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)
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:

pip install torch torchvision peft Pillow