Final project for cs1460 (Computational Linguistics)
- cs login: mlavrent
- paper: A BERT Baseline for the Natural Questions
The notebook relies on being in a Google Drive drive with the following hierarchy:
MyDrive
└- Colab Notebooks
├- qa-final-data/
│ ├─ dev.json
│ └- train.json
├- qa-model.model (optional, if loading from saved model)
└- qa-final.ipnyb
In other words, just put this repository in MyDrive/Colab Notebooks and you should be all set.
If qa-model.model is present, the notebook will just load the saved fine-tuned model and avoid training again (this may help for running quickly). If it isn't present, it'll fine-tune the model again.
The model takes about 8 minutes per epoch to train. Since I have it training for 4 epochs, that's 30-40 minutes of training time. If you're just interested in running the model on some questions and documents, you can find the fine-tuned model here (warning - 253 MB). To use it, make sure you put it in your repository as specified in the "How to run" section.
The model achieves the following results on the validation set once fine-tuned:
precision: 0.64
recall: 0.69
f1-score: 0.61