email-spam-classifier-train-function.py

def train_model(model, train_data, optimizer, batch_size, epochs=10):
    losses = {}
    random.seed(1)

    for epoch in range(epochs):
        random.shuffle(train_data)

        batches = minibatch(train_data, size=batch_size)
        for batch in batches:
            # Split batch into texts and labels
            texts, labels = zip(*batch)

            # Update model with texts and labels
            model.update(texts, labels, sgd=optimizer, losses=losses)
        print("Loss: {}".format(losses['textcat']))

    return losses['textcat']