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# custom

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3082
- Accuracy: 0.8922
- F1: 0.7977

## 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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1

faces faces_easy beaver yin_yang binocular bonsai brain brontosaurus buddha butterfly camera cannon car_side leopards ceiling_fan cellphone chair chandelier cougar_body cougar_face crab crayfish crocodile crocodile_head motorbikes cup dalmatian dollar_bill dolphin dragonfly electric_guitar elephant emu euphonium ewer accordion ferry flamingo flamingo_head garfield gerenuk gramophone grand_piano hawksbill headphone hedgehog airplanes helicopter ibis inline_skate joshua_tree kangaroo ketch lamp laptop llama lobster anchor lotus mandolin mayfly menorah metronome minaret nautilus octopus okapi pagoda ant panda pigeon pizza platypus pyramid revolver rhino rooster saxophone schooner barrel scissors scorpion sea_horse snoopy soccer_ball stapler starfish stegosaurus stop_sign strawberry bass sunflower tick trilobite umbrella watch water_lilly wheelchair wild_cat windsor_chair wrench