|
--- |
|
dataset_info: |
|
features: |
|
- name: text |
|
dtype: string |
|
- name: label |
|
dtype: int64 |
|
- name: label_text |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 330105 |
|
num_examples: 392 |
|
- name: test |
|
num_bytes: 87036 |
|
num_examples: 99 |
|
download_size: 251248 |
|
dataset_size: 417141 |
|
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 Salts vs Semiconductor Materials Binary Classification |
|
size_categories: |
|
- n<1K |
|
--- |
|
# Wikipedia Salts vs Semiconductor Materials Binary Classification |
|
This dataset is derived from the English Wikipedia articles and is designed for binary text classification tasks in the fields of chemistry and materials science. The dataset is divided into two classes based on the thematic content of the articles: |
|
- **Salts:** This class includes articles that focus on salts, which are ionic compounds composed of cations and anions. Topics may cover the properties, types, synthesis, and applications of various salts in different fields such as chemistry, biology, and industry. |
|
- **Semiconductor Materials:** This class comprises articles related to semiconductor materials, which have electrical conductivity between that of a conductor and an insulator. Topics may include the properties, types, synthesis, and applications of semiconductor materials in electronics, photovoltaics, and other technologies. |
