Update README.md

README.md

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----
-license: mit
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+---
+language: en
+license: mit 
+library_name: peft
+tags:
+- image-classification
+- pytorch
+- resnet
+- lora
+- birds
+- cub-200-2011
+- fine-tuning
+- computer-vision
+datasets:
+- cub-200-2011 # 使用 Hugging Face Datasets 库的标识符（如果存在）或自定义名称
+pipeline_tag: image-classification
+widget:
+- src: https://images.unsplash.com/photo-1518992028580-6d57bd80f2dd?ixlib=rb-1.2.1&auto=format&fit=crop&w=600&q=80 # 示例图片 URL
+  example_title: Example Bird 1 (e.g., Cardinal)
+- src: https://images.unsplash.com/photo-1552728089-57bdde30beb3?ixlib=rb-1.2.1&auto=format&fit=crop&w=600&q=80 # 示例图片 URL 2
+  example_title: Example Bird 2 (e.g., Blue Jay)
+---
+
+# ResNet50 + LoRA for Bird Classification (CUB-200-2011)
+
+This repository contains LoRA (Low-Rank Adaptation) adapters fine-tuned on the CUB-200-2011 dataset for bird image classification. These adapters are designed to be applied to a standard `torchvision.models.resnet50` base model.
+
+## Model Details
+
+*   **Base Model:** `torchvision.models.resnet50` (pre-trained on ImageNet).
+*   **Fine-tuning Method:** Low-Rank Adaptation (LoRA) using the `peft` library.
+*   **Dataset:** [Caltech-UCSD Birds-200-2011 (CUB-200-2011)](https://data.caltech.edu/records/65de6-vp158)
+*   **Number of Classes:** 200 bird species.
+*   **LoRA Configuration:**
+    *   Rank (`r`): 8 (as used in training, please verify/update)
+    *   Alpha (`lora_alpha`): 16 (as used in training, please verify/update)
+    *   Target Modules: ["fc", "conv1", "layer4.0.conv1"] (Please list the actual modules targeted during training)
+    *   Dropout: 0.05
+    *   Bias: "none"
+
+## How to Use
+
+First, make sure you have `torch`, `torchvision`, and `peft` installed:
+```bash
+pip install torch torchvision peft Pillow