datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
textclassificationMNLIcis5300-text-classification
Complex Word Identification (CIS 5300)
Dataset Description
This dataset supports the Complex Word Identification (CWI) task: given a word in context, predict whether it is complex (likely to be difficult for non-native speakers, children, or people with reading disabilities) or simple.
CWI is the first step in lexical simplification — the task of rewriting text to make it more accessible. Before you can simplify a word, you need to identify which words need… See the full description on the dataset page: https://huggingface.co/datasets/CCB/cis5300-text-classification.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.Scientific-text-classificationAmharic-News-Text-classification-Dataset
An Amharic News Text classification Dataset
In NLP, text classification is one of the primary problems we try to solve and its uses in language analyses are indisputable. The lack of labeled training data made it harder to do these tasks in low resource languages like Amharic. The task of collecting, labeling, annotating, and making valuable this kind of data will encourage junior researchers, schools, and machine learning practitioners to implement existing classification models… See the full description on the dataset page: https://huggingface.co/datasets/israel/Amharic-News-Text-classification-Dataset.pubmed-text-classification-cased
ml4pubmed/pubmed-text-classification-cased
A parsed/cleaned version of the source data retaining case.
Text-Classification-and-Relation-Event-Extraction-Mix-datasetsThe paper of GIELLM dataset.
https://arxiv.org/abs/2311.06838
Cite:
@article{gan2023giellm,
title={Giellm: Japanese general information extraction large language model utilizing mutual reinforcement effect},
author={Gan, Chengguang and Zhang, Qinghao and Mori, Tatsunori},
journal={arXiv preprint arXiv:2311.06838},
year={2023}
}
The dataset constructed base in livedoor news corpus 関口宏司 https://www.rondhuit.com/download.html
cancer-text-classificationshort-text-multi-labeled-emotion-classificationja-toxic-text-classification-open2ch
Open 2ch-based toxic classification dataset
Based on p1atdev/open2ch
We apply keyword-based filtering to collect toxic texts
We use Perspective API to filter non-toxic texts from the original corpus
3k texts for each class, toxic (label=1) and non-toxic (label=0) texts
perspective_api_score is a prediction of toxicity score by the Perspective API
charles-dickens-text-classification
Dataset Description
This Dataset is designed to classify paragraphs of text as either written by Charles Dickens or generated to imitate various distinct writing styles. The primary use case is in the domain of literary analysis and text generation, where it can help distinguish between authentic Dickensian text and stylistic imitations.
The dataset was created from paragraphs extracted from “Great Expectations” by Charles Dickens. The original text was taken from the Gutenberg… See the full description on the dataset page: https://huggingface.co/datasets/GuillermoTBB/charles-dickens-text-classification.Hierarchical_Text_Classification_Intent_Classificationmulti-label-text-classificationai-human-text-classification
AI vs Human Sentence Classification Dataset
Dataset Summary
sentence_dataset is a sentence-level binary classification dataset containing approximately 9.84 million sentences labelled as either AI-generated (1) or human-written (0).
It was constructed by extracting individual sentences from two source datasets and merging them:
Dataset 1 — ai_vs_human_content_v2_20000.csv: 20,000 rows of short text and code snippets with rich metadata (prompt, topic, source… See the full description on the dataset page: https://huggingface.co/datasets/Nerdy37/ai-human-text-classification.text_category_classificationline-level-code-vs-text-classificationThis dataset was created for SemEval-2026 Task 13, which focuses on distinguishing machine-generated code from human-written code across multiple programming languages and domains.
While the original SemEval task operates at the code snippet level, this dataset provides line-level annotations that enable finer-grained analysis of how code-like and text-like content is distributed within mixed inputs. The dataset is intended to support research in machine-generated code detection, robust… See the full description on the dataset page: https://huggingface.co/datasets/violetakastreva/line-level-code-vs-text-classification.kalashnikov1405_facebook-text-classification
Facebook Text classification
Mirror of the Kaggle dataset kalashnikov1405/facebook-text-classification by kalashnikov1405, released under CC0: Public Domain. All credit goes to the original author; please cite and link the Kaggle page when using this data.
Facebook text classification of the dataset of 5000 row
Original description (from Kaggle)
The Facebook Text Classification Dataset consists of 5,000 social media posts designed for text analytics and machine… See the full description on the dataset page: https://huggingface.co/datasets/haoxianc/kalashnikov1405_facebook-text-classification.arabic-text-classificationaction-required-text-classificationThis dataset was created to support the task of classifying short text messages based on whether they require user action. The goal is to distinguish between different types of communicative intent, specifically whether a message requires immediate action, suggests optional action, or is purely informational.
The dataset consists of short sentences resembling real-world messages, such as system notifications, emails, or app prompts. Each sample is labeled with one of three classes:… See the full description on the dataset page: https://huggingface.co/datasets/McOwska/action-required-text-classification.short-text-classification-v1
Short Text Classification v1
A small human-written dataset of short texts labeled by sentiment and risk perception.
Intended Use
Text classification, sentiment analysis, and educational research.
License
CC-BY-4.0
text-classification-chatGPT-100covid-tweet-text-classificationtext_classificationtext_category_classificationTextClassificationcovid-tweet-text-classificationwriting-models-text-classification-6006738d_300_3000text-classificationtext-classification-datasetwriting-models-text-classification-a5c5b635