Even if you use the same seed, you will not get the same results because the last layer of the model, the classification head, will be initialized randomly the same way if you label are mapped to 0, 1, 2, 3, 4, or another permutation. That means that the initial weight for ‘a’ will be different if ‘a’ is mapped to 0 or 4. Then going from there, you will get different losses, so different gradients and different updates, and will end up with a completely different model.