Text Classification
ILUR-news-text-classification-corpus
News Texts Dataset
We release a dataset of over 12000 news articles from iLur.am, categorized into 7 classes: sport, politics, weather, economy, accidents, art, society. The articles are split into train (2242k tokens) and test sets (425k tokens).
For more details, refer to the paper.
Mental-Health_Text-Classification_Dataset
Mental Health Text Classification Dataset (4-Class)
Dataset Description
This dataset contains short, user‑generated texts labeled for 4‑class mental health classification: Suicidal, Depression, Anxiety, and Normal. It is a derived dataset created by combining and cleaning three public mental‑health corpora, then re‑labeling them into a unified 4‑class scheme and exporting CSV files suitable for both classical ML and modern NLP models.
The repository includes:
An… See the full description on the dataset page: https://huggingface.co/datasets/ourafla/Mental-Health_Text-Classification_Dataset.textclassificationMNLItask679_hope_edi_english_text_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task679_hope_edi_english_text_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task679_hope_edi_english_text_classification.multi-label-class-github-issues-text-classification
Dataset Card for "multi-label-class-github-issues-text-classification"
More Information needed
PubMed_MultiLabel_Text_Classification_Dataset_MeSHThis dataset consists of a approx 50k collection of research articles from PubMed repository. Originally these documents are manually annotated by Biomedical Experts with their MeSH labels and each articles are described in terms of 10-15 MeSH labels. In this Dataset we have huge numbers of labels present as a MeSH major which is raising the issue of extremely large output space and severe label sparsity issues. To solve this Issue Dataset has been Processed and mapped to its root as Described… See the full description on the dataset page: https://huggingface.co/datasets/owaiskha9654/PubMed_MultiLabel_Text_Classification_Dataset_MeSH.