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do_eval 下计算的是平均的p,r和f1 对于数据非常不平衡的多分类NER,好像只看平均值参考意义不大 我如何得到每一类标签的p,r和f1呢? 代码里用estimator来进行封装,我很难将过程中的一些值输出,还请不吝赐教:)
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可以通过自定义hook的方式打印: output_spec = tf.contrib.tpu.TPUEstimatorSpec( mode=mode, loss=total_loss, eval_metrics=eval_metrics, evaluation_hooks = eval_hooks, scaffold_fn=scaffold_fn) 在hook里可以直接打印tensor的值,计算详细指标也方便些,具体的实现可以在网上搜一下
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do_eval 下计算的是平均的p,r和f1
对于数据非常不平衡的多分类NER,好像只看平均值参考意义不大
我如何得到每一类标签的p,r和f1呢?
代码里用estimator来进行封装,我很难将过程中的一些值输出,还请不吝赐教:)
The text was updated successfully, but these errors were encountered: