vit-base-cats-vs-dogs
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the cats_vs_dogs dataset. It achieves the following results on the evaluation set:
- Loss: 0.0182
- Accuracy: 0.9937
Model description
More information needed
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: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1177 | 1.0 | 622 | 0.0473 | 0.9832 |
| 0.057 | 2.0 | 1244 | 0.0362 | 0.9883 |
| 0.0449 | 3.0 | 1866 | 0.0261 | 0.9886 |
| 0.066 | 4.0 | 2488 | 0.0248 | 0.9923 |
| 0.0328 | 5.0 | 3110 | 0.0182 | 0.9937 |
Framework versions
- Transformers 4.13.0.dev0
- Pytorch 1.8.1+cu111
- Datasets 1.15.1
- Tokenizers 0.10.3
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