Crosslingual Segmental Language Model

Related tags

Deep LearningXLSLM
Overview

Crosslingual Segmental Language Model

This repository contains the code from Multilingual unsupervised sequence segmentation transfers to extremely low-resource languages (2021, C.M. Downey, Shannon Drizin, Levon Haroutunian, and Shivin Thukral). The code here is a modified version of the repository from the original MSLM paper. The mslm package can be used to train and use Segmental Language Models.

In this repository, we additionally make available our preparation of the AmericasNLP 2021 multilingual dataset (see Data/AmericasNLP) and the target K'iche' data (Data/GlobalClassroom).

Paper Results

The results from the accompanying paper can be found in the Output directory. *.csv files include statistics from the training run, *.out contain the model output for the entire corpus, *.score contain the segmentation scores of the model output.

The results from the October 2021 pre-print (which we will refer to as Experiment Set A) are reproducible on commit 2b89575. We will consider this the official commit of the October 2021 pre-print.

Usage

The top-level scripts for training and experimentation can be found in RunScripts. Almost all functionality is run through the __main__.py script in the mslm package, which can either train or evaluate/use a model. The PyTorch modules for building SLMs can be found in mslm.segmental_lm, modules for the span-masking Transformer are in mslm.segmental_transformer, and modules for sequence lattice-based computations are in mslm.lattice. The main script takes in a configuration object to set most parameters for model training and use (see mslm.mslm_config). For information on the arguments to the main script:

python -m mslm --help

Environment setup

pip install -r requirements.txt

This code requires Python >= 3.6

Training

./RunScripts/run_mslm.sh 
    
     
     

     
    
   

or

python -m mslm --input_file 
   
     \
    --model_path 
    
      \
    --mode train \
    --config_file 
     
       \
    --dev_file 
      
        \
    [--preexisting]

      
     
    
   

Evaluation

./RunScripts/eval_mslm.sh 
    
     
      
      

      
     
    
   

Where is a text file containing all of the words from the training set

Owner
C.M. Downey
PhD Student in Computational Linguistics / NLP
C.M. Downey
Pretrained Cost Model for Distributed Constraint Optimization Problems

Pretrained Cost Model for Distributed Constraint Optimization Problems Requirements PyTorch 1.9.0 PyTorch Geometric 1.7.1 Directory structure baseline

2 Aug 28, 2022
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Segmentation Transformer Implementation of Segmentation Transformer in PyTorch, a new model to achieve SOTA in semantic segmentation while using trans

Abhay Gupta 161 Dec 08, 2022
๐Ÿ•น๏ธ Official Implementation of Conditional Motion In-betweening (CMIB) ๐Ÿƒ

Conditional Motion In-Betweening (CMIB) Official implementation of paper: Conditional Motion In-betweeening. Paper(arXiv) | Project Page | YouTube in-

Jihoon Kim 81 Dec 22, 2022
Code for the RA-L (ICRA) 2021 paper "SeqNet: Learning Descriptors for Sequence-Based Hierarchical Place Recognition"

SeqNet: Learning Descriptors for Sequence-Based Hierarchical Place Recognition [ArXiv+Supplementary] [IEEE Xplore RA-L 2021] [ICRA 2021 YouTube Video]

Sourav Garg 63 Dec 12, 2022
A repo to show how to use custom dataset to train s2anet, and change backbone to resnext101

A repo to show how to use custom dataset to train s2anet, and change backbone to resnext101

jedibobo 3 Dec 28, 2022
This is the second place solution for : UmojaHack Africa 2022: African Snake Antivenom Binding Challenge

UmojaHack-Africa-2022-African-Snake-Antivenom-Binding-Challenge This is the second place solution for : UmojaHack Africa 2022: African Snake Antivenom

Mami Mokhtar 10 Dec 03, 2022
Find-Lane-Line - Use openCV library and Python to detect the road-lane-line

Find-Lane-Line This project is to use openCV library and Python to detect the road-lane-line. Data Pipeline Step one : Color Selection Step two : Cann

Kenny Cheng 3 Aug 17, 2022
Small-bets - Ergodic Experiment With Python

Ergodic Experiment Based on this video. Run this experiment with this command: p

Michael Brant 3 Jan 11, 2022
Code for the Population-Based Bandits Algorithm, presented at NeurIPS 2020.

