> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wandb.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# How do I log metrics on two different time scales?

To log metrics on two different time scales, log indices like `batch` and `epoch` alongside your metrics. For example, you might log training accuracy per batch and validation accuracy per epoch. Call `run.log({'train_accuracy': 0.9, 'batch': 200})` in one step and `run.log({'val_accuracy': 0.8, 'epoch': 4})` in another. In the UI, set the value you want as the x-axis for each chart. To set a default x-axis for a specific index, use [`Run.define_metric()`](/models/ref/python/experiments/run#define_metric). For the preceding example, use the following code:

```python theme={null}
import wandb

with wandb.init() as run:
    run.define_metric("batch")
    run.define_metric("epoch")

    run.define_metric("train_accuracy", step_metric="batch")
    run.define_metric("val_accuracy", step_metric="epoch")
```

***

<Badge stroke shape="pill" color="orange" size="md">[Experiments](/support/models/tags/experiments)</Badge><Badge stroke shape="pill" color="orange" size="md">[Metrics](/support/models/tags/metrics)</Badge>