Error code: DatasetGenerationError
Exception: ArrowInvalid
Message: Float value 42.5 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 42.5 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 |
|---|---|---|---|---|---|---|---|---|---|
MatthiasPi | https://huggingface.co/spaces/MatthiasPi/submission-template | 2025-01-10T16:32:50.808477 | Random Baseline | 0.136177 | 0.000317 | 0.000117 | {
"run_id": "1d631af1-e600-49cd-9cc2-3d8da45b71e4",
"duration": 0.006064094137400389,
"emissions": 1.1708387390292789e-7,
"emissions_rate": 0.000019178521081557062,
"cpu_power": 150,
"gpu_power": 0,
"ram_power": 46.42727851867676,
"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
} |
MatthiasPi | https://huggingface.co/spaces/MatthiasPi/submission-template | 2025-01-17T13:18:22.505601 | Test LogReg with tf idf | 0.385562 | 1.696771 | 0.626336 | {
"run_id": "99975a94-7461-40c8-b50e-06cf85f29653",
"duration": 31.097927659982815,
"emissions": 0.0006263363529498245,
"emissions_rate": 0.000020140860097166842,
"cpu_power": 150,
"gpu_power": 0,
"ram_power": 46.42727851867676,
"cpu_energy": 0.0012957335094591447,
"gpu_energy": 0,
"ram_energy": 0.0004010370718363578,
"energy_consumed": 0.0016967705812955024,
"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
} |
MatthiasPi | https://huggingface.co/spaces/MatthiasPi/submission-template | 2025-01-17T15:20:34.373442 | logreg_model_test | 0.654635 | 6.028456 | 2.22531 | {
"run_id": "87fd234c-ecf9-4321-a09f-e85493e90015",
"duration": 110.49092253399976,
"emissions": 0.002225310203990858,
"emissions_rate": 0.00002014035739185608,
"cpu_power": 150,
"gpu_power": 0,
"ram_power": 46.42727851867676,
"cpu_energy": 0.004603604281916697,
"gpu_energy": 0,
"ram_energy": 0.0014248513084470014,
"energy_consumed": 0.006028455590363699,
"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
} |
Nonnormalizable | https://huggingface.co/spaces/Nonnormalizable/frugal-ai-submission | 2025-01-17T21:02:15.979235 | bert base finetuned | 0.954061 | 0.735867 | 0.271634 | {
"run_id": "a7bc830f-a34c-400e-b8c9-0281a4df7cff",
"duration": 12.184559035000007,
"emissions": 0.00027163372750799934,
"emissions_rate": 0.000022293353473434155,
"cpu_power": 42.5,
"gpu_power": 151.77790775358343,
"ram_power": 23.22706890106201,
"cpu_energy": 0.0001437867093013889,
"gpu_energy": 0.0005135015219119999,
"ram_energy": 0.00007857855274787132,
"energy_consumed": 0.0007358667839612602,
"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": 8,
"cpu_model": "AMD EPYC 7R13 Processor",
"gpu_count": 1,
"gpu_model": "1 x NVIDIA L40S",
"ram_total_size": 61.93885040283203,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
"test_size": 0.2,
"test_seed": 42
} |
Nonnormalizable | https://huggingface.co/spaces/Nonnormalizable/frugal-ai-submission | 2025-01-20T22:13:45.735445 | bert base finetuned | 0.707137 | 0.802577 | 0.296259 | {
"run_id": "fd39edfd-0b26-4dd9-b408-28af47c3e89e",
"duration": 10.02831170599893,
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"cpu_power": 42.5,
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"cpu_energy": 0.00011806081655971385,
"gpu_energy": 0.0006199971626639766,
"ram_energy": 0.00006451919850928279,
"energy_consumed": 0.0008025771777329733,
"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": 8,
"cpu_model": "AMD EPYC 7R13 Processor",
"gpu_count": 1,
"gpu_model": "1 x NVIDIA L40S",
"ram_total_size": 61.93885040283203,
"tracking_mode": "machine",
"on_cloud": "N",
"pue": 1
} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
"test_size": 0.2,
"test_seed": 42
} |
Nonnormalizable | https://huggingface.co/spaces/Nonnormalizable/frugal-ai-submission | 2025-01-24T19:26:49.598109 | bert base fine tuned on just training data, Nvidia T4 small | 0.69073 | 1.097854 | 0.405256 | {
"run_id": "6efd251e-8020-4035-ba52-c80b8635e030",
"duration": 24.44813642599999,
"emissions": 0.00040525583135712126,
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"cpu_power": 105,
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"ram_power": 5.74672794342041,
"cpu_energy": 0.0007131214148625003,
"gpu_energy": 0.00034570444322999997,
"ram_energy": 0.00003902862425829526,
"energy_consumed": 0.0010978544823507955,
"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
} |
Nonnormalizable | https://huggingface.co/spaces/Nonnormalizable/frugal-ai-submission | 2025-01-24T19:43:56.086948 | bert mini fine tuned on just training data, Nvidia T4 small | 0.649713 | 0.130344 | 0.048114 | {
"run_id": "27e6335b-a8af-4494-9c69-7dd6823f2b55",
"duration": 3.2131511560000945,
"emissions": 0.00004811441008229286,
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"cpu_power": 105,
"gpu_power": 35.43962510355979,
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"cpu_energy": 0.00009362092299585734,
