metadata
dataset_info:
features:
- name: synthetic_wrong_text
dtype: string
- name: text
dtype: string
- name: cer
dtype: float64
splits:
- name: train
num_bytes: 10857034
num_examples: 94909
download_size: 7622382
dataset_size: 10857034
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
Interpres OCR Correction (IOC) is the dataset that is desgined for training ByT5 models to correct transcribed Medieval Latin texts. The data is collected from the OCR results from multiple OCR models/engines like Deepseek-OCR, PaddleOCR-v5, TrOCR-Medieval, TRIDIS, ... on the CATMuS Latin dataset. The CER range is 0.1-0.4 to make sure the dataset doesn't capture too much gibberish cases and also not too easy.