nateraw/food This model is a fine tuned version of google/vit base patch16 224 in21k on the nateraw/food101 dataset. It achieves the following results on the evaluation set: Loss: 0.4501 Accuracy: 0.8913 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: 0.0002 train batch size: 128 eval batch size: 128 seed: 1337 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e 08 lr scheduler type: linear num epochs: 5.0 mixed precision training: Native AMP Training results Training Loss Epoch Step Validation Loss Accuracy : : : : : : : : : : 0.8271 1.0 592 0.6070 0.8562 0.4376 2.0 1184 0.4947 0.8691 0.2089 3.0 1776 0.4876 0.8747 0.0882 4.0 2368 0.4639 0.8857 0.0452 5.0 2960 0.4501 0.8913 Framework versions Transformers 4.9.0.dev0 Pytorch 1.9.0+cu102 Datasets 1.9.1.dev0 Tokenizers 0.10.3
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