| --- |
| tags: |
| - image-classification |
| - imagenette |
| - resnet50-pytorch |
| - pytorch |
| datasets: |
| - imagenette |
| metrics: |
| - accuracy |
| --- |
| |
| # ImageNette resnet50-pytorch |
|
|
| ## Model Description |
|
|
| resnet50-pytorch trained on 10-class ImageNet subset (ImageNette) with advanced augmentation techniques. |
|
|
| ### Model Architecture |
| - **Architecture**: resnet50-pytorch |
| - **Dataset**: ImageNette |
| - **Classes**: 10 |
|
|
| ### Training Configuration |
| - **Batch Size**: 128 |
| - **Optimizer**: sgd (momentum=0.9, weight_decay=1e-3) |
| - **Scheduler**: onecycle |
| - **Augmentation**: HorizontalFlip, ShiftScaleRotate, Cutout, ColorJitter |
| - **MixUp**: Alpha=0.2 |
| - **Label Smoothing**: 0.1 |
| - **Mixed Precision**: True |
| - **Gradient Clipping**: 1.0 |
| |
| ### Performance |
| - **Best Test Accuracy**: 24.28% |
| - **Total Epochs Trained**: 2 |
| - **Final Train Accuracy**: 16.16% |
| - **Final Test Accuracy**: 24.28% |
| |
| ### Training History |
| - **Best Epoch**: 2 |
| - **Train Loss**: 2.4702 → 2.3422 |
| - **Test Loss**: 2.6904 → 2.1273 |
| |
| ### Usage |
| |
| ```python |
| import torch |
| from huggingface_hub import hf_hub_download |
|
|
| # Download model |
| checkpoint_path = hf_hub_download( |
| repo_id="pandurangpatil/imagenet10trial", |
| filename="best_model.pth" |
| ) |
| |
| # Load checkpoint |
| checkpoint = torch.load(checkpoint_path, map_location='cpu', weights_only=False) |
| |
| # Load model (you'll need to have the model definition) |
| # from models import get_model |
| # model = get_model('resnet50-pytorch', num_classes=10) |
| # model.load_state_dict(checkpoint['model_state_dict']) |
| # model.eval() |
| ``` |
| |
| ### Training Details |
| - **Dataset**: ImageNette (9469 train, 3925 test) |
| - **Classes**: 10 |
| - **Image Size**: 160×160 or 224×224 |
| - **Normalization**: mean=(0.485, 0.456, 0.406), std=(0.229, 0.224, 0.225) |
| |
| ### Files |
| - `best_model.pth` - Best performing model checkpoint |
| - `training_curves.png` - Training/test accuracy and loss curves |
| - `lr_finder_plot.png` - Learning rate finder results |
| - `metrics.json` - Complete training history |
| - `config.json` - Hyperparameter configuration |
| |
| ### License |
| MIT |
| |
| ### Citation |
| ```bibtex |
| @misc{resnet50-pytorch-imagenette, |
| title = {ImageNette resnet50-pytorch}, |
| year = {2025}, |
| publisher = {HuggingFace}, |
| url = {https://huggingface.co/pandurangpatil/imagenet10trial} |
| } |
| ``` |
| |
