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vit-base-patch16-224-finetuned-cifar10
This model is a fine-tuned version of google/vit-base-patch16-224 on the cifar10 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0427
- Accuracy: 0.9876
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2518 | 1.0 | 390 | 0.0609 | 0.9821 |
| 0.1985 | 2.0 | 780 | 0.0532 | 0.983 |
| 0.197 | 3.0 | 1170 | 0.0427 | 0.9876 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
