cifar10-lt
This model is a fine-tuned version of google/vit-base-patch16-224 on the cifar10-lt dataset. It achieves the following results on the evaluation set:
- Loss: 0.1132
- Accuracy: 0.9659
- F1: 0.9660
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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Base model
google/vit-base-patch16-224Evaluation results
- Accuracy on cifar10-lttest set self-reported0.966
- F1 on cifar10-lttest set self-reported0.966