There are the metrics to compare models, You can read it as, Top 1 Accuracy, Top 5 Accuracy. In Imagenet there are 1000 classes. If the image you gave is of “Cat” and cat comes in Top 5 predictions then it is acc@5. If you want to be strict and want the class you are detecting, “Cat” in this case should come as 1st detection with highest confidence. Then it is acc@1.
Based on above theory, you can see acc@5 is more than acc@1 for all the models. Predicted class is Correct if we look at top 5 predictions but wrong if we take first prediction as result.
If you have less than 5 classes, then obviously you cant use top 5 accuracy metric.
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