Add evaluation results on lewtun/dog_food dataset

README.md

@@ -21,6 +21,63 @@ model-index:
     - name: Accuracy
       type: accuracy
       value: 0.7253333333333334
+  - task:
+      type: image-classification
+      name: Image Classification
+    dataset:
+      name: lewtun/dog_food
+      type: lewtun/dog_food
+      config: lewtun--dog_food
+      split: test
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6866666666666666
+      verified: true
+    - name: Precision Macro
+      type: precision
+      value: 0.7181484576740136
+      verified: true
+    - name: Precision Micro
+      type: precision
+      value: 0.6866666666666666
+      verified: true
+    - name: Precision Weighted
+      type: precision
+      value: 0.7235392474854474
+      verified: true
+    - name: Recall Macro
+      type: recall
+      value: 0.7006250320552644
+      verified: true
+    - name: Recall Micro
+      type: recall
+      value: 0.6866666666666666
+      verified: true
+    - name: Recall Weighted
+      type: recall
+      value: 0.6866666666666666
+      verified: true
+    - name: F1 Macro
+      type: f1
+      value: 0.6690027379410202
+      verified: true
+    - name: F1 Micro
+      type: f1
+      value: 0.6866666666666666
+      verified: true
+    - name: F1 Weighted
+      type: f1
+      value: 0.6647526870157503
+      verified: true
+    - name: loss
+      type: loss
+      value: 0.9549381732940674
+      verified: true
+    - name: matthews_correlation
+      type: matthews_correlation
+      value: 0.5737269361889515
+      verified: true
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You