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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 e9d9fcb2dd482b54ca83140fca1cfddab48604b2), ['hf://datasets/hf-audio/multilingual_evals@e9d9fcb2dd482b54ca83140fca1cfddab48604b2/multilingual_de.csv', 'hf://datasets/hf-audio/multilingual_evals@e9d9fcb2dd482b54ca83140fca1cfddab48604b2/multilingual_es.csv', 'hf://datasets/hf-audio/multilingual_evals@e9d9fcb2dd482b54ca83140fca1cfddab48604b2/multilingual_fr.csv', 'hf://datasets/hf-audio/multilingual_evals@e9d9fcb2dd482b54ca83140fca1cfddab48604b2/multilingual_it.csv', 'hf://datasets/hf-audio/multilingual_evals@e9d9fcb2dd482b54ca83140fca1cfddab48604b2/multilingual_latest.csv', 'hf://datasets/hf-audio/multilingual_evals@e9d9fcb2dd482b54ca83140fca1cfddab48604b2/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 e9d9fcb2dd482b54ca83140fca1cfddab48604b2), ['hf://datasets/hf-audio/multilingual_evals@e9d9fcb2dd482b54ca83140fca1cfddab48604b2/multilingual_de.csv', 'hf://datasets/hf-audio/multilingual_evals@e9d9fcb2dd482b54ca83140fca1cfddab48604b2/multilingual_es.csv', 'hf://datasets/hf-audio/multilingual_evals@e9d9fcb2dd482b54ca83140fca1cfddab48604b2/multilingual_fr.csv', 'hf://datasets/hf-audio/multilingual_evals@e9d9fcb2dd482b54ca83140fca1cfddab48604b2/multilingual_it.csv', 'hf://datasets/hf-audio/multilingual_evals@e9d9fcb2dd482b54ca83140fca1cfddab48604b2/multilingual_latest.csv', 'hf://datasets/hf-audio/multilingual_evals@e9d9fcb2dd482b54ca83140fca1cfddab48604b2/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 |
|---|---|---|---|
assemblyai/universal-3-pro | -1 | 2.42 | 2.76 |
CohereLabs/cohere-transcribe-03-2026 | 606.88 | 3.33 | 2.87 |
elevenlabs/scribe_v2 | -1 | 2.3 | 2.19 |
facebook/omniASR-CTC-1B-v2 | 762.41 | 7.2 | 9.64 |
facebook/omniASR-CTC-300M-v2 | 1,011.36 | 14.06 | 18.89 |
facebook/omniASR-CTC-3B-v2 | 526.62 | 5.04 | 7.3 |
facebook/omniASR-CTC-7B-v2 | 310.76 | 4.89 | 7.01 |
facebook/omniASR-LLM-1B-v2 | 47.07 | 5.92 | 6.6 |
facebook/omniASR-LLM-300M-v2 | 47.8 | 7.78 | 10.31 |
facebook/omniASR-LLM-3B-v2 | 45.28 | 4.63 | 6.48 |
facebook/omniASR-LLM-7B-v2 | 42.5 | 3.72 | 5.06 |
ibm-granite/granite-speech-4.1-2b-nar | 1,402.39 | 4.87 | 3.78 |
microsoft/azure-speech-06-2026 | -1 | 1.93 | 1.88 |
microsoft/Phi-4-multimodal-instruct | 122.69 | 3.99 | 4.25 |
microsoft/VibeVoice-ASR-HF | 113.69 | 7.44 | 20.97 |
mistralai/Voxtral-Mini-3B-2507 | 149.66 | 3.64 | 5.29 |
mistralai/Voxtral-Mini-4B-Realtime-2602 | 42.1 | 4.87 | 7.81 |
mistralai/Voxtral-Small-24B-2507 | 82.96 | 2.61 | 3.19 |
modulate/multilingual | -1 | 4.02 | 2.87 |
nvidia/canary-1b-v2 | 1,307.83 | 3.43 | 4.69 |
nvidia/nemotron-3.5-asr-streaming-0.6b | 1,109.98 | 8.46 | 9.46 |
nvidia/parakeet-tdt-0.6b-v3 | 3,362.94 | 4.16 | 4.07 |
openai/whisper-large-v3 | 327.55 | 3.2 | 4.79 |
openai/whisper-large-v3-turbo | 338.32 | 3.67 | 8.58 |
Qwen/Qwen3-ASR-0.6B-hf | 384.27 | 5.41 | 7.97 |
Qwen/Qwen3-ASR-1.7B-hf | 368.59 | 3.35 | 4.6 |
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 |
assemblyai/universal-3-pro | -1 | 2.2 | 2.76 |
CohereLabs/cohere-transcribe-03-2026 | 737.32 | 3.26 | 2.79 |
elevenlabs/scribe_v2 | -1 | 1.85 | 2.55 |
facebook/omniASR-CTC-1B-v2 | 876.12 | 5.25 | 7.39 |
