OOD Generalization and Detection (ACL 2020)

littleRound

Last update: Jan 9, 2023

Related tags

Deep Learning transformers albert bert robustness roberta out-of-distribution out-of-distribution-detection domain-generalization out-of-domain

Overview

Pretrained Transformers Improve Out-of-Distribution Robustness

How does pretraining affect out-of-distribution robustness? We create an OOD benchmark and use it to show that pretrained transformers such as BERT have substantially higher OOD accuracy and OOD detection rates compared to traditional NLP models.

This repository most of the code for the paper Pretrained Transformers Improve Out-of-Distribution Robustness, ACL 2020.

Requires Python 3+ and PyTorch 1.0+.

To correctly use RoBERTa model, see allennlp_glue_patch/notes.py.

Citation

If you find this useful in your research, please consider citing:

@inproceedings{hendrycks2020pretrained,
    Author = {Dan Hendrycks and Xiaoyuan Liu and Eric Wallace and Adam Dziedzic Rishabh Krishnan and Dawn Song},
    Booktitle = {Association for Computational Linguistics},                            
    Year = {2020},
    Title = {Pretrained Transformers Improve Out-of-Distribution Robustness}}

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Comments

OOD Detection

Hello, thanks for publishing the code used in your interesting paper! I am wondering if this repo also contains the code for the OOD Detection part, i.e. for recording the confidence scores on the SST-2 dataset and on the 5 validation datasets. I am curious how you calculated the FPR95 and anomaly. Going through all files I cannot find the related code. Do I miss it or is it not added? Thank you very much for your time, @tpatzelt

opened by tpatzelt 2
requriments.txt is missing.
Hi can you mention the version of allennlp and other modules you have used in a requirments.txt. It seems allennlp has changed a lot and the commands mentioned in the readme does not work. For example while running the command

allennlp train config/test/sst-lstm.json -s model/test-lstm[sst-2] --include-package allennlp_glue_patch

I encountered the following error.

"No module named allennlp.run"
opened by islamazhar 1
Json decode error while using BERT and ROBERTA models while using SST-2 dataset and imdb dataset

While I try to use the bert or roberta config using allennlp I get the following error

"json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)"

I was wondering which version of allennlp do you recommend for the code or is there some specific resolution you know regarding this issue.

opened by bhavdeep98 0

Owner

littleRound

Ph.D. Student, EECS, UC Berkeley B.Eng., Computer Science, SJTU

GitHub https://arxiv.org/abs/2004.06100

Github for the conference paper GLOD-Gaussian Likelihood OOD detector

FOOD - Fast OOD Detector Pytorch implamentation of the confernce peper FOOD arxiv link. Abstract Deep neural networks (DNNs) perform well at classifyi

17 Jun 19, 2022

The code release of paper 'Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization' NIPS 2020.

Domain Generalization for Medical Imaging Classification with Linear Dependency Regularization The code release of paper 'Domain Generalization for Me

56 Dec 28, 2022

OOD Generalization and Detection (ACL 2020)

Related tags

Overview

Pretrained Transformers Improve Out-of-Distribution Robustness

Citation

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Comments

OOD Detection

requriments.txt is missing.

Json decode error while using BERT and ROBERTA models while using SST-2 dataset and imdb dataset

Owner

littleRound

Github for the conference paper GLOD-Gaussian Likelihood OOD detector

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