Bert NER model start and end position None after fine-tuning
HI All,I have fine-tuned a BERT NER model to my dataset. The model that I am fine-tuning is “dslim/bert-base-NER”. I have been successfully able to train the model using the following script as refrence:https://colab.research.google.com/github/NielsRogge/Transformers-Tutorials/blob/master/BERT/Custom_Named_Entity_Recognition_with_BERT_only_first_wordpiece.ipynb#scrollTo=zPDla1mmZiaxThe prediction form the base model contained the start and end position of the word in the original text like:{‘entity_group’: ‘ORG’, ‘score’: 0.9992545247077942, ‘word’: ‘A’,‘start’: 10, ‘end’: 11}{‘entity_group’: ‘ORG’, ‘score’: 0.998507097363472, ‘word’: ‘##bcCorp Ltd’, ‘start’: 11, ‘end’: 22}While the prediction from the re-trained model is:{‘entity_group’: ‘ORG’,‘score’: 0.747031033039093,‘word’: ‘##7’,‘start’: None,‘end’: None},{‘entity_group’: ‘ORG’,‘score’: 0.9055356582005819,‘word’: ‘Games , Inc’,‘start’: None,**  ‘end’: None**}I am passing the position ids to the model during the training process. I looked at the model training parameters but, could not find a way to pass start and end position of the words to model training process. I have the start and end position of the tokenized words.