Indonesian Question Answering
Indonesian Question Answering and its Datasets
Building Systems that automatically answer questions posed by humans in a natural language
By Wilson Wongso, Steven Limcorn and AI-Research.id team
June 1, 2021
Models
| Name | Description | Author | Link |
|---|---|---|---|
| IndoBERT-Lite base fine-tuned on Translated SQuAD v2 | IndoBERT-Lite trained by Indo Benchmark and fine-tuned on Translated SQuAD 2.0 for Q&A downstream task. | Akmal | HuggingFace |
| IndoBERT-Lite-SQuAD base fine-tuned on Full Translated SQuAD v2 | IndoBERT-Lite trained by Indo Benchmark and fine-tuned on Translated SQuAD 2.0 for Q&A downstream task. | Akmal | HuggingFace |
| SQuAD Bahasa Albert Model | Finetuned Albert base language model with translated SQuAD. Based on huseinzol05’s Albert Bahasa. | Akmal | HuggingFace |
| SQuAD IndoBERT-Lite Base Model | Fine-tuned IndoBERT-Lite from IndoBenchmark using Translated SQuAD datasets. | Akmal | HuggingFace |
| IndoBERT Base-Uncased fine-tuned on Translated Squad v2.0 | IndoBERT trained by IndoLEM and fine-tuned on Translated SQuAD 2.0 for Q&A downstream task. | Rifky | HuggingFace |
Datasets
| Name | Description | Author | Link |
|---|---|---|---|
| FacQA | The goal of the FacQA dataset is to find the answer to a question from a provided short passage from a news article. Each row in the FacQA dataset consists of a question, a short passage, and a label phrase, which can be found inside the corresponding short passage. There are six categories of questions: date, location, name, organization, person, and quantitative. | Ayu Purwarianti, Masatoshi Tsuchiya, and Seiichi Nakagawa | HuggingFace |
| TyDi QA | TyDi QA is a question answering dataset covering 11 typologically diverse languages with 204K question-answer pairs. The languages of TyDi QA are diverse with regard to their typology – the set of linguistic features that each language expresses – such that we expect models performing well on this set to generalize across a large number of the languages in the world. | Jonathan H. Clark and Eunsol Choi and Michael Collins and Dan Garrette and Tom Kwiatkowski and Vitaly Nikolaev and Jennimaria Palomaki | HuggingFace |
| mLAMA | This dataset provides the data for mLAMA, a multilingual version of LAMA. Regarding LAMA see https://github.com/facebookresearch/LAMA. For mLAMA the TREx and GoogleRE part of LAMA was considered and machine translated using Google Translate, and the Wikidata and Google Knowledge Graph API. | Nora Kassner and Philipp Dufter and Hinrich Schütze | HuggingFace |