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What is the mini-batch accuracy in CNN training?

18 vues (au cours des 30 derniers jours)
jonghyun kim
jonghyun kim le 31 Jan 2017
hello~
when i train my CNN, log text appear in my command window.
for example,
my question is, what is the meaning of mini-batch accuracy value for each line?
is it average accuracy for every 50 iteration, or exactly for '50th' iteration?
thank you for reading~

Réponses (1)

Sally Al Khamees
Sally Al Khamees le 3 Fév 2017
The mini-batch accuracy reported during training corresponds to the accuracy of the particular mini-batch at the given iteration. It is not a running average over iterations. During training by stochastic gradient descent with momentum (SGDM), the algorithm groups the full dataset into disjoint mini-batches.
An iteration corresponds to the calculation of the network’s gradients for each mini-batch.
An epoch corresponds to moving through every available mini-batch.
Hope this helps
  4 commentaires
shefali saxena
shefali saxena le 12 Fév 2019
Hello Ravish
Do you find any solution??
I am working on 1D(ECG Signal) with CNN model and the overall accuracy of my model is 75%
I have 40 records each record consists of 1x15000 data. My model consists of 15-22 layers.
how can I increase accuracy....
Pendela Neelesh
Pendela Neelesh le 26 Nov 2021
Modifié(e) : Pendela Neelesh le 26 Nov 2021
Train you model different kernel sizes. Validation accuracy can be low due to overfitting, try using dropouts in the model(if not included), add non linearity to the model by relu aactivation.
You can also use agumentation if the training dataset is small. Use feature extraction techniques(such as PCA, ICA etc) before training to decrease the computational complexity.

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