library_name: transformers
metrics:
- accuracy
base_model:
- microsoft/swin-large-patch4-window12-384-in22k
license: apache-2.0
tags:
- vision
- image-classification
model-index:
- name: cub-200-bird-classifier-swin
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: cub-200-subset
type: cub-200-subset
args: default
metrics:
- name: validation_accuracy
type: accuracy
value: 0.8653
- name: test_accuracy
type: accuracy
value: 0.8795
Model Card for Model ID
Model Details
Model Description
This model was created for the "Feather in Focus!" Kaggle competition of the Information Studies Master's Applied Machine Learning course at the University of Amsterdam. The goal of the competition was to apply novel approaches to achieve the highest possible accuracy on a bird classification task with 200 classes. We were given a labeled dataset of 3,926 images and an unlabeled dataset of 4,000 test images. Out of 32 groups and 1,083 submissions, we achieved the #1 accuracy on the test set with a score of 0.87950.
- Model type: [More Information Needed]
- License: [More Information Needed]
- Finetuned from model [optional]: [More Information Needed]
Training Details
Training Data
The training data consists of an unknown subset of the cub-200-2011 dataset, https://paperswithcode.com/dataset/cub-200-2011
Training Procedure
Preprocessing
Data augmentation was applied to the training data in a custom Torch dataset class. Because of the size of the dataset images were not replaced but duplicated and augmented. The only augmentations applied were HorizontalFlips and Rotations (10 degrees) to align with the relatively homogenous dataset.
Training Hyperparameters
| Hyperparameter | Value |
|---|---|
| Optimizer | AdamW |
| Learning Rate | 1e-4 |
| Batch Size | 32 |
| Epochs | 2 |
| Weight Decay | - |
| Scheduler | - |
| Mixed Precision | Torch AMP |
Speeds, Sizes, Times [optional]
[More Information Needed]
Evaluation
Testing Data, Factors & Metrics
Testing Data
The testing data consists of an unknown subset of the cub-200-2011 dataset, https://paperswithcode.com/dataset/cub-200-2011
[More Information Needed]
Factors
[More Information Needed]