giufo
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xlm-roberta-farpo-protest-identification-classifier

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Evaluation

Accuracy: 0.80
Weighted F-score: 0.80
Individual F-scores: 0.78/0.81
Precision: 0.81/0.79
Recall: 0.76/0.83
AUC: 0.80

Paper

Title: Automating Protest Event Analysis: A Transformer-Based Hybrid Approach
Authors: Formisano, G., Froio, C., Castelli Gattinara, P.
Status: Conditionally accepted for publication
Journal: Political Science Research & Methods
Cite as: Formisano, G., Froio, C., Castelli Gattinara, P. (conditionally accepted). Automating Protest Event Analysis: A Transformer-Based Hybrid Approach. Political Science Research & Methods.

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0.3B params

Tensor type

F32

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Dataset used to train giufo/xlm-roberta-farpo-protest-identification-classifier

Collection including giufo/xlm-roberta-farpo-protest-identification-classifier

Farpo Collection

All datasets and models for Formisano, Froio, and Castelli Gattinara’s Automating Protest Event Analysis. • 6 items • Updated Jun 15