Downloads · 30 days
0
convBERT-turk-based-cyberbullying-tokenizer
AIZinu/convBERT-turk-based-cyberbullying-tokenizer
convBERT-turk-based-cyberbullying-tokenizer is a text classification model from AIZinu. Use it when you need a label for a piece of text. It is set up for transformers, PyTorch. The card lists the license as mit.
This model is a Turkish-based convBERT model created to classify Turkish social media bullying data. Classes included in the model
Access
Public
Updated May 15, 2024
Repo size
—
Likes
0
Public
Repo makeup
Click a slice to open those files.
.txt251 KB · 98%
At a glance
- Task
- Text Classification
- Library
- transformers, PyTorch
- License
- mit
- Access
- Public
- Created
- May 15, 2024
- Updated
- May 15, 2024
- SHA
- ddc902ea
Model card
From the Hugging Face model README
About the Model
This model is a Turkish-based convBERT model created to classify Turkish social media bullying data. Classes included in the model
- Cinsiyetçilik
- Irkçılık
- Kızdırma
- Nötr
The model was trained from a dataset containing 2981 Twitter data.
The success rates achieved in training the model are as follows:
| Cinsiyetçilik | Irkçılık | Kızdırma | Nötr | |
|---|---|---|---|---|
| Precision | 0.9 | 0.89 | 0.85 | 0.90 |
| Recall | 0.9 | 0.91 | 0.88 | 0.86 |
| F1 Score | 0.9 | 0.90 | 0.86 | 0.88 |
Accuracy: 0.88
Dependency
pip install transformers
pip install torch
Example
from transformers import ConvBertTokenizer, ConvBertForSequenceClassification,TextClassificationPipeline
tokenizer = ConvBertTokenizer.from_pretrained("AIZinu/convBERT-turk-based-cyberbullying")
model = ConvBertForSequenceClassification.from_pretrained("AIZinu/convBERT-turk-based-cyberbullying")
pipe= TextClassificationPipeline(model=model, tokenizer=tokenizer)
print(pipe("Hadi modeli deneyelim"))
Result:
[{'label': 'LABEL_3', 'score': 0.9994651675224304}]
Model Card Authors
- Bilge Nur BEKAR
- Task
- Text Classification
- Library
- transformers, PyTorch
- License
- mit
- Languages
- tr
- Created
- May 15, 2024
- Updated
- May 15, 2024