Model Type | affective analysis, instruction-following |
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Use Cases |
Areas: | |
Applications: | Sentimental polarity classification, Categorical emotions classification, Sentiment strength regression, Emotion intensity regression |
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Primary Use Cases: | Affective classification, Sentiment analysis |
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Limitations: | Challenges in application due to bias and over-generalization |
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Considerations: | Adjust task description according to specific task. |
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Supported Languages | |
Training Details |
Data Sources: | AAID instruction tuning data |
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Methodology: | |
Model Architecture: | Finetuned based on OPT-13B |
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Safety Evaluation |
Risk Categories: | potential bias, incorrect predictions, over-generalization |
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Ethical Considerations: | Potential bias and over-generalization illustrated as possible risks. |
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Responsible Ai Considerations |
Fairness: | Bias such as gender gaps indicated. |
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Mitigation Strategies: | Challenges acknowledged in applying in real-world scenarios. |
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Input Output | |