Closes #134 | Create dataset loader for Sundanese Twitter Dataset for Emotion

[nadyadtm]

Please name your PR after the issue it closes. You can use the following line: "Closes #ISSUE-NUMBER" where you replace the ISSUE-NUMBER with the one corresponding to your dataset.

Checkbox

• [x] Confirm that this PR is linked to the dataset issue.
• [x] Create the dataloader script nusantara/nusa_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 _NUSANTARA_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 NusantaraConfig for the source schema and one for a nusantara 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_nusantara --path=nusantara/nusa_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.

[SamuelCahyawijaya]

/test dataset=su_emot

[github-actions[bot]]

Run result

Check test log here: https://github.com/IndoNLP/nusa-crowd/actions/runs/3163023077

[gentaiscool]

Hi @nadyadtm want to followup on the changes request by @muhsatrio. Let us know if you need any help :)

[nadyadtm]

Thank you for the corrections, I will do the correction and sent it soon

[nadyadtm]

Hello, I'm sorry I'm still newbie in git. But I have some problem in git rebase upstream/master. When I want to do that it is conflicted in previous commit, not the recent commit. Do I need to skip rebase step and push the file or should I do something else? Thanks in advance

[muhsatrio]

/test dataset=su_emot

[muhsatrio]

/test dataset=su_emot