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;
Example
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;
[{'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!