snacks_classification

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.4458
• Accuracy: 0.8942

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: 0.0001
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 13

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	303	0.7200	0.8649
1.0168	2.0	606	0.5468	0.8723
1.0168	3.0	909	0.4612	0.8848
0.3765	4.0	1212	0.5239	0.8660
0.2585	5.0	1515	0.4193	0.8890
0.2585	6.0	1818	0.4571	0.8775
0.2038	7.0	2121	0.4538	0.8838
0.2038	8.0	2424	0.4508	0.8880
0.1827	9.0	2727	0.4748	0.8880
0.1568	10.0	3030	0.4928	0.8764
0.1568	11.0	3333	0.3684	0.9099
0.1305	12.0	3636	0.4205	0.8984
0.1305	13.0	3939	0.4537	0.8963

Framework versions

• Transformers 4.37.2
• Pytorch 2.1.0+cu121
• Datasets 2.17.1
• Tokenizers 0.15.2