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

Loss: 0.4855
Accuracy: 0.8548

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: 3e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 15
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6061	1.0	176	0.5937	0.6855
0.481	2.0	352	0.5138	0.8226
0.5522	3.0	528	0.4973	0.8065
0.4092	4.0	704	0.5557	0.7903
0.4882	5.0	880	0.4998	0.7984
0.4442	6.0	1056	0.4647	0.8387
0.5749	7.0	1232	0.4464	0.8306
0.4529	8.0	1408	0.5366	0.8065
0.5287	9.0	1584	0.4633	0.8387
0.3821	10.0	1760	0.4983	0.8387
0.2409	11.0	1936	0.4855	0.8548
0.2025	12.0	2112	0.5102	0.8387
0.2045	13.0	2288	0.4942	0.8387
0.4097	14.0	2464	0.4954	0.8387
0.5798	15.0	2640	0.4941	0.8387

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1

itsLeen/finetuned-fake-food

finetuned-fake-food

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

itsLeen/
finetuned-fake-food