Semantic run plot legends

Create meaningful legends for run line plots to visually distinguish them based on metrics you log to W&B. Identify trends and patterns based on the highest, lowest, or latest values of a metric across your training and evaluation runs. Runs are bucketed and colored in plots based on the plot’s configured metric, Y value, and number of buckets.

Navigate to your workspace’s settings page to configure the metric-based colors for runs:

1. Navigate to your W&B project.
2. Select the Workspace tab from the project sidebar.
3. Click on the Settings icon (⚙️) in the top right corner.
4. From the drawer, select Runs then select Metric-based colors.
   • From the Metric dropdown, select the metric you want to use for assigning colors to runs.
   • From the Y value dropdown, select the y value you want to use for assigning colors to runs.
   • Set the the number of buckets to a value from 2 to 8.

The following sections describe how to set the metric and y value and as how to customize the buckets used for assigning colors to runs.

Configure a metric

The options in your Metric dropdown are derived from the key-value pairs you log to W&B and default metrics defined by W&B.

Default metrics

• Relative Time (Process): The relative time of the run, measured in seconds since the start of the run.
• Relative Time (Wall): The relative time of the run, measured in seconds since the start of the run, adjusted for wall clock time.
• Wall Time: The wall clock time of the run, measured in seconds since the epoch.
• Step: The step number of the run, which is typically used to track the progress of training or evaluation.

Custom metrics

Color runs and create meaningful plot legends based on custom metrics logged by your training or evaluation scripts. Custom metrics are logged as key-value pairs, where the key is the name of the metric and the value is the metric value.

For example, the following code snippet logs accuracy ("acc" key) and loss ("loss" key) during a training loop:

import wandb
import random

epochs = 10

with wandb.init(project="basic-intro") as run:
  # Block simulates a training loop logging metrics
  offset = random.random() / 5
  for epoch in range(2, epochs):
      acc = 1 - 2 ** -epoch - random.random() / epoch - offset
      loss = 2 ** -epoch + random.random() / epoch + offset

      # Log metrics from your script to W&B
      run.log({"acc": acc, "loss": loss})

Within the Metric dropdown, both "acc" and "loss" are available options.

Configure a y value

You can choose from the following options:

• Latest: Determine color based on Y value at last logged step for each line.
• Max: Color based on highest Y value logged against the metric.
• Min: Color based on lowest Y value logged against the metric.

Customize buckets

Buckets are ranges of values that W&B uses to categorize runs based on the metric you select. Buckets are evenly distributed across the range of values for the specified metric and each bucket is assigned a unique color. Runs that fall within that bucket’s range are displayed in that color.

Consider the following configuration:

• Metric is set to "Accuracy" (abbreviated as "acc").
• Y value is set to "Max"

With this configuration, W&B colors run based on their accuracy values, using the maximum accuracy value logged for each run.

Six buckets are defined for the metric, with each bucket representing a range of accuracy values. Within the Buckets section, the following range of buckets are defined:

• Bucket 1: (Min - 0.5798)
• Bucket 2: (0.5798 - 0.6629)
• Bucket 3: (0.6629 - 0.7460)
• Bucket 4: (0.7460 - 0.8292)
• Bucket 5: (0.8292 - 0.9123)
• Bucket 6: (0.9123 - Max)

In the line plot below, the run with the highest accuracy (0.957) is colored in a deep purple (Bucket 6), while the run with the lowest accuracy (0.7993) is colored in a lighter purple (Bucket 4). The other runs are colored based on their accuracy values, with the color gradient indicating their relative performance.