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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
item_id: string
start: timestamp[s]
freq: string
target: list<item: float>
child 0, item: float
past_feat_dynamic_real: fixed_size_list<item: list<item: float>>[7]
child 0, item: list<item: float>
child 0, item: float
-- schema metadata --
huggingface: '{"info": {"features": {"item_id": {"dtype": "string", "_typ' + 347
to
{'item_id': Value('string'), 'start': Value('timestamp[s]'), 'freq': Value('string'), 'target': List(Value('float32'))}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1872, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 609, in wrapped
for item in generator(*args, **kwargs):
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/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/python3.12/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/python3.12/site-packages/datasets/table.py", line 2281, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2227, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
item_id: string
start: timestamp[s]
freq: string
target: list<item: float>
child 0, item: float
past_feat_dynamic_real: fixed_size_list<item: list<item: float>>[7]
child 0, item: list<item: float>
child 0, item: float
-- schema metadata --
huggingface: '{"info": {"features": {"item_id": {"dtype": "string", "_typ' + 347
to
{'item_id': Value('string'), 'start': Value('timestamp[s]'), 'freq': Value('string'), 'target': List(Value('float32'))}
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 1342, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 907, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1739, 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 1925, 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.
item_id string | start timestamp[s] | freq string | target list |
|---|---|---|---|
0 | 2015-01-01T00:00:00 | 5T | [61.93913650512695,59.23252487182617,61.99180221557617,62.480655670166016,62.490482330322266,62.5417(...TRUNCATED) |
1 | 2015-01-01T00:00:00 | 5T | [64.2808837890625,65.08245086669922,65.30912017822266,65.191650390625,65.28766632080078,68.001235961(...TRUNCATED) |
2 | 2015-01-01T00:00:00 | 5T | [62.077396392822266,64.80834197998047,64.80391693115234,67.20659637451172,67.32328796386719,66.41279(...TRUNCATED) |
3 | 2015-01-01T00:00:00 | 5T | [60.78642272949219,65.85395050048828,64.26608276367188,63.988426208496094,64.70740509033203,62.72486(...TRUNCATED) |
4 | 2015-01-01T00:00:00 | 5T | [63.12067413330078,59.20623016357422,62.239200592041016,65.80850982666016,65.70866394042969,63.67469(...TRUNCATED) |
5 | 2015-01-01T00:00:00 | 5T | [64.44831848144531,62.4967155456543,63.816612243652344,64.75755310058594,65.35836791992188,63.123970(...TRUNCATED) |
6 | 2015-01-01T00:00:00 | 5T | [63.41112518310547,65.99217987060547,60.19683074951172,62.01144790649414,65.09144592285156,62.115444(...TRUNCATED) |
7 | 2015-01-01T00:00:00 | 5T | [64.7394790649414,64.71804809570312,65.44779205322266,66.33447265625,63.09504699707031,68.0616760253(...TRUNCATED) |
8 | 2015-01-01T00:00:00 | 5T | [63.009918212890625,61.24407196044922,63.79776382446289,61.702735900878906,62.18679428100586,61.0574(...TRUNCATED) |
9 | 2015-01-01T00:00:00 | 5T | [65.26490020751953,65.60872650146484,66.01715850830078,65.73542785644531,65.09737396240234,65.096916(...TRUNCATED) |
End of preview.
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contrastive-training-tiny-bundles
Training bundles for the Tiny tier of the contrastive forecasting model family.
Layout
tiny_mixed_v2/shard_NNNNN.parquet— 1088 parquet shards, 10,757,768 rows totaltiny_mixed_v2/manifest.json— row counts per sourcetiny_mixed_v2/README.md— per-bundle notes on shuffling, sampling bias, and NaN handlingeval/<dataset>/— GIFT-Eval reference sets (shared across bundles)
Mix (source_id → observed share of rows in tiny_mixed_v2)
- 0 gift: 45.2%
- 1 wiki_hourly: 15.4%
- 2 wiki_daily: 2.2%
- 3 wiki_stl_residual: 2.2%
- 4 wiki_stl_seasonal: 1.5%
- 5 wiki_stl_trend: 0.7%
- 6 synthetic: 32.9%
Target was 50 / 14 / 2 / 2 / 1.4 / 0.6 / 30; gift undershot slightly because the stage 1 gift sampler was interrupted at ~82% of its byte budget and the pipeline was resumed from the partial stage 1 output.
History
- tiny_mixed_v2 (2026-04-15) — current bundle. Globally shuffled
via the two-pass bucket shuffle in
rnd/scripts/training_data_prep(PR #194). Seetiny_mixed_v2/README.mdfor sampling-bias and NaN-rate details. - tiny_mixed_v1 (2026-04-13) — superseded and removed from HEAD
(commit
ec048cfa). Still reachable in the HF git history at any commit prior to the removal. Used a bounded-buffer local shuffle that caused the training-curve dip and the deterministic NaN incident reported in the contrastive-forecasting tiny-training run.
Generated by rnd/scripts/training_data_prep.
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