Add evaluation results on autoevaluate/mnist-sample dataset

README.md

@@ -20,6 +20,63 @@ model-index:
     - name: Accuracy
       type: accuracy
       value: 0.9833333333333333
+  - task:
+      type: image-classification
+      name: Image Classification
+    dataset:
+      name: autoevaluate/mnist-sample
+      type: autoevaluate/mnist-sample
+      config: autoevaluate--mnist-sample
+      split: test
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.95
+      verified: true
+    - name: Precision Macro
+      type: precision
+      value: 0.9478535353535353
+      verified: true
+    - name: Precision Micro
+      type: precision
+      value: 0.95
+      verified: true
+    - name: Precision Weighted
+      type: precision
+      value: 0.9510353535353535
+      verified: true
+    - name: Recall Macro
+      type: recall
+      value: 0.9530555555555555
+      verified: true
+    - name: Recall Micro
+      type: recall
+      value: 0.95
+      verified: true
+    - name: Recall Weighted
+      type: recall
+      value: 0.95
+      verified: true
+    - name: F1 Macro
+      type: f1
+      value: 0.9496669557378175
+      verified: true
+    - name: F1 Micro
+      type: f1
+      value: 0.9500000000000001
+      verified: true
+    - name: F1 Weighted
+      type: f1
+      value: 0.9496869212452598
+      verified: true
+    - name: loss
+      type: loss
+      value: 0.12397973984479904
+      verified: true
+    - name: matthews_correlation
+      type: matthews_correlation
+      value: 0.9442456228021371
+      verified: true
 ---
 
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