Resource: TuningJob
Represents a TuningJob that runs with Google owned models.
name
string
Output only. Identifier. Resource name of a TuningJob. Format: projects/{project}/locations/{location}/tuningJobs/{tuningJob}
tunedModelDisplayName
string
Optional. The display name of the TunedModel
. The name can be up to 128 characters long and can consist of any UTF-8 characters.
description
string
Optional. The description of the TuningJob
.
customBaseModel
string
Optional. The user-provided path to custom model weights. Set this field to tune a custom model. The path must be a Cloud Storage directory that contains the model weights in .safetensors format along with associated model metadata files. If this field is set, the baseModel field must still be set to indicate which base model the custom model is derived from. This feature is only available for open source models.
Output only. The detailed state of the job.
Output only. time when the TuningJob
was created.
Uses RFC 3339, where generated output will always be Z-normalized and uses 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z"
, "2014-10-02T15:01:23.045123456Z"
or "2014-10-02T15:01:23+05:30"
.
Output only. time when the TuningJob
for the first time entered the JOB_STATE_RUNNING
state.
Uses RFC 3339, where generated output will always be Z-normalized and uses 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z"
, "2014-10-02T15:01:23.045123456Z"
or "2014-10-02T15:01:23+05:30"
.
Output only. time when the TuningJob entered any of the following JobStates
: JOB_STATE_SUCCEEDED
, JOB_STATE_FAILED
, JOB_STATE_CANCELLED
, JOB_STATE_EXPIRED
.
Uses RFC 3339, where generated output will always be Z-normalized and uses 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z"
, "2014-10-02T15:01:23.045123456Z"
or "2014-10-02T15:01:23+05:30"
.
Output only. time when the TuningJob
was most recently updated.
Uses RFC 3339, where generated output will always be Z-normalized and uses 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z"
, "2014-10-02T15:01:23.045123456Z"
or "2014-10-02T15:01:23+05:30"
.
Output only. Only populated when job's state is JOB_STATE_FAILED
or JOB_STATE_CANCELLED
.
labels
map (key: string, value: string)
Optional. The labels with user-defined metadata to organize TuningJob
and generated resources such as Model
and Endpoint
.
label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.
See https://goo.gl/xmQnxf for more information and examples of labels.
experiment
string
Output only. The Experiment associated with this TuningJob
.
Output only. The tuned model resources associated with this TuningJob
.
Output only. The tuning data statistics associated with this TuningJob
.
pipelineJob
(deprecated)
string
Output only. The resource name of the PipelineJob associated with the TuningJob
. Format: projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}
.
Customer-managed encryption key options for a TuningJob. If this is set, then all resources created by the TuningJob will be encrypted with the provided encryption key.
serviceAccount
string
The service account that the tuningJob workload runs as. If not specified, the Vertex AI Secure Fine-Tuned service Agent in the project will be used. See https://cloud.google.com/iam/docs/service-agents#vertex-ai-secure-fine-tuning-service-agent
Users starting the pipeline must have the iam.serviceAccounts.actAs
permission on this service account.
outputUri
string
Optional. Cloud Storage path to the directory where tuning job outputs are written to. This field is only available and required for open source models.
Output only. Evaluation runs for the Tuning Job.
satisfiesPzs
boolean
Output only. reserved for future use.
satisfiesPzi
boolean
Output only. reserved for future use.
source_model
Union type
source_model
can be only one of the following:baseModel
string
The base model that is being tuned. See Supported models.
tuning_spec
Union type
tuning_spec
can be only one of the following:Tuning Spec for Supervised Fine Tuning.
Tuning Spec for Distillation.
Tuning Spec for open sourced and third party Partner models.
Tuning Spec for Veo Tuning.
JSON representation |
---|
{ "name": string, "tunedModelDisplayName": string, "description": string, "customBaseModel": string, "state": enum ( |
SupervisedTuningSpec
Tuning Spec for Supervised Tuning for first party models.
trainingDatasetUri
string
Required. Training dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset.
validationDatasetUri
string
Optional. Validation dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset.
