add classes and accuracy metrics
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README.md
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license: mit
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---
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license: mit
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datasets:
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- copenlu/mm-framing
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RoBERTa topic classifier for topic injection into the Longformer Framing Classifier. Classifies input text into one of 19 discrete topics:
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1. Business & Economy
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2. Crime & Safety
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3. Disaster & Accidents
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4. Education
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5. Entertainment
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6. Environment & Nature
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7. Health
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8. Immigration
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9. Infrastructure & Transport
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10. Legal
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11. Lifestyle & Culture
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12. Media
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13. Other/Unknown
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14. Politics
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15. Science & Technology
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16. Social Issues
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17. Sports
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18. War & Conflict
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19. Weather
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These were derived empirically by consolidating the unstructured gpt_topic field from the mm_framing silver dataset into
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discrete categories based on similarity.
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Achieved a 76.4% validation accuracy on 64,000 examples, which was deemed sufficient for assisting domain-specific reasoning in downstream model.
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