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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    DatasetGenerationError
Message:      An error occurred while generating the dataset
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, 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 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in cast_table_to_schema
                  arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2261, in <listcomp>
                  arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1802, 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 1802, 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 2122, in cast_array_to_feature
                  raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
              TypeError: Couldn't cast array of type
              struct<lighteval_sha: string, num_few_shot_default: null, num_fewshot_seeds: null, override_batch_size: null, max_samples: null, job_id: int64, start_time: timestamp[s], end_time: string, total_evaluation_time_secondes: string, model_name: string, model_sha: string, model_dtype: string, quant_type: string, weight_dtype: string, model_size: double>
              to
              {'lighteval_sha': Value(dtype='string', id=None), 'num_few_shot_default': Value(dtype='null', id=None), 'num_fewshot_seeds': Value(dtype='null', id=None), 'override_batch_size': Value(dtype='null', id=None), 'max_samples': Value(dtype='null', id=None), 'job_id': Value(dtype='int64', id=None), 'start_time': Value(dtype='timestamp[s]', id=None), 'end_time': Value(dtype='string', id=None), 'total_evaluation_time_secondes': Value(dtype='string', id=None), 'model_name': Value(dtype='string', id=None), 'model_sha': Value(dtype='string', id=None), 'model_dtype': Value(dtype='string', id=None), 'model_size': Value(dtype='float64', id=None)}
              
              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 1321, 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 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 1882, 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 2038, 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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config_general
dict
results
dict
task_info
dict
versions
dict
{ "lighteval_sha": "1.14", "num_few_shot_default": null, "num_fewshot_seeds": null, "override_batch_size": null, "max_samples": null, "job_id": 2, "start_time": "2024-04-10T05:04:42", "end_time": "2024-04-10-05-16-22", "total_evaluation_time_secondes": "", "model_name": "facebook/opt-1.3b", "model_sha": "", "model_dtype": "bfloat16", "model_size": 1.3 }
{ "harness|winogrande|0": { "acc": 0.5951065509076559, "acc_stderr": 0.013795927003124934 }, "harness|arc:easy|0": { "acc": 0.5707070707070707, "acc_stderr": 0.010156678075911085, "acc_norm": 0.5088383838383839, "acc_norm_stderr": 0.010258180468004831 }, "harness|arc:challenge|0": { "acc": 0.23464163822525597, "acc_stderr": 0.012383873560768675, "acc_norm": 0.29692832764505117, "acc_norm_stderr": 0.013352025976725222 }, "harness|truthfulqa:mc|0": { "mc1": 0.24112607099143207, "mc1_stderr": 0.014974827279752332, "mc2": 0.38653059858550987, "mc2_stderr": 0.014234618399973241 } }
{ "model": "facebook/opt-1.3b", "base_model": "", "revision": "main", "private": false, "precision": "bfloat16", "params": 1.3, "architectures": "OPTForCausalLM", "weight_type": "Original", "status": "FINISHED", "submitted_time": "2024-04-10T11:23:43", "model_type": "🟒 : pretrained", "job_id": 2, "job_start_time": "2024-04-10T05:04:42" }
{ "harness|winogrande|0": 0, "harness|arc:easy|0": 0, "harness|arc:challenge|0": 0, "harness|truthfulqa:mc|0": 1 }
{ "lighteval_sha": "1.14", "num_few_shot_default": null, "num_fewshot_seeds": null, "override_batch_size": null, "max_samples": null, "job_id": 3, "start_time": "2024-04-10T05:34:32", "end_time": "2024-04-10-05-42-53", "total_evaluation_time_secondes": "", "model_name": "facebook/opt-125m", "model_sha": "", "model_dtype": "bfloat16", "model_size": 0.125 }
