NewsRecLib provides several evaluation metrics, for evaluating recommendation models on the following dimensions: classification, ranking, diversity, and personalization. Note that NewsRecLib relies on TorchMetrics for the metric implementation. Custom metrics are built by extending the Metric class.
The user can add any metric available in All TorchMetrics or implement a new one, following this guide.