# Named Entity Recognition 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_ner',
                 labels=[
                     'B-PERSON', 'I-ORG', 'B-ORG', 'I-LOC', 'B-MISC',
                     'I-MISC', 'I-PERSON', 'B-LOC', 'O'
                 ],
                 use_cuda=False,
                 args={"use_multiprocessing": 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 = 0.0004407190410447974

f1_score = 0.999519076627124

precision = 0.9994389677005691

recall = 0.9995991983967936


{}
transformers pytorch jax bert token-classification autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #jax #bert #token-classification #autotrain_compatible #endpoints_compatible #has_space #region-us 

# Named Entity Recognition 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.



## Training data

Training data is from URL

## Eval results

On the test set my results were

eval_loss = 0.0004407190410447974

f1_score = 0.999519076627124

precision = 0.9994389677005691

recall = 0.9995991983967936


# Named Entity Recognition 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. ## Training data

Training data is from URL ## Eval results

On the test set my results were

eval_loss = 0.0004407190410447974

f1_score = 0.999519076627124

precision = 0.9994389677005691

recall = 0.9995991983967936
TAGS
#transformers #pytorch #jax #bert #token-classification #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Named Entity Recognition 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. ## Training data

Training data is from URL ## Eval results

On the test set my results were

eval_loss = 0.0004407190410447974

f1_score = 0.999519076627124

precision = 0.9994389677005691

recall = 0.9995991983967936
passage: TAGS
#transformers #pytorch #jax #bert #token-classification #autotrain_compatible #endpoints_compatible #has_space #region-us 
# Named Entity Recognition 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.## Training data

Training data is from URL## Eval results

On the test set my results were

eval_loss = 0.0004407190410447974

f1_score = 0.999519076627124

precision = 0.9994389677005691

recall = 0.9995991983967936