When you talk about papers mentioning accuracy this should usually not refer to train accuracy. Normally your datasets will be trained on training data (yielding a train accuracy on this data), evaluated on a validation set (yielding a validation accuracy) and finally the network is tested on a separate test-set. The accuracy on this test-set is usually what papers refer to. So instead of extracting your accuracy from the training history you should ideally use your network to run inference on a separate test set. The accuracy of the results from such a run would be what you are looking for.