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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 1 new columns ({'Epoch'}) and 2 missing columns ({'magnification', 'data size'}).
This happened while the csv dataset builder was generating data using
hf://datasets/zwang2/breakhis_lora_results/res_everything/train_loss_epoch_100_10%.csv (at revision bbdcc1f6f24c67baf0ca16d08c224f09d8464878)
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
Epoch: int64
Ours: double
ResNet-50: double
ResNeXt-50: double
densenet121: double
AlexNet: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 955
to
{'data size': Value(dtype='int64', id=None), 'Ours': Value(dtype='float64', id=None), 'ResNet-50': Value(dtype='float64', id=None), 'ResNeXt-50': Value(dtype='float64', id=None), 'densenet121': Value(dtype='float64', id=None), 'AlexNet': Value(dtype='float64', id=None), 'magnification': 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 1323, 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 938, 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 1 new columns ({'Epoch'}) and 2 missing columns ({'magnification', 'data size'}).
This happened while the csv dataset builder was generating data using
hf://datasets/zwang2/breakhis_lora_results/res_everything/train_loss_epoch_100_10%.csv (at revision bbdcc1f6f24c67baf0ca16d08c224f09d8464878)
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? Open a discussion for direct support.
data size
int64 | Ours
float64 | ResNet-50
float64 | ResNeXt-50
float64 | densenet121
float64 | AlexNet
float64 | magnification
string |
|---|---|---|---|---|---|---|
5 | 1 | 1 | 1 | 1 | 0.821705 | high |
5 | 1 | 1 | 1 | 1 | 1 | low |
5 | 1 | 1 | 1 | 1 | 0.992481 | all |
5 | 1 | 1 | 1 | 1 | 0.895522 | 40 |
5 | 1 | 1 | 1 | 1 | 1 | 100 |
5 | 1 | 1 | 1 | 1 | 1 | 200 |
5 | 1 | 1 | 1 | 1 | 0.967213 | 400 |
6 | 1 | 1 | 1 | 1 | 1 | high |
6 | 1 | 1 | 1 | 1 | 0.963636 | low |
6 | 1 | 1 | 1 | 1 | 0.99375 | all |
6 | 1 | 1 | 1 | 1 | 0.987654 | 40 |
6 | 1 | 1 | 1 | 1 | 1 | 100 |
6 | 1 | 1 | 1 | 1 | 1 | 200 |
6 | 1 | 1 | 1 | 1 | 0.72973 | 400 |
7 | 1 | 1 | 1 | 1 | 0.994475 | high |
7 | 1 | 1 | 1 | 1 | 1 | low |
7 | 1 | 1 | 1 | 1 | 0.975871 | all |
7 | 1 | 1 | 1 | 1 | 1 | 40 |
7 | 1 | 1 | 1 | 1 | 0.979592 | 100 |
7 | 1 | 1 | 1 | 1 | 1 | 200 |
7 | 1 | 1 | 1 | 1 | 1 | 400 |
8 | 1 | 1 | 1 | 1 | 0.941748 | high |
8 | 1 | 1 | 1 | 1 | 1 | low |
8 | 1 | 1 | 1 | 1 | 0.997647 | all |
8 | 1 | 1 | 1 | 1 | 0.953271 | 40 |
8 | 1 | 1 | 1 | 1 | 1 | 100 |
8 | 1 | 1 | 1 | 1 | 1 | 200 |
8 | 1 | 1 | 1 | 1 | 0.928571 | 400 |
9 | 1 | 1 | 1 | 1 | 0.99569 | high |
9 | 1 | 1 | 1 | 1 | 1 | low |
9 | 1 | 1 | 1 | 1 | 0.993737 | all |
9 | 1 | 1 | 1 | 1 | 0.677686 | 40 |
9 | 1 | 1 | 1 | 1 | 1 | 100 |
