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Fix ineffective no_decay bug when using BERTAdam #32

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Nov 20, 2018
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Fix ineffective no_decay bug when using BERTAdam #32

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4 changes: 2 additions & 2 deletions examples/run_classifier.py
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Original file line number Diff line number Diff line change
Expand Up @@ -503,8 +503,8 @@ def main():
param_optimizer = list(model.named_parameters())
no_decay = ['bias', 'gamma', 'beta']
optimizer_grouped_parameters = [
{'params': [p for n, p in param_optimizer if n not in no_decay], 'weight_decay_rate': 0.01},
{'params': [p for n, p in param_optimizer if n in no_decay], 'weight_decay_rate': 0.0}
{'params': [p for n, p in param_optimizer if not any(nd in n for nd in no_decay)], 'weight_decay_rate': 0.01},
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I think all(nd not in n for nd in no_decay) would be clearer

{'params': [p for n, p in param_optimizer if any(nd in n for nd in no_decay)], 'weight_decay_rate': 0.0}
]
optimizer = BertAdam(optimizer_grouped_parameters,
lr=args.learning_rate,
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