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Commit
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Update files from the datasets library (from 1.9.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.9.0

Files changed (2) hide show
  1. README.md +12 -3
  2. turkish_product_reviews.py +1 -1
README.md CHANGED
@@ -18,6 +18,7 @@ task_categories:
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  task_ids:
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  - sentiment-classification
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  paperswithcode_id: null
 
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  ---
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  # Dataset Card for Turkish Product Reviews
@@ -55,6 +56,10 @@ paperswithcode_id: null
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  This Turkish Product Reviews Dataset contains 235.165 product reviews collected online. There are 220.284 positive, 14881 negative reviews.
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  ### Languages
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  The dataset is based on Turkish.
@@ -121,7 +126,11 @@ The dataset does not contain any additional annotations.
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  ## Considerations for Using the Data
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- ### Discussion of Social Impact and Biases
 
 
 
 
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  [More Information Needed]
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@@ -141,8 +150,8 @@ The data is under the [CC-BY-SA-4.0 License](https://github.com/fthbrmnby/turkis
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  ### Citation Information
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- [More Information Needed]
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  ### Contributions
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- Thanks to [@basakbuluz](https://github.com/basakbuluz) for adding this dataset.
 
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  task_ids:
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  - sentiment-classification
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  paperswithcode_id: null
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+ pretty_name: Turkish Product Reviews
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  ---
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  # Dataset Card for Turkish Product Reviews
 
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  This Turkish Product Reviews Dataset contains 235.165 product reviews collected online. There are 220.284 positive, 14881 negative reviews.
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+ ### Supported Tasks and Leaderboards
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+
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+ [More Information Needed]
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+
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  ### Languages
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  The dataset is based on Turkish.
 
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  ## Considerations for Using the Data
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+ ### Social Impact of Dataset
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+
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+ [More Information Needed]
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+
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+ ### Discussion of Biases
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  [More Information Needed]
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  ### Citation Information
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+ No citation available for this dataset.
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  ### Contributions
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+ Thanks to [@basakbuluz](https://github.com/basakbuluz) for adding this dataset.
turkish_product_reviews.py CHANGED
@@ -55,7 +55,7 @@ class TurkishProductReviews(datasets.GeneratorBasedBuilder):
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  logger.info("⏳ Generating examples from = %s", filepath)
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  for file_idx, f in enumerate(sorted(filenames)):
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  filename, file_extension = os.path.splitext(f)
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- label = "negative" if file_extension == "neg" else "positive"
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  file_fullpath = os.path.join(filepath, f)
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  with open(file_fullpath, encoding="utf-8") as f:
 
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  logger.info("⏳ Generating examples from = %s", filepath)
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  for file_idx, f in enumerate(sorted(filenames)):
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  filename, file_extension = os.path.splitext(f)
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+ label = "negative" if file_extension == ".neg" else "positive"
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  file_fullpath = os.path.join(filepath, f)
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  with open(file_fullpath, encoding="utf-8") as f: