Code for the paper "Balancing Training for Multilingual Neural Machine Translation, ACL 2020"

Related tags

Deep LearningmultiDDS
Overview

Balancing Training for Multilingual Neural Machine Translation

Implementation of the paper

Balancing Training for Multilingual Neural Machine Translation

Xinyi Wang, Yulia Tsvetkov, Graham Neubig

Data:

The preprocessed and binarized data for fairseq can be downloaded here

To process data from scrach, see the script

util_scripts/prepare_multilingual_data.sh

Training Scripts:

The training scripts for many-to-one translation of the related language group (Related M2O) is under the directory job_scripts/related_ted8_m2o/.

Our methods:

MultiDDS-S:

job_scripts/related_ted8_m2o/multidds_s.sh 

MultiDDS:

job_scripts/related_ted8_m2o/multidds.sh 

Baselines:

Proportional:

job_scripts/related_ted8_m2o/proportional.sh 

Temperature:

job_scripts/related_ted8_m2o/temperature.sh 

The scripts for Related O2M is under the directory job_scripts/related_ted8_o2m/

The scripts for Diverse M2O is under the directory job_scripts/diverse_ted8_m2o/

The scripts for Diverse O2M is under the directory job_scripts/diverse_ted8_o2m/

Inference Scripts:

Each of the experiment script directory contains a trans.sh file to translate the test set. To translate the test set for the Related M2O MultiDDS-S

job_scripts/related_ted8_m2o/trans.sh checkpoints/related_ted8_m2o/multidds_s/ 

To translate other experiment, simply replace the argument with the experiment checkpoint directory.

Citation

Please cite as:

@inproceedings{wang2020multiDDS,
  title = {Balancing Training for Multilingual Neural Machine Translation},
  author = {Xinyi Wang, Yulia Tsvetkov, Graham Neubig},
  booktitle = {ACL},
  year = {2020},
}
Owner
Xinyi Wang
Xinyi Wang
Structure Information is the Key: Self-Attention RoI Feature Extractor in 3D Object Detection

Structure Information is the Key: Self-Attention RoI Feature Extractor in 3D Object Detection abstract:Unlike 2D object detection where all RoI featur

DK. Zhang 2 Oct 07, 2022
PyTorch Implementation for AAAI'21 "Do Response Selection Models Really Know What's Next? Utterance Manipulation Strategies for Multi-turn Response Selection"

UMS for Multi-turn Response Selection Implements the model described in the following paper Do Response Selection Models Really Know What's Next? Utte

Taesun Whang 47 Nov 22, 2022
This is a Python wrapper for TA-LIB based on Cython instead of SWIG.

TA-Lib This is a Python wrapper for TA-LIB based on Cython instead of SWIG. From the homepage: TA-Lib is widely used by trading software developers re

John Benediktsson 7.3k Jan 03, 2023
PyTorch module to use OpenFace's nn4.small2.v1.t7 model

OpenFace for Pytorch Disclaimer: This codes require the input face-images that are aligned and cropped in the same way of the original OpenFace. * I m

Pete Tae-hoon Kim 176 Dec 12, 2022
Indoor Panorama Planar 3D Reconstruction via Divide and Conquer

HV-plane reconstruction from a single 360 image Code for our paper in CVPR 2021: Indoor Panorama Planar 3D Reconstruction via Divide and Conquer (pape

sunset 36 Jan 03, 2023
Code repo for "RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network" (Machine Learning and the Physical Sciences workshop in NeurIPS 2021).

RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network An official PyTorch implementation of the RBSRICNN network as desc

Rao Muhammad Umer 6 Nov 14, 2022
python 93% acc. CNN Dogs Vs Cats ( Pytorch )

English | 简体中文(测试中...敬请期待) Cnn-Classification-Dog-Vs-Cat 猫狗辨别 (pytorch版本) CNN Resnet18 的猫狗分类器,基于ResNet及其变体网路系列,对于一般的图像识别任务表现优异,模型精准度高达93%(小型样本)。 项目制作于

apple ye 1 May 22, 2022
Hierarchical Aggregation for 3D Instance Segmentation (ICCV 2021)

HAIS Hierarchical Aggregation for 3D Instance Segmentation (ICCV 2021) by Shaoyu Chen, Jiemin Fang, Qian Zhang, Wenyu Liu, Xinggang Wang*. (*) Corresp

Hust Visual Learning Team 145 Jan 05, 2023
GPU Programming with Julia - course at the Swiss National Supercomputing Centre (CSCS), ETH Zurich

Course Description The programming language Julia is being more and more adopted in High Performance Computing (HPC) due to its unique way to combine

Samuel Omlin 192 Jan 03, 2023
Arch-Net: Model Distillation for Architecture Agnostic Model Deployment

Arch-Net: Model Distillation for Architecture Agnostic Model Deployment The official implementation of Arch-Net: Model Distillation for Architecture A

MEGVII Research 22 Jan 05, 2023
Nightmare-Writeup - Writeup for the Nightmare CTF Challenge from 2022 DiceCTF

Nightmare: One Byte to ROP // Alternate Solution TLDR: One byte write, no leak.

1 Feb 17, 2022
HeartRate detector with ArduinoandPython - Use Arduino and Python create a heartrate detector.

Syllabus of Contents Syllabus of Contents Introduction Of Project Features Develop With Python code introduction Installation License Developer Contac

1 Jan 05, 2022
Lightweight mmm - Lightweight (Bayesian) Media Mix Model

Lightweight (Bayesian) Media Mix Model This is not an official Google product. L

Google 342 Jan 03, 2023
Robotic Process Automation in Windows and Linux by using Driagrams.net BPMN diagrams.

BPMN_RPA Robotic Process Automation in Windows and Linux by using BPMN diagrams. With this Framework you can draw Business Process Model Notation base

23 Dec 14, 2022
This is a code repository for paper OODformer: Out-Of-Distribution Detection Transformer

OODformer: Out-Of-Distribution Detection Transformer This repo is the official the implementation of the OODformer: Out-Of-Distribution Detection Tran

34 Dec 02, 2022
Unified file system operation experience for different backend

megfile - Megvii FILE library Docs: http://megvii-research.github.io/megfile megfile provides a silky operation experience with different backends (cu

MEGVII Research 76 Dec 14, 2022
Vector Neurons: A General Framework for SO(3)-Equivariant Networks

Vector Neurons: A General Framework for SO(3)-Equivariant Networks Created by Congyue Deng, Or Litany, Yueqi Duan, Adrien Poulenard, Andrea Tagliasacc

Congyue Deng 332 Dec 29, 2022
LEAP: Learning Articulated Occupancy of People

LEAP: Learning Articulated Occupancy of People Paper | Video | Project Page This is the official implementation of the CVPR 2021 submission LEAP: Lear

Neural Bodies 60 Nov 18, 2022
LexGLUE: A Benchmark Dataset for Legal Language Understanding in English

LexGLUE: A Benchmark Dataset for Legal Language Understanding in English ⚖️ 🏆 🧑‍🎓 👩‍⚖️ Dataset Summary Inspired by the recent widespread use of th

95 Dec 08, 2022