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vit-base-patch16-224-in21k-image-classification-sagemaker
This model is a fine-tuned version of vit-base-patch16-224-in21k on the cifar10 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3033
- Accuracy: 0.972
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 313 | 1.4603 | 0.936 |
| 1.6548 | 2.0 | 626 | 0.4451 | 0.966 |
| 1.6548 | 3.0 | 939 | 0.3033 | 0.972 |
Framework versions
- Transformers 4.6.1
- Pytorch 1.7.1
- Datasets 1.6.2
- Tokenizers 0.10.3
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