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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 2025, in cast_array_to_feature
casted_array_values = _c(array.values, feature[0])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1804, in wrapper
return func(array, *args, **kwargs)
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<history: list<item: string>, responses: list<item: string>, label: int64>
to
{'your_persona': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'history': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'responses': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'label': Value(dtype='int64', 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 datasetNeed help to make the dataset viewer work? Open a discussion for direct support.
train
list | valid
list | test
list |
|---|---|---|
[{"your_persona":["i like to remodel homes.","i like to go hunting.","i like to shoot a bow.","my fa(...TRUNCATED) | [{"your_persona":["i read twenty books a year.","i am a stunt double as my second job.","i only eat (...TRUNCATED) | [{"your_persona":["i love to meet new people.","i have a turtle named timothy.","my favorite sport i(...TRUNCATED) |
[{"history":["hey .. i installed a pata card in my comp with __number__ hd s on it dmesg says the ca(...TRUNCATED) | [{"history":["one of the disks mounts by it self the other i mount by typing sudo mount __path__ in (...TRUNCATED) | [{"history":["cool also i feel like i m helping the project by using it more traffic to the site etc(...TRUNCATED) |
[{"history":["i think we could import the old comments via rsync, but from there we need to go via e(...TRUNCATED) | [{"history":["Any ideas on how lts will be released ?","already is"],"responses":["We are talking 12(...TRUNCATED) | [{"history":["anyone knows why my stock oneiric exports env var 'USERNAME'? I mean what is that used(...TRUNCATED) |
[{"history":["昆明 那里 配 眼镜 比较 便宜","云大 附近 很多 店 应该 有 竞争 (...TRUNCATED) | [{"history":["my hometown 的 中文 歌词 很 感动","英文 版 是 小田 亲自 翻译 的 更(...TRUNCATED) | [{"history":["被 天秤 绝交 了 还能 和好 么","哭 死 我 了 我 想 他 了 眼睛 又 (...TRUNCATED) |
YAML Metadata
Warning:
The task_categories "conversational" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, other
💻 [Github Repo] • 📃 [Paper]
Overview
This a collection of datasets used in the paper titled "Uni-Encoder: A Fast and Accurate Response Selection Paradigm for Generation-Based Dialogue Systems".
The following datasets have been included:
- Ubuntu Corpus V1
- Ubuntu Corpus V2
- PersonaChat
- Douban Conv Corpus
All datasets have been standardized to a unified format for research need.
Citation
@inproceedings{song2023uni,
title={Uni-encoder: A fast and accurate response selection paradigm for generation-based dialogue systems},
author={Song, Chiyu and He, Hongliang and Yu, Haofei and Fang, Pengfei and Cui, Leyang and Lan, Zhenzhong},
booktitle={Findings of the Association for Computational Linguistics: ACL 2023},
pages={6231--6244},
year={2023}
}
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