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image_classification_vit

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: 0.1271
Accuracy: 0.9857

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: 3
total_train_batch_size: 96
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3469	0.9986	239	0.2654	0.9701
0.2503	1.9972	478	0.1579	0.9817
0.1793	2.9958	717	0.1271	0.9857

Framework versions

Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

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Safetensors

Model size

85.8M params

Tensor type

F32

Model tree for SolubleFish/image_classification_vit

Base model

google/vit-base-patch16-224-in21k

Finetuned

(2543)

this model

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Evaluation results

Accuracy on imagefolder
self-reported

0.986