Grokking: Generalization beyond Overfitting on small algorithmic datasets (Paper Explained)
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AI • Machine Learning • Tech on Instagram: "Grokking in large language models (LLMs) refers to a phase where a model obtains a deep, general understanding of a task after extended training. Before grokking, a model may perform well on training examples but fail to generalize; after grokking, it starts solving new cases correctly with more training data. In LLMs, signs of real understanding include stable performance on out-of-distribution data, consistent reasoning across varied prompts, and rob
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