Datasets:

---

vedangfake

/

chess-bench-results

like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
position_id: string
model: string
task: string
task_category: string
representation: string
run_id: timestamp[s]
condition: string
value: string
latency_ms: double
finished: bool
attempts: int64
max_new_tokens: int64
thinking_enabled: bool
force_answer_prompt: bool
prompt: string
model_input: string
output: string
reasoning: string
reasoning_chars: int64
answer_chars: int64
token_usage: struct<input_tokens: int64, output_tokens: int64, reasoning_tokens: null, total_tokens: int64, cache (... 286 chars omitted)
  child 0, input_tokens: int64
  child 1, output_tokens: int64
  child 2, reasoning_tokens: null
  child 3, total_tokens: int64
  child 4, cache_read_tokens: null
  child 5, cache_write_tokens: null
  child 6, cache_hit_tokens: null
  child 7, cache_miss_tokens: null
  child 8, usage_source: string
  child 9, usage_complete: bool
  child 10, stream_events: null
  child 11, time_to_first_token_ms: null
  child 12, generation_seconds: double
  child 13, output_tokens_per_second: double
  child 14, reasoning_tokens_per_second: null
cache_hit: null
cache_miss: null
fallback: null
api_error: null
no_answer_reason: null
position_metadata: struct<fen: string, task_extra: struct<instruction: string, input: string, output: string, candidate (... 69 chars omitted)
  child 0, fen: string
  child 1, task_extra: struct<instruction: string, input: string, output: string, candidate_a: string, candidate_b: string, (... 36 chars omitted)
      child 0, instruction: string
      child 1, 
...
 cache_hit_tokens_n: int64
      child 34, cache_hit_tokens_total: null
      child 35, cache_hit_tokens_mean: null
      child 36, cache_hit_tokens_median: null
      child 37, cache_hit_tokens_p95: null
      child 38, cache_miss_tokens_n: int64
      child 39, cache_miss_tokens_total: null
      child 40, cache_miss_tokens_mean: null
      child 41, cache_miss_tokens_median: null
      child 42, cache_miss_tokens_p95: null
      child 43, generation_seconds_n: int64
      child 44, generation_seconds_total: double
      child 45, generation_seconds_mean: double
      child 46, generation_seconds_median: double
      child 47, generation_seconds_p95: double
      child 48, output_tokens_per_second_n: int64
      child 49, output_tokens_per_second_total: double
      child 50, output_tokens_per_second_mean: double
      child 51, output_tokens_per_second_median: double
      child 52, output_tokens_per_second_p95: double
      child 53, reasoning_tokens_per_second_n: int64
      child 54, reasoning_tokens_per_second_total: null
      child 55, reasoning_tokens_per_second_mean: null
      child 56, reasoning_tokens_per_second_median: null
      child 57, reasoning_tokens_per_second_p95: null
      child 58, time_to_first_token_ms_n: int64
      child 59, time_to_first_token_ms_total: null
      child 60, time_to_first_token_ms_mean: null
      child 61, time_to_first_token_ms_median: null
      child 62, time_to_first_token_ms_p95: null
cell: string
generated_at: timestamp[s]
to
{'cell': Value('string'), 'run_id': Value('timestamp[s]'), 'model': Value('string'), 'task': Value('string'), 'variant': Value('string'), 'task_category': Value('string'), 'thinking_enabled': Value('bool'), 'max_new_tokens': Value('int64'), 'generated_at': Value('timestamp[s]'), 'metrics': {'accuracy': {'n': Value('int64'), 'n_attempted': Value('int64'), 'api_error': Value('int64'), 'parse_rate': Value('float64'), 'accuracy_strict': Value('float64'), 'accuracy_of_parsed': Value('float64'), 'correct': Value('int64'), 'wrong': Value('int64'), 'no_answer': Value('int64'), 'parse_error': Value('int64')}, 'token_usage': {'sample_count': Value('int64'), 'fallback_counts': {}, 'missing_exact_usage': Value('int64'), 'input_tokens_n': Value('int64'), 'input_tokens_total': Value('float64'), 'input_tokens_mean': Value('float64'), 'input_tokens_median': Value('float64'), 'input_tokens_p95': Value('float64'), 'output_tokens_n': Value('int64'), 'output_tokens_total': Value('float64'), 'output_tokens_mean': Value('float64'), 'output_tokens_median': Value('float64'), 'output_tokens_p95': Value('float64'), 'reasoning_tokens_n': Value('int64'), 'reasoning_tokens_total': Value('null'), 'reasoning_tokens_mean': Value('null'), 'reasoning_tokens_median': Value('null'), 'reasoning_tokens_p95': Value('null'), 'total_tokens_n': Value('int64'), 'total_tokens_total': Value('float64'), 'total_tokens_mean': Value('float64'), 'total_tokens_median': Value('float64'), 'total_tokens_p95': Value('float64'), '
