Styled Augmented Translation

Last update: Dec 29, 2022

Related tags

Overview

SAT

Style Augmented Translation

Introduction

By collecting high-quality data, we were able to train a model that outperforms Google Translate on 6 different domains of English-Vietnamese Translation.

English to Vietnamese Translation (BLEU score)

Vietnamese to English Translation (BLEU score)

Get data and model at Google Cloud Storage

Check out our demo web app

Visit our blog post for more details.

Using the code

This code is build on top of vietai/dab:

To prepare for training, generate tfrecords from raw text files:

python t2t_datagen.py \
--data_dir=$path_to_folder_contains_vocab_file \
--tmp_dir=$path_to_folder_that_contains_training_data \
--problem=$problem

To train a Transformer model on the generated tfrecords

python t2t_trainer.py \
--data_dir=$path_to_folder_contains_vocab_file_and_tf_records \
--problem=$problem \
--hparams_set=$hparams_set \
--model=transformer \
--output_dir=$path_to_folder_to_save_checkpoints

To run inference on the trained model:

python t2t_decoder.py \
--data_dir=$path_to_folde_contains_vocab_file_and_tf_records \
--problem=$problem \
--hparams_set=$hparams_set \
--model=transformer \
--output_dir=$path_to_folder_contains_checkpoints

In this colab, we demonstrated how to run these three phases in the context of hosting data/model on Google Cloud Storage.

Dataset

Our data contains roughly 3.3 million pairs of texts. After augmentation, the data is of size 26.7 million pairs of texts. A more detail breakdown of our data is shown in the table below.

	Pure	Augmented
Fictional Books	333,189	2,516,787
Legal Document	1,150,266	3,450,801
Medical Publication	5,861	27,588
Movies Subtitles	250,000	3,698,046
Software	79,912	239,745
TED Talk	352,652	4,983,294
Wikipedia	645,326	1,935,981
News	18,449	139,341
Religious texts	124,389	1,182,726
Educational content	397,008	8,475,342
No tag	5,517	66,299
Total	3,362,569	26,715,950

Data sources is described in more details here.

Comments

Data leakage issue in evaluation?

Hi team @lmthang @thtrieu @heraclex12 @hqphat @KienHuynh

The obtained results of a Transformer-based model on the PhoMT test set surprised me. My first thought was that as VietAI and PhoMT datasets have several overlapping domains (e.g. Wikihow, TED talks, Opensubtitles, news..): whether there might be a potential data leakage issue in your evaluation (e.g. PhoMT English-Vietnamese test pairs appear in the VietAI training set)?

In particular, we find that 6294/19151 PhoMT English-Vietnamese test pairs appear in the VietAI training set (v2). When evaluating your model on the PhoMT test set, did you guys retrain the model on a VietAI training set variant that does not contain PhoMT English-Vietnamese test pairs?

Cheers, Dat.

opened by datquocnguyen 3

Demo website is not working

Hi, seems like the easiest to reach out here but https://demo.vietai.org/ is down, looks like the page tried to serve a 404 error page.

Connection failed with status 404, and response "<!DOCTYPE html> <html lang=en> <meta charset=utf-8> <meta name=viewport content="initial-scale=1, minimum-scale=1, width=device-width"> <title>Error 404 (Not Found)!!1</title> <style> *{margin:0;padding:0}html,code{font:15px/22px arial,sans-serif}html{background:#fff;color:#222;padding:15px}body{margin:7% auto 0;max-width:390px;min-height:180px;padding:30px 0 15px}* > body{background:url(//www.google.com/images/errors/robot.png) 100% 5px no-repeat;padding-right:205px}p{margin:11px 0 22px;overflow:hidden}ins{color:#777;text-decoration:none}a img{border:0}@media screen and (max-width:772px){body{background:none;margin-top:0;max-width:none;padding-right:0}}#logo{background:url(//www.google.com/images/branding/googlelogo/1x/googlelogo_color_150x54dp.png) no-repeat;margin-left:-5px}@media only screen and (min-resolution:192dpi){#logo{background:url(//www.google.com/images/branding/googlelogo/2x/googlelogo_color_150x54dp.png) no-repeat 0% 0%/100% 100%;-moz-border-image:url(//www.google.com/images/branding/googlelogo/2x/googlelogo_color_150x54dp.png) 0}}@media only screen and (-webkit-min-device-pixel-ratio:2){#logo{background:url(//www.google.com/images/branding/googlelogo/2x/googlelogo_color_150x54dp.png) no-repeat;-webkit-background-size:100% 100%}}#logo{display:inline-block;height:54px;width:150px} </style> <a href=//www.google.com/><span id=logo aria-label=Google></span></a> <p><b>404.</b> <ins>That’s an error.</ins> <p>The requested URL <code>/healthz</code> was not found on this server. <ins>That’s all we know.</ins> ".

opened by VietThan 1

Got RuntimeError when run on Google Colab

I ran the Readme.md samples on Google Colab with GPU and got this Error "RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! (when checking argument for argument index in method wrapper__index_select)".

