datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
nli_fever
Overview
The original dataset can be found here
while the Github repo is here.
This dataset has been proposed in Combining fact extraction and verification with neural semantic matching networks. This dataset has been created as a modification
of FEVER.
In the original FEVER setting, the input is a claim from Wikipedia and the expected output is a label.
However, this is different from the standard NLI formalization which is basically a pair-of-sequence to label problem.
To… See the full description on the dataset page: https://huggingface.co/datasets/pietrolesci/nli_fever.FEVER_test_top_250_only_w_correct-v2
FEVERHardNegatives
An MTEB dataset
Massive Text Embedding Benchmark
FEVER (Fact Extraction and VERification) consists of 185,445 claims generated by altering sentences extracted from Wikipedia and subsequently verified without knowledge of the sentence they were derived from. The hard negative version has been created by pooling the 250 top documents per query from BM25, e5-multilingual-large and e5-mistral-instruct.
Task category
t2t
Domains
Encyclopaedic, Written… See the full description on the dataset page: https://huggingface.co/datasets/mteb/FEVER_test_top_250_only_w_correct-v2.climate_fever
Dataset Card for ClimateFever
Dataset Summary
A dataset adopting the FEVER methodology that consists of 1,535 real-world claims regarding climate-change collected on the internet. Each claim is accompanied by five manually annotated evidence sentences retrieved from the English Wikipedia that support, refute or do not give enough information to validate the claim totalling in 7,675 claim-evidence pairs. The dataset features challenging claims that relate multiple facets… See the full description on the dataset page: https://huggingface.co/datasets/tdiggelm/climate_fever.fever
Dataset Card for BEIR Benchmark
fever is one of the datasets from the Fact Checking task within BEIR, measuring Wikipedia abstract retrieval for a given fact/statement as query.
Dataset Summary
BEIR is a heterogeneous benchmark built from 18 diverse datasets representing 9 information retrieval tasks.
Fact-checking: FEVER, Climate-FEVER, SciFact
Question-Answering: NQ, HotpotQA, FiQA-2018
Bio-Medical IR: TREC-COVID, BioASQ, NFCorpus
News Retrieval: TREC-NEWS, Robust04… See the full description on the dataset page: https://huggingface.co/datasets/BeIR/fever.climate-fever-decontaminated
climate-fever (Decontaminated)
A decontaminated version of the climate-fever dataset from the BEIR benchmark, with samples found in the mgte-en pre-training dataset removed.
Decontamination methodology
Contamination was detected using a two-pass approach against the full mgte-en dataset (484 GB, 1,235 parquet files):
Pass 1: Exact hash matching
All texts (queries and corpus documents) were normalized (lowercased, unicode NFKD, whitespace collapsed) and hashed… See the full description on the dataset page: https://huggingface.co/datasets/lightonai/climate-fever-decontaminated.climate-fever
Dataset Card for BEIR Benchmark
climate-fever is one of the datasets from the Fact Checking task within BEIR, measuring Wikipedia abstract retrieval for a given claim about climate.
Dataset Summary
BEIR is a heterogeneous benchmark built from 18 diverse datasets representing 9 information retrieval tasks.
Fact-checking: FEVER, Climate-FEVER, SciFact
Question-Answering: NQ, HotpotQA, FiQA-2018
Bio-Medical IR: TREC-COVID, BioASQ, NFCorpus
News Retrieval: TREC-NEWS… See the full description on the dataset page: https://huggingface.co/datasets/BeIR/climate-fever.fever-decontaminated
fever (Decontaminated)
A decontaminated version of the fever dataset from the BEIR benchmark, with samples found in the mgte-en pre-training dataset removed.
Decontamination methodology
Contamination was detected using a two-pass approach against the full mgte-en dataset (484 GB, 1,235 parquet files):
Pass 1: Exact hash matching
All texts (queries and corpus documents) were normalized (lowercased, unicode NFKD, whitespace collapsed) and hashed with xxHash-64.… See the full description on the dataset page: https://huggingface.co/datasets/lightonai/fever-decontaminated.fever-evidence-related
Dataset Summary
This dataset is extracted from Fever dataset (https://fever.ai), pre-processed and ready to train and evaluate.
The training objective is a text classification task - given a claim and evidence, predict if evidence is related to claim.
beir-fever
FEVER — BEIR, unified schema
A normalised copy of the dataset behind the mteb task FEVER, one of the tasks of the BEIR benchmark as mteb defines it. Same queries, documents
and relevance judgements as the benchmark evaluates — reshaped into one strict schema shared by every dataset
in this collection.
