Comments (2)
The code line means that we build an embedding matrix that can map any word in datasets (including dev and test in addition to training) to the corresponding word representation initialized with the pre-trained GloVe vector.
We can, of course, utilize the pre-trained vector for a word that is not included in the training set but appears in the test set, even though the vector would not be fine-tuned during training.
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Hello, why does the code stop after running an epoch
from bimpm-pytorch.
Related Issues (13)
- Memory issues HOT 1
- RuntimeError: Expected object of backend CUDA but got backend CPU for argument #3 'index' HOT 1
- self.TEXT.build_vocab(self.train, self.dev, self.test, vectors=GloVe(name='840B', dim=300)) ,the error always exists.
- Access to pretrained model
- what the grammer about f'XXXXXXXXXXXXXXXXX', i means the f HOT 1
- AttributeError: 'BIMPM' object has no attribute 'mp_w1' HOT 1
- Memory error HOT 5
- Less accuracy in reimplementation HOT 1
- RuntimeError: Cannot initialize CUDA without ATen_cuda library HOT 1
- Size([400, 350]) instead of ([400, 300]) HOT 1
- Improving performance HOT 2
- The hyper parameter for SNLI and QQP
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from bimpm-pytorch.