vit-base-patch16-224-in21k-dogs-cats2
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the Dogs_vs_Cats dataset. It achieves the following results on the evaluation set:
- Loss: 0.0111
- Accuracy: 0.9968
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: 5e-05
- 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: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.0691 | 1.0 | 625 | 0.0187 | 0.995 |
0.0332 | 2.0 | 1250 | 0.0147 | 0.9958 |
0.0446 | 3.0 | 1875 | 0.0139 | 0.9946 |
0.0241 | 4.0 | 2500 | 0.0178 | 0.9952 |
0.0412 | 5.0 | 3125 | 0.0117 | 0.9968 |
0.0683 | 6.0 | 3750 | 0.0168 | 0.995 |
0.0081 | 7.0 | 4375 | 0.0143 | 0.9962 |
0.0316 | 8.0 | 5000 | 0.0111 | 0.9968 |
0.0184 | 9.0 | 5625 | 0.0124 | 0.9968 |
0.021 | 10.0 | 6250 | 0.0128 | 0.9964 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1
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