# last_loss_data = loss_data
# 在屏幕上打印本轮分类结果
acc = str(round(100. * correct_pred.data.numpy() / all_pred, 2))
print(mode)
print('acc: ', acc)
print(classification_report(y_true, y_pred, target_names=target_names))
print(precision_recall_fscore_support(y_true, y_pred, average='macro'))
return acc, cla
print('开始训练 ...')
acc_on_dev = []
for epoch in range(1, args.epochs + 1):
print('第', str(epoch), '轮训练')
batch_generator = train_batch_iterator.__iter__()
acc, cla = run(batch_generator, 'train', cla)
batch_generator = dev_batch_iteraor.__iter__()
acc, cla = run(batch_generator, 'dev', cla)
acc_on_dev.append(str(acc))
with open('acc_records.txt', 'a') as f:
f.write(' '.join(acc_on_dev) + '\n')
