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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
logos: list<item: struct<file: string, src: string, title: string, url: string>>
vs
model_name: string
publisher: string
full_model_name: string
overall_latam_score: double
spanish_score: double
spanish_spanish: double
spanish_copa_es: double
spanish_escola: double
spanish_mgsm_direct_es_spanish_bench: double
spanish_openbookqa_es: double
spanish_paws_es_spanish_bench: double
spanish_teleia: double
spanish_teleia_cervantes_ave: double
spanish_teleia_pce: double
spanish_teleia_siele: double
spanish_wnli_es: double
spanish_xnli_es_spanish_bench: double
teleia_score: double
teleia_teleia_cervantes_ave: double
teleia_teleia_pce: double
teleia_teleia_siele: double
portuguese_score: double
portuguese_assin2_rte: double
portuguese_bluex: double
portuguese_enem_challenge: double
portuguese_faquad_nli: double
portuguese_oab_exams: double
translation_score: double
translation_flores_plus_bidirectional: double
translation_flores_arb_por: double
translation_flores_arb_spa: double
translation_flores_cmn_por: double
translation_flores_cmn_spa: double
translation_flores_deu_por: double
translation_flores_deu_spa: double
translation_flores_eng_por: double
translation_flores_eng_spa: double
translation_flores_fra_por: double
translation_flores_fra_spa: double
translation_flores_hin_por: double
translation_flores_hin_spa: double
translation_flores_ita_por: double
translation_flores_ita_spa: double
translation_flores_por_spa: double
translation_opus: double
translation_opus_100_en-es: double
translation_opus_100_en-pt: double
structured_extraction_score: double
structured_extraction_extraction_quality_score: double
structured_extraction_composite_score: double
structured_extraction_schema_validity: double
structured_extraction_field_f1_partial: double
structured_extraction_hallucination_rate: double
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
                  for key, example in iterator:
                                      ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
                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: Schema at index 1 was different: 
              logos: list<item: struct<file: string, src: string, title: string, url: string>>
              vs
              model_name: string
              publisher: string
              full_model_name: string
              overall_latam_score: double
              spanish_score: double
              spanish_spanish: double
              spanish_copa_es: double
              spanish_escola: double
              spanish_mgsm_direct_es_spanish_bench: double
              spanish_openbookqa_es: double
              spanish_paws_es_spanish_bench: double
              spanish_teleia: double
              spanish_teleia_cervantes_ave: double
              spanish_teleia_pce: double
              spanish_teleia_siele: double
              spanish_wnli_es: double
              spanish_xnli_es_spanish_bench: double
              teleia_score: double
              teleia_teleia_cervantes_ave: double
              teleia_teleia_pce: double
              teleia_teleia_siele: double
              portuguese_score: double
              portuguese_assin2_rte: double
              portuguese_bluex: double
              portuguese_enem_challenge: double
              portuguese_faquad_nli: double
              portuguese_oab_exams: double
              translation_score: double
              translation_flores_plus_bidirectional: double
              translation_flores_arb_por: double
              translation_flores_arb_spa: double
              translation_flores_cmn_por: double
              translation_flores_cmn_spa: double
              translation_flores_deu_por: double
              translation_flores_deu_spa: double
              translation_flores_eng_por: double
              translation_flores_eng_spa: double
              translation_flores_fra_por: double
              translation_flores_fra_spa: double
              translation_flores_hin_por: double
              translation_flores_hin_spa: double
              translation_flores_ita_por: double
              translation_flores_ita_spa: double
              translation_flores_por_spa: double
              translation_opus: double
              translation_opus_100_en-es: double
              translation_opus_100_en-pt: double
              structured_extraction_score: double
              structured_extraction_extraction_quality_score: double
              structured_extraction_composite_score: double
              structured_extraction_schema_validity: double
              structured_extraction_field_f1_partial: double
              structured_extraction_hallucination_rate: double

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mauroibz/leaderboard-results

Results from model evaluations on the leaderboard

This dataset contains evaluation results from the leaderboard system.

Structure

  • Each JSON file contains results for a specific model evaluation
  • Files are organized by organization/model structure
  • Each result file includes:
    • Model configuration
    • Evaluation results across different benchmarks
    • Metadata about the evaluation run

Usage

These results are used by the leaderboard system to display model performance.

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