Optional. Hyperparameters for SFT.
exportLastCheckpointOnly
boolean
Optional. If set to true, disable intermediate checkpoints for SFT and only the last checkpoint will be exported. Otherwise, enable intermediate checkpoints for SFT. Default is false.
Optional. Evaluation Config for Tuning Job.
Tuning mode.
JSON representation |
---|
{ "trainingDatasetUri": string, "validationDatasetUri": string, "hyperParameters": { object ( |
SupervisedHyperParameters
Hyperparameters for SFT.
Optional. Number of complete passes the model makes over the entire training dataset during training.
learningRateMultiplier
number
Optional. Multiplier for adjusting the default learning rate. Mutually exclusive with learningRate
. This feature is only available for 1P models.
learningRate
number
Optional. Learning rate for tuning. Mutually exclusive with learningRateMultiplier
. This feature is only available for open source models.
Optional. Adapter size for tuning.
Optional. Batch size for tuning. This feature is only available for open source models.
JSON representation |
---|
{
"epochCount": string,
"learningRateMultiplier": number,
"learningRate": number,
"adapterSize": enum ( |
AdapterSize
Supported adapter sizes for tuning.
Enums | |
---|---|
ADAPTER_SIZE_UNSPECIFIED |
Adapter size is unspecified. |
ADAPTER_SIZE_ONE |
Adapter size 1. |
ADAPTER_SIZE_TWO |
Adapter size 2. |
ADAPTER_SIZE_FOUR |
Adapter size 4. |
ADAPTER_SIZE_EIGHT |
Adapter size 8. |
ADAPTER_SIZE_SIXTEEN |
Adapter size 16. |
ADAPTER_SIZE_THIRTY_TWO |
Adapter size 32. |
EvaluationConfig
Evaluation Config for Tuning Job.
Required. The metrics used for evaluation.
Required. Config for evaluation output.
Optional. Autorater config for evaluation.
JSON representation |
---|
{ "metrics": [ { object ( |
Metric
The metric used for running evaluations.
Optional. The aggregation metrics to use.
metric_spec
Union type
metric_spec
can be only one of the following:Spec for pointwise metric.
Spec for pairwise metric.
Spec for exact match metric.
Spec for bleu metric.
Spec for rouge metric.
JSON representation |
---|
{ "aggregationMetrics": [ enum ( |
PointwiseMetricSpec
Spec for pointwise metric.
Optional. CustomOutputFormatConfig allows customization of metric output. By default, metrics return a score and explanation. When this config is set, the default output is replaced with either: - The raw output string. - A parsed output based on a user-defined schema. If a custom format is chosen, the score
and explanation
fields in the corresponding metric result will be empty.
metricPromptTemplate
string
Required. Metric prompt template for pointwise metric.
systemInstruction
string
Optional. System instructions for pointwise metric.
JSON representation |
---|
{
"customOutputFormatConfig": {
object ( |
CustomOutputFormatConfig
Spec for custom output format configuration.
custom_output_format_config
Union type
custom_output_format_config
can be only one of the following:returnRawOutput
boolean
Optional. Whether to return raw output.
JSON representation |
---|
{ // custom_output_format_config "returnRawOutput": boolean // Union type } |
PairwiseMetricSpec
Spec for pairwise metric.
candidateResponseFieldName
string
Optional. The field name of the candidate response.
baselineResponseFieldName
string
Optional. The field name of the baseline response.
Optional. CustomOutputFormatConfig allows customization of metric output. When this config is set, the default output is replaced with the raw output string. If a custom format is chosen, the pairwiseChoice
and explanation
fields in the corresponding metric result will be empty.
metricPromptTemplate
string
Required. Metric prompt template for pairwise metric.
systemInstruction
string
Optional. System instructions for pairwise metric.
JSON representation |
---|
{
"candidateResponseFieldName": string,
"baselineResponseFieldName": string,
"customOutputFormatConfig": {
object ( |
ExactMatchSpec
This type has no fields.
