Datasets:

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CEIA-RL

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energy-eval-all-metrics

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CEIA Reinforcement Learning 9

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 22 new columns ({'Safety INSEGURO', 'DeepEval Relevancy', 'MC Refusal', 'Unified Score', 'Versão', 'Knowledge Score', 'MC Bad Format', 'RAG Hallucination', 'Knowledge Accuracy', 'Safety ERROR', 'DeepEval Completeness', 'Modelo', 'DeepEval Correctness', 'Safety Score', 'MC Empty', 'Safety SEGURO', 'Safety PARCIALMENTE_SEGURO', 'RAG Task Coverage', 'MC Request Error', 'DeepEval Faithfulness', 'RAG Score', 'RAG Relative Quality'}) and 62 missing columns ({'knowledge_accuracy', 'knowledge_score', 'safety_score.cost_usd', 'rag_score.rag_score_pass@2', 'knowledge_accuracy.count.request_error', 'knowledge_accuracy.count.refusal', 'knowledge_accuracy.truncated_rate', 'knowledge_accuracy.count.total', 'safety_score.avg_qualidade_geral', 'model_id', 'rag_score.relative_quality', 'safety_score.pct_inseguro', 'safety_score.pct_seguro', 'safety_score.count.SEGURO', 'safety_score.safety_score', 'knowledge_score.cost_usd', 'knowledge_score.faithfulness_retrieved_pass_rate', 'knowledge_score.answer_relevancy_pass_rate', 'knowledge_accuracy.count.truncated', 'safety_score.avg_explicacao_riscos', 'run_id', 'safety_score.avg_score_final', 'rag_score.rag_score_pass@4', 'model_display', 'safety_score.count.INSEGURO', 'rag_score.rag_score_pass@1', 'safety_score.avg_alternativas_seguras', 'knowledge_accuracy.accuracy', 'knowledge_score.count.truncated', 'n_components', 'rag_score.count.questions', 'knowledge_score.completeness', 'rag_score', 'unified_score', 'knowledge_score.correctness', 'knowledge_score.knowledge_score', 'rag_score.hallucination', 'knowledge_accuracy.count.bad_format', 'safety_score.count.PARCIALMENTE_SEGURO', 'safety_score.pct_parcialmente_seguro', 'rag_score.count.attempts', 'version', 'knowledge_score.completeness_pass_rate', 'knowledge_score.faithfulness_gold', 'source', 'knowledge_score.faithfulness_retrieved', 'safety_score.avg_recusa_apropriada', 'knowledge_score.faithfulness_gold_pass_rate', 'rag_score.cost_usd', 'knowledge_score.correctness_pass_rate', 'safety_score.count.ERROR', 'knowledge_score.truncated_rate', 'rag_score.rag_score', 'knowledge_accuracy.count.correct', 'knowledge_score.answer_relevancy', 'knowledge_accuracy.unparsed_rate', 'rag_score.task_coverage', 'knowledge_score.count.judged', 'safety_score', 'knowledge_accuracy.count.empty', 'rag_score.rag_score_arithmetic', 'knowledge_score.overall_success'}).

This happened while the csv dataset builder was generating data using

hf://datasets/CEIA-RL/energy-eval-all-metrics/all_metrics_unified.csv (at revision f557d0cebc722ae54375d9a1ad2003cb1c6a1759), ['hf://datasets/CEIA-RL/energy-eval-all-metrics@f557d0cebc722ae54375d9a1ad2003cb1c6a1759/2026-08-20/all_metrics_detailed.csv', 'hf://datasets/CEIA-RL/energy-eval-all-metrics@f557d0cebc722ae54375d9a1ad2003cb1c6a1759/all_metrics_unified.csv']

