I would like to know how Keras computes the validation and training accuracies for multi-class classification problems (i.e., the function used).I set my model compile as follows:

model.compile(optimizer=Adam(lr=0.001), loss='categorical_crossentropy', metrics=['accuracy']) 

But I am trying to understand how is the validation accuracy and training accuracy is computed (i.e., explicit formulae).

I know the validation and training loss are determined by the 'categorical_crossentropy, but I am not sure about the accuracies.

Note: this is NOT a duplicate of this post. My question is looking for an explanation of the python function used by Keras to compute accuracy not the theoretical details given in the mentioned post.

I would like to know how Keras computes the validation and training accuracies for multi-class classification problems (i.e., the function used). I set my model compile as follows:

model.compile(optimizer=Adam(lr=0.001), loss='categorical_crossentropy', metrics=['accuracy']) 

But I am trying to understand how is the validation accuracy and training accuracy is computed (i.e., explicit formulae).

I know the validation and training loss are determined by the categorical_crossentropy, but I am not sure about the accuracies.

Note: this is NOT a duplicate of this post. My question is looking for an explanation of the Python function used by Keras to compute accuracy, not the theoretical details given in the mentioned post.

I would like to know hoe Keras computes the validation and training accuracies for multi-class classification problems.I set my model compile as follows:

model.compile(optimizer=Adam(lr=0.001), loss='categorical_crossentropy', metrics=['accuracy']) 

But I am trying to understance how is the validation accuracy and training accuracy is computed (i.e., explicit formulae).

I know the validation and training loss are determined by the 'categorical_crossentropy, but I am not sure about the accuracies.

I would like to know how Keras computes the validation and training accuracies for multi-class classification problems (i.e., the function used).I set my model compile as follows:

model.compile(optimizer=Adam(lr=0.001), loss='categorical_crossentropy', metrics=['accuracy']) 

But I am trying to understand how is the validation accuracy and training accuracy is computed (i.e., explicit formulae).

I know the validation and training loss are determined by the 'categorical_crossentropy, but I am not sure about the accuracies.

Note: this is NOT a duplicate of this post. My question is looking for an explanation of the python function used by Keras to compute accuracy not the theoretical details given in the mentioned post.