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CNN with Julia
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# Training loop | |
# See: https://github.com/FluxML/model-zoo/blob/master/vision/mnist/conv.jl | |
best_acc = 0.0 | |
last_improvement = 0 | |
accuracy_target = 0.97 #Set an accuracy target. When reached, we stop training. | |
max_epochs = 100 #Maximum | |
for epoch_idx in 1:100 | |
global best_acc, last_improvement | |
# Train for a single epoch | |
Flux.train!(loss, params(model), train_set, opt) | |
# Calculate accuracy: | |
acc = accuracy(train_set_full...) | |
@info(@sprintf("[%d]: Train accuracy: %.4f", epoch_idx, acc)) | |
# Calculate accuracy: | |
acc = accuracy(test_set...) | |
@info(@sprintf("[%d]: Test accuracy: %.4f", epoch_idx, acc)) | |
# If our accuracy is good enough, quit out. | |
if acc >= accuracy_target | |
@info(" -> Early-exiting: We reached our target accuracy of $(accuracy_target*100)%") | |
break | |
end | |
if epoch_idx - last_improvement >= 10 | |
@warn(" -> We're calling this converged.") | |
break | |
end | |
end |
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