Datasets:

---

MinhTriet

/

vimedaqa-rft-a0-res-test

Like 0

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
adapter: string
pe_avg: double
pe_se: double
bertscore_phobert_f1: double
bleu: double
meteor: double
rougeL: double
n: int64
avg_phobert: double
vs_R0: double
vs_R1: double
phán_quyết: string
run: string
val_log: list<item: struct<step: int64, eval_loss: double, eval_runtime: double, eval_samples_per_second: dou (... 236 chars omitted)
  child 0, item: struct<step: int64, eval_loss: double, eval_runtime: double, eval_samples_per_second: double, eval_s (... 224 chars omitted)
      child 0, step: int64
      child 1, eval_loss: double
      child 2, eval_runtime: double
      child 3, eval_samples_per_second: double
      child 4, eval_steps_per_second: double
      child 5, eval_entropy: double
      child 6, eval_num_tokens: double
      child 7, eval_mean_token_accuracy: double
      child 8, epoch: double
      child 9, eval_avg_phobert: double
      child 10, eval_pe_avg: double
      child 11, eval_test_avg_phobert: double
      child 12, eval_test_pe_avg: double
n_train: int64
hp: struct<lr: double, warmup: double, wd: double, sched: string, neftune: double, epochs: int64, batch: (... 21 chars omitted)
  child 0, lr: double
  child 1, warmup: double
  child 2, wd: double
  child 3, sched: string
  child 4, neftune: double
  child 5, epochs: int64
  child 6, batch: int64
  child 7, accum: int64
n_checkpoint_tranh_max: int64
test: struct<adapter: string, pe_avg: double, pe_se: double, bertscore_phobert_f1: double, bleu: double, m (... 114 chars omitted)
  child 0, adapter: string
  child 1, pe_avg: double
  child 2, pe_se: double
  child 3, bertscore_phobert_f1: double
  child 4, bleu: double
  child 5, meteor: double
  child 6, rougeL: double
  child 7, n: int64
  child 8, avg_phobert: double
  child 9, vs_R0: double
  child 10, vs_R1: double
  child 11, phán_quyết: string
đối_chứng_bề_mặt: struct<độ_dài_A0: double, độ_dài_gold: double, độ_dài_y*_train: double, phủ_context_A0 (... 71 chars omitted)
  child 0, độ_dài_A0: double
  child 1, độ_dài_gold: double
  child 2, độ_dài_y*_train: double
  child 3, phủ_context_A0: double
  child 4, phủ_context_gold: double
  child 5, trùng_nguyên_văn_gold: double
best_val_avg_phobert: double
m4: bool
smoke: bool
to
{'run': Value('string'), 'm4': Value('bool'), 'smoke': Value('bool'), 'n_train': Value('int64'), 'hp': {'lr': Value('float64'), 'warmup': Value('float64'), 'wd': Value('float64'), 'sched': Value('string'), 'neftune': Value('float64'), 'epochs': Value('int64'), 'batch': Value('int64'), 'accum': Value('int64')}, 'best_val_avg_phobert': Value('float64'), 'n_checkpoint_tranh_max': Value('int64'), 'val_log': List({'step': Value('int64'), 'eval_loss': Value('float64'), 'eval_runtime': Value('float64'), 'eval_samples_per_second': Value('float64'), 'eval_steps_per_second': Value('float64'), 'eval_entropy': Value('float64'), 'eval_num_tokens': Value('float64'), 'eval_mean_token_accuracy': Value('float64'), 'epoch': Value('float64'), 'eval_avg_phobert': Value('float64'), 'eval_pe_avg': Value('float64'), 'eval_test_avg_phobert': Value('float64'), 'eval_test_pe_avg': Value('float64')}), 'test': {'adapter': Value('string'), 'pe_avg': Value('float64'), 'pe_se': Value('float64'), 'bertscore_phobert_f1': Value('float64'), 'bleu': Value('float64'), 'meteor': Value('float64'), 'rougeL': Value('float64'), 'n': Value('int64'), 'avg_phobert': Value('float64'), 'vs_R0': Value('float64'), 'vs_R1': Value('float64'), 'phán_quyết': Value('string')}, 'đối_chứng_bề_mặt': {'độ_dài_A0': Value('float64'), 'độ_dài_gold': Value('float64'), 'độ_dài_y*_train': Value('float64'), 'phủ_context_A0': Value('float64'), 'phủ_context_gold': Value('float64'), 'trùng_nguyên_văn_gold': Value('float64')}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, 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 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
              adapter: string
              pe_avg: double
              pe_se: double
              bertscore_phobert_f1: double
              bleu: double
              meteor: double
              rougeL: double
              n: int64
              avg_phobert: double
              vs_R0: double
              vs_R1: double
              phán_quyết: string
              run: string
