EMNLP 2021 paper "Pre-train or Annotate? Domain Adaptation with a Constrained Budget".

Overview

Pre-train or Annotate? Domain Adaptation with a Constrained Budget

This repo contains code and data associated with EMNLP 2021 paper "Pre-train or Annotate? Domain Adaptation with a Constrained Budget".

@inproceedings{bai-etal-2021-pre,
    title = "Pre-train or Annotate? Domain Adaptation with a Constrained Budget",
    author = "Bai, Fan  and
              Ritter, Alan  and
              Xu, Wei",
    booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2021",
    address = "Online and Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
}

Installment

git clone https://github.com/bflashcp3f/ProcBERT.git
cd ProcBERT
conda env create -f environment.yml
conda activate procbert

Data & Model Checkpoints

Three procedural-text datasets (WLP, PubMed and ChemSyn) can be downloaded here, and model checkpoints (ProcBERT and Proc-RoBERTa) are accessible through HuggingFace.

Experiment

Setup

# After downloading the data, update the DATA_PATH variable in code/utils.py
DATA_PATH=<DATA_PATH>

Budget-aware Domain Adaptation Experiments (with EasyAdapt)

# Named Entity Recognition (NER) 
python code/ner_da_budget.py     \
  --lm_model procbert     \
  --src_data pubmed     \
  --tgt_data chemsyn     \
  --gpu_ids 0,1   \
  --output_dir ./output/da/pubmed_chemsyn     \
  --learning_rate 1e-5     \
  --task_name fa_ner     \
  --batch_size 16     \
  --max_len 512    \
  --epochs 25 \
  --budget 700 \
  --alpha 1   \
  --save_model

# Relation Extraction (RE)
python code/rel_da_budget.py \
  --lm_model procbert \
  --src_data pubmed     \
  --tgt_data chemsyn     \
  --gpu_ids 0,1  \
  --output_dir ./output/da/pubmed_chemsyn \
  --learning_rate 1e-5 \
  --task_name fa_rel \
  --batch_size 48 \
  --max_len 256 \
  --epochs 5 \
  --budget 700 \
  --alpha 1 \
  --down_sample \
  --down_sample_rate 0.4 \
  --save_model

To obtain ProcBERT results with different budgets under six domain adaptation settings:

# NER
sh script/ner/run_ner_da_budget_all.sh

# RE
sh script/rel/run_rel_da_budget_all.sh

Budget-aware Target-domain-only Experiments

# Named Entity Recognition (NER) 
python code/ner_budget.py \
  --lm_model procbert \
  --data_name chemsyn \
  --gpu_ids 0,1  \
  --output_dir ./output/chemsyn \
  --learning_rate 1e-5 \
  --task_name ner \
  --batch_size 16 \
  --max_len 512 \
  --epochs 25 \
  --budget 700 \
  --save_model

# Relation Extraction (RE)
python code/rel_budget.py \
  --lm_model procbert \
  --data_name chemsyn \
  --gpu_ids 0,1  \
  --output_dir ./output/chemsyn \
  --learning_rate 1e-5 \
  --task_name rel \
  --batch_size 48 \
  --max_len 256 \
  --epochs 5 \
  --budget 700 \
  --down_sample \
  --down_sample_rate 0.4 \
  --save_model

To obtain ProcBERT results with different budgets on three datasets:

# NER
sh script/ner/run_ner_budget_all.sh

# RE
sh script/rel/run_rel_budget_all.sh

Auxiliary Experiments

# Named Entity Recognition (NER) 
python code/ner.py \
  --lm_model procbert \
  --data_name chemsyn \
  --gpu_ids 0,1  \
  --output_dir ./output/chemsyn \
  --learning_rate 1e-5 \
  --task_name ner \
  --batch_size 16 \
  --max_len 512 \
  --epochs 20 \
  --save_model

# Relation Extraction (RE)
python code/rel.py \
  --lm_model procbert \
  --data_name chemsyn \
  --gpu_ids 0,1  \
  --output_dir ./output/chemsyn \
  --learning_rate 1e-5 \
  --task_name rel \
  --batch_size 48 \
  --max_len 256 \
  --epochs 5 \
  --down_sample \
  --down_sample_rate 0.4 \
  --save_model

To obtain ProcBERT results on all three datasets:

# NER
sh script/ner/run_ner_all.sh

# RE
sh script/rel/run_rel_all.sh
Owner
Fan Bai
Fan Bai
Simple telegram bot to convert files into direct download link.you can use telegram as a file server 🪁

TGCLOUD 🪁 Simple telegram bot to convert files into direct download link.you can use telegram as a file server 🪁 Features Easy to Deploy Heroku Supp

