ResNet18-FT-PetImages-11.7M

License & Attribution

This repository contains weights or code derived from the ResNet18 foundational architecture developed by the ResNet Authors. This ResNet18 model is fine-tuned using popular CatsVsDogs PetImages dataset.

• License: Distributed under the https://opensource.org/license/bsd-3-clause.
• Original Model Base: https://huggingface.co/microsoft/resnet-18
• Copyright Notice: Copyright 2025-2026 Hugging Face & The ResNet Authors.
• Research paper introducing this model: https://arxiv.org/abs/1512.03385

Dataset:

You can find the fine-tuning dataset using the link: https://huggingface.co/datasets/Man1103/PetImages.

Fine-tuning Configuration Metrics:

• Training Dataset: 50:50 class-balanced cats and dogs images with random transformations during training.
• Training strategy: Two stage fine-tuning strategy with:
  • Stage-1: This is where only classification FC layer is trained.
  • Stage-2: This is where last two features extraction layers and classification FC layer are trained.
• Num epochs: 30
• Device: CUDA (Nvidia Tesla T4 GPU)
• Training batch size: 128
• Testing batch size: 256
• Learning rate:
  • For stage-1: 0.001
  • For stage-2: 0.00001
• Accuracy Score:
  • Training: 0.1 (100.0%)
  • Testing: 0.1 (100.0%)

Please refer to preprocessing and training pipelines in the model files:

• Preprocessing pipeline: preprocessing.py
• Training pipeline: train.py