testing much worse than training?

[aquiraa]

Basically my training and validation resulted in 88-90% accuracy but the testing is very low.. only about 25%. I'm guessing it's overfitting but I'm not sure how to fix this. Also here is my code:

import os
import numpy as np
import matplotlib.pyplot as plt
import cv2
from tensorflow.keras import layers
from google.colab import drive
import tensorflow as tf

drive.mount('/content/drive')
img_height = 256
img_width = 256
class_names = ['rice_blast', 'brown_spot', 'leaf_blight', 'healthy']

gdrive_path="drive/My Drive/rice_disease"
train_ds = tf.keras.preprocessing.image_dataset_from_directory(
gdrive_path,
validation_split=0.2,
subset="training",
seed=123,
image_size=(img_height, img_width),
)
validation_ds = tf.keras.preprocessing.image_dataset_from_directory(
gdrive_path,
validation_split=0.2,
subset="validation",
seed=123,
image_size=(img_height, img_width),
)
gdrive_path="drive/My Drive/rice_disease_test"
test_ds = tf.keras.preprocessing.image_dataset_from_directory(
gdrive_path,
seed=123,
image_size=(img_height, img_width),
)
def preprocessing_fn(inputs):
"""Preprocess input columns into transformed columns."""
x = inputs['x']
y = inputs['y']
s = inputs['s']
x_centered = x - tft.mean(x)
y_normalized = tft.scale_to_0_1(y)
s_integerized = tft.compute_and_apply_vocabulary(s)
x_centered_times_y_normalized = (x_centered * y_normalized)
return {
'x_centered': x_centered,
'y_normalized': y_normalized,
's_integerized': s_integerized,
'x_centered_times_y_normalized': x_centered_times_y_normalized,
}
model = tf.keras.Sequential([
tf.keras.layers.Flatten(input_shape=(img_height, img_width, 3)),
tf.keras.layers.Dense(32, activation='relu'),
tf.keras.layers.Dense(10),
tf.keras.layers.Dropout(0.2),
])
model.compile(optimizer='adam',
loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
metrics=['accuracy'])

history = model.fit(train_ds, epochs=10)
image_results = model.evaluate(validation_ds)

print('\nValidation accuracy:', image_results)
test_results = model.evaluate(test_ds)
print('/nTest accuracy:', test_results)