Source
mteb/fever @ bea83ef9e8fb (the revision pinned in mteb)
Domain · languages
fact-checking · eng
Queries / documents / qrels (all splits)
123,142 / 5,416,568… See the full description on the dataset page: https://huggingface.co/datasets/Hyukkyu/beir-fever.fever_bm25_top100_kilt
Dataset Card for "fever_bm25_top100_kilt"
More Information needed
BEIR-climate-fever-interprettl_ts_prompted_mergedfever-claim-related
Dataset Summary
This dataset is extracted from Climate Fever dataset (https://www.sustainablefinance.uzh.ch/en/research/climate-fever.html), pre-processed and ready to train and evaluate.
The training objective is a text classification task - given a claim and evidence, predict if claim is related to evidence.
climate-fever-vn
ClimateFEVER-VN
An MTEB dataset
Massive Text Embedding Benchmark
A translated dataset from CLIMATE-FEVER is a dataset adopting the FEVER methodology that consists of 1,535 real-world claims regarding climate-change. The process of creating the VN-MTEB (Vietnamese Massive Text Embedding Benchmark) from English samples involves a new automated system: - The system uses large language models (LLMs), specifically Coherence's Aya model, for translation. - Applies advanced embedding models… See the full description on the dataset page: https://huggingface.co/datasets/GreenNode/climate-fever-vn.mnli_anli_fevernli_wanli_lingnli_xnli_train
Dataset Card for "mnli_anli_fevernli_wanli_lingnli_xnli_train"
Train data in a harmonized format for multiple NLI datasets.
feverfever
Dataset Card for "fever"
FEVER dataset with evidence retrieved by KGAT, see my paper for more info.
Labels are converted to integers with the rule:
"SUPPORTS": 0
"NOT ENOUGH INFO": 1
"REFUTES": 2
fever-vn
FEVER-VN
An MTEB dataset
Massive Text Embedding Benchmark
A translated dataset from FEVER (Fact Extraction and VERification) consists of 185,445 claims generated by altering sentences extracted from Wikipedia and subsequently verified without knowledge of the sentence they were derived from. The process of creating the VN-MTEB (Vietnamese Massive Text Embedding Benchmark) from English samples involves a new automated system: - The system uses large language models (LLMs), specifically… See the full description on the dataset page: https://huggingface.co/datasets/GreenNode/fever-vn.beir-climate-fever
ClimateFEVER — BEIR, unified schema
A normalised copy of the dataset behind the mteb task ClimateFEVER, one of the tasks of the BEIR benchmark as mteb defines it. Same queries, documents
and relevance judgements as the benchmark evaluates — reshaped into one strict schema shared by every dataset
in this collection.
Source
mteb/climate-fever @ 47f2ac6acb64 (the revision pinned in mteb)
Domain · languages
fact-checking · eng
Queries / documents / qrels
1,535 / 5… See the full description on the dataset page: https://huggingface.co/datasets/Hyukkyu/beir-climate-fever.fever_ftThe dataset contains a random 0.7/0.1/0.2 train/dev/test splits of fever dataset from BEIR https://github.com/beir-cellar/beir for benchmarking embedding model fine-tuning.
hl-feverclimate_fever_fixed
Dataset Card for "climate_fever_fixed"
Dataset Summary
This dataset was created to aid our team in developing a model to more accurately perform climate change-related fact checking. We approach this task from a perspective heavily impacted
by the work of the ClimateBERT team. With that in mind, our team likewise leveraged a BERT Language model to solve this task. This dataset presents an
edited version of the Climate_Fever dataset, hosted by HuggingFace. Climate_Fever… See the full description on the dataset page: https://huggingface.co/datasets/rexarski/climate_fever_fixed.pl_ps_prompted_mergednfcorpus-scifact-fiqa-fever-hotpotqa-combineclimate_fever_plusThe dataset provided combines the Climate-Fever dataset and claim reviews from the website Climate Feedback (https://climatefeedback.org/)
FYI, the train dataset contains claim-evidence pairs from Climate-Fever and Climate Feedback, while test and validation dataset only contains data from CLIMATE-FEVER
For detail, please read this paper
climate_fever_adoptedFeverousFEVERfever-sft
Dataset Card for "fever-sft"
More Information needed
fever_contrastive