Optimizing Deeper Transformers on Small Datasets

Related tags

Deep LearningDT-Fixup
Overview

DT-Fixup

Optimizing Deeper Transformers on Small Datasets

Paper published in ACL 2021: arXiv

Detailed instructions to replicate our results in the paper can be found in the folders spider and reclor.

Cite

If you found this codebase or our work useful, please cite:

@InProceedings{xu2021optimizing,
  author = {Xu, Peng and Kumar, Dhruv and Yang, Wei and Zi, Wenjie and Tang, Keyi and Huang, Chenyang and Cheung, Jackie Chi Kit and Prince, Simon J.D. and Cao, Yanshuai},
  title = {Optimizing Deeper Transformers on Small Datasets}
  booktitle = {The 59th Annual Meeting of the Association for Computational Linguistics (ACL 2021)},
  month = {August},
  year = {2021},
  publisher = {ACL}
}
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai

Coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks an

Aman Chadha 1.7k Jan 08, 2023
Official code repository for the work: "The Implicit Values of A Good Hand Shake: Handheld Multi-Frame Neural Depth Refinement"

Handheld Multi-Frame Neural Depth Refinement This is the official code repository for the work: The Implicit Values of A Good Hand Shake: Handheld Mul

55 Dec 14, 2022
A demo of how to use JAX to create a simple gravity simulation

JAX Gravity This repo contains a demo of how to use JAX to create a simple gravity simulation. It uses JAX's experimental ode package to solve the dif

Cristian Garcia 16 Sep 22, 2022
Pansharpening by convolutional neural networks in the full resolution framework

Z-PNN: Zoom Pansharpening Neural Network Pansharpening by convolutional neural networks in the full resolution framework is a deep learning method for

20 Nov 24, 2022
The backbone CSPDarkNet of YOLOX.

YOLOX-Backbone The backbone CSPDarkNet of YOLOX. In this project, you can enjoy: CSPDarkNet-S CSPDarkNet-M CSPDarkNet-L CSPDarkNet-X CSPDarkNet-Tiny C

Jianhua Yang 9 Aug 22, 2022
PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos

PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos. By adopting a unified pipeline-ba

PyKale 370 Dec 27, 2022
This is the implementation of our work Deep Extreme Cut (DEXTR), for object segmentation from extreme points.

This is the implementation of our work Deep Extreme Cut (DEXTR), for object segmentation from extreme points.

Sergi Caelles 828 Jan 05, 2023
Download from Onlyfans.com.

OnlySave: Onlyfans downloader Getting Started: Download the setup executable from the latest release. Install and run. Only works on Windows currently

4 May 30, 2022
Implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"

SinGAN This is an unofficial implementation of SinGAN from someone who's been sitting right next to SinGAN's creator for almost five years. Please ref

35 Nov 10, 2022
source code for https://arxiv.org/abs/2005.11248 "Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics"

Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics This work will be published in Nature Biomedical

International Business Machines 71 Nov 15, 2022
"Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback"

This is code repo for our EMNLP 2017 paper "Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback", which implements the A2C algorithm on top of a neural encoder-

Khanh Nguyen 131 Oct 21, 2022
Code release for ConvNeXt model

A ConvNet for the 2020s Official PyTorch implementation of ConvNeXt, from the following paper: A ConvNet for the 2020s. arXiv 2022. Zhuang Liu, Hanzi

Meta Research 4.6k Jan 08, 2023
Learning to See by Looking at Noise

Learning to See by Looking at Noise This is the official implementation of Learning to See by Looking at Noise. In this work, we investigate a suite o

Manel Baradad Jurjo 82 Dec 24, 2022
STARCH compuets regional extreme storm physical characteristics and moisture balance based on spatiotemporal precipitation data from reanalysis or climate model data.

STARCH (Storm Tracking And Regional CHaracterization) STARCH computes regional extreme storm physical and moisture balance characteristics based on sp

Onosama 7 Oct 20, 2022
Meta-learning for NLP

Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks Code for training the meta-learning models and fine-tuning on downstr

IESL 43 Nov 08, 2022
an Evolutionary Algorithm assisted GAN

EvoGAN an Evolutionary Algorithm assisted GAN ckpts

3 Oct 09, 2022
Catalyst.Detection

Accelerated DL R&D PyTorch framework for Deep Learning research and development. It was developed with a focus on reproducibility, fast experimentatio

Catalyst-Team 12 Oct 25, 2021
Dynamic hair modeling from monocular videos using deep neural networks

Dynamic Hair Modeling The source code of the networks for our paper "Dynamic hair modeling from monocular videos using deep neural networks" (SIGGRAPH

53 Oct 18, 2022
Translation-equivariant Image Quantizer for Bi-directional Image-Text Generation

Translation-equivariant Image Quantizer for Bi-directional Image-Text Generation Woncheol Shin1, Gyubok Lee1, Jiyoung Lee1, Joonseok Lee2,3, Edward Ch

Woncheol Shin 7 Sep 26, 2022
We present a regularized self-labeling approach to improve the generalization and robustness properties of fine-tuning.

Overview This repository provides the implementation for the paper "Improved Regularization and Robustness for Fine-tuning in Neural Networks", which

NEU-StatsML-Research 21 Sep 08, 2022