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Log metrics#

A metric can be accuracy, MSE, or any numerical value. You can log scores and metrics as

  • single values, with = assignment.
  • series of values, with the append() method. Each append() call adds a value to the field.

Neptune displays all value series as charts.

Log scores (single value)
run["score"] = 0.97
run["test/acc"] = 0.97
Log metrics (series of values)
for epoch in range(100):
    # your training loop
    acc = ...
    loss = ...
    metric = ...

    run["train/accuracy"].append(acc)
    run["train/loss"].append(loss)
    run["metric"].append(metric)

See in Neptune 

Tip

In the experiments table, you can group and sort runs by the value of any field.

Setting custom index values#

You can specify custom index values with the step argument:

run["metric"].append(
    value=acc,
    step=i,
)

The entries logged for step must be strictly increasing Int or Float values.

This is effectively like setting custom values for the x axis of a chart.

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