
This model has been trained on a very small [dataset](https://github.com/yamanalab/ec-darkpattern/blob/master/dataset/dataset.tsv) having ~1.8k samples and 8 classes.
It performs horribly in classifying the type of dark pattern, but I did notice that it performs pretty well in classifying if it is a dark pattern or not. That is, it outputs "Not Dark Pattern" accurately most of the times (formal evaluation not done) when the given text is not a dark pattern (according to the examples in the dataset) and any of the other labels otherwise.
{"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["dark patterns"], "pipeline_tag": "text-classification"}
transformers tensorboard safetensors bert text-classification dark patterns en license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us