Fine-Tuning GPT-3 Using the OpenAI API and Python

pip install --upgrade openai -q

import os
from openai import OpenAI

client = OpenAI(
  api_key=os.environ['OPENAI_API_KEY'],
)

training_data = [
	{
    	"prompt": "What is the capital of France?->",
    	"completion": """ The capital of France is Paris.\n"""
	},
	{
    	"prompt": "What is the primary function of the heart?->",
    	"completion": """ The primary function of the heart is to pump blood throughout the body.\n"""
	},
	{
    	"prompt": "What is photosynthesis?->",
    	"completion": """ Photosynthesis is the process by which green plants and some other organisms convert sunlight into chemical energy stored in the form of glucose.\n"""
	},
	{
    	"prompt": "Who wrote the play 'Romeo and Juliet'?->",
    	"completion": """ William Shakespeare wrote the play 'Romeo and Juliet'.\n"""
	},
	{
    	"prompt": "Which element has the atomic number 1?->",
    	"completion": """ Hydrogen has the atomic number 1.\n"""
	},
	{
    	"prompt": "What is the largest planet in our solar system?->",
    	"completion": """ Jupiter is the largest planet in our solar system.\n"""
	},
	{
    	"prompt": "What is the freezing point of water in Celsius?->",
    	"completion": """ The freezing point of water in Celsius is 0 degrees.\n"""
	},
	{
    	"prompt": "What is the square root of 144?->",
    	"completion": """ The square root of 144 is 12.\n"""
	},
	{
    	"prompt": "Who is the author of 'To Kill a Mockingbird'?->",
    	"completion": """ The author of 'To Kill a Mockingbird' is Harper Lee.\n"""
	},
	{
    	"prompt": "What is the smallest unit of life?->",
    	"completion": """ The smallest unit of life is the cell.\n"""
	}
]

validation_data = [
	{
    	"prompt": "Which gas do plants use for photosynthesis?->",
    	"completion": """ Plants use carbon dioxide for photosynthesis.\n"""
	},
	{
    	"prompt": "What are the three primary colors of light?->",
    	"completion": """ The three primary colors of light are red, green, and blue.\n"""
	},
	{
    	"prompt": "Who discovered penicillin?->",
    	"completion": """ Sir Alexander Fleming discovered penicillin.\n"""
	},
	{
    	"prompt": "What is the chemical formula for water?->",
    	"completion": """ The chemical formula for water is H2O.\n"""
	},
	{
    	"prompt": "What is the largest country by land area?->",
    	"completion": """ Russia is the largest country by land area.\n"""
	},
	{
    	"prompt": "What is the speed of light in a vacuum?->",
    	"completion": """ The speed of light in a vacuum is approximately 299,792 kilometers per second.\n"""
	},
	{
    	"prompt": "What is the currency of Japan?->",
    	"completion": """ The currency of Japan is the Japanese Yen.\n"""
	},
	{
    	"prompt": "What is the smallest bone in the human body?->",
    	"completion": """ The stapes, located in the middle ear, is the smallest bone in the human body.\n"""
	}
]

import json

training_file_name = "training_data.jsonl"
validation_file_name = "validation_data.jsonl"

def prepare_data(dictionary_data, final_file_name):
    with open(final_file_name, 'w') as outfile:
        for entry in dictionary_data:
        	json.dump(entry, outfile)
        	outfile.write('\n')

prepare_data(training_data, "training_data.jsonl")
prepare_data(validation_data, "validation_data.jsonl")

training_file_id = client.files.create(
  file=open(training_file_name, "rb"),
  purpose="fine-tune"
)

validation_file_id = client.files.create(
  file=open(validation_file_name, "rb"),
  purpose="fine-tune"
)

print(f"Training File ID: {training_file_id}")
print(f"Validation File ID: {validation_file_id}")

training_file_id.id

response = client.fine_tuning.jobs.create(
  training_file=training_file_id.id, 
  validation_file=validation_file_id.id,
  model="davinci-002", 
  hyperparameters={
    "n_epochs": 15,
	"batch_size": 3,
	"learning_rate_multiplier": 0.3
  }
)

job_id = response.id
status = response.status

print(f'Fine-tunning model with jobID: {job_id}.')
print(f"Training Response: {response}")
print(f"Training Status: {status}")

import signal
import datetime


def signal_handler(sig, frame):
    status = client.fine_tuning.jobs.retrieve(job_id).status
    print(f"Stream interrupted. Job is still {status}.")
    return


print(f"Streaming events for the fine-tuning job: {job_id}")

signal.signal(signal.SIGINT, signal_handler)

events = client.fine_tuning.jobs.list_events(fine_tuning_job_id=job_id)
try:
    for event in events:
        print(
            f'{datetime.datetime.fromtimestamp(event.created_at)} {event.message}'
        )
except Exception:
    print("Stream interrupted (client disconnected).")

import time

status = client.fine_tuning.jobs.retrieve(job_id).status
if status not in ["succeeded", "failed"]:
    print(f"Job not in terminal status: {status}. Waiting.")
    while status not in ["succeeded", "failed"]:
        time.sleep(2)
        status = client.fine_tuning.jobs.retrieve(job_id).status
        print(f"Status: {status}")
else:
    print(f"Finetune job {job_id} finished with status: {status}")
print("Checking other finetune jobs in the subscription.")
result = client.fine_tuning.jobs.list()
print(f"Found {len(result.data)} finetune jobs.")