1. A method for evaluating performance of machine translation, the method comprising: receiving, by a machine translation device, a first document in a source language; translating, by a machine translation device, the first document in the source language to a second document in a target language, based, at least in part, on a first quantity of information, wherein the first quantity of information is obtained through, at least, preprocessing, before the translation, wherein the preprocessing includes, at least, tokenization; subsequent to the translation, performing, by a machine translation device, post processing to obtain a second quantity of information, wherein the post processing includes, at least, tokenization; evaluating, by a machine translation device, the second document in the target language, based, at least, on one or more aspects of the translation, the preprocessing, and the post processing, wherein the evaluation of the second document in the target language, based, at least, on the one or more aspects of the translation further comprises: comparing, by the machine translation device, the one or more aspects of the translation of the first document in the source language to the second document in the target language with a predetermined threshold, based, at least, on the first quantity of information and the second quantity of information; and determining, by the machine translation device, whether the comparison of the one or more aspects of the translation of the first document in the source language to the second document in the target language is greater than the predetermined threshold; and responsive to determining that the comparison of the one or more aspects of the translation of the first document in the source language to the second document in the target language is not greater than the predetermined threshold, translating, by the machine translation device, the first document to the second document, using available models, wherein the translation comprises: determining, by the machine translation device, that no new models are created and that no degradation has taken place on a translation performance; comparing, by the machine translation device, a first model used for a translation that failed to meet the predetermined threshold to a second model used for a translation that meets the predetermined threshold; and determining, by the machine translation device, that the first model and the second model exceeds a percentage of similarity, wherein the percentage of similarity is used to show that the first model and the second model are different and due to the difference, the second model is an improvement on the first model.