Update on GitHub

				

				from nlp import load_dataset

				dataset = load_dataset("anli")
				
			

Description

The Adversarial Natural Language Inference (ANLI) is a new large-scale NLI benchmark dataset, The dataset is collected via an iterative, adversarial human-and-model-in-the-loop procedure. ANLI is much more difficult than its predecessors including SNLI and MNLI. It contains three rounds. Each round has train/dev/test splits.

Citation

@InProceedings{nie2019adversarial,
    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},
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    year = "2020",
    publisher = "Association for Computational Linguistics",
}

Models trained or fine-tuned on anli

None yet. Start fine-tuning now =)