# Datasets used for spoiler generation task

## Dataset Description
This dataset contains multiple datasets used for spoiler generation task for Clickbait spoiling competition for 
training models based on Question Answering, text generation, or learn-to-rank problems.

## Dataset Structure
This dataset has 5 main directories:
  - clf_data - this dataset was used to train a classifier for two generated spoilers to decide
      which spoiler better matches a clickbait post. This model makes a binary classification,
      class 1 corresponds to the situation when the first spoiler is "better" than the second,
      and class 0 corresponds to the opposite situation
  - clickbait_spoiling_data - this dataset is the original dataset taken from the Clickbait spoiling competition
  - generated_questions - this dataset contains questions generated for clickbait posts by the Vicuna model
  - models_output - in this dataset were inserted generated spoilers from the best-selected models
  - regressor_data - this dataset was used to train a model that estimates the BLEU of generated
      spoiler without knowing reference spoiler



task_categories:question-answering task_categories:text-generation language:en spoiler generation clickbait spoiling region:us
{"language": ["en"], "task_categories": ["question-answering", "text-generation"], "tags": ["spoiler generation", "clickbait spoiling"]}
TAGS
#task_categories-question-answering #task_categories-text-generation #language-English #spoiler generation #clickbait spoiling #region-us 

# Datasets used for spoiler generation task

## Dataset Description
This dataset contains multiple datasets used for spoiler generation task for Clickbait spoiling competition for 
training models based on Question Answering, text generation, or learn-to-rank problems.

## Dataset Structure
This dataset has 5 main directories:
  - clf_data - this dataset was used to train a classifier for two generated spoilers to decide
      which spoiler better matches a clickbait post. This model makes a binary classification,
      class 1 corresponds to the situation when the first spoiler is "better" than the second,
      and class 0 corresponds to the opposite situation
  - clickbait_spoiling_data - this dataset is the original dataset taken from the Clickbait spoiling competition
  - generated_questions - this dataset contains questions generated for clickbait posts by the Vicuna model
  - models_output - in this dataset were inserted generated spoilers from the best-selected models
  - regressor_data - this dataset was used to train a model that estimates the BLEU of generated
      spoiler without knowing reference spoiler



# Datasets used for spoiler generation task ## Dataset Description
This dataset contains multiple datasets used for spoiler generation task for Clickbait spoiling competition for 
training models based on Question Answering, text generation, or learn-to-rank problems. ## Dataset Structure
This dataset has 5 main directories:
  - clf_data - this dataset was used to train a classifier for two generated spoilers to decide
      which spoiler better matches a clickbait post. This model makes a binary classification,
      class 1 corresponds to the situation when the first spoiler is "better" than the second,
      and class 0 corresponds to the opposite situation
  - clickbait_spoiling_data - this dataset is the original dataset taken from the Clickbait spoiling competition
  - generated_questions - this dataset contains questions generated for clickbait posts by the Vicuna model
  - models_output - in this dataset were inserted generated spoilers from the best-selected models
  - regressor_data - this dataset was used to train a model that estimates the BLEU of generated
      spoiler without knowing reference spoiler
TAGS
#task_categories-question-answering #task_categories-text-generation #language-English #spoiler generation #clickbait spoiling #region-us 
 # Datasets used for spoiler generation task ## Dataset Description
This dataset contains multiple datasets used for spoiler generation task for Clickbait spoiling competition for 
training models based on Question Answering, text generation, or learn-to-rank problems. ## Dataset Structure
This dataset has 5 main directories:
  - clf_data - this dataset was used to train a classifier for two generated spoilers to decide
      which spoiler better matches a clickbait post. This model makes a binary classification,
      class 1 corresponds to the situation when the first spoiler is "better" than the second,
      and class 0 corresponds to the opposite situation
  - clickbait_spoiling_data - this dataset is the original dataset taken from the Clickbait spoiling competition
  - generated_questions - this dataset contains questions generated for clickbait posts by the Vicuna model
  - models_output - in this dataset were inserted generated spoilers from the best-selected models
  - regressor_data - this dataset was used to train a model that estimates the BLEU of generated
      spoiler without knowing reference spoiler