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: 0.8460
Accuracy: 0.7455
F1 Macro: 0.5959
F1 Weighted: 0.7645

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: 0.0002
train_batch_size: 16
eval_batch_size: 8
seed: 42
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
num_epochs: 15
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro	F1 Weighted
1.8576	1.0	564	1.7057	0.2844	0.1599	0.3736
1.4609	2.0	1128	1.5769	0.4501	0.2754	0.5106
1.502	3.0	1692	1.2726	0.6637	0.4165	0.6799
1.7705	4.0	2256	1.2379	0.6208	0.4232	0.6596
1.5335	5.0	2820	1.3475	0.5788	0.4288	0.6291
1.1427	6.0	3384	1.3055	0.5878	0.4028	0.6421
1.1915	7.0	3948	1.1663	0.6537	0.4802	0.6864
0.9543	8.0	4512	1.0841	0.6836	0.4763	0.7054
1.2565	9.0	5076	0.9467	0.6078	0.5395	0.6484
1.1679	10.0	5640	0.9393	0.6776	0.5634	0.7090
1.19	11.0	6204	0.8992	0.6677	0.5324	0.7011
0.9055	12.0	6768	0.8849	0.6876	0.5730	0.7156
0.6657	13.0	7332	0.8501	0.7146	0.5919	0.7420
0.7657	14.0	7896	0.8460	0.7455	0.5959	0.7645
0.5182	15.0	8460	0.8811	0.7305	0.5851	0.7538

Framework versions

Transformers 4.56.1
Pytorch 2.8.0+cu126
Datasets 4.1.1
Tokenizers 0.22.0

himanshuvats/skin-cancer-model

skin-cancer-model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

himanshuvats/
skin-cancer-model