Error code: outputs = model.generate(tokenizer(inputs, return_tensors="pt", padding=True).input_ids.to('cuda'), max_length=512)

opened by kietbg0079 0
Got error 'AssertionError: Torch not compiled with CUDA enabled' on Macbook M1 pro

I have tried the example on my Macbook M1 pro but got this error: =>outputs = model.generate(tokenizer(inputs, return_tensors="pt", padding=True).input_ids.to('cuda'), max_length=512) raise AssertionError("Torch not compiled with CUDA enabled") AssertionError: Torch not compiled with CUDA enabled

Please help!

opened by htnha 4
Question about loading model

I have a question about loading model. I have trained a Russian-to-Vietnamese model base on your code and tensor2tensor. Every time I want to predict a new sentence, it always load the model again, even before that I have already predicted another sentence. I want to ask that if there is a way not to have reload the model when predict a new sentence. Thank you very much

opened by hieunguyenquoc 1
I have a issue about running decoder

Data loss: Unable to open table file /content/drive/MyDrive/SAT/checkpoint: Failed precondition: /content/drive/MyDrive/SAT/checkpoint; Is a directory: perhaps your file is in a different file format and you need to use a different restore operator?

I used a pretrain model : model.augmented.envi.ckpt-1415000.data-00000-of-00001, model.augmented.envi.ckpt-1415000.index, model.augmented.envi.ckpt-1415000.meta. All 3 file are put in checkpoint

Could somebody help me with this issue ?

opened by hieunguyenquoc 6

Releases(v1.0)

v1.0(Oct 2, 2021)

First version.

Trained on 3.3M training data points. Transformer with 9-layer encoder and 9-layer decoder. Tested on a multi-domain dataset, outperforming Google Translate. Experiments with style-tagging and data appending.
Source code(tar.gz)
Source code(zip)

Owner

GitHub Repository

Deep Reinforcement Learning based autonomous navigation for quadcopters using PPO algorithm.

PPO-based Autonomous Navigation for Quadcopters This repository contains an implementation of Proximal Policy Optimization (PPO) for autonomous naviga

16 Nov 11, 2022

Official pytorch implementation for Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion (CVPR 2022)

Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion This repository contains a pytorch implementation of "Learning to Listen: Modeling

50 Dec 17, 2022

Adversarial Color Enhancement: Generating Unrestricted Adversarial Images by Optimizing a Color Filter

ACE Please find the preliminary version published at BMVC 2020 in the folder BMVC_version, and its extended journal version in Journal_version. Datase

28 Dec 25, 2022

Official source code to CVPR'20 paper, "When2com: Multi-Agent Perception via Communication Graph Grouping"

When2com: Multi-Agent Perception via Communication Graph Grouping This is the PyTorch implementation of our paper: When2com: Multi-Agent Perception vi

34 Nov 09, 2022

Dogs classification with Deep Metric Learning using some popular losses

Tsinghua Dogs classification with Deep Metric Learning 1. Introduction Tsinghua Dogs dataset Tsinghua Dogs is a fine-grained classification dataset fo

45 Nov 09, 2022

Code for "Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo"

Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo This repository includes the source code for our CVPR 2021 paper on multi-view mult

66 Jan 04, 2023

Advanced Signal Processing Notebooks and Tutorials

Advanced Digital Signal Processing Notebooks and Tutorials Prof. Dr. -Ing. Gerald Schuller Jupyter Notebooks and Videos: Renato Profeta Applied Media

115 Dec 13, 2022

Official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Imbalance Classification"

DPGNN This repository is an official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Im

18 Oct 12, 2022

LQM - Improving Object Detection by Estimating Bounding Box Quality Accurately

Improving Object Detection by Estimating Bounding Box Quality Accurately Abstract Object detection aims to locate and classify object instances in ima

0 Sep 28, 2022

RodoSol-ALPR Dataset

RodoSol-ALPR Dataset This dataset, called RodoSol-ALPR dataset, contains 20,000 images captured by static cameras located at pay tolls owned by the Ro

45 Dec 15, 2022

A python package simulating the quasi-2D pseudospin-1/2 Gross-Pitaevskii equation with NVIDIA GPU acceleration.

A python package simulating the quasi-2D pseudospin-1/2 Gross-Pitaevskii equation with NVIDIA GPU acceleration. Introduction spinor-gpe is high-level,

2 Sep 20, 2022

TransNet V2: Shot Boundary Detection Neural Network

TransNet V2: Shot Boundary Detection Neural Network This repository contains code for TransNet V2: An effective deep network architecture for fast sho

212 Dec 27, 2022

A semantic segmentation toolbox based on PyTorch

Introduction vedaseg is an open source semantic segmentation toolbox based on PyTorch. Features Modular Design We decompose the semantic segmentation

407 Dec 15, 2022

Data labels and scripts for fastMRI.org

fastMRI+: Clinical pathology annotations for the fastMRI dataset The fastMRI dataset is a publicly available MRI raw (k-space) dataset. It has been us

51 Dec 22, 2022

To propose and implement a multi-class classification approach to disaster assessment from the given data set of post-earthquake satellite imagery.

2 Jan 05, 2022

[ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

When Does Self-Supervision Help Graph Convolutional Networks? PyTorch implementation for When Does Self-Supervision Help Graph Convolutional Networks?

106 Nov 11, 2022