## About the model
It is a bert-based model created to determine the types of bullying that people use against each other in social media.
Included classes;

- Nötr
- Kızdırma/Hakaret
- Cinsiyetçilik
- Irkçılık

3388 tweets were used in the training of the model. Accordingly, the success rates in education are as follows;
![alt text](/Users/seyma.sarigil/PycharmProjects/bert-base-turkish-bullying/src/image.jpg)


## Example
```sh
from transformers import AutoTokenizer, TextClassificationPipeline, TFBertForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("nanelimon/bert-base-turkish-bullying")
model = TFBertForSequenceClassification.from_pretrained("nanelimon/bert-base-turkish-bullying", from_pt=True)
pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer)

print(pipe('Bu bir denemedir hadi sende dene!'))
```
Result;
```sh
[{'label': 'Nötr', 'score': 0.999175488948822}]
```
label= It shows which class the sent Turkish text belongs to according to the model.
score= It shows the compliance rate of the Turkish text sent to the label found.

## License

gpl-3.0

**Free Software, Hell Yeah!**