Jishnu Ray Chowdhury

It should be like this: `from nltk.metrics.agreement import AnnotationTask evaluator1 = [3, 5, 5, 5, 5, 5, 5, 5, 5, 3, 3, 5, 5, 5, 5, 3, 5, 5, 5,...

> is it the same as validation Yes.

I don't think you can control how many words are generated directly. The maximum length is juts that: the maximum upperbound. In practice, the model is trained to predict a...

Yes. You can also try other models from github. On Thu, Aug 19, 2021, 4:38 AM Karima Marwazia Shaliha < ***@***.***> wrote: > umm, okay For that problem I understand,...

It's the number of neurons in the layers used to predict the local attention window position. https://arxiv.org/pdf/1508.04025.pdf (eqn. 9) if Wp transforms some vector of dimension d to 128, then...

I don't remember, I probably chose 128 randomly. Ideally, we are supposed to hyperparameter tune it. Same for 5. I have seen 1 or 5 been used as reasonable values...

I haven't touched Tensorflow in a while. But wouldn't this be for loading a checkpoint? > saver.restore(sess, r'C:\Users\james\Desktop\Title Generation - SENG 6245\Dataset250K.csv') It doesn't seem like normal Tensorflow checkpoint. >...

It should work, but the main error seems to be that len(val_batches_text) is 0. That means the source of the bug is in the code snippet where val_batches_text is being...

Probably you have to figure out what max length/min length are suitable for your dataset: https://github.com/JRC1995/Abstractive-Summarization/blob/master/Data_Pre-Processing.ipynb You have to probably change them: "text_max_len = 500 text_min_len = 25 summary_max_len =...

I don't think I released the pre-trained model (I don't think I even really fully trained it). At this point I don't think I have the checkpoint.