This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the wellCh4n/tomato-leaf-disease-image dataset. It achieves the following results on the evaluation set:

Loss: 0.0170
Accuracy: 0.9967

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 1337
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: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1879	1.0	1930	0.0915	0.9842
0.1685	2.0	3860	0.0688	0.9838
0.0118	3.0	5790	0.0271	0.9952
0.1	4.0	7720	0.0244	0.9952
0.0629	5.0	9650	0.0170	0.9967

Framework versions

Transformers 4.48.0.dev0
Pytorch 2.2.2+cu121
Datasets 3.2.0
Tokenizers 0.21.0

wellCh4n/tomato-leaf-disease-classification-vit

tomato-leaf-disease-classification-vit

Training procedure

Training hyperparameters

Training results

Framework versions

wellCh4n/
tomato-leaf-disease-classification-vit