{ "harness|winogrande|0": { "acc": 0.500394632991318, "acc_stderr": 0.014052481306049516 }, "harness|arc:easy|0": { "acc": 0.4351851851851852, "acc_stderr": 0.010173216430370904, "acc_norm": 0.3985690235690236, "acc_norm_stderr": 0.01004645540047793 }, "harness|arc:challenge|0": { "acc": 0.19539249146757678, "acc_stderr": 0.01158690718995291, "acc_norm": 0.23293515358361774, "acc_norm_stderr": 0.0123525070426174 }, "harness|truthfulqa:mc|0": { "mc1": 0.23990208078335373, "mc1_stderr": 0.014948812679062135, "mc2": 0.4285249783495301, "mc2_stderr": 0.01506992646587412 } }
{ "model": "facebook/opt-125m", "base_model": "", "revision": "main", "private": false, "precision": "bfloat16", "params": 0.125, "architectures": "OPTForCausalLM", "weight_type": "Original", "status": "FINISHED", "submitted_time": "2024-04-10T12:05:21", "model_type": "🟒 : pretrained", "job_id": 3, "job_start_time": "2024-04-10T05:34:32" }
{ "harness|winogrande|0": 0, "harness|arc:easy|0": 0, "harness|arc:challenge|0": 0, "harness|truthfulqa:mc|0": 1 }
{ "lighteval_sha": "1.14", "num_few_shot_default": null, "num_fewshot_seeds": null, "override_batch_size": null, "max_samples": null, "job_id": 4, "start_time": "2024-04-10T06:13:22", "end_time": "2024-04-10-06-34-20", "total_evaluation_time_secondes": "", "model_name": "facebook/opt-350m", "model_sha": "", "model_dtype": "bfloat16", "model_size": 0.35 }
{ "harness|winogrande|0": { "acc": 0.5272296764009471, "acc_stderr": 0.014031631629827698 }, "harness|arc:easy|0": { "acc": 0.44107744107744107, "acc_stderr": 0.01018829322104055, "acc_norm": 0.4027777777777778, "acc_norm_stderr": 0.01006396049498916 }, "harness|arc:challenge|0": { "acc": 0.20648464163822525, "acc_stderr": 0.011828865619002316, "acc_norm": 0.24232081911262798, "acc_norm_stderr": 0.012521593295800116 }, "harness|truthfulqa:mc|0": { "mc1": 0.2350061199510404, "mc1_stderr": 0.014843061507731624, "mc2": 0.40953888018781043, "mc2_stderr": 0.014695924210168897 } }
{ "model": "facebook/opt-350m", "base_model": "", "revision": "main", "private": false, "precision": "bfloat16", "params": 0.35, "architectures": "OPTForCausalLM", "weight_type": "Original", "status": "FINISHED", "submitted_time": "2024-04-10T13:12:22", "model_type": "🟒 : pretrained", "job_id": 4, "job_start_time": "2024-04-10T06:13:22" }
{ "harness|winogrande|0": 0, "harness|arc:easy|0": 0, "harness|arc:challenge|0": 0, "harness|truthfulqa:mc|0": 1 }
{ "lighteval_sha": "1.14", "num_few_shot_default": null, "num_fewshot_seeds": null, "override_batch_size": null, "max_samples": null, "job_id": 6, "start_time": "2024-04-11T00:40:02", "end_time": "2024-04-11-00-53-12", "total_evaluation_time_secondes": "", "model_name": "facebook/opt-350m", "model_sha": "", "model_dtype": "8bit", "quant_type": "Rtn", "weight_dtype": "int8", "model_size": 0.35 }
{ "harness|winogrande|0": { "acc": 0.5272296764009471, "acc_stderr": 0.014031631629827698 }, "harness|arc:easy|0": { "acc": 0.44065656565656564, "acc_stderr": 0.010187264635711981, "acc_norm": 0.4006734006734007, "acc_norm_stderr": 0.010055304474255554 }, "harness|arc:challenge|0": { "acc": 0.2090443686006826, "acc_stderr": 0.011882746987406451, "acc_norm": 0.24146757679180889, "acc_norm_stderr": 0.012506564839739432 }, "harness|truthfulqa:mc|0": { "mc1": 0.23745410036719705, "mc1_stderr": 0.014896277441041843, "mc2": 0.409767382680759, "mc2_stderr": 0.014709547172142332 } }
{ "model": "facebook/opt-350m", "base_model": "", "revision": "main", "private": false, "precision": "8bit", "quant_type": "Rtn", "weight_dtype": "int8", "params": 0.35, "architectures": "OPTForCausalLM", "weight_type": "Original", "status": "FINISHED", "submitted_time": "2024-04-11T05:48:05", "model_type": "🟒 : pretrained", "job_id": 6, "job_start_time": "2024-04-11T00:40:02" }
{ "harness|winogrande|0": 0, "harness|arc:easy|0": 0, "harness|arc:challenge|0": 0, "harness|truthfulqa:mc|0": 1 }
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