QomSSLab / CivilCriminalClassifier-fa-v1

QomSSLab/CaseTypeClassifier-fa

QomSSLab/CaseTypeClassifier-fa is a Persian legal text classifier that predicts whether a court ruling (رأی) belongs to a civil (حقوقی) or criminal (کیفری) category.
The model is designed for use in Iranian legal NLP pipelines, document organization, and downstream analysis of judicial data.

💡 Use Cases

• Automatic classification of Persian court rulings into civil or criminal categories.
• Preprocessing step for legal analytics and document retrieval systems.
• Assisting legal researchers and developers in structuring Persian legal corpora.

🧠 Model Details

• Language : Persian (Farsi)
• Task : Text Classification
• Classes : civil (حقوقی), criminal (کیفری)
• Pipeline Tag : text-classification

📦 Example Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

model_name = "QomSSLab/CaseTypeClassifier-fa"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)

text = "در این پرونده متهم به سرقت اموال عمومی محکوم شده است."
result = classifier(text)

print(result)

Example Output:

[
{'label': 'کیفری', 'score': 0.9969141483306885}
]

📊 Evaluation

The model was trained and evaluated on a balanced dataset of Persian court rulings.
It demonstrates high accuracy in distinguishing civil and criminal judgments.

✅ Final Performance: The model achieved 99.51% accuracy and 0.9951 F1-score on the validation set.

Limitations

• Performance may degrade on highly abbreviated or informal texts.
• Designed primarily for Iranian legal language; may not generalize to non-Iranian legal contexts.
• Does not classify subtypes (e.g., family, property, or financial cases).