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:
python
1from transformers import pipeline
23pipe = pipeline("text-classification", model="mfurkanerkan15/cognitive-distortion-detector-tr")4result = pipe("Her şey her zaman kötü gitmek zorunda.")5print(result)
