Comments (6)
Can you provide the context? because it gives me exactly the same number of questions I ask for.
from question_generation.
sure -
i'm using the t5 model from the nlp pipeline e2e
and i run the nlp argument given above: nlp(text5, model_args)
any additional context i can give ?
from question_generation.
thanks @krrishdholakia !
Here num_return_sequences
can't be used because the number questions generated will depend on the number of answers extracted. If the ans extraction model gives only two answer then only two questions will be generated.
num_return_sequences
is used with beam search or top-k top-p sampling in the .generate
method. With beam search, in most of the cases it returns the similar or slightly paraphrased version of the same questions, so I'm not using num_return_sequences
.
I'm trying out other methods for better answer extraction, but havn't got any good results yet. Will ping you if I find some other method to extract more answers.
from question_generation.
hey @patil-suraj,
they mention an interesting approach using top-k sampling in this article - https://medium.com/huggingface/how-to-build-a-state-of-the-art-conversational-ai-with-transfer-learning-2d818ac26313
thoughts on using this ?
from question_generation.
I have tried sampling but beam search results are better than sampling for this task. Feel free to give it try though!
from question_generation.
thanks @krrishdholakia !
Here
num_return_sequences
can't be used because the number questions generated will depend on the number of answers extracted. If the ans extraction model gives only two answer then only two questions will be generated.
num_return_sequences
is used with beam search or top-k top-p sampling in the.generate
method. With beam search, in most of the cases it returns the similar or slightly paraphrased version of the same questions, so I'm not usingnum_return_sequences
.I'm trying out other methods for better answer extraction, but havn't got any good results yet. Will ping you if I find some other method to extract more answers.
Hi @patil-suraj, great work! May I ask how do you control the number of answers extracted? My project came up with a different number of answers for different texts.
from question_generation.
Related Issues (20)
- Can we generate questions based on the type of question?
- abbrevation in question generated are some times coming in small case such as it instead of IT/ai instead AI etc
- Retraining the model valhalla/t5-small-e2e-qg with questions only
- Model trained for e2e-qg does not generate any questions
- How to get the `char end` and `char start` in the generated question and answers from valhalla/t5-base-qg-hl? HOT 1
- error while using onnx runtime
- Requirements.txt needed HOT 1
- How would you fix these issues to get the project running HOT 1
- Fine tuning a T5 model with another language
- How can i get this to work with transformer 4.x HOT 1
- Loss Function multi-task
- AttributeError: module 'dill._dill' has no attribute 'PY3' HOT 5
- requirements.txt file would be very useful
- unexepect <pad> HOT 1
- ValueError: substring not found HOT 1
- How can i run this project with transformers 4?. HOT 1
- Which Bart model used in the pipeline
- Is it possible to add a parameter for number of question to be generated in the question generation model
- No such file or directory: '/root/.cache/huggingface/datasets/squad_multitask/highlight_qg_format/1.0.0/dataset_info.json' HOT 5
- Fine-tuning using GPU HOT 1
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from question_generation.