dsmchr/trocr_russian_18th_century_printed

TrOCR Base for 18th-Century Russian Printed Texts

This model is a fine-tuned version of microsoft/trocr-base-printed for optical character recognition (OCR) of historical Russian printed texts from the eighteenth century.

Intended Use

The model is designed for recognizing printed Russian texts with prereform orthography, including historical character forms and typographic features typical of eighteenth-century publications.

Base-usage

from PIL import Image
from transformers import TrOCRProcessor, VisionEncoderDecoderModel

hf_model = VisionEncoderDecoderModel.from_pretrained("dsmchr/trocr_russian_18th_century_printed")

image = Image.open("./path/to/your/image")

processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-printed")
pixel_values = processor(images=image, return_tensors="pt").pixel_values

generated_ids = hf_model.generate(pixel_values)
generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
print(generated_text)

Training Dataset

The model was fine-tuned on a custom OCR dataset containing 14,911 manually aligned text lines.

The dataset was compiled from Russian printed books of various genres and printing houses, predominantly published during the second half of the eighteenth century. Ground-truth transcriptions preserve the original historical spelling.

Training Details

Parameter	Value
Base model	microsoft/trocr-base-printed
Epochs	3
Batch size	8
Maximum training steps	4473
Evaluation interval	Every 200 steps
Best checkpoint	Step 3600
Best validation CER	0.0534