plot Keras/tensorflow training history

keras_hist_ploy.py

import matplotlib as mpl
import matplotlib.pyplot as plt


model = make_model()
model.load_weights(initial_weights)
model.layers[-1].bias.assign([0.0])
zero_bias_history = model.fit(
    train_features,
    train_labels,
    batch_size=BATCH_SIZE,
    epochs=20,
    validation_data=(val_features, val_labels), 
    verbose=0)
    
    
def plot_loss(history, label, n):
  # Use a log scale to show the wide range of values.
  plt.semilogy(history.epoch,  history.history['loss'],
               color=colors[n], label='Train '+label)
  plt.semilogy(history.epoch,  history.history['val_loss'],
          color=colors[n], label='Val '+label,
          linestyle="--")
  plt.xlabel('Epoch')
  plt.ylabel('Loss')
  
  plt.legend()
  
plot_loss(zero_bias_history, "Zero Bias", 0)