This algorithm is a community detection algorithm.
What metric are you looking for, I must imagine it relates to your specific use case, since this is just an algorithm which (assuming property implemented) just gives it's output results.
If you have some form of ground truth community information for your dataset and want to evaluate if label propagation is a reasonable community detection algorithm to use with your dataset you could create a metric around that information using the true/false positives, and true/false negative information, in the form of AUC ROC analysis.
This is discussed in the Neo4j Graph Algorithms book and there is also a lot of information online about AUC ROC if you google it.
Connecting with duplicate for reference: https://stackoverflow.com/questions/63520403/neo4j-metric-for-label-propagation-algorithm-lpa