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: 0.0368
Accuracy: 0.9914

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 OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
3.1515	1.0	17	0.1797	0.9442
0.2623	2.0	34	0.0368	0.9914
0.1156	3.0	51	0.0266	0.9914

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cpu
Datasets 4.0.0
Tokenizers 0.22.2

manoghourii/swin-tiny-patch4-window7-224-finetuned-dermalyze-ai

swin-tiny-patch4-window7-224-finetuned-dermalyze-ai

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

manoghourii/
swin-tiny-patch4-window7-224-finetuned-dermalyze-ai