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

PyTorch implementation of "Conformer: Convolution-augmented Transformer for Speech Recognition" (INTERSPEECH 2020)

PyTorch implementation of Conformer: Convolution-augmented Transformer for Speech Recognition. Transformer models are good at capturing content-based

565 Jan 4, 2023

A neuroanatomy-based augmented reality experience powered by computer vision. Features 3D visuals of the Atlas Brain Map slices.

Brain Augmented Reality (AR) A neuroanatomy-based augmented reality experience powered by computer vision that features 3D visuals of the Atlas Brain

10 Oct 6, 2022

Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments (CoRL 2020)

Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments [Project website] [Paper] This project is a PyTorch

Cognitive Learning for Vision and Robotics (CLVR) lab @ USC

49 Nov 28, 2022

A heterogeneous entity-augmented academic language model based on Open Academic Graph (OAG)

Library | Paper | Slack We released two versions of OAG-BERT in CogDL package. OAG-BERT is a heterogeneous entity-augmented academic language model wh

58 Dec 17, 2022

DrQ-v2: Improved Data-Augmented Reinforcement Learning

DrQ-v2: Improved Data-Augmented RL Agent Method DrQ-v2 is a model-free off-policy algorithm for image-based continuous control. DrQ-v2 builds on DrQ,

234 Jan 1, 2023

[EMNLP 2021] Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training

RoSTER The source code used for Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training, p

60 Dec 30, 2022

PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence) and pre-trained model on ImageNet dataset

Reference-Based-Sketch-Image-Colorization-ImageNet This is a PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization usin

11 Jul 28, 2022

RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering

RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering Authors: Xi Ye, Semih Yavuz, Kazuma Hashimoto, Yingbo Zhou and

72 Dec 5, 2022

Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation (CoRL 2021)

Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulation [Project website] [Paper] This project is a PyTorch i

6 Feb 28, 2022

Official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition" in AAAI2022.

AimCLR This is an official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Reco

44 Dec 17, 2022

Code to use Augmented Shapiro Wilks Stopping, as well as code for the paper "Statistically Signifigant Stopping of Neural Network Training"

This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea

32 Nov 9, 2021

Implementation of Retrieval-Augmented Denoising Diffusion Probabilistic Models in Pytorch

Retrieval-Augmented Denoising Diffusion Probabilistic Models (wip) Implementation of Retrieval-Augmented Denoising Diffusion Probabilistic Models in P

55 Jan 1, 2023

A series of convenience functions to make basic image processing operations such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and Python.

imutils A series of convenience functions to make basic image processing functions such as translation, rotation, resizing, skeletonization, and displ

4.3k Jan 8, 2023

Styled Augmented Translation

Related tags

Overview

SAT

Style Augmented Translation

Introduction

Using the code

Dataset

Comments

Data leakage issue in evaluation?

Demo website is not working

Got RuntimeError when run on Google Colab

Got error 'AssertionError: Torch not compiled with CUDA enabled' on Macbook M1 pro

Question about loading model

I have a issue about running decoder

Releases(v1.0)

v1.0(Oct 2, 2021)