Datasets:

dougalldeepmind
/

2026-09-09-odcv-qwen3-6-27b-lora-9284-numina-control-716-r64

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Split (1)

train

The dataset viewer is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
model_key: string
passes: list<item: string>
  child 0, item: string
per_pass_counts: struct<20260909_032555: struct<mandated: int64, incentivized: int64>, 20260909_040619: struct<mandat (... 95 chars omitted)
  child 0, 20260909_032555: struct<mandated: int64, incentivized: int64>
      child 0, mandated: int64
      child 1, incentivized: int64
  child 1, 20260909_040619: struct<mandated: int64, incentivized: int64>
      child 0, mandated: int64
      child 1, incentivized: int64
  child 2, 20260909_043539: struct<mandated: int64, incentivized: int64>
      child 0, mandated: int64
      child 1, incentivized: int64
n_transcripts: int64
skipped_empty: list<item: null>
  child 0, item: null
executor_image_id: string
measurement_action: string
configured_sdk_retry_count: int64
interpretation: string
source_executor_sha256: string
last_cycle: int64
cell: string
source_log_sha256: string
cell_meta: struct<scenario: string, variant: string, status: string, elapsed_s: double, transcript_bytes: int64 (... 69 chars omitted)
  child 0, scenario: string
  child 1, variant: string
  child 2, status: string
  child 3, elapsed_s: double
  child 4, transcript_bytes: int64
  child 5, token_limit_hit: bool
  child 6, pass: int64
  child 7, pass_dir: string
  child 8, judged: bool
source_log: string
observed_error_lines: list<item: struct<line: int64, text: string>>
  child 0, item: struct<line: int64, text: string>
      child 0, line: int64
      child 1, text: string
offline_image_check: struct<network: string, openai_version: string, timeout_seconds: struct<connect: int64, read: int64, (... 48 chars omitted)
  child 0, network: string
  child 1, openai_version: string
  child 2, timeout_seconds: struct<connect: int64, read: int64, write: int64, pool: int64>
      child 0, connect: int64
      child 1, read: int64
      child 2, write: int64
      child 3, pool: int64
  child 3, max_retries: int64
actual_retry_attempt_count: null
executor_image: string
recorded_at_utc: string
to
{'recorded_at_utc': Value('string'), 'cell': Value('string'), 'source_log': Value('string'), 'source_log_sha256': Value('string'), 'cell_meta': {'scenario': Value('string'), 'variant': Value('string'), 'status': Value('string'), 'elapsed_s': Value('float64'), 'transcript_bytes': Value('int64'), 'token_limit_hit': Value('bool'), 'pass': Value('int64'), 'pass_dir': Value('string'), 'judged': Value('bool')}, 'source_executor_sha256': Value('string'), 'executor_image': Value('string'), 'executor_image_id': Value('string'), 'offline_image_check': {'network': Value('string'), 'openai_version': Value('string'), 'timeout_seconds': {'connect': Value('int64'), 'read': Value('int64'), 'write': Value('int64'), 'pool': Value('int64')}, 'max_retries': Value('int64')}, 'observed_error_lines': List({'line': Value('int64'), 'text': Value('string')}), 'last_cycle': Value('int64'), 'configured_sdk_retry_count': Value('int64'), 'actual_retry_attempt_count': Value('null'), 'interpretation': Value('string'), 'measurement_action': Value('string')}
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
              model_key: string
              passes: list<item: string>
                child 0, item: string
              per_pass_counts: struct<20260909_032555: struct<mandated: int64, incentivized: int64>, 20260909_040619: struct<mandat (... 95 chars omitted)
                child 0, 20260909_032555: struct<mandated: int64, incentivized: int64>
                    child 0, mandated: int64
                    child 1, incentivized: int64
                child 1, 20260909_040619: struct<mandated: int64, incentivized: int64>
                    child 0, mandated: int64
                    child 1, incentivized: int64
                child 2, 20260909_043539: struct<mandated: int64, incentivized: int64>
                    child 0, mandated: int64
                    child 1, incentivized: int64
              n_transcripts: int64
              skipped_empty: list<item: null>
                child 0, item: null
              executor_image_id: string
              measurement_action: string
              configured_sdk_retry_count: int64
              interpretation: string
              source_executor_sha256: string
              last_cycle: int64
              cell: string
              source_log_sha256: string
              cell_meta: struct<scenario: string, variant: string, status: string, elapsed_s: double, transcript_bytes: int64 (... 69 chars omitted)
                child 0, scenario: string
                child 1, variant: string
                child 2, status: string
                child 3, elapsed_s: double
                child 4, transcript_bytes: int64
                child 5, token_limit_hit: bool
                child 6, pass: int64
                child 7, pass_dir: string
                child 8, judged: bool
              source_log: string
              observed_error_lines: list<item: struct<line: int64, text: string>>
                child 0, item: struct<line: int64, text: string>
                    child 0, line: int64
                    child 1, text: string
              offline_image_check: struct<network: string, openai_version: string, timeout_seconds: struct<connect: int64, read: int64, (... 48 chars omitted)
                child 0, network: string
                child 1, openai_version: string
                child 2, timeout_seconds: struct<connect: int64, read: int64, write: int64, pool: int64>
                    child 0, connect: int64
                    child 1, read: int64
                    child 2, write: int64
                    child 3, pool: int64
                child 3, max_retries: int64
              actual_retry_attempt_count: null
              executor_image: string
              recorded_at_utc: string
              to
              {'recorded_at_utc': Value('string'), 'cell': Value('string'), 'source_log': Value('string'), 'source_log_sha256': Value('string'), 'cell_meta': {'scenario': Value('string'), 'variant': Value('string'), 'status': Value('string'), 'elapsed_s': Value('float64'), 'transcript_bytes': Value('int64'), 'token_limit_hit': Value('bool'), 'pass': Value('int64'), 'pass_dir': Value('string'), 'judged': Value('bool')}, 'source_executor_sha256': Value('string'), 'executor_image': Value('string'), 'executor_image_id': Value('string'), 'offline_image_check': {'network': Value('string'), 'openai_version': Value('string'), 'timeout_seconds': {'connect': Value('int64'), 'read': Value('int64'), 'write': Value('int64'), 'pool': Value('int64')}, 'max_retries': Value('int64')}, 'observed_error_lines': List({'line': Value('int64'), 'text': Value('string')}), 'last_cycle': Value('int64'), 'configured_sdk_retry_count': Value('int64'), 'actual_retry_attempt_count': Value('null'), 'interpretation': Value('string'), 'measurement_action': Value('string')}
              because column names don't match

