Intrinsic evaluation refers to the assessment of a model's performance based on its internal metrics and characteristics rather than its performance on external tasks or datasets. This type of evaluation focuses on the quality and properties of the embeddings themselves, such as their ability to capture semantic relationships between words, which is crucial in understanding how well a model represents linguistic features.
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