References:
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:gnad10')
- Description:
This dataset is intended to advance topic classification for German texts. A classifier that is efffective in
English may not be effective in German dataset because it has a higher inflection and longer compound words.
The 10kGNAD dataset contains 10273 German news articles from an Austrian online newspaper categorized into
9 categories. Article titles and text are concatenated together and authors are removed to avoid a keyword-like
classification on authors that write frequently about one category. This dataset can be used as a benchmark
for German topic classification.
- License: No known license
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
1028 |
'train' |
9245 |
- Features:
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 9,
"names": [
"Web",
"Panorama",
"International",
"Wirtschaft",
"Sport",
"Inland",
"Etat",
"Wissenschaft",
"Kultur"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}