Dog Breeds Classification
This model is a fine-tuned version of google/vit-base-patch16-224 on 71 Dog Breeds-Image Data Set (Kaggle). It achieves the following results on the evaluation set:
- Loss: 0.0763
- Accuracy: 0.9743
Model description
This Model is a Transfer Learning-based model and trained with the size of 224x224 pixels. This model can predict dog with 71 classes of breeds.
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4379 | 1.0 | 249 | 0.2430 | 0.93 |
| 0.1998 | 2.0 | 498 | 0.1380 | 0.9514 |
| 0.0739 | 3.0 | 747 | 0.1008 | 0.9614 |
| 0.0135 | 4.0 | 996 | 0.0834 | 0.9671 |
| 0.0036 | 5.0 | 1245 | 0.0763 | 0.9743 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1