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README.md

@@ -8,19 +8,32 @@ tags:
 - receipt-extraction
 pipeline_tag: image-to-text
 widget:
-- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/receipt.jpg
-  example_title: Sample Receipt
+  - src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/receipt.jpg
+    example_title: Sample Receipt
 ---
 
 # Receipt Donut (Fine-tuned Document UI)
 
 This model extracts structured JSON data directly from receipt images without needing a separate OCR engine. Fine-tuned on the `naver-clova-ix/donut-base-finetuned-cord-v2` base model.
 
+## Training Performance
+The model was trained for 11 epochs on an NVIDIA L4 GPU. Optimal convergence was reached at Epoch 9.
+
+![Learning Curve](learning_curve.png)
+
+## Sample Extraction Results
+Below are some examples of the model performing extraction on the validation set (Original Image vs. Model Output).
+
+![Sample 1](hub_assets/sample_result_0.png)
+![Sample 2](hub_assets/sample_result_1.png)
+![Sample 3](hub_assets/sample_result_2.png)
+
 ## Model Details
 - **Architecture:** Donut (Document Understanding Transformer)
 - **Task:** Image-to-JSON extraction
 - **Extracted Fields:** `merchant`, `date`, `subtotal`, `tax`, `total`, `address`
 - **Training Data:** 8,615 heavily augmented receipt images sourced from 8 diverse public datasets (CORD, WildReceipts, SROIE variants, etc.)
+- **License:** MIT
 
 ## Try it out!
 Use the **Hosted Inference API** widget on the right.