I’m trying to train multilingual NER model with own data. I took the data for ner_ontonotes_bert_mult and added some own data (english texts). When I trained the model and tested it on Czech texts, it failed. It was much worse than the pretrained ner_ontonotes_bert_mult. I’m not really sure how you trained the model. The dataset downloaded for ner_ontonotes_bert_mult seems to contain only English texts. But the documentation says that the model was trained on Ontonotes data and evaluated on Russian data. Does it mean that when you train the model, the training data was the Ontonotes data (only English texts) and validation data was the Russian texts? Or what data was in the training and validation set please?
I see parameter freeze_embeddings in BertSequenceTagger. Should I set this parameter to True if I don’t want to retrain BERT? E.g. if my training data is only English and I want to keep the model multilingual.