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Version: v1.2.0

Compare a project's experiments

You can compare experiments in a project to understand their similarities and differences. For example, comparing experiments in one project can help you visually understand similarities in the experiments learning rate, training batch loss, validation batch loss, and validation metric.

Instructions​

To compare experiments in a project, consider the following instructions:

  1. In the H2O Hydrogen Torch navigation menu, click view projects.
  2. In the projects table, click the project name containing the experiments you want to compare.
  3. Click Compare experiments.
  4. In the experiments table, select the experiments you want to compare.
  5. Click Compare experiments.
    Note

    After comparing experiments, H2O Hydrogen Torch displays the following two tabs: Charts and Config.

Charts​

After comparing a set of experiments from a project, several charts in the Charts tab become available to understand the similarities and differences between the experiment's learning rate, train batch loss, validation batch loss, and validation metric. Available charts are as follows:

Learning rate​

The Learning Rate graph displays the learning rate of all experiments throughout the training process visualized after each training batch.

learning-rate.png

Train batch loss​

The Train batch loss graph displays the current training loss of all experiments throughout the training process visualized after each training batch.

train-batch-loss.png

Validation batch loss​

The Validation batch loss graph displays the current validation loss of all experiments throughout the training process. Loss is calculated as the average of all validation batches. By default, it is calculated and visualized after each training epoch, but this frequency can be adjusted via the Evaluation epochs setting when creating an experiment.

validation-batch-loss.png

Validation {metric}​

The Validation {Metric} graph displays the current validation metric of all experiments throughout the training process. In this case, the {Metric} refers to the selected metric for the problem type (e.g., MAE for an image regression experiment). {Metric} is calculated on full validation set predictions. By default, it is calculated and visualized after each training epoch, but this frequency can be adjusted via the Evaluation epochs setting when creating an experiment.

validation-metric.png

Config​

After comparing a set of experiments from a project, a comparison table becomes available, highlighting similarities and differences between compared experiments.

To view only differences in the comparison table:

  1. Click the Show differences only toggle.
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