Why i getting value error at history here is my code below

import tensorflow as tf

import matplotlib.pyplot as plt

import numpy as np

# Check if TensorFlow detects a GPU

print$($tf$.$config.list$\_$physical$\_$devices$(\text{'}$GPU$\text{'}))$

# Load the MNIST dataset

mnist $=$ tf$.$keras.datasets.mnist

$($train$\_$xs$,$ train$\_$ys$),($test$\_$xs$,$ test$\_$ys$)=$ mnist.load$\_$data$()$

# Normalize the data

train$\_$xs $=$ train$\_$xs $/255\mathrm{.}0$

test$\_$xs $=$ test$\_$xs $/255\mathrm{.}0$

# Reshape the data to match the input shape expected by Conv$2$D layers

train$\_$xs $=$ train$\_$xs$.$reshape$(60000,28,28,1)$

test$\_$xs $=$ test$\_$xs$.$reshape$(10000,28,28,1)$

# One$-$hot encode the labels

num$\_$classes $=10$

train$\_$ys $=$ tf$.$keras.utils.to$\_$categorical$($train$\_$ys$,$ num$\_$classes$)$

test$\_$ys $=$ tf$.$keras.utils.to$\_$categorical$($test$\_$ys$,$ num$\_$classes$)$

# Import required layers and Sequential model

from tensorflow.keras.models import Sequential

from tensorflow.keras.layers import Conv$2$D$,$ MaxPooling$2$D$,$ Flatten, Dense

# Initialize the model

model $=$ Sequential$()$

# Add layers to the model

model.add$($Conv$2$D$($filters$=64,$ kernel$\_$size$=(5,5),$ activation$=$'relu', input$\_$shape$=(28,28,1)))$

model.add$($MaxPooling$2$D$($pool$\_$size$=(2,2),$ strides$=1))$

model.add$($Conv$2$D$($filters$=64,$ kernel$\_$size$=(5,5),$ activation$=$'relu'$))$

model.add$($MaxPooling$2$D$($pool$\_$size$=(2,2),$ strides$=1))$

model.add$($Flatten$())$

model.add$($Dense$(64,$ activation$=$'relu'$))$

model.add$($Dense$($num$\_$classes, activation$=$'softmax'$))$

# Print model summary

model.summary$()$

# Compile the model

model.compile$($

optimizer$=$'adam',

loss$=$'categorical$\_$crossentropy',

metrics$=[\text{'}$accuracy$\text{'}]$

$)$

# Train the model

history $=$ model.fit$($train$\_$xs$,$ train$\_$ys$,$ epochs$=5,$ validation$\_$data$=($test$\_$xs$,$ test$\_$ys$))$