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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type
struct<start_epoch: double, verify_torch_installation: struct<is_cuda_available: bool, cuda_device: string>, trainable_parameters_summary: struct<trainable_params: int64, all_params: int64, trainable_params_pct: double>, trainer_log: list<item: struct<loss: double, learning_rate: double, epoch: double, step: int64, train_runtime: double, train_samples_per_second: double, train_steps_per_second: double, total_flos: double, train_loss: double>>, model_memory_footprint: int64, cuda_memory_stats: struct<active.all.allocated: int64, active.all.current: int64, active.all.freed: int64, active.all.peak: int64, active.large_pool.allocated: int64, active.large_pool.current: int64, active.large_pool.freed: int64, active.large_pool.peak: int64, active.small_pool.allocated: int64, active.small_pool.current: int64, active.small_pool.freed: int64, active.small_pool.peak: int64, active_bytes.all.allocated: int64, active_bytes.all.current: int64, active_bytes.all.freed: int64, active_bytes.all.peak: int64, active_bytes.large_pool.allocated: int64, active_bytes.large_pool.current: int64, active_bytes.large_pool.freed: int64, active_bytes.large_pool.peak: int64, active_bytes.small_pool.allocated: int64, active_bytes.small_pool.current: int64, active_bytes.small_pool.freed: int64, active_bytes.small_pool.peak: int64, allocated_bytes.all.allocated: int64, allocated_bytes.all.current: int64, allocated_bytes.all.freed: int64, allocated_bytes.all.peak: int64, allocated_bytes.large_pool.allocated: in
...
segments.allocated: int64, oversize_segments.current: int64, oversize_segments.freed: int64, oversize_segments.peak: int64, requested_bytes.all.allocated: int64, requested_bytes.all.current: int64, requested_bytes.all.freed: int64, requested_bytes.all.peak: int64, requested_bytes.large_pool.allocated: int64, requested_bytes.large_pool.current: int64, requested_bytes.large_pool.freed: int64, requested_bytes.large_pool.peak: int64, requested_bytes.small_pool.allocated: int64, requested_bytes.small_pool.current: int64, requested_bytes.small_pool.freed: int64, requested_bytes.small_pool.peak: int64, reserved_bytes.all.allocated: int64, reserved_bytes.all.current: int64, reserved_bytes.all.freed: int64, reserved_bytes.all.peak: int64, reserved_bytes.large_pool.allocated: int64, reserved_bytes.large_pool.current: int64, reserved_bytes.large_pool.freed: int64, reserved_bytes.large_pool.peak: int64, reserved_bytes.small_pool.allocated: int64, reserved_bytes.small_pool.current: int64, reserved_bytes.small_pool.freed: int64, reserved_bytes.small_pool.peak: int64, segment.all.allocated: int64, segment.all.current: int64, segment.all.freed: int64, segment.all.peak: int64, segment.large_pool.allocated: int64, segment.large_pool.current: int64, segment.large_pool.freed: int64, segment.large_pool.peak: int64, segment.small_pool.allocated: int64, segment.small_pool.current: int64, segment.small_pool.freed: int64, segment.small_pool.peak: int64>, train_batch_size: int64, elasped_time: double>
to
{'start_epoch': Value(dtype='float64', id=None), 'trainable_parameters_summary': {'trainable_params': Value(dtype='int64', id=None), 'all_params': Value(dtype='int64', id=None), 'trainable_params_pct': Value(dtype='float64', id=None)}, 'trainer_log': [{'loss': Value(dtype='float64', id=None), 'learning_rate': Value(dtype='float64', id=None), 'epoch': Value(dtype='float64', id=None), 'step': Value(dtype='int64', id=None), 'train_runtime': Value(dtype='float64', id=None), 'train_samples_per_second': Value(dtype='float64', id=None), 'train_steps_per_second': Value(dtype='float64', id=None), 'total_flos': Value(dtype='float64', id=None), 'train_loss': Value(dtype='float64', id=None)}], 'model_memory_footprint': Value(dtype='int64', id=None), 'cuda_memory_stats': {'active.all.allocated': Value(dtype='int64', id=None), 'active.all.current': Value(dtype='int64', id=None), 'active.all.freed': Value(dtype='int64', id=None), 'active.all.peak': Value(dtype='int64', id=None), 'active.large_pool.allocated': Value(dtype='int64', id=None), 'active.large_pool.current': Value(dtype='int64', id=None), 'active.large_pool.freed': Value(dtype='int64', id=None), 'active.large_pool.peak': Value(dtype='int64', id=None), 'active.small_pool.allocated': Value(dtype='int64', id=None), 'active.small_pool.current': Value(dtype='int64', id=None), 'active.small_pool.freed': Value(dtype='int64', id=None), 'active.small_pool.peak': Value(dtype='int64', id=None), 'active_bytes.all.allocated': Value(dtype='int6
...
