Datasets:

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scimt-dispatch-sdf-dose-order-v1

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Arcadia Impact 8

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
schema_version: int64
status: string
stage: string
kind: string
created_at: timestamp[s]
resolved_config: struct<base_model: string, trust_remote_code: bool, plugins: list<item: string>, liger_fused_linear_ (... 984 chars omitted)
  child 0, base_model: string
  child 1, trust_remote_code: bool
  child 2, plugins: list<item: string>
      child 0, item: string
  child 3, liger_fused_linear_cross_entropy: bool
  child 4, liger_rope: bool
  child 5, liger_rms_norm: bool
  child 6, liger_glu_activation: bool
  child 7, datasets: list<item: struct<path: string, type: string, field: string>>
      child 0, item: struct<path: string, type: string, field: string>
          child 0, path: string
          child 1, type: string
          child 2, field: string
  child 8, dataset_prepared_path: string
  child 9, dataset_processes: int64
  child 10, sequence_len: int64
  child 11, sample_packing: bool
  child 12, pad_to_sequence_len: bool
  child 13, bf16: bool
  child 14, tf32: bool
  child 15, flash_attention: bool
  child 16, gradient_checkpointing: bool
  child 17, micro_batch_size: int64
  child 18, gradient_accumulation_steps: int64
  child 19, num_epochs: int64
  child 20, max_steps: int64
  child 21, optimizer: string
  child 22, learning_rate: double
  child 23, weight_decay: double
  child 24, max_grad_norm: double
  child 25, lr_scheduler: string
  child 26, cosine_min_lr_ratio: double
  child 27, warmup_ratio: double
  child 28, fsdp_version: int64
  child 29, fsdp_config: s
...
save_strategy: string
  child 32, save_steps: int64
  child 33, save_only_model: bool
  child 34, save_total_limit: int64
  child 35, seed: int64
  child 36, output_dir: string
resolved_config_path: string
dataset: struct<path: string, exists: bool, size_bytes: int64, sha256: string, nonempty_rows: int64, ordered_ (... 82 chars omitted)
  child 0, path: string
  child 1, exists: bool
  child 2, size_bytes: int64
  child 3, sha256: string
  child 4, nonempty_rows: int64
  child 5, ordered_example_sha256: string
  child 6, example_manifest: string
  child 7, example_manifest_sha256: string
schedule: struct<learning_rate: double, lr_scheduler: string, warmup_ratio: double, cosine_min_lr_ratio: doubl (... 2 chars omitted)
  child 0, learning_rate: double
  child 1, lr_scheduler: string
  child 2, warmup_ratio: double
  child 3, cosine_min_lr_ratio: double
step_plan: struct<raw_dataset_rows: int64, micro_batch_size: int64, gradient_accumulation_steps: int64, world_s (... 245 chars omitted)
  child 0, raw_dataset_rows: int64
  child 1, micro_batch_size: int64
  child 2, gradient_accumulation_steps: int64
  child 3, world_size_at_render: int64
  child 4, effective_global_batch_size: int64
  child 5, num_epochs: int64
  child 6, planned_optimizer_steps_before_length_filter: int64
  child 7, max_steps_override: int64
  child 8, logging_steps: int64
  child 9, save_strategy: string
  child 10, save_steps: int64
  child 11, save_total_limit: int64
seed: int64
index: int64
sha256: string
to
{'index': Value('int64'), 'sha256': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1816, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_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
              schema_version: int64
              status: string
              stage: string
              kind: string
              created_at: timestamp[s]
              resolved_config: struct<base_model: string, trust_remote_code: bool, plugins: list<item: string>, liger_fused_linear_ (... 984 chars omitted)
                child 0, base_model: string
                child 1, trust_remote_code: bool
                child 2, plugins: list<item: string>
                    child 0, item: string
                child 3, liger_fused_linear_cross_entropy: bool
                child 4, liger_rope: bool
                child 5, liger_rms_norm: bool
                child 6, liger_glu_activation: bool
                child 7, datasets: list<item: struct<path: string, type: string, field: string>>
                    child 0, item: struct<path: string, type: string, field: string>
                        child 0, path: string
                        child 1, type: string
                        child 2, field: string
                child 8, dataset_prepared_path: string
                child 9, dataset_processes: int64
                child 10, sequence_len: int64
                child 11, sample_packing: bool
                child 12, pad_to_sequence_len: bool
                child 13, bf16: bool
                child 14, tf32: bool
                child 15, flash_attention: bool
                child 16, gradient_checkpointing: bool
                child 17, micro_batch_size: int64
                child 18, gradient_accumulation_steps: int64
                child 19, num_epochs: int64
                child 20, max_steps: int64
                child 21, optimizer: string
                child 22, learning_rate: double
                child 23, weight_decay: double
                child 24, max_grad_norm: double
                child 25, lr_scheduler: string
                child 26, cosine_min_lr_ratio: double
                child 27, warmup_ratio: double
                child 28, fsdp_version: int64
                child 29, fsdp_config: s
              ...
              save_strategy: string
                child 32, save_steps: int64
                child 33, save_only_model: bool
                child 34, save_total_limit: int64
                child 35, seed: int64
                child 36, output_dir: string
              resolved_config_path: string
              dataset: struct<path: string, exists: bool, size_bytes: int64, sha256: string, nonempty_rows: int64, ordered_ (... 82 chars omitted)
                child 0, path: string
                child 1, exists: bool
                child 2, size_bytes: int64
                child 3, sha256: string
                child 4, nonempty_rows: int64
                child 5, ordered_example_sha256: string
                child 6, example_manifest: string
                child 7, example_manifest_sha256: string
              schedule: struct<learning_rate: double, lr_scheduler: string, warmup_ratio: double, cosine_min_lr_ratio: doubl (... 2 chars omitted)
                child 0, learning_rate: double
                child 1, lr_scheduler: string
                child 2, warmup_ratio: double
                child 3, cosine_min_lr_ratio: double
              step_plan: struct<raw_dataset_rows: int64, micro_batch_size: int64, gradient_accumulation_steps: int64, world_s (... 245 chars omitted)
                child 0, raw_dataset_rows: int64
                child 1, micro_batch_size: int64
                child 2, gradient_accumulation_steps: int64
                child 3, world_size_at_render: int64
                child 4, effective_global_batch_size: int64
                child 5, num_epochs: int64
                child 6, planned_optimizer_steps_before_length_filter: int64
                child 7, max_steps_override: int64
                child 8, logging_steps: int64
                child 9, save_strategy: string
                child 10, save_steps: int64
                child 11, save_total_limit: int64
              seed: int64
              index: int64
              sha256: string
              to
              {'index': Value('int64'), 'sha256': Value('string')}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              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 1869, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset