Model-Agnostic Meta Learning for Class Imbalance Adaptation

Create a 'Hardness-Aware' training wrapper that fits onto existing fine-tuning scripts. It should dynamically re-weight training samples based on model confusion during the run.

Suggested repo: hamrTune

"Stop over-training on easy data—adaptive meta-resampling for robust LLM fine-tuning."

Estimated effort: 45h