You Fine-Tuned Your Model. Now It's Worse. Here's the Concept You Were Never Taught.

Catastrophic forgetting occurs when fine-tuning a pre-trained model for a new task causes it to lose performance on previous tasks due to the lack of stability in gradient descent updates. This phenomenon is critical for developers as it highlights the need for strategies like Elastic Weight Consolidation, Experience Replay, and Knowledge Distillation to prevent knowledge loss during continual learning.

Read the full article at Towards AI - Medium

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