readme: # Part of Speech tagging Model for Telugu
  
  #### How to use
  Use the below script from your python terminal as the web interface for inference has few encoding issues for Telugu
  
  PS: If you find my model useful, I would appreciate a note from you as it would encourage me to continue improving it and also add new models.
  
  ```python
  from simpletransformers.ner import NERModel
  model = NERModel('bert',
                   'kuppuluri/telugu_bertu_pos',
                   args={"use_multiprocessing": False},
                   labels=[
                       'QC', 'JJ', 'NN', 'QF', 'RDP', 'O',
                       'NNO', 'PRP', 'RP', 'VM', 'WQ',
                       'PSP', 'UT', 'CC', 'INTF', 'SYMP',
                       'NNP', 'INJ', 'SYM', 'CL', 'QO',
                       'DEM', 'RB', 'NST', ],
                   use_cuda=False)
  
  text = "విరాట్ కోహ్లీ కూడా అదే నిర్లక్ష్యాన్ని ప్రదర్శించి కేవలం ఒక పరుగుకే రనౌటై పెవిలియన్ చేరాడు ."
  results = model.predict([text])
  ```
  
  ## Training data
  
  Training data is from https://github.com/anikethjr/NER_Telugu
  
  ## Eval results
  
  On the test set my results were
  
  eval_loss = 0.0036797842364565416
  
  f1_score = 0.9983795127912227
  
  precision = 0.9984325602401637
  
  recall = 0.9983264709788816
  