Comments (2)
Hi there,
Hope I can help you. Im only using DailyDialog dataset.
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However, it only uses the training data to build the vocabulary in the code.
In the paper is mentioned the ratio between train/valid/test and if you check DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset the size of the vocabulary is bigger than the one used here. However given the dimensions of train/valid/test sets, it is fair to assume that those missing tokens would be super rare. -
Is it essential to add [
,,]" in the start of the dialogue?
Yes, with this you will indicate to the dialogue system to reset and start over. Or that the next sentence following [,,]" is part from another topic.
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Thank you for the explanation!
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Related Issues (11)
- Stop training the context during train_G/train_D? HOT 3
- Code explanation HOT 3
- SWDA seems to give lot of repetition in the sample responses for the test data. HOT 4
- Unable to achieve published result in DailyDialogue HOT 3
- Wasserstein distance between prior and posterior HOT 3
- Confused about the evaluation of inter-dist metrics. HOT 4
- Warning when run sample.py:RNN module weights are not part of single contiguous chunk of memory. HOT 3
- seems the loss of both generator and discriminator would collapse? HOT 1
- Could I apply for your pretrained model in DailyDialog?
- It is reasonable if I set n_samples to 1 when I run the sample.py HOT 2
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