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: 1.4877
Accuracy: 0.5

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
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
No log	1.0	2	3.2296	0.0
No log	2.0	4	2.7874	0.1667
No log	3.0	6	2.4640	0.3333
No log	4.0	8	2.2000	0.3333
1.5523	5.0	10	1.9602	0.5
1.5523	6.0	12	1.7736	0.5
1.5523	7.0	14	1.6539	0.5
1.5523	8.0	16	1.5736	0.5
1.5523	9.0	18	1.5169	0.5
0.6818	10.0	20	1.4877	0.5

Framework versions

Transformers 4.54.1
Pytorch 2.7.1+cu126
Datasets 4.0.0
Tokenizers 0.21.4

natsu39/swin-tiny-patch4-window7-224-finetuned-car-models-classification-outer-layer-v001

swin-tiny-patch4-window7-224-finetuned-car-models-classification-outer-layer-v001

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

natsu39/
swin-tiny-patch4-window7-224-finetuned-car-models-classification-outer-layer-v001