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README.md
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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<!-- Provide a quick summary of what the model is/does. -->
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SetFit/CR
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{'micro': 0.901595744680851, 'macro': 0.8922009995738251, 'weighted': 0.9010032832777053}
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SetFit/sst2
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{'micro': 0.9203734211971444, 'macro': 0.9203422887733446, 'weighted': 0.9203396944046945}
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SetFit/sst5
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{'micro': 0.43936651583710407, 'macro': 0.41543751108645566, 'weighted': 0.4312698680247299}
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AmazonScience/massive
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{'micro': 0.3954270342972428, 'macro': 0.386758540904241, 'weighted': 0.3968475639919267}
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stanfordnlp/imdb
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positive ['negative', 'positive']
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{'micro': 0.9466, 'macro': 0.9465995193956745, 'weighted': 0.9465993912345211}
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SetFit/20_newsgroups
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{'micro': 0.3883430695698354, 'macro': 0.3697801544810726, 'weighted': 0.37658673042441476}
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SetFit/enron_spam
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{'micro': 0.544, 'macro': 0.5432692307692308, 'weighted': 0.5431230769230769}
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PolyAI/banking77
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{'micro': 0.2623376623376623, 'macro': 0.29566833181387553, 'weighted': 0.2956683318138756}
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takala/financial_phrasebank
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{'micro': 0.7098056537102474, 'macro': 0.585169173529447, 'weighted': 0.6875727976631041}
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ag_news
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{'micro': 0.7493421052631579, 'macro': 0.7292800055299333, 'weighted': 0.7292800055299334}
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dair-ai/emotion
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{'micro': 0.548, 'macro': 0.46040686059760794, 'weighted': 0.5544195013346873}
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MoritzLaurer/cap_sotu
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{'micro': 0.3746, 'macro': 0.38022241408794133, 'weighted': 0.3746413725365648}
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cornell-movie-review-data/rotten_tomatoes
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{'micro': 0.801125703564728, 'macro': 0.8011145022582223, 'weighted': 0.8011145022582222}
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Average Score: 0.5943268871385287
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## Model Details
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