Handle overflowing tokens
I have this code to tokenize and align labels for my bert ner model:def align_labels(labs, wids):
    new_labs = []
    current_word = None
    for wid in wids:
        if wid != current_word:
            current_word = wid
            label = -100 if wid is None else labs[wid]
            new_labs.append(label)
        elif wid is None:
            new_labs.append(-100)
        else:
            label = labs[wid]
            new_labs.append(label)
    return new_labs

def tokenize_and_align_labels(row):
    tokenized = tokenizer(
        row["tokens"],
        truncation=True,
        is_split_into_words=True,
        max_length=512
    )
    all_labs = row["lab_id"]
    new_labs = [ ]
    for i, labs in enumerate(all_labs):
        word_ids = tokenized.word_ids(i)
        new_labs.append(align_labels(labs, word_ids))

    tokenized['labels'] = new_labs
    return tokenizedHow can I handle overflowing tokens without loosing data?