Models have significantly higher uncertainty when translating idiom words vs regular words, meaning idioms are harder to translate. When translating regular words, random models are unaffected by changing idiom representations. However, reducing idiom context increases the pertained model’s uncertainty. For idiom translation, upswing the idiom-train data benefits the pertained but not the random model.