              val_log: list<item: struct<step: int64, eval_loss: double, eval_runtime: double, eval_samples_per_second: dou (... 236 chars omitted)
                child 0, item: struct<step: int64, eval_loss: double, eval_runtime: double, eval_samples_per_second: double, eval_s (... 224 chars omitted)
                    child 0, step: int64
                    child 1, eval_loss: double
                    child 2, eval_runtime: double
                    child 3, eval_samples_per_second: double
                    child 4, eval_steps_per_second: double
                    child 5, eval_entropy: double
                    child 6, eval_num_tokens: double
                    child 7, eval_mean_token_accuracy: double
                    child 8, epoch: double
                    child 9, eval_avg_phobert: double
                    child 10, eval_pe_avg: double
                    child 11, eval_test_avg_phobert: double
                    child 12, eval_test_pe_avg: double
              n_train: int64
              hp: struct<lr: double, warmup: double, wd: double, sched: string, neftune: double, epochs: int64, batch: (... 21 chars omitted)
                child 0, lr: double
                child 1, warmup: double
                child 2, wd: double
                child 3, sched: string
                child 4, neftune: double
                child 5, epochs: int64
                child 6, batch: int64
                child 7, accum: int64
              n_checkpoint_tranh_max: int64
              test: struct<adapter: string, pe_avg: double, pe_se: double, bertscore_phobert_f1: double, bleu: double, m (... 114 chars omitted)
                child 0, adapter: string
                child 1, pe_avg: double
                child 2, pe_se: double
                child 3, bertscore_phobert_f1: double
                child 4, bleu: double
                child 5, meteor: double
                child 6, rougeL: double
                child 7, n: int64
                child 8, avg_phobert: double
                child 9, vs_R0: double
                child 10, vs_R1: double
                child 11, phán_quyết: string
              đối_chứng_bề_mặt: struct<độ_dài_A0: double, độ_dài_gold: double, độ_dài_y*_train: double, phủ_context_A0 (... 71 chars omitted)
                child 0, độ_dài_A0: double
                child 1, độ_dài_gold: double
                child 2, độ_dài_y*_train: double
                child 3, phủ_context_A0: double
                child 4, phủ_context_gold: double
                child 5, trùng_nguyên_văn_gold: double
              best_val_avg_phobert: double
              m4: bool
              smoke: bool
              to
              {'run': Value('string'), 'm4': Value('bool'), 'smoke': Value('bool'), 'n_train': Value('int64'), 'hp': {'lr': Value('float64'), 'warmup': Value('float64'), 'wd': Value('float64'), 'sched': Value('string'), 'neftune': Value('float64'), 'epochs': Value('int64'), 'batch': Value('int64'), 'accum': Value('int64')}, 'best_val_avg_phobert': Value('float64'), 'n_checkpoint_tranh_max': Value('int64'), 'val_log': List({'step': Value('int64'), 'eval_loss': Value('float64'), 'eval_runtime': Value('float64'), 'eval_samples_per_second': Value('float64'), 'eval_steps_per_second': Value('float64'), 'eval_entropy': Value('float64'), 'eval_num_tokens': Value('float64'), 'eval_mean_token_accuracy': Value('float64'), 'epoch': Value('float64'), 'eval_avg_phobert': Value('float64'), 'eval_pe_avg': Value('float64'), 'eval_test_avg_phobert': Value('float64'), 'eval_test_pe_avg': Value('float64')}), 'test': {'adapter': Value('string'), 'pe_avg': Value('float64'), 'pe_se': Value('float64'), 'bertscore_phobert_f1': Value('float64'), 'bleu': Value('float64'), 'meteor': Value('float64'), 'rougeL': Value('float64'), 'n': Value('int64'), 'avg_phobert': Value('float64'), 'vs_R0': Value('float64'), 'vs_R1': Value('float64'), 'phán_quyết': Value('string')}, 'đối_chứng_bề_mặt': {'độ_dài_A0': Value('float64'), 'độ_dài_gold': Value('float64'), 'độ_dài_y*_train': Value('float64'), 'phủ_context_A0': Value('float64'), 'phủ_context_gold': Value('float64'), 'trùng_nguyên_văn_gold': Value('float64')}}
              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 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 1880, 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