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The Stanford Word Substitution (Swords) Benchmark
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fixed open_fn definition when evaluating on a personalized dataset
Hi, I've found a bug in the following method that is used for BERT-K and BERT-LS encoding sentences. **** In "methods/bert.py/_logits_for_dropout_target" **** with torch.no_grad(): embeddings = self.bert.embeddings(self.list_to_tensor(context_target_enc)) (Omitting Dropout procedure)...
Thanks for your code and contribution. I've conducted some testing on the legacy metrics, and it appears there might be an issue with the legacy metric-'best' score. When testing with...