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Error code: DatasetGenerationError Exception: ArrowNotImplementedError Message: Cannot write struct type 'transcribe' with no child field to Parquet. Consider adding a dummy child field. Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 620, in write_table self._build_writer(inferred_schema=pa_table.schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 441, in _build_writer self.pa_writer = self._WRITER_CLASS(self.stream, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__ self.writer = _parquet.ParquetWriter( File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__ File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'transcribe' with no child field to Parquet. Consider adding a dummy child field. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1886, in _prepare_split_single num_examples, num_bytes = writer.finalize() File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 639, in finalize self._build_writer(self.schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 441, in _build_writer self.pa_writer = self._WRITER_CLASS(self.stream, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__ self.writer = _parquet.ParquetWriter( File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__ File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'transcribe' with no child field to Parquet. Consider adding a dummy child field. 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 1417, in compute_config_parquet_and_info_response parquet_operations = convert_to_parquet(builder) File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1049, in convert_to_parquet builder.download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare self._download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1897, 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
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testInfo
dict | memoryStats
dict | latencyStats
dict | systemMeasurements
dict | staticAttributes
dict |
---|---|---|---|---|
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WhisperKit Evals Dataset
Overview
The WhisperKit Evals Dataset is a comprehensive collection of our speech recognition evaluation results, specifically designed to benchmark the performance of WhisperKit models across various devices and operating systems. This dataset provides detailed insights into performance and quality metrics, and model behavior under different conditions.
Dataset Structure
The dataset is organized into JSON files, each representing a single evaluation run. The file naming convention encodes crucial metadata:
{Date}_{CommitHash}/{DeviceIdentifier}_{ModelVersion}_{Timestamp}_{Dataset}_{UUID}.json
File Content
Each JSON file contains an array of objects with a testInfo
key, which includes:
diff
: An array of character-level differences between the reference and predicted transcriptions.prediction
: The full predicted transcription.reference
: The full reference transcription.wer
: Word Error Rate for the specific transcription.model
: The model used for the test.device
: The device on which the test was run.timings
: Various timing metrics for the transcription process.datasetRepo
: Repo on huggingface that was used as test data for the benchmarkdatasetDir
: Subfolder in the datasetRepo containing the specific audio files usedaudioFile
: The name of the audio file used.date
: Date that the benchmark was performed
It also includes various system measurements taken during the benchmarking process such as system diagnostics, memory, latency, and configuration.
Key Features
- Comprehensive Model Evaluation: Results from various WhisperKit models, including different sizes and architectures.
- Cross-Device Performance: Tests run on a range of devices, from mobile to desktop, allowing for performance comparisons.
- Detailed Metrics: Includes Word Error Rate (WER), processing speed, and detailed transcription comparisons.
- Rich Metadata: Each file contains extensive metadata about the test conditions and setup.
Use Cases
This dataset is invaluable for:
- Benchmarking speech recognition models
- Analyzing performance across different hardware
- Identifying specific strengths and weaknesses in transcription tasks
Contributing
We welcome contributions to expand and improve this dataset. Please refer to BENCHMARKS.md in the source repo.
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