| --- |
| license: apache-2.0 |
| pretty_name: PM4Bench QGO Training Data |
| language: |
| - ar |
| - cs |
| - en |
| - hu |
| - ko |
| - ru |
| - sr |
| - th |
| - vi |
| - zh |
| task_categories: |
| - image-to-text |
| tags: |
| - synthetic |
| - ocr |
| - grpo |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train/*.parquet |
| - split: validation |
| path: data/test/*.parquet |
| --- |
| |
| # PM4Bench QGO training data |
|
|
| This is the synthetic multilingual OCR corpus used for QGO-8B GRPO: |
|
|
| - 19,500 training rows |
| - 500 validation rows |
| - embedded image bytes |
| - prompt, rule-based reward target, answer, split, and auxiliary metadata |
|
|
| The release builder preserves row order and learning content. It changes only |
| historical machine-specific image path strings to portable basenames. Per-shard |
| source and release SHA-256 values are recorded in |
| `metadata/release_inventory.json`. |
|
|
| The dataset is synthetic and released under Apache-2.0. |
|
|
| `metadata/release_inventory.json` records every shard's row count, byte size, |
| source digest, release digest, and the only permitted transformation. The |
| repository-level `SHA256SUMS` covers the complete public snapshot. |
|
|
| Training code and the exact reward implementation are available at |
| <https://github.com/opendatalab/PM4Bench/tree/main/recipes/qgo>. |
|
|
