Datasets:

---

lilywchen

/

lucky-initialization-posttraining-100m-v1

like 0

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
batch_size: int64
limit_per_atomic_task: int64
max_length: int64
model_path: string
model_safetensors_sha256: string
olmes_commit: string
random_subsample_seed: int64
run_id: string
schema_version: int64
status: string
suite_members: struct<arc:rc::olmes:full: list<item: string>, arc:rc:bpb::olmes:full: list<item: string>, basic_ski (... 372 chars omitted)
  child 0, arc:rc::olmes:full: list<item: string>
      child 0, item: string
  child 1, arc:rc:bpb::olmes:full: list<item: string>
      child 0, item: string
  child 2, basic_skills:rc::olmes: list<item: string>
      child 0, item: string
  child 3, basic_skills:rc:bpb::olmes: list<item: string>
      child 0, item: string
  child 4, mmlu:rc::olmes: list<item: string>
      child 0, item: string
  child 5, mmlu:rc:bpb::olmes: list<item: string>
      child 0, item: string
  child 6, mt_mbpp_v2fix: list<item: string>
      child 0, item: string
  child 7, olmo3:base_easy:code_bpb: list<item: string>
      child 0, item: string
  child 8, olmo3:base_easy:math_bpb: list<item: string>
      child 0, item: string
  child 9, olmo3:base_easy:qa_bpb: list<item: string>
      child 0, item: string
  child 10, olmo3:base_easy:qa_rc: list<item: string>
      child 0, item: string
tasks: list<item: string>
  child 0, item: string
per_example_mean: double
data_sha256: string
per_example_std: double
source_examples: int64
mean_cross_entropy: double
assistant_tokens: int64
per_example_q95: double
examples: int64
per_example_q50: double
elapsed_seconds: double
per_example_q05: double
unscorable_examples: int64
to
{'assistant_tokens': Value('int64'), 'data_sha256': Value('string'), 'elapsed_seconds': Value('float64'), 'examples': Value('int64'), 'mean_cross_entropy': Value('float64'), 'model_safetensors_sha256': Value('string'), 'per_example_mean': Value('float64'), 'per_example_q05': Value('float64'), 'per_example_q50': Value('float64'), 'per_example_q95': Value('float64'), 'per_example_std': Value('float64'), 'schema_version': Value('int64'), 'source_examples': Value('int64'), 'status': Value('string'), 'unscorable_examples': Value('int64')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                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
              batch_size: int64
              limit_per_atomic_task: int64
              max_length: int64
              model_path: string
              model_safetensors_sha256: string
              olmes_commit: string
              random_subsample_seed: int64
              run_id: string
              schema_version: int64
              status: string
              suite_members: struct<arc:rc::olmes:full: list<item: string>, arc:rc:bpb::olmes:full: list<item: string>, basic_ski (... 372 chars omitted)
                child 0, arc:rc::olmes:full: list<item: string>
                    child 0, item: string
                child 1, arc:rc:bpb::olmes:full: list<item: string>
                    child 0, item: string
                child 2, basic_skills:rc::olmes: list<item: string>
                    child 0, item: string
                child 3, basic_skills:rc:bpb::olmes: list<item: string>
                    child 0, item: string
                child 4, mmlu:rc::olmes: list<item: string>
                    child 0, item: string
                child 5, mmlu:rc:bpb::olmes: list<item: string>
                    child 0, item: string
                child 6, mt_mbpp_v2fix: list<item: string>
                    child 0, item: string
                child 7, olmo3:base_easy:code_bpb: list<item: string>
                    child 0, item: string
                child 8, olmo3:base_easy:math_bpb: list<item: string>
                    child 0, item: string
                child 9, olmo3:base_easy:qa_bpb: list<item: string>
                    child 0, item: string
                child 10, olmo3:base_easy:qa_rc: list<item: string>
                    child 0, item: string
              tasks: list<item: string>
                child 0, item: string
              per_example_mean: double
              data_sha256: string
              per_example_std: double
              source_examples: int64
              mean_cross_entropy: double
              assistant_tokens: int64
              per_example_q95: double
              examples: int64
              per_example_q50: double
              elapsed_seconds: double
              per_example_q05: double
              unscorable_examples: int64
              to
              {'assistant_tokens': Value('int64'), 'data_sha256': Value('string'), 'elapsed_seconds': Value('float64'), 'examples': Value('int64'), 'mean_cross_entropy': Value('float64'), 'model_safetensors_sha256': Value('string'), 'per_example_mean': Value('float64'), 'per_example_q05': Value('float64'), 'per_example_q50': Value('float64'), 'per_example_q95': Value('float64'), 'per_example_std': Value('float64'), 'schema_version': Value('int64'), 'source_examples': Value('int64'), 'status': Value('string'), 'unscorable_examples': Value('int64')}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset