Then the best hyperparameter values were trained on the combination of training and development data and applied on the test set, to obtain the final results.
the skip-gram model then computes a probability of a context word given a target word as the product of the probabilities, given the target word's embeddings, of all decisions on a path from the root to the leaf corresponding to the context word.