synthetic-topic-classification-dataset-v1

<p align="center"> <img src="https://raw.githubusercontent.com/tanaos/.github/master/assets/logo.png" width="250px" alt="Tanaos – Train task specific LLMs without training data, for offline NLP and Text Classification"> </p> # Tanaos Topic Classification Training Dataset This dataset was created synthetically by Tanaos with the [Artifex](https://github.com/tanaos/artifex) Python library. The dataset is designed to **train and evaluate Topic Classification models** — models that can classify text into predefined topics or categories. Our flagship Topic Classification model, [tanaos-topic-classification-v1](https://huggingface.co/tanaos/tanaos-topic-classification-v1), was trained on this dataset. ## Dataset Summary The dataset contains text samples labeled with their corresponding topics. Each sample consists of a sentence or paragraph, along with a label indicating its topic category. The following topics are included: | Topic | Description | |--------|-------------| | `politics` | elections, policies, scandals, ideology. | | `health` | physical health, mental health, fitness, diets, medical advice. | | `technology` | gadgets, software, AI, cybersecurity. | | `entertainment` | movies, TV shows, music, celebrities, streaming platforms. | | `money_finance` | investing, budgeting, crypto, real estate. | | `relationships_dating` | romance, breakups, marriage, family drama. | | `education_learning` | schools, universities, self-study, online courses., | `work_careers` | job hunting, workplace culture, remote work, career advice. | | `science` | research, space, climate, biology, physics, chemistry and the scientific method. | | `society_culture` | identity, inequality, norms, language, and society. | | `gaming` | video games, esports, hardware, mods, and gaming culture. | | `lifestyle_hobbies` | travel, food, fashion, DIY, productivity systems. | | `sports` | teams, athletes, events, scores, and sports culture. | | `automotive` | cars, motorcycles, reviews, maintenance, and industry news. | | `other` | miscellaneous topics not covered by the other categories. | --- ## How to Use ```python from datasets import load_dataset dataset = load_dataset("tanaos/synthetic-topic-classification-dataset-v1") print(dataset["train"][0]) ``` ## Intended Use This dataset is meant for **training, fine-tuning, and evaluating** Topic Classification models. Common use cases: - Developing models to classify text into predefined topics or categories. - Benchmarking the performance of Topic Classification systems. - Researching techniques for improving text classification accuracy.