A metric can be accuracy, MSE, or any numerical value. You can log scores and metrics as
- single values, with
- series of values, with the
append()call adds a value to the field.
As of neptune-client
extend() are the preferred methods for logging series of values.
You can upgrade your installation with
pip install -U neptune-client or continue using
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)
In the runs 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
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.