This model is a fine-tuned version of google/vit-base-patch16-224 on the Rapidata/Animals-10 dataset. It achieves the following results on the evaluation set:

Loss: 0.0784
Accuracy: 0.9762

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: 8
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0997	1.0	2356	0.0928	0.9732
0.0752	2.0	4712	0.0678	0.9809
0.0743	3.0	7068	0.0584	0.9839
0.0882	4.0	9424	0.0605	0.9792
0.0656	5.0	11780	0.0653	0.9813

Framework versions

Transformers 4.52.4
Pytorch 2.7.0+cu128
Datasets 3.6.0
Tokenizers 0.21.1

MichaelMM2000/vit-base-animals10

vit-base-animals10

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MichaelMM2000/
vit-base-animals10