Embeddings

Embedding size refers to the dimensionality of the vector space in which data, such as words or items, are represented as dense vectors. Larger embedding sizes can capture more nuanced relationships but may increase computational complexity. Selecting an appropriate embedding size balances the model's capacity to learn meaningful representations with efficiency and generalization.