...
representation': Value('string'), 'run_id': Value('timestamp[s]'), 'position_id': Value('string'), 'prompt': Value('string'), 'thinking': Value('string'), 'model_answer': Value('string'), 'model_move': Value('string'), 'correct_answer': {'move': Value('string'), 'note': Value('string')}, 'verdict': Value('string'), 'no_answer_reason': Value('null'), 'compliance': Value('bool'), 'format': Value('null'), 'fallback': Value('null'), 'cache_hit_tokens': Value('null'), 'cache_miss_tokens': Value('null'), 'token_usage': {'input_tokens': Value('int64'), 'output_tokens': Value('int64'), 'reasoning_tokens': Value('null'), 'total_tokens': Value('int64'), 'cache_read_tokens': Value('null'), 'cache_write_tokens': Value('null'), 'cache_hit_tokens': Value('null'), 'cache_miss_tokens': Value('null'), 'usage_source': Value('string'), 'usage_complete': Value('bool'), 'stream_events': Value('null'), 'time_to_first_token_ms': Value('null'), 'generation_seconds': Value('float64'), 'output_tokens_per_second': Value('float64'), 'reasoning_tokens_per_second': Value('null')}, 'position_metadata': {'fen': Value('string'), 'task_extra': {'instruction': Value('string'), 'input': Value('string'), 'output': Value('string'), 'candidate_a': Value('string'), 'candidate_b': Value('string'), 'truth_label': Value('string'), 'theme': Value('string')}}, 'max_new_tokens': Value('int64'), 'attempts': Value('int64'), 'thinking_enabled': Value('bool'), 'latency_ms': Value('float64'), 'output_tokens': Value('null')})}
because column names don't match
Traceback:    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 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
              position_id: string
              model: string
              task: string
              task_category: string
              representation: string
              run_id: timestamp[s]
              condition: string
              value: string
              latency_ms: double
              finished: bool
              attempts: int64
              max_new_tokens: int64
              thinking_enabled: bool
              force_answer_prompt: bool
              prompt: string
              model_input: string
              output: string
              reasoning: string
              reasoning_chars: int64
              answer_chars: int64
              token_usage: struct<input_tokens: int64, output_tokens: int64, reasoning_tokens: null, total_tokens: int64, cache (... 286 chars omitted)
                child 0, input_tokens: int64
                child 1, output_tokens: int64
                child 2, reasoning_tokens: null
                child 3, total_tokens: int64
                child 4, cache_read_tokens: null
                child 5, cache_write_tokens: null
                child 6, cache_hit_tokens: null
                child 7, cache_miss_tokens: null
                child 8, usage_source: string
                child 9, usage_complete: bool
                child 10, stream_events: null
                child 11, time_to_first_token_ms: null
                child 12, generation_seconds: double
                child 13, output_tokens_per_second: double
                child 14, reasoning_tokens_per_second: null
              cache_hit: null
              cache_miss: null
              fallback: null
              api_error: null
              no_answer_reason: null
              position_metadata: struct<fen: string, task_extra: struct<instruction: string, input: string, output: string, candidate (... 69 chars omitted)
                child 0, fen: string
                child 1, task_extra: struct<instruction: string, input: string, output: string, candidate_a: string, candidate_b: string, (... 36 chars omitted)
                    child 0, instruction: string
                    child 1, 
              ...
               cache_hit_tokens_n: int64
                    child 34, cache_hit_tokens_total: null
                    child 35, cache_hit_tokens_mean: null
                    child 36, cache_hit_tokens_median: null
                    child 37, cache_hit_tokens_p95: null
                    child 38, cache_miss_tokens_n: int64
                    child 39, cache_miss_tokens_total: null
                    child 40, cache_miss_tokens_mean: null
                    child 41, cache_miss_tokens_median: null
                    child 42, cache_miss_tokens_p95: null
