localminimum / localminimum/R-net
Pre-trained model for QA
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- Dominant language
- Python
- Stars
- 319
- Forks
- 121
- PR merge metrics
- No merged PRs in 30d
Description
I am trying to build a QA model for a custom dataset. Is there a way in which I can fine-tune the model for initializing the weights(Tensorflow weights as initialization) trained on SQAD dataset onto my new dataset for QA?
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No file, test, or entry point is named. Start by locating the model-training and dataset-loading entry points, then determine whether TensorFlow weights trained on SQuAD can initialize training on a custom QA dataset; done means a reproducible fine-tuning path is documented.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100