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---
language:
- en
size_categories:
- 100M<n<1B
task_categories:
- text-classification
dataset_info:
features:
- name: premise
dtype: string
- name: hypothesis
dtype: string
- name: label
dtype:
class_label:
names:
'0': entailment
'1': neutral
'2': contradiction
splits:
- name: train
num_bytes: 370699678.0762534
num_examples: 1688053
- name: dev
num_bytes: 5041282.50235704
num_examples: 14450
- name: test_anli_r1
num_bytes: 405400.0
num_examples: 1000
- name: test_anli_r2
num_bytes: 405263.0
num_examples: 1000
- name: test_anli_r3
num_bytes: 468098.0
num_examples: 1200
- name: test_vitaminc
num_bytes: 1291371.9832599598
num_examples: 5520
download_size: 196618794
dataset_size: 378311093.56187046
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: dev
path: data/dev-*
- split: test_anli_r1
path: data/test_anli_r1-*
- split: test_anli_r2
path: data/test_anli_r2-*
- split: test_anli_r3
path: data/test_anli_r3-*
- split: test_vitaminc
path: data/test_vitaminc-*
tags:
- natural-language-inference
- fact-checking
---
This monolingual (English) NLI dataset is designed for performing Natural Language Inference, and is particularly Fact-Checking oriented.
Dev split is oriented to teach the model how to deal well with pure NLI (ANLI is well designed for this task) and test his general knowledge (Fact-Checking skills) with VitaminC, which is known for its robustness for this task.
It contains:
- 14.5k examples for the dev split of which:
- 848 from ANLI train_r1;
- 2273 from ANLI train_r2;
- 5023 from ANLI train_r3;
- 6306 from VitaminC dev.
- 4 test splits (the 3 test splits of the ANLI dataset and 10% of the VitaminC test split).
- The remaining data composes the train split.
Datasets references:
- SNLI: https://huggingface.co/datasets/stanfordnlp/snli
- ANLI: https://huggingface.co/datasets/facebook/anli
- FEVER: https://huggingface.co/datasets/pietrolesci/nli_fever
- MNLI: https://huggingface.co/datasets/nyu-mll/multi_nli
- QNLI: https://huggingface.co/datasets/yangwang825/qnli
- WNLI (augmented with GLUE): https://huggingface.co/datasets/gokuls/glue_augmented_wnli
- SciTail: https://huggingface.co/datasets/allenai/scitail
- RTE: https://huggingface.co/datasets/yangwang825/rte
- Climate-FEVER: https://huggingface.co/datasets/Jasontth/climate_fever_plus
- VitaminC: https://huggingface.co/datasets/tals/vitaminc |