---
dataset_info:
  features:
  - name: en
    dtype: string
  - name: vi
    dtype: string
  splits:
  - name: train
    num_bytes: 536891664
    num_examples: 2977999
  - name: dev
    num_bytes: 3341942
    num_examples: 18719
  - name: test
    num_bytes: 3633646
    num_examples: 19151
  download_size: 317794951
  dataset_size: 543867252
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: dev
    path: data/dev-*
  - split: test
    path: data/test-*
license: apache-2.0
---

- The original dataset is the high-quality work of VinAI Research. 
- I just simply to process and reformat this data into the standard Hugging Face datasets structure, making it accessible for pretraining compact models.

```python
@inproceedings{PhoMT,
    title     = {{PhoMT: A High-Quality and Large-Scale Benchmark Dataset for Vietnamese-English Machine Translation}},
    author    = {Long Doan and Linh The Nguyen and Nguyen Luong Tran and Thai Hoang and Dat Quoc Nguyen},
    booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing},
    year      = {2021},
    pages     = {4495--4503}
}
```