 Evaluation results
 
 When fine-tuned on downstream task of fake news binary classification, this model achieved the following results:
 (scores are rounded to 2 floating points)
 
 |              | precision | recall | f1-score | support |
 |:------------:|:---------:|:------:|:--------:|:-------:|
 |     Fake     |   1.00    |  1.00  |   1.00   |  4697   |
 |     True     |   1.00    |  1.00  |   1.00   |  4283   |
 |   accuracy   |     -     |   -    |   1.00   |  8980   |
 |  macro avg   |   1.00    |  1.00  |   1.00   |  8980   |
 | weighted avg |   1.00    |  1.00  |   1.00   |  8980   |
 
 Confision matrix:
 
 
 | Actual\Predicted  | Fake | True |
 |:-----------------:|:----:|:----:|
 |       Fake        | 4696 |  1   |
 |       True        |  1   | 4282 |
 
 The AUC score is 0.9997
 
 