Multilingual NER pretrained model fine tuning
HalloI want to fine tun a pretrained model for named entity recognition. I have chosen Roberta base to fine tun, I had the problem that the dataset contains some Russian words, which the model is not able to understand while the Tokenisation. I thought about adding these words (it depends on how many word I have) to the tokenizer, but I am not sure if the model will understand that those are ORG, OTH etc. so what do you recommend as a solution for this case. The dataset is .tsv file includes German words with numbers and labels I have made them in pandas data frame index, token, label then I get the sentence based on the boundars for example if index 1 this is a start of sentence and if index 1 this is end of the last sentence and beginning of new one. This is one of the sentences : (NEWSru.ua / : Политисполком СПУ отказал Морозу в отставке Die SPU legte wie auch vier weitere Parteien beim Obersten Gericht ’'der Ukraine Beschwerde gegen den Ablauf der Wahl ein und behauptet es sei bei der Auszählung zu Unregelmäßigkeiten gekommen .)  all the Russian words are supposed to be I-OTH in the truth label.