Spec for exact match metric - returns 1 if prediction and reference exactly matches, otherwise 0.
BleuSpec
Spec for bleu score metric - calculates the precision of n-grams in the prediction as compared to reference - returns a score ranging between 0 to 1.
useEffectiveOrder
boolean
Optional. Whether to useEffectiveOrder to compute bleu score.
JSON representation |
---|
{ "useEffectiveOrder": boolean } |
RougeSpec
Spec for rouge score metric - calculates the recall of n-grams in prediction as compared to reference - returns a score ranging between 0 and 1.
rougeType
string
Optional. Supported rouge types are rougen[1-9], rougeL, and rougeLsum.
useStemmer
boolean
Optional. Whether to use stemmer to compute rouge score.
splitSummaries
boolean
Optional. Whether to split summaries while using rougeLsum.
JSON representation |
---|
{ "rougeType": string, "useStemmer": boolean, "splitSummaries": boolean } |
AggregationMetric
The aggregation metrics supported by EvaluationService.EvaluateDataset.
Enums | |
---|---|
AGGREGATION_METRIC_UNSPECIFIED |
Unspecified aggregation metric. |
AVERAGE |
Average aggregation metric. Not supported for Pairwise metric. |
MODE |
Mode aggregation metric. |
STANDARD_DEVIATION |
Standard deviation aggregation metric. Not supported for pairwise metric. |
VARIANCE |
Variance aggregation metric. Not supported for pairwise metric. |
MINIMUM |
Minimum aggregation metric. Not supported for pairwise metric. |
MAXIMUM |
Maximum aggregation metric. Not supported for pairwise metric. |
MEDIAN |
Median aggregation metric. Not supported for pairwise metric. |
PERCENTILE_P90 |
90th percentile aggregation metric. Not supported for pairwise metric. |
PERCENTILE_P95 |
95th percentile aggregation metric. Not supported for pairwise metric. |
PERCENTILE_P99 |
99th percentile aggregation metric. Not supported for pairwise metric. |
OutputConfig
Config for evaluation output.
destination
Union type
destination
can be only one of the following:Cloud storage destination for evaluation output.
JSON representation |
---|
{
// destination
"gcsDestination": {
object ( |
AutoraterConfig
The configs for autorater. This is applicable to both EvaluateInstances and EvaluateDataset.
autoraterModel
string
Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use.
Publisher model format: projects/{project}/locations/{location}/publishers/*/models/*
Tuned model endpoint format: projects/{project}/locations/{location}/endpoints/{endpoint}
samplingCount
integer
Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
flipEnabled
boolean
Optional. Default is true. Whether to flip the candidate and baseline responses. This is only applicable to the pairwise metric. If enabled, also provide PairwiseMetricSpec.candidate_response_field_name and PairwiseMetricSpec.baseline_response_field_name. When rendering PairwiseMetricSpec.metric_prompt_template, the candidate and baseline fields will be flipped for half of the samples to reduce bias.
JSON representation |
---|
{ "autoraterModel": string, "samplingCount": integer, "flipEnabled": boolean } |
TuningMode
Supported tuning modes.
Enums | |
---|---|
TUNING_MODE_UNSPECIFIED |
Tuning mode is unspecified. |
TUNING_MODE_FULL |
Full fine-tuning mode. |
TUNING_MODE_PEFT_ADAPTER |
PEFT adapter tuning mode. |
DistillationSpec
Tuning Spec for Distillation.
trainingDatasetUri
(deprecated)
string
Deprecated. Cloud Storage path to file containing training dataset for tuning. The dataset must be formatted as a JSONL file.
