Skip to content

snowood1/SATP

BranchesTags

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

24 Commits
.idea
.idea
 
 
Data_TagTog_Annotated
Data_TagTog_Annotated
 
 
Data_TagTog_NotAnnotated
Data_TagTog_NotAnnotated
 
 
data
data
 
 
outdata
outdata
 
 
1_annotation_pipeline-12.21.ipynb
1_annotation_pipeline-12.21.ipynb
 
 
2_Preprocess-Data-12.20.ipynb
2_Preprocess-Data-12.20.ipynb
 
 
2_Preprocess-Data-12.27.ipynb
2_Preprocess-Data-12.27.ipynb
 
 
3.BiLSTM.ipynb
3.BiLSTM.ipynb
 
 
4. transformer_reduced_bert.ipynb
4. transformer_reduced_bert.ipynb
 
 
5. Baselines_reduced-2-step.ipynb
5. Baselines_reduced-2-step.ipynb
 
 
README.md
README.md
 
 
classify.py
classify.py
 
 
create_input_files.py
create_input_files.py
 
 
datasets.py
datasets.py
 
 
eval.py
eval.py
 
 
han_end2end.py
han_end2end.py
 
 
model.py
model.py
 
 
train.py
train.py
 
 
transformer_not_reduced_bert-20.ipynb
transformer_not_reduced_bert-20.ipynb
 
 
transformer_reduced_bert.ipynb
transformer_reduced_bert.ipynb
 
 
utils.py
utils.py
 
 

Repository files navigation

SATP_12.20

1. Annotation pipeline

1_annotation_pipeline-12.21.ipynb

2. Prepare our training/ testing data

2_Preprocess-Data-12.20.ipynb

3. Create word vector and dataloader from train.csv.

python create_input_files.py

4. Train our HAN model on train.csv

python train.py

5. Eval on our HAN model on test.csv

python eval.py

6. Visualiazation (Under developement)

python classify.py

Results:

/ Accuracy Recall Precision F1
Multi-label 0.857 0.526 0.769 0.625
Relevant or Not 0.885 0.885 0.885 0.885

About

No description, website, or topics provided.

Resources

Readme
Activity

Stars

1 star

Watchers

2 watching

Forks

2 forks
Report repository

Releases

No releases published

Packages

No packages published

Languages