                    child 43, generation_seconds_n: int64
                    child 44, generation_seconds_total: double
                    child 45, generation_seconds_mean: double
                    child 46, generation_seconds_median: double
                    child 47, generation_seconds_p95: double
                    child 48, output_tokens_per_second_n: int64
                    child 49, output_tokens_per_second_total: double
                    child 50, output_tokens_per_second_mean: double
                    child 51, output_tokens_per_second_median: double
                    child 52, output_tokens_per_second_p95: double
                    child 53, reasoning_tokens_per_second_n: int64
                    child 54, reasoning_tokens_per_second_total: null
                    child 55, reasoning_tokens_per_second_mean: null
                    child 56, reasoning_tokens_per_second_median: null
                    child 57, reasoning_tokens_per_second_p95: null
                    child 58, time_to_first_token_ms_n: int64
                    child 59, time_to_first_token_ms_total: null
                    child 60, time_to_first_token_ms_mean: null
                    child 61, time_to_first_token_ms_median: null
                    child 62, time_to_first_token_ms_p95: null
              cell: string
              generated_at: timestamp[s]
              to
              {'cell': Value('string'), 'run_id': Value('timestamp[s]'), 'model': Value('string'), 'task': Value('string'), 'variant': Value('string'), 'task_category': Value('string'), 'thinking_enabled': Value('bool'), 'max_new_tokens': Value('int64'), 'generated_at': Value('timestamp[s]'), 'metrics': {'accuracy': {'n': Value('int64'), 'n_attempted': Value('int64'), 'api_error': Value('int64'), 'parse_rate': Value('float64'), 'accuracy_strict': Value('float64'), 'accuracy_of_parsed': Value('float64'), 'correct': Value('int64'), 'wrong': Value('int64'), 'no_answer': Value('int64'), 'parse_error': Value('int64')}, 'token_usage': {'sample_count': Value('int64'), 'fallback_counts': {}, 'missing_exact_usage': Value('int64'), 'input_tokens_n': Value('int64'), 'input_tokens_total': Value('float64'), 'input_tokens_mean': Value('float64'), 'input_tokens_median': Value('float64'), 'input_tokens_p95': Value('float64'), 'output_tokens_n': Value('int64'), 'output_tokens_total': Value('float64'), 'output_tokens_mean': Value('float64'), 'output_tokens_median': Value('float64'), 'output_tokens_p95': Value('float64'), 'reasoning_tokens_n': Value('int64'), 'reasoning_tokens_total': Value('null'), 'reasoning_tokens_mean': Value('null'), 'reasoning_tokens_median': Value('null'), 'reasoning_tokens_p95': Value('null'), 'total_tokens_n': Value('int64'), 'total_tokens_total': Value('float64'), 'total_tokens_mean': Value('float64'), 'total_tokens_median': Value('float64'), 'total_tokens_p95': Value('float64'), '
              ...
              representation': Value('string'), 'run_id': Value('timestamp[s]'), 'position_id': Value('string'), 'prompt': Value('string'), 'thinking': Value('string'), 'model_answer': Value('string'), 'model_move': Value('string'), 'correct_answer': {'move': Value('string'), 'note': Value('string')}, 'verdict': Value('string'), 'no_answer_reason': Value('null'), 'compliance': Value('bool'), 'format': Value('null'), 'fallback': Value('null'), 'cache_hit_tokens': Value('null'), 'cache_miss_tokens': Value('null'), 'token_usage': {'input_tokens': Value('int64'), 'output_tokens': Value('int64'), 'reasoning_tokens': Value('null'), 'total_tokens': Value('int64'), 'cache_read_tokens': Value('null'), 'cache_write_tokens': Value('null'), 'cache_hit_tokens': Value('null'), 'cache_miss_tokens': Value('null'), 'usage_source': Value('string'), 'usage_complete': Value('bool'), 'stream_events': Value('null'), 'time_to_first_token_ms': Value('null'), 'generation_seconds': Value('float64'), 'output_tokens_per_second': Value('float64'), 'reasoning_tokens_per_second': Value('null')}, 'position_metadata': {'fen': Value('string'), 'task_extra': {'instruction': Value('string'), 'input': Value('string'), 'output': Value('string'), 'candidate_a': Value('string'), 'candidate_b': Value('string'), 'truth_label': Value('string'), 'theme': Value('string')}}, 'max_new_tokens': Value('int64'), 'attempts': Value('int64'), 'thinking_enabled': Value('bool'), 'latency_ms': Value('float64'), 'output_tokens': Value('null')})}
              because column names don't match