nanelimon/bert-base-turkish-bullying

About the model

It is a Turkish 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;

	Cinsiyetçilik	Irkçılık	Kızdırma	Nötr
Precision	0.925	0.878	0.824	0.915
Recall	0.831	0.896	0.843	0.935
F1 Score	0.875	0.887	0.833	0.925
Accuracy : 0.886

Dependency

pip install torch torchvision torchaudio pip install tf-keras
pip install transformers
pip install tensorflow

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, return_all_scores=True, top_k=2)

print(pipe('Bu bir denemedir hadi sende dene!'))

Result;

[[{'label': 'Nötr', 'score': 0.999175488948822}, {'label': 'Cinsiyetçi Zorbalık', 'score': 0.00042115405085496604}]]

• 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.

Authors

• Seyma SARIGIL: [email protected]
• Elif SARIGIL KARA: [email protected]
• Murat KOKLU: [email protected]
• Alaaddin Erdinç DAL: [email protected]

License

gpl-3.0

Free Software, Hell Yeah!