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### Model giving accuracy of 89% after training it by CT scan Images. and giving accuracy of 35% on testing. and low precision, recall, f1-score

This is what happens when you overfit the training data. Your model identifies idiosyncratic characteristics of the training data that are specific to that data sample but don't generalize to other ...
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### Model giving accuracy of 89% after training it by CT scan Images. and giving accuracy of 35% on testing. and low precision, recall, f1-score

you described your method extensively but haven't gone through the data and sampling. Is your data balanced? I am guessing not. If so, then looking at the accuracy may be misleading. Usually, the ...
As you get out past iteration $6000$, it seems like the train and test loss values are stable, as is the distance between them, which looks small. However, both values are tiny compared to the ...