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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 11 new columns ({'lang_score', 'char_rep_ratio', 'perplexity', 'lang', 'flagged_words_ratio', 'special_char_ratio', 'avg_line_length', 'alnum_ratio', 'word_rep_ratio', 'num_words', 'max_line_length'})
This happened while the json dataset builder was generating data using
/tmp/hf-datasets-cache/medium/datasets/71920310133875-config-parquet-and-info-BAAI-IndustryCorpus_progr-5c36d49b/downloads/716e12e7c067ada597f46b27dd01cf6effce61aefd300f8624ca7145f283d930
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
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 2256, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
text: string
alnum_ratio: double
avg_line_length: double
char_rep_ratio: double
flagged_words_ratio: double
industry_type: string
lang: string
lang_score: double
max_line_length: int64
num_words: int64
perplexity: double
special_char_ratio: double
word_rep_ratio: double
id: int64
to
{'id': Value(dtype='string', id=None), 'text': Value(dtype='string', id=None), 'industry_type': Value(dtype='string', id=None)}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1577, 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 1191, 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 2013, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 11 new columns ({'lang_score', 'char_rep_ratio', 'perplexity', 'lang', 'flagged_words_ratio', 'special_char_ratio', 'avg_line_length', 'alnum_ratio', 'word_rep_ratio', 'num_words', 'max_line_length'})
This happened while the json dataset builder was generating data using
/tmp/hf-datasets-cache/medium/datasets/71920310133875-config-parquet-and-info-BAAI-IndustryCorpus_progr-5c36d49b/downloads/716e12e7c067ada597f46b27dd01cf6effce61aefd300f8624ca7145f283d930
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
id string | text string | industry_type string |
|---|---|---|
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End of preview.
Industry models play a crucial role in driving enterprise intelligence transformation and innovative development. High-quality industry data is key to improving the performance of large models and realizing industry applications. However, datasets currently used for industry model training generally suffer from issues such as insufficient data volume, low quality, and lack of domain expertise.
To address these problems, we constructed and applied 22 industry data processing operators to clean and filter 3.4TB of high-quality multi-industry classified Chinese and English language pre-training datasets from over 100TB of open-source datasets including WuDaoCorpora, BAAI-CCI, redpajama, and SkyPile-150B. The filtered data consists of 1TB of Chinese data and 2.4TB of English data. To facilitate user utilization, we annotated the Chinese data with 12 types of labels including alphanumeric ratio, average line length, language confidence score, maximum line length, and perplexity.
Furthermore, to validate the dataset's performance, we conducted continued pre-training, SFT, and DPO training on a medical industry demonstration model. The results showed a 20% improvement in objective performance and a subjective win rate of 82%.
Industry categories: 18 categories including medical, education, literature, finance, travel, law, sports, automotive, news, etc. Rule-based filtering: Traditional Chinese conversion, email removal, IP address removal, link removal, Unicode repair, etc. Chinese data labels: Alphanumeric ratio, average line length, language confidence score, maximum line length, perplexity, toxicity character ratio, etc. Model-based filtering: Industry classification language model with 80% accuracy Data deduplication: MinHash document-level deduplication Data size: 1TB Chinese, 2.4TB English
Industry classification data size:
| Industry Category | Data Size (GB) | Industry Category | Data Size (GB) |
|---|---|---|---|
| Programming | 4.1 | Politics | 326.4 |
| Law | 274.6 | Mathematics | 5.9 |
| Education | 458.1 | Sports | 442 |
| Finance | 197.8 | Literature | 179.3 |
| Computer Science | 46.9 | News | 564.1 |
| Technology | 333.6 | Film & TV | 162.1 |
| Travel | 82.5 | Medicine | 189.4 |
| Agriculture | 41.6 | Automotive | 40.8 |
| Emotion | 31.7 | Artificial Intelligence | 5.6 |
| Total (GB) | 3386.5 |
For the convenience of users to download and use, we have split the large dataset into sub-datasets for 18 industries. The current one is the sub-dataset for the programming industry.
Data processing workflow:
- Downloads last month
- 25
Models trained or fine-tuned on BAAI/IndustryCorpus_programming