paddle.Model.fit在eval阶段不打印传入的metrics结果，最优结果的保存似乎也没有

[bbbxixixixi]

用SimNet做了个语义判断的程序
model = ppnlp.models.SimNet(
network='gru',
emb_dim=256,
vocab_size=len(vocab),
num_classes=3)
model = paddle.Model(model)
optimizer = paddle.optimizer.AdamW(
parameters=model.parameters(), learning_rate=0.001)
criterion = paddle.nn.CrossEntropyLoss()
metric = paddle.metric.Accuracy()
model.prepare(optimizer, criterion, metric)
model.fit(
train_loader,
evl_loader,
epochs=20,
save_dir='pretrained_model' )
发现在eval阶段只是输出loss等信息，并不会打印出整个eval data的评价指标
然后在最后结束时只存了个final model，paddlex会存一个best model，paddlenlp现在会根据eval阶段的最优解指标存一个模型吗？

[Steffy-zxf]

你好！paddle.Model.fit在eval阶段会打印eval data的评价指标。并且打印的指标是从一个累积的数值。同时paddle.Model.fit可以指定save_freq参数，间隔epoch数之后保存模型参数，参考 https://www.paddlepaddle.org.cn/documentation/docs/zh/api/paddle/hapi/model/Model_cn.html#model

simnet训练示例代码参考：https://github.com/PaddlePaddle/PaddleNLP/tree/release/2.0-rc/examples/text_matching/simnet

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