CODEWITHSUNDEEP
tensorflowkerasdeep-learningconv-neural-networklstm
Minha
Minha

Reputation: 3

Does a very low loss and low accuracy indicate overfitting?

I'm training a CNN-LSTM concat model and after 20 epochs I got an accuracy of 69% and a loss of 0.04?

I know that the combination of very high training accuracy and relatively low validation accuracy indicates overfitting but I was wondering if a low accuracy and a very low loss would also indicate overfitting.

Overall, the accuracy increased linearly and the loss decreased exponentially.

Upvotes: 0

Views: 1160

Answers (1)

Nopileos
Nopileos

Reputation: 2117

Some more details regarding task, loss and so on would be appreciated.

For the training set the loss should have a inverse relationship with the metric e.g. accuracy. If the loss goes down the accuracy should go up. If this is not the case you might want to have a look at the loss function and metric.

So a very low loss and very low accuracy on the same dataset would indicate for me, that something is wrong with the model I want to train and that the model is not learning to solve the task I want it to solve.

Upvotes: 0

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