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add training blowup sanity threshold to example.yaml
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configs/example.yaml

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@@ -99,6 +99,9 @@ early_stopping_patiences:
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early_stopping_lower_bounds: # stop early if a metric value is lower than the bound
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LR: 1.0e-5
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early_stopping_upper_bounds: # stop early if the training appears to have exploded
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validation_loss: 1.0e4
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# loss function
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loss_coeffs:
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forces: 1 # if using PerAtomMSELoss, a default weight of 1:1 on each should work well

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