Comments (2)
You should change the model specified by the variable model_name
from ganbert-pytorch.
Using model_name = 'google/electra-base-discriminator'
Gives me this error,
`======== Epoch 1 / 10 ========
Training...
RuntimeError Traceback (most recent call last)
in
78 # Generate the output of the Discriminator for real and fake data.
79 # First, we put together the output of the tranformer and the generator
---> 80 disciminator_input = torch.cat([hidden_states, gen_rep], dim=0)
81 # Then, we select the output of the disciminator
82 features, logits, probs = discriminator(disciminator_input)
RuntimeError: Tensors must have same number of dimensions: got 2 and 3`
from ganbert-pytorch.
Related Issues (20)
- Number of discriminator output HOT 1
- Is it possible to obtain the text representation generated fake examples? HOT 1
- how do we use the trained model HOT 1
- Support for validation set instead of evaluating on test set directly. HOT 3
- Is the number of unlabeled examples related to the model accuracy? HOT 1
- Train Accuracy in evaluation mode is decreased by every epoch HOT 1
- Generator doesn't work HOT 2
- Gan BERT for Multilabel Intent Classification HOT 1
- Unable to reproduce the results for 20-News dataset HOT 2
- Saving Best model during training
- Deploy the model to use with live data
- Normal distibution HOT 1
- Feature matching loss HOT 1
- Accuracy problem HOT 1
- do you have tensorflow code?thankyou HOT 1
- Save and deploy Model HOT 1
- Model errors when tried to change the dataset HOT 2
- How to show some illustration after complete train model ? HOT 3
- Calculate F1 HOT 3
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from ganbert-pytorch.