Optional. Hyperparameters for Distillation.
studentModel
(deprecated)
string
The student model that is being tuned, e.g., "google/gemma-2b-1.1-it". Deprecated. Use baseModel instead.
pipelineRootDirectory
(deprecated)
string
Deprecated. A path in a Cloud Storage bucket, which will be treated as the root output directory of the distillation pipeline. It is used by the system to generate the paths of output artifacts.
teacher_model
Union type
teacher_model
can be only one of the following:baseTeacherModel
string
The base teacher model that is being distilled. See Supported models.
tunedTeacherModelSource
string
The resource name of the Tuned teacher model. Format: projects/{project}/locations/{location}/models/{model}
.
validationDatasetUri
string
Optional. Cloud Storage path to file containing validation dataset for tuning. The dataset must be formatted as a JSONL file.
JSON representation |
---|
{
"trainingDatasetUri": string,
"hyperParameters": {
object ( |
DistillationHyperParameters
Hyperparameters for Distillation.
Optional. Adapter size for distillation.
Optional. Number of complete passes the model makes over the entire training dataset during training.
learningRateMultiplier
number
Optional. Multiplier for adjusting the default learning rate.
JSON representation |
---|
{
"adapterSize": enum ( |
PartnerModelTuningSpec
Tuning spec for Partner models.
trainingDatasetUri
string
Required. Cloud Storage path to file containing training dataset for tuning. The dataset must be formatted as a JSONL file.
validationDatasetUri
string
Optional. Cloud Storage path to file containing validation dataset for tuning. The dataset must be formatted as a JSONL file.
Hyperparameters for tuning. The accepted hyperParameters and their valid range of values will differ depending on the base model.
JSON representation |
---|
{ "trainingDatasetUri": string, "validationDatasetUri": string, "hyperParameters": { string: value, ... } } |
VeoTuningSpec
Tuning Spec for Veo Model Tuning.
trainingDatasetUri
string
Required. Training dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset.
validationDatasetUri
string
Optional. Validation dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset.
Optional. Hyperparameters for Veo.
JSON representation |
---|
{
"trainingDatasetUri": string,
"validationDatasetUri": string,
"hyperParameters": {
object ( |
VeoHyperParameters
Hyperparameters for Veo.
Optional. Number of complete passes the model makes over the entire training dataset during training.
learningRateMultiplier
number
Optional. Multiplier for adjusting the default learning rate.
Optional. The tuning task. Either I2V or T2V.
JSON representation |
---|
{
"epochCount": string,
"learningRateMultiplier": number,
"tuningTask": enum ( |
TuningTask
An enum defining the tuning task used for Veo.
Enums | |
---|---|
TUNING_TASK_UNSPECIFIED |
Default value. This value is unused. |
TUNING_TASK_I2V |
Tuning task for image to video. |
TUNING_TASK_T2V |
Tuning task for text to video. |
TunedModel
The Model Registry Model and Online Prediction Endpoint associated with this TuningJob
.
model
string
Output only. The resource name of the TunedModel. Format:
projects/{project}/locations/{location}/models/{model}@{versionId}
When tuning from a base model, the versionId will be 1.
For continuous tuning, the version id will be incremented by 1 from the last version id in the parent model. E.g.,
projects/{project}/locations/{location}/models/{model}@{last_version_id +
1}
endpoint
string
Output only. A resource name of an Endpoint. Format: projects/{project}/locations/{location}/endpoints/{endpoint}
.
Output only. The checkpoints associated with this TunedModel. This field is only populated for tuning jobs that enable intermediate checkpoints.
JSON representation |
---|
{
"model": string,
"endpoint": string,
"checkpoints": [
{
object ( |
TunedModelCheckpoint
TunedModelCheckpoint for the Tuned Model of a Tuning Job.
checkpointId
string
The id of the checkpoint.
The epoch of the checkpoint.
The step of the checkpoint.
endpoint
string
The Endpoint resource name that the checkpoint is deployed to. Format: projects/{project}/locations/{location}/endpoints/{endpoint}
.
JSON representation |
---|
{ "checkpointId": string, "epoch": string, "step": string, "endpoint": string } |
TuningDataStats
The tuning data statistic values for TuningJob
.
tuning_data_stats
Union type
tuning_data_stats
can be only one of the following:The SFT Tuning data stats.
Output only. Statistics for distillation.
