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The dataset generation failed because of a cast error
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 1 new columns ({'MLS WER'})
This happened while the csv dataset builder was generating data using
hf://datasets/hf-audio/multilingual_evals/multilingual_es.csv (at revision 44035251aa582eb738f3d26dcb822c9ec81d62de), ['hf://datasets/hf-audio/multilingual_evals@44035251aa582eb738f3d26dcb822c9ec81d62de/multilingual_de.csv', 'hf://datasets/hf-audio/multilingual_evals@44035251aa582eb738f3d26dcb822c9ec81d62de/multilingual_es.csv', 'hf://datasets/hf-audio/multilingual_evals@44035251aa582eb738f3d26dcb822c9ec81d62de/multilingual_fr.csv', 'hf://datasets/hf-audio/multilingual_evals@44035251aa582eb738f3d26dcb822c9ec81d62de/multilingual_it.csv', 'hf://datasets/hf-audio/multilingual_evals@44035251aa582eb738f3d26dcb822c9ec81d62de/multilingual_latest.csv', 'hf://datasets/hf-audio/multilingual_evals@44035251aa582eb738f3d26dcb822c9ec81d62de/multilingual_pt.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
model: string
RTFx: double
FLEURS WER: double
MCV WER: double
MLS WER: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 848
to
{'model': Value('string'), 'RTFx': Value('float64'), 'FLEURS WER': Value('float64'), 'MCV WER': 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 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 1 new columns ({'MLS WER'})
This happened while the csv dataset builder was generating data using
hf://datasets/hf-audio/multilingual_evals/multilingual_es.csv (at revision 44035251aa582eb738f3d26dcb822c9ec81d62de), ['hf://datasets/hf-audio/multilingual_evals@44035251aa582eb738f3d26dcb822c9ec81d62de/multilingual_de.csv', 'hf://datasets/hf-audio/multilingual_evals@44035251aa582eb738f3d26dcb822c9ec81d62de/multilingual_es.csv', 'hf://datasets/hf-audio/multilingual_evals@44035251aa582eb738f3d26dcb822c9ec81d62de/multilingual_fr.csv', 'hf://datasets/hf-audio/multilingual_evals@44035251aa582eb738f3d26dcb822c9ec81d62de/multilingual_it.csv', 'hf://datasets/hf-audio/multilingual_evals@44035251aa582eb738f3d26dcb822c9ec81d62de/multilingual_latest.csv', 'hf://datasets/hf-audio/multilingual_evals@44035251aa582eb738f3d26dcb822c9ec81d62de/multilingual_pt.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)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
model string | RTFx float64 | FLEURS WER float64 | MCV WER float64 |
|---|---|---|---|
assembly/universal-3-pro | -1 | 2.42 | 2.76 |
CohereLabs/cohere-transcribe-03-2026 | 650.74 | 3.33 | 2.87 |
