This model is a fine-tuned version of google/vit-base-patch16-224 on the dpdl-benchmark/oxford_flowers102 dataset. It achieves the following results on the evaluation set:

Loss: 0.0407
Accuracy: 0.9951

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: 0.0003
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1597	1.0	410	0.1298	0.9853
0.0549	2.0	820	0.0672	0.9902
0.0324	3.0	1230	0.0568	0.9902
0.0247	4.0	1640	0.0512	0.9902
0.0175	5.0	2050	0.0502	0.9902

Framework versions

Transformers 4.52.3
Pytorch 2.7.0
Datasets 3.6.0
Tokenizers 0.21.1

lautenad/vit-base-flowers102

vit-base-flowers102

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lautenad/
vit-base-flowers102