Datasets:

---

duyle2408

/

results_machine1_backbones

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 16 new columns ({'prob_NV', 'prob_BCC', 'prob_AKIEC', 'label_true', 'prob_MEL', 'prob_DF', 'prob_VASC', 'y_true', 'prob_INF', 'prob_BKL', 'prob_SCCKA', 'prob_BEN_OTH', 'y_pred', 'confidence', 'label_pred', 'prob_MAL_OTH'}) and 25 missing columns ({'clinical_sex', 'clinical_MONET_gel_water_drop_fluid_dermoscopy_liquid', 'clinical_MONET_skin_markings_pen_ink_purple_pen', 'clinical_site', 'is_augmented', 'clinical_MONET_erythema', 'clinical_age_approx', 'dermoscopic_MONET_ulceration_crust', 'dermoscopic_sex', 'ignore_metadata', 'clinical_skin_tone_class', 'dermoscopic_MONET_vasculature_vessels', 'dermoscopic_MONET_gel_water_drop_fluid_dermoscopy_liquid', 'dermoscopic_site', 'dermoscopic_MONET_hair', 'dermoscopic_age_approx', 'clinical_MONET_vasculature_vessels', 'dermoscopic_skin_tone_class', 'clinical_MONET_hair', 'clinical_MONET_ulceration_crust', 'dermoscopic_MONET_erythema', 'dermoscopic_MONET_pigmented', 'clinical_MONET_pigmented', 'label', 'dermoscopic_MONET_skin_markings_pen_ink_purple_pen'}).

