plotting keras model fitting statistics

gistfile1.txt

# model.fit(img_iter,
#           epochs=10,
#           steps_per_epoch=len(x_train)/batch_size, # Run same number of steps we would if we were not using a generator.
#           validation_data=(x_valid, y_valid))

import matplotlib.pyplot as plt

# Plotting the training loss
plt.plot(model.history.history['loss'], label='Training Loss')

# If you also want to plot the validation loss
plt.plot(model.history.history['val_loss'], label='Validation Loss')

# Adding title and labels
plt.title('Model Loss')
plt.ylabel('Loss')
plt.xlabel('Epoch')
# Adding legend
plt.legend()

# Show the plot
plt.show()