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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ArrowNotImplementedError
Message:      Cannot write struct type 'group_subtasks' with no child field to Parquet. Consider adding a dummy child field.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1821, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 781, in finalize
                  self.write_rows_on_file()
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 663, in write_rows_on_file
                  self._write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 771, in _write_table
                  self._build_writer(inferred_schema=pa_table.schema)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 812, in _build_writer
                  self.pa_writer = pq.ParquetWriter(
                                   ^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pyarrow/parquet/core.py", line 1070, in __init__
                  self.writer = _parquet.ParquetWriter(
                                ^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/_parquet.pyx", line 2363, in pyarrow._parquet.ParquetWriter.__cinit__
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'group_subtasks' 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 1347, 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 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1832, 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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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
lm_eval_version
string
upper_git_hash
null
tokenizer_pad_token
list
tokenizer_eos_token
list
tokenizer_bos_token
list
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
null
chat_template
null
chat_template_sha
null
total_evaluation_time_seconds
string
{ "hellaswag": { "name": "hellaswag", "alias": "hellaswag", "sample_len": 10042, "acc,none": 0.4879506074487154, "acc_stderr,none": 0.004988332289641878, "acc_norm,none": 0.6452897829117705, "acc_norm_stderr,none": 0.0047744764982386185 }, "piqa": { "name": "piqa", "alias": "pi...
{}
{ "arc_challenge": { "task": "arc_challenge", "dataset_path": "allenai/ai2_arc", "dataset_name": "ARC-Challenge", "training_split": "train", "validation_split": "validation", "test_split": "test", "doc_to_text": "Question: {{question}}\nAnswer:", "doc_to_target": "{{choices.label.index...
{ "arc_challenge": 1, "arc_easy": 1, "boolq": 2, "hellaswag": 1, "openbookqa": 1, "piqa": 1, "winogrande": 1 }
{ "arc_challenge": 0, "arc_easy": 0, "boolq": 0, "hellaswag": 0, "openbookqa": 0, "piqa": 0, "winogrande": 0 }
{ "arc_challenge": { "acc": true, "acc_norm": true }, "arc_easy": { "acc": true, "acc_norm": true }, "boolq": { "acc": true }, "hellaswag": { "acc": true, "acc_norm": true }, "openbookqa": { "acc": true, "acc_norm": true }, "piqa": { "acc": true, "acc_no...
{ "hellaswag": { "original": 10042, "effective": 10042 }, "piqa": { "original": 1838, "effective": 1838 }, "winogrande": { "original": 1267, "effective": 1267 }, "boolq": { "original": 3270, "effective": 3270 }, "arc_easy": { "original": 2376, "effective": 2376 ...
{ "model": "hf", "model_args": { "pretrained": "Diamegs/PIT-4B-FT-202212", "dtype": "float16", "trust_remote_code": true }, "model_num_parameters": 4438622208, "model_dtype": "torch.float16", "model_revision": "main", "model_sha": "54f12c5f9db421aae3c2359d28b1a6a052d83fb9", "batch_size": "au...
49b8206
1,778,832,442.792797
PyTorch version: 2.11.0+cu130 Is debug build: False CUDA used to build PyTorch: 13.0 ROCM used to build PyTorch: N/A OS: Ubuntu 22.04.3 LTS (x86_64) GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 Clang version: Could not collect CMake version: version 3.28.1 Libc version: glibc-2.35 Python version: 3.12.12 (main,...
5.7.0
0.4.12
null
[ "<|endoftext|>", "50256" ]
[ "<|endoftext|>", "50256" ]
[ "<|endoftext|>", "50256" ]
50,256
1,024
{}
hf
Diamegs/PIT-4B-FT-202212
Diamegs__PIT-4B-FT-202212
null
null
null
null
null
292.84565822035074

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