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when I train the ICAR-ENSO dataset,I found the hyperparameter settings of AdamW in the paper are different from the parameter settings in the earthformer_enso_v1.yaml file, so which one should be used?If I want to use global vector, should I modify those parameters? Thank you.
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Thank you for bringing up this issue. Your observation is correct regarding the default config on ICAR-ENSO, which slightly differs from that of SEVIR, N-body MNIST, and Moving MNIST. We have noticed that using lr=1e-3 and num_global_vectors=8 for training is rather unstable. Therefore, we have released a more stable config for better reproducibility.
Thank you.May I ask, when num_global_vectors=0 in earthformer_enso_v1.yaml, the global variable is not applied?The corresponding indicators should be: ,correct?How to use global vector to train ENSO dataset,I can get the second row of results?
Thank you for your question. Yes, num_global_vectors=0 indicates not using global vectors.
The training of Earthformer with global vectors (num_global_vectors=8) on ICAR-ENSO is rather unstable. To help alleviate this, I would recommend initializing some parameters to zero, similar to what we did in our PreDiff that used Earthformer.
when I train the ICAR-ENSO dataset,I found the hyperparameter settings of AdamW in the paper are different from the parameter settings in the earthformer_enso_v1.yaml file, so which one should be used?If I want to use global vector, should I modify those parameters? Thank you.
The text was updated successfully, but these errors were encountered: