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: 0.2075
Accuracy: 1.0

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 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: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	1	0.6230	0.7273
No log	2.0	2	0.5722	0.7273
No log	3.0	3	0.4570	0.7273
No log	4.0	4	0.3367	0.9091
No log	5.0	5	0.3078	0.9091
No log	6.0	6	0.3134	0.8182
No log	7.0	7	0.2473	0.9091
No log	8.0	8	0.2397	1.0
No log	9.0	9	0.2622	0.9091
0.3565	10.0	10	0.2396	0.9091
0.3565	11.0	11	0.2158	1.0
0.3565	12.0	12	0.2075	1.0

Framework versions

Transformers 4.49.0
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1

VasundharaBoomi/swin-tiny-patch4-window7-224-finetuned-parkinson-classification

swin-tiny-patch4-window7-224-finetuned-parkinson-classification

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

VasundharaBoomi/
swin-tiny-patch4-window7-224-finetuned-parkinson-classification