You have already directly transformed the logits to probabilities using the softmax. To set a threshold you could do something like:
threshold = 0.6
# Get the max probability and the index of the highest prediction for each output.
max_probabilities, max_indices = torch.max(proba, dim=1)
# Get an array of true if the probability is above the threshold, and false otherwise.
above_threshold = max_probabilities > threshold
# Get the predicted label if the probability is greater than the threshold and None otherwise.
results = [predicted_label.item() if above_threshold[index] else None for index, predicted_label in enumerate(max_indices)]