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MELODI
AnDiAMO
discourseSegmentation
disCut21
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d4bebcce
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ezzabady.morteza
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Discourse segmenter for DISRPT 2021
Discourse segmenter for DISRPT 2021
Data for DISRPT 2021: https://github.com/disrpt/sharedtask2021
Useful Links:
Website DISRPT 2021: https://sites.google.com/georgetown.edu/disrpt2021
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Data for DISRPT 2021: https://github.com/disrpt/sharedtask2021
Code for DISRTP 2019: https://gitlab.inria.fr/andiamo/tony
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Website DISRPT 2021: https://sites.google.com/georgetown.edu/disrpt2021
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Code for DISRTP 2019: https://gitlab.inria.fr/andiamo/tony
## Meeting 04.06.2021
Requirements:
TODO:
-
python 3.7
x- install allennlp 0.9 + tony19
-
requirements.txt:
`pip install -r requirements.txt`
x- train a model (on english for instance)
-
pytorch:
`pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio===0.9.0 -f https://download.pytorch.org/whl/torch_stable.html`
x- test it with tony script
x- begin reading the tutorial on allennlp
Usage:
x- continue with general reading NLP
-
train:
`bash expes.sh eng.rst.rstdt conllu bert train`
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test:
`bash expes.sh eng.rst.rstdt conllu bert test`
Next steps:
-
fine-tune with other model:
`bash expes.sh eng.rst.rstdt conllu bert train eng`
x- change to allennlp 1.xx
-
test on other model:
`bash expes.sh eng.rst.rstdt conllu bert test eng`
-
switch to xlm multi lingual
-
merge two datasets:
`bash merger.sh eng.rst.rstdt eng.rst.gum eng`
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play with some hyper-parameters
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split with stanza:
`python parse_corpus.py eng.rst.rstdt --parser stanza`
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go back on the architecture: add the CRF layer on top of BERT/LSTM
-
grouping the corpora during training
-
the sentence problem ? how do we address it
## Meeting 21.05.2021
TODO:
-
install allennlp 0.9 + tony19
-
train a model (on english for instance)
-
test it with tony script
-
begin reading the tutorial on allennlp
-
continue with general reading NLP
Next steps:
-
change to allennlp 1.xx
-
switch to xlm multi lingual
-
grouping the corpora during training
-
the sentence problem ? how do we address it
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