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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
input_text: string
label: float
app: string
wpm: int32
backspaces: int32
hour: int32
session_min: int32
notif_count: int32
text: string
-- schema metadata --
huggingface: '{"info": {"features": {"input_text": {"dtype": "string", "_' + 409
to
{'input_ids': List(Value('int32')), 'attention_mask': List(Value('int8')), 'labels': Value('float64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1816, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/arrow/arrow.py", line 74, in _generate_tables
yield Key(file_idx, batch_idx), self._cast_table(pa_table)
~~~~~~~~~~~~~~~~^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/arrow/arrow.py", line 54, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
input_text: string
label: float
app: string
wpm: int32
backspaces: int32
hour: int32
session_min: int32
notif_count: int32
text: string
-- schema metadata --
huggingface: '{"info": {"features": {"input_text": {"dtype": "string", "_' + 409
to
{'input_ids': List(Value('int32')), 'attention_mask': List(Value('int8')), 'labels': Value('float64')}
because column names don't match
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 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, 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.
input_ids list | attention_mask list | labels float64 |
|---|---|---|
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End of preview.
YAML Metadata Warning:The task_ids "regression" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-modeling, dialogue-generation, conversational, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, text2text-generation, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering, pose-estimation
FRIDAY Synthetic Burnout Telemetry
Synthetic Android telemetry dataset for training a lightweight burnout / urgency regression model (e.g. RoBERTa fine-tune). Each row represents a single keyboard + notification event captured on a simulated Android device.
Dataset structure
| Split | Rows |
|---|---|
| train | 500 |
| validation | 62 |
| test | 63 |
Fields
| Field | Type | Description |
|---|---|---|
input_text |
string | Serialised signal string fed directly to the tokeniser |
label |
float32 | Burnout / urgency score in [0, 1] |
app |
string | Source application (Slack, Gmail, WhatsApp, Teams, System) |
wpm |
int32 | Typing speed in words per minute |
backspaces |
int32 | Correction / backspace count in the session |
hour |
int32 | Hour-of-day the event was captured (0–23) |
session_min |
int32 | Continuous screen-on duration in minutes |
notif_count |
int32 | Pending notifications at event time |
text |
string | Raw message or notification body |
Citation
@misc{friday_burnout_2026,
title = {FRIDAY Synthetic Burnout Telemetry},
author = {Your Name},
year = {2026},
note = {Synthetic dataset for mobile stress detection research}
}
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