Closes #308 | Implement dataloader for Multilabel Multiclass Sentiment and Emotion Dataset from Indonesian Mobile Application Review

[elyanah-aco]

Closes #308.

Checkbox

• [x] Confirm that this PR is linked to the dataset issue.
• [x] Create the dataloader script seacrowd/sea_datasets/my_dataset/my_dataset.py (please use only lowercase and underscore for dataset naming).
• [x] Provide values for the _CITATION, _DATASETNAME, _DESCRIPTION, _HOMEPAGE, _LICENSE, _URLs, _SUPPORTED_TASKS, _SOURCE_VERSION, and _SEACROWD_VERSION variables.
• [x] Implement _info(), _split_generators() and _generate_examples() in dataloader script.
• [x] Make sure that the BUILDER_CONFIGS class attribute is a list with at least one SEACrowdConfig for the source schema and one for a seacrowd schema.
• [x] Confirm dataloader script works with datasets.load_dataset function.
• [x] Confirm that your dataloader script passes the test suite run with python -m tests.test_seacrowd seacrowd/sea_datasets/<my_dataset>/<my_dataset>.py.
• [ ] If my dataset is local, I have provided an output of the unit-tests in the PR (please copy paste). This is OPTIONAL for public datasets, as we can test these without access to the data files.

[MJonibek]

@elyanah-aco Thank you for implementing this dataloader. Everything works. But I have a question: Maybe it is better just to leave id_sent_emo_mobile_apps_source , instead of dividing it into two subsets, because they are the same.

c.c. @SamuelCahyawijaya what is your opinion regarding it?

[elyanah-aco]

@MJonibek I split dataset into two subsets because its two tasks share the same schema with features referring to two different cols. Is it possible to implement this w/o using subsets?