Datasets:

christian-hoang-04
/

vi-squad

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
benchmark_name: string
model_slug: string
total_samples: int64
provider_reported_cost_usd: double
source_runs: int64
samples: struct<context: string, dataset_id: int64, idx: int64, in_tokens: int64, out_tokens: int64, prompt:  (... 88 chars omitted)
  child 0, context: string
  child 1, dataset_id: int64
  child 2, idx: int64
  child 3, in_tokens: int64
  child 4, out_tokens: int64
  child 5, prompt: string
  child 6, provider_cost_usd: double
  child 7, question: string
  child 8, raw_output: string
  child 9, source: string
data: list<item: struct<id: int64, question: string, context: string>>
  child 0, item: struct<id: int64, question: string, context: string>
      child 0, id: int64
      child 1, question: string
      child 2, context: string
__count__: int64
-- schema metadata --
pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 893
to
{'__count__': Value('int64'), 'data': List({'id': Value('int64'), 'question': Value('string'), 'context': Value('string')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Missing a name for object member. in row 0
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 339, in _generate_tables
                  yield Key(shard_idx, 0), self._cast_table(pa_table)
                                           ~~~~~~~~~~~~~~~~^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              benchmark_name: string
              model_slug: string
              total_samples: int64
              provider_reported_cost_usd: double
              source_runs: int64
              samples: struct<context: string, dataset_id: int64, idx: int64, in_tokens: int64, out_tokens: int64, prompt:  (... 88 chars omitted)
                child 0, context: string
                child 1, dataset_id: int64
                child 2, idx: int64
                child 3, in_tokens: int64
                child 4, out_tokens: int64
                child 5, prompt: string
                child 6, provider_cost_usd: double
                child 7, question: string
                child 8, raw_output: string
                child 9, source: string
              data: list<item: struct<id: int64, question: string, context: string>>
                child 0, item: struct<id: int64, question: string, context: string>
                    child 0, id: int64
                    child 1, question: string
                    child 2, context: string
              __count__: int64
              -- schema metadata --
              pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 893
              to
              {'__count__': Value('int64'), 'data': List({'id': Value('int64'), 'question': Value('string'), 'context': Value('string')})}
              because column names don't match

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Vietnamese Vi-SQuAD Benchmark

Question-only release of the Vietnamese Vi-SQuAD benchmark used by the ViLLM evaluation project.

vi_squad_benchmark_question_only.json: 3,310 Vietnamese extractive reading-comprehension examples.
Each example contains id, question, and context.

This release intentionally contains benchmark inputs only. Reference answers and model generations are not included in this file.

Model outputs

visquad_3310_gpt5.6_luna_outputs.json: merged GPT-5.6 Luna outputs covering all 3,310 benchmark records.

The output artifact includes model generations and run metadata. It is an evaluation artifact, not a gold-answer annotation.

Provenance

The file is exported from the ViLLM project’s VMLU benchmark resources. Please consult the upstream VMLU/Vi-SQuAD publication and dataset terms before using it for training or redistribution.

Intended use

The dataset is intended for evaluation of Vietnamese-capable language models on context-grounded question answering.

Limitations

This repository does not independently relicense the underlying benchmark. Users are responsible for checking the original source license and citation requirements.

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Total file size:

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Vietnamese Vi-SQuAD Benchmark

Contents

Model outputs

Provenance

Intended use

Limitations