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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowInvalid
Message: Float value 44.4273 was truncated converting to int64
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 622, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2245, in cast_table_to_schema
arrays = [
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2246, in <listcomp>
cast_array_to_feature(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2005, in cast_array_to_feature
arrays = [
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2006, in <listcomp>
_c(array.field(name) if name in array_fields else null_array, subfeature)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1797, in wrapper
return func(array, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2102, in cast_array_to_feature
return array_cast(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1797, in wrapper
return func(array, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1949, in array_cast
return array.cast(pa_type)
File "pyarrow/array.pxi", line 996, in pyarrow.lib.Array.cast
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/compute.py", line 404, in cast
return call_function("cast", [arr], options, memory_pool)
File "pyarrow/_compute.pyx", line 590, in pyarrow._compute.call_function
File "pyarrow/_compute.pyx", line 385, in pyarrow._compute.Function.call
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.ArrowInvalid: Float value 44.4273 was truncated converting to int64
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 1420, 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 1052, 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 datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
username
string | space_url
string | submission_timestamp
string | model_description
string | accuracy
float64 | energy_consumed_wh
float64 | emissions_gco2eq
float64 | emissions_data
dict | api_route
string | dataset_config
dict |
|---|---|---|---|---|---|---|---|---|---|
AB739 | https://huggingface.co/spaces/AB739/submission | 2025-01-17T10:57:42.144706 | Tiny_DNN | 0.99915 | 0.500194 | 0.184639 | {
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"energy_consumed": 0.000500194175332175,
"country_name": "United States",
"country_iso_code": "USA",
"region": "virginia",
"cloud_provider": "",
"cloud_region": "",
"os": "Linux-5.10.230-223.885.amzn2.x86_64-x86_64-with-glibc2.36",
"python_version": "3.9.21",
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"cpu_count": 16,
"cpu_model": "Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz",
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"tracking_mode": "machine",
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} | /audio | {
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"test_size": 0.2,
"test_seed": 42
} |
Maxons | https://huggingface.co/spaces/Maxons/submission-template | 2025-01-25T16:00:48.755077 | Trivial | 0.576105 | 0.002229 | 0.000823 | {
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"duration": 0.041337982984259725,
"emissions": 8.229146365649971e-7,
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"cpu_power": 150,
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"energy_consumed": 0.0000022293091238675457,
"country_name": "United States",
"country_iso_code": "USA",
"region": "virginia",
"cloud_provider": "",
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"os": "Linux-5.10.230-223.885.amzn2.x86_64-x86_64-with-glibc2.36",
"python_version": "3.9.21",
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"cpu_count": 16,
"cpu_model": "Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz",
"gpu_count": null,
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"ram_total_size": 123.80607604980469,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /audio | {
"dataset_name": "rfcx/frugalai",
"test_size": 0.2,
"test_seed": 42
} |
NicolasDenier | https://huggingface.co/spaces/NicolasDenier/frugal-ai-challenge-submission | 2025-01-31T19:57:15.839059 | ChainsawDetector | 0.930291 | 11.89808 | 4.39199 | {
"run_id": "11a9d898-ee75-4be0-8268-809d986fadfd",
"duration": 218.06167178903706,
"emissions": 0.004391990242978844,
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"cpu_power": 150,
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"cpu_energy": 0.009085876910792046,
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"ram_energy": 0.0028122027751883976,
"energy_consumed": 0.011898079685980445,
"country_name": "United States",
"country_iso_code": "USA",
"region": "virginia",
"cloud_provider": "",
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"os": "Linux-5.10.230-223.885.amzn2.x86_64-x86_64-with-glibc2.36",
"python_version": "3.9.21",
"codecarbon_version": "2.8.3",
"cpu_count": 16,
"cpu_model": "Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz",
"gpu_count": null,
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"ram_total_size": 123.80607604980469,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /audio | {
"dataset_name": "rfcx/frugalai",
"test_size": 0.2,
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} |
TheoLvs | https://huggingface.co/spaces/TheoLvs/api-test | 2025-01-06T05:40:00.712337 | Random Baseline | 0.50907 | 0.003635 | 0.001342 | {
"run_id": "73f50b13-c7e5-4747-83ee-e67aae9883b3",
"duration": 0.062445457000649185,
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"cpu_power": 150,
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"ram_energy": 8.526860410434283e-7,
"energy_consumed": 0.0000036348674159879612,
"country_name": "United States",
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"region": "virginia",
"cloud_provider": "",
"cloud_region": "",
"os": "Linux-5.10.230-223.885.amzn2.x86_64-x86_64-with-glibc2.36",
"python_version": "3.9.21",
"codecarbon_version": "2.8.2",
"cpu_count": 16,
"cpu_model": "Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz",
"gpu_count": null,
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"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /audio | {
"dataset_name": "rfcx/frugalai",
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} |
aweber | https://huggingface.co/spaces/aweber/submission-template-frugal-ai-challenge | 2025-01-17T13:51:29.103030 | Random Forest | 1 | 0.948857 | 0.350256 | {
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"country_name": "United States",
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"region": "virginia",
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"cloud_region": "",
"os": "Linux-5.10.230-223.885.amzn2.x86_64-x86_64-with-glibc2.36",
"python_version": "3.11.9",
"codecarbon_version": "2.8.2",
"cpu_count": 16,
"cpu_model": "Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz",
"gpu_count": null,
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"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /audio | {
"dataset_name": "rfcx/frugalai",
"test_size": 0.2,
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} |
heka-ai | https://huggingface.co/spaces/heka-ai/submission-frugalai | 2025-01-31T20:37:03.483139 | Audio pipeline to classify sounds. | 0.951379 | 0.646342 | 0.238587 | {
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"region": "virginia",
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"cpu_count": 4,
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"gpu_count": 1,
"gpu_model": "1 x Tesla T4",
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"tracking_mode": "machine",
"on_cloud": "N",
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} | /audio | {
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} |
madhavarora03 | https://huggingface.co/spaces/madhavarora03/frugal-ai-submission | 2025-01-07T15:51:58.731503 | M5 Model | 0.897676 | 18.858065 | 6.96116 | {
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"cpu_count": 16,
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} | /audio | {
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madhavarora03 | https://huggingface.co/spaces/madhavarora03/frugal-ai-submission | 2025-01-07T17:59:32.173646 | M5 Model | 0.909155 | 3.840509 | 1.417664 | {
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"on_cloud": "N",
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} | /audio | {
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pierre-loic | https://huggingface.co/spaces/pierre-loic/submission | 2025-01-24T22:08:18.286966 | Random Baseline | 0.94246 | 17.090962 | 6.308862 | {
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"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /audio | {
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} |
pierre-loic | https://huggingface.co/spaces/pierre-loic/submission | 2025-01-27T18:58:26.558200 | Decision tree | 0.909722 | 1.105358 | 0.408026 | {
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"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /audio | {
"dataset_name": "rfcx/frugalai",
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} |
tlmk22 | https://huggingface.co/spaces/tlmk22/frugalai | 2025-01-10T15:27:04.545293 | model_0 | 0.935941 | 1.308675 | 0.483077 | {
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"country_name": "United States",
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"os": "Linux-5.10.230-223.885.amzn2.x86_64-x86_64-with-glibc2.36",
"python_version": "3.9.21",
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"cpu_count": 16,
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"ram_total_size": 123.80607604980469,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /audio | {
"dataset_name": "rfcx/frugalai",
"test_size": 0.2,
"test_seed": 42
} |