Deep Learning with PyTorch

Training and validating the model

We will use the same fit function that we have been using from Chapter 5, Deep Learning for Computer Vision. I am not including that here, to save space. The following code snippet contains functionality to train the model and shows the results:

train_losses , train_accuracy = [],[]val_losses , val_accuracy = [],[]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)

The result of the preceding code is as follows:

#Resultstraining ...