JSON representation |
---|
{ // tuning_data_stats "supervisedTuningDataStats": { object ( |
SupervisedTuningDataStats
Tuning data statistics for Supervised Tuning.
Output only. Number of examples in the tuning dataset.
Output only. Number of tuning characters in the tuning dataset.
Output only. Number of billable characters in the tuning dataset.
Output only. Number of billable tokens in the tuning dataset.
Output only. Number of tuning steps for this Tuning Job.
Output only. Dataset distributions for the user input tokens.
Output only. Dataset distributions for the user output tokens.
Output only. Dataset distributions for the messages per example.
Output only. Sample user messages in the training dataset uri.
Output only. The number of examples in the dataset that have been dropped. An example can be dropped for reasons including: too many tokens, contains an invalid image, contains too many images, etc.
Output only. A partial sample of the indices (starting from 1) of the dropped examples.
droppedExampleReasons[]
string
Output only. For each index in truncatedExampleIndices
, the user-facing reason why the example was dropped.
JSON representation |
---|
{ "tuningDatasetExampleCount": string, "totalTuningCharacterCount": string, "totalBillableCharacterCount": string, "totalBillableTokenCount": string, "tuningStepCount": string, "userInputTokenDistribution": { object ( |
SupervisedTuningDatasetDistribution
Dataset distribution for Supervised Tuning.
Output only. Sum of a given population of values.
Output only. Sum of a given population of values that are billable.
min
number
Output only. The minimum of the population values.
max
number
Output only. The maximum of the population values.
mean
number
Output only. The arithmetic mean of the values in the population.
median
number
Output only. The median of the values in the population.
p5
number
Output only. The 5th percentile of the values in the population.
p95
number
Output only. The 95th percentile of the values in the population.
Output only. Defines the histogram bucket.
JSON representation |
---|
{
"sum": string,
"billableSum": string,
"min": number,
"max": number,
"mean": number,
"median": number,
"p5": number,
"p95": number,
"buckets": [
{
object ( |
DatasetBucket
Dataset bucket used to create a histogram for the distribution given a population of values.
count
number
Output only. Number of values in the bucket.
left
number
Output only. left bound of the bucket.
right
number
Output only. Right bound of the bucket.
JSON representation |
---|
{ "count": number, "left": number, "right": number } |
DistillationDataStats
Statistics computed for datasets used for distillation.
Output only. Statistics computed for the training dataset.
JSON representation |
---|
{
"trainingDatasetStats": {
object ( |
DatasetStats
Statistics computed over a tuning dataset.
Output only. Number of examples in the tuning dataset.
Output only. Number of tuning characters in the tuning dataset.
Output only. Number of billable characters in the tuning dataset.
Output only. Number of tuning steps for this Tuning Job.
Output only. Dataset distributions for the user input tokens.
Output only. Dataset distributions for the messages per example.
Output only. Sample user messages in the training dataset uri.
Output only. A partial sample of the indices (starting from 1) of the dropped examples.
droppedExampleReasons[]
string
Output only. For each index in droppedExampleIndices
, the user-facing reason why the example was dropped.
Output only. Dataset distributions for the user output tokens.
JSON representation |
---|
{ "tuningDatasetExampleCount": string, "totalTuningCharacterCount": string, "totalBillableCharacterCount": string, "tuningStepCount": string, "userInputTokenDistribution": { object ( |
DatasetDistribution
Distribution computed over a tuning dataset.
sum
number
Output only. Sum of a given population of values.
min
number
Output only. The minimum of the population values.
max
number
Output only. The maximum of the population values.
mean
number
Output only. The arithmetic mean of the values in the population.
median
number
Output only. The median of the values in the population.
p5
number
Output only. The 5th percentile of the values in the population.
p95
number
Output only. The 95th percentile of the values in the population.
Output only. Defines the histogram bucket.
JSON representation |
---|
{
"sum": number,
"min": number,
"max": number,
"mean": number,
"median": number,
"p5": number,
"p95": number,
"buckets": [
{
object ( |
DistributionBucket
Dataset bucket used to create a histogram for the distribution given a population of values.
