![]() Since implementing multilingual tasks is somewhat tough in the field of NLP, there was no unified model for the Swiss national language before SwissBERT. Also, there is no separate neural language model for the fourth national language, Romansh. ![]() Switzerland has mainly four official languages – German, French, Italian, and Romansh and individual language models for each particular language are difficult to combine for performing multilingual tasks. SwissBERT has been introduced to overcome the challenges the researchers in Switzerland face due to the inability to perform multilingual tasks. □ JOIN the fastest ML Subreddit Community Called SwissBERT, this model has been trained on more than 21 million Swiss news articles in Swiss Standard German, French, Italian, and Romansh Grischun with a total of 12 billion tokens. Recently, a team of researchers from the University of Zurich has developed a multilingual language model for Switzerland. Followed by that, other language models like CamemBERT for French and GilBERTo for Italian were developed. The original BERT model was released for the English language. With BERT, bidirectionally training was introduced, which gave a deeper sense of language context and flow compared to the previous language models. This one-directional approach worked well for generating sentences by predicting the next word, attaching that to the sequence, followed by predicting the next to the next word until a complete meaningful sentence is obtained. The BERT language model is one of the most prominent examples of NLP advancements and uses self-supervised learning techniques.īefore developing the BERT model, a language model analyzed the text sequence at the time of training from either left-to-right or combined left-to-right and right-to-left. ![]() An attention mechanism learns contextual relations between words or sub-words in a textual corpus. BERT (Bidirectional Encoder Representations from Transformers) uses a Transformer attention mechanism. The language model is suitable for a number of NLP tasks, the ones that transform the input sequence into an output sequence. The famous BERT model has recently been one of the leading Language Models for Natural Language Processing. ![]()
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