This notebook explores an implementation of the Skip-gram with Negative Sampling (SGNS) model using PyTorch, applied to the text8 corpus. It presents both the theoretical formulation of the model as well as details of Negative Sampling for approximate training. The embeddings are trained with early stopping rule based on the extrinsic scores from evaluation on WordSim353 and Google analogy test set.
