Update yolov8-c3k2-2222-0.25-True-C2PSA.yaml

ultralytics/cfg/models/exp/yolov8-c3k2-2222-0.25-True-C2PSA.yaml

@@ -5,8 +5,8 @@
 nc: 80 # number of classes
 scales: # model compound scaling constants, i.e. 'model=yolov8n.yaml' will call yolov8.yaml with scale 'n'
   # [depth, width, max_channels]
-  n: [0.50, 0.25, 512] # YOLOv8n summary: 225 layers,  3157200 parameters,  3157184 gradients,   8.9 GFLOPs
-  s: [0.50, 0.50, 512] # YOLOv8s summary: 225 layers, 11166560 parameters, 11166544 gradients,  28.8 GFLOPs
+  n: [0.50, 0.25, 1024] # YOLOv8n summary: 225 layers,  3157200 parameters,  3157184 gradients,   8.9 GFLOPs
+  s: [0.50, 0.50, 1024] # YOLOv8s summary: 225 layers, 11166560 parameters, 11166544 gradients,  28.8 GFLOPs
   m: [0.50, 1.00, 512] # YOLOv8m summary: 295 layers, 25902640 parameters, 25902624 gradients,  79.3 GFLOPs
   l: [1.00, 1.00, 512] # YOLOv8l summary: 365 layers, 43691520 parameters, 43691504 gradients, 165.7 GFLOPs
   x: [1.00, 1.50, 512] # YOLOv8x summary: 365 layers, 68229648 parameters, 68229632 gradients, 258.5 GFLOPs
@@ -24,7 +24,7 @@ backbone:
   - [-1, 1, Conv, [1024, 3, 2]] # 7-P5/32
   - [-1, 2, C3k2, [1024, True]]
   - [-1, 1, SPPF, [1024, 5]] # 9
-  - [-1, 1, C2PSA, [1024]] # 10
+  - [-1, 2, C2PSA, [1024]] # 10
 
 # YOLOv8.0n head
 head: