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fix optimizer defaults
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simonbatzner committed Mar 26, 2023
1 parent 55bfc1f commit aecd7c0
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Showing 2 changed files with 10 additions and 4 deletions.
7 changes: 5 additions & 2 deletions configs/example.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -124,8 +124,11 @@ metrics_components:

# optimizer, may be any optimizer defined in torch.optim
# the name `optimizer_name`is case sensitive
optimizer_name: Adam # default optimizer is Adam
optimizer_amsgrad: false
# IMPORTANT: for NequIP (not for Allegro), we find that in most cases AMSGrad strongly improves
# out-of-distribution generalization over Adam. We highly recommed trying both AMSGrad (by setting
# optimizer_amsgrad: true) and Adam (by setting optimizer_amsgrad: false)
optimizer_name: Adam
optimizer_amsgrad: true

# lr scheduler, currently only supports the two options listed in full.yaml, i.e. on-pleteau and cosine annealing with warm restarts, if you need more please file an issue
# here: on-plateau, reduce lr by factory of lr_scheduler_factor if metrics_key hasn't improved for lr_scheduler_patience epoch
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7 changes: 5 additions & 2 deletions configs/full.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -266,8 +266,11 @@ metrics_components:

# optimizer, may be any optimizer defined in torch.optim
# the name `optimizer_name`is case sensitive
optimizer_name: Adam # default optimizer is Adam
optimizer_amsgrad: false
# IMPORTANT: for NequIP (not for Allegro), we find that in most cases AMSGrad strongly improves
# out-of-distribution generalization over Adam. We highly recommed trying both AMSGrad (by setting
# optimizer_amsgrad: true) and Adam (by setting optimizer_amsgrad: false)
optimizer_name: Adam
optimizer_amsgrad: true
optimizer_betas: !!python/tuple
- 0.9
- 0.999
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