task_categories:summarization size_categories:100K<n<1M language:th language:en license:cc-by-4.0 region:us
---
dataset_info:
  features:
  - name: document
    dtype: string
  - name: summary
    dtype: string
  - name: id
    dtype: string
  splits:
  - name: train
    num_bytes: 518590635
    num_examples: 204045
  - name: validation
    num_bytes: 28478150
    num_examples: 11332
  - name: test
    num_bytes: 28953771
    num_examples: 11334
  download_size: 349745164
  dataset_size: 576022556
license: cc-by-4.0
task_categories:
- summarization
language:
- th
- en
source_data:
- xsum
size_categories:
- 100K<n<1M
---
# Dataset Card for "xsum_eng2thai 🇬🇧🇹🇭"
- [Update 21/09/2023] [xsum_th](https://huggingface.co/datasets/potsawee/xsum_thai) 🇹🇭 is available. It's better than this dataset, and can be used for both Thai2Thai and Cross-Summarization.
  - The input documents are also translated using NLLB-200-3.3B
  - The target summaries (translated to Thai) are slightly different from this dataset in that, `no_repeat_ngram_size=6, repetition_penalty=1.2
` were used in translation to mitigate the repetition problem observed in this dataset. 
- This dataset is based on [XSum](https://huggingface.co/datasets/xsum). 
- The summaries were translated from English (as in the original XSum) to Thai using Meta's [NLLB-200-3.3B](https://huggingface.co/facebook/nllb-200-3.3B). 
- The dataset is intended for Cross-Lingual Summarization (English Document -> Thai Summary).

### Data Fields

- `id`: BBC ID of the article.
- `document`: a string containing the body of the news article 
- `summary`: a string containing a *translated* summary of the article.

## Data Structure

```
{
    "id": "29750031",
    "document": "news article in English",
    "summary": "summary in Thai"
}
```

### Data Splits
train/validation/test = 204045/11332/11334