binary-analysis
Amazon_Reviews_Binary_for_Sentiment_Analysis
Dataset Card for Dataset Name
The Amazon reviews polarity dataset is constructed by taking review score 1 and 2 as negative, and 4 and 5 as positive. Samples of score 3 is ignored. In the dataset, class 1 is the negative and class 2 is the positive. Each class has 1,800,000 training samples and 200,000 testing samples.
Dataset Details
Dataset Description
The files train.csv and test.csv contain all the training samples as comma-sparated values. There are 3… See the full description on the dataset page: https://huggingface.co/datasets/yassiracharki/Amazon_Reviews_Binary_for_Sentiment_Analysis.tatar-news-analysis-binary
Dataset Card for Tatar News Analysis Binary
Dataset Details
Dataset Description
A binary text classification dataset for Tatar news articles, designed to support tasks such as sentiment analysis, topic detection, or category classification (e.g., positive/negative, relevant/irrelevant). The dataset contains short news excerpts in the Tatar language with binary labels, collected from publicly available online sources. It is intended for training and… See the full description on the dataset page: https://huggingface.co/datasets/TatarNLPWorld/tatar-news-analysis-binary.Yelp_Reviews_for_Binary_Senti_Analysis
Dataset Card for Dataset Name
The Yelp reviews polarity dataset is constructed by considering stars 1 and 2 negative, and 3 and 4 positive. For each polarity 280,000 training samples and 19,000 testing samples are take randomly. In total there are 560,000 trainig samples and 38,000 testing samples. Negative polarity is class 1, and positive class 2.
Dataset Description
The files train.csv and test.csv contain all the training samples as comma-sparated values. There are 2… See the full description on the dataset page: https://huggingface.co/datasets/yassiracharki/Yelp_Reviews_for_Binary_Senti_Analysis.ModernBERT-512-Amazon_Reviews_Binary_for_Sentiment_Analysis