ultralytics 8.0.196 instance-mean Segment loss (#5285)

Co-authored-by: Andy <39454881+yermandy@users.noreply.github.com>

docs/yolov5/tutorials/transfer_learning_with_frozen_layers.md

@@ -4,8 +4,7 @@ description: Learn to freeze YOLOv5 layers for efficient transfer learning. Opti
 keywords: YOLOv5, freeze layers, transfer learning, model retraining, Ultralytics
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-📚 This guide explains how to **freeze** YOLOv5 🚀 layers when **transfer learning**. Transfer learning is a useful way to quickly retrain a model on new data without having to retrain the entire network. Instead, part of the initial weights are frozen in place, and the rest of the weights are used to compute loss and are updated by the optimizer. This requires less resources than normal training and allows for faster training times, though it may also result in reductions to final trained accuracy.
-UPDATED 25 September 2022.
+📚 This guide explains how to **freeze** YOLOv5 🚀 layers when **transfer learning**. Transfer learning is a useful way to quickly retrain a model on new data without having to retrain the entire network. Instead, part of the initial weights are frozen in place, and the rest of the weights are used to compute loss and are updated by the optimizer. This requires less resources than normal training and allows for faster training times, though it may also result in reductions to final trained accuracy. UPDATED 25 September 2022.
 
 ## Before You Start