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The dataset generation failed
Error code: DatasetGenerationError Exception: ArrowInvalid Message: Float value 39.4152 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 39.4152 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 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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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 |
---|---|---|---|---|---|---|---|---|---|
MatthiasPi | https://huggingface.co/spaces/MatthiasPi/submission-template | 2025-01-10T16:32:50.808477 | Random Baseline | 0.136177 | 0.000317 | 0.000117 | {
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"duration": 0.006064094137400389,
"emissions": 1.1708387390292789e-7,
"emissions_rate": 0.000019178521081557062,
"cpu_power": 150,
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"cpu_energy": 2.481934595076988e-7,
"gpu_energy": 0,
"ram_energy": 6.899150324747306e-8,
"energy_consumed": 3.1718496275517184e-7,
"country_name": "United States",
"country_iso_code": "USA",
"region": "virginia",
"cloud_provider": "",
"cloud_region": "",
"os": "Linux-5.10.228-219.884.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,
"gpu_model": null,
"ram_total_size": 123.80607604980469,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
"test_size": 0.2,
"test_seed": 42
} |
Oriaz | https://huggingface.co/spaces/Oriaz/submission-template-frugal-ai | 2025-01-06T16:33:16.165519 | Embedding + Logistic Regression | 0.724364 | 1.857997 | 0.685851 | {
"run_id": "ccbe2387-e097-4677-a6ed-39400a5a1485",
"duration": 44.544224079,
"emissions": 0.0006858505086018414,
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"cpu_power": 105,
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"gpu_energy": 0.00048769677904600016,
"ram_energy": 0.00007110498941534462,
"energy_consumed": 0.0018579968425613453,
"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",
"codecarbon_version": "2.8.2",
"cpu_count": 4,
"cpu_model": "Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz",
"gpu_count": 1,
"gpu_model": "1 x Tesla T4",
"ram_total_size": 15.324607849121094,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
"test_size": 0.2,
"test_seed": 42
} |
Oriaz | https://huggingface.co/spaces/Oriaz/submission-template-frugal-ai | 2025-01-07T17:33:25.876777 | Simple BERT classif | 0.912223 | 0.68278 | 0.252038 | {
"run_id": "3f3d2930-356e-4130-8023-ea5ad6b00227",
"duration": 15.627143449999494,
"emissions": 0.00025203752463818645,
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"cpu_power": 105,
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"cpu_energy": 0.0004557684610207844,
"gpu_energy": 0.00020206793943200463,
"ram_energy": 0.00002494347520752396,
"energy_consumed": 0.000682779875660313,
"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": "2.8.2",
"cpu_count": 4,
"cpu_model": "Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz",
"gpu_count": 1,
"gpu_model": "1 x Tesla T4",
"ram_total_size": 15.324600219726562,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
"test_size": 0.2,
"test_seed": 42
} |
Rcarvalo | https://huggingface.co/spaces/Rcarvalo/baseline | 2025-01-10T16:29:08.743708 | Random Baseline | 0.120591 | 0.000303 | 0.000112 | {
"run_id": "59d6c157-9469-4e87-88c6-5e5841d83ce0",
"duration": 0.00568622606806457,
"emissions": 1.1169021641940817e-7,
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"cpu_power": 150,
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"cpu_energy": 2.364860459541281e-7,
"gpu_energy": 0,
"ram_energy": 6.608727993768937e-8,
"energy_consumed": 3.0257332589181747e-7,
"country_name": "United States",
"country_iso_code": "USA",
"region": "virginia",
"cloud_provider": "",
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"os": "Linux-5.10.228-219.884.amzn2.x86_64-x86_64-with-glibc2.36",
"python_version": "3.9.21",
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"cpu_count": 16,
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"gpu_model": null,
"ram_total_size": 123.80606842041016,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
"test_size": 0.2,
"test_seed": 42
} |
TheoLvs | https://huggingface.co/spaces/TheoLvs/api-test | 2025-01-06T03:47:05.960059 | No description provided | 0.125513 | 0.000291 | 0.000108 | {
"run_id": "346f1734-0e48-4580-890d-26ca6381594e",
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"ram_energy": 6.407686637332611e-8,
"energy_consumed": 2.913377413572146e-7,
"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",
"codecarbon_version": "2.8.2",
"cpu_count": 16,
"cpu_model": "Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz",
"gpu_count": null,
"gpu_model": null,
"ram_total_size": 123.80607604980469,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | null | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
"test_size": 0.2,
