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: 0.2821
Accuracy: 0.9445

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: 5e-05
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: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5962	0.33	100	0.4781	0.9497
0.4348	0.66	200	0.3871	0.9466
0.3349	0.99	300	0.3750	0.9309
0.2495	1.32	400	0.2920	0.9476
0.2331	1.65	500	0.2821	0.9445
0.3387	1.98	600	0.2597	0.9476
0.3133	2.31	700	0.2536	0.9487
0.2615	2.64	800	0.2393	0.9529
0.2687	2.97	900	0.2392	0.9550

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2

abifitrabiandi/vit-snack-classification-fp16

vit-snack-classification-fp16

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

abifitrabiandi/
vit-snack-classification-fp16