Created
January 27, 2020 13:53
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N_EPOCHS = 5 | |
best_valid_loss = float('inf') | |
for epoch in range(N_EPOCHS): | |
#train the model | |
train_loss, train_acc = train(model, train_iterator, optimizer, criterion) | |
#evaluate the model | |
valid_loss, valid_acc = evaluate(model, valid_iterator, criterion) | |
#save the best model | |
if valid_loss < best_valid_loss: | |
best_valid_loss = valid_loss | |
torch.save(model.state_dict(), 'saved_weights.pt') | |
print(f'\tTrain Loss: {train_loss:.3f} | Train Acc: {train_acc*100:.2f}%') | |
print(f'\t Val. Loss: {valid_loss:.3f} | Val. Acc: {valid_acc*100:.2f}%') |
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