elevenlabs/scribe_v2 | -1 | 2.3 | 2.19 |
facebook/omniASR-CTC-1B-v2 | 742.2 | 7.2 | 9.64 |
facebook/omniASR-CTC-300M-v2 | 1,211.23 | 14.06 | 18.9 |
facebook/omniASR-CTC-3B-v2 | 491.17 | 5.04 | 7.3 |
facebook/omniASR-CTC-7B-v2 | 302.68 | 4.89 | 7.01 |
facebook/omniASR-LLM-1B-v2 | 50.29 | 7.09 | 7.28 |
facebook/omniASR-LLM-300M-v2 | 47.9 | 7.84 | 11.68 |
facebook/omniASR-LLM-3B-v2 | 49.38 | 4.68 | 7.14 |
facebook/omniASR-LLM-7B-v2 | 44.56 | 3.69 | 5.3 |
ibm-granite/granite-speech-4.1-2b-nar | 1,402.39 | 4.87 | 3.78 |
microsoft/azure-speech | -1 | 1.93 | 1.88 |
microsoft/Phi-4-multimodal-instruct | 123.08 | 3.68 | 4.1 |
mistralai/Voxtral-Mini-3B-2507 | 152.14 | 3.78 | 5.53 |
mistralai/Voxtral-Mini-4B-Realtime-2602 | 42.61 | 4.9 | 8.02 |
mistralai/Voxtral-Small-24B-2507 | 86.89 | 2.52 | 3.4 |
modulate/multilingual | -1 | 4.02 | 2.87 |
nvidia/canary-1b-v2 | 1,307.83 | 3.43 | 4.69 |
nvidia/parakeet-tdt-0.6b-v3 | 3,362.94 | 4.16 | 4.07 |
openai/whisper-large-v3 | 273.35 | 3.66 | 8.61 |
openai/whisper-large-v3-turbo | 331.51 | 3.66 | 8.61 |
Qwen/Qwen3-ASR-0.6B | 230.06 | 5.3 | 8.34 |
Qwen/Qwen3-ASR-1.7B | 233.18 | 3.21 | 4.89 |
reson8/resonant-1 | -1 | 2.56 | 3.01 |
reson8/resonant-1-flash | -1 | 2.56 | 3.01 |
soniox/stt-async-v5 | -1 | 2.66 | 4.62 |
speechmatics/enhanced | -1 | 3.56 | 1.99 |
assembly/universal-3-pro | -1 | 2.2 | 2.76 |
CohereLabs/cohere-transcribe-03-2026 | 723.2 | 3.26 | 2.79 |
elevenlabs/scribe_v2 | -1 | 1.85 | 2.55 |
facebook/omniASR-CTC-1B-v2 | 842.8 | 5.25 | 7.39 |
facebook/omniASR-CTC-300M-v2 | 1,088.31 | 9.37 | 13.45 |
facebook/omniASR-CTC-3B-v2 | 563 | 4 | 5.87 |
facebook/omniASR-CTC-7B-v2 | 360.67 | 3.88 | 5.62 |
facebook/omniASR-LLM-1B-v2 | 59.17 | 3.79 | 5.28 |
facebook/omniASR-LLM-300M-v2 | 65.22 | 5.31 | 7.51 |
facebook/omniASR-LLM-3B-v2 | 56.69 | 3.42 | 5.42 |
facebook/omniASR-LLM-7B-v2 | 53.96 | 2.94 | 4.07 |
ibm-granite/granite-speech-4.1-2b-nar | 1,617.91 | 3.61 | 3.95 |
microsoft/azure-speech | -1 | 1.75 | 2.24 |
microsoft/Phi-4-multimodal-instruct | 129.76 | 3.08 | 3.96 |
mistralai/Voxtral-Mini-3B-2507 | 188.46 | 3.46 | 4.28 |
mistralai/Voxtral-Mini-4B-Realtime-2602 | 53.09 | 2.8 | 5.05 |
mistralai/Voxtral-Small-24B-2507 | 104.14 | 2.86 | 3.01 |
modulate/multilingual | -1 | 3.77 | 2.78 |
nvidia/canary-1b-v2 | 1,466.05 | 2.63 | 3.94 |
nvidia/parakeet-tdt-0.6b-v3 | 3,786.16 | 3.25 | 3.53 |
openai/whisper-large-v3 | 328.27 | 2.73 | 5.88 |
openai/whisper-large-v3-turbo | 403.3 | 2.73 | 5.88 |
Qwen/Qwen3-ASR-0.6B | 312.53 | 4.47 | 6.52 |
