This model is a fine-tuned version of microsoft/swin-small-patch4-window7-224 on the cifar100 dataset. It achieves the following results on the evaluation set:

Loss: 0.6281
Accuracy: 0.8938

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: 4e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.72	1.0	781	0.6691	0.8077
0.6944	2.0	1562	0.4797	0.8495
0.2794	3.0	2343	0.4338	0.869
0.2569	4.0	3124	0.4263	0.879
0.1417	5.0	3905	0.4385	0.8819
0.0961	6.0	4686	0.4720	0.8854
0.0584	7.0	5467	0.4941	0.885
0.0351	8.0	6248	0.5253	0.885
0.0107	9.0	7029	0.5598	0.8887
0.0118	10.0	7810	0.5998	0.8858
0.0097	11.0	8591	0.5957	0.8941
0.0044	12.0	9372	0.6237	0.8912
0.0013	13.0	10153	0.6286	0.8929
0.0102	14.0	10934	0.6281	0.8938

Framework versions

Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1

MazenAmria/swin-small-finetuned-cifar100

swin-small-finetuned-cifar100

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MazenAmria/
swin-small-finetuned-cifar100