logit-adj-pytorch

PyTorch implementation of the paper: Long-tail Learning via Logit Adjustment

This code implements the paper: Long-tail Learning via Logit Adjustment : Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar. ICLR 2021.

Running the code

# To produce baseline (ERM) results:
python main.py --dataset cifar10-lt

# To produce posthoc logit-adjustment results:
python main.py --dataset cifar10-lt  --logit_adj_post 1

# To produce logit-adjustment loss results:
python main.py --dataset cifar10-lt  --logit_adj_train 0

# To monitor the training progress using Tensorboard:
tensorboard --logdir logs

Replace cifar10-lt above with cifar100-lt to obtain results for the CIFAR-100 long-tail dataset.

Results