Datasets:
| task_categories: | |
| - image-to-text | |
| language: | |
| - ne | |
| - hi | |
| - mr | |
| tags: | |
| - ocr | |
| - devanagari | |
| - glm-ocr | |
| pretty_name: Ocr Document Processing Eval | |
| # ocr_document_processing_eval | |
| Document-processing OCR proxy for digitization, KYC-like numeric fields, and RAG extraction checks. | |
| - Repo: `himalaya-ai/ocr-document-processing-eval` | |
| - Task: `document_processing_ocr` | |
| - Main raw file: `*.ocr.jsonl` with `image`, `ocr`, `source_repo`, and language/provenance columns. | |
| - Optional fine-tuning/eval file: `*.sharegpt.json` with `messages` and `images`. | |
| ## Source Mix | |
| - `indic_vision_bench_deva_ocr` `ocr/test`: 40% | |
| - `nayana_bench_deva_documents` `default/hi`: 20% | |
| - `nayana_bench_deva_documents` `default/mr`: 15% | |
| - `devanagari_digits_mixed` `default/train`: 15% | |
| - `hindi_handwritten_word_ocr` `default/test`: 10% | |
| ## Notes | |
| Generated by `scripts/sample_ocr_eval_sets.py` from the GLM fine-tuning workspace. | |
| If a source only exposes a train split, keep the deterministic held-out row ids out of SFT/training runs. | |