https://guotong1988.github.io/core_research/2024/02/01/auto-re-label/
Step-1, Train the model on origin training dataset, train.py
Step-2, Predict the training/dev datasets, predict.py
Step-3, Prepare the candidate training datasets, get_dataset_list.py
Step-4, Find the best dataset by dev accuracy, explore_train.py
transformers 4.38.2 or 4.26.1
torch 2.2.1 or 1.11.0
scikit-learn 1.3.2
datasets 2.18.0
accelerate 0.27.2
Label Error Correction With Human Labor: The Re-Label Method For Data-Centric Machine Learning
Controllable Label Error Fixing: Re-Label By Data Pattern For Controllable Deep Learning
The method proposed in this project (and its relate works) can be applied to all manually annotated (or dataset by LLMs) deep learning tasks, not just NLP tasks, but can be efficiently extended to CV tasks, speech recognition tasks, text-to-speech tasks, and more.