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评测代码是有问题的 #16

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nwf5d opened this issue Oct 17, 2019 · 2 comments
Open

评测代码是有问题的 #16

nwf5d opened this issue Oct 17, 2019 · 2 comments

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@nwf5d
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nwf5d commented Oct 17, 2019

使用提供的评测数据,得到的评测结果有问题。

eval_accuracy = 0.86040765
eval_f1 = 0.9527646
eval_loss = 0.5360181
eval_precision = 0.9510234
eval_recall = 0.95451

在precision和recall均在0.95时,accuracy理论上也在0.95左右
作者给出的评测代码对于多分类情况同样也是有问题的。
另外,因为tensorflow的tf.metrics实现的问题,在评测数据量较大时计算也会有问题。

@nwf5d nwf5d changed the title 评测代码应该是有问题的 评测代码是有问题的 Oct 17, 2019
@nwf5d
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nwf5d commented Oct 17, 2019

如果能有评测结果的文件(格式可以是:正确标签\t预测标签\t正文),使用sklearn的metrics包也可以得到正确结果。
发现output目录下有eval.tf_record文件,估计只是方便后续处理生成的中间结果文件
有没有方法可以输出最终的评测结果文件呢?

@tengben0905
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precision = TP / (TP + FP)
recall = TP / (TP + FN)
accuracy = (TP + TN) / (TP + FP + TN + FN)

在precision和recall均在0.95时,accuracy理论上也在0.95左右

这个是怎么算出来的?

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