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bad results when use models downloaded from huggingface #5
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Hi, If you look at this line of code in the training set-up https://github.com/frankaging/Quasi-Attention-ABSA/blob/main/code/util/train_helper.py#L300, There are two solutions: (1) using the google one for pre-trained weights importing like what you are doing. (2) change the code to integrate with both models. The second approach will require you to modify the variable namings of the model. Does this make sense? |
Hi,
I try to reproduct your work with pytorch BERT model download from huggingface, only to get a very bad result, the training loss keeps around 1.0 in the first 10 epochs. But when I follow your instruction, download google BERT model and converte it with the helper script, then the training process seems to go well.
I wonder why this is happening? Is this because these two models are very different?
Huggingface download link here: https://huggingface.co/bert-base-uncased/tree/main
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