"test_seed": 42
} |
TheoLvs | https://huggingface.co/spaces/TheoLvs/api-test | 2025-01-06T05:23:55.671189 | Random Baseline | 0.11977 | 0.000601 | 0.000222 | {
"run_id": "b9dffe34-eb0a-42b1-a1a2-62cd1a70cd99",
"duration": 0.011197488000107114,
"emissions": 2.2196880743239585e-7,
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"cpu_energy": 4.66463083284907e-7,
"gpu_energy": 0,
"ram_energy": 1.34859418024078e-7,
"energy_consumed": 6.01322501308985e-7,
"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",
"codecarbon_version": "2.8.2",
"cpu_count": 16,
"cpu_model": "Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz",
"gpu_count": null,
"gpu_model": null,
"ram_total_size": 123.80607604980469,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
"test_size": 0.2,
"test_seed": 42
} |
VanshK04 | https://huggingface.co/spaces/VanshK04/submission-template | 2025-01-11T11:52:01.884588 | Evaluate text classification for climate disinformation detection | 0.926989 | 14.691762 | 5.423235 | {
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"energy_consumed": 0.014691762370638628,
"country_name": "United States",
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"region": "virginia",
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"os": "Linux-5.10.228-219.884.amzn2.x86_64-x86_64-with-glibc2.36",
"python_version": "3.9.21",
"codecarbon_version": "2.8.2",
"cpu_count": 16,
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"gpu_model": null,
"ram_total_size": 123.80607604980469,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
"test_size": 0.2,
"test_seed": 42
} |
Zen0 | https://huggingface.co/spaces/Zen0/submission-template | 2025-01-11T21:55:16.772961 | FrugalDisinfoHunter Model | 0.141099 | 7.723333 | 2.850948 | {
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"duration": 141.54955771996174,
"emissions": 0.0028509476700947695,
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"cpu_power": 150,
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"energy_consumed": 0.007723332858850174,
"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",
"codecarbon_version": "2.8.2",
"cpu_count": 16,
"cpu_model": "Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz",
"gpu_count": null,
"gpu_model": null,
"ram_total_size": 123.80607604980469,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
"test_size": 0.2,
"test_seed": 42
} |
axel-darmouni | https://huggingface.co/spaces/axel-darmouni/submission-test | 2025-01-10T15:26:56.065288 | Random Baseline | 0.151764 | 0.000607 | 0.000224 | {
"run_id": "aff453ca-3ce5-4870-8cc5-b7cf2b9d83e7",
"duration": 0.011324439001327846,
"emissions": 2.2418575427696858e-7,
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"cpu_power": 150,
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"gpu_energy": 0,
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"energy_consumed": 6.073283002195078e-7,
"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",
"codecarbon_version": "2.8.2",
"cpu_count": 16,
"cpu_model": "Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz",
"gpu_count": null,
"gpu_model": null,
"ram_total_size": 123.80607604980469,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
"test_size": 0.2,
"test_seed": 42
} |
frugal-ai-challenge | https://huggingface.co/spaces/frugal-ai-challenge/submission-portal-text | 2025-01-06T03:14:52.790846 | Random baseline | 0.11895 | 0.001974 | 0.000729 | {
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"energy_consumed": 0.000001974336358150333,
"country_name": "United States",
"country_iso_code": "USA",
"region": "virginia",
"cloud_provider": "",
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"os": "Linux-5.10.228-219.884.amzn2.x86_64-x86_64-with-glibc2.36",
"python_version": "3.10.13",
"codecarbon_version": "2.8.1",
"cpu_count": 96,
"cpu_model": "Intel(R) Xeon(R) Platinum 8275CL CPU @ 3.00GHz",
"gpu_count": null,
"gpu_model": null,
"ram_total_size": 1121.8058815002441,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | null | null |
frugal-ai-challenge | https://huggingface.co/spaces/frugal-ai-challenge/submission-template | 2025-01-06T16:50:25.811675 | Random Baseline | 0.11813 | 0.001101 | 0.000406 | {
"run_id": "adab02e7-f48b-4dfd-bdaf-463b83e7509c",
"duration": 0.011773491998610552,
"emissions": 4.062875444159546e-7,
"emissions_rate": 0.00001985867523508468,
"cpu_power": 150,
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"gpu_energy": 0,
"ram_energy": 2.537395597842943e-7,
"energy_consumed": 0.0000011006494348684358,
"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",
"codecarbon_version": "2.8.2",
"cpu_count": 16,
"cpu_model": "Intel(R) Xeon(R) Platinum 8375C CPU @ 2.90GHz",
"gpu_count": null,
"gpu_model": null,
"ram_total_size": 123.80607604980469,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
"test_size": 0.2,
"test_seed": 42
} |