# Getting big losses and little accuracy on image classification model with cnn

i am currently working on image classification of artworks from this site https://www.kaggle.com/ikarus777/best-artworks-of-all-time and following the tutorial from this site https://towardsdatascience.com/https-medium-com-drchemlal-deep-learning-tutorial-1-f94156d79802 .

learn = cnn_learner(data, models.resnet34, metrics=accuracy)


And later this step

learn.fit_one_cycle(2)


I get a lot of losses and my accuracy is really low.

epoch     train_loss  valid_loss  accuracy  time
0         3.567351    3.466197    0.216014  05:01
1         3.134228    3.169943    0.229263  05:25


After reviewing the code i have become unsure whether if i am using the right classification algorithm or not.How do i avoid getting big losses and raise the accuracy of the model?

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• You need to run the training for some more time, just 2 epochs based on your data might not be enough. Over time, you should see the loss reducing and accuracy increasing. Ideally, as a rule of thumb, you run it until loss and accuracy stagnate. That would be a good point to evaluate the experiement and decide how to proceed. – Nischal Hp Feb 14 at 10:41