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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowNotImplementedError
Message: Cannot write struct type 'task_hashes' with no child field to Parquet. Consider adding a dummy child field.
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 583, in write_table
self._build_writer(inferred_schema=pa_table.schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 404, in _build_writer
self.pa_writer = self._WRITER_CLASS(self.stream, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
self.writer = _parquet.ParquetWriter(
File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
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.ArrowNotImplementedError: Cannot write struct type 'task_hashes' with no child field to Parquet. Consider adding a dummy child field.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2029, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 602, in finalize
self._build_writer(self.schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 404, in _build_writer
self.pa_writer = self._WRITER_CLASS(self.stream, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
self.writer = _parquet.ParquetWriter(
File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
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.ArrowNotImplementedError: Cannot write struct type 'task_hashes' with no child field to Parquet. Consider adding a dummy child field.
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 1396, 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 1045, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1029, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1124, 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 1884, 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 2040, 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.
results
dict | group_subtasks
dict | configs
dict | versions
dict | n-shot
dict | higher_is_better
dict | n-samples
dict | config
dict | git_hash
string | date
float64 | pretty_env_info
string | transformers_version
string | upper_git_hash
null | tokenizer_pad_token
sequence | tokenizer_eos_token
sequence | tokenizer_bos_token
sequence | eot_token_id
int64 | max_length
int64 | task_hashes
dict | model_source
string | model_name
string | model_name_sanitized
string | system_instruction
null | system_instruction_sha
null | fewshot_as_multiturn
bool | chat_template
null | chat_template_sha
null | start_time
float64 | end_time
float64 | total_evaluation_time_seconds
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
{
"gsm8k": {
"alias": "gsm8k",
"exact_match,strict-match": 0,
"exact_match_stderr,strict-match": 0,
"exact_match,flexible-extract": 0,
"exact_match_stderr,flexible-extract": 0
}
} | {
"gsm8k": []
} | {
"gsm8k": {
"task": "gsm8k",
"tag": [
"math_word_problems"
],
"dataset_path": "gsm8k",
"dataset_name": "main",
"training_split": "train",
"test_split": "test",
"fewshot_split": "train",
"doc_to_text": "Question: {{question}}\nAnswer:",
"doc_to_target": "{{answer}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 5,
"metric_list": [
{
"metric": "exact_match",
"aggregation": "mean",
"higher_is_better": true,
"ignore_case": true,
"ignore_punctuation": false,
"regexes_to_ignore": [
",",
"\\$",
"(?s).*#### ",
"\\.$"
]
}
],
"output_type": "generate_until",
"generation_kwargs": {
"until": [
"Question:",
"</s>",
"<|im_end|>"
],
"do_sample": false,
"temperature": 0
},
"repeats": 1,
"filter_list": [
{
"name": "strict-match",
"filter": [
{
"function": "regex",
"regex_pattern": "#### (\\-?[0-9\\.\\,]+)",
"group_select": null
},
{
"function": "take_first",
"regex_pattern": null,
"group_select": null
}
]
},
{
"name": "flexible-extract",
"filter": [
{
"function": "regex",
"regex_pattern": "(-?[$0-9.,]{2,})|(-?[0-9]+)",
"group_select": -1
},
{
"function": "take_first",
"regex_pattern": null,
"group_select": null
}
]
}
],
"should_decontaminate": false,
"metadata": {
"version": 3
}
}
} | {
"gsm8k": 3
} | {
"gsm8k": 5
} | {
"gsm8k": {
"exact_match": true
}
} | {
"gsm8k": {
"original": 1319,
"effective": 10
}
} | {
"model": "hf",
"model_args": "pretrained=EleutherAI/pythia-14m",
"model_num_parameters": 14067712,
"model_dtype": "torch.float16",
"model_revision": "main",
"model_sha": "f33025648652797a390d8c54835273845b437161",
"batch_size": 1,
"batch_sizes": [],
"device": "mps",
"use_cache": null,
"limit": 10,
"bootstrap_iters": 100000,
"gen_kwargs": null,
"random_seed": 0,
"numpy_seed": 1234,
"torch_seed": 1234,
"fewshot_seed": 1234
} | 928e8bb6 | 1,724,994,608.480619 | 'NoneType' object has no attribute 'splitlines' | 4.44.2 | null | [
"<|endoftext|>",
"0"
] | [
"<|endoftext|>",
"0"
] | [
"<|endoftext|>",
"0"
