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cognitive-distortion-detector-tr
mfurkanerkan15/cognitive-distortion-detector-tr
cognitive-distortion-detector-tr is a machine learning model from mfurkanerkan15. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
This model is a Turkish NLP classifier specialized in identifying cognitive distortions in text. It is designed as the initial component of a hierarchical classification system.
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At a glance
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Mar 15, 2026
- Updated
- Sep 16, 2026
- SHA
- 9bc26a4c
Datasets
Model card
From the Hugging Face model README
Cognitive Distortion Detector (Stage 1)
This model is a Turkish NLP classifier specialized in identifying cognitive distortions in text. It is designed as the initial component of a hierarchical classification system.
Model Description
The model acts as a binary classifier (Distorted vs. Not Distorted). Its primary goal is to filter text for potential cognitive biases before more specific analysis.
- Task: Binary Classification
- Language: Turkish
- Focus: Mental health-related language processing
Hierarchical Workflow
This model serves as the Gatekeeper:
- Stage 1 (This Model): Detects if any cognitive distortion is present.
- Stage 2 (Subsequent Classifier): Categorizes the detected distortion into specific types (e.g., Catastrophizing, Overgeneralization, Personalization).
Usage
You can easily integrate this model using the Hugging Face pipeline:
from transformers import pipeline
pipe = pipeline("text-classification", model="mfurkanerkan15/cognitive-distortion-detector-tr")
result = pipe("Her şey her zaman kötü gitmek zorunda.")
print(result)
- Type
- bert
- License
- mit
- Languages
- tr
- Created
- Mar 15, 2026
- Updated
- Sep 16, 2026