The suggested way to use same_topic senario do not cover all the authors in the test set

#3
by cpuyyp - opened

I follow the example in the summary as follows.

train_ds = load_dataset('guardian_authorship', name="cross_topic_1", split='train[:60%]+validation[:60%]+test[:60%]') 
tests_ds = load_dataset('guardian_authorship', name="cross_topic_1", split='train[-40%:]+validation[-40%:]+test[-40%:]')

However, simply

len(tests_ds.to_pandas()['author'].unique())

gives 11. But there are 13 authors.

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