Transformers, Pytorch, Machine Learning, Deep Dives, Data Science.
1:]).float().mean() acc += accuracy.item() history_loss.append(loss.item()) history_acc.append(accuracy.item()) return losses / len(list(loader)), acc / len(list(loader)), history_loss, history_acc And train the model for a couple of epochs: import torch import time import torch.nn as nn import