Qwen/Qwen3-ASR-1.7B | 257.71 | 2.99 | 4.12 |
reson8/resonant-1 | -1 | 2.24 | 2.93 |
reson8/resonant-1-flash | -1 | 2.24 | 2.93 |
soniox/stt-async-v5 | -1 | 2.4 | 4.27 |
speechmatics/enhanced | -1 | 2.61 | 2.05 |
assembly/universal-3-pro | -1 | 2.84 | 6.3 |
CohereLabs/cohere-transcribe-03-2026 | 699.77 | 4.33 | 5.28 |
elevenlabs/scribe_v2 | -1 | 2.93 | 4.4 |
facebook/omniASR-CTC-1B-v2 | 810.19 | 10.71 | 13.3 |
facebook/omniASR-CTC-300M-v2 | 1,195.36 | 21.08 | 21.89 |
facebook/omniASR-CTC-3B-v2 | 595.57 | 8.31 | 10.84 |
facebook/omniASR-CTC-7B-v2 | 335.72 | 7.65 | 10.12 |
facebook/omniASR-LLM-1B-v2 | 54.54 | 7.46 | 9.45 |
facebook/omniASR-LLM-300M-v2 | 55.84 | 11.23 | 12.63 |
facebook/omniASR-LLM-3B-v2 | 53.8 | 6.88 | 10.5 |
facebook/omniASR-LLM-7B-v2 | 50.19 | 5.21 | 7.33 |
ibm-granite/granite-speech-4.1-2b-nar | 1,510.5 | 6.24 | 6.38 |
microsoft/azure-speech | -1 | 2.78 | 4.28 |
microsoft/Phi-4-multimodal-instruct | 119.56 | 4.19 | 6.83 |
mistralai/Voxtral-Mini-3B-2507 | 181.52 | 4.29 | 7.78 |
mistralai/Voxtral-Mini-4B-Realtime-2602 | 51.91 | 8.19 | 9.62 |
mistralai/Voxtral-Small-24B-2507 | 95.19 | 3.53 | 5.58 |
modulate/multilingual | -1 | 4.71 | 5.27 |
nvidia/canary-1b-v2 | 1,456.55 | 4.35 | 6.58 |
nvidia/parakeet-tdt-0.6b-v3 | 3,618.38 | 4.68 | 6.35 |
openai/whisper-large-v3 | 295.12 | 4.88 | 11.62 |
openai/whisper-large-v3-turbo | 363.61 | 4.88 | 11.62 |
Qwen/Qwen3-ASR-0.6B | 237.95 | 7.12 | 10.81 |
Qwen/Qwen3-ASR-1.7B | 229.92 | 4.13 | 7.91 |
reson8/resonant-1 | -1 | 3.61 | 5.81 |
reson8/resonant-1-flash | -1 | 3.61 | 5.81 |
soniox/stt-async-v5 | -1 | 4.24 | 9.84 |
speechmatics/enhanced | -1 | 4.37 | 5.7 |
assembly/universal-3-pro | -1 | 1.56 | 3.97 |
CohereLabs/cohere-transcribe-03-2026 | 717.97 | 2.33 | 2.51 |
elevenlabs/scribe_v2 | -1 | 0.9 | 2.17 |
facebook/omniASR-CTC-1B-v2 | 876.58 | 4.85 | 8.15 |
facebook/omniASR-CTC-300M-v2 | 999.96 | 9.29 | 15.19 |
facebook/omniASR-CTC-3B-v2 | 566.33 | 3.34 | 6.37 |
facebook/omniASR-CTC-7B-v2 | 328.19 | 3.34 | 5.68 |
facebook/omniASR-LLM-1B-v2 | 52.82 | 3.4 | 6.12 |
facebook/omniASR-LLM-300M-v2 | 56.44 | 5.24 | 9.14 |
facebook/omniASR-LLM-3B-v2 | 54.35 | 3.36 | 7.17 |
facebook/omniASR-LLM-7B-v2 | 48.95 | 2.29 | 4.18 |
microsoft/azure-speech | -1 | 1.03 | 1.8 |
microsoft/Phi-4-multimodal-instruct | 118.14 | 1.93 | 3.31 |
mistralai/Voxtral-Mini-3B-2507 | 179.08 | 2.22 | 5.75 |
mistralai/Voxtral-Mini-4B-Realtime-2602 | 49.35 | 3.02 | 6.35 |
mistralai/Voxtral-Small-24B-2507 | 96.31 | 2.27 | 3.31 |
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