This happened while the csv dataset builder was generating data using

hf://datasets/duyle2408/results_machine1_backbones/report_backbone_convnext_base_nometa_concat_focal_s05_clean/val_predictions.csv (at revision c68b74407642663e59289280786700c0c016d6be), ['hf://datasets/duyle2408/results_machine1_backbones@c68b74407642663e59289280786700c0c016d6be/report_backbone_convnext_base_nometa_concat_focal_s05_clean/splits/val.csv', 'hf://datasets/duyle2408/results_machine1_backbones@c68b74407642663e59289280786700c0c016d6be/report_backbone_convnext_base_nometa_concat_focal_s05_clean/val_predictions.csv', 'hf://datasets/duyle2408/results_machine1_backbones@c68b74407642663e59289280786700c0c016d6be/report_backbone_effb2_nometa_concat_focal_s05_clean/splits/val.csv', 'hf://datasets/duyle2408/results_machine1_backbones@c68b74407642663e59289280786700c0c016d6be/report_backbone_effb2_nometa_concat_focal_s05_clean/val_predictions.csv', 'hf://datasets/duyle2408/results_machine1_backbones@c68b74407642663e59289280786700c0c016d6be/report_backbone_effv2b2_nometa_concat_focal_s05_clean/splits/val.csv', 'hf://datasets/duyle2408/results_machine1_backbones@c68b74407642663e59289280786700c0c016d6be/report_backbone_effv2b2_nometa_concat_focal_s05_clean/val_predictions.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 1837, 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 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              lesion_id: string
              clinical_path: string
              dermoscopic_path: string
              y_true: int64
              y_pred: int64
              label_true: string
              label_pred: string
              confidence: double
              prob_AKIEC: double
              prob_BCC: double
              prob_BEN_OTH: double
              prob_BKL: double
              prob_DF: double
              prob_INF: double
              prob_MAL_OTH: double
              prob_MEL: double
              prob_NV: double
              prob_SCCKA: double
              prob_VASC: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2544
              to
              {'lesion_id': Value('string'), 'label': Value('string'), 'clinical_path': Value('string'), 'clinical_age_approx': Value('float64'), 'clinical_sex': Value('string'), 'clinical_skin_tone_class': Value('int64'), 'clinical_site': Value('string'), 'clinical_MONET_erythema': Value('float64'), 'clinical_MONET_gel_water_drop_fluid_dermoscopy_liquid': Value('float64'), 'clinical_MONET_hair': Value('float64'), 'clinical_MONET_pigmented': Value('float64'), 'clinical_MONET_skin_markings_pen_ink_purple_pen': Value('float64'), 'clinical_MONET_ulceration_crust': Value('float64'), 'clinical_MONET_vasculature_vessels': Value('float64'), 'dermoscopic_path': Value('string'), 'dermoscopic_age_approx': Value('float64'), 'dermoscopic_sex': Value('string'), 'dermoscopic_skin_tone_class': Value('int64'), 'dermoscopic_site': Value('string'), 'dermoscopic_MONET_erythema': Value('float64'), 'dermoscopic_MONET_gel_water_drop_fluid_dermoscopy_liquid': Value('float64'), 'dermoscopic_MONET_hair': Value('float64'), 'dermoscopic_MONET_pigmented': Value('float64'), 'dermoscopic_MONET_skin_markings_pen_ink_purple_pen': Value('float64'), 'dermoscopic_MONET_ulceration_crust': Value('float64'), 'dermoscopic_MONET_vasculature_vessels': Value('float64'), 'is_augmented': Value('bool'), 'ignore_metadata': Value('bool')}
              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 1683, 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 1839, 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 16 new columns ({'prob_NV', 'prob_BCC', 'prob_AKIEC', 'label_true', 'prob_MEL', 'prob_DF', 'prob_VASC', 'y_true', 'prob_INF', 'prob_BKL', 'prob_SCCKA', 'prob_BEN_OTH', 'y_pred', 'confidence', 'label_pred', 'prob_MAL_OTH'}) and 25 missing columns ({'clinical_sex', 'clinical_MONET_gel_water_drop_fluid_dermoscopy_liquid', 'clinical_MONET_skin_markings_pen_ink_purple_pen', 'clinical_site', 'is_augmented', 'clinical_MONET_erythema', 'clinical_age_approx', 'dermoscopic_MONET_ulceration_crust', 'dermoscopic_sex', 'ignore_metadata', 'clinical_skin_tone_class', 'dermoscopic_MONET_vasculature_vessels', 'dermoscopic_MONET_gel_water_drop_fluid_dermoscopy_liquid', 'dermoscopic_site', 'dermoscopic_MONET_hair', 'dermoscopic_age_approx', 'clinical_MONET_vasculature_vessels', 'dermoscopic_skin_tone_class', 'clinical_MONET_hair', 'clinical_MONET_ulceration_crust', 'dermoscopic_MONET_erythema', 'dermoscopic_MONET_pigmented', 'clinical_MONET_pigmented', 'label', 'dermoscopic_MONET_skin_markings_pen_ink_purple_pen'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/duyle2408/results_machine1_backbones/report_backbone_convnext_base_nometa_concat_focal_s05_clean/val_predictions.csv (at revision c68b74407642663e59289280786700c0c016d6be), ['hf://datasets/duyle2408/results_machine1_backbones@c68b74407642663e59289280786700c0c016d6be/report_backbone_convnext_base_nometa_concat_focal_s05_clean/splits/val.csv', 'hf://datasets/duyle2408/results_machine1_backbones@c68b74407642663e59289280786700c0c016d6be/report_backbone_convnext_base_nometa_concat_focal_s05_clean/val_predictions.csv', 'hf://datasets/duyle2408/results_machine1_backbones@c68b74407642663e59289280786700c0c016d6be/report_backbone_effb2_nometa_concat_focal_s05_clean/splits/val.csv', 'hf://datasets/duyle2408/results_machine1_backbones@c68b74407642663e59289280786700c0c016d6be/report_backbone_effb2_nometa_concat_focal_s05_clean/val_predictions.csv', 'hf://datasets/duyle2408/results_machine1_backbones@c68b74407642663e59289280786700c0c016d6be/report_backbone_effv2b2_nometa_concat_focal_s05_clean/splits/val.csv', 'hf://datasets/duyle2408/results_machine1_backbones@c68b74407642663e59289280786700c0c016d6be/report_backbone_effv2b2_nometa_concat_focal_s05_clean/val_predictions.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)