I see, in that case you just need to change the --model_name_or_path parameter to be the folder of your last checkpoint, e.g. if you trained for 3k steps, the folder checkpoint-3000 would contain the model at checkpoint 3k, which is saved locally. Keep also in mind the number of checkpoints you want to keep locally with --save_total_limit.