## BERT Model for OGBV gendered text classification 


## How to use
```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
  
tokenizer = AutoTokenizer.from_pretrained("mlkorra/OGBV-gender-bert-hi-en")

model = AutoModelForSequenceClassification.from_pretrained("mlkorra/OGBV-gender-bert-hi-en")
```

## Model Performance

|Metric|dev|test| 
|---|--|--|
|Accuracy|0.88|0.81|
|F1(weighted)|0.86|0.80|

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

BERT Model for OGBV gendered text classification
------------------------------------------------


How to use
----------


Model Performance
-----------------


Metric: Accuracy, dev: 0.88, test: 0.81
Metric: F1(weighted), dev: 0.86, test: 0.80



TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #has_space #region-us 

passage: TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #has_space #region-us 
