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MPI cluster训练,请教一下__auc_evaluator_0__的Eval和CurrentEval的计算机制。 I0612 15:12:50.297226 18323 TrainerInternal.cpp:165] Batch=2760 samples=11304960 AvgCost=0.113212 CurrentCost=0.109198 Eval: auc_evaluator_0=0.7042 classification_error_evaluator=0.02633 CurrentEval: auc_evaluator_0=0.727945 classification_error_evaluator=0.0255005
The text was updated successfully, but these errors were encountered:
训练逻辑主要在TrainerInternal::trainOneBatch:
TrainerInternal::trainOneBatch
先调用forwardBackwardBatch,计算出当前batch的gradient,然后调用callback 更新了参数。
forwardBackwardBatch
然后调用了eval计算evaluator的值。
eval
之后才是显示结果
结果
先更新了参数,然后进行evaluat。
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这个是问 Eval 和 CurrentEval 这两个指标的区别吗?如果是的话:
因此,通常 current eval 抖动更强,在第一个 pass 的时候,current eval 评估效果会更好,eval 看上去更差一些。
update dist api (PaddlePaddle#2443)
f5aba69
jacquesqiao
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MPI cluster训练,请教一下__auc_evaluator_0__的Eval和CurrentEval的计算机制。
I0612 15:12:50.297226 18323 TrainerInternal.cpp:165] Batch=2760 samples=11304960 AvgCost=0.113212 CurrentCost=0.109198 Eval: auc_evaluator_0=0.7042 classification_error_evaluator=0.02633 CurrentEval: auc_evaluator_0=0.727945 classification_error_evaluator=0.0255005
The text was updated successfully, but these errors were encountered: