Why not fine-tune on TOEIC dataset?
Open
- Dominant language
- Python
- Stars
- 126
- Forks
- 24
- PR merge metrics
- No merged PRs in 30d
Description
Is there a reason that you didn't fine-tune BERT for solving TOEIC problems? Is it because the dataset for TOEIC problem solving is too small for fine-tuning?
Edit: You seem to have more than 7,000 examples of TOEIC blank-filling problems. This seems enough to fine-tune BERT for this task. Was there a reason that you didn't try that?
Contributor guide
No contributing guide indexed for this repository
Assessment
This issue has not been assessed yet.