Datasets:

---

morteza20

/

mteb_leaderboard

like 0

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 18 new columns ({'public_training_code', 'public_training_data', 'framework', 'loader', 'license', 'open_weights', 'zero_shot_benchmarks', 'name', 'revision', 'n_parameters', 'embed_dim', 'max_tokens', 'release_date', 'reference', 'similarity_fn_name', 'use_instructions', 'memory_usage', 'languages'}) and 5 missing columns ({'evaluation_time', 'mteb_version', 'scores', 'dataset_revision', 'task_name'}).

This happened while the json dataset builder was generating data using

hf://datasets/morteza20/mteb_leaderboard/results/NLPArtisan__qwen-1.8b-retrieval-test/external/model_meta.json (at revision 3a7c664609bebabdbad5017611c533236c0adb2b)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              name: string
              revision: string
              release_date: timestamp[s]
              languages: list<item: null>
                child 0, item: null
              loader: null
              n_parameters: null
              memory_usage: null
              max_tokens: null
              embed_dim: null
              license: null
              open_weights: bool
              public_training_data: null
              public_training_code: null
              framework: list<item: null>
                child 0, item: null
              reference: null
              similarity_fn_name: null
              use_instructions: null
              zero_shot_benchmarks: null
              to
              {'dataset_revision': Value(dtype='string', id=None), 'task_name': Value(dtype='string', id=None), 'evaluation_time': Value(dtype='null', id=None), 'mteb_version': Value(dtype='null', id=None), 'scores': {'dev': [{'hf_subset': Value(dtype='string', id=None), 'languages': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'map_at_1': Value(dtype='float64', id=None), 'map_at_10': Value(dtype='float64', id=None), 'map_at_100': Value(dtype='float64', id=None), 'map_at_1000': Value(dtype='float64', id=None), 'map_at_3': Value(dtype='float64', id=None), 'map_at_5': Value(dtype='float64', id=None), 'mrr_at_1': Value(dtype='float64', id=None), 'mrr_at_10': Value(dtype='float64', id=None), 'mrr_at_100': Value(dtype='float64', id=None), 'mrr_at_1000': Value(dtype='float64', id=None), 'mrr_at_3': Value(dtype='float64', id=None), 'mrr_at_5': Value(dtype='float64', id=None), 'ndcg_at_1': Value(dtype='float64', id=None), 'ndcg_at_10': Value(dtype='float64', id=None), 'ndcg_at_100': Value(dtype='float64', id=None), 'ndcg_at_1000': Value(dtype='float64', id=None), 'ndcg_at_3': Value(dtype='float64', id=None), 'ndcg_at_5': Value(dtype='float64', id=None), 'precision_at_1': Value(dtype='float64', id=None), 'precision_at_10': Value(dtype='float64', id=None), 'precision_at_100': Value(dtype='float64', id=None), 'precision_at_1000': Value(dtype='float64', id=None), 'precision_at_3': Value(dtype='float64', id=None), 'precision_at_5': Value(dtype='float64', id=None), 'recall_at_1': Value(dtype='float64', id=None), 'recall_at_10': Value(dtype='float64', id=None), 'recall_at_100': Value(dtype='float64', id=None), 'recall_at_1000': Value(dtype='float64', id=None), 'recall_at_3': Value(dtype='float64', id=None), 'recall_at_5': Value(dtype='float64', id=None), 'main_score': Value(dtype='float64', id=None)}]}}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1417, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1049, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1872, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 18 new columns ({'public_training_code', 'public_training_data', 'framework', 'loader', 'license', 'open_weights', 'zero_shot_benchmarks', 'name', 'revision', 'n_parameters', 'embed_dim', 'max_tokens', 'release_date', 'reference', 'similarity_fn_name', 'use_instructions', 'memory_usage', 'languages'}) and 5 missing columns ({'evaluation_time', 'mteb_version', 'scores', 'dataset_revision', 'task_name'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/morteza20/mteb_leaderboard/results/NLPArtisan__qwen-1.8b-retrieval-test/external/model_meta.json (at revision 3a7c664609bebabdbad5017611c533236c0adb2b)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)