Comments (3)
Hi @emrecncelik ,
Thank you for sharing that point. I was also concerned about the contradictive results that we and other related works obtained. As you pointed, the correct index should be 0 and the current default value on the code is wrong (I am currently working on a complete refactor of the repository, so I will correct it in the future). Still, the experiments were not done with that default value.
To be sure that the obtained results are "correct" (assuming that anything else is wrong) I ran that experiment again with 0 and 1 as the positive index, and I obtained the following results:
Positive index | Top-1 | Top-3 | Top-5 |
---|---|---|---|
0 (isNext) | 2.01 | 8.57 | 16.49 |
1 | 1.36 | 3.57 | 6.10 |
The model that I have used is: bert-large-uncased
I noticed that there is a typo on the paper where the reported Top-1 accuracy for the NSP model is 2.07
and the actual Top-1 accuracy is 2.01
.
Thank you for your comment!
from ask2transformers.
Thanks!
I think once I have finished the redesign of the repository will be much easier to add improvements, so stay tuned. 👌
from ask2transformers.
Oh I see, thanks for the clear explanation. Closing the issue then.
By the way, I'd be happy to help with the improvements in the package if you require any. (eg. Providing more flexible templates for topic classification like the ones in HuggingFace)
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Related Issues (12)
- Please update the README? HOT 3
- fine-tuning Few-Shot Relation Classification HOT 2
- Tutorial or examples HOT 2
- Typo in apostrophes HOT 1
- Zero-shot Tacred Relation Classification HOT 2
- How to reproduce the EAE task result? HOT 3
- verbalization HOT 4
- Few-Shot RE HOT 2
- Run GLUE for fine-tuning Few-Shot Relation Classification HOT 2
- Incomplete documentation
- Fewshot checkpoints for TACRED HOT 2
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