TrainingBucketConfiguration Struct
S3 bucket configuration for the training data.
Example
ts
import * as bedrock from 'aws-cdk-lib/aws-bedrock';
import * as kms from 'aws-cdk-lib/aws-kms';
declare const outputBucket: s3.IBucket;
declare const trainingBucket: s3.IBucket;
declare const validationBucket: s3.IBucket;
declare const kmsKey: kms.IKey;
declare const vpc: ec2.IVpc;
const model = bedrock.FoundationModel.fromFoundationModelId(
this,
'Model',
bedrock.FoundationModelIdentifier.AMAZON_TITAN_TEXT_G1_EXPRESS_V1,
);
const task = new tasks.BedrockCreateModelCustomizationJob(this, 'CreateModelCustomizationJob', {
baseModel: model,
clientRequestToken: 'MyToken',
customizationType: tasks.CustomizationType.FINE_TUNING,
customModelKmsKey: kmsKey,
customModelName: 'MyCustomModel', // required
customModelTags: [{ key: 'key1', value: 'value1' }],
hyperParameters: {
batchSize: '10',
},
jobName: 'MyCustomizationJob', // required
jobTags: [{ key: 'key2', value: 'value2' }],
outputData: {
bucket: outputBucket, // required
path: 'output-data/',
},
trainingData: {
bucket: trainingBucket,
path: 'training-data/data.json',
}, // required
// If you don't provide validation data, you have to specify `Evaluation percentage` hyperparameter.
validationData: [
{
bucket: validationBucket,
path: 'validation-data/data.json',
},
],
vpcConfig: {
securityGroups: [new ec2.SecurityGroup(this, 'SecurityGroup', { vpc })],
subnets: vpc.privateSubnets,
},
});