ueh-vdr-vit

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on UEH Visual Dish Recognition (UEH-VDR) dataset. It achieves the following results on the evaluation set:

• Loss: 0.4856
• Accuracy: 0.9296

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: 2e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	197	0.8112	0.8943
No log	2.0	394	0.5428	0.9220
0.9	3.0	591	0.4856	0.9296

Framework versions

• Transformers 4.37.2
• Pytorch 2.1.0+cu121
• Datasets 2.17.0
• Tokenizers 0.15.1