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@@ -36,61 +36,6 @@ A ModernBERT-based classifier that detects user satisfaction and dissatisfaction
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  | `WRONG_ANSWER` | System provided incorrect information | "No, that's wrong", "That's not right" |
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  | `WANT_DIFFERENT` | User wants alternative options | "Show me others", "What else?" |
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- ## Quick Start
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- ## Performance
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- | Metric | Score |
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- |--------|-------|
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- | Validation Accuracy | 95.47% |
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- | Validation F1 (Macro) | 95.41% |
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- | Adversarial Test Accuracy | 93.2% |
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- ### Per-Class Performance
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- | Class | Adversarial Accuracy |
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- |-------|---------------------|
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- | NEED_CLARIFICATION | 94.3% |
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- | WRONG_ANSWER | 97.0% |
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- | WANT_DIFFERENT | 88.6% |
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- ## Training Data
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- **Dataset**: [rootfs/user-satisfaction-dataset](https://huggingface.co/datasets/rootfs/user-satisfaction-dataset)
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- | Split | Examples |
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- |-------|----------|
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- | Train | 13,422 |
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- | Validation | 1,494 |
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- | Adversarial Test | 103 |
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- ## Use Cases
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- ### Semantic Routing
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- ### Quality Monitoring
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- Track satisfaction rates across your conversational AI system.
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- ### Feedback Loop
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- Automatically categorize user feedback for model improvement.
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- ## Training Details
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- | Parameter | Value |
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- |-----------|-------|
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- | Base Model | answerdotai/ModernBERT-base |
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- | Epochs | 10 |
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- | Learning Rate | 2e-5 |
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- | Batch Size | 16 |
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- | Max Sequence Length | 128 |
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- ## Citation
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  ## License
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  Apache 2.0
 
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  | `WRONG_ANSWER` | System provided incorrect information | "No, that's wrong", "That's not right" |
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  | `WANT_DIFFERENT` | User wants alternative options | "Show me others", "What else?" |
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  ## License
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  Apache 2.0