If you want to stay hip in machine learning and especially NLP, you have to know at least a bit about Transformers. You might say they’re more than meets the… ugh, forget it. In fact, lots of the amazing research I write about on is built on Transformers, like AlphaFold 2, the model that predicts the structures of proteins from their genetic sequences, as well as powerful natural language processing (NLP) models like GPT-3, BERT, T5, Switch, Meena, and others. Transformers are models that can be designed to translate text, write poems and op eds, and even generate computer code. Performance (12.67 BLEU).You know that expression When you have a hammer, everything looks like a nail? Well, in machine learning, it seems like we really have discovered a magical hammer for which everything is, in fact, a nail, and they’re called Transformers. Our work shows that the mT5 model, finetunedįollowing the curriculum learning procedure, achieves best translation (backtranslation, method based on equivalence constraint theory) under aĭiverse set of conditions. With (and in some cases is even superior to) several standard methods Weįind that, although simple, our synthetic code-mixing method is competitive This additional data, we adopt a curriculum learning approach where we firstįinetune the language models on synthetic data then on gold code-mixed data. Generating code-mixed texts from bilingual distributed representations that weĮxploit for improving language model performance. Of training data for code-mixing, we also propose a dependency-free method for (i.e., mT5 and mBART) on the task finding both to work well. Given the recent success of pretrained language models, weĪlso test the utility of two recent Transformer-based encoder-decoder models Range of models that convert monolingual English text into Hinglish (code-mixed
Monolingual and code-mixed language pairs. Lakshmanan Download PDF Abstract: We describe models focused at the understudied problem of translating between Authors: Ganesh Jawahar, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, Laks V.S.
0 kommentar(er)
