---
dataset_info:
  features:
  - name: text_bem
    dtype: string
  - name: text_en
    dtype: string
  splits:
  - name: train
    num_bytes: 2041746
    num_examples: 20121
  download_size: 1203727
  dataset_size: 2041746
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
task_categories:
- translation
language:
- af
- en
---

# Dataset Details

This dataset contains Bemba-to-English sentences which is intended to machine translation task. This dataset was gained from [Tatoeba-Translations](https://huggingface.co/datasets/ymoslem/Tatoeba-Translations) repository by Yasmin Moslem.
Tatoeba is a dataset of sentences and its translations [1]. 

# Preprocessing Notes

There are several preprocessing processes done with this dataset.

1. Take for about ~300k English data from Tatoeba.
2. Translating that English data using our [MT model](https://huggingface.co/kreasof-ai/nllb-200-600M-eng2bem) and keep the  translating score.
3. Keep the data that has score above 0,7.
4. Add `<bt>` tag in front of the Bemba sentences to indicate that the data is generated by back-translating method.

# Dataset Structure
```
DatasetDict({
    train: Dataset({
        features: ['text_bem', 'text_en'],
        num_rows: 20121
    })
})
```

# Reference

```

1. https://tatoeba.org/

```