update readme

README.md

@@ -1,8 +1,97 @@
 ---
+language:
+- id
 license: apache-2.0
 task_categories:
 - question-answering
 pretty_name: TyDi QA Indonesian
 size_categories:
 - 100K<n<1M
----
+source_datasets:
+- google-research-datasets/tydiqa
+configs:
+- config_name: primary_task
+  data_files:
+  - split: train
+    path: "train.parquet"
+  - split: validation
+    path: "valid.parquet"
+---
+
+# TyDi QA - Indonesian
+
+This is a dataset card for TyDi QA specifically for indonesian subset.
+
+This work only copy from the original dataset https://huggingface.co/datasets/google-research-datasets/tydiqa
+
+## Dataset Description
+
+### Dataset Summary
+
+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. It contains language phenomena that would not be found in English-only corpora. To provide a realistic
+information-seeking task and avoid priming effects, questions are written by people who want to know the answer, but
+don’t know the answer yet, (unlike SQuAD and its descendents) and the data is collected directly in each language without
+the use of translation (unlike MLQA and XQuAD).
+
+## Dataset Structure
+
+### Data Instances
+
+#### primary_task
+
+An example of 'validation' looks as follows.
+```
+This example was too long and was cropped:
+
+{
+    'annotations': {'minimal_answers_end_byte': array([-1], dtype=int32),
+                 'minimal_answers_start_byte': array([-1], dtype=int32),
+                 'passage_answer_candidate_index': array([-1], dtype=int32),
+                 'yes_no_answer': array(['NONE'], dtype=object)},
+    'document_plaintext': '\n transl.\n\n Ras (dari bahasa Prancis race, yang sendirinya dari '
+    'document_title': 'Ras manusia',
+    'document_url': 'https://id.wikipedia.org/wiki/Ras%20manusia',
+    'language': 'indonesian',
+    'passage_answer_candidates': {'plaintext_end_byte': array([  659,   843,  1195,  1353,  2125,  3607,  4161,  4508,  4740,
+        6530,  7665,  7999,  8561,  9209,  9615, 10690, 11126, 11979,
+       12746, 13304, 13486, 15385, 17455, 17505], dtype=int32),
+                               'plaintext_start_byte': array([    1,   660,   844,  1196,  1354,  2126,  3608,  4198,  4509,
+        4741,  6531,  7666,  8000,  8562,  9249,  9616, 10774, 11127,
+       11980, 12747, 13325, 13503, 15400, 17459], dtype=int32)},
+    'question_text': 'berapakah jenis ras yang ada didunia?'}
+```
+
+
+### Data Fields
+
+The data fields are the same among all splits.
+
+#### primary_task
+- `passage_answer_candidates`: a dictionary feature containing:
+  - `plaintext_start_byte`: a `int32` feature.
+  - `plaintext_end_byte`: a `int32` feature.
+- `question_text`: a `string` feature.
+- `document_title`: a `string` feature.
+- `language`: a `string` feature.
+- `annotations`: a dictionary feature containing:
+  - `passage_answer_candidate_index`: a `int32` feature.
+  - `minimal_answers_start_byte`: a `int32` feature.
+  - `minimal_answers_end_byte`: a `int32` feature.
+  - `yes_no_answer`: a `string` feature.
+- `document_plaintext`: a `string` feature.
+- `document_url`: a `string` feature.
+
+
+```
+@article{tydiqa,
+title   = {TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages},
+author  = {Jonathan H. Clark and Eunsol Choi and Michael Collins and Dan Garrette and Tom Kwiatkowski and Vitaly Nikolaev and Jennimaria Palomaki}
+year    = {2020},
+journal = {Transactions of the Association for Computational Linguistics}
+}
+
+```
+