This model was trained using the 'bert-base-uncased' from the transformer library and it was trained on the popular fake/real news dataset from Kaggle.
Pytorch is the framework used to train the model and it had an accuracy score of 93.5 % and here is what the classification report looks like.

            precision    recall  f1-score   support

           0       0.96      0.92      0.94      2348
           1       0.92      0.96      0.94      2142

    accuracy                           0.94      4490
   macro avg       0.94      0.94      0.94      4490
weighted avg       0.94      0.94      0.94      4490


---
license: apache-2.0
---


{}
region:us
TAGS
#region-us 

This model was trained using the 'bert-base-uncased' from the transformer library and it was trained on the popular fake/real news dataset from Kaggle.
Pytorch is the framework used to train the model and it had an accuracy score of 93.5 % and here is what the classification report looks like.

            precision    recall  f1-score   support

           0       0.96      0.92      0.94      2348
           1       0.92      0.96      0.94      2142

    accuracy                           0.94      4490
   macro avg       0.94      0.94      0.94      4490
weighted avg       0.94      0.94      0.94      4490


---
license: apache-2.0
---


TAGS
#region-us 

passage: TAGS
#region-us 
