omarelsherif010/glm-ocr-bnk-finetuning
GLM-OCR Fine-Tuning Pipeline Fine-tuning GLM-OCR 0.9B (CogViT encoder + GLM-0.5B decoder) for Korean financial document table recognition using LoRA via LLaMA-Factory. Performance Targets Metric Target TEDS (2-level nested) >= 90% TEDS (3-level nested) >= 85% Korean CER <= 1% Latency <= 0.5s/page Directory Structure glm_ocr_finetuning/ ├── config/ # Training/eval YAML configs │ ├──… See the full description on the dataset page: https://huggingface.co/datasets/omarelsherif010/glm-ocr-bnk-finetuning.
| Author / organization | omarelsherif010 |
|---|---|
| Downloads | 575 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 17 February 2026 |
| Last updated at source | 19 February 2026 |
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- 17 Oct 2026 Description: GLM-OCR Fine-Tuning Pipeline Fine-tuning GLM-OCR 0.9B (CogViT encoder + GLM-0.5B decoder) for Korean financial document table recognition using LoRA via LLaMA-Factory. Performance Targets Metric Target TEDS (2-level nested) >= 90% TEDS (3-l → GLM-OCR Fine-Tuning Pipeline Fine-tuning GLM-OCR 0.9B (CogViT encoder + GLM-0.5B decoder) for Korean financial document table recognition using LoRA via LLaMA-Factory. Performance Targets Metric Target TEDS (2-level nested) >= 90% TEDS (3-l
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