metadata

annotations_creators:
  - expert-generated
language:
  - en
  - de
  - fr
language_creators:
  - found
license: []
multilinguality:
  - multilingual
pretty_name: XNLI Parallel Corpus
size_categories:
  - 100K<n<1M
source_datasets:
  - extended|xnli
tags:
  - mode classification
  - aligned
task_categories:
  - text-classification
task_ids: []
dataset_info:
  - config_name: en
    features:
      - name: text
        dtype: string
      - name: label
        dtype:
          class_label:
            names:
              '0': spoken
              '1': written
    splits:
      - name: train
        num_bytes: 92288
        num_examples: 830
      - name: test
        num_bytes: 186853
        num_examples: 1669
  - config_name: de
    features:
      - name: text
        dtype: string
      - name: label
        dtype:
          class_label:
            names:
              '0': spoken
              '1': written
    splits:
      - name: train
        num_bytes: 105681
        num_examples: 830
      - name: test
        num_bytes: 214008
        num_examples: 1669
  - config_name: fr
    features:
      - name: text
        dtype: string
      - name: label
        dtype:
          class_label:
            names:
              '0': spoken
              '1': written
    splits:
      - name: train
        num_bytes: 830
        num_examples: 109164
      - name: test
        num_bytes: 221286
        num_examples: 1669
download_size: 1864
dataset_size: 1840

Dataset Card for XNLI Parallel Corpus

Dataset Description

Homepage:
Repository:
Paper:
Leaderboard:
Point of Contact:

Dataset Summary

Supported Tasks and Leaderboards

Binary mode classification (spoken vs written)

Languages

English
German
French

Dataset Structure

Data Instances

{ 'text': "And he said , Mama , I 'm home .", 'label': 0 }

Data Fields

text: sentence
label: binary label of text (0: spoken 1: written)

Data Splits

train: 830
test: 1669

Other Statistics

Vocabulary Size

English
- train: 4363
- test: 7128
German
- train: 5070
- test: 8601
French
- train: 4881
- test: 7935

Average Sentence Length

English
- train: 20.689156626506023
- test: 20.75254643499101
German
- train: 20.367469879518072
- test: 20.639904134212102
French
- train: 23.455421686746988
- test: 23.731575793888556

Label Split

train:
- 0: 166
- 1: 664
test:
- 0: 334
- 1: 1335

Out-of-vocabulary words in model

English
- BERT (bert-base-uncased)
  - train: 800
  - test: 1638
- mBERT (bert-base-multilingual-uncased)
  - train: 1347
  - test: 2693
- German BERT (bert-base-german-dbmdz-uncased)
  - train: 3228
  - test: 5581
- flauBERT (flaubert-base-uncased)
  - train: 4363
  - test: 7128
German
- BERT (bert-base-uncased)
  - train: 4285
  - test: 7387
- mBERT (bert-base-multilingual-uncased)
  - train: 3126
  - test: 5863
- German BERT (bert-base-german-dbmdz-uncased)
  - train: 2033
  - test: 3938
- flauBERT (flaubert-base-uncased)
  - train: 5069
  - test: 8600
French
- BERT (bert-base-uncased)
  - train: 3784
  - test: 6289
- mBERT (bert-base-multilingual-uncased)
  - train: 2847
  - test: 5084
- German BERT (bert-base-german-dbmdz-uncased)
  - train: 4212
  - test: 6964
- flauBERT (flaubert-base-uncased)
  - train: 4881
  - test: 7935

Dataset Creation

Curation Rationale

N/A

Source Data

https://github.com/facebookresearch/XNLI

Here is the citation for the original XNLI paper.

@InProceedings{conneau2018xnli,
  author = "Conneau, Alexis
        and Rinott, Ruty
        and Lample, Guillaume
        and Williams, Adina
        and Bowman, Samuel R.
        and Schwenk, Holger
        and Stoyanov, Veselin",
  title = "XNLI: Evaluating Cross-lingual Sentence Representations",
  booktitle = "Proceedings of the 2018 Conference on Empirical Methods
               in Natural Language Processing",
  year = "2018",
  publisher = "Association for Computational Linguistics",
  location = "Brussels, Belgium",
}

Initial Data Collection and Normalization

N/A

Who are the source language producers?

N/A

Annotations

Annotation process

N/A

Who are the annotators?

N/A

Personal and Sensitive Information

N/A

Considerations for Using the Data

Social Impact of Dataset

N/A

Discussion of Biases

N/A

Other Known Limitations

N/A

Additional Information

Dataset Curators

N/A

Licensing Information

N/A

Citation Information

Contributions

N/A