The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ParserError
Message: Error tokenizing data. C error: Expected 5 fields in line 3, saw 6
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 247, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 4196, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2533, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2711, in iter
for key, pa_table in ex_iterable.iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2249, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/csv/csv.py", line 198, in _generate_tables
for batch_idx, df in enumerate(csv_file_reader):
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
return self.get_chunk()
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
return self.read(nrows=size)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1923, in read
) = self._engine.read( # type: ignore[attr-defined]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
chunks = self._reader.read_low_memory(nrows)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Expected 5 fields in line 3, saw 6Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
BulMMLU Dataset
Objective of the project
The BulMMLU Benchmark is developed within the project IfGPT: Infrastructure for Fine-tuning Pre-trained Large Language Models aims to establish a freely accessible infrastructure for the selection and pre-processing of large datasets for Bulgarian as well as tailored data for particular industries and fine-tuning suitable freely available large language models for specific purposes.
BulMMLU Dataset
The BulMMLU dataset is a subject-specific benchmark for evaluating large language models on Bulgarian language, culture, economy, and history. It contains 523 questions in its test section and 4 questions in its evaluation section. It is designed following the MMLU (Massive Multitask Language Understanding) benchmark. MMLU was created to assess a model’s knowledge and reasoning abilities across a wide range of subjects, including mathematics, history, law, medicine, computer science, and many others. The original MMLU benchmark covers 57 academic and professional disciplines using multiple-choice questions. MMLU focuses not only on general facts but also on facts and specifics related to the English language, American history, law, and similar topics. In contrast, BulMMLU is a benchmark related to the Bulgarian language and facts about Bulgaria. It contains four subjects: the April Uprising, Contemporary Bulgarian Poets, the Modern Economy of Bulgaria, and Bulgarian Spelling and Grammar.
This work is part of the project Infrastructure for Fine-tuning Pre-trained Large Language Models, Grant Agreement No. ПВУ – 55 from 12.12.2024 /BG-RRP-2.017-0030-C01/.
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