User Satisfaction Classifier
A ModernBERT-based classifier that detects user satisfaction and dissatisfaction reasons from follow-up messages in conversational AI systems.
Key Insight
Follow-up messages alone contain sufficient signal for classification. No conversation context needed—just pass the user's response directly.
Labels
| Label | Description | Example |
|---|---|---|
SAT |
User is satisfied | "Thanks!", "Perfect", "Great!" |
NEED_CLARIFICATION |
User needs more explanation | "What do you mean?", "Can you explain?" |
WRONG_ANSWER |
System provided incorrect information | "No, that's wrong", "That's not right" |
WANT_DIFFERENT |
User wants alternative options | "Show me others", "What else?" |
License
Apache 2.0
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Model tree for llm-semantic-router/feedback-detector
Base model
answerdotai/ModernBERT-base