rorshark vit base 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: 0.0393 Accuracy: 0.9923 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: 8 eval batch size: 8 seed: 1337 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 : : : : : : : : : : 0.0597 1.0 368 0.0546 0.9865 0.2009 2.0 736 0.0531 0.9865 0.0114 3.0 1104 0.0418 0.9904 0.0998 4.0 1472 0.0425 0.9904 0.1244 5.0 1840 0.0393 0.9923 Framework versions Transformers 4.36.0.dev0 Pytorch 2.1.1+cu118 Datasets 2.15.0 Tokenizers 0.15.0
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