fix passing of metric to log function

chebai/models/base.py

@@ -122,8 +122,10 @@ def _log_metrics(self, prefix, metrics, batch_size):
         # don't use sync_dist=True if the metric is a torchmetrics-metric
         # (see https://github.com/Lightning-AI/pytorch-lightning/discussions/6501#discussioncomment-569757)
         for metric_name, metric in metrics.items():
-            m = metric.compute()
+            m = None  # m = metric.compute()
             if isinstance(m, dict):
+                # todo: is this case needed? it requires logging values directly which does not give accurate results
+                # with the current metric-setup
                 for k, m2 in m.items():
                     self.log(
                         f"{prefix}{metric_name}{k}",
@@ -137,7 +139,7 @@ def _log_metrics(self, prefix, metrics, batch_size):
             else:
                 self.log(
                     f"{prefix}{metric_name}",
-                    m,
+                    metric,
                     batch_size=batch_size,
                     on_step=False,
                     on_epoch=True,