9 | 1 | 1 | 1 | 1 | 1 | 200 |
9 | 1 | 1 | 1 | 1 | 1 | 400 |
10 | 1 | 1 | 1 | 1 | 0.929961 | high |
10 | 1 | 1 | 1 | 1 | 1 | low |
10 | 1 | 1 | 1 | 1 | 0.992467 | all |
10 | 1 | 1 | 1 | 1 | 0.932836 | 40 |
10 | 1 | 1 | 1 | 1 | 1 | 100 |
10 | 1 | 1 | 1 | 1 | 1 | 200 |
10 | 1 | 1 | 1 | 1 | 1 | 400 |
11 | 1 | 1 | 1 | 1 | 0.957746 | high |
11 | 1 | 1 | 1 | 1 | 1 | low |
11 | 1 | 1 | 1 | 1 | 0.940273 | all |
11 | 1 | 1 | 1 | 1 | 0.993243 | 40 |
11 | 1 | 1 | 1 | 1 | 0.987013 | 100 |
11 | 1 | 1 | 1 | 1 | 1 | 200 |
11 | 1 | 1 | 1 | 1 | 1 | 400 |
12 | 1 | 1 | 1 | 1 | 1 | high |
12 | 1 | 1 | 1 | 1 | 0.984802 | low |
12 | 1 | 1 | 1 | 1 | 0.990596 | all |
12 | 1 | 1 | 1 | 1 | 0.900621 | 40 |
12 | 1 | 1 | 1 | 1 | 1 | 100 |
12 | 1 | 1 | 1 | 1 | 0.981481 | 200 |
12 | 1 | 1 | 1 | 1 | 0.952381 | 400 |
13 | 1 | 1 | 1 | 1 | 0.946269 | high |
13 | 1 | 1 | 1 | 1 | 0.985955 | low |
13 | 1 | 1 | 1 | 1 | 0.997106 | all |
13 | 1 | 1 | 1 | 1 | 0.971264 | 40 |
13 | 1 | 1 | 1 | 1 | 1 | 100 |
13 | 1 | 1 | 1 | 1 | 1 | 200 |
13 | 1 | 1 | 1 | 1 | 1 | 400 |
14 | 1 | 1 | 1 | 1 | 0.955556 | high |
14 | 1 | 1 | 1 | 1 | 0.997396 | low |
14 | 1 | 0.998656 | 1 | 1 | 0.997312 | all |
14 | 1 | 1 | 1 | 1 | 0.994681 | 40 |
14 | 1 | 1 | 1 | 1 | 0.979592 | 100 |
14 | 1 | 1 | 1 | 1 | 1 | 200 |
14 | 1 | 1 | 1 | 1 | 1 | 400 |
15 | 1 | 1 | 1 | 0.997409 | 0.96114 | high |
15 | 1 | 1 | 1 | 1 | 0.990268 | low |
15 | 1 | 1 | 1 | 1 | 0.993726 | all |
15 | 1 | 1 | 1 | 1 | 0.99005 | 40 |
15 | 1 | 1 | 1 | 1 | 1 | 100 |
15 | 1 | 1 | 1 | 1 | 1 | 200 |
15 | 1 | 1 | 1 | 1 | 0.967213 | 400 |
40 | 1 | 0.998696 | 0.998696 | 0.999027 | 0.987354 | high |
40 | 1 | 0.998774 | 0.999085 | 1 | 0.994511 | low |
40 | 1 | 0.998586 | 0.999057 | 0.999529 | 0.983027 | all |
40 | 1 | 1 | 1 | 1 | 0.998131 | 40 |
40 | 1 | 1 | 1 | 1 | 0.998208 | 100 |
40 | 1 | 1 | 1 | 1 | 0.994444 | 200 |
40 | 1 | 1 | 1 | 1 | 1 | 400 |
70 | 1 | 0.999444 | 1 | 1 | 0.991106 | high |
70 | 1 | 1 | 1 | 0.999477 | 0.997386 | low |
70 | 1 | 0.999192 | 0.999731 | 0.998922 | 0.978179 | all |
70 | 1 | 1 | 1 | 1 | 0.996795 | 40 |
70 | 1 | 1 | 1 | 1 | 0.994882 | 100 |
70 | 1 | 1 | 1 | 1 | 1 | 200 |
70 | 1 | 1 | 1 | 1 | 0.985948 | 400 |
100 | 1 | 0.999611 | 0.999611 | 0.999221 | 0.985208 | high |
100 | 1 | 0.999268 | 1 | 0.999268 | 0.995974 | low |
100 | 1 | 0.999057 | 0.999057 | 0.997548 | 0.934352 | all |
100 | 1 | 0.999252 | 1 | 1 | 0.997756 | 40 |
100 | 1 | 1 | 1 | 1 | 0.994982 | 100 |
100 | 1 | 0.999259 | 1 | 1 | 0.996294 | 200 |
100 | 1 | 0.99918 | 0.99918 | 0.99918 | 0.997541 | 400 |
null | 0.728711 | 4.482546 | 4.662845 | 6.603554 | 10.351462 | null |
null | 0.614477 | 2.32143 | 2.162864 | 2.322345 | 4.892124 | null |
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