Hi there again
I just wanted to train a new model with a 90%/10%/0% split for the dataset (train, val, test). But my accuracy wont improve, even tho it should. i already trained it with a predefined 80%/20%/0% split. how can i solve this?
I literally changed nothing. but it works now. which seems strange
So now i did the same split as you guys did. 80/20/0. custom of course. first of all, the validation set seems to be the training set, because an epoch takes about a quarter of a time as before and there are way more validation accuracies than accuracies. i cant reconstruct the old state.
i ran four additional models, all of them got the same structure as the original one.
Run10 is the dataset splitted with your split option
following are the custom splitted runs:
Run32 - load full dataset - shuffle off
Run33 - load full dataset - shuffle on
Run34 - load one batch at a time - shuffle off
Run35 - load one batch at a time - shuffle on
do you have any ideas how i could fix this?
thanks in advance
I cant even reconstruct the old model with the same settings. dont know whats goin on.