Very Deep Transformers for Neural Machine Translation

This PyTorch package implements Very Deep Transformers for Neural Machine Translation, as described in:

Xiaodong Liu, Kevin Duh, Liyuan Liu and Jianfeng Gao
Very deep transformers for neural machine translation
arXiv version

Quickstart

Model Training

1. Data Preprocessing Please follow instructions: (https://github.com/pytorch/fairseq/tree/main/examples/scaling_nmt)
2. Model Train
   

   bash run_wmt14_en_fr.sh

3. Model Eval
   

   cd nmt_eval && bash eval_enfr.sh <model_path> <init_path>

Notes and Acknowledgments

FAIRSEQ (v0.9): https://github.com/pytorch/fairseq

How do I cite it?

@article{liu2020deepnmt,
  title={Very deep transformers for neural machine translation},
  author={Liu, Xiaodong and Duh, Kevin and Liu, Liyuan and Gao, Jianfeng},
  journal={arXiv preprint arXiv:2008.07772},
  year={2020}
}
   
@inproceedings{liu2020admin,
  title={Understanding the Difficulty of Training Transformers},
  author = {Liu, Liyuan and Liu, Xiaodong and Gao, Jianfeng and Chen, Weizhu and Han, Jiawei},
  booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020)},
  year={2020}
}
   

Contact Information

For personal communication related to this package, please contact Xiaodong Liu (xiaodl@microsoft.com), Kevin Duh (kevinduh@cs.jhu.edu) Liyuan Liu (ll2@illinois.edu), or Jianfeng Gao (jfgao@microsoft.com).

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