metadata
language:
- or
license: apache-2.0
base_model: Qwen/Qwen2.5-VL-3B-Instruct
datasets:
- shantipriya/odia-ocr-merged
tags:
- odia
- ocr
- vision-language
- lora
- peft
Odia OCR — Qwen2.5-VL-3B Fine-tuned (v2)
LoRA fine-tune of Qwen/Qwen2.5-VL-3B-Instruct on 66K Odia OCR image-text pairs (checkpoint-3800).
Metrics at step 3600: CER 9.60% | Exact Match 68.2% (500 test samples)
LoRA config: r=128, alpha=256, 7 target modules (q/k/v/o/gate/up/down proj)
Usage
from transformers import AutoProcessor, Qwen2_5_VLForConditionalGeneration
from peft import PeftModel
import torch
processor = AutoProcessor.from_pretrained("Qwen/Qwen2.5-VL-3B-Instruct", trust_remote_code=True)
model = Qwen2_5_VLForConditionalGeneration.from_pretrained("Qwen/Qwen2.5-VL-3B-Instruct", torch_dtype=torch.float16, device_map="auto")
model = PeftModel.from_pretrained(model, "shantipriya/odia-ocr-qwen-finetuned_v2")
model.eval()