Keras

MarkovML integrates with various machine-learning frameworks to automatically track experiments. When using auto_record() for Keras models, the following details are recorded:

1. Hyper-parameters: Details provided by keras.model.optimizer.get_config().
2. 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:

1. name: Keras model name.
2. notes: Notes for future reference. (optional)
3. 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