Dwaraka/Sentence_Classification_CoLA_BERT_base_uncased_Encoder_Only_Model
Text Classification
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Updated
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18
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 ({'The sailors rode the breeze clear of the rocks.'}) and 1 missing columns ({"Our friends won't buy this analysis, let alone the next one we propose."}). This happened while the csv dataset builder was generating data using hf://datasets/Dwaraka/CoLA_raw_dataset/in_domain_dev.tsv (at revision 6ee6c9de5117d542bf129b6dc8f22663c8d617a7) 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 gj04: string 1: int64 Unnamed: 2: string The sailors rode the breeze clear of the rocks.: string -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 782 to {'gj04': Value(dtype='string', id=None), '1': Value(dtype='int64', id=None), 'Unnamed: 2': Value(dtype='string', id=None), "Our friends won't buy this analysis, let alone the next one we propose.": 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 1321, 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 935, 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 ({'The sailors rode the breeze clear of the rocks.'}) and 1 missing columns ({"Our friends won't buy this analysis, let alone the next one we propose."}). This happened while the csv dataset builder was generating data using hf://datasets/Dwaraka/CoLA_raw_dataset/in_domain_dev.tsv (at revision 6ee6c9de5117d542bf129b6dc8f22663c8d617a7) 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)
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gj04
string | 1
int64 | Unnamed: 2
null | Our friends won't buy this analysis, let alone the next one we propose.
string |
---|---|---|---|
gj04 | 1 | null | One more pseudo generalization and I'm giving up. |
gj04 | 1 | null | One more pseudo generalization or I'm giving up. |
gj04 | 1 | null | The more we study verbs, the crazier they get. |
gj04 | 1 | null | Day by day the facts are getting murkier. |
gj04 | 1 | null | I'll fix you a drink. |
gj04 | 1 | null | Fred watered the plants flat. |
gj04 | 1 | null | Bill coughed his way out of the restaurant. |
gj04 | 1 | null | We're dancing the night away. |
gj04 | 1 | null | Herman hammered the metal flat. |
gj04 | 1 | null | The critics laughed the play off the stage. |
gj04 | 1 | null | The pond froze solid. |
gj04 | 1 | null | Bill rolled out of the room. |
gj04 | 1 | null | The gardener watered the flowers flat. |
gj04 | 1 | null | The gardener watered the flowers. |
gj04 | 1 | null | Bill broke the bathtub into pieces. |
gj04 | 1 | null | Bill broke the bathtub. |
gj04 | 1 | null | They drank the pub dry. |
gj04 | 0 | null | They drank the pub. |
gj04 | 1 | null | The professor talked us into a stupor. |
gj04 | 0 | null | The professor talked us. |
gj04 | 1 | null | We yelled ourselves hoarse. |
gj04 | 0 | null | We yelled ourselves. |
gj04 | 0 | null | We yelled Harry hoarse. |
gj04 | 1 | null | Harry coughed himself into a fit. |
gj04 | 0 | null | Harry coughed himself. |
gj04 | 0 | null | Harry coughed us into a fit. |
gj04 | 1 | null | Bill followed the road into the forest. |
gj04 | 1 | null | We drove Highway 5 from SD to SF. |
gj04 | 1 | null | Fred tracked the leak to its source. |
gj04 | 1 | null | John danced waltzes across the room. |
gj04 | 1 | null | Bill urinated out the window. |
gj04 | 1 | null | Bill coughed out the window. |
gj04 | 1 | null | Bill bled on the floor. |
gj04 | 1 | null | The toilet leaked through the floor into the kitchen below. |
gj04 | 1 | null | Bill ate off the floor. |
gj04 | 1 | null | Bill drank from the hose. |
gj04 | 1 | null | This metal hammers flat easily. |
