参考文献:
正規の
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:id_liputan6/canonical')
- 説明：
In this paper, we introduce a large-scale Indonesian summarization dataset. We harvest articles from this http URL,
an online news portal, and obtain 215,827 document-summary pairs. We leverage pre-trained language models to develop
benchmark extractive and abstractive summarization methods over the dataset with multilingual and monolingual
BERT-based models. We include a thorough error analysis by examining machine-generated summaries that have
low ROUGE scores, and expose both issues with ROUGE it-self, as well as with extractive and abstractive
summarization models.
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 10972 |
'train' | 193883 |
'validation' | 10972 |
- 特徴：
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"url": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"clean_article": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"clean_summary": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"extractive_summary": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
エクストリーム
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:id_liputan6/xtreme')
- 説明：
In this paper, we introduce a large-scale Indonesian summarization dataset. We harvest articles from this http URL,
an online news portal, and obtain 215,827 document-summary pairs. We leverage pre-trained language models to develop
benchmark extractive and abstractive summarization methods over the dataset with multilingual and monolingual
BERT-based models. We include a thorough error analysis by examining machine-generated summaries that have
low ROUGE scores, and expose both issues with ROUGE it-self, as well as with extractive and abstractive
summarization models.
- ライセンス: 既知のライセンスはありません
- バージョン: 1.0.0
- 分割:
| スプリット | 例 |
|---|---|
'test' | 3862 |
'validation' | 4948 |
- 特徴：
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"url": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"clean_article": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"clean_summary": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"extractive_summary": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}