ocated': Value(dtype='int64', id=None), 'reserved_bytes.all.current': Value(dtype='int64', id=None), 'reserved_bytes.all.freed': Value(dtype='int64', id=None), 'reserved_bytes.all.peak': Value(dtype='int64', id=None), 'reserved_bytes.large_pool.allocated': Value(dtype='int64', id=None), 'reserved_bytes.large_pool.current': Value(dtype='int64', id=None), 'reserved_bytes.large_pool.freed': Value(dtype='int64', id=None), 'reserved_bytes.large_pool.peak': Value(dtype='int64', id=None), 'reserved_bytes.small_pool.allocated': Value(dtype='int64', id=None), 'reserved_bytes.small_pool.current': Value(dtype='int64', id=None), 'reserved_bytes.small_pool.freed': Value(dtype='int64', id=None), 'reserved_bytes.small_pool.peak': Value(dtype='int64', id=None), 'segment.all.allocated': Value(dtype='int64', id=None), 'segment.all.current': Value(dtype='int64', id=None), 'segment.all.freed': Value(dtype='int64', id=None), 'segment.all.peak': Value(dtype='int64', id=None), 'segment.large_pool.allocated': Value(dtype='int64', id=None), 'segment.large_pool.current': Value(dtype='int64', id=None), 'segment.large_pool.freed': Value(dtype='int64', id=None), 'segment.large_pool.peak': Value(dtype='int64', id=None), 'segment.small_pool.allocated': Value(dtype='int64', id=None), 'segment.small_pool.current': Value(dtype='int64', id=None), 'segment.small_pool.freed': Value(dtype='int64', id=None), 'segment.small_pool.peak': Value(dtype='int64', id=None)}, 'elasped_time': Value(dtype='float64', id=None)}
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 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<start_epoch: double, verify_torch_installation: struct<is_cuda_available: bool, cuda_device: string>, trainable_parameters_summary: struct<trainable_params: int64, all_params: int64, trainable_params_pct: double>, trainer_log: list<item: struct<loss: double, learning_rate: double, epoch: double, step: int64, train_runtime: double, train_samples_per_second: double, train_steps_per_second: double, total_flos: double, train_loss: double>>, model_memory_footprint: int64, cuda_memory_stats: struct<active.all.allocated: int64, active.all.current: int64, active.all.freed: int64, active.all.peak: int64, active.large_pool.allocated: int64, active.large_pool.current: int64, active.large_pool.freed: int64, active.large_pool.peak: int64, active.small_pool.allocated: int64, active.small_pool.current: int64, active.small_pool.freed: int64, active.small_pool.peak: int64, active_bytes.all.allocated: int64, active_bytes.all.current: int64, active_bytes.all.freed: int64, active_bytes.all.peak: int64, active_bytes.large_pool.allocated: int64, active_bytes.large_pool.current: int64, active_bytes.large_pool.freed: int64, active_bytes.large_pool.peak: int64, active_bytes.small_pool.allocated: int64, active_bytes.small_pool.current: int64, active_bytes.small_pool.freed: int64, active_bytes.small_pool.peak: int64, allocated_bytes.all.allocated: int64, allocated_bytes.all.current: int64, allocated_bytes.all.freed: int64, allocated_bytes.all.peak: int64, allocated_bytes.large_pool.allocated: in
...
