metadata

dataset_info:
  features:
    - name: text
      dtype: string
    - name: label
      dtype: int64
    - name: label_text
      dtype: string
  splits:
    - name: train
      num_bytes: 786170
      num_examples: 908
    - name: test
      num_bytes: 208017
      num_examples: 228
  download_size: 578346
  dataset_size: 994187
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
license: cc-by-nc-sa-4.0
task_categories:
  - text-classification
language:
  - en
tags:
  - chemistry
  - wikipedia
  - chemteb
pretty_name: Wikipedia Solid-state vs Colloidal Chemistry Binary Classification
size_categories:
  - 1K<n<10K

Wikipedia Greenhouse Gases vs Enantiopure Drugs Binary Classification

This dataset is derived from the English Wikipedia articles and is tailored for binary text classification tasks in the fields of environmental science and pharmaceutical chemistry. The dataset is divided into two classes based on the thematic content of the articles:

Class 1 (Greenhouse Gases): This class includes articles that discuss various aspects of greenhouse gases. These are gases that trap heat in the Earth's atmosphere, contributing to the greenhouse effect and global warming. Topics may cover sources, types, impacts, and mitigation strategies related to greenhouse gases.
Class 2 (Enantiopure Drugs): This class contains articles focused on enantiopure drugs. Enantiopure drugs are pharmaceutical compounds that consist of only one enantiomer (a molecule that is a mirror image of another molecule but cannot be superimposed on it). These drugs are significant in medicinal chemistry due to their specific interactions with biological systems, leading to desired therapeutic effects and reduced side effects.