am I missing something? Because even using the ResNet50 model the accuracy is not improving.
def evaluate(model, iterator, criterion, device):
epoch_loss = 0
epoch_acc_1 = 0
total = 0
model.eval()
with torch.no_grad():
for (x, y) in iterator:
x = x.to(device)
y = y.to(device)
y_pred = model(x)
loss = criterion(y_pred, y)
_, predicted = torch.max(y_pred.data, 1)
total += y.size(0)
epoch_acc_1 += (predicted == y).float().sum()
epoch_loss += loss.item()
epoch_loss /= len(iterator)
epoch_acc_1 /= total
return epoch_loss, epoch_acc_1
def epoch_time(start_time, end_time):
elapsed_time = end_time - start_time
elapsed_mins = int(elapsed_time / 60)
elapsed_secs = int(elapsed_time - (elapsed_mins * 60))
return elapsed_mins, elapsed_secs