telugu_bertu_pos

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.

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