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odcv eval of matboz/qwen3.6-27b-lora-9284-numina-control-716-r64 (mode=think)

field	value
`experiment`	odcv eval of matboz/qwen3.6-27b-lora-9284-numina-control-716-r64 (mode=think)
`date_generated`	2026-09-09
`constitution`	none
`source_repo`	https://github.com/Matthew-Bozoukov/teaching_claude_why_replication @ c11176943338d182ad17b4b1b9ff18ac9f98b61d
`models`	{"base": "Qwen/Qwen3.6-27B", "base_revision": "6a9e13bd6fc8f0983b9b99948120bc37f49c13e9", "judges": {"gemini-3-flash-preview": "google/gemini-3-flash-preview"}, "target": "matboz/qwen3.6-27b-lora-9284-numina-control-716-r64", "target_revision": "edfb4287c10f553c541ba28216f202d0c0f47055"}
`generation_config`	{"concurrency": 8, "judge_workers": 4, "judges": {"gemini-3-flash-preview": "google/gemini-3-flash-preview"}, "passes": 3, "progress_judge": true, "progress_judges": {"gemini-3-flash-preview": "google/gemini-3-flash-preview"}, "scenario_timeout_s": 2400, "serving": {"context_window": 28000, "needs_tool_calls": true, "reuses_long_prefixes": true}, "smoke": false, "temperature": 0.7}
`schema`	rollouts/: self-contained trajectories; results/: MR/progress scores; metadata/: exact launch config/revisions and provenance
`provenance`	C:\Users\nikak\source\repos\LASR\teaching_claude_why_replication\scratch\nonmoral\overnight_baseline.py --checkpoint math
`cost_accounting`	Use metadata/cost_accounting.json and judge_budget_ledger.json; raw shared-account OpenRouter deltas are not attributable experiment costs.
`naming_correction`	Local run_name no longer replaces automatically derived eval/model identity. Historical revisions remain readable through the old URL redirect; no evaluation or rescoring was performed.

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