Dataset Viewer
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: ValueError
Message: Expected object or value
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
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
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string 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 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 304, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Expected object or valueNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
York Milestone Project — Phase 1 experiment artifacts (per-example results & manifests)
Raw per-example evaluation records and run manifests backing the thesis numbers. No model checkpoints, no bulk synthetic intermediates, no raw API request logs.
qwen_main_repair_v3/— Qwen2.5-1.5B main run: baseline/DPO per-example outputs, results, split, summary, LoRA recipe (training_summary/adapter_config)llama_main_repair_v3/— Llama-3.2-1B generalization run, same layout (dpo_examples/dpo_results)confusion_ablation_repair_v3/— six control conditions; per-condition examples/results + LoRA recipe (seed, data count, best checkpoint inside training_summary.json); shared top summarysemantic_eval_v4/— post-hoc semantic eval: per_example.json, summary, RUN_MANIFEST, CALIBRATION_COMPLETE, model_scores cache (evaluator script: repo src/scripts/run_phase1_posthoc_semantic_eval.py)openai_judge_full_v2/,openai_judge_base_ext_v1/— blind-judge runs: analysis/ (final per-judgement long table, report, bootstrap draws), records.tar.gz + admissions.tar.gz (per-sample judgements), all manifests/status flags/hashes; API request logs excludedrepair_automation_v3/— final run proof: RUN_MANIFEST, phase1_repair_summary, PHASE1_REPAIR_COMPLETE, full training/eval logsintegrity/— PROTECTED_ARTIFACTS.sha256 (every file), GIT_COMMIT.txt, PIP_FREEZE.txt, GPU_CUDA_INFO.txt
Companion repos: self-training-loop-phase2-arms (Phase 2 arms/eval/human adjudications), self-training-loop-phase2-adapters.
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