vit base patch16 224 in21k finetuned cifar10 This model is a fine tuned version of google/vit base patch16 224 in21k on the cifar10 dataset. It achieves the following results on the evaluation set: Loss: 0.2564 Accuracy: 0.9788 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: 1 Training results Training Loss Epoch Step Validation Loss Accuracy : : : : : : : : : : 0.4291 1.0 390 0.2564 0.9788 Framework versions Transformers 4.17.0 Pytorch 1.10.0+cu111 Datasets 2.0.0 Tokenizers 0.11.6
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