batched tokenization

docbank.py

@@ -68,8 +68,10 @@ _FEATURES = datasets.Features(
         "original_image": datasets.features.Image(),
         #"labels": datasets.Sequence(feature=datasets.Value(dtype='int64'))
         "labels": datasets.Sequence(datasets.features.ClassLabel(
-            names=['abstract', 'author', 'caption', 'date', 'equation', 'figure', 'footer', 'list', 'paragraph',
+            names=['abstract', 'author', 'caption', 'equation', 'figure', 'footer', 'paragraph',
                    'reference', 'section', 'table', 'title']
+            # names=['abstract', 'author', 'caption', 'date', 'equation', 'figure', 'footer', 'list', 'paragraph',
+            #        'reference', 'section', 'table', 'title']
         ))
         # These are the features of your dataset like images, labels ...
     }
@@ -246,7 +248,10 @@ class Docbank(datasets.GeneratorBasedBuilder):
                         tokens.append(row['token'])
                         bboxes.append(normalized_bbox)
                         #print(f'Before: {row[9]}')
-                        labels.append(row['label'])
+                        label = row['label']
+                        if (label == "list") or (label == "date"):
+                            label = "paragraph"
+                        labels.append(label)
                         #print(f'After: {row[9]}')
                         # tokenized_input = self.TOKENIZER(
                         #     row[0],