CleaR

This repository is about CleaR long paper: Towards Robust and Generalized Parameter-Efficient Fine-Tuning for Noisy Label Learning published in ACL 2024.

Requirements

• Python 3
• Transformers 4.27.2
• Numpy
• pytorch

Clean Routing

bash train.sh

• --dataset: Train dataset used for training.
• --lr: Set the learning rate.
• --epochs: Set the number of epochs.
• --batch_size: Set the batch size for conducting at once.
• --warm_up : Set the warm-up epoch
• --alg: PEFT routing strategy. Choose PEFT routing from : routing_adapter, routing_lora, routing_prefix, routing_bitfit, none.
• --adapter: PEFT routing strategy. Choose PEFT routing from : routing_adapter, routing_lora, routing_prefix, routing_bitfit, none.

Contact Info

For help or issues using CleaR, please submit a GitHub issue.

For personal communication related to CleaR, please contact Yeachan Kim<yeachan@korea.ac.kr> or Junho Kim <monocrat@korea.ac.kr>