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loss: <list[str]> (Optional)

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Description

The loss type to use during model optimization depending on the task type.

Available Options:

Task TypeAvailable loss options
Binary Classification/Multilabel Classificationbinary_cross_entropy (default)
focal
Multiclass Classificationcross_entropy (default)
Regression/Forecastingmae
mse
huber (default)
Temporal Link Predictioncross_entropy (default)
Static Link Predictioncross_entropy (default)
Multilabel Rankingcross_entropy (default)

By default, focal loss uses an alpha value of 0.25 (the weighting factor to balance positive vs. negative examples), and a gamma value of 2.0 (the balance between easy vs. hard examples). You can further customize this in the model plan by replacing the string by a dictionary:

loss:
- name: focal
  alpha: 0.5
  gamma: 4.0

By default, huber loss uses a delta value of 1.0. You can further customize this in the model plan by replacing the string by a dictionary:

loss:
- name: huber
  delta: 2.0

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Supported Task Types

  • All
lr_schedulermajority_sampling_ratio