commonMain.com.xebia.functional.openai.generated.model.FineTuningJobCheckpointMetrics.kt Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of xef-openai-client Show documentation
Show all versions of xef-openai-client Show documentation
Building applications with LLMs through composability in Kotlin
The newest version!
/**
*
* Please note:
* This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
* Do not edit this file manually.
*
*/
@file:Suppress(
"ArrayInDataClass",
"EnumEntryName",
"RemoveRedundantQualifierName",
"UnusedImport"
)
package com.xebia.functional.openai.generated.model
import kotlinx.serialization.Serializable
import kotlinx.serialization.SerialName
import kotlinx.serialization.Contextual
import kotlin.js.JsName
import kotlinx.serialization.json.*
/**
* Metrics at the step number during the fine-tuning job.
*
* @param step
* @param trainLoss
* @param trainMeanTokenAccuracy
* @param validLoss
* @param validMeanTokenAccuracy
* @param fullValidLoss
* @param fullValidMeanTokenAccuracy
*/
@Serializable
data class FineTuningJobCheckpointMetrics (
@SerialName(value = "step") val step: kotlin.Double? = null,
@SerialName(value = "train_loss") val trainLoss: kotlin.Double? = null,
@SerialName(value = "train_mean_token_accuracy") val trainMeanTokenAccuracy: kotlin.Double? = null,
@SerialName(value = "valid_loss") val validLoss: kotlin.Double? = null,
@SerialName(value = "valid_mean_token_accuracy") val validMeanTokenAccuracy: kotlin.Double? = null,
@SerialName(value = "full_valid_loss") val fullValidLoss: kotlin.Double? = null,
@SerialName(value = "full_valid_mean_token_accuracy") val fullValidMeanTokenAccuracy: kotlin.Double? = null
) {
}