loss='categorical_crossentropy',

metrics=['accuracy'])

# Обучение модели

history = model.fit(

x_train_small, y_train_small,

epochs=15,

batch_size=32,

validation_data=(x_val, y_val),

verbose=2

)

# Визуализация результатов

plt.figure(figsize=(12, 5))

# График точности

plt.subplot(1, 2, 1)

plt.plot(history.history['accuracy'], label='Train Accuracy', marker='o')

plt.plot(history.history['val_accuracy'], label='Validation Accuracy', marker='o')

plt.title('Accuracy vs Epochs')

plt.xlabel('Epochs')

plt.ylabel('Accuracy')

plt.legend()

plt.grid(True)

# График потерь

plt.subplot(1, 2, 2)

plt.plot(history.history['loss'], label='Train Loss', marker='o')

plt.plot(history.history['val_loss'], label='Validation Loss', marker='o')

plt.title('Loss vs Epochs')

plt.xlabel('Epochs')

plt.ylabel('Loss')

plt.legend()

plt.grid(True)

plt.tight_layout()

plt.show()