Code for EMNLP 2021 paper Contrastive Out-of-Distribution Detection for Pretrained Transformers.

Last update: Oct 28, 2022

Related tags

Deep Learning Contra-OOD

Overview

Contra-OOD

Code for EMNLP 2021 paper Contrastive Out-of-Distribution Detection for Pretrained Transformers.

Requirements

PyTorch
Transformers
datasets
wandb
tqdm
scikit-learn

Dataset

Most datasets used in paper are automatically downloaded by the datasets package. Instructions on downloading sst2 and multi30k are provided in readme.txt under the data folder.

Training and Evaluation

Finetune the PLM with the following command:

>> python run.py --task_name task

The task_name parameter can take sst2, imdb, trec, or 20ng. The training loss and evaluation results on the test set are synced to the wandb dashboard.

Owner

Wenxuan Zhou

Ph.D. student at University of Southern California

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Code for EMNLP 2021 paper Contrastive Out-of-Distribution Detection for Pretrained Transformers.

Related tags

Overview

Contra-OOD

Requirements

Dataset

Training and Evaluation

Owner

Wenxuan Zhou

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