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Model Description

This model adapts Moritz Laurer's zero shot base model for political texts. It is currently trained for zero-shot classification of stances towards political groups and people, although it should also preform well for topic and issue stance classification. Further capabilities will be added and benchmarked as more training data is developed.

Training Data

The model was trained using the PoliStance Affect dataset. The data contains ~27,000 political texts about U.S. politicians and political groups that have been triple coded for stance. The test set contains documents about six politicians that were not included in the training set in order to evaluate zero-shot classification performance.


Results below are performance on the PoliStance Affect test set.

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184M params
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Dataset used to train mlburnham/deberta-v3-base-polistance-affect-v1.0