README.md

---
title: Top5 Error Rate
emoji: 📈
colorFrom: yellow
colorTo: blue
sdk: gradio
sdk_version: 5.24.0
app_file: app.py
pinned: false
tags:
- evaluate
- metric
---

# Metric Card for Top-5 error rate

## Metric Description

The "top-5 error" is the percentage of times that the target label does not appear among the 5 highest-probability predictions. It can be computed with:
Top-5 Error Rate = 1 - Top-5 Accuracy
or equivalently:
Top-5 Error Rate = (Number of incorrect top-5 predictions) / (Total number of cases processed)
 Where:
- Top-5 Accuracy: The proportion of cases where the true label is among the model's top 5 predicted classes.
- Incorrect top-5 prediction: The true label is not in the top 5 predicted classes (ranked by probability).

## How to Use

At minimum, this metric requires predictions and references as inputs.

```python
accuracy_metric = evaluate.load("Aye10032/top5_error_rate")

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': ..., 'accuracy': ...}
```