This model is a fine-tuned version of google/vit-base-patch16-224 on the vuongnhathien/30VNFoods dataset. It achieves the following results on the evaluation set:

Loss: 0.5253
Accuracy: 0.8867

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: 64
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6211	1.0	275	0.6582	0.7996
0.3091	2.0	550	0.5436	0.8457
0.1674	3.0	825	0.5812	0.8565
0.0947	4.0	1100	0.5674	0.8648
0.0335	5.0	1375	0.6408	0.8517
0.0235	6.0	1650	0.5589	0.8803
0.006	7.0	1925	0.5129	0.8859
0.0054	8.0	2200	0.4975	0.8922
0.0017	9.0	2475	0.4996	0.8926
0.0027	10.0	2750	0.4998	0.8915

Framework versions

Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2

vuongnhathien/vit-base-add-2-decay

vit-base-add-2-decay

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

vuongnhathien/
vit-base-add-2-decay