edu-segmentation 0.0.87

To improve EDU segmentation performance using Segbot. As Segbot has an encoder-decoder model architecture, we can replace bidirectional GRU encoder with generative pretraining models such as BART and T5. Evaluate the new model using the RST dataset by using few-shot based settings (e.g. 100 examples) to train the model, instead of using the full dataset.

Final Year Project on EDU Segmentation:

To improve EDU segmentation performance using Segbot. As Segbot has an encoder-decoder model architecture, we can replace bidirectional GRU encoder with generative pretraining models such as BART and T5. Evaluate the new model using the RST dataset by using few-shot based settings (e.g. 100 examples) to train the model, instead of using the full dataset.

Segbot:
http://138.197.118.157:8000/segbot/
https://www.ijcai.org/proceedings/2018/0579.pdf

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Authors

Code Author: Qingyi
Packaging: Patria

How to Use

`from edu_segmentation import run_segbot_bart`: use `run_segbot_bart.run_segbot_bart()` to perform edu-segmentation (user will be prompted for input)