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When building model, it seems that the loaded glove embedding is not used. I think thats one of the reason that I can't reproduct the experiment result. https://github.com/lx865712528/JMEE/blob/494451d5852ba724d273ee6f97602c60a5517446/enet/models/ee.py#L20 https://github.com/lx865712528/JMEE/blob/494451d5852ba724d273ee6f97602c60a5517446/enet/run/ee/runner.py#L55
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Hi @airkid, I noticed the same problem, so I write code below to pass pretrained word embedding:
def load_model(self, fine_tune, embeddingMatrix=None): if fine_tune is None: return EDModel(self.a.hps, self.get_device(), embeddingMatrix=embeddingMatrix)
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Hi @ycc1028, the paperr mentions that pre-trained Glove word embedding is used
Hi @ycc1028 , after this modification it still can not reach the performance cause there are still another evaluate problem #6
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When building model, it seems that the loaded glove embedding is not used.
I think thats one of the reason that I can't reproduct the experiment result.
https://github.com/lx865712528/JMEE/blob/494451d5852ba724d273ee6f97602c60a5517446/enet/models/ee.py#L20
https://github.com/lx865712528/JMEE/blob/494451d5852ba724d273ee6f97602c60a5517446/enet/run/ee/runner.py#L55
The text was updated successfully, but these errors were encountered: