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vit-base-patch16-224-franciscoflores-classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0071
- accuracy : 0.9988
Model description
Transfer learning from a pre-trained image classification model determines which images are of a dog and which ones are of food
Intended uses & limitations
More information needed
Training and evaluation data
This model was trained using the "sasha/dog-food"
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|
| 0.0618 | 1.9 | 500 | 0.0146 |
| 0.0062 | 3.8 | 1000 | 0.0071 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
