Keras: Getting different values shown by fit_generator (verbose=1) and the metrics in the history object
Even the metrics shown in verbose mode (val_loss, val_acc, etc...) has rounding and sometimes the rounding conflict with EarlyStopping or ModelCheckPoint callbacks behaviour.
I think that this isn't really a problem, just a summary point of view. If you really need these numbers with all decimals places, the history is the right place to get it.
I'm new using Keras and I'm building a model to classify medical images. 
The dataset is very large and I am using fit_generator() function to optimize RAM space. 
When the model trains by batches, it shows statistics of each batch such as loss, precision, etc; and finally when it ends with all the batches at the end of the epoch, it gives me what I suppose is the average of these previous values, now the problem is: when I write a callback to save the training history, I get different values, close to those shown in the console but definitely different.
Could this be a floating point error or something like that?
This did not happen to me when I used the function fit () that showed me the same information as the one I got in the history object. 
I would appreciate any help on the subject, thank you for your time.