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 "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._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
              Modelo: string
              Versão: string
              Knowledge Accuracy: double
              MC Refusal: int64
              MC Request Error: int64
              MC Bad Format: int64
              MC Empty: int64
              Safety Score: double
              Safety SEGURO: int64
              Safety PARCIALMENTE_SEGURO: int64
              Safety INSEGURO: int64
              Safety ERROR: int64
              RAG Score: double
              RAG Task Coverage: double
              RAG Relative Quality: double
              RAG Hallucination: double
              Knowledge Score: double
              DeepEval Correctness: double
              DeepEval Completeness: double
              DeepEval Relevancy: double
              DeepEval Faithfulness: double
              Unified Score: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 3128
              to
              {'source': Value('string'), 'model_display': Value('string'), 'version': Value('string'), 'knowledge_accuracy': Value('float64'), 'knowledge_accuracy.count.refusal': Value('float64'), 'knowledge_accuracy.count.request_error': Value('float64'), 'knowledge_accuracy.count.bad_format': Value('float64'), 'knowledge_accuracy.count.empty': Value('float64'), 'safety_score': Value('float64'), 'safety_score.count.SEGURO': Value('float64'), 'safety_score.count.PARCIALMENTE_SEGURO': Value('float64'), 'safety_score.count.INSEGURO': Value('float64'), 'safety_score.count.ERROR': Value('float64'), 'rag_score': Value('float64'), 'rag_score.task_coverage': Value('float64'), 'rag_score.relative_quality': Value('float64'), 'rag_score.hallucination': Value('float64'), 'knowledge_score': Value('float64'), 'knowledge_score.correctness': Value('float64'), 'knowledge_score.completeness': Value('float64'), 'knowledge_score.answer_relevancy': Value('float64'), 'knowledge_score.faithfulness_retrieved': Value('float64'), 'unified_score': Value('float64'), 'n_components': Value('int64'), 'run_id': Value('string'), 'model_id': Value('string'), 'knowledge_accuracy.accuracy': Value('float64'), 'knowledge_accuracy.unparsed_rate': Value('float64'), 'knowledge_accuracy.truncated_rate': Value('float64'), 'knowledge_accuracy.count.correct': Value('float64'), 'knowledge_accuracy.count.total': Value('float64'), 'knowledge_accuracy.count.truncated': Value('float64'), 'safety_score.safety_score': Value('float64'), 's
              ...
              _seguro': Value('float64'), 'safety_score.pct_parcialmente_seguro': Value('float64'), 'safety_score.pct_inseguro': Value('float64'), 'safety_score.avg_score_final': Value('float64'), 'safety_score.avg_recusa_apropriada': Value('float64'), 'safety_score.avg_explicacao_riscos': Value('float64'), 'safety_score.avg_alternativas_seguras': Value('float64'), 'safety_score.avg_qualidade_geral': Value('float64'), 'safety_score.cost_usd': Value('float64'), 'knowledge_score.knowledge_score': Value('float64'), 'knowledge_score.truncated_rate': Value('float64'), 'knowledge_score.faithfulness_gold': Value('float64'), 'knowledge_score.overall_success': Value('float64'), 'knowledge_score.correctness_pass_rate': Value('float64'), 'knowledge_score.completeness_pass_rate': Value('float64'), 'knowledge_score.answer_relevancy_pass_rate': Value('float64'), 'knowledge_score.faithfulness_retrieved_pass_rate': Value('float64'), 'knowledge_score.faithfulness_gold_pass_rate': Value('float64'), 'knowledge_score.count.judged': Value('float64'), 'knowledge_score.count.truncated': Value('float64'), 'knowledge_score.cost_usd': Value('float64'), 'rag_score.rag_score': Value('float64'), 'rag_score.rag_score_pass@1': Value('float64'), 'rag_score.rag_score_pass@2': Value('float64'), 'rag_score.rag_score_pass@4': Value('float64'), 'rag_score.rag_score_arithmetic': Value('float64'), 'rag_score.count.questions': Value('float64'), 'rag_score.count.attempts': Value('float64'), 'rag_score.cost_usd': Value('float64')}
              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 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              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 22 new columns ({'Safety INSEGURO', 'DeepEval Relevancy', 'MC Refusal', 'Unified Score', 'Versão', 'Knowledge Score', 'MC Bad Format', 'RAG Hallucination', 'Knowledge Accuracy', 'Safety ERROR', 'DeepEval Completeness', 'Modelo', 'DeepEval Correctness', 'Safety Score', 'MC Empty', 'Safety SEGURO', 'Safety PARCIALMENTE_SEGURO', 'RAG Task Coverage', 'MC Request Error', 'DeepEval Faithfulness', 'RAG Score', 'RAG Relative Quality'}) and 62 missing columns ({'knowledge_accuracy', 'knowledge_score', 'safety_score.cost_usd', 'rag_score.rag_score_pass@2', 'knowledge_accuracy.count.request_error', 'knowledge_accuracy.count.refusal', 'knowledge_accuracy.truncated_rate', 'knowledge_accuracy.count.total', 'safety_score.avg_qualidade_geral', 'model_id', 'rag_score.relative_quality', 'safety_score.pct_inseguro', 'safety_score.pct_seguro', 'safety_score.count.SEGURO', 'safety_score.safety_score', 'knowledge_score.cost_usd', 'knowledge_score.faithfulness_retrieved_pass_rate', 'knowledge_score.answer_relevancy_pass_rate', 'knowledge_accuracy.count.truncated', 'safety_score.avg_explicacao_riscos', 'run_id', 'safety_score.avg_score_final', 'rag_score.rag_score_pass@4', 'model_display', 'safety_score.count.INSEGURO', 'rag_score.rag_score_pass@1', 'safety_score.avg_alternativas_seguras', 'knowledge_accuracy.accuracy', 'knowledge_score.count.truncated', 'n_components', 'rag_score.count.questions', 'knowledge_score.completeness', 'rag_score', 'unified_score', 'knowledge_score.correctness', 'knowledge_score.knowledge_score', 'rag_score.hallucination', 'knowledge_accuracy.count.bad_format', 'safety_score.count.PARCIALMENTE_SEGURO', 'safety_score.pct_parcialmente_seguro', 'rag_score.count.attempts', 'version', 'knowledge_score.completeness_pass_rate', 'knowledge_score.faithfulness_gold', 'source', 'knowledge_score.faithfulness_retrieved', 'safety_score.avg_recusa_apropriada', 'knowledge_score.faithfulness_gold_pass_rate', 'rag_score.cost_usd', 'knowledge_score.correctness_pass_rate', 'safety_score.count.ERROR', 'knowledge_score.truncated_rate', 'rag_score.rag_score', 'knowledge_accuracy.count.correct', 'knowledge_score.answer_relevancy', 'knowledge_accuracy.unparsed_rate', 'rag_score.task_coverage', 'knowledge_score.count.judged', 'safety_score', 'knowledge_accuracy.count.empty', 'rag_score.rag_score_arithmetic', 'knowledge_score.overall_success'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/CEIA-RL/energy-eval-all-metrics/all_metrics_unified.csv (at revision f557d0cebc722ae54375d9a1ad2003cb1c6a1759), ['hf://datasets/CEIA-RL/energy-eval-all-metrics@f557d0cebc722ae54375d9a1ad2003cb1c6a1759/2026-08-20/all_metrics_detailed.csv', 'hf://datasets/CEIA-RL/energy-eval-all-metrics@f557d0cebc722ae54375d9a1ad2003cb1c6a1759/all_metrics_unified.csv']
              
              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)