[DOC] LITE Time classifier metrics (#2464)

State that Keras Metrics class objects (and functions) can be used. Also link to
the Keras documentation.

aeon/classification/deep_learning/_lite_time.py

@@ -96,11 +96,13 @@ class LITETimeClassifier(BaseClassifier):
         The keras optimizer used for training.
     loss : str, default = "categorical_crossentropy"
         The name of the keras training loss.
-    metrics : str or list[str], default="accuracy"
-        The evaluation metrics to use during training. If
-        a single string metric is provided, it will be
-        used as the only metric. If a list of metrics are
-        provided, all will be used for evaluation.
+    metrics : str or list[str|function|keras.metrics.Metric], default="accuracy"
+        the evaluation metrics to use during training. each of this can be a
+        string, function or a keras.metrics.metric instance (for details, see
+        https://keras.io/api/metrics/).
+        if a single string metric is provided, it will be used as the only
+        metric. if a list of metrics are provided, all will be used for
+        evaluation.
 
     References
     ----------
@@ -398,11 +400,13 @@ class IndividualLITEClassifier(BaseDeepClassifier):
         The keras optimizer used for training.
     loss : str, default = "categorical_crossentropy"
         The name of the keras training loss.
-    metrics : str or list[str], default="accuracy"
-        The evaluation metrics to use during training. If
-        a single string metric is provided, it will be
-        used as the only metric. If a list of metrics are
-        provided, all will be used for evaluation.
+    metrics : str or list[str|function|keras.metrics.Metric], default="accuracy"
+        the evaluation metrics to use during training. each of this can be a
+        string, function or a keras.metrics.metric instance (for details, see
+        https://keras.io/api/metrics/).
+        if a single string metric is provided, it will be used as the only
+        metric. if a list of metrics are provided, all will be used for
+        evaluation.
 
     References
     ----------