"gpu_energy": 0.000031600025279965305,
"ram_energy": 0.00000512293992343425,
"energy_consumed": 0.0001303438881992569,
"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": 15.324600219726562,
"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,
"emissions_rate": 0.000015397088437067526,
"cpu_power": 105,
"gpu_power": 39.415202015964574,
"ram_power": 5.74672794342041,
"cpu_energy": 0.0012991950741000006,
"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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"ram_power": 5.746725082397461,
"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": "",
"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": 15.324600219726562,
"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 | {
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"duration": 0.00568622606806457,
"emissions": 1.1169021641940817e-7,
"emissions_rate": 0.000019273944302494004,
"cpu_power": 150,
"gpu_power": 0,
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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": "",
"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": 123.80606842041016,
"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 | {
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"duration": 0.005468626000038057,
"emissions": 1.075427759119887e-7,
"emissions_rate": 0.00001934562180582405,
"cpu_power": 150,
"gpu_power": 0,
"ram_power": 46.42727851867676,
"cpu_energy": 2.2726087498388857e-7,
"gpu_energy": 0,
"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,
"emissions_rate": 0.000019551923854500174,
"cpu_power": 150,
"gpu_power": 0,
"ram_power": 46.42727851867676,
"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 | {
"run_id": "97b62a7e-8059-4c0e-adc9-6f2d5945a92b",
"duration": 269.3269728734158,
"emissions": 0.0054232345628042735,
"emissions_rate": 0.000020141159692181115,
"cpu_power": 150,
"gpu_power": 0,
"ram_power": 46.42727851867676,
"cpu_energy": 0.011219244850003937,
"gpu_energy": 0,
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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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axel-darmouni | https://huggingface.co/spaces/axel-darmouni/submission-test | 2025-01-10T15:26:56.065288 | Random Baseline | 0.151764 | 0.000607 | 0.000224 | {
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christopher | https://huggingface.co/spaces/christopher/submission-template | 2025-01-14T19:48:46.540088 | Random Baseline | 0.123872 | 0.000437 | 0.000161 | {
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clementdesroches | https://huggingface.co/spaces/clementdesroches/submission-frugal-ai-challenge | 2025-01-14T21:12:48.033647 | random model | 0.124692 | 0.000279 | 0.000103 | {
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clementdesroches | https://huggingface.co/spaces/clementdesroches/submission-frugal-ai-challenge | 2025-01-14T21:58:52.112871 | RF overfitted like crazy | 0.974569 | 0.236869 | 0.087437 | {
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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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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 | {
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kantundpeterpan | https://huggingface.co/spaces/kantundpeterpan/submission-template | 2025-01-18T12:27:48.066129 | tfidf-rf | 0.879409 | 0.259167 | 0.095667 | {
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laureBe | https://huggingface.co/spaces/laureBe/baseline | 2025-01-15T10:48:24.207524 | Random Baseline | 0.652174 | 0.300764 | 0.111022 | {
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laureBe | https://huggingface.co/spaces/laureBe/baseline | 2025-01-15T10:57:05.945210 | Logistic Regression Baseline | 0.652174 | 1.285292 | 0.474446 | {
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maianume | https://huggingface.co/spaces/maianume/frugal-ai-challenge | 2025-01-20T22:22:26.779063 | Basic Distilbert Uncased | 0.652174 | 7.665037 | 2.829429 | {
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pierre-loic | https://huggingface.co/spaces/pierre-loic/submission | 2025-01-15T17:37:44.712429 | Random Baseline | 0.115669 | 0.000313 | 0.000116 | {
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seronk | https://huggingface.co/spaces/seronk/submission-template | 2025-01-25T16:01:14.764238 | Random Baseline | 0.133716 | 0.000339 | 0.000125 | {
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theterryzhang | https://huggingface.co/spaces/theterryzhang/submission-template | 2025-01-25T13:37:16.441759 | TF-IDF vectorizer and XGBoost classifier | 0.914684 | 0.210353 | 0.077648 | {
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