Open Internet by MindsNet

Detecting Catastrophic Forgetting in LLM Fine-Tuning

Catastrophic forgetting is a significant issue during LLM fine-tuning, where models forget previously learned information. There is a lack of tooling to detect and mitigate this problem. Existing research on continual learning highlights the need for solutions to this challenge.

Computing & Technology, Computer Science, Machine Learning