Comments (1)
Hi, I have also encountered it. I have tried to omit the problem by dropping the rows which are not correct:
df = pd.read_csv(dataset_path / '2_splits'/ f'ConvAbuseEMNLP{split}.csv')
df = df.astype({'example_id': 'int64'})
annot_columns = [f'Annotator{i+1}_is_abuse.{value}' for value in abuse_values for i in range(8)]
index_to_drop = []
for i, row in df.iterrows():
for c in annot_columns:
if row[c] not in ['0', '1', np.nan]:
index_to_drop.append(i)
break
df = df.drop(index_to_drop).reset_index(drop=False)
df = df.astype({c: 'float64' for c in annot_columns})
Unfortunately, it drops a large qunity of data (~10k) so it is half of all annotations. Therefore the test split has no examples labeled as -3, -2, 0 is_abusive
. I suggest fixing the entire dataset & reuploading.
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