] | 0 | 2,048 | {} | hf | EleutherAI/pythia-14m | EleutherAI__pythia-14m | null | null | false | null | null | 47,688.603724 | 47,704.988023 | 16.384299125005782 |
{
"gsm8k": {
"alias": "gsm8k",
"exact_match,strict-match": 0,
"exact_match_stderr,strict-match": 0,
"exact_match,flexible-extract": 0,
"exact_match_stderr,flexible-extract": 0
}
} | {
"gsm8k": []
} | {
"gsm8k": {
"task": "gsm8k",
"tag": [
"math_word_problems"
],
"dataset_path": "gsm8k",
"dataset_name": "main",
"training_split": "train",
"test_split": "test",
"fewshot_split": "train",
"doc_to_text": "Question: {{question}}\nAnswer:",
"doc_to_target": "{{answer}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 5,
"metric_list": [
{
"metric": "exact_match",
"aggregation": "mean",
"higher_is_better": true,
"ignore_case": true,
"ignore_punctuation": false,
"regexes_to_ignore": [
",",
"\\$",
"(?s).*#### ",
"\\.$"
]
}
],
"output_type": "generate_until",
"generation_kwargs": {
"until": [
"Question:",
"</s>",
"<|im_end|>"
],
"do_sample": false,
"temperature": 0
},
"repeats": 1,
"filter_list": [
{
"name": "strict-match",
"filter": [
{
"function": "regex",
"regex_pattern": "#### (\\-?[0-9\\.\\,]+)",
"group_select": null
},
{
"function": "take_first",
"regex_pattern": null,
"group_select": null
}
]
},
{
"name": "flexible-extract",
"filter": [
{
"function": "regex",
"regex_pattern": "(-?[$0-9.,]{2,})|(-?[0-9]+)",
"group_select": -1
},
{
"function": "take_first",
"regex_pattern": null,
"group_select": null
}
]
}
],
"should_decontaminate": false,
"metadata": {
"version": 3
}
}
} | {
"gsm8k": 3
} | {
"gsm8k": 5
} | {
"gsm8k": {
"exact_match": true
}
} | {
"gsm8k": {
"original": 1319,
"effective": 10
}
} | {
"model": "hf",
"model_args": "pretrained=EleutherAI/pythia-14m",
"model_num_parameters": 14067712,
"model_dtype": "torch.float16",
"model_revision": "main",
"model_sha": "f33025648652797a390d8c54835273845b437161",
"batch_size": 1,
"batch_sizes": [],
"device": "mps",
"use_cache": null,
"limit": 10,
"bootstrap_iters": 100000,
"gen_kwargs": null,
"random_seed": 0,
"numpy_seed": 1234,
"torch_seed": 1234,
"fewshot_seed": 1234
} | 928e8bb6 | 1,724,994,647.916991 | 'NoneType' object has no attribute 'splitlines' | 4.44.2 | null | [
"<|endoftext|>",
"0"
] | [
"<|endoftext|>",
"0"
] | [
"<|endoftext|>",
"0"
] | 0 | 2,048 | {} | hf | EleutherAI/pythia-14m | EleutherAI__pythia-14m | null | null | false | null | null | 47,728.003633 | 47,745.43858 | 17.434946957997454 |
{
"gsm8k": {
"alias": "gsm8k",
"exact_match,strict-match": 0,
"exact_match_stderr,strict-match": 0,
"exact_match,flexible-extract": 0,
"exact_match_stderr,flexible-extract": 0
}
} | {
"gsm8k": []
} | {
"gsm8k": {
"task": "gsm8k",
"tag": [
"math_word_problems"
],
"dataset_path": "gsm8k",
"dataset_name": "main",
"training_split": "train",
"test_split": "test",
"fewshot_split": "train",
"doc_to_text": "Question: {{question}}\nAnswer:",
"doc_to_target": "{{answer}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 5,
"metric_list": [
{
"metric": "exact_match",
"aggregation": "mean",
"higher_is_better": true,
"ignore_case": true,
"ignore_punctuation": false,
"regexes_to_ignore": [
",",
"\\$",
"(?s).*#### ",
"\\.$"
]
}
],
"output_type": "generate_until",
"generation_kwargs": {
"until": [
"Question:",
"</s>",
"<|im_end|>"
],
"do_sample": false,
"temperature": 0
},
"repeats": 1,
"filter_list": [
{
"name": "strict-match",
"filter": [
{
"function": "regex",
"regex_pattern": "#### (\\-?[0-9\\.\\,]+)",
"group_select": null
},
{
"function": "take_first",
"regex_pattern": null,
"group_select": null
}
]
},
{
"name": "flexible-extract",
"filter": [
{
"function": "regex",
"regex_pattern": "(-?[$0-9.,]{2,})|(-?[0-9]+)",
"group_select": -1
},
{
"function": "take_first",
"regex_pattern": null,
"group_select": null
}
]
}
],
"should_decontaminate": false,
"metadata": {
"version": 3
}
}
} | {
"gsm8k": 3
} | {
"gsm8k": 5
} | {
"gsm8k": {
"exact_match": true
}
} | {
"gsm8k": {
"original": 1319,
"effective": 10
}
} | {
"model": "hf",
"model_args": "pretrained=EleutherAI/pythia-14m",
"model_num_parameters": 14067712,
"model_dtype": "torch.float16",
"model_revision": "main",
"model_sha": "f33025648652797a390d8c54835273845b437161",
"batch_size": 1,
"batch_sizes": [],
"device": "mps",
"use_cache": null,
"limit": 10,
"bootstrap_iters": 100000,
"gen_kwargs": null,
"random_seed": 0,
"numpy_seed": 1234,
"torch_seed": 1234,
"fewshot_seed": 1234
} | 928e8bb6 | 1,724,994,712.620037 | 'NoneType' object has no attribute 'splitlines' | 4.44.2 | null | [
"<|endoftext|>",
"0"
] | [
"<|endoftext|>",
"0"
] | [
"<|endoftext|>",
"0"
] | 0 | 2,048 | {} | hf | EleutherAI/pythia-14m | EleutherAI__pythia-14m | null | null | false | null | null | 47,792.624844 | 47,819.535151 | 26.910307540994836 |
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