Deep Learning with PyTorch

Training and validating the model

We use the same fit and training logic as seen in the previous ResNet and other examples. We will just look at the training code and the results from it:

for epoch in range(1,10):    epoch_loss, epoch_accuracy = fit(epoch,fc,trn_feat_loader,phase='training')    val_epoch_loss , val_epoch_accuracy = fit(epoch,fc,val_feat_loader,phase='validation')    train_losses.append(epoch_loss)    train_accuracy.append(epoch_accuracy)    val_losses.append(val_epoch_loss)    val_accuracy.append(val_epoch_accuracy)#Resultstraining loss is 0.78 and training accuracy is 22825/23000 99.24validation loss is 5.3 and validation accuracy is 1947/2000 97.35training loss is 0.84 and training accuracy is 22829/23000 99.26validation loss is 5.1 and ...