results
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2654
- Accuracy: 0.9402
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.5724 | 1.0 | 34 | 0.4259 | 0.9163 |
0.3558 | 2.0 | 68 | 0.3116 | 0.9363 |
0.2732 | 3.0 | 102 | 0.2842 | 0.9363 |
0.2286 | 4.0 | 136 | 0.2690 | 0.9402 |
0.1984 | 5.0 | 170 | 0.2654 | 0.9402 |
Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
google/vit-base-patch16-224-in21kEvaluation results
- Accuracy on imagefoldervalidation set self-reported0.940