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mlburnham/deberta-v3-large-polistance-affect-v1.1
deberta-v3-large-polistance-affect-v1.1 is a zero-shot classification model from mlburnham. Use it when you need labels you did not train the model on. It is set up for transformers. The card lists the license as mit.
This model adapts Moritz Laurer's zero shot 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 topi…
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From the Hugging Face model README
This model adapts Moritz Laurer's zero shot 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.
The model was trained using the PoliStance Affect and PoliStance Affect_QT datasets.
The test set for both datasets 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.
<img src="https://cdn-uploads.huggingface.co/production/uploads/64d0341901931c60161f2a06/NLJtILuPLKtxN0bJJwD0C.png" width="750" height="500" /> <img src="https://cdn-uploads.huggingface.co/production/uploads/64d0341901931c60161f2a06/4tOqiINS6BWItRklrqkgY.png" width="750" height="500" />