jamal-ibrahim/risk_assesment

Risk Assessment Model

A text classification model fine-tuned on DistilBERT for automated reputational risk assessment of textual reviews and comments. The model classifies input text into three risk levels: Low, Medium, and High.

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Model Details

Property	Details
Base Model	DistilBERT (distilbert-base-uncased)
Task	Text Classification
Fine-tuning Data	~1,000 manually labeled reviews
Language	English

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Intended Use

This model is designed for automated screening of reviews, comments, and user feedback in the context of reputational risk management. It is intended to assist human analysts rather than replace them in decision-making workflows.

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Usage

from transformers import pipeline

pipe = pipeline("text-classification", model="jamal-ibrahim/risk_assesment")
result = pipe("The company has been accused of fraud.")
print(result)

Example output:

[{"label": "High", "score": 0.92}]

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Classes

Label	Description
Low	No significant reputational risk detected
Medium	Moderate concerns that may warrant further review
High	Severe reputational implications requiring immediate attention

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Limitations

• Trained on a relatively small, domain-specific dataset (~1,000 entries)
• Not suitable for legal or financial decision-making without qualified human oversight
• Generalization to domains outside the training distribution is not guaranteed
• Detailed training metrics and hyperparameters are not currently available

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License

This model is licensed under the Apache 2.0 License, consistent with the base DistilBERT model.