gj04 | 1 | null | They made him president. |
gj04 | 1 | null | They made him angry. |
gj04 | 0 | null | They caused him to become angry by making him. |
gj04 | 0 | null | They caused him to become president by making him. |
gj04 | 0 | null | They made him to exhaustion. |
gj04 | 1 | null | They made him into a monster. |
gj04 | 1 | null | The trolley rumbled through the tunnel. |
gj04 | 1 | null | The wagon rumbled down the road. |
gj04 | 1 | null | The bullets whistled past the house. |
gj04 | 1 | null | The knee replacement candidate groaned up the stairs. |
gj04 | 0 | null | The car honked down the road. |
gj04 | 0 | null | The dog barked out of the room. |
gj04 | 1 | null | The dog barked its way out of the room. |
gj04 | 1 | null | Bill whistled his way past the house. |
gj04 | 1 | null | The witch vanished into the forest. |
gj04 | 1 | null | Bill disappeared down the road. |
gj04 | 0 | null | The witch went into the forest by vanishing. |
gj04 | 1 | null | The witch went into the forest and thereby vanished. |
gj04 | 1 | null | The building is tall and wide. |
gj04 | 0 | null | The building is tall and tall. |
gj04 | 1 | null | This building is taller and wider than that one. |
gj04 | 1 | null | This building got taller and wider than that one. |
gj04 | 1 | null | This building got taller and taller. |
gj04 | 0 | null | This building is taller and taller. |
gj04 | 0 | null | This building got than that one. |
gj04 | 0 | null | This building is than that one. |
gj04 | 1 | null | Bill floated into the cave. |
gj04 | 0 | null | Bill floated into the cave for hours. |
gj04 | 0 | null | Bill pushed Harry off the sofa for hours. |
gj04 | 1 | null | Bill floated down the river for hours. |
gj04 | 1 | null | Bill floated down the river. |
gj04 | 1 | null | Bill pushed Harry along the trail for hours. |
gj04 | 1 | null | Bill pushed Harry along the trail. |
gj04 | 1 | null | The road zigzagged down the hill. |
gj04 | 1 | null | The rope stretched over the pulley. |
gj04 | 1 | null | The weights stretched the rope over the pulley. |
gj04 | 1 | null | The weights kept the rope stretched over the pulley. |
gj04 | 1 | null | Sam cut himself free. |
gj04 | 1 | null | Sam got free by cutting his finger. |
gj04 | 1 | null | Bill cried himself to sleep. |
gj04 | 0 | null | Bill cried Sue to sleep. |
gj04 | 1 | null | Bill squeezed himself through the hole. |
gj04 | 1 | null | Bill sang himself to sleep. |
gj04 | 1 | null | Bill squeezed the puppet through the hole. |
gj04 | 1 | null | Bill sang Sue to sleep. |
gj04 | 0 | null | The elevator rumbled itself to the ground. |
gj04 | 1 | null | If the telephone rang, it could ring itself silly. |
gj04 | 0 | null | She yelled hoarse. |
gj04 | 0 | null | Ted cried to sleep. |
gj04 | 1 | null | The tiger bled to death. |
gj04 | 1 | null | He coughed awake and we were all overjoyed, especially Sierra. |
gj04 | 1 | null | John coughed awake, rubbing his nose and cursing under his breath. |
gj04 | 1 | null | John coughed himself awake on the bank of the lake where he and Bill had their play. |
gj04 | 1 | null | Ron yawned himself awake. |
gj04 | 1 | null | She coughed herself awake as the leaf landed on her nose. |
gj04 | 1 | null | The worm wriggled onto the carpet. |
gj04 | 1 | null | The chocolate melted onto the carpet. |
gj04 | 0 | null | The ball wriggled itself loose. |
gj04 | 1 | null | Bill wriggled himself loose. |
gj04 | 1 | null | Aliza wriggled her tooth loose. |
gj04 | 1 | null | The off center spinning flywheel shook itself loose. |
cj99 | 1 | null | The more you eat, the less you want. |
cj99 | 1 | null | If you eat more, you want correspondingly less. |
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