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Why Is My Skip-Gram Implementation Producing Incorrect Results?

I’m implementing a Skip-Gram model for Word2Vec using Python. However, my model doesn’t seem to be working correctly, as indicated by the resulting embeddings and their visualization. Here is an example of the 3D plot of the embeddings, which shows words clustered together and overlapping, making it difficult to distinguish between them: