Embedding dimension refers to the size of the vector space in which words, sentences, or documents are represented in a continuous form. It captures the amount of information that can be encoded about each linguistic unit, impacting how well these embeddings capture semantic and syntactic relationships. A higher embedding dimension can provide more nuanced representations but may lead to overfitting, while a lower dimension can simplify the representation but might miss important details.
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