Models for all subtaks are saved and to reproduce their results, run notebooks Task_A_Test.ipynb, Task_B_Test.ipynb, Task_A_Test.ipynb respectively.
For training from scratch run Task_A_Training.ipynb, Task_B_Training.ipynb, Task_C_Training.ipynb respectively.
Note: Subtask A results for training from scratch may not be completely reproducible because we had to save and load model in the middle of training due to the hardware limitation.
forked from SUTNLP/RLAT-Transformer
-
Notifications
You must be signed in to change notification settings - Fork 0
License
pete2huan9/RLAT-Transformer
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
No description, website, or topics provided.
Resources
License
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published
Languages
- Jupyter Notebook 88.6%
- Python 11.4%