resume the training

[rambo1111]

If i trained a model on mario and saved it after 100000 total_timesteps

import gym_super_mario_bros
from nes_py.wrappers import JoypadSpace
from gym_super_mario_bros.actions import COMPLEX_MOVEMENT
from gym.wrappers import GrayScaleObservation
from stable_baselines3.common.vec_env import VecFrameStack, DummyVecEnv
from stable_baselines3 import PPO

env = gym_super_mario_bros.make('SuperMarioBros-v0')
env = JoypadSpace(env, COMPLEX_MOVEMENT)
env = GrayScaleObservation(env, keep_dim=True)
env = DummyVecEnv([lambda: env])
env = VecFrameStack(env, 4, channels_order='last')
state = env.reset()

model = PPO('CnnPolicy', env, verbose=1, learning_rate=0.00001, n_steps=512)
model.learn(total_timesteps=100000)
model.save("saved_model_1")

env.close()

In future if i load the model and resume it's training on the same environment like this

env = gym_super_mario_bros.make('SuperMarioBros-v0')
env = JoypadSpace(env, COMPLEX_MOVEMENT)
env = GrayScaleObservation(env, keep_dim=True)
env = DummyVecEnv([lambda: env])
env = VecFrameStack(env, 4, channels_order='last')
state = env.reset()

model = PPO.load('saved_model_1')
model.learn(total_timesteps=200)
model.save("saved_model_2")

will it work?
will the model will resume it's training for next 200 steps after it's training on 100000 steps?