Hello,
Is it correct to save the logits and probabilities of  best model like the following ?
for epoch in range(args.start_epoch, args.epochs):      
  if args.distributed:           
        train_sampler.set_epoch(epoch)
  adjust_learning_rate(optimizer, epoch)    # train for one epoch
  prec_train, loss_train = train(train_loader, model, criterion, optimizer, epoch)   
     # evaluate on validation set
   prec1, loss_val,my_logits,own_proba = validate(val_loader, model, criterion)    
   # remember best prec@1 and save checkpoint
   is_best = prec1 > best_prec1
   best_prec1 = max(prec1, best_prec1)
   save_checkpoint({
           'epoch': epoch + 1,
           'arch': args.arch,
           'state_dict': model.state_dict(),
           'best_prec1': best_prec1,
           'optimizer': optimizer.state_dict(),
           'logits' : my_logits,
           'proba': own_proba,        }, is_best)

Thank you