In this notebook, we'll walk you through the process of finetuning Haijun 3 Haiku on Amazon Bedrock

#What You'll Need

A dataset (or you can use the sample dataset provided here)

A service role capable of accessing the s3 bucket where you save your training data

#Install Dependencies

ry">Each line in the JSONL file should be a JSON object with the following structure:

{

"system": "",

"messages": [

{"role": "user", "content": "user message"},

{"role": "assistant", "content": "assistant response"},

...

]

}

• The system field is optional.

• There must be at least two messages.

• The first message must be from the "user".

• The last message must be from the "assistant".

• User and assistant messages must alternate.

• No extraneous keys are allowed.

#Sample Dataset - JSON Mode

baseModelIdentifier=base_model_id,

hyperParameters={

"epochCount": f"{epoch_count}",

"batchSize": f"{batch_size}",

"learningRateMultiplier": f"{learning_rate_multiplier}",

},

trainingDataConfig={"s3Uri": f"s3://{bucket_name}/{s3_path}"},

outputDataConfig={"s3Uri": output_path},

)

You can use this to check the status of your job while its training: