Datasets:

---

letrungtin2k5

/

scibert-backup

Like 0

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
task: string
model_name_or_path: string
num_labels: int64
ignore_mismatched_sizes: bool
train_file: string
validation_file: string
test_file: string
output_dir: string
max_length: int64
seed: int64
batch_size: int64
learning_rate: string
num_epochs: int64
warmup_ratio: double
label_smoothing: double
logging_steps: int64
field_map: struct<query: string, title: string, abstract: string, label: string>
  child 0, query: string
  child 1, title: string
  child 2, abstract: string
  child 3, label: string
mrr: double
num_samples: int64
sample_predictions: list<item: struct<query_id: string, label: int64, score: double>>
  child 0, item: struct<query_id: string, label: int64, score: double>
      child 0, query_id: string
      child 1, label: int64
      child 2, score: double
hit_at_5: double
hit_at_1: double
f1: double
hit_at_10: double
ndcg_at_10: double
precision: double
recall: double
accuracy: double
map: double
to
{'ndcg_at_10': Value('float64'), 'map': Value('float64'), 'mrr': Value('float64'), 'hit_at_1': Value('float64'), 'hit_at_5': Value('float64'), 'hit_at_10': Value('float64'), 'accuracy': Value('float64'), 'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_samples': Value('int64'), 'sample_predictions': List({'query_id': Value('string'), 'label': Value('int64'), 'score': Value('float64')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              task: string
              model_name_or_path: string
              num_labels: int64
              ignore_mismatched_sizes: bool
              train_file: string
              validation_file: string
              test_file: string
              output_dir: string
              max_length: int64
              seed: int64
              batch_size: int64
              learning_rate: string
              num_epochs: int64
              warmup_ratio: double
              label_smoothing: double
              logging_steps: int64
              field_map: struct<query: string, title: string, abstract: string, label: string>
                child 0, query: string
                child 1, title: string
                child 2, abstract: string
                child 3, label: string
              mrr: double
              num_samples: int64
              sample_predictions: list<item: struct<query_id: string, label: int64, score: double>>
                child 0, item: struct<query_id: string, label: int64, score: double>
                    child 0, query_id: string
                    child 1, label: int64
                    child 2, score: double
              hit_at_5: double
              hit_at_1: double
              f1: double
              hit_at_10: double
              ndcg_at_10: double
              precision: double
              recall: double
              accuracy: double
              map: double
              to
              {'ndcg_at_10': Value('float64'), 'map': Value('float64'), 'mrr': Value('float64'), 'hit_at_1': Value('float64'), 'hit_at_5': Value('float64'), 'hit_at_10': Value('float64'), 'accuracy': Value('float64'), 'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'num_samples': Value('int64'), 'sample_predictions': List({'query_id': Value('string'), 'label': Value('int64'), 'score': Value('float64')})}
              because column names don't match