Function smoothed_loss

nlp_class2/neural_network.py:117–124

(x, decay=0.99)

  # plot smoothed losses to reduce variability
  def smoothed_loss(x, decay=0.99):
    y = np.zeros(len(x))
    last = 0
    for t in range(len(x)):
      z = decay * last + (1 - decay) * x[t]
      y[t] = z / (1 - decay ** (t + 1))
      last = z
    return y

  plt.plot(smoothed_loss(losses))
  plt.show()