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raw_train_dataset.features
num_classes
ClassLabel
In 3. Fine-tuning a pretrained model - Processing the data - Loading a dataset from the Hub, there is an example of the output provided when doing:
It should expect (as per the document):
{'sentence1': Value(dtype='string', id=None), 'sentence2': Value(dtype='string', id=None), 'label': ClassLabel(num_classes=2, names=['not_equivalent', 'equivalent'], names_file=None, id=None), 'idx': Value(dtype='int32', id=None)}
but it actually outputs:
{'sentence1': Value(dtype='string', id=None), 'sentence2': Value(dtype='string', id=None), 'label': ClassLabel(names=['not_equivalent', 'equivalent'], id=None), 'idx': Value(dtype='int32', id=None)}
The ClassLabel output doesn't include num_classes and name_file.
name_file
The text was updated successfully, but these errors were encountered:
Successfully merging a pull request may close this issue.
In 3. Fine-tuning a pretrained model - Processing the data - Loading a dataset from the Hub, there is an example of the output provided when doing:
It should expect (as per the document):
but it actually outputs:
The
ClassLabel
output doesn't includenum_classes
andname_file
.The text was updated successfully, but these errors were encountered: