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  # Affective Norms Extrapolation Model for Polish Language
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  ## Model Description
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  This transformer-based model is designed to extrapolate affective norms for Polish words, including metrics such as valence, arousal, dominance, concreteness, age of acquisition, origin, significance, and imageability. It has been finetuned from the Polish RoBerta Model (https://github.com/sdadas/polish-roberta), enhanced with additional layers to predict the affective dimensions. This model was first released as a part of the publication: "Extrapolation of affective norms using transformer-based neural networks and its application to experimental stimuli selection." (Plisiecki, Sobieszek; 2023) [ https://doi.org/10.3758/s13428-023-02212-3 ]
 
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  # Affective Norms Extrapolation Model for Polish Language
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+ ## Disclaimer
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+ This model and other models from the word2vec line are finetuned to predict emotional load for singular words, not longer utterances.
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+ Their accuracy on long-form text is unknown.
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  ## Model Description
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  This transformer-based model is designed to extrapolate affective norms for Polish words, including metrics such as valence, arousal, dominance, concreteness, age of acquisition, origin, significance, and imageability. It has been finetuned from the Polish RoBerta Model (https://github.com/sdadas/polish-roberta), enhanced with additional layers to predict the affective dimensions. This model was first released as a part of the publication: "Extrapolation of affective norms using transformer-based neural networks and its application to experimental stimuli selection." (Plisiecki, Sobieszek; 2023) [ https://doi.org/10.3758/s13428-023-02212-3 ]