anli

• Description:

Adversarial NLI (ANLI) is a large-scale NLI benchmark dataset, collected via an iterative, adversarial human-and-model-in-the-loop procedure.

• Additional Documentation: Explore on Papers With Code north_east

• Homepage: https://github.com/facebookresearch/anli

• Source code: tfds.datasets.anli.Builder

• Versions:

  • 0.1.0 (default): No release notes.

• Download size: 17.76 MiB

• Auto-cached (documentation): Yes

• Feature structure:

FeaturesDict({
    'context': Text(shape=(), dtype=string),
    'hypothesis': Text(shape=(), dtype=string),
    'label': ClassLabel(shape=(), dtype=int64, num_classes=3),
    'uid': Text(shape=(), dtype=string),
})

• Feature documentation:

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Citation:

@inproceedings{Nie2019AdversarialNA,
    title = "Adversarial NLI: A New Benchmark for Natural Language Understanding",
    author = "Nie, Yixin and
      Williams, Adina and
      Dinan, Emily  and
      Bansal, Mohit and
      Weston, Jason and
      Kiela, Douwe",
      year="2019",
    url ="https://arxiv.org/abs/1910.14599"
}

anli/r1 (default config)

• Config description: Round One

• Dataset size: 9.04 MiB

• Splits:

• Examples (tfds.as_dataframe):

anli/r2

• Config description: Round Two

• Dataset size: 22.39 MiB

• Splits:

• Examples (tfds.as_dataframe):

anli/r3

• Config description: Round Three

• Dataset size: 47.03 MiB

• Splits:

• Examples (tfds.as_dataframe):