Different BERT results
Hello,i have trained different BERT models to evaluate which of these models perform best with my dataset.At the moment I got the problem that I always get different results when running the model again (e.g. run a new colab session).For a reproducible evaluation I want to get always the same results (e.g. F1) but I don’t know how to do this.I have ensured that my train/test/validation split is always the same.Here is an example notebook:Google ColabThanks in advance!
2022-05-25T10:36:04Z
used seed to make your results reproducible.random.seed(seed)
    np.random.seed(seed)
    if is_torch_available():
        tt.manual_seed(seed)
        tt.cuda.manual_seed_all(seed)