albertvillanova HF staff commited on
Commit
6291c54
1 Parent(s): f256e74

Revert addition of data files (#9)

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- Revert "add data files (#8)" (50f55e16859f2815a79532f56bc345805c0f6c41)
- Delete dataset_infos.json (8f31dd4fdd89365b7a4ba4ace8bc3f256eb330fd)
- Disable dataset viewer (45cb3670bb1d2256ab64aae560fdc5b3e0b11d4a)
- Add defunct disclaimer to dataset card (5e0a3f4e69c320a1ade094439dc55e7f059d07ac)
- Add the (501e9f32b14943cfa5c5acfbbf074314f38f8dec)

.gitattributes CHANGED
@@ -25,9 +25,3 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zstandard filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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- json/train/dataset_de_train.json filter=lfs diff=lfs merge=lfs -text
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- json/train/dataset_en_train.json filter=lfs diff=lfs merge=lfs -text
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- json/train/dataset_es_train.json filter=lfs diff=lfs merge=lfs -text
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- json/train/dataset_fr_train.json filter=lfs diff=lfs merge=lfs -text
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- json/train/dataset_ja_train.json filter=lfs diff=lfs merge=lfs -text
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- json/train/dataset_zh_train.json filter=lfs diff=lfs merge=lfs -text
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zstandard filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
README.md CHANGED
@@ -253,6 +253,7 @@ config_names:
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  - fr
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  - ja
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  - zh
 
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  ---
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  # Dataset Card for The Multilingual Amazon Reviews Corpus
@@ -297,6 +298,10 @@ config_names:
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  ### Dataset Summary
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  We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. ‘books’, ‘appliances’, etc.) The corpus is balanced across stars, so each star rating constitutes 20% of the reviews in each language.
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  For each language, there are 200,000, 5,000 and 5,000 reviews in the training, development and test sets respectively. The maximum number of reviews per reviewer is 20 and the maximum number of reviews per product is 20. All reviews are truncated after 2,000 characters, and all reviews are at least 20 characters long.
 
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  - fr
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  - ja
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  - zh
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+ viewer: false
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  ---
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  # Dataset Card for The Multilingual Amazon Reviews Corpus
 
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  ### Dataset Summary
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+ <div class="course-tip course-tip-orange bg-gradient-to-br dark:bg-gradient-to-r before:border-orange-500 dark:before:border-orange-800 from-orange-50 dark:from-gray-900 to-white dark:to-gray-950 border border-orange-50 text-orange-700 dark:text-gray-400">
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+ <p><b>Defunct:</b> Dataset "amazon_reviews_multi" is defunct and no longer accessible due to the decision of data providers.</p>
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+ </div>
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+
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  We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. ‘books’, ‘appliances’, etc.) The corpus is balanced across stars, so each star rating constitutes 20% of the reviews in each language.
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  For each language, there are 200,000, 5,000 and 5,000 reviews in the training, development and test sets respectively. The maximum number of reviews per reviewer is 20 and the maximum number of reviews per product is 20. All reviews are truncated after 2,000 characters, and all reviews are at least 20 characters long.
amazon_reviews_multi.py CHANGED
@@ -55,7 +55,7 @@ _LANGUAGES = {
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  _ALL_LANGUAGES = "all_languages"
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  _VERSION = "1.0.0"
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  _HOMEPAGE_URL = "https://registry.opendata.aws/amazon-reviews-ml/"
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- _DOWNLOAD_URL = "json/{split}/dataset_{lang}_{split}.json"
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  class AmazonReviewsMultiConfig(datasets.BuilderConfig):
 
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  _ALL_LANGUAGES = "all_languages"
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  _VERSION = "1.0.0"
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  _HOMEPAGE_URL = "https://registry.opendata.aws/amazon-reviews-ml/"
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+ _DOWNLOAD_URL = "https://amazon-reviews-ml.s3-us-west-2.amazonaws.com/json/{split}/dataset_{lang}_{split}.json"
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  class AmazonReviewsMultiConfig(datasets.BuilderConfig):
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