diff --git a/docs/en/reference/utils/callbacks/mlflow.md b/docs/en/reference/utils/callbacks/mlflow.md
index 2abdb3db..e3fab6c5 100644
--- a/docs/en/reference/utils/callbacks/mlflow.md
+++ b/docs/en/reference/utils/callbacks/mlflow.md
@@ -15,6 +15,10 @@ keywords: Ultralytics, MLflow, Callbacks, on_pretrain_routine_end, on_train_end,
 
 <br><br>
 
+## ::: ultralytics.utils.callbacks.mlflow.on_train_epoch_end
+
+<br><br>
+
 ## ::: ultralytics.utils.callbacks.mlflow.on_fit_epoch_end
 
 <br><br>
diff --git a/docs/en/reference/utils/callbacks/tensorboard.md b/docs/en/reference/utils/callbacks/tensorboard.md
index 075c9363..74fb3b15 100644
--- a/docs/en/reference/utils/callbacks/tensorboard.md
+++ b/docs/en/reference/utils/callbacks/tensorboard.md
@@ -27,7 +27,7 @@ keywords: Ultralytics, YOLO, documentation, callback utilities, log_scalars, on_
 
 <br><br>
 
-## ::: ultralytics.utils.callbacks.tensorboard.on_batch_end
+## ::: ultralytics.utils.callbacks.tensorboard.on_train_epoch_end
 
 <br><br>
 
diff --git a/ultralytics/utils/callbacks/clearml.py b/ultralytics/utils/callbacks/clearml.py
index dfb22039..dc0b2716 100644
--- a/ultralytics/utils/callbacks/clearml.py
+++ b/ultralytics/utils/callbacks/clearml.py
@@ -90,8 +90,10 @@ def on_train_epoch_end(trainer):
         if trainer.epoch == 1:
             _log_debug_samples(sorted(trainer.save_dir.glob('train_batch*.jpg')), 'Mosaic')
         # Report the current training progress
-        for k, v in trainer.validator.metrics.results_dict.items():
+        for k, v in trainer.label_loss_items(trainer.tloss, prefix='train').items():
             task.get_logger().report_scalar('train', k, v, iteration=trainer.epoch)
+        for k, v in trainer.lr.items():
+            task.get_logger().report_scalar('lr', k, v, iteration=trainer.epoch)
 
 
 def on_fit_epoch_end(trainer):
@@ -102,6 +104,8 @@ def on_fit_epoch_end(trainer):
                                         series='Epoch Time',
                                         value=trainer.epoch_time,
                                         iteration=trainer.epoch)
+        for k, v in trainer.metrics.items():
+            task.get_logger().report_scalar('val', k, v, iteration=trainer.epoch)
         if trainer.epoch == 0:
             from ultralytics.utils.torch_utils import model_info_for_loggers
             for k, v in model_info_for_loggers(trainer).items():
diff --git a/ultralytics/utils/callbacks/mlflow.py b/ultralytics/utils/callbacks/mlflow.py
index 05f5aedd..91dcff5e 100644
--- a/ultralytics/utils/callbacks/mlflow.py
+++ b/ultralytics/utils/callbacks/mlflow.py
@@ -32,7 +32,9 @@ try:
 
     assert hasattr(mlflow, '__version__')  # verify package is not directory
     from pathlib import Path
+
     PREFIX = colorstr('MLflow: ')
+    SANITIZE = lambda x: {k.replace('(', '').replace(')', ''): float(v) for k, v in x.items()}
 
 except (ImportError, AssertionError):
     mlflow = None
@@ -81,11 +83,18 @@ def on_pretrain_routine_end(trainer):
                        f'{PREFIX}WARNING ⚠️ Not tracking this run')
 
 
+def on_train_epoch_end(trainer):
+    """Log training metrics at the end of each train epoch to MLflow."""
+    if mlflow:
+        mlflow.log_metrics(metrics=SANITIZE(trainer.label_loss_items(trainer.tloss, prefix='train')),
+                           step=trainer.epoch)
+        mlflow.log_metrics(metrics=SANITIZE(trainer.lr), step=trainer.epoch)
+
+
 def on_fit_epoch_end(trainer):
     """Log training metrics at the end of each fit epoch to MLflow."""
     if mlflow:
-        sanitized_metrics = {k.replace('(', '').replace(')', ''): float(v) for k, v in trainer.metrics.items()}
-        mlflow.log_metrics(metrics=sanitized_metrics, step=trainer.epoch)
+        mlflow.log_metrics(metrics=SANITIZE(trainer.metrics), step=trainer.epoch)
 
 
 def on_train_end(trainer):
diff --git a/ultralytics/utils/callbacks/tensorboard.py b/ultralytics/utils/callbacks/tensorboard.py
index c1fce53b..86a50667 100644
--- a/ultralytics/utils/callbacks/tensorboard.py
+++ b/ultralytics/utils/callbacks/tensorboard.py
@@ -58,9 +58,10 @@ def on_train_start(trainer):
         _log_tensorboard_graph(trainer)
 
 
-def on_batch_end(trainer):
-    """Logs scalar statistics at the end of a training batch."""
+def on_train_epoch_end(trainer):
+    """Logs scalar statistics at the end of a training epoch."""
     _log_scalars(trainer.label_loss_items(trainer.tloss, prefix='train'), trainer.epoch + 1)
+    _log_scalars(trainer.lr, trainer.epoch + 1)
 
 
 def on_fit_epoch_end(trainer):
@@ -72,4 +73,4 @@ callbacks = {
     'on_pretrain_routine_start': on_pretrain_routine_start,
     'on_train_start': on_train_start,
     'on_fit_epoch_end': on_fit_epoch_end,
-    'on_batch_end': on_batch_end} if SummaryWriter else {}
+    'on_train_epoch_end': on_train_epoch_end} if SummaryWriter else {}