Update files from the datasets library (from 1.4.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.4.0
README.md
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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##
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- **Homepage:** [https://github.com/facebookresearch/anli/](https://github.com/facebookresearch/anli/)
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- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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- **Size of the generated dataset:** 73.55 MB
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- **Total amount of disk used:** 91.31 MB
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###
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The Adversarial Natural Language Inference (ANLI) is a new large-scale NLI benchmark dataset,
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The dataset is collected via an iterative, adversarial human-and-model-in-the-loop procedure.
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ANLI is much more difficult than its predecessors including SNLI and MNLI.
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It contains three rounds. Each round has train/dev/test splits.
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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##
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We show detailed information for up to 5 configurations of the dataset.
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###
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#### plain_text
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}
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```
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###
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The data fields are the same among all splits.
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- `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2).
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- `reason`: a `string` feature.
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###
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| name |train_r1|dev_r1|train_r2|dev_r2|train_r3|dev_r3|test_r1|test_r2|test_r3|
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##
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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##
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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##
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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###
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```
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@InProceedings{nie2019adversarial,
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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- **Homepage:** [https://github.com/facebookresearch/anli/](https://github.com/facebookresearch/anli/)
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- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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- **Size of the generated dataset:** 73.55 MB
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- **Total amount of disk used:** 91.31 MB
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### Dataset Summary
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The Adversarial Natural Language Inference (ANLI) is a new large-scale NLI benchmark dataset,
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The dataset is collected via an iterative, adversarial human-and-model-in-the-loop procedure.
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ANLI is much more difficult than its predecessors including SNLI and MNLI.
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It contains three rounds. Each round has train/dev/test splits.
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### Supported Tasks
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Languages
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## Dataset Structure
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We show detailed information for up to 5 configurations of the dataset.
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### Data Instances
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#### plain_text
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}
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```
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### Data Fields
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The data fields are the same among all splits.
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- `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2).
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- `reason`: a `string` feature.
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### Data Splits Sample Size
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| name |train_r1|dev_r1|train_r2|dev_r2|train_r3|dev_r3|test_r1|test_r2|test_r3|
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|----------|-------:|-----:|-------:|-----:|-------:|-----:|------:|------:|------:|
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|plain_text| 16946| 1000| 45460| 1000| 100459| 1200| 1000| 1000| 1200|
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## Dataset Creation
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### Curation Rationale
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Source Data
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Annotations
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Personal and Sensitive Information
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Discussion of Biases
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Other Known Limitations
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## Additional Information
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### Dataset Curators
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Licensing Information
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### Citation Information
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```
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@InProceedings{nie2019adversarial,
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