diff --git a/examples/dynamic_pruning.py b/examples/dynamic_pruning.py
index 0a2545f..2a4e81f 100644
--- a/examples/dynamic_pruning.py
+++ b/examples/dynamic_pruning.py
@@ -46,23 +46,23 @@ if __name__ == "__main__":
     vis = pt.models.VisGLVQ2D(train_ds)
     pruning = pt.models.PruneLoserPrototypes(
         threshold=0.01,  # prune prototype if it wins less than 1%
-        idle_epochs=30,  # pruning too early may cause problems
-        prune_quota_per_epoch=1,  # prune at most 1 prototype per epoch
-        frequency=5,  # prune every fifth epoch
+        idle_epochs=10,  # pruning too early may cause problems
+        prune_quota_per_epoch=5,  # prune at most 5 prototypes per epoch
+        frequency=2,  # prune every second epoch
         verbose=True,
     )
-    es = pt.models.EarlyStopWithoutVal(
-        monitor="loss",
-        min_delta=0.1,
-        patience=3,
+
+    es = pl.callbacks.EarlyStopping(
+        monitor="train_loss",
+        min_delta=0.001,
+        patience=15,
         mode="min",
-        verbose=True,
+        check_on_train_epoch_end=True,
     )
 
     # Setup trainer
     trainer = pl.Trainer.from_argparse_args(
         args,
-        max_epochs=250,
         callbacks=[
             vis,
             pruning,
diff --git a/prototorch/models/__init__.py b/prototorch/models/__init__.py
index a539264..251370c 100644
--- a/prototorch/models/__init__.py
+++ b/prototorch/models/__init__.py
@@ -2,22 +2,10 @@
 
 from importlib.metadata import PackageNotFoundError, version
 
-from .callbacks import (EarlyStopWithoutVal, PrototypeConvergence,
-                        PruneLoserPrototypes)
+from .callbacks import PrototypeConvergence, PruneLoserPrototypes
 from .cbc import CBC, ImageCBC
-from .glvq import (
-    GLVQ,
-    GLVQ1,
-    GLVQ21,
-    GMLVQ,
-    GRLVQ,
-    LGMLVQ,
-    LVQMLN,
-    ImageGLVQ,
-    ImageGMLVQ,
-    SiameseGLVQ,
-    SiameseGMLVQ,
-)
+from .glvq import (GLVQ, GLVQ1, GLVQ21, GMLVQ, GRLVQ, LGMLVQ, LVQMLN,
+                   ImageGLVQ, ImageGMLVQ, SiameseGLVQ, SiameseGMLVQ)
 from .lvq import LVQ1, LVQ21, MedianLVQ
 from .probabilistic import CELVQ, RSLVQ, LikelihoodRatioLVQ
 from .unsupervised import KNN, NeuralGas
diff --git a/prototorch/models/callbacks.py b/prototorch/models/callbacks.py
index 48f40fa..d6643fb 100644
--- a/prototorch/models/callbacks.py
+++ b/prototorch/models/callbacks.py
@@ -4,22 +4,6 @@ import pytorch_lightning as pl
 import torch
 
 
-class EarlyStopWithoutVal(pl.callbacks.EarlyStopping):
-    """Run early stopping at the end of training loop.
-
-    See:
-    https://pytorch-lightning.readthedocs.io/en/latest/common/early_stopping.html
-
-    """
-    def on_validation_end(self, trainer, pl_module):
-        # override this to disable early stopping at the end of val loop
-        pass
-
-    def on_train_end(self, trainer, pl_module):
-        # instead, do it at the end of training loop
-        self._run_early_stopping_check(trainer, pl_module)
-
-
 class PruneLoserPrototypes(pl.Callback):
     def __init__(self,
                  threshold=0.01,