Population-Based Bandits (PB2) Code for the Population-Based Bandits (PB2) Algorithm, from the paper Provably Efficient Online Hyperparameter Optimiza

Jack Parker-Holder 22 Nov 16, 2022
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions

torch-imle Concise and self-contained PyTorch library implementing the I-MLE gradient estimator proposed in our NeurIPS 2021 paper Implicit MLE: Backp

UCL Natural Language Processing 249 Jan 03, 2023
Contrastive Fact Verification

VitaminC This repository contains the dataset and models for the NAACL 2021 paper: Get Your Vitamin C! Robust Fact Verification with Contrastive Evide

47 Dec 19, 2022
The mini-AlphaStar (mini-AS, or mAS) - mini-scale version (non-official) of the AlphaStar (AS)

A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II.

Ruo-Ze Liu 216 Jan 04, 2023
Offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation

Shunted Transformer This is the offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation by Sucheng Ren, Daquan Zhou, Shengf

156 Dec 27, 2022
Demonstration of transfer of knowledge and generalization with distillation

Distilling-the-Knowledge-in-a-Neural-Network This is an implementation of a part of the paper "Distilling the Knowledge in a Neural Network" (https://

26 Nov 25, 2022
TF2 implementation of knowledge distillation using the "function matching" hypothesis from the paper Knowledge distillation: A good teacher is patient and consistent by Beyer et al.

FunMatch-Distillation TF2 implementation of knowledge distillation using the "function matching" hypothesis from the paper Knowledge distillation: A g

Sayak Paul 67 Dec 20, 2022
Supervised Sliding Window Smoothing Loss Function Based on MS-TCN for Video Segmentation

SSWS-loss_function_based_on_MS-TCN Supervised Sliding Window Smoothing Loss Function Based on MS-TCN for Video Segmentation Supervised Sliding Window

3 Aug 03, 2022
YOLO-v5 ๊ธฐ๋ฐ˜ ๋‹จ์•ˆ ์นด๋ฉ”๋ผ์˜ ์˜์ƒ์„ ํ™œ์šฉํ•ด ์ฐจ๊ฐ„ ๊ฑฐ๋ฆฌ๋ฅผ ์ผ์ •ํ•˜๊ฒŒ ์œ ์ง€ํ•˜๋ฉฐ ์ฃผํ–‰ํ•˜๋Š” Adaptive Cruise Control ๊ธฐ๋Šฅ ๊ตฌํ˜„

์ž์œจ ์ฃผํ–‰์ฐจ์˜ ์˜์ƒ ๊ธฐ๋ฐ˜ ์ฐจ๊ฐ„๊ฑฐ๋ฆฌ ์œ ์ง€ ๊ฐœ๋ฐœ Table of Contents ํ”„๋กœ์ ํŠธ ์†Œ๊ฐœ ์ฃผ์š” ๊ธฐ๋Šฅ ์‹œ์Šคํ…œ ๊ตฌ์กฐ ๋””๋ ‰ํ† ๋ฆฌ ๊ตฌ์กฐ ๊ฒฐ๊ณผ ์‹คํ–‰ ๋ฐฉ๋ฒ• ์ฐธ์กฐ ํŒ€์› ํ”„๋กœ์ ํŠธ ์†Œ๊ฐœ YOLO-v5 ๊ธฐ๋ฐ˜์œผ๋กœ ๋‹จ์•ˆ ์นด๋ฉ”๋ผ์˜ ์˜์ƒ์„ ํ™œ์šฉํ•ด ์ฐจ๊ฐ„ ๊ฑฐ๋ฆฌ๋ฅผ ์ผ์ •ํ•˜๊ฒŒ ์œ ์ง€ํ•˜๋ฉฐ ์ฃผํ–‰ํ•˜๋Š” Adap

14 Jun 29, 2022
RSNA Intracranial Hemorrhage Detection with python

RSNA Intracranial Hemorrhage Detection This is the source code for the first place solution to the RSNA2019 Intracranial Hemorrhage Detection Challeng

24 Nov 30, 2022
This repository provides the code for MedViLL(Medical Vision Language Learner).

MedViLL This repository provides the code for MedViLL(Medical Vision Language Learner). Our proposed architecture MedViLL is a single BERT-based model

SuperSuperMoon 39 Jan 05, 2023
Library for machine learning stacking generalization.

stacked_generalization Implemented machine learning *stacking technic[1]* as handy library in Python. Feature weighted linear stacking is also availab

114 Jul 19, 2022