Datasets:
Upload Newsify-Headlines.csv
Dataset Description:
This dataset contains headlines extracted from news articles, specifically designed for fine-tuning large language models (LLMs). The dataset includes headlines from various news outlets, focusing on key events and topics in the news. The data has been preprocessed and tokenized for use in natural language processing (NLP) tasks such as text classification, summarization, or language modeling.
Key Features:
Headlines: The main textual data in the dataset, consisting of short, attention-grabbing headlines from diverse news sources.
Cleaned Text: The headlines are cleaned and tokenized for model training, removing any unnecessary noise or characters.
Source: The dataset contains headlines scraped from publicly available news websites, ensuring a broad range of topics.
Text Length: Headlines have been truncated or padded to a consistent length of 128 tokens for uniformity and easier processing during training.
Intended Use:
This dataset is primarily intended for fine-tuning language models such as GPT-2 or similar transformers. It can be used for:
Training language models on news-specific data.
Fine-tuning models for generating or classifying headlines.
Experimentation with NLP techniques related to news article summarization, content prediction, or topic modeling.
Data Collection Method:
The headlines in this dataset have been scraped using automated tools from various news websites. The dataset includes a mixture of topics such as politics, technology, entertainment, and more, representing a wide range of public interest areas. The data has been carefully curated to ensure diverse and representative coverage.
Data Quality:
The headlines are structured and consistent, with an emphasis on clarity and relevance. They have been preprocessed to remove any irrelevant information (e.g., HTML tags) to make them ready for direct use in model training.
Licensing and Usage:
The dataset is available for research and educational purposes. Users must comply with the original source websites' terms of use and licensing requirements.