segments.allocated: int64, oversize_segments.current: int64, oversize_segments.freed: int64, oversize_segments.peak: int64, requested_bytes.all.allocated: int64, requested_bytes.all.current: int64, requested_bytes.all.freed: int64, requested_bytes.all.peak: int64, requested_bytes.large_pool.allocated: int64, requested_bytes.large_pool.current: int64, requested_bytes.large_pool.freed: int64, requested_bytes.large_pool.peak: int64, requested_bytes.small_pool.allocated: int64, requested_bytes.small_pool.current: int64, requested_bytes.small_pool.freed: int64, requested_bytes.small_pool.peak: int64, reserved_bytes.all.allocated: int64, reserved_bytes.all.current: int64, reserved_bytes.all.freed: int64, reserved_bytes.all.peak: int64, reserved_bytes.large_pool.allocated: int64, reserved_bytes.large_pool.current: int64, reserved_bytes.large_pool.freed: int64, reserved_bytes.large_pool.peak: int64, reserved_bytes.small_pool.allocated: int64, reserved_bytes.small_pool.current: int64, reserved_bytes.small_pool.freed: int64, reserved_bytes.small_pool.peak: int64, segment.all.allocated: int64, segment.all.current: int64, segment.all.freed: int64, segment.all.peak: int64, segment.large_pool.allocated: int64, segment.large_pool.current: int64, segment.large_pool.freed: int64, segment.large_pool.peak: int64, segment.small_pool.allocated: int64, segment.small_pool.current: int64, segment.small_pool.freed: int64, segment.small_pool.peak: int64>, train_batch_size: int64, elasped_time: double>
to
{'start_epoch': Value(dtype='float64', id=None), 'trainable_parameters_summary': {'trainable_params': Value(dtype='int64', id=None), 'all_params': Value(dtype='int64', id=None), 'trainable_params_pct': Value(dtype='float64', id=None)}, 'trainer_log': [{'loss': Value(dtype='float64', id=None), 'learning_rate': Value(dtype='float64', id=None), 'epoch': Value(dtype='float64', id=None), 'step': Value(dtype='int64', id=None), 'train_runtime': Value(dtype='float64', id=None), 'train_samples_per_second': Value(dtype='float64', id=None), 'train_steps_per_second': Value(dtype='float64', id=None), 'total_flos': Value(dtype='float64', id=None), 'train_loss': Value(dtype='float64', id=None)}], 'model_memory_footprint': Value(dtype='int64', id=None), 'cuda_memory_stats': {'active.all.allocated': Value(dtype='int64', id=None), 'active.all.current': Value(dtype='int64', id=None), 'active.all.freed': Value(dtype='int64', id=None), 'active.all.peak': Value(dtype='int64', id=None), 'active.large_pool.allocated': Value(dtype='int64', id=None), 'active.large_pool.current': Value(dtype='int64', id=None), 'active.large_pool.freed': Value(dtype='int64', id=None), 'active.large_pool.peak': Value(dtype='int64', id=None), 'active.small_pool.allocated': Value(dtype='int64', id=None), 'active.small_pool.current': Value(dtype='int64', id=None), 'active.small_pool.freed': Value(dtype='int64', id=None), 'active.small_pool.peak': Value(dtype='int64', id=None), 'active_bytes.all.allocated': Value(dtype='int6
...
ocated': Value(dtype='int64', id=None), 'reserved_bytes.all.current': Value(dtype='int64', id=None), 'reserved_bytes.all.freed': Value(dtype='int64', id=None), 'reserved_bytes.all.peak': Value(dtype='int64', id=None), 'reserved_bytes.large_pool.allocated': Value(dtype='int64', id=None), 'reserved_bytes.large_pool.current': Value(dtype='int64', id=None), 'reserved_bytes.large_pool.freed': Value(dtype='int64', id=None), 'reserved_bytes.large_pool.peak': Value(dtype='int64', id=None), 'reserved_bytes.small_pool.allocated': Value(dtype='int64', id=None), 'reserved_bytes.small_pool.current': Value(dtype='int64', id=None), 'reserved_bytes.small_pool.freed': Value(dtype='int64', id=None), 'reserved_bytes.small_pool.peak': Value(dtype='int64', id=None), 'segment.all.allocated': Value(dtype='int64', id=None), 'segment.all.current': Value(dtype='int64', id=None), 