feature_engg_text_24.py

for epoch in range(1, 6):
    loss = 0
    for i, elem in enumerate(skip_grams):
        pair_first_elem = np.array(list(zip(*elem[0]))[0], dtype='int32')
        pair_second_elem = np.array(list(zip(*elem[0]))[1], dtype='int32')
        labels = np.array(elem[1], dtype='int32')
        X = [pair_first_elem, pair_second_elem]
        Y = labels
        if i % 10000 == 0:
            print('Processed {} (skip_first, skip_second, relevance) pairs'.format(i))
        loss += model.train_on_batch(X,Y)  

    print('Epoch:', epoch, 'Loss:', loss)