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representation_learning

### Directory structure ###
├─config: 
| There are several config.yaml files that include hyperparameters and model class name and several options. 
|
├─data:
| Some data exist in this directory to use train or validation. 
| This directory does not exist in gihub because of their size of storage, so you download this google drive. 
|
├─origin_dataset
|  ├─LARC_dataset
|  ├─concept_eval
|  ├─concept_total
|  ├─concept_train
|  ├─corpus
|  ├─evaluation
|  ├─training
| There exists original data files. If you can use preprocess files, then you can get data that is simliar data in google drive.
| LARC_dataset is text data - https://github.com/samacqua/LARC
| concept total/train/eval just are divide. So this data is included in corpus.
| corpus is ConceptARC dataset. That include 16 kinds ARC tasks and each kind involve 10 problems -  https://github.com/victorvikram/ConceptARC
| training and evaluation are original ARC dataset.
|
├─dataset: 
| Dataset class was defined in this directory
| 
├─model: 
| Model class was defined in this directory
| 
├─preprocess: 
| This directory have some code that used when data preprosessed.
| 
├─trainer: 
| This directory have some code that used when trained model.
| 
├─utils: 
| etc such as visualization or fix seed as so on.

Overview

phase 1

phase 2

phase 3

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