Mr.Acid dev 6 Oct 18, 2022
Implementation of Fast Transformer in Pytorch

Fast Transformer - Pytorch Implementation of Fast Transformer in Pytorch. This only work as an encoder. Yannic video AI Epiphany Install $ pip install

Phil Wang 167 Dec 27, 2022
Let Xiao Ai speakers control third-party devices

A stupid way to extend miot/xiaoai. Demo for Panasonic Bath Bully FV-RB20VL1 逆向 Panasonic Smart China,获得控制浴霸的请求信息(HTTP 请求),详见 apps/panasonic.py; 2. 通过

bin 14 Jul 07, 2022
A natural language processing model for sequential sentence classification in medical abstracts.

NLP PubMed Medical Research Paper Abstract (Randomized Controlled Trial) A natural language processing model for sequential sentence classification in

Hemanth Chandran 1 Jan 17, 2022
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding

Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding

Bethge Lab 61 Dec 21, 2022
Course project of [email protected]

NaiveMT Prepare Clone this repository git clone [email protected]:Poeroz/NaiveMT.git

Poeroz 2 Apr 24, 2022
Mycroft Core, the Mycroft Artificial Intelligence platform.

Mycroft Mycroft is a hackable open source voice assistant. Table of Contents Getting Started Running Mycroft Using Mycroft Home Device and Account Man

Mycroft 6.1k Jan 09, 2023
Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge

Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge This is an implementation of the paper,

Mutian He 19 Oct 14, 2022
Implementation of legal QA system based on SentenceKoBART

LegalQA using SentenceKoBART Implementation of legal QA system based on SentenceKoBART How to train SentenceKoBART Based on Neural Search Engine Jina

Heewon Jeon(gogamza) 75 Dec 27, 2022
Production First and Production Ready End-to-End Keyword Spotting Toolkit

Production First and Production Ready End-to-End Keyword Spotting Toolkit

223 Jan 02, 2023
Nystromformer: A Nystrom-based Algorithm for Approximating Self-Attention

Nystromformer: A Nystrom-based Algorithm for Approximating Self-Attention April 6, 2021 We extended segment-means to compute landmarks without requiri

Zhanpeng Zeng 322 Jan 01, 2023
Chinese named entity recognization (bert/roberta/macbert/bert_wwm with Keras)

Chinese named entity recognization (bert/roberta/macbert/bert_wwm with Keras)

2 Jul 05, 2022
Big Bird: Transformers for Longer Sequences

BigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretical understanding of the c

Google Research 457 Dec 23, 2022
This is the main repository of open-sourced speech technology by Huawei Noah's Ark Lab.

Speech-Backbones This is the main repository of open-sourced speech technology by Huawei Noah's Ark Lab. Grad-TTS Official implementation of the Grad-

HUAWEI Noah's Ark Lab 295 Jan 07, 2023
Ray-based parallel data preprocessing for NLP and ML.

Wrangl Ray-based parallel data preprocessing for NLP and ML. pip install wrangl # for latest pip install git+https://github.com/vzhong/wrangl See exa

Victor Zhong 33 Dec 27, 2022
Convolutional Neural Networks for Sentence Classification

Convolutional Neural Networks for Sentence Classification Code for the paper Convolutional Neural Networks for Sentence Classification (EMNLP 2014). R

Yoon Kim 2k Jan 02, 2023
Official source for spanish Language Models and resources made @ BSC-TEMU within the "Plan de las Tecnologías del Lenguaje" (Plan-TL).

Spanish Language Models 💃🏻 A repository part of the MarIA project. Corpora 📃 Corpora Number of documents Number of tokens Size (GB) BNE 201,080,084

Plan de Tecnologías del Lenguaje - Gobierno de España 203 Dec 20, 2022
An Analysis Toolkit for Natural Language Generation (Translation, Captioning, Summarization, etc.)

VizSeq is a Python toolkit for visual analysis on text generation tasks like machine translation, summarization, image captioning, speech translation

Facebook Research 409 Oct 28, 2022
Extract city and country mentions from Text like GeoText without regex, but FlashText, a Aho-Corasick implementation.

flashgeotext ⚡ 🌍 Extract and count countries and cities (+their synonyms) from text, like GeoText on steroids using FlashText, a Aho-Corasick impleme

Ben 57 Dec 16, 2022
A python framework to transform natural language questions to queries in a database query language.

__ _ _ _ ___ _ __ _ _ / _` | | | |/ _ \ '_ \| | | | | (_| | |_| | __/ |_) | |_| | \__, |\__,_|\___| .__/ \__, | |_| |_| |___/

Machinalis 1.2k Dec 18, 2022