'segment.all.freed': Value(dtype='int64', id=None), 'segment.all.peak': Value(dtype='int64', id=None), 'segment.large_pool.allocated': Value(dtype='int64', id=None), 'segment.large_pool.current': Value(dtype='int64', id=None), 'segment.large_pool.freed': Value(dtype='int64', id=None), 'segment.large_pool.peak': Value(dtype='int64', id=None), 'segment.small_pool.allocated': Value(dtype='int64', id=None), 'segment.small_pool.current': Value(dtype='int64', id=None), 'segment.small_pool.freed': Value(dtype='int64', id=None), 'segment.small_pool.peak': Value(dtype='int64', id=None)}, 'elasped_time': Value(dtype='float64', 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 1529, 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 1154, 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? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
streamlit_config
dict | elt
dict | train
dict | eval
dict |
|---|---|---|---|
{
"n_epochs": 5,
"optim_name": "Lion",
"limit_samples": false,
"model_size": "Small",
"FormSubmitter:Configuration-Submit Run": true
} | {
"start_epoch": 1685390675.1638606,
"train_dataset_size": 14732,
"test_dataset_size": 819,
"max_source_length": 255,
"max_target_length": 50,
"elasped_time": 10.796925067901611
} | {
"start_epoch": 1685390685.9612148,
"trainable_parameters_summary": {
"trainable_params": 688128,
"all_params": 77649280,
"trainable_params_pct": 0.008862001038515747
},
"trainer_log": [
{
"loss": 1.917,
"learning_rate": 0.0001,
"epoch": 1,
"step": 1842,
"train_runtime": null,
"train_samples_per_second": null,
"train_steps_per_second": null,
"total_flos": null,
"train_loss": null
},
{
"loss": 1.8827,
"learning_rate": 0.0001,
"epoch": 2,
"step": 3684,
"train_runtime": null,
"train_samples_per_second": null,
"train_steps_per_second": null,
"total_flos": null,
"train_loss": null
},
{
"loss": 1.8599,
"learning_rate": 0.0001,
"epoch": 3,
"step": 5526,
"train_runtime": null,
"train_samples_per_second": null,
"train_steps_per_second": null,
"total_flos": null,
"train_loss": null
},
{
"loss": 1.84,
"learning_rate": 0.0001,
"epoch": 4,
"step": 7368,
"train_runtime": null,
"train_samples_per_second": null,
"train_steps_per_second": null,
"total_flos": null,
"train_loss": null
},
{
"loss": 1.8223,
"learning_rate": 0.0001,
"epoch": 5,
"step": 9210,
"train_runtime": null,
"train_samples_per_second": null,
"train_steps_per_second": null,
"total_flos": null,
"train_loss": null
},
{
"loss": null,
"learning_rate": null,
"epoch": 5,
"step": 9210,
"train_runtime": 2908.9079,
"train_samples_per_second": 25.322,
"train_steps_per_second": 3.166,
"total_flos": 6924203301273600,
"train_loss": 1.8643896113260043
}
],
"model_memory_footprint": 137843456,
"cuda_memory_stats": {
"active.all.allocated": 86935196,
"active.all.current": 923,
"active.all.freed": 86934273,
"active.all.peak": 1086,
"active.large_pool.allocated": 22674222,
"active.large_pool.current": 20,
"active.large_pool.freed": 22674202,
"active.large_pool.peak": 55,
"active.small_pool.allocated": 64260974,
"active.small_pool.current": 903,
"active.small_pool.freed": 64260071,
"active.small_pool.peak": 1045,
"active_bytes.all.allocated": 119341336440832,
"active_bytes.all.current": 195914752,
"active_bytes.all.freed": 119341140526080,
"active_bytes.all.peak": 437989376,
"active_bytes.large_pool.allocated": 99178618281984,
"active_bytes.large_pool.current": 117702656,
"active_bytes.large_pool.freed": 99178500579328,
"active_bytes.large_pool.peak": 345997312,
"active_bytes.small_pool.allocated": 20162718158848,
"active_bytes.small_pool.current": 78212096,
"active_bytes.small_pool.freed": 20162639946752,
"active_bytes.small_pool.peak": 116166144,
"allocated_bytes.all.allocated": 119341336440832,
"allocated_bytes.all.current": 195914752,
"allocated_bytes.all.freed": 119341140526080,
"allocated_bytes.all.peak": 437989376,
"allocated_bytes.large_pool.allocated": 99178618281984,
