Keras
MarkovML integrates with various machine-learning frameworks to automatically track experiments. When using auto_record()
for Keras models, the following details are recorded:
- Hyper-parameters: Details provided by
keras.model.optimizer.get_config()
. - Metrics: Epoch-time vs. epoch; Loss vs. epoch; Accuracy vs. epoch; Learning rate vs. epoch (if the adaptive learning rate is used with
LearningRateScheduler
callback).
To utilize this feature, simply call markov.keras.auto_record()
and provide the following:
name
: Keras model name.notes
: Notes for future reference. (optional)project_id
: Project ID of the Project you are working on.
Sample Code
import markov
import keras
MODEL_NAME = "My Test Keras Model"
markov.keras.auto_record(
name=MODEL_NAME,
notes="Testing Keras Auto Record with MarkovML",
project_id="some_project_id"
)
# Continue creating keras model and training
Updated 6 days ago
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