KeithHorgan/TweetClimateAnalysis
Text Classification
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Error code: ConfigNamesError Exception: ValueError Message: Couldn't infer the same data file format for all splits. Got {NamedSplit('train'): ('json', {}), NamedSplit('validation'): ('json', {}), NamedSplit('test'): ('csv', {})} Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 55, in compute_config_names_response for config in sorted(get_dataset_config_names(path=dataset, token=hf_token)) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names dataset_module = dataset_module_factory( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1512, in dataset_module_factory raise e1 from None File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1489, in dataset_module_factory return HubDatasetModuleFactoryWithoutScript( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1054, in get_module module_name, default_builder_kwargs = infer_module_for_data_files( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 513, in infer_module_for_data_files raise ValueError(f"Couldn't infer the same data file format for all splits. Got {split_modules}") ValueError: Couldn't infer the same data file format for all splits. Got {NamedSplit('train'): ('json', {}), NamedSplit('validation'): ('json', {}), NamedSplit('test'): ('csv', {})}
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This dataset has been automatically processed by AutoTrain for project TweetClimateAnalysis.
The BCP-47 code for the dataset's language is unk.
A sample from this dataset looks as follows:
[
{
"text": "What do you do if you are a global warming alarmist and real-world temperatures do not warm as much [...]",
"target": 16
},
{
"text": "(2.) A sun-blocking volcanic aerosols component to explain the sudden but temporary cooling of globa[...]",
"target": 0
}
]
The dataset has the following fields (also called "features"):
{
"text": "Value(dtype='string', id=None)",
"target": "ClassLabel(num_classes=18, names=['0_0', '1_1', '1_2', '1_3', '1_4', '1_6', '1_7', '2_1', '2_3', '3_1', '3_2', '3_3', '4_1', '4_2', '4_4', '4_5', '5_1', '5_2'], id=None)"
}
This dataset is split into a train and validation split. The split sizes are as follow:
Split name | Num samples |
---|---|
train | 23436 |
valid | 2898 |