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The dataset generation failed
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 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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"energy_consumed": 3.1718496275517184e-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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"tracking_mode": "machine",
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} | /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 | {
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"gpu_model": null,
"ram_total_size": 123.80607604980469,
"tracking_mode": "machine",
"on_cloud": "N",
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} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
"test_size": 0.2,
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} |
MatthiasPi | https://huggingface.co/spaces/MatthiasPi/submission-template | 2025-01-17T15:20:34.373442 | logreg_model_test | 0.654635 | 6.028456 | 2.22531 | {
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"ram_total_size": 123.80607604980469,
"tracking_mode": "machine",
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} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
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} |
Nonnormalizable | https://huggingface.co/spaces/Nonnormalizable/frugal-ai-submission | 2025-01-17T21:02:15.979235 | bert base finetuned | 0.954061 | 0.735867 | 0.271634 | {
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"country_name": "United States",
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"ram_total_size": 61.93885040283203,
"tracking_mode": "machine",
"on_cloud": "N",
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} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
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} |
Nonnormalizable | https://huggingface.co/spaces/Nonnormalizable/frugal-ai-submission | 2025-01-20T22:13:45.735445 | bert base finetuned | 0.707137 | 0.802577 | 0.296259 | {
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"ram_total_size": 61.93885040283203,
"tracking_mode": "machine",
"on_cloud": "N",
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} | /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 | {
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"cpu_count": 4,
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"tracking_mode": "machine",
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} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
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} |
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 | {
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} | /text | {
"dataset_name": "QuotaClimat/frugalaichallenge-text-train",
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} |
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 | {
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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": 4,
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"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,
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} |
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 | {
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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",
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"cpu_count": 4,
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"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,
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} |
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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"country_name": "United States",
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"os": "Linux-5.10.228-219.884.amzn2.x86_64-x86_64-with-glibc2.36",
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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,
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} |
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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"cpu_count": 16,
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"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 | {
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"country_name": "United States",
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"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": 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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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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