This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the DBQ/Matches.Fashion.Product.prices.France dataset. It achieves the following results on the evaluation set:

Loss: 1.2328
Accuracy: 0.6395

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: 0.0002
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0975	0.5714	500	1.2619	0.6111
0.8315	1.1429	1000	1.3133	0.6322
0.7266	1.7143	1500	1.2077	0.6356
0.5451	2.2857	2000	1.2895	0.6556
0.4287	2.8571	2500	1.2736	0.6644
0.2554	3.4286	3000	1.3801	0.6767
0.2265	4.0	3500	1.4924	0.6656
0.0738	4.5714	4000	1.6321	0.68
0.0761	5.1429	4500	1.6676	0.6767
0.0251	5.7143	5000	1.6911	0.7056
0.0147	6.2857	5500	1.7312	0.7
0.0051	6.8571	6000	1.7282	0.6922
0.0028	7.4286	6500	1.7679	0.6967
0.0017	8.0	7000	1.7642	0.6989

Framework versions

Transformers 4.40.0
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1

jolual2747/vit-clothes-classification

vit-clothes-classification

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jolual2747/
vit-clothes-classification