- name: model
dtype: string
- name: ckpt_num
dtype: int64
- name: score
dtype: float64
- name: __index_level_0__
dtype: int64
splits:
- name: results
num_bytes: 4236540
num_examples: 15936
download_size: 290910
dataset_size: 4236540
- config_name: spa_Latn
features:
- name: corpus
dtype: string
- name: category
dtype: string
- name: dataset
dtype: string
- name: task
dtype: string
- name: prompt
dtype: string
- name: model
dtype: string
- name: ckpt_num
dtype: int64
- name: score
dtype: float64
splits:
- name: results
num_bytes: 2065536
num_examples: 9216
download_size: 98706
dataset_size: 2065536
- config_name: ukr_Cyrl
features:
- name: corpus
dtype: string
- name: category
dtype: string
- name: dataset
dtype: string
- name: task
dtype: string
- name: prompt
dtype: string
- name: model
dtype: string
- name: ckpt_num
dtype: int64
- name: score
dtype: float64
splits:
- name: results
num_bytes: 1056612
num_examples: 4032
download_size: 40782
dataset_size: 1056612
configs:
- config_name: cat_Latn
data_files:
- split: results
path: cat_Latn/results-*
- config_name: ces_Latn
data_files:
- split: results
path: ces_Latn/results-*
- config_name: eus_Latn
data_files:
- split: results
path: eus_Latn/results-*
- config_name: fin_Latn
data_files:
- split: results
path: fin_Latn/results-*
- config_name: fra_Latn
data_files:
- split: results
path: fra_Latn/results-*
- config_name: glg_Latn
data_files:
- split: results
path: glg_Latn/results-*
- config_name: nor_Latn
data_files:
- split: results
path: nor_Latn/results-*
- config_name: spa_Latn
data_files:
- split: results
path: spa_Latn/results-*
- config_name: ukr_Cyrl
data_files:
- split: results
path: ukr_Cyrl/results-*
language:
- es
- fr
- cs
- uk
- fi
- ca
- nb
- nn
- gl
- eu
HPLT 3.0: Details on Corpus Comparison Results
Dataset Description
This dataset contains fine-grained results from our HPLT 3.0 release evaluations comparing the new HPLT 3.0 corpora with the previous HPLT 2.0 version, FineWeb2, and MADLAD-400. We pretrain 2.2B Llama-style decoder models on 100B tokens for each selected language and evaluate them using HPLT-E, a multilingual evaluation framework for comprehensive multi-prompt k-shot evaluation across 124 tasks and 500+ prompts in nine typologically diverse languages: Spanish (spa_Latn), French (fra_Latn), Czech (ces_Latn), Ukrainian (ukr_Cyrl), Finnish (fin_Latn), Catalan (cat_Latn), Galician (glg_Latn), Basque (eus_Latn), and Norwegian (Bokmål and Nynorsk; nor_Latn).
- Curated by: High Performance Language Technologies (HPLT)
- Languages: Spanish, French, Czech, Ukrainian, Finnish, Catalan, Galician, Basque, Norwegian Bokmål, and Norwegian Nynorsk
- Paper: arxiv.org/abs/2511.01066
- Repository: github.com/hplt-project/hplt-e
- License: Apache 2.0
Please find more details in our paper and GitHub repository.
Uses
This dataset is intended for reproducibility and research purposes. Find an example on how to access the results:
from datasets import load_dataset
dataset = load_dataset("HPLT/2508-datasets-evals", "spa_Latn", split="results").to_pandas()
Dataset Structure
Dataset Instances
Each dataset instance looks as follows:
{
'corpus': 'MADLAD-400 1.0',
'category': 'Language-specific & world knowledge',
'dataset': 'global_mmlu_spanish',
'task': 'global_mmlu_spanish_p0',
'prompt': '{{question.strip()}}\nA. {{option_a}}\nB. {{option_b}}\nC. {{option_c}}\nD. {{option_d}}\nRespuesta:',
'model': '69B',
'ckpt_num': 33000,
'score': 22.974
}
Dataset Fields
corpus: corpus name (HPLT 2.0,MADLAD-400 1.0,FineWeb2.1.0,HPLT 3.0)category: task categorydataset: evaluation dataset nametask: evaluation task (refers to a specific prompt)prompt: prompt used for evaluationmodel: number of pretraining tokens (B)ckpt_num: number identifier formodelscore: standard metric performance score
Cite Us
@article{oepen2025hplt,
title={HPLT\~{} 3.0: Very Large-Scale Multilingual Resources for LLM and MT. Mono-and Bi-lingual Data, Multilingual Evaluation, and Pre-Trained Models},
author={Oepen, Stephan and Arefev, Nikolay and Aulamo, Mikko and Ba{\~n}{\'o}n, Marta and Buljan, Maja and Burchell, Laurie and Charpentier, Lucas and Chen, Pinzhen and Fedorova, Mariya and de Gibert, Ona and others},
journal={arXiv preprint arXiv:2511.01066},
year={2025}
}
Contact Us
- Vladislav Mikhailov vladism@ifi.uio.no
- Stephan Oepen oe@ifi.uio.no