FineTuneJob - fixing of the Either types

cequence-io · Nov 24, 2023 · 734d5d0 · 734d5d0
1 parent dfd6a99
commit 734d5d0
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Showing 2 changed files with 4 additions and 4 deletions.
diff --git a/openai-core/src/main/scala/io/cequence/openaiscala/domain/response/FineTuneJob.scala b/openai-core/src/main/scala/io/cequence/openaiscala/domain/response/FineTuneJob.scala
@@ -47,10 +47,10 @@ case class FineTuneEvent(
 case class FineTuneHyperparams(
   // Number of examples in each batch or "auto".
   // A larger batch size means that model parameters are updated less frequently, but with lower variance.
-  batch_size: Option[Either[String, Int]],
+  batch_size: Option[Either[Int, String]],
 
   // Scaling factor for the learning rate or "auto". A smaller learning rate may be useful to avoid overfitting.
-  learning_rate_multiplier: Option[Either[String, Int]],
+  learning_rate_multiplier: Option[Either[Int, String]],
 
   // the number of epochs or "auto" (if not specified initially)
   // "auto" decides the optimal number of epochs based on the size of the dataset.

diff --git a/...-core/src/main/scala/io/cequence/openaiscala/domain/settings/CreateFineTuneSettings.scala b/...-core/src/main/scala/io/cequence/openaiscala/domain/settings/CreateFineTuneSettings.scala
@@ -9,11 +9,11 @@ case class CreateFineTuneSettings(
   // Number of examples in each batch or "auto".
   // A larger batch size means that model parameters are updated less frequently, but with lower variance.
   // Defaults to auto
-  batch_size: Option[Int],
+  batch_size: Option[Int] = None,
 
   // Scaling factor for the learning rate or "auto". A smaller learning rate may be useful to avoid overfitting.
   // Defaults to auto
-  learning_rate_multiplier: Option[Int],
+  learning_rate_multiplier: Option[Int] = None,
 
   // The number of epochs to train the model for.
   // An epoch refers to one full cycle through the training dataset.