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: 0.3382
Accuracy: 0.8562

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: 128
eval_batch_size: 128
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 512
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
5.3507	1.0	14	0.8673	0.6557
3.1899	2.0	28	0.4795	0.8184
1.5944	3.0	42	0.3992	0.8436
1.3952	4.0	56	0.3741	0.8499
1.1452	5.0	70	0.3601	0.8575
1.0478	6.0	84	0.3470	0.8562
1.0049	7.0	98	0.3360	0.8562
0.9361	8.0	112	0.3318	0.8525
0.9477	9.0	126	0.3297	0.8512
0.8568	10.0	140	0.3382	0.8562

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0

DUCBUI/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

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