Meta learning algorithms to train cross-lingual NLI (multi-task) models

Overview

MetaNLI

Meta learning algorithms to train cross-lingual NLI (multi-task) models

Train (source task)

Reptile

To train the model using Reptile algorithm, run the command below:

python reptile.py \
    --meta_tasks sc_en,sc_de,sc_es,sc_fr \
    --queue_len 4 \
    --temp 5.0 \
    --epochs 1 \
    --meta_lr 1e-5 \
    --scheduler \
    --gamma 0.5 \
    --step_size 4000 \
    --shot 4 \
    --meta_iteration 8000 \
    --log_interval 300

Prototypical

To train the model using Prototypical Networks algorithm, run the command below:

python prototype.py \
    --meta_tasks sc_en,sc_de,sc_es,sc_fr \
    --target_task sc_fa \
    --epochs 1 \
    --meta_lr 1e-5 \
    --lambda_1 1 \
    --lambda_2 1 \
    --scheduler \
    --gamma 0.5 \
    --step_size 1000 \
    --shot 8 \
    --query_num 0 \
    --target_shot 8 \
    --meta_iteration 2500 \
    --log_interval 50

Zero-shot Test (on target task)

To perform a zero-shot test of the trained model on the target task, run the command below:

python zeroshot.py \
    --load saved/model_sc.pt \
    --task sc_fa

Fine-tune (target task)

To fine-tune the trained model on the target task, run the command below:

python finetune.py \
    --save saved \
    --model_filename fine.pt \
    --load saved/model_sc.pt \
    --task sc_fa \
    --epochs 5 \
    --lr 1e-5
Owner
M.Hassan Mojab
M.Hassan Mojab
The ability of computer software to identify words and phrases in spoken language and convert them to human-readable text

speech-recognition-py Speech recognition is the ability of computer software to identify words and phrases in spoken language and convert them to huma

Deepangshi 1 Apr 03, 2022
simpleT5 is built on top of PyTorch-lightning⚡️ and Transformers🤗 that lets you quickly train your T5 models.

Quickly train T5 models in just 3 lines of code + ONNX support simpleT5 is built on top of PyTorch-lightning ⚡️ and Transformers 🤗 that lets you quic

Shivanand Roy 220 Dec 30, 2022
:mag: Transformers at scale for question answering & neural search. Using NLP via a modular Retriever-Reader-Pipeline. Supporting DPR, Elasticsearch, HuggingFace's Modelhub...

Haystack is an end-to-end framework that enables you to build powerful and production-ready pipelines for different search use cases. Whether you want

deepset 6.4k Jan 09, 2023
ConvBERT: Improving BERT with Span-based Dynamic Convolution

ConvBERT Introduction In this repo, we introduce a new architecture ConvBERT for pre-training based language model. The code is tested on a V100 GPU.

YITUTech 237 Dec 10, 2022
초성 해석기 based on ko-BART

초성 해석기 개요 한국어 초성만으로 이루어진 문장을 입력하면, 완성된 문장을 예측하는 초성 해석기입니다. 초성: ㄴㄴ ㄴㄹ ㅈㅇㅎ 예측 문장: 나는 너를 좋아해 모델 모델은 SKT-AI에서 공개한 Ko-BART를 이용합니다. 데이터 문장 단위로 이루어진 아무 코퍼스나

Dawoon Jung 29 Oct 28, 2022
Unofficial Parallel WaveGAN (+ MelGAN & Multi-band MelGAN & HiFi-GAN & StyleMelGAN) with Pytorch

Parallel WaveGAN implementation with Pytorch This repository provides UNOFFICIAL pytorch implementations of the following models: Parallel WaveGAN Mel

Tomoki Hayashi 1.2k Dec 23, 2022
A modular Karton Framework service that unpacks common packers like UPX and others using the Qiling Framework.

Unpacker Karton Service A modular Karton Framework service that unpacks common packers like UPX and others using the Qiling Framework. This project is

c3rb3ru5 45 Jan 05, 2023
Text preprocessing, representation and visualization from zero to hero.

Text preprocessing, representation and visualization from zero to hero. From zero to hero • Installation • Getting Started • Examples • API • FAQ • Co

Jonathan Besomi 2.7k Jan 08, 2023
A design of MIDI language for music generation task, specifically for Natural Language Processing (NLP) models.

MIDI Language Introduction Reference Paper: Pop Music Transformer: Beat-based Modeling and Generation of Expressive Pop Piano Compositions: code This

Robert Bogan Kang 3 May 25, 2022
CCF BDCI 2020 房产行业聊天问答匹配赛道 A榜47/2985

CCF BDCI 2020 房产行业聊天问答匹配 A榜47/2985 赛题描述详见:https://www.datafountain.cn/competitions/474 文件说明 data: 存放训练数据和测试数据以及预处理代码 model_bert.py: 网络模型结构定义 adv_train

shuo 40 Sep 28, 2022
Demo programs for the Talking Head Anime from a Single Image 2: More Expressive project.

Demo Code for "Talking Head Anime from a Single Image 2: More Expressive" This repository contains demo programs for the Talking Head Anime

Pramook Khungurn 901 Jan 06, 2023
A collection of Korean Text Datasets ready to use using Tensorflow-Datasets.

tfds-korean A collection of Korean Text Datasets ready to use using Tensorflow-Datasets. TensorFlow-Datasets를 이용한 한국어/한글 데이터셋 모음입니다. Dataset Catalog |

Jeong Ukjae 20 Jul 11, 2022
Simple Python library, distributed via binary wheels with few direct dependencies, for easily using wav2vec 2.0 models for speech recognition

Wav2Vec2 STT Python Beta Software Simple Python library, distributed via binary wheels with few direct dependencies, for easily using wav2vec 2.0 mode

David Zurow 22 Dec 29, 2022
Just Another Telegram Ai Chat Bot Written In Python With Pyrogram.

OkaeriChatBot Just another Telegram AI chat bot written in Python using Pyrogram. Requirements Python 3.7 or higher.

Wahyusaputra 2 Dec 23, 2021
Malaya-Speech is a Speech-Toolkit library for bahasa Malaysia, powered by Deep Learning Tensorflow.

Malaya-Speech is a Speech-Toolkit library for bahasa Malaysia, powered by Deep Learning Tensorflow. Documentation Proper documentation is available at

HUSEIN ZOLKEPLI 151 Jan 05, 2023
Huggingface Transformers + Adapters = ❤️

adapter-transformers A friendly fork of HuggingFace's Transformers, adding Adapters to PyTorch language models adapter-transformers is an extension of

AdapterHub 1.2k Jan 09, 2023
LightSeq: A High-Performance Inference Library for Sequence Processing and Generation

LightSeq is a high performance inference library for sequence processing and generation implemented in CUDA. It enables highly efficient computation of modern NLP models such as BERT, GPT2, Transform

Bytedance Inc. 2.5k Jan 03, 2023
Persian Bert For Long-Range Sequences

ParsBigBird: Persian Bert For Long-Range Sequences The Bert and ParsBert algorithms can handle texts with token lengths of up to 512, however, many ta

Sajjad Ayoubi 63 Dec 14, 2022
Code for the paper TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks

TestRank in Pytorch Code for the paper TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks by Yu Li, Min Li, Qiuxia Lai, Ya

3 May 19, 2022
Dust model dichotomous performance analysis

Dust-model-dichotomous-performance-analysis Using a collated dataset of 90,000 dust point source observations from 9 drylands studies from around the

1 Dec 17, 2021