  We study the morphologies of 3,964 galaxies and their progenitors with
$M_\star > 10^{10} M_\odot$ in the reference EAGLE hydrodynamical simulation
from redshifts $z=1$ to $z=0$, concentrating on the redshift evolution of the
bar fraction. We apply two convolutional neural networks (CNNs) to classify
35,082 synthetic g-band images across 10 snapshots in redshift. We identify
galaxies as either barred or unbarred, while also classifying each sample into
one of four morphological types: elliptical (E), lenticular (S0), spiral (Sp),
and irregular/miscellaneous (IrrM). We find that the bar fraction is roughly
constant between $z = 0.0$ to $z = 0.5$ (32% to 33%), before exhibiting a
general decline to 26% out to $z = 1$. The bar fraction is highest in spiral
galaxies, from 49% at $z = 0$ to 39% at $z = 1$. The bar fraction in S0s is
lower, ranging from 22% to 18%, with similar values for the miscellaneous
category. Under 5% of ellipticals were classified as barred. We find that the
bar fraction is highest in low mass galaxies ($M_\star \leq 10^{10.5}
M_\odot$). Through tracking the evolution of galaxies across each snapshot, we
find that some barred galaxies undergo episodes of bar creation, destruction
and regeneration, with a mean bar lifetime of 2.24 Gyr. We further find that
incidences of bar destruction are more commonly linked to major merging, while
minor merging and accretion is linked to both bar creation and destruction.
