Add Records to an Experiment Recorder
In this article, we will go over recording experiment data through the experiment recorder during the model training (experiment) step. The instructions to create an experiment recorder are here.
An ExperimentRecorder
has the following key methods:
start()
: start the model training and should be called just before the model training code begins executing.stop()
: end the model training and should be called right after the model training code has finished.add_record({"key": value})
: The API used to record metrics with MarkovML. Herekey
could be anystring
andvalue
could be anynumeric
value. Theadd_record
should be called the training loop to record metrics likeloss
andaccuracy
. These recorded metrics will be available as charts in the MarkovML app.
The recorder instance can also be utilized as a context manager using the with
statement to avoid explicit calls to the start()
and stop()
methods.
Follow the sample code pattern below to add records to the experiment tracking recorder.
Markov has easy integrations with many popular machine-learning frameworks. Please refer to the integration section on the next page for details.
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