This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.2119
Accuracy: 0.9122

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5888	1.0	41	0.4436	0.8348
0.3118	2.0	82	0.3028	0.8692
0.2284	3.0	123	0.2879	0.8795
0.203	4.0	164	0.2368	0.8950
0.2254	5.0	205	0.2276	0.8985
0.1976	6.0	246	0.2339	0.8967
0.1603	7.0	287	0.2191	0.9036
0.1556	8.0	328	0.2249	0.9036
0.1488	9.0	369	0.2018	0.9071
0.158	10.0	410	0.2119	0.9122

Framework versions

Transformers 4.46.3
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3

tdhcuong/swin-tiny-patch4-window7-224-finetuned-azure-poc-img-classification

swin-tiny-patch4-window7-224-finetuned-azure-poc-img-classification

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tdhcuong/
swin-tiny-patch4-window7-224-finetuned-azure-poc-img-classification