/
t_few_training_config.go
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/
t_few_training_config.go
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// Copyright (c) 2016, 2018, 2024, Oracle and/or its affiliates. All rights reserved.
// This software is dual-licensed to you under the Universal Permissive License (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl or Apache License 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose either license.
// Code generated. DO NOT EDIT.
// Generative AI Service Management API
//
// OCI Generative AI is a fully managed service that provides a set of state-of-the-art, customizable large language models (LLMs) that cover a wide range of use cases for text generation, summarization, and text embeddings.
// Use the Generative AI service management API to create and manage DedicatedAiCluster, Endpoint, Model, and WorkRequest in the Generative AI service. For example, create a custom model by fine-tuning an out-of-the-box model using your own data, on a fine-tuning dedicated AI cluster. Then, create a hosting dedicated AI cluster with an endpoint to host your custom model.
// To access your custom model endpoints, or to try the out-of-the-box models to generate text, summarize, and create text embeddings see the Generative AI Inference API (https://docs.cloud.oracle.com/#/en/generative-ai-inference/latest/).
// To learn more about the service, see the Generative AI documentation (https://docs.cloud.oracle.com/iaas/Content/generative-ai/home.htm).
//
package generativeai
import (
"encoding/json"
"fmt"
"github.com/oracle/oci-go-sdk/v65/common"
"strings"
)
// TFewTrainingConfig The TFEW training method hyperparameters.
type TFewTrainingConfig struct {
// The maximum number of training epochs to run for.
TotalTrainingEpochs *int `mandatory:"false" json:"totalTrainingEpochs"`
// The initial learning rate to be used during training
LearningRate *float64 `mandatory:"false" json:"learningRate"`
// The batch size used during training.
TrainingBatchSize *int `mandatory:"false" json:"trainingBatchSize"`
// Stop training if the loss metric does not improve beyond 'early_stopping_threshold' for this many times of evaluation.
EarlyStoppingPatience *int `mandatory:"false" json:"earlyStoppingPatience"`
// How much the loss must improve to prevent early stopping.
EarlyStoppingThreshold *float64 `mandatory:"false" json:"earlyStoppingThreshold"`
// Determines how frequently to log model metrics.
// Every step is logged for the first 20 steps and then follows this parameter for log frequency. Set to 0 to disable logging the model metrics.
LogModelMetricsIntervalInSteps *int `mandatory:"false" json:"logModelMetricsIntervalInSteps"`
}
// GetTotalTrainingEpochs returns TotalTrainingEpochs
func (m TFewTrainingConfig) GetTotalTrainingEpochs() *int {
return m.TotalTrainingEpochs
}
// GetLearningRate returns LearningRate
func (m TFewTrainingConfig) GetLearningRate() *float64 {
return m.LearningRate
}
// GetTrainingBatchSize returns TrainingBatchSize
func (m TFewTrainingConfig) GetTrainingBatchSize() *int {
return m.TrainingBatchSize
}
// GetEarlyStoppingPatience returns EarlyStoppingPatience
func (m TFewTrainingConfig) GetEarlyStoppingPatience() *int {
return m.EarlyStoppingPatience
}
// GetEarlyStoppingThreshold returns EarlyStoppingThreshold
func (m TFewTrainingConfig) GetEarlyStoppingThreshold() *float64 {
return m.EarlyStoppingThreshold
}
// GetLogModelMetricsIntervalInSteps returns LogModelMetricsIntervalInSteps
func (m TFewTrainingConfig) GetLogModelMetricsIntervalInSteps() *int {
return m.LogModelMetricsIntervalInSteps
}
func (m TFewTrainingConfig) String() string {
return common.PointerString(m)
}
// ValidateEnumValue returns an error when providing an unsupported enum value
// This function is being called during constructing API request process
// Not recommended for calling this function directly
func (m TFewTrainingConfig) ValidateEnumValue() (bool, error) {
errMessage := []string{}
if len(errMessage) > 0 {
return true, fmt.Errorf(strings.Join(errMessage, "\n"))
}
return false, nil
}
// MarshalJSON marshals to json representation
func (m TFewTrainingConfig) MarshalJSON() (buff []byte, e error) {
type MarshalTypeTFewTrainingConfig TFewTrainingConfig
s := struct {
DiscriminatorParam string `json:"trainingConfigType"`
MarshalTypeTFewTrainingConfig
}{
"TFEW_TRAINING_CONFIG",
(MarshalTypeTFewTrainingConfig)(m),
}
return json.Marshal(&s)
}