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loss = metric * mean of sample weights, fixes #63

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Aurélien Geron 2019-11-13 09:36:15 +08:00
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commit 00460cb555
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12_custom_models_and_training_with_tensorflow.ipynb
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@ -1289,7 +1289,7 @@
"* the loss since the start of the epoch is the mean of all batch losses seen so far. Each batch loss is the sum of the weighted instance losses divided by the _batch size_ (not the sum of weights, so the batch loss is _not_ the weighted mean of the losses).\n", "* the loss since the start of the epoch is the mean of all batch losses seen so far. Each batch loss is the sum of the weighted instance losses divided by the _batch size_ (not the sum of weights, so the batch loss is _not_ the weighted mean of the losses).\n",
"* the metric since the start of the epoch is equal to the sum of weighted instance losses divided by sum of all weights seen so far. In other words, it is the weighted mean of all the instance losses. Not the same thing.\n", "* the metric since the start of the epoch is equal to the sum of weighted instance losses divided by sum of all weights seen so far. In other words, it is the weighted mean of all the instance losses. Not the same thing.\n",
"\n", "\n",
"If you do the math, you will find that metric = loss * mean of sample weights (plus some floating point precision error)." "If you do the math, you will find that loss = metric * mean of sample weights (plus some floating point precision error)."
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