Datasets:

---

yuxiaoyang

/

opsd-qwen3-1p7b-origin75-math500-eval-results

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
base_model: string
dataset: string
enable_thinking: bool
temperature: int64
top_p: int64
top_k: int64
min_p: int64
presence_penalty: int64
max_new_tokens: int64
val_n: int64
num_problems: int64
total_solutions: int64
pass_at_n: int64
pass_at_n_pct: double
average_at_n: int64
average_at_n_pct: double
majority_vote_at_n: int64
majority_vote_at_n_pct: double
formatted_count: int64
format_rate: double
results: struct<correct: bool, formatted: bool, full_generation: string, generations: list<item: struct<corre (... 243 chars omitted)
  child 0, correct: bool
  child 1, formatted: bool
  child 2, full_generation: string
  child 3, generations: list<item: struct<correct: bool, formatted: bool, full_generation: string, predicted_answer: string> (... 1 chars omitted)
      child 0, item: struct<correct: bool, formatted: bool, full_generation: string, predicted_answer: string>
          child 0, correct: bool
          child 1, formatted: bool
          child 2, full_generation: string
          child 3, predicted_answer: string
  child 4, ground_truth: string
  child 5, majority_vote_correct: bool
  child 6, num_correct: int64
  child 7, pass_at_n: bool
  child 8, predicted_answer: string
  child 9, problem: string
  child 10, problem_id: int64
  child 11, val_n: int64
run_id: string
source_repo: string
checkpoint: string
run_label: string
eval_settings: struct<val_n: int64, max_new_tokens: int64, max_model_len: int64, enable_thinking: bool, temperature (... 79 chars omitted)
  child 0, val_n: int64
  child 1, max_new_tokens: int64
  child 2, max_model_len: int64
  child 3, enable_thinking: bool
  child 4, temperature: double
  child 5, top_p: double
  child 6, top_k: int64
  child 7, min_p: double
  child 8, presence_penalty: double
-- schema metadata --
pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 2796
to
{'run_id': Value('string'), 'run_label': Value('string'), 'source_repo': Value('string'), 'base_model': Value('string'), 'checkpoint': Value('string'), 'dataset': Value('string'), 'eval_settings': {'val_n': Value('int64'), 'max_new_tokens': Value('int64'), 'max_model_len': Value('int64'), 'enable_thinking': Value('bool'), 'temperature': Value('float64'), 'top_p': Value('float64'), 'top_k': Value('int64'), 'min_p': Value('float64'), 'presence_penalty': Value('float64')}, 'results': List({'source_repo': Value('string'), 'checkpoint': Value('string'), 'dataset': Value('string'), 'gpu_group': Value('string'), 'json': Value('string'), 'started_at': Value('timestamp[s]'), 'finished_at': Value('timestamp[s]'), 'summary': {'num_problems': Value('int64'), 'val_n': Value('int64'), 'max_new_tokens': Value('int64'), 'enable_thinking': Value('bool'), 'pass_at_n_pct': Value('float64'), 'average_at_n_pct': Value('float64'), 'majority_vote_at_n_pct': Value('float64'), 'format_rate': Value('float64')}})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 246, in _generate_tables
                  pa_table = paj.read_json(
                             ^^^^^^^^^^^^^^
                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
              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 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                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 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in 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/json/json.py", line 295, in _generate_tables
                  yield Key(shard_idx, 0), self._cast_table(pa_table)
                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              base_model: string
              dataset: string
              enable_thinking: bool
              temperature: int64
              top_p: int64
              top_k: int64
              min_p: int64
              presence_penalty: int64
              max_new_tokens: int64
              val_n: int64
              num_problems: int64
              total_solutions: int64
              pass_at_n: int64
              pass_at_n_pct: double
              average_at_n: int64
              average_at_n_pct: double
              majority_vote_at_n: int64
              majority_vote_at_n_pct: double
              formatted_count: int64
              format_rate: double
              results: struct<correct: bool, formatted: bool, full_generation: string, generations: list<item: struct<corre (... 243 chars omitted)
                child 0, correct: bool
                child 1, formatted: bool
                child 2, full_generation: string
                child 3, generations: list<item: struct<correct: bool, formatted: bool, full_generation: string, predicted_answer: string> (... 1 chars omitted)
                    child 0, item: struct<correct: bool, formatted: bool, full_generation: string, predicted_answer: string>
                        child 0, correct: bool
                        child 1, formatted: bool
                        child 2, full_generation: string
                        child 3, predicted_answer: string
                child 4, ground_truth: string
                child 5, majority_vote_correct: bool
                child 6, num_correct: int64
                child 7, pass_at_n: bool
                child 8, predicted_answer: string
                child 9, problem: string
                child 10, problem_id: int64
                child 11, val_n: int64
              run_id: string
              source_repo: string
              checkpoint: string
              run_label: string
              eval_settings: struct<val_n: int64, max_new_tokens: int64, max_model_len: int64, enable_thinking: bool, temperature (... 79 chars omitted)
                child 0, val_n: int64
                child 1, max_new_tokens: int64
                child 2, max_model_len: int64
                child 3, enable_thinking: bool
                child 4, temperature: double
                child 5, top_p: double
                child 6, top_k: int64
                child 7, min_p: double
                child 8, presence_penalty: double
              -- schema metadata --
              pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 2796
              to
              {'run_id': Value('string'), 'run_label': Value('string'), 'source_repo': Value('string'), 'base_model': Value('string'), 'checkpoint': Value('string'), 'dataset': Value('string'), 'eval_settings': {'val_n': Value('int64'), 'max_new_tokens': Value('int64'), 'max_model_len': Value('int64'), 'enable_thinking': Value('bool'), 'temperature': Value('float64'), 'top_p': Value('float64'), 'top_k': Value('int64'), 'min_p': Value('float64'), 'presence_penalty': Value('float64')}, 'results': List({'source_repo': Value('string'), 'checkpoint': Value('string'), 'dataset': Value('string'), 'gpu_group': Value('string'), 'json': Value('string'), 'started_at': Value('timestamp[s]'), 'finished_at': Value('timestamp[s]'), 'summary': {'num_problems': Value('int64'), 'val_n': Value('int64'), 'max_new_tokens': Value('int64'), 'enable_thinking': Value('bool'), 'pass_at_n_pct': Value('float64'), 'average_at_n_pct': Value('float64'), 'majority_vote_at_n_pct': Value('float64'), 'format_rate': Value('float64')}})}
              because column names don't match