datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
yelp_review_sampledYelp_Reviews_for_Sentiment_Analysis_fine_grained_5_classes
Dataset Card for Dataset Name
The Yelp reviews full star dataset is constructed by randomly taking 130,000 training samples and 10,000 testing samples for each review star from 1 to 5. In total there are 650,000 trainig samples and 50,000 testing samples.
Dataset Description
The files train.csv and test.csv contain all the training samples as comma-sparated values. There are 2 columns in them, corresponding to class index (1 to 5) and review text. The review texts are… See the full description on the dataset page: https://huggingface.co/datasets/yassiracharki/Yelp_Reviews_for_Sentiment_Analysis_fine_grained_5_classes.YelpReviewsThis dataset contains the Fictional Yelp review.
Two jsonl files (df_neg.jsonl & df_pos.jsonl) can be directly used for OpenAI / OpenPipe finetuning.
(This is what you need for replication)
More detailed data at df_pos_generated and df_neg_generated file. The oos files are out-of-sample cues.
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.yelp_boba_reviewsyelp-review-sentiment-subsetyelp_reviews