facebook/omniASR-CTC-300M-v2 | 1,107.76 | 9.37 | 13.44 |
facebook/omniASR-CTC-3B-v2 | 569.88 | 4 | 5.87 |
facebook/omniASR-CTC-7B-v2 | 353.73 | 3.88 | 5.61 |
facebook/omniASR-LLM-1B-v2 | 59.04 | 3.85 | 5.15 |
facebook/omniASR-LLM-300M-v2 | 60.47 | 5.39 | 7.33 |
facebook/omniASR-LLM-3B-v2 | 55.45 | 3.4 | 5.12 |
facebook/omniASR-LLM-7B-v2 | 53.05 | 2.93 | 4 |
ibm-granite/granite-speech-4.1-2b-nar | 1,617.91 | 3.61 | 3.95 |
microsoft/azure-speech-06-2026 | -1 | 1.75 | 2.24 |
microsoft/Phi-4-multimodal-instruct | 135.31 | 3.23 | 4.04 |
microsoft/VibeVoice-ASR-HF | 136.35 | 3.58 | 11.87 |
mistralai/Voxtral-Mini-3B-2507 | 183.34 | 3.25 | 4.36 |
mistralai/Voxtral-Mini-4B-Realtime-2602 | 53.15 | 2.8 | 5.02 |
mistralai/Voxtral-Small-24B-2507 | 101.48 | 2.79 | 2.9 |
modulate/multilingual | -1 | 3.77 | 2.78 |
nvidia/canary-1b-v2 | 1,466.05 | 2.63 | 3.94 |
nvidia/nemotron-3.5-asr-streaming-0.6b | 1,165.44 | 4.23 | 6.91 |
nvidia/parakeet-tdt-0.6b-v3 | 3,786.16 | 3.25 | 3.53 |
openai/whisper-large-v3 | 386.26 | 2.3 | 4.29 |
openai/whisper-large-v3-turbo | 660.78 | 2.73 | 4.98 |
Qwen/Qwen3-ASR-0.6B-hf | 435.03 | 4.46 | 6.39 |
Qwen/Qwen3-ASR-1.7B-hf | 442.85 | 2.92 | 4.03 |
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 |
assemblyai/universal-3-pro | -1 | 2.84 | 6.3 |
CohereLabs/cohere-transcribe-03-2026 | 635.11 | 4.33 | 5.28 |
elevenlabs/scribe_v2 | -1 | 2.93 | 4.4 |
facebook/omniASR-CTC-1B-v2 | 889.08 | 10.71 | 13.3 |
facebook/omniASR-CTC-300M-v2 | 1,065.82 | 21.08 | 21.89 |
facebook/omniASR-CTC-3B-v2 | 540.08 | 8.31 | 10.84 |
facebook/omniASR-CTC-7B-v2 | 332.74 | 7.65 | 10.12 |
facebook/omniASR-LLM-1B-v2 | 54.07 | 7.35 | 9.18 |
facebook/omniASR-LLM-300M-v2 | 54.82 | 11.21 | 12.07 |
facebook/omniASR-LLM-3B-v2 | 52.4 | 6.82 | 9.65 |
facebook/omniASR-LLM-7B-v2 | 48.3 | 5.19 | 7.26 |
ibm-granite/granite-speech-4.1-2b-nar | 1,510.5 | 6.24 | 6.38 |
microsoft/azure-speech-06-2026 | -1 | 2.78 | 4.28 |
microsoft/Phi-4-multimodal-instruct | 127.69 | 4.08 | 6.89 |
microsoft/VibeVoice-ASR-HF | 125.68 | 11.3 | 23.85 |
mistralai/Voxtral-Mini-3B-2507 | 158.29 | 4.13 | 7.8 |
mistralai/Voxtral-Mini-4B-Realtime-2602 | 50.43 | 8.19 | 9.57 |
mistralai/Voxtral-Small-24B-2507 | 89.24 | 3.61 | 5.5 |
modulate/multilingual | -1 | 4.71 | 5.27 |
nvidia/canary-1b-v2 | 1,456.55 | 4.35 | 6.58 |
nvidia/nemotron-3.5-asr-streaming-0.6b | 1,174.69 | 9.86 | 10.97 |
nvidia/parakeet-tdt-0.6b-v3 | 3,618.38 | 4.68 | 6.35 |
openai/whisper-large-v3 | 339.65 | 4.84 | 9.97 |
openai/whisper-large-v3-turbo | 591.2 | 4.9 | 11.06 |
Qwen/Qwen3-ASR-0.6B-hf | 396.31 | 7.06 | 10.78 |
Qwen/Qwen3-ASR-1.7B-hf | 378.72 | 4.06 | 7.84 |
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 |
assemblyai/universal-3-pro | -1 | 1.56 | 3.97 |
CohereLabs/cohere-transcribe-03-2026 | 687.45 | 2.33 | 2.51 |
elevenlabs/scribe_v2 | -1 | 0.9 | 2.17 |
facebook/omniASR-CTC-1B-v2 | 815.1 | 4.85 | 8.15 |
facebook/omniASR-CTC-300M-v2 | 1,041.23 | 9.29 | 15.18 |
facebook/omniASR-CTC-3B-v2 | 558.12 | 3.34 | 6.37 |
facebook/omniASR-CTC-7B-v2 | 330.31 | 3.34 | 5.68 |
facebook/omniASR-LLM-1B-v2 | 51.81 | 3.39 | 5.49 |
facebook/omniASR-LLM-300M-v2 | 52.82 | 5.41 | 8.39 |
facebook/omniASR-LLM-3B-v2 | 50.97 | 3.11 | 6.29 |
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