Update README.md

README.md

@@ -1,6 +1,6 @@
 ---
 title: Top5 Error Rate
-emoji: 👁
+emoji: 📈
 colorFrom: yellow
 colorTo: blue
 sdk: gradio
@@ -30,11 +30,15 @@ At minimum, this metric requires predictions and references as inputs.
 
 ```python
 accuracy_metric = evaluate.load("Aye10032/top5_error_rate")
-results = accuracy_metric.compute(references=[[0, 1, 2, 3, 4]], predictions=[0])
+
+labels: torch.Tensor = batch_data['labels']
+train_output = model(datas)
+
+results = accuracy_metric.compute(references=train_output.cpu(), predictions=labels)
 print(results)
 ```
 output is
 
 ```
-{'top5_error_rate': 0.0}
+{'top5_error_rate': ..., 'accuracy': ...}
 ```