--- license: cc-by-4.0 task_categories: - summarization language: - en pretty_name: Custom CNN/Daily Mail Summarization Dataset size_categories: - n<1K --- # Dataset Card for Custom Text Dataset ## Dataset Name Custom CNN/Daily Mail Summarization Dataset ## Overview This dataset is a custom version of the CNN/Daily Mail dataset, designed for text summarization tasks. It contains news articles and their corresponding summaries. ## Composition The dataset consists of two splits: - Train: 1 custom example - Test: 100 examples from the original CNN/Daily Mail dataset Each example contains: - 'sentence': The full text of a news article - 'labels': The summary of the article ## Collection Process The training data is a custom example created manually, while the test data is sampled from the CNN/Daily Mail dataset (version 3.0.0) available on Hugging Face. ## Preprocessing No specific preprocessing was applied beyond the original CNN/Daily Mail dataset preprocessing. ## How to Use ```python from datasets import load_from_disk # Load the dataset dataset = load_from_disk("./results/custom_dataset/") # Access the data train_data = dataset['train'] test_data = dataset['test'] # Example usage print(train_data['sentence']) print(train_data['labels']) ``` ## Evaluation This dataset is intended for text summarization tasks. Common evaluation metrics include ROUGE scores, which measure the overlap between generated summaries and reference summaries. ## Limitations - The training set is extremely small (1 example), which may limit its usefulness for model training. - The test set is a subset of the original CNN/Daily Mail dataset, which may not represent the full diversity of news articles. ## Ethical Considerations - The dataset contains news articles, which may include sensitive or biased content. - Users should be aware of potential copyright issues when using news content for model training or deployment. - Care should be taken to avoid generating or propagating misleading or false information when using models trained on this dataset.