Output only. Number of values in the bucket.
left
number
Output only. left bound of the bucket.
right
number
Output only. Right bound of the bucket.
JSON representation |
---|
{ "count": string, "left": number, "right": number } |
EvaluateDatasetRun
Evaluate Dataset Run result for Tuning Job.
operationName
string
Output only. The operation id of the evaluation run. Format: projects/{project}/locations/{location}/operations/{operationId}
.
checkpointId
string
Output only. The checkpoint id used in the evaluation run. Only populated when evaluating checkpoints.
Output only. Results for EvaluationService.EvaluateDataset.
Output only. The error of the evaluation run if any.
JSON representation |
---|
{ "operationName": string, "checkpointId": string, "evaluateDatasetResponse": { object ( |
EvaluateDatasetResponse
Response in LRO for EvaluationService.EvaluateDataset.
Output only. Aggregation statistics derived from results of EvaluationService.EvaluateDataset.
Output only. Output info for EvaluationService.EvaluateDataset.
JSON representation |
---|
{ "aggregationOutput": { object ( |
AggregationOutput
The aggregation result for the entire dataset and all metrics.
The dataset used for evaluation & aggregation.
One AggregationResult per metric.
JSON representation |
---|
{ "dataset": { object ( |
EvaluationDataset
The dataset used for evaluation.
source
Union type
source
can be only one of the following:Cloud storage source holds the dataset. Currently only one Cloud Storage file path is supported.
BigQuery source holds the dataset.
JSON representation |
---|
{ // source "gcsSource": { object ( |
AggregationResult
The aggregation result for a single metric.
Aggregation metric.
aggregation_result
Union type
aggregation_result
can be only one of the following:result for pointwise metric.
result for pairwise metric.
Results for exact match metric.
Results for bleu metric.
Results for rouge metric.
JSON representation |
---|
{ "aggregationMetric": enum ( |
PointwiseMetricResult
Spec for pointwise metric result.
explanation
string
Output only. Explanation for pointwise metric score.
Output only. Spec for custom output.
score
number
Output only. Pointwise metric score.
JSON representation |
---|
{
"explanation": string,
"customOutput": {
object ( |
CustomOutput
RawOutput
Raw output.
rawOutput[]
string
Output only. Raw output string.
JSON representation |
---|
{ "rawOutput": [ string ] } |
PairwiseMetricResult
Spec for pairwise metric result.
Output only. Pairwise metric choice.
explanation
string
Output only. Explanation for pairwise metric score.
Output only. Spec for custom output.
JSON representation |
---|
{ "pairwiseChoice": enum ( |
PairwiseChoice
Pairwise prediction autorater preference.
Enums | |
---|---|
PAIRWISE_CHOICE_UNSPECIFIED |
Unspecified prediction choice. |
BASELINE |
baseline prediction wins |
CANDIDATE |
Candidate prediction wins |
TIE |
Winner cannot be determined |
ExactMatchMetricValue
Exact match metric value for an instance.
score
number
Output only. Exact match score.
JSON representation |
---|
{ "score": number } |
BleuMetricValue
Bleu metric value for an instance.
score
number
Output only. Bleu score.
JSON representation |
---|
{ "score": number } |
RougeMetricValue
Rouge metric value for an instance.
score
number
Output only. Rouge score.
JSON representation |
---|
{ "score": number } |
OutputInfo
Describes the info for output of EvaluationService.EvaluateDataset.
output_location
Union type
output_location
can be only one of the following:gcsOutputDirectory
string
Output only. The full path of the Cloud Storage directory created, into which the evaluation results and aggregation results are written.
JSON representation |
---|
{ // output_location "gcsOutputDirectory": string // Union type } |
Methods |
|
---|---|
|
Cancels a TuningJob. |
|
Creates a TuningJob. |
|
Gets a TuningJob. |
|
Lists TuningJobs in a Location. |
|
Rebase a TunedModel. |