"allocated_bytes.large_pool.current": 117702656,
"allocated_bytes.large_pool.freed": 99178500579328,
"allocated_bytes.large_pool.peak": 345997312,
"allocated_bytes.small_pool.allocated": 20162718158848,
"allocated_bytes.small_pool.current": 78212096,
"allocated_bytes.small_pool.freed": 20162639946752,
"allocated_bytes.small_pool.peak": 116166144,
"allocation.all.allocated": 86935196,
"allocation.all.current": 923,
"allocation.all.freed": 86934273,
"allocation.all.peak": 1086,
"allocation.large_pool.allocated": 22674222,
"allocation.large_pool.current": 20,
"allocation.large_pool.freed": 22674202,
"allocation.large_pool.peak": 55,
"allocation.small_pool.allocated": 64260974,
"allocation.small_pool.current": 903,
"allocation.small_pool.freed": 64260071,
"allocation.small_pool.peak": 1045,
"inactive_split.all.allocated": 54760871,
"inactive_split.all.current": 160,
"inactive_split.all.freed": 54760711,
"inactive_split.all.peak": 231,
"inactive_split.large_pool.allocated": 16353277,
"inactive_split.large_pool.current": 2,
"inactive_split.large_pool.freed": 16353275,
"inactive_split.large_pool.peak": 12,
"inactive_split.small_pool.allocated": 38407594,
"inactive_split.small_pool.current": 158,
"inactive_split.small_pool.freed": 38407436,
"inactive_split.small_pool.peak": 225,
"inactive_split_bytes.all.allocated": 130298193663488,
"inactive_split_bytes.all.current": 62034944,
"inactive_split_bytes.all.freed": 130298131628544,
"inactive_split_bytes.all.peak": 209548288,
"inactive_split_bytes.large_pool.allocated": 110037039898624,
"inactive_split_bytes.large_pool.current": 16515072,
"inactive_split_bytes.large_pool.freed": 110037023383552,
"inactive_split_bytes.large_pool.peak": 182190080,
"inactive_split_bytes.small_pool.allocated": 20261153764864,
"inactive_split_bytes.small_pool.current": 45519872,
"inactive_split_bytes.small_pool.freed": 20261108244992,
"inactive_split_bytes.small_pool.peak": 63202304,
"max_split_size": -1,
"num_alloc_retries": 0,
"num_ooms": 0,
"oversize_allocations.allocated": 0,
"oversize_allocations.current": 0,
"oversize_allocations.freed": 0,
"oversize_allocations.peak": 0,
"oversize_segments.allocated": 0,
"oversize_segments.current": 0,
"oversize_segments.freed": 0,
"oversize_segments.peak": 0,
"requested_bytes.all.allocated": 116265027895056,
"requested_bytes.all.current": 194543924,
"requested_bytes.all.freed": 116264833351132,
"requested_bytes.all.peak": 436224892,
"requested_bytes.large_pool.allocated": 96108341755904,
"requested_bytes.large_pool.current": 116391936,
"requested_bytes.large_pool.freed": 96108225363968,
"requested_bytes.large_pool.peak": 344293376,
"requested_bytes.small_pool.allocated": 20156686139152,
"requested_bytes.small_pool.current": 78151988,
"requested_bytes.small_pool.freed": 20156607987164,
"requested_bytes.small_pool.peak": 116106628,
"reserved_bytes.all.allocated": 568328192,
"reserved_bytes.all.current": 568328192,
"reserved_bytes.all.freed": 0,
"reserved_bytes.all.peak": 568328192,
"reserved_bytes.large_pool.allocated": 419430400,
"reserved_bytes.large_pool.current": 419430400,
"reserved_bytes.large_pool.freed": 0,
"reserved_bytes.large_pool.peak": 419430400,
"reserved_bytes.small_pool.allocated": 148897792,
"reserved_bytes.small_pool.current": 148897792,
"reserved_bytes.small_pool.freed": 0,
"reserved_bytes.small_pool.peak": 148897792,
"segment.all.allocated": 85,
"segment.all.current": 85,
"segment.all.freed": 0,
"segment.all.peak": 85,
"segment.large_pool.allocated": 14,
"segment.large_pool.current": 14,
"segment.large_pool.freed": 0,
"segment.large_pool.peak": 14,
"segment.small_pool.allocated": 71,
"segment.small_pool.current": 71,
"segment.small_pool.freed": 0,
"segment.small_pool.peak": 71
},
"elasped_time": 2914.8779151439667
} | {
"start_epoch": 1685393600.8396957,
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