Datasets:

Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
original
ArXiv:
License:
lhoestq HF staff commited on
Commit
b6fe10a
1 Parent(s): c366cc2

Update datasets task tags to align tags with models (#4067)

Browse files

* update tasks list

* update tags in dataset cards

* more cards updates

* update dataset tags parser

* fix multi-choice-qa

* style

* small improvements in some dataset cards

* allow certain tag fields to be empty

* update vision datasets tags

* use multi-class-image-classification and remove other tags

Commit from https://github.com/huggingface/datasets/commit/edb4411d4e884690b8b328dba4360dbda6b3cbc8

Files changed (1) hide show
  1. README.md +3 -3
README.md CHANGED
@@ -14,9 +14,9 @@ size_categories:
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  source_datasets:
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  - original
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  task_categories:
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- - conditional-text-generation
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  task_ids:
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- - conditional-text-generation-other-meaning-representtion-to-text
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  paperswithcode_id: null
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  pretty_name: the Cleaned Version of the E2E Dataset
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  ---
@@ -69,7 +69,7 @@ https://arxiv.org/abs/1706.09254
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  ### Supported Tasks and Leaderboards
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- - `conditional-text-generation-other-meaning-representtion-to-text`: The dataset can be used to train a model to generate descriptions in the restaurant domain from meaning representations, which consists in taking as input some data about a restaurant and generate a sentence in natural language that presents the different aspects of the data about the restaurant.. Success on this task is typically measured by achieving a *high* [BLEU](https://huggingface.co/metrics/bleu), [NIST](https://huggingface.co/metrics/nist), [METEOR](https://huggingface.co/metrics/meteor), [Rouge-L](https://huggingface.co/metrics/rouge), [CIDEr](https://huggingface.co/metrics/cider).
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  This task has an inactive leaderboard which can be found [here](http://www.macs.hw.ac.uk/InteractionLab/E2E/) and ranks models based on the metrics above.
 
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  source_datasets:
15
  - original
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  task_categories:
17
+ - text2text-generation
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  task_ids:
19
+ - text2text-generation-other-meaning-representtion-to-text
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  paperswithcode_id: null
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  pretty_name: the Cleaned Version of the E2E Dataset
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  ---
 
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  ### Supported Tasks and Leaderboards
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+ - `text2text-generation-other-meaning-representtion-to-text`: The dataset can be used to train a model to generate descriptions in the restaurant domain from meaning representations, which consists in taking as input some data about a restaurant and generate a sentence in natural language that presents the different aspects of the data about the restaurant.. Success on this task is typically measured by achieving a *high* [BLEU](https://huggingface.co/metrics/bleu), [NIST](https://huggingface.co/metrics/nist), [METEOR](https://huggingface.co/metrics/meteor), [Rouge-L](https://huggingface.co/metrics/rouge), [CIDEr](https://huggingface.co/metrics/cider).
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  This task has an inactive leaderboard which can be found [here](http://www.macs.hw.ac.uk/InteractionLab/E2E/) and ranks models based on the metrics above.