Align metadata with AI Portal schemas

Replace the mixed model/benchmark document with standalone artifact metadata and an accuracy-only vision-detection report. Performance is omitted because the available timing is not the schema-required median end-to-end measurement.

benchmark/accuracy.yaml

@@ -0,0 +1,30 @@
+version: 1.2.0
+report_type: vision-detection
+profile: Arm-Optimized
+created_at: '2026-10-15T17:04:16Z'
+context:
+  target_ref: raspberry-pi-5-8gb
+  runtime:
+    name: Arm Runtime for YOLO26 on Raspberry Pi 5
+    execution_backend: cpu
+    version: 0.1.0
+    config:
+      n_threads: 4
+      optimisations:
+      - XNNPACK
+  dataset:
+    name: COCO 128 BY/SA
+    version: cb1edb8da4ff3cb54d40ecb12d3efecc116ff3de
+    slice: all
+    sample_count: 128
+    reference_url: https://huggingface.co/datasets/Arm/coco-128-by-sa/tree/cb1edb8da4ff3cb54d40ecb12d3efecc116ff3de
+  benchmark:
+    batch_size: 1
+    input_resolution: 640x640
+    num_runs: 128
+    warmup_runs: 0
+accuracy:
+  sub_task: coco_map
+  mAP_50_95_pct: 46.7817
+  mAP_50_pct: 63.2612
+  mAP_75_pct: 49.3637

metadata.yaml

@@ -1,43 +1,18 @@
-# Metadata generated by ARM Model Optimization Pipeline
-version: 1.0.0
-task: vision-detection
-created_at: '2026-09-23T04:33:02Z'
-context:
-  model:
-    id: yolo26n
-    base_model_id: yolo26n
-    profile: Arm-Optimized
-    weight_dtype: fp32
-    model_size_mb: 10.55
-    parameter_count: 2572280
-    format: arm-yolo26n-bundle
-  target:
-    name: Raspberry Pi 5
-    hardware_class: Edge Linux
-    cpu_architecture: arm64
-    cpu_model: Cortex-A76
-    cpu_core_count: 4
-    cpu_clock_ghz: 2.4
-    system_memory_gb: 8
-    os: linux
-    os_version: Raspberry Pi OS Bookworm
-  runtime:
-    name: arm-yolo26n
-    execution_backend: cpu
-    config:
-      optimisations:
-      - XNNPACK
-  dataset:
-    name: COCO 2017
-    sample_count: 128
-    reference_url: https://cocodataset.org/
-    slice: val2017
-  benchmark:
-    batch_size: 1
-    input_resolution: 640x640
-    num_runs: 50
-    warmup_runs: 10
-accuracy:
-  mAP_50_95_pct: 46.15
-  mAP_50_pct: 49.47
-  mAP_75_pct: 42.84
+schema_version: 1.0.0
+report_type: vision-detection
+task_type: object-detection
+title: YOLO26n for Raspberry Pi 5
+description: An Arm-optimized YOLO26n object-detection model for CPU inference on Raspberry Pi 5 using the project-specific Arm Runtime.
+family_name: YOLO26
+id: Arm/Arm-Runtime-for-YOLO26-on-Raspberry-Pi-5
+filename: runtime/arm_yolo26n_pi5_model/model/model.bin
+base_model_id: yolo26n
+vendor: Ultralytics
+base_model_url: https://docs.ultralytics.com/models/yolo26/
+profile: Arm-Optimized
+optimization:
+  optimized_by: Arm
+weight_dtype: fp16
+model_size_mb: 9.193
+parameter_count: 2572280
+format: arm-yolo26n-model