Datasets:
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---
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/
``` |